Magnetic Fe3O4 nanoparticles (MNPs) are becoming more important every day in drug targeting. We prepared here MNPs in a simple one-step reaction by following the solvothermal method assisted by azide and alkyne functionalized polyethylene glycol (PEG400) polymers, as well as by PEG6000 and the polyol -cyclodextrin (CD). The composition, morphology, and structure of the nanospheres were characterized using Transmission Electron Microscopy (TEM), Nuclear Magnetic Resonance (NMR), X-Ray Diffraction Diffractometry (XRD), Atomic Force Microscopy (AFM), Fourier-Transform Infrared Spectroscopy (FT-IR), Matrix-Assisted Laser Desorption/Ionization (MALDI) and Vibrating Sample Magnetometry (VSM). The obtained nanoparticles (@Fe3O4-PEGs and @Fe3O4-CD) showed diameters between 90-250 nm, depending on the polymer used and the Fe3O4·6H2O precursor concentration, typically, 0.13 M, 200 °C, and 24 h of reaction. MNPs exhibited superparamagnetic properties with high saturation of magnetization at room temperature, reaching values of 59.9 emu/g (@Fe3O4-PEG6000), and no ferromagnetism. Likewise, they showed temperature elevation after applying an alternating magnetic field (AMF) in all cases, obtaining Specific Absorption Rate (SAR) values of up to 51.87 ± 2.23 W/g in the case of @Fe3O4-PEG6000. Both PEGs and the βCD played a crucial role as electrostatic stabilizers in the formation of Fe3O4 nanospheres, providing a polymeric/polyol coating around the magnetic cores. Additionally, the formed systems are susceptible for click chemistry, as was demonstrated in the case of the cannabidiol-propargyl derivative (CBD-Pro), which was synthesized and covalently attached to the azide functionalized surface of the system @Fe3O4-PEG400-N3. Prepared MNPs are highly dispersible in water, remaining in suspension for over 3 days, and non-toxic in the T84 human colon cancer cell line, indicating that they are ideal candidates for biomedical applications.

Technological developments within the maritime sector are resulting in rapid progress that will see the commercial use of autonomous vessels, known as Maritime Autonomous Surface Ships (MASS). Such ships are equipped with a range of advanced technologies, such as IoT devices, artificial intelligence (AI) systems, machine learning (ML) based algorithms and augmented reality (AR) tools. Through such technologies, the autonomous vessels can be remotely controlled from Shore Control Centres (SCC) by using real-time data to optimise their operations, enhance safety and reduce the possibility of human error. Apart from the regulatory aspects, which are under definition by the International Maritime Organisation (IMO), cybersecurity aspects must be considered and properly addressed to prevent such complex systems from being tampered with. In this paper, we propose an approach to secure communication channels between the SCCs and the vessels using SECOM standard and the underlying digital infrastructure in charge of data collection, storage and processing by relying on a set of machine learning (ML) algorithms for anomaly detection. The proposed approach is validated against a real implementation of the SCC deployed at Livorno seaport premises. Finally, the experimental results and the performance evaluation are provided to assess its effectiveness accordingly.

Hybrid Power Switches (HPS) combine the advantages of SiC unipolar and Si bipolar devices and therefore can bridge the gap between these technologies. In this paper, the performance of a hybrid power switch configuration based on the latest SiC MOSFET and Si IGBT technologies is presented. The device is evaluated through experimental measurements of its characteristics under various conditions. The results show the HPS can achieve switching losses as low as a SiC MOSFET while offering the high current capability of the IGBT without significant increase in costs.

We present a case of a 47-year-old male who died unexpectedly from acute pulmonary hemorrhage 555 days after completing the BNT162b2 (Pfizer) COVID-19 vaccination primary series. Before death, he exhibited symptoms of a mild respiratory infection. Despite a healthy medical history and no medication use, the patient’s condition rapidly deteriorated and he experienced severe respiratory distress, followed by cardiopulmonary arrest with evidence of profuse pulmonary bleeding. Autopsy findings revealed massive lung congestion without embolism, normal heart size, moderate coronary atherosclerosis without myocardial infarction, and no evidence of other hemorrhagic events. The patient tested negative for COVID-19 and other respiratory pathogens at autopsy. Despite these findings, the medical examiner determined the cause of death was attributed to atherosclerotic and hypertensive cardiovascular disease, without considering the recent pulmonary hemorrhage and unremarkable medical history. Investigation into the vaccine batch indicated a higher-than-average number of serious adverse events, including fatalities. The patient's BNT162b2 batch was among the top 2.8% for reported deaths. Moreover, the autopsy failed to investigate potential contributions from the vaccine, such as the presence of the Spike protein or related antibodies. The evidence suggests that the pulmonary hemorrhage, exacerbated by a viral infection, was the immediate cause of death, with the COVID-19 vaccine potentially playing a role in the development of cardiopulmonary pathology and hemorrhage. We propose autopsy protocols for COVID-19 vaccine recipients to better investigate vaccine-related pathologies among those with one or more prior injections.

Over the coming decades, global freshwater withdrawals are expected to grow, especially in low and middle-income countries. Unless there are significant improvements in the efficiency of water use by economies, freshwater stress, crises and scarcity will worsen. This paper explores further the economic relationship between water use efficiency and scarcity. Because growing scarcity of freshwater in many regions and countries is not adequately reflected in markets, there is often insufficient incentives for investment and innovation to improve the efficiency of water use. To explore further changes in water use efficiency across countries, we conduct a panel analysis of water productivity changes for 130 countries over 1995 to 2020. Countries with lower initial levels of water use efficiency tended to have higher water productivity growth, whereas more agriculturally dependent economies displayed lower improvements in water use efficiency. Better institutional quality and capacity for innovation may also increase water use efficiency. We discuss the implications of these results for improving water use productivity in economies, and in particular, the opportunities and challenges for improving water markets and trades to alleviate water scarcity. We conclude by identifying further areas of research.

Conversational artificial intelligence (AI) has shown strong capabilities in providing low-cost and timely interventions for a wide range of people and increasing well-being. Therefore, this study examined ChatGPT’s efficacy in conducting psychological counseling and its potential for providing accessible psychological interventions, especially in school settings. This study assessed the strengths and limitations of AI to inform future research. Data were generated from ChatGPT’s responses to 80 counseling questions that college students asked during a school counseling setting. All the responses generated during these simulated counseling sessions were then analyzed using three primary metrics—warmth, empathy, and acceptance—following APA guidelines. The analysis adopted several natural language processing methodologies for emotion detection and empathy measurement to quantify ChatGPT’s high efficacy in presenting the appropriate emotions and reactions for counseling. Some responses demonstrated randomness, which is crucial for consideration regarding the use of ChatGPT or relevant technology in psychological counseling. The Discussion section also highlights future directions in the application of conversational AI to enhance students’ mental health.

The increased life expectancy of PLHIV (People Living with HIV) and the successful highly com-bined antiretroviral therapy (cART) poses new clinical challenges regarding aging and its co-morbid condition. It is commonly believed that HIV infection "accelerates" aging. Human immunodeficiency virus type 1 (HIV-1) infection is characterised by inflammation and immune activation that persists despite cART and that may contribute to the development of co-morbid conditions. Toxicity associated with cART contributes to persistent immune dysregulation. Therefore, we aimed to compare current cART regimens in the light of premature aging to evaluate residual immune activation and inflammation in virologically suppressed patients. We studied a panel of biomarkers (IFN-γ, IL-1β, IL-12p70, IL-2, IL-4, IL-5, IL-6, IL-13, IL-18, GM-CSF, TNF-α, C-reactive protein, D-dimer, soluble CD14), which could provide a non-invasive and af-fordable approach to monitor HIV-related chronic inflammation. The results of the current study do not provide hard evidence favoring a particular cART regimen, although they show less fa-vorable regimen profile containing protease inhibitor. Our data suggests incomplete reduction of inflammation and immune activation in terms of the effective cART. It is likely that the inter-est in various biomarkers related to immune activation and inflammation as predictors of clini-cal outcomes among PLHIV will increase in the future.

Sign language recognition technology can help people with hearing impairments to communicate with those who are hearing impaired. At present, with the rapid development of society, deep learning technology also provided certain technical support for sign language recognition work. In sign language recognition tasks, the use of traditional convolutional neural networks to extract spatio-temporal features from sign language videos suffers from insufficient feature extraction, resulting in low recognition rates. Nevertheless, video-based sign language datasets are very large and require a lot of computational resources for training and generalisation must be ensured, which poses a challenge for recognition. In this paper, we have presented a video-based sign language recognition method based on resnet and lstm. As the number of network layers increases, the ResNet network can effectively solve the granularity explosion problem and obtain better time series features. We use the Resnet convolutional network as the backbone model. At the initialisation stage, we obtain sign language features using ResNet; then, the learned feature space is used as the input of LSTM network to obtain long sequence features. The experimental results show that the accuracy of the above model is better than the mainstream model, and it can effectively extract the spatio-temporal features in sign language videos and improve the recognition rate of sign language actions.

Pakistan relies mostly on fossil fuel for fulfilling its energy demand which is expensive as 11 well as not friendly for the environment. The need of the hour is to shift from fossil fuels to renew-12 able energy resources like geothermal, wind, solar etc. to cater for global warming issues. Pakistan 13 has a lot of potential geothermal sites because of several fault lines and hot springs. A sound 14 knowledge of ground temperature is essential to use geothermal energy, which is obtained by drill-15 ing boreholes and putting sensors making it an expensive procedure. Thus, to avoid huge cost for 16 drilling bore holes, particularly for ground temperature analysis, a numerical approach has been 17 considered for determining ground temperature. Furthermore, correlation charts between air and 18 ground temperatures have been developed as there were no proper studies on the ground temper-19 ature of Pakistan. Then, with the help of a boreholes drilled in National University of Sciences and 20 Technology Islamabad Pakistan, the actual ground and numerically calculated temperatures have 21 been compared which shows an error margin in the range between 0.27% for higher depths to 7.3% 22 near surface. Thus, it is shown that the proposed method is easy to implement and better than large 23 scale testing methods for the depths at which geothermal energy is extracted.

Cancer is one of the most dreaded illnesses of the 20th century, cancer is continuing to spread and is becoming more common in the 21 st century.As of right now, breast cancer seems to be the most common cancer worldwide and the leading cause of cancer-related fatalities.In present study we used different network pharmacology tools for identification of target that involved in breast cancer that network pharmacology tool used target identification and validation process in drug discovery.In present study we used UniprotKB as text mining tool for identification of breast cancer gene in that we got the 2,658 gene in that we take the 165 in study the we done the GO and KEGG enrichment analysis in that we take pathways related to the breast cancer further we used STRING for determination protein-protein interaction in that we got the interaction between NDUFA1 with NDUFA3 and EREG,MYO1B with ACTN4 and XRCC3 with XRCC2.The interaction network was drawn and the network was analyzed by Cytoscape.

Rotator cuff (RC) repair leads to less than optimal results when dealing with massive lesions, so the use of scaffolds as biological support has been proposed to improve RC repair site biology. The present study aims to evaluate the clinical and radiographical outcomes in a series of patients suffering from massive or irreparable RC tears treated with patch (porcine or human scaffolds) repair (augmentation or bridging). Twenty-three patients with a minimum follow up of 24 months were subjectively with 3 patient-related outcome measurements (PROMs) (American Shoulder and Elbow Surgeons score, Constant score, visual analog scale), clinically and radiographically assessed before and after surgery. Regardless the technique (augmentation or bridging) or type of scaffold (porcine or human) employed, at follow up all patients experienced a statistically signif-icant improvement in all PROMs, and clinically. Patch repair represents a valid salvage procedure in massive or irreparable RC tears improving the quality of life and eventually delaying the need for prosthetic replacement.

Recently, the concept of participatory democracy developed in the early 1970s has come back into fashion to revitalize the public involvement in political decision-making processes. Public par-ticipation in forest policy has been fully conceptualized by the scientific community in the late 1990s and early 2000s, but in many contexts the practical application remains unfulfilled. The aim of this study is to identify and analyze the participatory techniques used in literature to increase knowledge and facilitate its transferability into forest policies and strategies. A literature review was carried out to offer an overview of the participatory techniques adopted in the deci-sion-making process. At the end of literature review, 25 participatory techniques were identified based on over 2,000 publications. Afterwards, the participatory techniques were assessed using seven indicators (degree of participation, type and number of participants, time scale, cost, po-tential influence on policy). The results showed that the type of actors involved in the participa-tory technique is a key variable for the complexity and usefulness of the process, while the number of participants influences how information is disseminated. The Principal Component Analysis highlighted that the participatory techniques can be divided in three groups: the first group includes those techniques with a high degree of participation and a contextual high po-tential influence on policies, the second one includes techniques with a costs in terms of re-sources, while the third one consists of those with a large number of participants and reduced time requirements.

We utilized camera traps to assess animal diversity, relative abundance, and anthropogenic activities in the Jhalana Reserve Forest (JRF), located amidst Jaipur, with a population of 3.9 million people. Between November 2017 and November 2019, camera traps were strategically deployed in both the tourist zone and peripheral areas, capturing 16,328 photos. This study represents the first comprehensive baseline assessment of animal diversity in JRF, documenting a total of 39 species, including 18 bird species, 14 mammals, and six domestic species, alongside human activity. Among the 14 mammal species, seven were carnivores. Notably, we identified 25 individual Indian leopards (Panthera pardus fusca) during 2017-2018, comprising 8 males and 17 females, highlighting the leopard as the apex predator in JRF. Concurrently, domestic animals accompanied by humans were observed within JRF. However, rigorous conservation efforts and patrols by the Rajasthan Forest Department resulted in a notable decline in human intrusion, reducing from 28.0% in 2017-18 to 3.9% in 2018-2019, with domestic animal activity reaching zero in the latter period. Consequently, the relative abundance of wildlife species increased during the study period of 2018-2019, underscoring the positive impact of conservation strategies implemented by authorities. Our findings affirm that camera traps effectively establish baseline data, assess animal diversity, and evaluate relative abundance in reserve forests situated within human-dominated landscapes. This study provides critical insights to inform the development and implementation of conservation strategies in similar protected areas.

