Online evaluation method of coal mine comprehensive level based on FCE.
Ontology highlight
ABSTRACT:
SUBMITTER: Shen L
PROVIDER: S-EPMC8366963 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:The opencast coal mine is a specific mine differing from the underground mine. There are differences in the way into the ore body, the organization of production, transport technology and other aspects. This study aimed to describe the prevalence of CWP among ex-dust miners in opencast coal mines and estimate the incidence trend of CWP by APC model in the future.All opencast miners who had been exposed to dust for at least 1 year in opencast mines were enrolled in this study. The database included demographic details, occupational history records with the date of dust exposure, physical examination records and pneumoconiosis diagnosis records. An age-period-cohort (APC) model has been carried out in order to explore the effects of the age, period and cohort on the prevalence of CWP among ex-dust opencast miners.8191 opencast miners were enrolled in the study, including 259 miners with CWP and 7932 miners without CWP. The incidence density of CWP would have an increasing trend in opencast mines from 2005 to 2024. The number of possible CWP patients predicted in this period was approximately 492. Of them, 275 miners could have suffered from CWP in 2005-2014 and 217 miners would suffer from CWP in 2015-2024 among the ex-dust opencast miners.The APC model had a goodness of fit in predicting the incidence trend of CWP in opencast coal mines. By this model, we predicted that 492 opencast miners could be diagnosed as CWP from 2005 to 2024. Therefore ex-dust opencast miners cannot be ignored and they should have regular physical examinations and detection for CWP.
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Project description:We aimed to estimate the economic losses currently caused by coal workers' pneumoconiosis (CWP) and, on the basis of these measurements, confirm the economic benefit of preventive measures. Our cohort study included 1,847 patients with CWP and 43,742 coal workers without CWP who were registered in the employment records of the Datong Coal Mine Group. We calculated the cumulative incidence rate of pneumoconiosis using the life-table method. We used the dose-response relationship between cumulative incidence density and cumulative dust exposure to predict the future trend in the incidence of CWP. We calculate the economic loss caused by CWP and economic effectiveness of CWP prevention by a step-wise model. The cumulative incidence rates of CWP in the tunneling, mining, combining, and helping cohorts were 58.7%, 28.1%, 21.7%, and 4.0%, respectively. The cumulative incidence rates increased gradually with increasing cumulative dust exposure (CDE). We predicted 4,300 new CWP cases, assuming the dust concentrations remained at the levels of 2011. If advanced dustproof equipment was adopted, 537 fewer people would be diagnosed with CWP. In all, losses of 1.207 billion Renminbi (RMB, official currency of China) would be prevented and 4,698.8 healthy life years would be gained. Investments in advanced dustproof equipment would be total 843 million RMB, according to our study; the ratio of investment to restored economic losses was 1:1.43. Controlling workplace dust concentrations is critical to reduce the onset of pneumoconiosis and to achieve economic benefits.
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Project description:Air velocity of coal mine ventilation is an important consideration that may cause serious damage. This paper proposes a simple, low cost and effective air velocity monitor (AVM) for coal mine ventilation. The AVM uses the lock-in characteristic of vortex-induced vibration (VIV) to sense the air velocity. Amplitude of the VIV is converted into frequency signal of a vortex-induced triboelectric nanogenerator (VI-TENG) to improve the durability. Structure of the AVM are designed, and parameters of the AVM are optimized with experiments. For the upper and lower air velocity thresholds of 3.1 and 3.6 m/s, the optimized flexible beam length, slider weight, electrode space and electrode width are 42.5 mm, 0.4 g, 0.2 mm and 0.5 mm, respectively. Experiments also show that the output frequency of the VI-TENG could represent the amplitude of VIV well with the correlation coefficient of 0.93. Durability test demonstrates that the AVM generates stable output frequency in 120,000 cycles. A prototype and its controller are fabricated. Wind tunnel tests of this prototype show that it can give alarm when the gas velocity goes above the upper threshold or below the lower threshold. The proposed AVM could be a good solution for simple and effective coal mine ventilation alarm.
