In this paper, we establish the existence and uniqueness results of the fractional Navier-Stokes evolution equation using the Banach fixed point theorem, where the fractional order β is in the form of the Atangana-Baleanu Caputo fractional order. The iterative method combined with the Laplace transform and Sumudu transform are employed to find the exact and approximate solutions of the fractional Navier-Stokes equation of a one-dimensional problem of unsteady flow of a viscous fluid in a tube. Mathematica software is used to present the solutions graphically.

It is documented that maternal diseases or treatments influence a newborn’s clinical status at birth; autoimmune diseases with circulating antibodies are often clinically expressed transiently in newborns due to the crossover of the specific IgG through the placenta during pregnancy. The offspring can inherit maternal genetic anomalies, but clinical expression usually becomes patent later in life. If prenatal medical history is not available or if signs or symptoms of a mother’s disease are revealed for the first time during pregnancy or postpartum, their effects on the newborn may be misattributed. In this article, we present three cases of pregnant women, without any known pathology before or during pregnancy, who gave birth to very sick preterm newborns that required admission to the Neonatal Intensive Care Unit (NICU). The neonates’ complications were considered initially as consequences of prematurity or infection, but later investigations revealed transient autoimmune disease in two of the cases (myasthenia gravis and hyperthyroidism) and a severe form of thrombophilia in the third case. In all cases, mothers were asymptomatic and unaware of their subclinical disease. Preemies’ diagnosis has contributed to the identification of their mothers’ pathology and adequate treatment was prescribed with favourable short- and long-term outcomes. In one of the cases (myasthenia gravis) both mother and child had associated infectious diseases in the perinatal period that complicated the clinical picture and created problems of diagnosis. This article intends to emphasize the paramount importance of prenatal care, for both mother and newborn. Repeated medical visits and investigations throughout the pregnancy are a good opportunity to detect subclinical diseases or predispositions. As newborns usually develop non-specific signs, one should have experience and pay attention to differentiate among etiologies. Our paper takes a reversed approach to the usual medical diagnosis pathway: from infant to mother instead of mother towards the infant, proving that inter-speciality collaboration can work bi-directionally.

Leishmaniasis, comprising cutaneous and mucocutaneous forms, is a parasitic disease caused by Leishmania species via sandfly bites, leading to skin ulcers and mucosal damage. Traditional treatments include antiparasitic drugs such as pentavalent antimonials, amphotericin B, and miltefosine, with immunotherapy and chemotherapy being explored for enhanced efficacy and reduced relapse. Mucocutaneous leishmaniasis (ML) balances IFN-γ and IL-10, affecting severity, while cutaneous leishmaniasis (CL) shows varied IFN-γ/IL-10 ratios influencing prognosis. Cytokines and chemokines are diagnostic and prognostic markers in CL. Research into neutrophils and the NLRP3 inflammasome informs Th1/Th2 response regulation. Live attenuated LdCen-/- parasites and genetically modified vaccines show promise, with miR-21 as a potential efficacy biomarker. Understanding cytokine networks is crucial for new treatment strategies.

The study examines the survival status of Scapharca broughtonii and Scallop Chlamys farreri under diverse seasons, sizes, and mixed breeding ratios. The objective is to explore the feasibility and economic benefits of the mixed breeding patterns of different shellfish varieties. The findings demonstrate that the overwintering mortality rate of mixed-cultured S.broughtonii ranges from 12.04% to 16.85%, which is conspicuously lower than that of individually cultured S.broughtonii. The summer mortality rate of mixed-cultured S.broughtonii with a size of 2.5 - 4.0 cm is significantly lower than that of individually cultured S.broughtonii (P < 0.05). There is no notable difference in the mortality between monoculture and polyculture of C.farreri. There is no significant disparity in the growth of C.farreri and S.broughtonii in monoculture and polyculture. The optimal polyculture size of the two scallops is 2.5 cm, and the ideal polyculture ratio is 1:1. The co-culture model of S.broughtonii and C.farreri in suspension cages has a high input-output ratio (1:1.9). It can effectively lower the winter and summer mortality rates of ark clams, representing an efficacious new methodology for marine shellfish farming.

Changing the symmetry of spin from SU(2) to the quaternion group, $Q_8$, has a number of ramifications. In this paper we first summarize the properties of Q-spin and then discuss some of those resulting changes. Many are counter to well-established ideas which change our view of the microscopic.

Selection is a fundamental interaction element in Virtual Reality (VR) and 3D user interfaces (UIs). Raycasting, one of the most common object selection techniques, has been known to have difficulties in selecting small or distant objects. Meanwhile, recent advancements in computer vision technology have enabled seamless vision-based hand tracking in consumer VR headsets, enhancing accessibility to freehand mid-air interaction and highlighting the need for further research in this area. This study proposed a new technique called TouchView which utilizes a virtual panel with a modern adaptation of the Through-the-lens metaphor to improve freehand selection for VR UI. TouchView enables faster and less demanding target selection by allowing direct touch interaction with the magnified object proxies reflected on the panel view. Repeated-measures ANOVA on the results of a follow-up user experiment on multitarget selection with 23 participants showed that TouchView outperformed the current market-dominating freehand raycasting technique, Hybrid Ray in terms of task performance, perceived workload, and preference. The user behavior was also analyzed to understand the underlying reasons for these improvements. The proposed technique can be used in VR UI applications to enhance the selection of distant objects, especially for cases with frequent view shifts.

Abstract: Conventional antibiotic and multidrug treatments become less and less effective and a discovery of new effective and safe antibacterial agents got a global priority. The returning to the natural antibacterial product is relatively new current trend. Terrestrial biota is a rich source of biologically active substances whose antibacterial potential was not fully utilized. Aim of this review is to present the current state-of-the art of terrestrial biota-derived antibacterial agents and inspired by nature treatments. It is a summary of the most important sources and new identified or modified antibacterial agents and treatments during the last 5 years. It focuses on the significance of plants- animals- and bacteria-derived biologically active agents as powerful alternatives to antibiotics as well as on the advantages of utilizing natural antibacterial molecules alone or in combinations with antibiotics. The main conclusion is that the terrestrial biota derived antibacterial products and substances open variety of new ways to modern improved therapeutic strategies. New terrestrial sources of known antibacterial agents and new antibacterial agents from terrestrial biota were discovered during the last 5 years, which are under investigation together with some long ago known but now surviving their renaissance for the development of new medical treatments. Use of natural antibacterial peptides as well as combinational therapy by commercial antibiotics and natural products outlines as the most promising for treating of bacterial infections. In vivo testing and clinical trials are necessary to reach clinical application.

Based on the land use data of Qingmei Harbor Mangrove Nature Reserve in Sanya, China, in 2009, 2015 and 2022, this paper utilizes the PLUS model to predict the land use changes in the region in 2035 under three development scenarios, namely natural development, urban construction and ecological protection. The results of the study show that the area of building land in this region increased rapidly from 2009-2015, and the corresponding cropland, parkland and arbor forest land as a whole showed a different degree of decline, while the expansion of the area of manmade land, such as building land, basically came to a standstill after 2015. However, the mangrove area in this region has maintained a stable growth trend from 2009-2022. The results of multi-scenario modeling of land in this region showed that the area of building land, unutilized land, and artificial land such as parkland and grassland increased the most under the urban development scenario. In the ecological protection scenario, the area of ecological land, such as arbor forest land and river and lagoon, increases significantly. However, there is no significant increase in the area of mangrove forests under any of the three development scenarios. At present, the task of “returning ponds to wetlands” has been basically completed in this area, and the space for large-scale expansion of mangrove forests in Qingmei Harbor is limited in the future, and the focus of subsequent work should be shifted to the enhancement of the quality and function of mangrove ecosystems.

HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP) is a chronic progressive neurological disorder and shares many radiological and clinical features with other more prevalent myelopathies. Here, we quantified spinal cord and brain volumes in adults with HAM/TSP in comparison with healthy volunteers (HVs) and participants diagnosed with multiple sclerosis (MS). Clinical disability and MRI were assessed in 24 HVs, 43 HAM/TSP, and 46 MS participants. Spinal cord cross-sectional area (SCCSA) and brain tissue volumes were measured and compared. HAM/TSP participants had significantly lower SCCSA at C2-3 (54.0±8 mm2), C4-5 (57.8±8 mm2), and T4-9 (22.7±4 mm2) and significantly elevated brain white matter hyperintensity (WMH) fraction (0.004±0.008) was compared to HVs (C2-3: 69.4±8 mm2, C4-5: 75.1±9 mm2, T4-9: 34.1±4 mm2; all p &lt; 0.0001; and WMH: 0.0004±0.0007; p &lt; 0.001). In HAM/TSP, SCCSA at all levels but not WMH showed the significant correlation with clinical disability scores. Brain white matter hyperintensities in HAM/TSP, therefore, may not be related to clinical disability. SCCSA and WMH in our limited MS cohort were higher than the HAM/TSP cohort (67.6±8 mm2, 72.7±9 mm2, 33.4±5 mm2; p &lt; 0.0001). Principal component analysis suggested that SCCSA and WMH may be used to differentiated HAM/TSP from MS. Understanding these differences may help establish early diagnostic criteria for HAM/TSP patients.

In order to enhance the efficiency and combined performances of nitriding layer, aluminum-modified plasma nitriding (Al-PN) was developed in this research by adding some FeAl particles around the samples during plasma nitriding (PN) for 42CrMo steel. The results show that the efficiency is dramatically enhanced almost 6 times comparing with traditional PN, with the effective hardening layer increasing from 224 μm to 1246 μm at 520℃/4h. More importantly, the compound layer increased just a little bit from 11.64 μm to 14.32 μm, which remarkably reduces the ratio of the compound layer thickness to effective hardening layer thickness, thus being quite beneficial to decrease the brittleness level, making the brittleness level decreasing from Level 4 to Level 1. Meanwhile, ultra-high surface hardness and excellent wear behaviors are obtained by aluminum-modified plasma nitriding (Al-PN) due to the formation of dispersed strengthening phased of AlN and FexAl in the nitriding layer, with the surface hardness increasing from 755 HV0.025 to 1251 HV0.025, wear rate decreasing from 8.15 x10-5g N-1 m-1 to 4.07 x10-5g N-1 m-1. In other words, comparing with PN, the wear resistance has been almost doubled by Al-PN. Therefore, the research can provide comprehensive insights into the surface characteristics and combined performances of the aluminum-modified plasma nitriding layer.

Climate change presents an urgent global challenge, manifesting in rising temperatures and extreme weather events with severe societal impacts. The Eastern Mediterranean, warming faster than the global average, faces immediate repercussions. Climate literacy emerges as pivotal, empowering individuals to comprehend climate science and act accordingly. This study delves into climate literacy, attitudes, and 'greening' behaviours in the Eastern Mediterranean hotspot of Greece, based on a survey of 1,962 citizens. Findings indicate high climate literacy but lower adoption of 'greening' behaviours, especially those involving financial costs. Regression analyses highlight the significant role of climate literacy, concerns about personal impacts, coping appraisal and trust in institutions in promoting 'greening' behaviours. The study underscores the need for multifaceted strategies emphasizing financial motivation, trust-building, and societal norm shifts. Socio-demographic disparities, including gender and occupation, highlight areas for targeted interventions. The emphasis on the mental health impacts of climate-related events underscores the need for holistic disaster management. Policy implications are discussed, highlighting the potential of expanded climate literacy to catalyze collective action toward sustainability.

Trematode infections cause long-term suffering and debilitation, posing a significant threat to global animal health and production and leading to considerable economic losses. Studies on the epidemiology and control of these infections in Tanzania are limited, and most have been conducted in abattoir settings. The study aims to fill the knowledge gap by determining the prevalence, distribution, and risk factors for trematode infections in domesticated ruminants in two ecological zones of Tanzania. A cross-sectional study was conducted in Lake Victoria and the southern highlands of Tanzania. Rectal fecal samples were collected and examined for Fasciola spp., paramphistomes, and schistosome infections using the sedimentation technique. A total of 1367 domesticated ruminants were sampled and examined for trematode infections. Prevalence of trematode infections was found to be 65.7%. The individual frequency of F. gigantica, paramphistomes, and S. bovis (based on egg morphology only,) was 35.1%, 60.2% and 3.1%, respectively. Adult cattle were more likely to be infected with paramphistomes (AOR: 1.98; 95% CI: 1.40-2.78) and S. bovis (AOR: 8.5; 95% CI: 1.12–64.19) than weaners. It was found that trematode infections in domesticated ruminants are prevalent across Tanzania, therefore effective and community-acceptable prevention and control strategies are highly needed.

