AbstractLarge numbers of urban lakes are facing issues related to cyanobacteria, commonly known as blue-green algae, resulting in significant threats to humans and animal health due to their production of microtoxins and Anatoxin-A. These toxins induce acute effects including gastrointestinal distress, and respiratory problems, underscoring the need to protect urban lakes to safeguard community health and ecosystem well-being. A comprehensive monitoring program is a critical step to address cyanobacteria-related issues. Monitoring results of dissolved phosphorous, nitrates(N), Total Kjeldahl Nitrogen (TKN), total phosphorous (TP), TSS, and Escherichia coli (E. coli) concentrations, are used to understand the importance of different pathways events during dry conditions (no prior rainfall) and wet events (rainfall during or proceeding monitoring events) plus a microbial source tracking procedure, to understand impacts on growth characteristics of cyanobacteria and microtoxins. The Mann-Kendall Trend Test is used to characterize trends of various parameters (using transitions of ‘wet’ and ‘dry’ to the Lake and within the Lake), to identify the impact of various management strategies and/or the impact of various sources from overland land uses for a) wet events to the Lake, b) dry events to the Lake, c) wet events in the Lake, and d) dry events within the Lake. Microbial source tracking methods are used along the shoreline of Fairy Lake to interpret elevated levels of fecal pollution and E. coli bacteria in water samples, aiding in the identification of pollution sources. Blue-green algae have been observed at least once each year from 2018 to 2023. Microtoxins and Anatoxin-A were present in nine samples with a maximum of 1.72 mg/L and 0.02 mg/L, respectively. Frequent beach closures have occurred every year, raising public concerns regarding both ecological and recreational aspects for Fairy Lake.

Considering the spectrum shortage problem of IoT devices, we introduce a collaborative spectrum sensing (CSS) framework in this paper to identify available spectrum resources, so that IoT devices can access it and meanwhile avoid causing harmful interference to the normal communication of the primary user (PU). However, in the process of the PU’s signal detection in IoT devices, the issue about the stopping time and decision cost arises. To this end, we propose a distributed cognitive IoT model, which includes two IoT devices independently using sequential decision rules to detect the PU. On this basis, we define the stopping time and cost function for IoT devices, and formulate an average cost optimization problem in CSS. To solve this problem, we further regard the optimal stopping time problem as a finite horizon problem, and solve the threshold of the optimal decision rule by dynamic programming. At last, numerical simulation results demonstrate the correctness of our proposal in terms of the global false alarm and miss detection probability, and it always achieves minimal average cost under various cost of each observation taken and thresholds.

This study presented a novel and sustainable method for producing chitin nanocrystals (PA-ChNCs) using phosphoric acid hydrolysis. The produced PA-ChNCs were used as stabilizers for Pickering emulsions and their physicochemical properties as well as stabilization mechanisms were systematically investigated. The PA-ChNCs exhibited small particle sizes and high surface areas, enabling an effective adsorption at the oil/water interface, which prevented coalescence in Pickering emulsions. The particle size and surface charge PA-ChNCs were strongly pH-dependent, which were critical factors for stabilizing Pickering emulsions. The study showed that emulsions with higher O:W ratios (50%) exhibited larger droplets but greater viscosity, forming a stable gel-like matrix that was more stable than emulsions with other O:W ratios after storage for 30 days. Emulsions with higher PA-ChNCs concentrations (2.0 wt%) and higher pH values (pH 10) showed small droplets and high viscosity, leading to stable emulsions. This research contributes to the development of sustainable and effective emulsifiers for use in the food industry, making utilization of seafood waste in an eco-friendly manner possible. Overall, this study highlights the potential of using newly developed PA-ChNCs as stabilizers for Pickering emulsions in food products.

Practical applications of CsPbX3 nanocrystals (NCs) are limited by their poor stability. The formation of heterojunction between CsPbX3 NCs and oxides is an effective means to protect perovskite from polar solvents and other external factors. Significantly improving the stability and photocatalytic properties of the core/shell perovskite is very important for its application in photoelectric and photocatalytic technology. Here, we report the synthesis of asymmetrical CsPbBr3/TiO2 core-shell heterostructure NCs at single particle level by hot injection liquid phase synthesis and sol-gel method, where each CsPbBr3 NCs is partially covered by titanium dioxide. It is shown that the type II arrangement is generated at the heterogeneous interface, which greatly facilitates the separation of electron-hole pairs and increases the carrier transport efficiency. More crucial, due to the protection of titanium dioxide shell, the product has higher long-term stability in humid air compared with bare CsPbBr3 NCs. The asymmetrical core-shell heterostructure prepared in this study not only improves the stability of CsPbX3 NCs, but also provides some ideas for optoelectronic device applications and TiO2-based photocatalysts.

Background: Amidst escalating climate change concerns, sustainable practices in healthcare logistics are critical. This study evaluates the ecological impact and efficiency of medical sample transportation using drones, combustion cars, and electric cars across diverse terrains and weather in Liechtenstein and Switzerland. Methods: We conducted a comparative analysis of CO2 emissions, transport distances, and delivery times for each transportation modality. Data collection involved multiple runs under various conditions, with CO2 emissions measured using onboard systems, and transport efficiency assessed via GPS tracking and time monitoring. Results: Combustion cars exhibited the highest average CO2 emissions at 159.5 grams per kilometer (g/km). Electric cars emitted significantly less, averaging 3.43 g/km, which is 2.15% of combustion car emissions. Drones were the most environmentally friendly, with an average emission of 0.09 g/km, representing 0.07% of combustion car emissions and 2.6% of electric car emissions. Drones also showed substantial transport efficiency, covering 17% shorter distances on flat terrain and 24% shorter in mountainous areas, with time savings ranging from 13% to 80%. Conclusion: This study highlights the potential of drone technology to revolutionize healthcare logistics by reducing environmental impact and optimizing operational efficiency. Integrating drones can significantly lower the carbon footprint, improve sample integrity, and enhance patient care, promoting a greener, more resilient healthcare system.

Proposed fundamental laws of biology and a model of health and disease underscore the importance of the lymphatic system. The lymphatics are responsible for two of the laws of biology and the fulcrum of health and disease balancing proliferation with regeneration through the immune system. It is responsible for protection from the environment and repair of senile and damaged tissue. Life is constantly bombarded by forces that increase entropy. Lymphatics provide negative entropy to maintain health. Lymphatics help maintain cellular homeostasis removing products of metabolism. Using these principles, the role of lymphatics is investigated in salt sensitivity hypertension, cardiorenal system, the new pillar of heart failure and kidney disease - Sodium-Glucose Transport Protein 2 (SGLT2) Inhibitors, and brain diseases. The realization of organ lymphatics in maintenance of health and disease opens the avenue to new therapeutics. This is the unrealized potential of lymphatic study.

Semisolid casting can provide excellent castings, but the nature of the pore-forming mechanisms has not been properly clarified. In the current communication, it was suggested that hydrogen precipitated during slurry making might have a decisive role in the formation of both gas and shrinkage porosity. Intensive stirring at the end of the slurry making process may act as a degassing step. Without the intense stirring, structures of primary slurry particles form around the hydrogen pores, strongly affecting pore formation and feeding during the intensification stage.

Infrared thermography has already been proven to be a significant method in non-destructive evaluation since it gives information with immediacy, rapidity and low cost. However, the thorniest issue for wider application of IRT is the quantification. In this work, we proposed a specific depth quantifying technique by employing the Gated Recurrent Units (GRU) in composite material samples via pulsed thermography (PT). Carbon Fiber Reinforced Polymer(CFRP) embedded with flat bottom holes were designed via Finite Element Method (FEM) modeling in order to precisely control the depth and geometrics of the defects. The GRU model automatically quantified the depth of defects presented in the CFRP material. The proposed method evaluated the accuracy and performance of synthetic CFRP data from FEM for defect depth predictions.

The present study discusses how adopting cryptos affects financial inclusion in developing economies. Primary constructs like Financial Inclusion (FI), Perceived Economic Empowerment (PEE), Trust in Financial Institutions (TFI), User Satisfaction (US), and Cryptocurrency Adoption (CA) were tested through Structural Equation Modeling (SEM). The results indicated that CA significantly and positively influenced FI, US, TFI, and PEE. These relationships extend to the interaction effects: US, TFI, and PEE all positively related to FI. It is a reflection of cryptocurrencies as an opportunity to redress most of the afflictions characteristic of traditional finance systems and to promote financial inclusion and economic empowerment in developing countries. Future research should also investigate whether digital literacy and regulatory environments support cryptocurrency access.

Proton Exchange Membrane Fuel Cell (PEMFC) is a fast-developing battery technology, and the key to its reliability and lifespan improvement lies in the accurate assessment of durability. However, the degradation mechanism of PEMFC is hard to determine and its internal parameters are highly coupled. Thus, the development of the more accurate life prediction model that meets the actual scenarios is urgent to investigate. To solve this problem, a multi-feature fusion life prediction method based on Temporal Convolutional Network-Gated Recurrent Unit (TCN-GRU) is proposed. A TCN algorithm is used as the prediction base model, and two GRU modules are included to the model to strengthen the model expression ability and improve its predictive accuracy. Two widely recognized datasets and two operating conditions are utilized for model training and prediction, respectively. Comparisons are made with single-feature parameter models in terms of Root Mean Square Error (RMSE) and Determination Coefficient (R2). The results show that the prediction accuracy of the TCN-GRU multi-feature fusion model is higher than that of the single-feature models in terms of stability and anti-interference under both operating conditions. Furthermore, with the increase of input feature parameters, the TCN-GRU model is closer to the real value, which proves once again that the proposed model can meet the accuracy requirements of the life prediction of PEMFC.

Photodynamic therapy has emerged as a non-invasive treatment modality for various diseases, leveraging photosensitizing compounds to induce localized cytotoxicity upon light activation. This review explores the isolation and characterization of photosensitizing compounds sourced from microalgae, focusing on their potential applications in photodynamic therapy. Microalgae represent a rich source of bioactive molecules, including chlorophylls, phycobiliproteins, and carotenoids, which exhibit inherent photosensitizing properties. Methodologies for the extraction and purification of these compounds from different microalgal species are discussed, emphasizing the importance of optimizing extraction techniques to enhance yield and purity. Characterization techniques such as UV-Vis absorption spectroscopy, fluorescence spectroscopy, and mass spectrometry are highlighted for elucidating the chemical structures and photophysical properties of isolated compounds. Furthermore, the review examines the photodynamic efficacy of microalgae-derived photosensitizers through in vitro and in vivo studies, assessing their cytotoxic effects on cancer cells and antimicrobial activity against pathogens. The integration of microalgae-derived photosensitizers into PDT protocols represents a promising avenue for developing sustainable and effective therapeutic strategies, underscoring the potential of these natural compounds in advancing biomedical applications.

This paper introduces an intelligent model that combines military expertise with the latest ad-vancements in machine learning (ML) and Geographic Information Systems (GIS) to support humanitarian demining decision-making processes. The model is based on direct input and val-idation from field decision-makers for their practical applicability and effectiveness. With a survey polling the inputs of demining experts, 95% of the responses came with an affirmation of the potential of the model to reduce threats and increase operational efficiency. It includes mili-tary-specific factors that factor in the proximity to strategic locations as well as environmental variables like vegetation cover and terrain resolution. With Gradient Boosting algorithms such as XGBoost and LightGBM, the accuracy rate is almost 97%. Such precision levels further enhance threat assessment, better allocation of resources, and around a 30% reduction in the cost and time of conducting demining operations, signifying a strong synergy of human expertise with algo-rithmic precision for maximal safety and effectiveness in demining

Amorphous Indomethacin has enhanced bioavailability over its’ crystalline forms, yet amorphous forms can still possess a wide variety of structures. Here, Empirical Potential Structure Refinement (EPSR) has been used to provide accurate molecular models on the structure of five different amorphous Indomethacin samples, that are consistent with their high energy x-ray diffraction patterns. It is found that the majority of molecules in amorphous Indomethacin are non-bonded or bonded to one neighboring molecule via a single hydrogen bond, in contrast the doubly bonded dimers found in the crystalline state. The EPSR models further indicate a substantial variation in hydrogen bonding between different amorphous forms, leading to a diversity of chain structures not found in any known crystal structures. The majority of hydrogen bonds are associated with the carboxylic acid group, although a significant number of amide hydrogen bonding interactions are also found in the models. Evidence of some dipole-dipole interactions are also observed in the more structurally ordered models. The results are consistent a distribution of Z-isomer intra-molecular type conformations in the more disordered structures, that dis-tort when stronger inter-molecular hydrogen bonding occurs. The findings are supported by 1H and 2H NMR studies of the hydrogen bond dynamics in amorphous Indomethacin.

A monolayer of endothelial cells (ECs) lines the lumen of blood vessels and as such provides a semi-selective barrier between the blood and the interstitial space. Compromise of the lung EC barrier due to inflammatory or toxic events may results in pulmonary edema, which is a cardinal feature of acute lung injury (ALI) and its more severe form, the acute respiratory distress syndrome (ARDS). The EC functions are controlled, at least in part, via epigenetic mechanisms mediated by histone deacetylases (HDACs). Zinc-dependent HDACs represent the largest group of HDACs and are activated by Zn2+. Members of this HDAC group are involved in the epigenetic regulation primarily via modifying the structure of chromatin upon removal of acetyl groups from histones. In addition, they can deacetylate many non-histone histone proteins, including those located in extra nuclear compartments. Recently, the therapeutic potential of inhibiting zinc-dependent HDACs for EC barrier preservation has gained momentum. However, the role of specific HDAC subtypes in EC barrier regulation remains largely unknown. This review aims to provide an update on the role of zinc-dependent HDACs in endothelial dysfunction and its related diseases. We will broadly focus on biological contributions, signaling pathways and transcriptional roles of HDACs in endothelial pathobiology associated mainly with lung diseases and we will discuss the potential of their inhibitors for lung injury prevention.

