Small to train,small to test: Dealing with low sample size in model evaluation

Sample size is a key issue in species distribution modelling. While many studies focused on the relevance of sample size for model calibration, the importance of the size of the dataset used for model evaluation has received much less attention. Here, we highlight two previously published approaches to address the problem, and which are relatively simple to implement: the pooling evaluation and the implementation of null models. We discuss the importance of these or other potential approaches that are critical for model evaluation in rare species, which represent the bulk of biodiversity, and for which accurate models are most necessary in a conservation context.     

PATHWAYS to improve end-of-life care--a community approach

Midwest Bioethics Center responded to the SUPPORT study with a strategic initiative called PATHWAYS to Improve End-of-Life Care: A Community Approach. This article introduces that initiative and reviews its substantial contributions in the broad sense. The effects of this program, although its evaluation has yet to be completed, are far-reaching because PATHWAYS tackled the problem of dying, not as a medical problem, but as a problem for the community as a whole.     

菊花种质资源与遗传改良研究进展

本文对菊花(Dendranthemamorifolium)种质资源的调查、搜集、研究与评价、菊花杂交育种、诱变育种和生物技术育种等方面取得的成果进行了综述,并对目前存在的问题及今后的发展方向进行了探讨.     

菊花种质资源与遗传改良研究进展

本文对菊花(Dendranthema morifolium)种质资源的调查、搜集、研究与评价、菊花杂交育种、诱变育种和生物技术育种等方面取得的成果进行了综述,并对目前存在的问题及今后的发展方向进行了探讨。     

The methods of automatic analysis of epileptic EEG

The methods of automatic evaluation of epileptic EEG are reviewed. The aims of the computer analysis of seizure activity and different approaches to this problem are presented.     

Ligand-receptor interaction. Klotz-Hunston problem for two classes of binding sites and its solution

The problem of the affinity and quantity determination of two classes of binding sites for ligand-receptor interaction using either Scatchard or Klotz plots was considered. Klotz and Hunston previously solved this problem only for the case of a representation of experimental data using the Scatchard plot. Since their publication, it was the common view that only the use of the Scatchard plot allows solving this problem. However, in some cases, using the Klotz plot is more convenient for a representation of experimental data concerning ligand-receptor interaction, though usually, this plot was used only for the evaluation of receptor affinity with one class of binding sites. In the present paper, it was demonstrated that Klotz plot also could be used for the evaluation affinity and quantity of two classes of binding sites.     

Flexible modelling in survival analysis. Structuring biological complexity from the information provided by tumor markers

The aim of the present article is to introduce and discuss the problem of optimal modelling of the prognostic information provided by putative prognostic variables, possibly measured on a quantitative scale. A number of methodological aspects will be treated, with particular reference to the role of spline functions and artificial neural networks, which will be discussed in the context of the analysis of survival data. The problem of the evaluation and the choice of the optimal statistical models will be examined, with particular attention to the critical aspects related to the definition of prognostic indexes on the basis of the results of the selected models. Clinical examples in breast cancer on the evaluation of the prognostic impact of several tumor markers are provided. This paper is addressed to all researchers who are interested in the evaluation of the prognostic role of tumor markers, therefore we will stress the necessity of integrating the methodologies of biological, clinical and statistical research in the assessment of prognosis.     

A comparative analysis based on different strength criteria for evaluation of risk factor for dental implants

A numerical analysis is developed to study the interaction phenomena between endousseus titanium dental implants and surrounding jawbone tissue. The interest is focused on the most appropriate evaluation of the stress state arising in the tissue because of the implant under physiological loading. The problem is considered with regard to linear elastic response of the one and to short time effect. Different configurations of bone-implant system are described, using axial-symmetrical and three-dimensional models, by means of finite and geometric element method. The investigation attains to the stress states induced in bone that lead to a limit condition near the effective failure surface. The parameter commonly adopted in literature, such as the Von Mises stress, represents an excessive simplification of problem formulation, leading to an incorrect evaluation of the real failure risk for the implant, due to the assumption of the isotropic and deviatoric nature of the adopted stress measure. More suitable criterion can be assumed, such as the Tsai-Wu criterion, to take into account the anisotropy that characterises the response of bone, as well as the influence of a hydrostatic stress state. The analysis developed offers a comparison of results by using different criteria, leading to an evaluation of reliability of the procedure to be followed and addressing also to an evaluation of a risk factor for the implant investigated.     

