The present novel corona virus (2019-nCoV) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. The infection induced death rate is also very high. There is no vaccine or anti-viral medicine for such infection. So at this moment a major worldwide problem is that how we can control this pandemic. On the other hand, India is a high population density country, where the corona virus disease (COVID-19) has started to spread from $1^{st}$ week of March, 2020 in a significant number of COVID-19 positive cases. Due to this high population density human to human social contact rate is very high in India. So control of the pandemic COVID-19 in early stage is very urgent and challenging problem. Mathematical models are employed in this paper to study the COVID-19 dynamics, to identify the influential parameters and to find the proper prevention strategies to reduce the outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the key model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impacts on the disease dynamics have also been studied. Future trends of the disease transmission has been Predicted from our model with some control measures. Finally, the positive measures to control the disease have been summarized.

Spin dependent quantum transport properties in twisted carbon nanotube and stretched carbon nanotube are calculated using density functional theory (DFT) and non-equilibrium green’s function (NEGF) formulation. Twisting and stretching have no effect on spin transport in CNTs at low bias voltages. However, at high bias voltages the effects are significant. Stretching restricts any spin-up current in antiparallel configuration (APC) which results in higher magneto resistance (MR). Twisting allows spin-up current almost equivalent to the pristine CNT case resulting in lower MR. High spin filtration is observed in PC and APC for pristine, stretched and twisted structures at all applied voltages. In APC, at low voltages spin filtration in stretched CNT is higher than in pristine and twisted ones with pristine giving higher spin filtration than twisted CNT.

The main purpose of this research is to analyze the perception of climate change impacts on human health in Bangladesh through data from nationality representative surveys conducted in some district of Bangladesh. In Bangladesh there have a few research has been conducted on public perceptions about the impact of climate change on human health. A structured questionnaire method was conducted, and data collected from 615 respondents. The findings of this study reveal that out of 615 respondents, 76.0% of the respondents replied positively while remaining 24.0%, almost one-fourth of total respondents, indicated that they have not heard the term climate change before. Knowledgeable in climate change, 92.5% of respondents agreed that climate change has an impact on human health while only 7.5% respondents disagreed with this statement. 90.5% of respondents argued that they are agreed with the opinion that climate change is a serious threat to human health.

Lily database online genomic resource composed of Korean Lily Germplasm Collection, Transcriptome Sequences, molecular markers, transcription factors (TF) and DEGs data. A total of ~0.23 gb of RNA-sequences data were mined for gene identification, marker development and gene expression analysis. As a result, 47,863 SSR, 20,929 SNP and 1213 COS-marker were developed. A total of 1327 TF genes were identified and characterized. This is the first unique, user-friendly, genomic resource database for Lilium species. It is a relational database based on a ‘three-tier architecture’ that catalogs all the information in MySQL table and a user-friendly query interface and data visualization page developed using JavaScript, PHP and HTML code. The search parameters are highly flexible, user can be retrieved data by using either single or multiple search parameters. Data present in this database can be used for germplasm characterization, gene discovery, population structure analysis, QTL mapping and accelerating the lily variety improvements. This database can be accessed through this link: http://www.genomicsres.org/lilidb/.

The detection of coronavirus (COVID-19) is now a critical task for the medical practitioner. The coronavirus spread so quickly between people and approaches 100,000 people worldwide. In this consequence, it is very much essential to identify the infected people so that prevention of spread can be taken. In this paper, the deep feature plus support vector machine (SVM) based methodology is suggested for detection of coronavirus infected patient using X-ray images. For classification, SVM is used instead of deep learning based classifier, as the later one need a large dataset for training and validation. The deep features from the fully connected layer of CNN model are extracted and fed to SVM for classification purpose. The SVM classifies the corona affected X-ray images from others. The methodology consists of three categories of Xray images, i.e., COVID-19, pneumonia and normal. The method is beneficial for the medical practitioner to classify among the COVID-19 patient, pneumonia patient and healthy people. SVM is evaluated for detection of COVID-19 using the deep features of different 13 number of CNN models. The SVM produced the best results using the deep feature of ResNet50. The classification model, i.e. ResNet50 plus SVM achieved accuracy, sensitivity, FPR and F1 score of 95.33%,95.33%,2.33% and 95.34% respectively for detection of COVID-19 (ignoring SARS, MERS and ARDS). Again, the highest accuracy achieved by ResNet50 plus SVM is 98.66%. The result is based on the Xray images available in the repository of GitHub and Kaggle. As the data set is in hundreds, the classification based on SVM is more robust compared to the transfer learning approach. Also, a comparison analysis of other traditional classification method is carried out. The traditional methods are local binary patterns (LBP) plus SVM, histogram of oriented gradients (HOG) plus SVM and Gray Level Co-occurrence Matrix (GLCM) plus SVM. In traditional image classification method, LBP plus SVM achieved 93.4% of accuracy.

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.

Molecular markers, including Simple Sequence Repeat (SSR), Single Nucleotide Polymorphism (SNP), and Intron Length Polymorphism (ILP), are widely utilized in crop improvement and population genetics studies. However, these marker resources remain insufficient for Musa species. In this study, we developed genome-wide SSR, SNP, and ILP markers from Musa and its sister species, creating a comprehensive molecular marker repository for the improvement of Musa species. This database contains 2115474 SSR, 63588 SNP, and 91547 ILP markers developed from thirteen Musa species and two of its relative species. We found that 77% of the SSR loci are suitable for marker development; 38% of SNP markers originated from the genic region, and transition mutations (C↔T; A↔G) were more frequent than transversion. The database is freely accessible and follows a ‘three-tier architecture,’ organizing marker information in MySQL tables. It has a user-friendly interface, written in JavaScript, PHP, and HTML code. Users can employ flexible search parameters, including marker location in the chromosome, transferability, polymorphism, and functional annotation, among others. These distinctive features distinguish the Musa Marker Database (MMdb) from existing marker databases by offering a novel approach that is tailored to the precise needs of the Musa research community. Despite being an in silico method, searching for markers based on various attributes holds promise for Musa research. These markers serve various purposes, including germplasm characterization, gene discovery, population structure analysis, and QTL mapping.

The global focus on geopolymer binder production has increased due to the adoption of waste materials and industrial byproducts. Given the gradual decline of the availability of fly ash and ground granular blast furnace slag (GGBFS) resulting from the decarbonization process in electricity and steel productions, waste clay brick powder (WCBP), could be a viable substitute of these pozzolanic by-products. This research is dedicated to thoroughly investigate the techno-eco-efficiency performance of WCBP when utilized as a geopolymer precursor. The favorable mechanical characteristics exhibited by fly ash-GGBFS-WCBP-based geopolymer binder emphasize the importance of assessing its sustainability alongside its technical viability. The study employed life cycle analysis (LCA), following ISO 14040-44 standards, and using the Simapro software, to evaluate the environmental implications of the use of WCBP-based geopolymer mixtures. Human toxicity emerged as the primary impact. Moreover, the analysis of life cycle costs highlighted key financial factors, with around 65-70% attributed to alkaline activators of the total cost. The production of alkaline activators was identified as a critical point for both environmental impact and economic considerations due to energy consumption. While WCBP-rich samples exhibit a 1.7-0.7% higher environmental impact compared to the control mix (CM), their high mechanical strength and cost-effectiveness make them technologically and economically efficient geopolymer mixes. In conclusion, the portfolio analysis for techno-eco-efficiency affirms that mixes containing 40%, 30%, and 20% WCBP are more efficient than those using 10% and 0% WCBP, respectively.

