A comprehensive review of the healthy worker effect in occupational epidemiological studies

The reduction of mortality and morbidity rates among occupational cohort studies may be attributed to the presence of the healthy worker effect (HWE). Occupational epidemiologic studies investigating worker’s health are prone to the risk of having the HWE phenomenon and this special form of bias has been debated over the years. Hence, it’s imperative to explore in-depth the magnitude and sources of HWE, and further, elucidate the factors that may affect HWE and strategies reducing HWE. The HWE should be considered as a mixed bias between selection and confounding bias. The validity threats due to the HWE among morbidity studies are the same as the mortality studies. The consequent reduction due to the HWE in the association between the exposure and outcome may lead to underestimating some harmful exposures in the workplace or occupational settings. Healthy hire effect and healthy worker survivor effect are the main sources of HWE. Several factors can increase or decrease the probability of HWE; therefore, the investigators should consider them among future occupational epidemiological studies. Many strategies can help in reducing the impact of HWE, but each strategy has its weaknesses and strengths. Not all strategies can be applied among all occupational epidemiological studies. Mathematical procedures still need further investigations to be validated. HWE is a consequence of inappropriate comparison groups in nature. The usage of the general population as a reference group is not an appropriate choice. By considering the HWE sources and factors and using appropriate strategies, the impact of HWE may be reduced

An Enterprise Computer-Based Information System (CBIS) in the Context of Its Utilization and Customer Satisfaction

Information systems is the study of technology, organizations, and people. An enterprise computer-based information system (CBIS) is type of technology where people can buy and sell their items online, therefore, it is a part of the online business process. This relationship has resulted in the reengineering of the information systems’ model, the formulation of new requirements for training and education, and opening new investment windows for the development of new technologies at both the computer hardware and software application level to meet the needs of newly emerging business models. The aim of this chapter is to provide a comprehensive survey on enterprise CBISs in the context of its utilization and customer satisfaction

Multi-constraints based deep learning model for automated segmentation and diagnosis of coronary artery disease in X-ray angiographic images

Background: The detection of coronary artery disease (CAD) from the X-ray coronary angiography is a crucial process which is hindered by various issues such as presence of noise, insufficient contrast of the input images along with the uncertainties caused by the motion due to respiration and variation of angles of vessels. Methods: In this article, an Automated Segmentation and Diagnosis of Coronary Artery Disease (ASCARIS) model is proposed in order to overcome the prevailing challenges in detection of CAD from the X-ray images. Initially, the preprocessing of the input images was carried out by using the modified wiener filter for the removal of both internal and external noise pixels from the images. Then, the enhancement of contrast was carried out by utilizing the optimized maximum principal curvature to preserve the edge information thereby contributing to increasing the segmentation accuracy. Further, the binarization of enhanced images was executed by the means of OTSU thresholding. The segmentation of coronary arteries was performed by implementing the Attention-based Nested U-Net, in which the attention estimator was incorporated to overcome the difficulties caused by intersections and overlapped arteries. The increased segmentation accuracy was achieved by performing angle estimation. Finally, the VGG-16 based architecture was implemented to extract threefold features from the segmented image to perform classification of X-ray images into normal and abnormal classes. Results: The experimentation of the proposed ASCARIS model was carried out in the MATLAB R2020a simulation tool and the evaluation of the proposed model was compared with several existing approaches in terms of accuracy, sensitivity, specificity, revised contrast to noise ratio, mean square error, dice coefficient, Jaccard similarity, Hausdorff distance, Peak signal-to-noise ratio (PSNR), segmentation accuracy and ROC curve. Discussion: The results obtained conclude that the proposed model outperforms the existing approaches in all the evaluation metrics thereby achieving optimized classification of CAD. The proposed method removes the large number of background artifacts and obtains a better vascular structure

Augmenting the Robustness and Efficiency of Violence Detection Systems for Surveillance and Non-Surveillance Scenarios

