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3篇 您的检索式:作者名="S.Clarke"
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1Agricultural impacts of longwall mine subsidence:the experience in Illinois,USA and Queensland,Australia显示文摘Unlike conventional room and pillar underground coal mining,where subsidence is designed to be prevented,subsidence is a planned outcome of other methodologies.These include high extraction retreat,where the roof supporting pillars are systematically removed,and longwall mining,which employs a machine that mines a continuous strip of coal,thus leaving no roof supports.Both types result in the surface dropping -70% of the mined-out thickness.In Illinois there was a concern that farm land thus subsided would be lost to productive agriculture.Consequently,the possibility that planned mine subsidence would be banned in Illinois lead to the creation of the Illinois Mine Subsidence Research Program in 1985 to investigate agricultural impacts of planned mine subsidence and the possibility of mitigating its impact.Its findings established that subsidence was not as detrimental as feared and that the impacts could be mitigated.The project was a successful collaboration of state and federal governments and local Universities.Similarly,in Queensland,longwall mining is opposed by some in the farming community.In response,Bandanna Energy,the company planning the mining,organized the Agricultural Coexistence Research Committee to oversee research into the mitigation of longwall mining impacts.Although the soils,climate,and regulatory regimes are different,concerns of the local communities are similar.Robert G.Darmody R.Bauer D.Barkley S.Clarke D.Hamilton 2014International Journal of Coal Science & Technology2014,1,2:3
2The relationship between safety climate and safety performance:A meta-analytic review显示文摘S.Clarke 0,,04:1
3Discussion of ‘Prior-based Bayesian Information Criterion (PBIC)’显示文摘1.Summary The authors have the basis for a reformulation of the BIC as we think of it now.This problem is both hard and important.In particular,to address it,the authors have put six incisive ideas in sequence.The first is the separation of parameters that are common across models versus those that aren’t.The second is the use of an orthogonal(why not orthonormal?)transformation of the Fisher information matrix to get diagonal entries di that summarise the parameter-by-parameter efficiency of estimation.The third is using Laplace’s method only on the likelihood,i.e.Bertrand S.Clarke 2019Statistical Theory and Related Fields2019,3,1:0
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