Hasil untuk "Industrial hygiene. Industrial welfare"

Y. Yoon, J. Nelson

Cesilia Charles, Lutengano Mkonongo, David Masanja et al.

Infection prevention and control remains an essential component of effective healthcare delivery and disease prevention. This study aimed to explore healthcare workers’ perspectives on factors influencing compliance with infection prevention and control practices in Katavi Regional Referral Hospital, Tanzania. With a qualitative approach, we aimed to enable a broader narrative, gain a more detailed understanding of IPC practices, and identify experiences that may be overlooked in a forced-choice questionnaire. A cross-sectional design using a phenomenological approach was employed. An interview guide was used to collect data from 19 participants (five doctors, four nurses, four laboratory practitioners, and six from administration positions; ward in-charges, quality improvement officers and administrative officers) between 24 July 2025, and 23 August 2025. Among participants, nine were the key informants, and 10 were involved in in-depth interviews. Thematic analysis revealed that the availability of IPC supplies, desire for personal and patient protection, high patient volume, awareness of IPC protocols, institutional support, supportive supervision, and HCWs’ attitudes towards IPC activities were factors influencing IPC compliance. Strengthening structured supervision, ensuring a constant supply of IPC materials, and investing in continuous IPC capacity building may be an important approach in enhancing compliance with IPC practices and reducing hospital-associated infection risk in Katavi Regional Referral Hospital and similar resource-limited healthcare settings.

Jialyu Huang, Yiwei Zhang, Penghui Nie et al.

Abstract Polystyrene nanoplastics (PS-NPLs) and perfluorobutanoic acid (PFBA) are pervasive contaminants of great concern and can enter human body primarily through gastrointestinal tract. However, their single and combined effects on female reproductive health remain poorly explored. In this study, PFBA was found to be adsorbed onto PS-NPLs through both chemical and physical interactions. Compared with single exposure, co-exposure to PS-NPLs (0.04 mg/d) and PFBA (0.28 mg/d) for 28 days caused more severe ovarian toxicity in rats, as evidenced by decreased primordial follicles, increased follicular atresia, and sex hormone abnormalities. Mechanistically, the co-exposure was associated with the gut barrier damage and elevated levels of lipopolysaccharide in the bloodstream, concomitant with altered redox homeostasis, inflammation and NLRP3/caspase-1-related pyroptosis of the ovary. Moreover, supplementation with probiotic Lactiplantibacillus plantarum P101 partially attenuated ovarian injury via modulating gut microbiota and mitigating the above process. Taken together, our study revealed a synergistic impact of PS-NPLs and PFBA on female reproduction, uncovered the underlying mechanisms from the perspective of gut-ovary axis, and provided valuable insights into potential preventive strategies.

Hasan Tarik Akbaba, Efe Bozkir, Anna Puhl et al.

Extended Reality (XR) offers transformative potential for industrial support, training, and maintenance; yet, widespread adoption lags despite demonstrated occupational value and hardware maturity. Organizations successfully implement XR in isolated pilots, yet struggle to scale these into sustained operational deployment, a phenomenon we characterize as the ``Pilot Trap.'' This study examines this phenomenon through a qualitative ecosystem analysis of 17 expert interviews across technology providers, solution integrators, and industrial adopters. We identify a ``Great Inversion'' in adoption barriers: critical constraints have shifted from technological maturity to organizational readiness (e.g., change management, key performance indicator alignment, and political resistance). While hardware ergonomics and usability remain relevant, our findings indicate that systemic misalignments between stakeholder incentives are the primary cause of friction preventing enterprise integration. We conclude that successful industrial XR adoption requires a shift from technology-centric piloting to a problem-first, organizational transformation approach, necessitating explicit ecosystem-level coordination.

