Physico-chemical characteristics of fresh faecal matter from a residential apartment: a short-term study conducted at Thiruvananthapuram, Kerala, India.

The study presents findings from physico-chemical and elemental analyses of fresh faecal matter from a residential apartment in Thiruvananthapuram, Kerala, India. Samples were taken every 8-10 days over 4 months to account for variability and establish baseline data. The study also examines the influence of dietary patterns and toilet cleaners on faecal sludge properties.

Designing a summative assessment blueprint in community medicine: an expert consensus approach at All India Institute of Medical Sciences.

Background: Despite the increasing integration of competency-based education in medicine, there remains a significant gap in effectively assessing educational outcomes, underscoring the urgent need for designed assessment blueprints that accurately reflect both curriculum content and competency standards in Community Medicine for undergraduate students. This study, conducted across the All-India Institute of Medical Sciences (AIIMS) network, develops a summative assessment blueprint aimed at standardizing evaluations in medical education across diverse geographic locations in India.

Methods: Twenty-five experts from 10 All India Institutes of Medical Science were invited via email and contributed for summative assessment for a theory paper.

Topology synthesis of coupled inductor based four port DC-DC converter for multi-input PV-battery application with autonomous mode selection.

Multiport converters are the most reliable and integral component for latest renewable source integration with multiple inputs. This article is one among the kind, which proposes a novel Coupled Inductor based Four Port topology Multiport Converter (CI-FP-MPC) for integrating multiple PV sources with different voltages. The adoption of coupled inductor contributes an increased voltage gain with reduced stress on the switches and diodes.

Innovative modified-net architecture: enhanced segmentation of deep vein thrombosis.

A new era for diagnosing and treating Deep Vein Thrombosis (DVT) relies on precise segmentation from medical images. Our research introduces a novel algorithm, the Modified-Net architecture, which integrates a broad spectrum of architectural components tailored to detect the intricate patterns and variances in DVT imaging data. Our work integrates advanced components such as dilated convolutions for larger receptive fields, spatial pyramid pooling for context, residual and inception blocks for multiscale feature extraction, and attention mechanisms for highlighting key features.