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In this investigation, we focused on the synthesis and characterization of CsCaF3 compound doped with europium (Eu3+) ions using a solid-state route. To analyze the crystal structure of the synthesized phosphors, X-ray diffraction analysis was employed. Additionally, the doped sample underwent examination of surface morphology and elemental composition through Field Emission Scanning Electron Microscopy and EDAX mapping. The color of the pure and doped CsCaF3 sample was quantified and fitted using Color coordinate graph by the Commission Internationale de l'Eclairage (CIE). The red emission on the doped CsCaF3 compound was detected at 465 nm, which is the transition from 5D0 to 7Fj (j = 0, 1, 2, and 3). The 0.5 mol. % Eu3+ doped CsCaF3 sample was found to have a color purity of 81% and an associated color temperature of 1660 K, indicating its suitability for aesthetic lighting applications. Furthermore, thermoluminescence study, electron paramagnetic resonance (EPR), and effective atomic number (Zeff) calculations were conducted to provide valuable information for potential radiation dosimetry applications.

The diverse range of uses of unmanned aerial vehicles has garnered significant attention in research. The scientific literature that supports the data obtained from UAVs recording information from various sensors is presented in this manuscript. It summarizes current developments in remote sensing, including radar, photogrammetry, thermal imaging, light detection and ranging sensors (LiDAR), data gathering, and analysis. It is predicated on the instruments’ ability to gather and analyze accurate data. To identify some of the most urgent research problems, it also shows surveys based on research methodologies. The present research focuses on the proliferation and social effects of unmanned aerial vehicles (UAVs). It also encourages novice researchers to pursue this area of study and suggest novel approaches to the design or setup of these flying machines. UAVs have entirely transformed due to advancements in internet technology and current technologies which include camera defects, environmental monitoring, charging, impediments, crop monitoring, energy consumption, military applications, and technology gaps.

Green-synthesized silver and copper nanoparticles (NPs), along with their composites, exhibit various biological activities. Ocimum sanctum (Holy basil), traditionally used as medicine in South Asia, treats respiratory disorders, digestive issues, skin diseases and inflammatory conditions. Modern scientific studies support these bioactivities; however, no studies have investigated their bioactivity in combination with NPs. In this study, silver and copper NPs were synthesized using AgNO3 and CuSO4·5H2O solutions, respectively, with Ocimum sanctum leaf extract, and their antibacterial, antioxidant and anticancer properties were examined. Spectroscopic analyses, including Fourier transform infra-red (FTIR), transmission electron microscopy (TEM) and X-ray diffraction (XRD), elucidated the physicochemical characteristics of the green-synthesized nanoparticles (Os-AgNPs and Os-CuNPs), revealing sizes of 11.7 and 13.1 nm, respectively. The Os-AgNPs:Os-CuNPs nano-composite with a 1:2 ratio exhibited a zone of inhibition ranging from 8 to 12 mm against tested bacterial pathogens. Additionally, the NPs and their composites demonstrated potent antioxidant activity, with notable 2-diphenyl-2-picrylhydrazyl (DPPH) scavenging activity observed in composites with ratios of 2:1 and 1:2. Furthermore, they displayed potential anticancer activity against human leukaemia (Jurkat) cancer cells. Although no distinct difference in anticancer property was observed among the NPs and their composites, our study highlights their well-defined nanostructure and significant biological activity, suggesting their potential as therapeutic agents in the pharmaceutical industry.

In this study, we synthesized and characterized pure CsCaF3 and CsCaF3 doped with samarium (Sm3+) ions using a solid-state method. X-ray diffraction analysis was employed to examine the crystal structure, while field emission scanning electron microscopy analyzed the surface morphology of the doped sample. A color coordinate graph was used to calculate the color, with the Commission Internationale de l'Eclairage (CIE) fitting the color of both pure and doped samples. Upon excitation at 405 nm (6H5/2→6F7/2 transition), the doped CsCaF3 emitted an orange light. The CsCaF3:Sm3+ sample (0.8 mol%) displayed 86% color purity and a color temperature of 2191 K, making it suitable for lighting applications. The thermoluminescence (TL) curve of the beta-irradiated CsCaF3:Sm3+ (0.8 mol%) sample showed peaks at 174 °C and 297 °C. Preheating techniques eliminated the low-temperature peak, and the peak temperature of maximal TL intensity (Tm) was 297 °C. The activation energy (Ea) and frequency factor (s) were determined using the peak shape method and varying heating rates. The dosage response of CsCaF3:Sm3+ (0.8 mol%) was examined for potential dosimetry applications.

Abstract Over the past few years, explainable artificial intelligence (XAI) has become increasingly popular as a result of the demand for AI systems that are simpler to comprehend and with greater interpretability. This study provides a conceptual framework and a quick assessment of the work done in explainable artificial intelligence. Using the Vosviewer application, the researchers analyzed 4781 research publications from the Scopus database, spanning 2004 to 2023. Observations indicate a rapid and exponential growth in the quantity of publications, commencing in 2018. The importance of the study is shown by the analysis of publishing activities according to the year of publication and the geographical area, together with citation analysis, research methodologies, and data analysis techniques. The researchers have highlighted ten interesting areas that require further study from future researchers. Moreover, the work emphasizes the legal, ethical, and social consequences for the researchers.

To enhance the photoluminescence property of Li7La3Zr2O12 (LLZO), Eu was doped using a solid-state synthesis technique. X-ray diffraction and Raman spectroscopy analysis were used to examine the crystal structure of the synthesized phosphors. The optical band gap values of pristine and Eu3+ doped LLZO phosphor investigated using ultraviolet-visible (UV-Vis) spectroscopy were measured to be 2.74 and 2.97 eV, respectively. The wavelengths of pure and doped LLZO samples were measured and fitted by the Commission Internationale de l’Eclairage (CIE) chromatic coordinate graph. These samples were found to emit blue emission at 354 nm (pure LLZO) and red emission at 464 nm (doped phosphor), which correspond to the 5D0 to 7Fj (j = 0, 1, 2, and 3) transition. The purity of the color and correlated color temperature with respect to the 0.9 M.W% Eu3+ doped (activated) LLZO sample were estimated to be 80% and 1719K, respectively. The indication of its maximum emissive capability at this rate was found suitable for aesthetic lighting applications.

Abstract The oxidation resistance of Hf0.28B0.72 and Hf0.11Al0.20B0.69 thin films was investigated comparatively at 700 °C for up to 8 h. Single-phase solid solution thin films were co-sputtered from HfB2 and AlB2 compound targets. After oxidation at 700 °C for 8 h an oxide scale thickness of 31 $$\pm$$ ± 2 nm was formed on Hf0.11Al0.20B0.69 which corresponds to 14% of the scale thickness measured on Hf0.28B0.72. The improved oxidation resistance can be rationalized based on the chemical composition and the morphology of the formed oxide scales. On Hf0.28B0.72 the formation of a porous, O, Hf, and B-containing scale and the formation of crystalline HfO2 is observed. Whereas on Hf0.11Al0.20B0.69 a dense, primarily amorphous scale containing O, Al, B as well as approximately 3 at% of Hf forms, which reduces the oxidation kinetics significantly by passivation. Benchmarking Hf0.11Al0.20B0.69 with Ti–Al-based boride and nitride thin films with similar Al concentrations reveals superior oxidation behavior of the Hf-Al-based thin film. The incorporation of few at% of Hf in the oxide scale decelerates oxidation kinetics at 700 °C and leads to a reduction in oxide scale thickness of 21% and 47% compared to Ti0.12Al0.21B0.67 and Ti0.27Al0.21N0.52, respectively. Contrary to Ti–Al-based diborides, Hf0.11Al0.20B0.69 shows excellent oxidation behavior despite B-richness.

