Working Conditions Research Articles

Exploring apprentice selection by skilled trade artisans in the Ghanaian construction industry

Purpose This paper aims to investigate the factors influencing trade artisans’ choice of skills selection as apprentice’s trainee in the Ghanaian construction sector and to identify and address the challenges associated with traditional apprenticeship. Trade artisans with technical know-how in construction and general workplace skills from the traditional apprenticeship training (TAT) in the area of construction were selected from selected sites and training centers. Design/methodology/approach This paper adopted the purposive sampling technique with the aim of gathering knowledge from individuals with expertise in the research area, particularly trade craftsmen who have been trained through the TAT system and are directly involved in construction-related works. Partial least square structure equation modelling (PLS-SEM) analytical approach and principal component analysis were used to reduce the dimensionality of the data set and preserve as much information as possible. Findings Three major components, namely, personal and social interest, job assessment and stability and family and faith were identified as the variables that influence an artisan's choice of a skill trade. These influenced the choice of apprenticeship training by young trainees in choosing apprenticeship as a mode of training. Personal interest, living situation of artisans and parents’ educational attainment are the most influencing factors that determine artisans’ choice of selected trades. Moreover, the study also shed light on the challenges inherent in traditional apprenticeship systems, such as the lack of formal technical education, limited access to modern technology and information and poor working conditions. Practical implications The study underscores the imperative for stakeholders to enhance apprenticeship programmes within the construction sector. This involves providing more stable job opportunities, improving working conditions and offering access to modern technology and information. Such enhancements not only attract more young individuals to apprenticeship training but also ensure the sustainability and relevance of the workforce in meeting industry demands. Originality/value The study finally developed a model that could be used as a foundation for future PLS-SEM evaluation and identified the factors that influence the selection of apprenticeship training by trade artisans.

Physiotherapy experiences of injured immigrant workers in Quebec: an intersectional perspective.

Immigrant workers are more likely to suffer work-related injuries compared to native-born Canadians. Their physical rehabilitation usually involves physiotherapy. This study sought to better understand the experiences of injured immigrant workers receiving compensation and physiotherapy treatments. We conducted a qualitative study using an interpretive descriptive methodology. Semi-structured interviews were completed with 10 compensated immigrant workers about the physiotherapy services they received. Transcripts were analyzed thematically and with an intersectional lens. Two major themes were identified: 1) complex pathways to physiotherapy, and 2) key pillars of physiotherapy experiences. The first theme demonstrates that a lack of familiarity with the health and compensation systems, delayed access to physiotherapy, and cumulative burdens complicate the care of immigrant workers. The second theme shows that moral/emotional support, pain relief, and the recognition of sociocultural beliefs and fears are key aspects to improving the experiences of care for these workers. This study offers new insights into physiotherapy in the context of a work injury, which may help physiotherapists adapt care to the complex needs of immigrant workers. The intersectional lens used in the analysis offers interesting ways of accounting for the multiple social identities of these workers.

Teachers’ social competencies, occupational health, and personal well-being are associated with their use of snark in the classroom

Teachers’ social competencies, occupational health, and personal well-being are associated with their use of snark in the classroom

Study of the hydraulic characteristics of an airfoil‐shaped weir trough measurement and control integrated facility combined with numerical simulation

AbstractIn this study, an integrated measurement and control facility with an airfoil weir as the primary overcurrent structure is proposed by considering the flow characteristics over different shapes of weir trough facilities as well as the approach of merging measurement and control functions. The incomplete self‐similarity theory and dimensional analysis are used to derive the stage‐discharge relationship. The hydraulic characteristics of the facility under different shape‐related parameters, weir crest heights (rotation angles), and flows are studied by combining model testing and numerical simulation. The findings demonstrate that changes in shape‐ related parameters and rotation angle do not affect the linear relationship between the water depths in the critical and reference sections. The mean error in the discharge formula derived by dimensional analysis is 2%. The Froude number is less than 0.25 under all the working conditions. From the backwater height and head loss, it can be seen that the larger the P/C (the maximum airfoil thickness P to the chord length C ratio) value of the facility under the premise of unifying the weir crest height, the better the overflow capacity. When the height of the weir crest is 0.3778 m, the negative pressure on the surface of the airfoil weir increases with increasing P/C value.

