Hidden beneath the ground in coalmines, or behind the walls of factories, injured bodies of workers have too often been overlooked. Using the 1842 Hartley Colliery disaster as a case study, this paper contrasts journalistic neglect with the ways in which working-class poets illuminated responses to large-scale injury. Often the greatest difficulty in industrial disaster was in securing access to trapped victims. Arriving late on the scene, neither journalists nor doctors were able to influence the outcome of events: in most cases emergency treatment was provided by workers themselves. While journalists struggled to portray these men's stories, working-class poets such as Joseph Skipsey brought attention to their collaborative actions even in the face of injury or death. The actions of these colliers as first responders had a lasting significance, foreshadowing working-class involvement in the wider cultural shift towards collective responsibility for healthcare.
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http://dx.doi.org/10.1136/medhum-2020-011892 | DOI Listing |
Environ Microbiol Rep
February 2025
Faculty of Engineering, Department of Chemistry, Istanbul University-Cerrahpaşa, Istanbul, Türkiye.
Marine mucilage disasters, primarily caused by global warming and marine pollution, threaten food security and the sustainability of marine food resources. This study assessed the microbial risks to public health in common sole, deep-water rose shrimp, European anchovy, Atlantic horse mackerel and Mediterranean mussel following the mucilage disaster in the Sea of Marmara in 2021. The total viable count, total Enterobacteriaceae count and the presence of Escherichia coli O157:H7, Salmonella spp.
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January 2025
Key Laboratory of Groundwater Resources and Environment (Jilin University), Ministry of Education, Changchun, 130021, China.
The Luoyang area of the Yellow River Basin, as a typical resource-based city, its special industrial structure and complex geological structure make the ecological and geological environment of the area extremely fragile. In order to realize the sustainable development of the region in this fragile ecological-geological environment, it is necessary to study its Ecological Geological Environmental Carrying Capacity (EGECC) to better serve the regional ecological-geological environment restoration and management work. This study constructs an indicator system encompassing three subsystems: Geological Environment (GE), Social Environment (SE), and Ecological Environment (EE).
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January 2025
Department of Industrial Engineering, UiT-The Arctic University of Norway, Narvik, Norway.
Background: Retail involves directly delivering goods and services to end consumers. Natural disasters and epidemics/pandemics have significant potential to disrupt supply chains, leading to shortages, forecasting errors, price increases, and substantial financial strains on retailers. The COVID-19 pandemic highlighted the need for retail sectors to prepare for crisis impacts on sales forecasts by regularly assessing and adjusting sales volumes, consumer behavior, and forecasting models to adapt to changing conditions.
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January 2025
Guangdong Ocean University, Zhanjiang, China.
H4Nx avian influenza viruses (AIVs) have been isolated from wild birds and poultry and can also cross the species barrier to infect mammals (pigs and muskrats). The widespread presence of these viruses in wild birds and poultry and their ability to be transmitted interspecies make them an undeniable hazard to the poultry farming industry. In the present study, we collected fecal and swab samples from wild birds and poultry in Guangdong Province from January 2019 to March 2024, and various subtypes of AIVs were isolated, including 19 strains of H4 subtype AIVs.
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January 2025
College of Safety Science and Engineering, Anhui University of Science and Technology, Huainan, 232001, People's Republic of China.
The construction of a predictive model that accurately reflects the spontaneous combustion temperature of coal in goaf is fundamental to monitoring and early warning systems for thermodynamic disasters, including coal spontaneous combustion and gas explosions. In this paper, on the basis of programming temperature experiment and industrial analysis, 381 data sets of 9 coal types are established, and feature selection was executed through the utilization of the Pearson correlation coefficient, ultimately identifying O, CO, CO, CH, CH, CH/CH, CH/CH, CH/CH, CO/CO, and CO/O as input indicators for the prediction model. The chosen indicator data were divided into training and testing sets in a 4:1 ratio, the Particle Swarm Optimization (PSO) methodology was applied to optimize the parameters of the XGBoost regressor, and a universal PSO-XGBoost prediction model is proposed.
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