Numerical and experimental methods for the assessment of a human finger-inspired soft pneumatic actuator for gripping applications.

The increasing demand for soft robotic systems in agricultural, biomedical and other applications has driven the development of actuators that can mimic the flexibility and adaptability of human muscles. Several studies have explored the design and implementation of soft actuators for robotic applications, however, there is a need for soft actuators demonstrating delicate gripping capabilities but also excel in specific biomedical applications, such as therapeutic massaging. The objective of this work is to develop a multi-finger soft pneumatic actuator mimicking human fingers for Ayurvedic therapeutic massaging and gripping applications.

Incremental cost of treating antimicrobial-resistant infections among hospitalised patients in India: a cohort study.

Background: Accurate estimates of incremental cost (IC) attributable to antimicrobial resistance (AMR) provide information of immense public health importance to the policy makers. Here, we present the IC from patient perspective for treating antimicrobial-resistant pathogens in India.

Methods: This cohort study was conducted in eight hospitals including government (GH), private (PH) and trust hospitals (TH), considering their ownership, geographical location and categories of cities.

Deciphering stakeholder voice on the challenges of transformative healthcare 5.0 ecosystem: a quality function deployment analyses.

Purpose: The healthcare ecosystem continues to evolve with new technological developments with the support of its stakeholders. The technology-driven and patient-centric Healthcare 5.0 (H5.

Species identification for Indian seafood markets: A machine learning approach with a fish dataset.

The Indian sea fish market is a dynamic and significant sector, contributing to both the domestic economy and the global seafood trade. This fish dataset is specifically curated for machine learning applications in the Indian seafood industry. It includes a comprehensive collection of images representing eight commercially significant fish species native to Indian waters, comprising a total of 8488 images.

Partially observable Markov models inferred using statistical tests reveal context-dependent syllable transitions in Bengalese finch songs.

Generative models have diverse applications, including language processing and birdsong analysis. In this study, we demonstrate how a statistical test, designed to prevent overgeneralization in sequence generation, can be used to infer minimal models for the syllable sequences in Bengalese finch songs. We focus on the partially observable Markov model (POMM), which consists of states and the probabilistic transitions between them.

Unraveling the Relationship Between Vitamin D and Noncommunicable Diseases: A Systemic Review and Meta-Analysis.

Background: Subclinical vitamin D insufficiency is frequent in both developing and developed countries. Even after rickets was eliminated in the 1930s by fortifying milk, up to 1 billion people worldwide suffer from subclinical vitamin D deficiency (VDD). Numerous noncommunicable diseases (NCDs), including depression, autoimmune illnesses, diabetes, osteoporosis, and cardiovascular disease, are linked to this deficiency.

From diagnosis to therapy: The role of LncRNA GAS5 in combatting some cancers affecting women.

Long non-coding RNAs (lncRNAs) are a collection of non-coding RNA molecules that consist of more than 200 nucleotides. In human malignancies, these lncRNAs exhibit abnormal expression patterns and play a significant role in either suppressing or promoting tumor growth. They achieve this by modulating various functions and mechanisms within cancer cells, including proliferation, invasion, metastasis, apoptosis, and resistance to different therapeutic approaches.

From Micro to Macro: Understanding the Far-Reaching Consequences of B12 Deficiency on Women's Health.

Background: Vitamin B12 (B12), playing the role of a coenzyme in one-carbon metabolism, is an important vitamin necessary for human health.

Objectives: To systematically review evidence to identify the complications of B12 deficiency among women.

Methods: We conducted a systematic search of quantitative studies on disorders associated with B12 deficiency among women, published in English in the last 25 years (1999-2024), using electronic databases such as Scopus, Web of science, CINAHL, PubMed, and Medline.

Artificial intelligence-based cardiovascular/stroke risk stratification in women affected by autoimmune disorders: a narrative survey.

Women are disproportionately affected by chronic autoimmune diseases (AD) like systemic lupus erythematosus (SLE), scleroderma, rheumatoid arthritis (RA), and Sjögren's syndrome. Traditional evaluations often underestimate the associated cardiovascular disease (CVD) and stroke risk in women having AD. Vitamin D deficiency increases susceptibility to these conditions.

An Artificial Intelligence-Based Non-Invasive Approach for Cardiovascular Disease Risk Stratification in Obstructive Sleep Apnea Patients: A Narrative Review.

Background: Obstructive sleep apnea (OSA) is a severe condition associated with numerous cardiovascular complications, including heart failure. The complex biological and morphological relationship between OSA and atherosclerotic cardiovascular disease (ASCVD) poses challenges in predicting adverse cardiovascular outcomes. While artificial intelligence (AI) has shown potential for predicting cardiovascular disease (CVD) and stroke risks in other conditions, there is a lack of detailed, bias-free, and compressed AI models for ASCVD and stroke risk stratification in OSA patients.

An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks.

Energy efficiency plays a major role in sustaining lifespan and stability of the network, being one of most critical factors in wireless sensor networks (WSNs). To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. The proposed AVOACS method improves clustering by including four critical terms: communication mode decider, distance of sink and nodes, residual energy and intra-cluster distance.

Matairesinol repolarizes M2 macrophages to M1 phenotype to induce apoptosis in triple-negative breast cancer cells.

Objective: Triple-Negative Breast Cancer (TNBC), the most challenging subtype of Breast Cancer (BC), currently lacks targeted therapy, presenting a significant therapeutic gap in its management. Tumor Associated Macrophages (TAMs) play a significant role in TNBC progression and could be targeted by repolarizing them from M2 to M1 phenotype. Matairesinol (MAT), a plant lignan, has been shown to exhibit anticancer, anti-inflammatory and immunomodulatory activities.