Research on dynamic constraint mechanism and motion control of intelligent vehicles based on preview distance optimization under complex road conditions

Aiming at the coupling and conflict issues between intelligent vehicle dynamics characteristics and path tracking system under complex road conditions, this paper investigates the dynamics constraint mechanism and motion control of intelligent vehicles, and proposes an intelligent vehicle lateral–vertical cooperative control method based on optimized preview distance. To begin with, an intelligent vehicle path tracking control system based on expected yaw velocity has been designed by establishing a three-degree-of-freedom dynamic model for intelligent vehicle. Then, we analyzed the mechanism by which changes in vehicle speed, road curvature, and preview distance affect the accuracy of vehicle path tracking and handling stability. Considering the “human-vehicle-road” system in intelligent transportation systems, critical values for collision and instability were set. Furthermore, we designed a proactive optimization method for preview distance under different working conditions, using an optimization algorithm to improve path tracking accuracy while ensuring vehicle stability, based on the lateral displacement deviation and lateral orientation deviation representing the accuracy of path tracking, as well as the lateral acceleration representing handling stability. Finally, hardware-in-the-loop platform test was conducted. The simulation and test results show that the optimized path tracking algorithm reduces lateral deviation to as low as 0.05 m, and the stability constraint control in the algorithm can be triggered promptly even under extreme conditions.

Mental health challenges of recent immigrants in precarious work environments — a qualitative study

IntroductionRecent immigrants from racialized minority backgrounds and those who are notproficient in the local language are some of the most vulnerable members of society. Despitehaving postsecondary educational qualifications and permanent residency status, many areengaged in precarious employment. There is a scarcity of research that has explicitly focused onthe work experiences and mental health challenges faced by these immigrants.MethodsUsing agrounded theory approach and semi-structured face-to-face interviews, this study examined thework experiences and mental health challenges of 42 recent immigrant employees from twocities in Canada who were working in various industries and engaged in precarious employment.FindingsEighty-one percent of the employee participants were overqualified for their jobs.Findings highlighted several ongoing mental problems that participants experienced, stemmingfrom challenging physical and psychological workplace conditions, negative mindsets associatedwith their recent immigrant status, and other contextual factors and barriers. However, variouscoping strategies, both constructive and unconstructive, were used to address this mental distress.DiscussionThe study proposes a multidimensional approach to address workplace conditions topromote good mental health for these employees. This includes preventative programs for raisingawareness among employers about the importance of recent immigrant employees’ mental healthand well-being and policy and legislation changes to ensure the employer’s commitment tocreating a safe and culturally friendly workplace. The approach also recommends that recentimmigrant employees receive occupational health and safety training, learn about Canadianworkplace norms and culture, and have access to professional healthcare services.

The Effect of Construction Workers’ Work Resilience on Their Leisure Sports Participation: The Mediating Role of Safety and Health Awareness

This study, grounded in psychological capital theory and the work resource model, investigates the impact of construction workers’ work resilience on their leisure sports participation. An interdisciplinary integration model was developed, incorporating work resilience, safety and health awareness, and leisure sports participation, providing empirical evidence for enhancing the well-being of the construction workforce. The study specifically examines the roles of physiological resilience, psychological resilience, social support, and occupational engagement in this context. A survey conducted with 663 construction workers in China and Korea revealed the following: (1) physiological resilience, psychological resilience, social support, and occupational engagement significantly and positively influence workers’ leisure sports participation; (2) safety and health awareness serves as a significant mediator between work resilience and leisure sports participation among construction workers. These findings underscore the importance of improving the work environment and creating semi-natural restorative landscapes to promote the physical and mental health of construction workers, as well as their engagement in leisure sports. The study calls for governmental and community initiatives, including policy support and resource allocation, to comprehensively enhance the overall well-being of construction workers.

Leveraging Supervised Machine Learning Algorithms for System Suitability Testing of Mass Spectrometry Imaging Platforms.

Quality control and system suitability testing are vital protocols implemented to ensure the repeatability and reproducibility of data in mass spectrometry investigations. However, mass spectrometry imaging (MSI) analyses present added complexity since both chemical and spatial information are measured. Herein, we employ various machine learning algorithms and a novel quality control mixture to classify the working conditions of an MSI platform. Each algorithm was evaluated in terms of its performance on unseen data, validated with negative control data sets to rule out confounding variables or chance agreement, and utilized to determine the necessary sample size to achieve a high level of accurate classifications. In this work, a robust machine learning workflow was established where models could accurately classify the instrument condition as clean or compromised based on data metrics extracted from the analyzed quality control sample. This work highlights the power of machine learning to recognize complex patterns in MSI data and use those relationships to perform a system suitability test for MSI platforms.