Violence detection holds immense significance in ensuring public safety, security, and law enforcement in various domains. With the increasing availability of video data from surveillance cameras and social media platforms, the need for accurate and efficient violence detection algorithms has become paramount. Automated violence detection systems can aid law enforcement agencies in identifying and responding to violent incidents promptly, thereby preventing potential threats and ensuring public protection. This research focuses on violence detection in large video databases, proposing two keyframe-based models named DeepkeyFrm and AreaDiffKey. The keyframes selection process is critical in violence detection systems, as it reduces computational complexity and enhances accuracy. EvoKeyNet and KFCRNet are the proposed classification models that leverage feature extraction from optimal keyframes. EvoKeyNet utilizes an evolutionary algorithm to select optimal feature attributes, while KFCRNet employs an ensemble of LSTM, Bi-LSTM, and GRU models with a voting scheme. Our key contributions include the development of efficient keyframes selection methods and classification models, addressing the challenge of violence detection in dynamic surveillance scenarios. The proposed models outperform existing methods in terms of accuracy and computational efficiency, with accuracy results as follows: 98.98% (Hockey Fight), 99.29% (Violent Flow), 99% (RLVS), 91% (UCF-Crime), and 91% (ShanghaiTech). The ANOVA and Tukey tests were performed to validate the statistical significance of the differences among all models. The proposed approaches, supported by the statistical tests, pave the way for more effective violence detection systems, holding immense promise for a safer and secure future. As violence detection technology continues to evolve, our research stands as a crucial stepping stone towards achieving improved public safety and security in the face of dynamic challenges

Foot Function Index for Arabic-speaking patients (FFI-Ar) : translation, cross-cultural adaptation and validation study

Background: Foot Function Index (FFI) is a valid and reliable outcome measure, which is widely used to measure the foot and ankle functional level and disorders. Until now, no validated Arabic version of the FFI is available. This study was conducted at a tertiary care hospital in Riyadh, Saudi Arabia. The purpose of this project was to translate and adapt the FFI into Arabic and to evaluate its psychometric properties of validity and reliability. Methods: The study consisted of two phases. The first phase was the translation and cultural adaptation of the FFI to Arabic. The next phase involved, testing the psychometric properties of the Arabic version of the FFI on a sample of 50 consecutive participants which included internal consistency, test–retest reliability, floor and ceiling effects and construct validity. Results: The mean age of the study participants was 38 ± 12.94 years. Both the genders were evenly enrolled with 50% of the participants as male and 50% as female. Majority of them complained of plantar fasciopathy (32%) followed by pes planus (22%) and ankle sprain (18%). The scores of FFI-Ar were normally distributed, confirmed by a significant Shapiro–Wilk test. The mean value of FFI-Ar total score was 47.73 ± 19.85. There were no floor or ceiling effects seen in any of the subscales and total score. The internal consistency was good with the Cronbach’s alpha value of 0.882, 0.936 and 0.850 for the pain, disability and activity limitation subscales, respectively. The reproducibility of the FFI-Ar was analysed by intra-class correlation coefficient which revealed good to excellent test–retest reliability. A significant correlation was found between FFI-Ar and SF-36 and numeric rating scale (NRS) confirming its construct validity. Conclusion: The FFI-Arabic version showed good validity and reliability in patients with foot and ankle problems. This tool can be used in usual practice and research for analysing foot and ankle disorders in Arabic-speaking people

Vibration analysis of size dependent micro FML cylindrical shell reinforced by CNTs based on modified couple stress theory

