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Abstract Landslides are frequent all over the world, posing serious threats to human life, infrastructure, and economic operations, making them chronic disasters. This study proposes a novel landslide detection methodology that is automated and based on a hybrid deep learning approach. Currently, Deep Learning is constrained by the lack of applicability, lack of data, and low efficiency in landslide detection but with recent advancement in deep learning-based solutions for landslide detection has sparked considerable advantages over traditional techniques. In order to prevent and mitigate disaster, we introduced a hybrid model based on remote sensing technologies such as satellite images. Specifically, the proposed approach consists hybrid U-Net model integrated with a pyramid pooling layer for landslide detection, which uses high-resolution landslide images from the Landslide4Sense dataset. The UNet-Pyramid model has the following modifications: To improve feature acquisition and advancements to strengthen the model’s attention U-Net architecture is integrated with the pyramid pooling layers and OBIA technique. The UNet-Pyramid model was trained and validated using labeled images taken from the Landslide4Sense dataset and the validated set using OBIA to improve its efficacy. The overall Precision, Recall, and F1 Score of the UNet-pyramid model for landslide detection are 91%, 84%, and 87%, respectively.

Ganglionic cysts are benign soft-tissue lesions with unclear etiology and pathogenesis commonly occurring on the wrists and hands. Although their diagnosis and management in these characteristic locations are easy, rare occurrences in atypical locations are difficult to diagnose. Ultrasonography and magnetic resonance imaging (MRI) are helpful in diagnosing and differentiating a ganglionic cyst from other soft-tissue lesions. Here, we report a case of 60-year-old male patient with intramuscular ganglionic cyst, measuring 68×41×48 mm, arising in the extensor digitorum muscle of the left leg, which was diagnosed using MRI and treated using excision and biopsy.

Abstract This randomised, crossover, sham-controlled study explored the neural basis of source-monitoring, a crucial cognitive process implicated in schizophrenia. Left superior temporal gyrus (STG) and dorsolateral prefrontal cortex (DLPFC) were the key focus areas. Thirty participants without neurological or psychological disorders underwent offline sham and active tDCS sessions with specific electrode montage targeting the left STG and DLPFC. Source-monitoring tasks, reality monitoring (Hear-Imagine), internal source-monitoring (Say-Imagine), and external source monitoring (Virtual–Real) were administered. Paired t-test and estimation statistics was performed with Graphpad version 10.1.0. The Benjamini–Hochberg procedure was employed to control the false discovery rate in multiple hypothesis testing. A significant improvement in internal source monitoring tasks (p = 0.001, Cohen's d = 0.97) was observed, but reality monitoring tasks demonstrated moderate improvement (p = 0.02, Cohen's d = 0.44). The study provides insights into the neural mechanisms of source monitoring in healthy individuals and proposes tDCS as a therapeutic intervention, laying the foundation for future studies to refine tDCS protocols and develop individualized approaches to address source monitoring deficits in schizophrenia.

In this study, a series of platinum (Pt)-doped strontium iron oxide (SrFe2O4) catalysts with varying particle sizes were synthesized through the four different catalysis synthesis methods such as solution combustion synthesis (SCS), co-precipitation (Co-PPT), oxalic acid assisted sol-gel (OXA) and, hydrothermal (HT). The objective was to investigate the impact of particle size on the catalytic activity and long-term stability of these four catalysts. The XRD and Raman results confirmed the formation of the SrFe2O4 perovskite structure. HRTEM, SEM, and other characterizations revealed a clear correlation between the synthesis conditions and the resulting particle sizes. The highest%CH4 conversion was around 95 % for the catalyst prepared through Solution combustion synthesis and the catalyst was found to be thermally stable up to. 100 h at 800 °C with a negligible variation of conversion while maintaining the H2/CO ratio at 2.0. To gain insight into catalytic activity, stability, and selectivity of catalysts we have performed Temperature-programmed surface reaction (TPSR) at a controlled temperature ramping program. This study also includes the study of coke deposition on the spent catalysts through different characterization techniques. Furthermore, we have performed a kinetic study to find the initial rate of the reaction and the activation energy of the Pt-doped SrFe2O4 catalyst and it has been found that activation energy was 35 KJ/mol for the catalyst Pt/SrFe2O4 synthesis through the solution combustion method.

Objectives: Monitoring of Leishmania transmission is considered a strategic priority for sustaining elimination of visceral leishmaniasis as a public health problem in the Indian subcontinent. The objective of this study was to evaluate whether serological surveys can distinguish between communities with and without Leishmania transmission, and to assess which serological marker performs best. Methods: Seven villages were selected from Bihar and Uttar Pradesh state, India, and categorized as either currently endemic (CE), previously endemic (PE) or nonendemic (NE). Blood samples were analyzed with the rK39 RDT, direct agglutination test (DAT), and rK39 ELISA. Results: Contrary to the rK39 RDT and DAT, the rK39 ELISA showed a significant difference between all three categories of endemicity, with a seroprevalence of 5.21% in CE villages, 1.55% in PE villages, and 0.13% in NE villages. Even when only looking at the seroprevalence among children aged

ABSTRACT: Tributyltin (TBT), an organotin-endocrine-disrupting substance, is recognized as one of the most important toxic environmental pollutants. The present study was carried out to investigate the developmental toxicity of TBT on zebrafish embryos. Eggs of zebrafish were exposed to 2.5, 5, and 10 µg of TBT per liter of E3 medium for 72 hours to evaluate various parameters of developmental toxicity. The TBT exposure resulted in a dose-dependent negative effect on the hatching rate and increased larval mortality. Different abnormalities in larvae, following exposure to various concentrations of TBT, have also been observed. The tail and spinal deformities, along with dwarfism, were important abnormalities observed in TBT-exposed zebrafish embryos. It has been concluded that tributyltin produced deleterious effects on embryos and larvae during developmental stages, along with multiple deformities that ultimately affected the survival and growth of fish

In recent years, the field of biomedical video source identification has witnessed a significant evolution driven by advances in both fuzzy-based systems and machine learning models. This paper presents a comprehensive survey of the current state of the art in this domain, highlighting the transition from traditional fuzzy-based approaches to the emerging dominance of machine learning techniques. Biomedical videos have become integral in various aspects of healthcare, from medical imaging and diagnostics to surgical procedures and patient monitoring. The accurate identification of the sources of these videos is of paramount importance for quality control, accountability, and ensuring the integrity of medical data. In this context, source identification plays a critical role in establishing the authenticity and origin of biomedical videos. This survey delves into the evolution of source identification methods, covering the foundational principles of fuzzy-based systems and their applications in the biomedical context. It explores how linguistic variables and expert knowledge were employed to model video sources, and discusses the strengths and limitations of these early approaches. By surveying existing methodologies and databases, this paper contributes to a broader understanding of the field’s progress and challenges.

