The introduction of Artificial Intelligence (AI) has fundamentally transformed digital advertising, advancing precision, efficiency, and scalability far beyond the capabilities of traditional advertising methods. This paper presents a detailed analysis of AI’s integration into the advertising sector, focusing on critical technologies, including multi-touch attribution (MTA), reinforcement learning (RL), recommendation systems (RS), and large language models (LLMs). We examine the evolution of AI in digital marketing, explore current trends, and assess emerging technologies such as federated learning and transfer learning, emphasizing their role in real-time ad personalization, campaign optimization, and enhanced user engagement. Through an exploration of AI-driven strategies used by major corporations such as Google, IBM, and Coca-Cola, this paper underscores AI’s transformative impact on advertising and anticipates future trends that may further revolutionize the field. Additionally, we address key challenges of deploying AI at scale, including issues of interpretability, ethical considerations, and data privacy, offering potential solutions.

The article addresses the issues of scalability and security in blockchain networks, with a focus on sharding algorithms and decentralized data storage. Key challenges include the low throughput and high transaction latency in public networks such as Bitcoin and Ethereum. Sharding is examined as a method to enhance performance through data distribution, but it raises concerns regarding node management and reliability. Sharding schemes, such as Elastico, OmniLedger, Pyramid, RepChain, and SSchain, are analyzed, each presenting its own advantages and drawbacks. Alternative architectures like Directed Acyclic Graphs (DAG) demonstrate potential for improved scalability but require further refinement to ensure decentralization and security. Protocols such as Brokerchain, Meepo, AHL, Benzene, and CycLedger offer unique approaches to addressing performance and transaction consistency issues. The article emphasizes the need for a comprehensive approach, including dynamic sharding, multi-level consensus, and inter-shard coordination. Additionally, a conceptual model is proposed that incorporates sharding of transactions, states, and networks, which enables greater scalability and efficiency.

Ipfs and public peer-to-peer (P2P) networks were adopted to make AI calculations more decentralized. Taking AI workloads over a decentralized network could bring better fault tolerance, guarantee data safety, and increased privacy. This research explores the challenges of centralized AI, such as data confidentiality, scalability, and accessibility, while discussing the promise of decentralized AI. Combining IPFS with decentralized systems improves scalability, data protection, and fault tolerance.

Agro-industrial lignocellulosic waste can be bioconverted to fungal biomass and then utilized as a high nutritional value food alternative for ruminants, with potential for ruminal methane (CH4) mitigation. This study was carried out to evaluate the changes in the enzymatic expression and nutritional value of palm kernel cake fermented with Pleurotus ostreatus (FPKC), as well as the differences in the in vitro fermentation parameters and methane production in diets based on tropical forages with the inclusion of 20% FPKC. The highest activity of laccases and cellulases occurred on day 13 with values of 0.75 ± 0.09 U/g and 266.7 ± 20.8 U/g; respectively. The biological pretreatment decreased the contents of (p< 0.05) neutral detergent fiber (NDF), acid detergent fiber (ADF) and lignin (LIG) by 29%, 20.5% and 46.6% respectively, while those of crude protein (CP) increased by 69.65%. The inclusion of FPKC resulted in increases (p

Climate Change is among the greatest threats to health in the 21st century, requiring urgent scale-up of adaptation interventions. We aim to summarize adaptation interventions that were funded by the Belmont Forum and the European Union, the largest global funders of climate change and health research. A systematic search was conducted (updated February 2023) to identify articles on adaptation interventions for health within this funding network. Data extracted included study characteristics, types of interventions, and study outcomes. Results were synthesised narratively within the PRISMA-ScR guidelines. 197 articles were screened, with 37 reporting on adaptation interventions. The majority of interventions focused on the general population (n=17), with few studies examining high-risk populations such as pregnant women and children (n=4) or migrants (n=0). Targeted interventions were mostly aimed at behaviour change (n=8) and health system strengthening (n=6), while interventions with mitigation co-benefits such as nature-based solutions (n=1) or the built environment (n=0) were limited. The most studied climate change hazard was extreme heat (n=26). Several studies reported promising findings, principally on interventions to counter heat impacts in workers and pregnant women, and improving risk awareness in communities. These findings provide a platform on which to expand research and public health interventions towards safeguarding public health from the effects of climate change.

This study examines the relationship between safety climate and safety performance in large-scale construction sites in Ethiopia. A cross-sectional survey was conducted among 1,203workers from 22 large-scale construction sites. The Nordic Safety Climate Questionnaire was administered using interviews. A model was hypothesized to determine the interrelations between safety climate and performance; examined and validated using confirmatory factor analysis. The results show that the mean score of the seven safety climate dimensions was low: 2.70, ranging from 2.33 to 3.08. Similarly, the mean score of the safety performance construct was 2.95 for safety participation and 3.58 for safety compliance. The model predicts a strong positive correlation between safety climate and the safety performance constructs with 29.2% of the variance in safety involvement and 28.6% of the variance in safety compliance. The suggested association between self-reported injuries and safety climate was not confirmed. Nonetheless, a Pearson correlation analysis demonstrates a statistically significant negative correlation with safety climate. In conclusion, a low score for all the safety climate dimensions shows safety in the construction sector needs improvement. Safety climate positively influences employees’ safety behavior (safety compliance and safety participation) and minimizes occupational injuries.

This paper investigates the transformative potential of integrating technical and methodological tools such as GraphQL, openEHR, Redis, and Pervasive Business Intelligence in healthcare. Modern healthcare systems face data silos, interoperability, and efficient data communication challenges. The integration of these technologies offers innovative solutions to address these challenges. GraphQL, known for its flexible data retrieval capabilities, simplifies data communication and integration. openEHR, a standards-based approach to healthcare data management, fosters interoperability through an unified data model. Redis, a scalable data storage and caching system, enhances application performance and real-time data processing. Pervasive Business Intelligence empowers healthcare analytics, aiding data-driven decision-making. This paper explores these technologies’ benefits, integration possibilities, and synergies. The practical implications of this integration are demonstrated through a real-world case study. The findings underscore the potential to revolutionise healthcare data management, communication, and analysis, improving patient care and operational efficiency.

Achieving Foot-and-Mouth Disease (FMD)-free status without vaccination marks a significant milestone for Brazil, a major agricultural powerhouse with extensive cattle herds and vast borders. This certification represents not only a scientific and logistical achievement but also an oppor-tunity for enhanced market access and strengthened biosecurity. However, transitioning to this status involves challenges, including maintaining stringent monitoring and surveillance, man-aging porous border regions, and mitigating risks from neighboring regions with varying FMD statuses. This review explores the expectations surrounding Brazil’s new status, including antic-ipated economic benefits, the influence on Brazil’s international trade position, and the role of sustainable disease management practices. We also discuss potential risks, such as accidental re-introduction and surveillance gaps, which could impact livestock health and trade dynamics. With a focus on effective biosecurity, regional cooperation, and advanced diagnostic capabilities, Bra-zil’s journey to maintaining FMD-free status highlights both the opportunities and complexities of disease control in a nation deeply reliant on its agricultural sector. This status demands ongoing surveillance to support Brazil’s agricultural economy and ensure long-term health security for its livestock industries.

This study proposes indicators based on urban, demographic, and hydrological parameters to assess the effectiveness of low-impact development (LID) techniques, such as rooftop rainwater harvesting, aimed at reducing water scarcity in a residential area vulnerable to water shortages in a semi-arid city in the Global South. In the study area, the necessary water demand is identified according to land use requirements established by national and local regulations, and an urban configuration pinpoints spaces suitable for rainwater harvesting for self-consumption. Additionally, hydrological design conditions are defined to evaluate the potential volumes of recoverable water. Accordingly, indicators of infiltrated water, availabel water for consumption, runoff water, and sufficient water are established, enabling the proposal of strategies to mitigate water scarcity and enhance water management.

(1) Background: A new type of capillary refill time measurement system is proposed to be designed to achieve non-invasive, mechanised and standardised measurement of the microcirculatory status of the human body; (2) Methods: First, a mechanical measurement device based on electromagnetic pressurisation technology was designed for the measurement of microcirculation monitoring indexes such as capillary refill time, and the measurement control logic was set based on clinical application scenarios; second, the haemoglobin content in the arterial blood flow in the distal capillary bed was continuously monitored, and a software system was designed for the automatic acquisition, transmission, analysis, computation, and storage of the raw data and noise removal algorithms were proposed for the mutational noise present in the data; finally, healthy adult subjects were recruited to carry out a preliminary clinical observational study to evaluate the reproducibility and reliability of the measured parameters; (3) Results: A capillary refill time meter test machine was developed with good CRT reproducibility, both between different observers and between different numbers of observations for a uniform observer; (4) Conclusions: Rapid non-invasive monitoring of microcirculation has been successfully achieved, making non-invasive monitoring of microcirculation further mechanised and standardised, with the advantages of simple measurement and high accuracy.

The use of centrifugal pumps for water supply and distribution applications is evident in every industry as they efficiently transport fluid from a certain point. However, the sector faces severe concerns regarding its operating efficiency due to accumulated losses and sudden power consumption growth. Thus, it is crucial to find a remedy to mitigate these concerns and improve the performance of the centrifugal pump. This study aims to provide an improved design of centrifugal water pumps by analyzing the effects of changing its design parameters. Splitter blades, with a length of 80% of the main blade, will be included in the design. Using ANSYS software to generate a baseline design model, CFD analysis will be conducted. Then, an optimization study will be performed using the Response Surface Method (RSM) to formulate an optimized design. Results indicate that finding a perfect balance between the placement of the splitter blades, the design of the volute tongue clearance and thickness, and configuring the ellipse ratio of the splitter blades improves the pump's performance. The optimal design results in 27.35%, 15.70%, 28.18%, 16.67%, and 8.36% improvement in total efficiency, total head, static efficiency, static head, and power consumption, respectively.

In the AQbD framework, DOE plays a very important role as it provides information about how experimental input variables influence the critical method attributes. Based on the information obtained from the DOE, mathematical models are generated and used to build the MODR a robust region of operability. Data treatment steps are usually carried out in software such as Fusion QbD, Minitab, StaEase 360, among others. Although there are many papers in the literature using DOE, none of them address important aspect of data treatment for optimization and MODR generation and compare different software calculations. The purpose of this study is to contribute to a better understanding of data treatment aspects that are frequently misread or not fully understood, such as model selection, ANOVA results and residual analysis. The discussion will be guided using the separation of curcuminoids by ultra-high performance liquid chromatography and eight quality attribute as responses. The results highlighted the importance of the correct selection and evaluation of the models due to their influence the generation of the MODR and emphasizes the insertion of the uncertainty in the contour plots to proper obtain the MODR regarding the definitions of the USP General Chapter &lt;1220&gt; and ICH Q14 guidelines.

Falls among older adults pose significant public health challenges associated with severe physical, psychological, and economic consequences. Exercise interventions are crucial for reducing fall risk through diverse biomechanical, physiological, and psychological mechanisms. This integrative review synthesizes evidence from systematic reviews, meta-analyses, randomized controlled trials, and cohort studies published between 2004 and 2024, sourced from databases including PubMed, MEDLINE, EBSCO (EDS), and Google Scholar. Key findings highlight that balance and strength training enhances postural control, gait stability, and joint mobility while promoting neuromuscular coordination. Resistance training is particularly effective in mitigating sarcopenia and improving muscle strength and joint function, aiding quick responses to balance perturbations. Cognitive exercises enhance attention, spatial awareness, and decision-making, reinforcing fall prevention. Psychological benefits include reduced fear of falling, increased confidence, improved mood, support adherence and social engagement, and sustaining physical activity. Holistic models demonstrate the efficacy of integrating physical, cognitive, and social elements for comprehensive fall prevention. The review emphasizes the importance of multidisciplinary strategies and underscores the need for continued cross-disciplinary research to refine evidence-based practices that optimize outcomes for older adults, thereby highlighting the ongoing nature of the research and the potential for further advancements in the field.

This paper presents a novel approach to relativistic kinetic energy through the lens of the Hypergeometrical Universe (HU) Theory, introducing an Absolute Reference Frame (ARF) that fundamentally reinterprets the Lorentz transformation. HU suggests that the physics underlying Lorentz transformations is not an intrinsic time dilation or relativistic mass increase but rather an Absolute-Velocity-Dependent Force. This force diminishes at high velocities, effectively tapering off particle interactions and yielding a bounded kinetic energy that matches classical expectations at the speed of light: KE = mc**2 /2. This model contrasts sharply with conventional relativity, which predicts unbounded kinetic energy as velocity approaches c. This theoretical divergence finds a compelling empirical anchor in the unusual case of Soviet scientist Anatoli Bugorski, who survived exposure to a high-energy proton beam. While relativistic models would predict an energy deposition near 4.6 kJ, likely resulting in fatal damage, Bugorski’s injuries aligned closely with HU’s prediction of a capped energy deposition, around 0.285 J. The HU model explains this outcome as a natural consequence of diminished force interactions at relativistic speeds, leading to reduced energy transfer upon impact. This reframing has significant implications for high-energy physics and particle penetration in solid materials. According to HU, reduced force efficiency at high velocities leads to phenomena traditionally interpreted as time dilation and relativistic mass. For example, at near-light speeds, particles encounter lower interaction cross-sections, resulting in greater penetration, not because of a true mass increase but due to a physical tapering of the HU force. The paper proposes calorimetric experiments in particle accelerators to empirically differentiate between HU and relativistic predictions. By measuring thermal energy deposition instead of relying on penetration depth, these experiments could directly observe the Absolute-Velocity-Dependent Force in action. This approach could profoundly impact our understanding of high-energy dynamics, particularly in applications like spacecraft shielding. This work invites experimental physicists and theorists to explore HU’s framework through accessible computational models and experimental designs provided in accompanying GitHub repositories. This innovative model challenges the established foundations of relativity and offers a new perspective on high-velocity particle interactions, making it a pivotal contribution to modern physics and potential aerospace applications.

