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Relevant biochar characteristics influencing compressive strength of biochar-cement mortars

Biochar 2024年第1期6卷 1544-1570页

作者： Julia Hylton Aaron Hugen Steven M.Rowland Michael Griffin Lori E.Tunstall Colorado School of Mines GoldenUSA.2 National Renewable Energy LaboratoryGoldenUSA.

To counteract the contribution of CO_(2)emissions by cement production and utilization,biochar is being harnessed as a carbon-negative additive in *** the cement replacement and biochar dosage will increase the carbon offset,but there is large variability in methods being used and many researchers report strength decreases at cement replacements beyond 5%.This work presents a reliable method to replace 10%of the cement mass with a vast selection of biochars without decreasing ultimate compressive strength,and in many cases significantly improving *** carefully quantifying the physical and chemical properties of each biochar used,machine learning algorithms were used to elucidate the three most influential biochar characteristics that control mortar strength:initial saturation percentage,oxygen-to-carbon ratio,and soluble *** results provide additional research avenues for utilizing several potential biomass waste streams to increase the biochar dosage in cement mixes without decreasing mechanical properties.

关键词： Biochar Concrete Compressive strength Predictor variables multivariate linear model

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James-Stein estimation problem for a multivariate normal random matrix and an improved estimator

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linear ALGEBRA AND ITS APPLICATIONS 2017年 532卷 231-256页

作者： Liu, Xiaoqian Liu, Liangyuan Hu, Jianhua Shanghai Int Studies Univ Sch Econ & Finance Shanghai 200083 Peoples R China Shanghai Univ Finance & Econ Sch Stat & Management Shanghai 200433 Peoples R China

In this paper, we provide the proof of nonexistence of the James-Stein estimator in the whole parameter space for normal random matrices, equivalently, for multivariate linear regression models, which solves the open problem raised by S.F. Arnold [1]. By introducing the concepts of left and right James-Stein estimators, we obtain the left James-Stein estimator of mean matrix and show that the left James-Stein estimator has minimaxity and optimality in terms of the Efron-Morris type modification. We construct a new minimax combination estimator with lower risk by absorbing the advantages of the left James-Stein estimator and the existing modified Stein estimator. Risk comparisons through finite sample simulation studies illustrate that the proposed combination estimator has a better performance, under the mean-squared error or l(2) risk, compared with all existing estimators. (C) 2017 Elsevier Inc. All rights reserved.

关键词： Admissibility James-Stein estimator James-Stein estimation problem Lost function Minimaxity multivariate linear model Shrinkage estimator

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Spatio-temporal variation prediction on Cd content in the rice grains from Northern Zhejiang Plain during 2014–2019 based on high-precision soil geochemical data

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Journal of Geographical Sciences 2023年第2期33卷 413-426页

作者： YIN Hanqin LU Xinzhe SUN Rui HUANG Chunlei KANG Zhanjun XU Mingxing WEI Yingchun CAI ZiHua State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074China Technology Innovation Center of Ecological Evaluation and Remediation of Agricultural Land in Plain Area MNRHangzhou 311200China Zhejiang Institute of Geological Survey Hangzhou 311200China

In recent years,Cadmium(Cd)pollution has been found in many soil geochemical surveys in Northern Zhejiang Plain,a crucial rice production area in East China,located in the lower Yangtze *** more scientifically predict the effect of soil Cd on rice safety,data including 348 local rhizosphere soil-rice samples obtained in 2014 were used in this ***,we extracted 90% of random samples as variables based on soil Cd content(Cd_(soil)),soil organic matter(SOM),pH,and other *** addition,a multivariate linear model for rice Cd content(Cd_(rice))prediction based on the indicators including the soil Cd content(Cd_(soil)),the soil organic matter(SOM),and the pH *** remaining 10%of random samples were used for the significance *** on the 2014 soil Cd content(Cd_(soil14))and the 2019 soil Cd content(Cd_(soil19)),this study predicted Cd content in 2019 rice grains(Cd_(p-rice19)).The spatio-temporal variation of Cdrice was contrasted in the five years from 2014 to 2019,and the risk areas of rice safety production were analyzed using the Geographical Information System(GIS).The results indicated that compared with the actual Cd content in 2014 rice grains(Cdrice14),the proportion of Cd_(p-rice19),which exceeded the standard food level in China(GB2762-2017),increased ***,the high-value areas of Cdrice distributed greatly coincidentally in these two *** contrast,both Cdrice and Cdsoil show very different spatial *** dominant reason is the distribution of the local canal systems,indicating that economic activities and agricultural irrigation may aggravate the risk of soil Cd pollution,thus threatening safe rice production.