Background: Self-care practices plays an important role in reducing the mortality and morbidity associated with hypertensive complications. Therefore, this study aimed to assess poor self-care practices on hypertension and its predictors among patients attending the non-communicable disease clinics in urban and rural primary healthcare settings in Puducherry, South India. Methods: A cross-sectional analytical study was conducted among people with hypertension aged ≥18 years from September to December 2023. Systematic random sampling technique was used to recruit the participants. The data on self-care practices were captured using the “Hypertension Self-Care Activity Level Effects (H-SCALE)” questionnaire. The subscales were medication adherence, low-salt diet, physical activity, smoking, alcohol and weight management. Participants who adhered 60 years of age and 182 (68.2 %) were females. About 79 (29.6 %) had poor self-care practices. Among 267, 63 (23.6 %) had uncontrolled hypertension and it was more among those with poor self-care practices (46.1 % Vs 24.5 %). After adjusting for co-variates, urban residents (APR: 1.7, 95 % CI: 1.1–2.4, p = 0.004) and uncontrolled hypertension status (APR: 1.8, 95 % CI: 1.1–2.4, p

Metal nanoparticles have a lot of interesting characteristics, and the field of medicinal applications may benefit significantly from them. In this investigation, gold-platinum (Au-Pt) bimetallic nanoparticles were synthesized employing leaf extract from Croton Caudatus Geisel. Utilizing transmission electron microscopy (TEM) examination and powder X-ray diffraction, the size of the synthesized nanoparticles was found to be between 12 and 33 nm. Using Debye Scherrer equation, particle size of the synthesized nanoparticle is determined and also consistent with transmission electron microscopy (TEM) analysis. The materials tend to be rectangular-shaped. This is a single-step, green protocol that does not employ any capping or reducing agents. The bio-active compounds in leaf extract act as reducing/capping/stabilizing agents and also fabricated with surface of the nanoparticles. Since green synthesis is an easy, stable, quick, low-cost, and environmentally friendly process, it opens up new possibilities for the synthesis of nanoparticles. Bimetallic nanoparticle synthesis generally involves mixing two different aqueous metal solutions with a natural reducing agent, like a plant extract. It has been proposed that plant phytochemicals with reducing or antioxidant properties reduce metal ions into metal nanoparticles. Scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive X-ray (EDX) analysis, Fourier-transform infrared (FT-IR) spectroscopy, and ultraviolet (UV) spectroscopy were all utilized to completely characterize the synthesized nanoparticles. It has been found that biological studies exploring in vitro antibacterial, in vitro antifungal, and anti-cancerous activity showed significant implications. In accordance with study results, the synthesized nanomaterials had a strong cytotoxic effect on HeLa cancer cell lines, with an MTT assay IC50 value of 37.17 μg/ml/24 h.

A commercial donkey farm at Tirunelveli with 323 pregnant donkeys was facing an abortion storm affecting 53 (16.4%) pregnant jennies in the last trimester, which were presented to LAC-OP-OG unit of Veterinary Clinical Complex, Veterinary College and Research Institute, Tirunelveli. Clinical examination revealed pyrexia (39.4℃) and congested conjunctival mucous membrane. Gynaecological examination revealed oedematous vulva with serosanguinous vaginal discharge. Ultrasonography examination revealed the presence of corpus luteum, medium-sized follicles, thickened uterine endometrium and fluid accumulation at the tip of both uterine horns. Serum progesterone and cortisol levels were 5.35±0.28 ng/mL and 6.14±0.13 ng/mL, respectively. Microbiological examination of foetal fluids revealed gram-negative bacilli which was confirmed as Salmonella spp. Histopathology of aborted foetal parts revealed cellular degenerative changes. All jennies were treated with antibiotics, and antihistamines along with intrauterine douching for five consecutive days. Other pregnant jennies in the farm were isolated and prophylactic antibiotics and immune booster supplements were administered. Thus, this study documented unconventional infectious agent such as Salmonellosis emerging as a leading cause of abortion storm and reproductive loss in donkey farming in Tamil Nadu.

Abstract Economics is the study of the allocation of scarce resources to meet human wants and needs and has a critical role to play in addressing challenges related to environmental sustainability, community resilience, and food security. In the context of aquaculture, the key to such a discussion is understanding the linkages of aquaculture farming businesses with other economic sectors and how policy decisions that affect aquaculture result in economic ripples throughout local, regional, and national economies. The only previous national estimates of the economic contributions of U.S. aquaculture are nearly 30 years old. The current study was based on comprehensive data from detailed farm‐level surveys (that captured 77% of the total value of U.S. aquaculture) supplemented by information from publications on the remaining aquaculture sectors. The economic contributions measured in this study were limited to those at the farm level and do not include subsequent impacts that occur as farmed products move through processing, distribution, food service, and retail sectors in the U.S. economy. Results showed that U.S. aquaculture farms contributed $4 billion annually and supported more than 22,000 jobs each year. Labor income and value‐added contributions were $1 billion and $3 billion, respectively. Analysis of the linkages of U.S. aquaculture production activities with other economic sectors showed that nearly all (96%) economic sectors were supported to some degree by U.S. aquaculture farms. Foodfish farms generated the greatest contributions, followed by mollusk farms. Freshwater aquaculture farms contributed twice that of the contributions of marine aquaculture because of the greater size of the freshwater aquaculture sector. Growth of both freshwater and marine sectors would increase overall contributions to the economy. Constraints to growth of aquaculture include regulatory barriers that have restricted existing sectors from meeting current demand for their products. The lack of an adequate regulatory framework for offshore marine aquaculture has constrained its growth and development, especially with respect to the rest of the world. Streamlined regulations implemented in a more timely and efficient manner could result in substantially greater economic contributions from existing U.S. aquaculture farms. The total economic impact of U.S. aquaculture production is likely three to four times greater than the farm‐level impacts estimated in this study as a result of impacts that occur as aquaculture products move downstream through various marketing channels. Additional research is needed to measure the impacts of U.S. aquaculture products in the processing, distribution, food service, supermarket, and restaurant levels of the marketing chain to fully capture the total economic contributions from U.S. aquaculture.