Abstract Background To assess the feasibility of partial penectomy under local anesthesia and penile nerve blocks. Methods A total of 45 patients underwent partial penectomy under local anesthesia over the last 15 years at our institute. These patients were included in group A. We took 45 age-matched controls for comparison in group B. All patients underwent partial penectomy with the standard technique. The control group underwent partial penectomy under general or spinal anesthesia, and the intervention group underwent partial penectomy under local anesthesia. Patients’ tolerance to anesthesia and surgery was compared, and postoperative pain and other complications were assessed. Results Mean age was 53.5 years in group A (case) and 52.8 years in group B (controls). Out of 45 patients in group A, 9 were ASA I, 16 were ASA II, 8 were ASA III, and 12 were ASA IV patients. Out of control patients, 35 underwent surgery under spinal and 10 underwent surgery under general anesthesia. All patients tolerated the anesthesia and surgery well. The duration of anesthesia and surgery was shorter in group A (p

The electrocatalytic oxygen evolution reaction (OER) is an arduous step in water splitting due to its slow reaction rate and large overpotential. Herein, we synthesized glycerate-anion-intercalated nickel–iron glycerates (NiFeGs) using a one-step solvothermal reaction. We designed various NiFeGs by tuning the molar ratio between Ni and Fe to obtain Ni4Fe1G, Ni3Fe1G, Ni3Fe2G, and Ni1Fe1G, which we tested for their OER performance. We initially analyzed the catalytic performance of powder samples immobilized on glassy carbon electrodes using a binder. Ni3Fe2G outperformed the other NiFeG compositions, including NiFe layered double hydroxide (LDH). It exhibited an overpotential of 320 mV at a current density of 10 mA cm–2 in an electrolytic solution of pH 14. We then synthesized carbon paper (CP)-modified Ni3Fe2G as a self-supported electrode (Ni3Fe2G/CP), and it exhibited a high current density (100 mA cm−2) at a low overpotential of 300 mV. The redox peak analysis for the NiFeGs revealed that the initial step of the OER is the formation of γ-NiOOH, which was further confirmed by a post-Raman analysis. We extensively analyzed the catalyst’s stability and lifetime, the nature of the active sites, and the role of the Fe content to enhance the OER performance. This work may provide the motivation to study metal-alkoxide-based efficient OER electrocatalysts that can be used for alkaline water electrolyzer applications.

We report growth and characterization of n-Si/p-SnOx heterojunction using RF sputtering for deposition of p-type SnOx under controlled growth oxygen pressure over n-type silicon (Si) wafer. The heterojunction properties of Si/SnOx were varied by controlling the growth oxygen pressure of SnOx. Several characterization techniques, including PL (photoluminescence), AFM (atomic force microscopy), FESEM (field emission scanning electron microscopy), XRD, I-V characteristics and Hall measurement, were conducted to analyze the structural, optical, and electrical properties of the n-Si/p-SnOx heterojunction. The knee voltage (Vknee), or cut-in voltage, was calculated by analyzing the gradient of the dark current-voltage (J-V) curves when the bias was applied in the forward direction. The Vknee values for type-I, type-II, and type-III n-Si/p-SnOx heterojunctions were determined to be 0.62 V, 0.84 V, and 1.0 V, respectively. The ideality factors (n1 and n2) were determined to be 1.52, 2.22, 3.52, and 8.41, 9.31, 10.34, respectively, for various heterojunction types. The reverse saturation current densities, J01 and J02 ranging from approximately 10−7 to 10−6 A/cm2, and 10−5 to 10−4 A/cm2, respectively. The objective of this experimental work is to investigate especially, the prospect of silicon /metal-oxide (Si/SnOx) based heterojunction to be used as optical sensors with tunable optoelectronic properties of SnOx.

To analyze and compare the intraoperative and post-operative outcomes of “on-clamp” laparoscopic partial nephrectomy (LPN) with “preoperative super-selective angioembolization” before LPN. This randomized clinical study was conducted at Gauhati Medical College Hospital, Guwahati, India, between November 2021 and November 2023. Adult patients of either gender diagnosed with T1 renal tumors were included in the study. All patients underwent diethylenetriamine pentaacetate scan preoperatively and at 1-month follow-up. The patients were randomized using a parallel group design with an allocation ratio of 1:1 to receive either preoperative angioembolization followed by LPN or conventional “on-clamp” LPN. Demographic and baseline parameters were recorded along with pre- and post-operative data. There was no significant difference between the two groups in terms of age (P = 0.11), gender distribution (P = 0.32), body mass index (P = 0.43), preoperative hemoglobin (P = 0.34), and preoperative estimated glomerular filtration rate (eGFR; P = 0.64). One patient in the embolization group required radical nephrectomy because of accidental backflow of glue into the renal artery during embolization whereas four patients required clamping due to inadequate embolization. Preoperative super-selective embolization yielded significantly less blood loss, compared to “on-clamp” LPN (145 [50.76 mL] vs. 261 [66.12 mL], P < 0.01). There was no significant difference between post-operative eGFR (at 1 month) between the two groups (P = 0.71). Preoperative embolization offers improved outcomes in the dissection plane, total operative time, and blood loss, compared to conventional “on-clamp” LPN but has no significant effect on change in eGFR.

Intraosseous ganglion is a benign cystic bony lesion containing viscous and mucinous gelatinous material, which is usually seen in middle-aged individuals. It is similar to soft-tissue ganglion cysts present in other parts of the body. We, hereby, report a rare case of idiopathic intraosseous ganglion of the tibia in a young adult who presented with chronic pain in his lower leg. The patient was subjected to X-ray and MRI investigations and managed by excisional curettage of the lesion and histopathological examination. On histopathology, the diagnosis of intraosseous ganglion was confirmed. On 2-year follow-up, the patient was doing well without any complication and recurrence. This report describes the diagnosis and successful management of intraosseous ganglion at a very rare site in a young individual. More in-depth studies are required to understand the predisposing factors, underlying pathology, early diagnosis, and management of this lesion.

Introduction: Rapid beta-cell senescence caused by telomere shortening is associated with type 2 diabetes. Hence, studying telomere dynamics in prediabetic stages or First Degree Relatives of Diabetics (FDRD) is crucial. Telomere attrition is influenced by oxidative stress, which is prevalent in diabetics, prediabetics, and FDRD due to dyslipidaemia. The relationship between telomerase activity and glycaemic control, insulin resistance, oxidative stress, dyslipidaemia, adipocytokines, and inflammatory markers remains unclear and requires further investigation. Aim: To assess and compare telomerase levels, oxidative stress (malondialdehyde), adipocytokines (leptin, adiponectin, and Interleukin-6 (IL-6), lipid profiles, and Body Fat Percentage (BF%) across the glycaemic spectrum in the Indian population. Materials and Methods: This cross-sectional study was conducted at the Department of Physiology, JIPMER, Puducherry, from 2016 to 2018, involving four groups: Group I (control group, non diabetic, healthy, non FDRD, n=63), Group II (FDRD, non diabetic, n=63), Group III (prediabetics, n=63), and Group IV (diabetics, n=63). Participants aged 30-50 years, matched for age and gender, were recruited. Anthropometric variables, cardiovascular parameters, telomerase levels, Malondialdehyde (MDA), adiponectin, leptin, IL-6, and lipid profiles were assessed. Mean differences were analysed using one-way Analysis of Variance (ANOVA) or Kruskal-Wallis test, while Pearson’s correlation analysis was performed to assess the correlation between telomerase levels, glucose concentration, and BF%. Results: An increasing trend in circulating telomerase levels, lipid profiles, and BF% was observed across the glycaemic spectrum. Circulating leptin concentrations did not differ between the groups. However, there was a decrease in circulating adiponectin concentration as the glycaemic status progressed. Increased MDA levels were observed only in the diabetics group. Telomerase levels showed a significant association with circulating glucose concentration (fasting and postprandial) and BF%. Conclusion: The circulating telomerase level increased along the glycaemic spectrum (non FDRD

