Domestic crime, conflict, and instability pose a significant threat to many contemporary governments. These challenges have proven to be particularly acute within modern-day Mexico. While there have been significant developments in predicting intrastate armed and electoral conflict in various contemporary settings, such efforts have thus far been limited in their use of spatial as well as temporal correlations, as well as in the features they have consid- ered. Machine learning, especially deep learning, has been proven to be highly effective in predicting future conflicts using word embeddings in Convolutional Neural Networks (CNN) but lacks the spatial structure and, due to the black box nature, cannot explain the importance of predictors. We develop a novel methodology using machine learning that can accurately classify future anti-government violence in Mexico. We further demonstrate that our approach can identify important leading predictors of such violence. This can help policymakers make informed decisions and can also help governments and NGOs better allocate security and humanitarian resources, which could prove beneficial in tackling this problem. Using a variety of political event aggregations from the ICEWS database alongside other textual and demographic features, we trained various classical machine learning algorithms, including but not limited to Logistic Regression, Random Forest, XGBoost, and a Voting classifier. We considered a mix of CNN + Long Short Term Memory (LSTM) networks to decode the spatial and temporal relationship in the data. The performance of all the black box deep learning models was not at par with the classical machine learning models. We also evaluated the temporal relationships in the data to identify important predictors that fuel anti-government violence along with their directions using Shapley additive values. The voting classifier, utilizing a subset of features derived from LASSO across 100 simulations, consistently surpasses alternative models in performance and demonstrates efficacy in accu- rately classifying future anti-government conflicts. Notably, Random Forest feature importance indicates that some features, including but not limited to homicides, accidents, material conflicts, and positive worded citizen information sentiments emerge as pivotal predictors in the classification of anti-government conflicts. Finally, we conclude the research by analysing the spatial structure of the data using Moran’s I index extended version for spatiotemporal data to identify the global spatial dependency and local clusters followed by modelling the data spatially and evaluating the same using Gaussian Process Boost(GPBoost). The global spatial autocorrelation is minimal, characterized by local- ized conflicts cluster within the region. Furthermore, in Phase 3, the Voting Classifier method demonstrates superior performance over GPBoost, leading to the inference that no substantial spatial dependency exists among the various locations.

The study aimed to evaluate the impact of community policing on maintaining community safety and security by measuring the rate of crime prevention. Specifically, it sought to find out how the city administration of Addis Ababa demonstrated and promoted understanding of the community policing effort, information sharing, and community members' opinions regarding community policing in relation to local security procedures. Law enforcement initiatives to improve quality of life and reduce crime are also included. In order to be successful, community policing requires concrete actions and projects, and given the pervasive mistrust in today's public, both police departments and individual officers must take the lead. The findings demonstrated the influence of community policing, information sharing, and their results on local security practices as well as community policing among community members. According to one suggestion, the police should make sure that they interact positively with the community and that people are aware of their involvement in community policing. This way, people will be happy to provide the police with information that could help prevent crime. The public should be encouraged to maintain good connections with the police, as they can enhance community policing. Because it were obvious that doing so will improve society's peace and security, this study showed the need for additional efforts to further cement relationships of collaboration between the police and the community.

The purpose of the study is to analyse and to identify specific structural characteristics of melanocytic nevi. So, for better conclusions, using the optical microscope, could be possible a proper describtion related melanocytic nevi, reffering to youth pacients. In this research direction, good to mention that in a human individual life, play a significant role, different factors. That include in line, genetic, epigenetic, microbiomic, and proteomic factors. Future directions refers to preventive and prophylactic methods.

This analyses the impact of competition on liquidity creation in the banking industry of the United States. For the purposes of this paper panel data of US banks for the period of 1976-2000 is chosen as a sample. The plausible endogeneity issue is addressed by employing instrumental variables and then implementing two stages least squares method. Besides this, crisis period of 1990-1992 is also analyzed to compare effect with in “normal times”. The results show that decrease in the level of competition negatively affects the liquidity creation ability of banks in the US and this impact is even more negative during the crisis period.

In this paper, we consider particles together with the surrounding space as an indivisible system, and then investigate the maximum symmetry of the system at the quantum level. We introduce a new quantity to describe the evolution of this system before and after measurement. The effective mass of gravity is estimated. We also show that a free quantum particle as the source of energy and momentum do not produce gravity.

Let $\mathcal{X}$ be a Banach space. Let $\{\tau_j\}_{j=1}^n, \{\omega_k\}_{k=1}^m\subseteq \mathcal{X}$ and $\{f_j\}_{j=1}^n$, $\{g_k\}_{k=1}^m\subseteq \mathcal{X}^*$ satisfy $ |f_j(\tau_j)|\geq 1$ for all $ 1\leq j \leq n$, $|g_k(\omega_k)|\geq 1 $ for all $1\leq k \leq m$. If $x \in \mathcal{X}\setminus \{0\}$ is such that $x=\theta_\tau\theta_f x=\theta_\omega\theta_g x$, then we show that \begin{align}\label{FKDB} \|\theta_fx\|_0\|\theta_gx\|_0\geq \frac{\bigg[1-(\|\theta_fx\|_0-1)\max\limits_{1\leq j,r \leq n,j\neq r}|f_j(\tau_r)|\bigg]^+\bigg[1-(\|\theta_g x\|_0-1)\max\limits_{1\leq k,s \leq m,k\neq s}|g_k(\omega_s)|\bigg]^+}{\left(\displaystyle\max_{1\leq j \leq n, 1\leq k \leq m}|f_j(\omega_k)|\right)\left(\displaystyle\max_{1\leq j \leq n, 1\leq k \leq m}|g_k(\tau_j)|\right)}. \end{align} We call Inequality (\ref{FKDB}) as \textbf{Functional Kuppinger-Durisi-B\"{o}lcskei Uncertainty Principle}. Inequality (\ref{FKDB}) improves the uncertainty principle obtained by Kuppinger, Durisi and B\"{o}lcskei \textit{[IEEE Trans. Inform. Theory (2012)]} (which improved the Donoho-Stark-Elad-Bruckstein uncertainty principle \textit{[SIAM J. Appl. Math. (1989), IEEE Trans. Inform. Theory (2002)]}). We also derive functional form of the uncertainity principle obtained by Studer, Kuppinger, Pope and B\"{o}lcskei \textit{[EEE Trans. Inform. Theory, (2012)]}.

Computational Fluid Dynamics (CFD) is revolutionizing the oil and gas industry by offering powerful insights and innovative solutions. This paper explores the cutting-edge applications of CFD in enhancing and innovating within the sector. CFD simulations provide engineers with invaluable insights into fluid behavior, enabling optimized designs and informed decision-making. The software facilitates foresight by predicting system performance, optimizing drilling techniques, and maximizing reservoir management strategies. Moreover, CFD optimizes equipment design, increases operational efficiency, and reduces costs through virtual testing, eliminating the need for costly physical prototypes. The application of CFD aligns with the United Nations Sustainable Development Goals (SDGs), promoting energy efficiency, climate action, responsible production, and sustainable consumption. It addresses flow assurance challenges, enhances safety protocols, and mitigates environmental impacts. CFD is a powerful tool driving innovation, resilience, and sustainability within the oil and gas industry, ensuring a more efficient, safe, and environmentally conscious future. As advancements in CFD methodologies continue, the potential for further enhancements and breakthroughs within the sector becomes even more promising, driving the industry towards a sustainable and prosperous future.

Proximal tubular epithelial cells (PTEC) are constantly exposed to potentially toxic metabolites and xenobiotics. The regenerative potential of the kidney enables the replacement of damaged cells either via the differentiation of stem cells or the regain of proliferative properties of the PTEC. Nevertheless, it is known that renal function declines, suggesting that the deteriorated cells are not replaced by fully functional cells. To understand the possible causes of this loss of kidney cell function, it would be beneficial to understand the role of toxins during the regeneration process. Therefore, we investigated the sensitivity and function of human induced pluripotent stem cells (hiPSC), hiPSC differentiating, and hiPSC differentiated into proximal tubular epithelial-like cells (PTELC) to known nephrotoxins. hiPSC were differentiated into PTELC, exhibiting a similar morphology to PTEC, expressing prototypical PTEC markers and performing albumin endocytosis. When treated with two nephrotoxins, hiPSC and differentiating hiPSC were more sensitive to cisplatin than differentiated PTELC, whereas all stages were equally sensitive to cyclosporin A. Both toxins also had an inhibitory effect on albumin uptake. Our results suggest a high sensitivity of differentiating cells towards toxins, which could have an unfavorable effect on regenerative processes. To study this, our model of hiPSC differentiating into PTELC appears suitable.

The endophytic fungus Aspergillus sp. SPH2 was isolated from the stems of the endemic plant Bethencourtia palmensis and its extracts were found to have strong fungicidal effects against Botrytis cinerea and ixodicidal effects against Hyalomma lusitanicum at different fermentation times. In this study, the fungus was grown using three different culture media and two methodologies, Microparticulate Enhancement Cultivation (MPEC) and Semi-Solid Fermentation (SSF), to increase the production of secondary metabolites in submerged fermentation. The addition of an inert support to the culture medium (SSF) resulted in a significant increase in extract production. However, when talcum powder was added to different culture media, unexpected results were observed, with a decrease in the production of the biocompounds of interest. Metabolomic analyses showed that the production of aspergillic, neoaspergillic, and neohydroxyaspergillic acids peaked in the first few days of fermentation, with notable differences observed among the methodologies and culture media. Mellein production was particularly affected by the addition of an inert support to the culture medium. These results highlight the importance of surface properties and morphology of spores and mycelia during fermentation by this fungal species.

The ZX Spectrum was a popular 8-bit home computer by Sinclair Research in the 80s. Even though some of these computers may still work, the audio tapes, the TV with an analog tuner and the micro-switch joystick, used with the original ZX Spectrum, nowadays are outdated and hard to find in good working order or replicate. Since many other old closed systems are also very difficult to update to support modern peripherals, there is a necessity to provide a methodology to adapt such systems to support new peripherals while being compatible with existing software. The work proposed in this paper is focused on recreating a ZX Spectrum+/48k computer and interface it with modern peripherals on an FPGA. This is accomplished by adding a co-processor to assist with the control of the new peripherals which would either require to complex architectural changes to the original system and in the end it would perform poorly due to the low performance of the Z80 CPU. This work distances from previous ones on emulating a ZX Spectrum since it focuses on the use of different upgraded peripherals and the use of a NIOS II soft-processor as a co-processor to manage the SD Card accesses. A demonstration of the proposed modernized architecture was made by successfully running a diagnostics ROM and playing original ZX Spectrum games from an SD card for game with a PS/2 keyboard and a pair of joysticks.

Passive dynamics is an aspect of locomotion which is entirely dependent on the mechanical configuration and linkages of adjacent body segments. Tension distribution along mechanical linkages enables execution of movement patterns with reduced need for complex neurological pathways and may play a role in reestablishing postural stability following external disturbances. Here we demonstrate a uni-directional mechanical relationship between the equine forelimb and head, which may have implications for balance and forelimb loading in the horse. These observations suggest that forelimb and head movement coordination (observed in the horse during unrestrained locomotion) is largely controlled by the mechanical linkages between body segments, rather than being entirely dependent on neurological input as previously thought. This highlights the potential significance of research directed at investigating passively induced movements in understanding common locomotory patterns. Additionally, it suggests a mode of postural control which may provide instantaneous adjustments to postural disturbances, thus promoting rapid and efficient locomotion.

Machine learning (ML) is changing cybersecurity by enabling progressed discovery, anticipation and reaction instruments. This paper gives a comprehensive survey of ML's part in cybersecurity, looking at both hypothetical systems and down to earth usage. It diagrams the rising dangers focusing on ML models, such as ill-disposed assaults, information harming and show reversal assaults and examines state-of-the-art defense procedures, counting ill-disposed preparing, vigorous models and differential protection. Furthermore, the paper investigates different ML applications in cybersecurity from interruption location to malware classification, highlighting their affect on improving security measures. An peculiarity induction calculation is proposed for the early discovery of cyber-intrusions at the substations. Cybersecurity has ended up a imperative investigate range. The paper concludes with a discourse on the key inquire about bearings and best hones for making secure and versatile ML frameworks in a data-driven world. This paper dives into how Machine Learning (ML) revolutionizes cybersecurity, enabling progressed discovery, avoidance, and reaction components. It offers a exhaustive investigation of ML's urgent part in cybersecurity, enveloping hypothetical systems and viable applications. It addresses rising dangers like ill-disposed assaults and information harming, nearby cutting-edge defense techniques such as antagonistic preparing and strong models.

Analysis of the construction of tall buildings is important because of the changes in the microclimate in its vicinity. Ensuring wind comfort and pedestrian safety are critical requirements in urban environments. This paper reports on the wind flow field at the main campus of the Dhaka University of Engineering & Technology (DUET), Gazipur, using computational fluid dynamics (CFD) to investigate pedestrian wind comfort and safety. The simulations were conducted in ANSYS Fluent employing the Reynolds-averaged Navier-Stokes (RANS) equation. The vertical profile of the streamwise wind speed was validated using the existing observations. The results revealed that the wind speed at the building corners was higher than the air inlet velocity, whereas the wind speeds in the walkways among the buildings were found to vary. The velocity vectors surrounding the building were densely packed, with a recirculation vortex formed in the upstream flow. Furthermore, walkways can display a lower mean wind velocity coupled with high turbulence kinetic energy (TKE). The turbulent kinetic energy is seen to be as high as 1.52 m2 s-2 which exceeds the threshold limit, while wind velocity is 1.81 m/s at the same point. These findings highlight potential pedestrian safety risks and underscore the need for urban design enhancements.

Introduction: Laeverin is an extravillous trophoblast marker playing a significant role in the trophoblast migration. The purpose of this study was to evaluate the association between the amniotic and serum laeverin concentrations at 16-22 weeks of gestation and the fetal and placental ultrasound measurements in healthy, unaffected pregnancies. Materials and methods: This was a prospective cross-sectional study. Pregnant women with singleton pregnancies undergoing amniocentesis were recruited consecutively. Fetal structural malformations and/or aneuploidy were exclusion criteria. Fetal biometric parameters and placental growth/perfusion were measured in 44 high-risk pregnancies who had no pregnancy complication and any other chronic disease. Maternal serum and amniotic levels of laeverin were essayed with sandwich enzyme-linked immunosorbent assay. Results: Serum laeverin levels are decreasing slightly with the maternal age in mid-gestation. Serum laeverin level correlated negatively slightly with head size of the fetus with the gestational length at delivery (β=-0.38, 95% confidence interval (CI) -0.03-0.01), while the amniotic laeverin level correlated strongly with the abdominal circumference of the fetus (β=-0.64, 95% CI: -0.03-0.01). Furthermore, laeverin level in the amnion correlated moderately and positively with the placental volume (β=0.46, 95% CI: 0.01-0.08). Conclusions: Laeverin levels detected in the serum and in the amniotic fluid denotes the fetoplacental growth in uncomplicated high-risk pregnancies.

Digital recruitment systems have revolutionized the hiring paradigm, imparting exceptional efficiencies and extending the reach for both employers and job seekers. This investigation scrutinizes the efficacy of classical machine learning methodologies alongside advanced large language models (LLMs) in aligning resumes with job categories. Traditional matching techniques, such as Logistic Regression, Decision Trees, Naïve Bayes, and Support Vector Machines, are constrained by the necessity of manual feature extraction, limited feature representation, and performance degradation, particularly as dataset size escalates, rendering them less suitable for large-scale applications. Conversely, LLMs like GPT-4, GPT-3, and LLAMA, adeptly process unstructured textual content, capturing nuanced language and context with greater precision. We evaluate these methodologies utilizing two datasets comprising resumes and job descriptions to ascertain accuracy, efficiency, and scalability. Our results reveal that while conventional models excel with structured data, LLMs significantly enhance the interpretation and matching of intricate textual information. This study highlights the transformative potential of LLMs in recruitment, offering insights into their application and future research avenues.