After a long waited span, the whole world could see the ray of covid-19 vaccine to resist the planet to watch the death procession. But some country people especially the people of Bangladesh keep them aside to take the vaccination. This study aims to understand the perception towards the COVID-19 vaccination program in Bangladesh and the targeted subject is the university student as they are suffering highly depression nowadays. Higher education has been affected globally as a result of the COVID-19 pandemic in 223 countries. Moreover, for this pandemic situation, the university students can not complete their graduation which binds them to enter their professional career. Alike all of the developed countries, as well as developing countries, Bangladesh, also considered vaccination as an effective measure to protect the peoples from the Covid-19 virus. This study targeted three psychological factors of the university students and surveyed 322 students from the different universities in Bangladesh to understand their perception regarding vaccines. Moreover, it is seen that most of the students doubt the effectiveness of the vaccine which interrupts them from taking the vaccine willingly.

Stock market prediction is a challenging task to perform, as we know the fluctuations that take place in the market makes it versatile and hard to predict the prices. In this research, we have explored the power of usage of hybrid ensemble algorithms to improve the predictive accuracy in the stock market forecasting. Our research comprises construction and evaluation of diverse hybrid models using different algorithms. The methodology presented in the paper involves comprehensive data preparation, feature engineering, and model normalization. Evaluating the different hybrid models, one stands out distinctly: LSTM (long short-term memory networks) + GRU (Gated recurrent units) + Conv1D (one-dimensional convolutional layer) hybrid. It illustrated its potential to revolutionize decision-making tools for investors and financial analysts in stock market analytics. The harmonious integration of algorithms not only underscores the effectiveness of hybrid modeling but also beckons for further exploration within the ever-evolving domain of predictive modeling, driven by the pursuit of precision and accuracy. This model shows a remarkable accuracy metrics including a Mean Absolute Error (MAE) of 0.95, a Mean Squared Error (MSE) of 2.1222, a Root Mean Squared Error (RMSE) of 1.52, and a R-squared (R2) score of 0.9982.

— Big Data analytics has come a long way since its inception. This field is growing day by day. With the advent of large handling capacity of computational analysis of modern computing systems as well as Internet of Things (IoT), this field has revolutionized the way we think about data. It has influenced the major domains such as healthcare, automobile, computing, climatology, and space communications. Of late, the health care sector has been largely influenced by this. This communication deals with the areas of healthcare where big data analytics has been largely influential. Encompassing the basics of Big Data Analytics (BDA) driven by IoT, the applications of it in healthcare sector are outlined, accompanied by future expectations. Additionally, it also presents a comprehensive analysis of recent application with special reference to Covid-19 in this sector.

Begomovirus infection in plant causes a great economic loss in many countries every year. Increasing rate of the infectivity of this single stranded DNA virus forces to study of its transmission in detail for the necessary researches regarding the control of this disease. This pathogenic virus is whitefly vector borne and transferred from one plant to another plant during the suckling of phloem sap by that vector. Viral transmissibility through this insect vector may depend on the genetic variations within the cryptic species groups. Two distinct categories of begomoviruses viz., bipartite and monopartite types consist of different genome organization. Virion particles modify the intracellular environment of the host according to their need of replication and survival. Viral replication takes place through RCR as well as RDR methods. Interplay among host, vector and pathogen is crucial for the establishment of infection. Several endosymbiotic organisms living within the insect vector also have vital role here. Being infected with this virus, host plant responds with defensive activities like TGS, PTGS, autophagy, hormonal regulation, metabolic alteration etc. However, virus also counteracts those through the manipulation of several pathways of cellular events. It is necessary to study in different directions and utilize advanced molecular biological techniques to develop begomovirus resistance within plants.

Zephyranthes citrina Baker is a bulbous herb, commonly known as yellow rain lily belongs to the family Amaryllidaceae. It is a native of tropical and subtropical America but nowadays it is cultivated as a popular ornamental herb in several parts of the world including India. This herb represents one of the richest sources of phytochemicals, especially alkaloids and possesses great potential for pharmaceutical applications. It shows remarkable antiprotozoal, antimicrobial, anti-Alzheimer, cytotoxic, antioxidant, anti-inflammatory, analgesic, and dye removal activities. This review is an effort to give a detailed study of the literature on the biological activities of Zephyranthes citrina. This review concludes that Zephyranthes citrina has a great potential to treat various diseases and could be used as a source for novel healthcare products in the near future, which requires further experimentation.

Global severity maps of ongoing dengue epidemic and COVID-19 pandemic do not overlap. Countries with high dengue endemicity (>1.5 million cases/year) are observably less hit by COVID-19 in terms of infection, transmission and mortality. Based on non-overlap of dengue and COVID-19 severity maps and evidence of SARS-CoV-2 serological cross-reactions with dengue, we wonder whether immediate immunization of susceptible populations in Europe, North America and Asia (China, Iran) with available live-attenuated dengue vaccines, will cue the anti-viral immune response to thwart COVID-19 (viral interference). Risk of developing post-vaccination “Antibody-dependent Enhancement” is low as dengue is not endemic in the aforesaid regions.

Consumption is thus fundamentally related to sustainably because every decision pertaining to what to buy, what quantity the buy, how many to consume, or how to dispose of things has a direct influence on the natural world and the generations to come, and the overall impact of every single the customer's purchase is disastrous. A framework-based systematic literature review (SLR) was conducted to better comprehend the body of research on digital innovation and sustainability driving consumer behavior. This was done in order to acquire a deeper understanding of the studies that have already been done in this area. to provide (i) a comprehensive review of the current research landscape and (ii) a rich roadmap for future research. This study evaluated the literature especially in terms of theory, context, traits, and methodology. A total of 107 research articles published between 2013 and 2022 were found using scientific methods in the Scopus database. The findings showed that most research appears to have employed qualitative methodologies and was grounded in the setting of China and Italy. This review could help scholars better grasp the relationship between digital innovation and sustainability, opening the door for additional study and advancement in the field. Additionally, by extending the literature study and emphasizing the elements that can improve digital innovation and sustainability, practitioners will be given a better overall understanding of how to approach the problem.

The Internet of Vehicles (IoV) is an emerging field that has attracted significant attention due to its potential to transform transportation and mobility. IoV enables the development of new services and applications that can improve transportation systems' efficiency, safety, and sustainability. However, ensuring secure and trustworthy communication among the different components of an IoV system is a critical challenge that needs to be addressed. This paper proposes a blockchain-enabled communication framework for secure and trustworthy IoV applications. The proposed framework leverages the security and decentralization features of blockchain technology to provide secure communication channels for different components of the IoV system, including vehicles, infrastructure, and service providers. The proposed framework provides an identity management system to authenticate and authorize users and devices, thereby preventing unauthorized access and data breaches. To evaluate the effectiveness of the proposed framework, we conducted experiments using a real-world IoV scenario, and the results demonstrate that the proposed framework can provide secure and trustworthy communication for IoV applications. The proposed blockchain-enabled communication framework offers a promising approach to address the security and trust challenges in IoV communication systems.

