Coal Mine Workers Research Articles

Research on risk analysis and prevention policy of coal mine workers' group behavior based on evolutionary game

The analysis and prevention of behavior risk is one of the important measures to reduce accidents. This research adopts the game method to study group safety behavior, and applies the research to behavioral risk prevention in the daily safety management of coal mining enterprises. First, the influencing factors and quantitative relationship of group behavior were determined through investigation. Then, the dynamic game matrix was constructed, and the dynamic game evolution model of "formal group--informal group" was established. The evolution law of group safety behavior was discussed and analyzed from 3 aspects, i.e., management decision, environment, and manager. Finally, the research was applied to coal mine enterprises, and its effectiveness was verified by summarizing and analyzing the behavior violation data for 2 years. It was found that under the influence of management decisions, the level of safe behavior increased by 21.875% in formal groups, and increased by 21.467% in informal groups. In addition, under the influence of the group environment, the level of safe behavior decreased by 79.875% and 86.667% in formal groups and informal groups, respectively. The research explains the dynamic evolution law of coal mine workers and provides a theoretical basis and reference for the management and control of coal mine workers' unsafe behavior.

Violations by Party Members in the City Committee Files of the Communist Party of Croatia in Karlovac, 1946–1953

This paper deals with violations by members of Communist Party of Croatia in Karlovac from 1946 to 1953. Several topics will be presented, which include mischievous behavior and issues connected to alcoholism; religion; misappropriation, theft, and embezzlement; and work in coal mines. First goal of this paper is to identify what the violations members were sanctioned for. The second goal is to showcase personal stories of people who were sanctioned to see what in fact happened and what kinds of behavior were sanctioned. The archival material used consists of records of the city committee, basic party organizations, and the Register of Sanctioned Party Members.

Mapping of decades-old underground coal mine workings using electrical resistivity tomography

Mapping of decades-old underground coal mine workings using electrical resistivity tomography

Occupational incidence in the modern socio-economic conditions of Donbass

An analysis of the current state of occupational pathological assistance to the working contingent of industrial enterprises of the Donetsk People's Republic is presented. When analyzing the dynamics of occupational morbidity for the period 2017-2021, it shows a significant increase from 12.3 cases in 2017 to 30.5 cases in 2021 (per 10,000 workers), mainly due to workers in coal mines. Most of all occupational diseases were registered among workers of the main underground professions - miners of a stope (37.5%) and sinkers (23.3%). The observed increase in occupational morbidity is considered from the standpoint of today's specifics of the working conditions of coal mining enterprises in Donbass. First of all, the absence of a leading occupational hazard with simultaneous multifactorial industrial exposure, often exceeding the threshold values of limit values, as well as a change in operating factors and the intensity of their impact during the length of service. Most cases of occupational diseases identified when workers applied for medical help to the Republican Center for Occupational Pathology had pronounced chronic forms of diseases in workers with work experience in harmful production factors of 20-39 years (up to 75%) and over 50 years of age - more than half of all cases (2020 - 52.7%, 2019 - 51.2%, 2018 - 53%, 2017 - 51.8%). At the same time, when analyzing primary medical documentation (originals of outpatient cards, professional examination cards) working in hazardous conditions, it is noted that more than 80% are «healthy». One of the main reasons for the growth of occupational morbidity is the poor quality of medical examinations carried out by general medical institutions, which causes late detection of occupational and work-related pathologies, the development of advanced forms of general somatic diseases that prevent employees from fulfilling their job duties. In the structure of occupational pathology in the DPR, the largest share falls on diseases caused by physical overload - 44.3%; industrial aerosols - 37.1%; physical factors: vibration - 17.2%, noise - 0.7%. It is concluded that all of the above processes are due to a number of interrelated reasons - a change in the socio-economic situation caused the economic instability of coal enterprises, which led to worsening working conditions, a reduction in the number of employees, an increase in intensive appeals to the Republican Center for Occupational Pathology in order to resolve the issue of the relationship of morbidity with the profession, and , consequently, the solution of social problems through compensation for damage to health.