Bovine Respiratory Disease Complex, a complex respiratory ailment in cattle, results from a combination of viral and bacterial factors, compounded by environmental stressors such as overcrowding, transportation, and adverse weather conditions. Its impact extends beyond mere health concerns, posing significant economic threats to the cattle industry. This study presents an extensive investigation into viral pathogens associated with BRDC in Serbian cattle, utilizing serum samples and nasal swabs. A cross-sectional study was conducted in 2024 across 65 randomly selected dairy farms in Serbia, excluding vaccinated farms. Farms were categorized by livestock count: small (≤50 animals), medium-sized (51-200 animals), and large (>200 animals). Serum samples from adult cattle older than 24 months were tested for antibodies against BVDV, BHV-1, BRSV, and BPIV3. Nasal swab samples from animals with respiratory signs were tested using PCR for viral genome detection. Results showed seropositivity for all four viruses across all farms, with BPIV3 exhibiting universal seropositivity. Medium-sized and large farms demonstrated higher seropositivity for BRSV and BHV-1 compared to small farms (p<.05). True seroprevalence estimates at the animal level were 84.29% for BRSV, 54.08% for BVDV, 90.61% for BHV-1, and 84.59% for BPIV3. PCR analysis of nasal swabs revealed positive detections for BRSV (20%), BHV-1 (1.7%), BVDV (8%), and BPIV3 (10.9%). Influenza D virus was not found in any of samples. This study provides critical insights into the prevalence and circulation of viral pathogens associated with BRDC in Serbian cattle, emphasizing the importance of surveillance and control measures to mitigate the impact of respiratory diseases in cattle populations.

Stairs are among the key elements in architectural composition, both aesthetically and spatially. They are also one of the main innovations in architecture and building, allowing pedestrians to bridge considerable height differences with relative efficiency. It is therefore surprising that, in spite of all stair regulations in building codes, stairs are responsible for a huge number of accidents – second only to motorcars. The extent of safety failures suggests that user interaction with stairs is poorly understood by designers and policy makers. This is not unrelated to the lack of research into the design and use of stairs. Templer’s seminal work is the exception but it dates from 1992 and since then little has been done to understand the relation between architectural design and stair performance, including safety. To redress this, we can build on affordance-based analyses of stair climbability, which establish a clear connection between the form of a stair and the perception of action possibilities and dangers by all kinds of users. By doing so affordances establish a comprehensive and consistent framework for the analysis of architectural designs, which utilizes both domain and psychological knowledge, including as a foundation for computational applications.

Ten new Schiff bases, including thiocarbohydrazone derivatives (1–10), were synthesized using an efficient, uncomplicated, and environmentally friendly approach using the reaction of alkyl-substituted aldehydes. The thiocarbohydrazones that were obtained were derived from o-phthalaldehyde. The chemical structures of the compounds were identified by the utilization of UV-Vis spectroscopy, Fourier transform infrared (FT-IR), ¹H nuclear magnetic resonance (¹H NMR), ¹³C nuclear magnetic resonance (¹³C NMR), and elemental analysis methods. The thermal stability of thiocarbohydrazones was examined using thermogravimetric analysis (TGA-DSC). Investigations were conducted on urease inhibition tests, pharmacokinetic property research, and molecular docking. The collection of samples with the urease enzyme revealed significant molecular docking findings, with MolDock scores ranging from -153 to -189. The compounds have the potential to be effective drug candidates for treating certain diseases, as indicated by the consistent results of molecular docking, urease inhibition tests, and pharmacokinetic characteristics investigations.

Health and well-being are a major concern for the elderly who experienced evacuation due to the 2011 Fukushima Daiichi Nuclear Power accident. This study examined the feasibility of a picture sound book with Ninja-essence to maintain or improve exercise habits and physical and mental conditions of the elderly affected by the Fukushima Daiichi Nuclear Power plant accident. We conducted a pre–post intervention study to evaluate a picture sound book with Ninja-essence for returnees and evacuees post lifting evacuation restrictions. In total, 29 people participated in this study. Residents in two groups, returnees and evacuees, were provided with the tool. Results of the pre–post changes were analyzed using descriptive statistics, i.e., Fisher’s exact test and t-test, and a significant difference was observed in both groups of participants between their left and right hand-grip strength, the maximum phonation time in the participants of the group that regularly engaged in exercise, and in the questions regarding swallowing exercises and singing songs or practicing words (p < 0.013 and 0.033); 16 of 29 participants reportedly enjoyed the program. The results demonstrated the future possibility of determining the improved outcome of this program in larger samples.

Many middle-aged and older adults (MAOA) do not engage in sufficient physical activity (PA) despite its well-documented benefits for healthy aging. Existing PA interventions often fail to reach or engage the target population effectively. This study investigates MAOA's preferences for recruitment strategies to optimize the reach and uptake of PA interventions, thereby enhancing their impact on healthy aging and public health. Qualitative interviews were conducted with 39 MAOA participants (69% female, mean age = 69.46, SD = 7.07), guided by McGuire's Theory on Persuasive Communication. Factors related to the source, message content, channel, receiver characteristics, and target behavior of recruitment strategies were analyzed. Findings suggest a preference for trustworthy sources (e.g., healthcare professionals over commercial entities) and positive, non-ageist messaging. MAOA vary in channel preferences but emphasize the importance of personalization. Despite heterogeneity, MAOA commonly perceive themselves as sufficiently active, necessitating improving knowledge on what constitutes sufficient PA, and easy enrollment or trying-out interventions. Tailoring recruitment strategies to diverse MAOA segments, based on age, seems crucial for effective engagement. Future research could explore quantitative research into how communication factors relate to various target population characteristics.

In the evolving landscape of cybersecurity threats, the Permanent Denial of Service (PDoS) attacks have emerged as a particularly damaging form of cyber aggression. Unlike the more well-known Denial of Service (DoS) attacks, which disrupt services temporarily, PDoS attacks aim to inflict irreversible damage to systems, often resulting in significant system overhauls and requiring hardware replacement. To enable the development of effective security measures, but also to address the knowledge gaps, this paper offers an in-depth exploration of PDoS attacks, emphasizing their distinguishing characteristics, underlying mechanisms, and potential further development. Through a comprehensive case study, the research highlights diverse tactics and strategies employed by attackers, from targeting IoT devices to manipulating boot processes and exploiting firmware vulnerabilities. A novel classification of PDoS attack vectors is proposed, that also explains the ways in which the systems can be compromised. The findings confirm the pressing need for adaptive and robust defense mechanisms to mitigate the threats posed by PDoS attacks in our interconnected digital world.

Many natural and artificial liquid environments such as rivers, oceans, lakes, water storage tanks, aquariums, and urban water distribution systems, are difficult to access. As a result, technology is needed to enable autonomous liquid sampling to monitor water quality and ecosystems. The existing in-situ sample acquisition and handling systems for liquid environments are currently limited to a single use and are semi-autonomous, relying on an operator. Liquid sampling systems should be robust and light and withstand long-term operation in remote locations. The system components involved in liquid sampling should be sterilisable to ensure reusability. Here, we introduce a prototype of a liquid sampler that can be used in various liquid environments and may be valuable for the scientific characterisation of different natural, remote, and planetary settings. The Autonomous Planetary Liquid Sampler (APLS) is equipped with pre-programmed fully autonomous extraction, cleaning, and sterilisation functionalities. It can operate in temperatures between -10 ℃ and 60 ℃ and pressure of up to 0.24 MPa (~24 m depth below mean sea level on Earth). As part of the control experiment, we demonstrate its safe and robust autonomous opera-tion in a laboratory environment using a liquid media with Bacillus subtilis. A typical sampling procedure required 28 s to extract 250 mL of liquid, 5 s to fill the MilliQ water, 25 s for circulation within the system for cleaning and disposal, and 200 s to raise the system temperature from ~30 °C ambient laboratory temperature to 150 °C. The temperature is then maintained for another 3.2 hours to sterilise the critical parts, allowing a setup reset for a new experiment. In the future, the liquid sampler will be combined with various existing analytical instruments to characterise the liquid solution and enable the autonomous, systematic monitoring of liquid environments on Earth.

Household waste is the primary source of environmental pollution due to global population growth compared to other sources of waste. This research aims to develop a smart and integrated household waste management system framework. The resulting framework not only focuses on dimensions of information technology but also links it with other integrated dimensions. This research attempts to conduct a Systematic Literature Review (SLR) using the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) protocol to produce a smart and integrated household waste management framework. The framework's design is carried out by identifying the type of household waste management process based on the Integrated Sustainable Waste Management (ISWM) framework, dimensions that support smart household waste management, and stakeholders involved. The SLR results, namely dimensions and subdimensions that support the framework of a smart and integrated household waste management system, were validated by a resource person from the Indonesian Ministry of Environment and Forestry. The smart and integrated household waste management framework that has been developed in this research contains five main dimensions: Information Technology, Operational Infrastructure, Governance, Economy, and Social-culture. This framework also addresses stakeholder engagement to support smart household waste management systems and identifies waste management processes based on the ISWM framework. This research uses the PRISMA technique to provide a framework for smart and integrated household waste management systems in the initial stage. The proposed framework has been validated and can be further developed as a smart and integrated household waste management system. This research also contributes to the involvement of various dimensions identified to deal with waste problems.

Sect. Tuberculata in the genus Camellia, is named after the "tubercle-like projections on the surface of the capsule and ovary". Due to complex morphological variations in these taxon and insufficient field investigations, the interspecific relationships are unclear, the species definitions are vague, and the names are confusing. This is not conducive to the conservation and study of these species. Therefore, herein, we systematically explored the taxonomic status of five sect. Tuberculata species using morphological, pollen morphology, and molecular phylogenetic methods. The result showed that (1) morphological characteristics for the flower, fruit, and leaves of C. anlungensis and C. leyeensis were similar. Furthermore, the pollen characteristics and pollen wall ornamentation showed that it was no significant difference between the two species. (2) there were significant differences between C. acutiperulata and C. anlungensis in terms of leaf shape (elliptic vs. obovate), calyx characteristics (sepal apex pointed vs. sepal oblong), and fruit shape (subglobose folds with shallow verruculose vs. flat folds and verruculose protuberances with pronounced internal cleavage). (3) C. pyxidiacea and C. rubituberculata differed in flower color (white or few light vs. red), fruit verrucae (obviously deeply cleft vs. shallowly uncracked). (4) a phylogenetic tree based on the chloroplast genome showed that C. anlungensis and C. leyeensis form a single clade (BS = 100%, PP = 1.0) and were on a different branch with C. acutiperulata in clade II, (BS = 100%, PP = 1.0); C. pyxidiacea and C. rubituberculata were clustered on different branches of clade I (BS = 99%, PP = 1.00). Integrated above results, we consider that C. leyeensis should be treated as a homonym of C. anlungensis; C. acutiperulata, C. pyxidiacea, C. rubituberculata respectively as a separate species. Clarifying the taxonomic status of these five species not only advances our understanding of the significance and complexity of the systematic classification of the genus Camellia but also has important implications for diversity conservation and population genetics.

Introduction: Unicompartmental knee arthroplasty (UKA) is gaining traction as a treatment for knee osteoarthritis due to faster recovery, better range of motion, and reduced healthcare costs compared to total knee arthroplasty (TKA). UKA preserves healthy parts of the knee, leading to a quicker return to function and less pain. However, TKA offers potentially longer-lasting results with lower revision rates. This study investigates the National Inpatient Sample (NIS) database for UKA and TKA patients to understand their relative benefits and limitations, aiming to inform patient care and resource allocation. Methods: This retrospective analysis examined outcomes following UKA and TKA using the Nationwide Inpatient Sample (NIS) database (2016-2019). Patients undergoing elective UKA or TKA (n=2,606,925) were identified using ICD-10 codes (Appendix). To minimize confounding factors, propensity score matching was performed using patient demographics, hospital characteristics, and comorbidities, resulting in a balanced cohort of 136,890 patients. In-hospital mortality, length of stay, postoperative complications, and hospitalization costs were compared (p < 0.05). This study received exempt IRB approval due to de-identified data. Results: The prevalence of UKA procedures significantly increased over the study period, with primary osteoarthritis being the leading cause for both UKA and TKA. Patients undergoing UKA were younger and had less comorbidities compared to those undergoing TKA. Propensity score matching effectively balanced these baseline characteristics between the two groups. Examining hospitalization outcomes in propensity-matched cohorts revealed low in-hospital mortality for both groups (0.015%). However, UKA demonstrated a clear advantage in terms of shorter length of stay (1.53 days vs. 2.47 days) and lower total hospitalization charges ($55,976 vs. $61,513). While UKA had slightly higher rates of intraoperative fracture and pulmonary edema compared to TKA, TKA was associated with a significantly increased risk of various complications. These included blood transfusion, blood loss anemia, acute coronary artery disease, pulmonary embolism, pneumonia, and acute kidney injury. Conclusion: UKA shows promise as a less-invasive option for younger patients with one-sided knee osteoarthritis, potentially offering shorter hospital stays, lower costs, and potentially fewer complications.

Background: Previous studies of the hydroethanolic extract of Virola elongata inner stem bark (HEVe) have demonstrated its antioxidant, gastroprotective, and antiulcer properties, but have not evaluate its anti-inflammatory potential. Methods: HEVe was obtained by maceration and phytochemicallly analyzed. Its systemic anti-inflammatory activity was assessed by its effect on lipopolysaccharide (LPS)-induced peritonitis in mice. HEVe gel (HEgVe) was employed to evaluate topical anti-inflammatory activity by measuring the ear edema resulted from croton oil-induced dermatitis in mice. Cell viability assay was conducted to determine non-cytotoxic concentrations of HEVe. RAW 264.7 cells were stimulated by LPS to determinate cytokine and nitric oxide production.Results: Phytochemical analysis of HEVe revealed the presence of phenolic acids, neolignans, flavonoids, and monomeric catechins. Oral treatment of acute peritonitis with HEVe reduced total leukocytes, neutrophils, TNF-α and IL-1β, and elevated IL-10 levels. The application of HEgVe reduced local edema. The HEVe on RAW 264.7 cells exhibited no cytotoxicity and cells with HEVe reduced TNF-α, IL-1β, and NO levels, and increased IL-13 levels. Conclusions: HEVe demonstrated systemic and topical multitarget anti-inflammatory activity, which is likely due to the combined effects of secondary metabolites. HEVe emerges as a promising herbal remedy for inflammation with minimal cytotoxicity, emphasizing its potential therapeutic significance.

