Multi-Alignment method coupled with phylogenetic analysis we disclosed the Nsp9 and Nsp10 non-structural proteins of Corona Virus as rRNA RlmH/K methyltransferases with similarities with bin recombinase and int-core integrase fold. Further, Nsp9 has similarities to S8 ribosomal protein and Nap10 has similarity to S10 ribosomal protein. Previously, we showed Nsp13, Nsp14, Nsp15 and Nsp16 are also different types of rRNA RlmE/N and Cfr-like methyltransferases-ribonuclease with RNA helicase domains. Two domains of Nsp13 astonishingly have similarities to ribosomal proteins L6 and L9. Taken together, Nsp9/10 and Nsp13-16 proteins could mimic host ribosome assembly and also could methylate rRNA of mitobibosome preventing mitochondrial protein synthesis and oxidative phosphorylation. Low ATP synthesis causes lowering blood pressure following coma but very ATP concentration (1-10nM) surely induces platelets aggregation through vWA, collagen and GpIIb/IIIa proteins followed by fibrin formation and blood clotting as recently have seen in the lung of many Corona virus infected patients. We have also postulated that two polyproteins itself resemble like 28S and 38S mitoribosome subunits and compete with rRNAs inhibiting the ribosome turnover and new protein synthesis due to their similarities with many ribosomal proteins. Such finding may be valuable in computer-based novel drug design against Corona virus.

Covid-19 infections are rapidly spreading worldwide with more than 100000 death and thus understanding the molecular mechanism of tropism of human cells is an urgent need for drug design. We have described here a bioinformatics approach to predict the functional aspects of non-structural nsp16 protein of Corona virus. The covid-19 7098 AA large polyprotein was degraded into sixteen proteins and last nsp16 protein was found an RlmE type rRNA methyltransferase. Nsp16 has no similarity to bacterial RlmABCD but has 25 percent similarity to the bacterial RlmE protein which methylates the U2551 2-hydroxy group of Ribose. The nsp16 proteins of different corona viruses like covid-19, bat-coronavirus, SARS and MERS have strong homology. Mrm2 and Dim1 like yeast and mammalian rRNA methyltransferases have 26-33 percent homologies but not with 2-O-capping MTase as reported previously. Rrp8 MTases also has no similarity to nsp16. We postulated that mitochondrial rRNA methylation of bronchial cells were mediated by the nsp16 protein causing inhibition of protein synthesis due to poor assembly of aminoacyl-tRNA or mRNA and peptidyl transferase at the PTC. This is one of the new molecular mechanism of corona virus cellular tropism and different than ACE-2 mediated blockage of cellular signalling to inhibit aldesterone biosynthesis with abnormal Na⁺ ions in cells. We also designed primers based on nsp16 cDNA sequence (nt 20659-21552, accession no MT121215) specific for Covid-19 diagnosis by RT-PCR.

AMR and drug void have caused huge panic today with few thousand death per year. MDR Typhoid was a serious old disease and caused serious health hazard in humen and animals demanding an update on molecular biology of the status on transferable genetic elements. R-plasmids combined in F’-plasmid and the new MDR conjugative plasmids were shown abundant in Sanmonella ranging 70-440kb with similarities. BlaTEM, blaCTX-M, blaOXA, blaNDM mdr genes were abundant in >50 plasmids analyzed and metal resistant gene clusters are predominant in most large plasmids. Among the acetyltransferase all catA1, aacA1 and aac-1b-cr genes were located. Abundant streptomycin phosphotransferases (StrAB) and rarely colistin resistant Mcr-5/9 phosphoethanolamine–lipid A transferase were detected. Altered isomeric dihydropterote synthases (Sul1/2/3) were present giving sulfamethoxazole resistance and dhfr gene frequently associated giving trimethoprim resistance. Metal resistant gene clusters like SilABC (CusABC), PcoAB, RcnA, terABC, and merABCXT etc were found in many Salmonella enterica plasmids. Toxin genes like HipA and virulence genes like spvABD were located in few plasmids increasing virulence and pathogenesis. Drug efflux genes tetA or tetB and OqxB, floR, CmlA were frequent where as QepA and EamA genes were rarely seen. Thus, Salmonella metal resistant genes combined with antibiotic resistant genes has tried to overcome the both toxic antibiotics and metalions causing Typhoid AMR. Such acquisition spreads salmoniasis in the live stocks (pig, cow, chicken) where toxic soil and water dominate increasing chance of MDR typhoid in human.

Vaccines are one of the most effective medical interventions, playing a pivotal role in treating infectious diseases. Although traditional vaccines comprising of killed, inactivated, or live attenuated pathogens have resulted in protective immune responses, negative consequences of their administration have been well-appreciated. Modern vaccines have evolved to contain purified antigenic proteins, epitopes, or antigen-encoding mRNAs, rendering them relatively safe. However, reduced humoral and cellular responses pose major challenges to modern vaccine platforms. Protein nanoparticle (PNP)-based vaccines have garnered substantial interest in recent years for their ability to present repetitive array of antigens for improving immunogenicity and enhancing protective responses. Discovery and characterization of naturally occurring PNPs from various living organisms such as bacteria, archaea, viruses, insects, and eukaryotes, as well as computationally designed structures and approaches to link antigens to the PNPs have paved the way for unprecedented advances in the field of vaccine technology. In this review, we focus on some of the widely used naturally occurring and optimally designed PNPs for their suitability as promising vaccine platforms for displaying native-like antigens from viral pathogens for protective immune responses. Such platforms hold great promise in combating emerging and re-emerging infectious diseases and enhancing vaccine efficacy and safety.

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

In this exploratory work, we have examined the impact of an external static electric field on the H2 storage capacity of clathrate hydrates. To this end, we have chosen the 512 clathrate hydrate and examined the encapsulation of 1 - 4 H2 molecules within it. Results suggest that with the help of moderate electric fields (±0.10 to ±0.31V/Å), the encapsulation of 1 H2 molecule within the 512 clathrate hydrate becomes thermodynamically more favorable. In the cases of 4H2@512 and 2H2@512, however, the concerned processes become thermodynamically more favorable only when the field is applied along a specific direction. No favorable outcome could be observed in the case of 3H2@512, irrespective of the direction of the applied field. It appears from the results obtained herein that it might be possible to design a suitable external electric field to facilitate the hydrogen storage capacity of clathrate hydrates at ambient conditions, at least in certain cases.

Artificial membrane systems can serve as models to investigate molecular mechanisms of different cellular processes, including transport, pore formation, and viral fusion. However, the current simulacrums such as SUVs, GUVs, and the supported lipid bilayers suffer from issues, namely high curvature, heterogeneity, and surface artefacts, respectively. Freestanding membranes provide a facile solution to these issues, but current systems developed by various groups use silicon or aluminium oxide wafers for fabrication that involves access to a dedicated nanolithography facility and high cost while conferring poor membrane stability. Here, we report the development, characterization and applications of an easy-to-fabricate suspended lipid bilayer (SULB) membrane platform leveraging commercial track-etched porous filters (PCTE) with defined microwell size. Our SULB system offers a platform to study the lipid composition-dependent structural and functional properties of membranes with exceptional stability in a high throughput fashion. With dye entrapped in PCTE microwells by SULB, we show that sphingomyelin significantly augments the activity of pore-forming toxin, Cytolysin A (ClyA) and the pore formation induces lipid exchange between the bilayer leaflets. Further, we demonstrate high efficiency and rapid kinetics of membrane fusion by dengue virus in our SULB platform. Our suspended bilayer membrane mimetic offers a novel platform to investigate a large class of biomembrane interactions and processes.

Total 219 countries and territories globally suffering from the recent pandemic COVID-19 is now in its second wave with more brutality, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) . It has several symptoms like as persistent fever; respiratory illnesses; cough; fatigue; shortness of breath; loss of appetite; persistent pain or pressure in the chest; dysgeusia; acute respiratory distress syndrome (ARDS) etc., and here the things to worry about is the development of pulmonary fibrosis after COVID-19 in both peoples who had died of due to acute respiratory distress syndrome (ARDS) or those who survived. Due to COVID-19, dysregulated immune response and wound repair mainly in elderly patients causes this secondary pulmonary fibrosis. Thus using anti-fibrotic agents could be meaningful in these circumstances although their efficacy in treating COVID-19 is subject to more detailed laboratory research works. In this review article you will get to know about the lung fibrosis generation due to COVID-19 infection, about anti-fibrotic agents and the currents challenges of this field.

Decision tree algorithms have been among the most popular algorithms for interpretable (transparent) machine learning since the early 1980s. On the other hand, deep learning methods have boosted the capacity of machine learning algorithms and are now being used for non-trivial applications in various applied domains. But training a fully-connected deep feed-forward network by gradient-descent backpropagation is slow and requires arbitrary choices regarding the number of hidden units and layers. In this paper, we propose near-optimal neural regression trees, intending to make it much faster than deep feed-forward networks and for which it is not essential to specify the number of hidden units in the hidden layers of the neural network in advance. The key idea is to construct a decision tree and then simulate the decision tree with a neural network. This work aims to build a mathematical formulation of neural trees and gain the complementary benefits of both sparse optimal decision trees and neural trees. We propose near-optimal sparse neural trees (NSNT) that is shown to be asymptotically consistent and robust in nature. Additionally, the proposed NSNT model obtain a fast rate of convergence which is near-optimal up to some logarithmic factor. We comprehensively benchmark the proposed method on a sample of 80 datasets (40 classification datasets and 40 regression datasets) from the UCI machine learning repository. We establish that the proposed method is likely to outperform the current state-of-the-art methods (random forest, XGBoost, optimal classification tree, and near-optimal nonlinear trees) for the majority of the datasets.

A chronically stable electrode material with low impedance for recording neural activity and high charge-injection capacity for functional electro-stimulation is desirable for the fabrication of implantable microelectrode arrays that aims to restore impaired or lost neurological functions in humans. For this purpose, we have investigated the electrochemical properties of sputtered ruthenium oxide (RuOx) electrode coatings, deposited on planar microelectrode arrays, using an inorganic model of interstitial fluid (model-ISF) at 37o C as the electrolyte. Through a combination of cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) modelling study we have established the contribution of faradaic reaction as the major charge-injection contributor within the safe neural stimulation potential window of 0.6 V vs Ag|AgCl. We have also established the reversibility of the charge-injection process for sputtered RuOx film by applying constant charge-per-phase current stimulations at different pulse widths and by comparing the magnitudes of leading and trailing access voltages during voltage transient measurements. Finally, the impedance of the sputtered RuOx film was found to be reasonably comparable in both its oxidized and reduced states, although electronic contribution from capacitive double-layer was found to be slightly higher for the completely oxidized film around 0.6 V than its reduced counterpart around -0.6V.

Since December 2019, the worldwide spread of COVID-19 has brought the majority of the world to a standstill, affecting daily lives as well as economy. Under these conditions, it is imperative to develop a cure as soon as possible. On account of some of the adverse side effects of the existing conventional drugs, researchers all around the world are screening natural antiviral phytochemicals as potential therapeutic agents against COVID-19. This paper aims to review interactions of some specific phytochemicals with the receptor binding domain (RBD) of the Spike glycoprotein of SARS-CoV-2 and suggest their possible therapeutic applications. Literature search was done based on the wide array of in-silico studies conducted using broad spectrum phytochemicals against SARS-CoV-2 and other viruses. We shortlisted 26 such phytochemicals specifically targeting the S protein and its interactions with host receptors. To validate the previously published results, we also conducted molecular docking using the AutoDockVina application and identified 6 high potential phytochemicals for therapeutic use based on their binding energies. Besides this, availability of these compounds, their mode of action, toxicity data and cost-effectiveness were also taken into consideration. Our review specifically identifies 6 phytochemicals that can be used as potential treatments for COVID-19 based on their availability, toxicology results and low costs of production. However, all these compounds need to be further validated by wet lab experiments and should be approved for clinical use only after appropriate trials.

With an explosion of data in the nearly every domain, from physical and environmental sciences to econometrics and even social science, we have entered a golden era of time-domain data science. In addition to ever increasing data volumes and varieties of time-series, there's a plethora of techniques available to analyses them. Unsurprisingly, machine learning approaches are very popular. In environmental sciences (ranging from climate studies to space weather/solar physics), machine learning (ML )and deep learning (DL) approaches complement the traditional data assimilation approaches. In solar and astrophysics, multiwavelength time-series or lightcurves along with observations of other messengers like gravitational waves provide a treasure trove of time-domain data for ML/DL approaches for modeling and forecasting. In this regard, deep learning algorithms such as recurrent neural networks (RNNs) should prove extremely powerful for forecasting as it has in several other domains. Such methods agnostic of the physics can only predict transient flares that are represented in the original distribution trained on (eg. coloured noise fluctuations) and not special, isolated episodes (eg. a one-off outburst like a major coronal mass ejection) potentially distinguishing them. Therefore it is vital to test robustness of these techniques ; here we attempt to make a small contribution to this by exploring sensitivity of RNNs with some rudimentary experiments. We test the performance of a very successful class of RNNs, the Long Short Term Memory (LSTM) algorithms with simulated lightcurves. As an example, we focus on univariate forecasting of time-series (or lightcurves) characteristic certain variable astrophysical objects (eg. active galactic nuclei or AGN). Specifically, we explore the sensitivity of training and test losses to key parameters of the LSTM network and data characteristics namely gaps and complexity measured in terms of number of Fourier components. We find that typically, the performances of LSTMs are better for pink or flicker noise type sources. The key parameters on which performance is dependent are batch size for LSTM and the gap percentage of the lightcurves. While a batch size of $10-30$ seems optimal, the most optimal test and train losses are under $10 \%$ of missing data for both periodic and random gaps in pink noise. The performance is far worse for red noise. This compromises detectability of transients. Thus, we show that generative models (time-series simulations) are excellent guides for use of RNN-LSTMs in building forecasting systems

Food is the component that serves the primary purpose of survival for all of us. In the pre-pandemic situation, engagement with online food communities was considerably low. People enjoyed the experience of going outdoors and sharing experiences about the food and the restaurants. However, with the lockdown and imposition of the rules, going outdoors has become unfeasible. The pandemic has also affected consumers' consumption behaviour regarding food. No literature has studied the consumers' emerging trend of food consumption behaviour during the pandemic. I intend to explore and understand the dominant themes and consumer insights regarding food consumption through netnography to address this gap. I have considered the "Dil se Foodie" community as one of the largest online food communities on Facebook.

