As fatigue properties of as-built components of additively manufactured (AM) metals are considerably weaker than those of wrought metals because of rougher surface, post-processing is necessary to improve fatigue properties. To demonstrate improvement of fatigue properties of AM metals by post-processing, powder bed fusion (PBF) using laser sintering (LS) AlSi10Mg, i.e., PBF-LS/AlSi10Mg was treated by “submerged laser peening (SLP)” using a fiber laser and/or a Nd:YAG laser, then evaluated by plane bending fatigue tests. At SLP, “laser ablation (LA)” is generated by a pulsed laser, and a bubble is generated after LA, which behaves like a cavitation bubble that is named as “laser cavitation (LC)”. In the present paper, LA-dominated SLP is called as “laser treatment (LT)”, while LC-collapse-dominated SLP is called as “laser cavitation peening (LCP)”, as impact at LC collapse is used for peening. It was revealed that SLP using the fiber laser was LT rather than LCP. It was demonstrated that the fatigue strength at N = 10^7 was 85 MPa for LCP, and 103 MPa for combined process of blasting (B) + LT + LCP, whereas the fatigue strength of as-built specimen was 54 MPa.

Cannabidiol (CBD), a non-psychotropic main component of the Cannabis plant, is approved as a drug in the European Union (EU) under the name “Epidyolex”. However, the approval process as a food ingredient under the Novel Food Regulation was paused by the European Food Safety Authority (EFSA) due to a lack of safety data. Nevertheless, there is a growing, unregulated market in which CBD is advertised with various health claims and different dosage instructions. Of particular concern is its toxic effect on the liver and possible reproductive toxicity in humans. Studies suitable for calculating a benchmark dose were identified from the available data. Animal studies yielded a Benchmark Dose Lower Confidence Limit (BMDL) of 43 mg/kg bw/day, which translates into a safe human dose of approximately 15 mg/day. Only a Lowest Observed Adverse Effect Level (LOAEL) of 4.3 mg/kg bw/day could be identified from the human data. This updated risk assessment confirmed the Health-based Guidance Value (HBGV) of 10 mg/day based on human LOAEL. Despite existing data gaps, preliminary regulation appears advisable as the current form of the gray CBD market is unacceptable from the standpoint of consumer safety and protection.

This study examines the Soil Organic Carbon (SOC) within Greek croplands, offering a comprehensive understanding of its dynamics. SOC, a cornerstone in soil health, nutrient cycling, and global carbon dynamics, assumes critical significance in sustainable agriculture and climate change mitigation. Drawing on diverse soil properties, including pH, soil texture as well as different drainage and slope categories, the research explores the nuanced relationships shaping SOC dynamics in the diverse agroecological landscape of Greece. The investigation transcends local boundaries, emphasizing SOC's global role in climate change mitigation by sequestering carbon dioxide. Two maps were used as data sources: 1) SOC stock baseline map (2010) by JRC, 2) SOC stock map (2021) by the Institute of Soil and Water Resources, Hellenic Agricultural Organization – DIMITRA in collaboration with FAO. Greek croplands emerge as a mosaic of agroecological diversity, where anthropogenic activities wield transformative influences on SOC stock, demanding a delicate balance between agricultural productivity and soil health. The study unveils the influence of Soil Order, weaving a tapestry of SOC variability. Microscopic factors, from soil texture to cation exchange capacity, further shape SOC dynamics, emphasizing the role of clayey soils and coarse materials in carbon retention. Although soil organic carbon decreased from 2010 to 2021 the degree of carbon loss varied. This scientific endeavor synthesizes existing knowledge and unveils novel insights, offering a narrative woven from diverse soil properties. The findings contribute valuable insights for sustainable land management practices and climate change mitigation strategies, underscoring the importance of region-specific approaches in addressing global challenges.

Ubiquitin-specific protease 2 (USP2) maintains mitochondrial integrity in culture myoblasts. In this study, we investigated molecular mechanisms underlying the protective role of USP2 on mitochondria. Knockout (KO) of the Usp2 gene or chemical inhibition of USP2 induced robust accumulation of mitochondrial reactive oxygen species (ROS), accompanied by defects in mitochondrial membrane potential, in C2C12 myoblasts. ROS removal by N-acetyl-L-cysteine restored the mitochondrial dysfunction induced by USP2 deficiency. Comprehensive RT-qPCR screening and following protein analysis indicated that both genetic and chemical inhibition of USP2 elicited a decrease of uncoupling protein 2 (UCP2) at mRNA and protein levels. Accordingly, the introduction of a Ucp2-expressing construct effectively recovered mitochondrial membrane potentials, entailing an increment of the intracellular ATP level in Usp2KO C2C12 cells. In contrast, USP2 deficiency also decreased peroxisome proliferator-activated receptor  coactivator 1 (PGC1 protein in C2C12 cells, while it upregulated Ppargc1a mRNA. Overexpression studies indicate that USP2 potentially stabilizes PGC1 in an isopeptidase-dependent manner. Given that PGC1 is an inducer of UCP2 in C2C12 cells, USP2 might ameliorate mitochondrial ROS by maintaining the PGC1–UCP2 axis in myoblasts.

Functional neurological disorder (FND) is a complex condition that involves a disruption in the brain's ability to properly integrate sensory input and prior expectations, leading to motor dysfunction in functional motor disorders (FMD). This study investigates the role of sensory attenuation and the sense of agency in FMD, focusing on how these mechanisms can be leveraged for therapeutic interventions. Sensory attenuation, the brain's ability to predict and reduce the intensity of self-generated sensory inputs, is impaired in FMD, leading to a reduced sense of agency. This impairment disrupts motor control and contributes to the perception of involuntary movements.We propose using a bipedal reaching virtual reality (VR) task combined with a haptic ankle device to explore and potentially rehabilitate these impairments. In this task, foot positions are represented by VR objects, with initial weighting favoring the unaffected limb. This weighting gradually shifts to the affected limb as its involvement increases under operant conditioning. The task occasionally introduces perturbations to probe motor-related processing and feedback correction, providing a sensitive measure of visuomotor control. Additionally, we incorporate neuroimaging techniques, specifically functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG), to monitor brain activity and assess the effectiveness of these interventions. This approach aims to enhance understanding of the neural mechanisms underlying FND and develop targeted therapies that improve motor control by leveraging the interplay between sensory attenuation and amplification.Our findings could provide valuable insights into the treatment of FND, emphasizing the importance of feedback modulation and the integration of modern technologies like VR and haptic feedback in therapeutic interventions. This research has the potential to significantly improve the prognosis and quality of life for individuals with FND.

This article focuses on the leader-following consensus of fuzzy fractional order singular perturbation multi-agent systems (FOSPMASs) with order in 0,2. By employing the T-S fuzzy modeling approach, a fuzzy FOSPMAS is constructed. Subsequently, a fuzzy observer-based controller is designed and the error system corresponding to each agent is derived. Through a series of equivalent transformations, the error system is decomposed into fuzzy singular fractional order systems (SFOSs). According to the admissibility of SFOSs, the consensus conditions of the fuzzy FOSPMAS are obtained based on linear matrix inequalities (LMIs) without equality constraint. Finally, the effectiveness of the criteria is verified through an RLC circuit model.

Introduction: Senescence-resembling alterations on lymphocytes of dialysis patients have been widely described. However, pathophysiology behind these phenomena has not been clarified. In this study, we examine the impact of dialysis prescription and residual renal function on T and B lymphocytes, in dialysis patients. Methods: T and B cell subsets were determined with flow cytometry in 36 hemodialysis and 26 hemodiafiltration patients, according to the expression of CD45RA, CCR7, CD31, CD28, CD57 and PD1 for T cells, and IgD and CD27 for B cells. Immune phenotype was associated with dialysis modality, hemofiltration volume, and mortality. Results: Compared to hemodialysis, hemodiafiltration patients had significantly decreased percentage of CD4+CD28-CD57- T cells [3.8(2.4-5.3) vs 2.1(1.3-3.3)%, respectively, P=0.002] and exhausted CD4+ T cells [14.1(8.9-19.4) vs 8.5(6.8-11.7)% , respectively, P=0.005]. Additionally, hemofiltration volume was negatively correlated to CD8+ EMRA T cells (r=-0.46, P=0.03). Finally, exhausted CD4+ T cells percentage could predict all-cause mortality in dialysis patients, independently of age. Conclusion: Hemodiafiltration, especially with high hemofiltration volume, may have beneficial effects on senescence-related immune phenotype. Immune phenotype may also be a predicting factor for mortality in dialysis patients.

This study investigates the characteristics of formaldehyde (HCHO) concentration and its reduction in newly constructed apartment buildings in Dubai. It addresses the significant health risks of high HCHO levels due to poor ventilation and extensive use of VOC-emitting materials. The research explores the effectiveness of various mitigation strategies, including air purifiers, photocatalyst applications, and window ventilation, in the living room, master bedroom (MBR), Room 1, and Room 2. HCHO concentrations were measured under different conditions: sealed windows, operation of an air purifier with a VOCs filter, and the application of a photocatalyst. The study followed a quantitative approach, recording real-time HCHO levels over 24 hours. Results indicated that sealing windows led to HCHO concentrations surpassing the domestic standard of 0.1 ppm, with the MBR recording the highest concentration at 0.73 ppm. The air purifier showed minimal impact within the first 8 hours but achieved an 18% reduction after 24 hours of operation. Applying a photocatalyst to room surfaces resulted in a 50% reduction in HCHO levels. Ventilation through window openings significantly improved air exchange rates, with the air exchange per hour (ACH) increasing proportionally with window opening size. Smaller rooms with larger window-to-volume ratios, such as Room 1 and Room 2, maintained HCHO concentrations below the WHO standard of 0.1 ppm with partial window openings. The study concludes that window ventilation is the most effective strategy for reducing HCHO concentrations, highlighting the importance of integrating comprehensive ventilation designs in modern residential buildings to ensure healthier indoor environments in Dubai.

The metaverse is gradually expanding. There is a growing number of photo and video recordings of metaverse virtual worlds being used in multiple domains, with growing collections. An essential element of the metaverse and its recordings are avatars. In this paper, we present a novel task of avatar detection in metaverse recordings, supporting semantic retrieval in collections of metaverse recordings and other use cases. Our work addresses the characterizations and definitions of avatars and presents a new model supporting avatar detection. The latest object detection algorithms are trained and tested on a variety of avatar types in metaverse recordings. Our work achieves a higher level of accuracy than existing models, which encourages further research in this field.

The geological and hydrological conditions of tunnels near reservoirs are complex, and the impact of water level changes on the stability and leakage assessment of the lining structure is not considered in the current leakage evaluation. In order to construct an evaluation model for leakage level of tunnels near reservoirs, the influence of water level changes on tunnel stability and changes in environmental conditions on the leakage of tunnels were researched. Based on the AHP and extensibility theory, a hierarchical system for leakage assessment, incorporating values from nine indexes representing three aspects: geological conditions, hydrological conditions, and tunnel engineering. Numerical simulation was used to analyze the influence of water level changes. It was found that the water level change index greatly influences the displacement and stress distribution inside the tunnel structure. The leakage evaluation model was applied to the Tiebeishan Tunnel, resulting in a rating of 3, indicating medium-level leakage. Attention should be paid to water leakage in tunnels with changes in reservoir water levels. The leakage evaluation model for tunnels near reservoirs can effectively assess leakage levels under various conditions, providing a reference for safety assessments of tunnel leakage near reservoirs.

Recently, we published that the monoclonal antibody (D12 mAb) recognizes gp63 of L. mexicana, it is responsible for COX activity. This D12 mAb exhibited cross-reactivity with Trypanosoma cruzi, Entamoeba histolytica, Acanthamoeba castellanii, and Naegleria fowleri. COX activity assays performed in these parasites suggested the potential presence of such enzymatic activity. In our investigation, we confirmed that wild-type recombinant gp63 exhibits COX-like activity, in contrast to a mutated recombinant gp63 variant. Consequently, our objective was to identify sequences orthologous to gp63 and subsequently analyze the binding of arachidonic acid (AA) to the putative active sites of these proteins. Given the absence of a crystallized structure for this protein in the Protein Data Bank (PDB), it was imperative to first obtain a three-dimensional structure by homology modeling, using leishmanolysin (PDB ID: LML1) as a template in the Swiss model. Database. The results obtained through molecular docking simulations revealed the primary interactions of AA close to the Zinc atom present in the catalytic site of gp63-like molecules of several parasites, predominantly mediated by hydrogen bonds with HIS264, HIS268 and HIS334. Furthermore, COX activity was evaluated in commensal species such as E. dispar and during the encystment process of E. invadens.

A testable hypothesis with quantitative predictions is put forward, proposing that strong acids produced on land at a rate correlated with global population are an increas-ing cause of increasing atmospheric CO2 pressure (pCO2). This hypothesis widens the imbalance assumed between the global uptake of CO2 by photosynthesis and emissions of CO2 from all sources, including the combustion of fossil fuels, causing greater atmos-pheric pCO2. Our modelling tests for reactions of dissolved inorganic carbon show that increasing atmospheric CO2 is caused thermodynamically by falling land surface pH values, but only with bicarbonate present. Strong acids generated by oxygen from re-duced inorganic compounds of nitrogen and sulphur emit CO2 almost stoichiometrically from dissolved bicarbonate in the pH range of most global soils, between 6 to above 8. We show that each decrease of aqueous pH value of 0.01 units from acidification of sur-face water near pH 8 potentially increases the pCO2 in the atmosphere by about 7 ppmv. The surface pH value of the ocean near 8.10 in 2000 has been shown to decrease at this rate, a result of equilibrating with the rising atmospheric pCO2. Therefore, our qualita-tive estimates of increasing atmospheric CO2 driven by irreversible acidification on land are critical and need broad scale validation. Unfortunately, these acidifying processes on land from excessive nitrogen fertiliser, export of alkaline produce from farmlands and other processes were not considered by previous biogeochemical reviews. However, several very recent research studies showing CO2 emissions from soil during nitrifica-tion are consistent with our hypothesis. Despite counter measures to curb excessive CO2 emissions, including carbon capture and geological storage, the increasing Keeling curve for pCO2 may continue to rise because zero carbon policies do not address these causes. We recommend that this hypothesis be further tested by in situ experiments in neutral soils and water, designed to compare CO2 emissions under the acidifying conditions de-scribed in this article. Corrective counter measures can then be designed and applied.