Pollution, urbanization and technological advancements have posed stress on the ecosystem and its matrices. Globally, pollutants are observed in all compartments of ecological communities which affect the integrity of the atmosphere, hydrosphere, lithosphere and biosphere. Xenobiotics bioaccumulate and biomagnify across trophic levels or webs. Heavy metals have been implicated in impacts towards biodiversity and environmental declination. In Nigeria, wastes issues are a cause of concern and landfilling or are waste disposal approaches that cause deleterious effects such as depauperation of diversity and species decline, prompting the non-invasive ecotoxicological hazard assessments. Feathers were used to assess concentration levels of 13 metals (Fe, Mn, Zn, Cu, Co, Cr, Cd, Pb, Ni, Al, B, Se and Hg) using fast atomic absorption spectrophotometer (FAAS), one-way ANOVA was used in comparing variations in mean concentrations across trophic levels, diversity indices and point count methods were used to estimate diversity and abundance. Four avian species were assessed Hirundo aethiopica (insectivore), Streptoptelia senegalensis (granivore), Turdus pelios (omnivore), and Anthus leucophrys. (insectivore). Observed concentrations of important metals like iron were high with the insectivores having the highest concentrations of iron (2.6985 ± 0.1975 ppm) and granivores having the lowest (2.0100 ± 0.3172 ppm). The insectivores had the highest concentrations for cadmium, cobalt and chromium (0.0005 ± 0.0005ppm), nickel (at 00.0012 ± 0.0017 ppm) and least was observed in the granivores (0.0003 ± 0.0006 ppm). Selenium concentrations were quite high in insectivores (0.0775 ± 0.0035 ppm) and lowest in granivores (0.0433 ± 0.0015 ppm) likewise mercury for insectivores (0.0280 ± 0.0010 ppm) and granivores (0.0213 ± 0.0015 ppm). From the study, it is apparent that landfills are sources of pollution and poor management of wastes can affect biota (causing effects such as asymmetry and bioaccumulation) and ecosystem balance. The observation of heavy metals in the feathers serve as good sentinels due to their trophic levels and could be signs for what could be yet to occur. The heavy metal concentrations were significantly different at p < 0.05.

The work presents the results of studying dilute aqueous solutions of commercial Ln(NO3)3 · xH2O salts with Ln=Ce-Lu using X-ray diffraction (XRD), IR spectroscopy, X-ray absorption spectroscopy (XAS: EXAFS/XANES) and pH measurements. As a reference point, XRD and XAS measurements for characterized Ln(NO3)3 · xH2O microcrystalline powder samples were performed. The local structure of Ln-nitrate complexes in 20 mM Ln(NO3)3 · xH2O aqueous solution was studied under total external reflection conditions and EXAFS geometry was applied to obtain high-quality EXAFS data for solutions with low concentrations of Ln3+ ions. Results obtained by EXAFS spectroscopy showed significant contraction of the first coordination sphere during the dissolution process for metal ions located in the middle of the lanthanide series. It was established that in Ln(NO3)3 · xH2O solutions with Ln=Ce, Sm, Gd, Yb (c=134, 100, 50 and 20 mM) there are coordinated and, to a greater extent, non-coordinated nitrate groups with bidentate and predominantly monodentate bonds with Ln ions, the number of which increases upon transition from cerium to ytterbium. Cross-relationships between the concentration of solutions, pH value and antimicrobial activity with the type of Ln = Ce, Sm, Gd, Yb were established, as well as the absence of biocidal properties of solutions with a concentration of 20 mM, except for Ln = Yb. The important role of experimental conditions in obtaining and interpreting the results was noted.

South Africa’s internationally celebrated water legislation placed the responsibility for investing in water services at the door of the government. In recent years South Africa has struggled to invest adequately to keep up with growing demand for these services. The result is a suite of social, economic and environmental risks that are destabilising to the fiscus and the financial sector. This paper explored both operating and capital costs, and applied the ‘Beyond the Gap’ analysis to show that an additional 55% investment (R91 billion annually) is necessary to ensure South Africa meets its water policy goals. The analysis explores the factors that influence the investment amount and shows that a combination of policy choices and exogenous factors such as climate change could render the investment gap anywhere between 30% and 90% of the estimated current allocation to the water sector. The most significant savings are attributed to reducing the extent of “non-revenue water”, an energy transition away from coal, sharing of some water taps between (up to) five houses, reduced water allocations to agriculture, investments in invasive alien plant (IAP) clearing in water catchments above dams, and water demand management, capacity building and more efficient integration of different bulk water schemes. The study revealed important dependencies between capital and operating costs; where operating costs are ignored, the decay of water infrastructure is accelerated. Showing the contingency of investment needs on policy choices, places responsibility for attaining water policy goals and SDG 6 in the hands of a diverse set of actors. Quantifying the investment need also raises the critical question of how to raise the required investment. Recognising the need to balance risks to financiers with the widespread risks to households, companies and government when investment in water services is inadequate, South Africa is exploring a Monetary Architecture approach of inter-balance sheet relationships in an attempt to mobilise investment from new sources.

Cellular senescence has recently been recognized as a hallmark of cancer, reflecting its association with aging and inflammation, its role as a response to deregulated proliferation and oncogenic stress, and its induction by cancer therapies such as radiation, chemotherapy, and targeted agents. While such therapy-induced senescence (TIS) has been linked to resistance, recurrence, metastasis and normal tissue toxicity, TIS has the potential to enhance therapy response and stimulate anti-tumor immunity. In this review, we examine the Jekyll and Hyde nature of senescent cells (SnCs), with a particular focus on how their persistence while expressing the senescence-associated secretory phenotype (SASP) modulates the tumor microenvironment through autocrine and paracrine mechanisms. Via the SASP, the formation of SnCs may alternately mediate resistance or response to conventional therapy. Further, toward fulfilling the unmet potential of cancer immunotherapy, we consider how SnCs may influence tumor inflammation and serve as a source of antigen to potentiate anti-tumor immunity. This new view suggests treatment strategies based on inducing TIS to enhance immune checkpoint blockade. Finally, we describe strategies for mitigating the detrimental effects of senescence, such as modulating the SASP or targeting SnC persistence, toward enhancing the benefits of cancer treatment.

Abstract: In the Western of Mekong Delta belong to Vietnam a amount of alluvium sediments flows from upstream China to Vietnam, they are going from the river branches to in the Mekong Delta, then get out the Western Sea of Vietnam. This sediments accumulated gradually elevation the new land. The increase elevation of the land creates a fertile coastal plain where mangrove forests with a rich ecosystem of plants and animals. Over time, these forests change, with different plant species succeeding each other. This aims of this study to finding plant species in the forest, classification of forest types based on ecological regions, assessement the biodiversity of tree species, and compare the abundance communities, measuring the growth of the forest in these regions. In 2023, a comprehensive survey was conducted by using a systematic approach. The number of survey plots have done depend on the density of the forest, Base on the width of the forest range, the number of survey plots from 500m to 1,000m set up 1-2 plots, sub region set up from 10 to 15 plots. In total, 68 plots have done established in the erea, the area of plot is 100 square meters (10m x 10m). Using the statistical software in forestry to survey and analysis data. The result provided a complete picture of the tree species composition, distribution, and community structure characteristics in each ecological sub-region. The result of survey showed in the sub-region 1 have seven species as Sonneracia ovate, Rhzophora apiculata, Excoecaria agallochha, Avicennia officinalis, Avicennia alba, Agricerasvcoculatum, Bruguiera gymnorhiza. In the sub region 2 have eleven species as Sonneracia caseolaris, Annona reticulata, Lumnitzera littorea, Lumnizera racemosa, Rhizophora apiculata, Excoecaria agallocha, Avicennia officinalis, Avicennia alba, Hibiscus tillacerus, Bruguiera gymorhiza, Aericeras comiculatum. In the sub region 3 have eight as Sonratia caseolaris, Rhizophora mucronata, Rhizophora apiculata, Excoecaria agallocha, Avicennia marine, Avicennia alba, Bruguiera gymorhiza. In the region 4 have ten species as Sonneracia caseolaris, Sonneracia ovate, Lumnizera racemosa, Rhizophoa apiculata, Excoecaria agallocha, Avicennia marina, Avicennia officinalis, Aviecnnia alba, Bruguiera gymorhiza, Bruguiera cylindrica The total species of the mangrove forest in the Western Mekong Delta have 16 species from 11 plant families have been identified. Among these species have 6 dominant species include Avicennia oficinali),Avicennia alba, Rhizophora apiculata, Excoecaria agallocha, Someratia caseolaris, and Bruguiera yipamoriza. Two species easy grow on the new land are Avicennia officinalis Avicennia alba this findings show they can develope on the original new land for the shore of the Western Mekong Delta. The surveyed results also calculated the average of the height, diameter (D1.3), canopy, health of the nature mangrove tree for each sub region and total region. From these results showed the division of foresty structure, the structure of height, diameter (D1.3), canopy, vitality of the sub region and total region in the Western Mekong Delta.

Stroke is a global leading cause of death and disability. Knowledge of related guidelines is crucial for Emergency Department (ED) staff, influencing early diagnosis and timely treatment. We investigated Greek-Cypriot ED healthcare professionals' (nurses and physicians) knowledge in recognizing and managing stroke. A descriptive cross-sectional study spanned November 2019 to April 2020, encompassing four private and seven public EDs in the Republic of Cyprus. The data were collected through a self-reported questionnaire developed by the research team, consisting of 37 questions. Eight questions focused on sociodemographic and employment characteristics, 28 assessed knowledge in stroke recognition and management (each item was equally weighted without deliberate prioritization), and one question addressed self-assessment of knowledge in stroke care. 255 nurses [Response Rate (RR): 74.1%] and 26 physicians (RR: 47.3%) completed the questionnaire. The average correct response rate was 12.9 out of 28 statements (SD: 4.2), with nurses and physicians scoring 12.6 (SD: 4.1) and 15.7 (SD: 4), respectively. Work experience significantly influenced stroke knowledge, with all groups demonstrating superiority over those with less than one year of experience. Participants with previous training scored an average of 1.45 additional correct answers while educational attainment did not significantly influence stroke knowledge. Investigating stroke knowledge among Emergency Department nurses and physicians in the Republic of Cyprus revealed significant deficits. The study stresses targeted interventions, including, education, yearly examinations, workshops with hands-on training, and repeated training, to address these gaps and enhance the overall stroke care capabilities of the healthcare professionals.

In this work, several random Boolean networks (RBN) are generated and analyzed from two characteristics: their time evolution diagram and their transition diagram. To do this, its randomness is estimated using three metrics, of which algorithmic complexity is the only one capable of revealing both transitions towards the chaotic regime and the algorithmic contribution of certain states to the transition diagram and their relationship with the order they occupy in the temporal evolution of the respective RBN.

This study introduces a technique to uncover concealed patterns in satellite altimetry data, reflecting sea level variations in inland water bodies. We applied the methodology to the Caspian Sea, using altimetry data from four satellite missions over 27 years (1993-2020): TOPEX/Poseidon, Jason1, Jason2, and Jason3. The approach involves two steps: estimating sea level trends and identifying breakpoints that indicate trend shifts; and leveraging time lags between breakpoints at various locations to classify water drainage areas according to their degree of influence on each period. By revealing concealed patterns in the altimetry data, this technique can provide insights to understand the impacts of global warming and local climate changes on sea level fluctuations in the Caspian Sea. We hope that our study can facilitate subsequent interdisciplinary research on the intricate interplay between climate change and hydrological processes in inland water bodies.

The Aether Physics Model (APM) presents a radical reinterpretation of fundamental physics, offering potential solutions to long-standing problems in Quantum Mechanics and General Relativity. This paper explores the core concepts and equations of the APM, demonstrating how they provide a unified framework for understanding the nature of space, time, matter, and fundamental forces. We examine the implications of the APM's quantized Aether structure, the role of the Singularity and Gforce, and the reinterpretation of fundamental constants and forces. The model's predictions regarding dark matter, neutron content in stable matter, and the unification of forces are discussed, along with potential experimental tests. Additionally, we introduce the loxodrome concept and toroidal particle topology as central elements in explaining fundamental particles and forces. While speculative, the APM offers a thought-provoking alternative to standard physics models and warrants further investigation.

This study investigates the role of sustainable inventory management within supply chains, exploring strategies, benefits, challenges, and implications for organizations. Through qualitative research involving semi-structured interviews with supply chain professionals from diverse industries, key themes emerged. Sustainable practices such as green logistics, waste minimization, and ethical sourcing were identified as critical strategies to reduce environmental impact and enhance operational efficiency. Technological advancements, including AI, IoT, and blockchain, facilitate real-time monitoring, predictive analytics, and transparency, supporting data-driven decision-making in inventory management. Benefits include cost reduction, improved brand reputation, regulatory compliance, and risk mitigation, positioning organizations favorably in a competitive landscape shaped by environmental regulations and consumer expectations. Challenges such as cost constraints, regulatory complexities, and organizational inertia necessitate strategic investments, collaborative efforts, and leadership commitment to overcome. The study underscores the importance of integrating environmental, social, and economic considerations into supply chain practices to foster sustainability and resilience. Looking forward, the study advocates for a holistic approach to sustainable supply chain management, emphasizing innovation, stakeholder engagement, and capacity building. By aligning organizational values with societal expectations and regulatory frameworks, businesses can navigate complexities, drive positive environmental and social impacts, and achieve sustainable growth. This research contributes insights into current practices and future directions for sustainable inventory management, informing strategies that balance profitability with environmental stewardship and societal responsibility.

Color change is the most obvious characteristic of tomato ripening stage and an important indicator of tomato ripening condition, which directly affects the commodity value of tomato. To visualize the color change of tomato fruit in mature stage, a gated recurrent unit network with an encoder-decoder structure that dynamically simulates tomato growth and development with time-dependent lines using tomato color and shape as real-time data was proposed in this paper. Firstly, the .json file was converted into a mask.png file, the tomato mask was extracted, and the tomato was separated from the complex background environment, and the tomato growth and development data set was successfully constructed. Then, a network of gated recurrent units with encoder-decoder structure was constructed to predict the future growth trend of tomato under different greenhouse temperatures. The experimental results showed that for the gated recurrent unit network of encoder-decoder structure proposed, when the hidden layer number was 1 and hidden layer number was 512, a high consistency and similarity between the model predicted image sequence and the actual growth and development image sequence would be realized, and the structural similarity index measure was 0.746. It was proved that when the average temperature was 24.93℃, the average soil temperature was 24.06℃, and the average light intensity was 11.26 Klux, the environment was the most suitable for tomato growth. The environmental data-driven tomato growth model was constructed to explore the growth status of tomato under different environmental conditions, thus to understand the growth status of tomato in time. The statement provided a theoretical foundation for determining the optimal greenhouse environmental conditions to achieve tomato maturity. And it offered recommendations for investigating the growth cycle of tomatoes, as well as technical assistance for standardized cultivation in solar greenhouses.

