Spin Assisted Layer-by-Layer (SA-LbL) assembly is one of the Layer-by-Layer (LbL) assembly variants. It is considered as the fastest LbL assembly, however, the deficiency of layering quality on bigger polymeric support size poses a significant challenge to the application of SA-LbL assembly at a larger or industrial scale. To address the challenge, combined spin-spray assisted Layer-by-Layer (SSA-LbL) is employed to prepare membrane. In this study, nanofiltration (NF) thin film composite membranes were prepared by alternate deposition of branched-polyethyleneimine (PEI) and poly(sodium 4-styrenesulfonate) (PSS) on polyethersulfone (PES) ultrafiltration (UF) membrane support. The resulting membrane was then tested to separate NaCl from water. One of the membranes produced in this work, i.e., (PEI/PSS)10 achieved rejection rate of 76.2 %; permeability of 2.79 l/h·m2·bar tested at pressure of 10 bar, temperature of 24.58 ± 0.51 °C , and NaCl-Feed concentration of 2076.75 ± 40.51 ppm. The membrane fouling resistance was also examined in 5 days-test. The membrane showed stable performance and lost only about 30% flux from the initial flux due to fouling which was comparable to that of commercial NF membrane such as NF90. Hence, this work shows that SSA-LbL can be considered as a promising and innovative membrane fabrication technique as it offers flexibility and applicability for preparing membrane from various materials as well as pertinence to industrial scale.

This study explores the application of AncorLam HR (Höganäs, Sweden), a soft magnetic composite (SMC) material, in the stator core of an axial flux permanent magnet (AFPM) drive motor. Building on previous research that provided mechanical and thermal properties of AncorLam HR, the study focuses on analyzing how the manufacturing process affects the motor core's shape. A bulk prototype was created based on Case 3, which demonstrated the least deviation in density and internal stress. The prototypes were produced under the specified conditions of SPM 7 and 90°C, resulting in an average density and simulation density error of 0.54%, which confirms the effectiveness of the process. To further verify the reliability, the microstructure of the AncorLam HR powder and the resulting bulk prototype was analyzed. Scanning electron microscopy (SEM) measurements at 5mm, 20mm, and 25mm on Sample 2, which had the highest density, confirmed the consistency between simulation and prototype density trends. Additionally, electron backscatter diffraction (EBSD) analysis revealed a random orientation of the powder, while X-ray diffraction (XRD) showed consistent iron (Fe) peaks at 44.9°, 65.0°, and 82.3° in both the powder and bulk prototypes, indicating no significant change in the internal phase structure. Further analysis using energy-dispersive spectroscopy (EDS) and transmission electron microscopy (TEM) identified that the phosphorus (P) content was eliminated during the molding process, which led to the destruction of the insulating layer, a critical performance factor for SMC materials. In AFPM motor simulations, the average torque was measured at 34.5 mN·m, with core loss increasing as frequency increased. The observation of iron loss spikes during motor startup indicates the need for further research to optimize material selection. This study confirms the viability of using AncorLam HR in electric vehicle motor cores and provides essential data for improving the performance of AFPM motors. Future research should prioritize optimizing SMC materials to enhance the performance and efficiency of AFPM motor applications.

Biodiesel, a potent replacement for petroleum diesel, is derived from fatty acids in biomass through transesterification, which is renewable, non-toxic, and biodegradable and is a powerful replacement for petroleum diesel. Lewis acid has been proven effective for esterification and transesterification. The Lewis base enhances the electrophilic and nucleophilic properties of the molecules that bind to it, leading to the remarkable versatility in the Lewis base catalytic reaction. Many studies have shown that Lewis acid/base catalyzed in-situ transesterification is a fast and environmentally friendly method for producing biodiesel. The utilization of Lewis acid-base sites to catalyze transesterification has been shown to enhance their efficiency and utilization of ac-id-base active sites. This review explores biodiesel production by different catalysts using Lewis acid-base sites, the conditions for catalytic transesterification, the effects of different reaction parameters on biodiesel production, and biodiesel production process.

Biological pre-treatment holds much promise as an innovative and sustainable strategy to improve biogas production from crop residues. In the present study, a novel hot spring cellulolytic microbial consortium (HSCMC) was used to pre-treat crop residues, such as maize stover, wheat straw and soybean straw to improve biogas production by anaerobic digestion (AD). Results indicated that the ash and volatile solids in maize stover were significantly reduced by maximum values of 21.3 % and 69.2 % respectively, after 7 days of pre-treatment over non-treated residues. The maximum decline of 83.9 % in total solid content was reported in wheat straw. The total reducing sugar content was increased by maximum yields of 60.9 %, 96.3 % and 84.7 % in maize stover, wheat straw and soybean straw, respectively. Furthermore, the HSCMC consortium enhanced the cumulative methane yield of wheat straw, maize stover and soybean straw by 50.6 %, 50.2 % and 56.6 %, respectively. Increased methane yield from pre-treated crop residues implies that this method could be an economically viable option for large-scale valorization of the AD process.

The COVID-19 pandemic has significantly altered how people work, with an increasing number transitioning to working-from-home (WFH). This paradigm shift has raised various challenges in adapting living spaces to meet the needs of remote work. Dedicated workspaces or home offices need to be customised for creativity and productivity. Thus, this systematic literature review explores the potential challenges and limitations of implementing modern office design features in residential environments. The study synthesises findings from 108 peer-reviewed articles published within the last decade, focusing on ergonomics, productivity, work-life balance, and spatial constraints. The study found several challenges in translating office design features to home settings. Firstly, spatial limitations in residential areas often restrict the implementation of open-plan layouts and collaborative zones, which are hallmarks of modern office designs. Secondly, the integration of ergonomic furniture and adjustable workstations are limited by budget constraints and the dual-purpose nature of many home spaces. Furthermore, the review highlights the psychological challenges of maintaining work-life boundaries when professional and personal spaces overlap. Noise pollution and distractions emerge as significant factors impacting productivity in home offices, which contrasts controlled modern office environments. The review suggests that the complete replication of modern office design in homes may be impractical, a hybrid approach that adapts key features to residential constraints could enhance home office productivity. Potential solutions could include modular furniture designs, the simulation of collaborative spaces, and the development of noise-cancelling technologies specifically for home environments. This study contributes to the growing body of knowledge on remote work environments and provides valuable insights for enhancing work-life balance, environmental sustainability, and economic growth.

The article focusses on detecting the unbalance of a mechanical component in the electric drive system of a two-mass servomechanism with a PMSM motor, which is connected to the load via a long, flexible shaft. In the example analysed, the degree of unbalance was determined using the reference current signal from the speed controller of the FOC control system. The authors pre-sented a two-mass model with an unbalanced mechanical system. The STFT transform was used to analyse the symptoms of unbalance and an artificial neural network MLP was used for system state inference. The effectiveness of the presented analysis, based on the reference current signal from the sensor embedded in the control system, was experimentally confirmed.

The increasing importance of hydropower generation has led to the development of new smart technologies and the need for reliable and efficient equipment in this field. As long as hydropower power plants are more complex to build up than other power plants, the operation regimes and maintenance activities become essential for the hydropower companies to optimize their performance, such that including the data-driven approaches in the decision-making process represents a challenge. In the paper, a comprehensive and multi-task framework integrated into a Knowledge Discovery module based on Data Mining to support the decisions of the operators from the control rooms and facilitate the transition from the classical to smart Supervisory Control and Data Acquisition (SCADA) system in hydropower plants has been designed, developed, and tested. It integrates tasks related to detecting the outliers through advanced statistical procedures, identifying the operating regimes through the patterns associated with typical operating profiles, and developing strategies for loading the generation units that consider the number of operating hours and minimize the water amount used to satisfy the power required by the system. The proposed framework has been tested using the SCADA system's database of a hydropower plant belonging to the Romanian HydroPower Company. The framework can offer the operators from the control room comparative information for a time horizon longer than one year. The tests demonstrated the utility of a Knowledge Discovery module to ensure the transition toward smart SCADA systems that will help the decision-makers improve the management of the hydropower plants.

In a 2014 paper by C. Fulton, D. Pearson, and S. Pruess, a new characterization of the spectral density function is given for a Sturm-Liouville equation. These authors provide spectral theory showing that the Appell system, a companion linear system of ordinary differential equations, can be utilized to obtain a spectral density function. Though this new method is both elegant for its simplicity and fully viable (as is shown in this work), it has largely been ignored in the literature since its discovery with no citations yet logged in the MathSciNet database. To motivate greater attention towards this 2014 paper, the new spectral theory within it, and its potential applications, work is given here by this author demonstrating a nontrivial example of this new spectral method being applied towards the Bessel Equation in its Liouville-Normal (L-N) form. Validations of results obtained in this paper are also given, showing full agreement with the classical results obtained by E.C. Titchmarsh.

Obesity and chronic inflammation are well-known risk factors for cancer. Interleukin-33 (IL-33) functions in inflammatory diseases, particularly those related to obesity and cancer. However, the correlation and molecular mechanisms linking IL-33, obesity, and cancer remain unclear. IL-33 is a nuclear cytokine released as an alarm signal when cells are damaged or stressed. It is expressed in epithelial, endothelial, and fibroblast-like cells during normal conditions and in-flammation. When IL-33 is present, immune cells expressing the IL-1RL1/ST2 receptor are alerted in response to tissue damage or cell injury. Research on IL-33 and its correlation with obesity has revealed improvements in inflammatory and metabolic changes associated with obesity. IL-33 can have both pro-tumorigenic and antitumorigenic effects, depending on the cellular content, in-flammatory environment, expression levels, and bioactivity of IL-33. This review will discuss the various functions of IL-33 in obesity-driven inflammation and cancers and how they intersect.

This investigation pioneers an examination of the scarcely explored terrain of social diversity in medical education, assessing the complex impacts of socioeconomic status (SES), prior working experiences, and completed apprenticeships on a spectrum of psychological and academic facets among first-year medical students (n = 336) in an urban university setting. By utilizing a systematic and detailed approach, the study illuminates prior anatomical knowledge and various psycholog-ical constructs, marking a significant stride into a domain where knowledge remains profoundly limited. Analyses indicated that SES significantly affects financial anxiety (F(4, 331) = 17.391, p < .001) and academic behavioral confidence (F(4, 331) = 4.323, p = 0.002). Students with prior working experience reported higher self-perceived clinical experience but lower A-level grades (t(279.459) = -6.690, p < .001), competence in natural sciences (t(321.045) = -3.178, p = 0.002), and online competence (t(319.429) = -2.026, p = 0.044). Those who completed an apprenticeship showed higher resilience, academic confidence, self-efficacy, and greater concerns about balancing studies and work (t values ranging from 2.020 to 3.158, p < 0.05). Correlation analysis revealed a positive relationship between resilience (RQS) and coping with academic stress (CAS) (r = 0.632, p < .001), as well as between resilience and academic behavioral confidence (ABC) (r = 0.608, p < .001). Negative correlations were observed between resilience, coping with academic stress, academic confidence, and cognitive test anxiety (CTA) (r values from -0.235 to -0.404, p < .001). The findings emphasize the need for tailored support for students from diverse SES backgrounds and with varying expe-riences. The study highlights the value of a comprehensive approach in medical education, con-sidering the diverse backgrounds and experiences of students. Future research should explore the long-term impact of these factors on professional competencies and patient care, leveraging the diversity of the student body for a holistic educational experience.

This study aimed to investigate the impact of specific single nucleotide polymorphisms (SNPs) on clinical and laboratory outcomes in COVID-19 patients receiving Paxlovid treatment. The primary focus was on genetic variants in IFNAR2, OAS1, OAS3, and ACE2. Laboratory parameters were assessed at admission and discharge, including oxygen saturation, white blood cell count, absolute neutrophil and lymphocyte counts, erythrocyte sedimentation rate, platelet count, hematocrit, and various liver and kidney function tests. The results demonstrated significant associations between certain SNPs and clinical outcomes. Patients with the IFNAR2 rs2236757 G allele exhibited improved oxygen saturation and lower eosinophil counts. The OAS3 rs10735079 and OAS1 rs10774671 G allele was associated with lower eosinophil and total bilirubin levels. Furthermore, patients with the ACE2 rs2074192 C allele showed increased segmented neutrophils and AST levels, while the T allele was associated with lower total bilirubin levels. These findings indicate that the efficacy of Paxlovid treatment may be influenced by genetic variations in IFNAR2, OAS1, OAS3, and ACE2. Further research is warranted to investigate the potential therapeutic implications of these genetic markers.

Laboratories generate various forms of wastes which contribute to a complex network of profound and multifaceted environmental challenges and associated public health issues if not properly managed.Traditional laboratory practices particularly in developing countries, often lead to excessive waste generation, chemical contamination and resource depletion, coupled with inefficient waste management which poses risks to both ecosystem and public health. As the environmental impact of laboratory waste escalates, the need for effective waste management becomes increasingly important and urgent for safeguarding environmental health. This review examines the impact of laboratory waste management practices on environmental health and explores sustainable laboratory medicine as a mitigating response. Sustainable laboratory medicine adopts practices such as green laboratory principles involving waste minimization, resource conservation, the use of eco-friendly materials as well as energy-efficient protocols and innovative waste segregation and treatment technologies. This approach complies with regulatory standards as well as emphasizes proactive orientation towards environmental stewardship, operational efficiency and innovation while maintaining scientific integrity. Sustainable laboratory medicine appears to be a crucial framework that mitigates the environmental health impacts associated with laboratory-derived waste. This review advocates for a paradigm shift towards sustainable laboratory operations and emphasizes the need for comprehensive training, institutional commitment, and regulatory support.

