scholarly journals Classification of coal seam outburst hazards and evaluation of the importance of influencing factors

2017 ◽  
Vol 9 (1) ◽  
Author(s):  
Xianzhi Shi ◽  
Dazhao Song ◽  
Ziwei Qian
Keyword(s):  
Coal Seam ◽  
Multivariate Regression ◽  
Multivariate Regression Analysis ◽  
Scientific Basis ◽  
Prevention Measures ◽  
Coal Seam Gas ◽  
Geological Factors ◽  
Hazard Level ◽  
Outburst Hazard

AbstractCoal and gas outbursts are the result of several geological factors related to coal seam gas (coal seam gas pressureTo classify the outburst hazard level of a coal seam by means of statistical methods, this study considered the geological parameters of coal seam gas and statistical data on the amount of material involved in coal outbursts. Through multivariate regression analysis, a multivariate regression equation between the outburst coal quantity andUsing a significance evaluation of the aforementioned factors, the relative contributions of the gas-related geological parameters to the outburst hazard level of a coal seam were found to follow the orderThis work provides a scientific basis for evaluating the outburst hazard level of a coal seam and adopting feasible and economical outburst-prevention measures.

scholarly journals Prediction and Assessment of Back Break by Multivariate Regression Analysis, and Random Forest algorithm in hot strata/fiery seam of open-pit coal mine

2021 ◽  
Author(s):  
Mukul Sharma ◽  
Bhanwar Singh Choudhary ◽  
Hemant Agrawal
Keyword(s):  
Regression Analysis ◽  
Random Forest ◽  
Coal Seam ◽  
Coal Mine ◽  
Multivariate Regression ◽  
Multivariate Regression Analysis ◽  
Open Pit ◽  
Design Parameters ◽  
Random Forest Algorithm ◽  
Blast Design

Abstract Coal seam in mines sometimes catches fire due to its property of spontaneous heating. Drilling and blasting techniques are the most economical operation for the removal of overburden and extraction of coal in an open-pit coal mine. Blasting in a fiery seam is one the most dangerous and risky operations and various environmental and technical problems are associated with it. While blasting in a fiery coal seam, it is essential to use the minimum amount of explosive in a hole and the blast should be taken quickly. As the amount of explosive to be used must be comparatively lesser; therefore, it becomes important to perform the blasting in a manner to maximize the utilization of explosive energy. Improper utilization of energy causes back break, which is one of the technical concerns for management due to the in-stability of high wall. This study is a unique attempt to predict back break, especially in fiery coal seam through the experimental blasts and their analysis by Multivariate Regression Analysis (MVRA), and Random Forest algorithm (RFA). Total 26 blasting were conducted at open pit mine. To obtain the most optimum blast design parameter, blast design parameters were varied. The observed back break during trial blasts varies from 1.4 to 10 m. The Sensitivity analysis performed with the collected data and it has been found that stiffness ratio and stemming length are the most influential parameters on generation of back break. The MVRA and RFA analysis have been adopted for accurate prediction of back break. The results show that the RFA analysis predicts the backbreak and achieved the RMSE of ± 0.59 m while in MVRA, RMSE achieved was ± 0.99 m, making RFA more suitable method to be used for backbreak prediction in fiery seam blasting.

Coal seam gas legislation of Queensland

2009 ◽  
Vol 49 (2) ◽  
pp. 590
Author(s):  
Paul Careless
Keyword(s):  
Coal Seam ◽  
Coal Gasification ◽  
Regulatory Regime ◽  
Underground Coal Gasification ◽  
Coal Seam Gas ◽  
Land Access ◽  
Exploration And Production ◽  
Gasification Products ◽  
Ongoing Concern

An overview will be presented of the Queensland petroleum and environmental legislation relating to the exploration for and production of coal seam gas with three key focusses: a discussion of the statutory classification of coal seam gas as petroleum and the relevant statutory regulatory regime, which applies particularly with respect to competing or coincident minerals such as coal and coal gasification products; a description of the principal features and requirements for both exploration and production tenures, including land access and compensation obligations. Reference will be made to associated environmental authorities and licences, and particular environmental issues such as the containment and disposal of water will be brought to the surface as a part of production operations; and, how the legislation has sought to deal with the coordination of exploration and production operations between coal seam gas, conventional coal mining and the more recent technology of underground coal gasification with respect to the same areas. The paper will conclude with a discussion of areas of ongoing concern and difficulty including the ability to transport associated water through pipeline systems, land access and gas storage in natural underground reservoirs.