Approaches to the treatment of gastroesophageal reflux disease taking into account the diversity of its clinical formsnurse

The article is devoted to the work of paramedical personnel in conditions of active hostilities, both in the historical aspect and in the military conflict of the present time. The working conditions of paramedical personnel in a combat situation and the objective difficulties in providing medical care, as well as the requirements for physical, special and military training, are reflected.

Comparative study of adaptive trajectory tracking controller for four-wheel mobile robot with prescribed-prediction performance

The nonlinear external disturbances and unmodeled dynamics characteristics have crucial impacts on trajectory tracking control accuracy of a four-wheel mobile robot (FWMR) under complicated working conditions. In this work, an adaptive trajectory tracking controller is designed for the FWMR to achieve the prescribed-prediction performance. On the basis of establishing the FWMR’s dynamics equations, an enhanced prescribed performance function (EPPF) is constructed to restrain the tracking errors of the FWMR within a certain range without requiring the exact initial conditions, thus guaranteeing the transient performance of the control system. Then, an optimal-predictive control (OPC) approach is presented to fulfill the asymptotic stability of the tracking errors of the FWMR. Specifically, the radial basis function neural network (RBFNN) incorporating a minimum parameter learning approach that are implanted into the expected controller is designed to attenuate the nonlinear external disturbances and the unmodeled dynamics of the FWMR. Lastly, comparative simulation investigations are carried out to illustrate the superiority of the proposed EPPF-OPC controller, and moreover, the comparative experiments are further performed to validate the practical effectiveness of the EPPF-OPC controller based on a self-established robot operating system (ROS) test platform of the FWMR.

Experimental research on strain distribution measurement of PC beams based on weak grating array sensing technology

The strain and deformation of bridges are important parameters to reflect the state of bridge structures. The traditional measurement methods are to obtain the partial strain of a bridge by point strain sensor or to obtain the deformation of some special bridge positions by static level and other methods. These methods can not realize the continuous distributed measurement of bridge stress state. The grating array is a new sensing technology with the characteristics of large capacity, long distance, distribution, and high precision. In this paper, the grating array strain optical cable is installed on PC (pre-stressed concrete) beams to conduct loading and unloading experiments under various working conditions compared with other measurement methods. The experimental results show that the grating array strain sensing technology can realize the distributed measurement of bridge strain, and offer a what we believe is a novel approach to bridge health monitoring.

Flow Mechanism Study on the Effect of Controllable Speed Casing With Different Axial Starting Points on Transonic Compressor Rotor Stability

Abstract The controllable speed casing represents an exploring approach to casing technology, designed to enhance the adaptability of casing in compressors under variable working conditions. This paper developed a numerical study into the effects of the axial starting point of the rotatable ring in the controllable speed casing on stability enhancement and performance. Additionally, the study sought to unveil the action mechanism of the rotating casing on various flow elements within the tip passage. The findings indicated that the optimal axial starting point for achieving the most pronounced stability enhancement effect in each rotating speed of the rotatable ring was located at the tip leading edge. In terms of the flow mechanism, the rotation of the rotatable ring was found to enhance the throughflow of the mainstream and the tip vortex, while exacerbating the backflow of the tip leakage flow, which occurred at middle and rear of the tip clearance and had not evolved into tip vortex.

High-Level Feature Fusion Deep Learning Model for Fault Detection in Handling Equipment in Dry Bulk Ports

The flexibility of handling equipment in dry bulk ports is poor, and frequent equipment fault induced by the high-load and high-power working conditions greatly impacts the overall port handling operations, making accurate fault detection play an important role in improving the efficiency and stability of dry bulk port operations. However, as we know, most fault detection methods for port handling equipment depend heavily on monitoring sensor data, which is not applicable in the dry bulk port due to high configuration and maintenance cost, as well as the high false alarm rate of monitoring sensors caused by strong background noise. To solve the problem, this study proposes a High-Level Feature Fusion Deep Learning Model, which uses different deep learning sub-models to extract features of structured and unstructured data. It fuses the extracted feature vectors to achieve fault detection in the handling equipment, establishing the mapping relationship between the fault (e.g., waiting for the pre-loading process, equipment fault, and others) and multi-source heterogeneous operation and maintenance data for the handling equipment, including reclaimers, belt conveyors, dumpers, and ship loaders. To verify the effectiveness of the proposed method, the actual data of a coal port in Northern China is employed as an example. The results show the deep learning model can achieve high prediction accuracy (over 86%) with high efficiency (0.5 s for each sample), which provides decision support for the fault detection in dry bulk port handling equipment.