The aim of this study is to characterize the compound extremes of rainfall and temperature in Côte d’Ivoire. For this purpose, we analyzed the outputs of fourteen (14) climate models from the CORDEX-Africa project. Results show an increase (approximately 4.3°C) of the surface temperature and a decrease (5,90 %) of the mean rainfall in the near (2036-2065) and far futures (2071-2100) over Côte d’Ivoire during January-February-March (JFM) period. The analysis of the compound extremes of wet/warm type highlights an increase in the frequency of this climatic hazard in the northern and central parts of the country during January-March (JFM) season in the near and far futures. The dry/warm mode will increase in the central and southern parts of the country during the near future and in the whole country during the far future. These increase in compound extremes could lead to an increase in droughts and natural disasters over the country and could have a negative impact on socio-economic activities, such as transportation and agricultural production. This work could provide decision support for political decision-makers in formulating future public policies for managing agricultural production, food security, and natural disasters.

Background and Objectives: The deltopectoral (DP) flap represents a reconstructive option for head and neck. It is a fasciocutaneous flap raised from the anterior chest wall below the clavicle. Its role partially declined with the arise of free flaps. However, it still remains a valid option in patients that could not undergo a reconstruction with free flaps. The aim of this retrospective study was to evaluate the role of the DP flap in head and neck reconstruction, with a focus on surgical outcomes and complications. Materials and Methods: Thirty-one patients who underwent head and neck reconstruction with DP flap were included in the study. The delayed technique was not used in any procedure to harvest the flap beyond the deltopectoral groove. The patients’ characteristics, the recipient site, the closure of the donor site and the flap-related complications were recorded. Results: The median time to autonomization of DP flap was 23 days. Post-operative complications were observed in 10 subjects (32.3%). A partial necrosis was seen in 5 patients (16.1%), while a complete necrosis developed only in one case (3.2%). The diabetes mellitus was the only parameter associated to post-operative complications. In particular, the percentage of necrosis in subjects with or without diabetes was 66.7% and 8.0%, respectively. Conclusions: The DP has a wide range of applications in head and neck reconstruction and a low complication rate can be observed. The delayed technique does not necessarily need to be applied, and the flap can be extended beyond the deltopectoral groove when necessary. However, patients with diabetes mellitus have a higher risk of postoperative necrosis of the distal portion of the flap.

Current standard of care for brain tumor management includes maximal safe surgical resection followed by concurrent chemotherapy and radiation therapy. Recent advances in image-guided surgical techniques have enhanced the precision of tumor resections, yet there remains a critical need for innovative technologies to further improve patient outcomes. The emerging use of theranostic technologies to improve surgical outcomes can further augment the efficacy of adjuvant radiosurgery/radiotherapy and systemic therapies. Stanford Neurosurgery is a leader in the field of translational neuro-oncology. In this review, we provide an expert view of how theranostics can be integrated into future therapeutic treatment algorithms to help improve survival for patients with brain tumors.

Microscale swimmers have to face the dominance of viscous forces over inertial forces, the so-called low Reynolds number (hereafter Re) regime. The undulatory motion of an elastic tail is one of the few possible mechanisms for the self-propulsion of microswimmers in the particular conditions of low Re. Instead of using a complex arrangement of multiple actuators along the body of the swimmer, this work studies the propulsion of a swimming microrobot that is able to generate a non-reciprocal motion by moving a passive elastic tail with non-uniform properties using only a single actuator located at its head. A simulation model is developed in MATLAB to evaluate the effect of different mass and elasticity distributions in the tail on the microrobot propulsion. The results are used to observe the undulating motion of the tail and to optimize the design of the robotic microswimmers in terms of efficiency.

As the primary secondary tree species in Northeast China, Quercus mongolica possesses significant ecological and economic value. This study employed the Biomod2 platform in conjunction with ArcGIS spatial analysis to assess the potential suitable habitat distribution area of Q. mongolica under current climatic conditions. Furthermore, it forecasted the distribution range and niche changes of potentially suitable habitats for Q. mongolica from 2022 to 2090, and pinpointed the key environmental factors influencing its distribution. The findings reveal that the total potential suitable area for Q. mongolica covers 74,994.792 km², predominantly spread across Inner Mongolia, Heilongjiang, Jilin, and other regions. The primary determinants of suitable area distribution were peak temperature of hottest month, lowest temperature of coldest month and altitude. Under future climate scenarios, the potentially suitable habitats of Q. mongolica are anticipated to diminish to varying extents, with the distribution center exhibiting a tendency towards northward migration. Concurrently, the overlap among different climate scenarios is predicted to expand over time. This investigation facilitates a comprehensive understanding of Q. mongolica's adaptation to climate change, enabling informed adjustments and serving as a valuable reference for the preservation and sustainable management of Q. mongolica populations.

This paper explores how smart cities can cope with land subsidence and liquefaction in the context of rapid urbanization in Japan. Since the 1960s, liquefaction has become an important topic in geotechnical engineering, and great efforts have been made to evaluate the resistance of soil to liquefaction. There is currently a lack of machine learning applications specifically for smart cities in areas such as geological hazards. This study uses two machine learning techniques, artificial neural networks and ensemble learning, to obtain a prediction model with high performance in predicting the bearing layer depth to improve the accuracy of geo-engineering surveys. The model was developed by analyzing actual survey data from 433 locations in Setegaya, Tokyo, by using artificial neural networks (ANNs) and bagging, respectively. The results show that machine learning has great advantages in predicting the bearing layer depth. In addition, compared with a single model such as artificial neural networks, the prediction performance of ensemble learning can be improved by about 20%. Both interdisciplinary approaches can help predict address risks and thus promote sustainable urban development, highlighting the potential of smart cities in the future.

The COVID-19 pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has exposed the vulnerabilities and unpreparedness of the global healthcare system in dealing with emerging zoonoses. In the past two decades, coronaviruses (CoV) have been responsible for three major viral outbreaks, and the likelihood of future outbreaks caused by these viruses is high and nearly inevitable. Therefore, effective prophylactic universal vaccines targeting multiple circulating and emerging coronavirus strains are warranted. This study utilized an immunoinformatic approach to identify evolutionarily conserved CD4+ (HTL) and CD8+ (CTL) T cells, and B-cell epitopes in the coronaviral spike (S) glycoprotein. A total of 132 epitopes were identified, with the majority of them found conserved in the bat CoV, pangolins CoV, endemic coronaviruses, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). Their peptide sequences were then aligned and assembled to identify the overlapping regions. Eventually, two major peptide assemblies were derived based on their promising immune-stimulating properties. In this light, they can serve as lead candidates for universal coronavirus vaccine development, particularly in the search for pan-coronavirus multi-epitope universal vaccines that can confer protection against current and novel coronaviruses.

Non-viral mediated plasmid DNA transfection by electroporation (EP) is an established method for gene transfection. In this study, the usefulness of direct EP at an intradermal (i.d.) site (D_EP) with implanted electrodes to achieve a high protein expression level was investigated. In addition, D_EP application with various intervals with a low application voltage was also evaluated to confirm its effect on protein expression. A higher protein expression level was observed after green fluorescent protein (GFP)- and luciferase-encoding DNA were delivered by i.d. injection followed by D_EP application. When luciferase expression was observed with an in vivo imaging system, continuous expression was confirmed over 21 days after i.d. injection followed by D_EP at 100 V. This approach provided increased gene expression levels compared with conventional EP methods via the stratum corneum layer. In addition, the effect of application voltage on luciferase expression was investigated; two-time applications (repeated D_EP) at 20 V with 5 min intervals showed similar luciferase expression level to single D_EP application with 100 V. Histological observations showed the skin became thicker after a single D_EP at 100 V, whereas no apparent thickness changes was confirmed after repeated D_EP at 20 V with 5 min intervals. This study revealed that direct i.d. voltage application achieved high protein expression levels even at low voltages. Skin is a promising administration site for DNA vaccines, so this approach may be effective in DNA vaccine delivery into skin tissue.

Sentiment analysis is a pivotal tool for gauging the public’s perception and understanding of human communication across digital social media platforms. However, due to linguistic complexities and limited resources, sentiment analysis is not well-represented in many African languages. While benchmark Africa-Centric Pre-trained Language Models (PLMs) have been developed for various Natural Language Processing (NLP) tasks, their applications in eXplainable Artificial Intelligence (XAI) remain unexplored. In this study, we introduce a novel approach that combines Africa-centric PLMs with XAI techniques for sentiment analysis. We demonstrate that applying attention mechanisms and visualisation techniques improves the transformer-based model’s transparency, trustworthiness, and decision-making abilities when making sentiment predictions. We then employ the SAfriSenti—a multilingual sentiment corpus for South African under-resourced languages. We use the corpus to perform various sentiment analysis experiments and also enable comprehensive evaluations, comparing the performance of Africa-centric models against mainstream PLMs. The Afro-XLMR model outperformed all models and achieved an average F1-score performance of 71.04% across the five tested languages and the lowest error rate among the evaluated models. Additionally, we incorporated techniques like Local Interpretive Model-Agnostic Interpretation (LIME) and Shapley Additive Interpretation (SHAP) in the sentiment classifier’s output to enhance the Afro-XLMR model’s interpretability and explainability. As a result, the use of XAI strategies ensures that sentiment predictions are not only accurate and interpretable but also understandable, fostering trust and reliability in the decision-making of AI-driven NLP technologies, particularly in the context of African languages.

This paper critically reviews the convergence between Business Ecosystem Theory and Social Network Theory in sustainability studies. While both frameworks view organizations as part of larger, interconnected systems, they can be differentiated by six key dimensions: unit of analysis, focus, decomposability, types of relationships, market segment, and worldview. To better reflect real-world phenomena, this paper argues for a new stream of theoretical convergence that is practical, reliable, generalizable, and reproducible. Specifically, it proposes shifting from interoganizational networks to interfunctional networks, which reduces complexity, enhances stability over time, and provides a clearer theoretical distinction. This is illustrated through a case study of Tesla Inc.’s ecosystem, built from data presented in the company’s 10K form, which also serves as an example of the emergence of a new strategic construct named the Business Ecosystem Footprint. This construct could assist managers in understanding where their organization stands within the network of functions, guiding them in making informed decisions about resource allocation and diversification, specifically aimed at supporting financial goals as well as sustainability and decarbonization objectives. The article concludes by suggesting potential research agendas, such as automating ecosystem mapping, exploring the constraints of the new construct, and testing new hypotheses related to firm performance.

The rapid expansion of Bangladesh's financial infrastructure, coupled with the increasing digitization of banking services, underscores the critical importance of cybersecurity. Machine learning and deep learning methodologies have emerged as potent tools in combating cyber threats such as intrusion, malware, and fraud. By harnessing artificial intelligence and data-driven analysis, these techniques enable real-time scrutiny of vast banking data, facilitating proactive defense against cyberattacks. Bangladesh's evolving financial landscape, characterized by governmental digitalization initiatives and a national financial inclusion strategy, heightens the imperative for robust cybersecurity measures. This paper explores the application of machine learning and deep learning techniques in bolstering banking cybersecurity within the context of Bangladesh's burgeoning digital economy.

The integration of connected autonomous vehicles into the transportation system introduces significant enhancements in driving experience and convenience. Yet, it simultaneously raises important concerns regarding the security and privacy of passenger data. As individuals increasingly depend on these connected vehicles, particularly rental cars with advanced infotainment systems, safeguarding their personal information becomes a paramount imperative, presenting significant challenges that must be addressed to maintain user trust and comply with privacy regulations. This paper investigates risks associated with personal information stored in connected vehicle technology, emphasizing the importance of robust security and privacy practices. In the advent of cyber threats and the need for data protection, we examine a risk management framework (RMF) as suggested by NIST, which aims to address these quintessential concerns preemptively. Our research moves beyond the limitations of manual safeguarding methods, supporting the necessity for an advanced automated technical solution. To address these issues, we introduce and meticulously assess the efficacy of “Vehicle Inactive Profile Removal” (VIPR), an innovative technical solution conceived to actively eliminate the risks and potential oversights that stem from the prevalent tendency of renters to leave personal data unerased in the infotainment systems of rented connected vehicles. We provide a thorough evaluation of VIPR through various scenarios, including vehicle return to a rental depot, subsequent rentals, and ridesharing contexts. Our proof of concept includes an array of experiments to demonstrate how VIPR proficiently and autonomously removes previous renters’ “Inactive” profiles from a simulated infotainment system. The results highlight how VIPR constitutes a critical step towards enhancing the privacy and security of personal data, thereby promoting a safer, more responsible use of connected vehicle technology in society.

The earth infrastructure is the backbone of the global economy, connecting people, enhancing quality of life, and promoting health and safety. However, its vulnerabilities are becoming apparent due to climate change, mainly through frequent wetting and drying (wd) cycles. This study aimed to assess the impact of controlled w-d cycles on the hydromechanical properties of clayey and silty sand soils and its implications for the performance of a typical flood embankment. Volumetric changes were monitored during the w-d cycles. Soil water characteristic curve (SWCC), saturated hydraulic conductivity (ksat), effective cohesion (c’) and effective angle of internal friction (ϕ’) were measured at 1 and 10 w-d cycles. The results indicated that the 10 w-d cycles decreased the saturated moisture content and a flatter SWCC compared to the 1 w-d cycle for clayey soil. The ksat was also significantly higher at 10 w-d cycles than the 1 w-d cycle for clayey soil. An insignificant difference was found in both SWCC and ksat at 1 and 10 w-d cycles for silty sand soil. The ϕ’ for the clayey soil decreased from 28.5 to 20.1 as the wd cycles increased from 1 to 10, while the c’ remained unchanged at 10 kN/m2. On the other hand, for the silty sand soil, the ϕ’ increased from 34.6 to 37.5 with an increase in w-d cycles from 1 to 10, and the c’ remained constant at 1 kN/m2. Numerical modelling of transient water flow coupled with slope stability analysis revealed the dependence of flood embankment performance on the soil's hydromechanical properties and the flooding duration. These findings underscore the need for proactive measures to mitigate landslide risks in regions prone to frequent w-d cycles, thereby ensuring the safety and resilience of slopes and associated infrastructure.