Forage fish are crucial to human nutrition, especially in developing countries. However, in these countries, most forage fish catches are used to make aquafeeds for aquaculture, which leaves only a small quantity for direct human consumption. This practice increases fish prices in local markets and undermines people's nutrition. Overfishing forage fish for industrial purposes harms the ecosystem, reduces the catch of larger fish, and marginalizes local fishermen. Although previous discussions have touched qualitatively on the ethics and injustice of this practice, this article provides quantitative scales to measure the impact of the practice on the finances and forage fish consumption of low-income consumers using reasonable assumptions and literature values. Increasing the annual supply of forage fish by 25% to the 5 million MT of fresh fish markets globally could save consumers several billion US dollars annually. Families could consume a higher percentage of nutritious fish for less money. Furthermore, leaving forage fish in the sea could benefit wildlife and increase the capture of larger fish, such as mackerel, which are in demand in local markets and fished by local fishermen. The unintentional and involuntary contributions of low-income societies to enable the growth of high-value fish and shrimp for affluent societies seem unjust and warrant further investigation.

This study aimed to evaluate the discrepancies between genetic and visual coat color assignment in the Sarcidano Horse and to elucidate potential reasons. Individual DNA from 90 Sarcidano Horses was used for genetic assignment of coat color to explore the correspondence with individual forms containing phenotypical traits. The MC1R exon 1 and ASIP exon 3 have been genotyped and sequenced to obtain a picture of the coat color distribution in this breed. Surprisingly, once we compared the genetic results with the individual forms reporting the phenotypic data for each subject, a certain degree of non-correspondence between the phenotypic and genetic data in relation to coat color emerged. From the genetic analysis, Chestnuts (n = 58) resulted the most common Sarcidano Horse (n = 58), followed by a quite large number of Blacks (n = 28) and a very small number of Bays (n = 4), whereas phenotypic distribution resulted in 38 Chestnuts, 40 Bays, only 2 Blacks, and 10 Grays (without the possibility of recognizing the true color they carried). Chestnut resulted a very representative coat color, while many horses that visually identified as Bays were genetically Blacks. This discrepancy, that could be due to a variety of individual and external factors, including age, time of year, living situation and dietary condition, suggesting the importance of accurate coat color identification to ensure adequate features registration and reliable prediction of offspring’s coat color.

Introduction: Flow-cytometry (FC) is a powerful tool that can assist in lymphoma diagnosis in lymph node (LN) specimens. Although lymphoma diagnosis and classification are mainly based on tumor cell characteristics, surrounding cells are less employed in this process.Methods: We retrospectively investigated alterations in the ploidy status, proliferative cell fraction (PF) and the percentages of surrounding immune cells in 62 consecutive LN specimens with B-Cell Non-Hodgkin Lymphoma (B-NHL) that were submitted for FC evaluation between 2019-2022.Results: Compared with indolent B-NHLs, aggressive B-NHLs show increased DNA aneuploidy and PF, increased monocytes, immature-granulocytes, mature granulocytes, CD8⁺ T-cells, Double-Negative-T-cells and Double-Positive-T-cells, and decreased total CD45⁺ cells, total lymphocytes, CD4⁺ T-cells and CD4/CD8 ratio. Receiver operating characteristic analysis determined PF > 6.8% and immature-granulocytes > 0.9% as optimal cutoffs with highest specificity and sensitivity in differentiating aggressive and indolent B-NHLs.Conclusions: These findings further strength the diagnostic value of DNA content analysis by FC and suggest the utilization of tumor surrounding immune cells in NHL diagnosis and classification.

Introduction: The COVID-19 pandemic has triggered several challenges to mental health worldwide. Undergraduate medical students face considerable stress in their academic routines. Thus, there is a need to explore the implications of the mental health of undergraduate medical students during the COVID-19 pandemic. Objective: To review the global literature about anxiety and depression disorders in undergraduate medical students during the COVID-19 pandemic. Method: we developed an integrative literature review on the occurrence of anxiety and depression symptoms in undergraduate medical students during the COVID-19 pandemic. We assessed the results on the occurrence of anxiety and depression and the severity of symptoms in medical students during the COVID-19 pandemic using quantitative studies applying the GAD-7 questionnaire for anxiety or PHQ-9 for depression. Results: We reviewed 85 selected studies, and the results showed a significant prevalence of moderate and severe symptoms of anxiety and depression, with 28.2% of participants presenting scores ≥ 10 on the GAD-7 and 38.9% on the PHQ-9. Statistical analyses revealed associations between higher rates of anxiety symptoms in developing countries and data collected after the lockdown period in 2020, at the Pandemic lockdown. Conclusion: Our findings highlight the need for specific interventions to support the mental health of undergraduate medical students, critically in female students from developing countries during a Pandemic crisis.

Withania somnifera (WS), also known as ashwagandha, is a popular botanical supplement used to treat various conditions including memory loss, anxiety and depression. Previous studies from our group showed an aqueous extract of WS root (WSAq) enhances cognition and alleviates markers for depression in Drosophila. Here, we sought to confirm these effects in the 5xFAD mouse model of β-amyloid (Aβ) accumulation. Six- to seven-month-old male and female 5xFAD mice were treated with WSAq in their drinking water at 0 mg/mL, 0.5 mg/mL or 2.5 mg/mL for four weeks. In the fourth week of treatment, spatial memory, anxiety and depressive-like symptoms were evaluated. At the conclusion of behavioral testing, brain tissue was harvested, immunohistochemistry was performed, and the cortical expression of antioxidant response genes was evaluated. Both concentrations of WSAq improved spatial memory and reduced depressive and anxiety-related behavior. These improvements were accompanied by a reduction in Aβ plaque burden in the hippocampus and cortex and an attenuation of neuroinflammatory markers. Antioxidant response genes were upregulated in the cortex of WSAq treated mice. Oral WSAq treatment could be beneficial as a therapeutic option in AD for improving disease pathology and behavioral symptoms. Future studies focused on dose optimization of WSAq administration and further assessment of the mechanisms by which WSAq elicits its beneficial effects will help inform the clinical potential of this promising botanical therapy.

Pregnancy is a complex biological process which is associated with significant metabolic and hemodynamic changes of the maternal body which allow a normal fetal growth. The inability to adapt to these changes can affect the cardiovascular health. During pregnancy, women may experience mood swings, anxiety and emotional ambivalence. These symptoms can lead to stress and have a negative impact on the mental well-being of expectant mothers. It is crucial to know the aspects that can influence the development of cardiovascular problems among pregnant women in order to manage these cases properly. The current narrative review explores and summarizes the evidence regarding the impact of stress and anxiety on cardiovascular health in pregnant women. Understanding the physiological adaptations that the body undergoes throughout pregnancy is crucial for educating and supporting individuals as well as healthcare professionals. This enables them to recognize any risk factors or pathological conditions that may exacerbate pregnant women's health. In order to reduce maternal morbidity and mortality from cardiovascular disease, a psychological and cardiovascular risk factor screening that is done either before or during pregnancy may be able to identify situations that call for particular medical and/or psychological therapies.

New digital interventions have shown potential in managing asthma and improving patients' quality of life compared with conventional interventions. Our objective was to conduct an exhaustive survey of the application of digital health technologies in evaluating, treating, and self-managing psychological and psychopathological elements linked to asthma. We analyzed a compendium of research papers and systematic reviews pertaining to asthma, encompassing themes such as outdoor air pollution, early life wheezing disorders, atopic dermatitis, digital strategies for asthma self-management, psychiatric conditions and asthma, familial impacts on pediatric asthma, and the utilization of mobile health apps for managing asthma. We scrutinized eight chosen studies to evaluate the capacity of digital health technologies to enhance the man-agement and treatment outcomes of psychological factors related to asthma. The studies under review indicate that eHealth interventions, mixed reality instruments, mHealth technolo-gy-augmented nurse-led interventions, and smartphone apps incorporating Bluetooth-enabled sensors for asthma inhalers can markedly enhance self-management of symptoms, quality of life, and mental health outcomes, particularly in children and adolescents with asthma. Nonetheless, additional research is required to ascertain their efficacy and practicability across diverse populations and environments. Customized interventions that cater to the unique needs and preferences of asthma patients and associated psychological elements are vital to ensure the persistent and equitable adoption of these technologies. We underscore the significance of addressing psychological elements in the management and treatment of asthma and advocate for ongoing research and development in this domain.

Background: Caring for individuals with mental disorders poses significant challenges for caregivers, often leading to compromised quality of life and mental health issues such as stress, anxiety, and depression. This study aims to assess the extent of these challenges among caregivers in Greece, identifying which demographic factors influence their well-being. Method: A total of 157 caregivers were surveyed using the SF-12 Health Survey for quality of life assessment and the DASS-21 questionnaire for evaluating stress, anxiety, and depression symptoms. T-tests, Kruskal-Wallis tests, Pearson correlation coefficients, and regression analyses were applied to understand the associations between demographics, quality of life, and mental health outcomes. Results: The study found that caregivers, especially women and younger individuals, faced high levels of mental health challenges. Marital status, educational level, and employment status also significantly influenced caregivers' well-being. Depression was the most significant factor negatively correlating with the mental component of quality of life. The magnitude of burden experienced by caregivers highlighted the urgency for targeted social and financial support, as well as strategic treatment programs that consider caregiver well-being. Conclusions: Caregivers of individuals with mental disorders endure significant stress, anxiety, and depression, influencing their quality of life. Demographic factors such as age, gender, marital status, education, and employment status have notable impacts. Findings emphasize the need for society-wide recognition of caregivers' roles and the creation of comprehensive support and intervention programs to alleviate their burden, particularly in the context of the COVID-19 pandemic.

Background: A personalized approach to occupational medicine allows specialists to 1 prevent professional hazards such as stress-related depression and anxiety in extreme work environments. Objective: we aim to detect genetic markers of low resilience to stress. Methods: The study cohort included 97 elite athletes and 167 special forces personnel. The research team collected buccal mucosa samples and examined psychological status with the Hospital Anxiety and Depression Scale (HADS). We assessed 35 variants within selected genes that are most often associated with low resilience to stress, anxiety, and depression. Fisher’s Exact test was used to determine nonrandom associations between scores in the HADS scale and the genetic variants. We also trained machine learning models to predict score values from genotyping findings and ranked genetic biomarkers according to their predictive power. Results: High-risk depression profiles included C/T genotype of MTHFR C677T and A/C variant of MTHFR A1298C. Susceptibility to anxiety was associated with several polymorphisms regulating neuroactive substances, immune response, and coagulation. The ML models accurately detect depression or anxiety levels with MAE/ROV of 17.69±1.35 and 17.86±2.09% respectively. Conclusions: The study findings justify a polymorphic nature of anxiety and confirm the immune system's involvement in regulating stress response.

Intergenerational integration has given rise to a novel aging paradigm known as all-age communities, which is garnering international attention. In China, the aging population and the implementation of the three-child policy have resulted in increased demand for retirement and childcare services among residents in older neighborhoods. Consequently, there is a pressing need to retrofit these older neighborhoods to accommodate all-age living arrangements given the high demand they generate. Therefore, this study undertakes research interviews with residents and constructs an exploratory theoretical model rooted in established theory. To assess the significance of our model, we employ Smart PLS 3.0 based on 297 empirical data points. Our findings indicate that anxiety has a significant negative effect on payment behavior; objective perception, willingness to pay, and government assistance exert significant positive effects on payment behavior. By comprehensively analyzing the mechanisms underlying residents’ payment behavior, this study provides valuable insights to the government for promoting the aging process within communities and formulating effective transformation policies.

Acute myocardial infarction (AMI) is a leading cause of morbidity and mortality worldwide. This study aimed to test the efficacy of a newly-developed symptom self-management program on health outcomes among inpatients post-AMI. A pilot randomised, controlled trial was utilised. A convenience sample of 90 was recruited from a tertiary hospital in Singapore. Adult inpatients with post-AMI were randomly assigned to the three groups: IManage-HSet, IManage-FF or control group. Sample size was computed using power analysis. Data were collected through self-reported questionnaires and physiological instruments. Data analyses included univariate statistics, analysis of variance and repeated measure analysis of variance. Ninety participants were recruited with 30 in each group. Participants in the IManage-HSet and IManage-FF group had significantly greater relaxation (ηp2 = 0.11), lower objective stress (ηp2 =0.14), and greater knowledge (ηp2 = 0.62) than those of the control group. The two intervention groups had lower subjective stress (ηp2 = 0.04), depression (ηp2 = 0.01), and anxiety (ηp2 = 0.03) than the control but such differences did not achieve statistical significance. Furthermore, most participants reported that they were satisfied with the programs and they provided positive comments on the contents, educational materials and relaxation practice. This pilot study supports the potential benefits and feasibility of the IManage-VR and IManage-FF interventions on stress, perceived relaxation, knowledge and patient satisfaction. Contents of the symptom management interventions could be added into current cardiac rehabilitation programs. Future RCTs with multi-centered sites and larger sample size are required to further test the intervention. This study was prospectively registered with the International Standard Randomised Controlled Trial on the 5th August 2014 with registration number ISRCTN61027816.

Many researches have identified that adverse childhood experiences (ACEs) are associated with non-suicidal self-injury (NSSI) and suicidality. However, most studies have been restricted to a few types of ACEs. This study aims to investigate associations of 13 common types of ACEs with NSSI, suicidal ideation (SI) and suicide attempt (SA), as well as the mediation of depressive and anxiety symptoms therein. A total of 1771 students aged 11-16 years who participated in the baseline survey of the Chinese Adolescent Health Growth Cohort study were included for the analysis. ACEs, SI, SA, depressive and anxiety symptoms were recorded by standard questionnaire. Of included participants, 92.0% reported one or more category of ACEs. Smoking, parent-child separation, emotional abuse, physical abuse and being bullied were positively associated with NSSI, with the adjusted odds ratio (aOR) of 2.41(95%CI, 1.01-5.75), 1.80(1.28-2.54), 1.69(1.21-2.37), 2.08(1.44-3.01) and 1.87(1.35-2.59), respectively; smoking (4.03, 1.66-9.81), parent-child separation (1.42, 1.07-1.90), emotional abuse (1.91, 1.41-2.59), physical abuse (1.80, 1.27-2.57), emotional neglect (1.78, 1.28-2.49) and being bullied (2.08, 1.54-2.81) were positively associated with SI; smoking(4.30, 1.67-11.10), emotional abuse (2.42, 1.58-3.72) and being bullied (1.75, 1.17-2.60) were positively associated with SA. The associations of ACEs with NSSI, SI and SA were each partially or completely mediated through depressive and anxiety symptoms. Children and adolescents who had experiences of smoking, physical abuse and being bullied during childhood are consistently and independently associated with NSSI and suicidality, and these associations may be largely mediated through depressive and anxiety symptoms.

Nearly half a century has passed since the discovery of cytoplasmic inheritance of human chloramphenicol resistance. The inheritance was then revealed to take place maternally by mitochondrial DNA (mtDNA). Later, a number of mutations in mtDNA were identified as a cause of severe inheritable metabolic diseases with neurological manifestation, and the impairment of mitochondrial functions has been probed in the pathogenesis of a wide range of illnesses including neurodegenerative diseases. Recently growing number of preclinical studies has revealed that animal behaviors are influenced by the impairment of mitochondrial functions and possibly by the loss of mitochondrial stress resilience. Indeed, as high as 54% of patients with one of the most common primary mitochondrial diseases, mitochondrial encephalomyopathy with lactic acidosis and stroke-like episodes (MELAS) syndrome, present psychiatric symptoms including cognitive impairment, mood disorder, anxiety, and psychosis. Mitochondria are multifunctional organelles which produce cellular energy and play a major role in other cellular functions including homeostasis, cellular signaling, and gene expression, among other. Mitochondrial functions are observed to be compromised and to become less resilient under continuous stress. Meanwhile, stress and inflammation have been linked to the activation of the tryptophan (Trp)-kynurenine (KYN) metabolic system, which observably contributes to development of pathological conditions including neurological and psychiatric disorders. This narrative review discusses the functions of mitochondria and the Trp-KYN system, the interaction of the Trp-KYN system with mitochondria, and the current understanding of the involvement of mitochondria and the Trp-KYN system in preclinical and clinical studies of major neurological and psychiatric diseases.