Strip-mined land (SML) disturbed by coal-mining is the non-crop land resource that can be utilized to cultivate high-yielding energy crops such as miscanthus for bioenergy applications. However, the biomass yield potential, annual availability and environmental impacts on growing energy crops in SML are less understood. In this study, we estimated the yield potential of miscanthus (Miscanthus sinensis) in SML and its environmental impacts on local streams using the Soil and Water Assessment Tool (SWAT). After calibration and validation of the SWAT model, the results demonstrated that miscanthus yield potentials were 2.6 (0.8−5.53), 10.0 (1.3−16.0) and 16.0 (1.34−26.0) Mg ha^-1 with the fertilizer application rate of 0, 100, and 200 kg-N ha^-1 respectively. Furthermore, cultivation of miscanthus in the SML has the potential to reduce sediment (~20%) and nitrate (2.5%−10.0 %) loads reaching to water streams with a marginal increase in phosphorus load. The available SML in the United States could produce about 10 to 16 dry Tg of biomass per year without negatively impacting the water quality. In conclusion, SML can provide a unique opportunity to produce biomass for bioenergy applications, while improving stream water quality in highly dense mining area (the Appalachian region) in the United States.

The severity of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), greatly varies from patient to patient. In the present study, we explored and compared mutation profiles of SARS-CoV-2 isolated from mildly affected and severely affected COVID-19 patients in order to explore any relationship between mutation profile and disease severity. Genomic sequences of SARS-CoV-2 were downloaded from GISAID database. With the help of Genome Detective Coronavirus Typing Tool, genomic sequences were aligned with the Wuhan seafood market pneumonia virus reference sequence and all the mutations were identified. Distribution of mutant variants was then compared between mildly and severely affected groups. Among the numerous mutations detected, 14,408C>T and 23,403A>G mutations resulting in RNA-dependent RNA polymerase (RdRp) P323L and spike protein D614G mutations, respectively, were found predominantly in severely affected group (>82%) compared with mildly affected group (<46%, p<0.001). The 241C>T mutation in the non-coding region of the genome was also found predominantly in severely affected group. The 3,037C>T, a silent mutation, also appeared in relatively high frequency in severely affected group. We concluded that RdRp P323L and spike protein D614G mutations predominate in severely affected COVID-19 patients. Further studies will be required to explore whether these mutations have any impact on the severity of COVID-19.

The cartographic cum site-effectuated view of Shillong region of northeast India is presented here. Starting from the existing tectonics, the prevalent geological settings of the study area is comprehensively delineated. The seismic prone area is further overviewed in the context of site effects with accompaniment of available borehole information. The resonance frequency estimates form ambient noise survey along with receiver functions are outlined which implicates a heterogeneous subsurface. This further helps in segregating the region into two compelling profiles, thereby enabling us to get a deeper insight in the probable subsurface as well as heterogeneity. Eventually, the influence of topography over strata was also highlighted and interpreted as well.

There is a lot of discussion underway with conflicting opinions examining the airborne nature of the SARS-CoV2 virus. Surprisingly, important phenomena prevalent with respect to aerosols (suspended droplets) have not been considered. In this Technical Note, we propose a methodology for the coupling of aerosol phenomena (such as evaporation, particle transport accounting for drag) to accurately establish the lifetimes of the droplets. A characteristic time analysis illustrates the time scales for evaporation and settling: for example, the characteristic time for evaporation of a 10 µm droplet is 0.036 s at a relative humidity of 25%; compared to a settling time of about 500 s. For any particle smaller than ~ 100 µm, the evaporation of the emitted or exhaled droplet has to be considered. Coupling evaporation of the droplet as it settles, we estimate the horizontal distance traversed. Trajectories of a 10 µm and 100 µm particle emitted with a typical initial velocity of release associated with coughing and sneezing indicates the greater spread in the horizontal direction when evaporation is accounted for. The life time of the 10 µm particle increases from 8.3 min to 12 hours (will be intercepted prior and the actual airborne time will then be shorter); and for a 100 µm particle from 4.9 s to 39.4 s.

The combined efect of shape and electrostatic complementarities (Sc, EC) at the interface of the interacting protein partners (PPI) serves as the physical basis for such associations and is a strong detterminant of their binding energetics. EnCPdock (https://www.scinetmol.in/EnCPdock/) presents a comprehensive web-platform for the direct conjoint comparative analyses of complementarity and binding energetics in PPIs. It elegantly interlinks the dual nature of local (Sc) and non-local complementarity (EC) in PPIs using the Complementarity Plot. It further derives an AI-based ∆G_binding with a prediction accuracy comparable to the state-of-the-art. This book-chapter presents a practical manual to conceptualize and implement EnCPdock with its various features and functionalities, collectively having the potential to serve as a valuable protein engineering tool in the design of novel protein interfaces.

Arsenic (As) contamination of groundwater is a common problem in BDP. The alkaline pH of the groundwater provides favourable condition for geomicrobiochemical processes, where organic matter also plays an important role in mobilization of As. The total arsenic content (AsT) of the groundwater is in the range of 69-178 µgL-1 with mean value of 118.58 µgL-1. The groundwater quality of monitored drinking water wells are related to local land–use pattern and rural sanitation installation and practices (which can have a strong influence on microbial contamination). The study indicates that As heterogeneity, probably a consequence of microbial heterogeneity is a feature of the study area. The excessive total and fecal coliform (TC and FC) count of the ponds possibly suggest uncontrolled surface run offs and sewage leakage, notably from nearby pit-latrine, which increased the microbial contamination in these water sources. The tube wells located in close proximity (~ 2-3 m) of the surveyed ponds are also contaminated with high TC and FC values, due to faulty water supply system, pond water infiltration and cracked tube well platforms. Coliforms may influence geomicrobiological processes in groundwater and thereby, contribute in As release and mobilization. The TC and FC values of monitored tube wells and ponds show seasonal variation, with high TC and FC values during wet season. Attempt has been made to focus on sanitation risk of the monitored wells (based on sanitation and fecal coliform scores) which is usually less explored. The sanitary risk score reveal the need of immediate attention to all the sites, as 25.0 %, 58.3 %, 11.1 % and 5 % of tube wells of the six sites fell under very high risk (sanitary risk score ≥ 9), high risk (sanitary risk score 6-8), intermediate risk (sanitary risk score 3-5) and low risk category (sanitary risk score 0-2), respectively. Fecal coliform score classified all the sites under intermediate risk category (FC count 10-100 per 100 ml of water). The predominance of As heterogeneity particularly in areas under high risk category (showing high TC and FC contamination) is observed along with the similar sinusoidal pattern of TC, FC and AsT content. Finally, this study shed light on the factors responsible for unsafe nature of monitored tube wells and the influence of anthropogenic activities on the microenvironment of the groundwater, which could be a probable reason behind the As heterogeneity in the groundwater of the study area.

Mathematical modeling is crucial in investigating the pandemic of the ongoing coronavirus disease (COVID-19). The primary target area of the SARS-CoV-2 virus is epithelial cells in the human lower repertory track. During this viral infection, infected cells can initiate innate and adaptive immune responses to viral infection. Immune response in COVID -19 infection can lead to longer recovery time and more severe secondary complications. We formulate a target cell limited mathematical model by incorporating a saturation term for SARS-CoV-2 infected epithelial cell loss reliant on infected cell levels. Forward and backward bifurcation between disease-free and endemic equilibrium points has been analyzed. Global stability of both disease-free and endemic equilibrium is provided. We have seen that the disease-free equilibrium is globally stable for $R_0<1$, and endemic equilibrium exists and is globally stable for $R_0>1$. Impulsive application of drug dosing has been applied for the treatment of covid-19 patients. Also, the dynamics of the impulsive system are discussed when a patient takes drug holidays. The numerical simulations are performed in support of our analytical findings and for the qualitative analysis of the system's dynamics with and without impulse drug dosing.