The microvessel neurovascular unit with its brain endothelial cell (BEC) and blood-brain barrier remodeling is important in the development of impaired cognition in sporadic or late-onset Alzheimer’s disease (LOAD) and vascular dementia or vascular cognitive impairment and dementia including cerebral amyloid angiopathy in neurodegeneration. LOAD is considered to be the number one cause of dementia globally; however, when one considers the role of mixed dementia (MD) (the combination of both the amyloid cascade hypothesis and the vascular hypothesis of LOAD), it becomes apparent that MD is the number one cause. The microvessel BECs are the first cells in the brain to be exposed to the peripheral neurotoxins of the systemic circulation and are therefore the brain cells at the highest risk for early and chronic injury. Therefore, it is not surprising that microvessel BECs are the first cells to undergo injury and the response to injury wound healing mechanism and remodeling that is excessive and recurrent in the aging process plus other age-related diseases such as cerebro-cardiovascular disease, hypertension, type 2 diabetes mellitus, Parkinson’s disease, plus others. This narrative review explores the intricate relationship between microvessel remodeling, cerebral small vessel disease (SVD), and neurodegeneration as occurs in LOAD. Further, it discusses the current understanding of how microvessel dysfunction, disruption, and pathology contribute to the pathogenesis of LOAD and thus, highlights potential avenues for therapeutic interventions.

The growth of photosynthetic organisms requires specific ranges of temperature and photosynthetically active radiation that are technically difficult to achieve and control, especially in outdoors cultures. In such cases, a typical meteorological sequence can be a useful tool to estimate the growth of photosynthetic organisms. This work proposes a new methodology based on long-term meteorological sequences to simulate the growth of photosynthetic organisms. A case of study that addresses the simulation of the growth of microalgae (Chlorella vulgaris) in Riosequillo, north of the Madrid region (Spain), is shown for the four seasons of the year, and these estimates are then compared with the observed results of an experimental microalgae culture in domestic wastewater. The results also show great agreement with the probability distribution function of the biomass concentration per day, obtaining the best results for typical meteorological sequences of summer and spring. The methodology seems to confirm the representativeness of typical meteorological sequences and also allows the identification of the most likely production scenarios for the feasibility analysis of projects, which has potential application in decision-making processes.

The utilization of foam in contact with individuals often leads to its deterioration, necessitating periodic material changes to prevent degradation and maintain sanitary conditions. Foam, a porous plastic material formed by an aggregation of bubbles, offers lightweight and impact-absorbing properties, yet its porosity and susceptibility to wear pose challenges. The project's overarching goal is to develop a technological application for repurposing spent foam materials and textile elements from leisure facilities into impact absorption systems. This initiative aims to minimize environmental impact by reusing materials and leveraging their technical characteristics, including those of polyurethanes and textiles. By addressing the challenge of foam deterioration, the project seeks to create sustainable solutions. The development of impact absorption systems will involve the utilization of spent foam, either by reintegrating it into the system after its initial use or combining it with waste textiles. This innovative approach not only promotes sustainability but also enhances safety by ensuring the availability of high-quality impact-resistant elements. Through this endeavor, the project aims to contribute to both environmental conservation and the advancement of effective anti-impact measures in leisure facilities.

Damage to peripheral arteries by the atherosclerotic process accounts for about 3% of the world's population, which puts this problem in the category of major social problems. Modified lipoproteins and cholesterol crystals are known to accumulate in the arterial intima and cause the formation of proatherogenic macrophages, foam cells, and inflammation. Defective efferocytosis of apoptotic foam cells leads to the formation of a necrotic core, a sign of failure to resolve inflammation. Resolution of inflammation is mediated by specialized pro-resorption lipid mediators, proteins and signaling gases. Improving the balance between pro-inflammatory and anti-inflammatory factors contributes to the reverse development of local atherogenesis. Active direct intervention in the reconstruction of the adventitial layer of the arterial wall using cholesterol-affinity polysaccharide hydrogels containing a cocktail of growth factors creates conditions for the formation of additional extracellular matrix and reversal of cholesterol mass from the subintimal zone. Creating concentration and electrostatic gradients in the adventitia zone using a hydrogel may be one of the effective ways to degrade early soft atherogenic plaques and locally restore the damaged structure of the vessel wall. Growing scientific interest in the previously insufficiently studied adventitia indicates its important role in angionesis and atherogenesis.

Despite the existing effective treatment methods, tuberculosis (TB) is the second most deadly infectious disease globally, its carriers in the latent and active phases accounting for more than 20% of the world population. An effective method to control TB and reduce the mortality is regular population screening and diagnosis of the latent form of TB in order to take preventive and curative measures. Numerous methods allow diagnosing TB and directly detecting Mycobacterium tuberculosis (M.tb) biomarkers, including M.tb DNA, proteins, and specific metabolites, as well as antibodies produced by the host immune system in response to M.tb. PCR, ELISA, immunofluorescence and immunochemical analyses, flow cytometry, and other methods allow the detection of M.tb biomarkers or the host immune response to M.tb by recording the optical signal of fluorescent or colorimetric dyes included in the diagnostic tools. Current research in biosensors is aimed at increasing the sensitivity of detection, which can be achieved by using brighter and more photostable optical tags containing fluorescent quantum dots. Here, we review current methods for detection of M.tb biomarkers using optical sensor systems, primarily quantum dot–based nanosensors, and summarize M.tb biomarkers whose detection can be made significantly more sensitive by using quantum dot–based nanosensors.

This study assesses the alignment of Singaporean companies’ sustainability reporting with the newly introduced International Financial Reporting Standard S1, a global framework for sustainability-related financial disclosures. Given Singapore’s role as a major financial hub, understanding the extent to which local companies comply with this standard is critical to promoting transparency and accountability in sustainability practices. The study was conducted in two phases: the first phase was to summarize the timing of different countries’ preparations for the implementation of the IFRS S1 standard, as well as their attitudes. The second phase was a content analysis of the sustainability reports of 70 listed companies. The findings show that while companies are generally proactive in reporting governance, strategy, and metrics, they fall short in risk management disclosure, which is an important requirement of IFRS S1. This gap highlights the challenges companies face in incorporating comprehensive risk management practices into sustainability reporting. This study provides a reference for improving future sustainability reporting and encourages companies to align more closely with IFRS S1 to meet investors’ growing demand for transparent and standardized sustainability disclosures.

Medullary thyroid carcinoma (MTC) is a rare yet aggressive form of thyroid cancer, comprising a disproportionate share of thyroid cancer-related mortalities despite its low prevalence. MTC differs from other differentiated thyroid malignancies due to its heterogeneous nature, presenting complexities in both hereditary and sporadic cases. Traditional management guidelines, designed primarily for papillary thyroid carcinoma (PTC), fall short in providing the individualized care required for MTC patients. In recent years, the sheer volume of data generated from clinical evaluations, radiological imaging, pathological assessments, genetic mutations, and immunological profiles has made it humanly impossible for clinicians to simultaneously analyze and integrate these diverse data streams effectively. This data deluge necessitates the adoption of advanced technologies to assist in decision-making processes. Holomics, an integrated approach that combines various omics technologies, along with artificial intelligence (AI), emerges as a powerful solution to address these challenges. AI-driven precision oncology can significantly enhance the diagnostic work-up, staging, risk stratification, management, and follow-up care of MTC patients by processing vast amounts of complex data quickly and accurately. AI algorithms can identify patterns and correlations that may not be apparent to human clinicians, thereby improving the precision of personalized treatment plans. Moreover, the implementation of AI in MTC management enables the collation and synthesis of clinical experiences from across the globe, facilitating a more comprehensive understanding of the disease and its treatment outcomes. This global approach aligns with the United Nations Sustainable Development Goal 3, which aims to ensure healthy lives and promote well-being for all at all ages. By leveraging AI and holomics, we can strive towards making personalized healthcare accessible to every individual, regardless of their economic status, thereby improving overall survival rates and quality of life for MTC patients worldwide. In conclusion, the integration of holomics and AI in the management of medullary thyroid carcinoma represents a significant advancement in precision oncology. This innovative approach not only addresses the complexities of a rare and aggressive disease but also paves the way for global collaboration and equitable healthcare solutions, ultimately transforming the landscape of MTC treatment and care.

Vitamin D and iron deficiencies are the most prevalent micronutrient deficiencies among women of reproductive age (WRA) in Morocco. Recent studies suggest that Vitamin D deficiency (VDD) may reduce iron bioavailability necessary for erythropoiesis, potentially leading to iron deficiency (ID) and anemia. This study investigates the association between vitamin D status, iron levels, and anemia risk among Moroccan WRA aged 18-49 years. A cross-sectional study was conducted with 463 participants. Serum levels of 25(OH)D, blood count parameters, iron, ferritin, C-reactive protein, and creatinine were measured. Lifestyle factors, including dietary intake, sun exposure, and physical activity, were evaluated using validated questionnaires, and anthropometric data were collected. Linear and logistic regression models assessed the relationships between variables, while Receiver Operating Characteristic (ROC) curve analysis evaluated the predictive accuracy of VDD for ID and anemia. VDD (25(OH)D &lt; 20 ng/ml) was significantly associated with lower levels of hemoglobin, hematocrit, red blood cells, and ferritin (all p &lt; 0.01), suggesting a role of vitamin D in erythropoiesis and iron storage. Multivariate logistic regression showed that VDD increased the risk of anemia (OR: 7.17, 95% CI: 3.19-19.28, p &lt; 0.001), ID (OR: 2.20, 95% CI: 1.32-3.77, p = 0.007), and IDA (OR: 4.10, 95% CI: 1.73-12.08, p = 0.004). Dietary iron intake was inadequate among all participants, with minimal protective effect against anemia and ID (β(SE): -0.08(0.03), p = 0.030 and β(SE): -0.05(0.02), p=0.037 respectively). ROC analysis demonstrated moderate discriminative power for VDD in diagnosing IDA and anemia (AUC: 0.643 and 0.603) but reduced accuracy for ID (AUC: 0.575). This study identifies VDD as a significant risk factor for impaired iron status and anemia among Moroccan WRA, underscoring the need for targeted nutritional interventions and further research to explore effective prevention strategies.

Septic arthritis (SA) represents an orthopedics urgency and mainly affects the knee joint. Due to its devastating effects on cartilage, immediate management is crucial. SA is characterized by an an-nual incidence of 2 to 10 cases per 100,000 individuals, with mortality rates fluctuating between 0.5% and 15%, with a substantially higher mortality rate observed in older people (15%) in con-trast to younger cohorts (4%). The etiology of septic arthritis is multifactorial: a spectrum of Gram-positive and Gram-negative bacteria can contribute to the development of this condition, especially Staphylococcus aureus. The treatment involves urgent (arthroscopic or arthrotomic) debridement associated with adequate antibiotic therapy. Intra-articular antibiotic carriers can also be used to increase their local concentration and effectiveness. The case of a 67-years-old woman affected by knee SA from methicillin-susceptible S. aureus is presented. She was treated with an arthroscopic debridement enhanced by intra-articular antibiotic-loaded calcium sulphate beads, together with antibiotic therapy. At 2-year follow-up, the infection has been eradicated and the patient fully recovered. This is the first description, to our knowledge, in English Literature of the use of antibiotic-loaded calcium sulphate beads as an adjuvant in the surgical treatment of SA of a native knee joint.

In response to the problem of poor detection ability of object detection models for small-scale targets in intelligent transportation scenarios, a fusion method is proposed to enhance the features of small-scale targets, starting from feature utilization and fusion methods. The algorithm is based on the YOLOv4 tiny framework and enhances the utilization of shallow and mid level features on the basis of FPN, improving the detection accuracy of small and medium-sized targets; In view of the problem that the background of the intelligent traffic scene image is cluttered and there is more redundant information, the CBAM attention module is used to improve the attention of the model to the traffic target; To address the problem of data imbalance and prior bounding box adaptation in custom traffic datasets that expand traffic images in COCO and VOC, we propose a Copy Paste method with improved generation method and a K-means algorithm with improved distance measurement to enhance the model's detection ability for corresponding categories. Comparative experiments were conducted on a customized 260 thousand traffic dataset containing public traffic images, and the results showed that compared to YOLOv4 tiny, the proposed algorithm improved mAP by 4.9% while still ensuring the real-time performance of the model.

This study addresses the gap in research on the application of thermochromic polymers (TPs) in food packaging and their potential for real-time temperature monitoring, aiding in the assessment of food quality and shelf-life. TPs exhibit a visible color change in response to temperature varia-tions. A comprehensive systematic review (SR) across multiple engineering peer-review databases using predefined terms was conducted. Additionally, international patent databases were inves-tigated using the same predefined terms. Independent experts reviewed the methodology to identify and address potential biases. A total of 288 eligible articles and 922 patents were identified. After a duplicate selection and extraction process according to the inclusion criteria, four related full-text publications were selected from the initial 288 articles, and five relevant patents were selected from the 922 patents. The qualitative review suggests that TPs hold significant promise as food packaging materials due to their unique physical properties. The study concludes that TPs offer valuable properties for the food packaging industry, meriting further investigation to exploit their benefits fully.

