This study aims to propose a method for constructing basic digital twin data in South Korea by adhering to international standards and utilizing publicly available data. Specifically, the study focuses on designing and proposing a digital twin data model for buildings, which are the most applicable among the basic digital twin data. To achieve this, the first section provides essential background information, introduces concepts and requirements related to digital twin basic data, and offers a brief overview of CityGML. The second section explains the methodology and data used in this study. The third section presents the main findings: the selection of public data (buildings) for constructing digital twin basic data, the mapping process using CityGML, and the creation of UML diagrams. The fourth section discusses these findings. Finally, the conclusion and suggestions for future research are provided. This approach enhances the accuracy of building-related digital twin data and supports the use of digital twin services in both public and private sectors by enabling various spatial analyses.

The COVID-19 pandemic has underscored the intricate interplay between viral infections and opportunistic bacterial pathogens such as Klebsiella pneumoniae. K. pneumoniae harbors various antibiotic resistance determinants like extended-spectrum and plasmid-mediated AmpC β-lactamases and carbapenemases. In the two years following the pandemic, carbapenemase producing K. pneumoniae isolates obtained routinely in outpatient and inpatient setting demonstrated similar resistance patterns which prompted research. The aim was to compare and subsequently analyze carbapenem-resistant hospital and outpatient’s K. pneumoniae isolates’ resistance mechanisms, traits and molecular epidemiology, following the COVID-19 pandemic. Disk diffusion and broth dilution method were the methods of choice to determine antibiotic susceptibility. β-lactamases were screened by phenotypic methods and confirmed with PCR. In total 113 isolates were analysed. Resistance to amoxicillin-clavulanate and ertapenem was confirmed in all strains. High resistance rates (over 90%) were observed for extended-spectrum cephalosporins, and ciprofloxacin. OKNV testing and PCR detected OXA-48 in 106, NDM in 7 and KPC in only one isolate. ESBLs accompanied carbapenemases in 103 isolates. Carbapenem resistance in K. pneumoniae is becoming a global problem, hence careful monitoring of its resistance traits is of utmost importance in order to combat the arising threat. OXA-48 seems to continue predominating in the turbulent period after pandemic.

Abstract: This in vitro study aimed to analyze the surface roughness (Ra) and color stability (ΔEab, ΔE00) following simulated mechanical brushing, and to evaluate the microtensile (μTBS) to dentin of Self Adhering Resin Flowable (SARF). The selected materials were Constic, Yflow AS, and Tetric N flow (TNF/control). Thirty composite resin cylinders were fabricated for surface property evaluation. Ra and color were assessed both before and after simulated brushing. The thresholds of 50:50% perceptibility and acceptability of color difference of the evaluated resins were assessed. For μTBS analysis, fifteen molars were selected, sectioned to expose flat dentin surfaces, and restored according to manufacturers' instructions. Subsequently, they were sectioned into sticks for microtensile testing. Statistically significant differences in Ra among the groups, with Constic exhibiting the highest Ra value (p < 0.05), while Yflow AS showed the lowest Ra value. No statistically significant difference in color was observed among the groups (p > 0.05). The 50:50% perceptibility and acceptability thresholds set at 1.2 and 2.7 for ΔEab and 0.8 and 1.8 for ΔE 00. All the results fell within the acceptable limits. The mean μTBS values of Constic, Yflow AS, and TNF were 10.649 MPa, 8.170 MPa, and 33.669 MPa, respectively. The study revealed increased Ra and comparable color stability among all tested composite resins after abrasion. However, SARF exhibited lower μTBS compared to conventional using an adhesive system.

Glioblastoma (GBL) is one of the more malignant primary brain tumors, currently treated by a multimodality strategy including surgery, radio- and chemotherapy, mainly consisting of Temozolomide(TMZ)-based chemotherapy. Tumor relapse often occurs due to the establishment of TMZ resistance, with a patient median survival

Understanding creation as divine kenosis, which has become rather widespread since the last century, may emphasize the strong connection between the creation theology and the key Christian doctrine of the Incarnation while contributing to the dialogue between theology and science. At the same time, this theological project requires a thorough rethinking of divine action to avoid representing divine agency and natural causality as the competitive factors and to affirm divine kenosis as the definitive trait of God without compromising divine simplicity and freedom. To this end, the concept of “divine kenotic creativity” is suggested and discussed in this paper.

This paper detects bidding behaviors in the auction with the random cutoff, where a winning bid needs to be above and the closest to the random cutoff. In this auction, each bidder is eager to predict the random cutoff in order to use the predicted random cutoff as bid. Furthermore, one of deep learning models, the transformer model is employed as one empirical method to anticipate the random cutoff. The result shows that the predicted random cutoff turns out to be a winner with probability of about 20 percent. This paper contributes to economic literature in terms of investigating the connection between a deep learning model and an auction based on the economic theory.

This study investigates the fabrication and characterization of large-sized ceramic-reinforced TWIP (Twinning-Induced Plasticity) steel matrix composites using the lost foam casting technique. Various ceramic shapes and sizes, including blocky, flaky, rod-like, and granular forms, were evaluated for their suitability as reinforcement materials. The study found that rod-like and granular ceramics exhibited superior structural integrity and formed strong interfacial bonds with the TWIP steel matrix, compared to blocky and flaky ceramics, which suffered from cracking and fragmentation. Detailed microstructural analysis using scanning electron microscopy (SEM) and industrial computerized tomography (CT) revealed the mechanisms influencing the composite formation. The results demonstrated that rod-like and granular ceramics are optimal for reinforcing TWIP steel composites, providing excellent mechanical stability and enhanced performance. This work contributes to the development of advanced composite materials with potential applications in industries requiring high-strength and durable materials.

Following the detection of highly pathogenic avian influenza (HPAI) virus in countries bordering Kenya to the west, we conducted surveillance among domestic and wild birds along the shores of Lake Victoria. In addition, between 2018 and 2020, we conducted surveillance among poultry and poultry workers in live bird markets and among wild migratory birds in various lakes that are resting sites during migration to assess introduction and circulation of avian influenza viruses in these populations. We tested 7,464 specimens (oropharyngeal and cloacal swabs) from poultry and 6,531 fresh fecal specimens from wild birds for influenza A viruses by real-time RT-PCR. Influenza was detected in 3.9% (n=292) of specimens collected from poultry and 0.2% (n=10) of fecal specimens from wild birds. On hemagglutinin subtyping, most of the influenza A positives from poultry (274/292, 93.8%) were H9. Of 34 H9 specimens randomly selected for further subtyping, all were H9N2. On phylogenetic analysis, these viruses were genetically similar to other H9 viruses detected in East Africa. Only two of the ten influenza A positive specimens from the wild bird fecal specimens were successfully subtyped; sequencing analysis of one specimen collected in 2018 was identified as low pathogenicity avian influenza H5N2 virus of the Eurasian lineage and the second specimen, collected in 2020, was subtyped as H11. A total of 18 OP/NS swabs from poultry workers with ARI (12%) were collected; none were positive for influenza A virus. We observed significant circulation of H9N2 influenza viruses in poultry in live bird markets in Kenya. During the same period, low pathogenic H5N2 virus was detected in a fecal specimen collected in a site hosting a variety of migratory and resident birds. Although HPAI H5N8 was not detected in this survey, these results highlight the potential for introduction and establishment of highly pathogenic avian influenza viruses in poultry populations and the associated risk of spillover to human populations.

The human eye is a vital source of collecting information worldwide via daily observation. The computer science area recognizes it in research as a human-computer interaction. Human blink is an integral part of this observation as a research topic. Several studies have been conducted on eye blinking and left-right eye movements. Previous studies conducted on the eye blink consider the availability of hardware devices high in the budget, high Precision, and low light expo-sure, unlike our study, which uses low-budget devices as simple as a webcam and more versatile usable techniques, incredibly both dim and high light to name a few. This study offers the observational approach via ResNet101v2, VGG-19, and Convolution Neural Network (CNN) architectures. Outperforming both VGG-19 and CNN in this study, ResNet101v2 achieves an impressive accuracy of 98.2%. In contemporary times, deep learning in AI is taking an advanced form. This study attempts to provide a new insight into the real-world implementation of the eye blink.

In order to explore the effect of Wickerhamomyces on the production of flavor compounds in Xiaoqu Baijiu, this study examined the correlation between the fungal communities in Xiaoqu and ester compounds. It was hypothesized that Wickerhamomyces contributes to the aroma of Xiaoqu. Enhanced fermentation methods were used to validate the role of Wickerhamomyces in Xiaoqu Baijiu brewing. Compared to traditional Xiaoqu, enhanced fermentation significantly increased the acidity of fermented grains and starch utilization rate (P<0.05). The fungal communities in fermented grains were analyzed by high-throughput sequencing technology. The dominant fungi in both control and test groups were Saccharomyces, Cyberlindnera, Rhizopus, and Meyerozyma, with Wickerhamomyces replacing Saccharomymycopsis in the enhanced group. Flavor compounds in the fermentation experiments were analyzed, revealing that ethyl acetate content in Xiaoqu Baijiu increased by 949.94 mg/L in the test group, while isoamyl alcohol decreased by 23.62 mg/L and isobutanol decreased by 34.81 mg/L. Functional prediction analysis using PICRUSt2 confirmed a higher relative abundance of enzymes involved in ethyl acetate metabolism and a lower relative abundance of enzymes involved in higher alcohol metabolism in the test group. These findings demonstrate that Wickerhamomyces enhances ethyl acetate production and reduces higher alcohols during Xiaoqu Baijiu brewing, offering a theoretical foundation for enhancing the quality of Xiaoqu Baijiu.

We assessed the impact of social determinants of health (SDOH) and psychosocial factors on screening behavior in a nationally representative sample of women in the US. A retrospective population-level cross-sectional sample was extracted from the 2022 Health Information National Trends Survey. Descriptive statistics were conducted for demographic characteristics and covariates. Population-based estimates with 95% confidence intervals (95% CI) were produced for Pap testing behaviors across study years. We used logistic regression models to assess Pap testing differences based on SDOH and psychosocial factors, adjusting for covariates, with a significance level of 0.05 for hypothesis testing. Women (n=2,224) with a mean age of 46.96 participated in the study. Our study found that 90% of women were interested in cervical cancer screening, with an 80% actual screening rate. Screening rates differed by age group and rurality. SDOH and psychosocial factors were associated with participants’ interest in screening and in actual screening behavior. The impacts of SDOH and psychosocial factors on screening behavior were 3% and 1%, respectively. The SDOH and psychosocial factors are associated with the uptake of cervical cancer screening among women in the United States. Policies must be directed at bridging the gap created by these SDOHs.

Stormwater runoff from large roads is a major source of pollutants to receiving waters. Porous pavements have been shown to substantially reduce many of these pollutants, but studies are lacking on arterial roads. We sampled typical stormwater pollutants in runoff from sections of an arterial road 9-16 years after installation of three pavement types: control with conventional asphalt, porous asphalt overly, and full-depth porous asphalt. Both types of porous pavements substantially reduced most of the stormwater pollutants measured. Total suspended solids, turbidity, total lead, total copper, and 6PPD-quinone were all reduced by &gt;75%. Total nitrogen, ammonia, total phosphorus, biochemical oxygen demand, total and dissolved copper, total mercury, total zinc, total polycyclic aromatic hydrocarbons, and di-2-ethylhexyl phthalate were all reduced by &gt;50%. Reductions were lower or absent for nitrate, orthophosphate, E. coli, dissolved lead, and dissolved zinc. Most reductions were statistically significant. Many pollutants exceeded applicable water quality standards in the control samples but met them with both types of porous pavement. This study demonstrates that porous overlays and full-depth porous asphalt can provide substantial reductions of several priority stormwater pollutants on arterial roads for many years after installation.

Texas cotton production is facing challenges arising from increased temperatures and extended droughts. One potential solution to mitigate these environmental stresses lies in enhancing soil health through measures aimed at increasing soil organic matter and microbial biomass. Our field study investigated the effectiveness of adding residue on soil surface to increase soil organic matter content, microbial biomass, and cotton production under experimental warming with open-top chambers (OTCs). The OTCs raised the air temperature by 2 °C but did not affect soil temperature. OTCs also increased microbial biomass and soil respiration rate. Residue addition increased moisture content in non-irrigated (i.e., dryland) soils under experimental warming and concurrently reduced the daily temperature range in warmed plots. Furthermore, residue addition increased microbial biomass and soil respiration, particularly under OTC treatments in dryland soils. We also observed increased soil organic matter, microbial biomass, cotton biomass, and yield in irrigated fields compared to dryland. Our findings suggest that residue retention can mitigate the adverse effects of warming by stabilizing soil microclimate and enhancing soil organic matter and microbial biomass levels, especially in drylands. This, in turn, can help attenuate the potential impacts of future climate change on soil health and crop production in semiarid environments.

Although metastasis-associated protein 1 (MTA1) is known to play a role in cancer invasion and metastasis of various cancers, the clinical significance of its expression in canine urothelial carcinoma (UC) has not been explored. We sought to evaluate the expression of MTA1, cyclooxygenase 2 (COX2) and E-cadherin (E-cad) in association with clinicopathological parameters in clinical samples of canine UC. Here, we show that MTA1 and COX2 are overexpressed in canine UC samples compared to normal canine bladder samples, whereas E-cad levels are higher in normal bladder. The results demonstrated that MTA1 expression correlated with aggressive clinicopathological features such as high tumor-grade, muscular/vascular invasion, and metastasis. The expression of MTA1 differed in tumors depending on their localization, with the highest being in the urethra adjoining the prostate. Unexpectedly, higher E-cad levels were detected in metastatic tumor cells compared to primary tumor cells. Overall, these findings suggest that MTA1 may represent a key upstream effector tightly associated with COX2 and E-cad-mediated events in canine UC. Accordingly, MTA1 may be considered a feasible interceptive and therapeutic target for canine UC treatment.