Sonoelastography, a novel ultrasound-based technique, is emerging as a valuable tool in prenatal diagnostics by quantifying tissue elasticity and stiffness in vivo. This review explores the application of sonoelastography in assessing maternal and fetal health, with a focus on cervical, placental, pelvic floor, and fetal tissue evaluations. In the cervix, sonoelastography aids in predicting preterm birth and assessing labor induction success. For the placenta, it provides insights into conditions like preeclampsia and intrauterine growth restriction through elasticity measurements. Assessing fetal tissues, including the lungs, liver, and brain, sonoelastography offers a non-invasive method for evaluating organ maturity and detecting developmental anomalies. Additionally, pelvic floor assessments enable better management of childbirth-related injuries and postpartum recovery. While current studies support its safety when used within established limits, further research is necessary to confirm long-term effects. Future advancements include refining protocols, integrating machine learning, and combining sonoelastography with other diagnostic methods to enhance its predictive power. Sonoelastography holds promise as an impactful adjunct to conventional ultrasound, providing quantitative insights that can improve maternal and fetal outcomes in prenatal care.

This paper explores the overall picture regarding security systems in healthcare through an extensive review of the literature. As the healthcare sector has now become digitalized, the security of healthcare systems and, by extension, the protection of patient data is a key concern in the modern era of technological advances. Therefore, a secure and integrated system is now essential. Thus, to evaluate the relationship between security systems and healthcare quality, we conducted literature research to identify studies reporting their association. The timeline of our review is based on published studies covering the period from 2018 to 2024, with entries identified through a search of the relevant literature, focusing on the most recent developments due to advances in artificial intelligence and algorithmic approaches. Thirty-three studies were included in our final survey. Our findings underscore the critical role of security systems in healthcare that significantly improve patient outcomes and maintain the integrity of healthcare services. According to our approach, the studies analyzed highlight the growing importance of advanced security frameworks, especially those incorporating artificial intelligence and algorithmic methodologies, in safeguarding healthcare systems while enhancing patient care quality. According to this study, most of the research analyzed uses algorithmic technology approaches, many researchers prove that ransomware is the most common threat to hospital information systems, and more studies are needed to evaluate the performance of the systems created against this attack.

This study presents the development of zirconium polycarboxylate gel systems as substrates for advanced fluorescence sensing devices. Zirconium-based metal-organic gels (MOGs) offer a promising alternative due to the robustness of the Zr-O bond, which provides enhanced chemical stability. In this work, zirconium polycarboxylate gels were synthesized using green solvents in a rapid room temperature method. Fluorescein, naphthalene-2,6-dicarboxylic acid and 4,4',4'',4'''-(porphine-5,10,15,20-tetrayl)tetrakisbenzoic acid were incorporated as fluorophores to give the gel luminescent properties, enabling it to be used as a sensor. These fluorophores produce specific changes in the perceived colour and intensity of the fluorescence emission upon interaction with different analytes in solution, allowing a qualitative identification of different solvents and compounds. However, the fragile structure of neat gels hinders reproducible quantitative analysis of fluorescence emission, so to increase mechanical stability during manipulation, a composite material was developed by combining the MOGs with quartz microcrystals, which proved to be a more reliable fluorescent system. The results show that the material can identify univocally different solvents and analytes in aqueous solutions by the quantitative analysis of the emissions intensities. This work presents an innovative approach to create advanced fluorescence sensors with improved mechanical properties and stability using zirconium polycarboxylate gels and multiple fluorophores.

Background/Objectives: Hospitalization among older adults represents an increasingly significant challenge in Mexico due to the high prevalence of chronic diseases and the current strain on the country’s public healthcare services. This study aims to develop a predictive model for hospitalization using longitudinal data from the Mexican Health and Aging Study (MHAS) using the Random Forest (RF) algorithm. Methods: Three machine learning models based on RF were designed and evaluated under different data partition configurations, with and without interaction between inputs. The models were validated using nested cross-validation to ensure robustness and prevent overfitting. Evaluation metrics included sensitivity, specificity, and the kappa coefficient, along with their respective standard errors. Results: The M2 model, which included interaction and a 20% test proportion, achieved the best balance between sensitivity (0.7215, standard error ±0.0038) and specificity (0.4935, standard error ±0.0039), despite the imbalance in the dataset and the heterogeneity of the population. This ability of the model to balance performance allows it to handle the complexities of predicting hospitalizations well across different patient profiles. Conclusions: The M2 model shows great potential for clinical application by enabling the anticipation of hospital demand and enhancing resource planning. This suggests substantial benefits for healthcare systems, particularly in optimizing the care of older adults. Future research will focus on integrating subgroups based on comorbidities and applying advanced techniques for handling missing data to further optimize predictive capacity.

In September 2024, bluetongue virus serotype 3 (BTV-3) was first identified in Portugal, specifi-cally in the Alentejo region (Évora District), using molecular diagnostic methods. The initial case involved a sheep exhibiting severe clinical symptoms, including head oedema, prostration, nasal discharge, and significant respiratory distress. A subsequent case was documented in another sheep from a different farm within the same district, which presented with high fever (41.5°C), nasal discharge, and arthritis, ultimately resulting in mortality. Within one month of these initial detections, additional cases in both sheep and cattle were reported in neighboring districts, indi-cating the virus rapid spread within the region. In response to this emerging threat, extensive monitoring efforts are being undertaken to delineate the distribution of BTV-3, and vaccination campaigns targeting this serotype have been initiated. These measures aim to mitigate the impact of the virus on livestock health and prevent further transmission.

The transition to sustainable systems often faces significant challenges, with polarisation emerging as a critical obstacle due to divergent views on sustainability. Understanding the underlying drivers of polarisation and promoting inclusivity in decision-making processes is essential for fostering collective action. This study uses the agent-based HUMAT framework to develop a dialogue tool to explore the complexities of community opinion dynamics such as polarisation and potential pathways to reconciliation in divided communities. By simulating scenarios such as unsatisfied, divided, and reconciled communities, the tool provides key insights into how individual characteristics—such as assertiveness and openness to change—affect community cohesion, satisfaction, and collective decision-making outcomes. Moreover, the study examines intervention strategies that reduce polarisation, offering actionable pathways toward consensus. The visual representation of dynamics across different scenarios has the potential to engage stakeholders in the decision-making process, encouraging deeper reflection on community collaboration and participation. While limitations such as simplified assumptions and the lack of empirical calibration limit its predictive accuracy, the dialogue tool shows strong potential for both educational and policy applications. It offers valuable insights into social influences, conformity, and opinion dynamics, making it a promising tool for fostering inclusive, informed decision-making processes and enhancing community engagement in sustainability transitions.

PRMT5 methyltranserase is an enzyme that produces monomethyl arginine (MMA) as well as symmetric dimethyl arginine (sDMA), posttranslational modifications that regulate several cellu-lar processes, including stage conversion in parasitic protozoa. Entamoeba histolytica, the etiologic agent of human amebiasis, has two stages in its life cycle, the trophozoite, which is the replicative form, and the cyst, corresponding to the infective phase. The study of the molecular mechanisms that regulate differentiation in this parasite has been overdue by the lack of efficient protocols for in vitro encystment. For this reason, Entamoeba invadens, a reptile parasite, has been used as a dif-ferentiation model system for the genus. Here, we demonstrated the presence of sDMA in E. in-vadens, which increases during encystment, and identified the PRMT5 protein of this microorgan-ism (EiPRMT5). In addition, we performed 3D modeling of this enzyme, as well as its molecular docking with the PRMT5 inhibitor EPZ015666, which predicted the affinity of the drug for the ac-tive site of the enzyme. In agreement, EPZ015666 reduced trophozoite viability and encystment. Therefore, EiPRMT5 is a potential target for the inhibition of amebiasis spread.

Mungbean (Vigna radiata) is a key pulse crop in Bangladesh, playing a crucial role in the country's agricultural economy and food security. However, challenges such as soil degradation, nutrient depletion, and low yield potential hinder its productivity. This study investigates the effects of integrated nutrient management (INM) practices, including vermicompost, on the yield, quality, and soil health of mungbean (Vigna radiata) in the coastal region of Gopalganj, Bangladesh. A randomized complete block design (RCBD) was employed with three treatment groups: control (traditional inorganic fertilizers), organic fertilization (vermicompost), and integrated nutrient management (a combination of organic and inorganic fertilizers). Results indicated that the INM treatment significantly improved the emergence rate, with 85% of seeds emerging within 8 days, compared to 75% and 70% in the organic and control treatments, respectively. Plant growth parameters, including plant height (60 cm) and the number of leaves (15), were highest in the INM treatment, followed by the organic (50 cm and 12 leaves) and control treatments (45 cm and 10 leaves). The INM group also showed the highest mungbean yield (26 tons/ha), with larger average tuber weight (180 g) and fewer defects (5%), compared to the organic (22 tons/ha, 160 g, 10% defects) and control groups (20 tons/ha, 150 g, 15% defects). Soil health assessments revealed significant improvements in soil nutrient content, including nitrogen (24 mg/kg), phosphorus (18 mg/kg), and potassium (230 mg/kg), and higher microbial activity (130) in the INM treatment, suggesting enhanced soil fertility. These results highlight the potential of INM practices in improving mungbean productivity, quality, and long-term soil health, offering a sustainable approach to agriculture in Bangladesh. This study underscores the importance of adopting integrated fertilization strategies to achieve higher crop yields and ensure soil sustainability.

Down the Hole (DTH) Hammer drilling has high rock breaking efficiency and strong advantage in hard rock drilling, which can reduce the cost of geothermal drilling. However, when the drill bit rotation speed and the DTH percussion frequency do not match properly, specially when the drill bit diameter is large and the ball tooth diameter is small, while drilling high strength formation, the edge teeth of the drill bit are prone to fracture and break, leading to the failure of the drill bit and a significant reduction in its lifespan.This paper investigates the failure modes firstly, then analyzes the failure mechanism of large diameter DTH bit, and proposes a novel method of cluster edge teeth of DTH hammer drill bit in large diameter geothermal well with high strength rock. The drill bits of this innovative design have been mass-produced. Widespread field applications have shown significant improvements in drill bit life and drilling efficiency, obtaining the reduction of drilling costs.

The clumping index (CI) is a key structural parameter that quantifies the nonrandomness of the spatial distribution of vegetation canopy leaves. Investigating seasonal variations in the CI is crucial, especially for estimating the leaf area index (LAI) and studying global carbon and water cycles. However, accurate estimations of the seasonal CI have substantial challenges, e.g., from the need for accurate hot spot measurements, i.e., the typical feature of the bidirectional reflectance distribution fumnction (BRDF) shape in the current CI algorithm framework. Therefore, deriving a phenologically simplified stable CI product from a high-frequency CI product (e.g., 8 days) to reduce the uncertainty of CI seasonality and simplify CI applications remains important. In this study, we applied the discrete Fourier transform and an improved dynamic threshold method to estimate the start of season (SOS) and end of season (EOS) from the CI time series and indicated that the CI exhibits significant seasonal variation characteristics that are generally consistent with the MODIS land surface phenology (LSP) product (MCD12Q2), although seasonal differences between them probably exist. Second, we divided the vegetation cycle into two phenological stages based on the MODIS LSP product, ignoring the differences mentioned above, i.e., the leaf-on season (LOS, from greenup to dormancy) and the leaf-off season (LFS, after dormancy and before greenup of the next vegetation cycle), and developed the phenologically simplified two-stage CI product using the MODIS 8-day CI product suite. Finally, we assessed the accuracy of this CI product (RMSE = 0.06, bias = 0.01) via 95 datasets from 14 field-measured sites globally. This study revealed that the CI exhibited an approximately inverse trend in terms of phenological variation compared with the NDVI. Globally, based on the phenologically simplified two-stage CI product, the CILOS is smaller than the CILFS across all land cover types. Compared with the LFS stage, the quality for this CI product is better in the LOS stage, where the QA is basically identified as 0 and 1, accounting for more than ~90% of the total quality flag, which is significantly higher than that in the LFS stage (~60%). This study provides relatively reliable CI datasets that capture the general trend of seasonal CI variations and simplify potential applications in modeling ecological, meteorological, and other surface processes at both global and regional scales. Therefore, this study provides both new perspectives and datasets for future research in relation to CI and other biophysical parameters, e.g., the LAI.

The period from mid-February to May marks the celebration of the Amarula fruit har-vest, vital for producing Amarula Cream liqueur, an alcoholic beverage made from sugar, cream, and fruits. The fruits of the Amarula plant are rich in ascorbic acid, con-taining three times the vitamin C found in orange juice, along with various minerals and antioxidants. Despite these nutritional benefits, research indicates that the full potential of Amarula fruit still needs to be explored, posing a risk to the plant's sus-tainability. In Kwa-Zulu Natal (KZN), there is a growing trend of utilising Amarula fruits in producing "utshwala bamaganu," a locally favoured alcoholic beverage fer-mented from fruits and sweetened with sugar. However, households with limited al-cohol consumption often do not partake in this beverage. In KZN, most non-alcoholic fermented drinks are maize-based, raising concerns about potential vitamin A defi-ciencies in rural areas where excessive consumption of these beverages may displace more nutritious food options. This study addresses these issues by developing non-alcoholic fermented beverages incorporating Amarula fruits and Provitamin A biofortified maize. Using an experimental design, recipes sourced from key informants were combined, standardised, and modified by substituting traditional white maize meals with 100% Provitamin A biofortified maize to enhance the nutritional profile of the beverages. At full concentration, Amarula juices served as both the sugar source and fermenting agent, while other ingredients remained unchanged. Various fermen-tation techniques—including roasting, milling, and boiling—were employed to assess differences in nutrient composition. The beverage samples were analysed for nutri-tional content, focusing on vitamin A, amino acids, and mineral compositions. Fol-lowing analysis, 60 consumers participated in sensory evaluations using a 5-point he-donic scale to provide feedback. Descriptive statistics were employed for data analysis, including means and standard deviations. The results revealed significant nutritional improvements, particularly in essential minerals like zinc and iron; Sample 2 exhibited the highest iron content at 53 ppm. Roasting significantly enhanced flavour and over-all acceptability, with consumers rating Sample 1 the highest. However, vitamin A levels across all samples were below detection limits, likely due to degradation from heat exposure. This study highlights the potential of incorporating Amarula and bio-fortified maize into fermented beverages to enhance food and nutrition security. The findings suggest that optimizing fermentation and processing methods could improve nutritional benefits, although retaining vitamin A remains challenging. Future research should focus on re-fining fermentation techniques to preserve heat-sensitive nutrients, conducting micro-bial analyses to explore probiotic properties, and educating consumers about the nutri-tional advantages of biofortified products. Expanding market research could enhance product acceptability and facilitate the commercialization of nutritionally fortified beverages.