Most of the system-level designs contain sequential circuits. Power optimization of these circuits at many levels is required to build a portable device with a long battery life. A dynamic clock gating technique was used in this work to reduce the power and temperature of a 16-bit counter. The simulation was performed on cadence SCL 180 nm technology, for a supply voltage of 1.8 V at a frequency of 500 MHz. With the proposed approach, a 77.16% power reduction was achieved at the cost of 14.83% in area overhead. Moreover, the layout of the circuits was also designed in the Innovus tool to obtain a more accurate silicon area and gate count. The Innovus output files ".flp file" and ".pptrace file" were used as inputs to the HotSpot tool for determining the absolute temperature of the integrated circuits (ICs). The obtained temperature results were compared with the ordinary 16-bit counter, and it was found that the proposed approach was able to reduce temperature by 14.34%.

This study demonstrates the use of computational methods to simulate the molecular dynamics involved in hemoglobin concentration sensing, utilizing Material Studio and the TCAD Silvaco device simulator. A non-invasive and flexible Graphene/MoS2 heterostructure has been proposed for sensing hemoglobin concentration in blood samples. The findings reveal a notable shift in the wavelength-dependent refractive index and extinction coefficient, as well as significant changes in the absorption coefficient and reflectivity of the Graphene/MoS2 heterostructure in response to different hemoglobin concentrations, specifically within an approximate range of 0.3 μm to 1 μm. Moreover, the spectral response of the heterostructure demonstrates that at a particular wavelength of approximately 600 nm, a maximum response is obtained. This wavelength can be considered optimal for detecting various levels of hemoglobin using this heterostructure. The anticipated outcome is a comprehensive understanding of the fundamental principles, ultimately resulting in the development of an exceptionally sensitive platform for detecting hemoglobin concentration.

Background: COVID-19 pandemic posed a huge stress on health-care givers affecting their physical and mental health. Wellness strategies like yoga can improve flexibility, resilience, and outlook. Aim: The present study explored the effect of 8-week standard common yoga protocol (CYP) intervention on autonomic functions, emotional stress, oxidative stress, and inflammation markers in the nurse group of health-care givers. Materials and Methods: It is a randomized controlled trial where 50 nurses underwent CYP and 50 participated as controls. Anthropometric parameters, cardiovascular parameters, autonomic function including time and frequency domain parameters, biochemical parameters, and psychological stress using the questionnaire were assessed before and after 8-week CYP. Results: Total 88 nurses completed the study with 42 and 46 participants, respectively, in the CYP and control groups. CYP intervention resulted in a significant reduction in cardiovascular parameters systolic blood pressure, diastolic blood pressure, mean arterial pressure, pulse pressure, and rate pressure product (P < 0.001, P < 0.001, P < 0.001, P < 0.001, and P = 0.002, respectively), perceived stress score and Depression, Anxiety, and Stress Scale psychological variables of depression, anxiety, and stress, and serum lipid parameters compared to the control group. CYP significantly increased total power, low frequency, high frequency, root mean square of successive differences between adjacent NN intervals, change in successive normal sinus (NN) intervals exceeds 50 ms, and pNN50% (P < 0.001, P = 0.006, P = 0.006, P = 0.039, P < 0.001, and P = 0.013, respectively) suggesting improved resting autonomic modulation and parasympathodominance due to higher vagal efferent activity. There were significant reductions in serum cortisol, tumor necrosis factor-alpha, interleukin (IL)-1, and IL-6 in both the groups. Serum telomerase significantly reduced (P = 0.024) and total antioxidant capacity (P = 0.036) increased in the CYP group post intervention. Conclusion: CYP intervention was beneficial in improving psychophysiological, autonomic, and biochemical profile of the nurse group of health-care workers.

Humans possess an intrinsic ability to hide their true emotions. Micro-expressions are subtle changes in facial muscles that are involuntary by nature and easy to hide. To address these issues, several machine and deep learning models have been proposed in the past few years. Convolution neural network (CNN) is a deep learning method that has widely been adopted in vision-related tasks due to its remarkable performance. However, CNN suffers from overfitting due to a large number of trainable parameters. Additionally, CNN cannot capture global information with respect to an input image. Furthermore, the identification of important regions for the classification of micro-expressions is a challenging task. Self-attention mechanism addresses these issues by focusing on key areas. Furthermore, specific transformers, known as vision transformers are widely explored in vision-related applications. However, existing vision transformers divide an input image into a fixed number of patches due to which local correlation of image pixels is lost. Further, a vision transformer relies on self-attention mechanism which effectively captures global dependencies but does not exploit the local spatial relationships in an image. In this work, we propose a vision transformer based on convolution patches to overcome this problem. The proposed algorithm generates $c $ number of feature maps from input images using $c $ filters through convolution operation. These feature maps are then applied to a transformer model as fixed-size image patches to perform classification. Thus, the proposed architecture leverages advantages of both convolutional layers and transformer, and captures both spatial information and global dependencies respectively, leading to improved performance. The performance of the proposed model is evaluated on three benchmark datasets: CASME-I, CASME-II, and SAMM and compared with state-of-the-art machine and deep learning models, which generated classification accuracy of 95.97%, 98.59%, and 100%, respectively.

Cyber-Physical Systems (CPSs) are becoming increasingly complex and interconnected as they attempt to meet the demands of evolving society. As a result, monitoring and maintaining them becomes a more complex and demanding task for control system operators and cyber defenders. While the literature on visualization techniques in the context of cybersecurity is extensive, the same cannot be said for studies on visualization for the security of cyber-physical systems. This paper aims to fill that gap by: 1) defining the main features of a visualizations workflow for security visualizations in cyber-physical systems. The workflow includes the acquisition of cyber and physical data, processing of data, selection, and configuration of both visualization tools and end-user interactions. 2) Providing an overview of cyber-physical security visualization systems, with a focus on smart grids as a case study. Finally, we use the perspectives gained from this analysis to provide insights and directions for future research and design of cyber-physical visualization techniques.

Abstract As today's power grid is evolving into a densely interconnected cyber‐physical system (CPS), a high fidelity and multifaceted testbed environment is needed to perform cybersecurity experiments in a realistic grid environment. Traditional standalone CPS testbeds lack the ability to emulate complex cyber‐physical interdependencies between multiple smart grid domains in a real‐time environment. Therefore, there are ongoing research and development (R&D) efforts to develop an interconnected CPS testbed by sharing geographically dispersed testbed resources to perform distributed simulation while analysing simulation fidelity. This paper presents a networked federation testbed for cybersecurity evaluation of today's and emerging smart grid environments. Specifically, it presents two novel testbed architectures, including cyber federation and cyber‐physical federation, identifies R&D applications, and also describes testbed building blocks with experimental case studies. It also presents a novel co‐simulation interface algorithm to facilitate distributed simulation within cyber‐physical federation. The resources available at the PowerCyber CPS security testbed at Iowa State University (ISU) and the US Army Research Laboratory are utilised to develop this platform for performing multiple experimental case studies pertaining to wide‐area protection and control applications in power system. Finally, experimental results are presented to analyse the simulation fidelity and real‐time performance of the testbed federation.