ABSTRACTTyphoid fever is a significant public health concern with most of the sufferers between 15 and 25 y of age in Nepal. We undertook this study to demonstrate Vi polysaccharide conjugated with diphtheria toxoid (Vi-DT) conjugate vaccine which is non-inferior to Typbar typhoid conjugate vaccine, a Vi polysaccharide vaccine conjugated with tetanus toxoid (Vi-TT) with a focus on the adult population from Dhulikhel Hospital which was one of the total four sites in Nepal. In this study, we assigned the eligible participants in 1:1:1:1 ratio by block randomization, and stratified into three age groups (6 months to less than 2 y, 2 y to less than 18 y, and 18 y to 45 y), allotted to Group A, B, C, and D. Group A, B, and C received 25 μg (0.5 mL) of Vi-DT study vaccine and participants in Group D received 25 μg (0.5 mL) Vi-TT vaccine. We descriptively analyzed safety in all the participants receiving one dose of the investigational vaccine. The anti-Vi-IgG seroconversion rate in Vi-DT recipients was 99.71% (97.5% CI 98.04–99.96; 344 of 345 participants) and 99.13% (94.27–99.87; 114 of 115) in Vi-TT recipients which indicates that Vi-DT vaccine is non-inferior to Vi-TT vaccine. In safety aspect, 16.81% of total subject had at least one solicited adverse reaction and 22.61% of the Vi-TT participants experienced at least one solicited adverse reaction with most of them being local adverse reactions. None of the enrolled participants reported serious adverse events. Our study shows that a single dose of the Vi-DT vaccine is immunogenic, safe to administer and non-inferior to the Vi-TT vaccine four weeks after vaccination.

The impact of contaminants on Copepod sp. and its molecular response is least explored, despite their abundance and dominance among invertebrates in aquatic environments. In the present investigation, Dioithona rigida, a cyclopoid zooplankton, was treated with selenium nanoparticles (SeNPs) to determine the associated biochemical changes, and the chronic exposure effects were recorded using transcriptomic analysis. It was found that, SeNPs were acutely toxic with a lethal dose 50% of 140.9 mg/L. The de novo assembled transcriptome of the copepod comprised 81,814 transcripts, which underwent subsequent annotations to biological processes (23,378), cellular components (21,414), and molecular functions (31,015). Comparison of the expressed transcripts against the treated sample showed that a total of 186 transcript genes were differentially expressed among the D. rigida treatments (control and SeNPs). The significant downregulated genes are coding for DNA repair, DNA-templated DNA replication, DNA integration, oxidoreductase activity and transmembrane transport. Similarly, significant upregulations were observed in protein phosphatase binding and regulation of membrane repolarization. Understanding the impact of SeNPs on copepods is crucial not only for aquatic ecosystem health but also for human health, as these organisms play a key role in marine food webs, ultimately affecting the fish consumed by humans. By elucidating the molecular responses and potential toxicological effects of SeNPs, this study provides key insights for risk assessments and regulatory policies, ensuring the safety of seafood and protecting human health from the unintended consequences of nanoparticle pollution.

This study investigates the characteristics of an unsteady, incompressible, and electrically conductive flow. The flow consists of H2O based nanofluid that contains suspended sphere-shaped Cu nanoparticles. The flow occurs across an oscillating and porous vertical plate. Simultaneous non-dimensional governing partial differential equations are solved by pdepe solver in MATLAB 22a, accounting for thermophysical properties and relevant parameters. We analyzed the behavior of the Cu -H2O nanofluid in relation to various fundamental parameters, including thermal buoyancy force, kinetic energy, thermal conductivity, volume fraction of nanoparticles, and time. Additionally, we determined the rate of local heat transfer and skin friction of the Cu-water nanofluid, presenting the results in tabular form. Our findings were compared with previously reported results to validate the accuracy and reliability of the pdepe solver. The pdepe solver in MATLAB is a straightforward and convenient tool for simulating and visualizing models, It is an alternative method for solving IBVP of parabolic & hyperbolic.

Background: Soil-transmitted helminth infections (STHs) in pregnancy have been linked to maternal anemia, low birth weight, and adverse perinatal outcomes. STH includes Ascaris lumbricoides, hookworm, and Trichuris trichiura. However, conflicting evidence exists regarding these effects. Hence, we aimed to assess the association of STH infections with perinatal outcomes. Methods and Materials: A community-based cohort study was conducted among pregnant women in primary care settings in Puducherry, South India, during December 2019 to April 2021. Stool samples were collected for STH screening and confirmed using polymerase chain reaction. Information on perinatal outcomes and hemoglobin levels were extracted from case records. The association of pre-term birth, low birth weight, anemia, and miscarriages with STH infection was analyzed using the Chi-square test. Results: Among the 650 women enrolled, 58 (8.9%) had one of the STH infections. At the time of recruitment, 336 (52.0%) women had anemia. Twenty-four women (3.7%) had miscarriages, 14 (2.2%) had pre-term birth, and 65 (10.4%) had low-birth-weight (LBW) babies. All 14 pre-term babies had LBW, and out of 65 LBW, 40 were in mothers with anemia. Incidence of LBW, pre-term deliveries, and anemia were higher in women with STH than in those without STH (LBW: 12.3% vs 10.2%, P = 0.62; pre-term: 3.5% vs 2.1%, P = 0.5; and anemia: 54.4% vs 51.85, P = 0.7). Conclusion: Though the incidence of anemia, LBW, and pre-term delivery was higher in women with STH infections compared to those without STH, we did not find any significant association between the presence of STH infections and perinatal outcomes.

Abstract Aquaculture is a rapidly growing food production technology, but there are significant concerns related to its environmental impact and adverse social effects. We examine aquaculture outcomes in a three pillars of sustainability framework by analyzing data collected using the Aquaculture Performance Indicators. Using this approach, comparable data has been collected for 57 aquaculture systems worldwide on 88 metrics that measure social, economic, or environmental outcomes. We first examine the relationships among the three pillars of sustainability and then analyze performance in the three pillars by technology and species. The results show that economic, social, and environmental outcomes are, on average, mutually reinforced in global aquaculture systems. However, the analysis also shows significant variation in the degree of sustainability in different aquaculture systems, and weak performance of some production systems in some dimensions provides opportunity for innovative policy measures and investment to further align sustainability objectives.

Simulating and analyzing thermal behavior in the human body is crucial for various biomedical applications. The skin, composed of multiple layers, is connected to the vascular bed, which comprises venules and capillaries. Blood, the body's primary thermoregulator, flows towards the tissue through capillaries and away through venules. These blood vessels, separated by a thin layer of tissue, prevent mixing while enabling efficient heat exchange. Understanding this counterflow mechanism is vital for studying heat transfer within the vascular bed. In this study, the capillary, tissue, and venule are modeled as regions 1, 2, and 3, respectively, forming a three-layered rectangular channel. Heat transfer occurs via diffusion through the semi-permeable tissue layer, with slip conditions applied at its interface. The bioheat transport equation, combined with the Navier-Stokes equation, governs the thermal and fluid behavior. Analytical expressions for velocity are derived for all regions, while the temperature distribution, transformed into integral equations, is solved numerically. The resulting system of linear equations provides insights into the thermal dynamics within the vascular bed, with findings represented graphically.