Pre-employment hearing threshold levels of 59,601 Australian male coal miners compared to an otologically normal international male population (ISO7029:2019)

Objective This study compared the pre-employment median hearing threshold level (HTL) distribution from a population of coal miners from New South Wales (NSW), Australia, to an otologically normal, age-matched population described by the International Standards Organisation (ISO) ISO 7029:2019, to determine any differences. Design This was an observational, retrospective, repeated cross-sectional study. Study sample De-identified audiometric records of 59,601 male employees entering NSW coal mining in three representative five-year periods between 1991 and 2015 were utilised. Results The median HTL deviation of the mining population was statistically significantly different (p < 0.05) from the ISO population, for almost all analyses. Overall, the mining population cohorts have higher (worse) median HTLs compared to the ISO population. The greatest difference occurs at 4 kHz in older age groups, likely indicating noise-induced hearing loss. Conclusion These findings indicate that some NSW coal mine workers commence their careers with evidence of pre-existing hearing loss (HL), in an industry with excessive noise exposures. These results provide Australian mining and other noisy industries with evidence to support a review of hearing conservation strategies to improve mitigation of hearing loss across the working lifespan.

Defining the Primary Work Stress Factors of Chinese Coal Miners-A Mixed-Methods Study.

Studies have indicated that coal miners in China have higher levels of perceived job stress. However, few studies have investigated the work stress structure of coal miners. Our study focused on the work stress of coal miners in China, with a primary aim to determine the work stress structure of coal miners in China using a mixed-methods approach. Semi-structured interviews were performed with thirty-three people (team leaders and frontline coal miners) conducted with participants from various state-owned large- and medium-sized coal mines in China. Grounded theory was used to construct an initial model for the concept of coal miners' work stress. Using the results of this initial survey and findings in the existing literature, we then constructed a preliminary questionnaire regarding coal miners' work stress and administered the questionnaire to 900 coal miners in the Shaanxi, Henan, Inner Mongolia, and Gansu provinces. The results show that the work stress structure for coal miners differs from that for other occupational types in China, due to differences in the Chinese culture and foreign cultural influences. We revised our questionnaire based on these considerations and administered a new survey to the frontline production workers in coal mines. The preliminary questionnaires were revised and analyzed through exploratory and confirmatory factor analysis, resulting in a final formal model for work stress, which was supported by content and structural validity. In this research, we used the framework of grounded theory to conduct an empirical analysis of the structure model of coal miners' work stress. The findings support that the primary work stress factors of Chinese coal miners included the stress of the work environment, job responsibility, interpersonal relationships, career development, the family environment, and organizational systems. Coal enterprises should therefore always take these factors into consideration when developing and implementing safety management policies aimed at to improve the occupational health status of coal miners.

COAL WORKERS’ PNEUMOCONIOSIS: A COMPARATIVE ANALYSIS OF LIGNITE AND HARD COAL MINE WORKERS

Physical and chemical properties of coal and its relationship with coal workers’ pneumoconiosis (CWP) have been studied previously. However definitive conclusions have not been reached, primarily due to the complex nature of coal mine dust. It remains unclear exactly which properties of coal mine dust related to the grade of coal cause differences in the exposure–response relationship. The aim of the study is to identify the coal mine environmental factors, and personal factors affecting the severity of CWP. This study was a retrospective cross-sectional study and included total of 116 coal mine workers diagnosed as CWP in a tertiary hospital between January 1, 2014, and December 31, 2021. Of the cases, 77 (66.4%) worked in a hard coal mine and 39 (33.6%) worked in a lignite mine, and mean age was 60.2 ± 11.5 years. There was a significantly higher prevalence of concomitant pulmonary disease in hard coal mine workers compared to lignite mine workers (p= 0.005). In addition, the prevalence of progressive massive fibrosis (PMF) was higher in hard coal mine workers compared to lignite mine workers, and a statistically significant difference was found (p= 0.004). The value of FEV1 and FEV1/FVC were significantly lower in hard coal mine workers than in lignite mine workers (p= 0.005, p= 0.002). As a conclusion, concomitant lung disease, presence of PMF and impairment in lung functions, which are important causes of mortality and morbidity for CWP, were found to be more common in hard coal mine workers than in lignite mine workers. Therefore, taking into account the type of coal mine while making protective arrangements to prevent pneumoconiosis in coal mines may contribute to reduce the burden of CWP.

