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To obtain high performance, generalization, and accuracy in machine learning applications, such as prediction or anomaly detection, large datasets are a necessary prerequisite. Moreover, the collection of data is time-consuming, difficult, and expensive for many imbalanced or small datasets. These challenges are evident in collecting data for financial and banking services, pharmaceuticals and healthcare, manufacturing and the automobile, robotics car, sensor time-series data, and many more. To overcome the challenges of data collection, researchers in many domains are becoming more and more interested in the development or generation of synthetic data. Generating synthetic time-series data is far more complicated and expensive than generating synthetic tabular data. The primary objective of the paper is to generate multivariate time-series data (for continuous and mixed parameters) that are comparable and evaluated with real multivariate time-series synthetic data. After being trained to produce such data, a novel GAN architecture named as MTS-TGAN is proposed and then assessed using both qualitative measures namely t-SNE, PCA, discriminative and predictive scores as well as quantitative measures, for which an RNN model is implemented, which calculates MAE and MSLE scores for three training phases; Train Real Test Real, Train Real Test Synthetic and Train Synthetic Test Real. The model is able to reduce the overall error up to 13% and 10% in predictive and discriminative scores, respectively. The research’s objectives are met, and the outcomes demonstrate that MTS-TGAN is able to pick up on the distribution and underlying knowledge included in the attributes of the real data and it can serve as a starting point for additional research in the respective area.

Heavy metals pose serious threats to both individuals and the environment, and there is growing global concern over potentially harmful elements. Heavy metal contamination can have a significant impact on the soil ecosystem's functioning. This requires convenient, efficient, and beneficial remediation approaches. The \"ecosystem engineer\", earthworms, can modify and enhance soil quality. The ability of earthworms to bioaccumulate metals in substantial amounts in their tissues makes them potentially beneficial as an ecological indicator of soil pollution. Vermiremediation is a new discipline of research in which earthworms are used to detoxify organically contaminated soils. Earthworms have an influential metabolic system, and their gut bacteria and chloragocyte cells play a significant role in their tendency to valorize and detoxify heavy metals. Remediation by earthworms can be considered sustainable, efficient, and ecologically beneficial. The present review provides a wide range of information on earthworms' appropriateness as prospective species for bioremediation and detoxification of toxic metal-contaminated soil to mitigate human health and environmental problems.

Oxygen is indispensable for most organisms on the earth because of its role in respiration. However, it is also associated with several unwanted effects which may sometimes prove fatal in the long run. Such effects are more evident in cells exposed to strong oxidants containing reactive oxygen species (ROS). The adverse outcomes of oxidative metabolism are referred to as oxidative stress, which is a staple theme in contemporary medical research. Oxidative stress leads to plasma membrane disruption through lipid peroxidation and has several other deleterious effects. A large body of literature suggests the involvement of ROS in cancer, ageing, and several other health hazards of the modern world. Plant-based cures for these conditions are desperately sought after as supposedly safer alternatives to mainstream medicines. Phytochemicals, which constitute a diverse group of plant-based substances with varying roles in oxidative reactions of the body, are implicated in the treatment of cancer, aging, and all other ROS-induced anomalies. This review presents a summary of important phytochemicals extracted from medicinal plants which are a part of Indian ethnomedicine and Ayurveda and describes their possible therapeutic significance.