Extending from the current Elaboration likelihood model scholarship, this article proposes a framework for applying ELM to cricket bat purchase. Professional cricketers or fans require comprehensive and adequate pieces of information about cricket bat through the Internet. Buyers simultaneously encourage internet reviews for product impressions, and they experience meaningful associations. ELM and the Internet exemplify the cricket bat buying process by engaging buyers with product specification and create a meaningful relationship between buyers and sellers. At the same time, buyers feel empowered to choose a product of their choice. Describing the Elaboration likelihood model, we have facilitated an approach for cricket bats buying. This article has explored how ELM through the Internet can encourage buyers to be informative about cricket bats while silencing retailers' voices and visions into a unique buyer-seller relationship.

Blazars are highly variable and display complex characteristics. A key characteristic is the flux distribution or flux PDF whose shape depends upon the form of the underlying physical process driving variability. The BL Lacertae, Mrk 421 is one of the brightest and most variable blazars across the electromagnetic spectrum. It has been reported to show hints of lognormality across the spectrum from observed histograms of radio to gamma-ray fluxes. This would imply that the underlying mechanisms may not conform to the "standard" additive, multi-zone picture, but could potentially have multiplicative processes. This is investigated by testing the observed lightcurves at different wavelengths with time-series simulations. We find that the simulations reveal a more complex scenario, than a single lognormal distribution explaining the multiwavelength lightcurves of Mrk 421.

In the present work we consider two modified Chevallier-Polarski-Linder (CPL) models in the background of homogeneous and isotropic FLRW space-time, namely (i) the generalized CPL model (Model I) and (ii) the logarithmic form of the the equation of state for the dark energy. From the observational data sets ((Pantheon+)+BAO+HST), we find that at the present epoch (redshift $z=0$), the equation of state for the dark energy converges almost at the same value $\omega_{fld}\approx -0.86$ and the variation of $\omega_{fld}(z)$ with respect to the redshift parameter is very small for both models. we also find that the present value of the Hubble parameter $H_0$ is almost same for both the models. Finally, we compare the models in the light of Akaike, Bayesian Information Criterion (BIC) and Bayesian Evidence. However, we find that Model II is better compared to the Model I from the estimated value of the deceleration parameter.

Article explores participant specific study of muscle inherehit dynamics hidden inside the diognostic electromyography (D-EMG) signals during load pull exercises, aiming to uncover underlying patterns and nonlinear behaviors. Employing a multi-step analytical framework, the study first evaluates signal stationarity through Quantile-Quantile (Q-Q) plot and surrogate data analyses, revealing insights into signal stability. Subsequent use of phase space reconstruction techniques exposes intrinsic dynamics within the EMG signals, visualized through Poincar´e maps, elucidating attractor geometry and system dynamics. Histogram analysis further dissects the Poincar´e maps, offering insights into signal behavior relative to physiological processes. Additionally, the study quantifies the largest Lyapunov exponent from the Poincar´e maps, providing a measure of dynamical complexity within the muscle EMG signals during load pull exercises. By integrating these methods, this research sheds light on the nuanced interplay between EMG signals and muscle activity during dynamic exercises, offering valuable insights for rehabilitation strategies.

The triple-negative breast cancer (TNBC) subtype is one of the most aggressive forms of breast cancer that has poor clinical outcome and still remains as an unmet clinical challenge. Accumulating evidence suggests that intratumoral heterogeneity or the presence of phenotypically heterogeneous cell populations within a tumor plays a crucial role in chemoresistance, tumor progression and metastasis. Increased understanding of the molecular regulators of intratumoral heterogeneity will enable the development of effective therapeutic strategies in TNBC. We have identified a molecular mediator involved in intratumoral heterogeneity in breast cancer using an unbiased approach. We isolated two heterogeneous tumor cell populations from the 4T1 TNBC tumor model and phenotypic characterization revealed that the cells are distinct in terms of their morphology, proliferation and self-renewal ability in vitro; as well as primary tumor formation and metastatic potential in vivo. Further, RNA sequencing on both cell populations was performed to identify the molecular mediators underlying this heterogeneity. Bioinformatic analysis performed on the differentially expressed genes along with the Kaplan-Meier survival analysis in TNBC patients identified Metastasis associated colon cancer 1 (Macc1) as the top candidate gene mediating the aggressive phenotype. The role of Macc1 in regulating the proliferative phenotype was validated using siRNA mediated gene knockdown. The role of Macc1 in the aggressive cancer cell phenotypes and disease progression is being studied further using a small molecule transcriptional inhibitor of Macc1 in cell line and animal models, thus increasing our understanding of the molecular underpinnings of intratumoral heterogeneity in breast cancer that is critical to the improvement in the treatment of women currently living with the highly aggressive TNBC subtype.

Last Chance Tourism (LCT) is an increasingly popular phenomenon whereby tourists seek encounters with vanishing landscapes, cultures, and endangered species. However, there are concerns that it is not sufficiently ecologically informed, has a large carbon footprint, and may put further pressure on vulnerable ecosystems and communities. The Arctic has emerged as a major global frontier for LCT, and at the same time is at the forefront of disruptive and accelerating climate change. Here a review of important LCT literature is combined with a review of key insights from the concept of Ecological Grief, which calls for explicitly mourning the losses of formerly ecologically rich landscapes, species diversity, and traditional knowledge. While there is currently insufficient engagement with grief and mourning in LCT, Ecological Grief can provide a new research focus as well as a pathway to share empathy, concern, and sorrow between scientists, communities, and visitors—thereby offering an alternative way to critically reflect upon our connections with the vanishing cryosphere in the Anthropocene.

Aluminum (Al), making up a third of the Earth's crust, is a widespread toxic contaminant, particularly in acidic soils. It impacts crops at multiple levels, from the cellular to the whole plant. This review delves into aluminum's reactivity, including its cellular transport, involvement in oxidative redox reactions, development of specific metabolites, and the influence of genes on the production of membrane channels and transporters, as well as its role in triggering apoptosis leading to senescence. It discusses the involvement of channel proteins in calcium influx, vacuolar proton pumping, the suppression of mitochondrial respiration, and the initiation of programmed cell death. At the cellular nucleus level, the effects of Al on gene regulation through alterations in nucleic acid modifications, such as methylation and histone acetylation, are examined. The review in addition outlines the pathways of Al induced metabolic disruption specifically citric acid metabolism, regulation of proton excretion, induction of specific transcription factors, modulation of Al-responsive proteins, changes of citrate and nucleotide glucose transporters and overall metal detoxification pathways in tolerant genotypes. It also considers the expression of phenolic oxidases in response to oxidative stress, their regulatory feedback on mitochondrial cytochrome proteins, and their consequences on root development. Ultimately, the review focuses on the selective metabolic pathways that facilitate Al exclusion and tolerance, emphasizing compartmentalization, antioxidative defense mechanisms, and the control of programmed cell death to manage metal toxicity.

The current theories of consciousness do not address the two major problems:What is the solution to the hard problem of consciousness or What is the experience of self-existence? and How is conscious perception computed? We address these questions using our hypothesized theory:The Self Simulation theory and propose a model of computation of consciousness.The components of the model are an interconnected network of auxiliary processors or Auxiliary Neural Networks(AN) which receives input from the external sensory modalities,computes a representation of the information and relays it to the NCC(Neural Correlates of Consciousness), the NCC – a processing unit which can be neuro anatomically distributed in location but computationally connected to each other and to the Auxiliary Networks,and a working memory which the NCC references for further computation of information.Computation of conscious perception is achieved via the decoding of the content of the memory by the NCC.The self simulation theory accounts not only for the various phenomenal experiences but also experimentation paradigms conducted in the past.

Medical Trust-Network is one of the most promising fields of study in network science. Establishment of trust within medical entities ensures better treatment and increases better medical facilities. The word ‘Trust’ signifies a very important behavioral aspect between any human entities, especially among doctors and patients. To represent such relationships Trust Network Models are built to express the interactions between human entities within such networks. Though the idea of a Trust-Network has traditionally been one of the major areas of research, yet the concept of a medical trust network model is relatively a new domain. In this paper, we introduce an overall multilayered Trust Network to represent the entire healthcare architecture. More specifically our model is based on an evolutionary graph system with a discrete relationship between the three most important entities of any healthcare system, namely – Doctors, Departments, and Hospitals. Observations indicate that based on our model, the medical healthcare system is a multilayered model unlike a feed-forward model as indicated by previous studies.

Real-world time series data sets contain a combination of linear and nonlinear patterns, making the time series forecasting problem more challenging. In this paper, a new hybrid methodology is introduced for forecasting univariate time series data sets using a multiplicative error modeling approach. An autoregressive integrated moving average (ARIMA) model is combined with an autoregressive neural network (ARNN) for improving the predictions of individual forecast models. The proposed multiplicative ARIMA-ARNN model glorifies the chances of capturing the different combinations of linear and nonlinear patterns in time series. The model shows outstanding performance on six standard time-series data sets compared to other widely used single and hybrid forecasting models.

Urbanization induced land use land cover (LULC) changes intensify the urban heat island effects. It magnifies the risk of urban dwellers and sometimes causes the loss of human life, defined as heat-related health risk (HRHR). Hence, urban LULC planning plays a crucial role. Present study analyses the impact of composition and configuration of urban LULC defined as urban landscape metric (ULM) on HRHR in Delhi at the ward level. Firstly, the HRHR is measured by using satellite thermal and other digital data. Then, measured HRHR is validated by conducting a rapid field survey. Thirdly, ULM measured at ward level using Fragstat 4 software. Finally, both, HRHR and ULM linked with bi-variate Moran's I and impacts of ULM are assessed using ordinary least square (OLS) and spatial error (SE) regression. The result indicates the high risk is found as clustered in north-east, central and middle of south-west Delhi. Built-up density intensifies HRHR and abundance of vegetation reduce it; however, it is not similar for all vegetation patches. Larger vegetation patches surrounded by dense built-up might not able to reduce the risk as much as a large vegetation patch could in other regions. Findings can be helpful for heat resilient city planning.

Thalassemia is a common monogenic autosomal disorder prevalent in India. HbE beta thalassemia is a compound heterozygous state of two different beta globin mutations (HBB), predominant in the Eastern India. In HbE-beta thalassemia (β⁺/β°) patients, one HBB mutation does not produce any functional protein (β°); another mutation produces a structural altered haemoglobin, variant E (β⁺). It has been observed that in HbE-beta thalassemia patients with same type of HBB mutations, there exist diverse phenotypic presentation ranging from very severe, with regular transfusion-dependence to clinically non severe requiring very less transfusion or no transfusion. To explore this phenotypic mystery, we performed trio based expanded whole exome sequencing (WES) of two extreme phenotypes of HbE beta thalassemia subjects with similar HBB genotype and their parents. For WES library preparation, Agilent Sure select V6+UTR kit was used and sequencing was done through the Illumina HiSeq 2500 platform. This study aimed to search for de novo or inherited variants associated with the clinical severity. Six significant inherited variants were found in the genes, ATOH8, TTLL4, P2RX7, PRSS54, SLC9C2 and VRK2 in severe subject, however only one significant inherited variant in MTRR gene was found in non-severe subject. Bioinformatic analysis also confirms that each variant significantly changes in respective protein structure. The identified genes were either associated with iron absorption, oxidative stress, hematopoietic stem cell differentiation, structural organization of RBC cytoskeleton or regulating anemia. No significant de novo variant were identified associated with clinical severity. The finding of this study indicates that the combined effect of mutation load in major pathways may responsible for severe phenotype.