The hot pressing process for 100% coriander-based fiberboards was optimized using an induction RocTool system, which offers rapid mold heating and cooling. The fiberboards were made with deoiled press cake as a proteic binder and extrusion-refined straw as reinforcement. A Doehlert’s experimental design evaluated the influence of pressure (10-50 MPa), molding time (60-300 s), and mold temperature (155-205°C) on fiberboard properties, energy consumption, cost, and environmental impact. The results showed that the RocTool device allows better temperature control during shaping, resulting in exacerbated adhesive properties for proteins. Using the isoresponse curves, optimal hot pressing conditions were 35 MPa, 300 s, and 205°C, corresponding to a 40.6 MPa flexural strength. However, it was observed that to achieve a MDF-like fiberboard with minimal production cost, much less restrictive molding conditions were sufficient, i.e., 32.5 MPa, 170 s, and 160°C. The study revealed that maximum thermopressing conditions emitted 3.87 kg of CO2 eq., while conditions leading to the MDF-like board reduced emissions to 1.45 kg CO2 eq., resulting in a more environmentally-friendly material.

Disruptions in power quality have a negative impact on many energy consumers. These include lighting, where interference manifests itself, among others, in the form of light flickering. The article presents phenomena accompanying the operation of modern light sources against the background of exemplary results of studies on the flicker of conventional light sources, such as incandescent or fluorescent lamps. To assess the effects of these phenomena, it is necessary to use measures other than those traditionally used. The results of measurements carried out in accordance with different recommendations take into account both power supply disturbances and the properties of modern light sources.

Increased platelet activity is a risk factor of thrombotic events in cardiovascular patients. We studied the relationship between platelet function, platelet size and content of reticulated platelets (RP) in patients with coronary heart disease (CHD, n = 55) and acute coronary syndrome (ACS, n = 95) receiving acetylsalicylic acid + clopidogrel or ticagrelor respectively. Control group consisted of patients with risk factors for CHD, but no CHD/ACS and free of antiplatelet drugs (n = 66). Platelet function was evaluated by exposure of activated glycoprotein (GP) IIb-IIIa and P-selectin. In the control group, platelets were activated by TRAP (Thrombin Receptor Activating Peptide) 10 µM, ADP 20, 5, 2.5 µM and in CHD/ACS groups, by TRAP 10 µM, ADP 20, 5 µM (+/- epinephrine 20 µM). Platelet size was assessed by mean volume, % large forms and forward scattering. RP were stained by thiazole orange. In the control group activated GP IIb-IIIa and P-selectin correlated with platelet size and RP content after platelet activation by all agonists. Despite the decrease of platelet activity by antiplatelet drugs, most correlations (primarily for activated GP IIb-IIIa) were preserved in CHD/ACS patients. In conclusion, increased platelet size and RP content are associated with increased platelet activity and reduced efficacy of antiplatelet therapy.

The study assessed the impact of different diets on gastrointestinal pH, intestinal microbiota, digestive tract morphometry, and productive performance in guinea pigs. A total of 160 improved genotype guinea pigs were used, distributed into three groups with different diets: alfalfa (T1), alfalfa + concentrate (T2), and concentrate (T3), to which a mixture of probiotics combined with vitamins, minerals was added and amino acids in T2 and T3. Gastrointestinal pH showed significant differences between treatments in the various segments of the digestive tract. The intestinal microbiota varied according to the diet, with Escherichia coli being the predominant bacterium in weaned guinea pigs. Intestinal morphometry was significantly altered with the addition of a reinforced probiotic mixture, improving the length and density of intestinal villi. Productive parameters such as weight gain, feed consumption, and feed conversion were better in guinea pigs fed a mixed diet with 0.5% probiotic mixture. These results indicate that intestinal pH may influence microbial composition, which impacts productive efficiency and immune health, highlighting the importance of balanced nutrition and supplementation to optimize the health and performance of guinea pigs.

A novel multicomponent glasses with nominal compositions of (50-x)MoO3:xWO3:25La2O3:25B2O3, x = 0, 10, 20, 30, 40, 50 mol% doped with 3 mol % Eu2O3 were prepared using a conventional melt quenching method. Their structure, thermal behavior and luminescent properties were investigated by Raman spectroscopy, differential thermal analysis and photoluminescence spectroscopy. Physical parameters as density, molar volume, oxygen molar volume and oxygen packing density were determined. Glasses are characterized with high glass transition temperature. Raman analysis revealed that the glass structure is built up mainly from tetrahedral (MoO4)2- and (WO4)2- units providing Raman bands of around 317 cm-1, 341-352 cm-1, 832-820 cm-1 and 928-935 cm-1. At the same time with the replacement of MoO3 with WO3 some fraction of WO6 octahedra are produced, which number increases with the increasing WO3 content. A strong red emission from the 5D0 level of Eu3+ ions was registered under near UV (395 nm) excitation using the 7F0 →5L6 transition of Eu3+. PL emission gradually increases with increasing WO3 content evidencing that WO3 is more appropriate component than MoO3. The integrated fluorescence intensity ratio R (5D0 →7F2/5D0 →7F1) was calculated to estimate the degree of asymmetry around the active ion, suggesting a location of Eu3+ in non-centrosymmetric sites.

The decline in global pollinator populations has raised serious concerns about the sustainability of ecosystems and agricultural productivity. Urban environments, often characterized by habitat loss and environmental stressors, are considered challenging habitats for pollinators. However, urban green spaces, including street and ornamental trees, can play a crucial role in supporting pollinators by providing essential food resources. This study aimed to evaluate the sugar and amino acid production of eight urban tree species to determine their potential contributions to pollinator nutrition. Our findings revealed significant variability among species regarding nectar volume, sugar content, and amino acid composition, emphasizing the importance of considering multiple factors when assessing the utility of floral resources. Consequently, Tilia amurensis, Heptacodium miconioides, Aesculus turbinata, and Wisteria floribunda demonstrated superior potential in supporting urban pollinator communities. Contrastingly, Sorbus commixta, Styrax japonicus, and Cornus kousa, often favored for their aesthetic appeal, showed less potential. This study underscores the need for urban tree selection that prioritizes species that provide diverse and abundant nutritional resources for pollinators while balancing aesthetic and ecological values. Our results offer a foundation for better-informed urban biodiversity management and contribute to creating pollinator-friendly urban environments.

This review explores the critical difficulties confronting global agriculture in the face of changing climate patterns and limited resources, highlighting the importance of sustainable practices. With agriculture as the largest consumer of water worldwide, sustainable techniques are critical for long-term survival and ecological harmony. Even with advancements, rapid population increase and changing environment conditions demand immediate investment in cutting-edge technologies. Optimizing agricultural operations, increasing output, and reducing resource waste can be achieved through smart farming, which utilizes machine learning and Internet of Things tech-nologies. Particular difficulties like decreasing cultivator proportions and rising costs are empha-sized, with a focus on developing nations where agriculture plays a crucial role in the economy. Additionally, the anticipated rise in food demand highlights how urgent it is to find sustainable alternatives. But problems like inappropriate land and agricultural land fragmentation still exist, necessitating creative solutions. The paper explores how agriculture could be revolutionized by machine learning and IoT-based hydroponics, providing insights into how to improve resilience, productivity, and sustainability in the face of changing environmental and socioeconomic dy-namics. Through a thorough investigation, this paper advances the discussion on sustainable ag-riculture by demonstrating the important role that technology-driven strategies play in addressing concerns about environmental sustainability and global food security.

This research investigates the energy consumption of buildings managed by traditional Building Management Systems (BMS) and proposes the integration of Internet of Things (IoT) technology to enhance energy efficiency. Conventional BMS often suffer from significant energy wastage and safety hazards due to sensor failures or malfunctions. These issues arise when building systems continue to operate under unknown conditions while the BMS is offline, leading to increased energy consumption and operational risks. The study demonstrates that integrating IoT systems with existing BMS can substantially improve energy efficiency in smart buildings. The research involved designing a system architecture prototype, performing MATLAB simulations, and real-life case study which revealed that IoT devices are effective in reducing energy waste, particularly in Heating, Ventilation, and Air Conditioning (HVAC) systems and lighting. Additionally, an auxiliary bypass system was incorporated in parallel with the IoT system to enhance reliability in the event of IoT system failures. Preliminary findings indicate that the integration of IoT systems with traditional BMS significantly boosts energy efficiency and safety in smart buildings. This integration offers a promising solution for advancing energy management practices and policies, thereby improving both operational performance and sustainability in building management.

Due to global climate change, cold temperatures have significantly impacted rice production, resulting in reduced yield and quality. In this study, we investigated two traits related to cold tolerance (CT) of 1992 diverse rice accessions at the seedling stage. Geng accessions exhibited higher levels of CT compared to xian accessions, with the GJ-tmp subgroup displaying the strongest CT. However, extreme CT accessions were also identified within the xian subspecies. Through GWAS analysis based on survival rate (SR) and leaf score of cold tolerance (SCT), a total of 30 QTLs associated with CT at the seedling stage were identified, among which four QTLs (qSR3.1a, qSR4.1a, qSR11.1x and qSR12.1a) were found to be important. Furthermore, five candidate genes (LOC_Os03g44760, LOC_Os04g06900, LOC_Os04g07260, LOC_Os11g40610 and LOC_Os12g10710) along with their favorable haplotypes were identified through gene function annotation and haplotype analysis. Pyramiding multiple favorable haplotypes resulted in a significant improvement in CT performance. Subsequently, three selected accessions (CX534, B236, and IRIS_313-8565), carrying different superior alleles for CT, were selected and recommended for molecular breeding for CT using marker-assisted selection (MAS). The findings from this study provide valuable resources for enhancing rice's ability for CT while laying a foundation for future cloning of novel genes involved in conferring CT.

Robotic systems are crucial in modern manufacturing. Complex assembly tasks require the collaboration of multiple robots. Their orchestration is challenging due to tight tolerances and precision requirements. In this work we set up two Franka Panda robots performing a peg-in-hole insertion task. We structure the control system hierarchically, planning the robots’s trajectories feedback-based with a central policy trained with reinforcement learning. These trajectories are executed by a low-level impedance controller on each robot. To enhance training convergence, we use reverse curriculum learning incorporating domain randomization, varying initial configurations of the task. After training, we test the system in a simulation, studying the impact of curriculum parameters on emerging process characteristics like process time and variance. Finally, we transfer the trained model to a real-world setup, comparing results with simulation as well as classical path planning and control approaches.

This article introduces a new interpretation to Socialism that approaches it via a heuristic study of Epochs. It is intended by this study that the intention of socialism (what it politically, socially, et cetera is proclaimed to be) is to be proposed to be indeterminate.The expectation of what Socialism is to be as a future entity is merely an interpretation that is predicated on Marx’s Capitalist Laws that have been since shown to be false. Its argument is suggested significantly by Engels’ discussions of human development and therein places an added focus on a historically based platform.

Keywords: cranberry, exercise, proteomics, oxylipins, gut microbiome, metabolomics, immunity

Cyclin-dependent kinase 1 (Cdk1) is a master regulator of the G2-M transition between DNA replication and cell division. This study investigates the regulation of cardiomyocyte (CM) proliferation during the early neonatal period and following ischemic injury in adult mice. We analyzed cell cycle dynamics with the assessment of DNA synthesis, and cytokinesis in murine hearts during the first 15 days after birth. A distinct proliferative block was observed at 1 day, followed by a second wave of DNA synthesis at 4 days, leading to CM binucleation (CMBN) by day 5. Genome-wide mRNA profiling revealed differential expression of cell cycle regulatory genes during this period, with a downregulation of factors involved in cell division and mitosis. The loss of Cdk1 impaired CMBN but extended the neonatal CM proliferation window until day 10 post-birth. In adult hearts, cardiac-specific ablation of Cdk1 triggered CM proliferation post-myocardial infarction (MI) in specific zones, driven by the activation of EGFR1 signaling and suppression of the anti-proliferative p38 and p53 signalling. This was accompanied by restoration of fractional shortening, mitochondrial function, and decreased reactive oxygen species. Additionally, cardiac hypertrophy was mitigated, and survival rates post-MI were increased in Cdk1 knockout mice. These findings reveal a novel role of Cdk1 in regulating cell cycle exit and re-entry in differentiated CM and offer insights into potential strategies for cardiac repair.

This paper discusses the application and advantages of artificial intelligence technology in digital media interactive product design. Firstly, the development background of artificial intelligence technology and its promoting effect on design innovation is introduced, and the application of new technologies, such as generative adversarial networks in art creation and design personalization, is definitely analyzed. It then explores in detail the ability of AI to break traditional constraints in interactive design, innovate design, and optimize user experience, especially in digital media. Finally, the case study of Microsoft Cortana shows the method of classifying and processing user queries by machine learning system and its experimental results. The research of this paper provides the theoretical basis and empirical support for the application of artificial intelligence technology in the future interactive design of digital media and has important academic and practical significance.

This study focuses on the development and evaluation of an AI-based digital therapeutic prototype for adolescent mental health management and disaster response. The system integrates real-time monitoring, AI-driven conversation analysis, personalized psychological treatment programs, and multimodal data analysis. An algorithm was developed to detect gaslighting and verbal abuse using a BERT-based classification model, achieving 85% accuracy in gaslighting detection and 87% ac-curacy in verbal abuse detection. Additionally, a disaster psychological recovery support module was included, which demonstrated a 30% improvement in users' stress reduction rates in simulated disaster scenarios. The results of this study suggest that such digital therapeutic approaches can significantly contribute to early intervention in adolescent mental health issues and provide effec-tive support during disasters. The developed prototype demonstrates the potential of AI and digital technology to innovate mental health management and disaster response strategies.