INTRODUCTION: While postmenopausal osteoporosis management evolved in recent years, it nonetheless remains underdiagnosed and undertreated. Given that general practitioners are the keystone of patient screening and referral in France, the present study was conducted to assess their professional positioning in the management of postmenopausal osteoporosis. METHODS: The present is a qualitative study based on semi-directed interviews, carried out between July 2020 and February 2021, with randomly chosen Alsatian general practitioners. Interviews were conducted until data saturation. Consolidated criteria for qualitative research reporting grid was used as well as Nvivo software to categorize the datas. RESULTS: Twenty-three general practitioners (GPs) were interviewed. Study participants recognized that the investigation and treatment of osteoporosis begins at a primary care level, typically with the GP. While some initiated screening by prescribing bone mineral density (BMD) assessments, only few prescribed the associated laboratory assessment and spinal X-rays in search of curable osteopathy or vertebral fracture. For those GPs who do take the opportunity to initiate treatments for patients, there is an understanding that first line options often include calcium and vitamin D, at a “preventive” level. The interviewed physicians interacted mainly with gynecologists and rheumatologists. Fracture liaison services were widely acclaimed. Several barriers were identified in their care management. The absence of a defined role between specialists and the lack of communication between the latter were an additional highlighted barrier. CONCLUSION: This study sheds further light on the discrepancy between the means available to treat osteoporosis, and the modest impact of the care observed.

Cellular senescence is the irreversible growth arrest subsequent to oncogenic mutations, DNA damage or metabolic insult. Senescence is associated with aging and chronic age associated diseases such as cardiovascular disease and diabetes. The involvement of cellular senescence in Acute Kidney Injury (AKI) and Chronic Kidney Disease (CKD) is not fully understood however, recent studies suggest that such patients have a higher-than-normal level of cellular senescence and accelerated aging. This study aimed to discover key biomarkers of senescence in AKI and CKD patients compared to other chronic ageing diseases as controls. We show that senescence proteins CKAP4 and PTX3 are upregulated in AKI and CKD patients compared with controls with chronic diseases suggesting they may play in a role in overall kidney disease development. Additionally, CKAP4 was found to be differentially expressed in both AKI and CKD when compared to unhealthy controls hence this biomarker could be prognostic senescence biomarker of both AKI and CKD.

In this paper, we report a comprehensive and consistent annotation of the locus encoding the horse T cell receptor b-chain (TRB), as inferred from the most recent genome assembly. The horse TRB locus spans approximately 1 Mb, making it the largest locus among the mammalian species stud-ied to date, with a significantly higher number of genes related to extensive duplicative events. In the region, 136 TRBV, belonging to 29 subgroups, 2 TRBD, 13 TRBJ and 2 TRBC genes, were iden-tified. The general genomic organization resembles that of other mammals, with a V-cluster of 135 TRBV genes, located upstream of two in-tandem aligned TRBD-J-C clusters, and an inverted TRBV gene at the 3’ end of the last TRBC gene. However, the horse b-chain repertoire would be affected by a high number of non-functional TRBV genes. Thus, we queried a transcriptomic da-taset derived from splenic tissue of a healthy adult horse, using each TRBJ gene as a probe to ana-lyse clonotypes encompassing the V(D)J junction. This analysis provided insights into the usage of the TRBV, TRBD and TRBJ genes and the variability of the juxtaposition region. Our results clearly demonstrated that the horse β-chain constitutes a complex level of variability broadly like that described in other mammalian species.

Biochar has a carbon-based porous structure that is advantageous for adsorbing air pollutants. The pore structure of biochar ranges from several tens to hundreds of m²/g depending on the production temperature. We compared the pore characteristics of biochar with its NOx and SOx adsorption performances to evaluate its adsorbing potential. Biochar was produced from cypress biomass via slow pyrolysis in a fixed-bed reactor and CO2 partial gasification. Slow pyrolysis experiments at 500–700°C were conducted to produce biochar, followed by yield, proximate, elemental, and surface area analyses. CO2 partial gasification activated the biochar produced by slow pyrolysis at the same temperature, and similar analyses were performed. NO and SO2 adsorption experiments were conducted separately and together for biochar produced under each condition. Biochar produced at 600°C showed the highest specific surface area. CO2 partial gasification increased the surface area at each temperature, reaching 680.3 m²/g at 700°C. In single adsorption experiments, N2 carbonized biochar showed NO and SO2 adsorption efficiencies of 84–90% and 88.2–91.4%, respectively, with similar trends in simultaneous adsorption experiments. CO2 activated biochar exhibited higher adsorption efficiencies due to its increased surface area, with NO and SO2 adsorption at 89.8–93.9% and 92–98.9%, respectively. Biochar activated at 700°C simultaneously adsorbed approximately 99% NO and SO2. The NO adsorption efficiency increased with increasing surface area of the small pores, whereas the SO2 adsorption efficiency improved with the development of both small and large pores.

Underreporting is the main limitation of the spontaneous reporting systems. This study aims to reduce underreporting enhancing public participation in vaccinovigilance through an SMS-based reporting system integrated with electronic immunization registries (IRs). Using the VigiVax software, parents of vaccinated children aged 2 years or younger received a single SMS inquiry about adverse events following immunization (AEFI). Responses were collected, validated by health operators and integrated with the information on IRs. AEFI reports were automatically submitted to the Italian Pharmacovigilance system. Among 254,160 SMS messages sent, corre-sponding to 451,656 administered doses (AD), 71,643 responses were collected (28.2% response rate), 21,231of them (8.3%) reporting an AEFI. After seriousness assessment based on clinical criteria, 50 reports (0,24%) were classified as serious. Among these, causality assessment identi-fied 31 reports at least potentially related to the vaccination (RR: 6.86/100,000 AD). Febrile seizures following MMRV vaccination accounted for 11 of these 31 cases, with an incidence of 32 per 100,000 AD. No fatal outcomes were reported. Our findings support the highly favorable risk profile of pediatric vaccinations and the possibility to improve spontaneous reporting through the integration of digital technologies

Extended Reality (XR) technologies—encompassing Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR)—merge elements of the physical world with virtual environments, revolutionizing various sectors, including healthcare. This paper explores the transformative potential of XR when combined with advanced digital tools to enhance therapeutic practices for individuals with disabilities or social isolation. Emphasizing the pivotal role of healthcare professionals, particularly nurses, the study investigates how these experts can effectively integrate XR technologies to maximize therapeutic benefits. The research includes a pre-implementation phase that assesses the knowledge and acceptance levels of both healthcare professionals and the general population. This foundational study highlights the potential of XR in expanding access to artistic and recreational activities, drawing insights from efforts by the Opera di Santa Maria del Fiore (Florence) to democratize timeless artistic experiences. The findings underscore the im-portance of defining key terms and understanding stakeholder readiness before full-scale implementation.

A superparamagnetic graphene oxide based drug carrier Fe3O4@SiO2/N–rGO was prepared through surface modification, material doping, and composite methods. This carrier has a large number of active sites, suitable for loading anticancer drugs, It can increase the drug load. Currently, the widely used drug in clinical use is epirubicin hydrochloride (EPI). The graphene based complex has a pH sensitive property and exhibits a pH sensitive property at pH=4.3. The release efficiency (RE) is 77.4%, making it suitable for drug release in cancerous acidic liquids. The physicochemical properties of drug carriers were studied using X–ray diffraction, Raman spectroscopy, and Fourier transform infrared spectroscopy. Electrochemical signals confirm that the anticancer drug EPI acts on the graphene plane through hydrogen bond interactions and π – π stacking.

unnel fires are generally detected using various sensors, including measuring temperature, CO concentration, and smoke concentration. To address the ambiguity and inconsistency in multi-sensor data, this paper proposes a tunnel fire detection method based on an improved Dempster-Shafer (DS) evidence theory for multi-sensor data fusion. To solve the problem of evidence conflict in DS theory, a two-level multi-sensor data fusion framework is adopted. The first level of fusion involves feature fusion of the same type of sensor data, removing ambiguous data to obtain characteristic data, and calculating the basic probability assignment (BPA) function through the feature interval. The second level fusion derives basic probability numbers from the BPA, calculates the degree of evidence conflict, normalizes to obtain the relative conflict degree, and optimizes the BPA using the trust coefficient. The classical DS evidence theory is then used to integrate and obtain the probability of tunnel fire occurrence. Different heat release rates, tunnel wind speeds, and fire locations are set, forming four fire scenarios. Sensor monitoring data under each simulation condition are extracted and fused using the improved DS evidence theory. The results show that the proposed improved DS evidence theory method detects the probability of fire occurrence in the four scenarios as 67.5%, 71.0%, 82.8%, and 83.5%, respectively, and identifies fire occurrence in approximately 2.4 seconds, an improvement of 64.7% to 70% over traditional methods. This demonstrates the feasibility and superiority of the proposed method, highlighting its significant importance in ensuring personnel safety.

Detecting IgE sensitizations in the serum of allergic dogs is commonly done using allergen extracts, but these are difficult to standardize. This article details the development and validation of the Pet Allergy Xplorer (PAX; Nextmune, Stockholm, Sweden), the first multiplex macroarray for the detection of IgE sensitization in dogs using allergen extracts and molecular components; the PAX is derived from the Allergy Xplorer (ALEX2; MacroArray Diagnostics, Vienna, Austria). The selection of allergens, cartridge processing, strategy for identifying and blocking IgE directed against cross-reactive carbohydrate determinants (CCD), and the method used for determining the positivity threshold are described. The validation of the PAX included evaluations of the specificity of its anti-IgE monoclonal antibody, specificity of IgE binding to target allergens, assay precision, and internal consistency. Additionally, the influence of possible confounding factors, such as sample type, the influence of hemolysis, lipemia, bilirubinemia, and elevated CCD-IgE, was tested. Finally, the sensitization rates of 23,858 European dogs to 145 environmental and Hymenoptera venom allergens were summarized. The PAX is accurate and reproducible and has a unique CCD-detection and blocking strategy; its molecular allergens offer a unique window on allergen cross-reactivity.

This research aimed at examining how social enterprises mitigate climate change in Ghana, examining their strategies, impacts on the environment that affect climate change, and barriers. The research adopted a cross-sectional survey design, descriptive and involved 185 social enterprises. Questionnaires were administered online and data was analyzed using descriptive statistics and regression analysis. The findings revealed that the most used strategies include the development of new funding structures and advocacy for sustainable farming. It also highlights numerous environmental concerns such as the judicious use of hazardous materials and pollution. Nevertheless, results from regression analysis showed that the relationship between the number of social entrepreneurship activities and the impact on the environment is relatively low and the role of other factors may be more significant. Some of the main barriers that were found include competition from large organizations, cultural perspectives towards climate change, policy instability and lack of adequate technical education. Accordingly, the recommendations proposed are developing specialized funding programs for climate-focused social enterprises; climate change education and awareness campaigns; and capacity building to upgrade technical competencies in clean technologies and climate resilience design.

The Mixture of Experts (MoE) architecture has evolved as a powerful and versatile approach for improving the performance and efficiency of deep learning models. This survey aims to provide the fundamental principles of MoE in details, a paradigm that harnesses the collective power of multiple specialized "expert" models working in concert to tackle complex tasks.Our exploration is a thorough analysis of the core components that constitute the MoE framework. We begin by dissecting the routing mechanism, a crucial element responsible for dynamically assigning input data to the most appropriate expert models. This routing process is pivotal in ensuring that each expert's specialized knowledge is optimally utilized. The survey places significant emphasis on expert specialization, a key feature that sets MoE apart from traditional architectures. We examine various strategies for developing and training specialized experts, exploring how this specialization enables MoE models to effectively handle diverse and multifaceted problems.Load balancing, another critical aspect of MoE systems, receives thorough attention. We discuss techniques for efficiently distributing computational resources among experts, ensuring optimal model performance while managing hardware constraints. This section provides insights into the delicate balance between model capacity and computational efficiency. Furthermore, we provide an in-depth discussion of the expert models themselves, examining their architectural designs, training methodologies, and how they interact within the larger MoE framework. This includes an analysis of different types of experts, from simple neural networks to more complex, task-specific architectures. The survey also navigates through diverse research avenues within the MoE landscape, highlighting recent advancements and innovative applications across various domains of machine learning. We pay particular attention to the burgeoning use of MoE in two rapidly evolving fields: computer vision and large language model (LLM) scaling. By providing this comprehensive overview, our survey aims to offer researchers and practitioners a deep understanding of MoE's capabilities, current applications, and potential future directions in the ever-evolving landscape of deep learning.The Mixture of Experts (MoE) architecture has evolved as a powerful and versatile approach for improving the performance and efficiency of deep learning models. This survey aims to provide the fundamental principles of MoE in details, a paradigm that harnesses the collective power of multiple specialized "expert" models working in concert to tackle complex tasks.Our exploration is a thorough analysis of the core components that constitute the MoE framework. We begin by dissecting the routing mechanism, a crucial element responsible for dynamically assigning input data to the most appropriate expert models. This routing process is pivotal in ensuring that each expert's specialized knowledge is optimally utilized. The survey places significant emphasis on expert specialization, a key feature that sets MoE apart from traditional architectures. We examine various strategies for developing and training specialized experts, exploring how this specialization enables MoE models to effectively handle diverse and multifaceted problems.Load balancing, another critical aspect of MoE systems, receives thorough attention. We discuss techniques for efficiently distributing computational resources among experts, ensuring optimal model performance while managing hardware constraints. This section provides insights into the delicate balance between model capacity and computational efficiency. Furthermore, we provide an in-depth discussion of the expert models themselves, examining their architectural designs, training methodologies, and how they interact within the larger MoE framework. This includes an analysis of different types of experts, from simple neural networks to more complex, task-specific architectures. The survey also navigates through diverse research avenues within the MoE landscape, highlighting recent advancements and innovative applications across various domains of machine learning. We pay particular attention to the burgeoning use of MoE in two rapidly evolving fields: computer vision and large language model (LLM) scaling. By providing this comprehensive overview, our survey aims to offer researchers and practitioners a deep understanding of MoE's capabilities, current applications, and potential future directions in the ever-evolving landscape of deep learning.

