Identities of Transgender People in Ancient Tamil Literature

In human society, it is natural to see two genders, male and female. It is somewhat surprising that the work of transgender people, who can be called the third gender, is somewhat surprising. In the Mahabharatam, the story of the birth of a transsexual is extended. In nature's creation, we find these people incarnated as transsexuals in practical life. The records of transgenders can be found in abundance in Sangam literary grammar. Transgender people, who have been marginalized in society, are denied the right to participate in public. Transgenders living in small groups in the human community have been ridiculed as "identityless." This is the situation today. In the Sangam literary records, their identity has been recognized socially. It can be said that their contribution to the level of education is low. Transgenders, who are marginalized people, are more likely to be rejected at all levels. Since they lacked the right to education, there was no context in grammatical and literary fiction in which the pedis (hermaphrodites), the transgenders, could register their right to life. No one comes forward to help in public, fearing that if they raise their voice for them, they will be respected as untouchables in society. This denial is also a contemporary phenomenon. As a result, it is necessary to compile how third-gender identities are recorded in the literary field. Transgenders, also known as hermaphrodites, exist as records in literary life. The location of such people's lives is clearly visible in grammatical and literary fiction

Effects of Cyclic Strain and Growth Factors on Vascular Smooth Muscle Cell Responses

Under physiological and pathological conditions, vascular smooth muscle cells (SMC) are exposed to different biochemical factors and biomechanical forces. Previous studies pertaining to SMC responses have not investigated the effects of both factors on SMCs. Thus, in our research we investigated the combined effects of growth factors like Bfgf (basic fibroblast growth factor), TGF-β (transforming growth factor β) and PDGF (platelet-derived growth factor) along with physiological cyclic strain on SMC responses. Physiological cyclic strain (10% strain) significantly reduced SMC proliferation compared to static controls while addition of growth factors bFGF, TGF-β or PDGF-AB had a positive influence on SMC growth compared to strain alone. Microarray analysis of SMCs exposed to these growth factors and cyclic strain showed that several bioactive genes (vascular endothelial growth factor, epidermal growth factor receptor, etc.) were altered upon exposure. Further work involving biochemical and pathological cyclic strain stimulation will help us better understand the role of cyclic strain and growth factors in vascular functions and development of vascular disorders

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all >0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council

Dry spell analysis for effective water management planning

Abstract: Knowing the dry and wet periods with rainy seasons is essential for successful water management planning in any particular area. With this view, this study analyzed the thirty years (1975-2004) monthly rainfall data of Udumalpet station located in Parambikulam Aliyar sub basin (Tamilnadu) on annual, seasonal and monthly basis for planning a suitable water conservation management system. Sixty two per cent of the total rainfall is received from North East Monsoon and seventeen per cent from South-West Monsoon. In the study period, four years were found to be wet, four years were found to be dry and the remaining twenty two years were found to be normal years. The analysis showed that the annual and seasonal rainfall data did not clearly indicate the problem of drought in the region; whereas the monthly rainfall data indicated serious concerns to deal with drought particularly during the winter and summer months. It also revealed that the winter months were the most susceptible to severe drought conditions. Out of 30 years of study, January and February were found to be the dry months which normally facilitate for the good harvest of the kharif sown long duration crops. There is a need to adopt adequate moisture conservation measures like mulching etc. to mitigate the effect of drought spells during critical periods of crop growth, and to construct water harvesting ponds/tanks for application of pre-sowing irrigation to Rabi (winter) crops, and supplemental irrigation during periods of water scarcity

A novel approach for protein secondary structure prediction using encoder–decoder with attention mechanism model

Computational biology faces many challenges like protein secondary structure prediction (PSS), prediction of solvent accessibility, etc. In this work, we addressed PSS prediction. PSS is based on sequence-structure mapping and interaction among amino acid residues. We proposed an encoder–decoder with an attention mechanism model, which considers the mapping of sequence structure and interaction among residues. The attention mechanism is used to select prominent features from amino acid residues. The proposed model is trained on CB513 and CullPDB open datasets using the Nvidia DGX system. We have tested our proposed method for Q 3 and Q 8 accuracy, segment of overlap, and Mathew correlation coefficient. We achieved 70.63 and 78.93% Q 3 and Q 8 accuracy, respectively, on the CullPDB dataset whereas 79.8 and 77.13% Q 3 and Q 8 accuracy on the CB513 dataset. We observed improvement in SOV up to 80.29 and 91.3% on CullPDB and CB513 datasets. We achieved the results using our proposed model in very few epochs, which is better than the state-of-the-art methods