Analysis of Geological Factors Affecting Coal Seam Gas Content and Prediction

2013 ◽  
Vol 634-638 ◽  
pp. 3645-3649
Author(s):  
Lin Chao Dai ◽  
Guang Cai Wen ◽  
Zhen Liu ◽  
Hui Ming Yang ◽  
Bo Wang
Keyword(s):  
Coal Seam ◽  
Controlling Factors ◽  
Gas Content ◽  
Influence Coefficient ◽  
Nonlinear Prediction ◽  
Single Factor ◽  
Coal Seam Gas ◽  
Factor Method ◽  
Main Controlling Factors ◽  
Geological Factors

In order to determine coal seam gas content accurately, the single factor method was adopted to study geological factors that affect coal seam gas content of a coal mine. Bedrock depth, 50m influence coefficient and coal thickness are identified as the main controlling factors of gas content. And the corresponding correlation coefficient are: 0.6011, 0.3899, 0.2527. Factors such as effective trapping thickness, moisture content and ash content are regarded as secondary factors. Then the SVM theory was used to set up a nonlinear prediction model between coal seam gas content and main controlling factors, and the gas content was predicted. Results show that single factor method can be used to determine main controlling factors of coal seam gas and the gas content SVM model can predict gas content accurately. Besides, the research findings can provide technical basis for gas drainage and gas outburst prevention.

scholarly journals 1574. Multivariate Regression Analysis to Determine Independent Predictors of Treatment Outcomes in the RESTORE-IMI 2 Trial

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S785-S786
Author(s):  
Robert Tipping ◽  
Jiejun Du ◽  
Maria C Losada ◽  
Michelle L Brown ◽  
Katherine Young ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Clinical Response ◽  
Treatment Outcomes ◽  
Multivariate Regression ◽  
Multivariate Regression Analysis ◽  
Apache Ii Score ◽  
Double Blind ◽  
Mitt Population ◽  
Study Results ◽  
All Cause Mortality

Abstract Background In the RESTORE-IMI 2 trial, imipenem/cilastatin/relebactam (IMI/REL) was non-inferior to PIP/TAZ for treating hospital-acquired/ventilator-associated bacterial pneumonia (HABP/VABP) in the primary endpoint of Day 28 all-cause mortality (D28 ACM) and the key secondary endpoint of clinical response (CR) at early follow-up (EFU; 7-14 d after end of therapy). We performed a multivariate regression analysis to determine independent predictors of treatment outcomes in this trial. Methods Randomized, controlled, double-blind, phase 3, non-inferiority trial comparing IMI/REL 500 mg/250 mg vs PIP/TAZ 4 g/500 mg, every 6 h for 7-14 d, in adult patients (pts) with HABP/VABP. Stepwise-selection logistic regression modeling was used to determine independent predictors of D28 ACM and favorable CR at EFU, in the MITT population (randomized pts with ≥1 dose of study drug, except pts with only gram-positive cocci at baseline). Baseline variables (n=19) were pre-selected as candidates for inclusion (Table 1), based on clinical relevance. Variables were added to the model if significant (p < 0.05) and removed if their significance was reduced (p > 0.1) by addition of other variables. Results Baseline variables that met criteria for significant independent predictors of D28 ACM and CR at EFU in the final selected regression model are in Fig 1 and Fig 2, respectively. As expected, APACHE II score, renal impairment, elderly age, and mechanical ventilation were significant predictors for both outcomes. Bacteremia and P. aeruginosa as a causative pathogen were predictors of unfavorable CR, but not of D28 ACM. Geographic region and the hospital service unit a patient was admitted to were found to be significant predictors, likely explained by their collinearity with other variables. Treatment allocation (IMI/REL vs PIP/TAZ) was not a significant predictor for ACM or CR; this was not unexpected, since the trial showed non-inferiority of the two HABP/VABP therapies. No interactions between the significant predictors and treatment arm were observed. Conclusion This analysis validated known predictors for mortality and clinical outcomes in pts with HABP/VABP and supports the main study results by showing no interactions between predictors and treatment arm. Table 1. Candidate baseline variables pre-selected for inclusion Figure 1. Independent predictors of greater Day 28 all-cause mortality (MITT population; N=531) Figure 2. Independent predictors of favorable clinical response at EFU (MITT population; N=531) Disclosures Robert Tipping, MS, Merck & Co., Inc. (Employee, Shareholder) Jiejun Du, PhD, Merck & Co., Inc. (Employee, Shareholder) Maria C. Losada, BA, Merck & Co., Inc. (Employee, Shareholder) Michelle L. Brown, BS, Merck & Co., Inc. (Employee, Shareholder) Katherine Young, MS, Merck & Co., Inc. (Employee, Shareholder)Merck & Co., Inc. (Employee, Shareholder) Joan R. Butterton, MD, Merck & Co., Inc. (Employee, Shareholder) Amanda Paschke, MD MSCE, Merck & Co., Inc. (Employee, Shareholder) Luke F. Chen, MBBS MPH MBA FRACP FSHEA FIDSA, Merck & Co., Inc. (Employee, Shareholder)Merck & Co., Inc. (Employee, Shareholder)