Diabetes mellitus (DM) is one of the principal manifestations of metabolic syndrome and its prevalence with modern lifestyle is increasing incessantly. Chronic hyperglycemia can induce several vascular complications that were referred to be the major cause of morbidity and mortality in DM. Although several therapeutic targets have been identified and accessed clinically, the imminent risk of DM and its prevalence are still ascending. Substantial pieces of evidence revealed that histone deacetylase (HDAC) isoforms can regulate various molecular activities in DM via epigenetic and post-translational regulation of several transcription factors. To date, 18 HDAC isoforms have been identified in mammals that were categorized into 4 different classes. Classes I, II, and IV are regarded as classical HDACs, which operate through a Zn-based mechanism. In contrast, class III HDACs or Sirtuins depend on nicotinamide adenine dinucleotide (NAD+) for their molecular activity. Functionally, most of the HDAC isoforms can regulate β cell fate, insulin release, insulin expression and signaling, and glucose metabolism. Moreover, the roles of HDAC members have been implicated in the regulation of oxidative stress, inflammation, apoptosis, fibrosis, and other pathological events, which substantially contribute to diabetes-related vascular dysfunctions. Therefore, HDACs could serve as the potential therapeutic target in DM towards developing novel intervention strategies. This review sheds light on the emerging role of HDACs/isoforms in diabetic pathophysiology and emphasized the scope of their targeting in DM for constituting the novel interventional strategies for metabolic disorders/complications.

The risk of 'zoonotic spillovers,' or the transmission of viruses from animals to humans, has been raised by climate change and the devastation of nature, as infectious disease experts have long warned. Even as the world works to stop the spread of the currently unfolding pandemic of coronavirus disease 2019 (COVID-19) and the breakout of monkeypox virus (MPXV), a new animal virus, the Langya henipavirus (LayV), has been discovered in humans in Eastern China. The scientists say there is little danger of the virus spreading among humans, but it shares genetic material with Hendra virus and Nipah virus, two other henipaviruses that infect humans and cause life-threatening respiratory diseases. Humans infected with LayV can expect to experience high body temperature, cough, weariness, poor appetite, muscle discomfort, myalgia, nausea and vomiting. It is likely that the virus will spread from animals to humans. Currently, the health authorities of Taiwan and other health organizations are tracking the progress of the ailment to ensure it does not reach humans. Researchers have examined 25 species of small wild animals for presence of the virus, and so far, shrews are the only ones that have tested positive for the virus's RNA. Based on these results, shrews are a possible candidate for the virus's natural reservoir. Too far, no therapies or vaccines have been developed and licensed for henipaviruses like the LayV. When other therapies fail to alleviate viral infections, ribavirin may be the next best thing. The need for novel vaccinations against the LayV infection and the timely delivery of these vaccines to areas at high epidemiological risk is real. To lessen the likelihood of a health calamity being caused by this newly developing virus, it is crucial to conduct active surveillance in a transparent and globally collaborative manner. The questions that have not been answered yet require additional study.

The integration of diverse distributed generation (DG) units, encompassing both Renewable Energy Sources (RES) and non-RES technologies delves into voltage levels, current distributions, and power flows, aiming to optimize and effectively manage the distribution network. An RES-based DGs such as photovoltaic systems and wind turbines, alongside non-RES units like fuel cells and micro turbines. This study proposes a hybrid approach the Multi-Objective Genetic Algorithm - Grey Wolf Optimizer (MOGA-GWO). By merging the strengths of multi-objective genetic algorithms with the efficiency of the Grey Wolf Optimizer, this advanced algorithm seeks semi-optimal solutions for multi-objective optimization problems. The algorithm aims to improve convergence speed without compromising solution quality, offering a promising solution for optimizing the characteristics of DG and RES integration in distribution networks compared to Cuckoo Search and Simulation Annealing Techniques. Key algorithmic operations include individual representation, initialization, fitness function computation, selection, crossover, mutation, and ending conditions. The DG optimal power flow problem is explored with a focus on minimizing generation costs, improving voltage profiles, minimizing losses, enhancing reliability, integrating renewable energy, reducing environmental impact, managing congestion, and ensuring compliance with operational constraints. Beyond traditional considerations, the study emphasizes neglected objectives and constraints, such as cyber-security concerns, real-time operation, regulatory frameworks, social acceptance, lifecycle environmental impact, grid resilience, data privacy, aging infrastructure compatibility, and economic viability.

Motivated by the work of Saridakis (Phys. Rev. D 102, 123525 (2020)), the present study reports the cosmological consequences of Barrow holographic dark energy (HDE) and its thermodynamics. Literatures demonstrate that Dark Energy (DE) may result from electroweak symmetry breaking that triggers a phase transition from early inflation to late time acceleration. In the present study, we incorporated viscosity in the Barrow HDE. A reconstruction scheme is presented for the parameters associated with Barrow holographic dark energy under the purview of viscous cosmology. Equation of state (EoS) parameter is reconstructed in this scenario and quintessence behaviour is observed. Considering BarrowHDE as a specific case ofNojiri-Odintsov (NO) HDE, we have observed quintom behaviour of the EoS parameter and for some values of n the EoS has been observed to be very close to −1 for the current universe. The generalised second law of thermodynamics has come out to be valid in all the scenarios under consideration. Physical viability of considering Barrow HDE as a specific case of NO HDE is demonstrated in this study.

A reliable Electronic Voting Machine (EVM) is proposed and implemented in this study, which is integrated with a biometric fingerprint scanner to ensure a secure election process. This biometric EVM includes features such as an interactive user interface, hack-free design and master lock. The EVM system has the capability of registering user data and storing them in a database through proper authentication. Moreover, the system proposed lowers the requirement for human resources. This paper provides a detailed description of the systematic development of the hardware and software used. The software part includes algorithm development and implementation. A thorough and in-depth understanding of the data and the communication protocols along with the pathways used for storage of data in the devices is provided. Additionally, the cost of the system is 62.82% less than the officially existing EVM machines of India. Furthermore, this study seeks to demonstrate the benefits of such an approach from a technological and a social standpoint.

The beautiful structures of single and multi-domain proteins are clearly ordered in some fashion but cannot be readily classified using group theory methods that are successfully used to describe periodic crystals. For this reason, protein structures are considered to be aperiodic, and may have evolved this way for functional purposes, especially in instances that require a combination of softness and rigidity within the same molecule. By analyzing the solved protein structures, we show that orientational symmetry is broken in the aperiodic arrangement of the secondary structural elements (SSEs), which we deduce by calculating the nematic order parameter, $P_2$. We find that the folded structures are nematic droplets with a broad distribution of $P_2$. We argue that non-zero values of $P_2$, leads to an arrangement of the SSEs that can resist mechanical forces, which is a requirement for allosteric proteins. Such proteins, which resist mechanical forces in some regions while being flexible in others, transmit signals from one region of the protein to another (action at a distance) in response to binding of ligands (oxygen, ATP or other small molecules).

Several studies have shown promising treatments for type 1 diabetes mellitus (T1DM) using developing gene therapy methods. This review article focuses on summarizing possible new treatment options and outlining their pros and cons, since there is no cure for T1DM as of yet. New treatments involve islet and stem cell transplantation, genetic vaccination, and immunological precursor cell-mediated therapy. Since most of these methods are still in their early stages, efficacy in human trials of this type of treatment is still largely unknown, however, researchers are hopeful after numerous successes in trials with non-obese diabetic (NOD) mice.

The invention of nanoscience not only brings a revolutionary change in the field of science but also changed the direction of research. Today the whole world is under the trigger of nano and nanoparticles have multidimensional applications in every aspect of life including environmental point of view. Till today a plethora of nanoparticles have been synthesized and have also been applied for multiple purposes and hence grabbed the attention of researchers all over the world. Among the bunch of NPs discovered to date, we have a particular interest in silver nanoparticles (AgNPs) because of their cost-effectiveness and huge abundance in the earth’s crust. With respect to every passing day, due to various kinds of anthropological activities, the quality of the environment such as air, water and soil is depleting which ultimately hampers the human civilization. To encompass the growing environmental issues, many techniques have been adopted. Among the many strategies, tackling the current issues regarding environment through nanoscience is highly worthy as because of its cost-effectiveness, less time consuming and easy handling process. This article reviews the potential of nanoparticles, particularly silver nanoparticles, for a wide range of environmental applications, such as soil, air, and water remediation.

Metazoans have an elaborate and functionally segmented body. It evolves from a single cell by systematic divisions. Metazoans attain structural complexity with exquisite precision, which is a molecular mystery. The indispensable role of centrioles in cell division and ciliogenesis can shed insight into this riddle. Cell division helps in growth of the body and is a highly regulated and integrated process. Its errors cause malignancies. The cell mass is organized during organogenesis. Prior to it, the centrioles are retrieved from the cell cycle to initiate ciliogenesis. The cilia-modulated developmental signaling pathways elaborate the body plan. The secluded compartment of the cilium reduces noise during signaling and is essential for a precise body plan development. The dysfunctional centrioles and cilia can distort body plan. Thus, centriole has a dual role in growth and cellular organization. This concept review analyses the comprehensive interactome and the key domain features (like C2 domain) of molecules which connect and disarm the centriole from the cell cycle and ciliogenesis by switching on or off the essential regulators of the pathways. The concentration of these signaling pathways at the centriole reinforces the hypothesis that centriole is the molecular workstation to carve out structural design and complexity in metazoans.

Campylobacter is one of the major foodborne pathogens of concern in its growing trend of antimicrobial resistance. C. jejuni and C. coli are the major causative agents, with C. jejuni contributing to most of the cases in approximately 90% in the world. Infection is transmitted to humans due to consumption of contaminated food and water. Campylobacteriosis caused by C. jejuni is commonly presented with severe diarrhoea, abdominal pain, fever, headache, nausea, and vomiting with some extreme cases resulting in Guillain–Barré syndrome (GBS) and acute flaccid paralysis. Symptoms are severe in cases of children below 5 years, elderly and individuals who are immunocompromised. The infection is usually sporadic, and self-limiting and thus does not require antibiotics for treatment. Still, the antimicrobial resistance in Campylobacter is a major concern because of the transmission of resistance from animal sources to humans. This review highlights the recent epidemiology, geographical impact, resistance mechanisms, spread of Campylobacter spp. and the strategies to control the transmission of Campylobacter from veterinary sources and its antimicrobial resistance.

The coal mining process generates wastes such as overburden and tailings, the disposal of which is a significant environmental challenge. The circular economy model of eliminat-ing waste and regenerating the economy and ecosystems can minimise the impact of coal mining wastes. Another resource-intensive industry is the construction industry, which is responsible for significant resource consumption, waste generation, and emissions. Reus-ing and recycling coal mining wastes as secondary or value-added building materials in the construction industry per circular economy principles will help minimise the impact and have environmental and economic benefits. Several studies have demonstrated the use and reuse of coal mining wastes in the construction industry. This article conducts a systematic literature review to understand the state-of-the-art utilisation of coal mining waste in the construction industry. After a series of refinements using the PRISMA approach, 54 articles were included in the review. The articles were further divided based on using coal mining wastes in the construction industry as end products/application areas. The review results show that coal mining waste has been successfully used to make bricks and aggregates (fine and coarse), replace cement, and develop geopolymers, concrete, roads, and embankments. The studies suggest the utilisation of coal mining waste primarily in non-structural components, with very few studies suggesting using coal mining waste in structural applications. The systematic literature review helped in understanding the knowledge development related to the possible application of coal mine wastes in the construction industry, identifying the gap in the field, and suggesting future research directions.

In contemporary society, digital technology permeates every aspect of our routines. This study assessed students' comprehension of the environmental impacts of prolonged screen time, specifically during binge-watching sessions. It investigated awareness of carbon emissions from electronic device usage, binge-watching habits, and influencing factors such as content preferences, duration, and frequency. The study also explored potential interventions to mitigate environmental impacts. Using a mixed-methods approach, data were collected from 525 higher education students (150 male, 375 female) through self-designed standardized questionnaires. The analysis involved Percentage, t-test, ANOVA, Multiple Correlation, and coding processes. Results indicated that 66.67% of students had a high level of understanding regarding the environmental impact of binge-watching, while only 4.76% were highly aware of the carbon emissions from extended screen time. Additionally, 23.81% exhibited high levels of binge-watching habits and behavior. Gender disparities were significant; females demonstrated a deeper understanding of the environmental impacts (t=4.08, p < α) and showed different binge-watching habits compared to males (t=3.16, p < α). However, no significant gender difference was found in awareness of carbon emissions (t=0.28, p > α). A notable difference (t=12.98, p < α) was observed between students' understanding of environmental impacts and their awareness of carbon emissions. The study also revealed a weak positive correlation (R=0.36) and significant differences [F(2, 1572) = 320.10, p < 0.05, 0.01] in understanding the environmental impacts, awareness of carbon emissions, and binge-watching behaviors. Factors influencing binge-watching and potential regulatory measures were also identified.

To understand SARS-CoV-2 microevolution, this study explored the genome-wide frequency, gene-wise distribution, and molecular nature of all point-mutations detected across its 71,703 RNA-genomes deposited in the GISAID repository, till 21 August 2020. Globally, nsp1/nsp2/nsp3/ nsp11 and orf7a/orf3a/S were the most mutation-ridden non-structural and structural genes respectively. Phylogeny based on 4,618 spatiotemporally-representative genomes revealed that entities belonging to the early lineages are mostly spread over Asian countries (including India, the biggest hotspot of the pandemic) whereas the recently-derived lineages are more globally distributed. Of the total 16,602 polymorphism-bearing sites in the pan-genome, 11,037 and 4,965 involved transitions and transversions, which in turn were predominated by cytidine-to-uridine and guanosine-to-uridine conversions, respectively. Positive selection of nonsynonymous mutations (dN/dS >1) in most of the structural, but not non-structural, genes indicated that SARS-CoV-2 has already harmonized its replication/transcription machineries with the host’s metabolic system, while it is still redefining virulence/transmissibility strategies at the molecular level.