This work presents emission line flux and kinematic structure mapping based on IFU data of the planetary nebulae Abell 30 (A30). The IFU has a field of view (FoV) of 16" x 12.3" and was used to partially cover knots J1 and J2, and completely cover knots J3 and J4 of A30. Our emission line flux map shows recombination species C II, C III, He I, O II as well as forbidden line species [O III], [Ne III] and [Ne IV] of high excitation level are all distributed in different parts of the knots. The kinematic structure shows considerable variation in both the velocities and spatial locations of these knots with positive and negative velocity excursions from the systematic value. Forbidden line species [O III], [Ne III] are distributed in both knots J3 and J4 but they are travelling at different speeds in opposite directions. Despite variation in distribution of the species, the velocities of [Ne IV] and [O III] are similar and travelling in the same direction while the other species [Ne III], He I, and O II share similar velocity of 200kms−1 up in the opposite direction. The complexity of distribution and kinematic structure of the knots revealed in this work indicates a strong tendency towards the hypothesis of multiple triggering events in the past history of A30.

Introduction: Lymph-nodal prostate cancer oligometastases are differently treated according to their site: pelvic are locoregional lymph-nodes, instead para-aortic lymph-nodes are considered as distant metastases. Aim of the study was a comparison between para-aortic and pelvic oligometastases treated with stereotactic body radiation therapy (SBRT). Material/methods: This is a retrospective analysis. De-novo metastatic or extra-nodal disease were excluded. Univariate and multivariate analyses were performed; pattern of recurrence was evaluated too. A propensity score matching (PSM) was applied to create comparable cohorts. Primary end-point was the progression-free survival (PFS). Secondary end-points were biochemical relapse-free survival (BRFS), ADT-free survival (ADTFS), polymetastases-free survival (PMFS), local progression-free survival (LPFS) and pattern of relapse. Results: 240 lymph-nodal oligometastases in 164 patients (127 pelvic and 37 para-aortic) were treated. Median PFS was 20 and 11 months in pelvic and para-aortic patients respectively (p=0.042). The difference was not confirmed at the multivariate analysis (p=0.06). Median BRFS was 16 and 9 months respectively in pelvic and para-aortic group (p=0.07). No statistically significant differences for ADTFS or PMFS were detected. The cumulative 5-years LPFS was 90.5%. At PSM no statistically significant differences for all the study end-points were detected. Conclusions: Patients affected by para-aortic disease might have PFS comparable to pelvic disease; local control is high in both cohorts. Our results support the use of SBRT also to para-aortic metastases.

Information theoretic quantities such as entropy, entropy rate, information gain, and relative entropy are often used to understand the performance of intelligent agents in learning applications. Mean squared error has not played a role in these analyses, primarily because it is not felt to be a viable performance indicator in these scenarios. We build on a new quantity, the log ratio of entropy powers, to establish that minimum mean squared error (MMSE) estimation, prediction, and smoothing are directly connected to Mutual Information Gain or Loss in an agent learning system modeled by a Markov chain for many probability distributions of interest. Expressions for mutual information gain or loss are developed for MMSE estimation, prediction, and smoothing and an example for fixed lag smoothing is presented.

Abstract Global marine fish harvest has reached a plateau over the last decade. Efforts to increase aquaculture tend to face limitations in water resources and contamination problems. Of the current fish harvest at least 50% is discarded as waste. The chemical and microbiological contaminations limit the utilization of harvested fish. There is a need to improve fish preservation to minimize spoilage and process them into more appealing products. Instead of resorting to individual food processing methods, the efficiency of processing could best be increased by a combination of conventional and modern processing methods, or combinations of modern processing methods. Fish waste is a rich source of oils containing essential fatty acids, polypeptides, and amino polysaccharides that could be utilized through upscaling of the current scientifically proven methods, to new processing technologies. Separation of collagens, gelatins, bioactive peptides, edible fish oils, and chitosan form the primary stages in the utilization of fish waste. The products need purification to meet food quality and safety standards, and desirable industrial characteristics. The diversity of information and products generated through new methods requires advanced data handling and prediction systems, such as artificial intelligence, to address food safety and get the best out of fish processing and utilization.

Primordial axion stars, hypothetical stars formed from axions, could play an essential role in forming galaxy halos. These stars could have originated in the early universe shortly after the Big Bang. We show that while “normal” axions coalesce into a gravitationally bound Bose-Einstein condensate, forming a dense object - an axion star, the ultralight axions could act as the initial seeds for galaxy halos.

This study describes the synthesis and characterization of mixed hydrotalcite–organosilica membrane for gas separation. Hydrotalcite exhibits the capability to adsorb carbon dioxide at elevated temperatures. High surface area and favorable coating properties are essential to harness its potential for practical applications. Stable alcohol-based dispersions are needed for thin film applications of mixed membranes containing hydrotalcite. Currently, producing such dispersions without the need for delamination and dispersion agents is a challenging task. This work introduces for the first time a manufacturing approach to overcoming the drawbacks mentioned above. It includes a synthesis of hydrotalcite nanoparticles, followed by agent-free delamination of their layers and final dispersion into alcohol without dispersion agents. Further, the hydrotalcite-derived sorption agent is dispersed in a matrix based on organo-silica gels derived from 1,2-bis(triethoxysilyl)ethane (BTESE). The analytical results indicate that the interconnection between hydrotalcite and BTESE-derived gel occurs via forming a strong hydrogen bonding system between the interlayer species (OH groups, CO32-) of hydrotalcite and oxygen and silanol active gel centers. These findings lay the foundation for applications involving incorporating hydrotalcite-like compounds into silica matrices, ultimately enabling the development of materials with exceptional mass transfer properties. In part 2 of this study, gas separation performance of the organo-silica and the hydrotalcite-like materials and their combined form will be investigated

This research paper focuses on the synthesis and characterization of Cu-doped Mg-Co ferrites with varying compositions (Mg_0.6-xCo_0.4Cu_xFe₂O₄, where x = 0.0, 0.1, 0.2, and 0.3) using a solid-state reaction method. This paper also investigates the structural, morphological, magnetic, and electrical characteristics of synthesized Mg_0.6-xCo_0.4Cu_xFe₂O₄, where x = 0.0, 0.1, 0.2, and 0.3. The X-ray diffraction (XRD) technique confirms the ferrites spinel structure in the Fd-3m space group, with average crystallite sizes ranging from 57.29 to 48.57 nm. Fourier Transform Infrared (FTIR) spectroscopy verifies chemical and structural changes, while scanning electron microscopy (SEM) reveals cubic crystal growth with an average grain size of 1 to 1.5 μm. DC electrical resistivity decreases with increasing temperature and Cu²⁺ substitution, ranging from 1.4 x 10⁶ Ω-cm to 6.7 x 10⁵ Ω-cm. The study suggests a correlation between resistivity and Cu²⁺ concentration. Magnetic behaviour, studied using a Vibrating Sample Magnetometer (VSM), shows dependence on dopant concentration, with coercivity ranging from 157 Oe to 256 Oe. The results indicate potential applications in magnetic storage devices, antennas, transformers, and high-frequency electronics.

In this work, we present two datasets for specific areas located in South Tyrol (Italy) and in Tyrol (Austria) that can be exploited to monitor and understand water resource dynamics in mountain regions. The idea is to provide the reader with information about the different sources of water supply over five defined test areas. The Snow Cover Fraction (SCF) and Soil Moisture Content (SMC) datasets are derived from machine learning algorithms based on remote sensing data. Both SCF and SMC products are characterized by a spatial resolution of 20 m and are provided for the period from October 2020 to May 2023 (SCF) and from October 2019 to September 2022 (SMC) respectively, each covering 3 seasons of interest, winter for SCF and spring-summer for SMC. For SCF maps, the validation with very high-resolution images shows high correlation coefficients of around 0.9. The SMC products were originally produced with an algorithm validated at global scale, but here, to obtain more insight in the specific alpine mountain environment, the values estimated from the maps are compared with ground measurements of automatic stations located at different altitudes and characterized by different aspects in the Val Mazia catchment in South Tyrol (Italy). In this case a MAE between 0.05 and 0.08 and an unbiased RMSE between 0.05 and 0.09 m3·m-3 were achieved. The datasets presented can be used as input for hydrological models as well as to hydrologically characterize the study alpine area starting from different sources of information.

To study the spatial accessibility of healthcare services in cities on the Tibetan Plateau, this paper proposes an improved 3SFCA method in the main urban area of Xining City. The improved 3SFCA method incorporates both selection weights from the Huff model and the M2SFCA approach to addressing suboptimal allocation of supply resources. Results show that the accessibility of healthcare for the main urban area of Xining City decreases in a circle to four axes, with good accessibility in the east and center but poor accessibility in the north. And there is a positive spatial relationship between population and accessibility. Besides, this paper proposes a framework for studying the spatial accessibility of healthcare on the Tibetan Plateau.

Previous research demonstrates that the interruption of immersive experiences may lead to a bias in the results of questionnaires. Thus, the traditional way of presenting questionnaires, paper-based or web-based, may not be compatible with evaluating VR experiences. Recent research has shown the positive impact of embedding questionnaires contextually into the virtual environment. However, a comprehensive overview of the available VR questionnaire solutions is currently missing. Furthermore, no clear taxonomy exists for these different solutions in the literature. To address this, we present a literature review of VR questionnaire user interfaces (UI) following PRISMA guidelines. Our search returned 1.109 initial results, which were screened for eligibility, resulting in a corpus of 25 papers. This paper contributes to HCI and games research with a literature review of embedded questionnaires in VR, discussing the advantages and disadvantages and introducing a taxonomy of in-VR questionnaire UIs.

The objectives of this paper are to investigate the tradeoffs between a physically constrained neural network and a deep, convolutional neural network and to design a combined ML approach ("VarioCNN"). Our solution is provided in the framework of a cyberinfrastructure that includes a newly designed ML software, GEOCLASS-image, modern high-resolution satellite image data sets (Maxar WorldView data) and instructions/descriptions that may facilitate solving similar spatial classification problems. Combining the advantages of the physically-driven connectionist-geostatistical classification method with those of an efficient CNN, VarioCNN provides a means for rapid and efficient extraction of complex geophysical information from submeter resolution satellite imagery. A retraining loop overcomes the difficulties of creating a labeled training data set. Computational analyses and developments are centered on a specific, but generalizable, geophysical problem: The classification of crevasse types that form during the surge of a glacier system. A surge is a glacial catastrophe, an acceleration of a glacier to typically 100-200 times its normal velocity. GEOCLASS-image is applied to study the current (2016-2024) surge in the Negribreen Glacier System, Svalbard. The geophysical result is a description of the structural evolution and expansion of the surge, based on crevasse types that capture ice deformation in six simplified classes.

The neuronal etiology of obesity is centered around diet-induced inflammatory state in the arcuate nucleus of the hypothalamus which impairs the functionality of pro-opiomelanocortine neurons (POMCs) responsible for whole-body energy homeostasis and feeding behavior. Intriguingly, systemic salt inducible kinase 2 (SIK2) knockout mouse demonstrated reduced food intake and energy expenditure along with modestly dysregulated metabolic parameters suggesting a causal link between the absence of SIK2 activity in POMCs and the observed phenotype. To test this hypothesis, we conducted a comparative secretomics study from POMC neurons following pharmacologically induced endoplasmic reticulum (ER) stress induction, a hallmark of metabolic inflammation and POMC dysregulation in diet induced obese (DIO) mice. Our data provide significant in vitro evidence for the POMC specific SIK2 activity in controlling the energy metabolism and feeding in DIO mice by regulating the nature of related POMC secretome. Our data also suggests that under physiological stress conditions SIK2 may act as a gatekeeper for the secreted inflammatory factors and signaling molecules critical for cellular survival and energy homeostasis. On the other hand, in the absence of SIK2 gate opens leading to surge of inflammatory cytokines and apoptotic cues concomitant with the dysregulation of POMC neurons.

Disease transmission in wildlife is linked to ecosystem and human health, and host community structure can mediate pathogen spread. Here, we decompose the well-known susceptible-infected (SI) compartmental models of disease transmission for multi-host communities to explore the disease-biodiversity relationship. We examine the parameters involved in interspecific transmission and link them to the multi-host outbreak potential, R0. We partition R0 into its separate elements that can be associated with either the recipient or donating host, and show how this allows us to identify maintenance versus spillover hosts, allowing us to quantify separate stages of spillover into a novel, recipient host. We further suggest that the evolutionary relatedness between donating and recipient host may play a role in the probability a pathogen establishes in a novel species, as illustrated by the observed phylogenetic signal in the host-breadth of multi-host pathogens. We discuss how anthropogenic changes to the environment and wildlife communities, such as the reduction and fragmentation of wildlife habitat, might alter the mode and dynamics of disease transmission. This discussion contributes to the ongoing debate on the relationship between disease incidence and biodiversity. Through a synthesis of classic ecological theory, we illustrate how pathogens can affect host populations through phenomena such as in/direct symbioses, that can save a pathogen from extinction or suppress competing host species, but we highlight how host diversity can simultaneosuly influence the survival and success of the pathogen, suggesting a complex feedback between hosts and parasites in multi-host communities. Our review provides a guide to common derivations of interspecific transmission, and underscores the critical connections between community and disease-ecology.

This article describes a novel topical composition constituted by gamma-amino butyric acid (GABA) and microbial chondroitin sulfate. This composition, formulated by the author and manufactured in a certified facility in the United States of America, exhibits potential for non-invasive intervention in anxiety management, sleep quality enhancement, and promotion of brain-related functions like meditation and nonlocal consciousness. The core component comprises GABA, a key inhibitory neurotransmitter within the central nervous system, complexed with a suitable carrier molecule, microbial chondroitin sulfate. This complexation aims to enhance transdermal absorption and optimize delivery of GABA to target tissues. The proposed mechanism of action involves modulation of GABAergic signal transduction pathways. Application of the topical composition allows GABA penetration into the skin and potentially deeper tissues, where it interacts with GABA receptors. This interaction leads to mental calmness and relaxation as assessed by electroencephalography. The influence of GABAergic signaling on brain circuits demonstrated in this article, when associated with meditation and nonlocal consciousness, suggests potential for the composition to support these practices. The advantage of such an approach consists in avoiding the potential systemic side effects associated with oral or injectable administration of GABA, anxiolytics or hypnotics. Furthermore, the combination of GABA and microbial chondroitin sulfate may offer synergistic benefits, potentially enhancing the overall biological effects. In conclusion, this article presents a novel topical approach for managing anxiety, enhancing sleep quality, and potentially facilitating meditation and nonlocal consciousness through modulation of GABAergic signaling pathways. While further research is necessary, the potential for a non-invasive and potentially side-effect-free intervention in these areas is promising.

This paper focuses on the paradigm that explains the link between energy transitions and financial transformations. In particular, it attempts to shed some light on the following question: How did the transition from wood to coal affect financial development in late 18^th and early 19^th century Britain? The results demonstrate that the energy transition in Britain during the 1^st Industrial Revolution constituted an important moment in the country's financial development and can be used as an example of how an energy innovation can foster the financial development of particular countries or regions.