Biodiversity, as an important component of ecosystems, faces unprecedented decline due to factors such as habitat loss. Many ecosystem services depend on biodiversity and influence crop yield and quality. In viticulture, the importance of groundcover management, as cover crops or spontaneous grassing, is particularly important for the conservation of biodiversity and consequently, the preservation of ecosystem services. The integration of remote sensing technologies and artificial intelligence in this context remains limited, especially concerning groundcover classification in viticulture. In response to this challenge, our research focuses on developing a methodology for the identification and classification of groundcovers within vineyards inter-row. Employing an Unmanned Aerial Vehicle, equipped with RGB cameras, and advanced deep learning models, we categorize groundcovers into nine classes of which seven distinct cover crop communities groups. Our study aims to establish a method for identifying vineyard inter-row groundcover, with the ultimate goal of creating a comprehensive groundcover map. The results demonstrate that using the UNet model with backbone architectures significantly enhances classification performance. Specifically, the model with an EfficientNetB0 backbone achieved an accuracy of 85.4%, a mean IoU of 59.8%, and a Jaccard score of 73.0%. This study validates the capabilities remote sensing and deep learning technologies in supporting the monitoring of biodiversity in vineyards, laying the groundwork for future researches to allow the model to monitor larger surface with time and cost advantages and expanding the dataset to encompass a broader range of vineyard types, soil conditions, and geographic.

Mask-wearing-induced discomfort often leads to unconscious loosening of the mask to relieve the discomfort, thereby compromising its protective efficacy. This study investigated how leakage flows affect mask-associated thermoregulation and vapor trapping to inform better mask designs. An integrated ambience-mask-face-airway model with various mask-wearing misfits was developed. The transient warming/cooling effects, thermal buoyancy force, tissue heat generation, vapor phase change, and fluid/heat/mass transfer through a porous medium were considered in this model, which was validated using Schlieren imaging, a thermal camera, and velocity/temperature measurements. Leakages from the top and side of the mask were analyzed in comparison to a no-leak scenario under cyclic respiration conditions. Results showed a significant inverse relationship between mask leakage and facial skin temperature/humidity. An equivalent impact from buoyancy forces and exhalation flow inertia was observed both experimentally and numerically, indicating a delicate balance between natural convection and forced convection that is sensitive to leakage flows and critical in thermo-humidity regulation. For a given gap, the leakage fraction was not constant within one breathing cycle, but constantly increased during exhalation. Persistently higher temperatures were found in the nose region throughout the breathing cycle in a sealed mask and were mitigated during inhalation when gaps were present. Vapor condensation occurred within the mask medium during exhalation in all mask-wearing cases. The thermal and vapor temporal variation profiles were sensitive to the location of the gap, highlighting the feasibility of leveraging temperature and relative humidity to test mask fit and quantify leakage fraction.

This study investigates the process of planning for future inpatient resources (beds, staff and costs) for maternity (pregnancy and childbirth) services. The process of planning is approached from a patient centered philosophy; hence, how do we discharge a suitably rested healthy mother who is fully capable of caring for the newborn baby back into the community. It demonstrates some of the difficulties in predicting future births and investigates trends in the average length of stay. While it is relatively easy to document longer-term (past) trends in births and the conditions relating to pregnancy and birth, it is exceedingly difficult to predict the future nature of such trends. The issue of optimum average bed occupancy is addressed via the Erlang B equation which links number of beds, average bed occupancy and turn-away. Turn-away is the proportion of times that there is not an immediately available bed for the next arriving inpatient. Economy of scale implied by queuing theory (and the implied role of population density) explains why many well intended community-based schemes fail to gain traction. The paper also addresses some of the erroneous ideas around the dogma that reducing length of stay ‘saves’ money. Maternity departments are encouraged to understand how their costs are calculated to avoid the trap where it is suggested by others that in reducing the length of stay, they will reduce costs and increase ‘efficiency’. Indeed, up to 60% of calculated maternity ‘costs’ are apportioned hospital overheads from supporting departments such as finance, personnel, buildings and grounds, IT, information, etc., along with depreciation charges on the hospital-wide buildings and equipment. These costs, “the fixed costs dilemma”, are totally beyond the control of the maternity department and will vary by hospital depending on how these costs are apportioned to the maternity unit. Premature discharge, one of the unfortunate outcomes of turn-away, is demonstrated to shift maternity costs into the pediatric and neonatal departments as ‘boomerang babies’ then require the cost of avoidable inpatient care. Examples are given from the English NHS of how misdirected government policy can create unforeseen problems.

We present a unification of fundamental physical laws from a single principle: maximizing the Shannon entropy of all possible measurements relative to a system's initial state, under a universal measurement constraint. By solving this entropy maximization problem, we find that the most sophisticated solution involves 3+1-dimensional measurements encompassing both bivectors and complex numbers. This solution describes a relativistic quantum theory that naturally yields the metric tensor of general relativity via a double-copy mechanism applied to the Dirac current. Moreover, it inherently incorporates the SU(3)xSU(2)xU(1) gauge symmetries of the Standard Model. These findings expose deep connections between information theory and the mathematical structures underpinning fundamental physics, providing new insights into the emergence of 3+1 spacetime dimensions, gravity, and the fundamental symmetries of our universe.

Chronic inflammation and oxidative stress play significant roles in the development of various diseases like diabetes, cancer, and cardiovascular diseases. This study aimed to explore the po-tential therapeutic benefits of Annona crassiflora (Araticum-do-Cerrado) leaves, specifically fo-cusing on their anti-inflammatory, antioxidant, and anti-glycation properties. To achieve this, a hydroethanolic extract of the plant’s leaves (EHAC) was prepared and subjected to phytochemical analysis and in vitro tests to evaluate its effects. The tests included assessing its impact on fibro-blast cytotoxicity, anti-inflammatory capabilities (phagocytosis and macrophage spreading), an-tioxidant activity (DPPH and lipid peroxidation), and anti-glycation activity. The results indicated that EHAC contains high levels of phenolic compounds, including rutin and quercetin. The ex-tract demonstrated strong anti-inflammatory activity by significantly inhibiting phagocytosis and macrophage spreading. Furthermore, it exhibited high antioxidant capacity by inhibiting lipid peroxidation and scavenging free radicals. Additionally, it showed notable anti-glycation activity by completely inhibiting the formation of AGEs at the tested concentrations. The cell viability remained above 95% at concentrations up to 800 µg/mL. In conclusion, EHAC has significant therapeutic potential, and further research is warranted for its development as a phytotherapeu-tic, with the aim of preserving the biodiversity of the Brazilian Cerrado.

Vision-language-action (VLA) models represent a promising direction for developing general-purpose robotic systems, demonstrating the ability to combine visual understanding, language comprehension, and action generation. However, systematic evaluation of these models across diverse robotic tasks remains limited. In this work, we present a comprehensive evaluation framework and benchmark suite for assessing VLA models. We profile three state-of-the-art VLM and VLAs —GPT-4o, OpenVLA, and JAT—across 20 diverse datasets from the Open-X-Embodiment collection, evaluating their performance on various manipulation tasks. Our analysis reveals several key insights: (1) current VLA models show significant variation in performance across different tasks and robot platforms, with GPT-4o demonstrating the most consistent performance through sophisticated prompt engineering, (2) all models struggle with complex manipulation tasks requiring multi-step planning, and (3) model performance is notably sensitive to action space characteristics and environmental factors. We release our evaluation framework and findings to facilitate systematic assessment of future VLA models and identify critical areas for improvement in the development of general-purpose robotic systems.

Ambient dose rate surveying has the objective, in most cases, to quantify terrestrial radiation levels. This is true in particular for Citizen Monitoring projects. Readings of detectors, which do not provide spectrally resolved information, such as G-M counters, are the sum of contributions from different sources, including cosmic radiation. To estimate the terrestrial component, one has to subtract the remaining ones. In this paper, we investigate the cosmic response of two particular monitors, the bGeigie Nano which has been used extensively in the Safecast Citizen Monitoring project and its upgraded version, the new CzechRad which uses the same G-M detector, and show how the local contribution of cosmic radiation can be estimated.

Background/Objectives: The present study aimed to identify information from health research that used mixed-method data collection, considering the approach of face-to-face interviews and telephone interviews (MMFT), with a more specific focus on identifying its themes, objectives, designs, populations involved and implementation process. Methods: A scoping review was developed, with systematic searches applied in March 2024, in five databases (Pubmed; Scielo; Scopus and Web of Science), Google Scholar and reference lists. The inclusion criteria were based on the strategy "Participants" (observational epidemiological studies, with no restrictions as to where they were carried out, sampling technique or sample profile); "Concept” (use of MMFT in data collection) and “Context” (studies carried out in the health area, with no restrictions on the theme/subject). The review process was conducted by three researchers who worked independently. Results: from the initial 1,515 potential references, the synthesis of this review was composed of data from seven original studies, highlighting: cross-sectional design, involvement of adults and/or elderly people without specific health conditions, variability between data collection strategies and complementary use of online approaches. Conclusions: based on the evidence generated, it is recommended that future studies assess aspects of the MMFT approach in terms of response rate, cost reduction and increasing the speed with which health surveys are carried out.

Objective: This review is aimed at evaluating the role of imaging evaluation in the diagnosis of peripheral vestibular disorders. Methods: The study is a literature review conducted on PubMed and the Cochrane Library. Results: Imaging is not usually recommended in initial consultations for vestibular disorders because only 5-10% of MRI scans reveal findings directly related to the disease. The study is a review of the literature that highlights the utility and limitations of imaging such as computed tomography (CT) and magnetic resonance imaging (MRI). It follows the diagnostic approach from history and physical examination to laboratory tests and imaging. Some conditions like vestibular neuritis and BPPV have limited imaging utility due to the fine details required. Conversely, high-resolution CT and MRI are important for diagnosing Meniere's disease, acoustic neuroma, and superior canal dehiscence. Conclusion: The imaging role varies a lot among specific conditions. Advances in imaging technology, particularly high-resolution MRI, promise enhanced diagnostic capabilities.

This paper seeks to enhance volt-var control strategies within reconfigurable microgrids by integrating innovative technologies of power-to-hydrogen (P2H) via electrolyzers and hydrogen-to-power (H2P) through fuel cells. Specifically, it focuses on the simultaneous coordination of electrolyzer, hydrogen storage, and fuel cell alongside on-load tap changers, smart PV inverters, renewable energy sources, diesel generators, and electric vehicle aggregation (EVA) within the microgrid system. Additionally, dynamic network reconfiguration is employed to enhance microgrid flexibility, facilitate power sharing, and improve the overall system adaptability. Given the inherent unpredictability linked to resources, the unscented transformation method is employed to account for these uncertainties in the proposed volt-var control strategy. Finally, the model is formulated as a convex optimization problem and is solved by GUROBI, which leads to having a time-efficient volt-var model with high accuracy. To assess the effectiveness of the model, it is eventually examined on a modified 33-bus microgrid in several cases. Through the results of the under-study microgrid, the developed volt-var control is a great remedy to the simultaneous operation of EVA, P2H and H2P in reconfigurable microgrids with flatter voltage profile across the microgrid.

Abstract: Cyanobacteria play a crucial role in marine ecosystems as primary producers of food and oxygen for various organisms while helping remove waste and toxic substances from the environment. They are essential to the carbon cycle and help regulate the climate. These marine autotrophs also aid in the absorption of essential elements and support diverse life forms. They help degrade organic compounds including petroleum hydrocarbons as well as heavy metals. Fluctuations in cyanobacteria populations can indicate ecosystem health, influencing both human well-being and wildlife. Their significance also extends to potential technological advancements, thus providing valuable resources for fields such as pharmacology, medicine, health care, biofuels, cosmetics, and bioremediation. However, some species produce toxins that pose risks to human health and marine organisms. Consequently, cyanobacteria are a major focus of research aimed at preserving and improving marine ecosystems-especially given the environmental damage caused by past and potential future conflicts. This review highlights their roles in phycoremediation and other industrial and biotechnological applications with a particular focus on the Arabian Gulf region.

A near-exact analytical solution of the statistical Susceptible-Infectious-Recovered (SIR) epidemics model for a constant ratio k0 of infection to recovery rates is derived. The derived solution is not of inverse form as the known solutions in the literature but expresses rather directly the three compartmental fractions S(τ ), I(τ ) and R(τ ) and thus the rate of new infections j(τ ) = S(τ )I(τ ) in terms of the single function U (τ ) and the reduced time τ (the time-integrated infection rate), involving the principal and non-principal branches of Lambert’s function. Exact analytical formulas for the peak time and the maximum fraction of I(τ ) are obtained proving that the rate of new infections peaks before the fraction of infected persons. Our analysis is not entirely analytically exact because the reduced time dependence of the function U (τ ) obeying a nonlinear integro-differential equation is only obtained approximately by expanding a double-exponential function to first-order at small reduced times, and employing an accurate simple approximation of the principal Lambert function at large times, respectively.

Radiation therapy remains to be one of the main treatment modalities for the management of breast cancer. Several reports have asserted that low dose photon irradiation, which is the most available radiation modality, can promote migration and invasion of malignant cells. Also, some approved chemotherapy drugs used in the management of breast cancer are implicated in promoting metastasis. Therefore, it has become critical to unravel novel therapies that are effective on tumour cells and can reduce the metastatic potential. Methods: Malignant (MCF-7), triple-negative (MDA-MB-231) and spontaneously immortalized MCF-10A human breast cancer cell lines were pre-treated with pan-HDACi SAHA or multi-target inhibitor CUDC-101 and exposed to 2Gy and 6Gy 148 MeV mid-SOBP protons or 250KeV X-rays. Wound healing and trans-well invasion assays were performed. Imaging was done at 4-hour intervals for wound healing assays, and at 24-hours post-irradiation for trans-well migration assays. Results: Significant reduction in migration was observed after treatment with proton alone at lower doses (2Gy) and at higher (6Gy) doses in the MCF-7 cell line. In the triple negative cell line MDA-MB-231 cell line, reduction in migration was evident at higher doses(6Gy) protons. Combination therapy of CUDC-101 or SAHA and protons also inhibited migration and invasion in the MDA-MB-231 cell line. Treatment with CUDC-101 monotherapy showed benefit in reducing migration and invasion in the MDA-MB-231 cell line. Treatment with SAHA, either as monotherapy or in combination with X-rays, promoted migration in the MCF-7 cell line. Conclusions: CUDC-101 or proton monotherapies, as well as combination therapy with radiation, inhibits migration as monotherapy particularly in the MDA-MB-231 which has high metastatic potential.