Void fillers are required for osseous gaps generated after orthopedic procedures as medial open-wedge high-tibial osteotomy (MOWHTO) to provide sufficient structural support and a rapid osteosynthesis. We developed a novel three-dimensional (3D) printing-based platform technology using the customized 3D scaffolds covered with polycaprolactone (PCL)/β-tri-calcium phosphates (β-TCP)/bone decellularized extracellular matrix (dECM) for use as bone substitute scaffold, which can be effectively exploited to estimate the calculated correction angle with preoperative simulations. PCL/β-TCP/bone dECM scaffolds demonstrated significantly higher cell contain levels in cell seeding efficiency, excellent proliferation capacity, and promotion of early osteogenic differentiation compared with PCL/β-TCP scaffolds. The scaffolds promoted bone mineralization at the early time points of an in vivo study (8 weeks) and exhibited biodegradable properties (38% for 16 weeks). The correction angle measured after osteotomy using 3D printed scaffolds was estimated with high accuracy with low errors (10.3° ± 0.9°), was and was not significantly different even in the presence of lateral cortical hinge fractures. The customized 3D scaffold enriched with PCL/β-TCP/bone dECM yielded excellent cell seeding efficiency, proliferation capacity, early osteogenic differentiation, and bone mineralization outcomes. It is expected to solve the disadvantages related with bone union in MOWHTO, and to replace autografts in the future.

Background: Although several studies have been conducted on the use of Artificial Intelligence (AI) in mammography (MG), research focusing on the diagnosis of metachronous bilateral breast cancer (BC), which is typically more challenging to diagnose, remains limited. This study assessed whether AI could enhance the detection of BC, achieving earlier or more accurate diagnoses than radiologists in cases of metachronous contralateral BC. Methods: The study included patients who underwent unilateral BC surgery and subsequently developed contralateral BC during follow-up. We evaluated the capability of the AI-supported MG diagnostic system FxMammo™ (FathomX Pte Ltd, Singapore) to diagnose BC more accurately or earlier than radiologists' assessments. This evaluation was supplemented by reviewing MG readings by radiologists. Results: Out of 1,101 patients who underwent surgery, 10 patients who had initially received a partial mastectomy and later developed contralateral BC were analyzed. The AI system identified malignancies in 6 cases (60%), while radiologists identified 5 cases (50%). Notably, two cases (20%) were diagnosed solely by the AI system. Additionally, for these cases, the AI system had identified malignancies a year prior to the conventional diagnosis. Conclusions: This study highlights the AI system's effectiveness in diagnosing metachronous contralateral BC via MG. In some cases, the AI system consistently diagnosed cancer at earlier than radiological assessments.

Measurements of the properties of soft materials are important from the point of view of medical diagnostics of soft tissues as well as testing the quality of food products and many technical materials. One of the frequently used techniques for testing such materials, attractive due to its non-invasive nature, is the indentation technique, which does not puncture the material. The difficulty of testing soft materials, which affects the objectivity of its results, is related to the problems of stable positioning of the studied material in relation to the indentation apparatus, especially with a device held by the operator. This work concerns the comparison of test results using an indentation apparatus mounted in mobile and stationary handles. The tested materials are cylindrical samples of polyurethane foams with three different stiffnesses and the same samples with a 0.5- or 1-mm-thick silicone layer. The presented research uses an apparatus with a flat cylindrical indenter, with a surface area of 1 cm2, pressed to a depth of 10 mm (so-called deep tests). Based on the recorded force changes over time, five descriptors of the indentation test were determined and compared for both types of handles. The tests performed showed that the elastic properties of foam materials alone and with a silicone layer can be effectively characterized by the maximum forces during recessing and retraction, and the slopes of the recessing and retraction curves. In the case of two-layer materials, these descriptors reflect both the characteristics of the foams and the silicone layer. The results showed that the above property of the deep indentation method distinguishes it from the shallow indentation method. The repeatability of tests performed in the mobile and stationary holders were determined to be comparable.

Percutaneous coronary intervention (PCI) to chronic total occlusion (CTO) is still a subject of debate. The primary goal of revascularization is to provide symptomatic relief and enhancing left ventricular (LV) functions. Global longitudinal strain (GLS) is proven to be more sensitive than ejection fraction (EF), especially for subtle ischemic changes. The purpose of this study was to investigate the improvement in LV GLS after revascularization of symptomatic stable coronary patients with single-vessel CTO, categorized according to their collateral supply grades. 69 patients with successful CTO PCI were grouped according to their collateral supply grades, as well-developed (WD) and poor collateral groups and followed-up for 3 months. Basal characteristics were similar for both groups, except for lower EF (p=0.04) and impaired GLS (p

Access to reliable water supply is critical for sustainable development and public health, yet many peri-urban and rural communities in the developing world face challenges such as poor maintenance, faulty infrastructure, and inadequate governance of water services, hindering the UN’s Sustainable Development Goals (SDG). In Emina-Boadi, a small town in Kumasi, Ghana, residents increasingly rely on boreholes due to substandard service from the Ghana Water Company Limited (GWCL). This shift highlights concerns about water reliability, quality, and affordability, impacting public health and hindering progress toward SDG 6. This case study assesses water service levels using key performance indicators (KPIs) such as quantity, quality, affordability, accessibility, and reliability, focusing on sources like boreholes, hand pumps, piped water, hand-dug wells, rainwater, and surface waters. The study aims to delineate the roles of different water providers, understand community dynamics, and evaluate contributions to rural development and SDG 6 through stakeholder interviews and questionnaires. Leveraging the WASHCost framework, which aims to improve planning methods and provision of water and sanitation services by addressing the lack of cost information in rural and peri-urban areas, and the Joint Monitoring Programme (JMP) framework, which monitors progress toward global targets related to water, sanitation, and hygiene, the study categorizes indicators and draws connections among them. Findings reveal a significant preference for borehole services, with 87% usage and an 83% reliability rate compared to 13% for GWCL. Daily water consumption averages 60.75 liters per person, with on-premises access improving water collection efficiency to 7 minutes. Dissatisfaction with GWCL services highlights the need for improved delivery aligned with community needs and SDG targets. Adopting sustainable management practices, enhancing infrastructure, and improving governance are crucial for ensuring safe and affordable water access for all residents of Emina-Boadi and similar communities.

The objective of the study was to investigate the dynamics of collaborative learning in TBL through students’ reflections and feedback. The study utilized a mixed-methods approach. Quantitative data collection was done via feedback structured questionnaire. Qualitative data were collected from reflections submitted by 107 first-year MBBS students at the end of TBL session. We found five main themes related to students’ engagement with the session i.e. ( 1) conceptual clarity as the foundation, (2) collaborative learning culture, (3) communication skills, (4) informative and useful team discussions and (5) interactive learning for team development. The majority of the respondents (93%) listened to classmates and coordinated with group members in discussion, (77%) were willing to learn from other group members and contributed ideas to them, (79%) came prepared for session, (75%) found learning material assigned to them as appropriate. Respondents had positive perceptions regarding their participation in group work with a strong inclination towards agreement with the statements provided. The study highlights the positive effects of TBL in promoting peer to peer engagement, active engagement, teamwork skills, and knowledge sharing among undergraduate medical students, ultimately contributing to an effective learning experience.

This research explores the application of ARIMA (Autoregressive Integrated Moving Average) models and parallel computing techniques to analyze and forecast anemia diagnoses in children under 36 months in the Junín region of Peru. Using health data from 2023-2024, including insurance type, patient information, diagnosis dates, hemoglobin levels, and treatment details, we develop predictive models to understand trends and patterns in childhood anemia. The study aims to demonstrate the effectiveness of time series analysis and high-performance computing in addressing this critical public health issue. Results indicate improved forecasting accuracy and computational efficiency, potentially aiding in resource allocation and policy development for anemia prevention and treatment programs.

Trehalose is a naturally occurring disaccharide that has recently gained significant attention for its neuroprotective properties in various models of neurodegeneration. This review provides an overview of available experimental data on the beneficial properties of trehalose for central nervous system pathological conditions. Trehalose’s impact on neuronal cell survival and function was also examined. As a result, we identified that trehalose’s neuroprotection includes autophagy modulation as well as its capability to stabilize proteins and inhibit the formation of misfolded ones. Moreover, trehalose mitigates oxidative stress-induced neuronal damage by stabilizing cellular membranes and modulating mitochondrial function. Furthermore, trehalose attenuates excitotoxicity-induced neuroinflammation by suppressing pro-inflammatory cytokine release and inhibiting inflammasome activation. A possible connection of trehalose with the gut-brain axis was also examined. These findings highlight the potential therapeutic effects of trehalose in neurodegenerative diseases. According to the conclusions drawn from this study, trehalose is a promising neuroprotective agent as a result of its distinct mechanism of action, which makes this compound a candidate for further research and development of therapeutic strategies to combat neuronal damage and promote neuroprotection in various neurological diseases.

Sodium hypochlorite (NaOCl) is widely used in public healthcare facilities; this exposure can result in the development of bacterial tolerance to disinfectant, which has known links to antibiotic cross-resistance. However, the mechanism through which cross-resistance to antibiotics and disinfectants develops remains ambiguous. Therefore, this study aimed to examine the phenotypic, and transcriptomic changes caused by disinfectant exposure in gram-negative bacteria and determine the cause of cross-resistance to antibiotics. The results demonstrated that the misuse of disinfectants plays an important role in the emergence of disinfectant resistance and in the increase in antibiotic resistance. Antibiotic resistance may occur from exposure of gram-negative bacteria to subminimal inhibitory concentrations (MICs) of NaOCl. Ten passages of gram-negative bacteria in increasingly higher subMICs of NaOCl disinfectant was sufficient to increase the MIC to >2,500 µg/ml NaOCl, particularly in K. pneumoniae and P. aeruginosa. To determine the development of cross-resistance to antibiotics due to NaOCl exposure, the MICs for each antibiotic before and after exposure of each strain to sublethal concentrations of NaOCl were compared. After overnight incubation with a sublethal concentration of NaOCl, a statistically significant increase in MIC was only observed for imipenem (P<0.01). Investigation of the mechanism of cross-resistance by means of transcriptome analysis revealed that 1,250 µg/ml NaOCl-adapted K. pneumoniae and P. aeruginosa strains increased resistance to imipenem due to increased expression of the resistance-nodulation-cell division (RND) efflux pumps, such as AcrAB-TolC and MexAB/XY-OprM. Therefore, we suggest that exposure to NaOCl can influence the expression of RND efflux pump genes, contributing to imipenem cross-resistance.

Background Obesity is a major healthcare challenge worldwide. Recently, glucagon-like peptide-1 receptor agonists (GLP-1RAs) have emerged as a promising pharmacological option for managing type 2 diabetes mellitus (T2DM) and obesity in diabetic patients. Objective This systematic review aims to evaluate the efficacy and safety of GLP-1RAs in nondiabetic patients. Methods We systematically reviewed 2356 published articles from the past ten years (2013 to November 22, 2023). After rigorous screening, 11 articles were selected for an in-depth review. The analysis focused on the efficacy and safety of GLP-1RAs in nondiabetic patients, considering various baseline characteristics and subgroups. Results The review found that GLP-1RAs, including exenatide, liraglutide, semaglutide, and the dual glucose-dependent insulinotropic polypeptide and glucagon-like peptide-1 receptor agonist (GIP/GLP-1RA) tirzepatide, significantly promoted weight loss in obese/overweight nondiabetic patients. Additionally, these agents positively affected cardiovascular risk factors such as blood pressure, glycemic control, nephropathy, lipid levels, serum insulin levels, and C-reactive protein (CRP) profiles. However, GLP-1RAs, including tirzepatide, were associated with gastrointestinal adverse drug reactions such as nausea, diarrhea, vomiting, and constipation. These adverse events were typically transient, mild-to-moderate in severity, and subsided over time. Conclusion GLP-1RAs are effective and relatively safe for weight management and improving cardiovascular risk factors in nondiabetic patients, despite the occurrence of some gastrointestinal side effects. Further research is warranted to optimize the use of these agents in nondiabetic populations.

Heterosis of growth traits in economic fish has benefited the production of aquaculture for many years, yet its genetic and molecular basis has been remained obscure. Nowadays, a new germplasm of hybrid Jinhu grouper (Epinephelus fuscoguttatus♀ × E. tukula♂), exhibiting paternal-biased growth heterosis, has provided an excellent model for investigating the potential regulatory mechanisms of heterosis. We integrated transcriptome and methylome to unravel the changes of gene expression, epigenetic modification, and subgenome dominance in Jinhu grouper compared with maternal E. fuscoguttatus. Integration analyses showed that the heterotic hybrids showed lower genomic DNA methylation levels than the purebred parent, and the up-regulated genes were mostly DNA hypomethylation. Furthermore, allele-specific expression (ASE) detected paternal subgenome dominance regulated paternal-biased heterosis, and paternal bias differentially expressed genes (DEGs) were wholly up-regulated in the muscle. Muti-omics results highlighted the role of lipid metabolism, particularly “Fatty acid synthesis”, “EPA biosynthesis”, and “Signaling lipids”, in Jinhu grouper heterosis formation. Coherently, our studies have proved that the eicosapentaenoic acid (EPA) of Jinhu grouper was greater than that of maternal E. fuscoguttatus (8.46% vs 7.46%). Finally, we constructed a potential regulatory network for control of the heterosis formation in Jinhu grouper. Among them, fasn, pparg, dgat1, igf1, pomca, fgf8a, and fgfr4, were identified as key genes. Our results provide new and valuable clues for understanding paternal-biased growth heterosis in Jinhu grouper, taking a significant step towards the molecular basis of heterosis.