This study investigated modifications in the ubiquitin proteasome system (UPS) in a mouse model of type 2 diabetes mellitus (T2DM) and their relationship to heart complications. db/db mice heart tissues were compared with WT mice tissues using RNA sequencing, qRT-PCR, and protein analysis to identify cardiac UPS modifications associated with diabetes. The findings unveiled a distinctive gene profile in the hearts of db/db mice with decreased levels of nppb mRNA and increased levels of Myh7, indicating potential cardiac dysfunction. mRNA levels of USP18 (deubiquitinating enzyme), psmb8, and psmb9 (proteasome β-subunits) were downregulated in db/db mice while mRNA levels of RNF167 (E3 ligase) were increased. Corresponding LMP2 and LMP7 proteins were downregulated in db/db mice, and RNF167 was elevated in Adult diabetic mice. Reduced expression of LMP2 and LMP7, along with increased RNF167 expression, may contribute to future cardiac deterioration commonly observed in diabetes. This study enhances our understanding of UPS imbalances in the hearts of diabetic mice and raises questions about the interplay between the UPS and other cellular processes, such as autophagy. Further exploration in this area could provide valuable insights into the mechanisms underlying diabetic heart complications and potential therapeutic targets.

The performance of 5 forecasting models was investigated for predicting nursery mortality using the master table built for 3,242 groups of pigs (~ 13 million animals) and 42 variables, which concerned the pre-weaning phase of production and conditions at placement in growing sites. After training and testing each model’s performance through cross-validation, the model with the best overall prediction results was the Support Vector Machine model in terms of Root Mean Squared Error (RMSE=0.406), Mean Absolute Error (MAE=0.284), and Coefficient of Determination (R2=0.731). Subsequently, the forecasting performance of the SVM model was tested on a new dataset containing 72 new groups, simulating ongoing and near real-time forecasting analysis. Despite a decrease in R2 values on the new dataset (R2=0.554), the model demonstrated high accuracy (77.78%) for predicting groups with high (5>%) or low (5<%) nursery mortality. This study demonstrated the capability of forecasting models to predict the nursery mortality of commercial groups of pigs using pre-weaning information and stocking conditions variables collected post-placement in nursery sites.

As the use of microbial inoculants in agriculture rises, it becomes important to understand how the environment may influence microbial ability to promote plant growth. This work examines whether there are light dependencies in the biological functions of Azospirillum brasilense, a commercialized prolific grass-root colonizer. Though classically defined as non-phototrophic, A. brasilense possesses photoreceptors that could perceive light conducted through its host’s roots. Evidence for light dependency of four microbial processes were examined and noted: biological nitrogen fixation (BNF), auxin biosynthesis, ATP biosynthesis, and iron and manganese uptake. Functional mutants of A. brasilense were leveraged and studied in light and dark environments: HM053 (high BNF and auxin production), ipdC (capable of BNF, deficient in auxin production), and FP10 (capable of auxin production, deficient in BNF). HM053 exhibited the highest rate of nitrogenase activity with the greatest light dependency comparing iterations in light and dark environments. The ipdC mutant showed similar behavior with relatively lower nitrogenase activity observed, while FP10 did not show a light dependency. Auxin biosynthesis showed strong light dependencies in HM053 and FP10 strains, but not for ipdC. Iron is involved in the BNF biological process, and light dependency was observed for microbial 59Fe2+ uptake in HM053 and ipdC, but not FP10. Surprisingly, a light dependency for 52Mn2+ uptake was only observed in ipdC. Finally, ATP biosynthesis was sensitive to light across all three mutants favoring blue light over red light compared to darkness with observed ATP levels in descending order for HM053 > ipdC > FP10.

Abstract: Background: Non-invasive acquistion of beat-to-beat pulse transit time (PTT) via piezoelectric/piezocapacitive sensors (PES/PCS) may expand perioperative hemodynamic monitoring. This study evaluated the ability for PTT via PES/PCS to correlate with systolic, diastolic, and mean invasive blood pressure (SBPIBP, DBPIBP, and MAPIBP) and to detect SBPIBP fluctuations. Methods: PES/PCS and IBP measurements were performed in 20 patients undergoing abdominal, urological, and cardiac surgery. A Pearson’s correlation analysis (r) between 1/PTT and IBP was performed. The predictive ability of 1/PTT with changes in SBPIBP was determined by area under the curve (reported as AUC, sensitivity, specificity). Results: Significant correlations between 1/PTT and SBPIBP were found for PES (r=0.64) and PCS (r=0.55) (p<0.01), as well as MAPIBP/DBPIBP for PES (r=0.6/0.55) and PCS (r=0.5/0.45) (p<0.05). A 7% decrease in 1/PTTPES predicted a 30% SBPIBP decrease(0.82, 0.76, 0.76), while a 5.6% increase predicted a 30% SBPIBP increase (0.75, 0.7, 0.68). A 6.6% decrease in 1/PTTPCS detected a 30% SBPIBP decrease (0.81, 0.72, 0.8), while a 4.8% 1/PTTPCS increase detected a 30% SBPIBP increase (0.73, 0.64, 0.68). Conclusions: Non-invasive beat-to-beat PTT via PES/PCS demonstrated significant correlations with IBP and detected significant changes in SBPIBP. Thus PES/PCS as a novel sensor technology may augment intraoperative hemodynamic monitoring during major surgery.

Neck circumference (NC), neck circumference to height ratio (NHtR) and neck circumference to weight ratio (NWtR) appear to be good candidates for the non-invasive management of non-alcoholic fatty liver disease (NAFLD). This study aimed to evaluate the ability of routine variables to assess and manage NAFLD in participants with obesity and NAFLD included in a 2-year nutritional intervention program. Anthropometric measurements, biochemical variables and imaging techniques were performed at different study time-points (baseline, 6, 12 and 24 months). The nutritional intervention significantly improved all anthropometric measurements as well as the glucose profile and the hepatic enzymes. NC and neck ratios combined with ALT levels and HOMA-IR showed good prediction ability for the hepatic fat content and hepatic steatosis at all the study time-points in a ROC analysis. The prediction ability of the combination panels improved when the weight loss variable was also considered. NC and neck ratios are easy anthropometric measurements that in combination with routine biochemical variables (ALT and HOMA-IR) showed good prediction ability of NAFLD. More research studies are necessary to validate the utility of these simple and easy variables as surrogate markers of NAFLD since their application could improve the prevention and management of this prevalent disease.

Secretory leucoprotease inhibitor (SLPI) has multifaceted functions, including inhibition of protease activity, antimicrobial functions, and anti-inflammatory properties. In this study, we show that SLPI plays a role in controlling pulmonary P. aeruginosa infection. Mice lacking SLPI were highly susceptible to P. aeruginosa infection, however had no difference in bacterial burden. Utilising a model of P. aeruginosa LPS-induced lung inflammation, human recombinant SLPI (hrSLPI) administered intraperitoneally suppressed the recruitment of inflammatory cells in the bronchoalveolar lavage fluid (BALF) and resulted in reduced BALF and serum levels of inflammatory cytokines and chemokines. This anti-inflammatory effect of hrSLPI was similarly demonstrated in a systemic inflammation model induced by intraperitoneal injection of LPS from various bacteria or lipoteichoic acid, highlighting the broad anti-inflammatory properties of hrSLPI. Moreover, in bone-marrow-derived macrophages, hrSLPI reduced LPS-induced phosphorylation of p-IkB-α, p-IKK-α/β, p-P38, demonstrating that the anti-inflammatory effect of hrSLPI was due to the inhibition of the NFB and MAPK pathways. In conclusion, administration of hrSLPI attenuates excessive inflammatory responses and is therefore, a promising strategy to target inflammatory diseases such as acute respiratory distress syndrome or sepsis and could potentially be used to augment antibiotic treatment.

Uveal melanoma is the most common primary intraocular malignancy in adults characterized by insidious onset and poor prognosis strongly associated with tumor size and the presence of distant metastases, most commonly in the liver. Contrary to most tumor identification, biopsy followed by pathological exam is not recommended in ophthalmic oncology. Therefore, early and non-invasive diagnosis is essential to enhance patients’ chances for early treatment possibilities. We reviewed imaging modalities currently used in the diagnosis of uveal melanoma, i.e., fundus imaging, ultrasonography (US), optical coherence tomography (OCT), single-photon emission computed tomography (SPECT), positron emission tomography/computed tomography (PET/CT), magnetic resonance imaging (MRI), fundus fluorescein angiography (FFA), indocyanine green angiography (ICGA), fundus autofluorescence (FAF). The principle of imaging techniques was briefly explained, along with their role in the diagnostic process and a summary of their advantages and limitations. Further, the experimental data and the advancements in imaging modalities were searched. We described their innovations, showed current usage and research, and explained the possibilities of utilizing them to diagnose uveal melanoma and their potential application in personalized medicine such as theranostics.

Recently, there has been renewed interest in the performance, functionality, and sustainability of traditional small-scale storage interventions (check dams, farm bunds and tanks) used across India for the improvement of local water security. The Central Groundwater Board of India is en-couraging the construction of such interventions for the alleviation of water scarcity. It is of critical importance to understand the hydrological effect of these interventions at basin scales to maximise their effectiveness. The quantification of small-scale interventions in hydrological modelling is often neglected, especially in large-scale modelling exercises. A bespoke version of the GWAVA model was developed to assess the impact of interventions on the water balance of the Cauvery Basin and two smaller sub-catchments. Model results demonstrate that farm bunds appear to have a negligible effect on the estimated average annual simulated streamflow at the outlets of the two sub-catchments and the basin whereas tanks and check dams have a more significant effect. In-terventions generally were found to increase evaporation losses across the catchment. The model adaption used in this study provides a step-change in the conceptualisation and quantification of the consequences of small-scale storage interventions in large- or basin-scale hydrological models.

The negative effect of COVID-19 pandemic has reach world economy due to absence from work for SARS-CoV-2 infection in workers, among other things. However, some economic areas are essential to society and people must continue working outside home, to support economic reactivation; their serological profile could be different from global population. Cross-sectional study. Workers from health, construction, public transportation, public force, bike delivery messengers, independent or informal commerce areas, and residents of Bucaramanga or its metropolitan area were invited to participate. All participants self-completed a virtual survey and a blood test was taken to assess IgG and IgM with ARC COV2 test. Seroprevalence was estimated considering a complex survey design, correcting for finite population effect and adjusting for test performance. 7.045 workers were enrolled; 59.9% were women, most were residents of Bucaramanga and working in health occupations. Global adjusted seroprevalence was 19.5% (IC95% 18.6 - 20.4), being higher for Girón [27.9% (CI95% 24.5 - 31.30]). Workers with multiple contact with people during working hours or using public transportation to go to work had higher frequency of seropositivity for SARS-CoV-2. Seroprevalence among workers living in these four municipalities from the Colombian northeast area is still low.

Over two years (2012-2014), 719 nasopharyngeal samples were collected from 6 weeks to 12 months old infants presenting at emergency department with moderate to severe acute bronchiolitis. Viral testing was performed and we found 98% positive samples including 90% Respiratory Syncytial Virus, 34% Human Rhino Virus, and 55% viral co-detections with predominance of RSV/HRV co-infections (30%). Interestingly, we found that the risk of being infected by HRV is higher in the absence of RSV, suggesting interferences or exclusion mechanisms between these two viruses. Conversely, Coronavirus infection had no impact on the likelihood of co-infection involving HRV and RSV. Bronchiolitis is the leading cause of hospitalizations in infants before 12 months of age, and many questions about its role in the later chronic respiratory diseases (asthma and chronic obstructive pulmonary disease) do exist. Role of virus detection and burden of viral codetections need to be further explored, in order to understand the physiopathology of chronic respiratory diseases, a major public health issue.

Steroid analysis is important in the clinical assessment of endocrine function in health and disease. Although tandem mass spectrometry methods coupled with chromatographic separation are considered the gold standard analytical technique in this setting, enabling profiling of multiple steroids in a single sample, sample processing can be labour-intensive. Here we present a simple, efficient automated 96-well Supported Liquid Extraction method with dichloromethane/isopropanol as organic solvent, carried out on a Extrahera automated sample handler (Biotage), which completes sample preparation of 80 plasma samples (200µL) in 90 minutes. Compounds were separated on a Kinetex C18 column (150x3mm;2.6um) using a mobile phase of methanol and water (0.1% formic acid). The run time was 16 minutes on a Nexera uHPLC system (Shimadzu) with a QTrap 6500+ linear ion trap mass spectrometer (AB Sciex). Precisions ranged 8.1 to 18.1% RSD, bias -10.1-5.8%, and extraction recoveries 73.5-111.9%. LOQs ranged between 0.025–0.500 ng/mL.

BACKGROUND: From March to April 2020, Spain was the center of the SARS-CoV-2 pandemic, particularly Madrid with approximately 30% of the cases in Spain. The aim of this study is to report the suspected serious adverse drug reactions (SADRs) in COVID-19 patients versus non-COVID-19 patients detected by the prospective pharmacovigilance program based on automatic laboratory signals (ALSs) in the hospital (PPLSH) during that period. We also compared the results with the suspected SADRs detected during the same period for 2019. METHODS: All ALSs that reflected potential SADRs (including neutropenia, pancytopenia, thrombocytopenia, anemia, eosinophilia, leukocytes in cerebrospinal fluid, hepatitis, pancreatitis, acute kidney injury, rhabdomyolysis and hyponatremia were prospectively monitored in hospitalized patients during the study periods. We analyzed the incidence and the distribution of causative drugs for the COVID-19 patients. RESULTS: The incidence rate of SADRs detected in the COVID-19 patients was 760.63 (95% CI 707.89–816.01) per 10,000 patients, 4.75-fold higher than the SADR rate for non-COVID-19 patients (160.15 per 10,000 patients,95% CI 137.09–186.80), and 5.84-fold higher than the SADR rate detected for the same period in 2019 (130.19 per 10,000 patients, 95% CI 109.53–154.36). The most frequently related drugs were tocilizumab (59.84%), dexketoprofen (13.93%), azithromycin (8.43%), lopinavir-ritonavir (7.35%), dexamethasone (7.62%), and chloroquine/hydroxychloroquine (6.91%). CONCLUSIONS: The incidence rate of SADRs detected by the PPSLH in patients with COVID-19 was 4.75-fold higher than that of the non-COVID-19 patients. Caution is recommended when using medications for COVID-19 patients, especially drugs that are hepatotoxic, myotoxic, and those that induce thromboembolic events.