The human implantation failure during first trimester leads to spontaneous abortions. Spontaneous abortions are consecutive and occur twice or thrice (with or without prior live births) due to factors which are either maternal or fetal. However, it also constitutes of unknown etiology; known as unexplained recurrent spontaneous abortions (URSA). In this study, the medical terminated human normal early pregnancies (NEP) of the first trimester were taken as control samples, the normal decidual sample whose molecular and epigenetic changes were compared with that of decidua of human URSA subjects. Apoptosis-related genes reported in consecutive recurrent pregnancy loss became the basis for this study. So, in this study, we evaluated the hypothesis that “p53 methylation level through methyltransferases (G9aMT and DNMT1) implicates the fate of embryo towards sustenance or cessation of pregnancy”. Further, the interaction between P53, BAX, BCL-2, CASPASE-6, G9aMT, DNMT-1, and methylated p53 expression level(s) during the first trimester of both URSA and NEP are included in this study. The degree of p53 methylation during the first trimester is found to be significant and positively correlated with that of G9aMT ( p  < 0.05), BCL-2 ( p  < 0.001), and DNMT1 ( p  < 0.001) at both transcript and protein level. A significant and negative correlation (with p -value < 0.001) between the degree of p53 methylation during the first trimester and that of the expression level of TUNEL assay (Apoptosis), P53, BAX, and CASPASE-6 are also observed in the present study. A positive correlation between apoptosis and a higher level of p53 expression (which is possibly due to low degree of p53 methylation) is observed both at the transcript and protein level in URSA which is in line with our findings. The analysis performed using structural equation modelling (SEM) further throws light on the causal relationship between sustenance of pregnancy or URSA during the first trimester of a human pregnancy and degree of methylation of p53 which is closely correlated with the interaction between G9aMT, DNMT1, BCL-2, BAX, P53, CASPASE-6, and apoptosis.

Coronavirus disease 2019 (COVID-19) emerged as a new contagion during December 2019, since which time it has triggered a rampant spike in fatality rates worldwide due to insufficient medical treatments and a lack of counteragents and prompted the World Health Organization to declare COVID-19 a public health emergency. It is, therefore, vital to accelerate the screening of new molecules or vaccines to win the battle against this pandemic. Experiences from previous epidemiological data on coronaviruses guide investigators in designing and exploring new compounds for a safe and cost-effective treatment. Several reports on the severe acute respiratory syndrome (SARS) epidemic indicate that severe acute respiratory syndrome coronavirus (SARS-CoV) and the novel COVID-19 use angiotensin-converting enzyme 2 (ACE2) as a receptor for binding to the host cell in the lung epithelia through the spike protein on their virion surface. ACE2 is a mono-carboxypeptidase best known for cleaving major peptides and substrates. Its degree in human airway epithelia positively correlates with coronavirus infection. The treatment approach can be the neutralization of the virus entering lung epithelial cells by using sera containing antibodies collected from COVID-19–recovered patients. Hence, we herein propose a pulmonary aerosolized formulation or a nasal drop using sera, which contain antibodies to prevent, treat, or immunize against COVID-19 infection.

The global food system is increasingly vulnerable to climate change, biodiversity loss, and unsustainable practices, driving numerous plants, animals, fungi, and associated culinary traditions toward extinction. These endangered foods represent not only a loss of cultural heritage but also a critical diminishment of genetic and nutritional diversity essential for robust and resilient food systems. This systematic review, conducted in accordance with PRISMA guidelines, started with 412 records, 85 studies met the inclusion criteria, focusing on the role of neglected and underutilized species in food security, their drivers of decline, and related conservation policies. Our analysis, framed by the FAO’s four pillars of food security, demonstrates that endangered foods are vital for availability (providing climate-resilient genetic diversity), access (offering affordable nutrition), utilization (supplying unique micronutrients and bioactive compounds), and stability (buffering against production shocks). However, their potential is undermined by climate change, agricultural modernization favoring monocultures, socio-cultural erosion, and significant policy gaps. Case studies from Peru, West Africa, and the Pacific illustrate both the successful integration of these foods into security strategies and the persistent challenges of funding, market access, and infrastructure. The conservation and revitalization of endangered foods are imperative for achieving sustainable food systems and global nutritional resilience. This review concludes that effective integration requires a multi-faceted approach: strengthening seed sovereignty and agroecology, developing technology-enabled value chains, promoting food literacy, and implementing coherent policy frameworks that align conservation efforts with the Sustainable Development Goals (SDGs), particularly SDG 2 (Zero Hunger), SDG 12 (Responsible Consumption and Production), and SDG 15 (Life on Land). Graphical Abstract