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

This work discusses seismic isolation technologies and analyses the concept of geotechnical seismic isolation (GSI) system, which is characterized by new principles of operation, using geomaterial with modified properties to reduce inertial seismic loads on buildings and structures. The aim of the study is to develop a geotechnical seismic isolation system in the form of vertical barriers, with different geometrical characteristics, using rubber-soil mixture (RSM). The novelty of the work consists in determination of effective constructive and technical solutions of vertical seismic barriers from RSM, which are characterized by reliability in providing seismic isolation of construction objects. Soil and superstructure interactions are modeled in Plaxis software, using the Northridge earthquake accelerogram. The results confirm the positive impact of using RSM as an effective material for GSI vertical barriers. The present numerical and experimental results show that the GSI system using RSM can significantly reduce the seismic hazard. The results of computational-experimental modeling will become a research, analytical and design basis for the development of new ways to ensure earthquake resistance of construction objects.

This study evaluated the epidemiological and genetic susceptibility profile caused by coronavirus 2 (SARS-CoV-2) in children ≤3 years of age with acute gastroenteritis (AGE) or acute respiratory infection (ARI), living in the northwestern region of the Amazon (NWAR). Fecal and saliva sam-ples collected from 202 children (n=404) were subjected to detection of SARS-CoV-2 by RT-qPCR. Polymorphisms in the angiotensin-converting enzyme (ACE rs4646994) and ACE2 G8780A; rs2285666) genes were detected by SYBR GREEN real-time PCR and PCR/Alul digestion, respec-tively. Secretory and Lewis status of histo-blood group antigen (HBGA) was performed using phenotyping/ELISA. Frequencies for the AGE group: SARS-CoV-2; 8.9%; ARI group: SARS-CoV-2; 2.9%. The ACE I/I homozygous polymorphism gene was majority. Males with the ACE2 G8780A SNP were more susceptible to ARI symptoms than AGE (OR = 3.85; 95% CI-1.42-10.38; P 0.007). Most children were secretory FUT2 phenotype (92.6%). Surveillance of diarrhea and respiratory infections in children, along with understanding their causes, are crucial for identifying preven-tion and control strategies and for prioritizing and developing new vaccines. Clinical manifesta-tions of COVID-19 in children ≤3 years of age include AGE.

Detailed sonographic assessment of the fetal neuroanatomy plays a crucial role in prenatal diagnosis, providing valuable insights into timely well-coordinated fetal brain development and detecting even subtle anomalies that may impact neurodevelopmental outcomes. With recent advancements in artificial intelligence (AI) in general and medical imaging in particular, there has been growing interest in leveraging AI techniques to enhance the accuracy, efficiency, and clinical utility of fetal neurosonography. The paramount objective of this scoping review is to discuss the latest developments in AI applications in this field, focusing on image analysis, automation of measurements, prediction models for neurodevelopmental outcomes, visualization techniques, and integration into clinical routine.

The durability of bridge decks is a critical factor in ensuring the safety and longevity of transportation infrastructure. This article explores advanced materials and innovative techniques designed to mitigate cracking in bridge decks, a common issue that can compromise structural integrity and increase maintenance costs. It provides a comprehensive review of cutting-edge solutions such as Fiber-Reinforced Polymers (FRP), High-Performance Concrete (HPC), Ultra-High Performance Concrete (UHPC), and self-healing concrete technologies. Each material is analyzed for its ability to enhance strength, reduce permeability, and improve resistance to environmental stressors. Additionally, the article examines the role of surface treatments, sealants, and routine maintenance practices in prolonging the life of bridge decks. By synthesizing current research and practical applications, this article offers valuable insights and recommendations for engineers, contractors, and policymakers seeking to advance bridge deck durability through innovative materials and methodologies.

The Third U.S. National Marine Environmental DNA Workshop on June 2–5, 2024 brought together researchers, practitioners, and policymakers to overview and discuss: (1) environmental (e)DNA – defined as “DNA in the environment” – as a strategic U.S. national priority, (2) eDNA tool readiness and approaches to support decision-making, (3) emerging eDNA technologies, and (4) plans for implementation and adoption for environmental monitoring and ecosystem assessment “from microbes through whales”. Uses and applications of eDNA have been revolutionizing exploration, measurement, and monitoring of biodiversity across ecosystems, including the marine and freshwater aquatic environments emphasized in the Workshop, as well as terrestrial and aerial systems. The Workshop featured the launch of the new U.S. National Aquatic Environmental DNA Strategy from the White House Office of Science and Technology Policy (2024), with aquatic defined as freshwater to ocean waters, across all salinities; the Strategy was developed using outputs and a taskforce from the 2022 Second Workshop. The 2.5-day Third Workshop included speaker presentations, panel discussions, and networking on eDNA tools, applications, use, upscaling, and their future. The Workshop led into Capitol Hill Ocean Week (CHOW) events (June 5–6, 2024), during World Ocean Week. Note that this summary paper represents the author’s take-away view and interpretation, and not necessarily the overall views or consensus of the U.S. Government, Smithsonian Institution, workshop organizers, or speakers.

Using polymethylmethacrylate (PMMA) bone cement is widespread in orthopedic surgeries for implant fixation and as a carrier for antibiotic delivery to prevent and treat infections. This review comprehensively evaluates in vitro studies investigating the antibiotic elution profiles and mechanical properties of PMMA bone cement. We explore the kinetics of antibiotic release, factors influencing elution efficiency, and the impact of various antibiotics on the mechanical properties of PMMA composites. At the same time, we examine how the inclusion of antibiotics affects the mechanical integrity of PMMA, including parameters such as compressive strength, tensile strength, and fatigue resistance. Through a detailed analysis of these studies, this review aims to provide insights into optimizing PMMA bone cement formulations for enhanced therapeutic efficacy and structural performance.

The rapid evolution of digital payment systems has significantly transformed the retail industry, reshaping how transactions are processed and enhancing the overall shopping experience. This research explores the adoption of digital payment technologies in retail settings, focusing on the motivations, challenges, benefits, and impacts associated with their implementation. Retailers are increasingly driven by the need to meet consumer demands for convenience and speed, as well as to gain a competitive edge in a saturated market. Digital payment systems, including mobile wallets, contactless payments, and online payment gateways, have become essential tools for retailers seeking to streamline operations and improve customer satisfaction. The study highlights several key findings, including the challenges related to technical integration, security concerns, and cost implications. Technical difficulties in integrating new payment systems with existing point-of-sale infrastructure, coupled with the need for robust security measures, present significant obstacles. Despite these challenges, the long-term benefits of digital payments, such as increased transaction volumes, higher average transaction values, and valuable data insights, often outweigh the initial investment and ongoing costs. The research also underscores the positive impact of digital payments on customer behavior, noting improvements in transaction speed, convenience, and overall satisfaction. Furthermore, the findings reveal variations in the impact of digital payment systems across different retail settings, including large department stores, independent retailers, and e-commerce businesses. The ability to tailor digital payment solutions to the specific needs of each retail environment is crucial for maximizing benefits and ensuring successful implementation. Overall, the study provides a comprehensive understanding of the role of digital payment systems in modern retail and offers insights into the future trajectory of these technologies.

In recent times, the application areas of unmanned aerial vehicles (UAVs) are expanding, and autonomous functions are becoming increasingly prominent, eliminating the need for remote pilot control. Certain applications require the drone to use a docking station autonomously, even for wireless charging. This involves performing autonomous takeoff and landing, where high preci-sion is demanded. These maneuvers can be significantly influenced by environmental factors. The effectiveness of the precision landing function of the DJI Mavic 2 Pro UAV in strong winds is in-vestigated in this article based on experimental measurements conducted outdoors. New findings on the precision landing capabilities of the DJI Mavic 2 Pro UAV are presented in this paper, par-ticularly under windy conditions. The efficiency of precision landing is compared in cases when the precision landing function is enabled versus when it is disabled. It is investigated whether there is a statistically significant difference between the two landing modes in strong winds and it is examined whether the DJI Mavic 2 Pro can perform precision landing on a surface of a specific size in windy conditions. This helps to predict the suitability of the DJI Mavic 2 Pro for precise landing and wireless charging at a docking station in strong winds and high gusts.

The adoption of cloud-based supply chain management (SCM) solutions represents a transformative shift in how organizations manage their supply chains, offering significant advantages in terms of cost efficiency, flexibility, real-time data access, and the integration of advanced technologies. This study explores the multifaceted impacts of cloud-based SCM systems, focusing on both their benefits and the challenges encountered during their implementation. Through an in-depth analysis of interview and case study data, the research reveals that cloud-based solutions enable organizations to reduce capital and operational expenditures substantially while providing the scalability necessary to adapt to fluctuating demands. Real-time access to data enhances visibility and decision-making, and the incorporation of advanced technologies such as artificial intelligence and machine learning improves predictive analytics and process optimization. However, the study also identifies several critical challenges associated with the adoption of cloud-based SCM solutions. Key issues include data security concerns, integration difficulties with legacy systems, and the complexities of managing organizational change. Effective implementation requires meticulous planning, comprehensive training, and strategic vendor management to address these challenges successfully. The research highlights the importance of robust security measures, thorough integration strategies, and effective change management practices in overcoming these obstacles. The strategic outcomes of adopting cloud-based SCM solutions include improved operational efficiency, enhanced inventory management, and increased customer satisfaction. Additionally, organizations gain a competitive edge through better supplier coordination and greater responsiveness to market changes. Overall, the study demonstrates that while cloud-based SCM solutions offer substantial benefits, their successful adoption hinges on effectively managing associated challenges and leveraging their transformative potential.

The present study examined metabolites in Northern wild rice (WLD), the impact of WLD supplemented high fat (HF) diet on gut microbiota, short chain fatty acids (SCFAs) and correlation with metabolism or inflammation versus HF+white rice (WHR) in mice. C57BL/6J mice received HF diet supplemented with 26g% WHR, 26g% WLD, or 13g% WHR+13g% WLD (WTWD) for 12 weeks. The levels of fasting plasma glucose, total cholesterol, triglycerides, insulin resistance, inflammatory cytokines and monocyte adhesion were lower, and the abundances of fecal Lactobacillus gasseri species bacteria and propionic acid were higher in HF+WLD diet-fed mice compared to HF+WHR diet-fed mice (p<0.05). The anti-inflammatory effects of HF+WTWD diet were weaker than that in HF+WLD diet, but were greater than that in HF+WHR diet-fed mice (p<0.05). Relative abundances of fecal Lactobacillus gasseri and propionic acid in HF+WLD fed-mice were higher than that in HF+WHR fed mice. The abundance of fecal L. gasseri and propionic acid negatively correlated with metabolic and inflammatory markers (p<0.05). The findings suggest that WLD dose-dependently attenuated metabolic and inflammatory disorders in HF diet-fed mice. Interactions between WLD components and gut microbiota may upregulate fecal propionic acid and contribute to metabolic and anti-inflammatory benefits of WLD diet-induced insulin resistant mice.

The breast holds significant importance in women's lactation process. The breast has diverse tissues such as glandular, Cooper’s ligament, lactiferous ducts, adipose, muscles, and skin with various mechanical properties. Most soft tissues exhibit nonlinear, viscoelastic, and anisotropic mechanical behaviour. Stiffness is one of the commonly used mechanical properties for measuring mechanical behaviour in soft tissues. However, this is typically used in simplifying cases where analysis is limited to within the linear elastic region. Young’s modulus is the prevailing measure for quantifying stiffness in tissues. This systematic review examines commonly used techniques for mechanically characterising breast soft tissues to close the gap in the literature. Additionally, this systematic review summarises the mechanical behaviour of the breast tissues available in the literature and highlights the uncovered areas to understand the mechanical behaviour of breast tissues fully. These include a) more mechanical behaviour studies, allowing more accurate modelling for other applications, b) Viscoelastic analysis studies, and c) mechanical analysis on other breast tissues, such as the lactiferous duct, also known as the milk duct. The data obtained in the review can be used as inputs in computational models to analyse the behaviour of the breast tissues.

Background The operator's ability in performing carotid stenting (CAS) has improved clinical outcomes. However, more than 3% of patients need to be treated again after CAS. Most of the cases requiring further intervention are affected by hyperplasia. The recommended procedure is the DEBalloon. On the other hand, the literature reports a small number of carotid neoatherosclerosis cases and is recommended to be treated using elective Micronet-covered stent. Discriminating between the two types of in-stent-restenosis ISR (hyperplasia or neoatherosclerosis) is critical for a positive outcome.Case summary We describe a case in which a patient treated with carotid stenting 8 years before, was diagnosed with ISR. Due to the development of neurological symptoms and progressive increases in Peak Systolic Velocity (PSV) eight years following carotid stenting, a DEBalloon was used in a carotid in-stent-restenosis (ISR) standard procedure. About ten minutes after the procedure, the patient developed hemiplegia consistent with the treated carotid territory. The implantation of a MicroNet-covered stent excluded the thrombus and reverted symptoms with a normal MR control at 24 h. Conclusion This case illustrates that when in-stent stenosis evolves years after the stent implantation, neoatherosclerosis should be assessed, and a MicroNet-covered stent should be considered.

3D Printing /Additive manufacturing holds a promising future in healthcare as it aids in visualizing things and making 3D objects which is very important in different areas of medicine. The concept of one size fits all has failed the quality of care delivered by us in healthcare which demands customised needs for patient care to create 3D printed tissues, make personalized prosthetics, implants and physical models of the human body. The materials used for printing models and other healthcare devices for medical education, patient needs, and prototyping are increasing. The application of different materials for use in healthcare is not studied. New materials are also available for the various applications in healthcare industry. This experimental study was conducted to review the nine distinct 3D printing filament materials like PETG, PA, ABS, PLA, HIPS, PMMA, Ceramic, Carbon Fiber, and (PLA + Metal Composite) with the help of a 3D printed physical model of T-12 thoracic vertebrae using all the abovementioned materials. The evaluation of materials was based on diverse mechanical properties, applications across medical fields, performance metrics, costs, accuracy, and quality. The assessment This study also focuses on comparison of mechanical properties such as tensile strength, compressive strength of the abovementioned materials with human bone. The study also reviews the 3D printing process and explores its utilization in biomedical applications. The Insights about the application of various materials holds a promising future for development of newer materials for healthcare industry.