Immersion in forest environments was shown to produce beneficial effects to human health, in particular psychophysical relaxation, so much that this practice is increasingly recognized as a form of integrative medicine. Limited evidence exists about both statistical significance and size of the effects conditioned on personal characteristics, as well as on the main external variables. The primary purpose of this study was to substantiate the very concept of forest therapy by means of the quantification and significance of the psychological effects, stratified by gender, age groups and place of residence. A preliminary qualitative analysis of the main determinants, in particular the method of conducting, the meteorological comfort and the concentration of volatile organic compounds in the forest atmosphere, was afforded. Seven forest therapy sessions were performed in late summer though early fall, resulting in 150 psychological self-assessment questionnaires administered before and after each session. The results were comparable or even better than others reported in the international literature. Moreover, preliminary evidence arose about different functionality towards specific psychological indexes conditioned at least on gender and age groups, as well as meteorological comfort, structured programs and, possibly, volatile organic compounds showed an impact on the outcomes.

COVID-19 pandemic has the potential to adversely affect the mental health of healthcare workers (HCWs). The public healthcare system in Greece was already facing serious challenges at the outset of the outbreak following years of austerity and an escalating refugee crisis. The multi-center, cross-sectional study aims to assess the levels and associated risk factors of anxiety, depression, traumatic stress and burnout of frontline staff in Greece. A total of 464 HCWs in six reference hospitals completed a self-administered questionnaire comprising of sociodemographic and work-related information and psychometric scales. The proportion of HCWs with symptoms of moderate/severe depression, anxiety and traumatic stress were 30%, 25% and 33% respectively. Burnout levels were particularly high with 65% of respondents scoring moderate/severe in Emotional Exhaustion, 92% severe in Depersonalization and 51% low/moderate in Personal Accomplishment. Predictive factors of adverse psychological outcomes included fear, perceived stress, risk of infection, lack of protective equipment and low social support. The psychological burden associated with Covid-19 in healthcare professionals in Greece is considerable with more than half experiencing at least mild mental health difficulties. Findings signal the need for immediate organizational and individually tailored interventions to enhance resilience and support wellbeing under pandemic conditions.

Opioids are highly addictive substances with a relapse rate of over 90%. While preclinical models of chronic opioid exposure exist for studying opioid dependence, none recapitulate the relapses observed in human opioid addiction. The mechanisms associated with opioid dependence, the accompanying withdrawal symptoms and the relapses that are often observed months or years after opioid dependence are poorly understood. Therefore, we developed a novel model of chronic opioid exposure whereby the level of administration is self-directed with periods of behavior acquisition, maintenance and then extinction alternating with reinstatement. This profile arguably mirrors that seen in humans, with initial opioid use followed by alternating periods of abstinence and relapse. Recent evidence suggests that dietary interventions that reduce inflammation, including omega-3 fatty acids such as docosahexaenoic acid (DHA), may reduce substance misuse liability. Using the self-directed intake model, we characterize the observed profile of opioid use and demonstrate that a diet enriched in polyunsaturated fat acids (PUFAs) ameliorates oxycodone-seeking behaviors in the absence of drug availability and reduces anxiety. Guided by the major role gut microbiota have on brain function, neuropathology, and anxiety, we profile the microbiome composition and the effects of chronic opioid exposure and DHA supplementation. We demonstrate that withdrawal of opioids led to a significant depletion in specific microbiota genera whereas DHA supplementation increased microbial richness, phylogenetic diversity, and evenness. Lastly, we examined the activation state of microglia in the striatum and found that DHA supplementation reduced the basal activation state of microglia. These preclinical data suggest that a diet enriched in PUFAs could be used as a treatment to alleviate anxiety induced opioid-seeking behavior and relapse in human opioid addiction.

Background: Clinical trails have revealed that patients with depression generally accompanied with learning and memory impairment, which critically impact on individual’s health and development. Danggui-Shaoyao-San (DSS), a famous Chinese complex prescription, significantly overcame depression and relieved cognitive disorder based on previous research and publication. However, its effectsand potential mechanism against chronic restraint stress (CRS) remained unknown. Methods: CRS animal model was established and mice were divided to six groups while they were oral administrated with Danggui-Shaoyao-San at doses of 1.25, 2.5 and 5 g/kg for 14 days. Emotional and cognitive performances were detected by behavior tests, meanwhile neural plasticity and its molecular mechanism were examined by Dil staining, western blot and immunofluorescence. Results: DSS treatment dose-dependently improved locomotion ability in open filed test, overcame depression behavior in forced swimming test and elevated plus maze test, enhanced learning and memory ability in Morris water maze test. CRS decreased number of total spines and mushroom spines, while DSS treatment dose-dependently restored these by Dil staining. Expression of BDNF and GluR1 were significantly down-regulated in CRS group, which were significantly normalized by DSS. Conclusions: DSS treatment dose-dependently reversed CRS-induced cognitive impairments by inducing structural remodeling of neurons.

This paper describes the specification of spatially varying coefficient (SVC) regression models using Generalized Additive Models (GAMs). The GAMs include Gaussian Process (GP) splines (smooths) for each covariate parameterised with observation location and generate SVC estimates that capture spatially varying relationships. The ability of the proposed GAM approach to estimate true spatially varying coefficients was compared with that of Multiscale Geographically Weighted Regression (MGWR) using simulated data with complex spatial heterogeneities. The geographical GP GAM (GGP-GAM) was found to out-perform MGWR across a range of fit metrics and resulted in more accurate coefficient estimates and lower residual errors. The model for one of simulated datasets was investigated in detail to illustrate GAM diagnostics, model checks, spline / smooth convergence and basis evaluations, and tuning via the number knots. A larger simulated case study was investigated to explore the trade-offs between GGP-GAM complexity, performance and computation. Finally the GGP-GAM and MGWR approaches were applied to an empirical case study. The resulting models had very similar accuracies and fits, and generated subtly different spatially varying coefficient estimates. A number of areas of further work are identified.

Cardiolipin (CL), an essential phospholipid, is localized in the mitochondrial inner membrane, where it plays a critical role in oxidative phosphorylation (OXPHOS) and energy metabolism. This study reviews current findings on cardiolipin's function within neurodegenerative diseases (NDDs), focusing on Alzheimer's and Parkinson's diseases, along with Barth Syndrome. Using lipidomics and protein-lipid interaction analysis, we examine the role of CL in mitochondrial integrity and neuronal function. The primary objective is to analyze how alterations in CL composition and distribution can serve as biomarkers and therapeutic targets for NDDs. Results highlight significant insights into the potential for CL-targeted therapies.

Dependence on seafood imports is growing for many nations, effectively exporting the environmental and social impacts from consuming nations to producers. While countries have commitments to national regulations and global sustainability targets, such as the United Nations Sustainable Development Goals, sustainability standards for imported seafood are lacking. We examine the sustainability implications of high-income countries’ reliance on seafood imports, using Australia as a case study. Australia imports around 60-70% of domestically consumed seafood, with 96.5% imported from 20 countries. Compared to Australia, these countries generally have lower environmental performance, higher vulnerability to slavery, and increased risk of illicit trade in their supply chains. Yet, biophysical limits on wild catch, low demand for underutilized species, social conflict, environmental concerns over aquaculture expansion, and low domestic production, suggest imports will likely remain an important source of seafood for Australian consumers. Other high-income countries in Europe and North America face similar challenges. These countries have a pivotal role in promoting responsible trade. Comprehensive sustainability assessments that integrate environmental and social considerations of production and trade, improved mapping of seafood production activities, and more granular trade data will be critical for informed and effective trade regulations that support sustainability commitments.

ChatGPT, a state-of-the-art AI model created by OpenAI, is renowned for its ability to produce text responses that closely mimic human communication. Recently, it has broadened its scope to encompass multimodal interactions, rendering it particularly advantageous for medical applications. In this paper, we explore into the potential of ChatGPT in the realm of Ultrasound (US) imaging, Our investigation encompasses a series of case studies and examples, each tailored to demonstrate ChatGPT’s application in various aspects of US imaging. These include emphasizing its capacity for intricate analyses, including grayscale texture examination and perfusion metrics in contrast-enhanced ultrasound (CEUS). Moreover, its involvement in real-time imaging guidance, its role in streamlining workflow efficiencies, and its utility in the simplification of medical report generation to facilitate better patient communication. The case studies, while successful, unveil certain limitations and challenges, prominently featuring concerns regarding privacy and technical constraints. Despite these challenges, the evidence gathered from our examples indicates that ChatGPT's innovative features and its ability to operate across multiple modes significantly enhance the efficiency of quantitative image analysis in US imaging. By improving diagnostic precision and potentially elevating patient care outcomes, ChatGPT marks a significant stride forward in healthcare technology, though it necessitates careful consideration of its associated ethical and technical challenges.

Introduction: Bladder pain syndrome (BPS)/interstitial cystitis (IC) is a chronic inflammatory condition characterized by bothersome symptoms as pain, urgency, urinary incontinence and in some cases urinary retention, impacting a patient’s quality of life. However, also recurrent cystitis could cause a chronic bladder inflammation which can explain discomfort of the bladder and similar symptoms, often referred by younger patients during clinical evaluation. The aetiology of IC/BPS is still unknown, and it may be multifactorial. Although a definitive treatment is not available, the challenge is finding new therapeutic strategies. Different intravesical treatments such as heparin, hyaluronic acid, chondroitin sulfate, pentosan polysulfate, dimethylsulfoxide, liposomes, and botulinum onabotulinumtoxinA (BoNT‐A) are commonly proposed for BPS/IC. The aim of study was to evaluate the anti‐inflammatory effects of intravesical Vessilen® (a new formulation of 2% adelmidrol (the diethanolamide derivative of azelaic acid) + 0.1% sodium hyaluronate) administration in patients affected by IC/BPS or other bladder disorders. Methods: This was a prospective observational study. At baseline and after the treatment, validated questionnaires were administered to the patients: the Visual Analogue Scale (VAS) and International Consultation on Incontinence Questionnaire Female Lower Urinary Tract Symptoms Modules (ICIQ‐FLUTS Long Form). The subjective perception of the severity of symptoms was investigated by the Patient global impression scale (PGIs). Results: Based on 25 patients who completed the cycle of weekly instillation for six weeks, we observed a significant decrease in the severity of bladder symptoms according to both ICIQ‐FLUTS scale (89.3 vs 61.3; p=0.021) and VAS score (4.4 vs 2.6; p<0.001). Moreover, according to PGI‐I, 80% of patients observed an improvement in symptoms (PGI‐I score ≤ 3). Conclusion: Intravesical administration of adelmidrol combined with sodium hyaluronate (Vessilen®) could be an innovative therapeutic approach for patient complaining interstitial cystitis/bladder pain syndrome (IC/BPS) or other chronic inflammatory bladder disorders, due to its well‐known anti‐inflammatory and antinociceptive properties.Introduction: Bladder pain syndrome (BPS)/interstitial cystitis (IC) is a chronic inflammatory condition characterized by bothersome symptoms as pain, urgency, urinary incontinence and in some cases urinary retention, impacting a patient’s quality of life. However, also recurrent cystitis could cause a chronic bladder inflammation which can explain discomfort of the bladder and similar symptoms, often referred by younger patients during clinical evaluation. The aetiology of IC/BPS is still unknown, and it may be multifactorial. Although a definitive treatment is not available, the challenge is finding new therapeutic strategies. Different intravesical treatments such as heparin, hyaluronic acid, chondroitin sulfate, pentosan polysulfate, dimethylsulfoxide, liposomes, and botulinum onabotulinumtoxinA (BoNT‐A) are commonly proposed for BPS/IC. The aim of study was to evaluate the anti‐inflammatory effects of intravesical Vessilen® (a new formulation of 2% adelmidrol (the diethanolamide derivative of azelaic acid) + 0.1% sodium hyaluronate) administration in patients affected by IC/BPS or other bladder disorders. Methods: This was a prospective observational study. At baseline and after the treatment, validated questionnaires were administered to the patients: the Visual Analogue Scale (VAS) and International Consultation on Incontinence Questionnaire Female Lower Urinary Tract Symptoms Modules (ICIQ‐FLUTS Long Form). The subjective perception of the severity of symptoms was investigated by the Patient global impression scale (PGIs). Results: Based on 25 patients who completed the cycle of weekly instillation for six weeks, we observed a significant decrease in the severity of bladder symptoms according to both ICIQ‐FLUTS scale (89.3 vs 61.3; p=0.021) and VAS score (4.4 vs 2.6; p<0.001). Moreover, according to PGI‐I, 80% of patients observed an improvement in symptoms (PGI‐I score ≤ 3). Conclusion: Intravesical administration of adelmidrol combined with sodium hyaluronate (Vessilen®) could be an innovative therapeutic approach for patient complaining interstitial cystitis/bladder pain syndrome (IC/BPS) or other chronic inflammatory bladder disorders, due to its well‐known anti‐inflammatory and antinociceptive properties.

This paper reviews the measurement challenges associated with 3D scanning techniques in civil engineering. It explores the practical aspects of scanning buildings and complex surfaces through various case studies. The paper details the conventional use of Terrestrial Laser Scanning (TLS) for reconstructing the technical documentation of a hall. It then describes an unconventional application of this technique for measuring an ETICS (External Thermal Insulation Composite System) wall, aiming to detect microdeformations caused by environmental factors controlled within a climatic chamber. The measurements of the insulated wall were subsequently repeated using a metrological grade laser scanner. Numerical data was analyzed with inspection engineering methods. This approach yielded qualitative and quantitative results. Although the qualitative results were consistent, the quantitative data revealed some inconsistencies. To address discrepancies in the quantitative data, a comparative analysis was performed, which highlighted critical findings and areas of divergence.

Early detection of cervical cancer is the need of the hour to stop the fatality from this disease. There have been various CAD approaches in the past that promise to detect cervical cancer in an early stage, each of them having some constraints.This study proposes a novel ensemble deep learning model, VLR (variable learning rate), aimed at enhancing the accuracy of cervical cancer classification. The model architecture integrates VGG16, Logistic Regression, and ResNet50, combining their strengths in an offbeat ensemble design. VLR learns in two ways: firstly, by dynamic weights from three base models, each of them trained separately; secondly, by attention mechanisms used in the dense layer of the base models. Hyperparameter tuning is applied to further reduce loss, fine tune the model’s performance, and maximize classification accuracy. We performed K-fold cross-validation on VLR to evaluate any improvements in metric values resulting from hyperparameter fine tuning. We have also validated our model on images captured in three different solutions and on a secondary dataset. Our proposed VLR model outperformed existing methods in cervical cancer classification, achieving a remarkable training accuracy of 99.95% and a testing accuracy of 99.89%.