Oleylamine capped WS2 nanostructures were successfully formed at 320 °C via a relatively simple colloidal route. SEM and TEM analyses showed that the 3D nanoflowers that were initially formed disintegrated into 2D nanosheets after prolonged incubation. XPS and XRD analyses confirmed oxidation of WS2 into WO3. Sensors based on these oleylamine capped WS2 nanoflowers and nanosheets still showed a change in electrical response towards various concentrations of NH3 vapour at room temperature in a 25% relative humidity background despite the oxidation. The nanoflowers exhibited n-type response while the nanosheets displayed a p-type response towards NH3 exposure. The nanoflower based sensors showed better response to NH3 vapour exposure than the nanosheets. The sensors showed a good selectivity towards NH3 relative to acetone, ethanol, chloroform and toluene. Meanwhile, a strong interference of humidity to the NH3 response was displayed at high relative humidity levels. The results demonstrated that oleylamine limited the extent of oxidation of WS2 nanostructures. The superior sensing performance of the nanoflowers can be attributed to their hierarchical morphology which enhances the surface area and diffusion of the analyte.

There is a current pandemic of a new type of coronavirus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The number of confirmed infected cases has been rapidly increasing. This paper analyzes the characteristics of SARS-CoV-2 in comparison with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV), Middle East Respiratory Syndrome Coronavirus (MERS-CoV) and influenza. COVID-19 is similar to the diseases caused by SARS-CoV and MERS-CoV virologically and etiologically, but closer to influenza in epidemiology and virulence. The comparison provides a new perspective for the future of the disease control, and offers some ideas in the prevention and control management strategy. The large number of infectious people from the origin, and the highly infectious and occult nature have been two major problems, making the virus difficult to eradicate. We thus need to contemplate the possibility of long-term co-existence with COVID-19.

In the past decades, several new diseases have emerged in new geographical areas, with pathogens including Ebola, Zika, Nipah, and coronaviruses (CoVs). Recently, a new type of viral infection has emerged in Wuhan City, China, and initial genomic sequencing data of this virus does not match with previously sequenced CoVs, suggesting a novel CoV strain (2019-nCoV), which has now been termed as severe acute respiratory syndrome CoV-2 (SARS-CoV-2). Although Coronavirus disease 2019 (COVID-19) is suspected to originate from an animal host (zoonotic origin) followed by human-to-human transmission, the possibility of other routes such as food-borne transmission should not be ruled out. Compared to diseases caused by previously known human CoVs, COVID-19 shows less severe pathogenesis but higher transmission competence, as is evident from the continuously increasing number of confirmed cases globally. Compared to other emerging viruses such as Ebola virus, avian H7N9, SARS-CoV, or MERS-CoV, SARS-CoV-2 has shown relatively low pathogenicity and moderate transmissibility. Codon usage studies suggest that this novel virus may have been transferred from an animal source such as bats. Early diagnosis by real-time PCR and next-generation sequencing has facilitated the identification of the pathogen at an early stage. Since, no antiviral drug or vaccine exists to treat or prevent SARS-CoV-2, potential therapeutic strategies that are currently being evaluated predominantly stem from previous experience with treating SARS-CoV, MERS-CoV, and other emerging viral diseases. In this review, we address epidemiological, diagnostic, clinical, and therapeutic aspects, including perspectives of vaccines and preventive measures that have already been globally recommended.

Rocas Atoll is a unique environment in the Equatorial Atlantic Ocean, hosting a large number of endemic species and studies on the chemical diversity emerging from this biota are rather scarce. Therefore, the present work aims to assess the metabolomic diversity and pharmacological potential of the microbiota from Rocas Atoll. A total of 76 bacteria were isolated and cultured in liquid culture media to obtain crude extracts. About one third (34%) of these extracts were considered cytotoxic against human colon adenocarcinoma HCT-116 cell line. 16S rRNA gene sequencing analysis revealed that the bacteria producing cytotoxic extracts are mainly from the Actinobacteria phylum, including Streptomyces, Salinispora, Nocardiopsis and Brevibacterium genera, and in a smaller proportion from Firmicutes phylum (Bacillus). The search in the GNPS spectral library unveiled a high chemodiversity being produced by these bacteria, including rifamycins, antimycins, desferrioxamines, ferrioxamines, surfactins, surugamides, staurosporine and saliniketals, along with several unidentified compounds. Using an original approach, molecular network successfully highlighted groups of compounds responsible for the cytotoxicity of crude extracts. DEREPLICATOR+, a recently developed in silico tool (GNPS), allowed the identification of derivatives of the macrolide novonestimycin, as the cytotoxic compounds into the extracts produced by Streptomyces BRB-298 and BRB-302. Overall, these results highlighted the pharmacological potential of bacteria from this singular Atoll.

Easter Island (Rapa Nui) deforestation has traditionally been viewed as a single event, synchronous in time and space across the island and caused by Polynesian settlers. However, recent studies have challenged this idea introducing the concept of spatio-temporal heterogeneity and suggesting a role for climate change. This paper presents a continuous paleovegetation record of the last millennium (~960 to ~1710 CE), based on palynological analysis of a peat core from Lake Kao. During this time interval, deforestation was gradual, with three main pulses at ~1070 CE, ~1410 CE and ~1600 CE, likely driven by drought, anthropogenic practices (mostly fire) or the coupling of both. Some forest regeneration trends have been documented after the first and the second deforestation pulses. Forests were totally removed by 1600 CE, coinciding with the full permanent human settlement of the Kao area. Comparison with other continuous palynological records available for the last millennium (Aroi marsh and Lake Raraku), confirms that forest clearing was heterogeneous in time and space, rather than synchronous island-wide.

There is evidence that spaceflight poses acute and late risks on the central nervous system. To explore possible mechanisms, the proteomic changes following spaceflight in mouse brain were characterized. Space Shuttle Atlantis (STS-135) was launched at the Kennedy Space Center on a 13-day mission. Within 3–5 hours after landing, brain tissue was collected to evaluate protein expression profiles using quantitative proteomic analysis. Our results showed that there were 26 proteins that were significantly altered after spaceflight in the grey and/or white matter. While there was no overlap between the white and grey matter in terms of individual proteins, there was overlap in terms of function, synaptic plasticity, vesical activity, protein/organelle transport, and metabolism. Our data demonstrate that exposure to the spaceflight environment induces significant changes in protein expression related to neuronal structure and metabolic function. This might lead to a significant impact on brain structural and functional integrity that could affect the outcome of space missions.

In this paper, we investigate the use of fat tissue as a communication channel between in-body, implanted devices at R-band frequencies (1.7–2.6 GHz). The proposed fat channel is based on an anatomical model of the human body. We propose a novel probe that is optimized to efficiently radiate the R-band frequencies into the fat tissue. We use our probe to evaluate the path loss of the fat channel by studying the channel transmission coefficient over the R-band frequencies. We conduct extensive simulation studies and validate our results by experimentation on phantom and ex-vivo porcine tissue, with good agreement between simulations and experiments. We demonstrate a performance comparison between the fat channel and similar waveguide structures. Our characterization of the fat channel reveals propagation path loss of 1.4 dB and 3.8 dB per 20 mm for phantom and ex-vivo porcine tissue, respectively. These results demonstrate that fat tissue can be used as a communication channel for high data rate intra-body networks.

Angiogenesis is a hallmark of ovarian cancer (OC) it promotes rapid cell growth and the associated metastasis. Identifying new bioactive compounds to target angiogenesis may provide valuable paradigms as therapeutic strategies. Melatonin is a well-characterized indoleamine that possesses important anti-angiogenic properties in a set of aggressive solid tumors. Herein, we evaluated the role of melatonin therapy on the angiogenic signaling pathway in OC of an ethanol-preferring rat model that mimics the same pathophysiological conditions occurring in women. OC was chemically induced with a single injection of 7,12-dimethylbenz(a)anthracene (DMBA) under the ovarian bursa. After the rats developed serous papillary OC, half of the animals received i.p. injections of melatonin (200 µg/100 g body weight/day) for 60 days. Serum levels of melatonin were higher following therapy, and the expression of its receptor MT1R was significantly increased in OC-bearing rats, regardless of ethanol intake. TGFB1, a transforming growth factor-beta1, was reduced only after melatonin treatment. Importantly, vascular endothelial growth factor (VEGF) was severely reduced after melatonin therapy in animals given or not given ethanol. Conversely, the levels of VEGF receptor 1 (VEGFR1) was diminished after ethanol consumption, regardless of melatonin therapy, and VEGFR2 was only reduced following melatonin. Hypoxia-inducible factor (HIF)-1α was augmented with ethanol consumption, and notably, melatonin significantly reduced their levels. Collectively, our results suggest that melatonin attenuates angiogenesis in OC of an animal model of ethanol consumption; this provides a possible complementary therapeutic opportunity for concurrent OC chemotherapy.

Applying the iterative methodology for dimensionality reduction/feature selection using categorical gradient boosted trees, as it has been defined in and has been successfully applied on similar datasets in and , on a dataset consisted of 12708 gene expressions coming from 5052 individuals from 105 studies, we classify whether a person has acute myeloid leukaemia (AML) or is healthy. A CatBoost model on a dataset with reduced dimensions of 72 genes reached a ROC-AUC score of 0.9973 using ten fold cross validation (10CV) and ROC-AUC: 0.9988 on an inference dataset. We further investigate the options of using less genes that potentially could be used in clinical practise and genes than have not been associated to AML yet, or to blood cancer in general. On the same folds of the 10CV and on the same inference dataset the performance of the tuned CatBoost models show that it could be the case that not all genes with an association to AML have been found yet and 19 genes could be enough to predict AML: CatBoost63 (ROC-AUC: 0.9941, Test: 0.9942), CatBoost19: (ROC-AUC: 0.9946, Test: 0.9941) and CatBoost15: (ROC-AUC: 0.9922, Test: 0.9900). In addition, our results verify that a gene diagnostic test for AML could be possible in the future as well as further research is needed on these 15 genes that it could lead to new and better drugs.

Clockwork fermions represent a novel theoretical construct in high-energy physics, addressing such fundamental issues as mass hierarchies and dark matter. This review provides an examination of the theoretical underpinnings of clockwork fermions, their implications for particle physics, and the current state of experimental validations. Clockwork fermions represent a paradigm in particle physics, elegantly addressing the hierarchy problem and offering insights into the generation of small neutrino masses. We provide an analysis of the clockwork mechanism, emphasizing its theoretical innovation and the unique mass hierarchies it produces. We examine recent experimental efforts, including collider searches and direct detection experiments, that place constraints on clockwork models, while also exploring their potential cosmological implications.

In this paper, we study the asymptotic properties of slowly varying functions of one real variable in the sense of Karamata. We establish analogs of fundamental theorems on uniform convergence and integral representation for slowly varying functions with remainder depending on the types of remainder. We also prove several important theorems on the asymptotic representation of integrals of Karamata functions. Under certain conditions, we observe a “narrowing” of classes of slowly varying functions concerning the types of remainder. At the end of the paper, we discuss the possibilities of application of slowly varying functions in the theory of stochastic branching systems. In particular, under the condition of the finiteness of the moment of the type Exlnx for the particle transformation intensity, it is established that the property of slow variation with remainder is implicitly present in the asymptotic structure of a non-critical Markov branching random system.

Okra, a widely grown vegetable in many regions, often suffers from freshness loss during transportation, causing significant waste. Factors like variety, environment, maturity, and handling affect its quality. Current methods for checking okra tenderness are slow and prone to mistakes, so we need a better, non-damaging method. This study aims to use a device on a robot arm to assess okra freshness and tenderness. We tested 120 okra pods, storing some in a cold chamber for 24 hours (considered tender) and others at room temperature for two days before moving them to a cold environment for five more days (considered not tender). We used a force sensor on a robot arm to measure okra hardness without damaging it, then did tenderness tests. We found that certain sensor data, like the first slope (S1) and the difference between the maximum value and the first overshoot (Os), were good predictors of tenderness, with an accuracy rate of nearly 80%. We also validated this non-damaging method with weight loss, compression, and puncture tests, achieving a 95.5% accuracy rate in distinguishing between tender and non-tender okra pods.

Background. Epithelial ovarian cancer (EOC) is the deadliest gynecological malignancy worldwide. Brain metastasis (BM) is quite an uncommon presentation. However, the likelihood of central nervous system (CNS) metastasization should be considered in the context of disseminated disease. The therapeutic management of BMs is an unmet clinical need, to date. Case presentation. We identified across different Cancer Centers six cases of both BRCA wild-type and BRCA-mutated EOC spreading to the CNS. They presented either with a single brain lesion or with multiple lesions and most of them had intracranial-only disease. All cases received Poly-ADP ribose polymerase inhibitor (PARPi) maintenance, as by clinical practice, for a long time within a multimodal treatment approach. We also provide an insight into the available body of work regarding the management of this intriguing disease setting, with a glimpse of future therapeutic challenges. Conclusion. Despite the lack of unanimous guidelines, multimodal care pathways should be encouraged for optimal disease control of this unfortunate patient’s subset. Albeit not being directly investigated in BM patients, the PARPi maintenance is deemed to have a valuable role in this setting. Prospective research, aimed to implement worthwhile strategies in the multimodal patient journey of BMs from EOC, is eagerly awaited.