R. E. Zisook, S. Gaffney, J. S. Pierce et al.

Abstract This article presents a state-of-the-science analysis of the evolution of knowledge over time regarding the potential health hazards associated with exposure to airborne asbestos among the insulating trade, which included the state of knowledge of the International Association of Heat and Frost Insulators and Asbestos Workers Union (IAHFIAW), now known as the International Association of Heat and Frost Insulators and Allied Workers (IAHFIAW), and its connection to the National Insulation Contractors Association (NICA) and the National Insulation Manufacturers Association (NIMA); work practices, exposure controls, and personal protective equipment (PPE) that were recommended; and the major regulations and guidelines related to asbestos over the past 100 years in the United States (U.S.). The general timeline of knowledge regarding potential health hazards associated with insulator exposures to asbestos in the U.S. Navy is incorporated in this review, including specific examples of exposure monitoring, medical surveillance campaigns, and recommendations for work practice controls over time. This paper is divided into five time periods (late 1800s–1945; 1946–1962; 1963–1970; 1971–1981; and 1982–present) that were selected based on what were generally believed to be seminal events with respect to the recognition or knowledge of the hazards of asbestos in relation to the insulating trade, the development and standardization of workplace and respiratory controls, and the promulgation of occupational exposure limits (OELs) for asbestos. For each time period, the following topics are addressed: insulation product composition and usage; major developments in the recognition or knowledge of health hazards of asbestos, including key epidemiology studies; health studies of insulators; guidelines and regulations related to OELs for asbestos and sampling and analytical method development for characterizing exposures; and industrial hygiene sampling and recommendations for controlling exposure to asbestos during insulating operations. The goal of this analysis is to illustrate when specific scientific knowledge about asbestos health hazards was established and communicated among the scientific and industrial hygiene communities and within the IAHFIAW. Although this information is available in various separate documents and locations, the purpose of this work is to synthesize it together in a single document so that the reader can understand the full historical context of the evolution of asbestos health hazard knowledge within the insulator trade. To the best of the authors’ knowledge, this review represents the most comprehensive historical examination of the literature on exposure, health effects, and industrial hygiene controls related to asbestos used in insulating operations over time.

Paula Rocha, Stephanie Norotiana Andriamiharisoa, Ana Catarina Godinho et al.

Hand hygiene is a key measure to prevent healthcare-associated infections (HAIs), yet compliance remains low in Sub-Saharan Africa (SSA), due to limited resources, insufficient training, and behavioral challenges. Simulation-based education offers a promising approach to enhance technical and non-technical skills in safe learning environments, promoting behavioral change and patient safety. This study aimed to develop and pilot a contextually adapted hand hygiene simulation-based learning scenario for nursing students in SSA. Grounded in the Medical Research Council (MRC) Framework and Design-Based Research principles, a multidisciplinary team from European and African higher education institutions (HEIs) co-created this scenario, integrating international and regional hand hygiene guidelines. Two iterative pilot cycles were conducted with expert panels, educators, and students. Data from structured observation and post-simulation questionnaires were analyzed using descriptive statistics. The results confirm the scenario’s feasibility, relevance, and educational value. The participants rated highly the clarity of learning objectives (M = 5.0, SD = 0.0) and preparatory materials (M = 4.6, SD = 0.548), reporting increased knowledge/skills and confidence and emphasizing the importance of clear roles, structured facilitation, and real-time feedback. These findings suggest that integrating simulation in health curricula could strengthen HAI prevention and control in SSA. Further research is needed to evaluate long-term outcomes and the potential for wider implementation.

Changheon Han, Yun Seok Kang, Yuseop Sim et al.