Stem cell-derived therapies have shown substantial promise in regenerative medicine for the treatment of degenerative diseases and injuries. Mesenchymal Stem Cells (MSCs) exhibit a remarkable capacity to differentiate into diverse cell types, modulate immune responses, and facilitate tissue repair. Nevertheless, concerns regarding their potential to induce tumors arise from their intrinsic properties, environmental factors, and genetic mutations that occur during handling. This review explores the intricate challenges associated with the tumorigenic potential of stem cell-derived therapeutic products and examines the underlying mechanisms contributing to this risk, such as oncogene activation, suppression of tumor suppressor genes, and the influence of the microenvironment on stem cell behavior. Furthermore, it delves into the role of epigenetic modifications and chromosomal aberrations in cell culture and expansion. This article provides an overview of strategies to mitigate tumorigenic risks, encompassing rigorous quality control measures, refined differentiation protocols, and advanced screening techniques. It also highlights innovative approaches, such as gene editing technologies and small-molecule modulation of stem cell behavior, as promising avenues to enhance safety. Despite these challenges, ongoing research and technological advancements are actively addressing these concerns to ensure safer and more effective utilization of stem cell-based therapies in clinical settings.

Identifying locations of landslide slip surfaces provides critical information for understanding the volume of landslides and the scale of disasters, which is essential for formulating disaster preparedness and mitigation strategies. Based on hydrogeological survey data from 24 deep-seated landslide-prone sites in Taiwan's mountainous regions, this study first developed the hydraulic conductivity potential index (HCPI) using principal component analysis to quantify hydraulic properties of disturbed rock formation with six geological factors. Then, The regression analysis was performed to construct a permeability estimation model for the geological environment of landslides. Finally, the established model was utilized to develop an identification method for potential slip depths in landslide-prone sites. Results indicated a strong relation between HCPI and hydraulic conductivity with a determination coefficient of 0.895. The relation equation confirmed that its generated data concerning the depths of significant changes in hydraulic conductivity could be used to identify potential slip surfaces. Additionally, this study successfully establishes a rule for identifying potential slip zones by summarizing data concerning the generated hydraulic conductivity profiles, stratigraphic lithology, existing inclinometer slip depth records, and groundwater level of landslide sites. This identification method was then applied to predict potential slip depths for ten landslide sites where slip surfaces have not yet occurred. These findings offer a new alternative to having early information on potential sliding depths for timely disaster management and control implementation.

Leucine is an essential amino acid that cannot be produced endogenously in the human body and therefore needs to be obtained from dietary sources. Leucine plays a pivotal role in stimulating muscle protein synthesis along with isoleucine and valine as the group of branched-chain amino acids making them as one of the most popular dietary supplements for athletes and gym-goers. Individual effects of leucine, however, are not fully clarified, as most of the studies focused on the grouped effects of branched-chain amino acids. In recent years, leucine and its metabolites have been shown to stimulate muscle protein synthesis mainly via mammalian target of rapamycin complex 1 signaling pathway, thereby improving muscle atrophy in cancer cachexia. Interestingly, cancer research suggests that leucine may have either anti-cancer or carcinogenic effects. In the current manuscript, we aim to review leucine's roles in muscle protein synthesis, tumor suppression, and tumor progression, specifically summarizing the molecular mechanisms of leucine's action. The role of leucine is controversial in hepatocellular carcinoma, whereas its carcinogenic effects have been demonstrated in breast and pancreatic cancers. In summary, leucine being used as nutritional supplement for athletes needs more attention, as its oncogenic effects may have been identified by recent studies. Anti-cancer or carcinogenic effects of leucine in various cancers should be further investigated to have clear conclusions.

Cardiofaciocutaneous (CFC) syndrome, linked to mutations in genes including KRAS, BRAF, MEK1, and MEK2, leads to dysregulated RAS-MAPK signaling with limited therapeutic options. This study utilized molecular docking simulations to screen natural compounds against mutated KRAS, BRAF, MEK1, and MEK2 structures. Promising candidates such as Amentoflavone and Hypericin displayed strong binding affinities and favorable interactions with mutated sites, suggesting their potential as lead molecules for targeted therapies in CFC syndrome. This research offers novel insights into therapeutic interventions for this rare genetic disorder.

or the first time, this communication is intended to perform the possible biological role of natural compound Hypericin, in the Crystal Structure of dual-specificity tyrosine phosphorylation regulated kinase 2 (DYRK2), by Molecular and Dynamic Simulation. From Docking analysis by Autodock Vina and Autodock 4, Hypericin shows a significant ability to binds to DYRK2 protein, an important receptor for cell growth and development. Indeed, from docking studies Hypericin reports a binding energy value of about -13 kcal/mol and Estimated Inhibition Constant (Ki)of ca 1nM . Regarding MD simulation.From our results, this theoretical research it could has excellent future implications in the fight against cancer disease.

In this preliminary investigation, a concise molecular docking study using the Pyrx program screened thousands of compounds against the active site of HIV-1 reverse transcriptase. The Virtual Screening library was employed to assess binding energetics scores, focusing on identifying candidates with high Vina Scores. Eight compounds, including Tetrophan, Imatinib, Amentoflavone, Alprazolam, Bilobetin, Bafetinib, Nilotinib, and Ginketin, emerged as promising candidates with significant binding energies.Recognizing compounds that strongly bind to HIV-1 reverse transcriptase holds potential for antiretroviral drug development in the fight against HIV infection. Subsequently, the study evaluated the toxicity properties of these candidates using pKCSM. Amentoflavone, a natural biflavonoid found in Ginkgo biloba and Nilotinib, a tyrosine kinase inhibitor, demonstrated lower overall toxicity profiles compared to other candidates. Further toxicity analysis using Pro-Tox-II revealed Amentoflavone's higher predictive LD50, lower toxicity class, and reduced probabilities of hepatotoxicity, carcinogenicity, mutagenicity, and moderate immunotoxicity compared to Nilotinib. While Nilotinib, a pharmaceutical drug, exhibited higher probabilities of adverse effects in these categories. In summary, Amentoflavone and Nilotinib present as promising candidates with lower toxicity concerns. Amentoflavone, as a natural substance, showcases a more favorable toxicity profile than Nilotinib, offering valuable insights for potential therapeutic applications.

Background Cervical insufficiency, marked by recurrent painless cervix dilation leading to second-trimester pregnancy losses, is traditionally managed through cerclage placement and vaginal progesterone administration. However, a recent experimental approach targeted intra-amniotic inflammation or infection in a selected group of women with cervical dilation over 1 cm, intact membranes, and no uterine contractions in the second or third trimester. Case presentation We report a case of a 21 year old primigravid woman who experienced resolution of mid-trimester cervical insufficiency after the administration of triple antibiotic therapy, as confirmed by ultrasound monitoring. Remarkably, the patient successfully carried the pregnancy to term and delivered a healthy baby. Conclusions This case highlights the potential effectiveness of a novel combination of antibiotics, even in the presence of several high-risk pregnancy conditions, and underscores the possibility of a favorable outcome.

Background: The hub-and-spoke model (HSM), offers a framework for efficient healthcare service delivery. This scoping review seeks to establish the implementation and effectiveness of the HSM in Antimicrobial Stewardship (AMS) programs. Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) reporting guideline was followed. A systematic search was conducted in four electronic databases (PubMed, Medline, Cochrane library and Google scholar) from inception until January 2024. Studies where the HSM was used for delivering any AMS activity, intervention or action, were included. No study specific filters were applied and all populations, study designs and health settings were included. Data screening and selection was achieved using Rayyan. Three authors independently screened studies, with conflicts resolved by a fourth author. Data were narratively synthesized. Standard appraisal tools were impractical; however, critically evaluation of data collection and outcome reporting was ensured. Results: Out of 1,438 articles, three were included in the scoping review. The primary interventions utilising the HSM in AMS involved reducing antibiotic misuse, training healthcare professionals, case-based learning, establishing AMS programs, developing antibiograms, and formulating policies or guidelines pertinent to AMS. The studies demonstrated significant clinical improvements in AMS. Clinical outcomes from the studies include a significant reduction in antimicrobial usage and improved antibiotic management, with a notable decrease in days on antimicrobial therapy and increased antibiotic de-escalation. Key facilitators for AMS program success: tailored education, collaborative learning, strong leadership, strategic practices, and data-driven decisions. Key barriers: leadership challenges, change resistance, knowledge gaps, inadequate data systems, resource limitations, and technological constraints. Conclusion: The review identified a literature gap in HSM use for AMS programs. Further studies are needed to assess HSM's effectiveness, feasibility, and cost-effectiveness in AMS contexts.

The fast fashion industry has a significant impact on the environment at every stage of the product life cycle. There is a lack of research in the literature on the impact of fast fashion on the environment through logistics and transport. In this area, the greatest environmental impact is caused by air emissions, which is very important from the point of view of climate change. Therefore, this article deals with the analysis of the carbon footprint resulting from the fast fashion logistics process. The identification and assessment of fast fashion companies' sustainability efforts in the area of transport-related emissions and sustainable transformation strategies was conducted using a case study method for selected brands (H&M Group; Inditex, Shein). The study uses secondary data available in non-financial reports from 2023. After analyzing the data and content in non-financial reports on transport-related emissions, sev-eral important conclusions emerge. As a dominant practice, companies emphasize their reliance on external frameworks and standards, in particular the Global Reporting Initiative and the Task Force on Climate-related Financial Disclosures. Companies prioritize reducing emissions from significant factors, such as production processes. The data disclosed in the reports (scope 1, 2, 3) are not clearly formulated, but they can be used to calculate the level of CO2 emission reduction/increase. The ar-ticle contains recommendations for companies to improve their reporting by including additional indicators expressing the efficiency of transport-related emissions.

Sugarcane (Saccharum spp.) is a crop of great industrial and alimentary importance, essential for the production of numerous products. Given its significance, genetic improvement programs exist that involve a rigorous study process, from material selection to the development of new varieties, requiring at least seven selection phases. This study modeled the growth curve of the sucrose percentage (SP) in 33 hybrids and six control varieties (MEX 69-290, ITV 92-1424, CP 72-2086, COLMEX 94-8, COLMEX 95-27, RB 85-5113) during the plant and ratoon periods in the experimental fields of the Melchor Ocampo Sugar Mill, Jalisco, Mexico. For clustering the materials, k-means, k-medoids, and Density-based spatial clustering of applications with noise (DBSCAN) algorithms were used, considering four maturity types among the control varieties. The DBSCAN algorithm proved to be the most effective, as the means between groups were not statistically equal. The hybrids identified as candidates for subsequent phases due to their high SP were COSTA JAL, ATEMEX 99-48, ATEMEX 99-1, ATEMEX 99-61, MEX 70-486, MEX 80-1521, ITSAMEX 07-44814, ITSAMEX 06-6395, and ITSAMEX 07-1903. These results are crucial for improving the productivity and sustainability of the crop, with significant implications for the sugar industry.

This theoretical study presents a novel perspective on the potential anti-inflammatory properties of Bromelain, a natural agent extracted from pineapple stems. The investigation explores the binding capabilities of Bromelain to Apoptosis-associated speck-like containing CARD (ASC), a crucial adapter molecule known for its involvement in inflammatory processes and inflammasome formation. For the first time, these findings suggest that Bromelain exhibits a notable affinity for ASC, indicating its promising role as a natural anti-inflammatory agent. This study sheds light on the molecular interactions that may contribute to Bromelain's therapeutic potential in modulating inflammatory responses.

This article introduces a new method for modelling and verifying the execution of timed security protocols (TSP) and their time-dependent security properties. The method, which is both novel and reliable, uses an extension of interpreted systems, accessible semantics in multi-agent systems, and timed interpreted systems (TIS) with dense time semantics to model TSP executions. We enhance the models of TSPs by incorporating delays and varying lifetimes to capture real-life aspects of protocol executions. To illustrate the method, we model a timed version of the Needham-Schroeder Public Key Authentication Protocol. We have also developed a new SMT-based bounded model checking reachability algorithm for the proposed structures and implemented it with the tool. The method comprises a new procedure for modelling TSP executions, a translation of TSP into TIS, and a translation of TIS's reachability problem into the SMT problem. The paper also includes thorough experimental results for nine protocols modelled by TIS and discusses the findings in detail.

The study addressed the following questions: How does continuous lighting (CL) im-pact plant physiology, photosynthetic and stress response? Does the impact of CL de-pend on the source of light and other environmental factors (natural vs artificial)? Do responses to CL differ for native and non-native plant species in the Subarctic and, if differences exist, what physiological reasons might they be associated with? Experi-ments were conducted with three native to Subarctic (Geranium sylvaticum L., Geum rivale L., Potentilla erecta (L.) Raeusch.) and three non-native plant species (Geranium himalayense Klotzsch, Geum coccineum Sibth. & Sm., Potentilla atrosanguinea Loddiges ex D. Don) introduced in Polar-Alpine Botanic Garden (KPABG, 67°38′N). Obtained re-sults have shown that plants lack specific mechanisms of tolerance to CL. Protective responses are non-specific and induced by developing photo-oxidative stress. In cli-mate chambers under constant environmental conditions artificial CL causes leaf inju-ries due to oxidative stress, the main cause of which is circadian asynchrony. In nature plants are not photodamaged during the polar day as endogenous rhythms are main-tained due to daily fluctuations of several environmental factors (light intensity, spec-tral distribution, temperature and air humidity). The obtained data show that among possible non-specific protective mechanisms, plants use flavonoids to neutralize excess ROS generated under CL. In local subarctic plants, their photoprotective role is signif-icantly higher than in non-native introduced plant species.

