Association of corneal endothelial cell morphology with neurodegeneration in mild cognitive impairment and dementia.

Introduction: Corneal confocal microscopy (CCM) detects neurodegeneration in mild cognitive impairment (MCI) and dementia and identifies subjects with MCI who develop dementia. This study assessed whether abnormalities in corneal endothelial cell (CEC) morphology are related to corneal nerve morphology, brain volumetry, cerebral ischemia, and cognitive impairment in MCI and dementia.

Methods: Participants with no cognitive impairment (NCI), MCI, and dementia underwent CCM to quantify corneal endothelial cell density (CECD) and area (CECA), corneal nerve fiber morphology, magnetic resonance imaging (MRI) brain volumetry, and severity of brain ischemia.

A low-cost PPG sensor-based empirical study on healthy aging based on changes in PPG morphology.

Objective: We study the changes in morphology of the photoplethysmography (PPG) signals-acquired from a select group of South Asian origin-through a low-cost PPG sensor, and correlate it with healthy aging which allows us to reliably estimate the vascular age and chronological age of a healthy person as well as the age group he/she belongs to.

Methods: Raw infrared PPG data is collected from the finger-tip of 173 appar- ently healthy subjects, aged 3-61 years, via a non-invasive low- cost MAX30102 PPG sensor. In addition, the following metadata is recorded for each subject: age, gender, height, weight, family history of cardiac disease, smoking history, vitals (heart rate and SpO2).

Data journey map: a process for co-creating data requirements for health care artificial intelligence.

The Caribbean small island developing states have limited resources for comprehensive health care provision and are facing an increasing burden of noncommunicable diseases which is driven by an aging regional population. Artificial intelligence (AI) and other digital technologies offer promise for contributing to health care efficiencies, but themselves are dependent on the availability and accessibility of accurate health care data. A regional shortfall in data professionals continues to hamper legislative recognition and promotion of increased data production in Caribbean countries.

Aligning practitioner's perception: Empowering MAST framework for evaluating telemedicine services.

Objective: Telemedicine is a digital substitute for in-person healthcare service delivery systems that has gained popularity amid the global COVID-19 pandemic. The objective of this study was to evaluate telemedicine compatibility from the perspective of healthcare practitioners to enhance the effectiveness and spectrum of the Model for Assessment of Telemedicine.

Method: Primary and Secondary Healthcare and King Edward Medical University extended their respective telemedicine services in 2020 where 24,516 patients were benefited from the telemedicine services provided by 1273 doctors from different specializations.

Assessment of the air pollutants on automobiles emission dispersion: the effects of barrier height and the road surface temperature.

In the paper, a mathematical model was constructed that describes the specifications of the wind flow and the dispersion of pollutants, taking into account the variable temperature on the roadway surface, which varies depending on the time for some quarter of the city of Almaty. The impact of the traffic tidal flow was studied based on the data of measuring passing vehicles as a source of pollution by the CFD and on the spatial distribution of pollutants for various types of pollution. A test problem was performed to validate the numerical algorithm and the mathematical model.

Boruta-driven analysis of telehealth amalgamation across healthcare stratifications with diffuse-dual-channel and tiered-gatekeeper systems.

This study aimed to evaluate the adaptation and effectiveness of telemedicine with the diffuse-dual-channel system (DDS) and tiered-gatekeeper system (TGS) across different tiers of the healthcare system on technical-organizational-environmental (TOE) framework. The telemedicine services were extended as Tiered-gatekeeper system (TGS) by Primary and Secondary Healthcare (PSHC) and Diffuse-dual-channel system (DDS) by King Edward Medical University (KEMU) in 2020 benefiting 2605 and 21,905 patients, respectively. This cross-sectional survey is based on a structured questionnaire conducted on 172 healthcare practitioners (HCP) from KEMU and 76 from PSHC selected by purposive sampling and analysis is conducted through descriptive analysis and the Boruta features selection method.

Pinhole small-angle neutron scattering based approach for desmearing slit ultra-small-angle neutron scattering data.

Presented here is an effective approach to desmearing slit ultra-small-angle neutron scattering (USANS) data, based on complementary small-angle neutron scattering (SANS) measurements, leading to a seamless merging of these data sets. The study focuses on the methodological aspects of desmearing USANS data, which can then be presented in the conventional manner of SANS, enabling a broader pool of data analysis methods. The key innovation lies in the use of smeared SANS data for extrapolating slit USANS, offering a self-consistent integrand function for desmearing with Lake's iterative method.

Fluid-Infiltrated Metalens-Driven Reconfigurable Intelligent Surfaces for Optical Wireless Communications.

A reconfigurable intelligent surface (RIS), a leading-edge technology, represents a new paradigm for adaptive control of electromagnetic waves between a source and a user. While RIS technology has proven effective in manipulating radio frequency waves using passive elements such as diodes and MEMS, its application in the optical domain is challenging. The main difficulty lies in meeting key performance indicators, with the most critical being accurate and self-adjusting positioning.

Computational imaging for rapid detection of grade-I cerebral small vessel disease (cSVD).

An early identification and subsequent management of cerebral small vessel disease (cSVD) grade 1 can delay progression into grades II and III. Machine learning algorithms have shown considerable promise in medical image interpretation automation. An experimental cross-sectional study aimed to develop an automated computer-aided diagnostic system based on AI (artificial intelligence) tools to detect grade 1-cSVD with improved accuracy.