Cellulose in the nano regime, defined as nanocellulose, has been intensively used for water treatment. Nanocellulose can be produced in various forms including colloidal, water-re-dispersible powders, films, membranes, nano papers, hydrogels/aerogels, and three-dimensional (3D) objects. They were reported for the removal of water contaminants e.g., heavy metals, dyes, drugs, pesticides, pharmaceuticals, microbial cells, and other pollutants from water systems. This review summarized the recent technologies for water treatment using nanocellulose-based materials. A scientometric analysis of the topic was also included. Cellulose-based materials enable the removal of water contaminants, and salts offer advanced technologies for water desalination. They are widely used as substrates, adsorbents, and catalysts. They were applied for pollutant removal via several methods such as adsorption, filtration, disinfection, coagulation/flocculation, chemical precipitation, sedimentation, Reverse Osmosis (RO), ultrafiltration (UF), nanofiltration (NF), electrofiltration (Electrodialysis), ion-exchange, chelation, catalysis, and photocatalysis. Processing cellulose into commercial products enables the wide use of nanocellulose-based materials as adsorbents and catalysts.

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigation, and infrastructure construction. It is also essential for planners to make more informed decisions, optimize resource allocation, and support sustainable farming practices. This research paper investigates the accuracy of obtaining DEM data from four free global models (STRM30, ALOS30, COP30, and TanDEM-X90). The global DEM data has been compared to an actual GNSS-RTK DEM data surveyed onsite for two agricultural block areas in Aswan, the southern Government of Egypt. The two blocks are a part of a national project. For Block I and II, the RMSE of the Model STRM30 was 2.92 m and 3.59 m, respectively, indicating a poorer solution. Regarding accuracy, the ALOS30 model ranks third, reporting an RMSE of 2.58 m for block II and 3.30 m for block I. COP30 has an RMSE value of 1.06 m for blocks I and II and.91 m overall. TanDEM-X90 is the most accurate model in this investigation; block I provided an RMSE of 0.90 m with an SD of 0.58 m (SD95% = 0.38 m). After removing the anomalies, the model's stated RMSE for block II was 0.34 m, with an SD value of 0.62 m and 1.03 m. According to the classification using machine learning algorithms, with an accuracy of 84.7% for block I and 85% for block II, TanDEM-X90 is the best solution.

Objectives This study aimed to evaluate the eicosanoid and pro-resolutive parameters in Post Covid Syndrome (PCS) patients during 12 weeks of a supplementation with a marine oil enriched in SPMs. Patient and methods The study was conducted in 53 adult patients with a PCS. The subjects included must have had a positive COVID-19 test (PCR, fast antigen test, or serologic test) and persistent symptoms related to COVID-19 at least 12 weeks before their enrolment in the study. The following parameters were evaluated: Polyunsaturated fatty acids: EPA, DHA, ARA, DPA, Specialized Pro-resolving mediators (SPMs) 17-HDHA, 18-HEPE, 14-HDHA, resolvins, maresins, protectins, and lipoxins. The eicosanoids group included prostaglandins, thromboxanes, and leukotrienes. The development of the clinical symptoms of fatigue and dyspnea were evaluated using the Fatigue Severity Scale (FSS) and the Modified Medical Research Council (mMRC) Dyspnea Scale. Three groups with different amounts of intake were evaluated: daily use of 500mg, 1500mg, and 3000mg were compared to a control group without use of the product. Results In the serum from PCS patients, an increase of 17-HDHA, 18-HEPE, 14-HDHA could be observed. Also, a decrease in the ratio between the pro-inflammatory and pro-resolutive lipid mediators was detected. Both differences were significant (p < 0.05). There were no differences between the three treatment groups. Fatigue and dyspnoea showed a trend to improve after supplementation in all groups. Conclusions A clear enrichment in serum of the three monohydroxylated SPMs could be observed also at a dosage of 500 mg per day. In the same way, a clear improvement in fatigue and dyspnoea was observed with this dosage. Clinical Trial Registry: ISRCTN13270662.

Recommender Systems (RecSys) are crucial in managing information overload and enhancing user satisfaction across various digital platforms, including e-commerce and entertainment. Evolving from traditional models to Deep Neural Networks (DNNs) and, more recently, Large Language Models (LLMs), these systems leverage sophisticated algorithms to analyze user behaviors and preferences. LLMs, such as GPT-4, are trained on extensive datasets to comprehend and generate natural language, significantly advancing their ability to deliver personalized recommendations. This tutorial explores the transformative impact of LLMs on RecSys, discussing their development, application in handling complex datasets, and the integration of contextual insights. Real-world examples illustrate how LLMs enhance recommendation accuracy and user experience, highlighting challenges and future directions in the field.

This paper presents design and optimization of a small-size electromagnetic induction heating control system powered by a 3.7V-900mAh lithium battery and featuring an LC series resonant full bridge inverter circuit, which can be used in small size materials heating applications, such as micro medical devices. The effects of resonant capacitance, inductor wire diameter, heating tube material and wall thickness are studied to maximize the heating rate of the workpiece and meantime reduce the temperature rise of the NMOS transistor. The optimal circuit configuration meeting the design requirements was finally identified via comparing the operational parameters and NMOS transistor loss under different circuit conditions. The validation experiments were conducted on a designed electromagnetic induction smoking devices. The results indicate that under an output current of 4.6A, the heating tube can reach up to the temperature target of 250℃ within 11 seconds, and all NMOS transistors stay below 50°C in a 5 minutes heating process.

The 4 headwaters of the Chari fishery basin in the Central African Republic (CAR), Bamingui, Bangoran, Koukourou and N’délé (BBKN), contain a significant ichtyological fauna, although it remains little studied. The species of freshwater fish of the national parks of Bamingui Bangoran and Manovo Gounda St Floris have not been identified in depth. Fish is rich in animal protein and is very popular in the local and national markets. Its exploitation creates jobs for the populations living around BBKN’s fishery basins. Artisanal freshwater fishing contributes to the reduction of poverty of the BBKN population through the revenue it generates. The analysis of biodiversity consisted of identifying the species of fish captured by fishermen and the functional analysis consisted of mapping the key players in the fish value chain, characterizing fishing techniques and doing a social, environmental and economic study of the fish value chain. 250 stakeholders were directly surveyed. The results reveal the advantages for the actors, with a net monthly income of 1334$ for retailers, 1112$ for wholesalers, 889$ for fishmongers, 667$ for restaurateurs, 445$ for carriers and 223$ for fishermen. 18 families of fish including 43 species have been identified. The fish are artisanally caught. Fishing is done in two seasons: the favorable season (February to May) and less favorable season (November to January). The catches by effort units (CPUE) are 17 kg/day, or 510 kg/month and 4 kg/day, or 120 kg/month in the less favorable period. As the value chain is not sustainable, it is important to examine its sustainability.

Glaucoma, a global leading cause of blindness, necessitates accurate segmentation of the optic disc (OD) and optic cup (OC) for effective screening. However, existing segmentation methods based on convolutional neural networks (CNNs) suffer from high computational complexity and long inference times. In this paper, we propose an end-to-end segmentation method for the OD and OC using a lightweight MobileNetv3 as the feature extraction network. Our approach incorporates boundary branches and an adversarial learning network to achieve multi-label segmentation of the OD and OC. We evaluate the proposed method on three publicly available datasets: Drishti-GS, RIM-ONE-r3, and REFUGE. The experimental results demonstrate segmentation accuracies of 0.974/0.900, 0.966/0.875, and 0.962/0.880 for the OD and OC on the respective datasets, while significantly reducing inference time.

Aim: Ovarian cancer is the leading cause of gynecological cancer deaths worldwide. Treatment methods are listed as surgery, chemotherapy and radiotherapy depending on the stage of the cancer, but developing resistance to chemotherapy increases the need for alternative agents that act on the same pathways. In this study, the effects of rosmarinic acid (RA) and doxorubicin (DX) on the activation of FOXP3, an important tumor suppressor gene, in OVCAR3 cells were examined. Material Method: In the study, human ovarian adenocarcinoma cell line was used. MTT test was applied to determine the effect of rosmarinic acid and doxorubicin on the proliferation of OVCAR3 cells. Expression levels of FOXP3 for cell proliferation and Capase-3 for Apoptosis were determined by qRT-PCR and Western blot analysis. Wound healing model was applied to determine metastasis. The results were evaluated with one-way ANOVA in SPSS 20.0 program as p≤0.05. Results: It was determined that rosmarinic acid alone and in combination with doxorubicin inhibited the proliferation of OVCAR3 cells in a time- and dose-dependent manner for 24, 48 and 72 hours, and caused the cells to die by causing them to undergo apoptosis. It was observed that Caspase-3 expression increased approximately tenfold in OVCAR3 cells, while FOXP3 expression increased only in RA treatment and was downregulated in DX and RA+DX treatments. Coclusion According to the results of our study, it was observed that many steps of the signaling pathways related to proliferation, migration and apoptosis were affected by the combination of RA and DX in OVCAR3 cells. This shows that RA will gain an important place in cancer treatment with more comprehensive studies.

The Chinese community is one of the main minorities in Colombia, and although China has made advances in public health, it faces a growing burden of cardiovascular diseases. This study focuses on evaluating cardiovascular risk factors in Chinese immigrants in Barranquilla, Colombia, due to the lack of specific data on this population. Methods: A cross-sectional study was conducted with 67 Chinese immigrants over 18 years of age residing in Barranquilla. Sociodemographic, anthropometric, clinical, and biochemical data were collected through structured interviews and medical record reviews. Cardiovascular risk was estimated using the 10-year ASCVD (Atherosclerotic Cardiovascular Disease) formula from the ACC/AHA. Statistical tests were employed to assess significant differences and relationships between variables. Results: The sample included 54% women with an average age of 53 years. 75% were over 45 years old, with the main occupations being trade (43%) and homemaking (40%). 54% had social security. Significant differences were observed in systolic blood pressure and the prevalence of smoking and alcoholism between men and women. Women had higher levels of HDL and lower creatinine, while men had higher levels of hemoglobin and creatinine. Cardiovascular risk was high in 9% of cases, moderate in 39%, and low in 52%. Conclusions: Chinese immigrants in Barranquilla present a significant prevalence of cardiovascular risk factors influenced by their socioeconomic situation and barriers to accessing healthcare. Interventions should focus on improving access to healthcare services and promoting healthy lifestyles for this vulnerable community.

This study examines the potential of implementing a systematic approach to piloting desalination plants, with the objective of evaluating energy improvements in water desalination processes. The global scarcity of freshwater resources has significantly influenced the development of desalination technologies, with reverse osmosis emerging as one of the most prevalent and highly regarded methods. Pilot tests with the latest generation of reverse osmosis membranes in large desalination plants are becoming increasingly common. This is due to the fact that small-scale experiments are being carried out on the operation of new generation membranes with better salt rejection and lower energy consumption. The objective of this approach is to achieve the optimal water quality standard at the lowest possible cost. In this manner, pilot tests are being conducted prior to the determination of whether to alter the reverse osmosis membranes, as this represents a substantial investment. The objective of these tests is to minimise the risk of making an erroneous decision and to ensure optimal results in terms of energy consumption, operating costs and reduction of environmental impact, while complying with the requisite water quality standards. In this case, the Pareto analysis is employed to identify the two or three most significant causes whose treatment affects more than 80% of the potential energy savings to be implemented. This article introduces a novel approach to studying a total of 180 desalination plants at the territorial level in the Canaries.

Gastric cancer (GC) is a major cause of cancer-related mortality worldwide, often associated with a bad prognosis because of its asymptomatic phenotype until advanced stages, highlighting the need for its prevention and early detection. GC development is preceded by gastric preneoplasia lesions (GPNL), namely atrophic gastritis (AG), intestinal metaplasia (IM), and dysplasia (DYS). GC is currently diagnosed by endoscopy, which is invasive and costly and has limited effectiveness for the detection of GPNL. Therefore, the discovery of non-invasive biomarkers in liquid biopsies, such as blood samples, to identify the presence of gastric preneoplasia and/or cancer lesions at an asymptomatic stage, is of paramount interest. This comprehensive review provides an overview of plasma/serum proteins recently identified and their diagnostic performance for the prediction of GPNL and early cancer lesions. Autoantibodies appear as promising biomarkers for AG, IM and early gastric cancer detection, along with inflammation and immunity-related proteins and antibodies against H. pylori virulence factors. There is a lack of specific protein biomarkers to detect DYS. Despite the need for further investigation and validation, some emerging candidates could pave the way to develop reliable, non-invasive diagnostic tests for the detection and prevention of GC.

.Background: Facial features are the first basic spring of medical knowledge in children and adults with congenital malformation. Children born with multiple contractures almost always receive the misdiagnosis of arthrogryposis multiplex. Larsen syndrome can easily be diagnosed at birth via the proper interpretations of its characteristic facial features and multiple dislocations. Instant diagnosis can facilitate the orthopaedic strategy for early treatment and follow-ups. Material and Methods: Six children (four boys and two girls, age range from a few months to 7 year-old) have been referred to our departments for diagnosis and treatment. All children received their first misdiagnosis by the paediatricians as having arthrogryposis multiplex congenita . The clinical phenotype was our first decisive tool for diagnosis. All children exhibited the classical phenotype of Larsen syndrome, dish-like facies associated with multiple joint dislocations. Radiological phenotypic characteristics confirmed our clinical diagnosis. three children out of six showed unpleasant cervical spine deformities. The first child of a-2- year old became tetraplegic after minor trauma. One child presented with rigid cervical kyphosis . The third child wasa product of first related marriage and was born congenital tetraplegia . genotype has been carried out for confirmation . Results: Three children underwent open reduction for congenital hip and knee dislocations. one child underwent spinal fusion CO-C7 because of tetraplegia. 3D reformatted and reconstruction CT scan of the craniocervical junction in two children showed unusual male segmentations along C2-3 causing effectively the development of rigid cervical kyphosis and one child with congenital tetraplegia showed serious malsegmentation of C1/C2 associated with hypoplasia of the anterior and the posterior rings of the atlas. These findings in the last two children made any surgical intervention quite sophisticated. Four of these children were compatible with the autosomal dominant type of Larsen syndrome and manifested heterozygous mutation in FLNB mapped 3p14.3, encoding and actin-binding protein, filamin B. One child showed no mutations in the FLNB, though his clinical and radiological phenotype and his family history of first related marriage were totally compatible within the diagnosis of autosomal recessive type of Larsen syndrome. Conclusion: The orthopaedic strategy in patients with Larsen syndrome can not be achieved unless a precise diagnosis is has to be established as early as possible. Arthrogryposis multiplex congenita has been the first false diagnosis which was the reason for improper management.The most diagnostic confusion /error occurs to the paediatricians is the multiple contractures which are akin to arthrogryposis multiplex congenita. In practice, arthrogryposis multiplex congenita is a symptom complex rather than a precise diagnostic entity. The second diagnostic misconception is the generalized ligamentous hyperlaxity which can mimic hypotonia. Hypotonia in a newborn can be falsely categorized within the floppy infant syndrome. We used 3D reformatted CT scan to further understand the craniocervical junction pathology in three children with cervical spine kyphosis. Strikingly, mal segmentation and defective ossifications of the atlanto-axial spine segments in a child with Larsen syndrome and congenital tetraplegia

Cardiac arrest may cause significant hypoxic-ischemic injury leading to coma, seizures, myoclonic jerks, or status epilepticus. Mortality is high but accurate prognostication is challenging. A multimodal approach is employed, in which electroencephalograph (EEG) forms a key part with several recognised patterns of prognostic significance. In this retrospective study, clinical and qualitative features of the EEG of patients admitted to the Intensive Care Unit (ICU) at Kingston General Hospital following cardiac arrest from 2017-2020 were reviewed. The study included 81 adult patients (>18 years). Outcome was assessed using the Cerebral Performance Category as 1-2 (favourable) or 3-5 (unfavourable). EEG patterns were divided into groups within the highly malignant, malignant, and benign patterns described in the literature. There were a wide range of causes and 22% had a favourable outcome. Highly malignant, malignant, and benign patterns were associated with survival in 0%, 78% and 100% respectively and favourable outcomes in 0%, 44% and 100%. All patients with seizures died and 94% with myoclonus had unfavourable outcomes. In contrast, EEG reactivity and improvement on follow-up EEG was associated with a favourable outcome. In conclusion, highly malignant EEG, seizures and myoclonus were associated with unfavourable outcome, while patient with malignant EEG had better outcome.