| S-EPMC9268754 | biostudies-literature
Project description:The evaluation of the learning process is an effective way to realize personalized online learning. Real-time evaluation of learners' cognitive level during online learning helps to monitor learners' cognitive state and adjust learning strategies to improve the quality of online learning. However, most of the existing cognitive level evaluation methods use manual coding or traditional machine learning methods, which are time-consuming and laborious. They cannot fully mine the implicit cognitive semantic information in unstructured text data, making the cognitive level evaluation inefficient. Therefore, this study proposed the bidirectional gated recurrent convolutional neural network combined with an attention mechanism (AM-BiGRU-CNN) deep neural network cognitive level evaluation method, and based on Bloom's taxonomy of cognition objectives, taking the unstructured interactive text data released by 9167 learners in the massive open online course (MOOC) forum as an empirical study to support the method. The study found that the AM-BiGRU-CNN method has the best evaluation effect, with the overall accuracy of the evaluation of the six cognitive levels reaching 84.21%, of which the F1-Score at the creating level is 91.77%. The experimental results show that the deep neural network method can effectively identify the cognitive features implicit in the text and can be better applied to the automatic evaluation of the cognitive level of online learners. This study provides a technical reference for the evaluation of the cognitive level of the students in the online learning environment, and automatic evaluation in the realization of personalized learning strategies, teaching intervention, and resources recommended have higher application value.
| S-EPMC8551629 | biostudies-literature
Project description:Methane emitted by coal mine ventilation air (MVA) is a significant greenhouse gas. A mitigation strategy is the oxidation of methane to carbon dioxide, which is approximately twenty-one times less effective at global warming than methane on a mass-basis. The low non-combustible methane concentrations at high MVA flow rates call for a catalytic strategy of oxidation. A laboratory-scale coal-packed biofilter was designed and partially removed methane from humidified air at flow rates between 0.2 and 2.4 L min-1 at 30°C with nutrient solution added every three days. Methane oxidation was catalysed by a complex community of naturally-occurring microorganisms, with the most abundant member being identified by 16S rRNA gene sequence as belonging to the methanotrophic genus Methylocystis. Additional inoculation with a laboratory-grown culture of Methylosinus sporium, as investigated in a parallel run, only enhanced methane consumption during the initial 12 weeks. The greatest level of methane removal of 27.2±0.66 g methane m-3 empty bed h-1 was attained for the non-inoculated system, which was equivalent to removing 19.7±2.9% methane from an inlet concentration of 1% v/v at an inlet gas flow rate of 1.6 L min-1 (2.4 min empty bed residence time). These results show that low-cost coal packing holds promising potential as a suitable growth surface and contains methanotrophic microorganisms for the catalytic oxidative removal of methane.
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Project description:Anthropogenic methane emissions from China are likely greater than in any other country in the world. The largest fraction of China's anthropogenic emissions is attributable to coal mining, but these emissions may be changing; China enacted a suite of regulations for coal mine methane (CMM) drainage and utilization that came into full effect in 2010. Here, we use methane observations from the GOSAT satellite to evaluate recent trends in total anthropogenic and natural emissions from Asia with a particular focus on China. We find that emissions from China rose by 1.1?±?0.4?Tg?CH4?yr-1 from 2010 to 2015, culminating in total anthropogenic and natural emissions of 61.5?±?2.7?Tg?CH4 in 2015. The observed trend is consistent with pre-2010 trends and is largely attributable to coal mining. These results indicate that China's CMM regulations have had no discernible impact on the continued increase in Chinese methane emissions.
| S-EPMC6351523 | biostudies-literature
Project description:Acid mine drainage (AMD) is an environmental issue that can be characterized by either acidic or circumneutral pH and high dissolved metal content in contaminated waters. It is estimated to affect roughly 3000 miles of waterways within the state of Pennsylvania, with half being acidic and half being circumneutral. To negate the harmful effects of AMD, ∼300 passive remediation systems have been constructed within the state of Pennsylvania. In this study, we evaluated the microbial community structure and functional capability associated with Middle Branch passive remediation system in central PA. Sediment and water samples were collected from each area within the passive remediation system and its receiving stream. Environmental parameters associated with the remediation system were found to explain a significant amount of variation in microbial community structure. This study revealed shifts in microbial community structure from acidophilic bacteria in raw AMD discharge to a more metabolically diverse set of taxa (i.e., Acidimicrobiales, Rhizobiales, Chthoniobacteraceae) toward the end of the system. Vertical flow ponds and the aerobic wetland showed strong metabolic capability for sulfur redox environments. These findings are integral to the understanding of designing effective passive remediation systems because it provides insight as to how certain bacteria [sulfate reducing bacteria (SRBs) and sulfur oxidizing bacteria (SOBs)] are potentially contributing to a microbially mediated AMD remediation process. This study further supports previous investigations that demonstrated the effectiveness of SRBs in the process of removing sulfate and heavy metals from contaminated water.