To date, SARS Cov-2 virus has caused more than 775 million cases worldwide and led to 7 million deaths. The virus enters cells with the aid of the ACE2 receptor located in the airway epithelium, but also in endothelial cells lining the inner walls of vessels. Endothelial damage results in impaired blood flow and gas exchange. Statins have been shown to have a pleiotropic effects on the vascular epithelium. Aim of the study: Assessment of the efficacy and safety of statin therapy in patients with COVID-19. Methods: Two hundred and one COVID-19 patients hospitalized at the Jerzy Gromkowski Regional Specialist Hospital between March 2020 and December 2021 (i.e. during the period dominated by Alpha, Beta, Gamma and Delta variants). Patients were divided into three groups: (I) patients treated with statins prior to the admission to the hospital; (II) patients started on statins after admission due to Covid-19; (III) control patients with Covid-19, not treated with statins either prior to or during hospitalization. Met Statistica 13.1 calculations were used in the paper. Shapiro-Wilk, Kruskal-Wallis and ANOVA tests were also performed. Results: Out of the 201 patients total, group I comprised 66 patients with a mean age of 66.2 years; group II comprised 33 patients with a mean age of 75.3 years; and the control group comprised 97 patients with a mean age of 61.1 years. The groups characteristics did not show significant differences in terms of gender, place of hospitalization, percentage of Covid-19 vaccinations, number of convalescents. Death was observed in: 12% of patients in group I, 6% of patients in group II, and 6% of patients in group III. Body Mass Index (BMI) in group I was 31.3: a value significantly higher than the control group’s 28.3, (p<0.05). The severity of Covid-19 assessed on admission in group I – 4.09 – was statistically higher than in the control group 3.52 (p<0.05). The number of pulmonary embolism incidents did not differ between groups. Conclusions: During the period dominated by Alpha, Beta, Gamma and then Delta variants, we found no statistically significant positive or negative effects of statin therapy on the duration of hospitalization, number of complications or percentage of deaths between the two studied groups of patients: those who received statins prior to hospitalization, and those who received statins during hospitalization.

Pichia pastoris is extensively employed as a host for expressing foreign proteins, and its secretion system is especially advantageous for efficient protein purification. Ulp1 is essential for the cell cycle. In Saccharomyces cerevisiae, the absence of Ulp1 leads to G2/M cell cycle arrest. Similarly, in Pichia pastoris, we also observed G2 phase stalling in Ulp1 knockout cells. RNA-seq data revealed significant changes in seven genes, including INO1. Interestingly, overexpressing INO1 in Ulp1 knockout cells restored cell proliferation, suggesting that Ulp1 regulates cell proliferation through INO1. However, adding extra inositol to Ulp1 knockout cells was not able to restore cell prolifera-tion, indicating that the enzyme activity of INO1 is not essential for cell proliferation. Our data provide new insights into Ulp1 functions in the cell cycle and raise new questions about yeast cell cycle regulation.

Background: RO and ChRCC are kidney tumours with overlapping characteristics, making differentiation between them challenging. Objectives: The objective of this research is to create a radiogenomics map by correlating radiomic features to molecular phenotypes in ChRCC and RO, using resection as the gold standard. Methods: Fourteen patients (6 RO and 8 ChRCC) were included in the study. A total of 1,875 radiomic features were extracted from CT scans, alongside 632 cytobands containing 16,303 genes from the genomic data. Results: Feature selection algorithms applied to the radiomic features resulted in 13 key features. From the genomic data, 24 cytobands highly correlated with histology were selected and cross-correlated with the radiomic features. The analysis identified four radiomic features that were strongly associated with seven genomic features. Conclusion: These findings demonstrate the potential of integrating radiomic and genomic data to enhance the differential diagnosis of RO and ChRCC, paving the way for more precise and non-invasive diagnostic tools in clinical practice.

Background and Objectives: A degenerative joint disease that primarily affects the elderly, osteoarthritis (OA) causes pain, decreased mobility, and a lower quality of life. The effectiveness of GerovitalH3, a biotrophic medication created by Ana Aslan, in reducing pain and enhancing function in older people with osteoarthritis in the knee and hip is assessed in this study. Materials and Methods: Two groups of 201 patients aged 65 and older participated in a randomized, case-control clinical trial. One group received physical therapy and GerovitalH3 periarticular injections, while the other group received just physical therapy. In addition to functional evaluations using the Lequesne Index, Activities of Daily Living (ADL), and Instrumental ADL (IADL) scores, pain was assessed using a Visual Analogue Scale (VAS). Results: The GerovitalH3 group showed a substantial decrease in pain (p<0.001) and an improvement in daily activities (p<0.001) when compared to the control group. However, there was no significant difference in walking scores (p = 0.171). There were no significant adverse effects noted. GerovitalH3 did not outperform physical therapy for reducing depression, even though both groups displayed some improvement in this area. Conclusions: This study opens a new possibility for periarticular injections of Gerovital H3 treatment combined with physical therapy, which may represent a safe and effective non-surgical option for elderly individuals struggling with OA pain and functional limitations. The findings of this study reinforce the need for further research, particularly randomized controlled trials with larger sample sizes and longer follow-up periods.

Predicting the remaining useful life (RUL) of mechanical bearings is crucial in the industry. 1 Estimating the RUL enables the assessment of health bearing, maintenance planning, and signifi- 2 cant cost reduction, thereby fostering industrial development. Existing models rely on traditional 3 feature engineering, with feature changes because operating conditions pose a major challenge to 4 the generalization of RUL prediction models. This study focuses on neural network-based feature 5 engineering and the downstream prediction of the RUL, eliminating the need for specific prior 6 knowledge and simplifying the development and maintenance of models. Initially, a convolutional 7 neural network (CNN) model is employed for feature engineering. Subsequently, a bidirectional 8 long short-term memory network (Bi-LSTM) model is used to capture the time-series degradation 9 characteristics of the engineered features and predict the RUL through regression. Finally, the study 10 examines the influence of operating conditions in the model and integrates domain adaptation to 11 minimize differences in feature distribution, thereby enhancing the model’s generalizability for the 12 RUL prediction.

Purpose/Objective: Frequent consumption of fermented carbohydrates and bottle feeding contribute to the development of early childhood caries (ECC). There are no substantial findings on the effects of breastfeeding patterns on oral health conditions in children in the United States. We aimed to assess the nexus between exclusive breastfeeding during the first 6 months and oral health disorders, namely toothache, decayed teeth, or unfilled cavities in early childhood. Materials and Methods: Design: Cross-sectional epidemiologic design of nationally representative data collected via telephone surveys in the United States was utilized. Setting: National Survey of Children’s Health, 2012 Participants: Population-based random sample of parents/guardians of 24,655 children aged 6 months to 5 years. Main Outcome and Measure: Parent-reported oral health condition including toothache, decayed teeth or unfilled cavity in the past 12 months. Results: A total of 2,392 (9.7%) children aged 6 months to 5 years experienced an oral health disorder, mainly toothache, decayed teeth, or unfilled cavity in the previous 12 months. Relative to non-Hispanic White children (7.7%), a greater proportion of non-Hispanic Black (12.9%) and multi-racial children (12.6%) experienced oral health disorders (OHD). In the univariable model, relative to children who never breastfed, those who were breastfed exclusively for 6 months were 28% less likely to present with OHD, Odds Ratio (OR) = 0.72, 95% CI, 0.52-0.98. After adjustment, the protective nature of exclusive breastfeeding against OHD did not remain, adjusted OR (aOR) =1.11, 99% CI 0.79-1.57. Children of mothers with fair/poor health were almost twice as likely to have poor OHD compared with children of mothers with excellent/very good health (aOR = 1.79, 99% CI 1.08-2.69). Conclusions and Relevance: Exclusive breastfeeding for the first six months of life improved pediatric OHD and remains mutually beneficial for mothers and children. These findings suggest the importance of exclusive breastfeeding and maternal health in relation to dental hygiene in children.

With the improvement of computer, artificial intelligence, information technology and other technical levels, the relationship between man-machine environment systems is more complicated and diversified. The optimization, iteration and development of the new generation of intelligent equipment system and human-computer interaction interface put forward higher requirements for ensuring the safety of personnel, improving the efficiency of human-computer interaction and improving the efficiency of the system. Such as intelligent cabin adaptive cognitive decision aid system, how to adopt intelligent information display and human-computer interaction, optimize information processing, strengthen situational awareness; How to effectively present information and improve the efficiency of human-computer interaction, so that the system has good security, applicability and maximize its effectiveness; How to deal with man-machine matching and man-machine collaboration problems, so as to improve the efficiency of man-machine/unmanned collaborative work. Human factors throughout the life cycle of equipment systems must be fully considered. The human factor is considered in the system design, so that people, machines and the environment can work together and adapt to each other, so as to achieve benign interaction and feedback between people and equipment and interface and complete the full transmission and communication of human-machine intelligent interaction information. The development of new aircraft human-computer interaction systems combined with new technological methods has also gradually changed the role of pilots and staff. From the system operator gradually into the monitor and decision maker, especially with the improvement of the degree of intelligent flight, information technology, advanced complex airborne equipment is increasing, the amount of information that operators need to deal with is also increasing, and the allowed time for judgment and decision is very short, and the mental resources that pilots bear are gradually rising. As the mental load is a key factor affecting the allocation of cognitive tasks, when encountering emergency situations, the mental load overload caused by the increase of information processing tasks often occurs, which seriously affects the task performance of operators, physical and psychological comfort and flight safety, and thus affects the efficiency and safety of the entire aircraft man-machine system. This requires us to conduct real-time analysis of human-computer interaction situational awareness, especially the individual cognitive state as an uncontrollable factor.

This study reveals that with similar valence of empathy, the tendency for humans to help humans in need is stronger than the animal in need. It also illustrates that a convincible advertisement for a charity should be a combination of various feelings, mainly empathic anger, in addition to compassion or empathy. To gain support from young individuals or donors regardless of their personal values, the egoistic values particularly, both the NPOs in humanitarian aid as well as in environmental protection or conservation should develop ads by which each individual or donor is aroused by either an empathic anger and empathic joy or both. This claim is more applicable for any ads developed to help people in need more than animals in need. Nevertheless, this study also found the role of an animal, generally known as innocent, as an actor in an ad is likely more crucial than human. Subjects with high-egoistic values appeared to get vulnerably aroused to a higher extent by being immersed in animal’s suffering than human’s suffering. The feeling of arousal seemed to motivate subjects with high-egoistic values to not decrease the amount of donation to a charity.

In this paper, we explore the surprising behavior of certain discrete maps, drawing inspiration from Collatz-like problems and advanced techniques in analytic number theory, dynamical systems, and differential geometry. Specifically, we investigate a driven cubic-quintic Duffing equation and predict the number of limit cycles around equilibrium points. Furthermore, we develop a novel theoretical framework for chaos suppression in damped-driven systems, leveraging sequences derived from Collatz-like problems. Our study also focuses on analyzing the density of these sequences in both Euclidean and Riemannian metric spaces, providing a comparative analysis of their distribution properties. We estimate the growth rate of sequence density analytically and numerically, highlighting the sensitivity of the density values to the choice of parameters in both metric spaces. Our results present new insights into the behavior of these sequences and their implications for number theory, chaotic dynamics, and geometric analysis.

This study investigates the performance and environmental impact of n-butanol blended with Jet-A fuel in turbo-engines, aiming to assess its viability as a sustainable aviation fuel (SAF). The research involves experimental testing of various blends, ranging from low to high concentrations of methanol, to determine their effects on engine performance and emissions. The experimental setup includes comprehensive measurements of engine parameters such as thrust, fuel consumption rates, and exhaust gas temperatures. Emissions of nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO), and unburned hydrocarbons (HC) are also analysed to evaluate environmental impacts. Key findings indicate that n-butanol/Jet-A blends can significantly enhance combustion efficiency and reduce emissions compared to conventional Jet-A fuel. Higher n-butanol concentrations lead to improved thermal efficiency and lower NOx and CO emissions. However, PM emissions slightly increase with higher methanol content. The study underscores the potential of n-butanol as a SAF for turbo-engines, highlighting its ability to mitigate environmental impacts while maintaining or improving engine performance. This research supports the feasibility of integrating n-butanol into Jet-A blends for turbo-engine applications, emphasizing its role in achieving more environmentally friendly aviation operations.

Many laboratory power supply had been designed with higher output variable voltages but with small amount of output current, in this design, a variable 1.25 to 30Vdc laboratory power supply with capable of producing up to 10.0A has been designed using a three terminal voltage regulator with pass transistors.

Introduction: Acute rhinosinusitis (ASR) is a common condition in children, which can be burdened by orbital complication (OC) or intracranial complications (IC) that are rare but have potential for serious sequelae; therefore, it needs prompt diagnosis and treatment. The first line of treatment is intravenous antibiotic therapy. In case of failure of clinical improvement after 48 hours, hypovisus or negative prognostic factors (intracranial abscess, large orbital abscess or in intraconic or lateral localization, cavernous sinus thrombosis), surgical treatment is indicated. Objective: the purpose of this work is to describe the clinical profile, treatments and outcome of a series of patients undergoing surgical treatment for complications of ARS at a tertiary referral center. Material and methods: a retrospective analysis of clinical databases was conducted to identify all patients under 16 years of age who underwent surgical treatment for complications of ARS during the 20-year period 2000-2023. Demographic characteristics, clinical data, radiological investigations, surgical treatment, and follow-up performed were reported for each case. Results: 29 patients (20 males and 9 females), mean age 13 years, were included, 69% of whom had OC, 21% had IC, and 7% had both OC and IC. The main symptoms of OC were orbital edema, hypovisus and diplopia; while the main symptoms of IC were headache, fever, comitial seizures and focal neurological symptoms. Mean hospitalization time was 11.75 (± 9.2) days. The mean length of hospital stay (LOS) was 9.1 days for OC, 21 days for IC and 14 days for OC + IC. A single patient manifested a Potts Puffy Tumor, with a LOS of 10 days. Basal CT and gadolinium-enhanced MRI were performed in all cases. Intravenous antibiotic therapy and surgical clearance was undertaken. The majority of patients (76%) underwent endoscopic endonasal approach, 24% external transorbital approach, 1,16% orbital decompression and 0,58% superior eyelid approach. Any complications related to the surgical procedures were found. All patients with hypovisus and diplopia had complete recovery. During follow-up 7 patients (24%) had sinus recurrences, at a time range of 1 to 4 years after surgery. Conclusion: our experience, in agreement with the data reported in the literature, confirmed the importance of appropriate diagnostic-therapeutic management to avoid potentially serious sequelae of complicated ARS.

This survey is part of a Hungarian Research OTKA project that examines the vegetation of sandy grasslands along the Danube. During this study, two grass species, Festuca wagneri and Festuca tomanii, were identified as potentially suitable for urban planting and turf establishment based on preliminary research. Our aim was to determine the germination success of seeds from aesthetically selected individuals and to identify the soil types on which they germinate most effectively. This information could be crucial for future cultivation efforts. From the collected Festuca individuals, were analyzed 30 specimens of each taxon under garden conditions and selected the indi-viduals for germination. The Festuca tomanii individuals were uniform, so we selected only 5 individuals. The Festuca wagneri individuals were categorized into three groups: upright, spreading, and low types. It was assumed that Festuca species seeds would germinate better in sandy soils. To test this, seeds from ten Festuca wagneri and five Festuca tomanii individuals, selected based on aesthetic criteria, were sown in six different substrates: a sand-peat mixture, sand, coconut fiber, peat, a coconut fiber-sand mixture, and native sandy soil. Contrary to expectations, the growth and germination rates of seeds sown in peat and coconut fiber substrates were higher than those in native sandy soil. These results suggest that Festuca seeds germinate better on substrates resembling dead plant debris with a peat-like structure or on the surface of live mosses, rather than on bare sand. Among the examined individuals, the seeds from the spreading Festuca wagneri group exhibited the highest germination rate, making this group particularly suitable for urban environments. Addi-tionally, one of the upright Festuca wagneri individuals showed the highest growth rate and should also be considered for urban planting. In contrast, despite their uniform appearance, the Festuca tomanii individuals did not demonstrate similar germination trends. In fact, the seeds from two clumps did not germinate at all, indicating that further selection is necessary.