Consumer IoT (CIoT) manufacturers seek customer feedback to enhance their products and services, creating a smart ecosystem like a smart home. Due to security and privacy concerns, Blockchain-based federated learning (BCFL) ecosystems can let CIoT manufacturers update their Machine Learning (ML) model using end-user data. FL uses privacy-preserving ML techniques to forecast customers' needs and consumption habits, and blockchain replaces the centralised aggregator to safeguard the ecosystem. However, Blockchain technology (BCT) struggles with scalability and quick ledger expansion. In BCFL, local model generation and secure aggregation are other issues. This research contributes a novel architecture emphasising Gateway Peer (GWP) in blockchain network to resolve scalability, ledger optimisation and secure model transmission issues. In the architecture we replace the centralised aggregator by the blockchain network, while GWP restricts the number of local transactions to execute in BCN. Considering the security and privacy of FL processes, we have added differential privacy and advanced normalisation techniques to ML processes. The approaches strengthen end-users' cyber security and encourage the adoption of technological innovation standards by service providers. The proposed approach has been tested extensively using a well-respected Stanford Cars dataset. We experimentally demonstrate that the proposed architecture makes the network scalable and optimises the ledger significantly. In addition, the normalisation technique outperforms batch normalisation when features are under DP protection.

The aim of this study was to examine pathologic complete response (pCR) and overall survival (OS) of patients diagnosed with non-metastatic inflammatory breast cancer (IBC). A total of N=8,550 cases undergoing surgery were identified between 2004-2013, using the National Cancer Database (NCDB). Patients were grouped into 4 biologic subtypes (HR+/HER2-, HR+/HER2+, HR-/HER2+, HR-/HER2-). The median age at diagnosis was 56 years. On average, women were followed for 3.7 years [interquartile range=3.0]. The majority were white (80%), had private health insurance (50%), and presented with poorly differentiated tumors (57%). Approximately 46% of the cancers were >5cm. Most patients underwent mastectomy (94%) and received radiotherapy (71%). Differences by biologic subtypes were observed for grade, lymph node invasion, race, and tumor size (p<.0001). Compared with non-pCR (54%), patients experiencing pCR had superior 5-year survival (77%) (p<.0001). Survival was poor for triple-negative (TN) tumors (37%) vs. other biologic subtypes (60%) (p<.0001). On multivariable analysis, TN-IBC, positive margins, and not receiving either chemotherapy, hormonal therapy or radiotherapy were independently associated with poor 5-year survival (p<.0001). In this large multicentric analysis of IBC, categorized by biologic subtypes, we observed significant differential tumor, patient and treatment characteristics, and OS.

Tuberculosis (TB) continues to pose a global health challenge, exacerbated by the rise of drug-resistant strains. The development of new TB therapies is an arduous and time-consuming process. To expedite the discovery of effective treatments, computational structure-based drug re-purposing has emerged as a promising strategy. From this perspective, conditionally essential targets present a valuable opportunity, and the mycobactin biosynthesis pathway stands out as a prime example highlighting the intricate response of Mycobacterium tuberculosis (Mtb) to changes in iron availability. This study focuses on the re-purposing and revival of FDA-approved drugs (library) as potential inhibitors of MbtA, a crucial enzyme in mycobactin biosynthesis in Mtb conserved among all species of mycobacteria. Literature suggests this pathway to be associated with drug efflux pumps, which potentially contribute to drug resistance. This makes it a potential target for antitubercular drug discovery. Herein we utilized cheminformatics and structure-based drug repurposing approaches, viz., molecular docking, dynamics, and PCA analysis, to decode the intermolecular interactions and binding affinity of the FDA-reported molecules against MbtA. The virtual screening revealed ten molecules with significant binding affinities and interactions with MbtA. These drugs, originally designed for different therapeutic indications (4: antiviral, 3: anticancer, 1: CYP450 inhibitor, 1: ACE inhibitor, and 1: leukotriene antagonist), are repurposed as potential MbtA inhibitors. Furthermore, our study explores the binding modes and interactions between these drugs and MbtA, shedding light on the structural basis of their inhibitory potential. Principal component analysis highlighted significant motions in MbtA-bound ligands, emphasizing the stability of the top Protein-Ligand Complexes (PLCs). This computational approach provides a swift and cost-effective method for identifying new MbtA inhibitors, which can subsequently undergo validation through experimental assays. This streamlined process is facilitated by the fact that these compounds are already FDA-approved and have established safety and efficacy profiles. This study has the potential to lay the groundwork for addressing the urgent global health challenge at hand, specifically in the context of combating Antimicrobial Resistance (AMR) and Tuberculosis (TB).

Regulatory monitoring networks are often too sparse to support community-scale PM2.5 exposure assessment while emerging low-cost sensors have the potential to fill in the gaps. Recent advances in air quality monitoring have produced portable, easy-to use, low-cost, sensor-based monitors, which has given a new dimension to the air pollutant monitoring and has democratized the air quality monitoring process by making monitors and results directly available at community level. This study used PurpleAir(c) sensors for PM2.5 assessment in California, USA. Evaluation of PM2.5 from sensors included Quality Assurance &amp; Quality Control (QAQC) procedures, assessment with respect to reference monitored PM2.5 concentrations, and formulation of a decision support system integrating these observations using geostatistical techniques. The hourly and daily average observed PM2.5 concentrations from PurpleAir monitors followed the trends of observed PM2.5 at regulatory monitors. PurpleAir monitored PM2.5 also captured the peak PM2.5 concentrations due to incidents like forest fire. In comparison with reference monitored PM2.5 levels, it was found that PurpleAir PM2.5 concentrations were mostly higher. The most important reason for PurpleAir higher PM2.5 concentrations was the inclusion of moisture or water vapor as aerosol in contrast to measurements of PM2.5 excluding water content in FEM/FRM and non-FEM/FRM monitors. On long term assessment (2016-2020), R2 was between 0.54 and 0.86 at selected collocated PurpleAir and regulatory monitors for hourly PM2.5 concentrations. Past research studies have been conducted for mostly shorter time periods (&lt;3-4 months) that resulted in higher R2 values between 0.80 to 0.98. This study aims to provide reasonable estimations of PM2.5 concentrations with high spatiotemporal resolutions based on statistical models using PurpleAir measurements. The methods of Kriging and IDW, geostatistical interpolation techniques, showed similar spatio-temporal patterns. Overall, this study revealed that low-cost, sensor based PurpleAir sensors could be effective and reliable tools for episodic and long-term ambient air quality monitoring.

Biodiversity has become an issue of global anxiety over the past decades due to its rapid decline worldwide. Bangladesh as one of the most densely populated countries in the world is no more exception. The country, although, was once very rich in biodiversity, during the last few decades as a consequence of the rapid reduction in forest area, urbanisation, habitat modification, unsustainable natural resources use and collection and overall climate change it has decreased alarmingly. Of late, the government, as a signatory of various regional and international conservation treaties, has taken various initiatives to improve country’s dwindling biodiversity. This paper reviews the present situation of biodiversity in Bangladesh, management trends and major causes of biodiversity loss. A separate statutory body is fundamental to ensure conservation, sustainable use and equitable sharing of benefits arisen from biodiversity in the country.