Epicardial fat thickness as arterial hypertension predictor in normotensive patients with abdominal obesity

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
T Kuznetsova ◽  
M Druzhilov
Keyword(s):  
Blood Pressure ◽  
Regression Analysis ◽  
Blood Glucose ◽  
Waist Circumference ◽  
Arterial Hypertension ◽  
Multivariate Regression ◽  
Fasting Blood Glucose ◽  
Multivariate Regression Analysis ◽  
Epicardial Fat Thickness ◽  
Fat Thickness

Abstract Objective Arterial hypertension (HTN) is one of the most common diseases associated with obesity. Visceral obesity (VO) with dysfunctional visceral adipose tissue plays the main role in obesity induced HTN. Direct criteria of VO including echocardiographic epicardial fat thickness (EFT) may become an additional predictor of HTN. Purpose The aim was to assess the role of echocardiographic EFT (EEFT) as a predictor of HTN in normotensive patients with abdominal obesity (AO). Methods 526 normotensive men (according to ambulatory blood pressure monitoring (ABPM) without therapy) with AO (waist circumference (WC) >94 cm) and SCORE <5%, without cardiovascular diseases and diabetes mellitus were examined (age 45.1±5.0 years). The lipid and glucose profiles, creatinine, uric acid and C-reactive protein blood levels, albuminuria evaluation, echocardiography, carotid ultrasound, bifunctional ABPM were performed. The values of EEFT ≥75 percentile for persons 35–45 years and 46–55 years were 4.8 mm and 5.8 mm respectively. These values used as epicardial VO criteria. Patients with subclinical carotid atherosclerosis due to the lipid-lowering therapy administration (n=98) were excluded from the follow-up. Re-examination with ABPM was conducted on average through 46.3±5.1 months. Data were summarized as mean ± standard error, statistical analysis conducted with paired two-tailed t-tests, Pearson χ2 criterion and multivariate regression analysis. Results Data of 406 persons were available for analysis. HTN as average daily blood pressure ≥130/80 mm Hg was detected in 157 (38.7%) patients. These patients were characterized by initially higher values of age (45.9±4.6 years vs 44.3±4.9 years, p<0.001), waist circumference (106.9±7.3 cm vs 104.2±7.3 cm, p<0.001), body mass index (BMI) (32.0±3.3 kg/m2 vs 30.9±3.2 kg/m2, p<0.001), average daily systolic and diastolic blood pressure (120.7/74.5±4.6/3.4 mm Hg vs 118.2/73.2±5.5/3.9 mm Hg, p<0.001), EEFT (5.2±0.7 mm vs 4.4±1.0 mm, p<0.001). The epicardial VO was initially detected in 95 (23.3%) patients. In patients with HTN the initial prevalence of epicardial VO was greater (58.0% vs 23.3%, p<0.001). As predictors for the multivariate regression analysis the clinical and laboratory examinations data and EEFT were evaluated. According to the results a mathematical model for estimating the probability HTN was obtained: 0.696*fasting blood glucose + 0.198*systolic BP + 2.844*EFT – 40.166 (constant). Among these predictors EEFT was characterized by the highest standardized regression coefficient (0.302, p<0.001) (0.295, p<0.01 for fasting blood glucose, 0.035, p<0.001 for systolic BP). The Hosmer-Lemeshow test value was 0.863, the total percentage of correct classifications was 86%, the area under the ROC-curve was 0.913. Conclusions EEFT (4.8 mm for persons 35–45 years and 5.8 mm for persons 46–55 years) may be an additional predictor of HTN in normotensive patients with AO. Funding Acknowledgement Type of funding source: None