Deep learning-based machine listening is broadening the scope of industrial acoustic analysis for applications like anomaly detection and predictive maintenance, thereby improving manufacturing efficiency and reliability. Nevertheless, its reliance on large, task-specific annotated datasets for every new task limits widespread implementation on shop floors. While emerging sound foundation models aim to alleviate data dependency, they are too large and computationally expensive, requiring cloud infrastructure or high-end hardware that is impractical for on-site, real-time deployment. We address this gap with LISTEN (Lightweight Industrial Sound-representable Transformer for Edge Notification), a kilobyte-sized industrial sound foundation model. Using knowledge distillation, LISTEN runs in real-time on low-cost edge devices. On benchmark downstream tasks, it performs nearly identically to its much larger parent model, even when fine-tuned with minimal datasets and training resource. Beyond the model itself, we demonstrate its real-world utility by integrating LISTEN into a complete machine monitoring framework on an edge device with an Industrial Internet of Things (IIoT) sensor and system, validating its performance and generalization capabilities on a live manufacturing shop floor.

Pietro Chiavassa, Stefano Scanzio, Gianluca Cena

Wi-Fi is currently considered one of the most promising solutions for interconnecting mobile equipment (e.g., autonomous mobile robots and active exoskeletons) in industrial environments. However, relability requirements imposed by the industrial context, such as ensuring bounded transmission latency, are a major challenge for over-the-air communication. One of the aspects of Wi-Fi technology that greatly affects the probability of a packet reaching its destination is the selection of the appropriate transmission rate. Rate adaptation algorithms are in charge of this operation, but their design and implementation are not regulated by the IEEE 802.11 standard. One of the most popular solutions, available as open source, is Minstrel, which is the default choice for the Linux Kernel. In this paper, Minstrel performance is evaluated for both static and mobility scenarios. Our analysis focuses on metrics of interest for industrial contexts, i.e., latency and packet loss ratio, and serves as a preliminary evaluation for the future development of enhanced rate adaptation algorithms based on centralized digital twins.

Marcos Kalinowski, Lucas Romao, Ariane Rodrigues et al.

Lean R&D has been used at PUC-Rio to foster industry-academia collaboration in innovation projects across multiple sectors. This industrial experience paper describes recent experiences and evaluation results from applying Lean R&D in partnership with Petrobras in the oil and gas sector and Americanas in retail. The findings highlight Lean R&D's effectiveness in transforming ideas into meaningful business outcomes. Based on responses from 57 participants - including team members, managers, and sponsors - the assessment indicates that stakeholders find the structured phases of Lean R&D well-suited to innovation projects and endorse the approach. Although acknowledging that successful collaboration relies on various factors, this industrial experience positions Lean R&D as a promising framework for industry-academia projects focused on achieving rapid, impactful results for industry partners.

Azmine Toushik Wasi, Enjamamul Haque Eram, Sabrina Afroz Mitu et al.

Industry 5.0 marks a new phase in industrial evolution, emphasizing human-centricity, sustainability, and resilience through the integration of advanced technologies. Within this evolving landscape, Generative AI (GenAI) and autonomous systems are not only transforming industrial processes but also emerging as pivotal geopolitical instruments. We examine strategic implications of GenAI in Industry 5.0, arguing that these technologies have become national assets central to sovereignty, access, and global influence. As countries compete for AI supremacy, growing disparities in talent, computational infrastructure, and data access are reshaping global power hierarchies and accelerating the fragmentation of the digital economy. The human-centric ethos of Industry 5.0, anchored in collaboration between humans and intelligent systems, increasingly conflicts with the autonomy and opacity of GenAI, raising urgent governance challenges related to meaningful human control, dual-use risks, and accountability. We analyze how these dynamics influence defense strategies, industrial competitiveness, and supply chain resilience, including the geopolitical weaponization of export controls and the rise of data sovereignty. Our contribution synthesizes technological, economic, and ethical perspectives to propose a comprehensive framework for navigating the intersection of GenAI and geopolitics. We call for governance models that balance national autonomy with international coordination while safeguarding human-centric values in an increasingly AI-driven world.

G. Giudici, A. Milne, D. Vinogradov

Anna M. Krol, Marvin Erdmann, Ewan Munro et al.