This manuscript reviews three case studies from Brazil, Panama, and Portugal that illustrate Nature-based Solutions. The Tijuca Forest in Rio de Janeiro is a remarkable story of centuries of forest management that today is recognized as a UNESCO World Heritage Site. The Panama Canal Watershed produces water for Canal operations, electricity generation, and drinking water for half the country´s population. Traditional windmills and weirs near streams in the Alentejo Region, Portugal, have largely been abandoned due to the damming of the Guadiana River. Yet today, weirs are increasingly recognized for their important contribution to water provisioning in this dry region. All have a primary goal related to water provisioning, yet their ecosystem benefits are multiple. The cases offer important lessons for adaptation to climate change, cultural benefits from traditional human activities, and concerns about social equity.

The detection accuracy of bridge superficial defect using the deep neural network approach decreases significantly under light variation and weak texture condition. To address these issues, an enhanced intelligent detection method based on the YOLOv8 deep neural network is proposed in this study. Firstly, multi-branch coordinate attention (MBCA) is proposed to improve the accuracy of coordinate positioning by introducing a global perception module in coordinate attention mechanism. Furthermore, a deformable convolution based on MBCA is developed to improve the adaptability for complex feature shapes. Lastly, the deformable convolutional network-attention-YOLO (DAC-YOLO) detection algorithm is formed by replacing the deep C2F structure in the YOLOv8 architecture with deformable convolution. A supervised dataset consisting of 4794 bridge surface damage images is employed to verify the proposed method, and results show that it achieves improvements of 2.0% and 3.4% in mAP and R. Meanwhile, the model complexity decreases by 1.2G, increasing the detection speed by 3.5/f·s-1.

Interaction between multiple phases especially liquid-gas is one of the most common phenomena in industrial systems. Computer Vision enables modern systems to derive an automated and robust image-processing technique to address this issue. However, diverse experimental conditions still make it a challenging task to overcome. In Deep Learning, instance segmentation has created a niche in various computer vision applications as it aims to provide different instance IDs to objects belonging to the same class. In this paper, we propose a novel approach employing the YOLO (You Look Only Once) an end-to-end deep learning architecture for the detection and segmentation of bubbles in fluid flows. YOLOv5 offers significant improvements in both speed and accuracy compared to its predecessors like YOLOv3. Therefore, we train the YOLOv5 network on a dataset consisting of annotated images representing instances of bubbles across varied fluid flow environments. This paper provides both qualitative and quantitative evaluation of three YOLOv5 networks (small, medium, and extra-large) in detecting and segmenting bubbles with high accuracy and efficiency. Based on the metrics all three YOLOv5 models achieved high precision above 0.98 for bounding box detection and 0.97 for segmentation mask, and high recall value greater than 0.97 for box and 0.96 for mask quality was achieved. The achieved results indicate that the models accurately localize bubbles within the image frame, and distinguish bubble pixels from the background. Also, mean average precision (mAP50-95) consistently exceeds 0.84 across all models for the bounding box and 0.73 for the segmentation mask. The ascertained results emphasize the potential of YOLOv5 architecture as a powerful tool for automated bubble analysis in real-world applications. Our research contributes to advancing the field of deep neural networks in fluid systems and provides a fresh approach for future developments in automated bubble analysis.

A low cost, scalable and robust process has been proposed as innovative method for coating solar mirrors with a self-cleaning, transparent in the full solar range and versatile material based on auxetic aluminium nitrides, previously obtained on the laboratory scale. This work presents the scaling-up of fabrication process from laboratory to prototypal scale and pre-liminary results of outdoor self-cleaning solar mirror prototypes testing in the demonstrative CSP plant ENEASHIP located in Casaccia (Rome) ENEA research centre. Prototypes 50x40cm have shown stability in external conditions: no degradation occurs during the test campaign. Their washing restores the initial reflectance affected by soiling and the self-cleaning performance allows the utilization of a reduced quantity of water for cleaning operations with respect to uncoated glass of back surface mirrors. A similar self-cleaning AlN coating could be utilized on other solar components affected by soiling, such as glass envelopes of heat collecting elements, PV panels and everywhere are required self-cleaning performance combined to optical ones.

This paper presents the results of quantitative research examining the impacts of demographic and socioeconomic factors on community resilience to disasters. The survey was carried out utilising a questionnaire distributed and subsequently collected online from 321 participants during January 2024. The study employed an adapted version of the '5S' social resilience framework, encompassing five sub-dimensions – social structure (10 variables), social capital (9 variables), social mechanisms (17 variables), social equity and diversity (13 variables), and social belief (13 variables). This customized framework includes 62 indicators, providing a thorough assessment of community (social) disaster resilience in the research context. To explore the relationship between predictors and community (social) disaster resilience in Serbia, their attitudes towards the mentioned five sub-dimensions, as well as their engagement in preventive measures and their perception of resilience to various disasters with a particular focus on demographic and socio-economic impacts, statistical methods including t-tests, one-way ANOVA, Pearson’s correlation, and multivariate linear regression were employed. The results of the multivariate regressions across various community disaster resilience subscales indicate that age emerged as the most significant predictor for the social structure subscale. At the same time, education stood out as the primary predictor for the social capital subscale. Additionally, employment status proved to be the most influential predictor for both social mechanisms and social equity-diversity subscales, with property ownership being the key predictor for the social beliefs sub-scale. Despite being considered in the analyses, gender, marital status, income level, and number of household members did not emerge as the most significant predictors across the investigated community (social) disaster resilience subscales. The determined mean value of the community (social) disaster resilience index is M = 2.62, and the findings reveal that participants assigned the highest ratings to the social beliefs subscale (M = 2.76), while the lowest values were observed in the social structure subscale (M = 2.46). Findings can be used to create strategies and interventions aimed at enhancing the resilience of communities in Serbia by addressing the intricate interplay between demographic characteristics, socio-economic factors, and their ability to withstand, adapt to, and recover from different disasters.

The coffee industry loses millions of dollars annually worldwide due to the Coffee Berry Borer (CBB); these losses imply a decrease in quality and production. Traps are used to monitor their flight and for pest control. The main objective was to determine the flight pattern and trap capture percentages of the CBB population over time using column traps (CTs) in two independent field experiments. CTs were composed of four traps installed at four different heights 0.5, 1.5, 2.5, and 3.5m above ground. Our results demonstrated a significant difference in CBB capture by traps placed at different heights above the ground. The CT capture maintained a pattern throughout this study's lag; the lower the height, the greater the percentage of CBBs captured. In Experiments A and B, the traps placed at 0.5m caught 67% and 85% of the CBBs captured, respectively. Furthermore, the trap set at 1.5m above the ground in the multi-level CT showed a higher capture percentage than the individually placed trap (also at 1.5m). The pattern of the capture and proportion of the CBB in the CTs were maintained throughout the study despite the season, changes in temperature, and relative air humidity. We suggested that CTs could be explored as a useful tool for capturing the CBB, considering its monitoring and management.

The ecosystem plays a crucial role in mitigating climate change and protecting the environment. This study employs GIS technology to conduct an in-depth analysis of the current status of Queensland's ecosystem and develops a Climate Change Vulnerability Index (CCVI) model based on six sub-factors. These sub-factors include the Exposure Index (Mean surface temperature and precipitation), the Sensitivity Index (Population density, Building density, and Proximity to forests and nature reserves), and the Adaptive Capacity Index (Nighttime light radiation). The findings indicate that the CCVI value is lowest in the southeastern coastal region of Queensland, suggesting that this area is less vulnerable to climate change. However, other coastal areas and the far western inland regions exhibit higher CCVI values, indicating greater climate vulnerability. These areas require attention and the implementation of appropriate measures. By deepening our understanding of exposure, sensitivity, and adaptive capacity, we can formulate effective policies and measures to promote sustainable development and mitigate the negative impacts of climate change on the region. This study holds significant practical implications for guiding ecological planning and management decisions in the area.

DNA methylation is one of the epigenetic mechanisms which have been implicated in cellular differentiation, ageing and disease development. The effect of hypomethylating drug 5-aza-2´deoxycytidine (5-aza dC) on the biosynthetic profile of caudal region chondrocytes from chick sternum was studied in detail. The chondrocytes in culture were treated with varying doses of 5-aza dC for 48h and maintained subsequently without the treatment and harvested at selected time points for analysis of growth and differentiation status. 15µg/ml of 5-aza dC showed optimum Concentration at which there was a significant increase in DNA synthesis and RNA synthesis as per cell basis. There was also a significant increase in total protein synthesis and collagen synthesis as per cell basis at this concentration. This optimal concentration also showed to up regulate the gene expression of Type X collagen and alkaline phosphatase, which are the marker of hypertrophic chondrocyte expression. These results further support the notion that methylation is the major epigenetic factor controlling the differentiation and maturation of chondrocytes.

This study maps and quantifies the green infrastructure of the cities of Bujumbura, Kinshasa and Lubumbashi. A remote sensing approach, in conjunction with landscape ecology metrics, characterized this analysis, which was based upon three Landsat images acquired in 2000, 2013 and 2022 for each city. Spatial pattern indices show that green infrastructure was suppressed in the cities of Bujumbura and Kinshasa, in contrast to the city of Lubumbashi, which was characterized by a fragmentation of its green areas. Additionally, the values of the stability, aggregation and fractal dimension metrics suggest that the city of Bujumbura underwent rather intense dynamics and a reduction in the continuity of its green areas, while the city of Kinshasa shows weaker dynamics and tendances of patch aggregation in the study period. The city of Lubumbashi, in its turn, exhibits strong dynamics and an aggregation of its green infrastructure, in a context of a high level of anthropization. The evolution of the Normalized Difference Vegetation Index shows a sawtooth evolution of tall vegetation patches for the city of Bujumbura, against a gradual decrease in Kinshasa and Lubumbashi. It is advocated that the urban growth of these cities should be planned carefully in order to integrate the presence of sufficient green infrastructure.

Abstract Background The advent of monoclonal antibodies (mAbs) targeting calcitonin gene-related peptide (CGRP) pathway has transformed the management of migraine, offering newfound optimism for clinicians and individuals with episodic migraine (EM) and chronic migraine (CM). While randomized controlled trials (RCTs) have provided crucial insights into the effectiveness and safety profiles of these treatments, their translation into real-world clinical practice remains a e challenge. Objective This review aims to conduct a comprehensive assessment of real-world studies, offering valuable insights tailored for practical application in clinical settings. Methods We conducted a comprehensive literature search in PubMed, SCOPUS, and MEDLINE for real-life studies on erenumab, fremanezumab, and galcanezumab. Abstracts underwent rigorous screening by two reviewers for relevance. Data extraction from selected articles was performed using a standardized form, with verification by a second reviewer. Data synthesis was narrative, following PRISMA guidelines. Results Our search included 55 pertinent studies conducted between 2019 and 2023. Real-world study designs demonstrated notable variability in the selection and inclusion of migraine patients, influenced by factors such as attack frequency, data collection criteria, and primary/secondary objectives. Key findings commonly reported considerable improvements in efficacy outcomes (migraine frequency, analgesic use, pain severity, disability), high responder rates, and optimal safety and tolerability profiles. Conclusion Real-world evidence underscores the role of anti-CGRP mAbs as targeted therapies for both CM and EM patients. The overall results indicate that the effectiveness and tolerability of anti-CGRP mAbs in real-world applications may exceed those observed in RCTs, an unprecedented finding in clinical neurology.

Data leakage by statistical officers represents a significant statistical crime under the Indonesian Statistics Law. However, despite the legal provisions, there has been a notable absence of enforcement actions against such breaches, raising questions about the effectiveness and applicability of the current legal framework for addressing statistical crimes related to data leakage. This study identifies a research gap in the enforcement and operationalization of existing laws, emphasizing the lack of empirical data on how these legal provisions are applied in practice. Utilizing an empirical research methodology, this study analyzes data and real-world instances of statistical data leakage. The findings reveal that unethical behavior among statistical officers, inadequate data security measures, and the threat of social engineering significantly contribute to the potential for data breaches. The study's strength lies in its focus on providing a comprehensive understanding of these issues and proposing actionable solutions. This research not only fills the existing gap by offering empirical insights but also advances practical recommendations for enhancing data protection and legal enforcement mechanisms within Indonesia’s statistical framework.

In the realm of molecular science, intricate relationships between molecular structures and their biomedical and pharmacological characteristics have been revealed through empirical experiments. This exploration hinges on the application of numerical descriptors, known as Topological Indices, which illuminate the inherent properties of diverse molecular structures. With particular significance in the medical and pharmaceutical domains, these indices facilitate the prediction of biological features for new chemical compounds and drugs by quantifying weighted entropies. In the context of this paper, we delve into the concept of graph entropy, weaving it intricately with the topological properties of the crystalline framework of the copper oxide molecule, denoted as Cu\textsubscript{2}O$[i,j,t]$. Our primary objective is to unravel the mathematical symphony underlying the structural intricacies of Cu\textsubscript{2}O$[i,j,t]$ and to imbue it with the conceptual essence of entropy. We accomplish this through the computation of entropy, leveraging various topological indices, including weight. In addition to our analytical journey, we present a graphical comparison that juxtaposes the computed indices and entropies, shedding light on the interplay between mathematical analysis and the structural elegance of Cu\textsubscript{2}O$[i,j,t]$. This endeavor contributes to a deeper understanding of the material's multifaceted applications, spanning domains from chemical sensors to solar cells, photocatalysis, and batteries, where Cu\textsubscript{2}O's crystallographic structure plays a pivotal role.

The infections of bacterial origin represent a significant problem to public healthcare worldwide both in clinical and community settings. Recent decade was marked by limiting treatment options for bacterial infections due to growing antimicrobial resistance (AMR) acquired and transferred by various bacterial species, especially the ones causing healthcare-associated infections, which has become a dangerous issue noticed by the World Health Organization. Numerous reports shown that the spread of AMR is often driven by several species-specific lineages usually called the ‘global clones of high risk’. Thus, it is essential to track the isolates belonging to such clones and investigate the mechanisms of their pathogenicity and AMR acquisition. Currently, the whole genome-based analysis is increasingly used for these purposes, including epidemiological surveillance and analysis of mobile elements involved in resistance transfer. However, in spite of the exponential growth of available bacterial genomes, their representation usually lack uniformity and availability of supporting metadata, which creates a bottleneck for such investigations. In this dataset, we provide the results of a comprehensive genomic epidemiology analysis of 61,857 genomes of a dangerous bacterial pathogen Klebsiella pneumoniae. Important typing information including multilocus sequence typing (MLST)-based sequence types (STs), assignment of the isolates to known global clones, capsular (KL) and lipooligosaccharide (O) types, presence of CRISPR-Cas systems, and cgMLST profiles are given, and the presence of AMR and virulence genes within the genomes is also reported. This dataset will be useful for researchers in the field of K. pneumoniae genomic epidemiology, resistance analysis and prevention measure development.

