Artificial intelligence and job performance of healthcare providers in China.

Introduction: This study explores the influence of artificial intelligence (A.I.) applications on the job performance of healthcare providers, based on data from standardised-trained residents in the First People's Hospital of Yunnan Province in China.

ncRS: A resource of non-coding RNAs in sepsis.

Sepsis, a life-threatening condition triggered by the body's response to infection, presents a significant global healthcare challenge characterized by disarrayed host responses, widespread inflammation, organ impairment, and heightened mortality rates. This study introduces the ncRS database (http://www.ncrdb.

Longitudinal analysis of quality of life in primary lung cancer patients with chlamydia pneumoniae infection: a time-to-deterioration model.

Background: Chlamydia pneumoniae (Cpn) IgG and IgA has been strongly linked to lung cancer, but its impact on patients' quality of life remains unclear. Our objective was to investigate the relationship between pre-treatment Cpn IgG and IgA and time to deterioration (TTD) of the HRQoL in patients with primary lung cancer.

Methods: A prospective hospital-based study was conducted from June 2017 to December 2018, enrolling 82 patients with primary lung cancer admitted to the First Affiliated Hospital of Fujian Medical University for questionnaire surveys.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China.

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM, PM and coarse particles (PM). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate.

Interactions of particulate matter with temperature, heat index and relative humidity on pediatric hand, foot, and mouth disease in a subtropical city.

The associations of hand, foot, and mouth disease (HFMD) with meteorological variables and particulate matter (PM) remain controversial, and limited evidence is available on heat index (HI) and coarse particulate (PM). Moreover, temperature and humidity are considered major risk factors but their interaction with PM remains unclear. We combined the distributed lag non-linear and quasi-Poisson models to estimate the non-linear and lagged associations of meteorological variables and PM with HFMD based on reported HFMD during 2015-2019 in Fuzhou, China.

Nonlinear back-end optimization method for VSLAM with multi-convex combined maximum correntropy criterion.

Back-end optimization plays a key role in eliminating the accumulated error in Visual Simultaneous Localization And Mapping (VSLAM). Existing back-end optimization methods are usually premised on the Gaussian noise assumption which does not always hold true due to the non-convex nature of the image and the fact that non-Gaussian noises are often encountered in real scenes. In view of this, we propose a back-end optimization method based on Multi-Convex combined Maximum Correntropy Criterion (MCMCC).

Fault detection for NOx emission process in thermal power plants using SIP-PCA.

With the era of big data, data-driven models are increasingly vital to just-in-time decision support in pollution emission management and planning. This article aims to evaluate the usability of the proposed data-driven model to monitor NOx emission from a coal-fired boiler process using easily measured process variables. As the emission process is highly complex, process variables interact with each other, and they cannot guarantee that all the variables in the actual operation obey the Gaussian distributions.

Visual analysis of the prevention and control measures of COVID-19 in Chinese ports.

In 2022, COVID-19 solutions in China have entered a normal stage, and the solutions imported from ports have been transformed from emergency prevention and control measures to investigative long-term prevention and control measures. Therefore, it is necessary to study solutions for COVID-19 at border ports. In this study, 170 research papers related to the prevention and control measures of COVID-19 at ports from 2020 to September 2022 were retrieved from Wanfang database, HowNet database, Wip database, and WoS core collection.

Effect of Low-Temperature Plasma Surface Treatment on Bonding Properties of Single-Lap Joint of Thermosetting Composites.

Bonding is one of the main forms of composite bonding. In order to investigate the effect of low-temperature plasma surface treatment on the bonding properties of carbon fiber-reinforced epoxy resin composites (CF/EP), a single-lap joint of CF/EP was prepared. The surface of the CF/EP was treated with atmospheric pressure "low-temperature plasma spray" equipment, and the tensile shear strength, surface morphology, surface contact angle and surface chemical composition of the CF/EP before and after plasma treatment were characterized.

ECLNet: Center localization of eye structures based on Adaptive Gaussian Ellipse Heatmap.

Accurately localizing the center of specific biological structures in medical images is of great significance for clinical treatment. The center localization task can be viewed as an estimation problem of keypoints, and the heatmap is often used to describe the probability of the location of keypoints during estimation. Existing methods construct the heatmap from a Gaussian kernel function with a fixed standard deviation, therefore cannot adapt to morphologic changes of the target region.

A cyclodextrin-based turn-off fluorescent probe for naked-eye detection of copper ions in aqueous solution.

A novel fluorescent probe L consisting of β-Cyclodextrin (β-CD) and thiosemicarbazide moieties was designed for copper ions detection. Apparent fluorescence quenching of probe L in Tris-HCl（pH = 7.4）solution was observed only in the presence of Cu, among other interfering ions.

Association between physical activity and health-related quality of life: time to deterioration model analysis in lung adenocarcinoma.

Unlabelled: BACKGROUND AND PURPOSE : Health-related quality of life (HRQoL) is a key aspect of care for cancer survivors that can be improved by physical activity. Our aim was to explore the relationship between physical activity and time to deterioration (TTD) of the HRQoL in patients with lung adenocarcinoma (LUAD).