In this paper, we use open-source tools to perform quantum resource estimation to assess the requirements for industry-relevant quantum computation. Our analysis uses the problem of industrial shift scheduling in manufacturing and the Quantum Industrial Shift Scheduling algorithm. We base our figures of merit on current technology, as well as theoretical high-fidelity scenarios for superconducting qubit platforms. We find that the execution time of gate and measurement operations determines the overall computational runtime more strongly than the system error rates. Moreover, achieving a quantum speedup would not only require low system error rates ($10^{-6}$ or better), but also measurement operations with an execution time below 10ns. This rules out the possibility of near-term quantum advantage for this use case, and suggests that significant technological or algorithmic progress will be needed before such an advantage can be achieved.

Christian W. Frey

Industrial production processes, especially in the pharmaceutical industry, are complex systems that require continuous monitoring to ensure efficiency, product quality, and safety. This paper presents a hybrid unsupervised learning strategy (HULS) for monitoring complex industrial processes. Addressing the limitations of traditional Self-Organizing Maps (SOMs), especially in scenarios with unbalanced data sets and highly correlated process variables, HULS combines existing unsupervised learning techniques to address these challenges. To evaluate the performance of the HULS concept, comparative experiments are performed based on a laboratory batch

Gaya Herrington

In the 1972 bestseller Limits to Growth (LtG), the authors concluded that, if global society kept pursuing economic growth, it would experience a decline in food production, industrial output, and ultimately population, within this century. The LtG authors used a system dynamics model to study interactions between global variables, varying model assumptions to generate different scenarios. Previous empirical‐data comparisons since then by Turner showed closest alignment with a scenario that ended in collapse. This research constitutes a data update to LtG, by examining to what extent empirical data aligned with four LtG scenarios spanning a range of technological, resource, and societal assumptions. The research benefited from improved data availability since the previous updates and included a scenario and two variables that had not been part of previous comparisons. The two scenarios aligning most closely with observed data indicate a halt in welfare, food, and industrial production over the next decade or so, which puts into question the suitability of continuous economic growth as humanity's goal in the twenty‐first century. Both scenarios also indicate subsequent declines in these variables, but only one—where declines are caused by pollution—depicts a collapse. The scenario that aligned most closely in earlier comparisons was not amongst the two closest aligning scenarios in this research. The scenario with the smallest declines aligned least with empirical data; however, absolute differences were often not yet large. The four scenarios diverge significantly more after 2020, suggesting that the window to align with this last scenario is closing.

J. Panko, Liz Mittal, K. Franke et al.

Abstract Among the first 20 high-priority chemical substances selected by USEPA to undergo risk evaluation as part of the Toxic Substances Control Act, as amended by the Frank R. Lautenberg Chemical Safety for the 21st Century Act of 2016 is 1,3-butadiene (1,3-BD). Because much of the literature related to occupational exposure to 1,3-BD is associated with the use of the substance in synthetic rubber production and few data have been published for exposures to 1,3-BD manufacturing workers, existing industrial hygiene data collected at facilities where the substance is manufactured or processed as a reactant were compiled and analyzed. The dataset was comprised of personal air samples collected between 2010 and 2019 at facilities located throughout the United States and was compiled into a single database using a uniform data collection template. Data designated by the companies as full-shift were stratified by job group and one of three operational conditions of the workplace: routine, turnaround, and non-routine. Data designated by the companies as short-term and task-level were stratified by task description, sample duration, and operational condition. The final aggregated database contained a total of 5,676 full-shift personal samples. Mean concentrations of 1,3-BD for the job groups ranged from 0.012 ppm to 0.16 ppm. High-end estimates of 1,3-BD air concentrations for the job groups under routine operations ranged from 0.014 ppm to 0.23 ppm. The aggregated database also included 1,063 short-term and task-level personal samples. For short-term samples (< =15 min), mean concentrations ranged from 0.49 ppm to 3.9 ppm, with the highest concentrations observed for the cleaning and maintaining equipment tasks. For task samples with durations greater than 15 min, mean concentrations ranged from 0.49 to 3.6 ppm, with the highest concentrations observed for the unloading and loading task. In addition to the personal air sampling records, information on the use of PPE during various tasks was compiled and analyzed. This data set provides robust quantitative air concentration data and exposure control information for which occupational exposures to 1,3-BD in the Manufacturing and Processing as a Reactant condition of use can be assessed.

