Multivariate statistical analysis to assess the surface water quality of a snow and glacier-fed river: A case from Alaknanda River basin.

The water quality of Himalayan rivers has declined due to human activities, untreated effluent discharge, and poor sewage and drainage systems. The current study aimed to assess the water quality of these rivers using multivariate statistical analysis throughout four seasons. The analyses of 44 surface water samples taken during the monsoon, winter, spring, and summer seasons are well within the ranges acceptable for drinking and domestic use after the sedimentation.

Microbial Endophytes: Emerging Trends and Biotechnological Applications.

A plethora of knowledge on the role of endophytic microorganisms has been reported in recent years. The cooperative chemistry between the endophytes and the internal host tissue has turned them into a crucial aid for biotechnological applications. Microbial endophytes are ubiquitous among most plant species on earth and contribute to the benefit of host plants by generating a wide range of metabolites that provide the plant with survival value.

A Computerized Analysis with Machine Learning Techniques for the Diagnosis of Parkinson's Disease: Past Studies and Future Perspectives.

According to the World Health Organization (WHO), Parkinson's disease (PD) is a neurodegenerative disease of the brain that causes motor symptoms including slower movement, rigidity, tremor, and imbalance in addition to other problems like Alzheimer's disease (AD), psychiatric problems, insomnia, anxiety, and sensory abnormalities. Techniques including artificial intelligence (AI), machine learning (ML), and deep learning (DL) have been established for the classification of PD and normal controls (NC) with similar therapeutic appearances in order to address these problems and improve the diagnostic procedure for PD. In this article, we examine a literature survey of research articles published up to September 2022 in order to present an in-depth analysis of the use of datasets, various modalities, experimental setups, and architectures that have been applied in the diagnosis of subjective disease.

Imperative Role of Machine Learning Algorithm for Detection of Parkinson's Disease: Review, Challenges and Recommendations.

Parkinson's disease (PD) is a neurodegenerative disease that affects the neural, behavioral, and physiological systems of the brain. This disease is also known as tremor. The common symptoms of this disease are a slowness of movement known as 'bradykinesia', loss of automatic movements, speech/writing changes, and difficulty with walking at early stages.

A standalone computing system to classify human foot movements using machine learning techniques for ankle-foot prosthesis control.

This paper presents different machine learning techniques to classify the following foot movements: (i) dorsiflexion, (ii) plantarflexion, (iii) inversion, (iv) eversion, (v) medial rotation, and (vi) lateral rotation. The purpose is to design a real-time standalone computing system to predict the foot movements in the sagittal plane, useful for ankle-foot prosthesis control. Electromyography (EMG) and forcemyography (FMG) signals were acquired from the leg's tibialis anterior, medial gastrocnemius, lateral gastrocnemius, and peroneus longus muscles.

Identification of potent Antigen 85C inhibitors of Mycobacterium tuberculosis via in-house lichen library and binding free energy studies Part-II.

Tuberculosis remains the cause of mortality throughout the world. Currently, the available anti-tubercular drugs are not effective because of the existence of Multi-Drug resistant tuberculosis (MDR-TB) and Extensively-Drug resistant tuberculosis (XDR-TB). It has, therefore, become necessary to develop novel drugs that inhibit the activity of drug-resistant Mycobacterium tuberculosis.

Identification of potential Mycolyltransferase Ag85C inhibitors of Mycobacterium tuberculosis H37Rv via Virtual High Throughput Screening and Binding free energy studies.

Tuberculosis (TB) is a deadly disease which causes millions of death annually worldwide. Although TB is treatable but the rise of cases of multidrug-resistant and totally drug-resistant strains of Mycobacterium tuberculosis (Mtb) poses a great challenge to cure TB completely and this situation demands an urgent need for development of potential anti-tubercular drugs. In this regard, the antigen 85C (Ag85C) has emerged as an essential mycobacterial drug target as it plays a central role in synthesizing major components of the inner and outer layers of outer membrane of Mtb.

Systems biology of seeds: decoding the secret of biochemical seed factories for nutritional security.

Seeds serve as biochemical factories of nutrition, processing, bio-energy and storage related important bio-molecules and act as a delivery system to transmit the genetic information to the next generation. The research pertaining towards delineating the complex system of regulation of genes and pathways related to seed biology and nutrient partitioning is still under infancy. To understand these, it is important to know the genes and pathway(s) involved in the homeostasis of bio-molecules.

Augmentation of crop productivity through interventions of omics technologies in India: challenges and opportunities.

With the continuous increase in the population of developing countries and decline of natural resources, there is an urgent need to qualitatively and quantitatively augment crop productivity by using new tools and technologies for improvement of agriculturally important traits. The new scientific and technological omics-based approaches have enabled us to deal with several issues and challenges faced by modern agricultural system and provided us novel opportunities for ensuring food and nutritional security. Recent developments in sequencing techniques have made available huge amount of genomic and transcriptomic data on model and cultivated crop plants including etc.