This study aimed to explore the intricate relationship between mitochondrial dysfunction, infections, and neuroinflammation, focusing specifically on the impact of pathogenic epitopes of Epstein-Barr Virus (EBV) nuclear antigen 1 (EBNA1) in a mouse model of mitochondrial dysfunctions. The investigation included female middle-aged PARK2^-/- and C57BL/6J wild-type mice immunized with EBNA1_386-405 or with active experimental autoimmune encephalomyelitis (EAE) induction by myelin oligodendrocyte glycoprotein (MOG)_35-55 peptide. PARK2^-/- mice developed more severe EAE than wild-type mice. Following immunization with EBNA1_386-405, only PARK2^-/- exhibited symptoms resembling EAE. During the acute phase, PARK2^-/- mice immunized with either MOG_35-55 or EBNA1_386-405 exhibited similar infiltration of T cells and macrophages in the spinal cord and decreased GFAP expression in the brain. However, EBNA1_386-405 -immunized PARK2^-/- mice showed significantly increased frequencies of CD8a+ T cells and CD11c+ B cells, and distinct cytokine profiles in the periphery compared to wild-type controls. These findings highlight the role of EBV in exacerbating inflammation, particularly in the context of mitochondrial deficiencies.

The delayed effects of radiation alone and combined with skin injury on the kidney are poorly understood. We aimed to unravel and compare the inflammatory, oxidative stress, and survival signaling pathways in the kidney cortex before mice manifested renal dysfunction after these two injuries. Mice were analyzed 30 days post irradiation (9.5 Gy for radiation alone, 9.0 Gy for radiation combined with a skin wound). Radiation alone did not significantly alter BUN, NGAL, or KIM-1 protein levels, indicating preserved kidney function. However, the combined injury had increased KIM-1 protein levels, indicating a nuanced effect on renal health. Radiation and combined injury activated distinct inflammatory pathways. Radiation increased STAT3-Y705 phosphorylation, while combined injury boosted STAT1-Y701 phosphorylation. Additionally, radiation increased mRNA abundance of IFNγR1, IFNγR2, heparanase and IL-10, while combined injury tended to increase heparanase mRNA levels and reduced IL-4 mRNA levels. Both injuries increased the abundance of HO-1 protein, indicating oxidative stress, but radiation alone also reduced MnSOD and catalase proteins. Both injuries promoted AKT1-S473 phosphorylation and diminished p53 protein levels, suggesting inhibition of apoptosis. In summary, despite the distinct activation of inflammatory and oxidative stress pathways, both radiation alone and combined injury activated protective mechanisms such as HO-1 and AKT1, offering insights into molecular events before manifesting renal dysfunction.

Solar energy has emerged as a promising alternative to traditional fossil fuels due to its abundant availability and sustainability. Solar cells, the fundamental units of solar energy conversion, have undergone significant advancements in fabrication techniques to enhance their efficiency, durability, and cost-effectiveness. This review aims to provide a comprehensive overview of various methods employed in the preparation of solar cells, including thin-film, crystalline silicon, organic, and perovskite-based technologies. By analyzing recent research developments, challenges, and future prospects, this article sheds light on the evolving landscape of solar cell fabrication, contributing to the ongoing efforts in achieving widespread adoption of solar energy.

Land cover segmentation, a fundamental task within the domain of remote sensing, boasts a broad spectrum of application potential. In this article, we focus on the land cover segmentation tasks and complete the following research work: Firstly, to address the issues of uneven distribution of foreground and background and significant differences in target scales in remote sensing images, we propose a decoder called MDCFD based on multi-dilation rate convolution fusion. The decoder utilizes dilated convolution to expand the receptive field, enhancing the model's ability to capture global features and thus improving the model's ability to distinguish between foreground and background. Meanwhile, we design a multi-dilation rate convolution fusion module (MDCFM), which fuses the outputs of different dilation rate convolution layers. Secondly, aiming at the problems of diverse scenes, significant differences between categories, and many background interferences in remote sensing images, we propose a hybrid attention module called LKSHAM based on large kernel convolution. This module combines spatial attention and channel attention mechanisms and combines the two attention modules in series. By introducing large kernel convolution, the model's ability to extract contextual information is improved. At the same time, we adopt a strategy of decomposing large kernel convolution into multiple depthwise convolutions to reduce computational complexity. The improved network models designed by this paper can achieve an improvement of over 1.1% in the mIoU metric on segmentation tasks on the Potsdam and Vaihingen datasets.

We present a comprehensive database of near-shore wind observations that were carried out during the experimental campaign of the RUNE project. RUNE aims at reducing the uncertainty of the near-shore wind resource estimates from model outputs by using lidar, ocean, and satellite observations. Here we concentrate in describing the lidar measurements. The campaign was conducted from November 2015 to February 2016 at the west coast of Denmark and comprises measurements from eight lidars, an ocean buoy and three types of satellites. The wind speed was estimated based on measurements from a scanning lidar performing PPIs, two scanning lidars performing dual synchronized scans, and five vertical profiling lidars, of which one was operating offshore on a floating platform. The availability of measurements is highest for the profiling lidars, followed by the lidar performing PPIs, those peforming the dual setup, and the lidar buoy. Analysis of the lidar measurements reveals good agreement between the estimated 10-m wind speeds, although the instruments used different scanning strategies and measured different volumes in the atmosphere. The campaign is characterized by strong westerlies with occasional storms.

Georgia is ranked fifth highest among states for rates of HIV diagnosis. About 4% of persons living with HIV infection in the United States reside in Georgia, and almost 19% of these people do not know their HIV status. The present study examined the trends and associated factors of HIV testing among adults in Georgia between 2010 and 2014 by analyzing data of the Behavioral Risk Factor Surveillance System (BRFSS). A total of 30,791 persons aged ≥18 years were identified who responded to the question “Have you ever been tested for HIV?” Overall, there were 11,543 respondents who had been tested for HIV, with a decrease in percentage from 49.4% in 2010 to 43.7% in 2014 (p<0.001). Factors associated with HIV testing were being black (p<0.001), being younger than 55 years (p<0.001), single (p=0.02), attaining education level above high school (P<0.001), engaging in HIV high-risk behaviors (p<0.001), and not having healthcare coverage (p=0.03). Overall in Georgia, there has been a decline in the temporal trend of HIV testing, and more than half of adults have never been tested for HIV. For reducing HIV transmission in Georgia, enhancing access and utilization of HIV testing should be a public health priority.

Granulocyte-macrophage colony-stimulating factor (GM-CSF) is a pleiotropic myelopoietic growth factor and proinflammatory cytokine, clinically used for multiple indications and serving as a promising target for treatment of many disorders, including cancer, multiple sclerosis, rheumatoid arthritis, psoriasis, asthma, COVID-19. We have previously shown that dimeric Ca2+-bound forms of S100A6 and S100P proteins, members of the multifunctional S100 protein family, are specific to GM-CSF. To probe selectivity of these interactions, the affinity of recombinant human GM-CSF to dimeric Ca2+-loaded forms of 18 recombinant human S100 proteins was studied by surface plasmon resonance spectroscopy. Of them, only S100A4 protein specifically binds to GM-CSF with equilibrium dissociation constant, Kd, values of 0.3-2 μM, as confirmed by intrinsic fluorescence and chemical crosslinking data. Calcium removal prevents S100A4 binding to GM-CSF, whereas monomerization of S100A4/A6/P proteins disrupts S100A4/A6 interaction with GM-CSF and induces a slight decrease in S100P affinity for GM-CSF. Structural modelling indicates the presence in the GM-CSF molecule of a conserved S100A4/A6/P-binding site, consisting of the residues from its termini, helices I and III, some of which are involved in the interaction with GM-CSF receptors. The predicted involvement of the ‘hinge’ region and F89 residue of S100P in GM-CSF recognition was confirmed by mutagenesis. Examination of S100A4/A6/P ability to affect GM-CSF signaling showed that S100A4/A6 inhibit GM-CSF/S100-induced suppression of viability of monocytic THP-1 cells. The ability of the S100 proteins to modulate GM-CSF activity is relevant to progression of various neoplasms and other diseases, according to bioinformatics analysis. The direct regulation of GM-CSF signaling by extracellular forms of the S100 proteins should be taken into account in the clinical use of GM-CSF and development of the therapeutic interventions targeting GM-CSF or its receptors.

Intercalation of noble metals can produce giant Rashba-type spin-orbit splittings in graphene. The spin-orbit splitting more than 100 meV has not yet been achieved in graphene on a metallic or a semiconductor substrate. Here, we report the p-type graphene obtained by Pt intercalation of zero-layer graphene on SiC substrate. The spin splitting of ∼200 meV was observed at a wide range of binding energies. Comparing the results of theoretical studies of different models with the experimantal ones measured by spin-ARPES, XPS and STM methods, we came to the conclusion that inducing giant spin-orbit splitting requires not only a fairly close arrangement of graphene to Pt layer, but also the presence of graphene corrugation caused by non-flat Pt layer. This makes it possible to find a compromise between strong hybridization and increased spin-orbit interaction. In our case, this is achieved by forming Pt submonolayer ordered on a nanometer scale under graphene.

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread rapidly to most parts of the world, causing high numbers of deaths and significant social and economic impacts. SARS-CoV-2 is a novel coronavirus with a suggested zoonotic origin and with the potential for cross-species transmission among animals. Antarctica can be considered the only continent free of SARS-CoV-2 although at the end of the 2019-2020 tourist season, at least one SARS-CoV-2 positive tourist visited the Antarctic Peninsula. Therefore, concerns have been expressed regarding the potential human introduction of this virus to the continent through the activities of research or tourism with potential effects including those related to human health, but also the potential for virus transmission to Antarctic wildlife. This reverse-zoonotic transmission risk to Antarctic wildlife is assessed considering the available information on host susceptibility, dynamics of the infection in humans, and contact interactions between humans and Antarctic wildlife. Measures to reduce the risk are proposed as well as the identification of knowledge gaps related to this issue.

Coronavirus disease 2019 (COVID-19) can lead to systemic coagulation activation and thrombotic complications. We investigated the incidence of objectively confirmed venous thromboembolism (VTE) in 198 hospitalized patients with COVID-19 in a single-center cohort study. Seventy-four patients (37%) were admitted to the intensive care unit (ICU). At time of data collection, 58 (29%) were still hospitalized and 14% had died. During a median follow-up of 5 days (IQR, 3-9), 33 patients (17%) were diagnosed with VTE of whom 22 (11%) had symptomatic VTE, despite routine thrombosis prophylaxis. The cumulative incidences of VTE at 7 and 14 days were 15% (95% CI, 9.3-22) and 34% (95% CI, 23-46), respectively. For symptomatic VTE, these were 11% (95% CI, 5.8-17) and 23% (95% CI, 14-33). VTE appeared to be associated with death (adjusted HR, 2.9; 95% CI, 1.02-8.0). The cumulative incidence of VTE was higher in the ICU (25% at 7 days 95% CI, 15-36, and 48% at 14 days, 95% CI, 33-61) than on the wards (any VTE and symptomatic VTE 6.5 % at 7 days (95% CI, 1.5-17) and 10% at 14 days (95% CI, 2.9-24)).The observed risk for VTE in COVID-19 is high, particularly in ICU patients, which should lead to a high level of clinical suspicion and low threshold for diagnostic imaging for DVT or PE. Future research should focus on optimal diagnostic and prophylactic strategies to prevent VTE and potentially improve survival.

The Human immunodeficiency virus-1 (HIV-1) matrix (MA) domain is involved in the highly regulated assembly process of the virus particles that occur at the host cell’s plasma membrane. High-resolution structures of the MA domain determined using cryo X-ray crystallography have provided initial insights into the possible steps in the viral assembly process. However, these structural studies have relied on large and frozen crystals in order to reduce radiation damage caused by the intense X-rays. Here, we report the first XFEL study of the HIV-1 MA domain’s interaction with inositol hexaphosphate (IP6), a phospholipid headgroup mimic. We also describe the purification, characterization and microcrystallization of two MA crystal forms obtained in the presence of IP6. In addition, we describe the capabilities of serial femtosecond X-ray crystallography (SFX) using X-ray free-electron laser (XFEL) to elucidate the diffraction data of MA-IP6 complex microcrystals in liquid suspension at ambient temperature. Two different microcrystal forms of MA-IP6 complex both diffracted to beyond 3.5 Å resolution, demonstrating the feasibility of using SFX to study the complexes of MA domain of HIV-1 Gag polyprotein with IP6 at near-physiological temperatures. Further optimization of the experimental and data analysis procedures will lead to better understanding of the MA domain of HIV-1 Gag and IP6 interaction at high resolution and provide basis for optimization of the lead compounds for efficient inhibition of the Gag protein recruitment to the plasma membrane prior to virion formation.