This paper presents an on-device semi-supervised human activity detection system that can learn and predict human activity patterns in real time. The proposed semi-supervised learning (SSL) framework uses sparsely labelled user activity events acquired from Inertial Measurement Unit (IMU) sensors installed as wearable device. The objective is to learn classification of multiple classes of human activities in real-time. The proposed cluster-based learning model in this approach is trained with data from the same target user, thus preserving data privacy while providing personalized activity detection services. Two different cluster labelling strategies, namely, population-based, and distance-based, are employed to achieve the desired classification performance. A comparative study of these strategies has been presented in terms of classifiability and classification accuracies. The proposed system is shown to be computationally efficient, which is relevant in the context of limited computing resources on typical wearable devices. The trade-off between classification accuracy and computation complexity is analyzed for different algorithmic hyper-parameters and other system parameters. Extensive experimentation and simulation study have been conducted on a multi-user human activity data from the public do-main in order to validate the proposed learning paradigm.

Critical care of neonates involves substantial usage of antibiotics and exposure to multidrug resistant (MDR) nosocomial pathogens. These pathogens are often exposed to sub-MIC doses of antibiotics which might result in a range of physiological effects. Therefore, to understand the outcome of sub-inhibitory dosage of antibiotics on Staphylococcus populations, nasal swab specimens were collected from 34 neonates admitted to the Sick Newborn Care Unit between 2017-2018, a total of 41 non-repetitive isolates were included in this study. Staphylococcus haemolyticus was the prevalent species (58.54%) with high non-susceptibility to cefotaxime (CTX) (79.16%), gentamicin (87.50%), and meropenem (54.17%). Biofilm forming abilities of S. haemolyticus isolates in the presence of sub-optimal CTX (30μg/mL), the predominantly prescribed β-lactam antibiotic, were then determined by crystal violet assays and extracellular DNA (eDNA) quantitation. CTX was found to significantly enhance biofilm production among the non-susceptible isolates (p-valueWilcoxin test- 0.000008) with increase in eDNA levels (p-valueWilcoxin test- 0.000004). Additionally, no changes in non-susceptibility were observed among populations of two MDR isolates, JNM56C1 and JNM60C2 after >500 generations of growth in the absence of antibiotic selection in vitro. These findings demonstrate that sub-MIC concentration of CTX induces biofilm formation and short-term non-exposure to antibiotics does not alter non-susceptibility among S. haemolyticus isolates.

Balancing the levels of ammonia, in poultry facilities plays a role in enhancing the welfare and productivity of animals. Various environmental factors such as temperature, humidity, ammonia concentrations, carbon dioxide concentration and exposure to light have an impact on the wellbeing and efficiency of poultry. It is essential to monitor these elements to achieve outcomes necessitating practical, reliable and cost-effective solutions. Leveraging the Internet of Things (IoT) in conjunction with LoRa-WAN (Long Range Wide Area Network) technology presents an opportunity in the industry by enhancing connectivity among devices and facilitating real time data transmission. This research introduces a hardware and software setup for monitoring conditions at poultry farms through LoRa WAN and IoT technologies. More-over researchers employed Random Forest Machine Learning prediction models to tune the concentration of Ammonia (NH3) in poultry facilities across a wide area or multiple Poultry houses. Comparative assessments were conducted to evaluate the proposed system against devices revealing a correlation exceeding 0.9830 between the sensors and standard equipment while costing 28% less than traditional tools. The prototype displayed outcomes underscoring its potential, for managing poultry facilities across multiple farms with centralized oversight.

Long COVID is a phenomenon in which individuals experience persistent symptoms after recovering from COVID-19. The symptoms are discovered to be unique for every individual and can affect multiple organs systems in the body. This study aims to identify effective natural remedies for long COVID by analyzing hub genes associated with the symptoms of the condition and evaluating the repurposed drugs catered and used for treating the symptoms of long COVID. The most common and prevalent symptoms of long COVID were identified; Fatigue, Shortness of Breath, Loss of Smell, Headache, Brain Fog, Chest Pain, Insomnia, Heart Palpitations, Dizziness, Joint Pain, Depression, Anxiety, Tinnitus, Loss of Appetite. Hub genes for each of the symptoms provided an insight on the key biological pathways of the symptom. Repurposed drugs identified, provided the template to identify the natural compounds with similar structure as a potential therapeutic drug. The natural compounds were retrieved using fingerprint search of the repurposed drugs from the NPASS Database. The findings of this study suggest several natural remedies for each symptom based on the molecular docking of the hub gene and natural compound using iGEMDOCK. The identified natural remedies may hold promise in treating long COVID, but further research is required to explore the efficacy and effectiveness of the proposed natural compounds. The results of the study pose important implications for the development of effective treatments for long COVID.

Genetic variability in rice breeding program plays the very crucial role. It provides outstanding pool of superior alleles governing better agronomic and quality characters through association mapping. For the understanding of population structure and genetic relationship among the different rice lines is indispensable prior to setting of correlation among dynamic alleles and traits. In the present investigation, genetic diversity and population structure of 116 rice accessions by using 64 polymorphic SSR markers was targeted for the evaluation of the genetic relatedness and diversity. Genotyping assessment based on SSR markers revealed a total of 225 alleles, with an average PIC value of 0.755. The germplasm lines were classified into three distinct subgroups through population structure analysis, utilizing both model and distance-based approaches. AMOVA analysis showed that 11% of the total variation could be attributed to differences between groups, while the remaining 89% of the variation was likely due to differences within groups. The study suggests that the population structure and genetic relatedness should be considered when working with the core collection of 116 rice germplasm lines for association mapping, aiming to establish marker-trait associations.

Application of chemical pesticides to protect agricultural crops from pests and diseases is discouraged due to their harmful effects on human and environment. Therefore, alternative approaches for crop pro-tection through microbial or microbe originated pesticides have been gaining momentum. Wheat blast is a destructive fungal disease caused by Magnaporthe oryzae Triticum (MoT) pathotype, which poses a seri-ous threat to global food security. Screening of secondary metabolites against MoT revealed that antimy-cin A isolated from a marine Streptomyces sp. had significant inhibitory effect on mycelial growth in vitro. This study aimed to investigate the inhibitory effects of antimycin A on some critical life stages of MoT and evaluate the efficacy of wheat blast disease control by this natural product. Bioassay indicated that antimycin A suppressed mycelial growth, conidiogenesis, germination of conidia and formation of ap-pressoria in germinated conidia of MoT in a dose-dependent manner with minimum inhibitory concen-tration 0.005 μg/disk. If germinated, antimycin A induced abnormal germ tubes (4.8%) and suppressed the formation of appressoria. Interestingly, application of antimycin A significantly suppressed wheat blast disease in both seedling and heading stages of wheat supporting the results from invitro study. This is the first report on inhibition of mycelial growth, conidiogenesis, conidia germination, detrimental morphological alterations in germinated conidia, and suppression of wheat blast disease caused by a Triticum pathotype of M. Oryzae. Further study is required to unravel the precise mode of action of this promising natural compound for considering it as a biopesticide to combat wheat blast.

Long COVID, also referred to as post-COVID-19 condition, describes the lingering after-effects of COVID-19 infection. This complex syndrome encompasses a range of symptoms affecting physical well-being, cognitive function, and mental health. The widespread impact of long COVID extends beyond individual sufferers, placing significant strain on healthcare systems and causing far-reaching socioeconomic consequences. The scale of this multifaceted health crisis is unparalleled in recent history, affecting millions globally and challenging our understanding of post-viral conditions. This study aimed to explore the possibility of targeting G protein-coupled receptors (GPCRs) signaling pathway-related genes as therapeutics for long COVID using computational analysis. Targeting GPCRs and their signaling pathways holds significant promise for long COVID therapeutics, as these receptors are involved in crucial physiological processes including immune regulation, inflammation control, and neurotransmission. All of these are implicated in the diverse and persistent symptoms of long COVID, potentially offering a versatile approach to addressing multiple aspects of the condition simultaneously. This study identified 21 genes associated with GPCRs for further exploration as potential targets. Notably, GPCR genes such as HRAS, KRAS, GNAQ, and GNA11 were determined to be possible therapeutic targets for the pathophysiological mechanisms of long COVID. FDA-approved drugs targeting these genes were identified, including Binimetinib, Cabozantinib, Selumetinib, Panitumumab, Cetuximab, Adagrasib, Tipifarnib, and Sotorasib. Additionally, Naltrexone and Tipifarnib have emerged as potential new treatment options for long COVID. SARS-CoV-2 may hijack GPCR signaling pathways to dysregulate lung ion and fluid transport, contributing to the pathophysiology of pulmonary edema in patients with COVID-19. Further research is required to translate the findings into the development of therapeutics and to investigate the relationship between viral infection and GPCR signalling.

Water is an essential commodity to sustain life. The condition of water in Tiruchirappalli was measured using different Physicochemical parameters like Temperature, pH, TDS, Total Solids, Salinity, Total Hardness, and Electrical Conductivity. Water samples were collected from different places in Tiruchirappalli city, Tamil Nadu. Water samples were examined by different chemical methods. According to the results, Thiruvarambur-1 showed comparatively higher results in the case of every parameter compared to other sampling stations. Obtained results were further interpreted using statistical tools. Considering ECs as a principal component for the regression and correlation analysis with other parameters significant correlation was found. A strong correlation was observed between ECs and TDS, Total Hardness, Turbidity, and Salinity.

As the outbreak of coronavirus disease 2019 (COVID-19) is continuously increasing in India, so epidemiological modeling of COVID-19 data is urgently required for administrative strategies. Time series and is capable to predict future observations by modeling the data based on past and present data. Here, we have modeled the epidemiological COVID-19 Indian data using various models. Based on the collected COVID-19 outbreak data, we try to find the propagation rule of this outbreak disease and predict the outbreak situations in India. For India data, the time series model gives the best results in the form of predication as compared to other models for all variables of COVID-19. For new cases, new deaths, total cases and total deaths, the best fitted ARIMA models are as follows: ARIMA(0,2,3), ARIMA(0,1,1), ARIMA(0,2,0) and ARIMA(0,2,1). Based on time series analysis, we predict all variables for next month and conclude that the predictive value of Indian COVID-19 data of total cases is more than 20 lakhs with more than 43 thousand total deaths. The present chapter recommended that a comparison between various predictive models provide the accurate and better forecast value of the COVID-19 outbreak for all study variables.

As the demand of heating and air conditioning is increasing day by day due to getting a comfortable life, for that reason, the market for heat pump and air conditioning systems or both, is seeing a steady increase in low global warming potential. All researchers on heat pump and air conditioning systems are searching for environmentally friendly refrigerants. However, a significant number of contemporary refrigerants (HCFCs) have the potential to cause global warming and ozone depletion, such as those found in heat pump air conditioning systems. Using more environmentally friendly refrigerants, including hydrocarbon and blend refrigerant mixtures, is one way to lower GWP and Ozone depletion potential. This study examines the performance of several alternative refrigerants, including R32, R134A, R410A, R22, and R290. In order to examine the performance of R290, theoretical and simulation results are compared on various refrigerants while taking into account a number of performance parameters, including the refrigerant energy efficiency ratio, mass flow rate, coefficient of performance, cooling capacity, and compressor work for one ton of refrigeration (1TR) air conditioners. One player with a very low GWP is R290. However, the only drawback is that it can catch fire and is hazardous to use in split-type commercial heat pump air conditioning applications. The environmental and thermo physical properties of HC-290 are significantly better than those of other materials, according to theoretical and simulation studies utilizing Cool Pack software, hence it is a viable replacement.

To utilize heterosis and combining ability for grain yield and its attributing traits along with three physiological traits viz., leaf area index, chlorophyll fluorescence and chlorophyll content in bread wheat (Tritium aestivum L.) the crosses were attempted during rabi, 2019-20 in a half diallel mating scheme among 8 wheat varieties and the study was carried out during rabi, 2020-21 at Block No. D-13 field of Mahua block, Simradha research farm, Rani Lakshmi Bai Central Agricultural University, Jhansi. Analysis of variance showed significant differences for treatments. Based on per se performance the hybrids NW 5054 x PBW 723 (23.3 g), and HI 1544 x NIAW 34 (23.14 g), were identified for the higher grain yield. The hybrid HI 544 x NIAW 34 (18.41 %) was identified as the best heterotic cross for grain yield per plant and its component traits. The hybrids HI 1544 x NIAW 34 (3.40) and HI 1544 x GW 322 (2.76), as well as the parents HD 3086 (21.85) and PBW 723 (20.68), were identified as superior economic hybrids and parents based on SCA/GCA effects, per se performance for grain yield per plant, and its component trait in bread wheat. Days to heading, flag leaf length, biological yield per plant, harvest index, number of grains per spike, 1000 grain weight, spike length, leaf area index, chlorophyll fluorescence, and chlorophyll content were all positively correlated with grain yield per plant.

