SpecGMM: Integrating Spectral analysis and Gaussian Mixture Models for taxonomic classification and identification of discriminative DNA regions.

Motivation: Genomic signal processing (GSP), which transforms biomolecular sequences into discrete signals for spectral analysis, has provided valuable insights into DNA sequence, structure, and evolution. However, challenges persist with spectral representations of variable-length sequences for tasks like species classification and in interpreting these spectra to identify discriminative DNA regions.

Results: We introduce SpecGMM, a novel framework that integrates sliding window-based Spectral analysis with a Gaussian Mixture Model to transform variable-length DNA sequences into fixed-dimensional spectral representations for taxonomic classification.

Prevalence of severe and moderate anthropometric failure among children in India, 1993-2021.

Though child anthropometric failure (CAF) is a persistent problem in India, previous studies have often neglected state-level variance and aggregated moderate and severe CAF categories. This study addresses this gap by examining moderate and severe malnutrition across India's states and union territories (UTs) from 1993 to 2021. Data of children under 2 years old from five waves of National Family Health Surveys, a representative cross-sectional survey of Indian households, were analysed.

Transition of synchronization state during the quasiperiodic route to chaos in coupled friction-induced continuous oscillators.

Friction-induced vibration, particularly associated with the squealing problem in disk brake systems, has been a longstanding challenge in the automotive industry. In our research, we employed the synchronization theory to gain insights into the interaction between two coupled cantilever beams attached with tip masses. This proposed model emulates the dynamics of a mountain bike disk brake assembly.

Breeding and biotechnology approaches to enhance the nutritional quality of rapeseed byproducts for sustainable alternative protein sources- a critical review.

Global protein consumption is increasing exponentially, which requires efficient identification of potential, healthy, and simple protein sources to fulfil the demands. The existing sources of animal proteins are high in fat and low in fiber composition, which might cause serious health risks when consumed regularly. Moreover, protein production from animal sources can negatively affect the environment, as it often requires more energy and natural resources and contributes to greenhouse gas emissions.

How to mitigate selection bias in COVID-19 surveys: evidence from five national cohorts.

Non-response to surveys is a common problem; even more so during the COVID-19 pandemic with social distancing measures challenging data collection. As respondents often differ from non-respondents, this can introduce bias. The goal of the current study was to see if we can reduce bias and restore sample representativeness in a series of COVID-19 surveys embedded within five UK cohort studies by using the rich data available from previous waves of data collection.