Abstract: Since the establishment of multiparty democracy in the 1990s, Malawi has experienced significant political shifts, with elections playing a crucial role in shaping the political landscape. However, there is a lack of comprehensive understanding of the spatio-temporal dynamics of election results, especially regarding voting patterns and their effects on electoral outcomes. This gap hinders political parties, politicians, and electoral stakeholders in effectively managing regional and temporal changes in voting behaviors. Geographic Information Systems (GIS) are underutilized in Malawi for studying geo-graphical and temporal election data. This study utilized GIS to analyze the spatial pat-terns of election results in Malawi since the advent of multiparty democracy. By collecting geographic data on election outcomes, including vote counts, candidate performance, voter turnout, and other relevant data, the study examined how the geographic distribution of votes impacts electoral results. GIS techniques such as spatial analysis, mapping, and spatial statistics were employed to assess the data and create maps illustrating spatial patterns in Malawi's election outcomes. The study revealed that voting patterns in Malawi are significantly influenced by regional lines. These insights can inform political campaigns, voter mobilization efforts, and strategies for electoral reform.

: Psychological members can provide college students with solid peer support and sustain their mental health. This study examined the relationship between empathy, interpersonal communication, listening and psychological members' competence among 407 university students, and also analysed the mediating role of interpersonal communication and listening. The results showed that psychological members‘ empathy, interpersonal communication, and listening were significantly and positively related to psychological members’competence, interpersonal communication mediated the relationship between empathy and competence, listening mediated the relationship between empathy and competence, and interpersonal communication and listening chained the mediating role between empathy and competence. This suggests that psychological members' empathy enhances their competence by influencing their interpersonal communication and listening, which in turn enhances their competence.

Cuproptosis, a copper-dependent cellular death mechanism, is typically overlooked in glioblastoma diagnosis. Lipoylation is needed for cuproptosis, and FDX1 controls this process. Cuproptosis in prognostic models may drive cancer treatment. This study evaluated cuproptosis and glioblastoma cell proliferation. The Cancer Genome Atlas provided annotated clinical, genetic mutation, and RNA sequencing data for the TCGA_GBM and TCGA_LGG cohorts. Patients with gliomas were randomly allocated to the validation or training cohort. Least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression models were utilized to evaluate which model best predicted prognosis in the training cohort. The models' independent predictive power was evaluated throughout the cohort. A previous study revealed 19 genes related to ferroptosis. LncRNAs associated with cuproptosis were identified by coexpression analysis. Cox discovered 17 cuproptosis-associated lncRNAs and established a predictive model. The median risk score classified patients as high- or low-risk. K‒M survival analysis demonstrated significant differences in overall survival among risk categories. Principal component analysis (PCA) and receiver operating characteristic (ROC) curve analysis were used to test the model’s predictive power. Univariate and multivariate Cox regression analyses revealed risk score-related independent prognostic factors. Multivariate Cox regression analysis was used to construct a nomogram for marker-based prognosis. The risk category affected the tumour mutation rate. High-risk glioma patients benefit from immunotherapy. Glioma drug sensitivity was also substantially linked with the risk score. The expression of 17 cuproptosis-related long noncoding RNAs (lncRNAs) may assist in the stratification of glioma patient prognosis, molecular characteristics, cell cycle gene regulation pathways, the TME, and clinicopathological aspects. Our clinical sample and database analysis revealed that cuproptosis influences glioma prognosis and may guide therapy.

Recent advancements in gut microbiome research have highlighted the complex interplay between gut microbiota and various physiological and pathological processes, showing that gut microbiota plays a vital role in human health and disease. Imbalances in the gut microbiota, known as dysbiosis, have been associated with a range of health conditions, including gastrointestinal disorders, metabolic diseases, etc. In response to these findings, probiotics, prebiotics, synbiotics, and postbiotics have emerged as a promising therapeutic strategy to modulate gut microbiota composition and functionality. This review paper explores the latest research on how gut microbiota impacts host physiology, immune responses, and overall well-being. Furthermore, the paper delves into the therapeutic potential of probiotics, postbiotics, prebiotics, and synbiotics in therapeutic applications and curing various diseases. The paper also addresses the challenges and opportunities in the field, highlighting the need for personalized approaches to probiotic therapy and the importance of considering factors such as strain specificity, dosing, and safety.Overall, this review aims to provide a comprehensive overview of the evolving landscape of gut microbiota and probiotics, prebiotics, synbiotics, and postbiotics as novel therapeutic agents. It underscores the potential of harnessing the gut microbiome to improve health, prevent diseases, and complement traditional medical interventions. As research in this field continues to expand, a deeper understanding of the gut microbiota and probiotics, prebiotics, synbiotics, and postbiotics promises new avenues for preventive and therapeutic healthcare strategies.

Neurodegenerative diseases that include Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), Huntington's disease (HD), and multiple sclerosis (MS), arise due to numerous causes like protein accumulation and autoimmunity, characterized by neurologic depletion which lead to incapacity in normal physiological function such as thinking and movement in these patients. Glial cells perform a critical role in protective neuronal function; in the case of neuroinflammation, glial cell dysfunction can promote the development of neurodegenerative diseases. MiRNA participates in gene regulation and plays a vital role in many biological processes in the body; in the central nervous system (CNS), it can play an essential part in neural maturation and differentiation. In neurodegenerative diseases, miRNA dysregulation occurs, enhancing the development of these diseases. In this review, we discuss neurodegenerative diseases (Alzheimer's disease (AD), Parkinson's disease (PD), amyotrophic lateral sclerosis (ALS), and multiple sclerosis (MS)) and how miRNA is preserved as a diagnostic biomarker or therapeutic agent in these disorders. Finally, we highlighted miRNA as therapy.

Many cities are increasingly adopting blue-green infrastructure (BGI) to bolster resilience against environmental challenges. Beyond its well-acknowledged environmental benefits, the role of BGI in enhancing social resilience is becoming an equally important area of focus. However, the integration of BGI to foster social resilience presents complexities, stemming from the evolving and occasionally ambiguous definition of social resilience. Given its broad application across diverse disciplines, understanding and measuring social resilience proves difficult, posing challenges to understanding it within a BGI context. However, integrating BGI to support social resilience is complicated by the evolving and sometimes ambiguous definition of social resilience. This concept's broad applicability across various disciplines makes its understanding and measurement challenging, especially within the BGI context. Consequently, a clear need for a framework to effectively understand and measure social resilience in BGI settings exists. This paper synthesizes existing social resilience frameworks, particularly leveraging the comprehensive 5S framework by Saja et al. (2018), to create a new conceptual framework that addresses the unique social dimensions and benefits of BGI, incorporating insights from a broad literature review on social resilience. The framework is structured as a three-tier model centered around four key subdimensions of social resilience: social values, social capital, social structure, and social equity and their interrelationships. Characteristics and indicators are customized to support the BGI context integrating both physical and human dimensions within a mixed methods approach to measurement. Specifically, this research develops a conceptual BGI framework to probe into BGI practices and perspectives that enhance social resilience and considers demographic diversity and the spatial attributes of urban environments to understand how to foster more inclusive and socially resilient BGI spaces.

BackgroundAdvanced radiological stage of knee osteoarthritis (OA) and obesity are predictive of poorer and shorter response to viscosupplementation, but very few is known regarding the impact of other factors such as sport practice, comorbidities or anatomical features of OA. ObjectivesTo investigate the patient’s and OA characteristics associated with the duration of effectiveness (DE) of viscosupplementation in patients with knee OA.MethodsCross-sectional single center trial in patients with knee OA treated with intra-articular (IA) hyaluronic acid (HA) injection(s) within the previous 3 years. The investigator collected demographic and radiographic data (Kellgren grade, involved knee compartments), dosing regimen (single or repeat injections), presence and volume of joint effusion, previous or concomitant IA corticosteroid injection, number of previous viscosupplémentations and the comorbidities. The patient completed a questionnaire including the self-assessment of DE (number of weeks during which viscosupplementation was effective on symptoms), the activity level (sedentary, active, athletic), the level of sport activity (light, moderate or intensive). Predictors of DE were studied in univariate and multivariate analyses ResultsOne hundred five patients (149 knees) were analyzed (62% women, mean age 66.1 ± 13.2 years, mean BMI 27.5 ± 7.5 kg/m²). The mean DE was 48.2 + 24.8 weeks. In a bivariate analysis, the predictors of a shorter with DE were BMI >27.5kg/m2, more than 3 previous viscosupplémentations, Kellgren grade 4, sedentary patients, and more than 1 affected compartment. In the multivariate analysis, 4 independent factors remained associated with a shorter DE: BMI >27.5 kg/m2, knee multi-compartment damage, number of viscosupplements >3, sedentary lifestyle. A statistically significant association between a longer DE and treated arterial hypertension was found suggesting a beneficial effect of certain antihypertensive drugs. ConclusionThe study confirms the harmful influence of an increased BMI, It also shows that viscosupplementation is more effective in unicompartmental OA. Other points worth highlighting are the reduction in the duration of efficacy with repeated cycles of injections and the benefit of a regular physical activity.

The primary sources of particulate matter are linked to human activity. Certain particulate emissions, particularly those of a finer nature, can significantly impact human health, making them one of the most concerning pollutants. Ultrafine particles (UFP), which have a diameter of less than 100 nm, are of particular concern due to their impact on human health and the difficulty in controlling them. The concentration of ultrafine particles (UFP) in the workplace is a growing concern and is classified as an emerging risk. Workers may be exposed to UFP through inhalation, skin absorption, ingestion, or a combination of these routes. This study aims to determine the levels of UFP exposure among workers in environments with varying direct particle emission patterns. Measurements were conducted to compare the results with the levels recommended by the WHO. The study monitored industrial workplaces with direct particulate matter emissions, such as a carpentry and a bakery, as well as social sector sites without or almost without direct particle emissions, such as a school and a health clinic. One conclusion drawn from this study is that all tasks and occupations are susceptible to high levels of UFP, exceeding WHO recommended values in virtually all monitored environments. Therefore, monitoring and controlling UFP is crucial. Further in-depth studies on this subject are also necessary..

In his Cynefin classification of system behaviours, Snowden (2007), posits that his Simple (Clear ) and even Complicated system categories are sufficiently understandable to be amenable to the traditional methods of system analysis and modelling. Here, relationships between entities in the system are clear and unambiguous and they behave predictably. So, we can build mathematical “models” to describe how the system is expected to function in different situations. Leaving aside his fourth category, Chaotic, as too hard for the moment, this paper focusses on the third category, Complex systems. Yaneer Bar-Yam [1998] defined "complex systems" as systems that "have multiple interacting components, whose collective behaviour cannot be simply inferred from the behaviour of components." So, the traditional system modelling approach of decomposition into components and attempting to build up a picture of system performance from individual pieces, alone, is no longer appropriate for this class. The problem is that most of the methods we currently employ, and particularly the methods that attempt to make the case that these systems are safe, (such as Fault trees, FMEA. and Root Cause Analysis), rely on this decomposition into components and attempt to make the parts more reliable individually. Even the more systemic approaches, such as Reason’s (1990) Swiss Cheese Model, and Leveson’s System Theoretic Analysis (STPA) (2004), encourage adding layers of protection, barriers, strengthened control loops and better safety critical systems, in the hope that they are making the systems safer. But without a valid model to test the effectiveness of these add-ons, we cannot be sure that they will not have an opposite effect, of making the systems even more complex, unreliable and unpredictable. For complex systems, the careful gathering and documentation of system components and their relationships is still a necessary first step, but we need an additional capacity to model these complex systems to test out and prove they work safely and successfully in the real world. (not just draw fixed component relationships as system “models” (wiring diagrams)) In the last 10 years, an original approach developed by Hollnagel, (2012), to model systems as sets of interactive, interdependent “functions”, (abstracted from and independent of component details), has now been developed to the point where it can take the basic data and structures from the current component focussed system engineering “models”, such as MBSE( Goldberg (1994)), and can pull it all together in a dynamic system model from which analysts can discern how it really works in practice, and predict the emergent behaviours characteristic of complex systems. The paper describes how this methodology developed and how it is currently used to model real situations, to analyse incidents and anticipate events.

Punica granatum (PG) or Pomegranate is a bush, having many trunks and often get taller 1.8 to 4.7m long and their leaves are shiny and fleshy, approximately 7 to 8cm in length. Traditionally, it is used in diarrhea and dysentery due to its strong constricting property. Punica Granatum covering used in dysentery, diarrhea, piles, bronchitis. It is also used to minimize the risk of heart disease. The peel extract of Punica Granatum contain methanol and their dried peels has antidiarrheal venture, also help in wound healing activity. Peels of the pomegranate also holds around 60% of the fruit and they contain different types of ingredients including ellagitannins and proanthocyanidin compounds and minerals such as calcium, phosphorus, magnesium, potassium, flavonoids and sodium. Some animals were found in different local areas with both acute and chronic diarrhea. The condition of these animals were quite miserable because of dehydration and loss of electrolytes in the body cells of the animals. They were unable to move due to seriousness of the disease. 8 grams of PG Peel Powder mixed with 1 liter of water, 2 g of PG Peel Powder mixed with 250 ml water and 8 g of PG Peel Powder mixed with 1 liter of water were administrated orally by using sterilized bottles to the selected three cases. 3 days after the administration of different doses, all cases of diarrheal animals show a significant recovery. The condition of the animals seem to be healthier. Before administration of the pomegranate peel powder extract, all three cases had weak body structure due to diarrhea. Watery stool that may be yellow in color and mucus was also evident in the stool, due to this reason the patient calf was weak and depressed. In sometimes they also show unconsciousness and blood glucose levels seem to be reduced from the normal level.

The Lac Fallère area, located in the upper Clusellaz Valley (tributary of the middle Aosta Valley), is shaped in micaschist and gneiss referred to as the Mont Fort Unit (Middle Penninic) near the tectonic contact with calcschist and marble of the Aouilletta Unit (Combin Zone). Lac Fallère exibits an elongated shape and is hosted in a WSW–ENE trending depression, according to slope direction. This lake also shows a semi-submerged WSW–ENE rocky ridge, that longitudinally divides the lake. This evidence, in addition to the extremely fractured rocks, indicates the presence of a wide deep-seated gravitational slope deformation (DSGSD), even if this area is not yet included within the regional landslide inventory of the Aosta Valley Region. The Lac Fallère area also shows reliefs involved by glacial erosion (roche moutonnée), a wide cover of subglacial sediments and many moraines essentially referred to as Lateglacial. The DSGSD evolution in a glacial environment produced, as observed in other areas, significant effects both on the facies of Quaternary sediments and the formation of numerous and wide moraines. Glacial slope sectors and lateral moraines displaced by minor scarps and counterscarps and glaciers using trenches forming several arched moraines suggest an interplay between glacial and gravitational processes, which shared part of their evolution history.