J. Sahmel, S. Arnold, G. Ramachandran

Abstract The accuracy of exposure judgments, particularly for scenarios where only qualitative information is available or a systematic approach is not used, has been evaluated and shown to have a relatively low level of accuracy. This is particularly true for dermal exposures, where less information is generally available compared to inhalation exposures. Relatively few quantitative validation efforts have been performed for scenarios where dermal exposures are of interest. In this study, a series of dermal exposure judgments were collected from 90 volunteer U.S. occupational health practitioners in a workshop format to assess the accuracy of their judgments for three specific scenarios. Accuracy was defined as the ability of the participants to identify the correct reference exposure category, as defined by the quantitative exposure banding categories utilized by the American Industrial Hygiene Association (AIHA®). The participants received progressively additional information and training regarding dermal exposure assessments and scenario-specific information during the workshop, and the relative accuracy of their category judgments over time was compared. The results of the study indicated that despite substantial education and training in exposure assessment generally, the practitioners had very little experience in performing dermal exposure assessments and a low level of comfort in performing these assessments. Further, contrary to studies of practitioners performing inhalation exposure assessments demonstrating a trend toward underestimating exposures, participants in this study consistently overestimated the potential for dermal exposure without quantitative data specific to the scenario of interest. Finally, it was found that participants were able to identify the reference or “true” category of dermal exposure acceptability when provided with relevant, scenario-specific dermal and/or surface-loading data for use in the assessment process. These results support the need for additional training and education of practitioners in performing dermal exposure assessments. A closer analysis of default loading values used in dermal exposure assessments to evaluate their accuracy relative to real-world or measured dermal loading values, along with consistent improvements in current dermal models, is also needed.

Mila Tejamaya, Amelia Anggarawati Putri, Sapto Budi Nugroho et al.

Introduction: In line with the increasing number of COVID-19 cases from July to early August 2022, this paper aimed to analyze the perception of COVID-19 among Indonesians. Methods: A cross-sectional online study on COVID-19 risk perception was conducted in the first week of July 2022. A questionnaire adapted from ECOM (Effective Communication in Outbreak Management for Europe) was distributed online through social media to obtain information about the respondents’ knowledge, behavior, and risk perceptions on COVID-19. Results: There were 775 respondents. Most of them were female (61.3%), lived in the eight most targeted areas (84.1%), were unmarried (52.5%), held a bachelor’s degree (38.5%), and were Muslims (80.8%). The percentages of respondents who had been infected with COVID-19 were (43.8%). Most participants believed that their knowledge level of the disease was average and above average (>91%). Of the respondents, 83.6% perceived the seriousness of COVID-19 as serious and very serious. However, the anxiety level among these respondents was moderate (slightly and quite anxious). This indicates that even though most respondents still see COVID-19 as a serious disease, their level of fear is decreasing. Compared to a previous study, most respondents in the current study were more confident of their ability to control the risks associated with the transmission of the virus. Nevertheless, they still believe that outdoor activity and not using a face mask can significantly increase the probability of getting infected. Conclusion: The risk perception of COVID-19 in Indonesian community among our study population was appropriate.