The global construction sector contributes a significant share of total greenhouse gas (GHG) emissions. In Australia, infrastructure activity alone generates 18% of the GHG emissions budget. The use of low-embodied carbon building materials is crucial to achieving sustainability in the construction sector and to fulfill national and international climate goals. Industrial hemp (Cannabis sativa L.) is considered a promising feedstock for sustainable construction materials because of its biogenic carbon content, fast-growing cycles with low agricultural input requirements, and technical functionality which is comparable to traditional materials. This study has applied the life cycle assessment (LCA) guideline of ISO 14040:2006 to estimate the carbon footprint (CF) expressed in carbon dioxide equivalent (CO2eq) emissions of hemp-based building materials in Western Australia. The functional unit is 1 m2 of hemp-based board, and the system boundary includes cradle-to-gate stages, i.e., pre-farm, on-farm, and post-farm activities. The production of 1 m2 of hemp-based board is estimated to be - 2.302 kgCO2eq. Electricity from the public grid for lignin extraction during the post-farm stage is the main contributor to total CO2eq emissions (26%), followed by urea production (14%) during the pre-farm stage. Overall, the use of electricity from the SWIS during the post-farm stage accounts for 45% of total emissions. Sensitivity analysis shows that the CF of hemp-based boards is highly sensitive to the source of energy, i.e., total replacement of the SWIS by solar power decreases the CF from - 2.30 to -6.07 kgCO2eq (164%). The results suggest that hemp-based boards exhibit lower embodied GHG emissions compared to traditional materials, such as gypsum plasterboards.

Background: The practice of self-medication is common worldwide and is an important component of medical self-care. However, the practice can be dangerous and is linked to various risks for the patients and the entire community. This study aimed to estimate the prevalence and factors associated with self-medication among Bangladeshi adults. Methods: A cross-sectional survey was conducted between April and June 2021 among Bangladeshi adults (aged &gt;19 years) using convenient sampling. A total of 1320 data were collected through face-to-face interviews using a standardized questionnaire. Multivariable logistic regression analysis was used to identify factors associated with self-medication practice (SMP). Results: Overall, 41% of adults in our survey reported SMP. The most common illnesses that prompted SMP were common cold/flu (66.4%), gastric problems (65%), and headache (64.4%). The most frequent reasons for SMP were to get better services (30.59%), perceive SMP without side effects (23.28%), and save time with effectiveness (14.56%). Potential risk factors included 10 years (AOR = 1.91; 95% CI: 1.04 - 3.50) and &gt;12 years of schooling (AOR = 5.03; 95% CI: 2.27 - 11.15), being a businessman (AOR = 4.64; 95% CI: 1.74 - 12.37), having ≤6 family members (AOR = 2.13; 95% CI: 1.40 - 3.24), being a member of a social group (AOR = 1.53; 95% CI: 1.10 - 2.12), a health status check after every six months (AOR = 1.52; 95% CI: 1.08 - 2.13), and current ill-health (AOR = 1.41; 95% CI: 1.06 - 1.87). Protective factors identified included ≤30 years of age (AOR = 0.40; 95% CI: 0.17 - 0.93), and practice of modern (AOR = 0.39; 95% CI: 0.22- 0.69) and herbal (AOR = 0.45; 95% CI: 0.21- 0.97) healing types. Conclusion: More than one-third of the study participants reported practicing self-medication. Increasing the community’s awareness of the extreme consequences of SMP and not just the average experience might sway individuals away from SMP, and implementing strict jurisdiction could be a way to minimize the SMP.

Institutional support and quality education are linked in a significant way. During Covid-19, institutional support is critical to closing the huge academic gap that has emerged as physical academic practices have been moved to a virtual education system using technology. This research aims to assess institutional support for online education in Bangladesh during the Covid-19 pandemic. This analysis is focused on the three main elements of the Adapted Model of Institutional Support (AMIS) of Bond et al, 2007, and the Institutional Support Model (ISM) of Valverde and Rodriguez, 2002, namely Financial Support (FS), Technical Support (TS), and Mentoring Support (MS). According to the findings, a few universities in Bangladesh have provided average support for continuing online education, while others have just started taking online classes. Several problems have been discovered, such as the lack of dedicated software for conducting online academic activities, lack of training and grooming, lack of mentoring, poor internet access, lack of smartphones, high internet package rates, and so on. This study concludes with some policy recommendations for a smooth online education system in Bangladesh.

Sustainable manufacturing practices are becoming increasingly necessary due to the growing concerns regarding climate change and resource scarcity. Consequently, material recycling technologies have gradually become preferred over conventional processes. This study aimed to recycle waste polylactic acid (PLA) from household-disposed cups and lids to create 3D-printed parts and promote sustainable manufacturing practices. To achieve this, the current study utilised virgin and post-consumer PLA (sourced from household waste) blends. The PC-PLA wastes were shredded and sorted by size with the aid of a washing step, resulting in a filament with a 1.70 ± 0.5 mm diameter without fragmentation or dissolution. A 50:50 wt.% blend of virgin PLA (vPLA) and PC-PLA was selected as the standard recycling percentage based on previous research and resource conservation goals. The study investigated the impact of three 3D printing parameters (layer height (LH), infill density (I), and nozzle temperature (NT))on the quality of 3D-printed parts using a three-level L9 Taguchi orthogonal array. The findings revealed that blending PC-PLA with vPLA led to significant improvements in the tensile, flexural, and impact strengths by 18.40%, 8%, and 9.15%, respectively, compared to those of recycled PLA. This conclusion was supported by the investigation of the fracture surface area, which revealed fractographic features associated with printing parameters, such as plastic deformation and interfilament debonding. An ANOVA analysis revealed a positive influence of larger layer height and high nozzle temperature on the mechanical properties. Subsequently, the optimal printing parameters (LH: 0.3 mm, I: 100%, and NT: 215 °C) were determined using the S/N ratio, and a confirmation test using the optimum printing parameters exhibited a strong correlation with statistically predicted outcomes. Finally, the study used optimum printing parameters to fabricate 100% post-consumer recycled PLA 3D printed parts, demonstrating their potential for low-strength applications. Based on these findings, it can be concluded that virgin and post-consumer recycled PLA blended filament for fabricating 3D printed components is an effective way to support plastic recycling in the context of a circular economy.

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.

The study explored the community perception of maternal deaths influenced by natural disaster, practice of maternal complications during natural disaster among the rural population in Bangladesh. It also explored the challenges faced by the community for providing health care and referring the complicated pregnant mothers during disaster. Three focus group discussions (FGDs) and eight in-depth interviews (IDIs) were conducted in the marginalized rural communities in the flood-prone Khaliajhuri sub-district, Netrakona district, Bangladesh. Flood is one of the major risk factors for influencing maternal death. Pregnant mothers seriously suffer from maternal complication, lack of antenatal checkup and even any doctor during flood. During the time of delivery, it is difficult to find even a skilled attendant and referring the patient with delivery complications to the healthcare facility. Boat is the only mode of transport. Majority maternal deaths occur on the boats during transfer from the community to the hospital. The rural people feel that the maternal deaths influenced by natural disaster are the natural phenomena. It needs some pre-preparation to support pregnant women during the disaster. There is unawareness of maternal health, related care and complications during disaster among the local health service providers and volunteers.

Contact tracing has become a vital tool for public health officials to effectively combat the spread of new diseases, such asthe novel coronavirus disease COVID-19. Contact tracing is not new to epidemiologist rather, it used manual or semi-manualapproaches that are incredibly time-consuming, costly and inefficient. It mostly relies on human memory while scalabilityis a significant challenge in tackling pandemics. The unprecedented health and socio-economic impacts led researchersand practitioners around the world to search for technology-based approaches for providing scalable and timely answers.Smartphones and associated digital technologies have the potential to provide a better approach due to their high level ofpenetration, coupled with mobility. While data-driven solutions are extremely powerful, the fear among citizens is thatinformation like location or proximity associated with other personal data and can be weaponised by the states to enforcesurveillance. Low adoption rate of such apps due to the lack of trust questioned the efficacy and demanded researchers tofind innovative solution for building digital-trust, and appropriately balancing privacy and accuracy of data. In this paper,we have critically reviewed such protocols and apps to identify the strength and weakness of each approach. Finally, wehave penned down our recommendations to make the future contact tracing mechanisms more universally inter-operable andprivacy-preserving.