Transparent RFID tag wall enabled by artificial intelligence for assisted living.

Current approaches to activity-assisted living (AAL) are complex, expensive, and intrusive, which reduces their practicality and end user acceptance. However, emerging technologies such as artificial intelligence and wireless communications offer new opportunities to enhance AAL systems. These improvements could potentially lower healthcare costs and reduce hospitalisations by enabling more effective identification, monitoring, and localisation of hazardous activities, ensuring rapid response to emergencies.

Bobcat Optimization Algorithm: an effective bio-inspired metaheuristic algorithm for solving supply chain optimization problems.

Supply chain efficiency is a major challenge in today's business environment, where efficient resource allocation and coordination of activities are essential for competitive advantage. Traditional efficiency strategies often struggle for resources for the complex and dynamic network. In response, bio-inspired metaheuristic algorithms have emerged as powerful tools to solve these optimization problems.

SATS: simplification aware text summarization of scientific documents.

Simplifying summaries of scholarly publications has been a popular method for conveying scientific discoveries to a broader audience. While text summarization aims to shorten long documents, simplification seeks to reduce the complexity of a document. To accomplish these tasks collectively, there is a need to develop machine learning methods to shorten and simplify longer texts.

The Parasite-Derived Peptide, FhHDM-1, Selectively Modulates miRNA Expression in -Cells to Prevent Apoptotic Pathways Induced by Proinflammatory Cytokines.

We have previously identified a parasite-derived peptide, FhHDM-1, that prevented the progression of diabetes in nonobese diabetic (NOD) mice. Disease prevention was mediated by the activation of the PI3K/Akt pathway to promote -cell survival and metabolism without inducing proliferation. To determine the molecular mechanisms driving the antidiabetogenic effects of FhHDM-1, miRNA:mRNA interactions and predictions of the gene networks were characterised in -cells, which were exposed to the proinflammatory cytokines that mediate -cell destruction in Type 1 diabetes (T1D), in the presence and absence of FhHDM-1.

Fluid-responsive tunable metasurfaces for high-fidelity optical wireless communication.

Optical wireless communication (OWC), with its blazing data transfer speed and unparalleled security, is a futuristic technology for wireless connectivity. Despite the significant advancements in OWC, the realization of tunable devices for on-demand and versatile connectivity still needs to be explored. This presents a considerable limitation in utilizing adaptive technologies to improve signal directivity and optimize data transfer.

The real-time hand and object recognition for virtual interaction.

Recognizing hand-object interactions presents a significant challenge in computer vision. It arises due to the varying nature of hand-object interactions. Moreover, estimating the 3D position of a hand from a single frame can be problematic, especially when the hand obstructs the view of the object from the observer's perspective.

Capture rates of increase following white-nose syndrome across the eastern US.

Emerging infectious diseases threaten wildlife globally. While the effects of infectious diseases on hosts with severe infections and high mortality rates often receive considerable attention, effects on hosts that persist despite infection are less frequently studied. To understand how persisting host populations change in the face of disease, we quantified changes to the capture rates of (big brown bats), a persisting species susceptible to infection by the invasive fungal pathogen (; causative agent for white-nose syndrome), across the eastern US using a 30-year dataset.

Harnessing Green Electricity from Food: A Split Black Gram-Based Triboelectric Nanogenerator for a Self-Powered Autonomous Lighting System and Portable Electronics.

Triboelectric nanogenerators (TENGs) represent a promising solution to mounting environmental concerns associated with battery disposal amid the escalating demand for portable electronics. However, prevailing TENG fabrication predominantly relies on nonbiodegradable, nonbiocompatible, and synthetic materials, posing a grave ecological threat. To mitigate this, there is a pressing need to develop eco-friendly and green TENGs leveraging sustainable, naturally occurring materials.

Co-creation of a digital platform for peer support in a community of adolescent and young adult patients during and after cancer.

Purpose: Adolescents and young adults (AYAs) diagnosed with cancer report psychological challenges and social isolation. Peer support has been shown to be a valuable resource for coping with these experiences. The aim of this study was through co-creation map the needs for peer support among AYA cancer patients in Sweden; and building on these results to develop and test a prototype of a digital tool for peer support.

A review of social background profiling of speakers from speech accents.

Social background profiling of speakers is heavily used in areas, such as, speech forensics, and tuning speech recognition for accuracy improvement. This article provides a survey of recent research in speaker background profiling in terms of accent classification and analyses the datasets, speech features, and classification models used for the classification tasks. The aim is to provide a comprehensive overview of recent research related to speaker background profiling and to present a comparative analysis of the achieved performance measures.

Multi-model deep learning approach for segmentation of teeth and periapical lesions on pantomographs.

Introduction: The fields of medicine and dentistry are beginning to integrate artificial intelligence (AI) in diagnostics. This may reduce subjectivity and improve the accuracy of diagnoses and treatment planning. Current evidence on pathosis detection on pantomographs (PGs) indicates the presence or absence of disease in the entire radiographic image, with little evidence of the relation of periapical pathosis to the causative tooth.

A numerical approach to optimize the performance of HTL-free carbon electrode-based perovskite solar cells using organic ETLs.

Carbon electrode-based perovskite solar cells (c-PSCs) without a hole transport layer (HTL) have obtained a significant interest owing to their cost-effective, stable, and simplified structure. However, their application is limited by low efficiency and the prevalence of high-temperature processed electron transport layer (ETL), e.g.