This paper presents the design of a new neuro-generator of pseudorandom number type PRNG Pseudorandom Number Generator, which produces complex sequences with an adequate bit distri-bution. The circuit is connected to a neuronal module with six impulse neurons with different be-haviors: spike frequency adaptation, phasic spiking, mixed mode, phasic bursting, tonic bursting and tonic spiking. This module aims to generate a non-periodic signal that becomes the clock sig-nal for one of the LFSRs Linear Feedback Shift Register that the neuro-generator has. To verify its correct operation, the neuro-generator was subjected to a series of tests where the frequencies of the impulse neurons were modified. This modification allows generating a greater number of pulses at the output of the neuronal module, to obtain sequences with different characteristics that pass different NIST statistical tests National Institute of Standards and Technology of U.S. The results show that the new neuro-generator maintains pseudo-randomness in the sequences obtained with different frequencies and it can be implemented on reconfigurable FPGA Field Programmable Gate Array Virtex 7 xc7vx85t-2ffg1761 device. Therefore, it can be used for applications such as biologi-cal systems.

No study has focused on Uvaria macrophylla leaves with various traditional efficiencies. This paper therefore applied a database-affinity ultra-high-performance liquid chromatography with quadrupole orbitrap tandem mass spectrometry (UHPLC‑Q‑Orbitrap‑MS/MS) strategy, to analyze the lyophilized aqueous extract of U. macrophylla leaves. Through database comparison and MS fragment elucidation, the study has putatively identified 41 constituents belonging to flavonoid, phenolic acid, steroid, saccharide natural product classifications. Significantly, 4 groups of isomers (liquiritigenin vs isoliquiritigenin vs pinocembrin; oroxylin A vs wogonin vs galangin 3-methyl ether; isoquercitrin vs hyperoside; protocatechuic acid vs 2,5-dihydroxybenzoic acid) have been successfully distinguished from each other. All of 41 constituents were then subjected to a quantitative analysis based on linear regression equation established by the above UHPLC‑Q‑Orbitrap‑MS/MS strategy, and an ABTS+•-scavenging antioxidant assay. Finally, the chemical content was multiplied by the corresponding ABTS+•-scavenging percentage to calculate the antioxidant contribution. It was shown that the chemical contents of 41 constituents varied from 0.003 ± 0.000 to 14.418 ± 1.041 mg/g, and gallic acid showed the highest antioxidant contribution. Gallic acid is considered as a suitable antioxidant quality-marker (Q-marker) of U. macrophylla leaves. These findings have scientific implications for resource development and quality-control of U. macrophylla leaves.

Objective: Daratumumab (Dara) is the first-in-class human-specific anti-CD38 mAb approved for treating multiple myeloma (MM). However, DARA-induced depletion of CD38high natural killer (NK) cells results in crippled antibody-dependent cellular cytotoxicity (ADCC), which limits its clinical detection and prediction for Dara efficacy. Therefore, we aimed to explore new NK subsets that could predict Dara efficacy and the underlying mechanism in Dara development. Methods: Multicolour spectral flow cytometry monitored changes in the immune cells of 13 paired RRMM patients. We used machine learning-driven clustering, FlowSOM (Flow Self-Organizing Maps), and dimensional reduction with tSNE (t-distributed Stochastic Neighbour Embedding) to identify unique cell populations pre- and posttreatment. Then, in vitro, fratricide and proliferation assays were performed to explore the function of new NK subsets against MM under Dara treatment. Results: The NK cells were divided into 25 subsets, among which we found that the percentages of KIR-NKP46+ NK cells decreased in paired RRMM patients compared to healthy controls but increased significantly post-Dara treatment. The fold change in KIR-NKP46+ after one dose of Dara treatment can predict whether the best response could be achieved within one month (ROC=0.86, p=0.011). Further in vitro experiments showed that KIR-NKP46+ NK cells are superior to KIR+ NK cells, cooperatively acting with daratumumab to sustainably eradicate MM cells. Meanwhile, apoptosis was significantly decreased, and the proliferation ability was relatively increased post-Dara treatment. Conclusion: In conclusion, the fold change in KIR-NKP46+ NK cell subsets after one dose of Dara treatment can predict the outcome of the curative effect, indicating a putative role of KIR-NKP46+ subsets against MM cells. The mechanism attributed to a relative expansion of the subset due to decreased apoptosis and increased proliferation ability.

During tensile testing of materials, strain measurement is conducted using either contact or non-contact methods. Contact methods offer high accuracy and precision but are limited by the specimen's thickness and dimensions, whereas non-contact methods minimize damage to thin specimens and allow measurements in various environments, though they require longer prep-aration and calculation times. This paper proposes a circular grid marking pattern and a strain prediction algorithm using artificial intelligence (AI), which simplifies the preparation process and allows strain prediction without additional equipment. The circular grid pattern can be ar-ranged in various configurations from 1×5 to 5×7, and a laser marker, which requires minimal time, was used to engrave the pattern on the specimen to shorten the preparation time. The AI model, trained on image-based data, enables strain calculation regardless of the specimen's gauge length and size, and allows measurement of local strain as well as gauge-length strain. The reliability of this concept was verified by applying it to tensile testing.

For decades, compounds present in foods and beverages have been implicated in the etiology of human cancers. The International Agency for Research on Cancer (IARC) continues to classify such agents regarding their potential carcinogenicity in humans based on new evidence from animal and human studies. Furfuryl alcohol and β-myrcene belong to these potential human carcinogens due to be evaluated. The major source of furfuryl alcohol in foods is thermal processing and ageing of alcoholic beverages while β-myrcene occurs naturally as a constituent of essential oils of plants such as hops, lemongrass and derived products. This study aimed to summarize the occurrence of furfuryl alcohol and β-myrcene in foods and beverages using data from own nuclear magnetic resonance (NMR) analysis and literature review. The highest content of furfuryl alcohol was found in coffee beans (>100 mg/kg) and in some fish products (about 10 mg/kg) while among beverages, wines contained between 1–10 mg/L with 8 mg/L in pineapple juice. The content of β-myrcene was highest in hops. In conclusion, the data about the occurrence of the two agents is either very old or based on single sample analysis, and currently judged as insufficient for exposure and risk assessment. The results of this study point out the food and beverage groups that may be considered for future monitoring of furfuryl alcohol and β-myrcene.

: In this paper we present an optimization of the planar manufacturing scheme for stretch-free, shape induced metal interconnects to simplify the fabrication with the aim of maximizing the flexibility in the structure regarding to stress and strain. The Formation of trenches between silicon islands are actively used in the lithographic process to create arc shape structures by spin coating resist into the trenches. The resulting resist form is used as a template for the metal lines, which are structured on top. Because this arc shape is beneficial for the flexibility of these bridges. The trench depth as a key parameter for the stress distribution is investigated by applying numerical simulations. The simulated results show that the increase in penetration depth of the metal bridge into the trench increases the tensile load which is converted into a shear Force Q(x), that usually leads to increased strains the structure can generate. For the fabrication the filling of the trenches with resist is optimized by varying the spin speed. Compared to the theoretical resistance, the current-voltage measurements of the metal bridges show a similar behavior and almost every structural variation is capable of functioning as a flexible electrical interconnect in a complete island-bridge array.

This paper proposes a novel economic theory - Economic dynamics, which is the first in a series of articles on the economic dynamics. This paper is divided into four sections. Section 1 discusses the methodology and significance of the economic dynamics. The application of the standard model of theoretical physics as a new conceptual and modeling reference framework for the economic dynamics is an inevitable step beyond the Newtonian mechanics framework. Section 2 briefly outlines the content of the economic dynamics and its standard model, including market dynamics and its quantum electrodynamics model, both sharing the U(1) symmetry group; the sub-economic dynamics and its quantum chromodynamics model, both sharing the SU(3) symmetry group; the economic externality dynamics and its isospin dynamics model, both sharing the SU(2) symmetry group; and the ordinary rationality mechanism and its Higgs mechanism model, both causing spontaneous symmetry breaking. Additionally, through analysis of Pareto efficiency, it outlines economic gravity and its general relativity model. Section 3 provides three necessary foundational theoretical preparations for the economic dynamics, detailing scientific observation theory, economic rationality theory, and monetary pecuniary theory. Scientific observation theory first introduces the concept of observational directionality for empirical sciences, providing a shared orthogonal frame for cross-disciplinary observation, termed the orthogonality principle. By introducing the concept of observational disturbance degree, it distinguishes between high disturbance quadrants and low disturbance quadrants, corresponding to different mathematical paths, termed the diagonal rule. Quantum physics, higher-order cognition, and economic forward observation all fall within the high interference area, belonging to von Neumann's "yes-no" type of measurements, and are suitable for the same mathematical description. Economic rationality Theory, within the decision theory framework, defines three types of rationality theories: Economic rationality (or economic rational man), bounded rationality, and ordinary rationality, and defines the position of each rationality theory in the gauge field theory model of market dynamics. Economic rationality is a personified description of perfect competitive markets, the former being the global gauge potential, while the latter is the global gauge field strength. Bounded rationality describes specific market participants, the former being the local gauge potential, while the latter's market performance is the local gauge field strength. Ordinary rationality is the market ground state, possessing the properties of the Higgs field and the functions of the Higgs mechanism, causing spontaneous symmetry breaking in the market. The monetary pecuniary theory first argues for its light-like nature, thereby establishing a special relativity model of monetary peculiarity. This is a necessary condition for applying the gauge field theory model in market dynamics. Within the special relativity framework, using absolute prices (absolute time), a geometrized global money cone (light cone) can be constructed. Using intrinsic prices (proper time), individualized local wealth cones and poverty cones can be constructed, reflecting individual differences among market participants.

Technological advances in the last decades have led to the realization of the concept of a smart environment. A significant part of this development is decentralized ledger technology and its variant, a blockchain. The blockchain database is immutable, open to all stakeholders, secure by architecture and robust. Applying a blockchain in water supply sanitary control creates opportunities for optimization, higher quality of service, cost reduction, better sanitary standards and public control. Physical, chemical, and biological water supply contamination is a great source of public health hazards. Implementation of a blockchain for water supply IoT, from the source point to the consumption point, enables effective response to changing environments, possible cross-contamination, stormwater management or disaster and emergency action. The chapter encompasses all fundamental elements and principles of water collection, distribution and consumption, with a focus on the health hazards and sanitary requirements for potable water. The chapter listed the main contaminants, methods of their registration and elimination, and requirements for drinking water in accordance with WHO, EU Drinking Water Directive and EPA standards. Blockchain technology solutions are described for smart water supply, including smart supply management, smart contracts, tokenization, smart compliance systems, and, most importantly, effective utilization of distributed ledger technologies for sanitary monitoring of water sources, water treatment, and water distribution systems.

Hoof capability of domesticated, barefoot-kept horses and ponies traversing artificial environments remains undocumented. In this study, four equines were walked in-hand for 16 days, covering a distance of 50 km, over three solid surfaces. Subsequently, we conducted an assessment of hoof morphology. Hooves (n = 16) were radiographed before and after the trial, spaced 3 weeks apart, for sole depth measurement. External measurements of feet were recorded 24 hours before day 1 and repeated on day 9. Radiographs revealed increased sole depth in 11 hooves, notably at the palmar process, and some misalignment in certain phalanges. On day 9, after a 36-km distance, all hooves exhibited calloused soles and frogs, and required trimming. The front hooves of the horses had a pronounced, natural concavity. Hard surfaces were found to stimulate sole growth, with a portion of sole thickness preferentially accumulating within the dermal zone. Collectively, the maintenance of short trimming cycles to prevent misalignment, minimize hoof-wall loading and maintain a load-sharing system, may be necessary for barefoot-kept horses considering their rapid growth rate.

Public food trees are increasingly popular among researchers, urban planners and citizens, for their diversity of social, provisional and environmental benefits. However, the practice still faces several barriers, including the limited share of the population who uses them, and long-term management, studies to date suggesting municipality-citizen co-management partnerships as the most effective form, but still rare. Though participatory projects usually involve new plantations, several green spaces already harbor food trees which could be used to rapidly develop and test approaches for improving public usage and for co-management. Here we used a qualitative approach to explore usage and perception of public fruit trees and attitude towards public usage and participation, among green space visitors, staff and administrators of two urban green spaces harboring fruit trees in Birjand, Iran: one public park (Tohid Park) and one historic garden (Akbarieh Garden). Semi-structured interviews were conducted with twelve visitors of both spaces, four administrators and eight workers. We found that despite their great personal experience and interest in picking fruit, as well as a culture of strong relationships with fruit trees, visitors’ usage of the fruit was low, with a social norm against harvesting the fruit of others appearing as a main but easily remediable reason. Nevertheless, most visitors had a deep level of appreciation of these public fruit trees due in particular to the diverse pleasures that they provided (sensory, emotional, cognitive, experiential, social), and were greatly emotionally attached to them. They also had great interest in participating in their management and care, and more so in Tohid Park due to a greater potential social impact. According to some participants, education is needed to reduce damage that some citizens cause while picking fruit, or access should be restricted if maximizing production is the goal. These findings expand our understanding of the ways in which people can relate to existing urban fruit trees and suggest that they could be used to develop effective co-management schemes, thereby contributing to building smart and participatory edible cities.

Introduction: Childhood obesity is becoming an emerging public health issue as it is associated with increased morbidity and premature deaths. Determinants like the child’s household characteristics, maternal weight before the preconception stage, and maternal weight in childhood are studied. There is no study available to understand the association between overweight women of reproductive age and overweight children under five years of age. Studying these determinants to understand the problem can help in framing policies to intervene in the issue. Methods: The data for the study was collected from the National Family Health Survey 5 (NFHS5). It has been sub-grouped into urban and rural categories. The percentage of women with high-risk Waist-Hip-Ratio (WHR) and the percentage of overweight women were independent variables whereas the percentage of overweight under-five children was dependent. Simple linear regression, multiple linear regression, and Pearson correlation coefficient analysis were done for the collected data. Results: Study shows the percentage of overweight women has increased by 4.1%, and the percentage of overweight children has increased by 2% during the NFHS5 (2019-21) compared to NFHS4 (2015-16). Pearson correlation coefficient (R) is 0.5662 and Ꞵ-coefficient for multiple linear regression is 0.1397 for central obesity in women (%) and percentage of overweight children. Conclusion: Central obesity in women is more common than the overweight. Overweight in women as well as in children under five is increasing. Central obesity in women shows a moderate positive relation with overweight in children under five years.