Schiff base macromolecules have been successfully synthesized, utilizing a classical chemistry route and a dielectric barrier discharge (DBD) plasma technique. The synthesis of monomeric units has been accomplished through typical reactions of aldehyde and amine functional molecules. The condensation polymerization of the Schiff base molecules has been instigated chemically, using p-toluene sulfonyl chloride in refluxed ethanol. The molecular weight of the obtained polymers was discovered to be 524,664 and 1,503,228 for polymers 4a and 4b, respectively. Additionally, the polymerization reactions were prompted, employing a Dielectric Barrier Discharge (DBD) atmospheric pressure air plasma technique. The DBD plasma demonstrated a very powerful routine to produce high molecular weights macromolecules, which could be an ecofriendly strategy to acquire this class of materials. Moreover, the complexation of polymer 4b with various metal moieties, Ru (II), Co (II), Cu (II), and Ni (II), has been executed in order to have a comparative study of their antitumor activity against MCF-7, A-549, HCT-116, and HepG-2 cell lines. Furthermore, the density functional theory was exploited to optimize the polymers and their complexes, and their HOMO-LUMO and energy gap were calculated, which was utilized to examine the inter/intra molecular charge transfer. The molecular electrostatic potential map was similarly quantified to investigate the reactive sites that are present in the investigated molecules. The result for the docking study confirmed that these complexed polymers adopted numerous important interactions with the amino acid of the targeted enzyme.

Electrolysis of water is one of low-cost green hydrogen production technologies. The challenge is designing and developing low-cost and high-activity catalysts. Herein, we present a strategy to fabricate flexible electrocatalysts based on nickel-iron (NiFe) alloy coatings. NiFe coatings were plated on the flexible copper-coated polyimide surface (Cu/PI) using the low-cost and straightforward electroless metal plating method and morpholine borane as a reducing agent. It was found that Ni90Fe10, Ni80Fe20, Ni60Fe40, and Ni30Fe70 coatings were deposited on the Cu/PI surface, then the concentration of Fe2+ in the plating solution was 0.5 mM, 1 mM, 5 mM, and 10 mM, respectively. Morphology, structure, and composition of NixFey/Cu/PI catalysts have been examined using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), X-ray diffraction (XRD), and inductively coupled plasma optical emission spectroscopy (ICP-OES), whereas their activity has been investigated for hydrogen evolution (HER) and oxygen evolution (OER) reactions in 1 M KOH using linear sweep voltammetry (LSVs). It was found that the Ni80Fe20/Cu/PI catalyst exhibited the lowest overpotential value of –202.7 mV for the HER to obtain a current density of 10 mA cm–2 compared to Ni90Fe10/Cu/PI (–211.9 mV), Ni60Fe40/Cu/PI (–276.3 mV), Ni30Fe70/Cu/PI (–278.4 mV), and Ni (−303.4 mV). On the other hand, the lowest OER overpotential (344.7 mV) was observed for the Ni60Fe40/Cu/PI catalyst to obtain a current density of 10 mA cm–2 as compared with the Ni30Fe70 (369.9 mV), Ni80Fe20 (450.2 mV), Ni90Fe10 (454.2 mV) coatings, and Ni (532.1 mV). The developed Ni60Fe40/Cu/PI catalyst exhibit a cell potential of 1.85 V at 10 mA cm−2. The obtained catalysts seem to be suitable flexible catalysts for HER and OER in alkaline media.

This paper examines the quantitative structure–inhibitory activity relationship of 15-lipoxygenase (15-LOX) in sets of 100 homo- and heterocyclic compounds using GUSAR2019 software. Statistically significant valid models were built to predict the IC50 parameter. A combination of MNA- and QNA-descriptors with three whole molecular descriptors (topological length, topological volume, and lipophilicity) was used to develop 18 statistically significant valid consensus QSAR models. These compounds had varying degrees of inhibition of the catalytic activity of 15-LOХ: the range of variation in the pIC50 value was 3.873. The satisfactory coincidence between the theoretically calculated and experimentally determined pIC50 values for compounds TS1, TS2 and 1–8 suggests the potential use of models M1–M18 for virtual screening of virtual libraries and databases to find new potentially efficient inhibitors of 15-LOX.

Background/Objectives: The standard of care for acute bacterial skin and skin structure infections (ABSSSIs) requiring intravenous (IV) antibiotics includes vancomycin, administered over several days, in a hospital or outpatient setting resulting in significant costs. Dalbavancin, a long-acting single-dose lipoglycopeptide IV therapy may offer a cost-effective option for adult patients with ABSSSIs in Canada. Methods: A cost-utility analysis (CUA) was performed to evaluate the potential benefits of dalbavancin compared to other IV antibiotics for the treatment of adult patients with ABSSSIs who require IV antibiotics but whose hospitalization, if necessary, is anticipated to be £ 72 hours. Results: This analysis utilized a decision-analytic model showing that dalbavancin was dominant against all IV antibiotic comparators when considering the healthcare system or societal perspective and was associated with lower costs and improved patient adherence. For the sub-population analysis against PWID (people who inject drugs) and the homeless, dalbavancin generated even greater cost savings. Conclusions: We report that dalbavancin when used to treat ABSSSI requiring IV antibiotics may offer cost savings for Canadian healthcare providers through reduced hospitalization time, lower administration and labor costs, minimized risk of healthcare-acquired infections (HAIs), improved patient compliance and optimized resource allocation particularly in patients at risk of non-compliance (First Nations, the homeless and PWID).

This study investigates avifaunal diversity in the Magat Wetland areas in the Philippines, which serve as habitats for both endemic and migratory bird species. Using transect surveys and data from Department of Environment and Natural Resources (DENR), the research recorded 24 bird species, with dominant populations of E. garzetta and A. luzonica. Moderate avifaunal diversity, reflected in a Shannon-Wiener Diversity Index of 1.62, suggests an ecologically stable environment with critical resources supporting both abundant and rare species. However, pressures from habitat loss due to aquaculture, agricultural expansion, and tourism activities pose ongoing challenges for conservation. Local government efforts, including the establishment of a bird-watching site and eco-tourism initiatives, have raised awareness and engaged communities in conservation. Statistical modeling revealed that for each 1% increase in forest cover, the avian population is expected to increase by about 84 individuals, holding other factors constant. This highlights forest cover loss as a key factor affecting avifaunal populations, underscoring the importance of habitat preservation. Future research should focus on understanding the impact of human activities, climate change, and habitat quality on bird populations. This research underlines the critical role of the Magat Wetland as a biodiversity hotspot, advocating for sustainable management practices to preserve its ecological integrity amid increasing human development pressures.

A power amplifiers are crucial components that significantly influence the linearity and energy efficiency of next-generation communication system radio units. A key challenge in designing power amplifiers is managing high Peak-to-Average Power Ratio (PAPR) to achieve both high linearity and energy efficiency during back-off conditions. This paper presents simulation and measurement results for a dynamic load modulation power amplifier based on a ferroelectric tunable matching network. Experimental studies on the power amplifier with the tunable output matching network confirm its performance at 8 dB back-off while varying the control voltage applied to the ferroelectric element. Additionally, a bias modulator to adjust the transistor's load in relation to input power was designed. Measurement studies of the dynamic load modulation power amplifier demonstrated an efficiency of at least 50% at 8 dB back-off and higher 60% at peak power. Furthermore, it was found that the modulator output voltage adjustment function on input power of the bias modulator affects the linearity of the output power. Different bias responses are studied and, as a result, optimal output voltage response is found. The proposed load modulation power amplifier is promising for operation with high PAPR digital signals.

Human genome studies have suggested that strawberry notch homologue 1 (SBNO1) is crucial for normal brain development, with mutations potentially contributing to neurodevelopmental disorders. In a previous study, we observed significant developmental abnormalities in the neocortex of Sbno1 as early as one week after birth. In the present study, we conducted an extensive analysis of Sbno1 postnatal expression in the brain of C57BL/6 mice using a newly developed in-house polyclonal antibody against Sbno1. We found that Sbno1 is expressed in all neurons, with certain neuronal populations exhibiting distinct dynamic changes (both temporal and spatial) in expression level. These findings suggest that the neuronal expression of Sbno1 is developmentally regulated after birth. They also indicate that while Sbno1 may play a general role across all neurons, it may also serve more specialized functions in certain neuronal types and/or for certain cellular activities related to particular neuronal pathways.

Engaging in physical activity (PA) is crucial for individuals with Parkinson's disease (PD) to maintain functional independence and enhance their quality of life. However, difficulties in measuring PA create challenges when comparing and combining results from various studies, hindering the identification of effective, efficient, and beneficial PA interventions therefore the study aimed to compare the self-reported and objective PA of people with PD in the context of participation in functional physical rehabilitation (FPR). The International Physical Activity Questionnaire and an Actigraph GT3X+ were used to measure the PA. The study included 47 patients with idiopathic PD, aged 64.37±7.12 yrs., disease duration of 6.29 ± 4.02 yrs., in the II and III stages of the disease according to the Hoehn and Yahr scale. The patients were divided into two groups, participating (group A), and not participating (group B) in FPR. The study showed that in both groups, the self-reported level of physical activity was higher than the accelerometer-measured level. However, these differences were not statistically significant in the group participating in FPR. It was concluded that participation in FPR increases the possibility of a reliable assessment of the level of PA.

Public enterprises, also known as government-owned corporations or state-owned enterprises, are companies with government ownership, control, or partial ownership in sectors such as energy, telecommunications, healthcare, and transportation. Their primary goals are to serve the public's basic needs, advance economic growth, or protect national interests. Public enterprises can collaborate with privately held businesses or face competition. The percentage of public enterprises varies across nations, but they play significant roles in both liberal and private enterprise-oriented systems. Public enterprises are becoming increasingly important due to the state's increasing functions and philosophy, moving from laissez-faire to social welfare initiatives. The idea that the state should hold the majority of natural resources and capital-intensive sectors has gained widespread acceptance in modern states. Public businesses are considered essential tools for achieving social and economic growth, fostering technical innovation, and supporting private sector economic development. This article presents a Systematic Literature Review of the present body of research using the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) model. This study further investigates the research gaps (RG), formulates research questions (RQ), and makes an RG-RQ analysis. The study also explores public choice theory and the property rights paradigm, contributing to a better understanding of public enterprises' operations.

The age and sex specific data of the worldwide prevalence of hypertension (HT) shows that it is an important health challenge and requires to be screened, prevented and treated with high priority. One of the major causes of HT is the transition of normal weight status to overweight (OW) status and obesity in a population that leads to cardiovascular disease (CVD) and other disorders. A variety of factors/ variables are involved in the development of HT and OW related hypertension (OHT). We proposed the present study to consult the middle-aged men (age range: 51-60 years) having HT and OHT along with normal control (NC; age range: 51-60 years) men for investigating the two samples comparisons, analysis of variance and correlations of serum leptin (Lep), interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-α), serum testosterone (ST), total cholesterol (TC) and other variables in NC (n: 98; high normal weight BMI: 23-24.9 kg/m2, HT (n: 97; high normal weight BMI: 23-24.9 kg/m2) and OHT (n: 97; high overweight BMI: 28-29.9 kg/m2) subjects. Significant variations were obtained for the comparisons of TNF-α, Lep, ST and TC for the subject groups. The OHT vs. NC showed significant difference for ST. The OHT vs. NC and OHT vs. HT gave significant variation for IL-6. One-way ANOVA revealed significant change for TNF-α, Lep, IL-6, ST and TC levels among groups. Significant and positive linear associations were obtained for each other for TNF-α, Lep, TC and IL-6. The HT and OHT subject groups presented non-significant negative linear correlations for ST plotted against TC. Significant and negative linear association was found for ST plotted against each of Lep, TNF-α and IL-6. Conclusively, the current report provides pathophysiological evidence of the interactive role of serum Lep, TNF-α, ST, TC and IL-6 in middle-aged men with hypertension and overweight-related hypertension.

Gesture recognition has a crucial role in Human-Computer Interaction (HCI) and in assisting the elderly to perform automatically their everyday activities. In this paper three methods for gesture recognition and computer vision were implemented and tested in order to investigate the most suitable one. All methods, Machine learning using IMU, Machine learning on device and were combined with certain activities that were determined during a needs analysis research. The same volunteers took part to the pilot testing of the proposed methods. The results highlight the strengths and weaknesses of each approach, revealing that 60 while some methods excel in specific scenarios, the integrated solution of MoveNet and 61 CNN provides a robust framework for real-time gesture recognition.

Environmental issues and reduction of fossil resources led to the partial or total substitution of petroleum based materials with natural raw renewable ones. The continuous decrease in world oil reserves and unpredictable price fluctuations compelled both academia and the industry to invest massively in the production of new materials. One expanding domain is the obtaining of engineering materials from raw renewable natural resources as sustainable eco–friendly polymers for different applications. This is the first study on the obtaining, thermal, morphological, dielectric and wettability characterization of a composite from thermally cured solvent–free bio–based epoxidized and acrylated soybean oil containing low quantities of reactive diluent and TiO2 microparticles as filler. The microcomposite also possessed reduced initial matrix formulation viscosity and without the toxic curing agents. The material was characterized by Fourier–transform infrared spectroscopy, differential scanning calorimetry, thermogravimetry, scanning electron microscopy, broadband dielectric spectrometry and contact angle measurements. Here we demonstrate that the composite exhibits superior thermal stability, glass transition temperature, dielectric constant and hydrophobicity to the pristine matrix. All investigations recommend the microcomposite for optoelectronic devices and as layer in thin–film transistors. This study brings new contributions to green chemistry and sustainable materials.

Short text similarity, as a pivotal research domain within Natural Language Processing (NLP), has been extensively utilized in intelligent search, recommendation systems, and question-answering systems. The majority of existing models for short text similarity concentrate on aligning the overall semantic content of entire sentences, frequently neglecting the semantic correlations between individual phrases within the sentences. This challenge is particularly acute in the Chinese language context, where synonyms and near-synonyms can introduce substantial interference in the computation of text similarity. In this paper, we introduce a short text similarity computation methodology that integrates both sentence-level and phrase-level semantics. By harnessing vector representations of Chinese words/phrases as external knowledge, our approach amalgamates global sentence characteristics with local phrase features to compute short text similarity from diverse perspectives, spanning from the global to the local level. Experimental findings substantiate that the proposed model surpasses previous approaches in Chinese short text similarity tasks. Specifically, it attains an accuracy of 90.16% on the LCQMC, marking an enhancement of 2.23% over ERNIE and 1.46% over the previously top-performing model, Glyce + BERT.