Rapid urbanization and land use transformation coupled with climate change impact are witnessed for development urban heat island worldwide and make it major environmental concerns for human health. National Capital Region (NCR) is one of the fast sprawling National Capital city of India. The aim of the present study is to explore the spatial changes in major biophysical parameters of city over last 20 years from 2000 to 2020 using satellite data. The spatial variation in the land surface temperature and its relation with Land use, NDVI and Built-up area were evaluated and discussed in the present work. The major changes were observed in minimum and maximum temperature of the city, in 2000 minimum temperature was 23.20 °C and maximum 34.85 °C, which increased to 26.31 and 39.92 °C in 2010; and 31.70 to 44.74 °C in 2020 . Normalized differential vegetation index (NDVI) decrease from 82 to 62%, Non-Vegetated area has reduced to 62% from 82% due to fast urbanization and land transformation in last two decades. Barren and fallow land also reduces about 27% in last two decades and built-up area also shown increasing trend . The spatial changes in biophysical parameter of the city clearly indicated that NDVI, NDBI and Land use/land cover charges are the main driving forces for development of urban heat island in the city and many health issues related to heat waves are already reported in the city along with many other negative impacts on natural landscape and resources. The observations from present work will be very useful scientific information to understand the causes of elevated land surface temperature and mitigation measures. Results could be used by policy makers to develop the suitable model for long term sustainability of the cities.

One of the diseases that is constantly spreading and is estimated to cause a significant number of deaths worldwide is diabetes mellitus. It is determined by the quantity of a blood sugar molecule made from glucose. The possibility of this disease has been predicted using a variety of methods. To forecast diabetes at an early stage, adequate and clear data on diabetic individuals are needed. In this study, 520 records from a hospital in Bangladesh with 16 different characteristic numbers were used to make predictions. At UCI, this dataset is accessible to everyone. We used Random Forest, Ada Booster, KNN, and Bagging algorithms after feature selection. Through 10-fold cross-validation, it was discovered that the Random Forest method had the best test accuracy, scoring 97.03% correctly and 95.03% correctly.

The high concentration of antibiotics in aquatic environments is a serious environmental issue. In response, researchers have explored photocatalytic degradation as a potential solution. Through chemical vapor deposition (CVD), we synthesized copper selenide (β-Cu2−xSe) and found it an effective catalyst for degrading tetracycline hydrochloride (TC-HCl). The catalyst demonstrated an impressive degradation efficiency of approximately 98% and a reaction rate constant of 3.14 × 10−2 min−1. Its layered structure, which exposes reactive sites, contributes to excellent stability, interfacial charge transfer efficiency, and visible light absorption capacity. Our investigations confirmed that the principal active species produced by the catalyst comprises O2− radicals, which we verified through trapping experiments and electron paramagnetic resonance (EPR). We also verified the TC-HCl degradation mechanism using high-performance liquid chromatography–mass spectrometry (LC-MS). Our results provide valuable insights into developing the β-Cu2−xSe catalyst using CVD and its potential applications in environmental remediation.

The immune function of normal T cells partially depends on the maneuvering of lipid metabolism through various stages and subsets. Interestingly, T-cell malignancies also reprogram their lipid metabolism to fulfill bioenergetic demand for rapid division. The rewiring of lipid metabolism in T-cell malignancies not only provides survival benefits but also contributes to their stemness, invasion, metastasis, and angiogenesis. Owing to distinctive lipid metabolic programming in T-cell cancer, quantitative, qualitative, and spatial enrichment of specific lipid molecules occur. The formation of lipid rafts rich in cholesterol confers physical strength and sustains survival signals. The accumulation of lipids through de novo synthesis and uptake of free lipids contribute to the bioenergetic reserve required for robust demand during migration and metastasis. Lipid storage in cells leads to the formation of specialized structures known as lipid droplets. The inimitable changes in fatty acid synthesis (FAS) and fatty acid oxidation (FAO) are in dynamic balance in T-cell malignancies. FAO fuels the molecular pumps causing chemoresistance, while FAS offers structural and signaling lipids for rapid division. Lipid metabolism in T-cell cancer provides molecules having immunosuppressive abilities. Moreover, the distinctive composition of membrane lipids has implications for immune evasion by malignant cells of T-cell origin. Lipid droplets and lipid rafts are contributors to maintaining hallmarks of cancer in malignancies of T cells. In preclinical settings, molecular targeting of lipid metabolism in T-cell cancer potentiates the antitumor immunity and chemotherapeutic response. Thus, the direct and adjunct benefit of lipid metabolic targeting is expected to improve the clinical management of T-cell malignancies.

Breeding for aluminium (Al) tolerance is a vital approach for enhancing the productivity of field crops in acidic soil regions where Al toxicity seems to be the most restraining factor for crop performance. Sunflower is generally considered extremely sensitive to Al toxicity; although no comprehensive information on the evaluation of sunflower genotypes for Al tolerance is available. In this study, 50 sunflower genotypes (set-I and set-II) were evaluated for Al tolerance at the seedling stage under hydroponic conditions. Substantial genetic variability in Al tolerance was observed among the studied genotypes. High estimates of heritability were obtained for both the total root length (TRL) and root regrowth (RRG), together with high estimates of genetic advance. A cluster analysis separated the genotypes into five different groups among the studied germplasm, the genotypes; NDLR-06 and EC-601861 were observed to be highly Al tolerant in terms of root regrowth under Al stress. In conclusion, the findings lreveal the complex mechanisms of Al tolerance in sunflower and may help to find new genetic resource for the improvement of Al tolerance in sunflower breeding.

Digital breast tomosynthesis (DBT) stands out as a highly robust screening technique capable of enhancing the rate at which breast cancer is detected. It also addresses certain limitations that are inherent to mammography. Nonetheless, the process of manually examining numerous DBT slices per case is notably time-intensive. To address this, computer-aided detection (CAD) systems based on deep learning have emerged, aiming to automatically identify breast tumors within DBT images. However, the current CAD systems are hindered by a variety of challenges. These challenges encompass the diversity observed in breast density, as well as the varied shapes, sizes, and locations of breast lesions. To counteract these limitations, we propose a novel method for detecting breast tumors within DBT images. This method relies on a potent dynamic ensemble technique, along with robust individual breast tumor detectors (IBTDs). The proposed dynamic ensemble technique utilizes a deep neural network to select the optimal IBTD for detecting breast tumors, based on the characteristics of the input DBT image. The developed individual breast tumor detectors hinge on resilient deep-learning architectures and inventive data augmentation methods. This study introduces two data augmentation strategies, namely channel replication and channel concatenation. These data augmentation methods are employed to surmount the scarcity of available data and to replicate diverse scenarios encompassing variations in breast density, as well as the shapes, sizes, and locations of breast lesions. This enhances the detection capabilities of each IBTD. The effectiveness of the proposed method is evaluated against two state-of-the-art ensemble techniques, namely non-maximum suppression (NMS) and weighted boxes fusion (WBF), finding that the proposed ensemble method achieves the best results with an F1-score of 84.96% when tested on a publicly accessible DBT dataset. When evaluated across different modalities such as breast mammography, the proposed method consistently attains superior tumor detection outcomes.