Land surface temperature (LST) is a critical parameter for land surface and atmospheric interactions. However, the applicability of current land surface temperature estimates for field-level hydrological, agricultural, and ecological operations is still challenging due to their coarse spatiotemporal resolution. In the current article, we have downscaled 100 m LST to 10 m by using high-resolution Sentinel-1,2 optical-microwave data and three different models- 1) Thermal Sharpening (TsHARP); 2) Thin Plate Spline (TPS); and 3) Random Forest (RF). The extensive analysis was performed at agricultural farms in the semi-arid (IARI) region of India during the winter and summer seasons of 2020-21 and 2021-22, arid (CAZRI) and per-humid (UBKV) region (2021-2022). The calibration accuracy of the RF model was shown to better agreement with the coefficient of determination (R2) of 0.982, root means square error (RMSE) 0.181 and normalized root means square error (RMSE) 0.061 with their lower values of standard errors over three diverse agro-climatic zones. The findings demonstrate that the validation accuracy of models' varied according to the agroclimatic zones, although RF and TPS consistently outperformed as compared to the TsHARP models.

Observations of ocean surface winds from Indian scatterometer SCATSAT-1 have been combined with background wind field from a numerical weather prediction (NWP) model available at National Centre for Medium Range Weather Prediction (NCMRWF) to generate a 6-hourly gridded hybrid wind product. A distinctive feature of the study is to produce a global gridded wind field from SCATSAT-1 scatterometer passes with spatio-temporal data gaps at regular synoptic hours relevant for forcing models and other NWP studies. This is done by making use of concepts from the modern particle filter technique, which does not represent the model probability density function (PDF) following the Gaussian technique. The 6 hourly hybrid wind is generated for the entire year of 2018 and is validated using the wind speed from daily gridded level-4 SCATSAT-1 winds (L4AW), Cross Calibrated Multi-Platform dataset (CCMP) and global buoy data from National Data Buoy Centre (NDBC). The results indicate potential of the technique to produce scatterometer winds at the desired temporal frequency with significantly less noise and along swath biases. The study shows the generated hybrid winds have very high quality with respect to the already existing daily product available from ISRO.

Urinary peptides are the products of systemic protein turn over which are excreted out of the body and hence can serve as an important biomarker for various pathophysiology. These peptides in other species of bovine have been reported to possess several bioactive properties. To investigate the potential of urinary peptides we generated a peptidome profile from the urine of Murrah Buffaloes (n=10). Urine samples were processed using &lt;10 kDa MWCO filter, filtrate obtained was used for peptide extraction using Solid Phase Extraction (SPE). Eluate, obtained after SPE was extracted using ethyl acetate and the peptide-containing aqueous phase was collected. We extensively assessed the antimicrobial properties of the urinary aqueous phase. The nLC-MS/MS of the aqueous phase from 10 animals resulted in the identification of 8165 peptides originating from 6041 parent proteins. 76 Proteases responsible for the release of these sequences from precursor proteins were also identified. We further analyzed these peptide sequences to identify bioactive peptides and classify them into anti-cancerous, anti-hypertensive, anti-microbial, and anti-inflammatory groups with a special emphasis on antimicrobial properties. With this in mind, we simultaneously conducted experiments to evaluate antimicrobial properties of urinary aqueous extract on three pathogenic bacterial strains S. aureus, E. coli, &amp; S. agalactiae.

Study in black rice has gain prominence in recent times due to its high nutritive value, curative effect, and anti-oxidant properties. However, its poor agronomic traits, including low yield necessitates the incorporation of the colour-grain trait into elite varieties through plant breeding techniques. SSR markers play an important role in plant identification and breeding. Here, the generation of reference-based transcriptome, annotation of transcriptome datasets, and a large set of simple sequence repeat (SSR) markers derived from Black rice have been described. In all 28664 SSRs were predicted in 34978 (48.59%) expressed transcripts. However, 7068 (20.20%) transcripts were found to have more than one SSR. The identified SSRs were dominated by tri-nucleotide and tetra-nucleotide repeats representing about 54.11% and 33.31% respectively, of total SSRs. Validation of selected markers associated with anthocyanin trait performed across different black rice accessions established the reliability of the process used for mining SSR markers. The SSR markers identified in this study could be used to select varieties with desired traits, and to investigate the genetic mechanism underlying anthocyanin accumulation in the pericarps of black rice. Furthermore, the findings from this study may prove beneficial in future genetic diversity studies, primer development, and selective breeding programs.

Sexually transmitted infections encompass considerable effects on human sexual and reproductive health. Its presence is ubiquitous despite decades of prevention and management. The present study has been conducted to provide an insightful bibliometric analysis of syphilis based on the Scopus repository. Therefore, given the dearth of a consolidated bibliometric analysis on Syphilis, this investigation aimed to compile the literature of the last century (1921-2021) to gain insight into the publications pertinent to the burden, diagnosis, treatment, and management of Syphilis. In this study, we have provided the year-wise, and subject-wise publications, type of articles, country, funding organizations, institutions, citations, and H-index. The data obtained from the Scopus database was exported to CSV file format and then converted to Microsoft Excel version for analysis to curtail the chances of error in the information. It has been evidenced that the USA possesses the highest track of proven publications. Therefore, this study considerably contributes to the future leaders, researchers & specialists/ clinicians of the domain

Image registration has an imperative role in medical imaging. In this work, a grey-wolf optimizer (GWO) based non-rigid demons registration is proposed to support the retinal image registration process. A comparative study of the proposed GWO-based demons registration framework with cuckoo search, firefly algorithm, and particle swarm optimization- based demons registration is conducted. In addition, a comparative analysis of different demons registration methods, such as Wang’s demons, Tang’s demons, and Thirion’s demons which are optimized using the proposed GWO is carried out. The results established the superiority of the GWO-based framework which achieved 0.9977 correlation, and fast processing compared to the use of the other optimization algorithms. Moreover, GWO-based Wang’s demons performed better accuracy compared to the Tang’s demons and Thirion’s demons framework. It also achieved the best less registration error of 8.36×10^-5.

Valorization of food and fruit wastes has the potential for the production of sustainable energy and biochemicals. Approximately 70% of the weight of the original jackfruit (Artocarpus heterophyllus L.) fruit is lost during processing as waste in the form of peeled skin and core, both of which have not been utilized and, thus contribute to disposal as well as pollution issues. The major components, cellulose, and hemicellulose, can be biologically transformed easily into bioenergy sources like ethanol, methanol, and butanol; valuable phenolics and biotechnological products like pectin, citric acid, bromelain, ferulic acid, and vanillin; and many other products. These residues can also be utilized as essential sources for the biological transformation process leading to the production of numerous products with added value, such as phenolic antioxidants, phenolic flavor compounds, and organic acids. Thus, the value addition of jackfruit waste can support the sustainable solution towards food and nutritional security. In this way, zero waste can be achieved through novel biorefineries which are critically highlighted in this paper. Furthermore, novel technologies for the conversion of jackfruit wastes are summarized with recent findings.

The Himalaya is well known for high diversity and ethnobotanical uses of medicinal plants. However, not all areas of the Himalayas are well studied. In particular, studies on ethnobotanical uses of plants from the Eastern Himalayas are rare and lacking for many tribes. Past studies primarily focused on listing plants name and their traditional medicinal uses. However, studies on traditional ethnopharmacological practices on medicine preparation had not yet been reported in published literature from the Eastern Himalaya. In this study, we are reporting the first time ethnopharmacological used 24 medicines, their procedures of preparation and listed 53 plant species used for those medicines for Monpa tribe. Such documentations had not yet been done for other tribes in India. Our research demonstrates the urgent need to documents traditional medicine preparation procedures from the local healers before rapid cultural modernization forgets them in transforming country like India. This study should motivate national and international researchers to do more works on ethnopharmacology and bioprospecting.

In this study, global response analysis was performed to explore the mechanism of action of Usnic acid and its synergy with Norfloxacin, a well-known quinolone antibiotic to which MRSA clinical isolates showed resistance (MIC, 500 µg/mL). Microdilution assay, growth kinetics, microscopic analysis, and cell-based assays consistently showed that Usnic acid possess strong anti-staphylococcal activity (MIC, 7.8 µg/ml), causes cell leakage, modulates efflux pump activity, and synergizes with Norfloxacin against multi-drug resistant clinical isolate MRSA 2071. Whole cell proteome profiling using gel-free based nano-LC-ESI-QTOF-MS/MS revealed several proteins whose expression was significantly modulated by Usnic acid and Norfloxacin alone or in combination. Usnic acid downregulated the abundance of RNA polymerase subunits (RpoB, RpoC), carbamoyl phosphate synthase large subunit (PyrAB), chaperone (GroEL), and adenylosuccinate synthetase (PurA). Interestingly, proteins found to be upregulated in the presence of Usnic acid and Norfloxacin included oxidative stress-related proteins such as peroxidase (Tpx), alkyl hydroperoxide reductase (AphC), and general stress protein (UspA). This study clearly showed that Usnic acid affects numerous cellular targets and can potentiate the action of Norfloxacin. Furthermore, an in-vivo study emphasized the use of Usnic acid to develop as a safe phytopharmaceutical to repurpose old antibiotics through combination therapy against MRSA infections.

The reinforcing ability of the fillers results in significant improvements in properties of polymer matrix at extremely low filler loadings compared to conventional fillers. In view of this, present review article describes the different methods used in preparation of different rubber nanocomposites reinforced with nanodimensional individual carbonaceous fillers, such as graphene, expanded graphite, single walled carbon nanotubes, multiwalled carbon nanotubes and graphite oxide, graphene oxide and hybrid fillers consisting combination of individual fillers. This is followed by review of mechanical properties (tensile strength, elongation at break, Young modulus, and fracture toughness) and dynamic mechanical properties (glass transition temperature, crystallization temperature, melting point) of these rubber nanocomposites. Finally, Payne and Mullin Effects have also been reviewed in rubber filled with different carbon based nanofillers.

Proprotein convertase subtilisin/Kexin type 9 (PCSK9) is a proteolytic enzyme that indirectly regulates serum LDL cholesterol by destroying LDL receptors. In clinical studies, the main role of the proprotein convertase subtilisin/Kexin type9 (PCSK9) inhibitor in cholesterol regulation was elucidated. It is produced in the liver but is also present in the kidney and intestine. It prevents HMGCo from synthesizing cholesterol. SREBP-2 is a reductase that is induced by statins. In a dose-dependent manner, increasing SREBP-2 levels enhanced LDL-R and PCSK9 gene expression. At the minimum, two procedures have been developed to overcome the plasma level of PCSK9. This is the LDLR test, polyclonal antibodies, and sentience oligonucleotide. Lower dosage statin treatment with a proprotein convertase subtilisin/Kexin type9 inhibitor will be most efficient in lowering LDL and avoiding statin adverse effects. In multiple long-term trials, statins have been found to reduce cardiovascular mortality by 30% and stroke incidence by 20%. In this way, we conclude the role of PCSK9 in hypercholesterolemia.

Endocytosis in mammalian cells is a fundamental cellular machinery that regulates vital physiological processes, such as the absorption of metabolites, release of neurotransmitters, hormonal secretion, cellular defense, and delivery of biomolecules across the plasma membrane. A remarkable characteristic of the endocytic machinery is the sequential assembly of the complex proteins at the plasma membrane followed by transportation of various cargo molecules to different cellular compartments. In all eukaryotic cells, functional characterization of endocytic pathways is based on dynamics of the protein complex modules. To coordinate the assembly and functions of the numerous parts of the endocytic machinery, the endocytic proteins interact significantly within and between the modules. Clathrin dependent and independent endocytosis, caveolar pathway and receptor mediated endocytosis have been attributed in a greater variety of physiological and pathophysiological roles such as, autophagy, metabolism, cell division, apoptosis, cellular defense, and intestinal permeabilization. Notably, any defect or alteration in the endocytic machinery results in the development of pathological consequences associated with human diseases such as cancer, cardiovascular diseases, neurological diseases, and inflammatory diseases. In this review, an in-depth endeavor has made to illustrate the process of endocytosis, and associated mechanisms describing pathological manifestation associated with dysregulated endocytosis machinery.

Laser-induced breakdown spectroscopy (LIBS) of pharmaceutical drugs that contain paracetamol is investigated in air and argon atmospheres. Characteristic neutral and ionic spectral lines of various elements and molecular signatures of CN violet and C₂ Swan band systems are observed. The relative hardness of all drug samples is measured as well. Principal component analysis, a multivariate method, is applied in data analysis for demarcation purposes of the drug samples. The CN violet and C₂ Swan spectral radiances are investigated for evaluation of possible correlation of the chemical and molecular structures of the pharmaceuticals. Complementary Raman and Fourier-transform-infra-red spectroscopies are used record molecular spectra of the drug samples. The applicationof the above techniques for the drug screening are important for identification and mitigation of drugs that reveal additives that may cause adverse side-effects.

Long COVID, characterized by persistent symptoms lasting from weeks to several months following initial infection with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), significantly impacts individuals' quality of life and poses a potential long-term burden on global healthcare systems. Clinical manifestations of Long COVID are diverse, affecting multiple systems including respiratory, cardiovascular, neurological, and gastrointestinal. While the precise mechanisms underlying Long COVID remain unclear, emerging evidence suggests involvement of various bodily pathways. This study employs bioinformatics tools to investigate the mechanisms of Long COVID and identify potential drug targets associated with key pathways, including inflammation, cytokines, immune response, coagulation, mitochondrial function, oxidative stress, and autonomic dysfunction. Tools such as the National Center for Biotechnology Information (NCBI) database, PubChem, UniProt, and iGEMDOCK were utilized for pathway analysis and molecular docking. The analysis aimed to identify drug molecules that may interact with target proteins to regulate or inhibit pathway activity, yielding several potential drug candidates for further investigation.