Keywords: free radicals; oxidative stress; hepatocellular carcinoma; anti-oxidants; kaempferol

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.

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.

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 main inhibitory neurotransmitter in the mammalian brain is 4-aminobutyric acid (GABA). Phthalimide acts as a sodium channel antagonist, one of the finest targets for treating epilepsy is the sodium channel and JNK kinase activity is inhibited to treat epilepsy. a novel compound with multiple targets of action for the treatment of epilepsy also anti-oxidant activity has been designed. The compounds are designed in two series aldehydes and aniline. Docking of all the designed compounds has been done with the suitable protein GABA-AT, sodium channel, JNK protein, and anti-oxidant from protein bank. QSAR was done for constructing many linear regression models. In combination with the developed Docking and QSAR outcomes, ADMET has been performed for the active compounds. The result shows that 11 of the compounds have excellent binding energy in docking with all the receptors and also have good QSAR results and follow the ADMET. The structural understanding of human GABA-AT inhibition was obtained from molecular dynamics simulation studies for compound no. 11 at 5 nanoseconds. Synthesis and pharmacological activity also suggest that the designed compound no.11 be considered the best Novel Compound.

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.

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.

Artificial Intellignece (AI) is a platform lending immense assistance in discovering and developing drugs and thus, various such approaches have been developed with the intent of simplifying and improving biomedical operations such as drug repurposing and drug discovery. In the past decade, AI-based investigation of nanomedicines, as well as non-nanomedicines has reached the clinical level. In semblance with the traditional methods of therapy, nanomedicine therapy is employed at limited doses. The study of a variety of drugs resulted in the conclusion that the effect of each drug is variable for every patient and, evaluating that perfect drug combination manually is a time-consuming as well as an inefficient treatment method. Therefore, the use of AI simplifies and reduces the time consumption in determining the perfect customized drug combination for nano-therapy. The area with the most potential for meeting this reality is to optimize the drug and dosage parameters. It is a universally known fact that cancer is dangerous and unique because of the exacting challenges it poses during treatment and, to achieve a better treatment, the therapeutic effect on each patient must be delineated even if the volume of data generated is massive. The article aims at analyzing the AI technologies that help yield results much quicker, make the analyses simple, and efficient.

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 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.

The mechanisms involved in immune responses to cancer have been extensively studied for several decades and, considerable attention has been paid to harnessing the immune system's therapeutic potential. Cancer immunotherapy has established itself as a promising new treatment option for a variety of cancer types. Various strategies including cancer vaccines, monoclonal antibodies (mAbs), adoptive T-cell-cancer therapy and immune test therapy have gained prominence through immunotherapy. However, it remains to be accomplished the full potential of cancer immunotherapy. In spite of having startling aspects, the cancer immunotherapies have some difficulties including the inability to effectively targeting the cancer antigens and the abnormalities in patient response. With the advancement of technology, this system has changed the genome-based immunotherapy process in the human body including generation of engineered T cells. Due to its high specificity, CRISPR-Cas9 has become a simple and flexible genome-editing tool to target nearly any genomic locus. Recently, the CD19-mediated CAR-T cell (chimeric antigen receptor T cell) therapy has opened a new avenue for the treatment of human cancer, though low efficiency is a major drawback of this process. Thus, increasing the efficiency of the CAR-T cell (engineered T cells that induce the chimeric antigen receptor) by using CRISPR-Cas9 technology could be a better weapon to fight against the cancer. In this review, we have broadly focused on the use of CRISPR-Cas9 technology for the modification of the T-cell, which can specifically recognize cancer cells and be used as immune therapeutics against cancer. We have also demonstrated the other potential strategies for the treatment of cancer.

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.

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.

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.

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.

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.

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.

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 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.

The livelihood of most of the fishers in Indian Sundarbans is dependent on Penaeus monodon post larvae fishing. These post larvae collectors are socially backward lacking economic security. The activity of collecting Penaeus monodon post larvae for rearing in aquaculture, destroy other aquatic species. Many other juveniles of shellfish and fin fish were destroyed in the process of collection of Penaeus monodon post larvae. The removal of juveniles before they reach maturity disturbs the ecological chain by hampering breeding processes and may cause extinction of some fish species in the long run. The present study is an attempt to estimate the economic value of juveniles destroyed in the collection of (Penaeus monodon) post larvae. In total 32 species were identified in P.monodon the post larval by-catch. The economic loss is assessed based on estimating biomass by taking a length-weight relationship from published literature. Further, the paper illustrates how does a profit enterprise is linked with natural resource exploitation. The paper explores government policy and nature conservation issues for social justice and effective conservation.In conclusion, suggestions are given to reduce the burden of livelihood on natural resources to the extent of exploitation and to strengthen institution and policy-making considering socio-ecological vulnerabilities of the area.

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.

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.

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.

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.

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.

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.

Despite saltmarshes being considered as nature-based solutions (NbS) towards climate change mitigation, India’s saltmarsh ecosystems are least studied. This study quantifies the seasonal variation in carbon stocks mono-specific saltmarsh species (Porteresia coarctata) and its potential to play an important role in India’s climate change mitigation plans. Seasonal (pre-and post-monsoon) sampling of P. coarctata surface water, biomass and 30 cm sediment core was collected across four locations on the east coast of India to quantify sediment dry bulk density (DBD), organic matter (OM%), organic carbon (Corg%), Corg stocks of sediment and biomass, total carbon (C%) and nitrogen (N%) and stable isotopes of δ13C and δ15N. In general, the sediment DBD, OM and Corg of P. coarctata meadows was higher in post-monsoon and was influenced by salinity and pH changes. Isotope (δ¹³C) modelling of various sediment C sources suggested, particulate organic matter (POM) contribution was highest (0.04-0.79%) followed by P. coarctata (0.01–052%) and other macrophytes across our study locations. The seasonal variation of δ¹³C showed increased contribution of marine derived particulate and dissolved organic matter into P. coarctata meadows in post-monsoon season. Heavier δ¹⁵N values were observed in post-monsoon season suggesting anthropogenic input, that was utilized by P. coarctata to increase its above and below-ground biomass and shoot density. The combined ecosystem (30 cm sediment + biomass) Corg stocks of P. coarctata was 1.7-fold higher in post-monsoon (4021.20± 917 Mg C) compared to pre-monsoon (2297.36 ±647 Mg C) season among the four locations with a sediment Corg contribution >70%. Based on the International Panel for Climate Change Tier II assessment the P. coarctata meadows (443 ha) can help in avoiding the pre and post-monsoon emissions of 8431.34 and 14757.84 Mg CO₂ respectively. The combined price of the total CO₂ equivalent stored in P. coarctata meadows in pre- and post-monsoon is US$ 14.50 and US$ 25.38 million respectively. Further studies quantifying the NbS potential of P. coarctata mono-specific and mixed meadows of India’s coast is needed along with integration of saltmarsh ecosystems into India’s National Action Plan on Climate Change.

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.

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.