Background Prevailing experimental and epidemiological evidence supports the role of circulating endogenous sex steroid hormones in the pathogenesis of ovarian carcinogenesis by dysregulation of cell differentiation, proliferation, and apoptosis but is scarce and inconclusive. Objectives This article evaluates the role of circulating levels of gonadotropins (follicle-stimulating hormone [FSH], luteinizing hormone [LH]) and androgens (testosterone, dehydroepiandrosterone-sulfate [DHEA-S]) for the risk of epithelial ovarian cancer in a case–control approach using samples collected in advance of clinical diagnosis. Materials and Methods A total of 100 epithelial ovarian cancer (EOC) patients and 100 healthy female controls were consequently enrolled in this hospital-based case–control study. Serum FSH, LH, testosterone, and DHEA-S were measured based on the principle of electrochemiluminescence immunoassay. Suitable descriptive statistics were used for different variables. Results Median values of FSH (58.9 vs. 45.5 IU/L, p = 0.02) and DHEA-S (163.43 vs. 142.2 ug/dL, p = 0.03) were significantly high in EOC patients compared with controls. Conditional logistic regression was used to estimate the odds ratio (OR) across increasing thirds of FSH and DHEA-S concentrations, and the results revealed that the highest third tertile of FSH (> 72.6 IU/L; OR = 3.0, confidence interval [CI] = 1.24–7.29, p trend = 0.04) and DHEA-S (> 194.2 ug/dL; OR = 3.8, CI = 1.26–11.61, p trend = 0.03) were significantly associated with increased risk of ovarian cancer in postmenopausal and premenopausal women, respectively. The statistically significant trend observed for FSH in postmenopausal women, remained only for the subgroup with menopause duration greater than 10 years (OR = 5.9, CI = 1.33–26.66, p trend = 0.04). FSH and DHEA-S concentrations and ovarian cancer risk were internally consistent with groups defined by oral contraceptive pill use, hormone replacement therapy, and smoking. However, no evidence was found for the association between serum LH and testosterone level with the occurrence of ovarian tumorigenesis. Conclusion Prediagnostic circulating concentration of FSH and DHEA-S unveiled a significant positive association with augmented risk of EOC, thus might serve as a predictive marker for the susceptibility to ovarian carcinogenesis and should be added in the screening profile of EOC for early recognition and scheduling necessary interventions/management strategies.

Introduction: Existing methodologies and risk stratification indices for predicting peri-operative cardiac complications in vascular surgery patient lack sufficient predictive value and therefore cannot be recommended for risk stratification. There are no Indian studies for preoperative cardiac risk scores for patients who undergo vascular and endovascular procedures. Therefore, an attempt was made to risk stratify and compare two existing cardiac risk indices (i.e., Detsky's modified cardiac risk index vs. Revised cardiac risk index [RCRI]) to predict peri-operative morbidity and mortality due to cardiac causes. The aim of this study: (a) To compare Detsky's modified cardiac risk index and RCRI to predict perioperative cardiovascular outcome in patients with peripheral vascular disease undergoing surgical intervention. (b) To predict perioperative cardiovascular outcome based on cardiac risk index in patients with peripheral vascular disease undergoing surgical intervention. Materials and Methods: This is an observational, prospective, longitudinal, controlled cohort study, which assessed 103 patients admitted at vascular centre for a period of 2 years. All patients undergoing vascular surgical procedure and evaluated by a cardiologist in the preoperative period were included in the study. Results: Eighteen patients (17.4%) had cardiac complications. The Detsky's index was found to be a satisfactory predictor of postoperative cardiac events (P < 0.001) as compared to RCRI which had a P < 0.003. There were a total of 10 mortalities (9.7%). Detsky's model and RCRI had positive predictive value (PPV) of 73.3% and 31.4%, specificity of 94.1% and 72.7%, respectively. Discussion: The overall sensitivity, specificity, PPV, negative predictive value of the Detsky's risk index, and RCRI in the prediction of cardiac events were 31.4%, 94.1%, 73.3%, 72.7% and 73.3%, 72.7%, 31.4%, 94.1%, respectively. In our study, the area under ROC for Detsky class was 0.76 versus 0.75 and superior to C statistic. However, the area under ROC for RCRI class was 0.72 versus 0.75 and inferior to C statistic. One important inference from the study was that 77.6% patients were smoker in the study group which emphasize the direct relation of peripheral vascular disease with smoking. Conclusion: The study concluded that patients with good surgical risk and profile undergoing minor vascular procedures can be operated without further testing. For other patients, the next step would be to incorporate the Detsky index. A Detsky score of 20 or more is comparable to a major clinical predictor in the American College of Cardiology/American Heart Association scheme.

Pediatric adrenocortical tumors (ACTs) are rare entities with an incidence of 0.2% of all pediatric tumors. Only two cases of antenatally detected ACT have been reported in the literature. Our case is the first report of an antenatally detected suprarenal mass which manifested with postnatal virilizing features and was proven to be adrenocortical adenoma on histology.

Introduction: To date, the focus on COVID-19 among children, especially in low- and middle-income countries, has been to address key issues including poor vaccination rates. However, the focus is changing with new variants and concerns regarding the development of hyperinflammatory syndromes. There have also been concerns with the overuse of antibiotics to treat patients with COVID-19, with the Indian Government developing guidelines, including those for children, to improve patient care. Consequently, a need to document the current management of children with COVID-19 in India and use the findings for future guidance. Materials and Methods: Pilot study assessing the management of children with COVID-19 among five hospitals in India using purposely developed case report forms, which had been piloted in Bangladesh. Results: Low numbers of children in hospital with COVID-19 (11.9% of in-patient beds). The majority were boys (58.3%) and between 11 and 18 years (55.5%). Reasons for admission were in line with previous studies and included respiratory distress/breathing difficulties. 69.4% of children with COVID-19 were prescribed antibiotics empirically, typically those on the Watch list, and administered parenterally, with only limited switching to oral therapy. A minority were prescribed antimalarials, antivirals and anti-parasitic medicines. There was appreciable prescribing of immune boosters and steroids. Conclusion: It was encouraging to see low hospitalisation rates. However, concerns with high empiric use of antibiotics and limited switching to oral formulations need to be addressed potentially, by instigating antimicrobial stewardship programmes. Similarly, other antimicrobials where these are not recommended.

The IEEE Access journal started in 2013, and in a short period, it has attained recognition for being a preferred multidisciplinary journal, with characteristics of rapid and continuous publishing. It is now ranked among the top journals in Engineering and Computer Science (General) by Scopus. Recognizing the distinctive nature of the journal and its contributions in the broader area of Engineering and Computer Science, this article attempts to present a detailed bibliometric analysis of the journal to identify publishing patterns, authorship and collaboration structure, citation impact, funding patterns of the published research, and the thematic structure of the publication. The gender distribution is also computed to identify papers published by male and female authors. The social media visibility of the articles and the Sustainable Development Goals (SDG) connections of articles were also identified. The results indicate that the IA journal can attract novel, high-quality multidisciplinary research, which aligns with the relevant and the most pressing SDGs. Furthermore, the journal has experienced increased multi-authored multidisciplinary research, and it is publishing a more significant percentage of articles with female first authors.