The enterprise software sector is experiencing a significant transformation driven by rapid technological progress and evolving business needs. An effective release management process is crucial for the solution providers and customers, as they incorporate the principles of Industry 4.0 and 5.0. With the growing dependence on software solutions and services, ensuring their quality, reliability, and security is highly necessary. The release management process incorporates strategic planning, regression testing, accurate deployment, and continuous monitoring of software updates. However, the rapid advancements in artificial intelligence (AI) and machine learning (ML) create a unique challenge to the release management process. The existing research needs to address the necessary adaptations for Industry 5.0, mainly in product-based software organizations, to the release management process without a change management system. After working with several software solution stakeholders, based on the responses from SaaS project stakeholders, we have presented a revised software release readiness workflow by incorporating a change management module. The preliminary result based on data over a limited period of time indicates that the revised workflow has the potential to improve the management of slippage, particularly by more effectively addressing NFR-related issues, thereby resulting in more predictable and reliable release cycles.

ABSTRACT Underwater mines may destroy friendly submarines and marine habitats, compromising nonmilitary security. Finding credible information is vital to avoiding scams and spotting hazards. This article employs Supervised Machine literacy models to appropriately categorize subsea items like mines or gems based on Sonar sounds. Python constructs three double classifier models using Gorman and Sejnowski (1988) training data. Through the extraction of key aspects from the Sonar signals, such as spectral components and intensity, the models are able to match newly obtained data with the gemstone order or mine. Delicacy decreases the chance of misidentifications in nonmilitary activities. Machine literacy offers full validation that accommodates real-world Sonar data noise and unpredictability. Based on test results, the highest performing algorithm will deliver the required ratio of accuracy to perceptivity for the bracket task. Central keywords: vaticination model, bracket algorithms, supervised machine literacy, SONAR, and aquatic mining emphasize particular foundations. Improved sophistication in spotting undersea Mines let nonmilitary defence systems respond to proven threats only, preventing friendly submarines or sea life from unnecessary damage owing to false duplicity. This work is a promising start to real-world mine detection devices. Further developments may incorporate greater training data sets, real-time testing on subsea platforms equipped with integrated sonar, and optimization for the discovery of new mine-types. Overall, machine learning and Sonar vision decrease signal fluctuation and noise, making it easier to determine accurate boundaries for non-military applications and environmental protection. The recommended automated discovery technique must balance computational efficiency, generalizability, and delicacy. Prior a real crime, new quality control and verification procedures could boost trust even further.

1) Landsat operational land imager (OLI) data and consequent laboratory measurements were used to predict Chlorophyll-a (Chl-a) concentration and the trophic states for an inland lake within the East Kolkata Wetland, India; 2) The most suitable band ratio was identified by performing Pearson correlation analysis between Chl-a concentrations and possible OLI band and band ratios from the study points; 3) The results showed highest correlation coefficient from the band ratio OLI5/OLI4 with an R value of 0.85. The prediction model was then developed by applying regression analysis between the band ratio OLI5/OLI4 and Chl-a concentration of the study points. The reflectance ratios of the validation points were given as input on the prediction model and the model output was considered as predicted Chl-a values of the validation points to check the efficiency of the prediction model. The regression model between laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points revealed a high correlation with an R² value of 0.78. Trophic State Index (TSI) of the lake was also calculated from laboratory-derived Chl-a value and model-fitted Chl-a value of the validation points. The study presented a high correlation of TSI determined from predicted data with TSI from laboratory reference data (R = 0.88). The TSI values of the lake ranged from 65 to 75 which indicate that the lake is appeared to be eutrophic to hypereutrophic conditions. 4) This empirical study showed that Landsat 8 OLI imagery can be effectively applied to estimate Chl-a levels and trophic states for inland lakes.

TaABCC13 is member of wheat ABCC subclass of transporters. The RNAi mediated silencing of this transporter in wheat results in lowering of seed phytic acid level and other developmental defects. In addition to that, wheat ABCC13 was involved in cadmium detoxification as evident by the complementation assays in yeast. The appearance of early lateral roots in these transgenic seedlings speculated the possibility for studying the role of localized auxin-mediated effects. In the current study, firstly, the expression of auxin related genes was studied in the transgenic roots. Enhanced expression of genes pertaining to either auxin biosynthesis or its transport was observed in transgenic wheat seedling roots suggesting the direct effect of the hormone. Further, the early emergence of lateral roots in transgenic wheat seedlings was affected due to the presence of auxin-transport inhibitor suggesting the direct effect of hormones in root development. In conclusion, herein we provide the novel evidence for the auxin mediated regulation of lateral root emergence in TaABCC13:RNAi seedlings.

Background: World Health Organization (WHO) declared that COVID-19 as a pandemic on March 11, 2020. There is sudden need of statistical modeling due to onset of COVID-19 pandemic across the world. But health planning and policy requirements the estimates of disease problem form clinical data. Objective: To predict recovery rate, cases load rate on the basis of cumulative confirmed Novel Corona virus (NCV) cases, recovered cases and deaths form COVID-19 in India. Methods: The reported COVID-19 cases in the country were obtained from website (https://datahub.io/core/covid-19#resource-covid-19_zip/). The cumulative NCV confirmed cases; recovery cases and deaths were used for estimating recovery rate, cases load rate and death rate till date 24 April 2020. Results: A total of 24530 NCV confirmed cases were reported nationwide in India on 24 April 2020. It is found that the recovery rate increased 22% and case load rate decreased 74%. Death rate is found to be very low 3%. The difference of cases load rate and recovery rate (delta) coincide at 50 % then NCV cases expected would be declined. Conclusion: The epidemic in the country was mainly caused by the importation of India. Lockdown as restricting the migration of population and decided to quarantine of population may greatly reduce the risk of continued spread of the epidemic in India. This study predicts that by 20 May 2020, the cases load rate lesser than recovery rate there after COVID-19 patients would be started to reducing.

Accumulation of extra fats in the body results in disturbance in homeostasis causing obesity. The pathophysiology of obesity has been associated with various genetic, epigenetic factors and the disturbed lifestyles of an individual. One of the outcomes is disturbance in the sleep cycle which leads to sleep disorders. The evolutionary significance of sleep lies in the fact that it saves energy and is crucial for adjustment of an individual to ecological and environmental factors, and thus maintains homeostasis. Sleep has an anabolic function and replenishes the wakefulness-associated loss of glycogen stores. However, the modern lifestyle is well known to disrupt sleep behavior and patterns affecting human health negatively. Alteration in homeostasis leads to several acute and chronic pathophysiological conditions like obesity and related metabolic morbidities being one amongst them. Shorter sleep duration and poor sleep quality are important risk factors associated with the development of obesity and have more adverse effects on energy homeostasis. Consequently, it is crucial to comprehend the obesity and sleep relationship and its therapeutic strategies, given that strong crosstalk exists between energy balance that favors obesity and sleep apnea. It is therefore highly recommended to the people with a high risk of obesity to maintain sleep discipline and good sleep hygiene in our daily life. Interventions are required to improve both sleep quality and quantity, and associated obesity. More focused research is needed for uncovering the pieces of evidence that determine whether such interventions can improve obesity-related health consequences. The present review discusses the important findings on the therapeutic and neuroendocrine mechanisms regulating sleep and obesity.

Bisphenols are widely used in the synthesis of polycarbonate plastics, epoxy resins and thermal paper, which are used in manufacturing items of daily use. Packaged foods and drinks are the main sources of exposure to bisphenols. These chemicals affect humans and animals by disrupting the estrogen, androgen, progesterone, thyroid, and aryl hydrocarbon receptor functions. Bisphenols exert numerous harmful effects because of their interaction with receptors, ROS formation, lipid peroxidation, mitochondrial dysfunction, and cell signal alterations. Both cohort and case-control studies have determined an association between bisphenol exposure and increased risk of cardiovascular diseases, neurological disorders, reproductive abnormalities, obesity, and diabetes. Prenatal exposure to bisphenol results in developmental disorders in animals. These chemicals also affect the immune cells and play a significant role in initiating the inflammatory response. Exposure to bisphenols exhibit age, gender, and dose-dependent effects. Even at low concentrations, bisphenols exert toxicity, and hence deserve a critical assessment for their uses. Since bisphenols have a global influence on human health, the need to discover the underlying pathways involved in all disease conditions is essential. Furthermore, it is important to promote the use of alternatives for bisphenols, thereby restricting their uses.

In a recent paper, we have shown how gravity and information can be related. The relation is based on the thermodynamic extension of the gravitational system under consideration using the holographic principle. Using this idea, we were able to derive the Gullstrand-Painlevé (GP) metric. In this short paper, we re-derive the GP metric using information. However, we now extend the spacetime to 5D with the fifth dimension being time, that is, the (3+1)D spacetime is now promoted to (3+1+1)D spacetime. We also comment on the possible Braneworld interpretation of this model.

Chronic hepatitis B (CHB) infection and the Hepatitis B virus X protein (HBx) are major risk factors associated with hepatocellular carcinoma (HCC). In CHB infection, HBx induces mitochondrial dysfunction, exhaustion and impaired function in hepatocytes. Restoring hepatocyte health along with reduction in virus replication could be an ideal treatment for CHB. Thiourea derivatives are well known for their antiviral property though their effect on mitochondrial and/ or hepatocyte health remains obscure. This study focus on the repurposing of thiourea derivatives (DSA-00, DSA-02, and DSA-09) on hepatocyte replenishment. HepG2.2.15 cells were treated with thiourea derivatives, alongside Entecavir (ETV). The proteomics analysis showed both DSA-00 and ETV were enriched with proteins associated with antiviral responses. In addition, DSA-00 additionally showed increase in proteins linked to mitochondrial response. Whereas DSA-02 exhibited association with innate immune system and citric acid cycle and DSA-09 displayed pathways similar to DSA-00 and ETV. Treated groups exhibited enhanced bio-energetic and antiviral response as compared to the untreated group. FACS analysis revealed the restoration of exhausted hepatocytes by thiourea derivatives through targeting mitochondria. Our findings suggest that thiourea derivatives hold potential as a novel therapeutic agent that seems to restore mitochondrial health along with anti-viral response in CHB.

The holographic principle states that the information about the volume of space is stored on its boundary. Assuming this holds, we can explain the aspects of gravity. The spacetime needs to be extended to 5D to explain gravity in this context. This naturally explains the four classical tests of gravity namely the gravitational redshift, the perihelion precession, the bending of light, and the gravitational time delay. We also show a novel way in which the universe expands in an accelerated manner at late times without the need for any form of dark energy.

This paper offers a novel geometric and visual approach to the renowned Four Color Map Theorem and K5 non-planarity problem while unveiling their profound connection to the "kissing number" problem in 2D. We represent planar graphs through circles and tangents, simplifying complex structures and shedding light on these classic problems. Our proofs by contradiction, rooted in the kissing number concept, reveal that both the Four Color Map Theorem and K5 non-planarity are fundamentally linked, as they pivot around the concept of coloring. This study bridges the realms of geometry and graph theory, providing fresh insights and emphasizing the significance of the kissing number problem in various fields.

The classical Einstein’s Field Equation has been derived previously by demanding that the Clausius relation dS = δQ/T holds. In this letter, we show that the semiclassical Einstein’s Field Equation can be recovered using the generalized entropy Sgen by using the non-equilibrium thermodynamics where the Clausius relation is replaced by the entropy balance relation dS = δQ/T +diS, where diS is some internal entropy. Moreover, since the quantum fields violate the classical focusing, we, therefore, have to use quantum focusing in this case. Using then Jacobson’s idea of thermodynamics of spacetime we recover the semiclassical equation of motion. We, therefore, in a sense also show the validity of the semiclassical approximation, a crucial approach for establishing a number of important ideas such as the Hawking effect.

Taro is an important root vegetable and has several medicinal and therapeutic properties. The two major therapeutic ingredients are flavonoids and triterpenoids, which are of prime importance. Additionally, the plant has antibacterial, antiparasitic, antiallergic, and anti-inflammatory properties. People often use it to treat a number of diseases by prescribing them as medications. Researchers from the pharmaceutical industry can thrive on C. esculenta by using whole-plant extracts. The identification of valuable terpenoids and therapeutics and their preparations are profusely dealt with in this article. Also, the new structural details of connective tissue are also studied as it helps researchers to investigate further uses of taro for humans, it is well known that xanthan can be obtained commercially as stabilizers, thickeners, binders, and more. It is essential to explore this plant for both medicinal and pharmaceutical properties.

Long COVID is the collective term used to describe the persistence of symptoms in individuals who have recovered from SARS-CoV-2 infection. Some people who have healed from COVID-19 continue to experience new or persistent symptoms that last for weeks or months. While Long COVID is becoming more widely recognized, its fundamental causes and effective therapies remain largely unclear. This study aims to explore the potential of phytochemical medications as a cutting-edge therapeutic strategy for treating Long COVID, also known as post-acute sequelae of SARS-CoV-2 infection (PASC).G protein-coupled receptors (GPCRs), which play a critical role in cell signaling, were the focus of this study. GPCRs are known to be involved in immunological and inflammatory responses and are considered potential targets for Long COVID therapy. The GPCRs examined included chemokine receptors, serotonin receptors, adrenergic receptors, and histamine receptors. The docking results demonstrated high binding affinity between phytochemical drug structures and these receptors for most drug-receptor combinations.The study consists of three main parts. First, data on receptors and drugs were retrieved from the Protein Data Bank (PDB) and PubChem, respectively. The receptors selected are those predicted to be linked to Long COVID. The structure of the drugs was converted from SDF to PDB format using OpenBabel from ChemInfo. Docking studies were performed to assess the binding affinity between the drugs (ligands) and their respective receptors (binding sites) using iGemDock v2.1.In conclusion, the findings of this study could have significant implications for the development of alternative therapies for Long COVID.