Roof and roofings built to protect the housing and homeowner from undesirable rainwater, have been seen an important structural element throughout history in the entire of housing. In this research, structural and spatial relationships between building envelope with isolation from water in traditional housing architecture are analyzed. Roof, eaves and rain gutters which are isolation from water items were investigated according to shapes, slope direction, materials, carrier systems and covering materials. The qualification of the roofing, eave and rain gutter elements which are equipment elements related to the comfort of the building envelope and the extent of changes in these elements were examined at the traditional housing level. Exemplary, the traditional housing in the city of Trabzon in Turkey were selected. During the completion process of the working, detailed aims related to structure-health reinforcements were specified with the relevant literature review. The chart form has been developed for compilation of information about the general characteristics of the housing in the research area and the building-health reinforcements within the aim of the research. Exemplary houses were selected by external observation technique and the data obtained as a result of observations, interview and determinations related to general characteristics and building-health reinforcements of these housing were handled into a chart form. By evaluating the data obtained; harmony and contrasts in system level practices, the dimensional properties of the elements at the spatial level, the greatness and accuracy levels preferred in various fittings, the harmony and contrasts in the materials, dimensions and practices of the elements at the system and spatial level, harmony and contrasts of applications of new opportunities at the level of building-health reinforcements in traditional housing, conclusions were drawn to identify special and general situations at the level of building-health reinforcements and to obtain information about the comfort requirements of traditional housing. Nowadays, where the health of the building, which is mostly ignored, is gaining importance day by day, concrete and applicable solution data are presented and interpreted for new designs to be made in this direction.

The use of C-type natriuretic peptide (CNP) in the interaction with the oocyte and in the temporary postponement of spontaneous meiosis resumption has already been well described. However, its action in pre-implantation developmental stage embryos remains to be understood. Thus, our study aimed to detect the presence of the canonical CNP receptor (natriuretic peptide receptor, NPR2) in germinal vesicle (GV), metaphase II (MII), presumptive zygotes (PZ), morula (MO), and blastocyst (BL) stage embryos and, later, to observe possible modulations on the embryos when co-cultured with CNP. In the Experiment I, we detected and quantified the NPR2 on the above-mentioned embryo stages. Following, Experiment II, intended to test different concentrations (100, 200, or 400 nM of CNP) at different times of inclusion in the in vitro culture (IVC; inclusion from the beginning, i.e. day 1, or from day 5). In Experiment III, it was used 400 nM of CNP on day 1 (D1) in the IVC, which did no demonstrate to be embryotoxic, and it showed potentially promising results in blastocyst production rate, when compared to the control. Thus, we analyzed the embryonic development rates of bovine embryos (D7) and hatching kinetics (D7, D8, and D9). Subsequently, morula and blastocyst were collected and evaluated for transcript abundance to competence and quality (apoptosis, oxidative stress, proliferation and differentiation) and lipid metabolism. Differences with probabilities less than P < 0.05, and/or Foldchange (FC) ˃1.5 were considered significant. We demonstrate the presence of NPR2 until the blastocyst development stage when there was a significant decrease in membrane receptors. There was no statistical difference in production rate after co-culture with 400 nM CNP. However, when we evaluated the abundance of morula transcripts, there was an upregulated transcription in ADCY6 (P=0.057), and downregulated transcripts, in BMP15 (P= 0.013), ACAT1 (P= 0.040), CASP3 (P=0.082). In addition, a total of 12 transcriptions in morula presented variation FC ˃1.5. In blastocysts, the treatment with CNP induced upregulation in BID, CASP3, SOX2, HSPA5 transcripts, and downregulation in BDNF, NLRP5, ELOVL1, ELOVL4, IGFBP4, and FDX1 transcripts (FC >1.5). Thus, our study identified and quantified the presence of NPR2 in bovine pre-implantation embryos. Furthermore, 400 nM of CNP in IVC, a concentration not previously described in the literature, modulated some transcripts related to embryonic metabolism and it was not embryotoxic morphologically.

The small business sector in Kazakhstan demonstrates dynamic growth, but its sustainable development in modern conditions requires activation from government agencies, society and entrepreneurs themselves The purpose of the article is to study the development of small entrepreneurship in Kazakhstan and develop a mechanism for sustainable development based on network interaction "business entities - society-state" with the identification of priority areas of development based on a rating approach. The methods of bibliographic analysis of scientific literature, statistical, correlation analysis, survey, comparative analysis, ranking based on data normalization were used. The results revealed the need to formalize indicators of sustainable development of the small business sector in strategic development programs; create conditions, support, explain the importance and prospects of investing in sustainable innovations by small businesses; form a balanced strategy for achieving carbon neutrality based on network interaction "business entities - society-state" with the identification of priority areas of development based on a rating approach to ensure transparency and publicity of decisions made. Conclusions are made about the need to popularize sustainable development among business entities, stimulate investment activity through government participation, legislative regulation of public presentation of non-financial reporting, and assist society in the formation of an ESG culture.

Late-onset Alzheimer’s disease (LOAD) is a dementia category disease that starts after the age of 65. Progressive problems in thinking, behaviour, learning etc. are its characteristics. Due to its progressive nature, early diagnosis is crucial. A complex pathway mechanism with different risk factors is involved in LOAD progression. A comprehensive study is done on factors causing LOAD, biomarkers used for diagnosis in clinical and preclinical stage of the disease, ML (Machine Learning) techniques to identify disease stage. We reviewed research papers on clinical and preclinical diagnosis of LOAD using ML techniques from biomarker data: MRI, PET image, MMSE, Genome / Gene expression, DNA / RNA binding sites with protein, Epigenetic expression /DNA, methylation, Speech and text. We have listed improvement scope after finding the gaps and scope of using Generative AI and SMOTE (Synthetic Minority Oversampling Technique) for data augmentation. At the end, we have elaborated current use of DL (Deep Learning) and CNN (‘Convolution Neural Network’) in Alzheimer’s disease (AD) diagnosis.

Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) are prevalent neurodevelopmental disorders with distinct diagnostic criteria but significant overlap in symptoms and comorbidity. This article explores the relationship between ADHD and ASD, examining their common neurodevelopmental origins, shared features, and distinct trajectories. Both disorders are highly heritable, with genetic studies identifying shared genetic variants and neurobiological abnormalities. Environmental factors, including prenatal and perinatal exposures, also contribute to their etiology. Despite these commonalities, ADHD and ASD exhibit distinct developmental trajectories, cognitive profiles, and long-term outcomes. Understanding the interplay between these disorders is crucial for developing effective diagnostic and treatment strategies. Future research should focus on elucidating the underlying mechanisms and developing targeted interventions for individuals with comorbid ADHD and ASD.

There is a pressing need for tools that can rapidly predict PM2.5 concentrations and assess health impacts under various emission scenarios, aiding in the selection of optimal mitigation strategies. Traditional chemical transport models (CTMs) like CMAQ are accurate but computationally intensive, limiting practical scenario analysis. To address this, we propose a novel method integrating a conditional U-Net surrogate model with health impact assessments, enabling swift estimation of PM2.5 concentrations and related health effects. The U-Net model was trained with 2019 South Korean PM2.5 data, including precursor emissions and boundary conditions. Our model showed high accuracy and significant efficiency, reducing processing times while maintaining reliability. By combining this surrogate model with the EPA’s BenMAP-CE tool, we estimated potential premature deaths under various emission reduction scenarios in South Korea, extending projections to 2050 to account for demographic changes. Additionally, we assessed the required PM2.5 emission reductions needed to counteract the increase in premature deaths due to an aging population. This integrated framework offers an efficient, user-friendly tool that bridges complex air quality modeling with practical policy evaluation, supporting the development of effective strategies to reduce PM2.5-related health risks and estimate economic benefits.

This study is based on the clamor of fish farmers for a cheaper fish feed alternative to current commercial feeds. At present, 70-80% of aquaculture costs come from feed cost, keeping farmers' income below their expectation. This study aimed to find alternative feeds or supplementary feeds that can perform similarly to the existing commercial feeds thereby reducing farmer expense and cutting down their cost of production and increasing their profitability. To do that, various indigenous raw materials were selected based on an earlier study which could result in a better feed alternative. The formulations for the study included four grow-out treatments mainly: control (commercial feed), taro+control (powdered Colocasia esculenta+commercial fish feed), bloodmeal (formulated fish feed based on bloodmeal), banana stem+control (chopped banana stem+commercial fish feed). A total of 12,000 fingerlings initially weighing 16 g (TL=10 cm) individually were assigned randomly to the four treatments (3000 in each cage measuring 6 x 6 m). Week zero was used for acclimation period, and fingerlings were fed with commercial fish feed. Then the first week used the treatment diets which were adjusted based on average body weight and sampled weekly (ABW=23g; TL=11 cm). The result of the study first showed significant differences between treatments on their fourth week in terms of the diet treatments (MS=0.103, df=3, F=4.12, P=0.0076) with the control and the taro+control showing no difference in terms of weight and length (TC vs CF; P=0.4524). But during the fifth week, the bloodmeal treatment showed increased weight and length for fish sampled (MS=0.109, df=3, F=4.10, P=0.0076) and provided similar weight and length as those from the taro+control and the control (TC vs CF; P=0.3721 and BM vs CF; P=0.0587). During the succeeding weeks, there were no significant differences between feed treatments from 6th weeks onwards, whether with weight [MS=0.130, df=3, F=1.14, P=0.333] or total length of the treatments [MS=0.008, df=3, F=0.40, P=0.75]. The FCR ratio showed taro (1.81) as lowest, followed by blood meal (2.09), and control (2.24) and then banana stem (2.84). In terms of weight gain, fish from the bloodmeal treatment gained the highest (236.97 g), followed by control (223.33 g), then taro (217.67 g) and banana stem (196.99 g). As a result, we find that the tested treatments such as bloodmeal formulated feed, taro+commercial feed, and banana stem+commercial feed can serve as an alternative to purely commercial fish feeds. Cost-benefit analysis showed that a better gross profit margin of 42% and cost-benefit ratio of 1.37 was observed in taro+commercial feed diet.

Self-healing, stretchable and moldable hydrogels have a great potential application in tissue engineering and soft robotics. Despite great success in reported hydrogels, it is still a great challenge to construct the moldable hydrogels with an ultrafast self-healing performance. Herein, the dynamic double network (DN) composite hydrogels (PBLH) with ultrafast self-healing, stretchable and moldable were successfully constructed by poly (vinyl alcohol) (PVA), borate, ε-poly-L-lysine (EPL) and hyaluronic acid (HA) based on an efficient one-pot method. Fourier transform infrared spectroscopy, X-Ray diffraction and rheological measurements confirmed the formation of dynamic double networks among PVA, B, EPL and HA through the cross-linking of dynamic borate bonds, electrostatic interaction and hydrogen bonding. Having fabricated the dynamic double network structure, the damage gap of the composite hydrogels can heal within 1 min, presenting an excellent self-healing ability. Simultaneously, the DN hydrogels can be molded to various shapes and the length of the DN hydrogels can be stretched to 15 times than original length. In addition, the DN hydrogels exhibited an excellent antibacterial property against Staphylococcus aureus (S. aureus) and Escherichia coli (E. coli). Our results illustrated that the DN composite hydrogels not only retain the advantages of traditional hydrogels, but also possess ultrafast self-healing, outstanding stretchable and antibacterial properties, presenting a prospective candidate for constructing biomedical materials.

Software-Defined Networking (SDN) has revolutionized network management by providing unprecedented flexibility, control, and efficiency. However, its centralized architecture introduces critical security vulnerabilities. This paper introduces a novel approach to securing SDN environments using IOTA 2.0 smart contracts. The proposed system utilizes the IOTA Tangle, a directed acyclic graph (DAG) structure, to improve scalability and efficiency while eliminating transaction fees and reducing energy consumption. We introduce three smart contracts: Authority, Access Control, and DoS Detector, to ensure trusted and secure network operations, prevent unauthorized access, maintain the integrity of control data, and mitigate denial-of-service attacks. Through comprehensive simulations using Mininet and the ShimmerEVM IOTA Test Network, we demonstrate the efficacy of our approach in enhancing SDN security. Our findings highlight the potential of IOTA 2.0 smart contracts to provide a robust, decentralized solution for securing SDN environments, paving the way for the further integration of blockchain technologies in network management.

Malta produces approximately 15,000 tons of bluefin tuna every year, by-products are estimated to count for 55% of the harvest. Maltese tuna farmers established a company that processes these by-products into fish meal and oil that are sold to the pet food industry. In this study the logistic of tuna farming and management in Malta was analysed and the environmental impact of the activity was estimated. The biomass quality and the preservation state of tuna head and liver was assessed. The head had the highest ash content (1.68±0.02%) while the liver had the highest protein content (16.18±0.02%) and the highest crude fat, (34.87±0.76%). The highest concentration of oil was found in the head’s skin (50.07±0.84%). The predominant saturated fatty acids (SFAs) were c14:0, c16:0 and c18:0. Monounsaturated FAs (MUFAs) were the major fatty acids present in all samples, with the highest values in the tuna head. The oxidation levels found in the by-products upon arrival at the processing plant doesn’t compromise their quality. No histamine formation was predicted. Some oxidation was observed in the oil after extraction. The Life Cycle Assessment estimated that the environmental score of the activity is 105pts per ton of fishmeal and 25kg of oil produced (2.82 tCO2 eq). It is concluded that the processing of tuna by-products in Malta is a sustainable alternative to traditional disposal methods and their quality is high enough to be used as a source of proteins and lipids in farmed-animals feed.

Despite various interventions in road safety work, fatal and severe road traffic accidents (RTAs) remain a significant challenge leading to human suffering and economic costs. Understanding the multicausal nature of RTAs, where multiple conditions and factors interact, is crucial for developing effective prevention measures in road safety work. This study investigates the multivariate statistical analysis of co-occurring conditions in RTAs, focusing on single-vehicle accidents with single occupancy and personal injury on Austrian roads outside built-up areas from 2012 to 2019. The aim is to detect recurring combinations of accident-related variables, referred to as blackpatterns (BPs), using the Austrian RTA database. The study proposes Fisher’s exact test to estimate the relationship between an accident-related variable and fatal and severe RTAs (severe casualties). In terms of pattern recognition, the study develops the maximum combination value (MCV) of accident-related variables, a procedure to search through all possible combinations of variables to find the one that has the highest frequency. The accident investigation proceeds with the application of pattern recognition methods, including binomial logistic regression and a newly developed method, the PATTERMAX-method, created to accurately detect and analyse variable-specific BPs in RTA data. Findings indicate significant BPs contributing to severe accidents. The combination of binomial logistic regression and the PATTERMAX-method appears to be a promising approach to investigate severe accidents, providing both insights into detailed variable combinations and their impact on accident severity.