The concept of a smart campus is rapidly gaining traction worldwide, driven by the growth of artificial intelligence (AI) and the Internet of Things (IoT) along with the digital transformation of higher education institutions. While numerous initiatives have been undertaken to enhance the capability of smart campus systems to keep pace with AI advancements, there have been few attempts to develop a cohesive conceptual framework for the smart campus and, to date, there has been limited empirical research conducted to validate the framework. This study bridges this gap by providing the first in-depth assessment of a holistic smart campus conceptual framework. The paper uses a Delphi Study approach to validate and consolidate a framework for assessing the robustness of the smart campus assessment framework for application in university settings. The framework consists of four domains, 16 categories, and 48 indicators, comprising a total of 68 items were validated by the experts across the globe. Two rounds of structured questionnaires were conducted to achieve consensus on the framework. The first round involved 34 experts from diverse geographic and professional backgrounds in the smart campus field. The second round included 21 of the earlier participants, which was sufficient to determine consensus. In total seven of the 48 indicators were agreed upon after round 1, increasing to 43 after round 2. The results indicate strong agreement among the experts, affirming the framework’s robustness. This study offers an expert-based, interpretive assessment on the development of the smart campus concept, with a particular focus on validating the smart campus framework.

Deprivation indices are used to monitor health inequities. However, their theoretical underpinnings have been based on the context of Western industrialized countries, which have distinct social and historical backgrounds compared to Latin America and the Caribbean and countries in the Global South. Following the Latin American Social Determination of Health perspective, particularly the category Modes of Living supported by the construct of precarity, we aimed to develop an index of precarity in the modes of living at the department level in Colombia and assess its geographical distribution and usefulness for public health purposes. We conducted an ecological cross-sectional study with national administrative records. We developed a precarity index through Principal Component Analysis and performed spatial autocorrelation analyses and regression models with child mortality indicators. Our final index comprised twenty indicators representing four dimensions of the modes of living and power relations. We found precarity not to distribute randomly in Colombia, with a center-periphery divide and higher precarity observed in the country's margin. We also found an association of our index with under-five mortality (SMR=1.19; 95%CI 1.08 – 1.31) and infant mortality (SMR=1.13; 95%CI 1.00 – 1.26). Our index highlights the relevance of considering the modes of living when devising deprivation indices or similar measures from Colombia or Latin America. This approach may provide different perspectives on the health-disease process and potential value for public health planning.

Classical Optimal Power Flow (OPF) is one of the complex and challenging problem in power system that includes non-convex, nonlinear and large-scale structure. With the use of incorporation of uncertain and intermittent wind energy sources in the OPF problem, the complexity of the problem escalates. In a power system, Flexible Alternating Current Transmission Systems (FACTS) devices can mitigate most of the problems associated with power quality and overload in the network. However, determining the placement and sizing of facts devices is an additional problem to minimize the total cost of production of the power system. As a result, in order to solve OPF problem which includes all of these conditions, an artificial intelligence based optimization algorithm needs to have an unusual exploration ability as well as exploitation–exploration balance. Weighted mean of vectors (INFO) is a new heuristic optimizer, which can help finding a more effective solutions in engineering design optimization problems. In this study, firstly, INFO algorithm was improved by using the Fitness–Distance Balance (FDB) method with its abilities. Then, the algorithm developed with a hyper-heuristic method to create the beginning optimal population by using Linear Population Reduction Success-History based Adaptive Differential Evolution (LSHADE). Finally, the developed algorithm has been applied for solving optimal placement and sizing of facts devices for optimal power flow problem incorporating wind energy source. The obtained results showed that the proposed algorithm is more effective solver for the problems cases while compared to the literature.

Telomerase presents over-expression in most of cancer cells and has been a near-universal marker of cancer. Studies revealed that inhibiting telomerase activity by utilizing oligonucleotides to down-regulate the expression of intracellular human telomerase reverse transcriptase (hTERT) mRNA was an effective method to achieve anti-tumor therapy. Considering oncogenic microRNA-21 has been proved to indirectly up-regulate hTERT expression and drive cancer metastasis and aggression through increased telomerase activity, here we constructed a AS1411-functionallized oligonucleotide-conjugated gold nanoprobe (Au-nanoprobe) to simultaneously down-regulate intracellular microRNA-21 and hTERT mRNA by using anti-sense oligonucleotide technology to explore their targeted anti-tumor therapy effect. In vitro cell studies demonstrated that Au-nanoprobes could effectively induce apoptosis and inhibit the proliferation of cancer cells through down-regulating intracellular hTERT activity. In vivo imaging and anti-tumor studies revealed that Au-nanoprobes could accumulate at the tumor site and inhibit the growth of MCF-7 tumor xenografted on balb/c nude mice, thus exert the potential of anti-tumor therapy.

The study investigated both the static and dynamic behavior of silicate materials through a series of experimental and numerical tests. Compression tests were conducted on cubic samples, three-point bending tests on beams, and perforation tests on silicate plates. In the compression tests, stress-strain curves were generated, enabling the calibration of the Concrete Damaged Plasticity (CDP) model for silicate materials. The tensile strength of the silicate was assessed using three-point bending tests, while dynamic perforation tests determined the impact resistance of silicate when subjected to a rigid projectile. The perforation tests provided insight into the failure mechanisms of silicate plates under projectile impact at velocities approaching the ballistic limit. Additionally, the numerical simulations for all the experimental tests were performed using the Abaqus software, in order to validate the accuracy of the material behavior model and confirmed the appropriateness of the calibrated parameters for the chosen model. The results showed a strong qualitative and quantitative correlation with the experimental data, demonstrating the robustness of the adopted approach.

Background/Objectives: Although the use of radiation-sensitizing agents has been shown to enhance the effect of radiation on tumor cells, the blood-brain barrier (BBB) impedes these agents from reaching brain tumor sites when given systemically. Localized methods of sensitizer delivery, utilizing hydrogels, have the potential to bypass the blood-brain barrier. This study examined the ability of photochemical internalization (PCI) of hydrogel-released bleomycin to enhance the growth-inhibiting effects of radiation on multi-cell glioma spheroids in vitro; Methods: Loaded fibrin hydrogel layers were created by combining thrombin, fibrinogen, and bleomycin (BLM). Supernatants from these layers were collected, combined with photosensitizer, and added to F98 glioma spheroid cultures. Following light (PCI) and radiation treatment, at increasing dosages, spheroid growth was monitored for 14 days; Results: PCI of released BLM significantly reduced the radiation dose required to achieve equivalent efficacy compared to radiation or BLM+RT alone. Both immediate and delayed RT delivery post BLM-PCI resulted in similar degrees of growth inhibition; Conclusion: Non-degraded BLM was released from the fibrin hydrogel. PCI of BLM synergistically increased the growth-inhibiting effects of radiation treatment compared to radiation and BLM, and radiation acting as a single treatment.

Psoriasis is a chronic, immune-mediated skin disease significantly impacting women, with disease severity often modulated by hormonal fluctuations. This review examines the influence of hormonal changes on the course of psoriasis in women, focusing on key life stages—including the menstrual cycle, pregnancy, postpartum, and menopause—and their impact on disease progression and symptomatology. Estrogen, the principal female sex hormone, plays a critical role in immune modulation. Variations in estrogen levels, which occur naturally throughout a woman's life, are associated with fluctuations in psoriasis severity. Low estrogen levels, as seen during menstruation or menopause, are linked to symptom exacerbation, while elevated levels during pregnancy may reduce symptoms in some women. However, responses are variable, with others experiencing no change or worsening during pregnancy. Postpartum, the rapid decline in estrogen often triggers severe flare-ups, while menopause, marked by a sustained estrogen reduction, frequently correlates with increased disease severity and flare frequency. The review also addresses the profound impact of psoriasis on women’s quality of life, including physical discomfort, psychological distress, and social stigma. Additionally, fertility concerns are discussed, as severe psoriasis and associated treatments may increase the risk of adverse pregnancy outcomes. Consideration is given to hormonal therapies, lifestyle modifications, and their effects on psoriasis, underscoring the need for personalized treatment approaches that account for hormonal influences. Understanding these hormonal dynamics is essential for developing targeted, effective management strategies that enhance quality of life for women affected by psoriasis.

We used WRF-Chem to simulate ash transport from Chile’s Calbuco volcano eruptions on April 22 and 23, 2015. Massive ash and SO2 ejections reached the upper troposphere, and particulates were transported over South America, observed over Argentina, Uruguay, and Brazil via satellite and surface data. Simulations from April 22 to 27 covered eruptions and particle propagation. Chemical parameters utilized GOCART; meteorological conditions came from NCEP-FNL reanalysis. Two simulations (GCTS1 and GCTS2) differed in ash mass fraction in the finest bins (0–15.6 μm): 2.4% and 16.5%, respectively, to assess model efficiency in representing plume intensity and propagation. Analyzing active synoptic components revealed their impact on particle transport and the Andes’ role as a natural barrier. We evaluated and compared simulated aerosol optical depth (AOD) with VIIRS Deep Blue Level 3 data and SO2 data from Ozone Mapper and Profiler Suite (OMPS) limb profiler (LP), both sensors onboard the Suomi National Polar Partnership (NPP) spacecraft. The model successfully reproduced ash and SO2 transport, effectively representing influencing synoptic systems. Both simulations showed similar propagation patterns, with GCTS1 yielding better results. Comparison with VIIRS Brightness Temperature Difference data confirmed the model’s efficiency in representing particle transport. Overestimation of SO2 may stem from emission inputs. This study demonstrates WRF-Chem’s feasibility under volcanic configurations to reproduce ash and SO2 patterns enabling studies on aerosol-radiation and aerosol-cloud interactions and the understanding of atmospheric behavior following volcanic eruptions.

The aims of the study were to assess the efficacy of the rate of perceived exertion (RPE) scale based on the number of repetitions in reserve (RIR) for the prescription of resistance training in cardiac rehabilitation and to compare it to the percentage of one-repetition maximum (1RM) prescription method. Sixteen male pa-tients (age 59.8 ± 7.6) with history of coronary artery disease were randomly assigned to two resistance training rehabilitation protocols lasting nine weeks and consisting of three sessions per week, with the same exercise selection, number of sets and repetitions, rest periods, but different load prescription method (RPE vs %1RM). Patients’ strength was evaluated pre- and post-intervention. Patients in the RPE group increased leg press by 24.25 ± 17.07 kg (p = 0.005; ES = 0.71), chest press by 7.25 ± 3.41 kg (p = 0.001; ES = 0.61), seated row by 13.88 ± 7.57 kg (p = 0.001; ES = 0.77), leg extension by 14.24 ± 4.53 kg (p < 0.000; ES = 0.76), shoulder press by 5.75 ± 4.06 kg (p = 0.005; ES = 0.80), lat pulldown by 7.50 ± 4.66 kg (p = 0.003; ES = 0.73). Post-intervention between-group analysis showed no statistically significant differences in strength gains (leg press p = 0.955; chest press p = 0.965; seated row p = 0.763; leg extension p = 0.565; shoulder press p = 0.868; lat pulldown p = 0.780) and trivial effect sizes for one prescription method over the other (leg press ES = -0.03; chest press ES = 0.00; seated row ES = 0.10; leg extension ES = -0.29; shoulder press ES = 0.18; lat pulldown ES = 0.05). RPE based on RIR seems to be an effective prescription method for resistance training in cardiac rehabilitation, showing similar efficacy to the standardized practice of percentage of 1RM.

Considering the sustained increase of dengue outbreaks in Latin America in recent years, this study proposes the use of machine learning (ML) tools with epidemiological data, meteorological climate parameters considering El Niño and La Niña (Niño 3.4 Index), and socioeconomic and demographic phenomena as a basis for the construction of an early warning system for dengue outbreaks in Zulia State, Venezuela. The study area covers 21 municipalities. Two ML models, support vector regression machine (SVM-R) and Gaussian process regression (GPR), were used. The data were used raw, standardised, and normalized for each model to be trained. The predictions of dengue outbreaks from the GPR and SVR algorithms show agreement with the dates of the real data; it was determined that there is a range of 2 to 3 weeks depending on the municipality. These coincide with previous studies showing that the algorithms do not work properly for some municipalities.

Abstract: Delta-like 1 homolog (DLK1), a non-canonical Notch ligand, is highly expressed in various malignant tumors, especially in hepatocellular carcinoma (HCC). CBA-1205 is an afucosylated humanized antibody against DLK1 with enhanced antibody-dependent cellular cytotoxicity (ADCC). The binding characteristics of CBA-1205 were analyzed by enzyme-linked immunosorbent assay and fluorescence-activated cell sorting assay. The ADCC activity of CBA-1205 was assessed. The anti-tumor efficacy of CBA-1205 was evaluated in xenograft mouse models, and toxicity and toxicokinetic profiles of CBA-1205 were evaluated in cynomolgus monkeys. CBA-1205 selectively bound to DLK1 among the Notch ligands and only to monkey and human DLK1. The binding epitope was between epidermal growth factor-like domains 1 and 2 of DLK1, which are not involved in any known physiological functions. The ADCC activity of CBA-1205 was confirmed using human peripheral blood mononuclear cells as effector cells. CBA-1205 as a single-agent and in combination with lenvatinib demonstrated long-lasting anti-tumor efficacy, including tumor regression, in two liver cancer xenograft models. The toxicity and toxicokinetic profiles of CBA-1205 in cynomolgus monkeys were favorable. These findings suggest that CBA-1205 has the potential to be a useful therapeutic option for drug treatment in HCC. A phase 1 study is ongoing in patients with advanced cancers (jRCT2080225288).