Considering animal welfare, the free-range laying hen farming model is increasingly gaining attention. However, in some countries, large-scale farming still relies on the cage-rearing model, making the focus on the welfare of caged laying hens equally important. To evaluate the health status of caged laying hens, a dataset comprising visible light and thermal infrared images was established for analyses, including morphological, thermographic, comb, and behavioural as-sessments, enabling a comprehensive evaluation of the hens' health, behaviour, and population counts. To address the issue of insufficient data samples in the health detection process for indi-vidual and group hens, a dataset named BClayinghens was constructed containing 61,133 images of visible light and thermal infrared images. The BClayinghens dataset was completed using three types of devices: smartphones, visible light cameras, and infrared thermal cameras. All thermal infrared images correspond to visible light images and have achieved positional alignment through coordinate correction. Additionally, the visible light images were annotated with chicken head labels, obtaining 63,693 chicken head labels, which can be directly used for training deep learning models for chicken head object detection and combined with corresponding thermal infrared data to analyze the temperature of the chicken heads. To enable the constructed deep-learning object detection and recognition models to adapt to different breeding environ-ments, various data enhancement methods such as rotation, shearing, colour enhancement, and noise addition were used for image processing. The BClayinghens dataset is important for ap-plying visible light images and corresponding thermal infrared images in the health detection, behavioural analysis, and counting of caged laying hens under large-scale farming.

Continuous-flow microwave heating stands out for its ability to rapidly and uniformly heat substances, making it widely applicable in chemical production. However, in practical applications, the permittivity of the heated liquid changes dramatically as the reaction progresses, affecting the efficiency and uniformity of continuous-flow heating. Herein, this work presents a novel microwave heating device based on coaxial structure for high-performance heating. Our approach commenced with the development of a multi-physical field model, incorporating a spiral polytetrafluoroethylene (PTFE) as a water channel and the coaxial waveguide as a container was established. The analysis shows that the uniform distribution of the sectional electric field of electromagnetic waves in the TEM mode within the coaxial structure can enhance heating uniformity. Then, a continuous-flow microwave heating system for different liquid loads was established, and experimental measurements were conducted. The heating efficiency for all loads exceeded 90%, which basely matched the simulation results, validating the accuracy of the model. Finally, the heating efficiency and uniformity under different permittivity loads were analyzed, as well as the impact of channel radius on heating efficiency. The device demonstrated high heating efficiency and stable heating uniformity across different loads. This continuous-flow microwave device is suitable for chemical research and production, contributing to the promotion of microwave energy applications in the chemical industry.

Molecular scattering (Rayleigh scattering) has been extensively utilized from the ground with lidars and from space to observe the limb, thereby deriving vertical temperature profiles between 30 and 80 km. In this study, we explore how temperature can be measured using the new Ozone Mapping and Profiler Suite (OMPS) sensor, aboard the Suomi NPP and NOAA-21 satellites. OMPS comprises three instruments primarily tasked with studying the composition of the stratosphere. Among them, the Limb Profiler (LP) measures the radiance of the middle atmosphere's limb (stratosphere and mesosphere, 12 to 90 km altitude) across wavelengths from 290 to 1020 nm. This new dataset has been leveraged to derive temperature profiles with a vertical resolution of 1 km. To validate the method, the OMPS-derived temperature profiles were compared with data from four ground-based lidars, the ERA5 and MSIS models, and MLS at the lidar locations. The results indicate that OMPS and the lidars agree within a margin of approximately 5 K from 30 to 80 km. Comparisons with the models also show similar results, except for ERA5 beyond 50 km. Comparisons with MLS exhibit slightly higher deviations than those with the lidars. We investigated various bias sources, such as different attenuation sources that can generate errors up to 120 K in the UV range, while instrumental errors are around 0.8 K, and noise issues can cause errors up to 150 K in the visible range for OMPS. This study also highlighted the interest in developing a new miniaturized instrument that could meet real-time observation of atmospheric vertical temperature profiles using a constellation of CubeSats.

With advancements in remote sensing technology and affordable design, uncrewed aerial systems (UAS), commonly known as drones, have become prevalent in both civil and military applications, such as agriculture, public safety, and aerial imaging. However, the rise in unlawful UAS activities, such as non-compliance with legal standards and potential terrorist attacks, has raised significant public concern, necessitating effective detection and mitigation solutions. Despite the growing importance of this issue, comprehensive and detailed examinations of existing counter-UAS solutions are lacking. To address this gap, this study conducts a bibliometric analysis and scoping review of the current literature to identify key topics and emerging trends in counter-UAS approaches. Utilizing co-word and social network analyses, the study identifies strong and weak connections between selected keywords from academic articles. This study summarizes the limitations and potential opportunities within counter-UAS research, suggesting an increasing focus on multisensory fusion and machine-learning approaches for drone detection and mitigation. Additionally, areas such as swarm drone operations, UAS traffic management (UTM), and UAS networks are identified as important but promising fields for further investigation. The findings of this study provide a foundation for enhancing air and ground safety through improved counter-UAS applications.

One of the main challenges associated with spatial entities affected by potentially irreversible adverse development processes (depopulation and related changes in the population structure, economic difficulties, declining accessibility and quality of services, etc.) is coping with their consequences – taking a planned approach (as opposed to passive observation of spontaneous developments) towards mitigating adverse effects on the quality of life of the local population. Public services (healthcare, education, culture, etc.), as a fundamental human need in modern society, but also a warranty of a certain level of living quality, are particularly important in such areas. Apparently, it is necessary to accept the closing of a number of facilities as a reality, and to take a planned approach seeking to mitigate the negative effects on the life of the local population. This is a context of our research, where these services are taken as a universal human right and striving for their equitable availability as a goal of national spatial development policies. The starting point in our analysis of this issue observed through the lens of the Serbian national legal and planning framework is the spatial plan of a local self-government unit as the basic platform for defining and operationalising spatial development policies at the local level. It has been examined whether it would be possible to use the mathematical modelling of optimal spatial solutions as support in making decisions that would minimise the negative effects of the closure of a number of public service facilities. The results for the selected research area and the network of primary healthcare facilities show that it is possible to stabilise the accessibility of these facilities by modelling the spatial organisation of primary healthcare despite the expected closure of as much as one-third of the facilities, while any other solution would give more or less unfavourable results.

In the presented work, on the example of thin-walled specimens made by selective laser melting technology from AlSi10Mg subjected to preliminary heat treatment, it is shown that there is a critical point of transition from the elastic-plastic region of the engineering stress-strain diagram to the yield and fracture stresses. It was found that the critical point has a strong statistically significant correlation (0.83 by Spearman and 0.93 by Pearson) with the strain hardening coeffi-cient calculated in the section from yield strength to fracture strength. A regression equation linking the critical transition point to the strain hardening coefficient was obtained. It is shown that with increasing plasticity of thin-walled samples obtained by selective laser melting of AlSi10Mg leads to a change in the type of stress distribution in the elastic-plastic region (the Weibull distribution changes to a normal distribution) and the contribution of the probability density of stress distribution described by the Cauchy distribution with a mode near the fracture stress to the full probability density of fracture increases.

As computer networks develop in size and complexity, the need for equipment that can characterize, inspect, monitor, and summarize the features of a transmission in real time grows. Many transmission and packet inspection theories are required to examine network traffic. Unfortunately, loss the track or traceability of one traffic scenarios against others over real-time network. Deep packet inspection (DPI) approaches can be used to alleviate the problem but still face flexibility constraints in the sense that it will be difficult to keep track of prior occurrences. There have been significant theoretical improvements in packet inspection, but the problem of event tracking flexibility remains unsolved. A novel approach for “integrating blockchain with DPI” in summarizing computer network traffic flow events has emerged as a result of this research: This technique captured traffic flows in the network, DPI report, and the entire transmission session header and load them into a smart-contract based- Blockchain. Two experimental scenarios are used to test the validity of the system. The first scenarios involve analysis of DPI transmission without integrating blockchain, follow by the captured of transmission session involving DPI with blockchain. The finding indicates that DPI transmission with blockchain is more secured against "Tampering Incidents", "Unauthorized Access Attempts", “Auditability” and many other security concern. Whereas, the performance overhead introduced by blockchain-based DPI indicate an increase in "DPI Processing Time from 68ms to 150ms, a "CPU Usage increment by 20%, Network Latency increment of 15ms from 20ms to 35ms, and almost all other computational resources increase. Therefore, the finding can be summarized that the performance overhead introduced by integrating blockchain with DPI increases, but it provides a secure DPI reports for decision making.

This study aimed to analyze the population dynamics of the mite Varroa destructor in honey bee (Apis mellifera) colonies in a temperate semi-arid climate in Mexico. Ten colonies homogeneous in population, food stores, and levels of mite infestation, were used. The mite infestation rate in brood and adult bees, total number of mites, daily mite fall, brood and adult bee population, and food stores, were determined periodically for 10 months. There was a significant effect (P &lt;0.05) of sampling period on the population of V. destructor in adult bees, brood, total mite population, and daily fallen mites. The total mite population increased 26% on average per colony. The increase in brood amount reduced the mite infestation rate in adult bees, and the opposite occurred when the brood decreased. Monitoring V. destructor populations by recording fallen mites is more reliable than determining mite infestation rates in bees, as mite fall has a dynamic pattern similar to that of the total mite population. The best period to apply an acaricide treatment in the region of study is between November and December because most mites were in the phoretic phase, since there was less brood in the colonies compared to other times.

Ground level ozone is an abiotic stress estimated to reduce mean global annual wheat yields by nearly 10%. This study in solardomes exposed an elite cultivar, and multiple lines of synthetic wheat (primary and F2) to four levels of ozone (30 ppb, 55 ppb, 80 ppb, 110 ppb) for three months, with two lines (cv Paragon and an F2 line, BC1) selected for X-ray microcomputed tomography. The uCT imaging revealed ozone’s effect on individual grain formation, both spatially within the spike and on grain shape. Reductions in grain number occurred primarily across the middle of the spike. Grain volume reductions were driven more by reduced width and depth than reduced length. Based on yield data, both lines demonstrated relative tolerance to ozone. Links between ozone’s effects on grain morphology and grain quality are also explored. These data provide information that could be utilised in wheat breeding programmes to increase tolerance to ozone of this staple food crop.

Canine influenza virus (CIV) H3N2 causes a highly contagious respiratory disease in dogs and has been the source of outbreaks across North America since 2015. An injectable RNA Particle (RP)-CIV H3N2 vaccine has been developed to protect dogs against this disease. To demonstrate efficacy, dogs were randomized into two treatment groups, then vaccinated subcutaneously twice, 21 days apart, with a placebo vaccine (n = 20) or a RP-CIV H3N2 vaccine (n = 20). Three weeks later, dogs were challenged intranasally with virulent CIV H3N2 and observed daily for 10 days for clinical signs of disease. Nasal swabs were also collected daily to evaluate shedding of the challenge virus. Ten days post-challenge, dogs were euthanized, and the lungs were examined for consolidation. RP-CIV H3N2 vaccination demonstrated a significant reduction in duration of clinical signs, duration and amount of virus shed, lung consolidation, and the incidence of suppurative pneumonia. To evaluate safety, dogs from multiple geographic regions were vaccinated subcutaneously, 3-4 weeks apart, with a RP-CIV H3N2 vaccine and observed for adverse events for 14 days after each administration. The RP-CIV H3N2 vaccine was deemed safe, with lethargy being the most reported adverse event at a rate of 1.6%.

Background: We investigated the significance of the para-aortic node (PALN) and other regional node metastases (RLN), reflecting malignant histological findings or poor patient prognosis, in patients with biliary duct cancers (BDC) and pancreatic carcinomas (PC) who underwent radical resections at two institutes. Methods: Conventional clinicopathological factors, including metastasis to the PALN and RLN, and surgical outcomes or long-term prognosis in 181 PC and 116 BDC patients between 1994 and 2022 were examined. Results: In patients with PC, cancer metastasis was observed in the RLN and PALN in 54% and 9% of patients, respectively. In patients with BDC, cancer metastasis was observed in the RLN and PALN in 39% and 9% of patients, respectively. Disease-free survival (DFS) and overall survival (OS) in patients with BDC and PALN metastasis were significantly lower than those without PALN metastasis; however, several patients survived over three years. Multivariate analysis revealed that, in patients with BDC, PALN metastasis was an independently related factor of OS, and RLN was an independently related factor for DFS, respectively (p

Smart agriculture is a new way of farming that uses advanced technology. It makes a significant contribution to improving the efficiency and productivity of farming practices. Systems that use drones to monitor pests and spray pesticides greatly reduce the burden on farmers. In addition, remote sensing technology facilitates the monitoring of crop growth conditions and the early detection of diseases and pests. However, the high cost of equipment to communicate sensor data is preventing farmers from adopting sensing systems. As a result, many studies have been conducted to make the sensing system available at a low cost. Nevertheless, many farmers have not yet adopted them. Therefore, this paper proposes an agricultural sensor network system using drones and optical camera communication (OCC). The proposed system aims to achieve high-density farm sensing at low cost. The proposed system uses OCC as the communication method for sensor data. Low cost light sources such as LED panels can be used as transmitters. In addition, existing agricultural drones equipped with cameras can be used as receivers. We also propose a trajectory control algorithm for the receiving drone to efficiently collect the sensor data. The proposed system is suitable for deploying sensor networks in areas with underdeveloped infrastructure and radio silence. In this paper, we conducted a preliminary experiment at a leaf mustard farm in Kamitonda-cho, Wakayama to demonstrate the effectiveness of the proposed system using a Mavic 2 Pro drone, launched by DJI Co., Ltd.