This study explores the synthesis and application of BODIPY-functionalized gold nanoparticles (AuNPs) for the sensitive detection of biothiols via an indicator displacement assay coupled with Surface-Enhanced Raman Scattering (SERS) techniques, alongside their efficacy for in vitro cancer cell imaging. Moreover, the assay allowed a visible colorimetric detection of biothiols under normal and ultraviolet light conditions. The BODIPY (boron-dipyrromethene) fluorophores were strategically conjugated to the surface of gold nanoparticles, forming a robust nanohybrid that leverages the plasmonic properties of AuNPs for enhanced spectroscopic sensitivity. The detection mechanism exploits the displacement of the BODIPY indicator upon interaction with biothiols, triggering a measurable change in fluorescence and SERS signals. This dual-mode sensing approach provides high selectivity and sensitivity for biothiol detection, with detection limits reaching nanomolar concentrations using fluorescence and femtomolar concentration for cysteine using SERS. Furthermore, the BODIPY-AuNP complexes demonstrated excellent biocompatibility and photostability, facilitating their use in fluorescence imaging of biothiol distribution within cellular environments and highlighting their potential for diagnostic and therapeutic applications in biomedical research.

In this study, we evaluated the antibacterial effect against Staphylococcus aureus and Salmonella Typhimurium in fried fish paste using floating electrode-dielectric barrier discharge (FE-DBD) plasma (1.1 kV, 43 kHz, N2 1.5 m/s, 1-60 min). In addition, quality evaluation (pH, VBN) of fried fish paste was conducted after FE-DBD plasma treatment. When FE-DBD plasma was treated for 1, 5, 10, 20, 30 and 60 min, S. aureus decreased by 0.16-1.13 log10 CFU/g, and S. Typhimurium decreased 0.25-1.13 log10 CFU/g. Both decreased &gt; log10 CFU/g at 60 min. The D-value was 58.92 and R2 was 0.97 for S. aureus using first-order kinetics, and the D-value was 43.60 and R2 was 0.97 for S. Typhimurium using the Weibull model. There was no significant difference in pH after FE-DBD plasma treatment (p &gt; 0.05). However, volatile basic nitrogen (VBN) significantly decreased as the treatment time increased (p &lt; 0.05), and it was the lowest at 60 min to 3.46. Therefore, FE-DBD plasma treatment could be considered as a technology for preserving the quality of processed foods.

The elevated environment temperature in summer plays adverse effects on bovine fertility. Antioxidant treatment may have positive impact to enhance oocyte competence could be possible strategy for alleviating the summer effects on bovine fertility. The present study was aimed to investigate the effects of exogenous melatonin treatment on oocyte development competence, blastocyst development rate, activity of antioxidant enzymes, expression profiles of development related genes and pregnancy rates in cattle during summer. The experiment was conducted in 44 non-lactating indigenous Sahiwal cattle divided into control and treatment group. Treatment group received (day 0) inj. Melatonin @ 18mg/50kg body weight while control group received inj. Corn oil, 4ml i.m. On day 4, all the cows were subjected to ovum pickup (OPU) to aspirate oocytes for in-vitro embryo production. Blood samples were used to determine lipid peroxidation (MDA) and antioxidant enzymes concentration (SOD, GSH), and also for plasma hormonal concentration analysis. The results revealed that blastocyst development rate (%) was higher in treatment group (p<0.05). Treatment group had increased (p<0.05) antioxidant enzymes (SOD and GSH), plasma melatonin and estradiol concentrations, and decreased (p<0.05) MDA concentrations than controls. The mRNA expression level of SOD2, HSPB1, BCL2, MT2 and STAR in oocytes, cumulus cells, COCs (immature and mature) and blastocyst were found to be higher, however, BAX was downregulated in melatonin-treated than control group. In conclusion, the results suggesting probable beneficial role of exogenous melatonin administration in reducing heat stress and enhancing blastocyst developmental competence in indigenous cattle.

Maize (Zea mays subsp. mays) is the staple food crop in the world. In this study, multi-layer perceptron (MLP), support vector machine (SVM), genetic algorithm-based multi-layer perceptron (MLP-GA), and genetic algorithm-based support vector machine (SVM-GA) hybrid artificial intelligence algorithms were used for the prediction of drought tolerance and stress tolerance indices in teosinte maize lines. Correspondingly, the gamma test technique was applied to determine efficient input and output vectors. The potential of developed models was evaluated based on statistical indices and graphical representation. Results of gamma test based on the least value of gamma and standard error indices show that day of anthesis (DOA), day of silking (DOS), yield index (YI), and gross yield per plant (GYP) information vector arrangements were determined as efficient information vector combination for drought-tolerant index (DTI) as well as the stress-tolerant index (STI). The results of MLP, SVM, MLP-GA, and SVM-GA algorithms were compared based on statistical indices and visual interpretation that have satisfactory for prediction of the drought-tolerant index and stress-tolerant index in maize crop. It has also seemed that genetic algorithm-based hybrid models (MLP-GA and SVM-GA) were found a better prediction of the drought-tolerant index and stress-tolerant index in maize crop. Similarly, the SVM-GA model has the highest potential to forecast the DTI and STI in maize crops as compared to MLP, SVM, MLP-GA models.

The metabolism of lipoproteins, which regulates the transit of the lipid to and from tissues, is crucial to maintaining cholesterol homeostasis. Cardiac remodeling is referred to as a set of molecular, cellular, and interstitial changes that, following injury, affect the size, shape, function, mass, and geometry of the heart. Acetyl coenzyme A (acetyl CoA), which can be made from glucose, amino acids, or fatty acids, is the precursor for the synthesis of cholesterol. In this article, authors explain concepts behind cardiac remodeling, its clinical ramifications, and the pathophysiological roles played by numerous various components, such as cell death, neurohormonal activation, oxidative stress, contractile proteins, energy metabolism, collagen, calcium transport, inflammation, and geometry. The levels of cholesterol are traditionally regulated by two biological mechanisms at the transcriptional stage. First, the SREBP transcription factor family regulates the transcription of crucial rate-limiting cholesterogenic and lipogenic proteins, which in turn limits cholesterol production. Immune cells become activated, differentiated, and divided, during an immune response with the objective of eradicating the danger signal. In addition to creating ATP, which is used as energy, this process relies on metabolic reprogramming of both catabolic and anabolic pathways to create metabolites that play a crucial role in regulating the response. Because of changes in signal transduction, malfunction of the sarcoplasmic reticulum and sarcolemma, impairment of calcium handling, increases in cardiac fibrosis, and progressive loss of cardiomyocytes, oxidative stress appears to be the primary mechanism that causes the transition from cardiac hypertrophy to heart failure. De novo cholesterol production, intestinal cholesterol absorption, and biliary cholesterol output are consequently crucial processes in cholesterol homeostasis. In the article's final section, the pharmacological management of cardiac remodeling is explored. The route of treatment is explained into different steps: including, promising, and potential strategies. This chapter offers a brief overview of the history of the study of cholesterol absorption as well as the different potential therapeutic targets.

The article discusses how tourism policy has changed since World War II, highlighting how the everchanging political and economic climate has shaped policies that were formerly centered on promoting inbound travel and tourist growth to becoming more inclusive and sustainable. Within that framework, the paper systematically examines the development of Indian tourism policy and thoroughly explores the implications of its most recent version. It concludes that modern tourism policies have evolved into comprehensive frameworks that structure the growth of the industry and make it more inclusive and sustainable. Nations such as India are well-suited to meet the demands of modern tourism and offer appropriate frameworks for sustainable and resilient tourist growth.

Climate-smart agriculture (CSA) is a new and emerging concept in climate discourse to address the issues of climate change impacts in agriculture. Few researchers and organizations have concentrated on CSA policies and practices in Nepal. This study aims to review and analyze the policies and practices in relation to CSA and define local level CSA indicators in the Central and Western Nepal. This study adopted the scoping review of climate policies and practices in Nepal and also utilized the household survey information particularly focusing on climate adaptation relating to agriculture. Through the scoping review, it is recognized that the number of climate policies in Nepal has specifically prioritized agriculture and food security as an important thematic area. Among those policies, National Adaptation Programme of Action (NAPA), National Framework for Local Adaptation Plan of Action (LAPA) and National Adaptation Plan (NAP) have specific sections on CSA practices, however, these policies/plans lack specific indicators. Different categories of CSA practices are common in Nepal, but many of these practices are popular as agricultural and environmental practices prior to the CSA concept and approach. The output indicators specific to CSA practices help the communities and policymakers to measure and monitor the progress of its implementation. Additional researches are required in this field to better understand the CSA concept, approaches, and mechanisms in the Nepalese context.

In this paper, an attempt has been made to analyze the effect of spool port/ groove geometry on the pressure drop and chamber pressures which effect the performance parameters of the flow distributor valve. The work mainly involves formulation of detailed mathematical model of the valve and compare them on the same platform. For mathematical modelling, Matlab has been used. The size of the orifices is considered same throughout the model for better comparison. Initially the construction and functioning of flow distributor valve along with working principles of hydrostatic motor (Rotary Piston) is shown. Next shown the analytical analysis of area change and pressure drops due to different geometry of the spool valve ports. After that the computational fluid dynamics (CFD) analysis has been shown. A complete mathematical model to describe such flow distributor valve is developed after having a comprehensive knowledge of orifice characteristics, flow interactions based on valve geometry. Equations of flow through different orifices (fixed and variable area) of the valve have been developed based on the relationships obtained earlier.

The master molecular regulators and mechanisms determining longevity and health span include nitric oxide (NO) and superoxide anion radicals (SOR). L-arginine, the NO synthase (NOS) substrate, can restore a healthy ratio between the dangerous SOR and the protective NO radical to promote healthy aging. Antioxidant supplementation orchestrates protection against oxidative stress and damage—L-arginine and antioxidants such as vitamin C increase NO production and bioavailability. Uncoupling of NO generation with the appearance of SOR can be induced by asymmetric dimethylarginine (ADMA). L-arginine can displace ADMA from the site of NO formation if sufficient amounts of the amino acid are available. Antioxidants such as ascorbic acids can scavenge SOR and increase the bioavailability of NO. The topics of this review are the complex interactions of antioxidant agents with L-arginine, which determine NO bioactivity and protection against age-related degeneration.

The master molecular regulators and mechanisms determining longevity and health span include nitric oxide (NO) and superoxide anion radicals (SOR). L-arginine, the NO synthase (NOS) substrate, can restore a healthy ratio between the dangerous SOR and the protective NO radical to promote healthy aging. Antioxidant supplementation orchestrates protection against oxidative stress and damage—L-arginine and antioxidants such as vitamin C increase NO production and bioavailability. Uncoupling of NO generation with the appearance of SOR can be induced by asymmetric dimethylarginine (ADMA). L-arginine can displace ADMA from the site of NO formation if sufficient amounts of the amino acid are available. Antioxidants such as ascorbic acids can scavenge SOR and increase the bioavailability of NO. The topics of this review are the complex interactions of antioxidant agents with L-arginine, which determine NO bioactivity and protection against age-related degeneration.

Solid waste management is a global issue that affects every individual living in the world directly or indirectly. Failing to manage the waste properly will cause harm on public health, our natural environment, and even our happiness and prosperity. When asked about the reason behind the failure of third time plastic ban in Bhutan, one of the Bhutanese said it’s because of the lack of cooperation from public to support the move of government. Clean Bhutan, a non-governmental organization (NGO) that aims Zero Waste Bhutan by 2030, has collected around 5,900 metric tons of waste from December 2014 to February 2018. This project will create some awareness regarding the management of waste at individual level when people come in contact with the family of the researcher. It also talks abot how waste management and biodiversity conservation can go side by side.

Conclusion: When applied to the air-abraded Filtek™ Bulk Fill Flowable Restorative composite surface, 10-MDP-containing adhesives perform better than 10-MDP-free adhesives. The binding strength was unaffected by the 10-MDP-containing adhesives' chemical makeup. The bond strength endurance of adhesives containing 10-MDP decreases with age. Keywords: keyword 1; keyword 2; keywords: low-viscosity bulk fill composite, universal adhesives, self-etch adhesive, 10-MDP, aging, bond strength.