Background: Radiotherapy plays an important role in the management and survival of patients with breast cancer. The aim of this study was to examine the association between age, comorbidities and use of radiotherapy in this population. Methods: Patients diagnosed with breast cancer from 2004–2013 were identified from the American College of Surgeons National Cancer Database (NCDB). Follow-up time was measured from the date of diagnosis (baseline) to the date of death or censoring. Adjusted hazard ratios (aHR) and 95% confidence intervals (95%CI) were used as the measure of association. Results: Independently of comorbidities and other important outcome-related factors, patients >65 years of age who received radiotherapy survived significantly longer than those who did not receive radiotherapy (aHR = 0.53, 95%CI = 0.52–0.54). However, as women aged, those with comorbidities were less likely to receive RT (adjusted P-trend by age <0.0001). Conclusions: The development of decision-making tools to assist clinicians, and older women with breast cancer and comorbidities, are needed to facilitate personalized treatment plans regarding RT. This is particularly relevant as the population ages and the number of women with breast cancer is expected to increase in the near future.

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 bioindicator potential of seagrass ecosystems in coastal trace metal monitoring is low for tropical island ecosystems. This study evaluated the bioindicator potential of six seagrass species exposed to anthropogenic trace metal pollution in the Andaman and Nicobar Islands (ANI) of India. Sediment and seagrass biomass, samples were analyzed for trace metals (Co, Cr, Cu, Fe, Mg, Mn, Ni, Pb, Zn) from four locations of ANI exposed to anthropogenic contamination. Geo accumulation Index values indicated moderate trace metal contamination in seagrass sediment. Seagrass trace metal accumulation from sediment was both species-specific and location- specific for ANI. Small seagrass species such as H. ovalis, H. beccarii and H. uninervis accumulated the maximum concentration of six trace metals (Cr, Cu, Fe, Ni, Pb, Zn) in their tissues compared to big seagrass species like T. hemprichii and E. acoroides of ANI. This study indicates leaves of small seagrass and roots of big seagrass species can serve as short- and long-term bioindicators respectively, of coastal trace metal contamination in tropical islands of ANI.

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.

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.

COVID-19 (2019-nCoV) is a pandemic disease with an estimated mortality rate of 3.4% (estimated by the WHO as of March 3, 2020). Until now there is no antiviral drug and vaccine for COVID-19. The current overwhelming situation by COVID-19 patients in hospitals is likely to increase in the next few months. About 15 percent of patients with serious disease in COVID-19 require immediate health services. Rather than waiting for new anti-viral drugs or vaccines that take a few months to years to develop and test, several researchers and public health agencies are attempting to repurpose medicines that are already approved for another similar disease and have proved to be fairly effective. This study aims to identify FDA approved drugs that can be used for drug repurposing and identify biomarkers among high- risk and asymptomatic groups. In this study gene-disease association related to COVID-19 reported mild, severe symptoms and clinical outcomes were determined. The high-risk group was studied related to SARS-CoV-2 viral entry and life cycle by using Disgenet and compared with curated COVID-19 gene data sets from the CTD database. The overlapped gene sets were enriched and the selected genes were constructed for protein-protein interaction networks. Through interactome, key genes were identified for COVID-19 and also for high risk and asymptomatic groups. The key hub genes involved in COVID-19 were VEGFA, TNF, IL-6, CXCL8, IL10, CCL2, IL1B, TLR4, ICAM1, MMP9. The identified key genes were used for drug-gene interaction for drug repurposing. The chloroquine, lenalidomide, pentoxifylline, thalidome, sorafenib, pacitaxel, rapamycin, cortisol, statins were proposed to be probable drug repurposing candidates for the treatment of COVID-19. However, these predicted drug candidates need to be validated through randomized clinical trials. Also, a key gene involved in high risk and the asymptomatic group were identified, which can be used as probable biomarkers for early identification.

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.

Tourism has increased in prominence as a key industry that generates employment and encourages economic diversity. The coastline region is a major contributor to worldwide tourism. Since then, coastal areas have been in the forefront of tourism infrastructure development. The presence of a large number of visitors has frequently had a negative influence on the efficient use of available resources. Maya Bay in Krabi Province, southern Thailand, is one example of a coastal area that has suffered from the negative effects of over-tourism Because of the Government of India's plan to place Lakshadweep on the world map of tourism destinations that compete with other archipelagos, it was critical that the current state of tourism in Lakshadweep be studied and precautionary measures be reviewed so that tourism growth does not devolve into over-tourism and Lakshadweep does not follow the same path as Maya Bay.

COVID-19 (coronavirus disease 2019) is a public health emergency of international concern caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). As of this time, there is no known effective pharmaceutical, phytopharmaceutical or traditional medicine for cure or prevention of COVID-19, although it is urgently needed. In this review, based on the current understanding of the disease molecular mechanisms of novel Coronavirus SARS-CoV-2 and its closest relative SARS-CoV and other human Coronaviruses, I have identified some naturally occurring plant based substances and Ayurvedic medicinal herbs that could feasibly be tested as a matter of urgency for prevention as well as therapeutic option for COVID-19 in India and other parts of the world. I conclude that dried rhizome of Curcuma longa L. i.e. turmeric, and its active ingredient curcumin may be effective in preventing as well as cure the COVID-19 pandemic due to its proven antiviral activities, this however need to be tested by appropriate clinical trials as research priority.

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.

Covid-19 has given a halt to all the activities in the world. Europe was most affected, followed by the United States of America. It has taken more than 350000 lives until now. In this study, we have assessed the severity of Covid-19 by analyzing the mortality rate of Covid-19 and other chronic diseases. The Covid-19 data and “death rate” data caused by other diseases were downloaded from the world health organization (WHO) website. A normalized method was used to see the mortality rate of Covid-19 in comparison to other diseases. The deaths caused by Covid-19 in April 2020 have overtaken the average number of deaths caused by Cancer, Cardiovascular diseases, and other diseases in Belgium, the United Kingdom (UK), Spain, France, and Ireland. Covid-19 was found to be strongly correlated with non-communicable respiratory diseases and Cancer with correlation coefficients 0.73 and 0.67 respectively. The severity of Covid-19 in the United States of America (USA) was moderate. The severity of Covid-19 in Asian countries was found to be low. Europe showed the highest diversity in the mortality rate of Covid-19. On average, except for a few European countries, Cardiovascular diseases, cancer, and non-communicable respiratory diseases were still more lethal and caused more deaths than Covid-19.

Circular dichroism (CD) spectroscopy is a valuable tool in the pharmaceutical industry for determining the secondary and tertiary structure, folding, stability, and interactions of proteins in biosimilars. However, protein aggregation due to its interaction with surfactants can introduce variations in CD spectra, leading to false interpretations. To investigate this effect, we prepared aqueous solutions of α-chymotrypsin with the same amount of surfactant but at different solution preparation steps. Interestingly, the CD spectra of these solutions showed slight differences despite having the same surfactant concentration. This suggests that the order of surfactant addition can influence protein conformation. To address this issue, we propose a method for preparing aqueous protein solutions that yields reproducible CD spectra. This method is expected to benefit the pharmaceutical industry by improving the accuracy of CD spectroscopy for protein structural analysis and evaluation of protein functionality.

The main objective of this paper is to identify the major research areas of ChatGPT through term and keyword co-occurrence network mapping techniques. For conducting the present study, total of 577 publications were retrieved from the Lens database for the network visualization. The findings of the study showed that “chatgpt” occurrence in maximum number of times followed by its related terms such as artificial intelligence, large language model, gpt, study etc. This study will be helpful to library and information science as well as computer or information technology professionals.

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.