Background: Neuroinflammation in the frontal cortex and hippocampus is the key contributor in the pathogenesis of neurodegenerative diseases. Lipopolysaccharide (LPS) is a bacterial endotoxin (E-coli phenol extract) used to induce the neuroinflammation in animal models. Our study is aimed to study the protective effect of metformin on the neuronal morphology of the frontal cortex and hippocampal regions in lipopolysaccharide induced neuroinflammation. Methods: This is an animal model study, which utilized the twenty-four male Wistar rats of about 6 weeks old. The rats were divided into 4 groups, which included control, experimental and treatment groups. 170 μg/kg of LPS injection was administered intraperitoneally once a week for the first eight weeks and the treatment groups received metformin, which was administered orally (100 mg and 200 mg/kg body weight/day). Rotarod test was used to confirm the neuronal loss and clinical analysis among the groups. Results: Neuronal loss caused by the exposure to LPS in the dentate gyrus, CA4, CA3, CA2, CA1 (cornu ammonis regions) and frontal cortex, has been improved by the metformin treatment. Among the two doses of metformin, 200 mg/kg body weight exhibited better effect than the 100 mg/kg/body weight. The rotarod test findings suggested that, in the MF treated groups, the number of falls were reduced. Conclusion: The histological analysis and clinical observation by the rotarod test revealed that, metformin attenuated the neuroinflammatory damage, suggesting that it has a neuroprotective role. This study recommends repurposing the usage of metformin as a neuroprotective agent.

In this study, Christensen's stochastic theory is utilized on rough surfaces' hydrodynamic lubricating effect to examine how surface roughness, couple stress fluid, slip velocity, magnetohydrodynamic (MHD), and the triangular surface interact. Modified Reynolds equation is derived analytically using combining theories of Stokes couple stresses, Lorentz forces, and Christensen's stochastic hypothesis about hydrodynamic lubrication. Pressure, load carrying capacity and squeeze film time expression is derived mathematically using Reynolds equation that accounts for surface roughness and coupling stress. For various parameters including rough parameter, slip velocity, Hartmann number, and couple stress, the lubricating characteristics are analysed graphically. Squeeze film time, load carrying capacity, and pressure are enhanced by an increase in slip velocity, couplestress and magnetic field. The lubrication characteristics decreases (increases) on squeeze film pressure, load carrying capacity and squeeze film time through increasing values of the longitudinal (transverse) roughness parameter.

Abstract The Delta Select channel catfish strain (DS) was developed by selection for increased growth and carcass yield. Progeny from DS and the Delta Control (DC) strain (a randomly bred strain from the same base population as DS) were compared in three trials. Trial 1: unvaccinated ~1‐year‐old fingerlings from each strain reared communally in 0.4‐ha ponds. Trial 2: vaccinated ~ 1‐year‐old fingerlings from each strain grown in separate replicated 0.4‐ha ponds and fish in about half the ponds were given an ESC vaccine‐booster at 13 months post‐hatch. Trial 3: same procedures as Trial 2, except fish were raised in replicate 0.04‐ha ponds with no vaccine‐booster. In Trial 1 DS were larger at stocking, larger at harvest, and had higher carcass yield than DC; in Trial 2 DS were larger at harvest, had better survival and higher production/ha than DC. Vaccine‐booster had no effect on fish growth or survival. DS and DC were not different for any traits in Trial 3. Although outcome varied among trials, the overall results indicated a vaccine booster did not affect growth or survival, DS strain fingerlings grew faster than DC fingerling, and DS had higher carcass yield than DC strain fish when reared communally.

Remote sensing images (RSIs), a keystone of modern agricultural technology, refer to spectral or visual data captured from drones, satellites, or aircraft without direct physical contact with the Earth's surface. These images provide a wide-ranging view of agricultural landscapes, providing valuable insights into land use, crop health, and environmental conditions. Agricultural food crop classification, a vital application within precision agriculture, includes the detection and classification of different crops cultivated in a certain region. Traditionally reliant on manual techniques, the development of technologies, particularly the incorporation of RSIs, has revolutionized this process. Agricultural food crop classification has become more sophisticated and automated by harnessing the wealth of data received from RS, which facilitates precise management and monitoring of crops on a large scale. Deep learning (DL), a branch of artificial intelligence, plays a more effective role in these synergies. The incorporation of DL into the RSI analysis enables high-precision and efficient detection of various crop types, assisting more informed decision-making in agriculture. This study proposes a new Dipper Throat Optimization Algorithm with Deep Learning based Food Crop Classification (DTOADL-FCC) algorithm using Remote Sensing Imaging for Agricultural Resource Management. The DTOADL-FCC method aims to apply DL algorithms for the classification of different crop types. In the DTOADL-FCC method, fully convolutional network (FCN) based segmentation process is performed. Next, the DTOADL-FCC method exploits the SE-ResNet model for learning intrinsic and complex features. The DTOADL-FCC method makes use of DTOA for the hyperparameter tuning process. Lastly, the classification of crop types takes place using the extreme learning machine (ELM) model. The study utilizes mathematical formulations including activation functions, loss functions, fitness calculations, and iterative update processes. A brief set of simulations showcases that the DTOADL-FCC method achieves remarkable performance over other techniques with much improved results.

This study's main goal is to examine the advantages of a two-dimensional Reiner-Philippoff fluid flow via a stretched sheet. Furthermore, radiative heat transmission and magnetic dipole media are taken into account. It is now possible to have a comprehensive understanding of the rheological properties of non-Newtonian fluids by the use of the Reiner-Philippoff fluid, which distinguished the transport mechanisms of the fluid. The boundary layer method is used in the process of developing the model. Through the use of similarity variables, these equations are converted into a two-dimensional model. In order to achieve the numerical answers, the RKF-45 order is used first. A combination of numerical standards and visual representations is used in order to demonstrate them. An analysis of the features of the entangled flow, including the distributions of velocity and temperature, is carried out from a visual standpoint. According to the results of this study, the temperature field gets more prominent with a thicker λ0 and the temperature of the fluid goes down with more γ1. Aside from that, the decrease of hat transfer occurs more often with pseudo-plastic fluids than with Newtonian dilatant fluids.

Alloys are used in a wide variety of contexts, including aircraft building, the military, industry, medicine, and manufacturing. Alloys including tools, equipment, cars, and structures. Furniture, shipping containers, and medical supply storage containers are among products that benefit from the usage of aluminium alloys. To further enhance simultaneous heat transmission, scientists have developed nano-fluids, which are essentially nano-particle suspensions in a regular fluid. Ferric Sulfate may be added to soil to improve its quality and is also used to clean water. Iron (3+) sulphate is an iron (III) and sulfate (III) combination with a 3:2 ratio of iron (III) to sulfate (III) ions. As a catalyst, mordant, and astringent, it serves several purposes. It is a sulphate of a metal and a molecule of iron. Due of these purposes, we employ the K-K model to study how alloys and nanoparticles affect surface flow and heat transfer. By making use of the boundary layer approach and the flow assumptions, the partial differential equations (PDEs) were generated by approximating the Navier-Stokes equation. This system is transformed into ordinary differential equations (ODE's) using similarity transformations. Using the BVP4C method, a system with non-dimensions is defined. Mathematical and pictorial explanations are provided for the consequences of the key physical variables. It is founded that the magnitude of the temperature field is directly proportional to the R value; a higher value indicates more heat conduction to the liquid. Additionally, the velocity of the fluid lessened by the impact of melting effect.