The interaction of poly(trimethylene carbonate) (PTMC) with alcohols were investigated as a model for polymer blending with polysaccharides. While 1-butanol, 2-butanol, ethylene glycol, 1,2-cyclohexanediol showed almost no detectable interaction with PTMC at both of solution state with 1H NMR and solid states of FT-IR, glucose and cellobiose suggests slight change of spectral pattern in FT-IR analysis. The thermal properties of the blending samples of PTMC and these alcohols were also investigated. Although the blend of PTMC with 1-butanol, 2-butanol, and ethylene glycol did not influence on thermal degradation behaviors due to the low boiling points to maintain the structure at blend sample preparation, however, the blend with PTMC and glucose or cellobiose tend to increase thermal resistances and increase glass transition temperature, hence, showed an existence of interaction through hydrogen bonding.

We developed a protein to rapidly and accurately diagnose Chagas disease, a life-threatening illness identified by the WHO as a critical worldwide public health risk. Complicating the current health situation are serological test limitations that contribute to most infected persons being unaware of their condition and therefore untreated. To improve diagnostic testing, we developed an immunological mimic of the etiological agent, Trypanosoma cruzi, by combining ten pathogen specific epitopes within the beta-barrel protein structure of Thermal Green Protein. The resulting multi-epitope protein, DxCruziV3, displayed high specificity and sensitivity as the antibody capture reagent in an ELISA platform with an analytical sensitivity that exceeds WHO recommendations. Within an immunochromatographic platform, DxCruziV3 showed excellent performance for the point of application diagnosis in a region endemic for multiple diseases, the municipality of Barcelos in the state of Amazonas, Brazil. In total, 167 individuals were rapidly tested using whole blood from a finger stick. As recommended by the Brazilian Ministry of Health, venous blood samples were laboratory tested by conventional assays for comparison. Test results suggest utilizing DxCruziV3 in different assay platforms can confidently diagnosis chronic infections by T. cruzi. Rapid and more accurate results will benefit everyone but will have the most noticeable impact in resource-limited rural areas where the disease is endemic.

Quantum observers, agents whose entanglement with a measured system may remain coherent, are analyzed in a consistent approach. Thought experiments, including one by Deutsch and one by Frauchiger and Renner, are discussed and modeled using quantum circuits. Terminology is suggested which helps avoid contradictions.

The adoption of an entrepreneurial mindset within the lenses of green entrepreneurship contributes to negotiating a transdisciplinary and multidisciplinary approach by intertwining industrial psychology and industrial engineering through [system dynamics] which forms part of the paper's focus. The methodology used in this study is a system dynamics methodology using data readily available online with a focus on quantitative methodology. This study's dynamic variable and the causal loop are formulated using the Euler mathematical equation with support from the Vensim modelling software (academic purposes license). Results and variables simulated in the current study are entrepreneurial mindsets [through subfield of education, values, intentions and gender representation] contribution and the conclusion is explained towards the end of the paper.

The present study aimed to undertake a detailed investigation of pathological epidemiology and molecular confirmation of Ehrlichia canis among pet dogs in smart city Bhubaneswar, Odisha, a state in eastern India. A total of 178 dogs were screened for Ehrlichiosis on the basis of history, clinical signs, blood, and buffy coat smear examination, resulting in only 56 dogs (31.46%) screening positive. The epidemiological study recorded an increase in incidences among dogs less than one year of age (41%), males (68%), German Shepherds (25%), dogs more than 20 kg body weight (75%), summer months (55%) and dogs housed on pukka houses with exposure to the outside (59%). The majority of the infected dogs had a history of tick infestation (79%) at some point in their life. Clinical signs showed non-typical manifestations like fever, lethargy, diarrhoea, epistaxis, hind limb edema, and corneal opacity. Haematological studies revealed anaemia and thrombocytopenia along with neutrophilia with relative lymphopenia and monocytosis. A decreasing trend was observed in the levels of total protein and albumin with an increase in the levels of globulin, AST, ALT, BUN, and creatinine. The ultrasonography studies revealed hepatosplenomegaly along with hyper-echogenicity in various organs. Pro-teinuria and haematuria were consistent, along with the presence of bile salts in the urine of affected dogs. Molecular confirmation from n-type PCR data using Ehrlichia-specific primers targeting p28 gene (843 bp) was done, and the identified gene sequences submitted to NCBI databases have accession numbers OQ383671-OQ383674 and OP886674-OP886677. Ticks collected from dogs were identified morphologically through microscopy and scanning electron microscopy as Rhipicephalus sanguineus.

Croton grewioides Baill., a species native to the Caatinga, popularly known as canela de cunhã, is used in traditional medicine to treat gastrointestinal diseases such as diarrhea, gastritis and stomach ulcers. This study aimed to identify the chemical composition of the essential oil of C. grewioides (OECG) and evaluate its antibacterial and antibiotic-modulating activities against both standard and multidrug-resistant bacteria. To analyze the compounds, present in the oil, gas chromatography coupled with mass spectrometry (GC/MS) and gas chromatography with flame ionization detector (GC/FID) techniques were used. In the bacteriological tests, the Minimum Inhibitory Concentration (MIC) was obtained using the broth microdilution technique. The modulating effect of the essential oil was determined by calculating the subinhibitory concentration followed by serial microdilution of the antibiotics. The MIC reduction factor (FRC) was calculated and its data expressed as a percentage. Analysis of the chemical composition identified the presence of the major compound estragole with a relative abundance of 50.34%. The MIC values obtained demonstrated efficacy in K. pneumoniae isolated from urine with MIC values of 512 µg/mL. OECG potentiated the effects of all antibiotics tested on S. aureus ATCC 29213, K. pneumoniae Carbapnemase, E. coli ATCC 25922 and S. aureus ATCC 29213 strains with their FRC of 97.65 %, 99.80 %, 99.85 % and 99.88 %, respectively. Thus, the essential oil of C. growioides presents synergistic effects when combined with the tested antibiotics, in addition to acting in the fight against bacterial resistance to antibiotics.

With the rapid development of electric vehicles, the infrastructure for charging stations is also expanding quickly, and the failure rate of charging piles is increasing. To address the effective operation and maintenance of charging stations, a method based on the XGBoost algorithm for electric vehicle DC charging stations is proposed. An operation and maintenance system is con-structed based on state analysis, considering the operation status of the charging station and users' charging habits. Factors such as driving and charging habits, road traffic, and charging station equipment are taken into account. The training sample data is established using historical data, online monitoring data, and external environmental data, and the charging station status evaluation model is trained using the XGBoost algorithm. Based on the condition assessment results, a risk assessment model is established in combination with fault parameters. Risk tracking of the charging station is conducted using the lack of power supply (ENC), evaluating the risk level of each station, and determining the operation and maintenance order. The optimal opera-tion and maintenance model for DC charging stations, aimed at achieving both economic and reliable goals, is constructed to determine the operation and maintenance schedule for each sta-tion. The results of the case study demonstrate that the state evaluation and operation and maintenance strategy can significantly improve the reliability of the system and the overall ben-efits of operation and maintenance while meeting the required standards.

Somatic cell nuclear transfer (SCNT) has great potential in the replication of high commercial value animals, threatened wild species for conservation purposes, and transgenic animals for biomedical purposes. However, SCNT has a low success rate, due to intrinsic factors of the technique itself, which will lead to low rates of embryonic development and epigenetic alterations in the cloned embryos. The objective of the present study was to evaluate the effect of OF-UF on the intracellular concentration of ROS, GSH, and the development of Ovis aries cloned and parthenogenetic embryos. The results did not show a beneficial effect on the development of parthenogenetic and cloned embryos at concentrations of 0.5% OF-UF. Furthermore, at 1% OF-UF, an adverse effect was observed in cloned embryos at the blastocyst stage and 2% OF and UF in parthenogenetic embryos in the first divisions. A decrease in ROS and GSH levels was observed in the parthenogenetic blastocysts treated with 1% OF-UF, but not in the clones, in which a higher concentration of GSH and a similar concentration of ROS was observed. No effect was observed of OF-UF on embryonic development and redox balance on sheep clone embryos by Handmade Cloning.

Backscatter communication, which transmits information by passively reflecting radio 1 frequency (RF) signals, has become a focal point of interest due to its potential to significantly enhance 2 the energy efficiency of Wireless Power Mobile Edge Computing (WPMEC) networks and extend the 3 operational lifespan of terminal devices. However, there is little research on the integration of user 4 cooperation in WPMEC scenarios within volatile network environments. In this paper, we propose 5 a dynamic task offloading scheme for a Backscatter-assisted WPMEC system, which involves two 6 mobile devices (MDs) and a Hybrid Access Point (HAP) with user cooperation. We formulate the 7 energy efficiency (EE) maximization problem as a stochastic programming problem, considering 8 the randomness of task arrivals and time-varying wireless channels. By leveraging Dinkelbach’s 9 method and stochastic network optimization technique, we transform the problem into a series of 10 deterministic sub-problems for each time slot, and convert the non-convex sub-problem into convex 11 ones. We propose a low-complex EE maximization algorithm to solve the convex problems efficiently. 12 Extensive simulations are conducted to validate the performance of our algorithm under various 13 system parameter settings. Experiment results demonstrate that our algorithm not only outperforms 14 the benchmark algorithms by approximately 23%, but also stabilize all queues within the MEC 15 system.

Background: The new therapeutic modality incorporating countermeasure against the most plausible environmental factor in inflammatory bowel disease, i.e., a plant-based diet, showed far better outcomes than current standards in inflammatory bowel disease. Infliximab is widely used for induction and subsequent scheduled maintenance therapy in patients with inflammatory bowel disease. However, the efficacy of infliximab diminishes over time. Objectives: To investigate the durability of scheduled infliximab maintenance therapy incorporating plant-based diet in inflammatory bowel disease. Methods: This was a prospective single-group trial at tertiary hospitals. Infliximab maintenance therapy was indicated in patients with severe or unresponsive to conventional therapy. Infliximab (5 mg/kg body weight) was infused every 8 weeks on an inpatient basis, and plant-based diet, a lacto-ovo-vegetarian diet, was served three or four times during hospitalization. Durability was assessed using the Kaplan-Meier method. Results: Twenty-four patients (16 with Crohn’s disease, eight with ulcerative colitis) were included: median age 27.5 years old, disease duration 53.5 months, and concomitant use of immunosuppressant 21%. Intensification of infliximab was employed in 46% of patients. There was no significant difference in durability rates between Crohn’s disease and ulcerative colitis. Durability rates were 87% at both 5 and 10 years. Plant-based diet score in the median follow-up period of 9.3 years, which indicates adherence to the plant-based diet, was significantly higher than the baseline score. Conclusions: Infliximab maintenance therapy incorporating plant-based diet yielded a high durability rate of 87% at 5 years in patients with Inflammatory bowel disease

Manual handling is a major risk factor for work-related musculoskeletal disorders and one of the leading causes of disability-adjusted life years globally, necessitating multifaceted risk reduction measures. One potential intervention for manual handling tasks is work technique training assisted by augmented feedback on biomechanical exposures. However, there is a research gap regarding its effectiveness specifically for manual handling tasks in both real work environments and controlled settings, as well as its ability to induce retained reductions in biomechanical exposure. The gap was investigated using a rapid review comprising a literature search using two databases and 11 reviews/overviews to identify studies from the past 20 years, up to studies published by June 1, 2024. Sixteen studies were identified, with 14 of them being of high or moderate methodological quality and were included. Three studies were conducted in real work environments and eleven in controlled settings. Most studies (n = 9) used auditory feedback, followed by vibration feedback (n = 6). In real work environments, the evidence for the effectiveness of sensor-based augmented feedback in reducing biomechanical exposure during administration was considered to be inconsistent and very limited directly after administration. For longer periods after administration, ranging from one week to more than six months, there is currently no evidence demonstrating the effectiveness of the feedback. In controlled settings, there was strong evidence for its effectiveness during and immediately after administration, and limited evidence for effectiveness up to six months post-administration when considering the tasks included in the training. Future research needs are discussed.

The investigation of exoplanetary habitability is integral to advancing our knowledge of extraterrestrial life potential and detailing the environmental conditions of distant worlds. In this analysis, we explore the properties of exoplanets situated with respect to circumstellar habitable zones by implementing a sophisticated filtering methodology on data from the NASA Exoplanet Archive. This research encompasses a thorough examination of 5,595 confirmed exoplanets listed in the Archive as of March 10th, 2024, systematically evaluated according to their calculated surface temperatures and stellar classifications of their host stars, taking into account the biases implicit in the methodologies used for their discovery. Our findings elucidate distinctive patterns in exoplanetary attributes, which are significantly shaped by the spectral classifications and mass of the host stars. The insights garnered from our study not only enhance the existing models for managing burgeoning exoplanetary datasets, but also lay foundational groundwork for future explorations into the dynamic relationships between exoplanets and their stellar environments.