Exploring the barriers and enablers of industrial solutions in renovation projects: a mixed-methods study in the finnish AEC industry

Offsite construction is a major approach to promote industrialisation in construction. However, implementation of prevailing industrial solutions is often less adequate and unsatisfactory, especially in renovation projects. Thus, the overall objective of this study is to understand the reasons behind the poor performance in implementation of the industrial solutions. The specific objectives include identifying the prominent barriers and enablers of prefabricated products in renovation projects. This study employed exploratory sequential mixed method. The qualitative data were gathered via semi-structured interviews to collect experiences and perception of experts related to industrial solutions. This was followed by quantitative data collection via questionnaire survey using a seven-point Likert scale. The major barriers and enablers of industrial solutions in renovation projects have been ranked in this study. The findings reveal that immutability of heritage buildings, the tolerances of old buildings and insufficient spaces to ensure construction work ranked the top three barriers for implementing industrial solutions in renovation projects. Moreover, the study identifies the most significant enablers including shorter project schedules, quality improvement and work safety improvement. The novelty of the research lies in the comprehensive presentation of the barriers and enablers of industrial solutions in the renovation project context. Policymakers, designers, and contractors can utilize these findings as guiding principles to enhance decision-making processes and create viable solutions for the obstacles encountered in renovation projects. This study further represents a vital step towards the efficient and effective implementation of industrial solutions in renovation projects, resulting in more sustainable and cost-effective outcomes.

Managing workplace AI risks and the future of work.

Artificial intelligence (AI)-the field of computer science that designs machines to perform tasks that typically require human intelligence-has seen rapid advances in the development of foundation systems such as large language models. In the workplace, the adoption of AI technologies can result in a broad range of hazards and risks to workers, as illustrated by the recent growth in industrial robotics and algorithmic management. Sources of risk from deployment of AI technologies across society and in the workplace have led to numerous government and private sector guidelines that propose principles governing the design and use of trustworthy and ethical AI. As AI capabilities become integrated in devices, machines, and systems across industry sectors, employers, workers, and occupational safety and health practitioners will be challenged to manage AI risks to worker health, safety, and well-being. Five risk management options are presented as ways to assure that only trustworthy and ethical AI enables workplace devices, machinery, and processes. AI technologies will play a significant role in the future of work. The occupational safety and health practice and research communities need to ensure that the promise of these new AI technologies results in benefit, not harm, to workers.

Influence of Working Conditions on Performance of Support Staff in Secondary Schools in Nakuru County, Kenya

This study assessed the influence of working conditions on the performance of support staff in public secondary schools within Nakuru County, Kenya. The objectives of the study were to: determine influence of work relationships and remuneration on work performance of support staff respectively. The study adopted the mixed methods research approach using the concurrent embedded design. Herzbergs’ two-factor theory provided the theoretical framework with a target population of 3,258 comprising of 362 principals, 362 deputy principals and 2, 534 support staff. Yamanes’ (1973) formula was used to determine a sample of 356 comprising of (40) principals, (40) deputy principals and (272) support staff who were selected by way of the stratified sampling technique. Semi-structured questionnaires were used to collect quantitative and qualitative information from principals and deputy principals, while support staffs provided quantitative and qualitative information through semi-structured interview schedules. Quantitative data collected was analyzed descriptively and inferential statistics generated while qualitative data was analyzed thematically based on the research objectives. The findings show that: work relationships and remuneration had the Pearsons’ correlation coefficient (R) of .724 and .678 respectively. The R² computed yielded values of .524 and .460 for working relationships and remuneration respectively suggesting that working relationships explained 52.4% of work performance of support staff while remuneration explained 46% of work performance. As a result of these findings, it was concluded that working conditions (work relationships and remuneration) moderately but positively influenced work performance of support staff in public secondary schools in Nakuru County. These findings are particularly important to School Boards of Management and the Ministry of Education who can utilize them to enhance work performance of support staff by enriching their working conditions. Further research to develop schemes of service for support staff across all public secondary schools is recommended in order to bolster their work performance

Climate Research Contributions in Occupational Safety

Objective: This work aimed to identify the additional contributions of the Climate Survey to the Safety area of some companies. Theoretical reference: As a theoretical framework, different questionnaire models were used to research the perceptions of the workforce. Method: A case study was used as a method, whose data collection instrument was a climate questionnaire, constructed from bibliographic research in the ISI Web of Science and Scopus databases, applied to a universe of 455 workers of an offshore organization. Results and Conclusion: Despite being strongly linked to the company culture, the Climate Survey revealed factors underlying risk behaviors, the scope and systemic nature of failures, proving to be an effective diagnostic tool for safety management. Search Implications: This study found that cost reduction policies and focus on financial results tend to reduce organizational investments, leading many companies to adopt reactive management models. And by restricting safety actions to the occurrence of accidents, they ignore unrecorded risks, their scope, latent causes and their systemic nature. Originality/value: This case study is original and assumes an inestimable value due to its scope.