Methods: We conducted a hospital-based prospective study.

Induced Mutation in Enhances the Performance of Soybean under Dense Planting Conditions.

CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1) is the key photomorphogenic inhibitor that has been extensively studied in higher plants. Nevertheless, its role has not been documented in the economically important soybean. Here we investigated the functions of two homologous genes, and , by analyzing and mutants with indels using CRISPR in soybean.

Construction of an immune-related lncRNA signature pair for predicting oncologic outcomes and the sensitivity of immunosuppressor in treatment of lung adenocarcinoma.

Background: Although immunotherapy has shown clinical activity in lung adenocarcinoma (LUAD), LUAD prognosis has been a perplexing problem. We aimed to construct an immune-related lncRNA pairs (IRLPs) score for LUAD and identify what immunosuppressor are appropriate for which group of people with LUAD.

Methods: Based on The Cancer Genome Atlas (TCGA)-LUAD cohort, IRLPs were identified to construct an IRLPs scoring system by Cox regression and validated in the Gene Expression Omnibus (GEO) dataset using log-rank test and the receiver operating characteristic curve (ROC).

Exploring Factors and Associate Responses for Anxiety in the Coronavirus Disease 2019 Pandemic: A Web-Based Survey in Japan.

Background And Objectives: Anxiety plays an important role in psychology. An exploration of anxiety and its associated reactions may provide insight into measures for addressing mental health problems caused by the coronavirus disease 2019 (COVID-19) pandemic. Data from this study provide potential correlational responses to anxiety.

GmCRY1s modulate gibberellin metabolism to regulate soybean shade avoidance in response to reduced blue light.

Soybean is an important legume crop that displays the classic shade avoidance syndrome (SAS), including exaggerated stem elongation, which leads to lodging and yield reduction under density farming conditions. Here, we compared the effects of two shade signals, low red light to far-red light ratio (R:FR) and low blue light (LBL), on soybean status and revealed that LBL predominantly induces excessive stem elongation. We used CRISPR-Cas9-engineered Gmcry mutants to investigate the functions of seven cryptochromes (GmCRYs) in soybean and found that the four GmCRY1s overlap in mediating LBL-induced SAS.

Effective Melanoma Recognition Using Deep Convolutional Neural Network with Covariance Discriminant Loss.

Melanoma recognition is challenging due to data imbalance and high intra-class variations and large inter-class similarity. Aiming at the issues, we propose a melanoma recognition method using deep convolutional neural network with covariance discriminant loss in dermoscopy images. Deep convolutional neural network is trained under the joint supervision of cross entropy loss and covariance discriminant loss, rectifying the model outputs and the extracted features simultaneously.

Short-term prediction of urban PM based on a hybrid modified variational mode decomposition and support vector regression model.

PM (particulate matter with a size/diameter ≤ 2.5 μm) is an important air pollutant that affects human health, especially in urban environments. However, as time-series data of PM are non-linear and non-stationary, it is difficult to predict future PM distribution and behavior.

The prevalence and influencing factors in anxiety in medical workers fighting COVID-19 in China: a cross-sectional survey.

The coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2 virus) has been sustained in China since December 2019, and has become a pandemic. The mental health of frontline medical staff is a concern. In this study, we aimed to identify the factors influencing medical worker anxiety in China during the COVID-19 outbreak.

SIP-Based Single Neuron Stochastic Predictive Control for Non-Gaussian Networked Control Systems with Uncertain Metrology Delays.

In this paper, a novel data-driven single neuron predictive control strategy is proposed for non-Gaussian networked control systems with metrology delays in the information theory framework. Firstly, survival information potential (SIP), instead of minimum entropy, is used to formulate the performance index to characterize the randomness of the considered systems, which is calculated by oversampling method. Then the minimum values can be computed by optimizing the SIP-based performance index.

Detecting complexes from edge-weighted PPI networks via genes expression analysis.

Background: Identifying complexes from PPI networks has become a key problem to elucidate protein functions and identify signal and biological processes in a cell. Proteins binding as complexes are important roles of life activity. Accurate determination of complexes in PPI networks is crucial for understanding principles of cellular organization.

An Ameliorated Prediction of Drug-Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features.

The prediction of drug-target interactions (DTIs) via computational technology plays a crucial role in reducing the experimental cost. A variety of state-of-the-art methods have been proposed to improve the accuracy of DTI predictions. In this paper, we propose a kind of drug-target interactions predictor adopting multi-scale discrete wavelet transform and network features (named as DAWN) in order to solve the DTIs prediction problem.

[Spectrum-Effect Relationship of GualouXiebai Dropping Pills on Myocardial Ischemia].

Objective: To study the relationship between HPLC characteristic spectrum and pharmacodynamics on anti-myocardial ischemia of GualouXiebai dropping pills.

Methods: HPLC characteristic spectrum of GualouXiebai dropping pills was established, dropping pills were divided into five dose groups (3.75, 11.