Is there a qualitative difference between apes’ and human ‘ability to estimate others’ mental states’, a.k.a. ‘Theory-of-Mind’? After opting for the idea that expectations are empty profiles that recognize a particular content when it arrives, I apply the same description to ‘vicarious expectations’ –very probably present in apes. Thus, (empty) vicarious expectations and one’s own (full) contents are distinguished without need of meta-representation. Then, I propose: First, vicarious expectations are enough to support apes’ Theory-of-Mind (including ‘spontaneous altruism’). Second, since vicarious expectations require a profile previously built in the subject that activates them, this subject cannot activate any vicarious expectation of mental states that are intrinsically impossible for him. Third, your mental states that think of me as a distal individual are intrinsically impossible states for me, and therefore, to estimate them, I must estimate your mental contents. This ability (the original nucleus of human Theory-of-Mind) is essential in human lifestyle. It is involved in unpleasant and pleasant self-conscious emotions, which respectively contribute to ‘social order’ and to cultural innovations. More basically, it makes possible the human (prelinguistic or linguistic) communication, since it originally made possible the understanding of others’ mental states as states that are addressed to me, and that are therefore impossible for me.

As pension benefits from statutory public schemes become less generous and many countries face pension-savings crises, the willingness to participate in supplementary retirement-saving instruments becomes crucial for sustainable financial well-being. The study highlighted factors influencing participation in auto-enrollment and private supplementary pension savings. The study focuses mainly on financial literacy and trust. We used the CAWI method with 867 interviews in Poland - the first country in Central and Eastern Europe to introduce an auto-enrolment pension system. Our study uses multivariable data-mining tools, and several regression models were applied. We used Logistic Regression (LR), Multivariate Linear Regression (MLR), and Factor Analysis of Mixed Data (FAMD) to support the LR analysis. We propose four regression models. Our findings present that: 1. The lower the consumer’s knowledge level, the more their decisions are based on trust. 2. Trust in the state, rather than trust in financial institutions, plays a crucial role for people with low financial literacy, which is a critical factor in choosing the auto-enrolment option for pension savings. 3. Men had higher odds of auto-enrolment pension saving than women. 4. Employees of economic universities and academics had higher odds of participating in capital pension plans than those of general universities and non-academics. Our findings can signal to governments and policymakers about factors influencing the choice of auto-enrolment supplementary retirement savings. These findings strengthen the role of sustainable economic education.

Research shows that observers and agents, as key concepts in physics and intelligence science respectively, exhibit profound intrinsic consistency. Based on this understanding, we propose and construct Theory of Universal Intelligent Evolution, known as Omega Theory, which offers an innovative exploration of Theory of Everything (ToE) from the perspective of intelligence science. Within the framework of Omega Theory, this paper unifies the research subjects and dynamic mechanisms of physics and intelligence science, revealing that the intelligence level of the observer is the fundamental source of the differences among classical mechanics, relativity, and quantum mechanics. Furthermore, this paper proposes that core concepts such as subjectivity and objectivity, determinism and uncertainty, as well as time and space, are inherently related to the intelligent state of agents and Universe.Omega Theory consists of three core models: Standard Agent Model, General Model of Agent Evolution, and Intelligent Universe Evolution Model. Standard Agent Model serves as a foundational axiom, defining the unified structure and functional framework of agents, and it is the cornerstone of the theory. Building upon this, we derive General Model of Agent Evolution and Intelligent Universe Evolution Model. Omega Theory posits that the fundamental units of Universe are agents, and that the entire universe is itself an agent. Matter is a special manifestation of agents, and each agent continuously evolves between the states of absolute zero intelligence and omniscience and omnipotence, driven by two intelligent forces that are derived from the theory.To validate this theory, we have designed a thought experiment in the "Experimental Universe 1," where classical mechanics, relativity, and quantum mechanics experiments can be simultaneously conducted. By adjusting the intelligence level of the observer, we observe that different physical theory scenarios emerge in succession as the observer's intelligence level changes.

In this paper various LLMs are tested in a specific domain using a Retrieval-Augmented Generation (RAG) system. The study focuses on the performance and behaviour of the models and was conducted in Spanish. A questionnaire based on The Bible, which consist of questions that vary in complexity of reasoning, was created in order to evaluate the reasoning capabilities of each model. The RAG system matches a question with the most similar passage from The Bible and feeds the pair to each LLM. The evaluation aims to determine whether each model can reason solely with the provided information or if it disregards the instructions given and makes use on its pretrained knowledge.

The evaluation of measurement uncertainty of natural gas properties calculated from composition data is an essential aspect of fiscal metering in the trade of natural gas. In particular in gas allocation, it is essential to have a reliable value for the uncertainty. This need is also reflected in the current edition of ISO 6976, the standard for computing natural gas properties, which follows much more closely the requirements of the “Guide to the expression of uncertainty in measurement”. A critical aspect in the uncertainty evaluation of natural gas properties is the fact that the amount fractions of the components of natural gas are always correlated after normalisation. A novel algorithm is provided to recover these correlations from the normalised fractions and associated standard uncertainties. The standard uncertainties are reproduced within 2 , which is acceptable for uncertainty calculations. The correlation coefficients obtained from the recovery algorithm agree with the ones obtained by normalisation. The algorithm requires only the data commonly stored by the natural gas industry as input and it enables providing values and credible associated uncertainties for natural gas properties calculated from composition.

In the face of rising threat of resistant pathogens, antimicrobial peptides (AMPs) offer a viable alternative to the current challenge due to their broad-spectrum activity. This study focuses on enhancing the efficacy of temporin-SHa derived NST-2 peptide (1), which is known for its antimicrobial and anticancer activities. We synthesized new analogs of 1 using three strategies, i.e. retro analog preparation, lysine addition/substitution, and levofloxacin conjugation. Analogs were tested in term of antibacterial, antifungal, and anticancer activities. Analog 2 corresponding to retro analog of NST-2 was found more active but also more hemolytic, reducing its selectivity index and therapeutic potential. Addition of lysine (in analog 3) and lysine substitution (in analog 7) reduced the hemolytic effect resulting in safer peptides. Conjugation with levofloxacin on lysine side chain (in analogs 4 and 5) decreased the hemolytic effect but unfortunately also the antimicrobial and anticancer activities of the analogs. Oppositely, conjugation with levofloxacin at the N-terminus of the peptide via β-alanine linker (in analogs 6 and 8) increased their antimicrobial and anticancer activity but also their hemolytic effect, resulting in less safe/selective analogs. In conclusion, lysine addition/substitution and levofloxacin conjugation, at least at the N-terminal position through β-alanine linker, were found to enhance the therapeutic potential of retro analogs of NST-2 whereas other modifications decreased the activity or increased the toxicity of the peptides.

This case report highlights a rare but significant complication associated with the use of granulocyte-colony stimulating factor (G-CSF) therapy, specifically splenic infarction, in a 67-year-old male with chronic myelomonocytic leukemia (CMML) undergoing chemotherapy. G-CSFs, such as Neulasta (pegfilgrastim), are frequently used to prevent febrile neutropenia in cancer patients undergoing myelotoxic chemotherapy. While G-CSF is effective in reducing the risk of neutropenia, its administration has been linked to uncommon but severe complications like splenic infarction and rupture. Our patient, receiving dose-dense chemotherapy with G-CSF support, developed severe abdominal pain midway through treatment. A computed tomography (CT) scan revealed multiple splenic hypodensities consistent with splenic infarction, but no active bleeding. Conservative management was successfully employed, avoiding surgical intervention. This case underscores the need for vigilance when administering G-CSF, particularly in patients at high risk for complications, and contributes to the limited body of literature on G-CSF-induced splenic infarction.

Cyberbullying is defined as the use of social media platforms to hurt or humiliate people online. The anonymity on these platforms makes it easy to spread hurtful content, sometimes leading victims to self-harm. This highlights the urgent need for efficient methods to identify to prevent cyberbullying. Numerous studies have addressed this issue by focusing on cyberbullying classification, primarily through binary classification using multi-modal data or multi-class approaches targeting either text or image data. While deep-learning advancements have improved cyberbullying identification, a gap remains in the multi-class classification of cyberbullying utilizing multi-modal data such as memes and this research aims to bridge this gap by accurately classifying cyberbullying across multiple data modalities through a hybrid deep-learning model that combines RoBERTa for text extraction and Vision Transformer (ViT) for images extraction as hybrid(RoBERTa+ViT) model using late fusion module process. Two datasets were utilized: a Private-dataset was collected from comments on social media videos and a Public-dataset that was downloaded from existing research. The hybrid model was trained on these two datasets and the model demonstrated notable performance, achieving an an accuracy of 99.24% on the Public-dataset and 96.1% on the Private-dataset, with F1-scores of 0.9924 and 0.9599, respectively.

Mitochondrial dysfunction is implicated in the pathogenesis of the neurological condition Autosomal Recessive Spastic Ataxia of Charlevoix Saguenay (ARSACS), yet precisely how mitochondrial metabolism is affected is unknown. Thus, to better understand changes in mitochondrial metabolism caused by loss of the sacsin protein (encoded by the SACS gene, that is mutated in ARSACS) we performed mass spectrometry-based tracer analysis, with both glucose and glutamine traced carbon. Comparing the metabolite profiles between wild-type and sacsin-knockout cell lines revealed increased reliance on aerobic glycolysis in sacsin-deficient cells, as evidenced by the increase in lactate and reduction of glucose. Moreover, sacsin knockout cells differentiated towards a neuronal phenotype had increased levels of tricarboxylic acid cycle metabolites relative to controls. We also observed disruption in the glutaminolysis pathway in differentiated and undifferentiated cells in the absence of sacsin. In conclusion, this work demonstrates consequences for cellular metabolism associated with loss of sacsin, which may be relevant to ARSACS.

Polyhedral cages (p-cages) describe the geometry of some families of artificial protein cages. We identify the p-cages made out of families of equivalent polygonal faces such that the faces of 1 family has 5 neighbours and P_1 edges, while those of the other family have 6 neighbours and P_2 edges. We restrict ourselves to polyhedral cages where the holes are adjacent to at most 4 faces. We characterise all the p-cages with a deformation of the faces, compared to regular polygons, not exceeding 10%.

This paper introduces the Hypergeometrical Universe (HU) Theory, a groundbreaking cosmological model that proposes a new shape and structure for the universe: the Lightspeed Expanding Hyperspherical Universe (LEHU). In HU, the universe began through a "Big Pop" event—a metric fluctuation driven by the Heisenberg Principle, rather than a singularity. This fluctuation initiated distinct cosmic phases—Blackholium, Neutronium, and Neutrinium—each associated with specific densities, states of matter, and degrees of freedom that drove cosmic evolution. Central to HU is the concept of matter emerging from deformed space, simplifying physics by reducing the universe to interactions between space, deformed space, and time. This model replaces complex mass and field-based theories, allowing natural laws to be derived from first principles. During phase transitions, such as the Blackholium-Neutronium shift, the universe acquired an extra degree of freedom with neutron formation, leading to observable oscillations in the Cosmic Microwave Background (CMB). The later Neutronium-to-Baryonic phase generated Baryonic Acoustic Oscillations (BAO), further imprinted in the CMB and reflective of the HU model’s unique particle interactions. To validate this framework, HU achieved the hyperspherical harmonic spectral decomposition of the CMB, addressing the complexity of observations by precisely locating Earth's position in the hyperspherical universe. Hyperspherical harmonics are not a complete basis set for data collected on a spherical surface, such as the CMB; therefore, HU’s accurate spectral decomposition required pinpointing Earth’s coordinates within this topology. By leveraging this spectral information, HU constructs a comprehensive 3D map of the universe, capturing cosmic structures with unprecedented clarity and validating HU’s predictions. This model has far-reaching implications for understanding cosmic origins, matter formation, and the inherent structure of space. HU presents a vision of the universe that challenges conventional models, offering new explanations for phenomena like the homogeneity of the CMB, the absence of antimatter, and the bounded nature of kinetic energy. This paper invites theoretical and experimental physicists to explore HU’s powerful framework, with computational models and spectral maps available to further investigate this transformative view of cosmology.

Transcriptome assembly and functional annotation are essential for understanding gene expression and biological function. Nevertheless, many existing tools lack the flexibility to integrate both short- and long-read sequencing data or fail to provide a complete, customizable workflow for transcriptome analysis. Here, we present TrAnnoScope, a comprehensive transcriptome analysis pipeline that provides a complete, customizable workflow capable of efficiently processing and integrating short- and long-read sequencing data to generate high-quality, full-length transcripts with detailed functional annotation. The pipeline encompasses steps from quality control to functional annotation, employing a range of tools and established databases, such as SwissProt, Pfam, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes. As a case study, TrAnnoScope was applied to RNA-Seq data from zebra finch brain, ovary, and testis tissues. TrAnnoScope produced comprehensive transcriptome, demonstrating strong alignment with the reference genome (99.63%) and capturing a significant proportion of nearly complete protein sequences (92.7%). The functional annotation process yielded extensive matches to known protein databases and successfully assigned relevant functional terms to majority of the transcripts. As such, TrAnnoScope successfully integrates multiple sequencing technologies to generate comprehensive transcriptomes with minimal user input. Its modular design, flexibility, and ease of use make it a valuable tool for researchers working with complex datasets, particularly for non-model organisms.

This study evaluates the impact of different irrigation scenarios on the yield of quinoa (Chenopodium quinoa) in the Chilean Altiplano. The research was conducted in Ancovinto, Tarapacá, Chile, using "Pandela" quinoa seeds. Four irrigation treatments were implemented: rainfed (T0), and irrigation at 100% ETc (T1), 66% ETc (T2), and 33% ETc (T3). Various climatic variables, soil moisture content, and agromorphological parameters were measured. Results indicated that rainfed conditions (T0) led to higher dry matter production in roots, stems, leaves, and panicles at the end of the growth cycle compared to irrigated treatments. Leaf Area Index (LAI) was also higher in rainfed conditions during the flowering stage, demonstrating the crop's adaptability to adverse water conditions. Plants under rainfed conditions reached greater heights and showed higher harvest indices (HI) and grain yield than those under irrigation. Water Use Efficiency (WUE) was significantly higher in rainfed conditions, suggesting more effective water utilization under water scarcity. The results obtained show that quinoa plants under traditional management (rainfed) exhibited the best response in the measured growth, development, and production variables, leading to higher production and harvest rates. Additionally, these was greater efficiency in water use, equivalent to 15,87 and 12,7 times that of the 100% and 33% ETc treatments, respectively. These findings highlight the quinoa's remarkable adaptability to harsh hydric conditions and the efficiency of traditional rainfed farming practices in the Altiplano.

