Integration of Conventional and Virtual Reality Approaches in Augmented Reality for Theory-Based Psychoeducational Intervention Design for Chronic Low Back Pain: Scoping Review.

Background: Psychoeducation positively influences the psychological components of chronic low back pain (CLBP) in conventional treatments. The digitalization of health care has led to the discussion of virtual reality (VR) interventions. However, CLBP treatments in VR have some limitations due to full immersion.

Developing a Machine Learning-Based Automated Patient Engagement Estimator for Telehealth: Algorithm Development and Validation Study.

Background: Patient engagement is a critical but challenging public health priority in behavioral health care. During telehealth sessions, health care providers need to rely predominantly on verbal strategies rather than typical nonverbal cues to effectively engage patients. Hence, the typical patient engagement behaviors are now different, and health care provider training on telehealth patient engagement is unavailable or quite limited.

Incorporating area-level social drivers of health in predictive algorithms using electronic health record data.

Objectives: The inclusion of social drivers of health (SDOH) into predictive algorithms of health outcomes has potential for improving algorithm interpretation, performance, generalizability, and transportability. However, there are limitations in the availability, understanding, and quality of SDOH variables, as well as a lack of guidance on how to incorporate them into algorithms when appropriate to do so. As such, few published algorithms include SDOH, and there is substantial methodological variability among those that do.

Performance analysis of image retrieval system using deep learning techniques.

The image retrieval is the process of retrieving the relevant images to the query image with minimal searching time in internet. The problem of the conventional Content-Based Image Retrieval (CBIR) system is that they produce retrieval results for either colour images or grey scale images alone. Moreover, the CBIR system is more complex which consumes more time period for producing the significant retrieval results.

The Impact of Electrophysiological Diversity on Pattern Completion in Lithium Nonresponsive Bipolar Disorder: A Computational Modeling Approach.

Introduction: Patients with bipolar disorder (BD) demonstrate episodic memory deficits, which may be hippocampal-dependent and may be attenuated in lithium responders. Induced pluripotent stem cell-derived CA3 pyramidal cell-like neurons show significant hyperexcitability in lithium-responsive BD patients, while lithium nonresponders show marked variance in hyperexcitability. We hypothesize that this variable excitability will impair episodic memory recall, as assessed by cued retrieval (pattern completion) within a computational model of the hippocampal CA3.

Molecular modeling aided design, synthesis and biological evaluation of quinazoline derivatives for the treatment of human cancer.

The quinazoline scaffold serves as a fundamental framework, demonstrating potent anti-tumor activity. Employing the pharmacophore-based scaffold hopping principle, we successfully synthesized a series of FAK/PLK1 inhibitors incorporating the quinazoline scaffold. The synthesized compounds were characterized using H NMR, C NMR, and HRMS techniques.

Deep learning-based MVIT-MLKA model for accurate classification of pancreatic lesions: a multicenter retrospective cohort study.

Background: Accurate differentiation between benign and malignant pancreatic lesions is critical for effective patient management. This study aimed to develop and validate a novel deep learning network using baseline computed tomography (CT) images to predict the classification of pancreatic lesions.

Methods: This retrospective study included 864 patients (422 men, 442 women) with confirmed histopathological results across three medical centers, forming a training cohort, internal testing cohort, and external validation cohort.

Glucocorticoids Alter Bone Microvascular Barrier via MAPK/Connexin43 Mechanisms.

Glucocorticoids (GCs) are standard-of-care treatments for inflammatory and immune disorders, and their long-term use increases the risk of osteoporosis. Although GCs decrease bone functionality, their role in bone microvasculature is incompletely understood. Herein, the study investigates the mechanisms of bone microvascular barrier function via osteoblast-endothelial interactions in response to GCs.

Hemispheric Asymmetry of Intracortical Myelin Orientation in the Mouse Auditory Cortex.

Communication sound processing in mouse AC is lateralized. Both left and right AC are highly specialised and differ in auditory stimulus representation, functional connectivity and field topography. Previous studies have highlighted intracortical functional circuits that explain hemispheric stimulus preference.

Adaptive hybrid ANFIS-PSO and ANFIS-GA approach for occupational risk prediction.

This study attempted to optimize the adaptive neuro-fuzzy inference system (ANFIS) using particle swarm optimization (PSO) and a genetic algorithm (GA) for calculating occupational risk. Numerous studies have shown that the ANFIS is a good approach for predicting engineering problems. However, it is not well investigated in the area of risk assessment.

The effect of a students led caregiving support program on depression, sleep quality and quality of life of the caregivers and patients with stroke.

Purpose: We aimed to provide care support to stroke patients and their caregivers and investigate this support's impact on the psychosocial characteristics of patients', caregivers', and volunteer students' depression, quality of life, and sleep quality.

Material/methods: Volunteer students received caregiving training and provided support to caregivers at patients' homes. Caregivers received care support through the project for four sessions, once a week.

Mediating Role of Platelet Count Increase in Unfractionated Heparin Treatment for Sepsis Patients: A Retrospective Cohort Analysis.

The role of heparin in sepsis therapy has been widely debated. The controversy surrounding heparin's use as an anticoagulant in sepsis may stem from differences in sepsis definitions, study designs, timing and dosage of drug administration, treatment duration, complications, and patient severity. In this study, we aimed to determine the optimal timing and dosage of heparin in patients with sepsis, identify specific subgroups that could benefit from heparin therapy, and explore laboratory markers to assess its efficacy.