Senolytic and senomorphic therapies gain more and more attention in the last decade. This kind of therapy is based on the killing of cellular senescent cells without harming the “normal” cells. Ageing is not a disease. Clinical studies on healthy people will be difficult to conduct. Therefore, one possibility is to draw on the large repertoire of medicinal plants and use their sneolytic properties to provide mild, anti-ageing therapies. Chamomile, goldenrod, reishi and green tea were tested for their ability to trigger senolysis quercetin was used as control substance. Cellular senescence was induced with 25µM etoposide in human dermal fibroblasts and established for at least 14 days. The plant extracts were tested for their antioxidant potential (DPPH assay) and their polyphenol content. Senolysis was determined by presto blue assay of young and etoposide-induced senescent cells, and ß-Gal assays were also performed. The senomporphic properties of the plants were investigated using IL-6 ELISA and qPCR. It turned out that chamomile triggers a kind of cytokine storm and causes the cytokine values in the Elisa and in the qPCR to rise extremely, and other senescence-associated phenotype (SASP) markers were also elevated. Goldenrod and quercetin tend to have a senolytic and senomorphic effect respectively. Regarding the senolytic and senomorphic properties of herbs, we have found that all tested herbs can have a senolytic effect, and a senomorphic effect of quercetin has also been uncovered. With regard to the effect of chamomile, however, we can say that seemingly harmless tea products may have harmful effects, especially in combination with chemotherapy, at least in cell culture experiments.

This paper presents and demonstrates the development of a new lightweight coating for aluminium alloy using a novel multicomponent alloy based on the AlSiMgCu system. This coating was applied using a newly designed approach that combined High-Velocity Oxy-Fuel (HVOF) and Plasma Spraying processes. This hybrid technique enables the deposition of coatings with enhanced performance characteristics. The microstructure was studied using optical microscopy (OM) and scanning electron with energy dispersive X-ray spectroscopy (SEM+EDS) microscopy, revealing good adhesion and compaction between the multicomponent coating and the A6061 substrate with 50 to 150 µm thickness. Vickers indentations were performed on the substrate and the new coating material, revealing a 50% improvement in the material's hardness compared to the casted alloy. Additionally, electrical conductivity measurements showed approximative x3.3 times values compared to the alloy in as-cast condition due to high solidification rates altering the morphology of the phases. Corrosion tests demonstrated a lower corrosion rate compared to other multicomponent aluminium alloys and similar to thermal treated A6061 alloy. Finally, tribological results obtained using ball on disc (BOD) test and laser scanning confocal microscopy, confirmed that the new multicomponent coating exhibited reductions in both friction coefficient and wear rate by more than 20% and 50%, respectively. This study demonstrates that using multi-component aluminium coatings could lead to developing of new automotive parts with enhanced properties for corrosion resistance, electrical conductivity, and wear conditions. Optimizing the thermal spraying parameters could further enhance the coating, achieving greater and more homogeneous thicknesses and yielding even higher performance properties.

Big data is considered to be the solution to many complex problems, but its application appears to be relegated to the problems that are factorable (e.g., the tensor-like operations which reflect separable elements), not the non-factorable data from teamwork, team intelligence, and possibly not individual consciousness. In contrast, the quantum likeness of interdependence is set apart from the standard science of teams by recognizing a measurement problem between a team and its individual teammates, and between individual beliefs and actions. Teams that concern us are based on artificial intelligence (AI) and machine learning (ML) systems, which we find lacking for two reasons. First, neither AI nor ML models the human's timeless need for debate to solve a problem at the social level when facing uncertainty or complexity, where the debate of proposed actions serves to establish the boundaries of a problem in reality, no matter how complex nor uncertain. Second, at the individual level exists the illusion of a unified reality propagated by a bifurcated brain that we assume is split to determine a context with narrative and bounded spaces. We hypothesize that the quantum-likeness of interdependence applied to autonomous human-machine teams suggests that at the social level, debate models an individual's bifurcated brain, providing advantages for human-machine teams in freer systems over those oppressed by command and control systems (e.g., authoritarian regimes). Human-machine teams are coming, but they are not yet available, forcing us to rely on data from human systems. We close with plans for future research.

Muon tomography leverages cosmic muons’ exceptional penetration capabilities to reconstruct detailed tomographic images via multiple Coulomb scattering interactions, making it invaluable for detecting High-Z materials critical to homeland security. This study introduces the Slope Intercept (SI) algorithm, a novel approach for rapid and precise tomographic image reconstruction. Implemented using Geant4 simulations in a standard-sized container tomography station, SI demonstrates superior performance in speed and simplicity compared to traditional methods. While the imaging results of SI and the Point of Closest Approach (POCA) algorithm are nearly identical, the SI algorithm is simpler to implement, requires shorter CPU time, and exhibits a smaller margin of error. Its computational efficiency and simplicity make it a robust alternative to the POCA algorithm. These findings highlight SI’s suitability for applications demanding robust imaging and efficient data processing, which are crucial for advancing security measures and scientific research.

Evapotranspiration is a critical component of the hydrological cycle, and it has a decisive impact on the ecosystem balance in arid and semi-arid regions. The Yinchuan Plain, located in the Gobi of Northwest China, has a strong surface ET. In order to assess the ET pattern in this region, we obtained the ETa of Yinchuan Plain between 1987 and 2020 using the GEE platform. We employed the Surface Energy Balance Model (SEBAL), specifically geeSEBAL, to analyze the change pattern of ET over different seasons, years, and land types. The results show that: ① In spring, the daily ETa of the Yinchuan Plain is highest in the central lake wetland area, with a maximum value of 4.32 mm day-1. In summer, it is concentrated around the croplands and water bodies, with a maximum value of 6.90 mm day-1; In Autumn and winter, it is mainly concentrated around the water bodies and impervious areas, with maximum values of 3.93 and 1.56 mm day-1, respectively. ② From 1987 to 2020, the ET of the Yinchuan Plain showed an obvious upward and downward trend in some areas with significant land use changes, but the overall ET of the region remained relatively stable without dramatic fluctuations. ③ The evapotranspiration of different underlying land use types in the Yinchuan Plain region is as follows: water body&gt;cultivated land&gt;impervious&gt;grassland&gt;bare land. Our results showed that geeSEBAL is highly applicable in the Yinchuan Plain area. It allows for the accurate and detailed inversion of ET in the study area, which facilitates the study of regional hydrological cycle and water governance.

Cancer cells display elevated reactive oxygen species (ROS) and altered redox status, Here based on these characteristics, we develop a multi-drug delivery platform AMB@PDAP-Fe (APPF), from magnetotactic bacterium AMB-1 and realize MRI-visualized tumor microenvironment-responsive photothermal-chemodynamic therapy. The Fe3+ in PDAP-Fe is reduced by the GSH at tumor site and is released in the form of highly active Fe2+, which catalyzes the generation of ROS through Fenton reaction and inhibits tumor growth. At the same time, the significant absorption of the mineralized magnetosomes in AMB-1 cells in the NIR region enable them to efficiently convert near-infrared light into heat energy for photothermal therapy (PTT), to which PDAP also contributes. The heat generated in the PTT process accelerates the process of Fe2+ release, thereby achieving an enhanced Fenton reaction in tumor microenvironment. In addition, the magnetosomes in AMB-1 are used as MRI contrast agent, and the curing process is visualized. This tumor microenvironment-responsive MTB-based multi-drug delivery platform displays a potency to combat tumor and demonstrates the utility and practicality of understanding the cooperative molecular mechanism when designing multi-drug combination therapies.

Background: Sarcopenia is a progressive muscle disorder characterized by muscle wasting, decreased strength, and a substantially elevated risk of developing severe and potentially life-threatening health complications. For decades, muscle wasting has been recognized as a clinical symptom in various severe diseases and conditions. However, with increasing life expectancy and an aging population, sarcopenia has emerged as a prominent age-related condition in primary care, significantly contributing to disability and mortality rates. Aim and Objective: Our goal was to elucidate the clinical characteristics associated with sarcopenia prevalence in postmenopausal women with type 1 osteoporosis. Methodology: 370 postmenopausal osteoporosis patients who routinely visited the physiotherapy department at Ali Fatima Hospital were examined in this cross-sectional investigation. Mean age 64.59 ± 5.85 years, it was discovered that the patients' quality of life, postural stability, muscular strength, and balance were related to the existence of sarcopenia. Conclusion: In summary, among postmenopausal female patients with type 1 osteoporosis, the incidence of sarcopenia was relatively high (90.35%), affecting quality of life in 39.82% of patients, postural instability in 92.21% of patients, and balance in 39.92% of patients.

Background: Filamentous fungi are an emergent cause of severe infections in immunocompromised patients. Timely and accurate identification is crucial to initiate appropriate therapy. Traditional identification methods are time-consuming, labor-intensive, and operator-dependent. Ma-trix-assisted laser desorption/ionization-time-of-flight (MALDI-TOF) mass spectrometry is a rapid and easy-to-perform identification method. This study evaluates the effectiveness of a commercial MALDI-TOF MS platform to identify filamentous fungi in a routine laboratory. Material and Methods: We included 67 fungal isolates from 35 species/species complexes within 15 genera, confirmed in mycology reference laboratories. 33 were from clinical samples and 34 from strain collections. The study used the VITEK MS system (v3.2.0 database), after sample extraction by VITEK MS Mould Kit. Results were classified into categories: ‘correct species’, ‘correct species complex’, ‘correct genus’, ‘incorrect identification’, and ‘no identification’. We also evaluated the practicality of the kit. Results: VITEK MS correctly identified 91.0% of isolates (58.2% to species, 29.9% to species complex, and 1.5% to genus level). In 82%, the result matched the species/species complex identified by reference methods. No misidentifications were observed. The kit was rapid and easy to use. Conclusion: The VITEK MS system showed a high capability to accurately identify filamentous fungi in a routine laboratory.

Background: Transcatheter aortic valve replacement (TAVR) is a proven treatment for severe aortic stenosis (AS). Transfemoral access is the most prevalent method, achieved either surgically or percutaneously. This study compares in-hospital outcomes and length of stay between surgical cut-down and fully percutaneous approaches. Methods: This retrospective, propensity-matched study analyzed medical records of all patients who underwent transfemoral TAVR at our center from January 2019 to December 2023. Outcomes were assessed based on Valve Academic Research Consortium-2 (VARC-2) consensus criteria. Results: 251 TAVR patients (77 propensity score matching pairs) were included (55% female) with a median (IQR) age of 80 (11) years. Surgical cut-down showed fewer vascular complications, bleeding, and transfusions. No death, stroke, atrial fibrillation (AF), or need for pacemaker was reported in this group. Fewer mean hospitali-zation days were observed in the total cohort over the years (p< 0.001). This reduction was more pronounced after 2021 when the surgical approach was adopted. Mean hospitalization days were 6.40 ±6.46 for percutaneous and 4.34 ±1.61 for surgical groups (p< 0.001). Conclusions: Surgical cut-down for TAVR femoral access yields superior outcomes and shorter hospital stays compared to fully percutaneous methods.

Ewing sarcoma (ES) is an aggressive bone and soft-tissue pediatric cancer. High vitronectin (VN) expression has been associated with poor prognosis in other cancers, and we aimed to determine the utility of this extracellular matrix glycoprotein as a biomarker of aggressiveness in ES. Silk-fibroin plus gelatin-tyramine hydrogels (HGs) were fabricated with and without cross-linked VN and cultivated with A673 and PDX73 ES cell lines for two and three weeks. VN secretion to culture media was assessed using ELISA. Morphometric analysis was applied for phenotypic characterization. VN release to culture media was higher in 3D-models than in monolayer cultures, and intracellular, intercellular and pericluster presence was also observed. A673-HGs showed lower density of clusters but a proportion of larger clusters than PDX73-HGs, which presented low cluster circularity. The cluster density of A673-HGs without added VN was higher than with added VN, and slightly lower in the case of PDX73-HGs. Furthermore, a culture time of three weeks provided no benefits in cluster growth compared to two weeks, especially in A673 -HGs. These advances in 3D modeling and digital quantification pave the way for future studies in ES and other cancers to deepen understanding about intra- and intercellular heterogeneity and anti-adhesion VN therapies.

This article presents a rigorous approach to the Collatz Conjecture, focusing on fundamental properties of Collatz sequences. We establish key properties of the Collatz function and its inverse, including surjectivity and injectivity. The structure of Collatz sequences is analyzed in depth, proving important results such as the Bounded Subsequence Property and the uniqueness of cycles. Central theorems on the properties of Collatz sequences, including the boundedness of all sequences and the nature of the unique cycle, are presented and proved. These results culminate in a complete resolution of the Collatz Conjecture, demonstrating that all Collatz sequences eventually reach the cycle {1, 4, 2}. We provide a rigorous proof of the conjecture, while emphasizing the need for thorough peer review and verification by the mathematical community given the significance of this long-standing problem.