OCCUPATIONAL DISEASES

Occupational diseases continue to be one of the major health problems of the able-bodied population worldwide. The reasons for this are numerous, but the main one is of course the nature of these diseases which by definition are chronic, progressive and degenerative, and the period of latency in which the disease does not have to manifest clinically can last for decades. The factors that can contribute to the development of an occupational disease, ie disease, are numerous and range from chemical, physical and biological to psychosocial risks, so there is a need to find new ways to control long-known risks, to observations of the most common workplace pathologies in the last twenty years, such as recurrent traumatic illnesses, immunodeficiency transmitted as a result of biological injuries and violence, and psychological trauma in the workplace. The aim of this paper is to evaluate the effect of noise as a function of its levels and the duration of workplace exposure on workers' health. This study was conducted with 10 workers from the metal factory "Zhelezara", Skopj which have been exposed to the noise the longest period. According to the results of the research, it can be noted that workers working in a noisy environment experience certain side effects from the noise, although they use different protective equipment for the entire duration of the working time. New knowledge in occupational health and safety practice is needed to respond to new challenges in this field.

Thermal Stress and Its Relationship with Industry: A Systematic Review of The Literature

Objective:This study systematically reviews the literature on the impact of environment temperature on industrial workers and the competitive capacity of industrial organizations. Theoretical Framework:Research such as that by Ferrari et al. (2023) and Varghese (2018) indicates that the relationship between heat and occupational health is predominant, influencing productivity and economic costs. Borg et al. (2021) highlight the need to explore the economic impacts of heat in the workplace to develop effective management policies. Hariyani et al. (2022) emphasize the importance of integrating sustainability and technology into organizational strategies to increase competitiveness. Method:Using the PRISMA protocol and the Science Direct, Web of Science, PubMed and Scopus databases, the research analyzed 329 documents from 31 journals. Results and Discussion:The results indicate that high environment temperatures affect the physical and mental health of workers, reducing productivity. Organizations implement strategic actions and mitigation measures when they perceive competitive advantages. However, industries do not see environment temperature as a direct factor in reducing competitiveness, addressing it as secondary to the economic axis, which creates a knowledge gap. Research Implications:This research allows organizations to create new strategies to mitigate risks that may reduce their competitive capabilities. In addition, it allows for the creation of direct actions for the thermal comfort of workers, due to the central role of human beings in the competitive capacity of industrial organizations. Originality/Value:This work highlights a gap in the scientific literature and in organizational strategies in the search for competitiveness, since the main actors in the manufacturing process, the workers, who are the most affected by exposure to AT, are not seen as elements sensitive to environmental risk .

The Wheel–Rail Contact Force for a Heavy-Load Train Can Be Measured Using a Collaborative Calibration Algorithm

The wheel–rail contact force is a crucial indicator for ensuring the secure operation of a heavy-load train. However, obtaining the real-time wheel–rail contact force of a heavy-load train is a challenging task as, due to safety considerations, it is not possible to install instrumented wheelsets on heavy-load trains. This work presents a novel approach to quantify the wheel–rail contact force of a heavy-load train, utilizing a cooperative calibration methodology. First, a ground measurement platform for the wheel–rail contact force of a heavy-load train is constructed on a selected rail section. The railway inspection car’s wheel–rail contact force measurement system is fine-tuned using a multilayer perceptron calibration approach, and the ground platform then uses the results to fine-tune the railway inspection car’s examined wheelset. Second, based on actual measured data on the wheel–rail contact force of a heavy-load train, and using the golden jackal optimization algorithm, the multilayer perceptron correction approach is employed to create a data relationship mapping model. This model correlates the corrected data on the wheel–rail contact force obtained from the railway inspection car with the wheel–rail contact force of a heavy-haul train with an axle load of 25 tons, and the precision of the mapping is guaranteed. Finally, by combining the wheel–rail contact force correction method for the railway inspection car and the contact force mapping model between the railway inspection car and the heavy-load train, collaborative calibration of the wheel–rail contact force of the heavy-load train is realized. The experimental results under two working conditions show that this method can realize high-precision, real-time measurement of the wheel–rail contact force of a heavy-load train. For the working condition of a straight-line section, the calibration error was within 1.593 kN, and the MAPE was 0.105%; for the working condition of a curved-line section, the calibration error was 2.344 kN, and the RMSE was 184.72 N.