ABSTRACT Lubricants play a crucial role in reducing friction and wear between surfaces in relative motion. Engine oil, as a lubricant, is specifically designed to minimize friction and wear between the moving parts of different equipment and machinery. Engine oil blending serves the purpose of adjusting the variety of lubricants available to meet specific performance requirements. Through blending, it is possible to tailor the characteristics of the lubricating oil, such as viscosity, stability, and additive content, to optimize its effectiveness in reducing friction, protecting engine components, and enhancing overall equipment performance. By customizing lubricant formulations through blending, manufacturers can address the diverse lubrication needs of modern engines and machinery, ensuring smooth operation, longevity, and efficiency.To enhance the quality of the lubricant and achieve the desired high-performance multi-grade engine oil, a systematic approach was followed. The process began with testing the specific gravity of the oil using a hydrometer and thermometer to ensure accurate measurements. Subsequently, 5 liters of base oil were carefully measured and poured into a stainless steel reactor pot to serve as the blending vessel. Following this, 1 liter of paraffin oil (100N) was added to the base oil to introduce specific properties to the blend. To further optimize the formulation, 0.42 kg (7% of the total blend) of additives, including a selection of specific performance-enhancing compounds, was incorporated. These additives, such as Aspen, Tackifier, and other essential components like anti-wear, corrosion inhibitors, detergents, dispersants, and antioxidants, were meticulously measured and added to the mix. Through this precise blending process, the goal was to craft a high-quality multi-grade engine oil that meets the stringent performance requirements for various operating conditions and equipment types. After the melted Aspen and dissolved tackifier were added to the mixture, thorough stirring was carried out to ensure uniform distribution until a homogeneous blend was achieved. The mixture was then exposed to heat to facilitate the reaction between the base oil and additives, reaching a temperature of 70°C for optimal blending. Subsequently, 0.5 kg of viscosity index improver was introduced into the mixture and stirred continuously for a period of 5 minutes to ensure proper integration. Following this step, 5 grams of dye were carefully added to the mixture, and stirring was continued to evenly disperse the coloring agent throughout the blend. This meticulous process aimed to ensure that all components were effectively incorporated, facilitating the production of a high-quality, customized multi-grade engine oil with enhanced performance characteristics and optimal lubricating properties. After subjecting the mixture to a temperature of 70°C, the heat source was removed, allowing the product to gradually cool down to room temperature, which was estimated to be around 30°C. Following this cooling process, the product underwent a filtration step to remove any residual impurities present in the mixture. A sample of the purified product was then extracted for further analysis. Quality control tests were meticulously carried out on the sample to ensure that the product met the rigorous standards set by the Standard Organization of Nigeria (SON). The results obtained from the quality control tests were highly promising, indicating that the product indeed complied with the stringent specifications outlined by the regulatory body. This adherence to quality standards is essential in ensuring the product's reliability and performance in various applications. The successful outcome of the quality control test underscores the meticulous attention to detail and commitment to excellence in the production process. The rigorous quality control procedures implemented in the analysis of the product highlight the commitment to upholding high standards of quality and safety in the manufacturing process. By consistently meeting and exceeding industry regulations and standards, the product not only demonstrates its reliability but also reflects a dedication to customer satisfaction and product excellence. The adherence to the SON standards showcases a commitment to producing top-quality products that meet the needs and expectations of consumers and industry stakeholders alike.

Background: Traumatic brain injury (TBI) remains a significant risk factor for post-traumatic epilepsy (PTE). The pathophysiological mechanisms underlying the injury-induced epileptogenesis are under under investigation. The dentate gyrus, a structure highly susceptible to injury, and has been implicated in the evolution of seizure development. Methods: Utilizing the murine unilateral focal control cortical impact (CCI) injury, we evaluated seizure onset using 24/7 EEG video analysis at 2-4 months post-injury. Cellular changes in the dentate gyrus and hilus of the hippocampus were quantified by non-biased stereology and Imaris image analysis to evaluate Prox1-positive cell migration, astrocyte branching and morphology, as well as neuronal loss at four months post-injury. Isolation of region-specific astrocytes and RNA-seq was performed to determine differential gene expression in PTE+ vs. PTE- that may comport with the epileptogenic process. Results: CCI injury resulted in 37% PTE+-incidence, which increased with injury severity and hippocampal damage. Histological assessments uncovered a significant loss of hilar interneurons that coincided with aberrant migration of Prox1-positive granule cells and reduced astroglial branching in PTE+ compared to PTE- mice. We uniquely identified Cst3 as a PTE+-specific gene signature in astrocytes across all brain regions. Conclusions: These findings suggest that epileptogenesis may emerge following TBI due to distinct aberrant cellular remodeling events and key molecular changes in the dentate gyrus of the hippocampus.

STUDY QUESTION: Which are the main research interests among patients of assisted reproductive technologies (ART)? SUMMARY ANSWER: Patients identified as research priorities that deserve further investigation: success rates and risks of ART, side-effects of treatments, resources to cope with infertility, effectiveness of alternative therapies, lifestyle habits to protect fertility, oocyte quality and ovarian reserve, and causes of genetic or hereditary infertility. WHAT IS KNOWN ALREADY: The involvement of patients and caregivers in setting research agendas in medicine has gathered significant momentum in the last decade. Patients’ involvement in setting research priorities offers several benefits: improved patient knowledge and awareness of their condition; greater understanding of the medical professionals of the impact of the condition on patients’ quality of life; reduced costs associated with redundant research activities. This is may be also applicable to research in infertility and ART, where patients’ interests have never been explored before. STUDY DESIGN, SIZE, DURATION: This is a cross-sectional study that consists of an anonymous online survey, which was sent up to three times to 2112 patients from 11 fertility centers in 5 countries between January-December 2018. The study design was based on the James Lind Alliance priority setting partnership model, which comprises the identification of patients groups, the exploration of the research agenda, the analysis of collected data and identification of priorities. PARTICIPANTS/MATERIALS, SETTING, METHODS: Overall, 2112 patients were contacted, and 945 surveys were answered (RR: 44.7%). Patients were asked to identify research questions relevant to them in the areas of infertility causes and prevention, fertility treatments (medication and ART), and the emotional aspects of infertility. Answers were categorized in topics and ranked by frequency. A long list of the top-30 research topics was extracted from the aggregate results, from which, a short list of the top-10 research topics was created. At the end, 10 research questions related to each of the 10 research topics were constructed, based on the answers given by patients. MAIN RESULTS AND THE ROLE OF CHANCE: Female (845, 89.4%) and male (100, 10.6%) patients were included. The mean age of patients was 37.8 (SD 1.74). Most of the patients did not have children at the time of the survey (523, 59%), while 51 (5.7%) were pregnant. Sixty (6.3%) patients did not start treatment, 579 (61.3%) were performing a treatment with their own gametes and 304 (32.2%) were treated through gamete donation. Patients were mainly interested in the effectiveness of ART -especially per clinical profile-, side effects of drugs, protection of fertility and prevention of infertility –especially through diet and exercise-, and psychological aspects of the infertility journey. The top-10 research questions (and weight) obtained were: 1) What are the side-effects of ART treatments? (41.6%); 2) What are the most effective methods to cope with infertility from the psychological point of view? (37.2%); 3) What effects could diet have on fertility? (25.9%); 4) What are ART success rates per clinical profile? (25.9%); 5) Are there habits and lifestyle factors that could prevent infertility? (20.0%); 6) What are the long-term risks associated to ART? (18.5%); 7) Are alternative therapies such as acupuncture, yoga, and meditation effective to treat/prevent infertility? (18.5%); 8) What is the impact of exercise on fertility? (15.4%); 9) How does oocytes quantity and quality affect fertility? (9.5%); 10) What are the genetic patterns or hereditary conditions causing/related to infertility? (9.5%). LIMITATIONS, REASONS FOR CAUTION: Although all respondents had attended a fertility center, not all of them were diagnosed as infertile (i.e. single women) and had started treatment at the time of response, while a few were pregnant; their priorities for research might have been influenced by their infertility journey. Also, all participants attended private fertility centers: areas of interest may be different in public settings. WIDER IMPLICATIONS FOR THE FINDINGS: Researchers and clinicians should keep in mind that, in addition to improvement of treatments’ success rates and side-effects, patients greatly value research on causes, prevention and emotional aspects of infertility. As their views might differ from those of medical professionals, patients’ voices should be incorporated in setting infertility research priorities.

Tuberculosis (TB) remains a global public health issue, particularly in developing countries. Hematopoietic stem cell transplant (HSCT) recipients are at elevated risk for TB due to immunosuppression. This retrospective study (2005-2022) assessed a preemptive latent tuberculosis infection (LTBI) screening and treatment strategy in 338 HSCT recipients and their donors. Screening included tuberculin skin test (TST) or QuantiFERON-TB Gold (QFT), and pulmonary imaging, with positive cases receiving isoniazid (INH) therapy. Statistical analyses aimed to compare TB reactivation rates, overall survival (OS), and relapse-free survival (RFS) across HSCT groups. Of 338 patients, 92 (27%) were diagnosed with LTBI. Screening involved TST in 325 cases and QFT in 13. INH therapy was completed by 81 patients, with 5 discontinuing due to hepatotoxicity. The cumulative incidence of active TB was 0.6%, and LTBI reactivation rate in patients who received INH was 1.2%. LTBI status did not affect OS or RFS. Our study exemplifies the effectiveness of LTBI protocols incorporating TST/QFT and CT-scan testing, followed by INH therapy, in reducing TB reactivation among HSCT recipients in a high-burden region.

The International Roughness Index (IRI) is the standard scale for evaluating road roughness in many countries in the world. The Taipei City government actively promotes a Road Smoothing Project and plans to complete the rehabilitation of the main and minor roads within its jurisdiction. This study aims to detect the road surface roughness in Taipei City and recommend appropriate IRI thresholds for road rehabilitation. A total of 171 asphalt concrete pavement sections in Taipei City with a total length of 803.49 km were analyzed and compared by IRI. The longitudinal profile of the detected road sections was measured using an inertial profiler. The statistical analysis showed that the IRI value prior to road leveling was mainly distributed between 5 and 8 m/km, while the IRI value after road leveling was mainly distributed between 3 and 4.5 m/km. This confirms that the implementation of the Road Smoothing Project has a significant effect on improving road smoothness. Moreover, based on the analysis results, it is recommended that the IRI threshold value for road rehabilitation in Taipei City be set at 4.50 m/km.

The article is focused mainly on verifying the suitability of data from experimental milling heat-treated beech wood and on investigation of the effect of technical and technological parameters of milling on the energy consumption of this process. The independent parameters of machining process are cutting speed, feed speed, rake angle, and hydrothermal modification of experimental wood material. Based on analysis of variance it can be argued that the greatest statistically significant effect on energy consumption have cutting speed and rake angle of the tool while the feed speed had the least influence. The measured data of cutting power during milling were used to build a regression model and validate it, while the most suitable type of model with correlation of 87 % is Classification and Regression Tree followed by model created by Random Forests method.

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

Background: Research suggests that cognitive and behavioural factors, including lifestyle behaviours, contribute to the mitigation of perceived stress and stress-related health outcomes in later life. Given that stress management and lifestyle behaviour interventions for older adults are an important target for healthcare efforts, there is a need to comprehensively measure stress and coping resources in later adulthood. Additionally, researchers need a relatively short, standardized assessment tool that can robustly measure stress and coping for longitudinal and intervention-based studies to reduce burden on participants and for cross-comparison across research. Methods: The Stress Assessment Inventory (SAI), a valid and reliable 123-item measure designed to assess occupational stress and coping resources in younger adults was examined in 294 independent older adults. Results: A shortened and revised SAI is proposed for older adults, with good internal consistency and strong criterion validity. The revised SAI for older adults was found to have a 4-factor model that captures Adaptive Cognitive Resources, Maladaptive Behavioural and Cognitive Habits, Social Support and Adaptive Health Habits. Conclusion: The current study supports the use of the inventory in community-dwelling older adult populations as a comprehensive tool to assess stress and coping for use by researchers and healthcare professionals.

(1) Background: With the global population aging, the demand for effective rehabilitation products for the elderly is increasing. Traditional products often fail to meet the comprehensive needs of elderly users, who require solutions addressing physical, psychological, and social aspects; (2) Methods: Using the Analytic Hierarchy Process, Quality Function Deployment, Axiomatic Design, and the System Usability Scale to identify and prioritize user needs, market research and user interviews were conducted to understand the preferences of the elderly and obtain design specifications. The focus was on multimodal sensory feedback, which was validated through the study; (3) Results: Elderly users have a strong preference for rehabilitation products that are durable, easy to use and have comprehensive sensory feedback. Intelligent rehabilitation bed as the carrier, strengthened structure, high strength material, ergonomic adjustment, integrated health monitoring system. Using digital technology for real-time health monitoring and personalized feedback to provide a comprehensive recovery experience, high user satisfaction was reported in the evaluation; (4) Conclusion: It is important to emphasize user-centered design and integrate multi-modal sensory feedback to meet the comprehensive rehabilitation needs of elderly users. Future studies should expand user samples and expert opinions to refine and validate the design and improve its effectiveness and usability.

The Zero Trust Architecture (ZTA) security system follows the "never trust, always verify" principle. The process constantly verifies users and devices trying to access resources. This paper describes how Microsoft Azure uses ZTA to enforce strict identity verification and access rules across the cloud environment to improve security. Implementation is time-consuming and difficult. Azure's extensive services and customizations require careful design and implementation. Azure administrators struggle to navigate and change configurations due to its complex user interface (UI). Each Azure ecosystem component must meet ZTA criteria. ZTA's comprehensive policy definitions, multi-factor and pass-wordless authentication, and other advanced features are tested in a mid-size business scenario. These configuration changes require a solid grasp of Azure's architecture and Zero Trust. Implementing an Azure ZTA reduces vulnerabilities and restricts authorized users' access to critical resources. Implementation is time-consuming and expensive, requires a significant commitment to changing IT procedures, and can be confusing because the same features are available in multiple places. Azure ZTA has shown great potential for both hybrid and cloud-native companies.

Cured-in-place pipe (CIPP) lining is a widely adopted method for pipeline renewal, offering advantages such as rapid installation and cost-effectiveness. However, concerns regarding the environmental impacts of volatile organic compound (VOC) emissions during the installation process have raised issues regarding the CIPP method. The literature review conducted in this paper indicated the need for stringent monitoring and management practices to mitigate adverse effects, emphasizing the importance of safe installation protocols. This paper presents the initial results of a case study focusing on VOC emissions, specifically investigating non-styrene polyester resins and water curing. To capture emissions from CIPP activities, the methodology involved air sampling using various equipment, including photoionization detectors (PID), summa canisters, passive worker sampler sorbent tubes, and method 13 cartridges. The preliminary findings indicate that non-styrene polyester resins do not exceed the exposure limits set out by the OSHA and USEPA. The future phases of this project will explore different resins and curing methods.