A Multinomial Model for the Quality Control of Colony Counting Procedures

The so‐called good‐laboratory‐practice (GLP) test provides an experimental design and appropriate statistical analysis for the problem of analyst performance assessment in microbiological laboratories. For a given sample material multiple dilution series are generated yielding colony counts from several dilution levels. Statistical evaluation is based on the assumption of Poisson‐distributed colony forming units. In this paper a new model based on conditional binomial and multinomial distributions is presented and it is shown how it is related to the standard model which assumes Poisson‐distributed colony counts. The effects of common working errors on the statistical evaluation of the GLP‐test are investigated.     

退化森林生态系统评价指标体系研究进展

森林是陆地生态系统的主要组成部分,而森林退化是全球面临的主要环境问题之一,准确评价退化森林生态系统是进行森林生态系统恢复与重建的重要前提,建立合理的评价指标体系目前已成为生态学研究的热点问题。在研究国内外提出的关于退化森林生态系统评价理论的基础上,综述了森林退化的定义、特征和一般过程,梳理了退化森林生态系统评价指标筛选的一般原则和指标体系构建的主要方法,分析比较了不同学者所提出的主要评价指标。并在此基础上,重新筛选、构建了一套退化森林生态系统评价指标体系,即从生态系统的组成结构、功能和生境这3个方面选取了32个能够较全面反映退化生态系统主要特征的评价指标,以期为构建我国区域尺度上的退化森林生态系统评价指标体系提供参考,为退化森林生态系统的恢复和重建提供科学依据。总结分析了退化森林生态系统评价指标体系在构建过程中产生的一些问题和不足,提出了今后开展研究和探索应该深入的方向,以提高评价指标体系的科学性、准确性和合理性。     

Complexity of the simplest phylogenetic estimation problem

The maximum-likelihood (ML) solution to a simple phylogenetic estimation problem is obtained analytically The problem is estimation of the rooted tree for three species using binary characters with a symmetrical rate of substitution under the molecular clock. ML estimates of branch lengths and log-likelihood scores are obtained analytically for each of the three rooted binary trees. Estimation of the tree topology is equivalent to partitioning the sample space (space of possible data outcomes) into subspaces, within each of which one of the three binary trees is the ML tree. Distance-based least squares and parsimony-like methods produce essentially the same estimate of the tree topology, although differences exist among methods even under this simple model. This seems to be the simplest case, but has many of the conceptual and statistical complexities involved in phylogeny estimation. The solution to this real phylogeny estimation problem will be useful for studying the problem of significance evaluation.     

生态建设的理论分析

20世纪80年代以来,生态恢复逐渐成为生态学和环境科学研究的热点领域。总结了近年来有关生态恢复的众多研究成果,认为生态建设是人类理性行为参与下积极的生态恢复与重建过程,它具有复杂性、针对性、动态性和不确定性特征,受地理环境地域分异的影响,其类型多种多样。从方案运筹的角度,提出了生态建设的共性原则,包括面向区域的问题导向原则、目标的科学性原则、参与的广泛性原则和科学监测与评价原则。生态建设是一个不断试验、学习和优化的过程。具体包括问题识别、方案设计、决策、实施、监测与评价以及方案调整等重要环节。公众参与对于生态建设是一种很好的知识、信息和资源输入渠道,对活化生态建设的管理运行机制,提高生态建设决策的科学性和有效性能够发挥重要作用。以这些理论分析为依据,对中国生态建设中存在的主要问题展开深入剖析,并提出建立科学评价机制是提高生态建设有效性的核心方略。     

Two-dimensional grey cloud clustering-fuzzy entropy comprehensive assessment model for river health evaluation

