Distress and coping mechanisms among people with diabetes: cross-sectional assessment from an NCD screening clinic of a tertiary care hospital in North India.

Background: Of the numerous complications encountered by people with diabetes (PWD), the effect on mental health is concerning. Within mental health, diabetes distress (DD) occurs when a patient has unfavourable emotional stress while managing their condition, which can be managed by coping strategies but are less studied together in Indian settings. So, the present study aimed to determine the proportion of DD and associated factors and coping skills among the PWD.

Non-thermal atmospheric plasma treatments enhance the growth, photosynthesis, metabolite accumulation, and nutritional value of geranium (Pelargonium graveolens L'Herit) leaves.

This study investigated the effects of non-thermal atmospheric plasma (NTAP) treatment on the growth, chemical composition, and biological activity of geranium (Pelargonium graveolens L'Herit) leaves. NTAP was applied at a frequency of 13.56 MHz, exposure time of 15 s, discharge temperature of 25 °C, and power levels (T1 = 50, T2 = 80, and T3 = 120 W).

Application of artificial intelligence in nursing practice: a qualitative study of Jordanian nurses' perspectives.

Background: Artificial Intelligence (AI) is increasingly applied in healthcare to boost productivity, reduce administrative workloads, and improve patient outcomes. In nursing, AI offers both opportunities and challenges. This study explores nurses' perspectives on implementing AI in nursing practice within the context of Jordan, focusing on the perceived benefits and concerns related to its integration.

Foliar application of nano biochar solution elevates tomato productivity by counteracting the effect of salt stress insights into morphological physiological and biochemical indices.

Nano-biochar considers a versatile and valuable sorbent to enhance plant productivity by improving soil environment and emerged as a novel solution for environmental remediation and sustainable agriculture in modern era. In this study, roles of foliar applied nanobiochar colloidal solution (NBS) on salt stressed tomato plants were investigated. For this purpose, NBS was applied (0%, 1% 3% and 5%) on two groups of plants (control 0 mM and salt stress 60 mM).

Controlling the energies of the single-rotor large wind turbine system using a new controller.

In wind energy generation systems, ensuring high energy quality is critical but is often compromised due to the limited performance and durability of conventional regulators. To address this, this work presents a novel controller for managing the machine-side inverter of a single-rotor large wind turbine system using an induction machine-type generator. The proposed controller is designed using proportional, integral, and derivative error-based mechanisms, which fundamentally differ from traditional proportional-integral (PI) regulators.

Leveraging two-dimensional pre-trained vision transformers for three-dimensional model generation via masked autoencoders.

Although the Transformer architecture has established itself as the industry standard for jobs involving natural language processing, it still has few uses in computer vision. In vision, attention is used in conjunction with convolutional networks or to replace individual convolutional network elements while preserving the overall network design. Differences between the two domains, such as significant variations in the scale of visual things and the higher granularity of pixels in images compared to words in the text, make it difficult to transfer Transformer from language to vision.

A quantum-optimized approach for breast cancer detection using SqueezeNet-SVM.

Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.

Efficient diagnosis of diabetes mellitus using an improved ensemble method.

Diabetes is a growing health concern in developing countries, causing considerable mortality rates. While machine learning (ML) approaches have been widely used to improve early detection and treatment, several studies have shown low classification accuracies due to overfitting, underfitting, and data noise. This research employs parallel and sequential ensemble ML approaches paired with feature selection techniques to boost classification accuracy.

Enhanced optical properties of chitosan polymer doped with orange peel dye investigated via UV-Vis and FTIR analysis.

The current research aims to determine the impact of orange peel dye (OPD), an eco-friendly addition, on the optical properties of biodegradable polymers. This study investigates the enhancement of optical properties in solid electrolytes based on chitosan (CS) and glycerol, with varying OPD concentrations. UV-Vis-NIR spectroscopy revealed significantly enhanced UV-visible light absorption in the 200-500 nm region and effective UV light blocking.

Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.

The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt.

Effects of Electronic Cigarettes on Periodontal Health: A Systematic Review and Meta-Analysis.

Objectives: The use of electronic cigarettes "e-cigarettes," or vaping is growing in popularity, especially among adolescents and young adults. While the effects of cigarette smoking on oral health are well-established, the exact impact that e-cigarettes may have on dental tissues is still uncertain. The aim of the current review was to summarize evidence related to the effect of vaping on the periodontal health status of e-cigarette users.

Global insight into rare disease and orphan drug definitions: a systematic literature review.

Objectives: This study sheds light on the available global definitions, classifications, and criteria used for rare diseases (RDs), ultrarare diseases (URDs), orphan drugs (ODs) and ultraorphan drugs (UODs) and provides insights into the rationale behind these definitions.

Design: A systematic literature review was conducted to identify existing definitions and the criteria used to define RDs, ODs and their subtypes.

Data Sources: Searches were performed in the PubMed/Medline, Embase, Scopus and Web of Science (Science and Social Sciences Citation Index) databases covering articles published from 1985 to 2021.

The incidence, clinical features, microbiology, and visual outcomes of endophthalmitis associated with glaucoma surgery in children.

Purpose To study the incidence, clinical features, microbiology, and visual outcome of endophthalmitis associated with glaucoma surgery in children at a tertiary care eye hospital in Saudi Arabia. Methods The medical records of patients <18 years of age who presented with endophthalmitis following glaucoma surgery between January 2008 and October 2018 were reviewed retrospectively. Results Endophthalmitis after glaucoma surgery was observed in 20 eyes, or 18 out of 853 eyes that underwent glaucoma surgery at our institution (2.