The design of school environments plays a pivotal role in promoting student wellness, mindfulness, and socio-emotional learning (SEL). This article explores the integration of Environment Behaviour Studies (EBS) concepts into school design to enhance students' overall well-being and academic success. It highlights the importance of indoor environmental quality, ergonomic and flexible learning spaces, and biophilic design in fostering a healthy and engaging learning atmosphere. Additionally, the article delves into the creation of mindfulness spaces, sensory-friendly environments, and the use of colour and aesthetics to support emotional regulation and mental health. By examining case studies of successful implementations, the article underscores best practices for designing schools that promote positive social interactions, ensure safety, and reflect community values. Ultimately, this comprehensive approach to school design aims to nurture holistic development, support socio-emotional learning, and prepare students for lifelong success.

Two-dimensional periodic Stokes flow of viscous incompressible fluid in a rectangular cavity with constant velocities applied to the top and bottom walls is considered. The study of chaotic advection regimes is reduced to the sequential solving of two problems. To solve the first problem, the analytical method of superposition, that allows to obtain any desired accuracy of the velocity field, is used. To solve the second problem, which is associated with obtaining the trajectories of individual fluid particles, numerical calculations of the Cauchy problem were performed. An analysis of the boundary conditions accuracy was performed based on the control of local integration. The advection of the selected volume of fluid in the rectangular cavity under the periodic motion of walls for a finite period time based on piecewise spline cubic interpolation is modelled. The obtained numerical results agree with well-known experimental data.

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

The past 40 years have seen automotive Electronic Control Units (ECUs) move from being purely mechanical controlled to being primarily digital controlled. While there has been significant improvements in terms of passenger safety and vehicle efficiency including optimised fuel consumption, rising ECU numbers have resulted in increased vehicle weight, greater demands placed on power,more complex hardware and software, ad-hoc methods for updating software, and subsequent rise in costs for both vehicle manufacturer and consumer. To address these issues, the research presented in this paper proposes virtualisation technologies to be applied within automotive Electrical/Electronic (E/E) architecture. To proposed approach is evaluated through a comprehensive study of the CPU and memory resource requirement in order to support container-based ECU automotive functions. This comprehensive performance evaluation reveals that lightweight container virtualisation has the potential to welcome a paradigm shift in the E/E architecture, promoting consolidation and enhancing the architecture through power, weight and cost savings. Container based virtualisation will also enable a robust mechanism to facilitate online dynamic software updates throughout the lifetime of a vehicle.

This research aims to investigate and conduct the impact of earnings management practices on the performance of the banking sector in Jordan. Data were collected from 24 main commercial banks from (2015 – 2021). The study examine how earnings management practices affect banking sector performance using debt ratios and equity ratios based on firm size and debt ratios, and measure the impact of earnings management on it using regression analysis. The result of the study reveal that a positive and statistically significant association between equity per share (EPS) and return on investment (ROI) with earnings management practices, also, earnings management techniques are positively and significantly impacted by return on equity (ROE), the hypothesis that returns on investment (ROI) encourage business managers to employ earnings management strategies. Also, the study show that dependent variables of earnings management is measured as a debt ratio and equity ratio. Variables that are independent or explanatory of earnings management are considered independent variables.

Major depressive disorder (MDD) is a prevalent mental health condition with substantial social and economic consequences. This study focuses on the interplay between genetic and environmen-tal factors in MDD, with particular emphasis on epigenetic mechanisms such as stochastic epige-netic mutations (SEMs), epigenetic age acceleration, and epigenetic drift. We conducted a meta-analysis of DNA methylation patterns across six datasets (n=1125 MDD cases, 398 controls in whole blood; n=95 MDD cases, 96 controls in brain tissues) from the Gene Expression Omnibus. The analysis did not reveal significant global methylation differences between MDD cases and controls. However, a brain-specific probe (cg25801113) near the SHF gene consistently exhibited hypomethylation, suggesting its potential relevance to MDD. SEMs were assessed, revealing a dis-tinct burden at the gene level in MDD cases, though no significant findings emerged for epigenetic age acceleration, indicating it may not play a central role in MDD. The study also identified rare epivariations in specific genes unique to MDD cases. In blood tissue, 51 genes were associated with these unique epivariations, while 1 gene was highlighted in the brain tissue. These results un-derscore the importance of exploring rare epivariations in understanding the molecular mecha-nisms underlying MDD and offer potential targets for further investigation.

While financial literacy is crucial in improving the population's financial well-being, its effectiveness can be enhanced by exposure to financial information. This paper investigates the nexus between financial literacy, financial information consumption, and financial well-being in rural Ghana. The study employed cross-sectional data from a survey of 663 rural households using simple random and cluster sampling with reflective-reflective constructs. The data was analyzed using Structural Equation Modelling-Partial Least Squares. The findings reveal that financial literacy and financial information consumption significantly enhance financial well-being among rural households in Ghana. Financial Literacy also promotes Financial Information Consumption. Notably, financial literacy's impact on financial well-being is stronger when mediated by the consumption of financial information. These findings underscore the importance of improving financial literacy and information access to uplift financial well-being in rural areas. Moreover, the study highlights that financial literacy education is crucial as it plays a mediating role; recipients of financial education experience a more substantial impact. Such findings emphasize the importance of acquiring financial knowledge and effectively processing financial information to achieve financial prosperity, particularly in rural areas. These findings should motivate individuals, especially those in rural areas, to process financial information successfully rather than merely acquiring financial knowledge to attain financial prosperity.

Costa Rica, renowned for its environmental sustainability, faces a pressing waste management crisis that endangers its ecological and public health achievements. This study provides a detailed analysis of Costa Rica's waste management challenges, particularly in urban areas like San José, where nearly half of the nation's waste is produced. Major issues include insufficient landfill capacity, a low recycling rate of 9.6%, and significant regional disparities in waste practices. Using a hybrid modeling approach with Linear Regression and ARIMA models, the study forecasts waste minimization trends from 2024 to 2050, emphasizing the critical role of public participation in recycling efforts.The findings reveal limited success in government initiatives like the Environmental Health Route and the National Circular Economy Strategy, especially in rural areas. The study underscores the need for improved infrastructure, targeted public education, and the adoption of innovative technologies like AI and blockchain to achieve sustainable waste management. Strategic recommendations are provided to help Costa Rica align its waste management practices with global standards, enhancing its environmental sustainability and addressing the ongoing crisis effectively.

Heat exchangers play a vital role in numerous sectors like power generation and automotive manufacturing. Enhancing the energy efficiency of these exchangers stands as a significant hurdle. Utilizing nanofluids emerges as an optimal solution to augment heat transfer rates, leveraging their superior thermal conductivity while addressing economic constraints linked with traditional heat exchanger technologies. The motivation for this study is to consider the comprehensive synergistic features of MWCNTs, SiO₂, and hybrid MWCNTs–SiO₂ EG-based nanofluids in plate heat exchangers. This was achieved by simulating a plate heat exchanger using CFD (Fluent and Gambit softwares) considering the comparison of two SiO₂, MWCNTs, and their hybrid forms at different mass concentrations. The Reynolds-Averaged Navier-Stokes (RANS) method was employed to model turbulent flows, and the nanoparticles were compared in both single-phase and two-phase states, with their properties derived from experimental studies. Moreover, Nusselt number, convective heat transfer coefficient, and pressure drop variations were computed at different Reynolds numbers. The findings indicated an increase in the Nusselt number with the incorporation of the hybrid nanofluid, achieving a maximum enhancement of 11.19% in comparison to EG at a Reynolds number of 240 and a concentration of 0.86 wt.%. Noticeably, the pressure drop remained negligible at lower Reynolds numbers, exhibiting marginal variations up to 0.3% at higher Reynolds numbers. At a concentration of 0.86 wt.% and a Reynolds number of 480, the introduction of MWCNTs, hybrid, and SiO₂ nano-additives resulted in respective increases in the heat transfer coefficient by 21.02%, 10.76%, and 2.16% and corresponding alterations in pressure drop of 0.11%, 0.04%, and 0.02%.

Canine parvovirus (CPV) infection is a widespread ailment among young dogs globally, characterized by high morbidity, mortality, and significant infectivity. Due to its grim prognosis, it is often likened to canine "cancer" with a medium-term mortality rate of 46.43% and late-stage mortality reaching up to 100%.Current treatment modalities primarily encompass fluid therapy, antiemetics, antimicrobial medications, pain relievers, and enteral nutrition. However, the absence of specific internationally recognized medications necessitates substantial care expenses. This review aims to elucidate recent advancements in pharmacological interventions for mitigating CPV infection symptoms, underscoring the potential of novel pharmaceutical technologies in veterinary medicine to enhance clinical outcomes for afflicted animals and their caregivers，lay a theoretical foundation for the development of specific drugs.

This review focuses on the pivotal role of radiotracers in breast cancer imaging, emphasizing their importance in accurate detection, staging, and treatment monitoring. Radiotracers, labeled with radioactive isotopes, are integral to various nuclear imaging techniques, including positron emission tomography (PET) and positron emission mammography (PEM). The most widely used radiotracer in breast cancer imaging is 18F-fluorodeoxyglucose (18F-FDG), which highlights areas of increased glucose metabolism, a hallmark of many cancer cells. This allows for the identification of primary tumors, metastatic sites, and assessment of tumor response to therapy. In addition to 18F-FDG, this review will explore newer radiotracers targeting specific receptors, such as estrogen receptors or HER2, which offer more personalized imaging options. These tracers provide valuable insights into the molecular characteristics of tumors, aiding in tailored treatment strategies. By integrating radiotracers into breast cancer management, clinicians can enhance early disease detection, monitor therapeutic efficacy, and guide interventions, ultimately improving patient outcomes. Ongoing research aimed at developing more specific and sensitive tracers will also be highlighted, underscoring their potential to advance precision medicine in breast cancer care.

The Riemann zeta function plays a crucial role in number theory and its applications. The Riemann Hypothesis (RH) posits that zeros of other than the trivial ones are located on the line defined by the equation Re(s) =1/2. This paper introduces a novel and straightforward proof of the Riemann Hypothesis. The proof employs a standard method, utilizing the eta function in place of the zeta function, under the assumption that the real part is greater than zero. The equation for the real and imaginary parts of the Riemann zeta function (eta function) is completely separated. Initially, let with s= . The value of the real part is determined by solving the equation, and the process is repeated for identifying the potential roots shared by the two functions, a common value is obtained, leading to a =1/2, which represents the real part of the main root of the function ζ(s). By plotting the zeta function for the obtained a, it is determined that the function has a root only at a =1/2. In another analysis, by identifying the roots of the common potential between the two functions ζ(s) and ζ(1-s), a common value is obtained, which leads to a =1/2. This value represents the real part of the main root of the function ζ(s). Additionally, using a standard method and with the help of two functions ζ(s) and ζ(1-s), the real part of the root of the zeta function is obtained. To create a generator function for prime numbers in terms of b, one can solve the root of the zeta function where it equals one (i.e., and obtain a relationship between b’ and prime numbers. Giving the value of zeta equal to one and s' = a' + ib’, similar to zeta equal to zero, the roots are again placed on the line. Then, by using the zeta function defined by multiplying prime numbers, we arrive at a new meaningful relation between b’ and its corresponding prime number is obtained.

A prime gap is the difference between consecutive prime numbers. The $n^{\text{th}}$ prime gap, denoted $g_{n}$, is calculated by subtracting the $n^{\text{th}}$ prime from the $(n+1)^{\text{th}}$ prime: $g_{n}=p_{n+1}-p_{n}$. Oppermann's conjecture is a prominent unsolved problem in pure mathematics concerning prime gaps. Despite verification for numerous primes, a general proof remains elusive. If true, the conjecture implies that prime gaps grow at a rate bounded by $g_{n}<{\sqrt {p_{n}}}$. This note presents a proof of Oppermann's conjecture using the Euler-Maclaurin formula on harmonic numbers. This proof simultaneously establishes Andrica's, Legendre's, and Brocard's conjectures.

The intricate relationship between genomic mutations and proteomic network topology represents a frontier in understanding cellular resilience and disease mechanisms. This study presents a novel approach to analyzing how proteomic topological structures evolve and potentially break down in response to accumulating genomic mutations, offering insights into the complex interplay between genetic alterations and protein interaction networks. We developed a computational model simulating a network of ten key proteins (A-J) over 20 discrete time points, each representing a state of increasing genomic mutation load. Our model incorporates dynamic protein interaction strengths that fluctuate in response to simulated genomic alterations and a topological representation of the protein network, allowing for visualization of structural changes. Not forgetting a quantitative measure of network integrity, correlating with the system's ability to maintain function under mutational stress. Our Key findings include: visualization of proteomic network evolution through a series of topological graphs, revealing how genomic mutations progressively alter protein interaction patterns and identification of a critical "breakage point" in the network topology, signifying a threshold where genomic mutations overwhelm the protein network's ability to maintain its functional structure. And also quantification of network properties, including interaction strengths and overall network density, demonstrating the non-linear relationship between genomic mutations and proteomic topological integrity.The observed breakage point may represent a critical threshold in disease progression, where the accumulation of genomic mutations leads to a collapse in the proteomic interaction network, potentially triggering pathological states. This methodology offers a new perspective on the genotype-phenotype relationship, viewing it through the lens of protein network topology. Our approach provides a framework for future studies to analyze how specific genomic mutations might impact proteomic structures, potentially leading to new insights in cancer research, neurodegenerative disorders, and other mutation-driven diseases. It also suggests that maintaining proteomic topological integrity could be a key factor in cellular resilience against genomic instability.