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

Electricity price signal is a direct reflection of the attributes of electric power commodities, but due to the influence of market supply and demand, power producers' offer, line capacity and other factors, electricity price signals often show a variety of abnormal forms. The identification and traceability of abnormal tariff signals is an important daily work of power trading centers at all levels. However, at present, it is common to rely on manual experience to analyze the causes of abnormal tariffs, which is inefficient and difficult to ensure the objective and scientific traceability of abnormal tariff causes. Since different types of abnormal tariff signals are caused by different dominant factors, if the key features of abnormal tariffs can be classified and matched, the identification efficiency can be effectively improved. For this reason, this paper proposes a traceability method of abnormal tariffs based on the comparison analysis of key features. First of all, based on the characteristics of historical tariff data, this paper completes the classification of tariff spike magnitude anomaly and tariff mean value anomaly, further establishes the key features of each type of abnormal tariff signal based on principal component analysis, and finally calculates the influence degree of each element within the key features one by one based on alternative algorithms, and then realizes the screening and traceability of the causes of abnormal tariffs based on the importance of the degree of influence ordering. The effectiveness of the proposed method has been verified in a large number of examples constructed based on the actual data of the electricity market, and the average correctness rate of the proposed method for the traceability of the causes of the average value and spike anomalies of the electricity price reaches more than 85%, which can reduce the labor cost in the process of the traceability of the causes of the anomalous electricity price.

Vascular impairment, muscle atrophy, and cognitive decline are important age-related conditions that have a significant impact on health. Vascular impairment directly disrupts the flow of blood, leading to the decline of muscle mass associated with aging (sarcopenia) and the decline of neuronal functions (neurodegeneration). Our inadequate understanding of the complex relationships between these conditions impedes precise diagnosis and effective treatment. This review analyzes the interrelated mechanisms that contribute to these conditions, with a specific focus on oxidative stress, chronic inflammation, and impaired nutrient delivery. The aim is to understand the common pathways involved and to suggest comprehensive therapeutic approaches. Vascular dysfunctions hinder the circulation of blood and the transportation of nutrients, resulting in sarcopenia characterized by muscle atrophy and weakness. Vascular dysfunction and sarcopenia have a negative impact on physical function and quality of life. Neurodegenerative diseases exhibit comparable pathophysiological mechanisms that affect cognitive and motor functions. Preventive and therapeutic approaches encompass lifestyle adjustments, addressing oxidative stress, inflammation, and integrated therapies that focus on improving vascular and muscular well-being. Better understanding of these links can enhance therapeutic strategies and lead to better outcomes for patients. Here, we highlight the intricate relationship among vascular dysfunction, degenerative muscle, and cognitive decline, underscoring the need for multidisciplinary approaches to treatment. Progress in this field can result in improved diagnosis, more potent therapeutic options, and enhanced preventative measures, all of which can contribute to an improved quality of life for the aging population.

This review paper focuses on the joint toxicity and interaction of carbon-based nanomaterials (CNMs) with co-existing pollutants in aquatic environments. It explores the potential harmful effects of chemical mixtures on living organisms, emphasizing the importance of scientific mod-eling to predict mixed toxic effects. The study involved a systematic literature review to gather information on the joint toxicity and interaction between CNMs and various co-contaminants in aquatic settings. A total of 53 publications were chosen and analyzed, categorizing the studies based on the tested CNMs, types of co-contaminants, and the used species. Common test models included fish and microalgae, with zebrafish being the most studied species. The review under-scores the necessity of conducting mixture toxicity testing to assess whether the combined effects of CNMs and co-existing pollutants are additive, synergistic, or antagonistic. The development of in silico models based on the solid foundation of research data represents the best opportunity for joint toxicity prediction, eliminating the need in a great quantity of experimental studies.

It is often said in human society that it all starts from the mind, and this is true. The answer to the question “Why is it that pets require much fewer years to fully develop than humans?” could be headed to the Theory of Relativity and the perceived time according to the levels of instinct and rationality. It is perhaps no wonder that the French language translates the word “mind” as “l’esprit”, which also means “spirit” in the English language. Given that the Theory of Relativity applies to all physical matter, the theory applies to chemistry, biology and psychology as well. The level of instinct is proportional with the perceived speed of time and implicitly, to the speed of time itself for the whole organism, given that the nervous system coordinates all bodily functions. A pet may experience a few years as humans experience over a decade, making their perceived lifetime to be approximately equal to the human’s. The same applies to the perception of space and its components. This aspect would emphasise upon the fact that all life on Earth shows the same degree of value with regards to uniqueness. Nevertheless, the values represented by the hierarchy of competences among living organisms at the same time differs based on species. Honour of uniqueness and hierarchy of competences represent two scientific concepts that never overcross. As a result, there is no evidence to suggest that scientific facts as such constitute a form of contradiction to philosophical and religious ideas, given that religion refers to animals as companions of humans. With regards to the clock of the living organism; there are three kinds of clocks in a living organism: the emotional clock, the cognitive clock and the molecular clock. These three categories actually constitute the temporal layers of our dimension, so they are in a relationship of interdependence. When one has a feeling that time is slower or quicker, they are not fully experiencing that change in the time speed, but only partially. And one can profoundly experience the change of perceived time speed when they experience profound feelings, which sweep them away from reality. Complete, deep mental focus can bring about this profound change in perception, which will make the individual feel as if they are in a different form of reality. When one is more instinctive, the person in cause perceives time as slower and sees more opportunities within the same frame of time and space. When one experiences the “Fight or flight” mode, the person in the cause finds themselves to be in danger and has two options; to try to prevail over the danger or to flee it. Whilst experiencing such a mode, people are much more alert and therefore, time passes more slowly and the physical space dilates. When people are relaxed, however, time and space become smaller, and when they are in a deep state of resting, they become very small. And where there is a smaller dimension, there is a greater speed, just as the circulating air gains speed when it crosses narrow passages.

Background Lower respiratory tract infections (LRTIs), particularly pneumonia, are a leading cause of morbidity and mortality among children worldwide, especially in low-resource settings. The World Health Organization (WHO) Integrated Management of Childhood Illness (IMCI) guidelines currently recommend antibiotic treatment for all case of with pneumonia based on clinical signs along, which can lead to over-prescription of antibiotics and contribute to antimicrobial resistance (AMR). Point of care Lung Ultrasound (LUS) has emerged as a promising diagnostic tool in this context and has demonstrated potential in distinguishing between bacterial and viral pneumonia, thus enabling more targeted antibiotic use. This study aims to explore whether integrating LUS into the IMCI-based management of clinical pneumonia will better identify those who would benefit from antibiotic treatment, reducing antibiotic overuse without compromising health outcomes. Methods An open label randomized controlled trial will enrol 3500 children aged 60 days to 12 years presenting with IMCI-defined pneumonia. Participants will be enrolled in Senegal, Tanzania, and South Africa. Participants will be randomly assigned in a ratio of 1:1, stratified by site and age group (<5years, 5-12years) to either an intervention group, where LUS will guide antibiotic prescriptions utilising a predefined interpretation framework, or a control group receiving routine IMCI-based care. The co-primary outcomes of this study are the reduction in antibiotic use on the day of enrolment (Day 1) and rate of clinical failure by Day 8, using an acceptable clinical difference of 1.5x as a non-inferiority margin (delta of 2.5%). Secondary outcomes will include adverse drug reactions, cure rates, hospital admissions including in-patient duration, and cost-effectiveness. Data will be collected at baseline (Day 1), Day 8, and Day 29 post-enrolment. Discussion This study seeks to provide evidence on the clinical and public health benefits of using LUS to improve the diagnosis and management of paediatric pneumonia in low-resource settings. If this intervention proves effective it could contribute significantly toward reducing unnecessary antibiotic prescriptions, thereby addressing AMR. The potential for LUS to be integrated into routine clinical practice could revolutionize pneumonia management, especially in areas with limited access to advanced diagnostic tools. Trial Registration This trial will be registered on ClinicalTrials.gov and The South African National Clinical Trials Register (SANCTR) prior to participant enrolment.

The integration of additive manufacturing (AM), commonly known as 3D printing, has revolutionized aerospace engineering by enabling the creation of complex, lightweight, and high-performance components. This paper explores the transformative impact of AM technologies on the design, production, and maintenance of aerospace systems. The aerospace industry demands high precision, reduced weight, and enhanced performance, all of which are facilitated by AM's ability to produce intricate geometries and optimize material usage. Key applications of AM in aerospace include the fabrication of engine components, structural parts, and customized tooling. The technology's capability to produce parts with complex internal structures, such as lattice designs, leads to significant weight reductions without compromising strength and durability. Furthermore, AM allows for rapid prototyping, enabling faster iteration and development cycles, which is crucial in the highly competitive aerospace sector.

Single nucleotide polymorphisms in the mitochondrial genome have been investigated in relation to breast cancer. Certain variants could be associated with an increased risk of this malignant disease. These associations underline the importance of mitochondrial function in cancer biology and highlight the potential for mtDNA-based biomarkers and future therapies. The general objective of this research was to develop a model which is capable of identifying nonlinear patterns in breast cancer mitochondrial sequences. Association rules were used to explore mtDNA variant positions. The analysis included 41 breast cancer patients and 28 control samples. An a priori algorithm identified significant association rules with lift > 1 and confidence > 0.5. A total of 5562 rules for cancer and 157,140 for control sequences were refined after redundancy removal. A total of 150 associations were identified, of which only 78 showed significant support and confidence, while 315 and 1438 positions showed strong associations with breast cancer. Association rules analysis revealed significant patterns, especially in sequences associated with the control region and a specific locus around genes coding for tRNAs and NADH dehydrogenase subunits. However, further research is necessary to establish causality, clinical relevance, and to confirm these findings.

Pancreatic cancer is a serious and aggressive type of cancer that affects the digestive system and has a low chance of survival. Although traditional treatment methods have achieved some efficacy, the survival rate of patients remains low. Therefore, exploring novel treatment strategies is important. This article looks at the research done on bioactive compounds and plant extracts for treating pancreatic cancer. Bioactive compounds, such as naringenin and ziyuglycoside II, have significant anticancer activity and exert anti-pancreatic-cancer effects by inducing cell apoptosis, inhibiting the cell cycle, and blocking signaling pathways. Plant extracts, such as epigallocatechin-3-gallate and resveratrol, also demonstrate good anti-pancreatic cancer activity and inhibit tumor growth and metastasis. Additionally, the combined application of bioactive compounds and plant extracts may result in improved therapeutic effects. This article aims to provide a theoretical basis for the application of bioactive compounds and plant extracts in the treatment of pancreatic cancer and to help guide future medical research and practice.

Indonesia possesses significant biomass potential, including palm oil plantations. The palm oil industry has experienced rapid expansion, with a 7.67% growth rate over the past decade and an 11.09% annual increase in palm oil production. Co-firing (HT-FRD) is a beneficial technology for reducing exhaust gas emissions generated by coal-burning power stations. By utilizing Computational Fluid Dynamics (CFD), the study has modeled and evaluated co-firing palm frond residue (HT-FRD) with hydrothermal treatment into a 315 MWe boiler. In the simulation, six different HT-FRD co-firing ratios: 0%, 5%, 15%, 25%, 35%, and 50% were used to demonstrate the differences in combustion characteristics and emissions in the combustion chamber. The data indicates that HT-FRD co-firing can enhance temperature distribution, velocity, and unburned particles. All in all, co-firing conditions with 5% - 15% HT-FRD ratios appear to have the most favorable combustion temperature, velocity, and exhaust gas characteristics.

The dynamic landscape of 3D printing has experienced a notable surge in the development of diverse filaments tailored for a wide range of applications in medicine. This experimental study thoroughly examines the mechanical properties of nine popular 3D printer filaments, namely PLA, ABS, HIPS, PETG, PA, Carbon Fiber, Ceramic, PMMA, and Metal composite. Focusing on key aspects such as tensile strength and compressive tests, the study delves into the intricate mechanical characteristics of these 3D printer filaments. In addition to the mechanical properties, the study provides a comprehensive exploration of essential filament attributes, including melting point, bed temperature requirements, and density of nine different filament properties. Furthermore, the study addresses crucial considerations in material selection for different applications. Through insightful comparisons, the article illuminates the advantages and limitations of various available filaments within the realm of applications. This study serves as a valuable resource, offering nuanced insights for researchers, engineers, and medical professionals seeking a deeper understanding of the mechanical characteristics of 3D printer filaments and their potential applications.