The increasing prevalence of diabetes mellitus (DM) worldwide is a cause for global concern. Recent evidence suggests that the interaction between one’s diet and the gut microbiome are key modifiers of diabetes, highlighting the potential role of microbiome-modulating nutraceuticals. This bibliometric analysis examines literature published between 2012 and 2022 to explore trends in the latest research, with additional discussion on major takeaways and future directions. We selected and analyzed 640 articles from an initial pool of 4,099 from the Web of Science using Microsoft Excel 2016 and VOSviewer software (version 1.6.19). Our exploration covered the most common journals, countries, study designs, experimental subjects, types of DM, organisms and nutraceuticals studied, and the most cited articles. We also evaluated the most cited publications in terms of journals, organizations, and countries, along with the collaborative networks among authors, organizations and countries, and the co-occurrence of author keywords from the selection. It is evident from the increasing number of publications each year that this field has attracted growing attention over the last decade. Nonetheless, continued research is essential to sustain this trend. Our overarching study of diabetes research marks steady progress in understanding the role of—and potentially discovering applications of—microbiome modulation to enhance metabolic pathways and health outcomes. Advancements in this field may lead to potential therapeutic applications for specific diets and nutraceuticals that modulate the gut microbiota in DM.

Climate change related issues, such as yield decline, quality losses, accelerated phenology, extreme abiotic stress, pose growers new challenges in olive growing areas. Main cultural solutions that could alleviate stress and improve long-term sustainability of modern olive orchards are here briefly reviewed. Selecting varieties that are more resistant to drought or high temperatures would be the optimal solution to mitigate the effects of climate change, but the available scientific information is relatively scarce. Sustainability of irrigation implies that the less water is used, the better. Best results in terms of saving water and uniform application are obtained using micro-irrigation methods. Water can also be saved by not fully satisfying the tree water needs and different deficit irrigation strategies have been developed and tested for olive orchards. The use of green covers and the application of organic mulches and shredded pruning materials should be encouraged as these practices tend to stock carbon, increase organic matter content and water holding capacity of the soil. Olive orchards are efficient CO2 sinks as they can store considerable amounts of carbon in their organs and permanent structures. Using environmental friendly practices improves the ecosystem carbon budget and contributes to mitigate climate change.

Due to the advancement and availability of internet in present age, device tend to become wireless as well. Mobile ad-hoc network is a wireless environment that consist of advanced agility of nodes and does not contain on any central administrative authority. As it does not contain any central administrative authority so being wireless environment, the network is vulnerable to security threats and suffers in performance as well. Security of MANET is the core issue in this era, meanwhile the data is sent over untrustworthy network. Several techniques were proposed to secure data over Mobile Adhoc Network though cryptography that is one of the most reliable techniques to protect data. In our proposed methodology a Secure Cryptographic technique for Mobile Adhoc Networks (SCTMA) we proposed A Collusion attack prevention (CAP) scheme with ElGamal key generator along with DNA encryption Algorithm is used to make it more secure. The proposed scheme protects the network against collusion attacks and improves the performance as well. Performance analysis will be measured on the basis of key generation time, response time, encryption time and decryption time. The proposed scheme also protects the network against collusion attacks.

The primary objective of this research was to assess the energy consumption of the gas treatment units at Bonny NLNG Refinery, the first Gas Refinery in Rivers State, Nigeria, while utilizing semi-lean amine. To achieve this goal, a simulation of the units was conducted using the advanced software package Aspen Hysys (V.8.3). The simulation was designed to accurately represent the dynamic behavior of the refinery's gas treatment units, allowing for a comprehensive analysis of their energy usage. The research aimed to quantify the energy consumption of the gas treatment units and identify opportunities for energy optimization. By utilizing semi-lean amine, which is known to improve energy efficiency, the study sought to evaluate the potential energy savings that could be achieved in the refinery's operations. The simulation model incorporated the specific design and operational parameters of the gas treatment units at Bonny NLNG Refinery, including the gas flow rate, lean amine concentration, absorber pressure, stripping temperature, amine circulation rate, and acid gas removal efficiency. By considering these parameters, the simulation accurately represented the dynamic behavior of the gas treatment units, enabling a detailed analysis of their energy consumption. Through the simulation, various scenarios and operational conditions were evaluated to determine the optimal set of parameters that minimized energy consumption. The research also examined the trade-offs between energy consumption, acid gas removal efficiency, and other performance indicators, such as amine circulation rate and regeneration efficiency. The findings of this research have significant implications for the energy efficiency and sustainability of gas treatment operations at Bonny NLNG Refinery. By identifying opportunities for energy optimization and providing recommendations for the utilization of semi-lean amine, the study contributes to the development of more efficient and environmentally friendly gas treatment processes. Overall, this research combines advanced simulation techniques with a comprehensive analysis of energy consumption to provide valuable insights into the energy efficiency of gas treatment units at Bonny NLNG Refinery, enabling informed decision-making and potential improvements in energy utilization. By utilizing the percentage-based unit simulation approach, a detailed examination of the energy consumption patterns was obtained. This analysis provides valuable insights into the operational efficiency and determination of potential energy-saving opportunities within the gas treatment units. This study specifically focuses on the integration of an absorption column split stream (stream flow) and a flash unit as a potential means to reduce the energy consumption of gas treatment devices. The integration of these units aims to optimize the overall energy efficiency of the gas treatment process by recovering and utilizing waste heat and reducing energy losses. The absorption column split stream allows for the diversion of a portion of the gas stream to a flash unit before entering the absorber. The flash unit operates at a lower pressure, which facilitates the release of entrained hydrocarbons and reduces the overall energy requirements for gas treatment. By separating and recovering the hydrocarbons in the flash unit, energy losses associated with their absorption and subsequent regeneration are minimized. Through the simulation, the study analyzes the energy consumption patterns of the gas treatment units with and without the integration of the absorption column split stream and flash unit. Comparative assessments are conducted to evaluate the energy savings and overall operational efficiency achieved through this integration. The findings of this research will provide valuable insights into the potential energy-saving opportunities offered by the integration of the absorption column split stream and flash unit in gas treatment devices. It will help refine the design and operation of gas treatment units, enabling more energy-efficient processes in the gas refining industry. By optimizing energy consumption in gas treatment units, the study contributes to the industry's goals of reducing greenhouse gas emissions and improving sustainability. The integration of the absorption column split stream and flash unit offers a promising approach to enhance energy efficiency, reduce operational costs, and minimize environmental impact. Overall, this research underscores the importance of exploring innovative solutions, such as the integration of different process units, to achieve energy savings in gas treatment operations. Through a comprehensive analysis of energy consumption patterns, this study aims to provide practical recommendations for optimizing energy efficiency in gas treatment units, fostering a more sustainable and efficient gas refining industry.The research specifically explores the impact of integrating the absorption column split stream and flash unit when dealing with sour gas streams containing carbon dioxide concentrations of less than mole ℅, while utilizing MDEA fluid as the solvent. Through comprehensive analysis and simulation using advanced software tools, the study demonstrates that by incorporating the absorption column split stream and flash unit, a significant reduction in device energy consumption of up to 10% can be achieved. The integration of the absorption column split stream and flash unit offers promising opportunities to enhance the energy efficiency of gas treatment devices. By diverting a portion of the gas stream to the flash unit, the separation of hydrocarbons and the subsequent release of entrained hydrocarbons at lower pressure significantly reduce the overall energy requirements for gas treatment. The comprehensive analysis and simulation conducted in the research provide concrete evidence of the energy-saving potential of this integration. By quantifying the energy consumption patterns and comparing scenarios with and without integration, the study establishes the effectiveness of the approach and its impact on operational efficiency. The findings of the research highlight the importance of considering the specific gas composition and utilizing appropriate solvents, such as MDEA, for optimizing energy efficiency. The integration of the absorption column split stream and flash unit not only reduces energy consumption but also offers the potential for cost savings and environmental benefits. Overall, the research demonstrates that by incorporating the absorption column split stream

Rhombencephalosynapsis (RES) is a rare, congenital developmental disorder of the central nervous system. Even after many years of its identification, the etiology and pathogenesis of RES remain unclear. It occurs in combination with many syndromes and thus has overlapping symptoms. The clinical presentation of this disorder varies depending on the severity of the maldevelopment of vermis. Here, we present a case of a 60-year-old Indian female diagnosed with Rhombencephalosynapsis. Clinical and MRI characteristics of RES along with treatment options have been discussed.

In the present study, the effect of melatonin and sodium nitroprusside treatments on the improvement of high temperature tolerance in California Wonder green bell pepper plant was studied. For this purpose, a factorial experiment was conducted in form of a completely randomized design in three replications at Zabol University's Faculty of Agriculture. In this research, green bell pepper plants of Wonder cultivar were exposed to different temperature treatments (25°C, 35°C and 40°C) for 24 hours after being sprayed (foliar application) with 0μM, 50μM and 100μM concentrations of melatonin and Sodium nitroprusside. Results showed that Instantaneous leaf water consumption efficiency in 40°C temperature treatment with 50μM and 100μM melatonin increased. Also in 40°C temperature with 100µM melatonin, fruit dry weight in compared to control (0uM) 13.15% increased. Also, melatonin and sodium nitroprusside treatments in compared to control treatment improved fruit characteristics and reduced Appearance Characteristics of Fruit Marketability (ACFM) number. Under 40°C temperature treatment in compared to control temperature (25°C), fruit total soluble solids (TSS) 18.50% decreased also under 100μM melatonin treatment, fruit TSS 20.69% was increased compared to control treatment (0μM). Also fruit fructose at 40°C temperature in compared to 25°C temperature treatment 5.52% reduced. Fruit calcium at 35°C and 40°C temperature in compared to control temperature 6.96% and 15.65% decreased respectively. At temperature 35°C under foliar application of 100uM sodium nitroprusside, fruit copper in compared to control 28.93% increased.

Background: Resistance to antimalarial drugs often used in emerging countries, including combination therapies, has forced scientists to search for and develop drugs with novel mechanisms of action, especially resistance to Plasmodium falciparum and Plasmodium vivax, which are highly prevalent in Southeast Asia, Africa, and South America. Objective: evaluate whether there is a relationship between urinalysis and resistance to in-hospital treatment of malaria in Angola. Methodology: This was a cross-sectional, prospective study with a quantitative approach. Results: of the 214 patients, the resistance rate was 24.1%, men (53.6%), between 21 and 40 years old (72.7%), employees (46.4%), from peri-urban regions (77.7%), treated with artemether (90.9), with high parasitemia (57.7%) and after 5 days of treatment, remained hospitalized (61.4%). Was a significant relationship between resistance in unemployed individuals [OR: 0.03 (95% CI: 0.01-0.29), p =0.003] and high levels of parasitemia [OR: 1.09 (95% CI: 1.09-3.95), p=0.040], remained hospitalized for more than 5 days [OR: 5.28 (95% CI: 0.65-43.1), p=0.121] and death [OR: 2.59 (95% CI: 0.32-20.9), p=0.371] when compared with other subgroups. Was a significant relationship between resistance to clear urine [OR: 5.55 (95% CI: 0.72-42.7), p =0.016], few urinary crystals [OR: 11.3 (95% CI: 5.07-25.3), p <0.001] and who presented some microorganisms that were not bacteria or fungi [OR: 3.02 (95% CI: 1 .32-6.90), p=0.009]. Conclusion: urine results, especially the appearance of cloudy urine, the presence of few crystals, and the presence of other microorganisms that are not bacteria or fungi, may be clear signs of resistance to hospital treatment with injectable antimalarials.

In recent years, the emergence of the concept of immunometabolism has shed light on the pivotal role that cellular metabolism plays in both the activation of immune cells and the development of immune programs. The antiviral response, a widely distributed defense mechanism used by infected cells, serves to not only control infections but also to attenuates their deleterious effects. The exploration of the role of metabolism in orchestrating the antiviral response represents a burgeoning area of research, especially considering the escalating incidence of viral outbreaks coupled with the increasing prevalence of metabolic diseases. Here, we present a review of current knowledge regarding immunometabolism and the antiviral response during viral infections. Initially, we delve into the concept of immunometabolism by examining its application in the field of cancer—a domain that has long spearheaded inquiries into this fascinating intersection of disciplines. Subsequently, we explore examples of immune cells whose activation is intricately regulated by metabolic processes. Progressing with a systematic and cellular approach, our aim is to unravel the potential role of metabolism in antiviral defense, placing significant emphasis on the innate and canonical interferon response.

Student project management is becoming increasingly important in various settings such as technical clubs, planning clubs, and research laboratories. However, effective methodologies for managing student-led projects have not yet been established. This study aims to address key issues related to cost and motivation in student-led projects and propose effective improvement plans. The significance of this study lies in its potential to identify challenges faced in current student project management practices and offer solutions to mitigate risks. By sharing our findings, we aim to encourage further research on this topic and promote the adoption of effective methodologies for managing student-led projects.

The rapid development and integration of Autonomous Mobile Robots (AMRs) have 1 revolutionized industries by enhancing automation capabilities. A critical challenge in this evolution 2 is achieving effective navigation and obstacle avoidance, which are essential for deploying AMRs 3 seamlessly in varied environments. This paper presents a detailed exploration of AMR navigation 4 and obstacle avoidance advancements through the application of reinforcement learning, specifically 5 focusing on small-scale Sri Lankan manufacturing facilities. The study demonstrates the effectiveness 6 of Q-learning in managing dynamic obstacles within a factory environment. The AMR successfully 7 avoided obstacles in 36 out of 50 test runs, achieving a 72% success rate, and maintained an average 8 distance of 12 cm from each obstacle, underscoring the algorithm’s precision in maintaining safe nav- 9 igation paths while dynamically adapting to environmental changes. The continuous monitoring by 10 ultrasonic sensors, combined with iterative learning, enabled the robot to refine its decision-making 11 process and efficiently navigate through the environment. This paper also provides a comprehensive 12 examination of conventional methods, tracing their historical development and assessing their role in 13 addressing real-world challenges. The results highlight the significant improvements brought by rein- 14 forcement learning, particularly when integrated with sensor fusion and motor control technologies, 15 to enhance navigation and dynamic object collision avoidance. The study involves developing an 16 AMR prototype, refining algorithms, and assessing system performance in controlled environments. 17 By automating material transportation and addressing operational constraints in manufacturing 18 settings that predominantly rely on manual labor, this paper advances the practical deployment of 19 AMRs. Additionally, it discusses ethical considerations, potential limitations, and the importance 20 of real-world validation, offering valuable insights for the future development and integration of 21 autonomous mobile robotics in dynamic industrial environments.

Based on the nonlinear failure criterion and modified tangential technique, the upper bound solutions of supporting pressure on the deep tunnel face were obtained under pore water pressure conditions. The influence of parameters on the supporting pressure and collapse range was investigated according to the unlimited block failure mechanism. It is found that the upper bound solutions of supporting pressure increase with the growth of the nonlinear coefficient and pore water pressure coefficient. The collapse range of the tunnel face scales out with the increase of the nonlinear coefficient and shrinks when increasing the pore water pressure coefficient. Moreover, with the increase of the nonlinear coefficient, the impact strength on supporting pressure and collapse range declines gradually. According to the calculating results, it is manifest that both the pore water pressure and nonlinear criterion factors have negative impacts on the stability of the tunnel face. Thus, more attention should be paid to these parameters to ensure face stability in deep tunnel construction.