Background: Among depressed patients, escitalopram plasma levels differed between those who were considered as extensive metabolizers and poor metabolizers of CYP2C19. However, the majority of research utilized the dose-response relationship. Consequently, we investigated the effect of variations in the CYP2C19 gene on the levels of drug in the bloodstream of individuals suffering from Major Depressive Disorder (MDD) in south India. Methods: A total of 109 individuals with MDD who were prescribed escitalopram at doses of 5, 10, 15, or 20 mg daily participated in this research. We used HPLC with SPD-10AVP UV-Visible detector to measure the escitalopram concentrations in the blood. The polymorphisms of the CYP2C19 were determined by employing the PCR techniques. Results: Our study found that 55% of the subjects were intermediate metabolizers, followed by extensive (19.3%), poor (17.4%), and ultra-rapid (8.3%). The significant correlation is identified between the steady state plasma concentration and Sex with (P - Value < 0.05), insignificant correlation was seen in Age and BMI with (P - Value > 0.05). The majority of gene variants seen in the study population were CYP2C19*1/*2, accounting for 49 individuals (44.9%). Conclusion: These findings showed that sex had a substantial impact on the CYP2C19 genetic variation. Medication administration to individuals with CYP2C19 PM requires special caution.

In the 21st century, there have been significant indigenous advancements in the field of physiotherapy. However, there still exist certain sociocultural and spiritual beliefs among practitioners. Through meticulous examination, evaluation, diagnosis, prognosis, and physical intervention, physiotherapists utilise mechanical movements and force to treat impairments and help improve function, mobility, and quality of life. The cultural framework plays a crucial role in how individuals experience health, illness, and disability. Simultaneously, sociocultural factors are pivotal in the physical function, health, and illness of individuals. This paper explores the social, cultural and spiritual influences on physiotherapy across different societal and professional contexts. While there have been several recent studies providing snapshots of advancements in technologies in the healthcare system, there are not as many focusing on these three aspects in the clinical practice of physiotherapists. Due to the different eras in the history of physiotherapy, the present article demonstrates how physiotherapists are influenced by social, cultural, and spiritual domains. It is challenging to generalise the results in every situation and geographical area. Therefore, physiotherapists should be proactive in addressing these healthy beliefs at the grassroots level within the healthcare society. To create a personalised treatment plan, goal-setting, and care plan for the patient, the physiotherapist finds great value in understanding the patient’s sociocultural and spiritual history.

An investigation of the influence that the Cattaneo–Christov heat and mass flux have on the whirling flow that occurs across a stretchable cylinder is being carried out in this study. This model takes into consideration the impact of a magnetic field, in addition to also taking into account heat and the diffusion of solutes. During the process of developing this mathematical model, the Navier-Stokes equation was employed to illustrate the flow that was predicted. Under the flow assumptions, the partial differential equations were derived from an approximation of the Navier-Stokes equation using the boundary layer approach. In order to make advantage of the ordinary differential equations formalism, the system is transformed via the application of similarity transformations. The Runge Kutta Felberg-45 (RKF-45) method gives an explanation of a system that does not have any dimensions. Both quantitatively and visually, the impacts of the key physical variables are shown. It is noticed that, the Swirl velocity profile decayed for higher values of magnetic parameter and Reynolds Number. Further we noticed that, the temperature fields strengthen with enhanced values of Eckert numbers (Ec1 and Ec2).

Abstract Feed conversion ratio (FCR) is widely used as a measure of feed use efficiency in commercial aquaculture production and research. Surprisingly, little work has focused on the factors that affect FCR in plankton‐based, commercial ponds despite the widespread use of FCR as a production metric. Proposals to use FCR as a numeric standard for environmental regulation (mandatory or voluntary) raise questions as to whether FCR meets the reliability and consistency requirements of a good metric, and whether it would lead to desired behavioral changes. This article summarizes FCR data from university research verification programs conducted on US catfish farms and databases developed from commercial farm records. The relevant research literature is synthesized with respect to factors that affect FCR. US catfish is used as a case study because pond‐level data from verification trials (Extension/research‐led on‐farm trials of best available science) and commercial farm records are available. While specific to US catfish production, the analysis provides insights into factors affecting FCR that likely apply to other pond‐based aquaculture species. Commercial verification of pond data showed (1) significant variation in FCR (coefficients of variation from 1% to 47%) among ponds with similar stocking, feeding, and aeration rates; (2) significant effects of survival on FCR; and (3) no significant effects on FCR of yield, feed type, management, or production system. Improvements in FCR would occur with improved survival that requires improved management of federally protected fish‐eating bird populations and development of additional, effective vaccines for diseases. FCRs were found to not exhibit the degree of reliability and consistency required for use as an effective metric or numeric standard for regulatory purposes. Use of FCR for mandatory or voluntary regulation is unlikely to lead to behavioral changes by farmers.

The aim of this study is to investigate convective heat transfer on a flat surface in the presence of magneto-hydro-dynamic (MHD) flow. The analysis considers the Darcy-Forchheimer porosity medium in the flow. The study focuses on analyzing the heat transfer rate, incorporating joule heating and convective-conductive heat flux effects. The influence of varying fluid properties on the flow behavior is examined. The governing flow equations are initially expressed as partial differential equations (PDEs) and then transformed into ordinary differential equations (ODEs) using appropriate similarity transformations. The numerical method RKF-45 is employed to solve these ODEs. The results highlight the impact of different parameters in the model. It is observed that a higher Darcy parameter leads to a decrease in fluid velocity. Additionally, the performance of carbon nanotubes is superior compared to MoS2 nanoparticles in this study.

The performance of electrochemical double-layer capacitors (EDLCs) is evaluated by the capacitance of activated carbon (AC) electrodes. The capacitance of AC electrodes is influenced by many factors such as precursor type, activation method, pore structure, surface chemistry and electrolytic properties. In this paper, we present a comparative study of machine learning based prediction of surface area, mesopore volume and total pore volume of activated carbon for energy storage applications. The ML models were trained on a dataset of synthetic data that were generated from the limited number of experimental data and which included the activation temperature, methylene blue number and iodine number of the activated carbon (AC). The best performing ML model was random forest model and XG boost model. The results of this study can be used to optimize the production of activated carbon and improve its performance in energy storage applications.

The performance of electrochemical double-layer capacitors (EDLCs) is evaluated by the capacitance of activated carbon (AC) electrodes. The capacitance of AC electrodes is influenced by many factors such as precursor type, activation method, pore structure, surface chemistry and electrolytic properties. In this paper, we present a comparative study of machine learning based prediction of surface area, mesopore volume and total pore volume of activated carbon for energy storage applications. The ML models were trained on a dataset of synthetic data that were generated from the limited number of experimental data and which included the activation temperature, methylene blue number and iodine number of the activated carbon (AC). The best performing ML model was random forest model and XG boost model. The results of this study can be used to optimize the production of activated carbon and improve its performance in energy storage applications.

