Visual detection of Mycobacterium tuberculosis in exhaled breath using N95 enrichment respirator, RPA, and lateral flow assay.

Tuberculosis (TB) is the second deadliest infectious disease worldwide. Current TB diagnostics utilize sputum samples, which are difficult to obtain, and sample processing is time-consuming and difficult. This study developed an integrated diagnostic platform for the rapid visual detection of Mycobacterium tuberculosis (Mtb) in breath samples at the point-of-care (POC), especially in resource-limited settings.

Microfluidic Chip-based Enrichment and Nucleic Acid Extraction for Quantitative Detection of Mycobacterium Smegmatis in Aerosols.

Tuberculosis (TB) is ranked as the third most prevalent infectious disease globally. Early detection and treatment are crucial for effective management. Conventional diagnostic methods primarily rely on sputum samples, which present challenges in accessibility and have limited accuracy in certain populations such as children, individuals with HIV, and those with extrapulmonary TB.

Entropy-based dynamic ensemble classication algorithm for imbalanced data stream with concept drift.

Online imbalanced learning is an emerging topic that combines the challenges of class imbalance and concept drift. However, current works account for issues of class imbalance and concept drift. And only few works have considered these issues simultaneously.

A bigura-based real time sentiment analysis of new media.

Public opinion mining is an active research domain, especially the penetration of the internet and the adoption of smartphones lead to the enormous generation of data in new media. Thus generation of large amounts of data leads to the limitation of traditional machine learning techniques. Therefore, the obvious adoption of deep learning for the said data.

Spatio-temporal pattern evolution and dynamic simulation of urban ecological resilience in Guangdong Province, China.

Currently, in-depth analyses concerning the dynamic simulation of urban resilience and forecasting future development trends are lacking. To address urban vulnerability and promote regional balance and sustainable development, this study assessed the urban ecological resilience of Guangdong Province from 2000 to 2020 using the entropy weight TOPSIS method. Furthermore, we examined the spatial and temporal variations and evolution of urban ecological resilience through measures such as kernel density estimation, Theil index, and the center of gravity standard deviation ellipse.

Comprehensive financial health assessment using Advanced machine learning techniques: Evidence based on private companies listed on ChiNext.

This study develops a specific and measurable framework for assessing the financial health (FH) of privately-owned companies listed on ChiNext, aimed at identifying financially sound enterprises and helping investors avoid losses caused by financial fraud or earnings management. The research proposes and tests four hypotheses related to key financial indicators and one overarching hypothesis regarding the model's performance. Using gradient boosting machines and random forests, the model achieves high accuracy and robustness against overfitting through iterative learning.

High-altitude exposure leads to increased modularity of brain functional network with the increased occupation of attention resources in early processing of visual working memory.

Unlabelled: Working memory is a complex cognitive system that temporarily maintains purpose-relevant information during human cognition performance. Working memory performance has also been found to be sensitive to high-altitude exposure. This study used a multilevel change detection task combined with Electroencephalogram data to explore the mechanism of working memory change from high-altitude exposure.

Environmental therapy: interface design strategies for color graphics to assist navigational tasks in patients with visuospatial disorders through an analytic hierarchy process based on CIE color perception.

Introduction: Environmental therapy theory has been applied in the research of disease prevention, and the effectiveness of using color and graphic designs to assist patients with spatial orientation has been confirmed. Visual-spatial impairments are common symptoms associated with cognitive decline. However, the interaction and driving factors between these impairments and spatial color and graphic designs remain unclear.

Assessing the impact of the national revitalization plan for old revolutionary base areas on green development.

Achieving green development in Old Revolutionary Base Areas (ORBAs) is an urgent task to narrow the regional gap and promote high-quality development. Starting from the dual perspective of development and environment, this paper used the Multi-period DID model to assess the impacts of the National Revitalization Plan (NRP) for ORBAs on economic growth and environmental quality, as well as its transmission mechanism, and to explore whether the implementation of the plan can promote the covered areas to achieve green development. The results find that the implementation of NRP boosts the ORBAs to achieve green development.

FTDZOA: An Efficient and Robust FS Method with Multi-Strategy Assistance.

Feature selection (FS) is a pivotal technique in big data analytics, aimed at mitigating redundant information within datasets and optimizing computational resource utilization. This study introduces an enhanced zebra optimization algorithm (ZOA), termed FTDZOA, for superior feature dimensionality reduction. To address the challenges of ZOA, such as susceptibility to local optimal feature subsets, limited global search capabilities, and sluggish convergence when tackling FS problems, three strategies are integrated into the original ZOA to bolster its FS performance.

Applied research on the design of protective clothing based on the Kano-QFD-PUGH method.

In order to improve the user experience of protective clothing for healthcare workers and reduce the design blindness and subjectivity of developers, we propose a research methodology that combines the Kano model, QFD quality function deployment, and PUGH decision-making scheme to develop conceptual solutions for medical protective clothing design. Firstly, we use the Kano model to identify the user requirements of healthcare workers and construct a hierarchy of functional requirements for protective clothing. Secondly, we use the QFD method to weigh the protective clothing design elements, convert user requirements into design elements, establish a relationship matrix between user requirements and design elements, and generate four conceptual design solutions based on the results.

Assessment of Compliance Status and Its Determinants Among Hypertensive Patients From County Areas in Zhejiang, China: A Cross-Sectional Study.