The comprehensive analysis of cross-country skiing races is a pivotal step in establishing effective training objectives and tactical strategies. This study aimed to establish a method for the classifi-cation of sub-techniques and analyzing skiing characteristics during cross-country skiing skating style timed races on snow using high-precision kinematic GNSS devices. The study involved at-taching GNSS devices to the heads of two athletes during skating style timed races on cross-country ski courses. These devices provided precise positional data and recorded vertical and hor-izontal head movements and ground over velocity (VOG). Sub-techniques were classified by de-fining waveform patterns for G2, G3, G4, and G6 based on these data. The validity of classifica-tion was verified by comparing GNSS data with video analysis, a process that yielded classifica-tion accuracies ranging from 94.0% to 99.3% for G2, G3, G4, and G6. Notably, G4 emerged as the fastest technique, with sub-technique selection varying among skiers and being influenced by skiing velocity and course inclination. The study's findings have practical implications for ath-letes and coaches, as they demonstrate that high-precision kinematic GNSS devices can accurate-ly classify sub-techniques and detect skiing characteristics during skate-style cross-country skiing races, thereby providing valuable insights for training and strategy development.

The application of three-dimensional (3D) printing/bioprinting technologies and cell therapies has garnered significant attention due to their potential in the field of regenerative medicine. This paper aims to provide a comprehensive overview of 3D printing/bioprinting technology and cell therapies, highlighting their results in diverse medical applications, while also discussing the capabilities and limitations of their combined use. The synergistic combination of 3D printing and cellular therapies has been recognised as a promising and innovative approach, and it is expected that these technologies will progressively assume a crucial role in the treatment of various diseases and conditions in the foreseeable future. This review concludes with a forward-looking perspective on the future impact of these technologies, highlighting their potential to revolutionize regenerative medicine through enhanced tissue repair and organ replacement strategies.

Globally, cancer is an important health problem worldwide, and has become one modern medicine’s most serious problems to prevent, diagnose, and treat. Many types of cancers still have non-negligible mortality rates, and new treatments need to be developed for them. This study aimed to elucidate cancer mechanisms and facilitate cancer treatment and prevention. The ideal temperature for cancer growth is 35°C; however, conditions were not consistent with chromosomal instability, loss of alleles of tumor-suppressor genes, abnormal DNA methylation, and collagen phagocytosis, which are known causes of cancer. In addition, when cancer develops, white blood cells attack the cancer tissue and remove it; however, as the decrease in body temperature drops, leads to a reduction in the immune potential of the white blood cells. Based on previous papers, this study focused on aimed to determine the effects of the low-temperature environment of 35°C, the temperature at which cancer is most likely to proliferate, and changes in adenosine triphosphate (ATP) levels. The study revealed that Therefore, the causes of cancer is caused by include chromosome fusion that occurs occurring due to the impaired DNA topoisomerase IIα proliferation and primary cilia rotation due to resulting from decreased intercellular adhesion.

The continuous expansion of Large Language Models (LLMs) has significantly transformed the fields of artificial intelligence (AI) and natural language processing (NLP). This paper reviews the rapidly evolving domain of language models and introduces the concept of Extremely Large Language Models (XtremeLLMs), a new category defined for models exceeding one trillion parameters. These models are monumental in scale and engineered to enhance performance across a diverse range of language tasks. This study aims to establish a comprehensive framework that explores the significant opportunities and complex challenges presented by such extensive scaling and emphasises the implications for future advancements in the field.

We here report the purification of a novel member of the galectin family, the β-Galactoside-binding lectin hRTL, from the marine sponge Chondrilla australiensis. The hRTL lectin is a tetrameric proto-type galectin with a subunit molecular weight of 15.5 kDa, consisting of 141 amino acids and sharing 92% primary sequence identity with the galectin CCL from the congeneric species C. caribensis. Transcriptome analysis allowed the identification of additional sequences belonging to the same family, bringing the total number of hRTLs to six. Unlike most other galectins, hRTLs display a 23 amino acids long signal peptide that, according to Erdman degradation, is post-translationally cleaved, leaving a N-terminal end devoid of acetylated modifications, unlike most other galectins. Moreover, two hRTLs display an internal insertion, which determines the presence of an unusual loop region that may have important functional implications. The characterization of the glycan binding properties of hRTL revealed that it had high affinity to-wards TF-antigen, sialyl TF, and type-1 N-acetyl lactosamine with a Galβ1-3 structure. When administered to DLD-1 cells, a colorectal carcinoma cell line expressing mucin-associated TF-antigen, hRTL could induce glycan-dependent cell death by activating MAP kinases, thereby inhibiting cancer cell proliferation.

Introduction: Peripheral neuropathies are very common and occur due to multiple causes including diabetes, tuberculosis, vasculitis, thyroid disorders, immune mediated diseases, vitamin B12 deficiency and drugs. Drug induced peripheral neuropathy (DIPN) is potentially irreversible, resulting in sensory deficits and paraesthesia. DIPN due to anti-tubercular drugs is common and can be implicated on linezolid, cycloserine and isoniazid.Case: 40-year-old female, diabetic with MDR-TB presented with severe, sharp, burning pain in her lower limbs. The patient was on all longer acting ATT drug regimen and was suspected with drug induced peripheral neuropathy. Conclusion: Linezolid, is used in treatment of tuberculosis and one of the major side effects includes peripheral neuropathy which is usually quite severe, presenting predominantly with sensory symptoms. Cessation of linezolid and neuropathic pain medications reduced the pain of patient from VCPS 8-10 to 1-2. Treatment of DIPN can be challenging as adverse drug reactions while treating tuberculosis should be kept in mind. It also warrants earliest treatment by identification of the drug in disguise and timely discontinuation of the drug.

This paper investigates the impact of network topologies on the security of wireless sensor networks (WSNs). We propose the use of Spectre Monotile aperiodic tiling for sensor deployment, demonstrating its superior security compared to regular deterministic topologies. Additionally, we introduce a novel Intrusion Effort Index to quantify network resilience against clone attacks. By implementing a smart random walk to simulate the scenario of malicious cloned nodes attempting to reach the central access point of a network, we take into consideration the worst-case scenario for a network as it is being attacked. Given all network topologies use the same intrusion detection system and security protocols, we discover the topology of a network will also play a role and provide an additional layer of security depending on how it is designed. Similar to a fog-of-war, the sensor positions play a vital role in how an intruder assesses a network. By tiling a plane non-periodically, an absence of regularity in the structure is produced, which obfuscates an intruder attempting to predict the next sensor position, due to a varying number of adjacent neighboring nodes each time it reaches a new node. After 10,000 rounds of simulation emulating different scenarios of malicious nodes compromising the network, we averaged the results to find total detections, total hops, and percentage of times the base station was reached. Our simulation results show that aperiodic tiling has the best security resilience and robustness compared to other flat network topologies.

Mycoviruses are highly genetically diverse, can significantly change their fungal host’s phenotype, yet, they are generally under-described in genotypic and biological studies. We propose Botrytis cinerea as a model mycovirus system in which to develop a deeper understanding of mycovirus epidemiology including diversity, impact, and the associated cellular biology of the host and virus interaction. Over 100 mycoviruses have been described in this fungal host. B. cinerea is an ideal model fungus for mycovirology as it has highly tractable characteristics – it is easy to culture, has a worldwide distribution, infects a wide range of host plants, can be transformed and gene-edited, and has an existing depth of biological resources including annotated genomes, transcriptomes, and isolates with gene knockouts. Focus on a model system for mycoviruses will enable the research community to address deep research questions that cannot be answered in a non-systematic manner. Since B. cinerea is a major plant pathogen, new insights may have immediate utility as well as creating new knowledge that complements and extends the knowledge of mycovirus interactions in other fungi, alone or with their respective plant hosts. In this review we set out some of the critical steps required to develop B. cinerea as a model mycovirus system and how this may be used in the future.

This study explores how the Household Dietary Diversity Score (HDDS) and spatial visualization can inform food governance in Chile, focusing on socio-demographic and geographical determinants affecting food consumption patterns. A national household database (n=4,407) provided by the “Family Support Program of Food Self-Sufficiency” (FSPFS) of the Ministry of Social Development and Family was analyzed. The findings revealed that Chilean vulnerable households were led mostly by women (86.6%), with an age average of 55.9 15.6 years old, versus 68.9 12.9 years in the case of men. The intake frequency analysis showed that dairy, fruits, and vegetables were below the recommended values in at least half of the households, and that fats and sugars were above recommended levels. Regarding the HDDS [0-189], the national average was of 91.4 ± 20.6 and was significantly influenced by the number of minors in the households, water access, food access issues, and residing in the Zona Sur. Finally, the spatial visualization showed that the Zona Central had higher consumption of fruits and vegetables, while the extreme zones Norte Grande and Zona Austral showed higher intakes of fats and sugars. These findings emphasize the importance of leveraging data insights like HDDS and spatial visualization to enhance food security and inform food governance strategies.

In previous papers we have derived equations of motion with radiation terms and proved the existence-uniqueness of periodic solution of the 3-body problem of classical electrodynamics. The number of equations of motion – 12 is more than the number of unknown functions – 9. It turns out that 9 equations are independent and the rest 3 ones are consequences of them. These three equations have a solution and they give the expressions for the energy of the moving particles. The main goal of the present paper is to estimate the energy of rounding about the nuclei particles and compare it with the values given by quantum mechanics.

Background: Post-marketing surveillance is crucial for gathering data on vaccine reactogenicity, enhancing public trust in immunization, and promoting vaccine uptake. This study aims to characterize adverse events following immunization (AEFI) and estimate the incidence rates of adverse reactions (ARs) associated with vaccines included in Taiwan's Expanded Program on Immunization (EPI). The study utilizes data from Taiwan's Vaccine Injury Compensation Program (VICP). Methods: Vaccine injury claims submitted to the VICP between 2014 and 2019 were analyzed. ARs were defined as AEFIs adjudicated as ‘related’ or ‘indeterminate’ by the VICP committee. Data on the annual number of vaccine doses administered was obtained from the Taiwan CDC, which helped calculate AR incidence rates. Results: A total of 491 AEFI claims were reviewed, with 327 (66.6%) categorized as ARs. AEFIs were mainly associated with the Bacillus Calmette-Guérin (BCG) vaccine (43.4%) and the seasonal influenza vaccine (22.0%). Most EPI vaccines demonstrated low AR incidence rates, ranging from 1.68 to 13.6 per million doses, with the exception of BCG, which exhibited 162.5 ARs per million doses. Shifting BCG immunization from below 5 months to at least 5 months reduced osteomyelitis incidence significantly, from 41.4 to 7.9 (P = 0.0014), but increased abscess and lymphadenitis cases. Conclusion: EPI vaccines in Taiwan are highly safe, with minimal AR incidences in the general population. The BCG vaccine remains an exception, occasionally causing severe ARs like osteomyelitis. Adjusting the immunization schedule to an older age may mitigate some of these adverse effects.

The Bax inhibitor-1 (BI-1) gene family, which is required for plant growth, development, and stress tolerance, remains largely unexplored in cauliflower. In this study, we identified and characterized cauliflower BI-1 family genes. On the basis of aligned homologous sequences and collinearity with Arabidopsis genes, we identified nine cauliflower BI-1 genes, which encoded proteins that varied regarding length, molecular weight, isoelectric point, and subcellular localization (i.e., Golgi apparatus, plasma membrane, cell membrane, and chloroplast). Phylogenetic analyses detected evolutionary conservation and divergence among these genes. Ten structural motifs were identified, with Motif 5 crucial for inhibiting apoptosis. According to the cis-regulatory elements in their promoters, these genes likely influence hormone signaling and stress responses. Expression profiles among tissues highlighted the diversity in the functions of these genes, which were significantly expressed in the silique and root. Focusing on BobBIL4, we investigated its role in brassinosteroid (BR)-mediated root development and salt stress tolerance. BobBIL4 expression levels increased in response to BR and salt treatments. The functional characterization of this gene in Arabidopsis revealed it enhances root growth and salinity tolerance. These findings provide insights into BI-1 gene functions in cauliflower, while also highlighting the potential utility of BobBIL4 for improving crop stress resistance.

This research article provides an unconditional proof of an inequality proposed by \textit{Srinivasa Ramanujan} involving the Prime Counting Function $\pi(x)$, \begin{align*} (\pi(x))^{2}<\frac{ex}{\log x}\pi\left(\frac{x}{e}\right) \end{align*} for every real $x\geq \exp(547)$, using specific order estimates of the \textit{Mertens Function}, $M(x)$. The proof primarily hinges upon investigating the underlying relation between $M(x)$ and the \textit{Second Chebyshev Function}, $\psi(x)$, in addition to applying the meromorphic properties of the \textit{Riemann Zeta Function}, $\zeta(s)$ with an intention of deriving an improved approximation for $\pi(x)$.