Luis Ignacio López Michelena

Introducción: El trabajo infantil es un problema mundial en el que intervienen factores sociales, culturales y económicos. Los niños trabajan en todos los sectores económicos, mayoritariamente en la agricultura, y se exponen a riesgos ocupacionales que pueden afectar su salud y dejar secuelas para la vida adulta. Objetivo: Determinar los efectos que tiene el trabajo en la salud de los niños, niñas y adolescentes. Métodos: Se realizó una revisión bibliográfica en los motores de búsqueda PubMed y Embase con el tesauro “child labor” y se incluyeron investigaciones publicadas entre 2017 y 2022. Resultados: Se identificaron consecuencias para la salud por exposición a riesgo químico, biomecánico, psicosocial y de seguridad. Dentro de las sustancias químicas, los metales y los pesticidas fueron las sustancias de mayor impacto, por afectaciones endocrina, renal y gastrointestinal, mientras que los factores de riesgo biomecánico como los movimientos repetitivos y las posturas inadecuadas causan trastornos dolorosos en la columna vertebral y las extremidades de los niños que trabajan. La exposición a peligros de seguridad se asocia con accidentes de trabajo mortales, especialmente en el sector de la agricultura. Adicionalmente, los niños que trabajan pueden desarrollar ansiedad, depresión y trastorno de estrés postraumático, afectando la salud mental en la infancia y la adolescencia, y dejando secuelas para la vida adulta. Conclusiones: Existe relación entre el trabajo infantil y los efectos negativos en la salud de los niños, esto debe motivar la toma de decisiones para lograr la erradicación del trabajo infantil en todas las actividades económicas a nivel mundial. Introduction: Child labor is a global problem in which social, cultural, and economic factors intervene. Children work in all economic sectors, mainly in agriculture, and are exposed to occupational risks that can affect their health and leave consequences for adult life. Objective: To determine the effects that work has on the health of children and adolescents. Methods: A bibliographic review was carried out in the Pubmed and Embase search engines with the "child labor" thesaurus and research published between 2017 and 2022 was included. Results: Consequences for health due to exposure to chemical, biomechanical, psychosocial, and safety risks were identified. Within the chemical substances, metals and pesticides were the substances with the greatest impact, due to endocrine, renal, and gastrointestinal effects, while biomechanical risk factors such as repetitive movements and inadequate postures cause painful disorders in the spine and extremities of working children. Exposure to safety hazards is associated with fatal workplace accidents, especially in the agriculture sector. Additionally, working children can develop anxiety, depression, and post-traumatic stress disorder, affecting mental health in childhood and adolescence, and leaving consequences for adult life. Conclusions: There is a relationship between child labor and negative effects on children's health, this should motivate decision-making to achieve the eradication of child labor in all economic activities worldwide. ; ; ; ; ; ;

Savvas Papaioannou, Andrew Markham, Niki Trigoni

To date, the majority of positioning systems have been designed to operate within environments that have long-term stable macro-structure with potential small-scale dynamics. These assumptions allow the existing positioning systems to produce and utilize stable maps. However, in highly dynamic industrial settings these assumptions are no longer valid and the task of tracking people is more challenging due to the rapid large-scale changes in structure. In this paper we propose a novel positioning system for tracking people in highly dynamic industrial environments, such as construction sites. The proposed system leverages the existing CCTV camera infrastructure found in many industrial settings along with radio and inertial sensors within each worker's mobile phone to accurately track multiple people. This multi-target multi-sensor tracking framework also allows our system to use cross-modality training in order to deal with the environment dynamics. In particular, we show how our system uses cross-modality training in order to automatically keep track environmental changes (i.e. new walls) by utilizing occlusion maps. In addition, we show how these maps can be used in conjunction with social forces to accurately predict human motion and increase the tracking accuracy. We have conducted extensive real-world experiments in a construction site showing significant accuracy improvement via cross-modality training and the use of social forces.

Oluwatosin Ogundare, Gustavo Quiros Araya, Ioannis Akrotirianakis et al.

This paper proposes a study of the resilience and efficiency of automatically generated industrial automation and control systems using Large Language Models (LLMs). The approach involves modeling the system using percolation theory to estimate its resilience and formulating the design problem as an optimization problem subject to constraints. Techniques from stochastic optimization and regret analysis are used to find a near-optimal solution with provable regret bounds. The study aims to provide insights into the effectiveness and reliability of automatically generated systems in industrial automation and control, and to identify potential areas for improvement in their design and implementation.