Cisplatin-based chemotherapy has long been the standard first-line treatment for metastatic urothelial carcinoma (mUC). However, owing to comorbidities, up to 50% of patients are ineligible for cisplatin, necessitating alternative primary treatment options. Immune checkpoint inhibitors (ICIs) have emerged as a vital alternative for those unable to receive cisplatin. However, the prognosis for advanced urothelial carcinoma remains grim, with challenges persisting in optimizing first-line therapy. Recent advancements have redirected attention towards innovative combinations in primary treatment. The combination of enfortumab vedotin (EV) and pembrolizumab has significantly improved overall and progression-free survival compared to chemotherapy alone. This marks a critical shift in first-line treatment options for patients who are cisplatin-ineligible or require alternatives to standard chemotherapy. While platinum-based chemotherapy continues to be essential for many patients, the approval of EV and pembrolizumab as first-line treatments for cisplatin-ineligible patients signifies a significant breakthrough in primary care. These therapies offer new options and enhance outcomes in terms of survival and response rates, highlighting the increasing relevance of ICI-containing regimens in frontline care. This review provides an exhaustive overview of the current frontline treatment landscape for mUC, incorporating clinical trial evidence and exploring investigational agents to aid in clinical decision-making and guide future therapeutic strategies.

Clustering algorithm such as k-Means is highly sensitive to the scale of input features. A common approach to mitigate this issue is Min-Max scaling normalization, which rescales feature values to a specified range. This paper investigates an alternative form of Min-Max scaling, where the normalization is based on both the minimum (Xmin) and mean (Xmean) of the feature, rather than the maximum value. The proposed method is shown to be particularly effective in improving clustering accuracy for datasets with varying scales and distributions. Experimental results demonstrate that using this modified Min-Max scaling approach leads to better-defined clusters, enhanced performance in terms of clustering accuracy, and reduced bias in distance-based clustering algorithms. We validate the method using several standard clustering techniques, including k-Means on publicly available datasets.

This research investigates the relationship between sustainable human resource management (SHRM) practices and employee happiness, with a focus on the mediating role of employee engagement. Using a sample of 473 women workers from one of India’s largest tea plantations, the study found a significant positive relationship between SHRM practices and employee happiness. Additionally, employee engagement was shown to mediate this relationship, indicating that SHRM practices enhance employee happiness primarily through increased engagement. The research aims to assess how sustainable human resource management affects workplace happiness among the women employees in the Indian tea plantation sector. The data was analyzed using IBM SPSS 25, and the research model was developed with WarpPLS 8.0. The study adopted Ehnert’s (2009) Sustainable Human Resource Management Practices, Singh & Aggarwal's (2017) Employee Happiness Scale (Happiness at Workplace), and Schaufeli et al.'s (2012) Employee Engagement Scale. The findings reveal a strong positive relationship between sustainable human resource management and employee happiness, with a correlation value of 0.943 at a significance level of 0.01. Moreover, there is a significant positive association between employee engagement and workplace happiness, with a correlation value of 0.947 and an R² of 0.99. These results confirm a robust positive relationship among sustainable human resource management, employee engagement, and employee happiness. This relationship emphasizes that fostering a positive work environment can significantly enhance employee engagement, leading to improved overall performance.

This study investigates the theoretical modeling and experimental analysis of composites made from randomly oriented flax fibers reinforced with recycled expanded polystyrene (EPS) waste. The effect of flax fiber volume fractions (20%, 30%, and 40%) on the composites' tensile strength and tensile modulus were examined. Several theoretical models namely the rule of mixtures (ROM) series, modified Bader and Bowyer, Hirsch, Cox-Krenchel, and Einstein-Guth model were compared against the experimental results of the formulated composites. The theoretical predictions of tensile strength from the Hirsch and modified Bader and Bowyer models showed close alignment with experimental results. Cox-Krenchel and Hirsch's models better predict the tensile modulus of a composite at 30% fiber loading. Additionally, this research accentuates the potential of utilizing natural fibers in combination with recycled EPS materials to produce eco-friendly composites with better performance for construction applications, such as house panels and automobile interior components.

Precipitation during a specific return period plays an important role in the design of hydraulic infrastructure. The traditional approach involves collecting annual maximum precipitation data from a station, then subjecting it to statistical probability distributions (PDFs), and finally selecting the one with the lowest value in a goodness-of-fit test (e.g., Kolmogorov-Smirnov). Nevertheless, this methodology assumes current data, leaving uncertainty regarding its suitability for outdated data. The aim of this study is to compare the probability density functions (e.g., Normal, Log Normal, Pearson III) with the machine learning algorithm known as Random Forest (RF) for calculating precipitation at different return periods, using the province of Arequipa in Peru as the study area, through 5 stations located in different parts of the province. This comparison was conducted using the RMSE metric in both methods to evaluate their performance, resulting in RF having a lower RMSE than PDFs in most cases in calculating precipitation for return periods of 2, 5, 10, 20, 50 and 100 years for the studied stations.

This paper presents a comprehensive system for converting and analyzing Electromagnetic Cardiac Interference (EMC) signals into high-quality Electrocardiogram (ECG) sig- nals. We introduce a multi-stage approach incorporating advanced preprocessing, adaptive filtering, robust QRS complex detection, and signal quality analysis. The proposed methodol- ogy demonstrates high efficiency in noise and artifact removal while preserving essential cardiac morphological features. Our system achieves a signal-to-noise ratio improvement of up to 20 dB and maintains QRS detection accuracy above 99% in normal conditions. The implemented solution provides automated documentation and quality metrics, making it suitable for both clinical and research applications.

Objective: This study aims to investigate the possible effects of gestational diabetes mellitus (GDM) on fetal heart structure and the relationship of this effect with maternal blood sugar control. Materials and Methods: In this cross-sectional study, 19 women with GDM at 24-36 weeks of gestation (case group) and 21 healthy pregnant women at the same weeks of gestation (control group) were examined. Fetal heart structure was evaluated by ultrasonography, interventricular septum (IVS) thickness, right and left ventricular sphericity indices, global sphericity index (GSI) and cardio-thoracic ratio were measured. In addition, mothers' HbA1c values (an indicator of blood sugar control) were recorded. Result: An increase in IVS thickness was observed in the fetuses of mothers with GDM. A more rounded trend was observed in the right ventricular structure, but this did not create a significant difference. No significant relationship was found between maternal blood sugar control and fetal heart structure. Conclusion: This study examined the effects of gestational diabetes on fetal cardiac morphology and the relationship of this effect with maternal glycemic control. Babies of mothers with GDM had a significantly thicker interventricular septum. A more rounded trend was detected in the right ventricular structure. However, this change was not found to be statistically significant. In addition, no significant correlation was found between maternal glycemic control and fetal cardiac morphology.

This study focuses on Tsunami detection using SIMRAD Radar. A tsunami is a condition in which sea waves overflow the land and cause severe damage, which can claim human lives, as well as important infrastructure such as schools, buildings, and housing on the coast. As a sovereign country and has resilience in various fields including security and ocean exploration, Indonesia must apply appropriate technology, in this case, a smart radar that can detect high sea waves from tens of km away even 100 km if radar capacity is maximized. And able to provide fast information for disaster emergency response teams to swiftly notify the surrounding community about the arrival of a tsunami, even predict before this tsunami hits the coast. In this research, a comprehensive measurement of the radar system is carried out. The radar used and developed is SIMRAD Radar Helo 6 and can be integrated with data from other hardware such as SBE 26Plus, to obtain comprehensive data about the marine environment. In the measurement process, several combinations of measurements are needed starting from how to get digital data, process digital data, and turn it into a real-time image in the form of a Graphical User Interface SIMRAD Radar Hello 6. In the search, SIMRAD Radar is placed on the coast, while SBE26Plus is placed in the ocean with a certain depth in the coastal area for seawater pressure and sea level measurement. This radar system can be converted from the SBE26Plus data results from the Acoustic Doppler Current Profiler (ADCP), and also SIMRAD real-time monitoring at the coastal position in a higher area to avoid obstacles.

Against the backdrop of the global goal of "carbon neutrality", the promotion of electric vehicles (EVs) is of great significance in reducing the use of fossil fuels and vehicle emissions, and in promoting the transformation of the automotive industry into a green and low-carbon direction. The wide application of electric vehicles not only reduces the dependence on non-renewable resources such as oil, but also significantly reduces carbon emissions in the transport sector, thus making an important contribution to the global response to climate change. In electric vehicles, ternary lithium batteries (NCM) and lithium iron phosphate batteries (LFP) are two widely used batteries. This paper investigates the resource and environmental impacts of 1KW ternary lithium batteries and lithium iron phosphate batteries during the battery production process based on the Life Cycle Assessment model. The importance of clean energy in reducing environmental pollution and global warming potential is revealed by introducing four different power generation types and the regional power generation structure in China into the power battery production process. The results of the study show that lithium iron phosphate batteries batteries have a clear advantage in terms of environmental friendliness. While Nickel Cobalt Manganese batteries are more advantageous in terms of performance. Environmental pollution during battery production can be effectively reduced through the comprehensive use of clean energy and optimization of the production process. Specific measures include improving the energy efficiency of the production process, adopting renewable energy for power supply, and reducing the use of hazardous substances. Through these measures, the battery industry can develop in a greener and more sustainable direction.

Background/Objectives: Pentacyclic Triterpenoids are increasingly studied as anti-cancer agents with many advantages comparative to synthetic chemotherapeutics. The aim of this study was to prepare liposomal and nanostructured lipid formulations including a standardized extract of silver birch (Betula pendula) outer bark (TTs) and to evaluate their potential as anti-cancer agents in vitro, using Melanoma B16-F10 and Walker carcinoma cells. Methods: Appropriate solvents were selected for an efficient TTs extraction, and original recipes were used to obtain Pegylated liposomes and nanolipid complexes with entrapped TTs, comparative to pure standards (betulinic acid and doxorubicin) in similar conditions. The composition, morphology and sizes of all nanoformulations were checked by High Performance Liquid Chromatography/Mass spectrometry, Transmission Electronic Microscopy and Diffraction Light Scattering. The entrapment efficiency and their impact on cell viability, cell cycle arrest and apoptosis by Flow Cytometry was also measured on both cancer cell lines. Conclusions: The standardized TTs showed good stability, synergistic effects of main components and superior comparative to pure betulinic acid. According to experimental data, TTs showed good entrapment in liposomal and NLC nanoformulations, both delivery systems including natural, biodegradable ingredients and enhanced bioavailability. The apoptosis and necrosis effects were more pronounced for TTs liposomal formulations in both types of cancer cells, with lower cytotoxicity comparative to Doxorubicin, and can be correlated with their increased bioavailability.

In the city of Valencia (Spain), existed from the Middle Ages until the mid-nineteenth century, a building that fulfilled a municipal strategic function: The “new flour-weighing house”. Its pur-pose was to distribute food to the population and collect the corresponding indirect municipal taxes. Today, the existence of this building is not remembered, neither by scientists nor by citizens, and its importance, location and appearance are unknown. The building investigated, behind which the medieval façade of the “flour-weighing house” is hidden, is the Colomina Palace. In the investigation, its growth phases have been detected and an idea of its structural organisation has been obtained. Research and investigation have been carried out by consulting historical, carto-graphic and archival material, together with advanced geomatics techniques, including close-range photogrammetry, terrestrial laser scanning and thermography. The fuse of colour and thermal imagery, altogether with point clouds and 3D models help to visualise and check the dif-ferent spatial transformations of the current “Colomina Palace”, adapting the sequence from me-dieval times into present.

We introduce a novel approach to study the dielectric permittivity of spin crossover (SCO) molecular materials using a radio frequency (RF) resonant tunnel diode oscillator (TDO) circuit. By fabricating a parallel plate capacitor using SCO particles embedded into a polymer matrix as an integral part of the LC tank of the TDO we were able to extract the temperature dependence of the dielectric permittivity from frequency measurements for a wide selection of resonance values, spanning from 100 kHz up to 50 MHz, with great precision (less than 2 ppm), in a broad temperature range. By making use of this simple electronic circuit to explore the frequency and temperature dependent dielectric permittivity of the compound Fe[(Htrz)2(trz)]BF4 we demonstrate the reliability and resolution of the technique and show how the results compare with those obtained using complex instrumentation.

Background: Recent publications suggest that the threshold for validation of the learning curve is 25 procedures. The aim of this study was to evaluate this threshold using another method which is little used, based on a composite quality indicator. Methods: We included all patients from the French medico-administrative database receiving robot-assisted surgery for lung cancer between 2019 and 2022 in hospitals performing at least 25 procedures. For postoperative complications analysis we used the Clavien-Dindo classification. We used the sequential probability ratio test to estimate the number of procedures from which a team achieved its learning curve. Results: In France, the number of robotic-assisted procedures has risen steadily over the years: 195 in 2019 and 1,567 in 2022: overall, 28 teams performed 3,707 Robot-Assisted surgery for lung cancer. The total number of patients with Clavien-dindo classification > II was 833 (24.7%). Among the 28 hospitals, 8 achieved their learning curve with a threshold ranging from 94 to 174 procedures, and a median of 110. Severe complications such as acute respiratory distress syndrome, respira-tory failure, heart failure, acute ischemia of the lower limbs and pulmonary embolism were signif-icantly more frequent in the group of hospitals that did not validate the learning curve threshold. Conclusion: This study suggests that the threshold of 25 procedures may not be sufficient enough to validate the robot-assisted surgery learning curve in lung cancer surgery. To significantly re-duce postoperative complications, a team would need to perform between 94 to 174 procedures to guarantee patient safety.

This study aims to evaluate the black bullhead Ameiurus melas, an invasive alien fish (IAF) in Serbia, as a bioindicator organism and the safety of natural and aquaculture specimens for human consumption. A set of biomarkers was analysed to assess the bioindicator potential at site exposed to agricultural activities. The genotoxic response was determined by alkaline comet assay and micronucleus assay in fish erythrocytes, and the metal pollution index (MPI) was calculated to assess the toxic element burden on fish. Water quality was evaluated using physicochemical pa-rameters and faecal indicator bacteria, while the sediment was analysed for the presence of pesti-cides. The concentration of metals and metalloids in fish muscle was monitored to assess the safety for human consumption, and the corresponding indices (MAC, THQ, HI) were calculated. All biomarker responses were linked by integrated biomarker response (IBR). Water analyses indi-cated the absence of communal wastewater, while sediment analysis revealed the presence of paclobutrazol, bifenthrin, and cyfluthrin. The IBR showed that June and September had the highest stress index, coinciding with peak pesticide use and precipitation. All indices confirmed the safety of black bullhead for human consumption. This study highlighted used approaches as nature-based solutions to the problem of IAF.