Informal and Nonformal Adult Learning in the Coal Seam Gas Protests: Mobilizing Practices and Building an Environmental Justice Movement for Change

2021 ◽  
pp. 074171362110053
Author(s):  
Tracey Ollis
Keyword(s):  
Adult Learning ◽  
Coal Seam ◽  
Environmental Justice ◽  
Water Supply ◽  
Case Study Research ◽  
Coal Seam Gas ◽  
The Public ◽  
Theory Of Practice ◽  
The Earth

This case study research examines informal adult learning in the Lock the Gate Alliance, a campaign against mining for coal seam gas in Central Gippsland, Australia. In the field of the campaign, circumstantial activists learn to think critically about the environment, they learn informally and incidentally, through socialization with experienced activists from and through nonformal workshops provided by the Environmental Nongovernment Organization Friends of the Earth. This article uses Bourdieu’s “theory of practice,” to explore the mobilization of activists within the Lock the Gate Alliance field and the practices which generate knowledge and facilitate adult learning. These practices have enabled a diverse movement to educate the public and citizenry about the serious threat fracking poses to the environment, to their land and water supply. The movements successful practices have won a landmark moratorium on fracking for coal seam gas in the State of Victoria.

scholarly journals Survey of Saliva Components and Virus Sensors for Prevention of COVID-19 and Infectious Diseases

Biosensors ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 14
Author(s):  
Priya Dave ◽  
Roberto Rojas-Cessa ◽  
Ziqian Dong ◽  
Vatcharapan Umpaichitra
Keyword(s):  
Infectious Diseases ◽  
Dental Health ◽  
The United States ◽  
Human Saliva ◽  
Field Application ◽  
Future Research ◽  
Prevention Measures ◽  
Control And Prevention ◽  
Close Distance

The United States Centers for Disease Control and Prevention considers saliva contact the lead transmission mean of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the coronavirus disease 2019 (COVID-19). Saliva droplets or aerosols expelled by sneezing, coughing, breathing, and talking may carry this virus. People in close distance may be exposed directly to these droplets or indirectly when touching the droplets that fall on surrounding surfaces and ending up contracting COVID-19 after touching the mucosa tissue of their faces. It is of great interest to quickly and effectively detect the presence of SARS-CoV-2 in an environment, but the existing methods only work in laboratory settings, to the best of our knowledge. However, it may be possible to detect the presence of saliva in the environment and proceed with prevention measures. However, detecting saliva itself has not been documented in the literature. On the other hand, many sensors that detect different organic components in saliva to monitor a person’s health and diagnose different diseases, ranging from diabetes to dental health, have been proposed and they may be used to detect the presence of saliva. This paper surveys sensors that detect organic and inorganic components of human saliva. Humidity sensors are also considered in the detection of saliva because a large portion of saliva is water. Moreover, sensors that detect infectious viruses are also included as they may also be embedded into saliva sensors for a confirmation of the presence of the virus. A classification of sensors by their working principles and the substances they detect is presented, including the sensors’ specifications, sample size, and sensitivity. Indications of which sensors are portable and suitable for field application are presented. This paper also discusses future research and challenges that must be resolved to realize practical saliva sensors. Such sensors may help minimize the spread of not only COVID-19 but also other infectious diseases.

Sign in / Sign up

Export Citation Format

Share Document