Discontinuous named entities in clinical Text: A systematic literature review.

Objective: Extracting named entities from clinical free-text presents unique challenges, particularly when dealing with discontinuous entities-mentions that are separated by unrelated words. Traditional NER methods often struggle to accurately identify these entities, prompting the development of specialised computational solutions. This paper systematically reviews and presents the methodologies developed for Discontinuous Named Entity Recognition in clinical texts, highlighting their effectiveness and the challenges they face.

Decoding the SARS-CoV-2 Infection Process: Insights into Origin, Spread, and Therapeutic Approaches.

Globally, over 768 million confirmed cases and 6.9 million deaths had been documented as of July 17, 2023. Coronaviruses have a relatively large RNA genome.

Carcinoma in a male accessory breast; Case report with literature review.

Introduction And Importance: Accessory breast is a rare condition where regression of the mammary ridge fails. This ectopic breast can function as the same pectoral breast and respond to hormonal effects. Furthermore, in rare cases, it can develop into malignancy.

Okra seed polysaccharides mitigate neuroinflammation and cognitive impairment via modulation of Nrf2/HO-1, HMGB1/RAGE/TLR4/NF-κB, NLRP3/Caspase-1, JAK-2/STAT-3, AMPK/SIRT1/m-TOR, PI3K/AKT/CREB/BDNF/TrkB and PERK/CHOP/Bcl-2 axes.

Global healthcare systems are under tremendous strain due to the increasing prevalence of neurodegenerative disorders. Growing data suggested that overconsumption of high-fat/high-carbohydrates diet (HFHCD) is associated with enhanced incidence of metabolic alterations, neurodegeneration, and cognitive dysfunction. Functional foods have gained prominence in curbing metabolic and neurological deficits.

Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmentation, yet misdiagnoses yield effective medical responses, impacting patient survival rates. Recent technological advancements have popularized deep learning-based medical image analysis, leveraging transfer learning to reuse pre-trained models for various applications.

Predicting land use and land cover changes for sustainable land management using CA-Markov modelling and GIS techniques.

This study addresses the significant issue of rapid land use and land cover (LULC) changes in Lahore District, which is critical for supporting ecological management and sustainable land-use planning. Understanding these changes is crucial for mitigating adverse environmental impacts and promoting sustainable development. The main goal is to evaluate historical LULC changes from 1994 to 2024 and forecast future trends for 2034 and 2044 utilizing the CA-Markov hybrid model combined with GIS methodologies.

Balloon-assisted placement of rib graft in endoscopic posterior cricoid split; a new technique.

Objective: This study aims to compare the outcomes of balloon-assisted rib graft placement with traditional graft placement in Endoscopic Posterior Cricoid Split with Rib Graft Placement (EPCS/RG).

Methods: We conducted a retrospective analysis of 23 patients who underwent EPCS/RG by a single senior surgeon at King Saud University Medical City from 2017 to 2024. Data were collected on demographics, surgical approach, and operative time.

A high-speed MPPT based horse herd optimization algorithm with dynamic linear active disturbance rejection control for PV battery charging system.

This study first proposes an innovative method for optimizing the maximum power extraction from photovoltaic (PV) systems during dynamic and static environmental conditions (DSEC) by applying the horse herd optimization algorithm (HHOA). The HHOA is a bio-inspired technique that mimics the motion cycles of an entire herd of horses. Next, the linear active disturbance rejection control (LADRC) was applied to monitor the HHOA's reference voltage output.

Solvent-dripping modulated 3D/2D heterostructures for high-performance perovskite solar cells.

The controlled growth of two-dimensional (2D) perovskite atop three-dimensional (3D) perovskite films reduces interfacial recombination and impedes ion migration, thus improving the performance and stability of perovskite solar cells (PSCs). Unfortunately, the random orientation of the spontaneously formed 2D phase atop the pre-deposited 3D perovskite film can deteriorate charge extraction owing to energetic disorder, limiting the maximum attainable efficiency and long-term stability of the PSCs. Here, we introduce a meta-amidinopyridine ligand and the solvent post-dripping step to generate a highly ordered 2D perovskite phase on the surface of a 3D perovskite film.

Advanced technologies in InGaN micro-LED fabrication to mitigate the sidewall effect.

The size of InGaN micro-LEDs is continuously decreasing to meet the demands of various emerging applications, especially in tiny micro-displays such as AR/VR. However, the conventional pixel definition based on plasma etching significantly damages the mesa sidewalls, leading to a severe reduction in efficiency as the micro-LED size decreases. This seriously impedes the development and application of micro-LEDs.

Synthesis of chitosan and carboxymethyl cellulose connect flavonoid (CH-Fla-CMC) composite and their investigation of antioxidant, cytotoxicity activities.

This study successfully synthesised and characterised composites combining chitosan (CH), carboxymethyl cellulose (CMC), and various flavonoids (Fla). This innovative approach demonstrates the potential for developing functional materials with antioxidant and food preservation properties. The composites CH-Fla-CMC (1-5) was characterised using advanced techniques such as FT-IR, UV-Vis, XRD, SEM, TEM, and TGA, providing robust data on their structural, morphological, and thermal properties.