Large language models (LLMs) have shown impressive performance and versatility. However, their billions of parameters and high computational costs hinder the development of personalized and privacy-preserving AI assistants operating locally on user devices. In this work, we explored the potential of pruning LLMs to create lightweight models suitable for user devices, using the moderate-sized Llama-2 7B model as an example. By adopting a simple yet effective pruning method, we found that up to 60% of the weights in the Llama-2 7B model could be pruned without significantly impairing its language modeling capabilities. Furthermore, despite occasional factual inaccuracies, the pruned model at the sparsity limit generated fluent and helpful answers to daily queries, demonstrating its feasibility of on-device AI assistants. These inaccuracies might originate from forgetting or hallucination due to pruning. We proposed a simple protocol to distinguish between the two mechanisms, as well as future directions to improve the pruned models for local AI assistants.

Charge-dipole interactions are very common interactions among atoms and molecules, especially materials that can emit light or contain free charges. The second-order charge-dipole interactions, proportional to $\frac{1}{R^4}$, are stronger than the second-order dipole-dipole interactions or van der Waals interactions, proportional to $\frac{1}{R^6}$, at longer distances. In reality, there is more than one atom or charge; therefore, we focus on few-body charge-dipole interactions, such as charge-dipole-dipole interactions. Laser cooling and trapping allow us to study such interactions with much higher precision. In this article, charge-dipole interactions will be investigated in ultracold gases. To increase the interaction strength, we excite the ultracold atoms to highly excited states, Rydberg states. Here, we treat one Rydberg atom as a dipole, the excited electron and the ion core are the two poles of an electric dipole. Specifically, we study charge-atom interactions in ultracold Rydberg gases.

Hundreds of minerals are chiral, that is, they appear in nature in two forms – left-handed and right-handed. Yet except for quartz, that key structural property remained, by-and-large in the shadow of the world of minerals in research, in museum displays, and for collectors. This review is devoted for providing a full picture of chiral minerals in nature. It starts with a general outline of the crystallographic background needed for the characterization of chiral minerals, continues with a detailed description of the many chemical and physical processes leading to their formation, follows with their chemical reactivities and transformations, with their physical properties, and with the ways to analyze and identify them. Many tables with listings of the various types of chiral minerals, are provided. It is hoped that this review will spark interest in this aspect nature’s crystals.

Gigantism in theropods represents one of the most intriguing phenomena in dinosaur evolution, showcasing extreme adaptations in body size and ecological roles. This literature review focuses on Giganotosaurus carolinii, one of the largest known theropods to have ever existed, to explore its unique aspects of gigantism and the subsequent ecological impacts. By analyzing features such as its skeletal morphology, comparative anatomy, and paleoenvironmental data, we assess the evolutionary pressures and biological constraints that shaped the gigantism observed in Giganotosaurus. We discover that the species exhibited a combination of physiological and ecological adaptations that allowed it to thrive as an apex predator in its Cretaceous environment. We will also further examine the implications of its size on prey dynamics, competition with other large theropods, and the overall ecosystem structure. Through a thorough, multidisciplinary approach, this research enhances our understanding of how gigantism influenced theropod behavior, interspecies interactions, and the broader paleoecological landscape.

This study utilized electrical resistivity imaging (ERI) to investigate subsurface characteristics near Nicolaus Copernicus University Polar Station on the western Spitsbergen-Kaffiøyra Plain, island in the Svalbard archipelago. Surveys along two lines, LN (148 meters) collected in 2022 and 2023 and ST (40 meters) collected in 2023, were conducted to assess resistivity and its correlation with ground temperatures. The LN line revealed a 1 to 2 meters thick resistive unsaturated outwash sediment layer, potentially indicative of permafrost. Comparing LN resistivity result between 2022 and 2023, a 600 Ohm-m decrease in the unsaturated active layer in 2023 was observed, attributed to a 5.8℃ temperature increase, suggesting a link to global warming. ERI along the ST line depicted resistivity reaching its minimum at approximately 1.6 meters, rising to over 200 Ohm-m at 4 meters, and slightly decreasing to around 150 Ohm-m at 7 meters. Temperature measurements from the ST line's monitoring well confirmed permafrost at a depth of 1.6 to 2 meters. Additionally, water content distribution in the ST line was estimated after temperature correction, revealing a groundwater table depth of approximately 1.06 meters, consistent with measurements from the S4 borehole on the ST line. This study provides valuable insights into Arctic subsurface dynamics, emphasizing the sensitivity of resistivity patterns to climate change and offering a comprehensive understanding of permafrost behavior in the region.

This investigation is part of a topical situation where wireless equipment is gradually being used for energy transfer, particularly for autonomous systems and the use of decarbonized en-ergies. A characteristic example of decarbonized autonomous use is linked to the substitution of thermal engine vehicles by electric vehicles (EVs) equipped with energy storage batteries. This response was considered in an ecological context of reducing air pollution and defending plane-tary biodiversity, which are currently vital. These EVs ultimately operate thanks to the wireless charging of their batteries when stationary or running. By changing long-established means of transport that have become a threat to biodiversity, it is necessary to ensure that innovative re-placement solutions protect this biodiversity. In addition, the construction of wireless power transfer (WPT) battery chargers for these EVs must offer an optimal ecology of clean energy saving. In such a context, the two concepts of One Health (OH) and Responsible Attitude (RA) will find their place in the design and control of WPT tools in EVs. This contribution aims to il-lustrate and analyze the roles of the green and non-wasteful OH and RA approaches in the de-sign and control of WPT embedded in EVs for the smart city (SC) environment. In the paper, WPT tools are first introduced. The design and control of EV battery charging tools are then examined. The biological effects on living tissues due to the electromagnetic field (EMF) radia-tion of WPT are analyzed. The phenomena and equations governing the design of WPT and the effects of EMF radiation are then exposed. The OH and RA approaches in the SC context are af-terward analyzed. The protection against the unsafe effects of WPT tools in the SC environment is consequently explored. The analyses followed in the paper are supported by examples of lit-erature.

Road conditions, often degraded by insufficient maintenance or adverse weather, significantly contribute to accidents, exacerbated by the limited human reaction time to sudden hazards like potholes. Early detection of distant potholes is crucial for timely corrective actions, such as reducing speed or avoiding obstacles, to mitigate vehicle damage and accidents. This paper introduces a novel approach that utilizes perspective transformation to enhance pothole detection at different distances, focusing particularly on distant potholes. Perspective transformation improves the visibility and clarity of potholes by virtually bringing them closer and enlarging their features, which is particularly beneficial given the fixed-size input requirement of object detection networks, typically smaller than the raw image resolutions captured by cameras. Our method automatically identifies the region of interest (ROI)—the road area—and calculates the corner points to generate a perspective transformation matrix. This matrix is applied to all images and corresponding bounding box labels, enhancing the representation of potholes in the dataset. This approach significantly boosts detection performance when used with YOLOv5-small, achieving a 45.7\% improvement in average precision (AP) at IoU thresholds of 0.5 to 0.95 for a single class, and notable improvements of 30.3\%, 78.6\%, and 278\% for near, medium, and far pothole classes, respectively, after categorizing them based on their distance. This work is the first to employ perspective transformation specifically for enhancing the detection of distant potholes.

Accurate measurement of pedaling kinetics and kinematics is vital for optimizing rehabilitation, exercise training, and understanding musculoskeletal biomechanics. Pedal reaction force, the main external force in cycling, is essential for musculoskeletal modeling and closely correlates with lower limb muscle activity and joint reaction forces. However, sensor instrumentation like 3-axis pedal force sensors is costly and requires extensive post-processing. Recent advancements in machine learning (ML), particularly neural network (NN) models, provide promising solutions for kinetic analyses. In this study, an NN model was developed to predict radial and mediolateral forces, providing a low-cost solution to study pedaling biomechanics with stationary cycling ergometers. Fifteen healthy individuals performed a 2-minute pedaling task at two different self-selected (58±5 rpm) and higher (72±7 rpm) cadences. Pedal forces were recorded using a 3-axis force system. The dataset included pedal force, crank angle, cadence, power, and participants' weight and height. The NN model achieved an inter-subject normalized root mean square error (nRMSE) of 0.15±0.02 and 0.26±0.05 for radial and mediolateral forces at high cadence, respectively, and 0.20±0.04 and 0.22±0.04 at self-selected cadence. The NN model's low computational time suits real-time pedal force predictions, matching the accuracy of previous ML algorithms for estimating ground reaction forces in gait.

Time-of-Flight (ToF) cameras are subject to high levels of noise and errors due to Multi-Path-Interference (MPI). To correct these errors, algorithms and neuronal networks require training data. However, the limited availability of real data has led to the use of physically simulated data, which often involves simplifications and computational constraints. The simulation of such sensors is an essential building block for hardware design and application development. Therefore, the simulation data must capture the major sensor characteristics. This work presents a learning-based approach that leverages high-quality laser scan data to generate realistic ToF camera data. The proposed method employs MCW-Net (Multi-Level Connection and Wide Regional Non-Local Block Network) for domain transfer, transforming laser scan data into the ToF camera domain. Different training variations are explored using a real-world dataset. Additionally, a noise model is introduced to compensate for the lack of noise in the initial step. The effectiveness of the method is evaluated on reference scenes to quantitatively compare to physically simulated data.

Keywords: mathematics and statistics support; higher education; text mining; international networking; resource optimization; quality education

In this paper we suggest a first ever construction of fractional integral and differential operators based on signed measures including a vector-valued case. The study focuses on constructing the fractional power of the Riemann-Stieltjes integral with a signed measure, using semigroup theory. The main result is a theorem that provides the exact form of a semigroup for the Riemann-Stieltjes integral with a measure having a countable number of extrema. The article provides examples of semigroups based on integral operators with signed measures and discusses the fractional powers of differential operators with partial derivatives.

Titanium-based metal-matrix composites manufactured by additive manufacturing offer tremendous lightweighting opportunities. However, processing high reinforcement content remains challenging. This study reports an improved manufacturing process for Ti-TiC enabling high reinforcement content and significant fracture strain concurrently: mechanical blending, followed by laser powder bed fusion and a single heat treatment. As-built microstructure shows both un-melted TiC particles and sub-stoichiometric TiC dendrites resulting from a partial dissolution of TiC particles. The heat treatment is shown to fully convert TiC dendrites into equiaxed TiC grains. Reduction of the C/Ti ratio in TiC during the process results in an increase in the reinforcement content, from a nominal 12 vol% to an effective 21.5 vol%. Ti-TiC tensile samples reached fracture strains of up to 1.7%, Young’s moduli of up to 149 GPa and ultimate tensile strengths of up to 827 MPa. Lower TiC initial powder size distributions displayed the best mechanical performance.

Formal Calculation uses an auxiliary form to calculate various nested sums and provides results in three forms. It is also a powerful tool for analysis. This article studies the symmetry of the coefficients in Formal Calculation. Three types of extended numbers were introduced, and many formulas for symmetric functions were obtained.

The COVID-19 pandemic has revealed significant disparities in disease severity and mortality across various population groups and regions. These disparities cannot be attributed solely to healthcare systems, socioeconomic factors, living conditions, or individual immune landscapes; environmental factors also play a crucial role. This work explores how variations in nasal morphology related to age, gender, and race can affect the respiratory system's ability to filter, warm, and humidify inhaled air. These variations may contribute to differences in how cold, dry, polluted, and infected air impact the respiratory system, thus influencing the observed patterns of disparities in COVID-19 outcomes. The analysis suggests that individuals with genetically determined wider nasal cavities, often found in populations originating from warmer climates, have decreased filtration and air conditioning efficiency, leading to increased susceptibility to respiratory infections and disproportionately high mortality rates from COVID-19. Moreover, age-related changes in nasal morphology, such as increased nasal volume and involution atrophy of the mucosa, contribute to impaired air conditioning and filtration, thereby increasing the risk of severe outcomes in the elderly. Gender differences in nasal morphology, with men typically having larger nasal passages compared to women, are linked to poorer air conditioning and filtration, potentially contributing to the higher risk of severe COVID-19 in men. Preliminary statistical analyses of the U.S. population suggest that men with favorable nasal structures may have a longer life expectancy than those with less optimal nasal anatomy; however, this should be regarded as a hypothesis. The findings underscore significant gaps in our understanding and highlight the urgent need for further research to unravel the complex interplay between nasal morphology, respiratory system dynamics, and environmental factors in shaping disease susceptibility and outcomes.

Background: The loss of a co-worker always evokes complex emotions. Such a loss is particularly challenging for those who spend many hours at work and develop close interpersonal relationships with their colleagues. While many studies have examined how losing colleagues affects employees in various organizations, no research has specifically examined this topic in the school environment. Methods: This qualitative study explored the experiences of school counsellors facing the loss of colleagues from their school educational team. Twenty-one school counselors ranging in age from 28 to 61 who had lost a colleague within the past five years were examined by semi-structured in-depth interviews. The interviews were transcribed and analyzed using thematic content analysis. Results: Three main themes emerged from the data: (1) “From Shock to Action”: School Counsellors’ Reactions to Colleague Loss; (2) “From Friendship to Conflict”: School Counsellors' Diverse Experiences with Colleague Loss; and (3) “The Burden of Care”: Coping Mechanisms for School Counsellors Facing Colleague Loss. Conclusion: This study highlights the complex experiences of school counsellors in dealing with the death of colleagues. It underscores the importance of providing long-term emotional support for counsellors throughout their careers, particularly when coping with crises and emergencies.