This paper addresses the challenges of improving the accuracy of low-cost particulate matter sensors (LCPMS) under high humidity conditions. Such weather conditions often lead to the overestimation of particle counts due to hygroscopic particle growth, resulting in a potential public concern, although most of the detected particles consist of just water. The paper presents an innovative design for an indicative air-quality measuring station that integrates the particulate matter sensor with a preconditioning subsystem designed to mitigate the impact of humidity. The preconditioning subsystem works by heating the incoming air, effectively reducing the relative humidity and preventing the hygroscopic growth of particles before they reach the sensor. To validate the effectiveness of this approach, parallel measurements were conducted using both preconditioned and non-preconditioned sensors over a period of 19 weeks. The data was analyzed to compare the performance of the sensors in terms of accuracy for PM1, PM2.5, and PM10 particles. The results demonstrated a significant improvement in measurement accuracy for the preconditioned sensor, especially in environments with high relative humidity. When the conditions were too severe and both sensors started measuring incorrect values, the preconditioned sensor measured values were closer to the actual values. Also, the period of measuring incorrect values was shorter with the preconditioned sensor. The results suggest that the implementation of air preconditioning subsystems in LCPMS can provide a cost-effective solution to overcome humidity-related inaccuracies, thereby improving the overall quality of measured air pollution data.

This study explores the potential spillback of dengue virus (DENV) from urban to wild environments through the detection of neutralizing antibodies against DENV in sylvatic populations of bats from the Argentinean Yungas. Sampling campaigns were conducted in the Yungas biogeographical region of northwest Argentina during April 2021 and 2022. Bat blood samples were collected and tested for neutralizing antibodies against DENV-1 using the Plaque-Reduction Neutralization Test (PRNT). DENV-1 antibodies were detected in 2.8% (4/143) of the bat samples, with positive samples found in four species: Sturnira lilium, S. erythromos, Artibeus planirostris, and Tadarida brasiliensis. All from sylvatic habitats. The presence of DENV-1 antibodies in sylvatic bats suggests potential exposure to the virus in wild areas, indicating a possible spillback of DENV in subtropical areas of Argentina. Further research is needed to understand the role of bats as reservoirs for DENV and their impact on the virus endemicity.

This study utilizes a regional numerical weather model incorporating multilayer urban canopy parameterization alongside a building energy model (BEP + BEM) to examine the sensitivity of various urban parameters, including those defining urban materials and building environments, during a real-case heatwave event in the Chicago Metropolitan Area (CMA) in August 2023. The application of local climate zones further refines this analysis. Findings indicate that wall conductivity and ground albedo play significant roles in affecting urban near-surface temperatures. Conversely, alterations in other urban parameters are found to exert minimal influence on near-surface temperatures throughout the heatwave. In terms of building energy consumption, the selection of the target indoor temperature emerges as a pivotal factor. While adjustments in ventilation rates also bear considerable effects, other variables appear to have a subdued impact on energy usage. Additionally, the marginal effect of wall emissivity on energy consumption highlights the intricate balance between different heat transfer mechanisms and the adaptive capacity of building heating and cooling systems.

The usage of classic segmentation methods has drastically decreased recently. Implementation of convolutional neural networks and their modifications leads to significantly improved results. With the help of U-net, you can perform automatic segmentation. However, this requires significantly more hardware and software resources. The use of cloud computing now provides a wide range of possibilities, which allows processing and sharing the obtained experience and results to improve the quality of diagnosis. This article presents an approach to implementing MLOPS for automatic image segmentation using U-net technology. The approach's key feature is the developed software block that allows the creation of a dataset based on given rules. The infrastructure also supports automatically deploying the necessary environment on the cloud, particularly on DigitalOcean.

Solar radiation corresponds to fundamental parameters for solar photovoltaic (PV) technology. Reliable solar radiation prediction became valuable to design solar PV systems, performance, operatively efficient planning, safety operation, grid dispatch and financial characteristics. However, high quality ground-based solar radiation measurements are scarce, especially for very short-term time horizon. Most of the existent studies trained the machine learning (ML) model used dataset with time horizon of 1-hour or day, very fewer studies have been reported using a dataset with a 1-mitute time horizon. In this study, a comprehensive evaluation of nine ensemble learning algorithms (ELA) is performed to estimate the solar radiation in Santo Domingo with a 1-minute time horizon dataset collected from a local weather station. The ensemble learning evaluated included seven homogeneous ensembles; Random Forest (RF), Extra Tree (ET), Adaptive Gradient Boosting (AGB), Gradient Boosting (GB), Extreme Gradient Boosting (XGB), Light Gradient Boosting (LGBM), Histogram-based Gradient Boosting (HGB) and heterogeneous ensemble named as Voting and Stacking. RF, ET, GB, HGB were combined to develop Voting and Stacking and Linear Regression (LR) was adopted in the second layer of the Stacking. Five technical metrics, Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Coefficient of Determination (R2) were used as criteria to determine the prediction quality of the developed ensemble algorithms. Comparison of the results indicates that the HGB algorithm offers superior prediction performance among the homogeneous ensemble learning and overall, the Stacking provides the best accuracy with metric values of MSE=3218.27, RMSE= 56.73, MAE=29.87, MAPE=10.60, R2=0.964.

Refractory materials are used worldwide in process equipment. However, gaseous and liquid process products penetrate the surface layer, and deep into the volume of refractories destructing rather expensive constructions complicated to repair. To address this challenge, there is a need to develop protective coatings for refractory that can limit the penetration of working media and extend their operational lifespan. In this work, the application of gas-dynamic cold spraying (CGDS) to produce a coating on the refractory using fine titanium dioxide (TiO2) particles is explored. These particles are accelerated within a nitrogen flow, passing through a Laval nozzle, and then sprayed onto a fireclay surface. The mechanisms of particle deposition and layer formation on porous surfaces through experiments and numerical simulations were investigated. The geometry of a typical refractory pore was determined, which was then incorporated into Computational Fluid Dynamics (CFD) simulations to model the cold spraying process of porous substrates. As a result, the influence of the particle size on its velocity and angle of penetration into pores was established. Experimental findings demonstrate the effective closure of pores and the formation of a particle layer on the refractory surface. Furthermore, the nanoindentation tests for the refractory samples showcase capabilities for checking coating thickness for porous materials.

Anxiety in older individuals is understudied despite its prevalence. Investigating its occurrence can be challenging, yet understanding the factors influencing its recurrence is important for improved management. This study aimed to model the recurrence of anxiety symptomatology in an older population within a five-month timeframe. Data included baseline socio-demographic and general health information for older adults aged 60 years or older with at least mild depressive symptoms. A Bayesian network model explored the relationship between baseline data and recurrent anxiety symptomatology. Model evaluation employed the Area Under the Receiver Operating Characteristic Curve (AUC). The Bayesian model was also compared to three machine learning models. The model achieved an AUC of 0.821 on the test data, using a threshold of 0.367. This result surpassed both the Logistic Regression and XGBoost models, but slightly behind SGDClassifier. Key factors associated with recurrence of anxiety symptomatology were: “Not being able to stop or control worrying”; “Becoming easily annoyed or irritable”; “Trouble relaxing”; and “depressive symptomatology severity”. The model demonstrated generalisation abilities and outperformed some machine learning models while being less complex and more explainable. These findings indicate a prioritised sequence of predictors to identify individuals most likely to experience recurrent anxiety symptomatology.

Sarcoidosis is an inflammatory condition that can affect multiple organ systems and is characterized by the formation of non-caseating granulomas in various organs, including heart. Due to suboptimal diagnostic rates, the true prevalence and incidence of cardiac sarcoidosis (CS) remain to be determined. In patients with suspected CS, initial examination should include 12-lead ECG or ambulatory ECG monitoring, as well as echocardiography with the estimation of LV, RV function and strain rate. In patients with confirmed extracardiac sarcoidosis and with high clinical suspicion for CS, sophisticated imaging modalities, including cardiac MRI and PET are indicated. Typical patterns of inflammation and myocardial scarring should pose a high suspicion for CS. In patients without diagnosed extracardiac sarcoidosis and high clinical suspicion, although with low diagnostic porobability, endomyocardial biopsy should be considered to establish the diagnosis of definite isolated cardiac sarcoidosis. Timely diagnosis enables the initation of therapy and close monitoring of adverse cardiac events that can be life-threatening, including sudden cardiac death, ventricular tachycardia, high-degree AV block, and heart failure. Implementation of biomarkers in correlation to cardiac imaging can determine the disease severity and progression, but also be helpful in following the treatment response. The formation of larger global registries can be helpful in the identification of independent predictors of adverse clinical events and development of specific diagnostic algorithms to reduce the overal risk of this serious condition.

In the bar of our Milky Way, there should be another supermassive black hole B which is with the mass almost 10−2~10−5 the Sgr A* and with a distance almost 10,000 lightyears from the Sgr A*. The bar is formed by the stars that are orbiting around the two black holes Sgr A* and B. And, in the bar, a lots of stars orbit around B while another lots of stars around Sgr A*. The two orbits form the peanut shape with “x-shaped structure” in the bar, while the boxy core is formed with all of the three orbits. And, the orbits of the stars out of the bar could be repulsed to a distant place by the black hole B to form the galactic spiral arms.

The USH1G protein SANS is a small multifunctional scaffold protein. It is involved in several different cellular processes, such as intracellular transport, in the cytoplasm, or splicing of pre-mRNA, in the cell nucleus. Here, we aimed to gain insight into the regulation of the subcellular localization and the nuclear-cytoplasmic shuttling of SANS and its paralogue ANKS4B, not yet reported in the nucleus. We identified karyopherins mediating the nuclear import and export by screening the nuclear interactome of SANS. Sequence analyses predicted in silico evolutionarily conserved nuclear localization sequences (NLSs) and nuclear export sequences (NESs) in SANS, but only NESs in ANKS4B, which are suitable for karyopherin binding.Quantifying the nuclear-cytoplasmic localization of wild-type SANS and NLS/NES mutants, we experimentally confirmed in silico predicted NLS and NES functioning in the nuclear-cytoplasmic shuttling in situ in cells. The comparison of SANS and its paralogue ANKS4B revealed substantial differences in the interaction with the nuclear splicing protein PRPF31 and in their nuclear localization. Finally, our results on pathogenic USH1G/SANS mutants suggest that the loss of NLSs and NESs and thereby the ability to control nuclear-cytoplasmic shuttling is disease-relevant.

The One Health approach often reaches classrooms through Environmental Education (EE), which aims to guide society's response to halt the ongoing environmental, health, economic, and value crises. However, this goal has not been achieved. One reason is that EE teaching has traditionally focused on learning isolated ecological concepts and standardized solutions. Additionally, teacher training has tended to neglect didactic content knowledge, resulting in a reduced capacity to influence students' concerns and behaviours. Despite EE's multidimensional nature, ineffective didactic strategies have prevented students from acquiring the systemic vision needed to address eco-social problems and devise sustainable solutions in line with the Sustainable Development Goals (SDGs). In this context, this work proposes strategies to improve EE teaching through the One Health approach to achieve Transformative Environmental Education (TEE). The practical examples presented demonstrate successful EE initiatives that integrate One Health into classrooms using effective methods promoted by Science Education research. Effective EE should inspire critical thinking, empowerment, and student reflection, fostering a deep understanding of socio-environmental issues and innovative solutions from early education to create committed citizens. Therefore, achieving TEE requires reforming teacher training programs to strengthen didactic competencies and promote transformative educational practices, emphasising systems thinking, scientific and epistemic practices, and environmental justice awareness.

This study presents an advanced defect detection approach for solar cells using the YOLOv10 deep learning model. Leveraging a comprehensive dataset of 10,500 solar cell images, annotated with 12 distinct defect types, our model integrates Compact Inverted Blocks (CIB) and Partial Self-Attention (PSA) modules to enhance feature extraction and classification accuracy. Training on the Viking cluster with state-of-the-art GPUs, our model achieved remarkable results, including a mean Average Precision ([email protected]) of 98.5%. Detailed analysis of the model's performance revealed exceptional precision and recall rates for most defect classes, notably achieving 100% accuracy in detecting black core, corner, fragment, scratch, and short circuit defects. Even for challenging defect types such as thick line and star crack, the model maintained high performance with accuracies of 94% and 96%, respectively. The recall-confidence and precision-recall curves further demonstrate the model's robustness and reliability across varying confidence thresholds. This research not only advances the state of automated defect detection in photovoltaic manufacturing but also underscores the potential of YOLOv10 for real-time applications. Our findings suggest significant implications for improving the quality control process in solar cell production.

With the rapid development of Intelligent Transportation Systems (ITS), vehicle type classification, as a key link in Automatic Toll Collection systems (ATC), is of great significance in improving traffic efficiency and reducing economic losses. This study proposes an intelligent vehicle classification system based on deep learning and multi-sensor data fusion to address the accuracy issues existing in vehicle classification methods based on optical sensors (OS) and human observers. The system significantly improves the accuracy and robustness of vehicle classification by combining deep Convolutional Neural Networks (CNN), LiDAR sensors, and machine learning algorithms. We first constructed a large-scale annotated dataset containing multiple vehicle types and complex traffic scenes to improve our model's capability to identify different vehicle characteristics. Next, CNN models based on different architectures were designed to extract global and local features of the vehicle, respectively. In addition, the LiDAR sensor was used to achieve the spatial structure architectures of the vehicle and combined with the output of the CNN model to improve classification performance under occlusion and complex scenes.

Using a scaling symmetry, it is shown how to compute polynomial conservation laws, generalized symmetries, recursion operators, Lax pairs, and bilinear forms of polynomial nonlinear partial differential equations thereby establishing their complete integrability. The Gardner equation is chosen as the key example for it comprises both the Korteweg-de Vries and modified Korteweg de Vries (mKdV) equations. The Gardner and Miura transformations which connect these equations are also computed using the concept of scaling homogeneity. Exact solitary wave solutions and solitons of the Gardner equation are derived using Hirota’s method and other direct methods. The nature of these solutions depends on the sign of the cubic term in the Gardner equation and the underlying mKdV equation. It is shown that flat (table-top) waves of large amplitude only occur when the sign of the cubic nonlinearity is negative (defocusing case) whereas the focusing Gardner equation has the standard elastically colliding solitons. The paper’s aim is to provide a review of integrability properties and solutions of the Gardner equation and illustrate the applicability of the scaling symmetry approach. The methods and algorithms used in this paper have been implemented in Mathematica but can be adapted for major computer algebra systems.