The Asian hornet, Vespa velutina, is an invasive species that has not only expanded its range in Asia but also invaded European countries, incurring significant costs on the local honey and bee industry. This phylogeographic study aims to trace the evolutionary trajectory of V. velutina and its close relatives, aiming to identify features that characterize an invasive species. The last successful invasion of Vespa velutina into France occurred in 2002.40, and into South Korea in 2002.77, estimated by fitting a logistic equation to the number of observations over time. The instantaneous rate of increase is 1.3667 for V. velutina in France and 0.2812 in South Korea, consistent with the interpretation of little competition in France and strong competition from local hornet species in South Korea. The invasive potential of two sister lineages can be compared by their distribution area when proper statistical adjustments are made to account for differences in sample size. V. velutina has a greater invasive potential than its sister lineage. The ancestor of V. velutina split into two lineages, one found in Indonesia/Malaysia and the other colonizing the Asian continent. The second lineage split into a sedentary clade inhabiting Pakistan and India, and an invasive lineage colonizing much of Southeast Asia. This latter lineage gave rise to subspecies V. v. nigrithorax that invaded France, South Korea, and Japan. My software PGT, which generates geophylogenies and computes geographic areas for individual taxa, is useful for understanding biogeography in general and invasive species in particular. I discussed the conceptual formulation of an index of invasiveness for comparison between sister lineages.

Extracellular vesicles (EVs) are natural carriers of biomolecules that play a crucial role in cell-to-cell communication and tissue homeostasis under normal and pathological conditions, including inflammatory diseases and cancer. Since the discovery of the pro-regenerative and immune-modulating properties of EVs, EV-based therapeutics have entered clinical trials for conditions such as myocardial infarction and autoimmune diseases, among others. Due to their unique advantages—such as superior bioavailability, substantial packaging capacity, and the ability to traverse biological barriers—EVs are regarded as a promising platform for targeted drug delivery. However, achieving sufficient accumulation of therapeutic agents at the target site necessitates a larger quantity of EVs per dose compared to using EVs as standalone drugs. This challenge can be addressed by administering larger doses of EVs, increasing the drug dosage per administration, or enhancing the selective accumulation of EVs at target cells. In this review, we will discuss methods to improve the isolation and purification of EVs, approaches to enhance cargo packaging—including proteins, RNAs, and small-molecule drugs—and technologies for displaying targeting ligands on the surface of EVs to facilitate improved targeting. Ultimately, this guide can be applied to the development of novel classes of EV-based therapeutics and to overcoming existing technological challenges.

FER zeolites has a unique framework structure and acid distribution, and is widely studied as a catalyst for reactions such as n-butene skeletal isomerization and dimethyl ether carbonylation. The BAS located in the 10-MR of FER zeolites serves as the active site for the isomerization reaction of n-butene skeletal to produce isobutene. In contrast, the acid site found in the 8-MR is prone to side reactions, such as polymerization and cracking, which can adversely affect the selectivity of isobutene. This study prepared five types of FER zeolites using different method, inducing Na-form or H-form crystal seeds without organic structure directing agents (OSDAS), using pyridine alone as a template, and combining the seeds with pyridine. The differences in the structure and acid distribution of the five zeolites were investigated, as well as their catalytic performance for the the skeletal isomerization of n-Butene. Experiments and characterization results showed that under hydrothermal synthesis conditions, the FER-PY+SH zeolites synthesized by using both H-form zeolites seeds and pyridine exhibited the highest aluminum concentrations at T1 and T3 positions, along with the greatest BAS of 10-MR. This unique composition contributed to the highest selectivity of isobutene. The FER-PY+SH catalyst was continuously used for 720 hours at 350 ℃, 0.1 MPa, and n-butene mass space velocity of 2.0 h^-1 for three recycles on 2160 h. During this period, the conversion of n-butene over 39%, while the selectivity of isobutene exceeded 95%.The catalyst exhibited excellent stability and activity.

Background/Objectives: Cardiovascular diseases are one of the leading causes of morbidity and mortality worldwide. Health-related quality of life is crucial to assess the impact of cardiovascular diseases and to guide therapeutic strategies. The Short Form 36 Health Survey and the RAND 36-Item Health Survey questionnaires are common tools for measuring health-related quality of life in patients with cardiovascular disease, but their reliability may vary according to the population studied. The aim of this study is to compare the reliability of the SF-36 and the RAND-36 in a population with cardiac pathology, addressing the question of which of these instruments offers a more consistent and useful measurement in this specific group. Methods: Cross-sectional observational study carried out at the University Hospital of Burgos (Spain). 413 patients with cardiovascular pathology referred to the Cardiac Rehabilitation Unit were included. Patients with incomplete data or who did not participate in the program were excluded. Internal consistency (Cronbach’s alpha), item-total correlation and reliability and a half-half analysis were performed. Results: Both questionnaires showed similar and adequate reliability for patients with cardiovascular pathology. Internal consistency, as measured by Cronbach’s alpha, was above 0.80 for most dimensions, supporting its robustness. Significant inter-item and inter-dimension correlations were found in both scales, except in some specific cases in the dimension ‘Physical Functioning’. The half-half analysis confirmed the good reliability of both scales. Conclusions: Both the SF-36 and the RAND-36 are highly reliable tools for assessing health-related quality of life in patients with cardiovascular disease. The results may have significant implications for clinical practice, helping in the selection of health-related quality of life monitoring instruments and in the evaluation of the efficacy of therapeutic interventions.

A Geometrical re-configurable structure based on RF Micro-electro-mechanical switches (RF-MEMS) is proposed in this work. The structure is composed of an array of gold metallic patches interconnected together utilizing RF-MEMS switches in order to change its geometry and, consequently, the scattering parameters. In particular, the reconfigurability is achieved by activating multiple RF-MEMS switches, which enables the change of electrical length and, consequently, the resonance frequency of the structure. As a proof of concept, an experimental antenna prototype composed of an array of 7 × 7 elements interconnected by a set of RF-MEMS switches has been designed, fabricated numerically and experimentally assessed. The structure can be set as an antenna or other basic radio frequency components. The obtained experimental results are in good agreement with the simulations, with an error of less than 5% for the considered radiating structures. The quite promising results demonstrated the potentialities and flexibility of the proposed structure.

This study examines the combined influence of both meteorological and non-climatic factors on rice production in Bangladesh between 1990 and 2020, using the Autoregressive Distributed Lag (ARDL) model. The key variables consist of temperature, precipitation, urbanisation, fertiliser management (specifically potassium levels), and the area of permanent crops. The findings highlight the substantial detrimental impact of temperature on rice output over a prolonged period, whereas precipitation and urbanisation have a favourable affect on rice productivity. However, the utilisation of potassium fertiliser has a detrimental effect on crop productivity. Furthermore, it has been demonstrated that the development of permanent crop fields has a beneficial effect on rice output. These findings provide important information for policymakers and agricultural stakeholders, highlighting the need for adaptive strategies to improve the ability of rice production to withstand the impacts of climate change and urbanisation. The significance of these discoveries applies to rice-producing regions worldwide, offering a strategic blueprint for sustainable cultivation of rice and ensuring food security.

Equine herpesvirus type 1 (EHV-1) causes rhinopneumonitis, abortion and neurological outbreaks (equine herpesvirus myeloencephalopathy, EHM) in horses. EHV-1 also causes lethal encephalitis in laboratory small animals such as mice and hamsters experimentally. EHV-1 ORF76 is a homologue of HSV-1 US9, which is a herpesvirus kinase. Starting with an EHV-1 bacterial artificial chromosome clone of neuropathogenic strain Ab4p (pAb4p BAC), we constructed an ORF76 deletion mutant (Ab4p∆ORF76) by replacing ORF76 with the rpsLneo gene. Deletion of ORF76 had no influence on replication, cell-to-cell spread in cultured cells or replication in primary neuronal cells. In western blots of EHV-1-infected cell lysates, an EHV-1 Us9-specific polyclonal antibody detected multiple bands ranging from 35 to 42-kDa. In a CBA/N1 mouse infection model following intranasal inoculation, the parent and Ab4p∆ORF76 revertant caused the same histopathology in the brain and olfactory bulbs. The parent, Ab4p∆ORF76 and revertant mutant replicated similarly in the olfactory mucosa, although Ab4p∆ORF76 was not transported to the olfactory bulbs and was unable to infect the CNS. These results indicated that the ORF76 (US9) plays an essential role in the anterograde spread EHV-1.

Artificial intelligence (A.I.) is the key to process big amounts of data to useful information for operators. In the present study the suitability of a 24/7 A.I. sound based coughing monitoring system for early detection of respiratory distress caused by porcine respiratory disease complex (PRDC) associated pathogens was assessed in the nursery of a conventional pig farm. Screening for PRDC associated pathogens was conducted by PCR examination of oral fluids (OFs) and bioaerosol samples (AS). A significant correlation between A.I. and human gained health data was observed in both batches. An increase in coughing episodes, either measured by A.I. or human, was significantly correlated with decreasing Ct-values of swIAV. The Odds to detect nucleic acids of PRRSV or Actinobacillus (A.) pleuropneumonia was significantly higher for OFs compared to AS. Moreover, PCR examinations of OFs revealed significantly lower Ct-values for swIAV and A. pleuropneumonia compared to AS. The quantity of swIAV RNA in OFs and AS was significantly associated with the A.I. calculated respiratory health score and thus, with clinical disease. Due to its reliable data A.I. based health monitoring is beneficial for early recognition of respiratory distress and thus can assist farmer’s daily work.

This study evaluated the impact of rough, smooth, and very smooth Titanium (Ti) and zirconia (Zr) surfaces on the neutrophil expression of elastase (NE), matrix metalloproteinase (MMP)-8, MMP-9 and extracellular traps (NETs). Ti and Zr disks with a diameter of 10mm and a thickness of 1.5mm were processed using diamond-impregnated polishing burs and paste to generate rough (R; Ra= > 3µm), smooth (S; Ra= ≥1 to 1.5µm) and very smooth (VS; Ra= <0.1µm) surfaces. Peripheral neutrophils from Wistar rats were cultured on these surfaces and the culture supernatants subsequently analyzed for the presence of NE, MMP-8, and MMP-9 by ELISA, while NETs formation was demonstrated immunohistochemically by staining neutrophils with CD16b and DNA with DAPI. Overall, the expression of NE and MMP-8 were significantly higher from neutrophils cultured on both on Ti and Zr rough surfaces compared to the very smooth surface (R>S>VS) after 2h and 4h of culture. The expression of MMP-9 also increased with culture time however no significant surface effects on expression were observed. Similarly, rough Ti and Zr surfaces (R & S) also showed significantly larger NETs formation compared to the very smooth surface (VS) after 4h and 8h culture. Our findings suggest that increasing surface roughness on Ti and Zr triggers higher secretion of NE, MMP-8 and NETs formation.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal malignancies, characterized by its aggressive progression and dismal prognosis. Advances in epigenetic profiling, specifically DNA methylation analysis, have significantly deepened our understanding of PDAC pathogenesis. This review synthesizes findings from recent genome-wide DNA methylation studies, notably those by Espinet et al. and Wang et al., which have delineated a complex DNA methylation landscape differentiating between normal and cancerous pancreatic tissues, as well as across various stages and molecular subtypes of PDAC. These studies identified specific differentially methylated regions (DMRs) that not only enhance our grasp of the epigenetic drivers of PDAC but also offer potential biomarkers for early diagnosis and prognosis, enabling the customization of therapeutic approaches. The review further explores how DNA methylation profiling could facilitate the development of subtype-tailored therapies, potentially improving treatment outcomes based on precise molecular characterizations. Overall, leveraging DNA methylation alterations as functional biomarkers holds promise for advancing our understanding of disease progression and refining PDAC management strategies, which could lead to improved patient outcomes and a deeper comprehension of the disease’s underlying biological mechanisms.

The present work offers a contemporary synthesis of the application of the Oxford Nanopore^® MinION^™ within the context of cultural heritage biodeterioration investigations, while also providing a comprehensive discussion of possible future perspectives for their utilization in this research field. Owing to the distinctive characteristics of this device, the past few years have witnessed the consistent increase on the application of this system in a variety of cultural heritage materials. In fact, the technique has been useful to understand microbial biodeteriogens diversity and some of their metabolic and biodeteriogenic features. Considering the immense potential for application of this system, this manuscript explores and discusses further possibilities of the technique, focusing on helping understand critical questions on the cultural heritage biodeterioration area. Its application in various differential contexts, has opened doors for prospective applications on other interesting sub-areas of research meriting future investigations, including: biodeteriogens genome and transcriptome analysis, metatranscriptomics, biodeteriorative metabolism studies, inter and intra kingdom interactions analysis, resistome profiling, object history and context studies, in situ applications, bioprospecting and biotechnology.

Nanoporous graphene structures have high accessible surface area for lithium-ion adsorption or intercalation. Here, we present theoretical investigations on lithium-ion adsorption mechanism in a graphene nanopore. Ab initio electronic structure calculations are performed based on density functional theory. We also study different lithium-ion distributions in graphene nanopores to determination multilayer lithium-nanoporous graphene structures for lithium-ion batteries. We believe, these multilayer nanoporous graphene nanostructures with more pores opening can offer improved capacity and better rate performance for energy storage applications.