Abstract This study synthesized a highly efficient KOH-treated sunflower stem activated carbon (KOH-SSAC) using a two-step pyrolysis process and chemical activation using KOH. The resulting material exhibited exceptional properties, such as a high specific surface area (452 m2/g) and excellent adsorption capacities for phenol (333.03 mg/g) and bisphenol A (BPA) (365.81 mg/g). The adsorption process was spontaneous and exothermic, benefiting from the synergistic effects of hydrogen bonding, electrostatic attraction, and stacking interactions. Comparative analysis also showed that KOH-SSAC performed approximately twice as well as sunflower stem biochar (SSB), indicating its potential for water treatment and pollutant removal applications. The study suggests the exploration of optimization strategies to further enhance the efficiency of KOH-SSAC in large-scale scenarios. These findings contribute to the development of improved materials for efficient water treatment and pollution control.

As machine learning software increasingly shapes crucial decisions in our daily lives, ensuring the fairness of these decisions is paramount. Individual fairness guarantees non-discrimination based on protected attributes, such as race or gender. Discriminatory instances reveal individual discrimination included in machine learning software. Existing methods for detecting individual discrimination often rely on initial “seed” instances, which are data points selected from the dataset that have more likelihood of exhibiting discrimination. These seed instances are then used as the basis for generating more discriminatory instances. While effective, this approach may inadvertently overlook discrimination embedded within seemingly fair non-seed instances. To overcome this limitation, this paper proposes FairBS, an approach that utilizes non-seed instances to generate discriminatory instances using counterfactual analysis. FairBS first constructs an explainer based on dataset input features and a model under test. It then generates an input instance and checks it for discrimination. If the input instance is non-discriminatory, FairBS uses the explainer to create counterfactual examples of that instance, by causing minimal perturbation to its feature values, which then produce other instances with opposite predictions. Extensive experiments on five datasets and five machine learning models demonstrate that our proposed approach outperforms state-of-the-art methods in both efficiency and effectiveness across all datasets and models. Our approach generates an average of $\times 13.44$ more discriminatory instances at $\times 14.51$ faster speed compared to existing seed-based methods. These findings indicate that FairBS expands the boundaries of fairness testing beyond the discriminatory seed instances, providing a powerful tool that can be used by software engineers to better ensure fairness in machine learning software.

The complexity of the power system has increased due to recent grid modernization and active distribution systems. As a result, monitoring and controlling modern power systems have become challenging. Dynamic security assessment (DSA) in power systems is a critical operational situational awareness (OpSA) tool for the energy control center (ECC). State-of-the-art (SOTA) DSA has been based on traditional state estimation utilizing the supervisory control and data acquisition (SCADA) / phasor measurement units (PMU) and transmission network topology processing (TNTP) based on SCADA monitoring of relay signals (TNTP-SMRS). Due to the slow data rates of SCADA, these applications cannot efficiently support an online DSA tool. Furthermore, an inaccurate network model based on TNTP-SMRS can lead to erroneous DSA. In this paper, a distributed dynamic security assessment (D-DSA) based on multi-level distributed linear state estimation (D-LSE) and efficient and reliable hierarchical transmission network topology processing utilizing synchrophasor network (H-TNTP-PMU) has been proposed. The tool can be used in real-time operation at the ECC of modern power systems. D-DSA architecture comprises three levels, namely Level 1 - component level security assessment (substations and transmission lines), Level 2 - area level security assessment, and Level 3 - network level security assessment. D-DSA concurrently evaluates all available substations’ security in the substation security assessment (SSA) and all available transmission lines’ security in the transmission line security assessment (TSA). Under the area security assessment (ASA), all SSA and TSA in each area are separately integrated to assess the area SSI (ASI-SSI) and TSI (ASI-TSI). Subsequently, each area’s area-level security index (ASI) is calculated by fusing ASI-SSI and ASI-TSI. At the network level security assessment, network SSI (NSI-SSI) and TSI (NSI-TSI) are estimated by fusing all ASI-SSIs and ASI-TSI, respectively. Network level security index (NSI) is estimated by fusing the NSI-SSI and NSI-TSI in network security assessment (NSA). Typical results of D-DSA are presented for two test systems, the modified two-area four-machine power system model and the IEEE 68 bus power system model. Results indicate that the proposed D-DSA can complete the assessment accurately at the PMU data frame rate, enabling online security assessment regardless of the network size.

Modern software systems are becoming more intricate, making identification of risks in the software requirement phase— a fundamental aspect of the software development life cycle (SDLC)—complex. Inadequate risk assessment may result in the malfunction of a software system, either in the development or production phase. Therefore, risk prediction plays a crucial role in software requirements, serving as the first step in any software project. Hence, developing adaptive predictive models that can offer consistent and explainable insights for handling risk prediction is imperative. This study proposes novel ensemble class balanced nested dichotomy (EBND) fuzzy induction models for risk prediction in software requirement. Specifically, the proposed EBND models employ a hierarchical structure consisting of binary trees featuring distinct nested dichotomies that are generated randomly for each tree. Thereafter, we use an ensemble principle to refine rules generated from the resulting binary tree. The predictive efficacy of the suggested EBND models is further extended by introducing a data sampling method into their prediction process. The inclusion of the data sampling method acts to mitigate the underlying disparity in the class labels that may affect its prediction processes. The efficacy of the EBND models is then evaluated and compared to current solutions using the open-source software risk dataset. The observed findings revealed that the EBND models demonstrated superior predictive capabilities when compared to the conventional models and state-of-the-art methodologies. Specifically, the EBND models achieved an average accuracy threshold value of 98%, as well as high values for the f-measure metric.

Controlled salinity water flooding also known as engineered water flood has been tested as a potential enhanced oil recovery (EOR) method in laboratory as well as at pilot/field scale. However, there are cases seen where the method has failed to show its potential for EOR. Scientists believe that the lack of understanding of case specific underlying mechanism is the primary reason. Many of the literatures claims reduction of interfacial tension as the primary oil recovery mechanism; but recent findings highlighted that modification of electrical charges on rock surface with response to injection brine salinity has greater effect. In order to investigate the same and in search of more insightful mechanism, in this study we have designed and performed experiments with selected chemicals which can modify surface properties of sandstone and also the oil water interfacial tension. The electrical charge of the rock surface and oil–brine​ interfacial tension were modified by tuning salinity of injection water and adding surfactants (sodium dodecyl benzene sulfonate, SDBS and cetyltrimethylammonium bromide, CTAB). The electrical charge of the sandstone surfaces was quantified with zeta potential measurement. The oil recovery potential of the injection fluids was tested through laboratory core flooding experiments at controlled near reservoir conditions. Superposition of all the obtained results revealed that low salinity injection brine modifies the sandstone surface to higher negatively charged state than high salinity water. Therefore, with a negatively charged oil–brine interface it causes strong repulsive forces promoting detachment of residual oil and subsequent mobilization. The hypothesis is also proved by the fact that SDBS in spite of resulting in a lower interfacial tension reduction than CTAB yielded higher oil recovery. This is because of the negative zeta potential caused by SDBS to sandstone surface in comparison to the positive zeta potential observed in the case of CTAB.