Survivability is a critical concern in WSNs, heavily influenced by energy efficiency. Addressing severe energy constraints in WSNs requires solutions that meet application goals while prolonging network life. This paper presents an energy optimization approach (EOAMRCL) for WSNs, integrating the Grey Wolf Optimization (GWO) for enhanced performance. EOAMRCL aims to enhance energy efficiency by selecting the optimal duty-cycle schedule, transmission power, and routing paths. The proposed approach employs a centralized strategy using a hierarchical network architecture. During the cluster formation phase, an objective function, augmented with GWO, determines the ideal cluster heads (CHs). The routing protocol then selects routes with minimal energy consumption for data transmission to CHs, using transmission power as a metric. In the transmission phase, the MAC layer forms a duty-cycle schedule based on cross-layer routing information, enabling nodes to switch between active and sleep modes according to their network allocation vectors (NAV). This process is further optimized by an enhanced CSMA/CA mechanism, which incorporates sleep/activate modes and pairing nodes to alternate between active and sleep states. This integration reduces collisions, improves channel assessment accuracy, and lowers energy consumption, thereby enhancing overall network performance. EOAMRCL was evaluated in a MATLAB environment, demonstrating superior performance compared to EEUC, DWEHC, and CGA-GWO protocols, particularly in terms of network lifetime and energy consumption. This highlights the effectiveness of integrating GWO and the updated CSMA/CA mechanism in achieving optimal energy efficiency and network performance.

Drone technology has undoubtedly become an integral part of our everyday life these days. The business and industrial use of unmanned aerial vehicles (UAV) can provide advantageous solutions in many areas of life, and they are also optimal for emergency situations and for accessing hard-to-reach places. However, their application poses numerous technological and regulatory challenges to be overcome. One of the weak links in the operation of UAVs is the limited availability of energy. In order to address this issue authors developed a novel trajectory planning method for UAVs to optimize the energy necessity during flight. First, an “energy map” was created, which was the basis for trajectory planning, i.e., determining the energy consumption of the individual components. This was followed by configuring the 3D environment including partitioning of the work space (WS), in fact, defining the free spaces, occupied spaces (obstacles) and semi-occupied/free spaces. Then the corresponding graph-like path(s) were generated on the basis of the partitioned space, where a graph search-based heuristic trajectory planning was initiated, taking into account the most important wind conditions including velocity and direction. Finally, in order to test the theoretical results, some sample environments were created to test and analyse the proposed path generations. The method eventually proposed was able to determine the optimal path in terms of energy consumption.

Various studies on sustainability development as emerging competitive strategy present it as exogenous factor that businesses have to cope with for being successful. However, considering current changes in business processes in which customers are taking an important position, sustainability development tends to be endogenous factor. To study this change, this paper analyses how industrial benefits of bargaining power of buyers, one of five forces of M. Porter’ model fosters sustainability development. To achieve this objective, integrative literature review and statistical measure of the relation between price, quality of products, and sustainability achievement among countries are used. The findings are that, high quality products, one of the benefits of bargaining power is significant related to sustainability development, whereas low prices benefit is not. This is due to the fact that; low prices are not that main driver for current consumer generations which are more driven by social values than price competitiveness.

Graphene nanoplatelets (UGZ-1004) are advancing as a promising biomaterial for regenerative medicine. This study provides a detailed assessment of UGZ-1004, emphasizing its physical properties, cytotoxicity, intracellular interactions, and particularly its effects on mesenchymal stem cells (MSCs). UGZ-1004 was characterized to have lateral sizes and layer counts in line with ISO standards and exhibited high carbon purity (0.08%). Cytotoxicity evaluations demonstrated that UGZ-1004 is non-toxic to various cell lines, including fibroblast 3T3, epithelial kidney VERO, microglia BV-2, and MSCs, in accordance with ISO-10993-5/2020/2023 guidelines. The study focused on MSCs, revealing that UGZ-1004 supports their self-renewal and proliferation. MSCs exposed to UGZ-1004 maintained their characteristic surface markers and proliferation rates. Importantly, UGZ-1004 promoted significant upregulation of genes crucial for cell cycle regulation and DNA repair, such as CDK1, CDK2, and MDM2. This gene expression profile suggests that UGZ-1004 enhances MSC self-renewal capabilities, ensuring robust cellular function and longevity. Moreover, UGZ-1004 exposure led to the downregulation of genes associated with tumor development, including CCND1 and TFDP1, mitigating potential tumorigenic risks. These findings underscore the potential of UGZ-1004 to not only bolster MSC proliferation but also enhance their self-renewal processes, which are critical for effective regenerative therapies. The study highlights the need for continued research into the long-term impacts of graphene nanoplatelets and their application in MSC-based regenerative medicine.

Property Assessed Clean Energy (PACE) programs finance energy efficiency and renewable energy improvements in residential and commercial properties with a special tax assessment added to property taxes. The paper surveys the literature and documents the quantitative estimates of environmental and economic benefits. The paper extends to discuss the securitization of PACE loans. The issuance of PACE green bonds frees up capacity for more PACE improvements. In addition, we summarize the concerns raised after the programs have been implemented. Those concerns include consumer protection, audit after program implementation, and lien-related risks for lenders. We highlight the challenges and discuss measures to continue to grow PACE financing. The success of PACE programs will contribute to mitigating climate change and to achieving the United Nations Sustainable Development Goals (SDGs).

Let an odd integer be represented as $\sum \limits_{n > m} 2^n + 2^m - 1$ for $m \geq 1$. To transform $2^m - 1$ according to the Collatz rules, the $3x + 1$ step is applied, resulting in the even integer $2^{m + 1} + 2^m - 2$. This even integer, being exactly once divisible by 2, becomes the next odd integer $2^m + 2^{m - 1} - 1$. This represents the growth phase, as exactly one even step follows an odd step. However, while the overall value of the integer increases, terms with decreasing indices are generated after each odd-even cycle. After $m$ such cycles, a term $2^{m - m}$ (which equals 1) is generated, canceling the negative 1. Additional even steps are then performed until the integer becomes odd again, which occurs when the next smallest index becomes zero. The positive 1 thus obtained is written as $2^1 - 1$. If uninterrupted, the term $2^1 - 1$ has the trivial cycle $2^1 - 1 \rightarrow 2^2 \rightarrow 2^1 \rightarrow 2^1 - 1$. This represents the shrinkage phase, as two even steps follow an odd step. To interrupt the trivial cycle, a sequence such as $2^1 + 2^2 + \cdots$ must be available to combine with $2^1 - 1$ and produce $2^{\mathcal{M}} - 1$. This starts another growth phase that lasts for $\mathcal{M}$ odd-even cycles. Finally, there is an attempt to craft an integer that can escape the shrinkage phase in the Collatz dynamics.

Background: This study investigated the effect of indirect air-cooling on the variation in intrapulpal temperature (ΔT) during different light-curing protocols of bulk-fill resin composites in molars with class V cavities. Methods: A nonretentive class V cavity was prepared in an upper molar. The intrapulpal temperature changes with and without air-cooling were recorded with type K thermocouple. The cavity was restored with bulk-fill resin composites: Tetric PowerFlow and Filtek Bulk-Fill Flow. The tooth was exposed to different light-curing protocols (n=5) using the Valo Grand light-curing unit: (i) high-intensity light-curing of 3200 mW/cm² (3 and 6 s) and (ii) moderate-intensity light-curing of 1000 mW/cm² (10 and 20 s). The ΔT data were subjected to two-way ANOVA, followed by Bonferroni post hoc test. Results: A significant increase in temperature was observed with the use of the high-intensity light-curing resin composite without indirect air-cooling. In addition, the application of air-cooling significantly decreased the temperature in all the groups except for the Tetric PowerFlow bulk-fill resin composite at 3 s of light-curing. Conclusion: Indirect air-cooling resulted in a lower increase in intrapulpal temperature during the light-curing of bulk-fill resin composites, making it an effective alternative for controlling the temperature rise in class V restorations with 1 mm of remaining dentin.

Background and Objective: To examine the effect of ordered subset expectation maximization (OSEM) parameters on the quantitative image quality of cardiac SPECT images in two different frequently used SPECT cameras and determine the optimal settings for producing images of best diagnostic quality. Another objective was to assess if different cameras produced a significant change in optimal parameters and levels of detectability. Methods: The optimization of OSEM iterative reconstruction algorithm was carried out by comparing image quality metrics, namely, contrast-to-noise ratio (CNR) and defect contrast across 12 OSEM subset-iteration combinations to find the best choice for cardiac perfusion SPECT images. Eight frames were reconstructed using the SIMIND Monte Carlo Simulation package. An activity of 370 MBq (10mCi) and projection acquisition interval of 20 seconds per projection were used. Attenuation (AC) and scatter corrections (SC) were performed in this study for all images. Results: The 16-2 subset-iteration combination yielded the highest CNR and defect contrast values for both cameras. The difference between CNR values for two cameras was found to be around 5% only. Conclusions: Monte Carlo simulations can be useful to investigate how quantitative image quality behaves with respect to reconstruction parameters and correction algorithms in a controlled environment. The found optimum is similar to values reported in previous findings. In this study, the use of different camera brands did not affect the optimum. The quantitative detectability measures were also very similar.

Groundnut is an important cash crop and a diet component for rural households in sub-Saharan Africa. However, Aflatoxin contamination remains a barrier to promoting groundnut-based food products as food levels above maximum limit (ML) can adversely affect human health. Three objectives were set, namely, (i) to characterize the post-harvest operations and risk factors affecting aflatoxin contamination, (ii) to assess aflatoxin incidence in on-farm stores and, iii) to assess agronomic practices that can be integrated to improve yield and reduce aflatoxin contamination. The average aflatoxin levels in on-farm stores were 11.3-16.4μg/kg, in which the proportions of ML were 25.7% at 4μg/kg, 56.3% at 15μg/kg, and 80% at 20μg/kg (~5-7 months after harvest). The application of Aflasafe® resulted in safe or no aflatoxin contamination across the locations. Significant hazards identified during postharvest operations include intermittent rain at harvest and drying (6.5), insect pests attacks after harvest (6), prolonged harvest to stripping interval (6.6), drying on bare ground (6.2), storing on bare floor (6.9), use of poorly efficient shelling machines (6.5), and re-use of rejected nut (6.1). This study provides solutions to minimize aflatoxin risk if appropriate technologies (e.g. improved variety, fertilizer, rhizobia inoculant, and Aflasafe®) and policies are deployed.

Art therapy has a long history of applications in cognitive and motor rehabilitation. More recently, a growing body of scientific literature has highlighted the potential of virtual reality in neurorehabilitation, though it has focused more on the technology itself than on the principles adopted in digital scenarios. This study is a randomized controlled trial conducted on 40 patients with stroke, comparing a protocol of art therapy administered in virtual reality, which exploits the so-called Michelangelo effect, to conventional therapy. After 12 sessions, patients in the virtual art therapy group showed a significantly greater improvement in independence in activities of daily living, as assessed by the Barthel Index (interaction of time and group: p<0.01). Significant differences were also found in terms of upper limb muscle strength (Manual Muscle Test, p<0.01) and reduction in spasticity (Ashworth scale, p<0.01) in favor of the experimental group. In the virtual art therapy group, the effectiveness of the intervention was significantly correlated with patient participation (Pittsburgh Rehabilitation Participation Scale: R=0.45), patient satisfaction (R=0.50), and the perceived utility of the intervention by the therapist (R=0.47). These findings support the efficacy of virtual art therapy leveraging the Michelangelo effect. Further studies should also focus on cognitive domains that could benefit from this type of approach.

The advancement of high-temperature structural materials is crucial for the efficiency and performance of modern gas turbines, which are widely used in aviation and power generation. This paper explores the development and optimization of materials capable of withstanding extreme temperatures, mechanical stresses, and corrosive environments within turbine engines. The focus is on nickel-based superalloys, ceramic matrix composites (CMCs), and emerging materials such as high entropy alloys (HEAs) and refractory metals. Nickel-based superalloys are the current standard due to their excellent high-temperature strength and creep resistance, while CMCs offer potential for weight reduction and improved thermal efficiency. High entropy alloys, characterized by their unique multi-component systems, present promising properties including high strength and oxidation resistance at elevated temperatures. Additionally, advances in coating technologies and additive manufacturing are enhancing the durability and performance of these materials. The paper also discusses the challenges associated with material development, including the trade-off between strength and ductility, manufacturing complexities, and the need for long-term performance data. Future research directions are identified, focusing on the integration of computational materials science and advanced characterization techniques to accelerate the discovery and implementation of next-generation high-temperature materials. The successful development of these materials is essential for improving the efficiency and reducing the environmental impact of gas turbines.

Existing methods of hyperspectral anomaly detection still face several challenges: 1) Due to the limitations of self-supervision, avoiding the identity mapping of anomalies remains difficult; 2) The ineffective interaction between spatial and spectral features leads to the insufficient utilization of spatial information; 3) Current methods are not adaptable to the detection of multi-scale anomaly targets. To address the aforementioned challenges, we proposed a blind spot network based on multi-scale blind spot convolution for HAD. The multi-scale mask convolution module is employed to adapt to diverse scales of anomaly targets, while the dynamic fusion module is introduced to integrate the advantages of mask convolutions at different scales. The proposed approach includes a spatial-spectral joint module and a background feature attention mechanism to enhance the interaction between spatial-spectral features, with a specific emphasis on highlighting the significance of background features within the network. Furthermore, we propose a preprocessing technique that integrates pixel shuffle down-sampling (PD) operation with spatial spectral joint screening to address the issue of anomalous identity map-ping and facilitate finite-scale mask convolution to adapt to the detection of more scale targets. The proposed approach was assessed on four real hyperspectral datasets comprising anomaly targets of different scales. The experimental results demonstrate the effectiveness and superior performance of the proposed methodology compared with nine state-of-the art methods.