This study aimed to evaluate the impact of different closures used in second fermentation on the aromatic fraction of sparkling wine. Six types of closures (cork stoppers and screw cap) and 94 months of aging in bottle were investigated. Head-space-solid phase microextraction (HS-SPME) and thermal desorption (TD) procedures coupled to gas chromatography-mass spectrometry (GCMSMS) analysis was applied. The vectors containing the relative abundance of the volatile compounds are compositional vectors. The statistical analysis of compositional data requires specific techniques that differ from standard techniques.101 volatile compounds were identified. HS-SPME extracted highest percentage of ester, ketones and other compounds while TD was a useful tool for the obtention of alcohol, acid, ether and alkanes compounds. Esters was the most abundant family of compounds. Compositional data analysis applied to study the impact of different closures used in bottle-aging after second fermentation on the volatile composition of sparkling wine concluded that there are differences in the relative abundance of certain volatile compounds between cork stoppers and screw cap closures group. Overall, the most abundant part in screw cap closures was Ethyl hexanoate and, Ethyl octanoate in cork stoppers. Also, the proportion amount of Dimethylamine was higher in screw cap closures than cork stoppers group relative to the entire of the sample.

The growing global population and limitations in fish catch production have led to a surge in the demand for aquaculture. Contaminants of emerging concern (CEC) are frequently being detected at low levels in surface water. These CECs, which include previously unidentified or unregulated pollutants, pose potential risks to health and the environment, though their impacts are not yet fully understood. Extensive research studies have been proposed and undertaken to address the issue of aquaculture wastewater, aiming to minimize its impact and implement effective treatment methods. This review provides an analysis of various technologies used for treating aquaculture wastewater using advanced oxidation processes (AOPs) focusing on photocatalysis and ozonation. It examines their advantages and disadvantages, as well as their respective treatment efficacies and discusses their potential applications in sustainable aquaculture practices complying with the Sustainable Development Goals of 1,2 and 6 and the Environmental Social and Governance (ESG) framework.

Aim of the study was to determine the influence of climatic and hydrological changes on the growth of Scotch pine (Pinus sylvestris L.) and Black alder (Alnus glutinosa (L.) Gaertn) in the Narew National Park over past 50 years. The researches were based on tree increment cores extracted from 42 pine trees and 57 alder trees ranging in age from 25 to 88 years and climatic (temperature and precipitation for Bialystok) and hydrological (water level of the Narew River) data. Standardized data (5-year index) were analysed by species, generation (Y - 21-40 years, M - 41-60, O - 61-90) and decade using correlation analysis. The results of the study show that pine responded more strongly to changes in air temperature and changes in precipitation totals, while alder growth was more strongly related to fluctuations in the water level of the Narew River. The most variable climatic and hydrological conditions and the most difficult conditions for tree growth prevailed in the first and last decades (1971-1980, 2011-2020). The decrease in the water level of the Narew River that occurred over the last 50 years did not adversely affect the condition of the trees. Analysis of DBH growth rates showed that the younger generations (Y, M) grow faster than the older generation (O). One of the reasons for the accelerated tree growth and increased resistance to the decline in the water level of the Narew River may be the increase in CO2 concentration in the atmosphere. Accelerated tree growth and increased resistance to drought may have certain consequences like increased damage from wind as a result of the decrease in wood density or decline in the sensitivity of trees to climate and hydrological changes. However, less sensitivity to changes in climatic conditions may only apply to older trees.

Tsallis entropy has been widely used in image thresholding because of its non-extensive properties. The non-extensive parameter q contained in this entropy plays an important role in various adaptive algorithms and has been successfully applied in bi-level image thresholding. In this paper, the relationships between parameter q and pixels’ long-range correlations have been further studied within multi-threshold image segmentation. It is found that the pixels’ correlations are remarkable and stable for images generated by a known physical principle, such as infrared images and medical CT images. And the corresponding non-extensive parameter q can be evaluated by using self-adaptive Tsallis entropy algorithm. The results of this algorithm are compared with those of Shannon entropy algorithm and the original Tsallis entropy algorithm, in terms of quantitative image quality evaluation metrics PSNR (Peak Signal-to-Noise Ratio) and SSIM (Structural Similarity). Furthermore, we observed that for image series with the same background, the q values determined by the adaptive algorithm are consistently kept in a narrow range. Therefore, similar or identical scenes during imaging would produce similar strength of long-range correlations, which provides potential applications for unsupervised image processing.

Sub-national governments (SNGs) in developing countries have increasingly explored green municipal bonds as a financing tool, driven by promises of lower borrowing costs, enhanced reputation, and support for sustainable economic development. This study aims to critically examine these claims by analysing the actual costs and complexities associated with green municipal bonds (GMBs). The research involves a comparative analysis of traditional municipal bonds and GMBs, focusing on the financial and operational challenges faced by SNGs. Detailed case studies from Mexico City and Cape Town are used to illustrate the practical implications of issuing GMBs. The findings reveal that, despite similar or slightly lower interest rates, GMBs often entail higher issuance costs due to the need for certification, monitoring, and reporting of green projects. These additional costs, coupled with the necessity of hiring external consultants, make GMBs more expensive and difficult to replicate after initial transactions. Furthermore, the study highlights that the demand from investors has not met initial expectations. While green-aligned investors show a higher appetite for GMBs, they constitute only a small portion of the finance market. Traditional investors, primarily focused on financial returns, are less inclined to invest in GMBs solely based on their green label. Consequently, many SNGs have reverted to issuing traditional “vanilla” municipal bonds while still using the proceeds to fund green initiatives. This shift underscores the need for a realistic assessment of GMBs’ viability in developing countries and calls for a re-evaluation of strategies for promoting sustainable economic development through green finance.

Different materials prepared by appropriate synthesis methods and applying different post syn-thesis processes could be used as hole transport layer in perovskite solar cells. In the present work annealing was employed to enhance physical properties of copper oxide (CuO) thin films fabricated via spin coating technique and the effects of annealing on their optical, morphological, electrical and structural properties were investigated. The XRD findings revealed the polycrystalline structure with large crystallite size. Optical spectra showed larger transmission beyond the visible region, reduced absorption, and a decrease in bandgap energy from 1.93 eV to 1.81 eV. The Ag phonon modes at 299.22 and 304 cm-1 shown by the Raman shift confirmed the development of the CuO pure phase. FTIR spectra showed the Cu-O stretching band at 759, 764 and 446 cm−1. SEM revealed the agglomeration of nano crystallites with large grains on the surface. The carrier type conductivity of annealed CuO thin films was determined via two-point hot probe technique. Low resistivity values were determined via four-point probe method. These findings indicate that CuO thin films may be successfully used as a companion with an n-type layer in p-n junction solar cells, and a hole transport layer in perovskite solar cells.

As the use of AI in medical imaging has increased, so has the need to explain a model’s results. Segmentation models are one technique used to produce explainable results. Due to larger size and sophistication, segmentation models which operate on 2D data can often produce better results than models operating on 3D data. In the real world, imaging is combined with clinical factors for diagnosis. To replicate this, multimodal models are used which combine image and text modalities. I propose a multimodal arrangement that converts 3D scans to 2D and uses a 2D segmentation model (DeepLabV3) to analyze the images. This is combined with clinical biomarkers to achieve a complete confidence score. Using the Medical Segmentation Decathlon Lung (MSDL) dataset and the LUng CAncer Screening dataset (LUCAS), I achieved a testing Dice coefficient of 0.91 on segmentation with a receiver operating characteristic (ROC), average precision (AP), and F-Score of 0.89, 0.91, and 0.85 respectively on the final multimodal results. This approach raises the F-score from the previously achieved value of 0.508 to 0.85, creating a new baseline of what is achievable with multimodal lung cancer diagnostics and possible methods to achieve these accuracies.

This study investigates the effectiveness of a text summarization method applied to open-ended student evaluations at the Hellenic Open University, aiming to improve the analysis of qualitative feedback from online educational surveys. To address the challenges of processing large volumes of student feedback, an automated summarization technique utilizing advancements in Natural Language Processing (NLP) and text mining is proposed. Using the TextRank and the Walktrap algorithms, student comments on positive aspects, study challenges, and improvement suggestions were analyzed. The analysis revealed that while some students expressed satisfaction with tutor-student interactions and the organization of educational material, there were also negative comments about outdated content in some modules and scheduling issues. The findings highlight the importance of qualitative feedback for education quality, providing actionable insights for improving curricula and teaching effectiveness. This research responds to the growing need for effective qualitative data analysis in higher education and contributes to ongoing discussions about student satisfaction in distance learning environments. By effectively summarizing open-ended responses, university staff can better understand student experiences and make informed decisions to enhance the educational process.

To date the role of green leaf volatiles has been mainly constrained to their role in protecting plants against pests and pathogens. However, increasing evidence suggests that among the stresses that can significantly harms plants, GLV can also provide significant protection against an array of those including heat, cold, drought, light, and salinity. But while the molecular basis for this protection is still largely unknown, it seems obvious that a common theme in the way GLV work is that most if not all of these stresses are associated with physical damage to the plants, which in turn is the major event responsible for the production of GLV. Here, I summarize the current state of knowledge on GLV and abiotic stresses and provide a model that explains the multifunctionality of these compounds.

Computational fluid dynamics (CFD) modeling has emerged as a valuable tool for investigating complex processes like microencapsulation. This paper aims to validate the ability of CFD simula-tions to predict particle size distribution in a polymer microencapsulation process. The CFD mod-eling approach employed an Eulerian multiphase framework, incorporating a discrete population balance model to track the evolution of the droplet population. A realizable k-ε turbulence model and a multiple reference frame strategy were utilized to capture the system’s flow dynamics. The results reveal that while the CFD simulations align well with experimental data at higher agitation speeds (>10000 rpm), discrepancies arise at lower speeds (

This paper introduces LUNARMINERS framework and applies it for lunar water-ice extraction in Shackleton Crater at the lunar South Pole. The LUNARMINERS combines artificial intelligence swarm robotics with biomimetic swarm behavior. In the proposed framework, the foraging behavior of ants, the light attraction behavior of fireflies, and the migratory flight strategy of wild geese have been comprehensively analyzed and applied to robotic swarms for lunar mining. This research takes into consideration important aspects of the lunar environment, such as permanently shadowed regions (PSRs) and communication limitations in lunar craters, by simulating them in Robot Operating System (ROS). The LUNARMINERS framework has advantages over other methods in that it allows for the survey of an area of 0.025 km2 per day while achieving 100% water-ice deposition effectiveness. Studies show that by applying the LUNARMINER framework, the exploration of the entire Shackleton Crater can be completed in 3.75 Earth years via 15 robots. Simulations of the implementation of the proposed LUNARMINERS framework have demonstrated reliable high-levels of extraction efficiency, with the framework producing 12.9 metric tons of water-ice per day, which potentially can support up to 1,990 people per day based on astronaut’s daily water requirements from NASA's Human Integrated Design Handbook (HIDH) and thus, establishing a sustainable benchmark for lunar habitation. The results from this study show that the advances in the proposed LUNARMINERS framework can contribute to future lunar exploration and ISRU, setting new standards for sustainable off-Earth mining.

Emergency departments (EDs) are critical in urgent care, where accurate triage optimizes patient flow and resource allocation. Manual triage faces challenges due to increasing volume and com-plexity. This study compares logistic regression, gradient boosting, neural network, and random forest models in predicting Emergency Severity Index (ESI) triage levels for non-traumatic pa-tients at Lampang Hospital's ED. Using data from January 1, 2023, to April 30, 2024, we ana-lyzed 45,245 complete records. The gradient boosting model achieved the highest accuracy (0.81), significantly outperforming logistic regression (accuracy 0.64). Pain scale, sex, and mean arterial pressure were key predictors. This is the first comparison of these models for ESI triage in a Thai hospital, highlighting their potential to improve triage accuracy and efficiency. Implementing these models could enhance patient outcomes and resource management in ED.

Cys is one of the least abundant amino acids in proteins. However, it is often highly conserved and usually found in important structural and functional regions of proteins. Its unique chemical properties allow it to undergo several post-translational modifications, many of which mediated by reactive oxygen, nitrogen, sulfur or carbonyl species. Thus, in addition to their role in catalysis, protein stability and metal binding, Cys residues are crucial for redox regulation of metabolism and signal transduction. In this review, we discuss Cys post-translational modifications (PTMs) and their role in plant metabolism and signal transduction. These modifications include oxidation of the thiol group (S-sulfenylation, S-sulfinylation and S-sulfonylation), the formation of disulfide bridges, S-glutathionylation, persulfidation, S-cyanylation S-nitrosation, S-carbonylation, S-acylation, prenylation, CoAlation as well as the formation of thiohemiacetal. For each of these PTMs, we discuss the origin of the modifier, the mechanisms involved in PTM, as well as their reversibility. Examples of the involvement of Cys ​​PTMs in the modulation of protein structure, function, stability, and localization are presented to highlight their importance in the regulation of plant metabolic and signaling pathways.

Heating stage accounts for the largest proportion of building carbon emissions. In order to figure out heating situations of rural residential building in Gansu Province, Gannan region was selected to carry out on-site survey on heating condition including heating mode, energy used for heating, heating fees, residents’ satisfaction on heating and thermal environment of typical building. The results showed that local rural residents burnt scattered coal for heating with primitive heating stove with high heating cost and low efficiency, causing low air temperature and high heating fees. Besides carbon emissions caused by heating reached 5743.28 kgCO2em-2, Several strategies for improving the heating effect and reducing carbon were proposed taking economic benefits into consideration limited by rural economic development. A parameter of reduced carbon emissions per investment input was proposed to evaluate the carbon reduction strategies. Results showed that Biomass was the most economical way to reduce the carbon emissions, followed by thermal insulation design, natural gas furnace and air source heat pumps for heating, and it was not reasonable to blindly increase building insulation to reduce building carbon emissions. The optimum energy efficiency was 55% in Gannan. The results provided reference for building low-carbon design in rural areas, helped achieving low carbon goal with low investment.