Postbiotics are an emerging field in gut and gastroenterological research. Despite it being a vast field, limited scientific research has been conducted on this topic. Postbiotics are functional bioactive compounds generated in the cell wall matrix during fermentation that may be used to promote health. Postbiotics play a critical role in human immune development against communicable and noncommunicable diseases. This review focuses on the recent advances and future perspectives of postbiotics in health and food science. The review also discussed the criteria and different types of postbiotics and elucidated the significance of postbiotics. The paper further reviewed the role of postbiotics as preservatives, active ingredients in packaging systems, anti-biofilm agents, and decontaminant agents in food processing industries.

Abstract Background Eating disorders are strongly associated with body image concerns. Eating disorders tend to significantly impact the current and future health and quality of life of affected persons, their caregivers, and society. As body image is based on a social construct of ideal body image, it is essential to evaluate it in its cultural context. Methods The current study explored the relationship among body image perception, perceived stress, eating disorder behaviour and quality of life among female medical students (n = 777). Measurements included Body Shape Questionnaire, Body Image Quality of Life Inventory, Eating Attitudes Test-26 and Rosenberg Self-Esteem Scale. Multivariate analysis was conducted. Results There was a significant correlation between eating disorder behaviour and perceived body shape, body image, quality of life and self-esteem among our study participants. We also found eating disorder status was significantly associated with BMI, perceived body shape, quality of life and self-esteem. Conclusions This is of clinical implication to female medical students and healthcare professionals to engage early in primary and secondary prevention of eating pathologies. Increasing awareness of these facts among female students can help identify at-risk students and help them seek timely medical help.

This paper addresses the research gap in neutrosophic game theory, specifically the resolution of zero-sum two-person matrix games characterized by single-valued neutrosophic triangular numbers. We introduce a novel de-neutrosophication method leveraging Mellin’s transform to obtain crisp value indices, thereby translating neutrosophic linear programming problems into their crisp counterparts. The effectiveness and precision of our approach are demonstrated through a real-world telecom sector case study, showcasing its potential for yielding more accurate and dependable solutions.

This study examined seafood consumption during the early period of economic recovery following the COVID-19 pandemic. Specifically, surveys of U.S. consumers compared seafood purchasing behavior of the first two quarters of 2021 (Q1, 1 January through 31 March 2021, and Q2, 1 April through 30 June 2021) with those of 2020. Each survey included 100 seafood consumer respondents in each of the 20 U.S. metropolitan market areas. Following data cleaning, there were 1885 valid responses for Q1-2021 and 1940 for Q2-2021. A majority (57%) of respondents had received at least one dose of the COVID-19 vaccine before March 2021 and 70% had received at least one dose as of June 2021. Regardless of vaccination status, few respondents (6% to 9.5% for food generally and 4% to 6.5% for seafood) reported changes in seafood consumption. Seafood consumption away from home increased significantly in Q1-2021 as compared to 2020 and continued to increase but to a lesser degree in Q2-2021. Demographic differences were found in shopping behaviors by age, education, income, and gender, but not by ethnic group. Generally, higher-income females with higher education tended to purchase more seafood. Respondents reported increased numbers of shopping trips per year in Q1-2021 as compared to 2020, which continued into Q2-2021 for general food, but shopping trips for seafood decreased as compared to 2020. The frequency of takeout purchases (times/year) of prepared meals for home consumption of seafood decreased during Q1 from 2020 and remained at that level in Q2-2021, but home delivery purchases of prepared meals of seafood increased during this period. Approximately 50–55% of respondents reported no change in overall seafood consumption levels, while 28% noted an increase in seafood consumption compared to pre-pandemic periods, a significant increase from the 19% who had reported doing so pre-pandemic. In contrast, those reporting a decrease declined from 31% to 17% in comparison to pre-pandemic levels. Seafood consumption in the U.S. remained stable and recovered in early 2021, with a preference for dining out. Consumer behaviors varied by age, income, education, and gender, but not by ethnicity. These changes were primarily driven by access, availability, and income, indicating the need for further research on long-term consumption patterns. This study found apparent stability of seafood consumption by U.S. consumers, which recovered from pandemic consumption levels in early 2021, and there was little change in seafood consumption, frequency, or the types of seafood consumed. Vaccination status did not appear to affect seafood consumption.

Abstract Background In the dapagliflozin (DPF) synthesis, 5-Bromo-2-chlorobenzoic acid (5-BC impurity) and 4-Bromo-1-chloro-2-(4-ethoxybenzyl) benzene (4-BC impurity) are used as starting and reagent sources, respectively. The presence of 5-BC and 4-BC impurities in DPF could potentially affect the effectiveness of the final DPF product. The purpose of this investigation was to develop a stability indicating HPLC methodology for the separation of DPF, its process-related impurities and degradants. The method of analysis was developed on Xbridge Phenyl C18 column of dimensions, 250 × 4.6 mm, 5 μm with gradient elution using mobile phase made up of 0.05% aqueous trifluoroacetic acid and acetonitrile (AcN). Results The method proposed indicates a good linearity (R 2 = 0.9996 and 0.9993), good system precision (RSD ≤ 2%), good method precision (RSD ≤ 2%), accuracy (50–150%), LOD (0.000053 ppm and 0.0000165 ppm) and LOQ (0.00016 ppm and 0.00005 ppm) for 4-BC impurity and 5-BC impurity, respectively. LC–MS was used to detect and characterise degradants that were obtained in acid and base condition were identified and characterised. A comparison of the fragmentation pattern of the [M + H] + ions of DPF and its degradation products revealed the most likely processes for the generation of degradation products. Conclusion DPF sample quality can be evaluated using the suggested method for the presence of 4-BC impurity, 5-BC impurity and 2-(3-(4-ethoxy benzyl)-4-chloro phenyl)-tetrahydro-6-(hydroxy methyl)-2H-pyran-3,4,5-triol.

Background: People with a spinal cord injury (SCI) have poor survival rates in low- and middle-income group countries. SCI prevention is critical to decreasing societal and individual health expenditure. Knowledge of the mechanism of SCI and contributory factors is necessary for successful prevention programs. There are limited population-based studies that explain the cause of SCI in an emergent economy like India. Available studies are limited to a specific region or hospital. Our study was done to understand the causes of traumatic SCI all over India. Methods: Online survey was conducted among SCI patients. Patients were given objective questions. Consecutive participants in 6 months were included from April 2022 to October 2022. Snow-bowling method was followed. Participants who had a SCI with known etiology were included in the analysis (n = 96). Different mechanisms of SCI documented in the databases were stratified by personal characteristics using descriptive analysis. Results: Road traffic accidents (RTAs) followed by fall from height were the biggest contributor of SCI. The most common causes of SCI were RTAs (50%) and fall from height (37.50%), followed by assault (4.17%), and others (8.33%). Conclusion: In primarily agriculture-based countries, fall from height (especially tree) was expected to be a major mechanism of SCI; however, our study shows a reversal of a trend. Improvement in rural infrastructure is decreasing the gap between RTA and falls from height as a major mechanism of SCI. It is time to make health policies primarily to prevent RTA and fall from height.

