SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification.

Waste management handles all kinds of waste, including household, industrial, municipal, organic, biomedical, biological, and radioactive wastes. People still face challenges in proper disposal methods for different types of waste, including landfill-bound items, recyclable materials, and biodegradable waste. Inadequate waste management poses a significant and multifaceted global challenge.

Defatted Wheat Germ Protein-Derived Peptides Showed Multiple Biological Activities from the Stomach to Small Intestine: In Silico and In Vitro Approaches.

This study aimed to test the hypothesis that bioactive peptides can exert multiple bioactivities at different sites in the gastrointestinal tract. Our previous research identified 33 gastric-resistant peptides derived from wheat germ with potential antiadhesive activity against in the stomach. In this work, in silico digestion of these peptides with trypsin, thermolysin, and chymotrypsin produced 67 peptide fragments.

Prevalence and Characteristics of Influenza Cases From 2017 to 2019 at a Tertiary Care Teaching Hospital in Karnataka.

Introduction Influenza virus is a significant human pathogen causing severe acute respiratory illness (SARI) associated with significant mortality worldwide. The H1N1 Influenza virus that caused a pandemic in 2009 continued to cause periodic epidemics worldwide, with new variants posing significant public health problems. The present study was carried out to determine the prevalence and characteristics of influenza at a tertiary care teaching hospital.

Clinical and pathological correlation of P expression in oral cancers.

In our study, we aimed to evaluate the overexpression of P in 155 oral squamous cell carcinomas and to correlate with various clinicopathological features like depth of invasion, lymph nodal involvement, and margin status, which affect the local recurrence and prognosis. This cross-sectional study included 155 oral squamous cell carcinoma patients who underwent surgical resection of primary and nodal disease. The histopathological and clinical features were noted.

Prediction of Total Soluble Solids and pH of Strawberry Fruits Using RGB, HSV and HSL Colour Spaces and Machine Learning Models.

Determination of internal qualities such as total soluble solids (TSS) and pH is a paramount concern in strawberry cultivation. Therefore, the main objective of the current study was to develop a non-destructive approach with machine learning algorithms for predicting TSS and pH of strawberries. Six hundred samples (100 samples in each ripening stage) in six ripening stages were collected randomly for measuring the biometrical characteristics, i.