Due to the increasing need for time with respect to industrial growth and the speeding up of human day-to-day work, network evolution is always the center of focus for research organizations. Artificial intelligence (AI), on the other hand, is playing an increasingly important role in automating systems, increasing efficiency, and ensuring high dependability in complicated activities. Network and AI research are generating a boom in IoT applications, as firms strive to serve their consumers with ever-improving features and functionality. In this article, we look at the evolution of network technology across time as well as the role of AI in the next generation of networks. First, we will introduce the reader to the features of different network generations, technology used in. Second in the context of network evolution and AI, we will define the scope of IoT applications and their need in order to alleviate user demand. Consequently, we provide the requirements of advanced models in smart cities applications and insights on the development of future network for those applications. Our study showed that, though important features were introduced in the advanced automated networks, these are still to be tested under for automated applications that have strict requirements in terms of low latency, high reliability, and fast transmission.

Oral rotavirus vaccine (ORV) efficacy varies between countries, but underlying reasons aren’t fully understood. In this prospective cohort study, authors show that maternal rotavirus-specific antibodies in serum and breastmilk and pre-vaccination microbiota diversity are negatively correlated with ORV response in India and Malawi but not in the UK.

Abstract The entanglement entropy of many quantum systems is difficult to compute in general. They are obtained as a limiting case of the Rényi entropy of index m, which captures the higher moments of the reduced density matrix. In this work, we study pure bipartite states associated with S 3 complements of a two-component link which is a connected sum of a knot K $$ \mathcal{K} $$ and the Hopf link. For this class of links, the Chern-Simons theory provides the necessary setting to visualise the m-moment of the reduced density matrix as a three-manifold invariant Z( M K m $$ {M}_{{\mathcal{K}}_m} $$ ), which is the partition function of M K m $$ {M}_{{\mathcal{K}}_m} $$ . Here M K m $$ {M}_{{\mathcal{K}}_m} $$ is a closed 3-manifold associated with the knot K $$ \mathcal{K} $$ m , where K $$ \mathcal{K} $$ m is a connected sum of m-copies of K $$ \mathcal{K} $$ (i.e., K $$ \mathcal{K} $$ # K $$ \mathcal{K} $$ . . . # K $$ \mathcal{K} $$ ) which mimics the well-known replica method. We analayse the partition functions Z( M K m $$ {M}_{{\mathcal{K}}_m} $$ ) for SU(2) and SO(3) gauge groups, in the limit of the large Chern-Simons coupling k. For SU(2) group, we show that Z( M K m $$ {M}_{{\mathcal{K}}_m} $$ ) can grow at most polynomially in k. On the contrary, we conjecture that Z( M K m $$ {M}_{{\mathcal{K}}_m} $$ ) for SO(3) group shows an exponential growth in k, where the leading term of ln Z( M K m $$ {M}_{{\mathcal{K}}_m} $$ ) is the hyperbolic volume of the knot complement S 3 \ K $$ \mathcal{K} $$ m . We further propose that the Rényi entropies associated with SO(3) group converge to a finite value in the large k limit. We present some examples to validate our conjecture and proposal.

Leishmaniasis on the Indian subcontinent is thought to have an anthroponotic transmission cycle. There is no direct evidence that a mammalian host other than humans can be infected with Leishmania donovani and transmit infection to the sand fly vector. The aim of the present study was to evaluate the impact of sand fly feeding on other domestic species and provide clinical evidence regarding possible non-human reservoirs through experimental sand fly feeding on cows, water buffalo goats and rodents. We performed xenodiagnosis using colonized Phlebotomus argentipes sand flies to feed on animals residing in villages with active Leishmania transmission based on current human cases. Xenodiagnoses on mammals within the endemic area were performed and blood-fed flies were analyzed for the presence of Leishmania via qPCR 48hrs after feeding. Blood samples were also collected from these mammals for qPCR and serology. Although we found evidence of Leishmania infection within some domestic mammals, they were not infectious to vector sand flies. Monitoring infection in sand flies and non-human blood meal sources in endemic villages leads to scientific proof of exposure and parasitemia in resident mammals. Lack of infectiousness of these domestic mammals to vector sand flies indicates that they likely play no role, or a very limited role in Leishmania donovani transmission to people in Bihar. Therefore, a surveillance system in the peri-/post-elimination phase of visceral leishmaniasis (VL) must monitor absence of transmission. Continued surveillance of domestic mammals in outbreak villages is necessary to ensure that a non-human reservoir is not established, including domestic mammals not present in this study, specifically dogs.

Purpose: The present study was conceived to delineate the point of vascular dysfunction along the glycemic spectrum (normoglycemic individuals with no family history of diabetes, normoglycemic individuals with family history of diabetes, prediabetic individuals, and diabetic individuals). Materials and Methods: In this cross-sectional comparative study, we enrolled 252 participants of both gender in the age group of 30–50 years. They were classified based on their family history of diabetes and glycemic status into four groups along the glycemic spectrum as mentioned above. We measured flow-mediated dilation (FMD) from brachial artery and vascular function biomarkers such as enthothelin-1 (ET-1), von Willbrand Factor (vWF), Vascular Endothelial Growth Factor (VEGF) to assess the vascular function. The comparison of data between groups were done using One Way ANOVA/Kruskal–Wallis followed by post-hoc analysis using LSD/Mann–Whitney U Test depending on the normality of the data. Spearman correlation was done between vascular function and plasma glucose levels to identify its relationship. Linear regression was carried out to identify the factors influencing the FMD across the glycemic spectrum. Results: We observed that vascular function negatively correlated with blood glucose levels. However, endothelin-1 and vWF derangement was there even in normoglycemic first degree relatives of diabetes (FDRD) and the derangement increased in prediabetes and diabetes. Physiological dysfunction in terms of decreased flow-mediated dilation starts from prediabetes only. VEGF derangement is found only in diabetic individuals. Conclusion: Vascular dysfunction is found even in normoglycemic FDRD and the derangement increased and compounded with the advancement of disease.

Background: Principle of distraction and an indirect reduction was used to promote healing of fractures and adequate regeneration of cartilage at the subtalar joint. Aims and Objectives: The study was aimed to elaborate and develop role of Ilizarov as an alternative biological method to manage intraarticular fracture calcaneum with minimal chances of infection. Materials and Methods: Twenty-one patients were studied and the mean age of patients was 40.7 years (span: 20 to 65 years). Sanders CT classification was used to divide into type II, 11 (52.38%); type III, 7 (33.33%) and type IV, 3 (14.28%). The average followup was 17.2 months (range: 6 to 24 months). AOFAS scale for ankle and hindfoot was used for assessment of patients- 7 (33.33%) excellent, 7 (33.33%) good, 3 (14.28%) fair, and 4 (19.04%) poor results. The average score was 81.5 ±12.1. The mean period of treatment was 12 weeks (10 to 14 weeks). Results: On radiological assessment, Bohler’s angle change was 19.7±4.4 degrees to 33.51± 5.7 degrees; angle of Gissane changed from 126.4 ± 6.7 degrees preoperatively to 124.9 ± 6.9 degrees postoperatively; calcaneal height changed 40.14 ± 1.98 mm preoperatively to 43.33 ± 1.87 mm and width changed 45.09 ±3.65 mm preoperatively to 43.09 ±3.16 mm postoperatively and reduction malalignment >10 degrees in 5 patients. Superficial skin infection at wire insertion sites was the most common complication encountered in our cases. Conclusion: Our results with this ergonomic technique in a small number of 21 non-randomised cases with a mean followup of 17.2 years attribute towards an alternate surgical substitute to conventional open reduction techniques in the treatment of intra-articular fractures of calcaneum having lesser rate of complications.