This study investigates the use of geopolymer technology as an alternative for the management of mine tailings, which is a serious environmental problem in mining environments including that of Arequipa region of Peru. In this study, the mixture of stabilized mine tailings with different percentages of binders (metakaolin and pumice) and their impact on the mechanical, microstructural, and toxicological properties of the synthesized geopolymers were analyzed. The ratios of mine tailings to binder material varied between 100/0 and 0/100. The activation was carried out with an alkaline solution of sodium hydroxide (10M) and sodium silicate (modulus 2.5). 50 mm cubic specimens were fabricated, and 7 mixtures with 3 replicates each were evaluated. The evaluations included compressive strength at 7, 14, 28, and 56 days of curing, chemical analysis by X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR), microstructural characterization by Scanning Electron Microscopy (SEM/EDS), thermal behavior by thermogravimetry and differential thermal analysis (TGA/DTA) between 40°C and 1000°C, and toxicological tests by the Toxicity Characteristic Leaching Procedure (TCLP, EPA 1311) to determine the efficiency of immobilization of toxic metals. The results showed good mechanical strength, reaching 25 MPa at 7 days of curing, high microstructural stability with an average pore size of 7.21 μm, and good efficiency in the immobilization of heavy metals in geopolymers composed of 60% - 40% and 70% - 30% of the mine tailings - binders ratio, as the concentrations of As, Cd, Pb, Hg were below the established thresholds, acquiring the classification of non-hazardous materials. Geopolymers with 30 to 50% binder showed good mechanical behavior, microstructural stability, and high efficiency in the immobilization of heavy metals, complying with current regulations. Therefore, these geopolymers are suitable for various applications and in different environmental conditions.

Polarizable continuum methods (PCM) have been widely employed for simulating solvent effects, in spite of the fact that they either ignore specific interactions in solution or only partially reproduce non-specific contributions. Examples of three solvatochromic dyes with a negative, a positive and a reverse behavior illustrate the achievements and shortcomings of PCM calculations, and the causes for their variable success. As shown with a theoretical model that rationalizes and predicts the solvatochromism of phenolate merocyanines based on structural parameters, PCM shortcomings are to be held responsible for their eventual failure in reproducing experimental data.

This research aims to explore the use of sodium benzoate C6H5-COOH as corrosion inhibitor added to the mixing water of concrete, and test the mechanical performances of five types of concretes over several time periods, 7, 28, 56 and 90 days, in the absence and in the presence of limestone fillers. Hence the results confirm the increase in this resistance over time. Through this, tests were carried out cement paste after addition of sodium benzoate and limestone fillers, we see clearly that the start and the and setting time of cement shift out considerably which indicates that sodium benzoate aims to delay start and end setting time of cement. In addition, Abrams cone slump tests on concrete in the fresh state were carried out in order to see the influence of the addition of sodium benzoate and tests on the cement consistencies in the absence and presence of superplasticizing adjuvant “ORAFLOW THM 17200” which has the main role of improving the workability and quality of the concrete while comparing with ordinary concrete.

Mathematical optimization offers a valuable approach to tackle Industry scheduling problems. By formulating the scheduling challenge as a mathematical problem, mathematical optimization enables efficient and effective decision-making processes. Mathematical optimization is particularly beneficial in complex scheduling scenarios, such as in networked manufacturing environments, where multiple jobs and resources need to be coordinated. By leveraging optimization models and algorithms, it becomes possible to generate optimal process plans, considering factors like job dependencies, resource availability, and timing constraints. Through mathematical optimization, organizations can achieve improved efficiency, reduced lead times, and enhanced utilization of resources. Rigorous mathematical formulations and optimization techniques enables to surpass traditional manual planning methods and brings forth powerful computational capabilities. By optimizing various scheduling objectives, from minimizing makespan to maximizing resource utilization, mathematical optimization provides organizations with valuable insights and actionable plans. The purpose of this study is to discuss scheduling solutions for multiple jobs in a networked manufacturing setting based on mathematical optimization process. The study analyses a solver-based approach to generate the optimal process plans for multiple jobs and compare it with a more traditional game-theoretic approach. The objectives aim to develop two solver-based model using Z3 and Gurobi to generate optimal process plans; implement a game-theoretic model to solve for the same set of scheduling problems, and compare the computational time, solution quality, and efficiency of both approaches. To achieve this, the methodology will start with the problem definition. Multiple jobs are to be scheduled on a set of parallel machines. Each job has predefined processing times, deadlines, and priorities. The objective is to minimize the total completion time and maximize machine utilization while meeting all deadlines.

Palytoxins are a group of highly potent and structurally complex marine biotoxins that rank among some of the most toxic substances known to science. Palytoxins are naturally synthesized by a variety of marine organisms, including Palythoa zoanthids, Ostreopsis dinoflagellates, and Trichodesmium cyanobacteria, and are widely distributed in tropical and temperate regions where they can bioaccumulate in marine life. The evolution of research on palytoxins has been an intricate exchange between interdisciplinary fields, drawing insights from chemistry, biology, medicine, and environmental science in efforts to better understand and mitigate the health risks associated with this family of toxins. In this review, we begin with a brief history covering the discovery of this group of toxins and the events that led to its isolation. We then focus on the chemical structure of these compounds and their proposed mechanism of action. Finally, we review in vitro and in vivo studies related to their toxicity, with the aim to provide a broad overview of the current knowledge on palytoxin toxicology.

A novel approach is developed to improve the convergence of Physics-Informed Neural Networks (PINNs), aiming to employ them as real-time computational models within the framework of the digital twin for manufacturing processes. This method entails the weighting of physical equations, boundary conditions, and initial conditions to ensure their comparable magnitudes, with power being the chosen quantity in this study. The approach is applied to thermal problems, which are crucial for predicting manufacturing part defects. Different configurations, including complex boundary conditions and complex physics, were tested to assess the model’s robustness. The W-PINN demonstrates good predictions and strong stability compared to the classical PINN.

The field of biosensors has found great use for surface plasmon resonance (SPR), which has attracted attention for its multiple applications. With the goal of early cancer detection at the level of a single living cell, this research numerically investigates a very sensitive D-shaped fiber-optic biosensor based on surface plasmon resonance (SPR). The titanium oxide (TiO2) is coated on gold (Au), which is utilized as a thin-film plasmonic material in the suggested biosensor structure. The guiding of light in the fiber is modeled using the finite element method (FEM) when six different types of healthy human cells and their malignant counterparts are exposed to its sensitive region. Refractive index (RI) differences between cancer cells and healthy cells are found through the analysis of the optical spectra and their amplitudes. This enables us to identify small changes in the optical characteristics of cells that could be a sign of pathogenic alterations. In this work, we concentrated on three forms of cancer: skin cancer (basal cell) and breast cancer (MDA-MB-231 and MCF-7). The results show which parameters are optimal to ensure that the sensor performs well when used to detect the three types of cancer under study. When the suggested sensor’s performance is compared to SPR sensors that have previously been published in the literature, it becomes clear that our sensor offers great promise for early cancer detection.

A diet with low content of fermentable oligo-, di-, and monosaccharides and polyols (FODMAP) are established treatment for irritable bowel syndrome (IBS), with well-documented efficiency. A starch- and sucrose-reduced diet (SSRD) has shown similar promising effects. This randomized, non-inferiority study aimed to test SSRD against low FODMAP and compare the responder rates to a 4-week dietary intervention of either diet. 155 IBS patients were randomized to SSRD (n=77) or low FODMAP (n=78) for 4 weeks, with a follow-up 5 months later without food restrictions. The questionnaires Rome IV, IBS-severity scoring system (IBS-SSS), and visual analog scale for IBS (VAS-IBS) were completed at baseline and after 2 and 4 weeks and 6 months. Weight, height, waist circumference, and blood pressures were measured. Comparisons were made within the groups and between changes in the two groups. There were no differences between groups at baseline. The responding rate (RR=∆Total IBS-SSS ≥−50) of SSRD was non-inferior compared with low FODMAPs at week 2 (79.2% vs. 73.1%;p=0.661;95% confidence interval (CI)=-20-7.2) and week 4 (79.2% vs. 78.2%;p=1.000;95%CI=-14-12), with borderline-significance at follow-up (36.4% vs. 42.3%;p=0.252;95%CI=-9.4-21). All gastrointestinal and extraintestinal symptoms were equally improved (p<0.001 in most variables). SSRD rendered greater reductions in weight (p=0.006), body mass index (BMI) (p=0.005), and sugar craving (p=0.05), whereas waist circumference and blood pressure were equally decreased. Weight and BMI were regained at follow-up. In the SSRD group, responders at 6 months still had lowered weight (-0.7 (-2.5-0.1) vs. 0.2 (-0.7-2.2) kg; p=0.005) and BMI (-0.25 (-0.85-0.03) vs. 0.07 (-0.35-0.77) kg/m²; p=0.009) compared with baseline in contrast to non-responders. Those who had tested both diets preferred SSRD (p=0.032). A 4-week SSRD intervention was non-inferior to low FODMAP regarding effects on gastrointestinal and extraintestinal IBS symptoms. Reductions of weight, BMI, and sugar craving were most pronounced following SSRD.

In the present research, it has been tried to use the applied research bases in the field of business management with marketing orientation. Since there were wide and diverse spectrum in the field of economic activities in Isfahan province and Isfahan city, the model of economic sectors was used to categorize these activities. In this regard, the specific goals of the research in all five sectors of the model of economic sectors, drawing and prioritizing the components (in-dices) of the 7P marketing mix model in each of these economic sectors by the related individuals and members of subgroups of guilds and non-governmental organizations in Isfahan province, have been formed, specified and determined. Collecting data for processing and answer the question of this research, after designing a questionnaire in accordance with the AHP model standard, by spending a period of 2 months from September 2022 and ended in November 2022 , from the statistical population has been done.

This study explores the influence of social media marketing on brand loyalty, employing a qualitative research approach to gain in-depth insights into the key factors that drive consumer engagement and commitment. Through semi-structured interviews with 20 active social media users and a comprehensive analysis of social media content, the research identifies several critical elements affecting brand loyalty. Personalization emerged as a central theme, with tailored content, customized offers, and personalized recommendations significantly enhancing users' emotional connection with brands. High-quality content, characterized by engaging visuals and valuable information, was found to reinforce positive brand perceptions and sustain loyalty. Influencer marketing also plays a pivotal role, with authentic endorsements from relevant influencers boosting brand credibility and trust. Effective community management, involving active engagement, responsive feedback, and relationship-building, contributes to a positive brand experience and strengthens user loyalty. Targeted and relevant social media advertising supports brand loyalty, although excessive or irrelevant ads can lead to disengagement. The study also highlights the importance of balancing interaction frequency and content quality to maintain user interest without causing fatigue. Addressing social media fatigue by delivering relevant and valuable content is crucial for preventing user disengagement. Content that resonates with users' values and emotions further strengthens brand attachment. Consistency in brand voice, visual identity, and values ensures a coherent and positive brand experience. The findings emphasize the need for a strategic approach to social media marketing, integrating personalization, content quality, influencer partnerships, community management, advertising relevance, and consistency to build and sustain strong brand loyalty.

A recently published article posited the use of polymer matrix composites (PMCs) as a replacement material for low-carbon steel (LCS) in large power transformer (LPT) tanks [1]. PMCs offer potential advantages such as weight reduction, corrosion prevention, and self-healing of the tank material which may not be achievable with traditional LCS. LCS can arrest ballistic projectiles at relatively low velocities, but at higher velocities, penetration can occur leading to a potential major transformer failure. Numerical simulations of steel projectile impacts upon LCS plates and glass and/or carbon fiber polymer composite laminates showed that with sufficient thickness both could prevent projectile penetration. This prevention was especially efficient when the plates were coated with a high strain rate sensitive material such as polyurea (PU). Our simulations show that the addition of a 3 mm coating of PU to a standard 10 mm thick LCS plate used in LPT tanks could prevent penetration of a 400 m/s steel projectile. For PMC plates, the simulations with the same projectile velocity showed three times faster deceleration with a 3 mm PU coating than without the coating. Thus, two realistic approaches to improving the ballistic protection of LPTs are presented. In addition to their other advantages, this research clearly shows that PMCs with the coating could provide significant ballistic protection for the next generation of LPT tanks.

In the last decade, the application of non-Saccharomyces yeasts in oenology as a natural tool to obtain wine diversification and higher quality has aroused great interest. In this work, three M. pulcherrima strains, isolated from vineyard, were characterized through the evaluation of their main technological properties, antimicrobial activity and specific enzymatic activities (β-glucosidase, β-lyase, polygalacturonase and protease). The M. pulcherrima strains did not produce any inhibition against S. cerevisiae, while they were able to exert an antimicrobial action against some unwanted bacteria and yeasts frequently present in grape must and potentially causing alteration of wines. After this preliminary screening, M. pulcherrima AS3C1 has been selected to be used in the winemaking of red grape Vitis vinifera cv. Aglianico on a pilot scale. The effect of sequential inoculation of M. pulcherrima AS3C1 with a commercial strain of Saccharomyces cerevisiae was verified using for comparison a single inoculum with S. cerevisiae and a spontaneous fermentation. Our results showed a higher concentration of anthocyanins and catechins in wines obtained by sequential inoculation of M. pulcherrima AS3C1 and S. cerevisiae. On the basis of the data obtained, M. pulcherrima AS3C1 possesses an enzymatic profile and some oenological properties that could contribute positively to the definition of the chemical composition of wines, suggesting its possible use for red winemaking processes.