The United Nations’ Agenda 2030 has established a series of Sustainable Development Goals to address global challenges, including poverty, food insecurity, access to education, and social inequality. In this context, charitable organizations such as Caritas play a crucial role in mitigating the negative effects of these challenges and promoting fair and sustainable development. This study aims to analyze prevalent needs among individuals seeking assistance from Caritas in Campania and examine how the organization contributes to achieving the Agenda 2030 Goals in the region. The statistical investigation techniques considered include tandem analysis [], which considers a dimension-reduction technique, such as multiple factor analysis, and, then cluster analysis to identify similar groups of individuals. These exploratory data analysis methods have allowed for the identification of common needs, including food assistance, support for education, employment, and housing assistance. Subsequently, Caritas programs and initiatives aimed at meeting these needs and promoting sustainable development are explored. The results indicate that Caritas plays a significant role in addressing the urgent needs of the vulnerable population in Campania and contributes to the goals of Agenda 2030, particularly those related to poverty alleviation, immigration, health promotion, education, employment, and reduction of social inequalities. This study provides an important perspective on the relevance and effectiveness of Caritas’ work in the context of Agenda 2030.

(1) Background: This paper illustrates an innovative methodological approach chosen to study and map the colors of the Medieval wall painting of Santa Maria Antiqua in the Roman forum, one of the pilot sites of the EHEM project (Enhancement of Heritage Experiences: The Middle Ages. Digital Layered Models of Architecture and Mural Paintings over Time); (2) Methods: We chose to use two methods for gathering information about colors and mapping, specifically colorimetry by spot measurements and hypercolorimetric multispectral imaging (HMI) to map those same colors sampled through colorimetry; (3) Results: Chromatic data of all colors in the wall paintings were obtained in the CIELAB color space. In those same points, chromatic similarity maps were performed by the innovative HMI system, a multispectral imaging technique able to obtain also color data information by means of the advanced calibration software named SpectraPick®: this allowed to have a complete knowledge of the color characteristics and distribution; (4) Conclusion: The color measurements and mapping was an important result to improve the reading of Medieval wall paintings, fragmentary and stratigraphically complex, giving a new light in the knowledge of the colors and allowing to better understand the original appearance of the iconographic patterns, reconstructed with colors as faithfully as possible similar to the originals.

Orb web spiders are common and highly diversified animals found in almost all habitats. They have remarkable plasticity against biotic and abiotic factors, making them excellent indicators of environmental health. The web-creation behavior of spiders is influenced by disturbances in the environment. The aim of the research was to observe the alteration in the web-building behavior of Neoscona vigilans caused by human activities, specifically traffic disturbance. Spider webs were located and photographed at nighttime along the roadside, and their web characteristics were calculated. Spiders were captured from webs for their body measurements. Spider 4^th leg length, carapace width, and body length had a significant association with web size and diameter, CTL, capture area, and mesh size. The quantity of trapped prey, the height of the plant, and the foliage radius increased with the distance from the road. Conversely, anchor points and web elevation from the ground dropped. The highest and lowest proportion of anomalies (modifications/defects) were recorded as holes (52.7%) in 105 webs (100%) and supernumerary (0.7%) in 55 webs (52.4%), respectively. Road disturbance had a negative influence on the spider’s behavior as the webs formed in close proximity to the road had a higher frequency of anomalies with a gradual decrease distantly. We can gain further insight into how different environmental changes, disruptions, and pollutants lead to this imperfection in the otherwise flawless perfect structure of spider webs.

Pyrocumulonimbus (pyroCb) thunderclouds, produced from extreme bushfires, can initiate frequent cloud-to-ground (CG) lightning strikes containing extended continuing currents. This, in turn, can ignite new spotfires and inflict massive harm on the environment and infrastructures. This study presents a 3D numerical thundercloud model for estimating the lightning of different types and its striking zone for the conceptual tripole thundercloud structure which is theorized to elucidate the lightning phenomenon in pyroCb storms. More emphasis is given to the lower positive charge structure thundercloud to thoroughly examine various electrical parameters including the longitudinal electric field, electric potential, and surface charge density. The simulation outcomes on pyroCb thunderclouds with a tripole structure confirm the presence of negative longitudinal electric field initiation at the cloud’s lower region. This initiation is accompanied by enhancing the lower positive charge region, resulting in an overall positive electric potential increase. Consequently, negative surface charge density appears underneath the pyroCb thundercloud which has the potential to induce positive cloud-to-ground (+CG) lightning flashes. The suggested model would establish the basis for identifying the potential area impacted by lightning and could also be expanded to analyze the dangerous conditions that may arise in wind energy farms or power substations in times of severe pyroCb events.

Nanoporous materials, such as Metal-Organic Frameworks (MOFs), are renowned for their high selectivity as gas adsorbents due to their specific surface area, nanoporosity, and active surface chemistry. A significant challenge for their widespread application is their behavior and reduced gas uptake in wet conditions, attributed to competitive adsorption between gas and water. The current understanding of gas adsorption in wet materials is constrained by studies that utilize only small amounts of powdered porous materials (in the milligram range) within very small reactors (1-5 mL). This leaves a significant gap in knowledge about gas adsorption behaviors in larger reactors and when MOF sample sizes are increased (to the gram scale) for scaling up the process. Additionally, there is a notable dearth of experimental research in situations where MOFs are heavily saturated with water. To address these gaps, this study measures CH4 adsorption in MOFs under conditions of high moisture content, using larger samples of MOFs (in grams) and a large volume reactor. We selected commercially available MOFs, including HKUST-1, ZIF-8, MOF-303, and activated carbon. A high-pressure isotherms (at T = 274.15 K) using volumetric approach were measured to qualitatively compare the moles of gas adsorbed under both dry and wet conditions across different MOFs and weights. Experimental results show that the presence of water led to a decrease in total CH4 mmol adsorption in MOFs, with a more significant decrease observed in hydrophilic MOFs compared to hydrophobic ones. For hydrophilic MOFs, presence of crossover isotherms at crossover pressure provided evidence of water's conversion to hydrate and its positive role in enhancing total gas uptake, which varied among different hydrophilic MOFs. Oversaturated MOFs showed a larger deviation between dry and wet cases at higher pressures. The high-pressure isotherm data confirm the positive role of hydrophilic MOFs in the conversion of water to hydrate in oversaturated MOFs when MOFs sample size is large.

The shortage of physicians in rural communities contributes to increased mortality rates among Medicare beneficiaries. This increase in mortality risk is commonly due to diseases such as heart disease and cancer, including melanoma and non-melanoma skin cancer (NMSC). Mohs micrographic surgery (MMS) is considered the gold-standard treatment for NMSC tumors, however, due to a shortage of dermatologists and Mohs surgeons in rural areas, access to MMS is limited. In these areas, image guided superficial radiation therapy (IGSRT) serves as a viable option for the treatment of NMSC lesions, with fewer recurrences and 99% cure rates, which are comparable to MMS cure rates. IGSRT is performed in dermatology clinics with support from a multidisciplinary team, including radiation therapists, medical physicists, radiation oncologists, and dermatologists. As IGSRT is able to be performed by general dermatologists, Medicare beneficiaries in rural communities will have an increase in access to treatment options and a decrease in delayed skin cancer treatment.

In this study, a carbon fiber microelectrode (CF) was applied for the investigation of electrochemical behavior and determination of natural antioxidant, apocynin (APO). Given the limited solubility of APO in water, a mixture of anhydrous acetic acid (AcH) with 20%, v/v acetonitrile (AN) and 0.1 mol L-1 sodium acetate (AcNa) was used. The electrochemical properties of APO were examined through linear sweep voltammetry (LSV), differential pulse voltammetry (DPV), and cyclic voltammetry (CV). The anodic oxidation of APO, which is the basis of the method used, proved to be diffusion-controlled and proceeded with a two-electron and one proton exchange. Both radicals and radical cations, arising from the first and second step of electrode reactions, respectively, underwent subsequent chemical transformations to yield more stable final products (EqCiEiCi mechanism). Using optimized DPV conditions, the anodic peak current of APO at potential of 0.925 V vs Ag/AgCl showed a good linear response within the concentration range of 2.7×10-6 – 2.6×10-4 mol L-1. The detection and quantification limits were determined as 8.9×10-7 and 2.7×10-6 mol L-1, respectively. The developed DPV method enabled the successful determination of APO in herbal extracts and in dietary supplements. It should be noted that this is the first method of voltammetric determination of APO.

The quasi-experimental study examines the role of contemporary technologies, such as artificial intelligence and humanoid robots, in enhancing sustainability education for future teachers, emphasizing their impact on shaping sustainable beliefs in future generations. Involving 112 pre-service teachers, the research compares various contemporary and traditional learning methods. Pre- and post-test evaluations were conducted to assess changes in participants’ understanding of sustainability concepts and the variability of their responses. Results reveal significant improvements in sustainability awareness, with methods involving humanoid robots showing higher response variability. The study also identifies the development of new literacies crucial for effectively utilizing advanced technologies in promoting environmental sustainability. While artificial intelligence and humanoid robots match the efficacy of traditional methods, they notably engage young educators more effectively in sustainability topics. These findings highlight the need to integrate such technologies into educational framework to deepen the understanding of environmental issues and prepare youth for future challenges. However, further research is required to explore long-term effects and broader demographics. The research contributes significantly to educational technology and sustainability in education, showcasing the transformative potential of incorporating contemporary technologies in educational settings.

Correlated binary data in a 2x2 table has been analyzed from both the frequentist and Bayesian perspectives, but a fully Bayesian hierarchical model has not been proposed. This is a commonly used model for correlated proportions when considering, for example, a diagnostic test performance where negative subjects are tested a second time. We consider a new hierarchical Bayesian model for the parameters resulting from a 2x2 table with a structural zero. We investigate the performance of the hierarchical model via simulation. We then illustrate the usefulness of the model by showing how a set of historical studies can be used to build a predictive distribution for a new study that can be used as a prior distribution for both the rate ratio and marginal probability of a positive test. We then show how the prior based on historical 2x2 tables can be used to power a future study that accounts for pre-experimental uncertainty. High quality prior information can lead to better decision making by improving precision in estimation and by providing realistic numbers to power studies.

Pesticides are chemical compounds or mixtures of hazardous substances that are used by humans to increase and protect crops from pests and control disease-carrying insects. Because of its wide use, it may be poisonous to helpful and non-targeting plants and animals. Spraying or spreading pesticides over whole fields of crops can cause runoff to transfer the chemicals into aquatic ecosystems, and wind can carry the chemicals to nearby grazing regions, farms, and populated areas, where they can endanger other animals. This review summarises recent studies on pesticide combination toxicity to aquatic biota and approaches used to anticipate toxic effects. When toxicants harm economically significant organisms that humans consume, the negative effects become more severe and can cause stress conditions, vital organ damage, biochemical damage, or even the death of living things in both terrestrial and aquatic environments. Pesticides are highly toxic to aquatic organisms such as snails, fish, etc. Neurological dysfunction in freshwater organisms is also caused by pesticides. By producing excessive ROS, pesticides can cause severe biochemical and histological changes in freshwater organisms. So, it is therefore easy to understand the attention of the public on these substances. Because aquatic organisms play a major part in the food chain. However, through the biomagnification process, the quantity of pesticides increases in the higher organisms through the food chain. Which results play a terrific role in the higher organism’s body. So, It's essential to comprehend the way that insecticides work on aquatic organisms. In this review article, we are focusing on the way that pesticides work, which will help in the system of biomonitoring.

Performance analysis of companies is critical for decision-makers in the financial sector, particularly when resources are limited. This study investigates the properties of various Multi-Criteria Decision-Making (MCDM) methods, critically comparing their results in evaluating the performance of consumer goods companies listed on the Nigerian Stock Exchange (NSE). The analysis utilizes financial ratios, with weights derived using Buckley's Column Geometric Mean Method, a fuzzy ranking approach. The study concludes by comparing TOPSIS, VIKOR, and ELECTRE methods, determining the final rankings of these companies, and interpreting these rankings based on financial ratios over a five-year period (2016-2020).

Every country has a different philosophy of education, which in contemporary China manifests itself in ideological guidance at all levels and in all types of schools. China's education has entered a new era, but ideological and political education is still needed in schools and colleges, and its core interest is to cultivate newcomers of the times who can take on the important task of national rejuvenation; in other words, the education sector has to ensure the sustainability of the cultivation of talents as well as the sustainability of socialist development. In this context, ideological and political education has initiated a triple spatial shift, i.e., from classroom space to cyberspace, from physical space to virtual space, and from campus space to social space. The triple spatial transfer has a profound historical logic, which is the inevitable process of the continuous development of ideological and political education itself, and the historical convergence of the Party's proposition, people's expectation and social development in this era. The requirements of the external situation, the needs of internal development, and the needs of the political task constitute the direct reality of the triple spatial transformation. The future direction of the spatial transformation of ideological and political education will be reflected in the intersection of subject and space, the collision of individuality and commonality, and the fusion of unity and diversity.

Generating executable code from natural language instructions using Large Language Models (LLMs) presents challenges such as semantic understanding and handling ambiguous input. This study focuses on the SantaCoder model and explores the impact of in-context learning on code generation using the MBPP and HumanEval datasets for evaluation. Our results demonstrate significant improvements in three key metrics (defined in the paper): correctness@k, similarity@k and pass@k. To address the problem of selecting optimal demonstrations to maximize correctness and pass rates, we investigate two methods: latent concept selection and random selection in this paper. These findings highlight the effectiveness of in-context learning and the critical role of demonstration selection in enhancing the accuracy, efficiency, and versatility of the SantaCoder model in code generation.