Live-streaming commerce (LSC) is a new shopping method that combines the characteristics of social commerce and e-commerce. Since the global coronavirus disease 2019 (COVID-19) outbreak, the number of branded platforms is growing rapidly, and their competition is fiercer than ever. Understanding consumer needs and improving service quality become the key issue for survival. This study aims to develop and empirically validate a multi-dimensional hierarchical model for measuring service quality on LSC platforms. A hierarchical reflective construct was proposed to capture dimensions based on literature on e-retail and social commerce service quality. The pro-posed model was rigorously tested using two waves of survey data through the partial least squares method. Results showed that the service quality of LSC is a third-order, reflective con-struct and includes five primary dimensions (the streamer’s interaction quality, physical envi-ronment, website quality, outcome quality and ordering process) and twelve sub-dimensions (trustworthiness, expertise, responsiveness, telepresence, consumption scenarios, information quality, system operation quality, fulfillment and refund/compensation, privacy/security, contact and ease of use). Findings also supported the hypothesis that service quality has a significant impact on customers’ satisfaction and their behavioral intentions. Furthermore, we tested an al-ternative model, and the results showed that the relationship between dimensions and overall assessment is reflective rather than formative. We offered directions for further research on LSC service quality and discussed managerial implications stemming from the empirical findings.

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

Utilizing groundwater offers a promising solution to alleviate water stress in Ethiopia, providing a dependable and sustainable water source, particularly in regions with limited or unreliable surface water availability. However, effective decision-making regarding well drilling and placement is essential to maximize groundwater resource potential, enhancing agricultural productivity, reducing hunger, and bolstering food security in Ethiopia. This study concentrates on the development of two-stage stochastic mixed integer programming (SMIP) models to optimize well placement for sustainable agricultural irrigation, considering uncertain demand scenarios. Additionally, a deterministic mixed integer programming model is formulated for comparison with the two-stage SMIP. Experiments are conducted to explore various demand scenario distributions, revealing that the optimized total cost for the two-stage SMIP generally exceeds that of a deterministic setting, aligning with the two-stage SMIP's focus on long-term benefits. Moreover, slight differences are observed in well layouts under different assumption scenarios. The study also examines the impact of selected parameters, such as fixed construction costs, per-meter drilling costs, and demand scenarios. The out-of-sample performance shows that the stochastic model is more flexible and resilient, with 11% and 4% lower costs than deterministic cases 1 and 3, respectively. This flexibility provides a more robust long-term strategy for well placement and resource allocation in groundwater management.

Background: Malnutrition screening in hospitalized children is essential, and the STAMP is a val-idated tool for this purpose. The study aimed to modify STAMP for a Saudi context and assess the sensitivity and specificity of both the original and modified tools. Method: A cross-sectional study was conducted among 307 hospitalized children, where both the original and Saudi-modified STAMP were applied. Anthropometric measurements were also recorded, and statistical analysis was used to assess the tools' validity. Results: The Saudi-modified STAMP identified a higher percentage of children at high risk of malnutrition compared to the original STAMP (91.6% vs. 62.9%). The sensitivity, specificity, positive predictive value, negative predictive value, accuracy, and agreement of the Saudi-modified STAMP compared to the original were 94.3%, 13.2%, 64.8%, 57.7%, 0.654, and 0.089, respectively. Conclusion: The Saudi-modified STAMP showed excellent sensitivity and varied negative predictive value, indicating its potential effectiveness in screening for malnutrition among hospitalized children compared to the original STAMP and using an-thropometric measurements as references.

Artificial Intelligence (AI) is poised to revolutionize the architectural design and energy management of green buildings, offering significant advancements in sustainability and efficiency. This paper explores the transformative impact of AI on improving energy efficiency and reducing carbon emissions in commercial buildings. By leveraging AI algorithms, architects can optimize building performance through advanced environmental analysis, automation of repetitive tasks, and real-time data-driven decision-making. AI facilitates precise energy consumption forecasting and integration of renewable energy sources, enhancing the overall sustainability of buildings. Our study demonstrates that AI can reduce energy consumption and CO2 emissions by approximately 8% and 19%, respectively, in typical mid-size office buildings by 2050 compared to conventional methods. Further, the combination of AI with energy efficiency policies and low-emission energy production is projected to yield reductions of up to 40% in energy consumption and 90% in CO2 emissions. This paper provides a systematic approach for quantifying AI's benefits across various building types and climate zones, offering valuable insights for decision-makers in the construction industry.

Parkinson's disease (PD) is a prevalent neurodegenerative disorder marked by progressive motor and non-motor symptoms. Traditional treatments primarily manage symptoms rather than address the disease's root causes, highlighting the need for novel therapeutic approaches. Natural phytochemicals, particularly phenolic compounds, have shown potential due to their neuroprotective effects. Antiaris africana is commonly used in traditional African medicines to treat several illnesses including neurodegenerative disorders. However, its neuroprotective mechanism remains elusive. This study aimed to employ network pharmacology-based prediction to identify key targets and pathways through which A. africana exerts its effects on PD. Targets associated with Parkinsonism were identified and analyzed for interaction with compounds from A. africana. Protein-protein interaction (PPI) networks were constructed, and key hub genes were identified using Cytoscape. Functional enrichment analysis highlighted significant pathways involved in PD. Molecular docking was performed to evaluate the binding affinities of the compounds to PD-related targets. Our results reveal that compounds such as caffeic acid, chlorogenic acid, catechin, ellagic acid, epigallocatechin, gallic acid, isoquercitrin, kaempferol, quercetin, quercitrin, and rutin interact with key proteins implicated in PD, including APP, EGFR, CASP3, ESR1, AKT1, and MAPK8. Notably, rutin exhibited strong binding affinity for EGFR, and chlorogenic acid showed potential in modulating the APP pathway. These findings suggest that phenolic compounds in A. africana may exert neuroprotective effects through multiple molecular mechanisms, offering potential therapeutic strategies for PD. This study underscores the importance of integrating molecular docking and network pharmacology to elucidate the therapeutic potential of natural compounds in complex diseases like Parkinson's disease

When earthquake damage occurs, it is extremely important to quickly identify the presence or absence of such damage. In this study, we developed and evaluated a new remote sensing index to automatically determine "damage" by image analysis when damage greater than partial destruction of a house by an earthquake or tsunami occurs. The accuracy of the houses estimated as "damaged" was high and sufficient for the initial assessment of damage. The results of this research are expected to be utilized for more rapid damage assessment after a disaster.

In the framework of fully vertical GaN-on-Silicon device technology development, we report on the optimization of non-alloyed ohmic contacts on the N-polar n+ doped GaN face backside layer. This evaluation is made possible by using patterned TLMs (Transmission Line Model) through direct laser writing lithography after locally removing the substrate and buffer layers in order to access the n+ doped backside layer. As deposited non-alloyed metal stack on top of N-polar orientation GaN layer after buffer layers removal results in poor ohmic contact quality. To significantly reduce the related contact resistances, an HCl treatment is applied prior to metallization under various time and temperature conditions. A 3-minutes HCl treatment at 70°C is found to be the optimum condition to achieve thermally stable high ohmic contact quality. To further understand the impact of the wet treatment, SEM (Scanning Electron Microscopy) and XPS (X-ray Photoelectron Spectroscopy) analysis were performed. XPS revealed a decrease in Ga-O concentration after applying the treatment, reflecting the higher oxidation susceptibility of the N-polar face compared to the Ga-polar face, which was used as a reference. SEM images of the treated samples show the formation of pyramids on the N-face after HCl treatment, suggesting specific wet etching planes of the GaN crystal from the N-face. The size of the pyramids is time-dependent; thus, increasing the treatment duration results in larger pyramids, explaining the degradation of ohmic contact quality after prolonged high temperature HCl treatment.

Structural Units (SU) is a novel unit system, proposed as compatible to the International System of Units (SI), rooted in Spacetime Structure. Unlike SI, which evolved over history without a fixed reference frame, SU defines one Structural Unit as the space and time between two vertices in the Spacetime Structure. This perspective offers a unique viewpoint, where space and time units are proportionate. This correlation results in Natural constants being expressible through algebraic relationships involving the pure numbers π, φ (the Golden ratio), and α (the Fine Structure constant), not only simplifying Fundamental constants but also introducing a harmonious integration of geometric concepts. In contrast, SI currently relies on fixed values for seven constants derived from CODATA. It's crucial for Structural Units to seamlessly integrate with the existing International System of Units, proposing a theoretical framework, hitherto nonexistent, for the values of the various Fundamental Constants that have been experimentally obtained in our scientific endeavor. To ensure compatibility, the four Planck Units, (length, mass, time, and temperature), introduced by Max Planck in 1899, will be recalculated in SU and then converted back to SI using dimensional analysis. Additionally, to further validate this compatibility, we will examine the Schwarzschild radius from Relativity, the photon energy from Quantum Mechanics, and propose a new interpretation of the Uncertainty Principle under the SU framework. This potential harmonization of geometry and Natural constants in SU could offer a deeper understanding of the inherent order in the fabric of the Universe.

The co-occurrence of different arboviruses, through (re)emergence episodes in a particular region, often exacerbates public health crises associated with these pathogens. Considering the Brazilian epidemiological panorama of arboviruses cocirculation, such as Dengue (DENV), Zika (ZIKV), and Chikungunya (CHIKV) viruses, the imminent emergence of Mayaro virus (MAYV) in urban areas, and the presence of susceptible human hosts, we looked into the coinfection and superinfection impact of CHIKV and MAYV replication in Aedes aegypti. Mosquitoes were coinfected and superinfected with CHIKV and MAYV by artificial blood-feeding, and infection (IR), dissemination (DR), transmission (TR) rates, and viral load were evaluated by qRT-PCR. Our findings suggest that, Ae. aegypti can simultaneously transmit CHIKV and MAYV in coinfection scenarios. However, in superinfection assays, the initial infection (either CHIKV or MAYV) adversely affected the transmission capacity of the subsequently acquired virus, indicating replication interference between the viruses. These results have important implications for public health management actions in the country, emphasizing complex arbovirus transmission scenarios and the associated epidemiological risks.

This paper investigates location-based adaptive beamforming techniques, including Maximum Ratio Transmission (MRT) and Zero Forcing (ZF), in complex wireless environments. The study leverages a digital twin simulation of the University of Glasgow campus to evaluate the proposed schemes under realistic conditions, such as user mobility and multipath propagation. The results demonstrate significant performance improvements with the location-based beam steering approaches. In the open space scenario, the location-based schemes achieved up to 40\% higher Signal-to-Interference-plus-Noise Ratio (SINR) and 30\% higher received power, along with reduced interference. The gains were even more pronounced in the digital twin environment, with up to 50\% improvement in SINR and 40\% increase in received power. Furthermore, the study evaluates the energy efficiency of the location-based adaptive beamforming techniques, showing up to 20\% reduction in energy consumption compared to conventional fixed-beam approaches.

This study proposed a regression model for predicting fatigue properties based on crucial weld geometry factors in lap-welded joints with gaps using statistical analysis. Welding conditions were varied to build various weld geometries in joints configured in a lap from with gaps of 0, 0.2, 0.5, and 1.0 mm, and 87 S-N curves for the lap-welded joints were derived. As input variables, 17 weld geometry factors (7 lengths, 7 angles, and 3 area factors) were selected. The slope of the S-N curve using Basquin model from the S-N curve and the safe fatigue strength were selected as output variables for prediction to develop the regression model. Multiple linear regression models, multiple non-linear regression models, and second-order polynomial regression models were proposed to predict fatigue properties. Backward elimination was applied to simplify the models and reduce overfitting. Among the three proposed regression models, the multiple non-linear regression model had a coefficient of determination greater than 0.86. In lap-welded joints with gaps, the weld geometry factors representing fatigue properties were identified through standardized regression coefficients, and four weld geometry factors related to stress concentration were proposed.

Forest fires can occur suddenly and have significant environmental, economic, and social consequences. Timely and accurate evaluation and prediction of their progression, particularly the spread speed in difficult-to-access areas, are essential for emergency management departments to proactively implement prevention strategies and scientifically extinguish fires. This paper provides a comprehensive analysis of advanced technologies for predicting forest fire spread in China and globally. Incorporating remote sensing (RS) technology and forest fire science as the theoretical foundation, and utilizing the Wang Zhengfei forest fire spread model as the technical framework, this study constructs a forest fire spread model based on remote sensing interpretation. The model optimizes the method for acquiring parameters and enhances algorithm accuracy. By considering regional landforms (ridge lines, valley lines, slopes) and vegetation coverage, this paper establishes visual interpretation markers for identifying hotspots within the spread model. Utilizing statistical data from pixels within the fire line zone transforms the methodology for predicting forest fire spread speed, resulting in greater accuracy compared to conventional fixed-point predictions. Finally, the model was applied to the case of a forest fire in Mianning County, Sichuan Province, China and verified using high-time resolution mid-infrared image data and previous research findings. The results demonstrate that the predicted fire spread area from this RS-enabled model is consistent with both high-time resolution geostationary satellite data and previous research outcomes, indicating high reliability. This model can provide crucial fire spread information to relevant emergency departments, enabling effective preemptive measures and scientific firefighting strategies.