Prevalence of Periodontal Disease Among Coal Mine Workers in Tamilnadu

Coal miners are predisposed to poor oral hygiene and the resulting dental diseases. we planned to investigate the factors that contribute to the prevalence and severity of periodontal disease among Tamil Nadu coal mine workers. 1500 coal mine workers over the age of 18 were enrolled. A proforma was used to record information about socioeconomic status and habits, followed by a clinical examination that included periodontal parameters such as probing pocket depth (PPD), clinical attachment level (CAL), number of missing teeth, and periodontal screening and recording index (PSR). The study population was divided into three age groups. On analyzing the influence of age on the periodontal health, of the participants, PPD, PSR, and the number of missing teeth were found to be higher in the age group of 51-60 years and CAL was found to be higher in the age group of 41-50 years. Also, the periodontal health of the subjects was influenced by their tobacco usage. The PPD and PSR was found to be higher among past smokers than current users of smokeless tobacco. The number of missing teeth was found to be higher among current users of the smokeless form and clinical attachment level was found to be higher among current users of both forms of tobacco. Our findings indicate that periodontal disease was more prevalent among coal mine workers in Tamil Nadu than in the general population. This highlights the importance of including oral health education and tobacco cessation programs to educate workers on the importance of periodontal health and treatment.

Multiple Sequence Long and Short Memory Network Model for Corner Gas Concentration Prediction on Coal Mine Workings.

To further improve the accuracy of recurrent neural network in predicting the gas concentration in the upper corner of the mine tunnel, this paper proposes a method to construct a gas concentration prediction model based on multiple sequence long and short memory network, considering the spatial correlation between the gas concentration in the return airway and upper corner. The reliability of the model construction is improved by using the white noise test and smoothness test to verify the interpretability of the data in this paper and constructing supervised learning type data for gas concentration prediction model training and testing by means of data set division and data windowing. Through experimental comparison, grid search, and time series decomposition, the model algorithm, training parameters, and experimental results were combined to make an in-depth analysis of the influence of each parameter on the model training and the prediction. A training model of the spatially fused gas concentration prediction model with a network layer of 1 and a number of neurons of 32 as the model structure, Adam as the optimization algorithm, and a learning rate of 0.001 and a batch size of 32 as the training parameters was finally determined. The gas concentration prediction model trained in this paper performed well in the test set with a mean square error (MSE) of 0.0013, and its superiority was verified by comparing it with other models to provide some experience and basis for subsequent studies on gas concentration prediction in the upper corner.

Assessment of oral health status among underground coal mine workers of Bokaro city, Jharkhand, India: A cross sectional study

Aim: The aim of this study was to assess the oral health status of underground coal mine workers with the objectives of assessing their tobacco and alcohol habits, oral hygiene behaviours, dental caries and periodontal disease status as well as dental traumatic injuries.Methods: The Cross-Sectional Descriptive Study was conducted in Bokaro city, Jharkhand, India for the duration of 2 months. 400 subjects were included in the present study. Official permission was taken from the HRD department, Central Coal fields Limited (CCL), Ranchi headquarter. All the subjects who agreed to participate in the study were requested to give written informed consent prior to the beginning of the study.Results: Majority of them belongs to 51-60 years of age group (32.8%) followed by 41-50 years (29.3%), 31-40 years (24.5%) and

Research on Simulation and Decision-Making of Coal Mine Workers’ Behavior Risk

The behavior risk of workers is one of the main restricting factors in coal mine safety decision-making and management. In this paper, the behavior and decision-making process of individuals and organizations are modeled and analyzed to solve this challenge, based on data analysis and behavior decision-making. Based on system dynamics (SD), this paper proposes an unsafe behavior correction system (SD-Ipt) for coal miners to reduce occupational risk. The “1 + 1 + 3 + X” behavior risk correction decision-making system is constructed, and the implementation scheme of the system is put forward, which has been applied in coal mines. This study can effectively correct the unsafe behavior of coal mining enterprises and improve the occupational safety and health management ability of coal mining enterprises.

An Investigation of the Effects of Brain Fatigue on the Sustained Attention of Intelligent Coal Mine VDT Operators.