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Project description:Vegetation restoration is an available way to ameliorate degraded lands. In order to study the response of soil microbes to vegetation restoration in coal mining subsidence areas, the composition and distribution of soil microbes were discussed through three plots: unsubsided area (CA), new subsided area (NSA), and old subsided area (OSA) with different vegetation restoration time in Huabei coal mine. Meanwhile, changes in soil catalase and urease activity were explored and the correlation between soil bacteria, fungi, and environmental factors was analysed. The results demonstrated that Nitrospira was the dominant bacteria in all areas sampled. Microorganisms in the 0-20 cm and 40-60 cm soil layers of OSA had the highest Simpson index, whereas the index in NSA was lowest (at all soil depths). The catalase activity in NSA was significantly higher than that in CA, and there was no significant difference in catalase activity with soil depth, while the urease activity declined gradually with increasing soil depth. The urease activity in the 20-60 cm soil layer of NSA and OSA was significantly higher than that of CA. Furthermore, the distribution of bacteria was mainly affected by soil organic matter, available potassium, available phosphorus, and alkali-hydrolyzable nitrogen, whereas pH and catalase activity mainly affected fungal distribution. These results implied that soil catalase activity in NSA and urease activity in the 20-40 cm soil layer of NSA and OSA were significantly enhanced after vegetation restoration, and that long-term plant restoration could improve soil fertility and soil microbial community diversity in coal mining areas.
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Project description:A legacy of coal mining in the Appalachians has provided a unique opportunity to study the ecological niches of iron-oxidizing microorganisms. Mine-impacted, anoxic groundwater with high dissolved-metal concentrations emerges at springs and seeps associated with iron oxide mounds and deposits. These deposits are colonized by iron-oxidizing microorganisms that in some cases efficiently remove most of the dissolved iron at low pH, making subsequent treatment of the polluted stream water less expensive. We used full-cycle rRNA methods to describe the composition of sediment communities at two geochemically similar acidic discharges, Upper and Lower Red Eyes in Somerset County, PA, USA. The dominant microorganisms at both discharges were acidophilic Gallionella-like organisms, “Ferrovum” spp., and Acidithiobacillus spp. Archaea and Leptospirillum spp. accounted for less than 2% of cells. The distribution of microorganisms at the two sites could be best explained by a combination of iron(II) concentration and pH. Populations of the Gallionella-like organisms were restricted to locations with pH>3 and iron(II) concentration of >4 mM, while Acidithiobacillus spp. were restricted to pH<3 and iron(II) concentration of <4 mM. Ferrovum spp. were present at low levels in most samples but dominated sediment communities at pH<3 and iron(II) concentration of >4 mM. Our findings offer a predictive framework that could prove useful for describing the distribution of microorganisms in acid mine drainage, based on readily accessible geochemical parameters.
| S-EPMC4309714 | biostudies-literature
Project description:Water discharging from abandoned coal mines can contain extremely high manganese levels. Removing this metal is an ongoing challenge. Passive Mn(II) removal beds (MRBs) contain microorganisms that oxidize soluble Mn(II) to insoluble Mn(III/IV) minerals, but system performance is unpredictable. Using amplicon pyrosequencing, we profiled the bacterial, fungal, algal, and archaeal communities in four MRBs, performing at different levels, in Pennsylvania to determine whether they differed among MRBs and from surrounding soil and to establish the relative abundance of known Mn(II) oxidizers. Archaea were not detected; PCRs with archaeal primers returned only nontarget bacterial sequences. Fungal taxonomic profiles differed starkly between sites that remove the majority of influent Mn and those that do not, with the former being dominated by Ascomycota (mostly Dothideomycetes) and the latter by Basidiomycota (almost entirely Agaricomycetes). Taxonomic profiles for the other groups did not differ significantly between MRBs, but operational taxonomic unit-based analyses showed significant clustering by MRB with all three groups (P < 0.05). Soil samples clustered separately from MRBs in all groups except fungi, whose soil samples clustered loosely with their respective MRB. Known Mn(II) oxidizers accounted for a minor proportion of bacterial sequences (up to 0.20%) but a greater proportion of fungal sequences (up to 14.78%). MRB communities are more diverse than previously thought, and more organisms may be capable of Mn(II) oxidation than are currently known.
| S-EPMC4345392 | biostudies-literature