This paper examines the impact of stringent regulations on personal data protection on customer perception of data security and online shopping behavior. In the context of the rapidly expanding e-commerce landscape, ensuring the security of personal data is a complex and crucial task. The study of several legal frameworks, including Malaysia's compliance with EU regulations and Indonesia's Personal Data Protection Law, provides valuable insights into consumer data protection. The challenges of balancing data safeguarding and unrestricted movement and tackling misuse by external entities are significant and require careful consideration. This research elucidates the pivotal role of trust in e-commerce environments and the deployment of innovative e-commerce models designed to minimize personal data sharing. By integrating advanced privacy-enhancing technologies and adhering to stringent regulatory standards such as the GDPR, this study demonstrates effective strategies for robust data protection. The paper contributes to the academic discourse by providing a comprehensive framework that synergizes legal, technological, and procedural elements to fortify data security and enhance consumer trust in digital marketplaces. This approach aligns with international data protection standards and offers a pragmatic blueprint for achieving sustainable data security in e-commerce.

A Tamoxifen (TAM) response varies significantly among individuals due to genetic variations in cytochrome P450 2D6 (CYP2D6), as well as other TAM pharmacokinetic and/or pharmacodynamic proteins. In this study, 40 ER+ breast cancer patients who received at least 6 months of TAM treatment were prospectively recruited. The study aimed to evaluate, using HPLC-MS/MS, plasma concentrations of TAM and its metabolites, and to study the association with genetic polymorphisms (CYP2D6*4, CYP3A4*1B, CYP3A5*3, UGT2B7*2, UGT2B15*2, SULT1A1*2, and ESR1V364E) and adverse reactions. Bivariable linear regression analyses showed that CYP3A4*1/*1B is significantly associated with an increase of 4-hydroxyTAM plasmatic concentration, a decrease of endoxifen/4-hydroxyTAM ratio and the elimination of 17β estradiol. It was found that the CYP3A4*1/1B genotype alone could explain part of the variability in [4OHTAM], [endoxifen]/[4OHTAM], and 17β-estradiol plasma levels. Similarly, SULT1A1*1/*2 genotype affects the [endoxifen]/[4OHTAM] plasma ratio. Multivariable predictive models, incorporating both polymorphisms and non-genetic variables, are proposed to explain [NdesMeTAM]/[TAM], [4OHTAM]/[TAM], [endoxifen]/[NdesMeTAM], [endoxifen]/[4OHTAM], and 17β-estradiol plasma levels, as well as for predicting hot flashes and cramps. This preliminary study suggests that the genetic variants studied may influence the bioactivation and elimination of TAM, the clinically observed adverse reactions, and potentially the treatment efficacy.

Target detection technology plays a crucial role in fishery ecological monitoring, fishery diversity research, and intelligent aquaculture. Deep learning, with its distinct advantages, provides significant convenience to the fishery industry. However, it still faces various challenges in practical applications, such as significant differences in image species and image blurring. To address these issues, this study proposes a multi-scale, multi-level, and multi-stage cross-domain feature fusion model. In order to train the model more effectively, a new dataset called Fish52 (Multi-scene Fish dataset) was constructed, on which the model achieved an mAP of 82.57%. Furthermore, we compared prevalent one-stage and two-stage detection methods on the Lahatan (single-scene fish dataset) and Fish30 dataset and tested them on the F4k and FishNet dataset. The mAP of our proposed model on the Fish30, Lahatan, F4k, and FishNet datasets reaches 91.72%, 98.7%, 88.6%,and 81.5% respectively, outperforming existing mainstream models. Comprehensive empirical analysis indicates that our model possesses high generalization ability and has reached advanced performance levels. In this study, the depth of the model backbone is deepened, a novel neck structure is proposed, and anew module is embedded therein. To enhance the fusion ability of the model, a new attention mechanism module is introduced. In addition, in the adaptive decoupling detection header module, introducing classes with independent parameter sand regression adapters reduces interaction between different tasks. The proposed model can better monitor fishery resources and enhance aquaculture efficiency. It not only provides an effective approach for fish detection but also has certain reference significance for the identification of similar target sin other environments, and offers assistance for the construction of smart fisheries and digital fisheries.

This article compares chemical coagulation with electrocoagulation, two popular methods for the primary treatment of wastewater generated in the process of Underground Coal Gasification (UCG). The primary aim was to determine which method is more effective in the removal of cyanide and sulphide ions, metals and metalloids, as well as organic compounds. In both cases, experiments were conducted in batch 1 dm³ reactors, and the coagulation/flocculation process was carried out using iron ions. Four types of coagulants were tested during the chemical coagulation study: FeCl₂, FeSO₄, Fe₂(SO₄)₃, and FeCl₃. In the electrocoagulation experiments, pure iron Armco steel was used to manufacture the sacrificial iron anode. Both processes were tested under a wide range of operating conditions (pH, time, Fe dose) to determine their maximum efficiency for treating UCG wastewater. It was found that, through electrocoagulation, a dose as low as 60 mg Fe/dm³ leads to >60% cyanide reduction and >98% sulphide removal efficiency, while for chemical coagulation, even a dose of 307 mg Fe/dm³ did not achieve more than 24% cyanide ion removal. Moreover, industrial chemical coagulants, especially when used in very high doses, can be a substantial source of cross-contamination with trace elements.

Energy demand flexibility is important to balance supply and demand in energy systems based on renewables. However, attempts to steer the timing of energy demand seem to overlook how energy practices are influenced by the wider network of things and technologies in homes. Based on photos from house visits, this paper demonstrates the importance of various material relations for the timing of energy practices to assess the potential of flexible energy demand. The study focuses on the practices of washing clothes and charging batteries using three locations of material energy flexibility; embedded flexibility refers to built-in functions, connected flexibility lies in the interplay between technologies and objects, and networked flexibility situated in systems of things, including energy infrastructure, house layout, and matter. The results show how material relations challenge energy flexibility, for example, when devices compete over plugs, stuff is in the way, and convenience is prioritized. The study suggests that the flexibility of an appliance is viewed in a wider network of things, technologies, and infrastructures, including battery capacities, and that policy pays more attention to energy flexibility in the context of material networks and that energy flexibility risks being overlooked in demands for convenience and comfort.

Background: Increasing research data suggests that dysfunction of emotional brain systems may be an important contributor for the psychophysiology of schizophrenia. However, contemporary psychopathology consistently underestimates the role of emotions in the phenomenology of the disease. Psychotic arousal (PA) is a conceptually-defined psychopathological construct aimed to portray the experiential emotional state of acute psychosis. The concept provides an explanatory model for the emergence of psychosis, and the formation and maintenance of delusions based on neurobiological models on the formation of core consciousness and subjectivity. This is the first exploratory study of the major assumptions, endorsed in the project summarised as follows: 1) Psychotic arousal is a discrete state, eligible to investigation; 2) Abnormal experiential feelings are an integral part of this state; 3) The state is responsive to antipsychotic intervention during the first weeks of treatment.Methods: We developed accordingly the Psychotic Arousal Scale (PAS), explored its first psychometric properties and tested its relation to other psychopathological measures. 55 acute schizophrenia patients were evaluated with the PAS, the Positive and Negative Syndrome Scale, the Brown Assessment of Beliefs Scale, the Hamilton Anxiety, and the Calgary Depression. Cronbach α coefficients, t- test analysis, correlations and mixed linear regression models were applied for testing internal reliability of the scale, associations between parameters and sensitivity to change in three time periods during therapeutic intervention.Results: Results of the study support that (PA) is eligible for investigation as a discrete psychopathological state, abnormal experiential feelings are an integral part of this state, it presents high affinity with other affective measures, its degree of severity relates to the delusions’ conviction, and is amenable to antipsychotics early in treatment during the acute psychotic episode.Conclusions: Findings of this exploratory study are connotative of the presence of an emotional arousal impregnated by abnormal experiential feelings during acute psychosis, largely overlooked by contemporary psychopathology.

Commercial banks are financial institutions that accept public deposits and provide loans for consumption and investment to generate profit. The term "bank" originates from the Italian word "banco," meaning "desk" or "bench," which was used by Florentine bankers during the Renaissance for conducting transactions. Banking activities, however, date back to ancient times. The primary objective of this study is to examine the impact of internal control components on the organizational performance of local commercial banks in Burao, Somaliland. A descriptive research design was employed, utilizing primary data collected from these banks to assess the role of internal controls on organizational performance.The findings indicate a strong influence of internal control systems on organizational performance, revealing a significantly positive relationship between the two. Effective internal control systems contribute to the administration, completeness, and accuracy of records, and provide a safeguard against fraud and collusion, particularly among those in positions of authority or trust. For optimal performance, internal control systems must be robust and well-implemented. It is recommended that local commercial banks conduct regular internal audits of their accounting systems to mitigate risk and enhance internal control measures. Strengthening internal control systems tailored to the organization's operations and ensuring strict authorization protocols for access to bank assets are essential for improving organizational performance.

A unique nucleus, the cerebrospinal fluid-contacting nucleus (CsfR), has been identified in the brain parenchyma. This nucleus features neurons with somas located within the parenchyma and processes extending into the cerebrospinal fluid (CSF). This anatomical configuration suggests that the CsfR may serve as a crucial interface between the nervous and body fluid regulatory systems, potentially playing a significant role in overall physiological modulation. Despite its importance, the precise biological significance of the CsfR remains to be fully elucidated. Previous research has characterized the CsfR in rats, detailing its position, adjacency, neuron distribution, size reconstruction, and stereotaxic coordinates in rats and non-human primates. Given the relevance of mice as a model organism, especially the C57BL/6J strain, this study aims to explore the existence and morphology of the CsfR in mice. Our findings confirm the presence of the CsfR, consistently located in the ventral gray area of the lower part of the aqueduct and the upper part of the fourth ventricle floor. It is bilaterally symmetrical and heart-shaped, which is slightly different from the Y-shape observed in rats. This study provides significant references for researchers investigating this specialized nucleus.

Aim: To study the relationship between the location of chest pain (topography) and site of coronary artery involvement in patients of Acute coronary syndrome (ACS) undergoing percutaneous transluminal coronary angioplasty (PTCA). Materials and Method: This observational study analyzed 589 angina topographic sites in 411 consecutive patients hospitalized for Acute Coronary syndrome (ACS) who underwent PTCA at a tertiary care center between January 2017 and December 2019. All parameters including the characteristics and site of the anginal pain, Electrocardiogram (ECG), and Coronary angiography (CAG) findings were recorded and analyzed for their topographical correlation with site of culprit vessel involvement. Result: Out of 411 patients, 337 were Males (82.0%) and 74 (18.0%) were females with 589 topographic sites of angina. The mean age of the study subject was 57.03± 11.28 years. In both ST elevation Myocardial Infarction (STEMI) and Non-ST-elevation Myocardial Infarction (NSTEMI), the Left anterior descending (LAD) was the most affected vessel in 201(63.4%) and 49(53.3%) respectively. The correlation coefficient for LAD occlusion was 0.298 (p=0.001) for the Retrosternal site. The Left Circumflex (LCX) artery showed a positive correlation of 0.647 (p= 0.001) for Jaw with Neck pain and of 0.585 (p=0.001) for Backache with Shoulder pain. The Right Coronary Artery (RCA) showed a positive correlation of 0.713 (p=0.001) for Retrosternal plus Jaw and Neck pain and of 0.719 (p=0.001) for Retrosternal plus Backache. Conclusion: The study reveals a significant correlation between chest pain topography and site of coronary artery involvement. It provides a basis for future research to develop tools that help healthcare professionals quickly identify culprit artery in ACS.

The viticulture sector, spanning over 7.3 million hectares worldwide, plays a crucial economic role but faces challenges such as labor shortages, rising production costs, market competition, and climate change stresses. Addressing these issues requires monitoring the spatial and temporal variability in vineyard productivity. Traditional ground-based observations, though accurate, are time-consuming and limited in scope. Precision viticulture, leveraging technologies like GPS, remote sensing, and artificial intelligence, offers efficient, non-destructive monitoring tools. This study aims to develop and test a technological workflow using the mobile app Digivit, integrated with the AgroSat platform, to estimate yield variability in vineyards. The workflow was performed during the 2023 growing season in a series of vineyards near Siena (Italy) and involved two main steps: spatial variability characterization using AgroSat and yield estimation using the mobile Digivit app. AgroSat processed Sentinel-2 NDVI data to identify homogeneous zones, while Digivit used smartphone images of grape clusters to estimate yields. The field campaign, performed three weeks before harvest, involved monitoring representative vines within identified zones and uploading georeferenced images for cluster segmentation analysis. Yield estimates were validated against measured weights, showing a strong linear correlation (R²=0.85, RMSE=43.74g). Excluding one outlier improved correlation to R²=0.95, RMSE=14.58g. Vineyard-level yield predictions were compared with harvest data, achieving an overall error of approximately 7%, in agreement with other methods in the literature. The study demonstrates that the Digivit app provides accurate, timely yield prediction, supporting farmers in harvest planning and winemaking management. The user-friendly mobile app approach facilitates a broader adoption of precision viticulture technologies among farmers, overcoming barriers related to technical expertise.

Mediterranean mountain landscapes feature pastoralism, and the maintenance of sheep and goat grazing is the main challenge for their sustainability. To deliver pastoralism ecosystem services, particularly in reducing fire risk amidst global change, it is essential to align the herds' size and impact with the current foraging status of the ecosystems in real time. This approach allows for more efficient herding, thereby maintaining the resilience of these landscapes. Understanding complex grazing processes at a landscape scale can now be aided by the various sensors and trackers available. The development of geolocation technologies makes it possible to combine information at different scales on time to adapt pastoralism more efficiently in the context of rural abandonment. In this paper, we analyze artificial intelligence-based IoT data from the daily routes of three flocks of goats and sheep over a year in the mountains of central Portugal. A principal components analysis of the temporal geolocalization of the herds discriminates the spatial scale of the territorial selection attributed to the herders and the animals, analytically confirming what has been described empirically by several authors. The results confirmed the relevance of these operational solutions for understanding complex landscape processes and efficiently supporting sustainable management. Finally, our result shows that these innovative tools are reliable for monitoring animal ecosystem services in Mediterranean mountain landscapes in support of policy decisions on their remuneration.