Fall-related injuries (FRIs) are increasing among older adults, leading to complications, reduced quality of life, and deaths. Inflatable hip protectors(HPs) offer higher fracture prevention rates, but face acceptance challenges resulting in low adoption. Our study evaluates well-documented compliance parameters on our intelligent inflatable HP. Our human-centered designed inflatable garment prototype, Air-Sequr, may offer unique opportunities in hip fracture prevention.

Maintenance of the integrity of entire endothelium, glycocalyx included, and therefore of tissue aorta’s homeostasis, depends on the expressions of several molecular pathways and their interactions, such as syndecans molecules. Alterations in syndecans, i.e. quantitative or linking to their shedding, contributes to evocate endothelium dysfunction, which causes damage in the vessel wall due to the increased production of growth-stimulating and pro-inflammatory gene products. Inflammatory processes negatively affect the integrity of the endothelial glycocalyx, a dynamic layer of the luminal portion of endothelial cells composed of proteoglycans, glycoproteins, and glycosaminoglycans, i.e. syndecans. In turn, structural alterations of endothelial glycocalyx influence the coagulative state, increasing pro-thrombotic processes. The family of syndecans constitutes the major component of glycocalyx, or better the major source of cell surface heparan sulfate. It encompasses 4 components: syndecan-1, syndecan-2 and syndecan-4 (since syndecan-3 is expressed only in neural tissue), which have a fundamental role in regulating the events of acute and chronic aorta damage subsequently correlated with the formation of aneurysms. Considering such, the aim of our review is to highlight the current knowledge on the roles of syndecans, and based on the most recent literature, to analyze their relationship with the pathological processes of the aortic wall.

Colon cancer (CC) is a significant public health concern. With Asian Americans (AA) representing a rapidly growing demographic in the United States, our study examined CC prevalence among AA. The study merged 2017-2021 Medical Expenditure Panel Survey and County Health Ranking. Our analysis calculated age-adjusted CC rates and examined prevalence across states. Regression analyses were conducted to study county-level risk factors of CC. The CC age-adjusted rate among AA increased five-fold, from 155 per 100,000 in 2017 to 753 per 100,000 in 2021. State-level disparities revealed the highest CC prevalence in Arkansas, Rhode Island, and New Hampshire. Not speaking other languages and having insurance were significantly associated with higher CC rates, suggesting barriers to preventions and higher use of screening (p&lt;0.05). County-level analysis identified lower CC prevalence in regions with greater socioeconomic advantage (p&lt;0.05). Socioeconomic advantage seemed to facilitate higher screening rates, translated into higher CC rates. Our findings underscore the need for early preventions to address rising CC rates among AA. Future research should also explore geographic to better understand the disparities in CC risk.

Background: Fibromyalgia (FM) is characterized by chronic pain, significantly affecting the quality of life and functional capabilities of patients. In addition to pain, patients may experience insomnia, chronic fatigue, depression, anxiety, and headaches, further complicating their overall well-being. The Transient Receptor Potential Vanilloid 1 (TRPV1) receptor responds to various noxious stimuli and plays a key role in regulating pain sensitivity and inflammation. Thus, targeting TRPV1 may provide analgesic and anti-inflammatory benefits. This study investigates the efficacy of electroacupuncture (EA) in alleviating chronic pain in FM through TRPV1 and its downstream molecules in central nervous system (CNS). Methods: To model FM, we subjected mice to intermittent cold stress (ICS) for three days. The study comprised five rodent groups: Control, Intermitten cold stress induced FM (ICS), ICS + Electroacupuncture (EA), ICS + Sham Electroacupuncture (sham EA), and ICS + KO (TRPV1 knockout mice). Results: Our findings revealed that ICS induced allodynia and hyperalgesia in mice by day four, persisting until day 21. EA at 2 Hz and TRPV1 knockout significantly decreased both mechanical and thermal hypersensitivity (Withdrawal - Day 14: 2.43 ± 0.19 g; Day 21: 5.88 ± 0.47 g, n = 6, p &lt; 0.05; Latency - Day 14: 2.77 ± 0.22 s; Day 21: 5.85 ± 0.41 s, n = 6, p &lt; 0.05). In contrast, sham EA did not produce significant effects. Additionally, TRPV1 and several pain-related proteins were significantly elevated in the thalamus, somatosensory cortex (SSC), medial prefrontal cortex (mPFC), hippocampus, hypothalamus, cerebellum regions V (CB V), VI (CB VI) and VII (CB VII) after ICS model. Both EA at ST36 acupoint and TRPV1 knockout mice diminished overexpression of pain-related proteins, with the sham EA group showing no significant changes compared to the ICS group. Conclusion: Chronic widespread pain was reduced by EA and TRPV1 knockout, with the effects of EA on the TRPV1 pain pathway clearly evident in CNS after 21 days.

Currently, therapeutic Fc-fusion protein is used for treating disease. ESAT6 (6-kDa early secretory antigenic target), secreted by Mycobacterium tuberculosis, is involved in immune regulation. Administered via intranasal immunization, ESAT6-Fc fusion protein significantly alleviated allergic airway inflammation and mucus hypersecretion, reduced the proportions of Th2 cells, Th17 cells and eosinophils with no observable histopathological injury to principal organs in ovalbumin (OVA)-induced allergic asthma (AA) model mice. A analysis of the transcriptome was conducted to explore its mechanisms of immune regulation, which confirmed that ESAT6 exerts an anti-AA effect by mainly suppressing some signaling pathways activation including Natural Killer Cell-Mediated Cytotoxicity, T Cell Receptor, Th1 and Th2 Cell Differentiation, Th17 Cell Differentiation, and Chemokine, which all belong to immune system in organismal systems. Meanwhile, The RT-qPCR validation results of Differently Expressed genes (DEGs) including Cd28, Icos, Cd48, Cd247, Cd40l, Itgal, Itgb2 and Ccl5 from the aforementioned pathways were consistent with the RNA-seq results. This study revealed the fundamental mechanisms of immune regulation underlying the effects of ESAT6 on OVA-induced allergic asthma. More importantly, this study provides valuable insights into the application of mucosal immunotherapy in treating AA, and ESAT6-Fc has potential as a secure mucosal immunotherapy agent for AA.

Agro-industrial activities generate significant amounts of organic waste and a variety of effluents, thus posing environmental challenges. Viticulture in Argentina, covering 204,847 ha in 2023, faces water scarcity as a limiting factor conditioning its production. This industry produces large volumes of grape marc, sediments, and stalks, which can be valorized into products like alcohol, tartaric acid, and compost. However, these valorization processes generate effluents with high organic load and salinity, further stressing water resources. This study explores the potential of utilizing these effluents to cultivate plant biomass in arid regions (sorghum or perennial pasture), which could serve as bioenergy, animal feed, or composting co-substrates, contributing to circular bioeconomy principles. Sorghum plots showed better establishment and higher dry biomass yield (32.6 Tn/ha) compared to pasture (6.5 Tn/ha). Sorghum demonstrated better tolerance to saline soils and high salinity effluents, aligning with previous studies. Although pasture had lower biomass yield, it was more efficient in nutrient uptake, concentrating more NPK, ash, and soluble salts. Sorghum's higher yield compensates for its lower nutrient concentration. For biomass production, sorghum is preferable, but if nutrient capture from effluents is prioritized, summer polyphytic pastures are more suitable. These results suggest that the final selection between plant biomass alternatives highly depends on whether the goal is biomass generation or nutrient capture.

Over the past twenty years, camera networks, where individual cameras can function both independently and together, have become increasingly popular. Various application fields may impose distinct requirements on camera networks. In response to these demands, several coverage models have been developed in the scientific literature, such as area, trap, barrier, and target coverage. In this paper, a new type of coverage task, the Maximum Target Coverage with k-Barrier Coverage (MTCBC-k) problem is defined. Here, the goal is to cover as many moving targets as possible from time step to time step, while continuously maintaining k-barrier coverage over the region of interest (ROI). This approach is different from independently solving the two tasks and then merging the results. Generally, multiple camera configurations can ensure k-barrier coverage. The challenge is to find, at each time step, the optimal configuration where the cameras providing barrier coverage can also assist in covering targets, while the rest of the cameras efficiently cover the remaining targets. An ILP formulation for the MTCBC-k problem is presented. Additionally, two types of camera clustering methods have been developed. This approach allows for solving smaller ILPs within clusters, and combining their solutions. Furthermore, a polynomial-time greedy algorithm has been introduced as an alternative to solve the MTCBC-k problem. The conducted simulations convincingly supported the usefulness of both the clustering and the greedy methods.

Background/Objectives: Patients receiving solid organ transplantation require lifelong immunosuppression, making them more susceptible to COVID-19. Vaccination against COVID-19 is recommended for HTR. The aim of the present study was to compare the course of the disease in vaccinated and unvaccinated HTR hospitalized in a tertiary hospital in Slovenia and to evaluate possible hesitant groups. Methods: All SARS-CoV-2 positive HTR (N=79) between 1 March 2020 and 31 December 2023 at the Infectious Diseases Department, University Medical Centre Ljubljana, Slovenia, were included retrospectively. Demographic, clinical and vaccination data were extracted from medical documentation and statistical evaluation was performed. Results: The vaccination rate in the cohort was 63.3%. We found no statistically significant difference in vaccination rates regarding gender (male 68.4% vs. female 50%, p=0.128), but there was a statistically significant higher revaccination rate in males (male 52.7% vs. female 18.2%, p=0.021). Vaccinated HRT were statistically significantly older than unvaccinated (p=0.000) and had a significantly higher Charlson Comorbidity index (p=0.001). The vaccination rate among patients who received transplants before the pandemic (prior to 2020) was statistically significantly higher (71.7% vs. 46.2%; p=0.027). Conclusions: Our results indicate no significant differences in the clinical course of COVID-19 between vaccinated and unvaccinated HRT regarding acute respiratory insufficiency (ARI), length of hospital stay (LOS), intensive care unit admission and mortality. However, our findings do suggest statistically significant differences in COVID-19 vaccine acceptance rates; younger HRT and those transplanted after the pandemic are more hesitant to vaccination and female HRT accept booster doses less frequently.

As global focus persists on gender variety and corporate social responsibility, the participation and influence of women in corporate governance, particularly their effect on the environmental, social, and governance (ESG) performance of corporations, have garnered extensive scrutiny. Studies have shown that women usually exhibit a more prudent approach to risk. In corporations with decision-making and tend to care more about long-term corporate interests and social responsibilities, the presence of women in executive roles confers a distinctive edge in enhancing a firm's ESG outcomes. This study explores the influence of women directors' personal characteristics on performance in ESG corporations and the findings suggest that the proportion of female directors has a significant positive impact on the ESG performance of Chinese technology companies. Furthermore, the corporate risk appetite has a positive moderating effect on the relationship between the proportion of female directors and ESG performance. The higher education that female directors get, financial professional background, and long-term experience can more effectively promote the company's ESG performance. This study enhances the theoretical framework of corporate governance and ESG studies, while also offering innovative guidance for firms to enhance their ESG scores and develop effective risk management strategies.

Maize productivity has remained low and has worsened in the wake of a changing climate, resulting in new invasive pests, with earlier designated minor pests becoming major and pathogens transported by pests and/or entering their feeding sites. A study was conducted in 2021 in Kisumu and Makueni counties, Kenya, to determine how different maize cropping systems affect insect diversity, insect damage to maize, and their ability to spread Aspergillus spores in pre-harvest maize. The field experiments used a randomized complete block design with the four treatments maize monocrop, maize intercropped with beans, maize-bean intercrop with Trichoderma harzianum, and push-pull technology. The fall armyworm Spodoptera frugiperda (J.E Smith) (Lepidoptera: Noctuidae) was the most damaging pest in the two regions. The push-pull and the maize-bean intercropping technologies significantly reduced the maize foliage and ear damage caused by the Fall armyworm. Beetles passively spread mycotoxigenic Aspergillus spp. and Fusarium verticillioides on pre-harvest maize. Maize weevils, Sitophilus zeamais Motschulsky, 1855 (Coleoptera: Curculionidae) and Carpophilus dimidiatus Fabricius, 1792 (Coleoptera: Nitidulidae), earwigs, Forficula spp. L. (Dermaptera: Forficulidae) and carpenter ants, Camponotus spp. L. (Hymenoptera: Formicidae) carried the highest number of spores on their exoskeletons. The study stresses the role of insects in the spread of fungi on pre-harvest maize and their possible control by intercropping and other cropping technologies.

Purpose: This study evaluates the impact of Medicaid expansion under the Affordable Care Act (ACA) on melanoma staging at diagnosis, treatment utilization, and 3-year mortality outcomes. The objective is to determine whether Medicaid expansion led to earlier melanoma diagnosis and improved survival rates among non-elderly adults (ages 40-64) by analyzing data from the National Cancer Database (NCDB). Methods: A total of 12,667 patients, aged 40-64, diagnosed with melanoma from 2010 to 2020 were identified using the NCDB. Difference-in-difference (DID) analysis was performed to analyze tumor staging at presentation between Medicaid expansion states and non-Medicaid expansion states both prior to the expansion and after the expansion. Results: Of the total patients 2,307 were from the pre-expansion time period residing in Medicaid Expansion states (MES) and 1,804 in non-Medicaid expansion states. In the post-expansion time period there were 5,571 residing in the MES and 2,985 in the non-MES. DID analysis revealed a decrease in stage IV melanoma at diagnosis (DID -0.222, p <0.001) between MES and non-MES before and after Medicaid expansion. After expansion, in stage IV, the occurrence of primary surgery was 0.42 in non-MES and 0.44 (difference 0.02), DID analysis was not statistically significant. The use of immunotherapy in MES was significantly higher than non-MES after expansion (p<0.001), although DID analysis did not reveal a statistically significant difference. DID analysis showed a statistically significant decrease in 3-year mortality (DID -0.05, p=0.001) between MES and non-MES before and after Medicaid expansion. Conclusions: This study revealed the positive impact of the ACA’s Medicaid expansion on melanoma stage at presentation showing improved access to healthcare services can facilitate the diagnosis of early-stage melanoma and decrease mortality rate.