Objectives: Compliance is crucial for patients to control and manage their high blood pressure. This study assesses the compliance levels of hypertensive patients in China and explores the factors influencing compliance.

Design: A descriptive, cross-sectional design was conducted.

Online bilateral matching methodology for anti-epidemic resources based on spatial transmission risk.

This paper focuses on the online anti-epidemic resource allocation between demanders and suppliers considering the epidemic spatial spread. The spatial crowdsourcing with sharing platform is an effective way for anti-epidemic resource allocation, and a reasonable online matching strategy can improve the efficiency of resource utilization. The paper proposes online matching heuristic strategy (HSTRF-LRLUF strategy) and designs an online batch bilateral matching algorithm for anti-epidemic resources, which considers the impact of grid spatial aggregation and diffusion risk of emerging infectious diseases.

Relationship between loneliness and post-traumatic growth in patients with gynecologic malignancies: the mediating role of self-disclosure and psychological resilience.

Background: To explore the relationship between loneliness and post-traumatic growth, with a focus on the mediating role of psychological resilience and self-disclosure.

Methods: This study was a cross-sectional survey using the Loneliness Scale for Cancer Patients, the Distress Expression Index Scale (for measuring self-disclosure), the Psychological Resilience Scale, and the Posttraumatic Growth Scale on 215 inpatients with gynecologic malignancies at a tertiary care hospital in Guangzhou. Subsequently, Correlation, regression, and mediation analyses were performed using SPSS to test the relationships between the variables.

Image segmentation for pest detection of crop leaves by improvement of regional convolutional neural network.

Pest detection is important for crop cultivation. Crop leaf is the main place of pest invasion. Current technologies to detect crop pests have constraints, such as low efficiency, storage demands and limited precision.

The prediction of urban growth boundary based on the ANN-CA model: An application to Guangzhou.

Urban growth boundary (UGB) delineation is critical not only for China's urban planning policies, such as the "three control lines" of the Ministry of Natural Resources, but also for addressing global challenges related to sustainable urban development. This study contributes to the international discourse on urban growth management by developing an innovative artificial neural network-cellular automata (ANN-CA) model, tailored for cities experiencing rapid expansion. Using Guangzhou as a case study, we constructed an impact factor model that incorporates a wide range of factors, including urban spatial terrain, natural environment, current urban land classification, and industrial and economic conditions, along with the layout of modern service networks.

Downregulation of chemokine (C‑C motif) ligand 5 induced by a novel 8‑hydroxyquinoline derivative (91b1) suppresses tumor invasiveness in esophageal carcinoma.

Esophageal squamous cell carcinoma (ESCC) is a particularly aggressive form of cancer with high mortality. In the present study, a novel 8‑hydroxyquinoline derivative (91b1) was investigated for its anticancer activities in ESCC along with its associated mechanisms. The cytotoxic effect of 91b1 were evaluated across five ESCC cell lines using MTS assay, with cisplatin serving as a comparative standard.

From Clicks to Calm: Investigating the Link Between Mindfulness and Digital Hoarding Behavior Among Chinese Youth.

Background: Digital hoarding refers to the continuous acquisition of digital content and the difficulty in disposing of it. This behavior is increasingly common among today's youth. This study aims to explore the impact of mindfulness on digital hoarding behavior, investigating self-control as a mediator and upward social comparison via social media as a moderator.

The impact of teachers' emotional support on EFL learners' online learning engagement: The role of enjoyment and boredom.

Learning engagement is acknowledged as a vital proxy for evaluating the quality of online education, and teachers' emotional support, as an essential component of social support within the educational environment, positively influences learners' online learning engagement. The present study draws on Person-environment Interaction Model and Broaden-and-Build Theory to investigate the effect of teachers' emotional support on online learning engagement for English as a Foreign Language (EFL) learners and the mediating roles of academic emotions, specifically enjoyment and boredom. A questionnaire survey was conducted among 411 Chinese college EFL learners who were selected through convenience sampling.

Controlling shareholders' share pledge and share repurchase notices of listed companies.

States encourage listed companies to use stock repurchase to elevate the market value of listed firms. After China's promulgation of the new Company Law in 2018, the number of listed companies that issued stock repurchase notices has increased, and the frequency is also increasing. But whether market value management is the real incentive for the action remains debatable.

Fluorescent and colorimetric dual-readout platform for tuberculosis point-of-care detection based on dual signal amplification strategy and quantum dot nanoprobe.

Rapid and accurate diagnosis of tuberculosis (TB) is of great significance to control the spread of this devastating infectious disease. In this work, a sensitive and low-cost point-of-care testing (POCT) detection platform for TB was developed based on recombinase polymerase amplification (RPA)-catalytic hairpin assembly (CHA)-assisted dual signal amplification strategy. This platform could achieve homogeneous fluorescent and visual diagnosis of TB by using CdTe quantum dots (QDs) signal reporter.

Mitigate cross-market competition caused by the risk of uncertainty and improve firm performance through business intelligence.

In the face of various risks and uncertainties including political instability, technological advancements, and natural disasters, businesses involved in cross-market activities are encountering a more competitive environment. This study investigates the relationship between competitive intensity, business intelligence, internal process efficiency, and the performance of small and medium-sized manufacturing enterprises in China. By incorporating the Technology-Organization-Environment (TOE) framework and Dynamic Capabilities Theory, a research model is developed to demonstrate that competitive intensity improves firms' performance through the utilization of business intelligence capabilities and internal process efficiency.