Extensional rheology of shear-thickening nanoparticle suspensions

A filament-stretching rheometer is used to measure the extensional properties of shear-thickening nanoparticle suspensions as a function of concentration and extension rate. The experiments are performed using a series of colloidal suspensions consisting of concentrations of 17.5 wt%, 25 wt% and 30 wt% of fumed silica nanoparticles in polypropylene glycol. The shear rheology of these suspensions was found to demonstrate dynamic shear-thickening behavior owing to the formation of large hydrodynamic clusters. The critical value of angular frequency for the onset of shear-thickening was found to increase monotonically with decreased strain amplitude. The extensional rheology of all the tested suspensions demonstrated modest strain-hardening at low strain rates. At a critical extension rate, a dramatic increase in both the speed and magnitude of the strain-hardening is observed for both the 25 wt% and 30 wt% suspensions with increasing extensional rate. The steady state extensional viscosity as a function of extension rate shows sharp extensional thickening transition very similar to shear flows. The increase in strain-hardening is likely due to the formation of strings and clusters ordered in the flow direction. This hypothesis is confirmed by small-angle light scattering measurements of the flow of the nanoparticle suspension through a microfluidic hyperbolic contraction. The degree of alignment of nanoparticles is quantified from the analysis of the scattering patterns and found to increase significantly with increasing extension rate

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Not AvailableThe 4 (L) distributory of Pollachi main canal, Parambikulam-Aliyar-Palar (PAP) basin has been selected for an in-depth water management study. The project area has been divided into two zones namely, A zone and B zone. Each zone would get water from the canal system once in every two years. From the analysis of rainfall data of the rain gauge stations located in Parambikulam-Aliyar-Palar basin, it was observed that there was a wide temporal and spatial variability in annual rainfall over the years. The lowest annual rainfall recorded was 210.6 mm (over the plain) in 2003 and the highest of 5346.4 mm (in the hills) in 2007. The average annual rainfall for the period 1988-2010 was 1372.1 mm. The irrigation water requirement for the crops grown in the 4 (L) distributory was estimated using AquaCrop3.1 model for the years 2000-2010. The total irrigation water requirement during deficit rainfall year (2002) was 58.4 percent which is higher compared to normal year (2008). During the excess rainfall year (2007), the demand was 5.32 percent lower than the normal year demand. Therefore, the conjunctive use management of surface and groundwater resources in a command area can play a significant role in managing water by distributing the water throughout the season, while also maintaining the long-term sustainability of groundwater resources.Not Availabl

A widespread glutamine-sensing mechanism in the plant kingdom

Glutamine is the primary metabolite of nitrogen assimilation from inorganic nitrogen sources in microorganisms and plants. The ability to monitor cellular nitrogen status is pivotal for maintaining metabolic homeostasis and sustaining growth. The present study identifies a glutamine-sensing mechanism common in the entire plant kingdom except Brassicaceae. The plastid-localized PII signaling protein controls, in a glutamine-dependent manner, the key enzyme of the ornithine synthesis pathway, N-acetyl-l-glutamate kinase (NAGK), that leads to arginine and polyamine formation. Crystal structures reveal that the plant-specific C-terminal extension of PII, which we term the Q loop, forms a low-affinity glutamine-binding site. Glutamine binding alters PII conformation, promoting interaction and activation of NAGK. The binding motif is highly conserved in plants except Brassicaceae. A functional Q loop restores glutamine sensing in a recombinant Arabidopsis thaliana PII protein, demonstrating the modular concept of the glutamine-sensing mechanism adopted by PII proteins during the evolution of plant chloroplasts

Internet of Things enabled open source assisted real-time blood glucose monitoring framework

Abstract Regular monitoring of blood glucose levels is essential for the management of diabetes and the development of appropriate treatment protocols. The conventional blood glucose (BG) testing have an intrusive technique to prick the finger and it can be uncomfortable when it is a regular practice. Intrusive procedures, such as fingerstick testing has negatively influencing patient adherence. Diabetic patients now have an exceptional improvement in their quality of life with the development of cutting-edge sensors and healthcare technologies. intensive care unit (ICU) and pregnant women also have facing challenges including hyperglycemia and hypoglycemia. The worldwide diabetic rate has incited to develop a wearable and accurate non-invasive blood glucose monitoring system. This research developed an Internet of Things (IoT) - enabled wearable blood glucose monitoring (iGM) system to transform diabetes care and enhance the quality of life. The TTGOT-ESP32 IoT platform with a red and near-infrared (R-NIR) spectral range for blood glucose measurement has integrated into this wearable device. The primary objective of this gadget is to provide optimal comfort for the patients while delivering a smooth monitoring experience. The iGM gadget is 98.82 % accuracy when used after 10 hours of fasting and 98.04 % accuracy after 2 hours of breakfast. The primary objective points of the research were continuous monitoring, decreased risk of infection, and improved quality of life. This research contributes to the evolving field of IoT-based healthcare solutions by streaming real-time glucose values on AWS IoT Core to empower individuals with diabetes to manage their conditions effectively. The iGM Framework has a promising future with the potential to transform diabetes management and healthcare delivery