The cognitive and affective impacts of video games are subjects of ongoing debate, with recent research recognizing their potential benefits. This study employs the Gaming Skill Questionnaire (GSQ) to evaluate participants' gaming skills across six genres and overall proficiency. Eighty-eight individuals aged 20-40 participated, completed assessments of empathy and six cognitive abilities: verbal short-term memory, verbal working memory, visuospatial short-term memory, visuospatial working memory, psychomotor speed (hand-eye coordination), and attention. Cognitive abilities were examined using the Digit Span Test, Corsi Block Test, and Deary-Liewald Reaction Time Task, while empathy was assessed using the Empathy Quotient Questionnaire. Findings indicate that high video game skill levels correlate with improvements in visuospatial short-term and working memory, psychomotor speed, and attention. Different genres enhanced specific skills: RPGs positively influenced verbal working and visuospatial short-term memory but negatively affected empathy; action games improved psychomotor speed and attention; and puzzle games benefited visuospatial working memory. These promising results contribute positively to ongoing research on the cognitive and affective effects of video games, highlighting the potential for video games to enhance certain cognitive functions while also underscoring the complexity of their impact on empathy. Future research should further investigate genre-specific effects and long-term outcomes.

In previous studies, drones have been used to carry out visual inspections of heritage elements. In order to complement the information obtained with the common drone, a new underwater drone model is proposed for the specific case of old bridges. The aim is to verify the applicability of underwater drones for the inspection of submerged elements of old heritage bridges, given the large number of bridge disasters and collapses linked to failures in their foundations. To this end, we carried out an underwater inspection of the visible submerged elements (submerged but not buried) of three old bridges crossing different rivers. The different locations and characteristics of these bridges allow us to draw some initial conclusions. The results of the operations carried out show that underwater drones are not only useful for this type of inspection, but that the work is much safer than with the means currently used (underwater divers). In addition, the use of drones makes it possible to study certain parameters that can anticipate subsequent foundation problems affecting the entire bridge, such as the settlement or rotation of piers or abutments.

Recently concluded, large-scale cancer genomics studies involving multiregion sequencing of primary tumors and paired metastases appear to indicate that many or most cancer patients have one or more “clonal" mutations in their tumors. Clonal mutations are those that are present in all of a patient’s cancer cells. Clonally mutated proteins can potentially be targeted by inhibitors or E3 ligase small molecule glues, but developing new small molecule drugs for each patient is not feasible currently. Achilles Therapeutics is currently the only company specifically targeting clonal mutations. However, they are doing so with tumor-derived T cells. To address the potential limitations of immunotherapy, I have devised another approach for exploiting clonal mutations, which I call “Oncolytic Vector Efficient Replication Contingent on Omnipresent Mutation Engagement” (OVERCOME). The ideal version of OVERCOME would likely employ a bioengineered facultative intracellular bacterium. The bacterium would initially be attenuated, but (transiently) reverse its attenuation upon clonal mutation detection.

Background: The study investigates patients' use of eHealth services, awareness of the availability of these services, and their intention to use them in primary care. It also examines patient characteristics and factors that influence their use. Methods: A cross-sectional design using questionnaire were conducted. Based on the unified theory of acceptance and use of technology (UTAUT), participants rated the two most common services. Descriptive analyses and linear correlation analyses were performed. Simple linear regression was conducted identify factors influencing participants' intention to use eHealth services. Results: 1203 participants were surveyed and their’ ages averaged 43.7 years. Participants usage rates varied, with the lowest at 2.4% for measuring vital signs and the highest at 47.4% for booking appointments. Intentions to use services ranged from 22.5% for video consultations to 46.6% for prescription refill requests. Approximately 20% of respondents were unaware of each service's availability. Positive associations were found between all constructs and the intention to use online services, with younger age being the most significant factor. Conclusions: Use of and intentions to use eHealth services varied greatly. Participants were often unaware of the availability of services. Promoting the availability and benefits of eHealth services could enhance patient engagement in primary care settings.

For decades, there has been worry regarding phytic acid's function in lowering mineral bioavailability. Given its widespread prevalence in nuts, grains, legumes, and oilseeds, it is critical to revisit this topic in light of contemporary eating trends. The food pyramid advocates increased cereal and grain consumption as the foundation of a healthy diet. Phosphorus is also an important macro-mineral nutrient for chicken, as it promotes growth, bone formation, genomic function, high-quality flesh, and egg production. Imbalanced organic phosphorus sources in the diet can reduce phosphorus digestibility and increase environmental contamination. Moreover, phytic acid is an antinutritional molecule present in cereals and staple crops including wheat, maize, rice, and sorghum, which chelates P and important divalent cations like Fe and Ca and zinc. As a result, these cations cannot be absorbed by monogastric animals or humans, and phytic acid inhibits nutritional intake, with levels inversely related to protein and starch digestibility. The environmental impact of phytate, a common organic phosphorus molecule, is substantial. It can contribute nutrients to algae blooms in lakes, causing eutrophication. Furthermore, phytate's stability in complexation with metal ions might inhibit enzymatic hydrolysis, influencing its destiny in agricultural soils. In this paper, we summarize several approaches to addressing the challenges associated with phytic acid's interaction with the environment.

Fixed-time artificial insemination is an important technique in swine production that can improve reproductive efficiency and meat production quality by making better use of the genetic potential of breeding males and reducing the costs associated with double or multiple inseminations. Our goal was to evaluate the vaginal application of the GnRH agonist triptorelin acetate to synchronize post-weaning sows and facilitate implantation of a single fixed-time insemination. In a first experiment, the efficacy of treatment with the triptorelin in animals with or without signs of estrus was analyzed using a single insemination at a fixed time compared to the control following the standard insemination strategy. Farrowing rate was comparable between triptorelin and control groups (100 vs. 87.50%), but triptorelin without estrus had a lower rate (50%). Litter size did not differ between groups. Estradiol and progesterone levels at 96- and 120-hours post-weaning were similar in the control and triptorelin groups (P>0.05). These results suggest that Triptorelin has the potential to synchronize ovulation in pigs without affecting post-weaning hormonal profiles. In a second experiment, the objective was to evaluate the productive and economic impact of implementing a treatment with triptorelin acetate 96 hours after weaning compared to the standard insemination protocol. Sows were grouped according to treatment (control vs. triptorelin) and estrus onset (≤5 days and >5 days after weaning considered as late estrus). Farrowing rate was lower in the control late estrus group than in the control and triptorelin groups and similar to the triptorelin late estrus group. No differences were found for litter size, live or dead piglets born (P>0.05). We developed an estimation model to assess the cost/benefit of intravaginal triptorelin administration at 96 h post-weaning. The overall result is that the use of triptorelin increases the benefit per inseminated sow in the range of €15-20. This improvement is mainly related to an increase in the reproductive performance of the treated sows compared to the control sows and the reduction in the number of inseminations per sow. These results highlight the potential of triptorelin to optimize reproductive management in pigs, improving efficiency and economic viability.

Digital solutions in the field of restorative neurology offer significant assistance, enabling patients to engage in rehabilitation activities remotely. This research introduces ReMoVES, an Internet of Medical Things (IoMT) system delivering telemedicine services specifically tailored for Multiple Sclerosis rehabilitation, within the overarching framework of the STORMS project. The ReMoVES platform facilitates the provision of a rehabilitative exercise protocol, seamlessly integrated into the Individual Rehabilitation Project, curated by a multidimensional medical team operating remotely. This manuscript delves into the second phase of the study, elucidating the technology employed, the outcomes achieved, and the practical, professional, and academic implications. The STORMS initiative, as the genesis of digital telerehabilitation solutions, aims to enhance the quality of life for Multiple Sclerosis patients.

In this paper, we study facial expression recognition (FER) using three modalities obtained from the Light Field camera; sub-aperture (SA), depth map, and all-in-focus (AiF) images. Our objective is to construct a more comprehensive and effective FER system by investigating multimodal fusion strategies. For this purpose, we employ EfficientNetV2-S, pre-trained on AffectNet, as our primary convolutional neural network. This model, combined with a BiGRU, is used to process SA images. We evaluate various fusion techniques at both decision and feature levels to assess their effectiveness in enhancing FER accuracy. Our findings show that the model using SA images surpasses state-of-the-art performance, achieving 88.13% ± 7.42% accuracy under the subject-specific evaluation protocol and 91.88% ± 3.25% under the subject-independent evaluation protocol. These results highlight our model's potential in enhancing FER accuracy and robustness, outperforming existing methods. Furthermore, our multimodal fusion approach, integrating SA, AiF and depth images, demonstrates substantial improvements over unimodal models. The decision-level fusion strategy, particularly using average weights, proved most effective, achieving 90.13% ± 4.95% accuracy under the subject-specific evaluation protocol and 93.33% ± 4.92% under the subject-independent evaluation protocol. This approach leverages the complementary strengths of each modality, resulting in a more comprehensive and accurate FER system.

The objective of person re-identification (ReID) tasks is to match a specific individual across different times, locations, or camera viewpoints. The prevalent issue of occlusion in real-world scenarios affects image information, rendering the affected features unreliable. The difficulty and core challenge lie in how to effectively discern and extract visual features from human images under various complex conditions, including cluttered backgrounds, diverse postures, and the presence of occlusions. Some works have employed pose estimation or human keypoint detection to construct graph-structured information to counteract the effects of occlusions. However, this approach introduces new noise due to issues such as the invisibility of keypoints. Our proposed module, in contrast, does not require the use of additional feature extractors. Our module employs multi-scale graph attention for the reweighting of feature importance. This allows features to concentrate on areas genuinely pertinent to the re-identification task, thereby enhancing the model's robustness against occlusions. To address these problems, a model that employs multi-scale graph attention to re-weight the importance of features is proposed in this study, significantly enhancing the model’s robustness against occlusions. Our experimental results demonstrate that, compared to baseline models, the method proposed herein achieves a notable improvement in mAP on occluded data sets, with increases of 0.5%, 31.5%, and 12.3% in mAP scores.

Histological evidence of active prosthetic valve endocarditis (PVE) in cardiac valve tissue is widely regarded as a criterion established by Duke to confirm the presence of this condition, although the histological characteristics of mechanical prosthetic valve endocarditis have not yet been definitively established. The primary objective of this study was to determine the histologic differences in mechanical PVE in individuals with either early- or late-onset PVE, with the aim of distinguishing the unique aspects of this rare condition. Histological analysis of mechanical cardiac valve tissue was conducted in 27 patients who underwent surgical valve removal, comprising individuals with early onset and late-onset PVE. The findings were compared between the two groups. Histopathologically, PVE in individuals with mechanical heart valves is typically associated with the formation of vegetation and considerable neutrophil-rich infiltrates. In cases of early onset PVE, the affected valve tissue displays intense inflammation predominantly consisting of lymphocytes. In contrast, valve tissue samples from patients with late-onset PVE exhibit extensive fibrosis and inflammation, comprising macrophages, which are specialized immune cells and calcifications.

Garcinia indica (Thouars) Choisy (commonly known as Kokum) is an important medicinal plant in Ayurvedic medicine and belonging to the Clusiaceae family. Kokum is a highly traded medicinal plant species of India, dried rind of fruits and butter from seeds are traded in the markets. This study aimed to assemble the complete chloroplast (cp) genome of G. indica and compare it with the previously published cp genome within the Garcinia taxa to identify the potential species-specific barcode marker for Kokum authentication. The assembled cp genome, with a size of 1,56,891 bp, exhibits a typical quadripartite structure. The large single-copy (LSC) region spans 85,580 bp, and the small single-copy (SSC) region spans 17,181 bp, together comprising 64.5% of the genome. The pair of inverted repeats (IRA and IRB) are each 27,065 bp, covering the remaining 35.5% of the genome. A total of 126 unique genes were identified, including 86 protein-coding genes, 32 tRNA genes, and 8 rRNA genes. Phylogenetic analysis using complete cp genomes from 12 species in the Clusiaceae family indicated that 10 Garcinia species form a sister clade. Notably, the ycf1 gene in the LSC region was more divergent within the Garcinia species. This study presents the first report on the chloroplast genome of G. indica. This chloroplast genome resource provides a basis for identifying new DNA barcode marker as well as species-specific marker for herbal drug authentication of Kokum, and species delineation within the Garcinia genus.

In this work, the properties of a composition based on synthetic rubber ethylene-propylene ter-polymer and polymers with functional groups of the mixture are studied. Low efficiency of some compositions based on ethylene and propylene copolymer limits their use in the production of tires and rubber products. Therefore, we conducted a study to improve the disadvantages of SREPT-60 using butyl rubber + choro polyisoprene + butadiene-nitrile + butadiene styrene rubber and adding a plasticizer to the composition = α, methacrylate-(bis-diethylene glycol phthalate) -(btegf-9) The data obtained showed that a number of its indicators of rubber based on them were improved. Tear resistance, resistance to repeated stretching increased, adhesion of the composition to metal, chemical resistance increased, the degree of swelling in benzene and gasoline-benzene mixture decreased. Compositions based on the mixture SREPT-60 using butyl rubber + choro polyisoprene + butadiene-nitrile + butadiene styrene rubber and adding a plasticizer to the composition = α, methacrylate-(bis-diethylene glycol phthalate) -(btegf-9) +Dioctyl phthalate: (70:20:10) have high resistance to swelling in an aggressive environment (Benzene, gasoline, alcohol, acid, oil, etc.) mixture.