Two complementing selection systems based on cca-trimming exonucleases as a tool to monitor, select and evaluate enzymatic features of tRNA nucleotidyltransferases.

tRNA nucleotidyltransferase represents a ubiquitous and essential activity that adds the indispensable CCA triplet to the 3'-end of tRNAs. To fulfill this function, the enzyme contains a set of highly conserved motifs whose coordinated interplay is crucial for the sequence-specific CCA polymerization. In the human enzyme, alterations within these regions have been shown to lead to the manifestation of disease.

Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI.

A growing number of covariate modeling methods have been proposed in the field of popPK modeling, but limited information exists on how they all compare. The objective of this study was to perform a systematic review of all popPK covariate modeling methods, focusing on assessing the existing knowledge on their performances. For each method of each article included in this review, evaluation setting, performance metrics along with their associated values, and relative computational times were reported when available.

Geometric Study and Clinical Case Series for Mandible Reconstruction With a Single-Piece Scapular Free Flap.

Background: Virtual surgical planning (VSP) with simple cutting templates could help surgeons preoperatively plan scapula reconstructions in the vertical and horizontal orientations.

Methods: Virtually, eight defects were created in ten healthy mandibles and reconstructed with the subject-specific scapula vertically and horizontally. In the clinical series, 15 single-piece scapula mandible reconstructions planned with in-house VSP and guided with simple templates were compared with 15 freehand reconstructions.

Building for speech: designing the next-generation of social robots for audio interaction.

There have been significant advances in robotics, conversational AI, and spoken dialogue systems (SDSs) over the past few years, but we still do not find social robots in public spaces such as train stations, shopping malls, or hospital waiting rooms. In this paper, we argue that early-stage collaboration between robot designers and SDS researchers is crucial for creating social robots that can legitimately be used in real-world environments. We draw from our experiences running experiments with social robots, and the surrounding literature, to highlight recurring issues.

EzSkiROS: enhancing robot skill composition with embedded DSL for early error detection.

When developing general-purpose robot software components, we often lack complete knowledge of the specific contexts in which they will be executed. This limits our ability to make predictions, including our ability to detect program bugs statically. Since running a robot is an expensive task, finding errors at runtime can prolong the debugging loop or even cause safety hazards.

Exploring the pivotal variables of tongue diagnosis between patients with chronic kidney disease and health participants.

Introduction: Chronic kidney disease (CKD) is a significant global health problem associated with high morbidity and mortality rates. Traditional Chinese Medicine (TCM) utilizes tongue diagnosis to differentiate symptoms and predict prognosis. This study examines the relationship between tongue characteristics and CKD severity using an automatic tongue diagnosis system (ATDS), which captures tongue images non-invasively to provide objective diagnostic information.

HybNet: A hybrid deep models for medicinal plant species identification.

Real-time plant species detection plays an important role in fields ranging from medicine to biodiversity conservation. Images captured under unconstrained environments, scale variations, different lighting conditions, leaf orientation, complicated backdrops, and leaflet structure make plant species recognition rigorous and time-consuming. Our study addresses this challenge by introducing three pioneering hybrid models, seamlessly integrating the strengths of convolution neural networks.

Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis.

Purpose: This study employed the R software bibliometrix and the visualization tools CiteSpace and VOSviewer to conduct a bibliometric analysis of literature on lung cancer spread through air spaces (STAS) published since 2015.

Methods: On September 1, 2024, a computer-based search was performed in the Web of Science (WOS) Core Collection dataset for literature on lung cancer STAS published between January 1, 2015, and August 31, 2024. VOSviewer was used to visually analyze countries, institutions, authors, co-cited authors, and keywords, while CiteSpace was utilized to analyze institutional centrality, references, keyword bursts, and co-citation literature.

Attitudes of nurses toward telenursing and influencing factors in resource-limited settings: Northwest Ethiopia 2022.

Background: The worldwide scarcity of nurses is a pressing concern, with the World Health Organization predicting a deficit of 5.9 million nurses globally by 2025. Notably, 89% of this shortage is expected to impact low- and middle-income countries.

BananaImageBD: A comprehensive banana image dataset for classification of banana varieties and detection of ripeness stages in Bangladesh.

Bananas are among the most widely consumed fruits globally due to their appealing flavor, high nutritional value, and ease of digestion. In Bangladesh, bananas hold significant agricultural importance, being one of the most extensively cultivated fruits in terms of land coverage and ranking third in production volume. The banana image dataset presented in this article includes clear and detailed images of four common banana varieties in Bangladesh: Sagor Kola (), Shabri Kola (), Bangla Kola ( sp.

On the directional asymptotic approach in optimization theory.

As a starting point of our research, we show that, for a fixed order , each local minimizer of a rather general nonsmooth optimization problem in Euclidean spaces is either M-stationary in the classical sense (corresponding to stationarity of order 1), satisfies stationarity conditions in terms of a coderivative construction of order , or is asymptotically stationary with respect to a critical direction as well as order in a certain sense. By ruling out the latter case with a constraint qualification not stronger than directional metric subregularity, we end up with new necessary optimality conditions comprising a mixture of limiting variational tools of orders 1 and . These abstract findings are carved out for the broad class of geometric constraints and , and visualized by examples from complementarity-constrained and nonlinear semidefinite optimization.