Monte Carlo simulations were conducted to investigate the interaction between nucleation and the rates of chemical reduction in Au/Ag, Au/Pt and Au/Pd nanoparticles prepared in microemulsions using a one-pot method. The impact of nucleation on final nanostructure depends on the critical nucleus size value: at a high critical nucleus size, nucleation becomes the main factor in determining the final nanostructure, even with very large difference in reduction rates, as seen in the Au/Pd pair. However, when the critical nucleus size is small, the difference in reduction rates of the two metals becomes the key parameter determining the final nanostructure. Furthermore, the relevance of heteroatomic nucleation on the mechanism of nanoparticle formation depends on the difference between the reduction rates of the two metals. Smaller differences, such as in the Au/Ag or Au/Pt pairs, result in a greater impact of heteroatomic nucleation on the final nanostructure. In contrast, in the Au/Pd pair, heteroatomic nucleation becomes less important due to the low availability of Pd until late stages of synthesis. This study provides deeper insight into the complex mechanisms that govern reactions in microemulsions.

Background: Anterior cervical discectomy and fusion (ACDF) is a common procedure for cervical radiculopathy and myelopathy. Severe obesity (BMI ≥40 or BMI ≥35 with comorbidities) is associ-ated with increased perioperative risks. This study examines the impact of severe obesity on out-comes in patients undergoing single-level ACDF. Methods :Data from the Nationwide Inpatient Sample (2016-2019) were analyzed, including 85,585 patients who underwent single-level ACDF. Patients were classified as severely obese (n = 4,935) or non-obese (n = 80,650). Outcomes such as length of stay, complications, and in-hospital mortali-ty were compared using SPSS and MATLAB, with a significance level of p < 0.05. Results: Severely obese patients were younger (54 vs. 55.7 years, p < 0.001) and had more comor-bidities like type 2 diabetes (38% vs. 17.8%, p < 0.001) and obstructive sleep apnea (31.1% vs. 9.5%, p < 0.001). They experienced longer hospital stays (1.92 vs. 1.65 days, p < 0.001) but similar in-hospital mortality (0.1%, p = 0.506). Severe obesity was linked to higher odds of complications, the risk of developing dehiscence was 8.2 times higher in severely obese patients. Respiratory failure had an odds ratio of 6.5, while myocardial infarction showed an odds ratio of 5.5. Horner syn-drome was 4.7 times more likely to occur, and pulmonary edema had an odds ratio of 4.5. Dural tear risk was also significantly elevated, with an odds ratio of 4.1.The risk of developing acute kid-ney injury were 2.6 times higher, while the risk of pulmonary embolism was 2.5 times higher. Dysphonia was also more common in severely obese patients, with an odds ratio of 2.2. Conclusion: Severe obesity is associated with higher complication rates and longer hospital stays following ACDF. Tailored perioperative management is essential to mitigate risks and improve outcomes in this high-risk population.

Severe deficiency of ADAMTS13 (<10 iu/dL) is diagnostic of thrombotic thrombocytopenic purpura (TTP) and leads to accumulation of ultra-large VWF multimers, platelet aggregation and widespread microthrombi, which can be life-threatening. However, the clinical implications of a low ADAMTS13 activity level are not only important in an acute episode of TTP. In this article, we discuss the effects of a low ADAMTS13 activity in congenital and immune-mediated TTP patients not only at presentation, but once in a clinical remission. Evidence is emerging of the clinical effects of a low ADAMTS13 activity in other disease areas outside of TTP and here we explore the wider impact of low ADAMTS13 activity on the vascular endothelium and the potential for recombinant ADAMTS13 therapy in other thrombotic disease states.

Knowledge of local plant community characteristics is imperative for practical nature planning and management, and for understanding plant diversity and distribution drivers. Today, retrieving such data is only possible by fieldwork and is hence costly both in time and money. Here we used 9 bands from multispectral high-to-medium resolution (10–60 m) satellite data (Sentinel-2) and machine learning to predict the local vegetation plot characteristics at broad extent (approx. 30.000 km2) in terms of plants’ preferences for soil moisture, soil fertility, and pH, mirroring the levels of the corresponding actual soil factors. These factors are believed to be among the most important for local plant community composition. Our results showed that there are clear links between the Sentinel-2 data and plants abiotic soil preferences and using solely satellite data we achieved predictive powers between 26–59% improving to about 70% when habitat information was included as a predictor. This show that plants abiotic soil preferences can be detected quite well from space, but also that retrieving soil characteristics using satellites is complicated and that perfect detection of soil conditions using remote sensing – if at all possible – needs further methodological and data development.

Work disparities experienced by nurses in long-term care (LTC) can impact the retention, well-being, and health of this workforce. Despite the significant impact disparities experienced by nurses have on the workforce and LTC sector, a review of the available literature on work disparities has not been conducted on work disparities experienced by nurses in LTC. Consequently, this scoping review aimed to explore the nature and extent of research on meso-level work disparities experienced by nurses in LTC and how such disparities are linked with nurse health and well-being. Five databases were searched: MEDLINE (Ovid), EMBASE (Ovid), PsycINFO (Ovid), and CINAHL (EBSCO host). Of the 5,652 articles retrieved, 16 studies published between 1997 and 2024 met the inclusion criteria. The average number of work disparities within each study was 3.06 (minimum = 1, maximum = 6, SD = 1.62). Types of work disparities across the 16 studies were work opportunities (n = 19), work treatment (n = 18), job security (n = 8), and work compensation (n = 8). Only four articles investigated the association of a work disparity with a variable of health and well-being. Future research on how macro-level disparities intersect with meso-level work disparities may inform a contextual understanding of how disparities transpire in the work of nurses in LTC. Studies are required to address the gaps in knowledge regarding how work disparities negatively influence the health of nurses to inform better retention, well-being, and health of nurses in LTC.

IL1RA intron 2 86-bp repeat and IL4 intron 3 70-bp repeat are VNTRs that have been associated with various diseases, but their role in obesity is elusive. The objective of this study was to investigate the association of IL1RA and IL4 VNTRs with obesity and adiposity in 315 Malaysian subjects (128 M/187 F; 23 Malays/251 ethnic Chinese/41 ethnic Indians). The allelic distributions of IL1RA and IL4 were significantly different among ethnicities, and the alleles were associated with total body fat (TBF) classes. Individuals with IL1RA I/II genotype or allele II had greater risk of having higher adiposity - even after controlling for ethnicity [Odds Ratio (OR) of I/II genotype = 12.21 (CI = 2.54, 58.79; p = 0.002); II allele = 5.78 (CI = 1.73, 19.29; p = 0.004)]. However, IL4 VNTR B2 allele was only significantly associated with overall adiposity status before adjusting for ethnicity [OR = 1.53 (CI = 1.04, 2.23; p = 0.03)]. TBF was also significantly higher in those with IL1RA II allele compared with I allele (31.79 ± 2.52 vs. 23.51 ± 0.40; p = 0.005). Taken together, IL1RA intron 3 VNTR seems to be a genetic marker for overall adiposity status in Malaysian subjects.

L-cysteine, a precursor of essential components for plant growth, is synthesized by the cysteine synthase complex, which includes O-acetylserine(thiol) lyase (OAS-TL) and serine acetyltrans-ferase. In this work, we investigated how S-benzyl-L-cysteine (SBC), an OAS-TL inhibitor, affects the growth, photosynthesis, and oxidative stress of Ipomoea grandifolia plants. SBC impaired gas exchange and chlorophyll a fluorescence, indicating damage that compromised photosynthesis and reduced plant growth. Important parameters such as light-saturated net photosynthetic rate (PNmax), light saturation point (LSP), maximum carboxylation rate of Rubisco (Vcmax), electron transport rate (J), and triose phosphate utilization (TPU) decreased as a result. The quantum yield of photosystem II photochemistry (ϕPSII) and the electron transport rate through PSII (ETR) also decreased, as did the stomatal conductance (gs) and the photochemical quenching coefficient (qP). Additionally, SBC decreased the maximum fluorescence yield (Fm), variable fluorescence (Fv), and chlorophyll index, indicating possible damage to the photosynthetic apparatus. SBC triggered oxidative stress by increasing reactive oxygen species, malondialdehyde, and conjugated dienes. We hypothesize that dysfunctions in the sulfur-containing components of the photosynthetic electron transport chain, such as the cytochrome b6f complex, ferredoxin, and iron-sulfur (Fe-S) centers are the cause of these effects, which ultimately reduce the efficiency of electron transport and hinder photosynthesis in I. grandifolia plants. In short, our findings suggest that targeting OAS-TL with inhibitors such as SBC could be a promising strategy for the development of novel herbicides.

Cancer and infectious diseases are two of the world's major public health problems. Gemcitabine (GEM) is an effective chemotherapeutic agent against several types of cancer. In this study, we developed macrocapsules by incorporating GEM into a chitosan matrix blended with magnetite and zeolite. The physico-chemical characterization of the precursor materials and the new delivery system was carried out by HRTEM-ED, XRD, FESEM-EDS, FT-IR, TGA, encapsulation efficiency (%E.E.) and release profiles at pH 7.4 and 5.0. Cell viability tests on A549 and H1299 cell lines and microbiological properties against staphylococcal strains were performed. Our results revealed the successful production of hemispherical capsules with an average diameter of 1.22 mm, a rough surface and characteristic FT-IR material interaction bands. GEM encapsulation rates exceeded 80%, and release profiles were well-controlled over 24 hours at tested pH levels. Notably, cell viability in H1299 cells was lower than the free GEM control. Moreover, the formulation exhibited potent antimicrobial activity against Staphylococcus epidermidis, highlighting its dual action as a chemotherapeutic and antimicrobial agent. This dual effect underscores the potential of these macrocapsules as innovative delivery system for treating lung cancer in patients who are also at risk of infectious diseases and who are immunosuppressed.

This is an exercise to explore the concentration of Lithium, Lithium-7 isotope and the possible presence of black dirty ice in the lunar surface using spectral data obtained from the Clementine mission. The main interest in tracing the lithium and presence of dark ice in the lunar surface are closely related to future human settlement missions in the Moon. We investigate the distribution of Lithium and 7 Li isotope on the Lunar surface, employing spectral data from the Clementine images. We utilized Visible (VIS-NIR) imagery at wavelengths of 450, 750, 900, 950, and 1000 nm, along with Near-Infrared (NIR-SWIR) at 1100, 1250, 1500, 2000, 2600, and 2780 nm, encompassing 11 bands in total. This dataset offers a comprehensive coverage of about 80% of the lunar surface, with resolutions ranging from 100 to 500 meters, spanning latitudes from 80°S to 80°N. In order to extract quantitative abundance of Lithium, ground truth sites were used to calibrate the Clementine images. Samples (12045, 15058, 15475, 15555, 62255, 70035, 74220 and 75075) returned from Apollo missions 12, 15, 16 and 17 have been correlated to the Clementine VIS-NIR bands and five spectral ratios. The 5 spectral ratios calculated synthesize the main spectral features of sample spectra that were grouped by their Lithium and 7 Li content using Principal Component Analysis. The ratios spectrally characterize substrates of anorthosite, silica-rich basalts, olivine-rich basalts and High-T mare basalts and Orange soils. Our findings reveal a strong linear correlation between the spectral parameters and the lithium content in the 8 Apollo samples. With the values of the 11 Clementine bands and the 5 spectral ratios for each of the 8 lunar soils we performed linear regression models to estimate the concentration of Lithium and 7 Li. Also, we calculated Digital Terrain Models (DTMs; Altitude, Slope, Aspect, DirectInsolation and WindExposition) from LOLA-DTM to discover relations between relief and spatial distribution of the extended models of lithium and 7 Li. The analysis was conducted in a mask polygon extracted from Lunar Orbiter Laser Altimeter (LOLA) and located around the Apollo 15 landing site. This analysis seeks to uncover potential 7 Li enrichment through spallation processes, influenced by varying exposure to solar wind. To explore the possibility of find ice mixed with regolithe (black ice) we used a spectral library (350-2500nm) form ices dirty with different concentration of volcanic particles.

Despite past efforts towards therapeutical innovation, cancer remains a highly incident and lethal disease, with current treatments many times lacking efficiency and leading to severe side-effects. Hence, it is imperative to develop new, more efficient, and safer therapies. Bee venom has proven to have multiple and synergistic bioactivities, including antitumor effects. Nevertheless, some toxic effects have been associated with its administration. To tackle these issues, in this work, bee venom-loaded niosomes were developed, for cancer treatment. The vesicles had a small (150.4 ± 3.7 nm) and homogeneous (PDI of 0.162 ± 0.008) particle size, and revealed good therapeutic efficacy in in vitro gastric, colorectal, breast, lung, and cervical cancer models, with GI50 values between 12.37 ng/mL and 14.72 ng/mL. Additionally, they also revealed substantial anti-inflammatory activity, with an IC50 of 28.98 ng/mL, effects that have been reported to be complementary to direct antitumor activity. Finally, the niosomes' safety was assessed, both in vitro, on skin, liver and kidney cells, and ex vivo, in a HET-CAM assay, and results showed that compound encapsulation increased its safety. Hence, small and homogeneous bee venom-loaded niosomes were successfully developed, with substantial anticancer and anti-inflammatory effects, making them potentially promising primary or adjuvant cancer therapies.

Microarray gene expression analysis is a powerful technique used in cancer classification and research to identify and understand gene expression patterns that can differentiate between different cancer types, subtypes, and stages. However, microarray databases are highly redundant, inherently nonlinear, and noisy. Therefore, extracting meaningful information from such a huge database is a challenging one. The paper adopts the Fast Fourier Transform (FFT) and Mixture Model (MM) for dimensionality reduction and utilizes the Dragonfly optimization algorithm as the feature selection technique. The classifiers employed in this research are Nonlinear Regression, Naïve Bayes, Decision Tree, Random Forest and SVM (RBF). The classifiers' performances are analyzed with and without feature selection methods. Finally, Adaptive Moment Estimation (Adam) and Random Adaptive Moment Estimation (RanAdam) hyper-parameter tuning techniques are used as improvisation techniques for classifiers. The SVM (RBF) classifier with the Fast Fourier Transform Dimensionality Reduction method and Dragonfly feature selection achieved the highest accuracy of 98.343% with RanAdam hyperparameter tuning compared to other classifiers.

