Examining the Moderating Role of Affective Commitment on the Influence of Job Satisfaction on Intent to Stay: Evidence from Healthcare Technical Staff.

Background: Healthcare technical workers are responsible for service delivery and are indispensable to the organisation. However, being in a client facing role, they perform under client pressures thereby experiencing stress. The enormity of the healthcare industry ensures the existence of multiple competing organisations.

Research on the mechanism of human-machine security collaboration of miners considering automation trust.

Safety in the coal mining industry is a long-standing issue. With the implementation of intelligent construction in coal mines, humans-machine collaboration is critical to accident prevention. We investigate the psychological dynamics among miners during intelligent construction by developing distinct evolutionary game models for miner security collaboration mechanisms, while also considering the level of trust in automation.

Automated Detection of Gastrointestinal Diseases Using Resnet50*-Based Explainable Deep Feature Engineering Model with Endoscopy Images.

This work aims to develop a novel convolutional neural network (CNN) named ResNet50* to detect various gastrointestinal diseases using a new ResNet50*-based deep feature engineering model with endoscopy images. The novelty of this work is the development of ResNet50*, a new variant of the ResNet model, featuring convolution-based residual blocks and a pooling-based attention mechanism similar to PoolFormer. Using ResNet50*, a gastrointestinal image dataset was trained, and an explainable deep feature engineering (DFE) model was developed.

Training in Roller Speed Skating: Proposal of Surface Electromyography and Kinematics Data for Educational Purposes in Junior and Senior Athletes.

: Roller skating shares biomechanical similarities with other sports, but specific studies on speed skaters are limited. Injuries, particularly to the groin, are frequent and related to acute and chronic muscle stress. Technology, particularly surface electromyography, can now be used to monitor performance and prevent injuries, especially those caused by muscular asymmetries.

A Spatial-Temporal Multi-Feature Network (STMF-Net) for Skeleton-Based Construction Worker Action Recognition.

Globally, monitoring productivity, occupational health, and safety of construction workers has long been a significant concern. To address this issue, there is an urgent need for efficient methods to continuously monitor construction sites and recognize workers' actions in a timely manner. Recently, advances in electronic technology and pose estimation algorithms have made it easier to obtain skeleton and joint trajectories of human bodies.

Prediction of Concrete Compressive Strength Based on ISSA-BPNN-AdaBoost.

Strength testing of concrete mainly relies on physical experiments, which are not only time-consuming but also costly. To solve this problem, machine learning has proven to be a promising technological tool in concrete strength prediction. In order to improve the accuracy of the model in predicting the compressive strength of concrete, this paper chooses to optimize the base learner of the ensemble learning model.

Exploring the Impact of Personal Factors on Residents' Willingness to Undergo Primary Care Initial Diagnosis in Beijing, China: A Mixed Methods Research.

: As the foundation and core strength of the healthcare system, the primary care initial diagnosis system has been receiving attention from both the medical and management communities. This study aimed to analyze residents' attitudes toward the system and explore the influencing factors relating to the system in Beijing; : Different methods were used to analyze the multidimensional data. This study selected 610 Beijing residents to complete the survey and used a purposeful sampling method to recruit 15 participants aged 25 to 70 for face-to-face individual semi-structured interviews, using both quantitative and qualitative research methods to carry out statistical analysis.

Effects of Stage Lighting on Visual Comfort at Summer Festivals: A Study in Portugal.

: The primary objective of this study was to assess the visual comfort and health impacts of stage lighting on attendees at summer festivals. Specifically, the study aimed to evaluate the effects of different types of lighting, including natural, artificial, and stage lighting, on symptoms such as glare, eye strain, tearing, and temporary vision loss. : A survey was conducted among attendees of various summer festivals in Portugal.

Closing Editorial for Smart Healthcare: Technologies and Applications.

It is our honor to present this editorial to close the Special Issue "Smart Healthcare: Technologies and Applications", which we are coordinating [...

Correlations Between the Bacterial and Fungal Flora and Amino Acid Composition of the Zhuangzu Acid Congee Produced Around the Zuojiang River Basin, Guangxi.

In this study, the bacterial, fungal, and amino acid compositions of the Zhuangzu acid congee (ZAC) along the Zuojiang River of Guangxi were analyzed. A total of 14 samples of ZAC were collected in four regions: Fusui (F), Ningming (N), Xiashi (X), and Suxu (S). The predominant bacterial phyla of the four groups were Firmicutes and Proteobacteria.

Cardioish: Lead-Based Feature Extraction for ECG Signals.

Electrocardiography (ECG) signals are commonly used to detect cardiac disorders, with 12-lead ECGs being the standard method for acquiring these signals. The primary objective of this research is to propose a new feature engineering model that achieves both high classification accuracy and explainable results using ECG signals. To this end, a symbolic language, named Cardioish, has been introduced.

Minimum and Maximum Pattern-Based Self-Organized Feature Engineering: Fibromyalgia Detection Using Electrocardiogram Signals.

Background: The primary objective of this research is to propose a new, simple, and effective feature extraction function and to investigate its classification ability using electrocardiogram (ECG) signals.