When dealing with complex models in real situations, many optimization problems require using more than one objective function to represent the relevant characteristics of the system under consideration adequately. This is why multiobjective optimization algorithms that can deal with several objective functions are required in order to obtain reasonable results in an adequate processing time. This paper presents the multiobjective version of a recent metaheuristic algorithm that optimizes a single objective function, known as the Majority-minority Cellular Automata Algorithm (MmCAA), inspired by cellular automata operation. The algorithm presented here will be known as the Multiobjective Majority-minority Cellular Automata Algorithm (MOMmCAA). The MOMmCAA adds repository management and multiobjective search space density control to complement the performance of the MmCAA and make it capable of optimizing multiobjective problems. To evaluate the performance of the MOMmCAA, benchmark test sets are taken (DTLZ, quadratic, and CEC-2020), along with real-world engineering design problems, compared against other multiobjective algorithms recognized for their performance (MOLAPO, GS, MOPSO, NSGA-II, and MNMA). The results obtained in this work show that MOMmCA produces comparable performance with the other metaheuristic methods, which shows it as a competitive algorithm to be used for multiobjective problems. MOMmCAA was implemented in MATLAB, and its source code can be consulted in GitHub. https://github.com/juanseck/MOMmCAA

(1) Food banks have played an important role in reducing food losses and waste and improving the food insecurity situation of vulnerable people. This study aims to conduct a systematic review of food bank evaluation studies and bring new perspectives for future research and decision-making. (2) 58 articles were selected and analyzed from a survey on the Web of Science and Science Direct Platforms. Bibliometric analyses and analyses of the evaluation methodologies used were presented. (3) The bibliometric results indicate an internationalization of the studies since 2013, with a focus on developed countries, and a direct relationship between the location of the research institutes and the location of the organizations studied. Analysis of evaluation methodologies showed that the main aspects evaluated are related to long-term impact, short-term impact and results, indicating less interest in the internal processes and activities of organizations. This result raises important questions for researchers and decision-makers: to what extent evaluation studies reflect the reality and context of a given country or region and to what extent evaluation studies reflect the management processes of food banks.

This research explores the feasibility of a data-driven optimization algorithm for placing sparse arrays of artificial hair-cell airflow velocity sensors to enable agile and robust flight-by-feel control of unmanned aircraft. The Sparse Sensor Placement Optimization for Prediction (SSPOP) algorithm exploits the information-rich features of large flow datasets to find a near-optimal set of locations for flow sensors on a wing. The flow information from these sensors can be used to predict flight state parameters such as the angle of attack, mimicking the fly-by-feel control systems observed in nature. We evaluate the effectiveness of this approach for a blunt-edged 45∘ swept delta wing. Exploiting the information in the complex airflow patterns over this wing, the SSPOP algorithm selects a sensor location design point (DP) which reliably ranks within the top 1% of all possible DPs by root mean square error in angle of attack prediction. This performance was consistent across models of various artificial hair lengths, and one model with variable hair lengths. This bioinspired dimension-reducing method for sensor placement optimization exhibits reliability and flexibility benefits when compared with a conventional greedy search algorithm and gradient-based optimization using auto-differentiation. The successful application of SSPOP in complex 3D flows paves the way for experimental evaluation of data-driven sparse sensor placement optimization for artificial hair-cell airflow sensors and is a major step toward biomimetic flight-by-feel.

It has been suggested that parasitic infections, common in Latin American populations, may amplify the inflammatory response of the airways. There are several reports in atopic and asthmatic patients, but few reports of parasitic infection in COPD patients. The study aimed to determine the prevalence of parasitic infections in COPD patients as compared to atopic and asthmatic patients attending the outpatient clinics of the Institute of Immunology and the pneumonology service of the University hospital. A case-control study was conducted: 100 patients with bronchial asthma, 100 patients with COPD, 100 individuals with atopy without respiratory symptoms, and 100 healthy individuals. Serum specific IgG antibody against the parasites Ascaris lumbricoides (Al), Strongyloides stercolaris (Ss) and Toxocara canis (Tc) were measured: by ELISA. IgE levels were used as an indirect indicator of atopy. Positive IgG for Al was observed in all groups, predominantly in atopic cohort, Ss positiveness was recorded only in 4 COPD patients and Tc positiveness was observed in all groups except in controls. There are significant correlations between the values of Al and IgE in controls, atopic and asthmatic patients not with COPD. No correlation was found for Tc. IgE levels and FEV1 correlate only in atopic and asthmatic patients. Parasitic infections are common in atopic patients and in moderate and severe asthmatic and COPD patients. Anti-inflammatory treatment may be responsible for the increase frequency of infection.

Green leaf volatiles (GLV) are important signaling compounds that help to regulate plant defenses against pests and pathogens. Made through the hydroperoxide lyase (HPL) pathway, they are rapidly produced upon damage and can signal this to other parts of the same plant or even plants nearby, where they can induce rapid defense responses directly or prime them against the impending danger. In this primed state plants can respond faster and/or stronger should pests or pathogens attack. However, while all proteins and genes involved in the biosynthesis of GLV have been identified, little is still known about how the first two steps in the pathway, e.g., oxygenation by a lipoxygenase (LOX) and subsequent cleavage by HPL are facilitated within the damaged tissue, resulting in the production of Z-3-hexenal (Z3al) as the first committed product of the pathway. Here, we provide evidence that several factors might be involved in the production of Z3al including pH, Ca2+, and an environment that is highly hydrophobic. We present a model in which the extraordinary circumstances that are present at the site of Z3al production are considered and shine new light on potential regulatory mechanisms.

Glioblastoma (GBM) is a prevalent type of malignancy within the central nervous system (CNS), associated with a poor prognosis. The standard treatment for GBM includes surgical resection of the tumor, followed by radiotherapy and chemotherapy; yet despite these interventions, overall treatment outcomes remain suboptimal. The blood-brain barrier (BBB), which plays a crucial role in maintaining the stability of brain tissue under normal physiological conditions of the CNS,also poses a significant obstacle to the effective delivery of therapeutic agents to GBM. Recent preclinical studies have demonstrated that nanomedicine delivery systems (NDDS) offer promising results, demonstrating both effective GBM targeting and safety, thereby presenting a potential solution for targeted drug delivery. This review explores the various strategies employed in preclinical studies to overcome the BBB for drug delivery. Subsequently, the results of clinical translation of NDDS has been summarized, highlighting the progress made. Finally, we discuss potential strategies for advancing NDDS development and accelerating their translational research through well-designed clinical trials in GBM therapy.

Compared to agonists, radiolabeled somatostatin receptor (SSTR) antagonists have advantages in neuroendocrine tumors (NETs). Articles on radiolabeled somatostatin receptor agonists or antagonists in NETs were included by searching the Web of Science (WoS) database. The included literature has been subjected to data collection and bibliometric study. A detailed analysis of the included clinical articles was also performed. 123 publications were identified for biblio-metric analysis. The number of publications on radiolabeled somatostatin receptor agonists and antagonists in the theranostics of NETs has increased significantly after 2014, with Germany publishing the most papers (39), followed by the United States (33) and Switzerland (28). The Swiss paper was cited the most, with 1783 quotations, followed by the USA (1338) and Germany (1330). The most common keywords were NETs (89), Peptide receptor-mediated radionuclide therapy (PRRT) (62), and antagonists (53). Antagonists had lower uptake in normal tissue and higher uptake in tumor tissue compared to agonists, with a high tumor-to-liver ratio. Research on radiolabeled somatostatin receptor agonists and antagonists in theranostics of NETs is increasing, with significant contributions from Europe and the United States. Radiolabeled somatostatin receptor antagonists are likely to be a hot topic in NETs theranostics.

The role of trees in watershed hydrology is governed by many environmental factors along with their inherent characteristics and not surprisingly has generated into diverse debates in the literature. Herein, this state-of-the-art review provides an opportunity to propose a conceptual model for understanding the role of trees in watershed hydrology and examine the conditions under which they can be an element that increases or decreases water supply in a watershed hydrology. To achieve this goal, this review addressed the interaction of forest cover with climatic conditions, soil types, infiltration, siltation and erosion, water availability, and the diversity of their ecological features. The novelty of the proposed conceptual model highlights that tree species and densities, climate, precipitation, type of aquifer, and topography are important factors affecting the relationships between trees and water availability. This suggests that forests can be used as a nature-based solution for conserving and managing natural resources, including water, soil and air. To sum up, forests can reduce people’s imprint, thanks to their role in improving water and air quality, conserving soil, and other ecosystem services. The outcomes of this study should be valuable for decision-makers when investing in reforestation in a watershed hydrology.

Since the 2005 discovery of the first enzyme capable of depolymerizing polyethylene terephthalate (PET), an aromatic polyester once thought to be non-biodegradable, extensive research has been undertaken to identify and engineer new biocatalysts for plastic degradation. This effort was directed towards developing efficient enzymatic recycling technologies that could overcome the limitations of mechanical and chemical methods. These enzymes are versatile molecules obtained from microorganisms living in various environments, including soil, compost, surface seawater, and extreme habitats such as hot springs, hydrothermal vents, deep-sea regions, and Antarctic seawater. Among various plastics, PET and polylactic acid (PLA) have been the primary focus of enzymatic depolymerization research, greatly enhancing our knowledge of enzymes that degrade these specific polymers. They often display unique catalytic properties that reflect their particular ecological niches. This review explores recent advancements in marine-derived enzymes that can depolymerize synthetic plastic polymers, emphasizing their structural and functional features that influence the efficiency of these catalysts in biorecycling processes. Current status and future perspectives of enzymatic plastic depolymerization are also discussed, with a focus on the underexplored marine enzymatic resources.

For a left module RM over non-commutative ring R, the notion for the class of nilpotent elements (nilR(M)) was first introduced and studied by SSevviiri and Groenewald . Moreover, Armendariz and semicommutative modules are generalizations of reduced modules and nilR(M)=0 in the case of reduced modules. Thus, the nilpotent class plays a vital role in these modules. Motivated by this, we present the concept of nil-Armendariz modules as a generalization of reduced modules and a refinement of Armendariz modules, focusing on the class of nilpotent elements. Further, we demonstrate that the quotient module M/N is nil-Armendariz if and only if N is within the nilpotent class of RM. Additionally, we establish that the matrix module Mn(M) is nil-Armendariz over Mn(R) and explore conditions under which nilpotent classes form submodules. Finally, we prove that nil-Armendariz modules remain closed under localization.

Objective We aim to assess the quality of life for women with genitourinary fistulas before and after surgery, utilizing the WHOQOL-BREF questionnaire to contrast the preoperative and postoperative results. Materials and Methods: This quasi-experimental study was conducted at the Department of Urology, SIUT, Karachi, Pakistan, from January to December 2023. We used the WHOQOL-BREF questionnaire to assess the quality of life. Participants completed the questionnaire both before the surgical intervention and three months after successful fistula repair. The collected data were entered and analysed using IBM SPSS v26, with a significance level set at p≤ 0.05. Results The participants had a mean age of 35.50 years, with a standard deviation of 8.87 years. Before undergoing genitourinary fistula repair, the average WHOQOL-BREF score was 12.17 with a standard deviation of 5.77. Following the repair, the mean score showed a significant improvement, rising to 96.67 with a standard deviation of 11.86. This marked improvement was statistically significant, with a p-value of 0.0001. Conclusion This study concludes that genitourinary fistula repair at our tertiary care hospital significantly and positively impacts patients' quality of life. The findings emphasize the critical role of timely and appropriate surgical intervention in improving overall well-being. Continued comprehensive care and support are vital for these patients' holistic recovery and long-term health.

This study investigates the effect of altitude on the fatty acid composition of grass, yak milk, and yak ghee on the Qinghai-Tibet Plateau, aiming to understand how environmental factors influence the nutritional quality of these products. Samples were collected from four different altitudes and analyzed for fatty acid profiles using gas chromatography. The findings reveal significant differences in fatty acid profiles, with notably higher concentrations of lauric acid (C12:0) and myristic acid (C14:0) at altitude A2 compared to others (p＜ 0.001). Furthermore, the fatty acid composition in yak milk and ghee is influenced by the grass consumed and the metabolism of rumen microorganisms. The results indicate that yaks adapt their lipid biosynthesis to high-altitude conditions, as evidenced by a significant increase in stearic acid (C18:0) levels at higher altitudes, which subsequently affects the nutritional value of their milk and ghee. These insights are crucial for improving yak breeding and dairy production practices, ultimately enhancing food security and nutritional health for local communities residing in high-altitude areas. The study underscores the necessity for further research on optimizing these natural resources for better health outcomes.

A one-dimensional numerical overland flow model based on the cascade plane theory was de-veloped to estimate rainfall-induced runoff and soil erosion on converging and diverging plane surfaces. The model includes three components: (i) soil infiltration using Horton’s infiltration equation, (ii) overland flow using the kinematic wave approximation of the one-dimensional Saint-Venant shallow water equations for a cascade of planes, and (iii) soil erosion based on the sediment transport continuity equation. The model’s performance was evaluated by comparing numerical results with laboratory data from experiments using a rainfall simulator and a soil flume. Four independent experiments were conducted on converging and diverging surfaces under var-ying slope and rainfall conditions. Overall, the numerically simulated hydrographs and sediment graphs closely matched the laboratory results, showing the efficiency of the model for the tested controlled laboratory conditions. The model was then used to numerically explore the impact of different plane soil surface geometries on runoff and soil loss. Seven geometries were studied: one rectangular, three diverging, and three converging. Constant soil surface area, rainfall intensity, and slope gradient were maintained in all simulations. Results showed that increasing convergence angles led to higher peak and total soil loss, while decreasing divergence angles reduced them.