The aim of the study was to assess the effects of an 8-week cognitive-motor training program on postural control and knee proprioception under single and dual-task conditions. Design: Randomized clinical trial. Methods: 20 healthy and physically active older adults (73.255.98 years) volunteered to participate and were randomly assigned into an experimental and a control group (EG and CG). Postural control was measured with the Romberg test, with open (RBOE), closed eyes (RBCE) and under unipodal dominant side (RUDL) conditions. Proprioception was assessed by measuring participants’ ability to reposition their dominant knee at 45º. Finally, performance on the cognitive task was measured through a subscale of the Barcelona Test called “categorical evocation in associations.” The EG and the CG completed 8-week training programme with two sessions the 30 minutes per week of postural control and proprioception exercises. The EG additionally included music in each session. Results: The results showed significant differences in both group at the postural control tests (RBOE and RBCE) and proprioceptive test post intervention. Conclusion: The 8-week training program had a positive impact on the post-intervention results for motor control and proprioception, but not on the results of the cognitive task. There were no significant differences between the groups that carried out sessions with or without music.

CD4 count recovery is the main goal for an HIV patient who initiated ART. Some patients respond positively to ART and attain CD4 count recovery, some patients might fail to recover their CD4 count due to non-adherence, treatment resistance, and virological failure, leading to HIV-related complications and death. The purpose of this study is to find the determinants of death in patients who failed to recover their CD4 count after initiating antiretroviral therapy. The data used in this study was obtained from KwaZulu-Natal, South Africa, where 2528 HIV-infected patients with a baseline CD4 count of 200 cells/ were initiated on ART. We used a Fine-Gray sub-distribution hazard and cumulative incidence function to estimate potential confounding factors of death, where CD4 count recovery was a competing event for failure due to death. Patients who were not suffering from tuberculosis were 1.33 times at risk of dying before attaining CD4 count recovery [aSHR 1.33; 95% CI (0.96-1.85] compared to those who had no tuberculosis. Rural patients had a higher risk of not recovering and leading to death [aSHR 1.97; 95%CI (1.57-2.47)] than those from urban areas. The patient’s tuberculosis status, viral load, regimen, baseline CD4 count, and location were significant contributors to death before CD4 count recovery. Intervention programs targeting HIV testing in rural areas for early ART initiation and promoting treatment adherence are recommended.

Pancreatic ductal adenocarcinoma (PDAC) is the fifth leading cause of cancer-related death in and presents the lowest 5-year survival rate for any form of cancer in the US. Only 20% of PDAC patients are suitable for surgical resection and adjuvant chemotherapy which remains the only curative treatment. Chemotherapeutic and genetherapy treatments are associated with adverse effects and lack specificity/efficacy. In this study we assess the oncolytic potential of immuno-oncolytic tanapoxvirus (TPV) recombinants expressing mouse monocyte chemoattractant protein (mMCP-1 or mCCL2), and mouse interleukin (mIL)-2, in human pancreatic BxPc-3 cells, using immunocompromised and CD-3+ T-cell reconstituted mice. Intratumoral treatment with TPV/∆66R/mCCL2 and TPV/∆66R/mIL-2 resulted in regression of BxPc-3 xenograft volume as compared to control in immunocompromised mice; mCCL-2 expressing TPV OV resulted in significant difference from control at p

Abstract—The static and fatigue analysis of plates with holes, made of 2D woven roving composites, is conducted. The parametrization of convex holes is proposed. Experimental results of specimens without holes and with different shapes of notches are discussed. The fatigue behaviour is considered with the use of the low cycle fatigue method. The analysis is supplemented by the numerical finite element modeling. The present work is an extension of the results discussed in the literature. The finite element modeling of plates with holes is presented in details in Ref [1-3] including also the problems of the accuracy. The experimental results and the form of specimens are shown in Ref [4]. Two parametrical description of static and fatigue behaviour of plates with holes characterizes the goal and the novelty of the paper. The fuzzy approach is employed to reduce the number of experimental data [5].

Invasive species represent an important agent of change and threat to native biological diversity due to their high ability to enter and establish themselves in natural or semi-natural ecosystems. Urban and peri-urban areas are an easy entrance door for invasive vegetal species firstly used as ornamental that can become naturalized. In this study, it was analysed the presence, frequency and distribution of invasive alien plant species in the urban, peri-urban and natural area surrounding the city of Córdoba, Southern Spain. Our research reveals the presence of 17 invasive plant species from 10 different families. It supposes the 35% of the invasive plant species detected in the Andalusia region, and 27% of Spain. The highest number was located in ruderal areas, following by abandoned crop fields, being phanerophytes the most abundant life-form. Regarding the native source area, the highest percentage come from the America continent. Data indicates that the use of non-native species as ornamental can enhance invader establishment, spread, and ecological impact, which can facilitate subsequent alien species success aided by global change conditions. Additionally, our results are a strong knowledge base for effective management strategies in the area and will help to addressing data gaps related to the distribution of alien species on a regional scale in the Mediterranean area.

Human endogenous retroviruses (HERV) are remnants of ancient retroviral infections that, over millions of years, became integrated into the human genome. While normally inactive, environmental stimuli such as infections have contributed to the transcriptional reactivation of HERV promoting pathological conditions including the development of autoimmunity, neurodegenerative disease and cancer. What infections then trigger HERV activation? Mycobacterium avium subspecies paratuberculosis (MAP) is a pluripotent driver of human disease. Aside from granulomatous diseases Crohn’s, sarcoidosis and Blau syndrome, MAP is associated with autoimmune disease: type one diabetes (T1D), multiple sclerosis (MS), rheumatoid arthritis and autoimmune thyroiditis. MAP is also associated with Parkinson’s disease. Autoimmune diabetes, multiple sclerosis and rheumatoid arthritis are the diseases with the strongest MAP/HERV association. There are several other diseases associated with HERV activation including diseases whose epidemiology and/or pathology would prompt speculation for a causal role of MAP. These include non-solar uveal melanoma, colon cancer, glioblastoma and amyotrophic lateral sclerosis (ALS). This article further points to MAP infection as a contributor to autoimmunity, neurodegenerative disease and cancer via unsilencing of HERV. We examine the link between the ever-increasing number of MAP- associated diseases, the MAP/HERV intersection with these diverse medical conditions and propose treatment opportunities based upon this association.

Badminton is one of the most popular racket sports played by children up to the elderly worldwide. Everyone can practice and play badminton as a leisure or competitive sport, regardless of age, experience, or skill level. It does not require physical contact among players and expensive equipment. Compared with closed-skill exercise (e.g., running, swimming), open-skill exercise (e.g., badminton, table tennis) has been reported to intervene more with cognitive function and prevent cognitive decline. In this review, we outline the characteristics of badminton’s beneficial effects on physical and cognitive aspects. The characteristics presented here indicate that intervention with regular badminton exercise could effectively improve cognitive function and prevent cognitive decline in the elderly.

Approximate entropy (ApEn) and sample entropy (SampEn) are statistical indices designed to quantify the regularity or predictability of time series data. Although ApEn has been a prominent choice for use in the analysis of non-linear data, it is currently unclear as to which method and parameter selection combination is optimal for its application in biomechanics. The goal of this research was to examine the differences between ApEn and SampEn related to center of pressure (COP) data during tandem standing balance tasks, while also changing the tolerance window, r. Six participants completed five, 30-second trials, feet-together and tandem standing with eyes-open and eyes-closed. COP data (fs = 60 Hz, downsampled from 1200 Hz) from ground reaction force platforms were collected. ApEn and SampEn were calculated using a constant vector length, i.e., m = 2, but differing values of r (tolerance window). For each of the participants, four separate one-way analysis of variance analyses (ANOVA) were conducted for ApEn and SampEn in the anterior-posterior (AP) and medial-lateral (ML) directions. Dunnett's intervals were applied to the one-way ANOVA analyses to determine which tandem conditions differed significantly from the baseline condition. ApEn and SampEn provided comparable results in the predictability of patterns for different stability conditions, with increasing instability, i.e., tandem eyes closed postures, being associated with greater unpredictability. The selection of r had a relatively consistent effect on mean ApEn and SampEn values across r = 0.15 * SD to r = 0.25 * SD, where both entropy methods tended to decrease as r increased. Mean SampEn values were generally lower than ApEn values. The results suggest that both ApEn and SampEn indices demonstrated relative consistency and were equally effective in quantifying the level of the center of pressure signal regularity during quiet tandem standing postural balance tests.

Photovoltaic shading devices (PVSDs) have the dual function of providing shade and generating electricity, which can reduce building energy consumption and improve indoor daylighting levels. This study adopts a parametric performance design method and establishes a one-click simulation process by using the Grasshopper platform and Ladybugtools. The research focuses on the effect of dynamic PVSDs on daylighting and energy consumption in an office building in Qingdao. Through simulation, the study calculates the monthly energy consumption and useful daylight illuminance (UDI) under different inclination angles and installation heights of PVSDs. And the optimal configuration of PVSDs for each month under three dynamic strategies (rotation, sliding, and hybrid) is determined. Additionally, different control strategies and fixed PVSDs are compared to clarify the impact of various control strategies on daylighting and energy consumption. The findings reveal that, compared to no shading, dynamic PVSDs in rotation strategy (with an installation height of 0 m), sliding strategy (with an inclination angle of 20°), and hybrid strategy can achieve energy savings of 32.13%, 47.22%, and 50.38%, respectively. They can increase the annual average UDI by 1.39%, 2.8%, and 3.1%, respectively.

Buildings are responsible for approximately 40% of global energy consumption, putting pressure on the construction industry to mitigate its environmental impact. Therefore, there is an urgent need for innovative solutions to reduce power consumption, particularly in lighting systems. The study’s primary objective was to investigate novel integrated lighting solutions that significantly reduce energy use and they explore their enhancement through Building Information Modeling (BIM) and the Internet of Things (IoT) to further improve energy efficiency and reduce the carbon footprint in buildings. Hence, this literature review aimed to examine energy-saving actions, retrofitting practices and interventions across a range of multi-use buildings worldwide over the past six years. The objective was to diagnose the goals being undertaken and ultimately validate new actions and contributions to minimise energy consumption. First, daylight harvesting and retrofitting solutions were examined in conjunction with the latest technologies, also referred to the external shadings. In consequence of this matter, comes the lack or unappropriated coordination, and so waste of energy, between daylight and electrical lighting. Secondly, how the integration of BIM facilitates the design process, providing a complete overview of all the variables of the building, thus improving indoor daylight performance and proper lighting with energy analysis. Lastly, the review addresses the role of IoT in providing real-time data from sensor networks, allowing for continuous monitoring of building conditions. This systematic literature review explores the integration of the fields to address the urgent need for innovative strategies and sustainability in the built environment. Furthermore, it thoroughly analyses the current state of the art, identifying best practices, emerging trends and concrete insight for architects, engineers, and researchers. The goal is to promote the widespread adoption of low-carbon systems and encourage collaboration among industry professionals and researchers to advance sustainable building design.

The common house mosquito (Culex pipiens) is a native vector for West Nile virus (WNV). Invasive species like the tiger mosquito (Aedes albopictus) and Asian bush mosquito (Aedes japonicus) are rapidly spreading through Europe, posing a major threat as vectors for dengue, chikungunya (CHIKV), and Japanese Encephalitis virus (JEV). These mosquitoes share a similar ecological niche as larvae, but the carry-over effects of aquatic larval interactions to terrestrial adult stage remain largely unknown and their medical relevance requires further investigation. This study examines the context-dependency of larval interactions among Aedes albopictus, Aedes japonicus and Culex pipiens. The survival, development time, growth, and energetic storage were measured in different European populations within density-response experiments (intraspecific) and replacement experiments (interspecific) at 20°C and 26°C. Overall, Ae. japonicus was the weakest competitor, while competition between Ae. albopictus and Cx. pipiens varied with temperature. Culex pipiens was infected with WNV, Ae. albopictus with CHIKV and Ae. japonicus with JEV. While no JEV infection was observed, mosquitoes experiencing interspecific interactions during their larval stages exhibited higher infection rates and viral RNA titers for CHIKV and WNV. This increased susceptibility for viral infection after larval competition suggests a higher risk of arbovirus transmission in co-occurring populations.

This study examines HIV/AIDS-associated knowledge and attitudes towards treating disadvantaged communities among predoctoral dental students in U.S. dental schools who had not yet commenced their Community-Based Dental Education (CBDE) training. It also compares the difference in knowledge and attitudes between students with reported community engagement with PLWHA, and those without. Our study comprised 89 predoctoral dental students within their D1-D3 years of dental school who had not yet initiated their Community-Based Dental Education (referred to as pre-CBDE dental students). Responses were collected via an online survey. Participants were 68% females, 94% heterosexual, of mean age (years): 25.9 ± 3.5 SD. The majority (62%) were in their first (D1) and second (D2) years of dental education. Of the thirty knowledge questions, only five received a minimum of 90% correct responses. Similarly, we found no statistical differences in most of the knowledge/attitude sections, between those with and without prior PLWHA exposure. Encouragingly, 90% of our participants reported prior experience working with disadvantaged communities. Early community engagement fosters a sense of professional responsibility towards administering dental care to disadvantaged communities and we propose that it must be encouraged among aspiring dental school students.

Bulinus snails surviving drought play a key role in seasonal transmission of urogenital schistosomiasis although our knowledge of their adaptation to dry season is still limited. We investigated the survival dynamic and infestation by Schistosoma haematobium of Bulinus snails during the dry and rainy seasons in a single pond in an area of seasonal schistosomiasis transmission in Senegal. Additionally, their aestivation capacity was evaluated under semi natural conditions. During the rainy season, of the 104 specimens collected, 98 (94.23%) and 06 (5.76%) were identified as B. senegalensis and B. umbilicatus, respectively. In the dry season, B. umbilicatus outnumbered B. senegalensis, however, all 5 (100%) B. senegalensis collected were viable and alive after interruption of aestivation by immersion in water while only 7 of 24 (29.16%) B. umbilicatus collected emerged from their dormant state. The adaptation of B. senegalensis and B. umbilicatus to the rainy and dry seasons, respectively, was also observed in semi-natural conditions. The rate of infestation with S. haeamatobium during the rainy season was 18.2% (19/104) while all the viable snails collected during the dry season were negative. B. senegalensis and B. umbilicatus have different seasonal dynamics with no evidence of maintaining S. haematobium infestation during the drought. Further studies including more survey sites and taking account both snails biology and ecological conditions are needed to better understand snail adaptation to seasonal changes and their ability to maintain S. haeamatobium infestation during drought.