Obtaining a closed form expression for the colored HOMFLY-PT polynomials of knots from 3-strand braids carrying arbitrary SU(N) representation is a challenging problem. In this paper, we confine our interest to twisted generalized hybrid weaving knots which we denote hereafter by Qˆ3(m1,−m2,n,ℓ). This family of knots not only generalizes the well-known class of weaving knots but also contains an infinite family of quasi-alternating knots. Interestingly, we obtain a closed form expression for the HOMFLY-PT polynomial of Qˆ3(m1,−m2,n,ℓ) using a modified version of the Reshitikhin-Turaev method. In addition, we compute the exact coefficients of the Jones polynomials and the Alexander polynomials of quasi-alternating knots Qˆ3(1,−1,n,±1). For these homologically-thin knots, such coefficients are known to be the ranks of their Khovanov and link Floer homologies, respectively. We also show that the asymptotic behavior of the coefficients of the Alexander polynomial is trapezoidal. On the other hand, we compute the [r]-colored HOMFLY-PT polynomials of quasi alternating knots for small values of r. Remarkably, the study of the determinants of certain twisted weaving knots leads to establish a connection with enumerative geometry related to mth Lucas numbers, denoted hereafter as Lm,2n. At the end, we verify that the reformulated invariants satisfy Ooguri-Vafa conjecture and we express certain BPS integers in terms of hyper-geometric functions F12[a,b,c;z].

Abstract Weaving knots W(p, n) of type (p, n) denote an infinite family of hyperbolic knots which have not been addressed by the knot theorists as yet. Unlike the well known (p, n) torus knots, we do not have a closed-form expression for HOMFLY-PT and the colored HOMFLY-PT for W(p, n). In this paper, we confine to a hybrid generalization of W(3, n) which we denote as W ̂ 3 $$ {\hat{W}}_3 $$ (m, n) and obtain closed form expression for HOMFLY-PT using the Reshitikhin and Turaev method involving ℛ $$ \mathrm{\mathcal{R}} $$ -matrices. Further, we also compute [r]-colored HOMFLY-PT for W(3, n). Surprisingly, we observe that trace of the product of two dimensional ℛ ̂ $$ \hat{\mathrm{\mathcal{R}}} $$ -matrices can be written in terms of infinite family of Laurent polynomials V n , t q $$ {\mathcal{V}}_{n,t}\left[q\right] $$ whose absolute coefficients has interesting relation to the Fibonacci numbers ℱ n $$ {\mathrm{\mathcal{F}}}_n $$ . We also computed reformulated invariants and the BPS integers in the context of topological strings. From our analysis, we propose that certain refined BPS integers for weaving knot W(3, n) can be explicitly derived from the coefficients of Chebyshev polynomials of first kind.

Purpose: To determine the effect of previous renal stone surgery on result and complications of percutaneous nephrolithotomy (PCNL). Materials and Methods: Total 300 patients were enrolled in the study. We enrolled 100 surgery-naive cases (those with no history of any renal surgery) as control and labeled them as Group A. Group B comprised 100 cases who had PCNL in the past. Group C constituted 100 patients who had open renal stone surgery in the past. Stones were classified using Guy's stone score. PCNL was performed by standard technique in prone position and technical features encountered during operation and outcomes were compared between groups. Complications were graded using modified Clavien grading system. Results: There were no differences between the three groups in age, gender, body mass index, stone burden, and stone opacity. Multiple calyceal stones and distorted pelvicalyceal system anatomy were more in Group C, but stone score showed no statistically significant difference from other groups. The mean operative time (68.91 ± 21.27 min) and fluoroscopy time (264.40 ± 74.90 s) were longer in Group C, but there was no statistically significant difference between the groups. Multiple access was significantly more common in Group C compared to the other two groups (P < 0.001). Access location too did not show any statistically significant difference between the groups. Postoperative complications were more in previous stone surgery patients, but did not show statistically significant difference. Conclusion: PCNL is a safe and effective treatment modality for patients with renal stones regardless of history of previous PCNL or open renal surgery.

The epidemic increase in online reviews' growth made the sentiment classification a fascinating domain in academic and industrial research. The reviews assist several domains, which is complicated to gather annotated training data. Several sentiment classification methodologies are devised for performing the sentiment analysis, but retrieval of information is not accurately performed, less effective, and less convergence speed. In this paper, we propose a sentiment paper proposes a sentiment classification model, namely Spider Monkey Crow Optimization algorithm (SMCA), for training the deep recurrent neural network (DeepRNN). In this method, the telecom review is employed to remove stop words and stemming to eliminate inappropriate data to minimize user's seeking time. Meanwhile, the feature extraction is performed using SentiWordNet to derive the sentiments from the reviews. The extracted SentiWordNet features and other features, like elongated words, punctuation, hashtag, and numerical values, are employed in the DeepRNN for classifying sentiments. To retrieve the required review, the Fuzzy K-Nearest neighbor (Fuzzy-KNN) is employed to retrieve the review based on a distance measure. With rigorous assessments and experimentation, it is observed that the proposed SMCA-based DeepRNN performs better in terms of accuracy of 97.7%, precision of 95.5%, recall of 94.6%, and F1-score 96.7%, respectively.

Video-assisted thoracoscopic surgery (VATS) is a less invasive approach for thoracoscopic surgery providing better visualization through minimal access. In addition, it offers less postoperative pain, fewer operative complications, and shortened hospital stay. These advantages make VATS ideal for the pediatric age group. Various societies recommend the use of VATS for Stage 2 pulmonary empyema and also in some cases of early Stage 3 where the plane of cleavage exists between the pleura and the exudate. A well-executed one-lung ventilation (OLV) is necessary for a successful VATS; however, performance of OLV and postoperative pain management in children poses a challenging task for an anesthesiologist.

Developing tools that help us understand and analyze the effects of cyber attacks on physical assets is necessary in order to detect and prevent harmful consequences of integrating Information and Communication Technologies (ICTs). In this paper, we review existing technologies for developing a fully virtualized cyber-physical testbed for cyber and physical data acquisition and machine learning anomaly detection. We present a testbed that uses network emulation and real industrial communication protocols to emulate the interactions of ICTs inside a wind-powered system. We use the testbed to simulate malicious cyber attacks, their effect on the physical system, and detection mechanisms for such disturbances using anomaly detection. The advantages of the presented virtualized testbed are: 1) integration of real industrial protocols, network analysis tools, and industry-leading data-engineering and machine learning tools; 2) enables a holistic analysis of cyber-physical systems by acquiring and analyzing simultaneously cyber and physical data; 3) cost effective solution for prototyping and testing that can run in a single laptop. The testbed combines unique technologies that enable testing of entire data-driven pipelines, including data acquisition, data management, analysis, and storage, emulating how they would run in a real system. We show how the presented approach can be used to analyze and profile both cyber and physical behavior. The experiments show the capabilities of the presented approach by demonstrating the successful detection of a malicious insertion command through observing anomalous behavior in both cyber and physical data.