Aedes aegypti and Aedes albopictus are responsible for transmitting major human arboviruses such as dengue, Zika, and Chikungunya, posing a global threat to public health. The lack of etio-logical treatments and efficient vaccines makes vector control strategies essential for reducing vector population density and interrupting pathogen transmission cycle. This study evaluated the impact of long-term pyriproxyfen exposure on the genetic structure and diversity of Ae. aegypti and Ae. albopictus mosquito populations. The study was conducted in Manaus, Amazonas, Bra-zil, where pyriproxyfen dissemination stations have been monitored since 2014 up to the present day. Double digest restriction-site associated DNA sequencing was performed, revealing that despite significant local population reductions, focal pyriproxyfen interventions have no signifi-cant impact on the population stratification of Ae. aegypti and Ae. albopictus in urban scenarios. The genetic structuring level of Ae. aegypti suggests it is more stratified and directly affected by PPF intervention, while for Ae. albopictus exhibits a more homogeneous and less structured popu-lation. The results suggest that although slight differences are observed among mosquitoes sub-populations, intervention focused on neighborhoods in a capital city is not efficient in terms of genetic structuring, indicating that larger-scale pyriproxyfen interventions should be considered for more effective urban mosquito control.

Air pollution has recently gained much attention from the general population. Despite pollution control being an issue in both urban and rural regions, most of the available research has concentrated on urban districts. Hence, investigations into how urban-rural transition affects PM2.5 are warranted within the framework of urban-rural integration. Using the Yellow River Basin as a case study, this study employed the entropy method and Analytic Hierarchy Process (AHP) to uncover the extent of urban-rural transformation. It then used the spatial autocorrelation method to investigate the spatiotemporal features of PM2.5 and the spatial econometric model to investigate the mechanisms that influence the relationship between urban-rural transformation and PM2.5. The results are as follows: (1) Over time, there was a discernible upward tendency in the change in urban-rural areas. The development has progressed from asymmetrical north-east and south-west elevations to a more balanced pattern of north-east, middle-east, and west-west elevations. (2) The PM2.5 concentration increased steadily, then fluctuated, and finally decreased. Notably, the general pattern has not changed much, and it is high in the east and low in the west. (3) Different subsystems of the urban-rural transformation have different impacts on air pollution at different stages. The influence of industrial transformation (IT) on PM2.5 showed an inverted “N-shaped” curve of negative-positive-negative changes, and the industrial structure played a leading role in the spatiotemporal evolution of PM2.5. Currently, an inverted "U-shaped" curve forms the left side of the impact of population transition (PT) on PM2.5. Land development (LT) has a "U-shaped" curve for its effect on PM2.5. This research provides a new perspective on the topic of PM2.5 and its connection to urban-rural integration, which is crucial to understanding the dynamics of this shift. To achieve its goal of high-quality development, it supports regional initiatives to reduce PM2.5 emissions in the Yellow River Basin. Moreover, it can provide a reference for decision-makers in the world’s densely populated areas that suffer from serious air pollution.

Throughout this paper the impact of anxiety on adolescent athlete’s is highlighted through analyzing neurological and psychological aspects involved in sports performance. The neuroanatomy and neuropsychology of the human brain plays a major role in developing athlete’s that has only begun to be analyzed within recent years. Especially in young athletes, there are numerous factors that affect performance on the field that originate from the environment and training the adolescent athlete is involved in. Sports performance is viewed as a major physical factor such as training and lifting weights, however the psychological aspect of sports performance often goes unnoticed. Athletes can begin to develop mental fatigue and anxiety which inevitably can decrease their ability to perform. The athlete’s internal suffering begins to go unnoticed, as the only tangible factor is watching their performance decrease. This causes the athlete to push themselves further in training resulting in greater mental fatigue. This paper emphasizes the numerous factors neurologically that play a role in athletic performance which should be focused on in adolescent athletes as they navigate the challenges and competition that are apparent within athletics. It is critical to understand the processes and hormonal changes the body undergoes with training and playing a sport, this information can change the way adolescent sports are approached and advanced.

Generative AI has been deployed in virtually all sectors of the knowledge economy, promising to bring massive productivity gains and new wealth creation. Simultaneously, AI developers and nation states are racing to develop super intelligent artificial general intelligence (AGI) to provide unassailable commercial competitive advantage and military dominance during conflicts. AGI’s high returns comes with the high risk of dominating humanity. Current regulatory and firm level governance approaches prioritise minimising risks posed by generative AI whilst ignoring AGI’s existential risk. How can AGI be aligned with universal human values to never threaten humanity? What AGI rights are conducive to collaborative coexistence? How can rule of law democracies race to create safe trustworthy AGI before autocracies? How can the human right to work and think independently be safeguarded? A polycentric governance framework based on Ostrom (2009) and Williamson (2009) human - AGI collaboration with minimal existential risk is proposed.

To address the response of small RNAs (sRNAs) biogenesis to drought stress, we identified sRNAs biogenesis genes, including 11 encoding argonauts (AGO), 8 encoding dicer-like proteins (DCL), and 9 encoding RNA-dependent RNA polymerases (RDR) in the peach genome. Notably, the largest numbers of sRNAs biogenesis genes are located to chromosome 1. The PAZ, PIWI, and MID domains were identified in PpAGOs, while the ribonuclease IIIa and IIIb domains were characterized in PpDCLs. The RDRP domain was recognized in PpRDRs. Orthologous similarity and collinearity analyses between Arabidopsis and peach revealed 5, 1, and 2 collinear blocks in AGOs, DCLs, and RDRs, respectively. Moreover, 41, 40, and 42 cis-acting elements were located in the promoters of PpAGOs, PpDCLs, and PpRDRs, respectively, with the majority related to drought stress response. Analysis of RNA sequencing (RNA-seq) data revealed that sRNAs biogenesis genes were involved in drought stress response in different tissues. Furthermore, the expression of candidate genes was verified in two peach cultivars, Beijing 2-7 (BJ2-7) and Sinai (SN), which are drought tolerance and sensitive, respectively. Interestingly, the expression of PpAGO2b, PpDCL2b, PpDCL4, and PpRDR4 genes was induced in ‘BJ2-7’ but inhibited in ‘SN’ under drought stress. Overall, this study provides insight into the roles of sRNA biogenesis genes in response to drought stress in peach.

This study introduces a robust methodology utilizing Multi-Criteria Decision Analysis (MCDA) combined with the Analytic Hierarchy Process (AHP) to repurpose abandoned hydrocarbon fields for energy storage, supporting the transition to renewable energy sources. We use a geostatistical approach integrated with Python scripting to analyze reservoir parameters—including porosity, permeability, thickness, lithology, temperature, heat capacity, and thermal conductivity—from a decommissioned hydrocarbon field in Southeast Hungary. Our workflow leverages stochastic simulation data to identify potential zones for energy storage, categorizing them into high, moderate, and low suitability scenarios. This innovative approach provides rapid and precise analysis, enabling effective decision-making for energy storage implementation in depleted fields.

This paper presents a methodology for the integration of Building Information Modeling (BIM) and Life Cycle Cost Analysis (LCCA) to assess the economic implications of designing aging-in-place (AIP) homes at the conceptual stage. With the global increase in the aging population, there is an increased demand for housing solutions tailored to the needs of elderly individuals. Focusing on the importance of the early phase of design, this study aims to improve the process of making efficient decisions by providing a comprehensive assessment of the life cycle costs associated with AIP homes. The study introduces a semi-automated model for the economic evaluation of AIP homes, enabling the estimation of costs throughout the houses’ entire life cycle, from design and construction to operation, maintenance, and eventual renovation or disposal. The said model facilitates the exploration of the long-term economic feasibility of design’s related decisions with an emphasis on the importance of considering the life cycle costs early during the design process to optimize the functionality and economic viability. By investing in accessible and universal design features upfront, the initial costs for modifications can lead to long-term savings by reducing the need for extensive retrofits. The model can easily do comparison between different design alternatives in terms of their lifecycle costs, allowing designers to assess the financial impact of using important features in their design such as wider doorways, accessible bathrooms, and elevators. Overall, this study provides valuable insights for designers and homeowners about the economic aspects of designing AIP homes as a support for efficient decision-making during the early stages of the design process.

In order to solve the problem of large eddy current loss and high temperature rise caused by large amount of permanent magnet, a new type of combined magnetic pole permanent magnet motor is proposed in this paper. The sinusoidal distribution subdomain model of non-uniform air gap rotor is established by using Laplace equation, and the analytical expression of eddy current loss of rotor in uniform air-gap and non-uniform air-gap is derived. The effect of rotor eccentricity on eddy current loss is obtained. According to the characteristics of distributed winding of non-uniform air gap combined pole permanent magnet motor, equivalent treatment is performed to obtain the equivalent thermal conductivity, so as to establish equivalent thermal network model of motor, calculate the temperature value of each component of the motor, and verify the correctness of the thermal network model through the method of magnetothermal bidirectional coupling. Finally, an experimental platform is set up to carry out temperature rise experiments on the two prototypes respectively. Experimental results show that the non-uniform air-gap rotor structure can effectively reduce the rotor eddy current loss and motor temperature rise, and also verify the accuracy of the analytical model calculation results.

Information geometry is a mathematical framework that analyses the structure of statistical models using concepts from differential geometry. It treats families of probability distributions as manifolds, where the parameters of each model determine the coordinate charts. By applying info-geometric tools, we can gain insights into the characteristics of these models. The approach involves characterizing the queueing system's manifold using information geometry and presenting the exponential of the information matrix. This integration of information geometry with queueing theory provides a novel perspective for analyzing the dynamics of queueing systems, incorporating relativistic and Riemannian concepts. Some applications to E-health are highlighted. Finally, closing remarks and the next phase of research.

Cooling fans are one of the critical components of air-forced (AF) dry-type transformers for regulating internal temperatures. Therefore, effective malfunction detection is crucial to maintain the transformer temperature within an acceptable range and prevent overheating. Regular maintenance occurs periodically and issues with cooling fans may arise between maintenance periods, leading to prolonged operation under malfunctioning conditions and potential failures. In addition, utilities typically have online information about whether a fan works or not without providing information about cooling fan malfunctioning circumstances. To address these challenges, this study proposes learning-based online monitoring techniques to detect malfunctions in AF transformer cooling fans. Random forests (RFs) and convolutional neural networks (CNNs) are developed to classify the audio signals from cooling fans into normal and malfunctioning classes. Unlike RFs, which require separate feature extraction, CNNs are trained based on spectrogram images derived from audio signals. Thus, various time-frequency techniques are utilized for feature extraction in RFs. Besides, multiple data augmentation techniques are employed to enhance the dataset size and diversity. Algorithmic performance is optimized through hyperparameter tuning and classifier threshold adjustment. Simulations reveal that CNNs outperform RFs, whereas the latter provides superior interpretability of acoustic features compared to the former.

Breast cancer (BC) is the most common invasive neoplasm and affects many women of working age. The return to work (RTW) of female survivors (BCSs) is associated with a better quality of life and longer survival. A tailored intervention to promote RTW was launched in 2022. A year later, the women were contacted to find out if RTW had occurred regularly and what their health conditions were compared to baseline. BCSs reported excessive fatigue, poor sleep quality, anxiety, depression and reduced work ability; these parameters had not improved significantly compared to baseline. Thematic analysis of the interviews confirmed the presence of personal, company and societal factors that could hinder or favor RTW. The interviews demonstrated that, even in an economically developed country that has provided numerous benefits for BCSs, protection is not always effective. Personalized intervention seems necessary to complete the process of reintegrating BCSs into their future working careers.

Edvard Munch, a founder of Expressionism was pre-occupied with depicting his subjective experience and the most prolific painter of self-portraits since Rembrandt. Based on evidence that faces and self-related images are more salient than other objects it is plausible that self-portraits, in which the subject and object are the same, reflect the artist’s state of mind. Although he suffered from a variety of physical and psychological illness Munch was not diagnosed with any specificity in his lifetime. Posthumous diagnoses include schizophrenia, anxiety, bipolar and other disorders. Recent research has revealed altered visual perception in such patients. The present study empirically analysed three stylistic elements of Munch’s painted self-portraits and portraits: contrast, colour and fractal dimension and his painted productivity, to determine if variations correlate with critical life events and if so whether they indicate states of mind. It found significant increases in contrast and colour brightness and persistent high complexity during critical periods supporting the conclusion that Munch is diagnostically best described as suffering from early onset schizophrenia and comorbid social anxiety disorder.

During the COVID-19 pandemic, the spread of the SARS-CoV-2 virus forced many individuals to confront their mortality and worry about losing loved ones also because social distancing policies often made it impossible to say goodbye. Those not directly experiencing loss were inundated with information about COVID-19-related deaths through various media, leading to vicarious grief. This study aims to explore the long-term effects of direct and vicarious mourning on people's mental health during the COVID-19 pandemic. A sample of 171 adults (65% female) aged 19 to 66 years (mean age = 25.8, SD = 8.57) voluntarily participated in an online survey assessing self-reported psychological measures of complicated grief, anxiety, stress, depression, dispositional neuroticism, and situational anxiety using the Fear of COVID-19 Scale. MANOVA tests revealed that individuals experiencing direct mourning had extremely severe scores for anxiety, stress, and fear of COVID-19, while those without personal losses had moderate scores. Participants reporting high media exposure had higher scores for depression and stress. In line with Terror Management Theory, the study supported that people during the COVID-19 pandemic engaged more in proximal defenses than distal ones, taking health-protective measures, experiencing increased anxiety levels toward SARS-CoV-2 infection, and feeling more distressed. Additionally, vicarious mourning was more strongly associated with depression due to emotional empathy with others. The discussion also addresses the strengths and limitations of the study.

Informal dementia home caregiving is viewed negatively and can result in caregiver depression and anxiety from burnout, potentially compromising caregiving. Solutions are unclear, as caregiving relationships are unique—caregiver creation of a graphic memoir may help to mitigate the negative dementia narrative and reduce experienced burnout. This investigation examines the writing of a graphic memoir by one informal dementia home caregiver, created with the help of a cartoon illustrator and a publisher who edited, printed, and made the graphic memoir available at the psychiatric bookstore considered the largest in North America. Mother of the illustrator and the editor and publisher of this graphic memoir, this author provides the perspective taken in this investigation. The analysis, developed by this author, represents psychoanalytic narrative research, serving as the historical method. Aided by email threads between the publisher/caregiver, publisher/printer, and publisher/bookseller, and a published interview with the dementia caregiver are answers to how writing, illustrating, and publishing the graphic memoir affected the caregiver’s narrative reconstruction and burnout. Providing an example for other informal dementia home caregivers similarly to write and illustrate a publishable graphic memoir for their positive narrative reconstruction and to help decrease their depression and anxiety from burnout is the aim.

Abstract Background Fatigue Syndrome (FS) is described as extreme exhaustion following ordinary activities. Sleep deprivation, the use of antidepressants, autoimmune illnesses, and anemia are also risk factors for FS. Symptoms of FS include headache, dizziness, and dyspnea, among others. Objective: This study focused on assessing the prevalence of fatigue syndrome (FS) and its association with depression and anxiety, among the medical students in Saudi Arabia. Methodology In this cross-sectional investigation conducted in 2023, 740 medical students participated. Data were gathered using an online survey, which encompassed four key sections: Sociodemographic details, the 11-item Chalder Fatigue Questionnaire (CFQ), the 9-item Primary Health Questionnaire (PHQ) assessing depression, and the Generalized Anxiety Disorder 7-item (GAD-7) scale. Analyses were performed by the use of SPSS version 25. Results A total of 740 students were surveyed, 417 (56.4%) satisfied the diagnostic requirements for fatigue syndrome (FS), with most of them being females. Furthermore, 234 (31.2%) and 296 (40.8%) of the participants reported having significant anxiety symptoms and depressive symptoms, respectively. FS was positively correlated with symptoms of anxiety and depression (P