A 7-point evidence-based care discharge protocol for patients hospitalized for exacerbation of COPD: consensus strategy and expert recommendation.

Acute exacerbations of COPD (ECOPD) are an important event in the life of a COPD patient as it causes significant deterioration of physical, mental, and social health, hastens disease progression, increases the risk of dying and causes a huge economic loss. Preventing ECOPD is therefore one of the most important goals in the management of COPD. Before the patient is discharged after hospitalization for ECOPD, it is crucial to offer an evidence-based care bundle protocol that will help minimize the future risk of readmissions and death.

Unseen crisis: Revealing the hidden health impact of indoor air pollution-A scoping review.

Indoor air pollution presents a critical public health challenge, particularly in countries such as India, where millions are exposed to harmful pollutants within their homes and workplaces. This scoping review delves into the multifaceted impacts of indoor air pollution on health outcomes, synthesizing evidence from various study designs and geographical regions A scoping review was conducted. Drawing on a comprehensive search strategy, which yielded 320 records, wherein 120 in PubMed, 108 in Web of Science, and 92 in SCOPUS.

Effectiveness of video assisted teaching program of pranayama on selected physiological parameters among patients with COPD.

Background: According to research on the global burden of illness, chronic obstructive pulmonary disease (COPD) is expected to rank third globally in terms of cause of mortality in the first 20 years of the 20 century and fifth in terms of major cause of impairment. A thorough yoga program can enhance general well-being and respiratory function, which will improve a person's capacity to complete daily chores.

Materials And Methods: One group pretest and posttest design in a quasi-experimental study was applied.

Therapeutic potential of antibody-drug conjugates possessing bifunctional anti-inflammatory action in the pathogenies of rheumatoid arthritis.

In an age where there is a remarkable upsurge in developing precision medicines, antibody-drug conjugates (ADCs) have emerged as a progressive therapeutic strategy. ADCs typically consist of monoclonal antibodies (mAb) conjugated to the cytotoxic payloads by utilizing a linker, combining the benefits of definitive target specificity of mAbs and potent killing impact of payload to achieve precise and efficient elimination of target cells. In addition to their well-established role in oncology, ADCs are currently demonstrating encouraging potential in addressing the unmet requirements in the treatment of autoimmune conditions such as rheumatoid arthritis (RA).

Tri-Ponderal Mass Index-A reliable anthropometric index for early screening of adolescent obesity in a school-based setting: A cross-sectional study.

Objective: This study was designed to examine the reliability of the Tri-Ponderal Mass Index (TMI) for early screening of adolescent obesity compared with anthropometric measures such as hip circumference, neck circumference, waist circumference, waist-height ratio, waist-hip ratio, and body mass index.

Methods: A school-based, cross-sectional study was conducted between July and December 2019 among 1101 school-going adolescents (both sexes) aged 12 to 17 years, in Rudrapur, Uttarakhand, India. Anthropometric measurements were collected using well-calibrated equipment, and age- and sex-specific BMI percentile cutoff values recommended by the Indian Academy of Pediatrics were used to define overweight and obesity.

Multi-objective optimization of laser machining parameters for carbon-glass reinforced hybrid composites: Integrating gray relational analysis, regression, and ANN.

This research aims to improve the accuracy of cutting fiber-reinforced polymers (FRPs) utilizing CO2 laser processing techniques, with a particular focus on carbon-glass fiber-reinforced hybrid composites (CGFRP) using epoxy resin. Establishing CO laser machining as a dependable and effective process for creating superior CGFRP components is the main goal. This research intends to optimize laser machining parameters to enhance surface quality and machining efficiency for these composites by a thorough parametric analysis.

Assessing the efficacy of mind mapping as a learning technique to enhance information retrieval in nursing students.

Background: Nursing education, rooted in conventional methods like didactic lectures and clinical experiences, is evolving to incorporate innovative learning strategies. This study delves into the effectiveness of mind mapping, an interactive technique, in enhancing information retrieval skills among nursing students. Departing from linear note-taking, mind maps visually organize information, aligning with contemporary learning theories emphasizing visual and interactive modalities.

Comparison of Taxonomic Resolutions of Various Typing Methods for and Species Isolated from Landfill Leachate.

Anaerobic bacteria and methanogenic archaea at municipal landfill dumping sites play a vital role in the landfill ecology, waste degradation, global warming and climate change. Although landfill works as a cheap way of solid waste management, unmanaged landfill plays a significant role in spreading pollutants and pathogens in natural ecosystems. The genera and are important groups of anaerobic microbes from a public and environmental health perspective.

Automated crack localization for road safety using contextual u-net with spatial-channel feature integration.

Accurate and timely crack localization is crucial for road safety and maintenance, but image processing and hand-crafted feature engineering methods, often fail to distinguish cracks from background noise under diverse lighting and surface conditions. This paper proposes a framework utilizing contextual U-Net deep learning model to automatically localize cracks in road images. The framework design considers crack localization as a task of pixel-level segmenting, and analyzing each pixel in a road image to determine if it belongs to a crack or not.

Artificial intelligence and machine learning approaches in cerebral palsy diagnosis, prognosis, and management: a comprehensive review.

Cerebral palsy (CP) is a group of disorders that alters patients' muscle coordination, posture, and movement, resulting in a wide range of deformities. Cerebral palsy can be caused by various factors, both prenatal and postnatal, such as infections or injuries that damage different parts of the brain. As brain plasticity is more prevalent during childhood, early detection can help take the necessary course of management and treatments that would significantly benefit patients by improving their quality of life.