Microplastics, plastic fragments smaller than 5 mm present in the environment due to the decomposition of larger plastics, can cause damage to various ecosystems and species of pollinating insects such as Apis mellifera bees. These bees play a crucial role in the ecology and production of honey and pollen, also serving as bioindicators of environmental quality as they are sensitive to contaminants such as microplastics. In this study, the presence of microplastics in these insects and their bee products, pollen, and honey, collected in August 2021 and August 2023 in rural areas (Tabio and Guasca) of Cundinamarca, Colombia, and urban areas (Universidad Nacional de Colombia) was evaluated. and Pontificia Universidad Javeriana) of Bogotá, Colombia. In each year, 24 bees, 10 grams of honey and 10 grams of pollen were collected per sampling point. Microplastics in bees and their products were identified and quantified by stereomicroscopy, with or without hydrogen peroxide digestion pretreatment. Microplastics were found in bees, pollen, and honey in both periods, with an increase in their quantity observed over time due to increasing environmental pollution. Blue fibers were the most common microplastics, with a greater amount recorded in 2023 compared to 2021.

Type-1 Diabetes Mellitus (T1D) onset and development is closely linked with imbalance of gut microbiome, while supplementation with probiotics may result in positive alterations in gut microbiome composition. In the present study, the effect of a dietary intervention including free or immobilized cells of the presumptive probiotic Pediococcus acidilactici ORE5 on Corinthian currants, a food with beneficial impact in the condition of diabetes, was investigated. Male Wistar rats were studied which were divided into 4 groups: healthy animals, which received the free (H_FP) or the immobilized cells (H_IPC), and diabetic animals, which received the free (D_FP) or the immobilized cells (D_IPC), for 4 weeks (109 cfu/day, in all groups). At the end of the dietary intervention, D_IPC group exerted lower concentration of the inflammatory cytokine IL-1b compared to D_FP. Consumption of immobilized on Corinthian currants P. acidilactici ORE5 cells by diabetic animals led to increased loads of fecal lactobacilli and lower levels of Enterobacteriaceae, coliforms, and E. coli, while Actinobacteria phylum, Akkermansia, and Bifidobacterium genera abundances were increased, and fecal lactic acid was elevated. Overall, the results of the present research demonstrated that functional ingredients can ameliorate gut dysbiosis present in T1D and could be used to design dietary patterns aiming at T1D management. However, well-designed clinical trials are necessary, in order to confirm the beneficial effects in humans.

Kagoshima Prefecture, Japan, is highly vulnerable to natural disasters, and requires effective disaster response and rehabilitation measures, particularly for vulnerable populations. This study aimed to investigate the current state of disaster preparedness in municipalities and identify gaps in support for vulnerable populations during disasters. A cross-sectional survey was conducted from January to March 2023, targeting officers in disaster countermeasures-related municipal departments. The survey assessed municipality awareness of vulnerable populations, understanding of their support needs, and the status of support systems during emergency evacuations. Overall, 51.2% of municipalities responded, of whom 86.4% were aware of vulnerable populations in their areas. However, only 54.5% had a clear understanding of their support needs. A small proportion of municipalities (18.2%–36.4%) had comprehensive support systems in place for vulnerable populations during emergency evacuations. Only 4.5% of municipalities were familiar with the concept of disaster rehabilitation, but 63.6% expressed interest in discussing evacuation plans with medical professionals. The findings reveal significant gaps in municipalities’ awareness and preparedness on disaster rehabilitation measures for vulnerable populations. This highlights the need for increased training, resources, and collaboration between local governments and healthcare professionals to ensure the safety and well-being of vulnerable populations during disasters.

Since the Industrial Revolution, nearly 700 GtC of carbon have been emitted into the atmosphere as CO2 derived from human activities, of which 292 GtC remain uncontrolled. Furthermore, the emission rate is increasing yearly, with the latest value (2022) of 11 GtC. By the end of this century, the atmospheric CO2 concentration is predicted to surpass 700 ppm. The effects of this sudden carbon release on the worldwide biogeochemical cycles and balances are not yet fully understood, but it is undeniable that global warming and climate change are already a fact, with this gas playing a starring role. Governmental policies and international agreements on emission reduction need to produce results quickly enough, and the deadline to act is running out. Besides the agreements to reduce emissions, alternative strategies to reverse this trend must be sufficiently promoted. Biological CO2 capture is a speedy flow of the carbon cycle capable of capturing over 115 GtC annually through photosynthesis. An increase of 6.5% in this capture and the subsequent stabilization of produced biomass could counteract the current CO2 emission rate. In this overview, the artificial culture of phytoplankton is considered a potential alternative to conducting this large-scale capture. A production system model is suggested and the main technological and political challenges for using large areas as partially-natural photobioreactors are discussed. The global implementation of these large CO2 sinks and the associated infrastructure would stabilize the carbon cycle while it is developed as a new source of richness.

With the development of Global Navigation Satellite Systems (GNSS), the quality and anti-jamming capability of satellite navigation signals are crucial. Binary Offset Carrier (BOC) modulation faces issues of false locking due to multi-peak ambiguity in its autocorrelation function, limiting its application. This paper examines FH-BOC modulation, which integrates BOC with frequency hopping technology, significantly improving anti-jamming, anti-multipath performance, and spectral efficiency. To meet the high dynamic tracking demands of FH-BOC signals, this study explores three types of carrier tracking loops: the traditional second-order frequency-locked loop assisted a third-order phase-locked loop, a linear Kalman filter-based tracking algorithm, and an adaptive Kalman filter-based tracking algorithm. A composite code tracking loop is also proposed. Simulations show that the adaptive Kalman filter algorithm achieves high-precision carrier tracking in dynamic environments and quickly converges during transitions. The composite code tracking loop, aided by the carrier loop, ensures precise synchronization of pseudocode and frequency-hopping subcarrier phases, demonstrating the superior performance of FH-BOC modulation in dynamic environments.

Background/Objectives: The study aimed to assess the reactogenicity and immunogenicity of various SARS-CoV-2 vaccines and compare their protective effects against COVID-19 among healthcare workers (HCWs) during the Omicron outbreak in Taiwan.Methods: Conducted from March 2021 to July 2023, this prospective observational study included healthy HCWs without prior COVID-19 immunization. Participants chose between adenovirus-vectored (AstraZeneca), mRNA (Moderna, BioNTech-Pfizer), and protein-based (Medigen, Novavax) vaccines. Blood samples were taken at multiple points to measure neutralizing antibody (nAb) titers, and adverse events (AEs) were recorded via questionnaires. Results: Of 710 HCWs, 668 (94.1%) completed three doses, and 290 (40.8%) received a fourth dose during the Omicron outbreak. AEs were more common with AstraZeneca and Moderna vaccines, while Medigen caused fewer AEs. Initial nAb titers were highest with Moderna but waned over time regardless of the vaccine. Booster doses significantly increased nAb titers, with the highest levels observed in Moderna BA1 recipients. The fourth dose significantly reduced COVID-19 incidence, with Moderna BA1 being the most effective.Conclusions: Regular booster doses, especially with mRNA and adjuvant-protein vaccines, effectively enhance nAb levels and reduce infection rates, providing critical protection for frontline HCWs during variant outbreaks.

Because we observed a reduced humoral immune response to the COVID-19 vaccine and subsequently discovered a lower susceptibility to COVID-19 in individuals carrying the ALDH2 rs671 variant, we hypothesized that rs671 is beneficial for cellular immunity against COVID-19. Using the IFN-γ enzyme-linked immunospot (ELISPOT) assay, we evaluated cellular immunity before and after COVID-19 vaccination in two subcohorts of a previously reported cohort. Subcohort 1 (26 participants) had six repeated observations at baseline and after one to three doses, whereas subcohort 2 (19 participants) had two observations, before and after the third dose. ELISPOT counts at six months after the second dose increased from baseline in carriers of the rs671 variant, but not in non-carriers. A positive effect of rs671 on ELISPOT counts was estimated using a mixed model, including the random effect of subcohort, repeated measures, and fixed effects of vaccine type, age, sex, height, lifestyle, steroid use, and allergic disease. There was no association between ELISPOT counts and specific IgG levels, suggesting a limitation in estimating protective potential by humoral response. There is lower humoral and higher cellular immunity against SARS-CoV-2 in rs671 variant carriers compared to non-carriers, providing a potential basis for optimizing preventive measures and drug discovery.

Cotton seeds as the main by-product of cotton are not only an important raw material for edible oil and feed but also a source of biofuel. The quality of cotton seeds directly affects cotton planting and is closely related to the yield and fiber quality. However, the molecular mechanism governing cotton seed size remains largely unexplored. This study investigates the regulatory mechanisms of cotton seed size by focusing on two cotton genotypes, N10 and N12, which exhibit notable phenotypic variations across multiple environments. Developing seeds were sampled at various stages (5, 20, 30, and 35 DAP) and subjected to RNA-seq. The temporal pattern clustering and WGCNA on differentially expressed genes identified 413 candidate genes, including these related to sugar metabolism that were significantly enriched in transcriptional regulation. A genetic transformation experiment indicated that the overexpression of the GhUXS5 gene encoding UDP-glucuronate decarboxylase 5 significantly increased seed size, suggesting an important role of GhUXS5 in regulating cotton seed size. This discovery provides crucial insights into the molecular mechanisms controlling cotton seed size, helping to unravel the complex regulatory network and offering new strategies and targets for cotton breeding to enhance the economic value of cotton seeds and overall cotton yield.

Developing recombinant Saccharomyces cerevisiae strains capable of transporting and fermenting cellobiose directly is a promising strategy for second-generation ethanol production from lignocellulosic biomass. In this study we cloned and expressed in the CEN.PK2-1C strain an intracellular βglucosidase (SpBGL7) from Spathaspora passalidarum, and co-expressed the cellobiose transporter SiHXT2.4 from Scheffersomyces illinoinensis, and two putative transporters from Candida tropicalis (CtCBT1) and Meyerozyma guilliermondii (MgCBT2). While all three transporters allowed cell growth on cellobiose, only the MgCBT2 permease allowed cellobiose fermentation, although cellobiose consumption was stuck (incomplete). The analysis of the βglucosidase and transport activities revealed that the cells stopped to consume cellobiose due to a drop in the transport activity. Since ubiquitinylation of lysine residues at the N- or C-terminal domains of the permease are involved in the endocytosis and degradation of sugar transporters, we constructed truncated versions of the permease lacking lysine residues at the C-terminal domain (MgCBT2ΔC), and at both the C- and N-terminal domain (MgCBT2ΔNΔC), and co-expressed these permeases with the SpBGL7 βglucosidase in an industrial strain. While the strain harboring the MgCBT2ΔC transporter continued to produce stuck cellobiose fermentations as the wild-type MgCBT2 permease, the strain with the MgCBT2ΔNΔC permease was able to consume and ferment all the cellobiose present in the medium. Thus, our results highlight the importance of expressing cellobiose transporters lacking lysine at the N- and C-terminal domains for efficient cellobiose fermentation by recombinant S. cerevisiae.

This study investigates Autism Spectrum Disorders (ASD) in Greece, focusing on estimating prevalence and identifying regional disparities in children aged 4 to 7 years. Utilizing a quantitative, descriptive, and exploratory methodology, the research employed a structured questionnaire to gather extensive maternal and child health data. The sample consisted of 517 mothers of children diagnosed with ASD from all over Greece contributing to a nuanced understanding of ASD predictors. The study aims to elucidate the role of prenatal factors in the likelihood of an ASD diagnosis and their impact on the subsequent functionality of children with ASD. The study identified significant predictors of lower functionality in children with ASD, including higher maternal age, delayed ASD diagnosis, lower family income, and higher birth order. Prenatal health issues, such as vaginal bleeding and infections, also influenced functional outcomes. Notably, a family history of neurological or psychiatric conditions appeared protective. The regression model demonstrated robust predictive power, underscoring the complexity of genetic, environmental, and socioeconomic factors in ASD development. The findings advocate for early diagnosis and intervention, systematic screening, and addressing socioeconomic disparities to improve functional outcomes. The results support evidence-based service development and policy adjustments to enhance early identification, intervention, and rehabilitation for children with ASD. Establishing standardized case-recording procedures and an ASD register at national and regional levels is recommended for systematic monitoring and resource evaluation.

(1) Background: Adolescent girls have increasingly faced mental health challenges. We examined prevalence trends and associated risk factors for depression among adolescent girls. (2) Methods: Data for girls aged 12 to 17 years (N=4346) from the 2021 cross-sectional National Survey on Drug Use and Health were analyzed. Factors associated with depression were examined using multiple regression analysis. (3) Results: Rates of severe depression were significantly higher (p&lt;.001) in older girls (adjusted odds ratio [AOR]: 1.63, 1.61, those who did not have authoritative parents (AOR: 3.40), and those with negative school experiences (AOR: 4.03). Black and Asian/Native Hawaiian or other Pacific Islanders were less likely to report severe depression than white girls. As previously reported, non-White girls were significantly less likely to receive treatment for depression (p&lt;.05). Parents’ characteristics and school experiences had no effect on the likelihood of receiving mental health treatment. (4) Conclusion: Depression has become increasingly common among American adolescent girls, who are now three times as likely as adolescent boys to have had recent experiences with depression. Our results show that family structure, parenting style, and negative school experiences significantly contribute to the rate of depression and that treatment disparities exist with regard to race and ethnicity. The results of our research could be valuable for policymakers, healthcare professionals, and educators in developing specific preventative initiatives and support networks that effectively address these unique challenges.