A region’s population growth inevitably results in higher water consumption. This persistent rise in water use increases the region’s wastewater production. Consequently, due to this increase in wastewater (influent), Wastewater Treatment Plants (WWTPs) are required to run effectively in order to handle the huge demand for treated/processed water (effluent). Knowing in advance the influent and effluent parameters increases the operational efficiency and enables cost-effective utilization of diverse resources at wastewater treatment plants. This paper is based on a prediction/forecasting of an influent quality parameter, namely total MLD, as well as effluent quality parameters, namely MPN, BOD, DO, COD and pH for the real-time data collected pre-, during and post-COVID-19 at the Bharwara WWTP in Lucknow, India. It is the largest UASB-based wastewater treatment facility in Uttar Pradesh and the second largest in Asia. In this paper, we propose a novel model namely, wPred comprising extensions of SARIMA with seasonal order and ANN-based ML models to estimate the influent and effluent quality parameters, respectively, and compare it with the existing machine learning models. The lowest sMAPE error for the influent parameters using wPred is 2.59%. The findings of the paper show a strong correlation (R-value), up to 0.99, between the effluent parameters actually measured and predicted. As a result, the model designed in this paper has an acceptable level of accuracy and generalizability which efficiently predicts/forecasts the performance of Bharwara WWTP.

Neurotransmitters are essential chemical messengers required for proper brain function, and any changes in their concentrations can lead to neuronal diseases. Therefore, sensitive and selective detection is crucial. This study presents a fast and simple colorimetric method for dopamine detection using three reagent solutions: AgNP and MPA, Ag/Au nanocomposite, and mercaptophenylacetic acid. TEM images showed a narrow distribution of Ag and Au nanoparticles with average sizes of 20 nm and 13 nm, respectively, with gold nanoparticles bound to the edges of silver nanoparticles. A paper-based biosensor was created using manual wax printing for the colorimetric detection of dopamine. Visual detection onsite showed color changes with both the silver nanoparticles and mercaptophenylacetic acid mixture and the silver–gold nanoparticle composite. Electrochemical detection using a glassy carbon electrode modified with 8 mM mercaptophenylacetic acid demonstrated high selectivity and sensitivity towards dopamine, with a peak in the range of 0.7–0.9 V. Interferences were minimized, ensuring high sensitivity and selective detection of dopamine.

Purpose--The paper aims to explore and identify the trends in E-Learning research at the global level. Design/methodology/approach--The data were collected from the Web of Science database covering the period from 1989-2018 in order to identify substantial contributions that have been published in the field of E-Learning. A total of 9826 records were retrieved. The data was analyzed to reveal different trends prevailing in E-Learning research including prominent contributing countries, authorship patterns adopted, the degree of collaboration, collaborative index, prominent sources for publication of research, visibility of research in term of citation trends like citations received/citations per paper etc. Findings--The analysis revealed a positive growth in literature. It is clear that USA and UK have contributed to more than half of the research output with PEI of 1.07 and 1.45 respectively. Computers & Education and Journal of Chemical Education were the two most used journals. The study also found out that Bradford's Law of scattering does not hold good to the journals cited in the three journals Keywords--E-Learning, Bibliometrics, Web of Science

Transfusion transmitted infections are major problem associated with blood transfusion. Accurate estimates of risk of TTIs are essential for monitoring the safety of blood supply and evaluating the efficacy of currently employed screening procedures. The present study was carried out to assess the percentage of voluntary donors and replacement donors and to find out prevalence and changing trends of various TTIs blood donors in recent years. A study was carried out on blood units of voluntary and replacement donors which were collected from January 2008 to December 2012. On screening of 180,371 replacement units, seropositivity of transfusion transmitted disease in replacement donors was 0.15% in HIV, 1.67% in hepatitis B surface antigen, 0.49% in hepatitis C virus, 0.01% in VDRL, and 0.009% in malaria. Of 11,977 voluntary units, seropositivity of transfusion transmitted disease in voluntary donors was 0.08% in HIV, 0.24% in hepatitis B surface antigen, 0.001% in hepatitis C virus, 0.008% in VDRL (sexually transmitted disease), and 0.01% in malaria. From results it has been concluded that prevalence of transfusion transmitted infection (HIV, HBV, HCV, VDRL, and malaria) was more in replacement donors in comparison to voluntary donors. Extensive donor selection and screening procedures will help in improving the blood safety.