This work mapped the research chronology and conceptual trends on conservation agriculture-soil health-sustainable development goals nexus by analyzing data from related literature. This is the first-time different bibliometric methods such as VOSviewer, Flourish, as well as Bibliometrix and Biblioshiny models in RStudio were simultaneously used to investigate the research impacts and/or interactions between conservation agriculture (CA), soil health and sustainable development at global scale. On 20th February 2024, a search was launched on the web of science core collection using related search terms to extract relevant data. After the screening and elimination, the search produced 835 papers which were used in the bibliometric analysis. The revealed that USA (31%), India (27%), Australia (7%), England (6%), China (6%), Canada (5%), and other countries had below 5% of the published documents. Many of the papers covered zero hunger (38%), climate action (30%), life on land (26%), while other SDGs had relatively low coverage. The study found the adoption of no till, cover cropping, and organic amendments by the authors as the common CA practices. The hybrid bibliometric approach provided a clear roadmap in understanding the global research trajectory on CA-soil health and SDGs nexus, as well as the roles of countries, authors, institutions, publishing journals. This knowledge could support in championing future debates on CA potential for effective discussion and policies, especially in the developing countries where there have been low publications.

The terrestrial subsurface harbors unique microbial communities that play important biogeochemical roles and allows studying a yet unknown fraction of the Earth’s biodiversity. The Saint-Leonard cave in Montreal city (Canada) is of glaciotectonic origin. Its speleogenesis traces back to the withdrawal of the Laurentide Ice Sheet, 13 000 years ago, during which the moving glacier dislocated the sedimentary rock layers. Our study is the first to investigate the microbial communities of the cave. By using amplicon sequencing, we analyzed the taxonomic diversity and composition of bacterial, archaeal and eukaryotes communities living in the groundwater (0.1µm- and 0.2µm-filtered water), in the sediments and in surface soils. We identified a microbial biodiversity typical of cave ecosystems. Communities were mainly shaped by habitat type and harbored taxa associated with a wide variety of lifestyles and of metabolic capacities. Although we found evidence of a geochemical connection between the above soils and the cave’s galleries, our results suggest that the community assembly dynamics are driven by habitat selection rather than dispersal. Furthermore, we found that the cave’s groundwater, in addition to being generally richer in microbial taxa than sediments, contained a considerable diversity of ultra-small bacteria and archaea.

This paper presents a new optimization algorithm to control the voltage of power system generators by the simultaneous tuning of the parameters of Automatic Voltage Regulator (AVR) and Power System Stabilizer (PSS) using a new technique called Particle Swarm Optimization with Periodic Oscillating Exponential Decay (PSO - POED). The proposed algorithm was applied to both the Single-Machine Infinite-Bus (SMIB) Power System and the 9-Bus Multi-Machine Power System. The results of the simulation show that the proposed method is efficient and guarantees an improvement in the dynamic stability and convergence rate of the simulations.

There is currently an exponential growth in the electric vehicle market, which will require an increase in the electrical grid capacity to meet the demand of charging. If, on the one hand, the introduction of energy generation from renewable sources can be used to meet that requirement, the intermittent nature of some of these sources poses challenges to the required real time equilibrium between generation and consumption. The impossibility of controlling generation from some of these sources leads to the attempt of controlling and manage the consumption of electricity, according with the levels of generation. In this context, the emergence of smart grids has introduced mechanisms that guarantee a balance between consumption and generation of electricity. One of these mechanisms is the smart charging of electric vehicles. Effective smart charging relies on communication between the supply equipment and the electric vehicle, en-abling the adjustment of the energy transfer according with the generation levels. Thus, there is a necessity for a standardised system that guarantees this communication. In this context, the ISO 15118 standard, allows high level communication mechanisms, much beyond the basic control solutions offered by the IEC 61851-1 specification. In this context, this paper presents the development of a charge emulation system, based on the ISO 15118 communication protocol and discusses its application for demand response purposes.

Circulating cell-free DNA (cfDNA) refers to small fragments of DNA molecules released after programmed cell death and necrosis in several body fluids such as blood, saliva, urine, and cerebrospinal fluid. The discovery of cfDNA has revolutionized the field of non-invasive diagnostics in the oncologic field, in prenatal testing, and in organ transplantation. Despite the potential of cfDNA and the solid results published in recent literature, several challenges remain, represented by low abundance, need for highly sensitive assays and analytical issues. In this review, the main technical advances in cfDNA analysis are presented and discussed, with a comprehensive examination of the current available methodologies applied in each field. Considering the potential advantages of cfDNA, this biomarker is increasing its consensus among clinicians, as it consents to monitor patients’ conditions in an easy and non-invasive way, offering a more personalized care. Nevertheless, cfDNA analysis is still considered a research marker to be further validated, and very few centers are implementing its analysis in the real-life assistance. As technical improvements are enhancing the performances of cfDNA analysis, its application will transversally improve patients’ quality of life.

Working capital management (WCM) is critical because it affects a company's profitability, liquidity, and investment decisions, all of which have an impact on financial performance. As a result, effective and efficient working capital management is an essential component for commercial and service businesses. Given the importance of the commercial and services industries to the Kenyan economy, the goal of this research was to look into the impact of working capital management on the financial performance of these firms, particularly those listed on the Nairobi Securities Exchange (NSE), from 2003 to 2022. Working capital management was measured using the average age of inventory, average collection period, average payment period, and cash conversion cycle, whereas financial performance was measured using return on asset, return on equity, and net operating profit margin. Using panel regression analysis, the results showed that the average inventory age, average collection period, average payment period, and cash conversion cycle were all negatively related to financial performance for NSE-listed commercial and services firms. Based on the findings, it is recommended that Kenyan commercial and services firms adopt prudent optimal working capital management practices in order to improve firm financial performance and maximize shareholder wealth.

This study introduces an advanced method for climate downscaling using a Super-Resolution Generative Adversarial Network (SRGAN), referred to as Elevation-integrated TEmperature and Precipitation SRGAN downscaling (E-TEPS), to enhance the spatial resolution of climate data, specifically 2m-temperature above the surface and total precipitation, from the high-resolution Euro-Mediterranean Center on Climate Change (CMCC) dataset over Italy. Traditional Numerical weather prediction (NWP) as well as global climate models (GCMs) generally lack the resolution required for local applications, and this research addresses that gap by refining GCM outputs to provide detailed local climate insights. E-TEPS incorporates elevation maps as auxiliary inputs, significantly improving the accuracy of downscaled temperature and precipitation data. Utilizing Google Cloud's computational resources, the model processes large climate datasets and runs complex training operations efficiently. The system is exceptionally fast, delivering all results in under 10 seconds. The model demonstrates superior performance over two interpolation methods (bicubic and linear), used as traditional downscaling methods, achieving lower Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE), higher Pearson Correlation for temperature, and higher agreement values for the precipitation. Visual comparisons confirm that E-TEPS generated high-resolution outputs exhibit fewer artifacts and better detail preservation, particularly in regions with complex terrain and variable climatic conditions. These findings underscore the potential of our model in delivering precise, high-resolution climate predictions, thereby enhancing the performance of early-warning systems and supporting more effective climate-related decision-making. This paper is the first part of a two-part series; the second part will demonstrate the integration of this downscaling method with the FourCastNet global forecasting model to enhance climate predictions at a regional level, particularly focusing on high-resolution forecasts for Italy.

Investments in small and medium-sized anaerobic digestion facilities have the potential to boost biogas production in Greece and other EU countries. This study aimed to evaluate the economic feasibility of anaerobic digestion facilities equipped with combined heat and power (CHP) units ranging from 50 to 400 kW, while treating livestock waste. For this purpose, data were gathered from various livestock operations (dairy cattle, poultry, swine, dairy sheep and goat) regarding their annual production, revenues, electricity and fuel usage, and waste generation. Waste samples were then collected and analyzed to assess their biochemical methane production potential. The capital and operational costs of anaerobic digestion facilities, from 50 and 400 kW, were calculated using the equations developed within the “eMT cluster” project. Findings indicate that current feed-in tariffs (FIT) of 0.21 € kWh-1 are insufficient to incentivize investment in anaerobic digestion facilities with capacities below 250 kW, highlighting the need for increased FIT rates or capital expenditure subsidies. Recommendations include shifting towards simplified technology and business models with reduced farmer involvement, coupled with supportive legislative framework and long-term electricity price guarantees. These measures are expected to foster the implementation of anaerobic digestion projects in the animal husbandry sector.

.With the increasing use of carbon fiber reinforced plastics in various area, carbon fiber composites based on prepregs have attracted attention in industries and academia research. However, prepreg manufacturing processes are costly, and the strength of structures varies depending on the orientation and defects (pores and delamination). For non-contact evaluation of internal defects, we proposed lock-in infrared thermography to investigate orientation angles after a compression test. We also conducted a drop-weight impact test to study the behaviour of the composites after impact according the fibers orientation for composite fabricated using unidirectional carbon fiber prepregs. Using CAI tests, we determined the residual compressive strength and confirmed the damage modes using a thermal camera. The results of the drop weight impact tests show that the specimen laminated at 0° suffered the largest damage because of susceptibility of the resin to impact. In contrast, the specimens oriented in of 0°/90° and +45°/–45° directions transferred more than 90% of the impact energy back to the impactor because of the lamination of fibers in the orthogonal directions. Furthermore, the specimens that underwent complete damage in the impact tests were subjected to the lock-in method and showed internal delamination and cut fibers. With the finite elements analysis, the damage of each ply could be observed. Moreover, the temperature differences in the residual compression tests were not significant.

Carbon capture, utilization, and storage (CCUS) considered a the key strategy for reducing the emissions of anthropogenic carbon dioxide from power generation plants, can be achieved by three main technologies: oxy-fuel combustion, pre-combustion, and post-combustion capture. Post-combustion carbon capture (PCC), where CO2 is removed after the fuel burning, is a crucial solution for reducing greenhouse gas emissions from natural gas power plants (NGPPs). However, high costs and energy penalties associated with PCC technologies hinder their widespread adoption. Recent advancements in hybrid PCC configurations have shown promise in improving efficiency and reducing costs. In effect, six PCC hybrid configurations below were identified as feasible process routes: • 2S-AB +AD: Two-stage Absorption + Adsorption hybrid • 2S-AB +MB: Two-stage Absorption + Membrane hybrid • 2S-AD +AB: Two-stage Adsorption + Absorption hybrid • 2S-AD +MB: Two-stage Adsorption + Membrane hybrid • 2S-MB +AB: Two-stage Membrane + Absorption hybrid • 2S-MB +AD: Two-stage Membrane + Adsorption hybrid Each hybrid has its own technical and economic challenges that need to be investigated in order to identify the best technique for carbon capture. In this paper, we performed Aspen Hysys design simulation of the six hybrids PCC configurations and also their economic evaluations using parameters like investment costs, operating costs, net present value, and rate of return, culminating in the use of three assessment parameters namely, levelized cost of electricity (LCOE), carbon emission intensity (CEI) and cost of carbon avoidance (COA), to evaluate the six hybrids PCC configurations and to determine the most viable option. Overall, it was found by dimensional analysis that the post combustion carbon capture using 2S-MB +AB: Two-stage Membrane + Absorption hybrid is the most viable for capturing CO2 from power generation plants and is hereby recommended. However, the choice of materials (membranes and absorbents) needs to be evaluated so as determined the best optimal configuration for commercialization.

With the development of human-computer interaction, the importance of emotion recognition is increasing. Emotion recognition technology provides practical benefits in various industries such as improving user experience, education, and organizational productivity. In education, emotion recognition can enable real-time understanding of students' emotional states and provide tailored feedback, and in the workplace, by monitoring employees' emotional states, it can improve work performance and job satisfaction. Therefore, multimodal-based research that combines text, speech, and video data for emotion recognition is being conducted in various industries. In this study, we propose an emotion recognition method that combines text and speech data, reflecting the characteristics of the Korean language. For text, KoELECTRA is used to perform embedding, and for speech, MFCC and pitch analysis are used to extract features. Finally, a multimodal transformer model is proposed that combines these two data types to perform emotion recognition. The multimodal transformer model processes text and speech data separately, and then learns the interaction between the two modalities through a Cross-Modal Attention mechanism. Through this, the complementary information from text and speech is effectively combined, improving emotion recognition performance. Experimental results show that the proposed model outperforms single-modality models, achieving a high accuracy of 73.13% and an F1-Score of 0.7344 in emotion classification. This study contributes to the advancement of emotion recognition technology by combining various language and modality data, and higher performance can be expected through the integration of additional modalities in the future.

To control the volatility and reduce the electricity costs for indoor farming, the agrivoltaics agrotunnel introduced here uses: 1) high insulation for a building dedicated to vertical growing, 2) high-efficiency LED lighting, 3) heat pumps (HPs), and 4), solar photovoltaics (PV) provide known electric costs for 25 years. In order to size the PV array, this study develops a thermal model for agrotunnel load calculations and validates it using the Hourly Analysis Program and measured data so the effect of plants’ evapotranspiration can be included. HPs are sized, plug loads (i.e., water pump energy needed to provide for the hybrid aeroponics/hydroponics system, DC power running the LEDs hung on grow walls, and dehumidifier assisting in moisture condensation in summer) are measured/modeled. Ultimately, all models are combined to establish an annual load profile for an agrotunnel that is then used to model the necessary PV to power the system throughout the year. The results find that agrivoltaics to power an agrotunnel range from 40 to 50kW and make up an areas from 3.2 to 10.48 m²/m² of an agrotunnel footprint. Net zero agrotunnels are technically viable although future work is needed to deeply explore the economics of localized vertical food growing systems.

In this study, a new diphosphate compound, Ag0.2Na0.6FeP2O7, was synthesized using a solid-state reaction method and extensively studied using various techniques. The compound's structure was confirmed through X-ray diffraction analysis, revealing a single-phase monoclinic structure with the P21/C space group. The electrical behavior of the compound was investigated, and its conductivity followed Jonscher's universal law. The correlated barrier hopping (CBH) model explained the temperature-dependent ac conductivity and parameter "s" well. The study also explored the contribution of single-polaron and bipolaron hopping to the a.c. conductivity and discussed the ionic conductivity in relation to the structural characteristics of the sample. Overall, this investigation significantly enhances our comprehension of the distinctive electrical properties of Ag0.2Na0.6FeP2O7 and its potential practical applications.