Intelligent mines require much more mental effort from visual display terminal (VDT) operators. Long periods of mental effort can easily result in operator fatigue, which further increases the possibility of operation error. Therefore, research into how brain fatigue affects the sustained attention of VDT operators in intelligent mines is important. The research methods were as follows: (1) Recruit 17 intelligent mine VDT operators as subjects. Select objective physiological indicators, such as reaction time, error rate, task duration, flicker fusion frequency, heart rate, electrodermal activity, and blink frequency, and combine these with the subjective Karolinska Sleepiness Scale to build a comprehensive brain fatigue evaluation system. (2) According to the fatigue-inducing experiment requirements, subjects are required to carry out mathematical operations in accordance with the rules during the presentation time, determine whether the results of the operations fall within the [7, 13] interval, and continue for 120 min to induce brain fatigue. (3) Perform the standard stimulus button response experiment of the sustained attention to response task, before and after brain fatigue, and compare each result. The results show that: (1) When the standard stimulus appeared in the EEG experiment, the amplitude of the early N100 component before and after brain fatigue was significantly different. When the bias stimulus appeared, the average amplitudes of the P200 component and the late positive component, before and after brain fatigue, were significantly different, suggesting that the brain fatigue of VDT workers in coal mines would reduce sustained attention; (2) After the 120 min of the continuous operation task, the subjects showed obvious brain fatigue. The objective brain fatigue was followed by an increase in reaction time, an increase in error rate, a decrease in flicker fusion frequency, an increase in heart rate, an increase in electrodermal current, an increase in the number of blinks, and a larger pupil diameter, and both the subjective and objective data indicated more significant changes in the subjects’ brain fatigue at the 45th and 90th min. The results of the study could provide insight into the reduction in operational efficiency and safety of VDT operators in intelligent mines due to brain fatigue and further enrich the research in the area of brain fatigue in VDT operations.

Graph Convolutional Network-Guided Mine Gas Concentration Predictor

Coal mining work has always been a high-risk job, although mining technology is now regularly very mature, many accidents still occur every year in various countries around the world, most of which are due to gas explosions, poisoning, asphyxiation and other accidents. Therefore it is important to monitor and predict both underground mine air quality. In this paper, we use the GCN spatio-temporal graph convolution method based on spectral domain for multivariate time series prediction of underground mine air environment. The correlation of these sequences is learned by a self-attentive mechanism, without a priori graph, and the adjacency matrix with an attention mechanism is created dynamically. The temporal and spatial features are learned by graph Fourier transform and inverse Fourier transform in TC module (temporal convolution) and GC module (graph convolution), respectively. Besides, the corresponding experimental predictions are performed on other public datasets. And a new loss function is designed based on the idea of residuals, which greatly improves the prediction accuracy. In addition, the corresponding experimental predictions were performed on other public datasets. The results show that this model has outstanding prediction ability and high prediction accuracy on most time-series prediction data sets. Through experimental verification, this model has high prediction accuracy for dealing with multivariate time series prediction problems, both for long-term and short-term prediction.

Cardiorespiratory function, resting metabolic rate and heart rate variability in coal miners exposed to hypobaric hypoxia in highland workplace.

BackgroundOwing to intermittent/acute exposure to hypobaric hypoxia, highland miners may often suffer, the physiological characteristics between highland and lowland miners, however, are rarely reported. The objective of this study was to compare the physiological characteristics of coal miners working at disparate altitudes.MethodsTwenty-three male coal mining workers acclimating to high altitude for 30 ± 6 days in Tibet (highland group; approx. 4500 m above sea level; 628.39 millibar), and 22 male coal mining workers in Hebei (lowland group; less than 100 m above sea level; 1021.82 millibar) were recruited. Tests were conducted to compare ventilatory parameters, circulation parameters, resting metabolic rate (RMR), and heart rate variability (HRV) indices between the two groups in resting state.ResultsVentilation volume per minute (VE) of the highland group was markedly raised compared to that of the lowland group (11.70 ± 1.57 vs. 8.94 ± 1.97 L/min, p = 0.000). In the meanwhile, O2 intake per heart beat (VO2/HR) was strikingly decreased (3.54 ± 0.54 vs. 4.36 ± 0.69 ml/beat, p = 0.000). Resting metabolic rate relevant to body surface area (RMR/BSA) was found no significant difference between the two groups. Evident reduction in standard deviation of NN intervals (SDNN) and remarkable increase in ratio of low- and high- frequency bands (LF/HF) were manifest in highland miners compared to that of lowland ones (110.82 ± 33.34 vs. 141.44 ± 40.38, p = 0.008 and 858.86 ± 699.24 vs. 371.33 ± 171.46, p = 0.003; respectively).ConclusionsThese results implicate that long-term intermittent exposure to high altitude can lead miners to an intensified respiration, a compromised circulation and a profound sympathetic-parasympathetic imbalance, whereas the RMR in highland miners does not distinctly decline.