关键词： Northern Zhejiang Plain soil cadmium pollution rice safety multivariate linear model

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Setting reference conditions for mesohaline and oligohaline macroinvertebrate communities sensu WFD: Helping to define achievable scenarios in basin management plans

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ECOLOGICAL INDICATORS 2015年 56卷 171-183页

作者： Vinagre, Pedro Almeida Pais-Costa, Antonia Juliana Marques, Joao Carlos Neto, Joao M. Univ Coimbra Fac Sci & Technol Dept Life Sci MARE Marine & Environm Sci Ctr P-3004517 Coimbra Portugal

The Water Framework Directive requires all Member States to achieve good ecological quality status for all waters (e.g., transitional waters). For that purpose, Member States must assess water bodies based on information on the Biological Quality Elements listed for each of them (e.g., benthic macroinvertebrates). However, the production of such a quality status classification (high, good, moderate, poor, bad) requires high reference conditions (associated with the absence of, or very low, human pressure) against which the deviation of the samples to be assessed can be measured. In transitional waters, upper stretches have seldom been included in monitoring activities, resulting in very little knowledge of mesohaline and oligohaline areas, which means further difficulty when defining the required reference conditions for these zones. Regarding the benthic macroinvertebrates, large datasets from the mesohaline and oligohaline stretches of the Mondego estuary (four seasons, five years, environmental parameters, density and biomass data) were used to estimate high reference condition values. In terms of environmental conditions, summer was identified as the most stable season and the most suitable for defining reference conditions for selected ecological indicators. For each indicator, the multivariate linear model expressing the best correlation with measured environmental parameters was selected. These models were used afterwards, by replacing the environmental parameters in those equations with their high reference values, to calculate the reference condition for each ecological indicator. Generally, macrobenthic communities within each stretch changed over the years, being mainly influenced by salinity and sediment organic matter. In both stretches, only a few taxa occurred and two species (the amphipod Corophium multisetosum and the bivalve Corbicula fluminea) were clearly dominant. Diversity values (for Margalef, Shannon and ES50 - Hurlbert indices) were low in b

关键词： Benchmarking multivariate linear model Resilience Transitional Waters Degradation and recovery paths Benthic macroinvertebrates

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Tests for multivariate analysis of variance in high dimension under non-normality

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JOURNAL OF multivariate ANALYSIS 2013年 115卷 204-216页

作者： Srivastava, Muni S. Kubokawa, Tatsuya Univ Toronto Dept Stat Toronto ON M5S 3G3 Canada Univ Tokyo Fac Econ Bunkyo Ku Tokyo 1130033 Japan

In this article, we consider the problem of testing the equality of mean vectors of dimension p of several groups with a common unknown non-singular covariance matrix Sigma, based on N independent observation vectors where N may be less than the dimension p. This problem, known in the literature as the multivariate analysis of variance (MANOVA) in high-dimension has recently been considered in the statistical literature by Srivastava and Fujikoshi (2006) [8], Srivastava (2007) [5] and Schott (2007) [3]. All these tests are not invariant under the change of units of measurements. On the lines of Srivastava and Du (2008) [7] and Srivastava (2009) [6], we propose a test that has the above invariance property. The null and the non-null distributions are derived under the assumption that (N, p) -> infinity and N may be less than p and the observation vectors follow a general non-normal model. (C) 2012 Elsevier Inc. All rights reserved.