Today, various dietary supplements are taken to improve endurance performance during physical activity. These supplements have proven to be very successful in controlling and balancing various hormone levels and have contributed to the prevention and healing of metabolic disorders and physical injuries. In this study, we sought to investigate the effects of the ACTN3 gene and nutrient supplementation, including beta-alanine, ashwagandha, L-carnitine, and iron, on athletic performance. The ACTN3 gene has been identified as a potential genetic determinant of athletic performance, particularly in activities that require high levels of power and strength. This study investigated the interaction between the ACTN3 gene and supplementation and highlighted the potential for personalized approaches to improve athletic performance. 24 subjects per group, were randomized in a parallel-group design to examine the effects of supplementation on the ACTN3 gene and athletic performance over a 21-day intervention period. Participants in the intervention were divided into four groups of six members each. The same subjects who did not take supplements formed the control group. In addition, the subjects were divided into 4 groups (G1, G2, G3, and G4), each consisting of subgroups of control and a treated. All treated groups (TG1, TG2, TG3, and TG4) received 4 supplements for 21 days, namely S1 (ashwagandha), S2 (iron), S3 (beta-alanine) and S4 (L-carnitine), together with the 4 control groups, i.e. CG1, CG2, CG3 and CG4, who received no supplements during the same period. In particular, this study determines the effect of these 4 supplements on actn3 gene expression, testosterone, cholesterol and BUN levels of the participants. The P-values determined for all parameters showed statistically significant values and the final result showed that all supplements had positive effects on the tested parameters. The result showed a highly significant difference between the intake of supplements before and after the intake of 24 athletes per group on the ACTN3 gene expression level and biochemical indicators.

We aimed to apply DNA barcoding tool for the molecular identification of horn snails T. telescopium using mitochondrial cytochrome oxidase I gene (mt-COI) and to investigate their evolutionary relationship along with location-specific bio-geographical variations. The molecular data sets of this study indicate that strong probability of T. telescopium species taxonomic confirmation using mt-COI sequences. Results of the phylogenetic analysis suggest that Telescopium sp. was monophyletic with disseminated nodes and the evolution of group II originated from group I. The substantial genetic distance among the mt-COI sequences (0.005 to 0.184) were noticed. Large divergence between the south-west coast of India and Australia region population indicates limited gene flow between the two continents. Our study suggests that the genera Telescopium is globally ubiquitous but genetically showing inter-region differentiation. We conclude that mt-COI gene can be used to identify gastropod T. telescopium species.

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.

Bacterial antibiotic resistance has become a major global health concern. One of the main reasons for the development of multi-drug resistance properties in bacteria is due to the bacterial efflux pump systems. They are important transport proteins, mainly involved in the removal of toxic substrates like antibiotics from inner cell environment. These pumps are responsible for the intrinsic ability of bacteria to get resistant to the antibiotic. Various types of efflux pumps are present in the Gram-positive and Gram-negative bacteria. Plant-derived products like Capsaicin, Olympicin A, and Indirubicin were found to be inhibitors of an efflux pump in Staphylococcus aureus similarly Ursolic acid derivatives; Daidzein and Lanatoside C were plant-derived inhibitors of an efflux pump in Escherichia coli. In this review detail information have been provided about efflux pump inhibitors that have been found to be effective in the Gram-positive bacteria and Gram-negative bacteria. The aim of this review is to focus on the role of plant-derived compounds as effective efflux pumps inhibitors with reference to mainly Staphylococcus aureus and Escherichia coli.

All transmission disease depends on the transmission opportunity or medium like humans in COVID-19. Due to globalization and regular movement of people from one country to another, spread of COVID 19 reached to 208 countries till May 10, 2020. For any society health is major concern for humanity as well as administration. Any pandemic is declared as and when it reached at a particular severity level and control vice versa. So, we have continued the daily COVID 19 cases analysis and segregated till May 10, 2020. We have included at least 25 countries for the analysis purpose due to limitation of number of observations in the analysis. Maximum number of day’s data available for China is for 100 days, followed by Iran for 81 days, minimum number of days data is for 16 days for Western Sahara and Tajikistan.

The situation in the world of pandemics is rapidly changing, and the second wave of COVID-19 has put a lot of pressure on the government and private sector, which are primarily responsible for controlling the situation. COVID-19 positive cases have increased in recent months relative to last year, and the number of patients admitted to hospitals has also increased, despite the fact that few of them were denied admission due to shortage of beds. Normal people who experience any symptoms immediately isolate themselves and begin taking the COVID medications prescribed by medical personnel and their team. During these times, all domestic people tossed the wrappers and boxes of medicines into the regular trash can, and the waste was handed over to the waste collector, who treated it like any other domestic waste and disposed of it using open dumping or other methods. The goal of this perspective is to suggest the collections of these types of waste from domestics, and protect the natural resources like water, soil, and even living beings like animals from pollution (from the effect of SARS-CoV-2). The main challenge for environmental waste management agencies is determining who has COVID positive and which houses generate these types of waste; thus, proposed strategy may be beneficial to the long-term sustainability of natural resources and animals.

Growth benefits of high speed rail (HSR) for enterprises are not automatic, but require a buoyant local economy and a robust strategy. Against above background, main objectives of ex-ante case study have been to investigate local socio-economic and spatial impacts of proposed HSR project around Ahmedabad station area on Mumbai-Ahmedabad HSR corridor, analyze the opportunities and challenges of HSR development and draw policy implications. Qualitative research methodology has been used to elicit the perceptions and perspectives of randomly selected 43 small, medium and large enterprises. Data has been analyzed using descriptive statistics. The study reveals that HSR induced greater human interaction will activate local economy, improve business efficiency and generate employment. Frequent travels on business trips can influence enterprises decision to settle near HSR station for easy access and likely to promote realty development. The proposed HSR project should be developed in synergy with urban dynamics of cities in transition and metropolitan service cities. Poor public transport connectivity is likely to be a major challenge in improving HSR accessibility and enhancing overall impacts of HSR, which can be improved by developing an integrated urban transport system, for which cooperation of all stakeholders and coherence with firms’ strategies is essential.

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.

Buffalo are silent breeders, therefore detecting estrus is a serious challenge. There is a rising need for sensitive and precise biomarkers in this scenario. Recent research on miRNA has demon-strated the importance of these molecules as biomarkers. Though there have been miRNA studies in saliva during the estrous cycle, there have been few miRNA research in blood samples. The current study was designed to look at blood miRNAs during the oestrous cycle in heifers (n=5) to address the issue of silent estrus. On the day of estrus and diestrus, blood samples from 60 heifers were obtained and pooled into (n=5) separate samples. Ultrasonography and progesterone assay was performed to confirm estrus. Then, employing particular miRNA adapters, small RNA se-quencing of miRNA was performed using the Illumina Miseq 2500. The UEA sRNA bioinfor-matics workbench identified 94 substantially differently expressed miRNAs (p>0.05) from these data. In estrus, 63 miRNA were upregulated and 31 miRNA were downregulated. When fold change was increased to (log2foldchange >1; q value less than 0.05), 25 miRNAs were elevated during estrus. miR-497, miR-582, miR-10174, miR-23, miR-223, miR-1296 were upregulated, whereas miR-10167, 671, 1246,122 were downregulated. miR-497 is unusually elevated (log2 foldchange>5) when compared to another miRNA (log2 foldchange >5) miRNet 2.0, Cytoscape, and MIENTURNET network software found that miR-497 has more degree centrality, above 60; it is associated with more than 60 nodes, followed by miR-93