Frequency of occurrence of cardiovascular risk factors in patients with anthracosilicosis in combination with arterial hypertension and coronary heart disease

Introduction. Clinical and experimental studies show the adverse effect of coal-rock dust not only on the bronchopulmonary, but also on the cardiovascular system. Coal mine workers have a high incidence of arterial hypertension and coronary heart disease. The key point in the prevention of the diseases of the circulatory system is the timely detection and correction of not only the main (non-occupational), but also occupational factors of cardiovascular risk. In this regard, the study of risk factors for arterial hypertension and coronary heart disease in coal mining workers is an urgent task. The study aims to explore the frequency and reveal the most significant non-occupational and occupational factors of cardiovascular risk in patients with anthracosilicosis in combination with arterial hypertension and coronary heart disease. Materials and methods. The study involved 269 coal mine workers: 139 miners with previously diagnosed anthracosilicosis and 130 miners in the control group without lung pathology. All of them underwent a comprehensive clinical, instrumental and laboratory examination to identify arterial hypertension, coronary artery disease and risk factors for the development of the diseases of the circulatory system. Results. According to the findings of the study, a significantly higher incidence of arterial hypertension and coronary heart disease was identified in the patients with anthracosilicosis compared with the miners who worked for a long time in harmful labour conditions but did not have occupational pulmonary pathology. The most significant non-occupational risk factors for arterial hypertension in the patients with anthracosilicosis were determined: age 50 years and older, the presence of fasting hyperglycemia, hyperhomocysteinemia, abdominal type of obesity, hypersthenic constitutional-morphological type according to the Rees-Eysenck index, blood group AB (IV). Occupational risk factors for the development of arterial hypertension in the patients with anthracosilicosis were also identified: work experience in hazardous working conditions of 25 years and more, the dust level in the working area exceeding the maximum permissible concentration by 10 times and more. In the patients with anthracosilicosis, the most significant risk factors for the development of coronary heart disease were: age 45 years and older, the presence of arterial hypertension, metabolic syndrome, andromorphic constitutional-morphological type according to the Tanner index, hyperhomocysteinemia, hyperfibrinogenemia, increased levels of soluble fibrin-monomer complexes and C-reactive protein. Occupational risk factors for the development of coronary heart disease in the patients with anthracosilicosis were also identified: work experience in hazardous working conditions of 20 years and more, the presence of respiratory failure (as a complication of an occupational disease). Limitations. This study is limited to a sample of workers in the main occupations of coal mines who are examined at the Research Institute for Complex Problems of Hygiene and Occupational Diseases. The age group of workers from 40 to 54 years old, with a long work experience in underground dusty conditions (more than 15 years) was studied. The study did not include persons with proven occupational diseases other than anthracosilicosis. Conclusions. The identified significant markers of cardiovascular risk can be applied to elaborate prognostic methods. Timely detection and elimination of cardiovascular risk factors as primary preventive measures should be used to reduce the level of cardiovascular incidence rate among individuals working in hazardous labour conditions. Ethics. This medical research involving a human was carried out in accordance with the ethical principles presented in the latest version of the Declaration of Helsinki by the World Medical Association.