Methods: In this research, we present a new and simple feature extraction function named the minimum and maximum pattern (MinMaxPat). In the proposed MinMaxPat, the signal is divided into overlapping blocks with a length of 16, and the indexes of the minimum and maximum values are identified.

Behaviorally informed digital campaigns and their association with social media engagement and COVID-19 vaccine uptake in Belize.

Background: Increasing vaccination coverage was key to curbing the COVID-19 pandemic globally. However, lack of trust in the vaccine and fear of side effects in regions like the Caribbean resulted in a low uptake despite enough vaccine supply.

Methods: We conducted two correlational analyses and one experiment between five sequential behaviorally informed Facebook campaigns, social media performance outcomes, and district-level vaccination data.

Cortisol awakening response prompts dynamic reconfiguration of brain networks in emotional and executive functioning.

Emotion and cognition involve an intricate crosstalk of neural and endocrine systems that support dynamic reallocation of neural resources and optimal adaptation for upcoming challenges, an active process analogous to allostasis. As a hallmark of human endocrine activity, the cortisol awakening response (CAR) is recognized to play a critical role in proactively modulating emotional and executive functions. Yet, the underlying mechanisms of such proactive effects remain elusive.

Effect of Community-Based Integrated Care for Patients With Diabetes and Depression (CIC-PDD) in China: A Pragmatic Cluster-Randomized Trial.

Objective: To develop a care model for patients with both diabetes and depression and assess the model's effectiveness.

Research Design And Methods: In this pragmatic cluster randomized trial, we allocated eight community health centers into two groups: the enhanced usual care group and the intervention group. A comprehensive care plan was developed for the intervention group based on the integrated care model.

Helping you helps me: Beneficial effects of regulating others' emotions on well-being and physiological stress.

Improving others' emotions is cognitively and emotionally demanding, potentially increasing stress levels and decreasing well-being. However, the opposite could also occur: Attempts at improving others' emotions-that is, extrinsic interpersonal emotion regulation-could enhance regulators' affective well-being and shield against physiological stress because we theorize that engaging in regulatory action to improve others' emotions can strengthen relationships, activate self-regulation, and elicit prosocial reward. In two studies, we test the consequences on regulators when they help others regulate their emotions.

A Systematic Review on the Outcomes of Climate Change in the Middle-Eastern Countries: The Catastrophes of Yemen and Syria.

The Middle East is facing serious climate change challenges, rendering it as one of the most affected regions worldwide. This paper aimed to investigate the outcomes of climate change in the Middle East. In 2024, a qualitative study was conducted employing a methodology that integrated systematic review for data collection and thematic analysis for data analysis.

Evaluation and spatiotemporal evolution of veterinary talent competitiveness: a new perspective of veterinary education.

Introduction: Improving the quantity and quality of veterinary talent cultivation is an urgent issue to address in current veterinary education and is key to enhancing veterinary talent competitiveness. Starting from an industrial perspective, the introduction of scientific analytical methods for studying veterinary talent competitiveness offers a new view on veterinary education and helps to improve the quality of veterinary education and talent cultivation.

Methods: This study develops a veterinary talent competitiveness evaluation index based on the characteristics of veterinary talent.

Explaining the framework of the pro-natalist policy implementation process in Iran: A study protocol.

Background: Population policies and programs around the world are considered as the basis for socio-economic' development. Demographic data in recent years show that Iran has faced a marked decrease in fertility, which makes it inevitable to take emergency measures and plan properly to increase childbearing. A significant point in this field is the basic role of the health system and universities of medical sciences.

Factors Required to Develop Strategic Purchasing for Diagnostic Imaging Services: An Expert Opinion.

Background: In recent decades, healthcare purchasing has been continuously searching for new approaches to improve performance. The pressure of expensive services resulting from more advanced health technology has increased the necessity of these changes. Strategic purchasing of health services, as a recommended approach, remains unknown in diagnostic imaging services.

Renewable energy, regional tourism, and exports to tackle stagnant growth in developed economies.

This study examines the effects of energy resources in the form of clean and unclean energy on the economic progress of 30 selected developed economies. This study used data from 1990 to 2020 and it employs the CS-ARDL method to obtain results. The results present that both clean and unclean energy significantly stimulate economic progress.

Release of complex imaging reports to patients, do radiologists trust AI to help?

Background: As a result of the 21st Century Cures Act, radiology reports are immediately released to patients. However, these reports are often too complex for the lay patient, potentially leading to stress and anxiety. While solutions such as patient portals or providing radiologist contact information have been proposed in the past, new generative artificial intelligence technologies like ChatGPT and Google Gemini may provide the most accessible and scalable method of simplifying radiology reports for patients.

From greenwashing to genuine sustainability: Insights from FinTech and banking executives in emerging market experience.

Greenwashing is the practice of deceiving stakeholders by making inflated or fraudulent promises about environmental responsibility. This study investigates greenwashing challenges in FinTech and banking industries, identifying effective strategies to foster genuine sustainability. The study employs a qualitative methodology, utilizing semi-structured interviews conducted with 12 respondents from the FinTech and banking sectors in Pakistan.