This paper presents a novel approach to decoding the Indus script, which was used by the Indus Valley Civilization (IVC) from approximately 3300 to 1900 BCE. The main focus of this research is the structural analysis of the signs within the Indus script. The central objective of the paper is to determine whether the Indus script can be classified as an alphabet, and it aims to provide compelling evidence regarding the number of primary signs. This includes establishing the actual count of Indus signs through the decomposition of compound signs, identifying diacritics and analyzing their consistent usage, as well as exploring the underlying concepts and implications associated with sign extraction. To comprehensively examine the Indus script, the paper analyzes over 400 signs, encompassing the entire script rather than a select subset of signs or texts. The visual decomposition of the signs employs a simple grid methodology. By summarizing the logical findings, the paper successfully identifies the primary signs and develops an understanding of their phonetic representation within the alphabet. The study recognizes the diverse writing styles used to combine the basic signs, The writing style of the Indus script incorporates variations in formation, composition, and combination, resulting in a significant number of signs. The research findings indicate that the Indus Script primarily consists of only 40 core signs.

The purpose of this scoping review was to identify gaps in the literature and summarize findings from studies examining the use of silicon-, silica-, and silicate-based toothpastes for the remineralization and repair of mineralized tooth tissues. A 10-year literature search was conducted using PubMed and Scopus, adhering to PRISMA 2020 guidelines. A total of 331 studies were initially identified, with 56 full-text review articles. After selecting the manuscripts, 27 studies were qualitatively analyzed by four reviewers, focusing on the results of both in vivo and in vitro methods. The findings suggest that toothpastes containing silicon, silica, and silicate demonstrate promising results for remineralization and enamel repair, with evidence of mineral layer formation and/or deep enamel surface remineralization under various conditions. Additionally, the use of these toothpastes can lead to the obliteration of dentinal tubules within a few days. The results collectively support the efficacy of these toothpastes in enamel repair. Most of the clinical studies focused on dentine hypersensitivity, followed by white spot lesions. In conclusion, silicon-, silica-, and silicate-based toothpastes (bioactive-Si-toothpastes) can be considered effective based mostly on laboratory studies. There remains a need for more in vivo research studies on enamel and dentin mineral repair. Existing studies provide strong evidence that these technologies can reduce dentin hypersensitivity and promote enamel-dentin repair.

The study investigates the economic feasibility and farmer acceptance of utilizing treated wastewater (TWW) for agricultural irrigation, particularly in the Northern Jordan Valley. Despite its potential to mitigate water scarcity, concerns persist regarding its impact on soil health, crop yield, and land utilization, hindering widespread adoption. The research aims to measure farm profitability and farmers' willingness to embrace TWW through various blending scenarios with traditional surface water sources. The yield response function to salinity was incorporated into profit function to simulate crop profitability and water values. Results indicate that the introduction of TWW negatively affects salt-sensitive crops like citrus but positively impacts others such as date palm, olives, tomatoes, and peppers due to increased fertilizer content in irrigation water. Economic performance indicators reveal a gradual decrease in water net productivity for citrus with increasing blending ratios of TWW, with the water value decreasing accordingly. Higher percentages of treated water do not consistently lead to increased productivity, profitability, or net value added, emphasizing the need for careful consideration and understanding of economic risks associated with specific crops and water quality. To mitigate the impact of water salinity on citrus production, growers are advised to improve soil quality, periodically flush the soil with low-salinity water, and use salt-tolerant rootstocks. Regular monitoring of soil and water salinity levels is crucial for informed decision-making. While using TWW, water may offer cost savings.

Recent measurements in the MRX laboratory plasma [J.Yoo et al, Phys. Rev. Lett. 132, 145101 (2024)] have evidenced the role of lower hybrid drift waves produced during magnetic reconnections in producing an effective anomalous resistivity and heating of electrons. A detailed modelization of the energy transfer from the waves to electrons is missing, though. In this work, we attempt such an exercise using a Hamiltonian test-particle model for wave-electron interaction, valid for low-β weakly collisional plasmas. Quantitative agreement with MRX results is found.

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

Background: The increasing prevalence of severe obesity among children and adolescents poses a significant challenge for pediatricians and general practitioners. This study aimed to investigate the relationships between biochemical results, anthropometry, blood pressure measurements and bioimpedance analysis (BIA)-derived parameters, to identify potential cardiometabolic complications associated with severe obesity. Methods: The study included 347 children (162 boys, 185 girls) aged 0-19 years, meeting criteria for severe obesity based on BMI thresholds for different age groups. Patients were recruited in four pediatric endocrinology centers in Poland (Zabrze, Cracow, Rzeszow, Szczecin). Each participant underwent anthropometric measurements, pubertal stage assessment, blood pressure measurement, biochemical and hormonal tests and BIA. Results: BMI showed significant associations with fat mass percentage (FM%) and waist-to-height ratio (WHtR), but not waist-to-hip ratio (WHR). The relationship between BMI and FM% was stronger in girls and prepubertal children. Metabolic syndrome (MetS) Z-score showed a strong positive correlation with BMI in pubertal children. Negative correlation between HDL and triglycerides was observed only in boys. Prepubertal children exhibited more significant correlations despite a smaller sample size and shorter duration of obesity. Conclusions: Considering multiple parameters beyond BMI alone provides a better understanding of cardiometabolic risks associated with severe obesity in children. MetS Z-score was not a reliable indicator of increased cardiometabolic risk in younger children. Early-onset severe obesity was associated with a higher risk of metabolic complications. Early intervention is crucial to mitigate metabolic complications in this population.

African swine fever virus (ASFV) continues to spread globally causing severe economic losses to the pig farmers. Vietnam licensed two live attenuated vaccines based on the ASFV strains ASFV-G-ΔI177L and ASFV-G-ΔMGF, to control the ongoing ASF outbreaks. In 2023, newly emerging highly virulent recombinant ASFV viruses containing genetic elements from both ASFV p72 genotype I and II (rASFV I/II) strains were reported from Northern Vietnam. This study evaluated if the two vaccine strains were able to protect the pigs against the emerging rASFV I/II strain VNUA/rASFV/TN1/23. Pigs vaccinated with ASFV-G-ΔMGF or ASFV-G-ΔI177L, when challenged with rASFV I/II, succumbed to the infection, or developed signs of chronic ASF. The findings from this study show that both vaccine strains that are licensed and used in Vietnam, are unlikely to protect pigs from the emerging highly virulent rASFV I/II strains. This complicates the ongoing efforts to control ASF in Asia and globally and emphasizes the urgent need for a novel vaccine that can effectively protect pigs from the rASFV I/II strains.

A Clinical Prognostic Index (CPI) for improved patient selection for stereotactic liver-directed radiotherapy (SBRT) was developed. Using a large single-center database, 195 patients treated with SBRT for local control, including 66 with hepatocellular carcinoma (HCC) and 129 with metastatic liver disease, were analyzed. Only patients ineligible for alternative treatments were included. Overall survival was 11.9 months and 9.4 months in the HCC group and metastatic groups, respectively. In the combined dataset, Child-Pugh Score (CPS) (p=0.002), serum albumin (p=0.039) and presence of extrahepatic disease (p=0.012) were significant predictors of early death on multivariable analysis and were included in the CPI (total score 0 to 5). Median survival was 23.8, 9.1, 4.5 and 2.6 months for patients with 0, 1-2, 3 and 4-5 points, respectively. In the HCC dataset, CPS (p&lt;0.001) and gross tumor volume (p=0.013) were predictive of early death. In the metastatic dataset, serum albumin (p&lt;0.001) and primary disease site (p=0.003) were predictive of early death. The AUC for the combined, HCC, and metastatic datasets are 0.78, 0.84, 0.80 respectively. Poor liver function (defined by CPS and serum albumin) and extrahepatic disease were most predictive of early death, providing clinically important expected survival information for patients and caregivers.

A simple model of a measurement in a laboratory isolated from the environment is analyzed in detail, demonstrating the features of the collapse effect. Such an experiment can readily be implemented today under the idealization of an observer's memory as a simple quantum system. The central role of loss of information is emphasized.

It is not plausible to predict disasters; however, still the least that may be done is to get ready for that. In disaster circumstances, nowadays, the existing internet of things (IoT) technology is rather developed and capable of being highly beneficial. For many countries, the early warning system for natural catastrophes is a crucial challenge, especially for high seismic hazard countries. Primary function of an early warning system is to assist individuals and authorities to save lives and reduce secondary damage once a disaster occurs. Even though such systems have been defined for the earthquake on the basis of IoT, the least attention has been focused on the post decisions for substructure monitoring systems which can control the gas and electric lifelines given the critical time. Combination of Fuzzy system with IoT can improve the decision making process after the disasters occur. This program minimizes costs and destruction in cities. Tehran is a high seismic hazard area which contains an expanded network of the gas transmission system. Hence, a major seismic event may cause serious loss directly and indirectly owing to the damage to the gas and electric transmission network. The proposed early warning system contains a grid of strong ground motion stations. Each station contains five sensors to collect accurate data and send the data to the cloud server, then the server executes relevant scenarios.

Abstract: Abstract: In the present era, there is no longer a necessity to rely on outdated and laborious methods for attendance management in the field of education. Managing attendance for large groups of students in a classroom can be a challenging and time-consuming task when it comes to recording data. Fortunately, modern technologies offer us the opportunity to streamline attendance management and make it more efficient. One effective approach is Real-Time Face Recognition, which simplifies the process of tracking attendance for numerous students daily. We employ the Haar cascade classifier to identify positive and negative facial attributes, along with the LBPH algorithm for accurate face recognition. These techniques are implemented using Python programming language and the OpenCV library while incorporating a user-friendly Tkinter GUI (Graphical User Interface) for seamless usability. By embracing these advancements, we can revolutionize how attendance is managed in educational environments.

The current study investigated the neuroprotective effects of rutin hydrate (RH) in an Alzheimer’s disease (AD)-like learning and memory impairments rat model. Since AD is an age-related degenerative brain disorder characterized by a progressive worsening in cognitive function and memory, RH may be a potential drug for the treatment of AD-like memory loss, and this work is aimed to evaluate whether RH has neuroprotective effects in memory deficits induced by scopolamine (SCO). In our study, RH demonstrated beneficial effects as a neuroprotector in the brain and improved learning, memory, and synaptic plasticity in a rat. Rats were administered RH (100 mg/kg) and SCO (1.5mg/kg), and performed behavioral tests such as Morris water navigation test, Y-maze test, and passive avoidance test to evaluate the ability of learning and memory. In accordance with these findings, RH behaviorally attenuated SCO-induced shortening of step-through latency in the PA test, increased the percent of alternation in the Y-maze, and increased the time spent in the target zone in the MWN. Moreover, the neuroprotective effect of RH on learning and memory was investigated through the long-term potential on organotypic hippocampal slice cultures. RH increased the total activity of field excitatory postsynaptic potential (fEPSP) following theta burst stimulation and attenuated SCO-induced blockade of fEPSP. This approach could potentially be used as a therapeutic strategy for the restoration of learning and memory function and the prevention of the progression of AD. SCO treatment decreased the levels of BDNF/TrkB/ERK/CREB/Bcl2 and increased the Bax protein level in rat hippocampus. RH ameliorated the expression of these proteins by attenuating SCO-induced up or downregulation in the hippocampus. Based on these findings, the results highlight the molecular and cellular mechanisms through which RH is proposed to exert its neuroprotective effects in the prevention and treatment of learning and memory deficit disorders.

Objectives: Valsalva maneuver is performed during strength physical exercises, because it stabilizes the torso through increased intra-abdominal pressure. By contrast, yoga practitioners are discouraged from Valsalva. Instead, they use ujjayi breath, which consists of unstopped breathing through the narrowed glottis. Methods: This study was an observational research performed in healthy participants. The aim of this study was to evaluate veins in the groin area during different types of breathing. We examined 10 healthy people in the standing body position during: a) normal breathing b) Valsalva maneuver c) ujjayi breath. We measured the cross-sectional areas of the femoral and the great saphenous veins in the proximity to the sapheno-femoral junction. Results: In comparison with normal breathing, there were only slight dilatations of examined veins during Valsalva and ujjayi. The cross-sectional area of femoral vein increased by 7-9% during Valsalva, and 2-4% during ujjayi; cross-sectional area of the great saphenous vein increased by 17-18% during Valsalva and 15-16% during ujjayi. In all participants the terminal and preterminal valves of the great saphenous vein were competent. However, Valsalva maneuver was associated with complete closure of the terminal valve, while during ujjayi breath this valve was opening and closing, following the breathing. Conclusions: In the standing body position both Valsalva and ujjayi breath have minimal effect on cross-sectional areas of the veins in the groin. On the other hand, ujjayi breath allows for undisturbed flow through the sapheno-femoral junction, while Valsalva interrupts this flow, with blood stagnation distally from the terminal valve.