Background: for patients with endocarditis, guidelines recommend repeating blood cultures until they become negative, but with very limited evidence. Methods: a literature review was done on the incidence and duration of persistent bacteremia and persistent fever in endocarditis patients, compared to their associations with persistent infection at day 7. Results: persistent bacteremia and persistent fever are common in the first few days after starting antibiotic therapy, a normal duration for either at or around < 3-7 days. Persistent bacteremia is more prevalent and longer lasting in Staphylococcus (especially MRSA) and Enterococcus species than in Streptococcus species. In one study the risk for persistent infection at day 7 was 50% in those with positive blood cultures at 48-72 hours while it was 32% in those with negativization of blood cultures. Both persistent bacteremia at 48-72 hours and persistent infection at day 7 are predictive of in-hospital mortality. Conclusion: persistent bacteremia after treatment for endocarditis is common and often accompanied by persistent fever. Persistent infection at 7 days (as indication for urgent surgery) cannot be reliably predicted by positive or negative blood cultures at 48-72 hours. The recommendation of performing survey blood cultures in all patients therefore needs to be reconsidered.

This paper studies the Bondi-Metzner-Sachs group in homogeneous projective coordinates, because it is then possible to write all transformations of such a group in a manifestly linear way. The 2-sphere metric, Bondi-Metzner-Sachs metric, asymptotic Killing vectors, generators of supertranslations, as well as boosts and rotations of Minkowski spacetime, are all re-expressed in homogeneous projective coordinates. Last, the integral curves of vector fields which generate supertranslations are evaluated in detail. This work prepares the ground for more advanced applications of the differential geometry of asymptotically flat spacetimes in projective coordinates.

Ranked Set Sampling (RSS) is a useful technique for improving the estimator of population mean when the sampling units in a study can be easily ranked than the actual measurement. RSS performs better than simple random sampling (SRS) when the mean of units corresponding to each rank is used. The performance of RSS can be increased further by assigning weights to the ranked observations. In this paper, we propose weighted RSS procedures to estimate the population mean of positively skew distributions. It is shown that the gain in the relative precisions of the population mean for chosen distributions are uniformly higher than those based on RSS. The gains in relative precisions are substantially high. Further, the relative precisions of our estimator are slightly higher than the ones based on Neyman’s optimal allocation model for small sample sizes. Moreover, it is shown that, the performance of the proposed estimator increases as the skewness increases by using the example of lognormal family of distributions.

As modern technologies, particularly home assistant devices, become more integrated into our daily lives, they are also making their way into the domain of energy management within our homes. Homeowners, now acting as prosumers, have access to detailed information in 15-minute or even 5-minute intervals, including weather forecasts, outputs from Renewable Energy Sources (RES)-based systems, appliance schedules and the current energy balance, which details any deficits or surpluses along with their quantities and the predicted prices on the Local Energy Market (LEM). The goal for these prosumers is to reduce costs while ensuring their home’s comfort levels are maintained. However, given the complexity and the rapid decision-making required in managing this information, the need for a supportive system is evident. This is particularly true given the routine nature of these decisions, highlighting the potential for a system that provides personalized recommendations to optimize energy consumption, whether that involves adjusting the load or engaging in transactions with the LEM. In this context, we propose a recommendation system powered by Large Language Models (LLM), Scikit-llm and Zero-Shot Classifiers, designed to evaluate specific scenarios and offer tailored advice for prosumers based on the available data at any given moment. Two scenarios for a prosumer of 5.9 kW are assessed using candidate labels, such as Decrease, Increase, Sell and Buy.

As technology continues to play a central role in shaping global industries, the performance of technology firms on the NASDAQ has significant implications for broader economic trends. Investors, facing an increasingly complex landscape, require detailed insights to make informed decisions and navigate market volatility. Moreover, amid the ongoing digital transformation, understanding the operational dynamics of technology companies is critical for policymakers and regulatory bodies to create frameworks that foster innovation while ensuring market stability. In the current context, characterized by rapid technological advancements, market uncertainties, and evolving consumer demands, the need for a comprehensive study on the operational efficiency of NASDAQ-listed technology companies is more pertinent than ever. Objective of our study is to identify relationships and patterns among selected financial metrics to assess the operational efficiency of NASDAQ-listed technology companies between 2011 to 2023. Financial metrics used in the study include following variables namely revenues, cost of goods sold, operating expenses, research, and development expenses, selling and general administrative expenses, and operating income. Johansen's cointegration methodology is employed to unveil long-term relationships and equilibrium adjustments among the considered variables. Results of our study underscore the paramount importance of efficiently managing the cost of goods sold (COGS) for achieving superior operating performance among these leading technology firms. The findings point to a nuanced interplay among these operational metrics, highlighting the interconnectedness and sustained relationships among them. This suggests that the top technology companies exhibit a sophisticated understanding of the dynamics between these variables, allowing them to navigate the complexities of the industry with strategic finesse.

Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems—thermal, externally loaded, internally reactive, open and closed––are developed via selection of suitable thermodynamic potentials. Here we simplify thermodynamic principles to specify convenient and consistently accurate system governing equations and characterization models. The formulations introduce a new and universal Phenomenological Entropy Generation (PEG) theorem. The systems and methods presented––and demonstrated on grease degradation, battery charging and discharging, metal fatigue and pump flow––can be used for design, analysis, and support of diagnostic monitoring and optimization.

Partial differential representation of self-similarity feature has been derived from notion of the homogenous function in general sense. This representation allows consideration of stochastic self-similar systems. As well as the partial differential representation allows consideration of Stochastic Partial Differential Equation.

The nuclear reactor measurement system is a crucial component of the nuclear measurement system in a nuclear power plant. Its primary function is to measure the power distribution within the reactor core using detectors, calibrate, and provide data on core fuel consumption. Therefore, the study of the detectors' reliability is crucial for ensuring the safe operation of the nuclear power system. The article describes the operational mechanism of the gas ionization chamber detector utilized in the intermediate-range detector of the off-board nuclear measurement system. It also analyzes the movement of particles between the plates during the ionization process of the nuclear reaction taking place in the detector. The functional relationship between the current in the recombination region and the ionization region involved in the actual working condition, and the change with the increase of voltage between the plates, is deduced. A mathematical model is established for the number of pulses generated between the plates and the magnitude of the voltage between the plates. Subsequently, the change in the offset of the voltage corresponding to the inflection point of the ping curve and the change rule of the slope of the ping curve are investigated. Combined with the analysis of experimental data, the results show that the initial particle energy of Ar+, the primary sensitive particle on the detector surface, follows a normal distribution and is influenced by the energy loss associated with the initial velocity and the voltage between the plates. The trends of the inflection points and slopes of the ping curves can be utilized to evaluate the performance and operational status of the detector. Combined with the results of the experimental data analysis, the fit is good, and the inflection point currents in the normal state decrease by about 1.5% annually. The intelligent diagnostic system, based on the method studied in this paper, has been successfully implemented in the RPN digital retrofit and upgrade project at Qinshan No. 2 Plant.

Castanopsis hystrix, a precious tree species in Southeast Asia, has the advantages of rapid growth and high-quality wood materials. However, there are problems such as long breeding cycle, time-consuming and low efficiency, which greatly restricts the industrial development of C. hystrix. To perform the genome selection (GS) for growth and wood traits and the early selection of superior progeny have great significance for the rapid breeding of new superior varieties of C. hystrix. The 226 clones in the main distribution and 479 progenies within 23 half-sib families were used as experimental materials in this study. Genotyping datasets were obtained by high-throughput re-sequencing technology, and GS studies were conducted on the growth (tree height (H), diameter at breast height (DBH)) and wood (wood density (WD), fiber length (FL), and fiber length-width ratio (LWR)) traits. The coefficient of variation (CV) of five phenotypic traits ranged from 10.1% to 22.73%, the average CV of growth traits was 19.93%, and the average CV of wood traits was 9.72%. The Pearson correlation coefficients between the five traits were almost significantly positive. Based on the Genomic Best Linear Unbiased Prediction (GBLUP) model, the broad-sense heritabilities of growth traits were higher than those of wood quality traits, and the different number of SNPs had little effect on the heritability estimation. GS prediction accuracy first increased and then reached a plateau around 3K SNPs for all five traits. The broad-sense heritability of these five traits was significantly positively correlated with their GS predictive ability (r=0.564, P

In this paper we illustrate a new, simple and complementary ground-based methodology to retrieve the vertically resolved atmospheric precipitation intensity through a synergy between measurements from the National Aeronautics and Space Administration (NASA) Micropulse Lidar network (MPLNET), an analytical model solution and ground-based disdrometer measurements. The presented results are obtained at two mid-latitude MPLNET permanent observational sites, located respectively at NASA Goddard Space Flight Center, USA, and at the Universitat Politècnica de Catalunya, Barcelona, Spain. The methodology is suitable to be applied to existing and/or future lidar/ceilometer networks with the main objective of either providing near-real time (3h latency) rainfall intensity measurements and/or to validate satellite missions, especially for critical light precipitation (<3 mm hr⁻¹).

Vitronectin is a glycoprotein, present in plasma and extracellular matrix, implicated in cell migration. The high amount of vitronectin found in neuroblastoma biopsies was associated with poor prognosis. However, there are almost no studies of vitronectin levels in neuroblastoma cell culture media nor in plasma of neuroblastoma patients. Vitronectin concentration in culture media of four neuroblastoma cell lines grown in monolayer and in 3D-models, and in plasma of 114 neuroblastoma patients, was quantified using ELISA. Three of the neuroblastoma cell lines secreted vitronectin to culture media when cultured in monolayer and 3D-models. Vitronectin release was higher by neuroblastoma cells cultured in 3D-models than in monolayer, and was still great when cells grown in 3D-scaffolds with cross-linked vitronectin. Vitronectin secretion occurred independently of cell numbers in cultures. Its concentration in plasma of neuroblastoma patients ranged between 52.4 and 870µg/mL (median, 218µg/mL). A ROC curve was used to establish a cutoff of 361µg/mL, above which patients over 18-months-old had worse prognosis (p=0.0018). Vitronectin could be considered a new plasma prognostic biomarker in neuroblastoma, and warrants confirmation in collaborative studies. Drugs inhibiting vitronectin interaction with cells and/or extracellular matrix could represent a significant improvement in survival for neuroblastoma patients.

Anthropogenic lighting elicits positive phototaxis responses (i.e., attraction) in birds, insects, and many other species across ecosystems. Impacts from lights in marine systems are poorly understood, despite evidence that vessel lighting can cause seabird disorientation and collisions, potentially leading to injury or mortality. The level of attraction generated by different types of lighting, including light-emitting diodes (LEDs), is also not well understood in most seabirds. Using fairy prions (Pachyptila turtur), a species showing strong positive phototaxis particularly to artificial lights on vessels, we investigated the effects of LED colour and lumen output at a colony during the breeding season. We used six random treatment groups (control (dark), red light, amber low lumen, amber high lumen, white low lumen, and white high lumen) and measured attraction and disorientation. Data was analysed using generalised linear mixed-effects models while accounting for environmental variables. Results showed that the control (“dark”) and red light attracted fewest birds, and attraction/disorientation did not differ between these. Medium responses were elicited by amber low/high and white low, while white high lumen induced the highest abundance and attraction/disorientation response. These results agreed with our desktop study, which predicted response rankings based on each light treatment’s colour spectrum and lumen output and a related species’ spectral response. Furthermore, time of night increased bird counts, as did higher humidity, increased moon illumination, and reduced moon visibility. Our data highlight the need to consider LED colour, lumen output, and time of night to reduce anthropogenic lighting impacts on land and at sea.

Drones have experienced rapid technological advancements, leading to the proliferation of small, low-cost, remotely controlled, and autonomous aerial vehicles with diverse applications, from package delivery to personal transportation. However, integrating these drones into the existing air traffic management (ATM) system poses significant challenges. The current ATM infrastructure, designed primarily for traditional manned aircraft, requires enhanced capacity, workforce, and cost-effectiveness to coordinate the large numbers of drones expected to operate at low altitudes in complex urban environments. To address this critical issue, this study aims to develop an intelligent, highly automated drone management system for integration into smart city transportation networks. The key objectives include: i) Developing a conceptual framework for an intelligent total transportation management system tailored for future smart cities, focusing on incorporating drone operations; ii) Designing an advanced air traffic management and flight control system capable of managing individual drones and drone swarms in complex urban environments; iii) Improving drone management methods by leveraging drone-following models and emerging technologies such as the Internet of Things (IoT) and the Internet of Drones (IoD); and iv) Investigating the landing processes and protocols for unmanned aerial vehicles (UAVs) to enable safe and efficient operations.

Detection methods have been developed to prevent transmission of zoonotic or xenozoonotic porcine viruses after transplantation of pig organs or cells to the recipient (xenotransplantation). Eleven xenotransplantation-relevant viruses including porcine cytomegalovirus, a porcine roseolovirus (PCMV/PRV), porcine lymphotropic herpesviruses -1, -2, -3 (PLHV-1, 2, 3), porcine parvovirus (PPV), porcine circovirus 2, 3, 4 (PCV2, 3, 4), hepatitis E virus genotype 3 (HEV3), porcine endogenous retrovirus-C (PERV-C) and recombinant PERV-A/C have been selected. In the past, several pig breeds, minipigs and genetically modified pigs generated for xenotransplantation had been analyzed using these methods. Here, spleen, liver and blood samples from 10 German slaughterhouse pigs were screened using both, PCR-based and immunological assays. Five viruses: PCMV/PRV, PLHV-1, PLHV-3 and PERV-C were found in all animals, and PCV3 in one animal. Some animals were latently infected with PCMV/PRV as only virus-specific antibodies were detected. Others were also PCR positive in spleen and/or liver, indicative of an ongoing infection. These results provide important information on the viruses that infect German slaughterhouse pigs and together with results of previous studies revealed that the methods and test strategies efficiently work under field conditions.