Background: Monogenic Alzheimer's disease (AD) has severe health and socioeconomic repercussions. Its rarest cause are presenilin 2 (PSEN2) gene mutations. We present two new cases with presumed PSEN2-AD, with unusual clinical and neuroimaging findings in order to provide more information on the pathophysiology and semiology of these patients. Methods: Women aged 69 and 62 years at clinical onset, marked by prominent behavioral and language dysfunction, progressing to severe dementia within three years. Neuroimaging, laboratory study, genetic testing. In addition, a systematic review of the PSEN2-AD were performed. Results: Neuroimaging revealed pronounced frontal white matter hyperintensities (WMH) and frontotemporal atrophy/hypometabolism. The genetic study unveiled PSEN2 variants: c.772G>A (p.Ala258Thr) and c.1073-2_1073-1del. Both cerebrospinal fluid (CSF) and experimental blood biomarkers shouldered AD etiology. Conclusions: Prominent behavioral and language dysfunction suggesting frontotemporal dementia (FTD) may be underestimated in the literature as a clinical picture in PSEN2 mutations. Thus, it may be reasonable to include PSEN2 in genetic panels when suspecting FTDL. PSEN2 mutations may cause striking WMH, arguably related with myelin disruption induced by amyloid accumulation.

The açaí (Euterpe oleracea Mart.) is a native fruit of the Amazon that is well-known due to its commercial value. Its production chain is centered in the state of Pará, largely supplied by extractivism. The processing of açaí fruits in nature generates huge amount of solid waste, which can pose serious risks to the environment if not used and managed properly. Due to a small number of systhematic studies on the effect of chemical activation by pyrolysis of açaí seeds and fibers, and with the aim of providing a basis for future applications of the waste generated by processing of açaí fruits, the present work proposes a study of the pyrolysis of açaí seeds and fibers and the physicochemical and compositional characterization of the aqueous phase products. In this way, açaí seeds were collected from a local artisan processing facility in the city of Belém, PA. The seeds were dried at 105°C until constant weight, and subsequently, the fibers were separated from the seeds in a rotating drum. The seeds and fibers were impregnated with NaOH solutions at 0.5M, 1.0M, and 2.0M, and then pyrolyzed at a laboratory scale at 450 °C and 1 atm. The liquid products from pyrolysis were characterized through acidity index analysis, Fourier-transform infrared spectroscopy, and gas chromatography. The increase in the concentration of the impregnating agent resulted in an increase in bio-oil yield from both the seeds and fibers, rising from 3.3% (raw seeds) to 6.6% (seeds impregnated with 2M NaOH) and from 1.2% (raw fibers) to 3.7% (fibers impregnated with 2M NaOH). The yield in the aqueous phase after biomass pyrolysis showed an inverse behavior to the bio-oil yield, decreasing from 33.7% (raw fibers) to 21.2% (fibers impregnated with 2M NaOH) and from 41% (raw seeds) to 37.5% (seeds impregnated with 2.0M NaOH). High acidity levels were found in the aqueous phase samples and bio-oils derived from the seeds and fibers, which decreased as the concentration of the impregnating agent increased. The increase in the concentration of the impregnating agent (NaOH) influenced the chemical composition of the obtained liquid products, leading to a decrease in oxygenated compounds and an increase in nitrogenous compounds in both experimental matrices, which was also evidenced by the reduction in acidity.

A cross-sectional study was organised to investigate the range, prevalence, and associated factors for occupational health problems related to dental practice among Cambodian dentists; Participants underwent a face-to-face interview to explore dentists work-related health problems; 106 Cambodian dentists participated in this study, 68.9% were male. Ages ranged from 29 to 71 years, averaging 36.1 years, with the majority (77.4%) in the 29-40 age group. They had 5 to 18 years of practice experience, and worked an average of 52.2 hours per week. Commonly reported health issues included back pain (88.7%), headaches (81.1%), shoulder pain (78.3%), arm/hand pain (57.5%), and eye problems (48.1%). 38.7% of participants felt stressed and 19.8% depressed. Some reported suicidal thoughts and taking medication for depression. Despite these challenges, 91.5% enjoyed practicing dentistry; Findings highlight the need for interventions and strategies to address the physical and mental well-being of Cambodian dentists. By addressing these issues, steps can be taken to enhance the working conditions and professional satisfaction of dental professionals, ultimately benefiting both the practitioners and their patients.

Electric tractors have many advantages, including high torque, excellent controllability, energy efficiency, simple structure, and electric interface for expansion. However, a significant limitation lies in their endurance. This study presents the design of an extended-range power supply system to ensure continuous endurance of electric tractor. The objective is to provide a continuous power source for our self-developed electric tractor while preserving the benefits of electric propulsion. Extended-range power systems utilize a primary mover, typically an oil-fueled internal combustion engine, to drive the generator for electricity generation, and the generated AC form electricity is subsequently converted into stable DC bus voltage by a power electronic converter. The hardware and control design of the extended-range power supply system have been finalized and validated through experimental trials. Results demonstrate the system’s capability to sustain a stable DC bus voltage amidst disruptions such as sudden load shifts and fluctuations in prime mover speed. Even with 50% sudden load change, the voltage drop is within 12% and could recover to ±3% within 4 seconds. The range extender can be used alone without battery to power the electric tractor, or it can used in parallel with other extended-range extenders or battery thanks with the droop control ability for power sharing.

Geopolymers, made from aluminosilicate raw materials, offer significant environmental advantages over conventional concrete (CC) mixes. This study explores the compressive strength, setting time, and durability of geopolymer concrete (GPC) cylinders, some of which include an additional ordinary portland cement (OPC) mix. Consistent material composition and testing methods are emphasized to achieve reliable results. MATLAB was utilized to develop and assess a neural network model predicting the compressive strength of GPC based on key variables. The model was validated using 16 experimental samples and 1047 samples from various studies. The performance plot displayed the Mean Squared Error (MSE) over iterations, identifying the best training performance at epoch 658 with an MSE of 5.3408. The Error Histogram highlighted distribution errors between predicted and actual compressive strength values, with the highest range from -1.015 to 0.3587, meaning that the predicted values were mostly within a small margin of error from the actual values. This narrow error range indicates that the ANN model has high accuracy in its predictions, as most errors are small and clustered around zero, demonstrating reliable performance in estimating compressive strength. Regression analysis showed varying correlation coefficients (training set R=0.98373, test set R=0.88164, and whole set R=0.96982), indicating adequate predictive accuracy. The results demonstrate that properly trained neural networks can effectively predict the compressive strength of GPC, highlighting its potential as a sustainable construction material.

Localized protein translation occurs through trafficking of mRNAs and protein translation machineries to different compartments of the cell, leading to rapid on-site synthesis of proteins in response to signaling cues. The spatiotemporally precise nature of the local translation process necessitates continual developments of technologies reviewed herein to visualize and map biomolecular components and the translation process with better spatial and temporal resolution, and with fewer artifacts. We also discuss approaches to control local translation, which can serve as a design paradigm for subcellular genetic devices for eukaryotic synthetic biology.

This study endeavors to elucidate the intricate interplay between gastronomic involvement, gastronomic knowledge, past gastronomic experiences, gastronomic attractiveness, destination attractiveness, tourist satisfaction, and the intention to revisit. In the context of this investigation, the research population comprises 300 international culinary tourists who have ventured to the Turkish Republic of Northern Cyprus (TRNC). Employing SPSS software, a confirmatory factor analysis (CFA) was conducted to rigorously assess construct validity, reliability, and the discriminant and convergent validity of the research model. The findings of this research study underscore the positive relationships that exist between various dimensions of gastronomy, namely involvement in gastronomy, knowledge of gastronomy, and previous gastronomic experiences, and the perceived attractiveness of gastronomy. These findings enhance our understanding of how culinary elements affect tourists' perceptions and experiences, highlighting the crucial role of gastronomy in destination appeal and visitor satisfaction. This research is a significant step towards enhancing our comprehension of the dynamic nexus between gastronomy and the tourism industry, ultimately benefiting destination management and strategy development.

The author introduces a novel theoretical framework that suggests matter and energy are both converted from curved space. In Space Theory, gravitation is generated by the flow of space, instead of being transmitted by the graviton as in String Theory. This theory also suggests that Newton's gravitational constant, denoted as G, may not be truly constant but could vary over time. The equivalent equation of space is S=Ec²=mc⁴, and the gravitation of hollow sphere space is S_μν=4πGm=(4/3)π((r+a)³-r³). The Space Theory also predicts that the surface gravitational acceleration of the neutron star Crab Pulsar (PSR B0531+21) is approximately 8.21924883×10⁶ m/s².

(1) Background: With the rising incidence of life expectancy, obesity, and tumours, understanding the incretory influence of adipose tissue in tumorigenesis becomes increasingly important. As the adipokines leptin and adiponectin are released by fat tissue, we aimed to analyse the expression of their respective receptors in tumours for which an association with obesity is epidemiologically hypothesized; (2) Methods: The expression of leptinR and adipoR1 were analysed in cohorts of renal cell cancer (n = 391), cervical cancer (n = 155), vulvar cancer (n = 107), and endometrial cancer (n = 90) by immunohistochemistry and correlated with clinicopathological parameters including survival times; (3) Results: Expression of leptinR was high in renal cell cancer (62.2% of cases), vulvar carcinoma (50%) and endometrial cancer (80.5% of tissue-samples). High expression was associated with favourable clinicopathological markers and longer overall survival times in renal cell cancer and vulvar cancer. AdipoR1 was only weakly expressed in all four tumor entities and did not show significant associations with clinicopathological parameters or prognosis; (4) Conclusion: High leptinR is a promising biomarker for favourable tumour outcome in renal cell carcinoma and vulvar carcinoma.

This article is some review of results that were obtained at 2007-2021 years development of “The Information as Absolute” concept and the informational physical model, which is based on the concept; including a number of fundamental physical problems are briefly considered in framework of the conception and the model. Recently in physics there are several publications, that present lists of the problems. However, those lists are essentially incomplete, for at least two reasons. Firsts of all, a number of phenomena are studied traditionally by philosophy, and so corresponding problems are usually considered to be “metaphysical”. However, they relate also to some concrete physical phenomena. For example, physics evidently studies Matter, and so the metaphysical problems “what is ontology of Matter”, “what is “Space”, “Time” and a few other physical phenomena and notions as well, are really a Meta-physical problems “what does physics study?” There are other fundamental physical problems, which are not considered as such in physics, and are absent in the “fundamental problems lists”. Those include the problems, which really exist, yet are incorporated into standard physical theories, and so are fundamental “implicitly”, which in physics are “solved by default” ‒ and mostly erroneously. Note, though, that a number of “Meta-physical”, and concrete fundamental, problems more in detail are considered in the paper “The Informational Conception and Basic Physics”, https://arxiv.org/abs/0707.4657, v5 (2021), so this paper is, in certain sense, an expanded conclusion of this paper, which includes, correspondingly, more in detail consideration of some more general physical problems; and, besides, in this article, the problem “what are Gravity and Electric Forces” is essentially clarified comparing with the arXiv 2021 paper version above, and additionally initial model of Nuclear Force is presented. Besides, the concrete problem “What is Life”, and the rational cosmological model, where a few vague points in standard cosmology rather probably are rationally clarified, while the fundamental problem “matter – antimatter asymmetry” in Matter is solved with rather large probability, are considered, and one of recently published rather complete “lists of fundamental problems” is commented in Appendix.

This article deals with an analytical approach to determining the stress state in trochoidal profiles under shear bending. The transverse shear stresses cannot be neglected, especially in the case of (space-saving) shafts with a low aspect ratio (l/d). In addition to bending stresses, the transverse shear stresses are a significant component of the principal stresses. The approach is based on a formulation of the elastic behavior of a non-circular-profiled shaft using complex stress functions, according to Muskhelishvili. In order to determine the shear stresses, similar to the torsion load case, a conformal mapping must be found that can completely transform the unit circle in the model plane to the profile area in the real plane. For simple and higher epiotrochoidal profiles, an exact and complete mapping was determined from the contour equation. The method was applied to such profiles as an example. Equations were derived to determine the maximum shear and bending stresses and the bending deformations. For practical applications, additional equations for the main stresses that are decisive in dimensioning were determined. Accompanying numerical investigations were carried out and compared with the analytical results, where a very good agreement was observed.

This narrative review explores the utilization of psychedelic states in therapeutic contexts, deliberately shifting the focus from psychedelic substances back to the experiential phenomena they induce, in alignment with the original meaning of the term "mind-manifesting." The review provides an overview of various psychedelic substances used in modern therapeutic settings and ritualistic indigenous contexts, as well as non-pharmacological methods that can arguably induce psychedelic states, including breathwork, meditation, and sensory deprivation. While the occurrence of mystical experiences in psychedelic states seems to be the strongest predictor of positive outcomes, the literature of the field yields several other psychological processes, such as awe, perspective shifts, insight, emotional breakthrough, acceptance, re-experiencing of memories, and certain aspects of challenging experiences, that are significantly associated with positive change. We additionally discuss in detail mystical experience related changes in metaphysical as well as self-related beliefs and their respective contributions to observed outcomes. We conclude that a purely medical and neurobiological perspective on psychological health is reductive and should not overshadow the significance of phenomenological experiences in understanding and treating psychological issues that manifest in subjective realities of human individuals.

The Kampar Peninsula, a significant peatland region in Riau, Indonesia, is vital for its carbon re-serves and biodiversity, including the Sumatran tiger. Covering approximately 735,091 hectares, it comprises critical peat domes essential for hydrological balance. This research investigates land use changes from 1990-2020 using the Normalized Difference Fraction Index (NDFI) to map disturb-ances and land cover changes. Additionally, interviews and regulatory analysis were conducted to examine the historical drivers of land use change in the Kampar Peninsula. In 2020, natural forests covered 433,395.20 hectares (59.9% of the total area), industrial pulpwood plantations (primarily acacia) covered 27.3%, oil palm plantations accounted for 10.4%, infrastructure occupied 2.4%, and water bodies made up 0.9%. Key drivers of land use change include the construction of access roads by oil companies since 1975 and government policies during the New Order period (1980s-1998) promoting forest exploitation and transmigration programs. These activities have significantly transformed the Kampar Peninsula's land cover, highlighting the need for sustainable management and conservation efforts.