关键词： Asymptotic distributions High dimension MANOVA multivariate linear model Non-normal model Sample size smaller than dimension

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multivariate analysis with an autoregressive covariance model

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COMMUNICATIONS IN STATISTICS-THEORY AND METHODS 1996年第3期25卷 555-569页

作者： Byrne, PJ COLL ST BENEDICT DEPT MATHST JOSEPHMN 56374

This paper addresses the problem of testing the multivariate linear hypothesis when the errors follow an antedependence model (Gabriel, 1961, 1962). Antedependence can be formulated as a nonstationary autoregressive model of general order. Three test statistics are derived that provide analogs to three commonly used MANOVA statistics: Wilks' Lambda, the Lawley-Hotelling Trace, and Pillai's Trace. Formulas are given for each of these statistics that show how they can be obtained from any statistical computing package that calculates the usual MANOVA statistics. These antedependent statistics would be appropriate in analyzing certain multivariate data sets in which repeated measurements are taken on the same subjects over a period of time.

关键词： Bartlett's correction multivariate analysis of variance multivariate linear model repeated measures Wilks' Lambda

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multivariate FUNCTIONAL LEAST-SQUARES

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JOURNAL OF multivariate ANALYSIS 1988年第1期25卷 45-64页

作者： HEATHCOTE, CR WELSH, AH UNIV CHICAGO CHICAGO IL 60637 USA

The paper is concerned with estimating multivariate linear and autoregressive models using a generalisation of the functional least-squares procedure. This leads to a family of estimators, indexed by a vector parameter, for which strong uniform consistency and weak convergence results are established. The structure of the limiting covariance matrix is explored and an adaptive estimator with an appropriately “small” covariance matrix is proposed. This estimator is asymptotically normally distributed and it is claimed that its use is particularly appropriate for models with long-tailed and possibly asymmetric error distributions.

关键词： 62H12 62F35 60F17 adaptive estimation empirical characteristic function functional least squares multivariate linear model robust estimation stochastic process vector autoregressive process

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Generalized Bayes minimax estimation of the normal mean matrix with unknown covariance matrix

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JOURNAL OF multivariate ANALYSIS 2009年第10期100卷 2296-2304页

作者： Tsukuma, Hisayuki Toho Univ Fac Med Ota Ku Tokyo 1438540 Japan

This paper addresses the problem of estimating the normal mean matrix in the case of unknown covariance matrix. This problem is solved by considering generalized Bayesian hierarchical models. The resulting generalized Bayes estimators with respect to an invariant quadratic loss function are shown to be matricial shrinkage equivariant estimators and the conditions for their minimaxity are given. (C) 2009 Elsevier Inc. All rights reserved.

关键词： Decision theory Equivariance Generalized Bayes estimation Hierarchical model Minimaxity multivariate linear model Posterior mean Quadratic loss Shrinkage estimator

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Bayesian nonparametric multivariate ordinal regression

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CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 2015年第3期43卷 337-357页

作者： Bao, Junshu Hanson, Timothy E. Univ S Carolina Dept Stat Columbia SC 29208 USA

multivariate ordinal data are modelled as a finite stick-breaking mixture of multivariate probit models. Parametric multivariate probit models are first developed for ordinal data, then generalized to finite mixtures of multivariate probit models. Specific recommendations for prior settings are found to work well in simulations and data analyses. Interpretation of the model is carried out by examining aspects of the mixture components as well as through averaged effects focusing on the mean responses. A simulation verifies that the fitting technique works, and an analysis of alcohol drinking behaviour data illustrates the usefulness of the proposed model. (C) 2015 Statistical Society of Canada

关键词： Finite mixture of probits linear dependent Dirichlet process multivariate linear model

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General M-estimation

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JOURNAL OF multivariate ANALYSIS 1997年第1期63卷 119-135页

作者： Bai, ZD Wu, Y YORK UNIV DEPT MATH & STATN YORKON M3J 1P3CANADA

In this paper, a general form of M-estimation is proposed and some asymptotics are investigated. The model covers all linear and nonlinear regression models, AR time series, EIVR models, etc. as its special cases. The dispersion functions may be convex or differences of convex functions, the later covers almost all useful choices of the dispersion functions. (C) 1997 Academic Press.

关键词： General M-estimation asymptotics multivariate linear model

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