Let $\mathcal{\mathcal{S}}_{\cos}^{\ast}$ denote the class of normalized analytic functions $f$ in the open unit disk $\mathbb{D}$ satisfying the subordination $\dfrac{zf^{\prime}(z)}{f(z)}\prec\cos z$. In the second section of this article we find the sharp upper bounds for the initial coefficients $a_{3}$, $a_{4}$ and $a_{5}$ and the sharp upper bound for module of the Hankel determinant $|H_{2,3}(f)|$ for the functions from the class $\mathcal{S}_{\cos}^{\ast}$. The first result of the next section deals with the sharp upper bounds of the logarithmic coefficients $\gamma_{3}$ and $\gamma_{4}$ and we found in addition the sharp upper bound for $\left|H_{2,2}\left(F_{f}/2\right)\right|$. For obtaining these results we used the very useful and appropriate Lemma 2.4 of N.E. Cho et al. [Filomat 34(6) (2020), 2061--2072], and the technique for finding the maximum value of a three variable function on a closed cuboid. All the maximum found values were checked by using MAPLE\texttrademark{} computare software, and we also found the extremal functions in each cases. All of our present results are the best ones and give sharp versions of those recently published in [Hacet. J. Math. Stat. 52, 596--618, 2023].

Deep learning architectures like ResNet and Inception have produced accurate predictions for classifying benign and malignant tumors in the healthcare domain. This enables healthcare institutions to make data-driven decisions and potentially enable early detection of malignancy by employing computer-vision-based deep learning algorithms. These Convolutional Neural Network algorithms, in addition to requiring huge amounts of data, can identify higher and lower-level features that are significant while classifying tumors into benign or malignant. However, these algorithms have limitations concerning explainability and identifying the exact features that are of importance and contributing to the final classification of tumors as benign or malignant. In this paper, we implement several explainable AI techniques, namely, LIME, Saliency Map, Occlusion Analysis, Grad-CAM, SHAP, and Smooth Grad to interpret the results of a custom ResNet60 classifier in the classification of ovarian tumors as benign or malignant. The ResNet60 model attained an accuracy of 97.50% for the test dataset.

Pulsating high frequency voltage injection can be used for sensorless control of SPMSM at zero and low speed ranges. However, the sensorless capability still faces challenges to the requirements of industrial application, especially at heavy load status. Aiming at this issue, this article proposes a sensorless capability expansion method for SPMSM based on inductance parameter identification. First, incremental inductances at d-q-axis and cross-coupling inductance are identified by three steps combining the rotating high frequency voltage injection and pulsating high frequency voltage injection, then, using polynomial curve fitting algorithm, apparent inductances are calculated. Second, positive DC current injection at d-axis is proposed to enhance the saliency ratio based on the analysis of parameter identification results. Compared with the conventional =0 or &lt; 0 method, when positive DC current is injected at d-axis, saliency ratio is enhanced. Third, convergence region is expanded at heavy load status and accuracy of rotor position estimation is improved using the proposed method. Finally, the experiment results validate that the sensorless capability of SPMSM is expanded.

Sesame seeds are abundant in sesamin, which exerts health-promoting effects such as extending the lifespan of adult Drosophila and suppression of oxidative stress accumulation by activating the Nrf2 transcription factor. Here, we investigated whether sesamin activated Nrf2 in larval tissues and induced the expression of Nrf2 target genes. In sesamin-fed larvae, Nrf2 was activated in the central nervous system (CNS), gut, and salivary glands. However, ectopic expression of Keap1 (Nrf2 inhibitor) in glial cells inhibited sesamin-induced Nrf2 activation in all tissues except in the neurons, indicating that sesamin activates Nrf2 in glia. We labeled the astrocytes as well as cortex and surface glia with red fluorescence to identify these glial cell types in which Nrf2 was activated; we observed their activation in both cell types. These data suggest that sesamin may stimulate the expression of antioxidative genes in glial cells. Among the 17 candidate Nrf2 targets, the mRNA levels of Cyp6a2 and Cyp6g1 in cytochrome P450 were elevated in the CNS, gut, and salivary glands of sesamin-fed larvae. However, this did not lead to resistance against imidacloprid, which is detoxified by these enzymes. Our results suggest that sesamin may exert similar health-promoting effects on the human CNS and digestive tissues.

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. Isoform switching, the process where cells alter the expression of various splice forms (isoforms) of a gene, plays a critical role in cellular function and adaptation. Our study provides a comprehensive analysis of splice forms prevailing across ten of the most studied human cell lines using public RNAseq data. We analyzed the occurrence of splice forms and found substantial justification for revising the canonical sequences for 56 genes, suggesting that these alternative splice forms should be recognized as canonical. Additionally, distinct profiles of splice form prevalence across these cell lines offer new insights into their specific biological roles. Our findings reinforce and expand upon previous insights into the link between isoform expression and oncological processes. Notably, we identified three genes exhibiting statistically significant changes between cancerous and normal tissues. Moreover, a comparative analysis of prevailing isoforms across diverse cell lines with prior research unveiled 140 common splice variants associated with cancer, highlighting their importance for prognostication and understanding oncogenesis. We revealed unique patterns and variations in isoform switching of these lines that provide new insights into the importance of selecting specific ones for research.

This study examines the optimization of ground source heat pump (GSHP) systems and energy piles for sustainable urban development, with a focus on Southeast Asia. GSHPs, which utilize geothermal energy for indoor HVAC needs, offer a sustainable alternative to traditional systems by utilizing consistent subsurface temperatures for heating and cooling. The study highlights the importance of understanding thermal movement within the soil, especially in soft marine clays prevalent in Southeast Asia, to improve GSHP system efficiency. Using a one-dimensional finite-difference model, the study examines the effects of soil thermal conductivity and density on system performance. The results show that GSHP systems, especially when integrated with energy piles, significantly reduce electricity consumption and greenhouse gas emissions, underscoring their potential to mitigate the urban heat island effect in densely populated areas. Despite challenges posed by the region's hot and humid climate, which could affect long-term effectiveness, the study highlights the need for further study, including field experiments and advanced modeling techniques, to optimize GSHP configurations and fully exploit geothermal energy in urban environments. The study's insights into soil thermal dynamics and system design optimization contribute to the advancement of sustainable urban infrastructure development.

The development of reliable predictive algorithm for house price as the housing market is a stand-out among the most involved regarding valuing the price and continues to fluctuate, is constantly a need for socio-economic advancement and welfare of citizen. In this paper, we develop machine learning algorithms for forecasting UK housing Price, and find an optimal algorithm that forecasts housing price accurately on the premises of the presence of many features or covariates. After applying correlation analysis to remove correlated variables in order to avoid multicollinearity, thereby increasing the statistical power, a novel method of using regression analysis to first of all understand and select statistically significant features for the various regions in England based on North South divide is adopted. These features are then used in the machine learning algorithm to further increase the statistical power of the algorithm, increase the level of accuracy for each of them and ultimately increase the predictive values for the algorithms. The model construction involves 3 stages: 1- correlation analysis to identify and remove correlated variables thereby avoiding multicollinearity and increasing the statistical power of the linear regression, 2 - using linear regression to determine variables that are statistically significant and 3 - building the machine learning algorithms based on the variables that are statistically significant from the linear regression. A comprehensive dataset of UK Paid housing Price from 2010 to 2019 was linked to a number of other datasets to generate a total 21 variables or features used for the models. Catboost, Gradient Boosting, Bagging, Random Forest, Extra Tree all achieved the excellent models performance result in all the regions considered. The comparison of the seven models showed that Extra Tree algorithm consistently achieved the best performance in term of level of accuracy in all the regions. K-Nearest Neighbours (KNN) is the only algorithm with less than 50% level of accuracy. Noticeably, the regions considered had varying or differing insignificant variables, implying that although many variables are common (statistically significant) to all the regions, there are regional differences and impact when modelling or predicting housing prices. This study validates the practicability of developing a machine learning methodology for the prediction of housing price. This research offers a reference for future house price prediction based on machine learning.

Hypoxia is one of the common abiotic stresses that negatively affects the development and productivity of agricultural crops. Quercetin is used to protect plants from oxidative stress when exposed to environmental stressors. O2 deficiency leads to impaired development and morphometric parameters in wheat varieties Orenburgskaya 22 (Triticum aestivum) and varieties Zolotaya (Triticum durum). Cytological analysis revealed various types of changes in the cytoplasm under conditions of hypoxia and treatment with quercetin. The most critical changes in the cytoplasm occur in the Zolotaya variety during pretreatment with quercetin followed by hypoxia, and in the Orenburgskaya 22 variety during hypoxia. Quercetin has a protective effect only on the Orenburgskaya 22 variety, and also promotes more effective recovery after exposure to low O2 content. Hypoxia causes an increase in ROS and activates the antioxidant system. It has been shown that the most active components of the antioxidant system in the Orenburgskaya 22 variety are MnSOD and Cu/ZnSOD, and in the Zolotaya variety GSH. We have shown that quercetin provides resistance only to the wheat genotype Orenburgskaya 22, as a protective agent against abiotic stress, which indicates the need for a comprehensive study of the effects of exogenous protectors before use in agriculture.

Artificial Intelligence (AI) emerges as a powerful catalyst poised to reshape the global sustaina-bility landscape by facilitating the attainment of Sustainable Development Goals (SDGs). This comprehensive Delphi study meticulously probes the insights of domain experts, shedding light on the strategic utilization of AI to advance these critical sustainability objectives. Employing rigorous statistical techniques, encompassing measures of central tendency and interquartile de-viation, this research scrutinizes consensus dynamics among experts and elucidates potential variations in their viewpoints. The findings resoundingly convey experts' collective positive perspective regarding AI's pivotal role in propelling the SDGs forward. Through two iterative rounds of extensive discussions, a compelling consensus crystallizes—AI indeed exerts an overall positive impact, exemplified by a robust mean score of 78.8%. Intriguingly, distinct SDGs manifest varied propensities toward AI intervention, with Goals 6, 7, 8, 9, 11, 13, 14 and 15 basking in the radiance of highly positive impacts. Goals 1, 2, 3, 4, 5, 10 and 12 exhibit positive impact scores, indicating a juncture ripe for positive advancements. Meanwhile, Goal 16 and Goal 17 languish with neutral scores, signifying a juncture demanding nuanced deliberations about AI's impact on peace, justice, and strong institutions as well as on partnerships for the goals respectively. This paper underscores AI as a formidable instrument poised to address humanity's most pressing challenges while harmonizing seamlessly with the overarching SDG objectives. It gracefully dovetails into established practices across pivotal domains such as health, education, and resilient infrastructures, amplifying the collective global endeavor to navigate the path toward a more sustainable future.

To solve large scale linear equations involved in the Fast Multipole Boundary Element Method (FM-BEM) efficiently, an iterative method named the generalized minimal residual method (GMRES)(m)algorithm with Variable Restart Parameter (VRP-GMRES(m) algorithm) is proposed. By properly changing a variable restart parameter for the GMRES(m) algorithm, the iteration stagnation problem resulting from improper selection of the parameter is resolved efficiently. Based on the framework of the VRP-GMRES(m) algorithm and the relevant properties of generalized inverse matrix, the projection of the error vector r_m+1 on r_m is deduced. The result proves that the proposed algorithm is not only rapidly convergent but also highly accurate. Numerical experiments further show that the new algorithm can significantly improve the computational efficiency and accuracy. Its superiorities will be much more remarkable when it is used to solve larger scale problems. Therefore, it has extensive prospects in the FM-BEM field and other scientific and engineering computing.

The African society is one of the societies with rich culture and traditions. Apart from the indigenous religion of Africa, Christianity and Islam are worshiped as the major religions of the African society. Literature reflects a great amount of influence of religions on the existing societies, people and cultures. African literature often mirrors the clash of indigenous religion with Christianity. In the writings of African authors one can find the elements of Christian beliefs and practices. The present paper, however, is focused on the African woman novelist Buchi Emecheta’s selected four novels: Second-Class Citizen (1974), The Bride Price (1976), The Slave-Girl (1977) and The Joys of Motherhood (1979). The paper attempts to discuss the impact of Christianity on the social and cultural aspects of the African society with special focus on African women. The findings reveal the positive as well as negative impacts of the new religion on African people and on the position of African women through the characters present in the selected novels. With the medium of writing and through Christianity, Emecheta seek to educate her society and improve upon the position of the African women.

Schistosomiasis is a debilitating parasitic disease of poverty that affects more than 200 million people worldwide, mostly in sub-Saharan Africa, and is clearly associated with the construction of dams and water resource management infrastructure in tropical and subtropical areas. Changes to hydrology and salinity linked to water infrastructure development may create conditions favorable to the aquatic vegetation that is suitable habitat for the intermediate snail hosts of schistosome parasites. With thousands of small and large water reservoirs, irrigation canals, and dams developed or under construction in Africa, it is crucial to accurately assess the spatial distribution of high-risk environments that are habitat for freshwater snail intermediate hosts of schistosomiasis in rapidly changing ecosystems. Yet, standard techniques for monitoring snails are labor-intensive, time-consuming, and provide information limited to the small areas that can be manually sampled. Consequently, in low-income countries where schistosomiasis control is most needed, there are formidable challenges to identify potential transmission hotspots for targeted medical and environmental interventions. In this study, we developed a new framework to map the spatial distribution of suitable snail habitat across large spatial scales in the Senegal River Basin by integrating satellite data, high-definition, low-cost drone imagery, and an artificial intelligence (AI)-powered computer vision technique called semantic segmentation. A deep learning model (U-Net) was built to automatically analyze high-resolution satellite imagery to produce segmentation maps of aquatic vegetation, with a fast and robust generalized prediction that proved more accurate than a more commonly used random forest approach. Accurate and up-to-date knowledge of areas at highest risk for disease transmission can increase the effectiveness of control interventions by targeting habitat of disease-carrying snails. With the deployment of this new framework, local governments or health actors might better target environmental interventions to where and when they are most needed in an integrated effort to reach the goal of schistosomiasis elimination.