The study, conducted at the Department of Medicine, Maulana Azad Medical College and associated Lok Nayak Hospital, aimed to investigate the prevalence of iron deficiency anaemia among anaemic overweight and obese individuals. Fifty participants were included after screening and consent, undergoing socio-demographic assessment, clinical evaluation, and laboratory investigations. Middle to old-aged individuals predominated (Mean ± SD: 54.54 ± 11.32 years), with females comprising 62%. All subjects were obese (mean BMI: 37.27 ± 5.71 kg/m²), with common comorbidities including hypertension (68%), diabetes (36%), and obstructive sleep apnea-hypopnea syndrome (32%). Nutritional deficiencies, particularly iron deficiency, were prevalent, affecting 62% of subjects, with 48% having iron deficiency alone. Anemia of chronic illness was observed in 38%. Laboratory parameters showed low hemoglobin (8.53 ± 1.23 g/dL), MCV (78.75 ± 10.13 fL), and elevated ESR (20.56 ± 21.47 mm/hour) and CRP levels (4.71 ± 3.32 mg/dL), indicating inflammation. Correlation analyses revealed negative associations between BMI and serum iron/ferritin and positive associations with serum hepcidin. The study underscores the significance of addressing nutritional deficiencies and monitoring iron status in obese populations, suggesting potential associations between obesity and iron metabolism. Further research is needed to explore these relationships for clinical management implications.

Both Stevens Johnson Syndrome (SJS) and toxic epidermal necrolysis (TEN) are main injurious cutaneous medication reactions that mostly affect the epidermis and mucus membranes. TEN and SJS affecting nearly 1 or 2/1,000,000 people per year, and can recognized as medical crises since they may be deadly. Mucocutaneous discomfort, hemorrhagic erosions, erythema, and more or less severe epidermal separation that appear as ulcer and patches of dermic loss are their defining characteristics. The sole difference between TEN and SJS at this time is the degree of skin detachment, making them two extremes of a spectrum of severe cutaneous adverse drug reactions (cADRs). In the majority of cases, drugs are considered as the principal reason of SJS/TEN, but herpes simplex virus and Mycoplasma pneumoniae infections are also recognized causes, along with lesser number of cases in which the cause is still unknown. Among the drugs with a "high" likelihood of producing TEN/SJS are carbamazepine (CBZ), trimethoprim-sulfamethoxazole, phenytoin, aminopenicillins, allopurinol, cephalosporins, other sulfonamide antibiotics, quinolones, phenobarbital, and NSAIDs of the oxicam variety. There is strong genetic evidence for SJS and TEN in Han Chinese due to the substantial association between the human leukocyte antigen (HLA-B*1502) and SJS brought on by CBZ. The diagnosis is made mostly based on clinical symptoms and the histological study of a dermal biopsy. Pemphigus vulgaris, bullous pemphigoid, linear IgA dermatosis, paraneoplastic pemphigus, disseminated fixed bullous drug eruption, acute generalized exanthematous pustulosis (AGEP), and staphylococcal scalded skin syndrome (SSSS) are among the differential diagnoses. The management of patients with SJS/TEN is complicated by the high risk of mortality, necessitating early diagnosis, estimation of the SCORTEN prognosis, identification and discontinuation of the causative drug, specialized supportive care, and high-dose injectable Ig therapeutic interventions. The reported fatality rates for SJS are 1-5% on average and 25-35% for TEN; it can be even higher in patients who are elderly or who have a significant amount of epidermal detachment on their skin. More than 50% of TEN patients who survive the disease experience long-term consequences.

Ruminants perhaps appeared about 50 million years ago (Ma). Five ruminant families had been extinct and about 200 species in 6 ruminant families are living today. The first ruminant family probably was small omnivore without functional ruminal microbiota to digest fiber. Subsequently, other ruminant families evolved around 18-23 Ma along with woodlands and grasslands. Probably, ruminants started to consume selective and highly nutritious plant leaves and grasses similar to concentrates. By 5-11 Ma, grasslands expanded and some ruminants used more grass in their diets with comparatively low nutritive values and high fibers. Historically, humans have domesticated 9 ruminant species that are mostly utilizer of low quality forages for human benefits. Thus, the non-functional rumen microbiota to predominantly concentrate fermenting microbiota, followed by predominantly fiber digesting microbiota had evolved for mutual complementary benefits of holobiont over the million years. The core microbiome of ruminant species seems the resultant of hologenome interaction in an evolutionary unit. The inertia and resilience properties of ruminal ecosystem seem to be due to this core microbiota, which makes the ecosystem most stable in response to perturbations because this core microbiota has evolutionary advantages with logically more generalists (i.e., wide metabolic versatile and redundancy). Also, a part of the ruminal microbiome shows highly plasticity, which is likely useful for evolutionary adaptability of holobiont. This review discusses ecological characteristics of ruminal microbial community in evolutionary perspectives. The updated understanding of ecological traits of ruminal microbiome would be helpful to better modulate the ruminal fermentation favorably for human benefits.

Sustainable Development Goals (SDGs) envisaged under Agenda 2030 are a set of seventeen goals which envisage a holistic approach towards attaining certain targets keeping humankind and the planet at center. There are total 169 targets spread across seventeen goals covering wide ranging issues and challenges the world is facing in the twenty-first century. And they are to be achieved by 2030. Concerted efforts of all the stakeholders ranging from indigenous communities, common citizens, scientists, policy makers, world leaders are needed to achieve all the goals and targets Of the seventeen goals, at least seven goals are of interest to the ethnobotanists and are associated with traditional ethnobotanical knowledge. Therefore to achieve those set of goals, a thorough understanding is required to disentangle the intricacies involving traditional ethnobotanical knowledge, indigenous people as traditional knowledge holders and their future role. Understanding relationships between traditional ethnobotanical knowledge and indigenous communities, seeking cooperation from and establishing partnerships with them would help us design policies to achieve intended outcomes of SDGs. In this paper, particular attention is attracted towards the potential role of traditional ethnobotanical knowledge in achieving select sustainable development goals and targets.

Trash mulches are very effective in preventing soil erosion; reduce sediment transport rate, runoff rate and increasing infiltration. The study was carried out with the objectives to observe the sediment outflow from sugar cane leaf (trash) mulch treatments at selected land slopes under simulated rainfall conditions by using rainfall simulator of size 10 m × 1.2 m × 0.5 m with the locally available soil material collected from Pantnagar. In the present study, trash mulches with different quantities were selected to observe the effect of mulching in soil loss reduction. The quantity of mulch was taken as, 6 t/ha, 8 t/ha and 10 t/ha, three rainfall intensities viz. 11cm/h, 13cm/h and 14.65cm/h at 0%, 2% and 4% land slopes were selected. The duration of rainfall was fixed (10 minutes) for every mulch treatment. The total runoff volume was found to be varying with different mulch rates for particular rainfall input and land slope. The runoff distribution pattern was observed to be increasing with the increase in land slope. The average sediment concentration (SC) and outflow was found to be increasing with the increasing land slope, but SC and outflow decreased with increasing mulch rate for particular land slope and rainfall intensity. The SOR (SOR) for no mulch treated land was higher as compared to trash mulch treated lands. Mathematical relationships were developed for relating SOR, SC, land slope and rainfall intensity for a particular mulch treatment. It was observed that values of SOR and average SC had a good correlation with rainfall intensity and land slope for each mulch treatment. The correlation coefficients of developed models were found to be more than 90%.

The low water solubility of any pharmacoactive molecules limits their pharmacological potential but the solubility parameter cannot compromise, so different approaches are employed to enhance their bioavailability. Pharmaceutically active molecules with low solubility convey a higher risk of failure for drug innovation and development. Pharmacokinetics, pharmacodynamics, and several other parameters, such as drug distribution, protein binding and absorption, are majorly affected by their solubility. Among all pharmaceutical dosage forms, the oral dosage forms cover more than 50 %, and the drug molecule should be water-soluble. For good therapeutic activity by the drug molecule on the target site, solubility and bioavailability are crucial factors. The pharmaceutical industry screening programs identified that around 40% of new chemical entities (N.C.E.s) face various difficulties at the formulation and development step. These pharmaceuticals are attributed to their less solubility and bioavailability. The bioavailability and drug solubility enhancement are significant challenges in the area of pharmaceutical formulations. According to the Classification of Biopharmaceutics, Class II and IV drugs (APIs) exhibits poor solubility, lower bioavailability, and less dissolution. Various technologies are discussed in this article to improve the solubility of the poorly water-soluble drug, for example, complexation of active molecules, utilization of emulsion formation, micelles, microemulsions, cosolvents, polymeric micelles preparation, particle size reduction technologies, pharmaceutical salts, prodrugs, solid-state alternation technique, soft gel technology, drug nanocrystals, solid dispersion methods, crystal engineering techniques and nanomorph technology. This review mainly describes several other advanced methodologies for solubility and bioavailability enhancement, such as crystal engineering, micronization, solid dispersions, nano sizing, use of cyclodextrins, solid lipid nanoparticles, colloidal drug delivery systems and drug conjugates, by some appropriate research reports.

This paper mainly focuses on the construction of a household welfare index to examine the welfare impact of international remittances in rural Bangladesh. This paper, in achieving this objective, uses primary data and several methods. This paper constructs a household welfare index newly to measure the level of household welfare. Besides, a linear regression and Chi-square test is used to examine the welfare and poverty impact of international remittances, respectively. Remittance receiving households enjoy the higher level of welfare more than non-recipient households in the study area. Household welfare is augmented by 0.116 if the household is under the shade of international remittances. A significant impact of international remittances on the reduction of household poverty is also found in this study. Therefore, this paper suggests policymakers for utilizing international remittances as a significant tool to enhance household welfare and to reduce household poverty.

Sorghum is a multipurpose crop, but Cr(VI) toxicity influenced the production of the crop and have established highlighted courtesy, due to robust toxicity and a comparatively less known mode of action. Many reports approve the negative impact of Cr(VI) on plants. Yet, it is not clear that, at what concentrations, Cr(VI) inhibits the growth and nutrient quality of Sorghum. In the present research, toxic effects appeared after 1ppm of Cr treatment. The plant growth decreased 15 – 20% and nutritional quality decreased 30 – 40% significantly with increasing concentration of Cr(VI). Toxic components increased 14 – 16% with increasing concentration of Cr(VI) in both the varieties (HJ 541 and SSG 59-3). Chromium was accumulated more in roots followed by shoots with increasing Cr(VI) treatments (0-4 ppm). Chromium at 4ppm level was becoming lethal to Sorghum. Sorghum cultivar SSG 59-3 was more tolerable to Cr toxicity than HJ 541. Chromium accumulated in Sorghum and increased HCN content and at higher doses adversely affects the nutritive values and growth making it toxic for animal consumption. These findings may be useful for scheming a mitigation strategy for chromium toxicity.

The recent outbreak of the new virus in Wuhan city, China from the sea food market has led to the identification of a new strain called the corona virus and named as novel corona virus (2019-nCoV) belonging to Coronaviridae family. This has created major havoc and concern due to the mortality of 250 persons and affecting more than 10,000 people. This virus causes sudden fever, pneumonia and also kidney failure. In this study a computational approach is proposed for drug and vaccine design. The spike protein sequences were collected from a protein database and analysed with various bioinformatics tools to identify suitable natural inhibitors for the N-terminal receptor binding domain of spike protein. Also, it is attempted to identify suitable vaccine candidates by identifying B-Cell and T-cell epitopes. In the drug design, the tanshinone Iia and methyl Tanshinonate were identified as natural inhibitors based on the docking score. In the vaccine design, B-cell epitope VLLPLVSSQCVNLTTRTQLPPAYTN was found to have the highest antigenicity. FVFLVLLPL of MHC class-I allele and FVFLVLLPL of MHC class-II allele were identified as best peptides based on a number of alleles and antigencity scores. The present study identifies natural inhibitors and putative antigenic epitopes which may be useful as effective drug and vaccine candidates for the eradication of novel corona virus.

This work presents datasets that can be used for getting a good understanding of an essential geoscience content knowledge that describe earth’s coordinate systems. This include coordinate system used for spherical/spheroidal earth with latitudes and longitudes and their subsequent transformations to 2d maps on a variety of media (paper as well as digital) using the process of map projections. The datasets include PDF documents that are embedded with 3d models, animations and mathematical equations. The dataset has separate PDF documents for geographic (for spherical earth) and projected (2d) coordinate systems. Additionally, the data set include individual 3d models that can be used in various digital systems (including apps) and the animations in mp4 format that can be watched on most of the modern digital devices.

To understand the physiological basis of tolerance to combined stresses to low phosphorus (P) and drought in mungbean (Vigna radiata (L.) R. Wilczek), a core set of 100 accessions were evaluated in hydroponics at sufficient (250 μM) and low (3 μM) P, and exposed to drought (dehydration) stress. The principal component analysis and ranking of accessions based on relative values revealed that IC280489, EC397142, IC76415, IC333090, IC507340 and IC121316 performed superior while IC119005, IC73401, IC488526 and IC325853 performed poorly in all treatments. Selected accessions were evaluated in soil under control (sufficient P, irrigated), low P (without P, irrigated), drought (sufficient P, withholding irrigation) and combined stress (low P, withholding irrigation). Under combined stress, a significant reduction in gas exchange traits (photosynthesis, stomatal conductance, transpiration, instantaneous water use efficiency), P uptake in seed and shoot was observed under combined stress as compared to individual stresses. Among accessions, IC488526 was most sensitive while IC333090 and IC507340 exhibited tolerance to individual or combined stress. The water balance and low P adaptation traits like membrane stability index, relative water content, specific leaf weight, organic acid exudation, biomass, grain yield and P uptake can be used as physiological markers to evaluate for agronomic performance. Accessions with considerable resilience to low P and drought stress can be either used as ‘donors’ in Vigna breeding program or cultivated in areas with limited P and water availability or both.