Time Zero for Net Zero: A Coal Mine Baseline for Decarbonising Heat

Mine water geothermal energy could provide sustainable heating, cooling and storage to assist in the decarbonisation of heat and achieving Net Zero carbon emissions. However, mined environments are highly complex and we currently lack the understanding to confidently enable a widespread, cost-effective deployment of the technology. Extensive and repeated use of the mined subsurface as a thermal source/store and the optimisation of operational infrastructure encompasses a range of scientific and technical challenges that require broad partnerships to address. We present emerging results of a pioneering multidisciplinary collaboration formed around an at-scale mine water geothermal research infrastructure in Glasgow, United Kingdom. Focused on a mined, urban environment, a range of approaches have been applied to both characterise the environmental change before geothermal activities to generate “time zero” datasets, and to develop novel monitoring tools for cost-effective and environmentally-sound geothermal operations. Time zero soil chemistry, ground gas, surface water and groundwater characterisation, together with ground motion and seismic monitoring, document ongoing seasonal and temporal variability that can be considered typical of a post-industrial, urban environment underlain by abandoned, flooded coal mine workings. In addition, over 550 water, rock and gas samples collected during borehole drilling and testing underwent diverse geochemical, isotopic and microbiological analysis. Initial results indicate a connected subsurface with modern groundwater, and resolve distinctive chemical, organic carbon and stable isotope signatures from different horizons that offer promise as a basis for monitoring methods. Biogeochemical interactions of sulphur, carbon and iron, plus indications of microbially-mediated mineral oxidation/reduction reactions require further investigation for long term operation. Integration of the wide array of time zero observations and understanding of coupled subsurface processes has significant potential to inform development of efficient and resilient geothermal infrastructure and to inform the design of fit-for-purpose monitoring approaches in the quest towards meeting Net Zero targets.

Measures to Carry Out Dust-proof Management in Coal Mining Work

Measures to Carry Out Dust-proof Management in Coal Mining Work

Numerically simulated behavior of diesel particulate matter emitted by hydraulic support transporters.

WC55-Y hydraulic support transporters allow an efficient transport of support equipment in fully mechanized mining faces. However, the diesel particulate matter (DPM) emitted by these transporters seriously pollutes the air environment along mine roadways, endangering the health of coal mine workers. In this paper, we simulated the diffusion dispersion of DPM during the functioning of a WC55-Y hydraulic support transporter (emitting high amounts of exhaust pollutants) by computational fluid dynamics, identifying high DPM concentration zones. While the transporter was driven along a coal auxiliary transportation roadway, the diffusion-dispersion characteristics of DPM changed: DPM reached a long horizontal diffusion distance and a high concentration. We found that to avoid the inhalation of DPM and reduce its potential harm, coal mine workers should keep a distance of at least 21.27m from the hydraulic support transporter while the vehicle runs along the roadway. Moreover, according to our simulation, the operators responsible for disassembling the hydraulic support transporter should wear protective equipment with good filterability while unloading it. Overall, the findings of this study can be applied to outline new work practice guidelines and design new optimum auxiliary ventilation for reducing underground miner exposure to DPM.

Effects of occupational stress and mental health on work-related musculoskeletal disorders in coal mine workers in Xinjiang

Effects of occupational stress and mental health on work-related musculoskeletal disorders in coal mine workers in Xinjiang

A Predictive Model for Abnormal Bone Density in Male Underground Coal Mine Workers.

The dark and humid environment of underground coal mines had a detrimental effect on workers’ skeletal health. Optimal risk prediction models can protect the skeletal health of coal miners by identifying those at risk of abnormal bone density as early as possible. A total of 3695 male underground workers who attended occupational health physical examination in a coal mine in Hebei, China, from July to August 2018 were included in this study. The predictor variables were identified through single-factor analysis and literature review. Three prediction models, Logistic Regression, CNN and XG Boost, were developed to evaluate the prediction performance. The training set results showed that the sensitivity of Logistic Regression, XG Boost and CNN models was 74.687, 82.058, 70.620, the specificity was 80.986, 89.448, 91.866, the F1 scores was 0.618, 0.919, 0.740, the Brier scores was 0.153, 0.040, 0.156, and the Calibration-in-the-large was 0.104, 0.020, 0.076, respectively, XG Boost outperformed the other two models. Similar results were obtained for the test set and validation set. A two-by-two comparison of the area under the ROC curve (AUC) of the three models showed that the XG Boost model had the best prediction performance. The XG Boost model had a high application value and outperformed the CNN and Logistic regression models in prediction.