Abstract We study the multi-boundary entanglement structure of the state associated with the torus link complement S 3 \T p,q in the set-up of three-dimensional SU(2) k Chern-Simons theory. The focal point of this work is the asymptotic behavior of the Rényi entropies, including the entanglement entropy, in the semiclassical limit of k → ∞. We present a detailed analysis of several torus links and observe that the entropies converge to a finite value in the semiclassical limit. We further propose that the large k limiting value of the Rényi entropy of torus links of type T p,pn is the sum of two parts: (i) the universal part which is independent of n, and (ii) the non-universal or the linking part which explicitly depends on the linking number n. Using the analytic techniques, we show that the universal part comprises of Riemann zeta functions and can be written in terms of the partition functions of two-dimensional topological Yang-Mills theory. More precisely, it is equal to the Rényi entropy of certain states prepared in topological 2d Yang-Mills theory with SU(2) gauge group. Further, the universal parts appearing in the large k limits of the entanglement entropy and the minimum Rényi entropy for torus links T p,pn can be interpreted in terms of the volume of the moduli space of flat connections on certain Riemann surfaces. We also analyze the Rényi entropies of T p,pn link in the double scaling limit of k → ∞ and n → ∞ and propose that the entropies converge in the double limit as well.

Background: As visceral leishmaniasis (VL) has recently expanded in previously non-endemic areas of Nepal, the health system is facing new challenges. Female community health volunteers(FCHVs) are playing an important role for VL elimination in Nepal. This study aimed to analyze the actual and potential role of FCHVs for VL elimination program as well as community awareness of the disease (VL) and protective measures. Methods: We used a concurrent embedded mixed methods design. Qualitative data were collected through in-depth interviews and focus group discussions with FCHVs of 22 VLendemic villages of 3 districts. Concurrently quantitative data were collected through formal interviews of 203 household heads of the same villages. Results: FCHVs are able to perform their duties in an efficient way with the support of their families and specific incentives. FCHVs in the VL-endemic region have a good ability to recognize the VL suspects and refer to health facilities. The feedback by the district health office on referred patients was weak thus missing the opportunity of involving FCHVs in the 6-months follow up. In houses with a previous VL case knowledge levels of prevention and treatment ofVL were significantly better than in houses without a previous VL case. More people in houses with a former VL patient were aware on VL transmission. Conclusion: FCHVs are playing an important role for VL elimination in Nepal through detection of suspected cases and referral and may play a role in vector surveillance.

Background: Oral health is an important component of general health, with dental caries affecting a person's ability to eat, speak, or socialize. Dental caries is one of the most prevalent diseases affecting human beings and persists till date as a challenge to the medical and dental profession in particular and the society in general. Aim: The study aims to assess the prevalence of dental caries among 12–15-years-old school-going children of government and private schools in Agra city, Uttar Pradesh, India. Materials and Methods: A crosssectional study was conducted among 12–15–years-old school-going children of government and private schools in Agra city, Uttar Pradesh, India. A total of 1600 school children were through a multistage random sampling procedure. The children were examined according to the World Health Organization criteria, 2013. Information regarding a patient's demographic profile was recorded using a self–administered questionnaire. Chi-square test was used to find the significance of study parameters. The level of significance (P value) was fixed at 0.05. Results: The present study reveals a prevalence of dental caries was almost of the same magnitude in the 12 and 13 years of age group, and it was found to be 28.6% and 28.9%, respectively among government and private school children. It was found that among 14 and 15 years of age groups, dental caries affected 22.9% and 19.6% of the study participants, respectively from both government and private school children. The results were found to be highly statistically significant between government and private school children regarding the number of carious teeth. Conclusion: The prevalence of dental caries was found to be the major public health problem among both the government and private school children of Agra city, which need immediate attention. Therefore, there is a need to develop preventive and promotional oral health strategies to combat this disease.

On top of their well known positive impact on air quality and CO2 emissions, electric vehicles generate less exhaust heat compared to traditional vehicles thanks to their high engine efficiency. As such, electric vehicles have the potential to mitigate the excessive heat in urban areas—a problem which has been exacerbated due to urbanisation and climate change. Still, the heat mitigation potential of electric vehicles has not been fully understood. Here, we combine high-resolution traffic heat emission inventories with an urban climate model to simulate the impact of the fleet electrification to the near-surface air temperature in the tropical city of Singapore. We show that a full replacement of traditional internal combustion engine vehicles with electric vehicles reduces the near-surface air temperature by up to 0.6°C. The heat mitigation potential is highest during the morning traffic peak and over areas with the largest traffic density. Interestingly, the reduction in exhaust heat emissions due to the fleet electrification during the evening traffic peak hardly leads to a reduction of near-surface air-temperatures, which is attributed to the different atmospheric conditions during morning and evening. This study presents a new quantification of the city-wide impact of electric vehicles on the air temperature in a tropical urban area. The results may support policy-makers toward designing holistic solutions to address the challenge of climate change adaptation and mitigation in cities.

The consequences of COVID-19 are not limited to physical health deterioration; the impact on neuropsychological well-being is also substantially reported. The inter-regulation of physical health and psychological well-being through the psychoneuroendocrineimmune (PNEI) axis has enduring consequences in susceptibility, treatment outcome as well as recuperation. The pandemic effects are upsetting the lifestyle, social interaction, and financial security; and also pose a threat through perceived fear. These consequences of COVID-19 also influence the PNEI system and wreck the prognosis. The nutritional status of individuals is also reported to have a determinative role in COVID-19 severity and convalescence. In addition to energetic demand, diet also provides precursor substances [amino acids (AAs), vitamins, etc.] for regulators of the PNEI axis such as neurotransmitters (NTs) and immunomodulators. Moreover, exaggerated immune response and recovery phase of COVID-19 demand additional nutrient intake; widening the gap of pre-existing undernourishment. Mushrooms, fresh fruits and vegetables, herbs and spices, and legumes are few of such readily available food ingredients which are rich in protein and also have medicinal benefits. BRICS nations have their influences on global development and are highly impacted by a large number of confirmed COVID-19 cases and deaths. The adequacy and access to healthcare are also low in BRICS nations as compared to the rest of the world. Attempt to combat the COVID-19 pandemic are praiseworthy in BRICS nations. However, large population sizes, high prevalence of undernourishment (PoU), and high incidence of mental health ailments in BRICS nations provide a suitable landscape for jeopardy of COVID-19. Therefore, appraising the interplay of nutrition and PNEI modulation especially in BRICS countries will provide better understanding; and will aid in combat COVID-19. It can be suggested that the monitoring will assist in designing adjunctive interventions through medical nutrition therapy and psychopsychiatric management.