Abstract Oncogene Moesin plays critical role in initiation, progression, and metastasis of multiple cancers. It exerts oncogenic activity due to its high-level expression as well as posttranslational modification in cancer. However, factors responsible for its high-level expression remain elusive. In this study, we identified positive as well as negative regulators of Moesin. Our study reveals that Moesin is a cellular target of F-box protein FBXW2. We showed that FBXW2 suppresses breast cancer progression through directing proteasomal degradation of Moesin. In contrast, AKT kinase plays an important role in oncogenic function of Moesin by protecting it from FBXW2-mediated proteasomal degradation. Mechanistically, AKT phosphorylates Moesin at Thr-558 and thereby prevents its degradation by FBXW2 via weakening the association between FBXW2 and Moesin. Further, accumulated Moesin prevents FBXW2-mediated degradation of oncogene SKP2, showing that Moesin functions as an upstream regulator of oncogene SKP2. In turn, SKP2 stabilizes Moesin by directing its non-degradable form of polyubiquitination and therefore AKT-Moesin-SKP2 oncogenic axis plays crucial role in breast cancer progression. Collectively, our study reveals that FBXW2 functions as a tumor suppressor in breast cancer by restricting AKT-Moesin-SKP2 axis. Thus, AKT-Moesin-SKP2 axis may be explored for the development of therapeutics for cancer treatment.

Background: COVID-19 is primarily known as a respiratory illness; however, many patients present to hospital without respiratory symptoms. The association between non-respiratory presentations of COVID-19 and outcomes remains unclear. We investigated risk factors and clinical outcomes in patients with no respiratory symptoms (NRS) and respiratory symptoms (RS) at hospital admission. Methods: This study describes clinical features, physiological parameters, and outcomes of hospitalised COVID-19 patients, stratified by the presence or absence of respiratory symptoms at hospital admission. RS patients had one or more of: cough, shortness of breath, sore throat, runny nose or wheezing; while NRS patients did not. Results: Of 178,640 patients in the study, 86.4 % presented with RS, while 13.6 % had NRS. NRS patients were older (median age: NRS: 74 vs RS: 65) and less likely to be admitted to the ICU (NRS: 36.7 % vs RS: 37.5 %). NRS patients had a higher crude in-hospital case-fatality ratio (NRS 41.1 % vs. RS 32.0 %), but a lower risk of death after adjusting for confounders (HR 0.88 [0.83–0.93]). Conclusion: Approximately one in seven COVID-19 patients presented at hospital admission without respiratory symptoms. These patients were older, had lower ICU admission rates, and had a lower risk of in-hospital mortality after adjusting for confounders.

Introduction: Some specific personality factors in patients of bipolar disorder are potential risk factors for developing comorbid substance use disorder. Comorbid substance use disorder is one of the most common factors associated with non-adherence to treatment in bipolar disorder patients leading to poor quality of life. We compared all three variables in bipolar disorder-1patients with or without substance use disorder. Methods: It is a cross-sectional study done on 90 patients of Bipolar disorder-1 diagnosed as per DSM-5, 45 without and 45 with comorbid substance use disorder. Personality factors, non-adherence to medication and quality of life were assessed and compared between both the groups using standardized tools and appropriate statistical analysis methods. Results: There was a significant difference between the groups in terms of distribution of socio-economic status (Bias Corrected Cramer'sV = 0.31 moderate association), gender (Bias Corrected Cramer'sV = 0.37 moderate association), distribution of 16 personality factor B (Cramer's V = 0.28) and factor G (χ2 = 6.222, p = 0.045) (Cramer's V = 0.26). Limitations: Small sample size and a cross-sectional study design. Conclusion: SUD and NSUD group differed on 16 PF factor B and G which are factors for reasoning and Rule-Consciousness respectively although on regression analysis this difference was not significant for factor G. In binary logistic regression multivariable model, an average score (as compared to low score) of personality factor B was found to significantly increase the ODDS of substance use. SUD group had more severity and greater number of episodes, had lower level of education, belonged to low socio-economic status.

Background The goal was to measure the piriform sinus, epiglottis, and thyroid cartilage in our sample population. Methods This study included 22 adult embalmed cadavers available in the Department of Anatomy. Dimensions were measured using a digital Vernier caliper. Results The mean height of the thyroid laminae was 27 ± 1.4 mm at the right side and 25.5 ± 1.4 mm at the left side. Mean width of the thyroid lamina was 27.1 ± 1.3 mm at the right side and 27.4 ± 0.9 mm at the left side. The mean thickness of thyroid cartilage was found to be 4.4 ± 0.4 mm and 3.9 ± 0.5 mm over the right and left sides. The mean length, width and thickness of the epiglottis were 29.1 ± 0.5 mm, 22.2 ± 0.6 mm and 2.6 ± 0.3 mm correspondingly. The height, width and thickness of the right piriform sinus were 25 ± 0.5 mm, 14.2 ± 0.5 mm and 12.6 ± 0.5 mm, the same parameters were 25.3 ± 1.3 mm, 15.1 ± 0.7 mm and 13.3 ± 0.4 mm for the left side. Conclusions The height and thickness of the thyroid cartilage were greater on the right side than on the left side (p

Background: Elderly people are one of the most vulnerable populations, with a higher risk of having chronic illnesses, infections, and eventual disability. Along with morbidity and death rates, the amount of disability is an essential metric in quantifying disease burden. This study estimates the prevalence of functional disability and associated socio-demographic characteristics and morbidities in a rural area of Puducherry. Methods: This cross-sectional study included 360 people aged 60 and above who are living in the study area. People who had difficulty in activities of daily living (ADL), blindness, bilateral hearing impairment, cognitive impairment, or a combination of these were regarded to have functional disability. Barthel index, Snellen's chart, Whisper test and Elderly cognitive assessment questionnaire were used to assess the disabilities. Simple descriptive analysis and the Chi-square test were incorporated in statistical analysis. In order to understand the factors associated with functional disability, multiple logistic regression is performed. Results: The prevalence of functional disability was found to be 30 % (95 % Confidence Interval: 25.5–34.9) among the 360 study participants. 13.8 % had ADL disability, 8 % had visual impairment, 11.6 % had hearing impairment and 9.7 % had cognitive impairment. Men had a lower prevalence (28.3 %) than women (31.2 %).The prevalence increased with age, low socio-economic status and found more common among persons who were widowed or widower. Disability increased with increasing morbidities. Discussion: Functional disability among elderly in rural area is very common. It is associated with morbidities and sociodemographic factors. To guarantee healthy ageing functional disabilities must be recognized early using appropriate methods.