In this manuscript, the sequel of agglomeration on the vibration of fiber metal laminated (FML) cylindrical shell in the micro phase using developed couple stress theory (MCST). Hamilton’s principle has been carried out for deriving the non-classical equations of motion of size dependent thin micro cylindrical shell on the basis of Love’s first approximation theory. Mori Tanaka and extended rule of mixture are utilized to estimate the mechanical attributes of carbon nanotubes (CNTs) and equivalent fiber, respectively. These four phases CNTs/fiber/polymer/metal laminated (CNTFPML) micro cylindrical shell is analyzed applying beam modal function model for several boundary limitations. Then, an investigation is performed to study the impacts of differing input parameters namely material length scale parameter, agglomeration, the distributions of agglomerated CNTs, the mass fraction of equivalent fiber and the volume fraction of CNTs on the frequency response of micro agglomerated CNTFPML cylindrical shell. The main output illustrated that the growth of frequencies is directly dependent to the increase of material length scale parameter for this agglomerated CNTFPML cylindrical shell so that through increasing the values of agglomeration parameters g and l and material length scale parameter l altogether, the frequencies of this cylindrical shell gro

Surface charge on chitosan/cellulose nanowhiskers composite via functionalized and untreated carbon nanotube

Improvement in chitosan (CS) was achieved by solution casting using cellulose nanowhiskers (CNWs) and multiwall carbon nanotubes (MWCNTs) to synthesize CS/CNW functionalized/treated MWCNTs (CS/CNWs/f-MWCNTs) and CS/CNW untreated MWCNTs (CS/CNWs/Un-MWCNTs) nanocomposite films. A comparison between effects of f-MWCNTs and Un-MWCNTs on CS/CNWs matrix have been studied with respect to change in their physical and mechanical properties. The surface morphology, chemical composition, mechanical properties and temperature decomposition of CS/CNWs/f-MWCNTs and CS/CNW/Un-MWCNTs nanocomposite films were characterized by Energy Dispersion Spectroscopy (EDS), Field Emission Scanning Electron Microscope (FESEM), Fourier-Transform Infrared Spectroscopy (FTIR) and Thermogravimetric Analysis (TGA). FESEM has shown that f-MWCNTs and Un-MWCNTs were well dispersed in CS/CNWs structure. Decrease in film ductility was observed with addition of Un-MWCNTs or f-MWCNTs. Moreover, Tensile strength (TS) and Young's modulus (YM) were increased with f-MWCNTs and seemed to be decreased in case of Un-MWCNTs. However, a decrease in elongation at break (EB) has experienced with addition of f-MWCNTs and Un-MWCNTs. Furthermore, thermal stability of chitosan composites presented a delay or prevention from degradation of CS/CNWs due to the strong interactions. Such modification in chitosan can improve its mechanical and surface properties. Hence, chitosan derived composites could achieve more applicability in packaging, medicinal and environmental applications

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Cross-Cultural Adaptation and Validation of the Arabic Version of Musculoskeletal Health Questionnaire (MSK-HQ-Ar)

Background: Musculoskeletal disorders (MSD) affect millions of people worldwide. Musculoskeletal Health Questionnaire (MSK-HQ) is a valid and reliable tool to assess the health of patients with MSD. However, this scale is not available in the Arabic language. The purpose of this study was to translate and cross-culturally adapt the Musculoskeletal Health Questionnaire (MSK-HQ) into Arabic (MSK-HQ-Ar) and evaluate its validity and reliability among participants with MSD. Methods: This cross-sectional study used guidelines from the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) to translate as well as validate the psychometric properties of MSK-HQ-Ar. Patients with MSD (n = 149) living in Taif participated in the study. Cronbach’s alpha and the intraclass correlation coefficient (ICC) were used to assess internal consistency and test-retest reliability of MSK-HQ-Ar respectively. Spearman’s correlation was used to assess the correlation between MSK-HQ-Ar and the European quality of life five-dimension, five-level scale (EQ-5D-5L). Results: Out of 149 participants, 119 completed the MSK-HQ-Ar twice. The scale showed good internal consistency, Cronbach’s alpha (0.88), and reliability (ICC 0.92–0.95). A strong association was found with the EQ-5D-5L scores. Conclusion: The adapted MSK-HQ-Arabic version revealed acceptable psychometric properties and is a valid and reliable outcome measure to assess MSK health among Arabic speaking patients with MSD