Abstract

The river health evaluation is typically complex non-linear system with characteristics of fuzziness and randomness. However, conventional gray clustering method has difficult to effectively describe fuzzy and random information simultaneously. For this purpose, the cloud model and fuzzy entropy theory are introduced to establish 2D gray cloud clustering-fuzzy entropy comprehensive evaluation model. Different with health level models, it reflects river health situation from aspects of health level and corresponding water body complexity simultaneously. The health level is obtained by gray cloud whitened weight function (first sub-system) and fuzzy entropy represents complexity and fuzziness of river health situation (second sub-system). Moreover, multi-level river health evaluation indicator system is constructed with dividing indicators into common and distinct sections according to differences on river characteristics. Meanwhile, indicator weights are determined by renewed combined weighting method based on minimum deviation principle. Finally, we conduct health evaluation work for rivers in the Taihu basin. The evaluation health levels and fuzzy entropy for river A–G are H3 (0.4888, relatively significant); H2 (0.5476, relatively fuzzy); H2 (0.7526, fuzzy); H2 (0.4731, relatively significant); H2 (05138, relatively fuzzy); H3 (0.5822, relatively fuzzy), and H2 (0.4064, relatively significant), respectively. Results are consistent with current river health situation and more intuitive than compared models. Furthermore, evaluation results with four different weighting methods are compared to further demonstrate rationality of the weighting method and evaluation model. Hence, the model proposed is demonstrated to provide new insight for solving river health assessment problem effectively.     

Reconstruction of cell-electrode-adjacencies on multielectrode arrays

The multichannel recordings of signals of many cells cultivated on a multielectrode array (MEA) impose some challenging problems. A meanwhile classic problem is the separation of the recordings of a single electrode into classes of recordings where each class is caused by a single cell. This is the well-known spike sorting. A “dual” problem is the determination of the set of electrodes that record signals of a single cell. This set is called the neighborhood of the cell and has often more than one element if the MEA has a large number of electrodes with high density. A method for the reconstruction of the neighborhoods from the multichannel recordings is presented. Special effort is directed to a precise peak detection. For the evaluation of the algorithm, artificial data, obtained from an appropriate model of MEA recordings, are used. Because the artificial data provide a ground truth, an evaluation of the accuracy of the algorithm is possible. The algorithm works well for realistic parameters.     

Real-time quantification of human physiological state in high temperature environments based on variable weight theory

Accurate real-time evaluation of human physiological state is significant for safety guidance and early warning for people in high temperature environments. The constant weight method often makes the evaluation results deviating from reality. In this paper, the variable weight theory is adopted to solve above problem. Firstly, a human physiological state evaluation system is proposed. Secondly, the constant weight and variable weight methods are used to obtain the weights of the indexes. Thus, the comprehensive evaluation score is obtained to quantify the human physiological state. Finally, a case study is conducted to demonstrate and verify the proposed evaluation system. It indicates that, the variable weight of rectal temperature, skin temperature, systolic pressure and heart rate is 0.2∼0.77, 0.11∼0.61, 0.03∼0.31, 0.03∼0.31, respectively. And the weights of the skin temperature and the rectal temperature account for a relatively large proportion, ranging from 50% to 92%. The physiological parameters with small constant weight may account for a larger percentage in the evaluation when the physiological parameters reach an extremely harmful condition. This paper can provide more reasonable and scientific method in physiological state quantification for people in high temperature environments.     

退化森林生态系统恢复评价研究综述

森林退化是一个世界性的问题,对退化的森林进行恢复评价是合理地进行森林生态系统管理的基础。介绍了森林退化的概念,综述了退化森林生态系统恢复评价的一般程序,主要包括恢复目标的确定、参照系的选择、评价指标体系的构建及定量评价等几个方面。目前,大多数退化森林恢复评价主要包括物种多样性、植被结构和生态学过程3个方面。其中,物种多样性包括物种丰富度和多度等;植被结构包括植被盖度、乔木密度、高度、胸高断面积、生物量和凋落物结构等;生态学过程包括养分库、土壤有机质以及生物间的相互关系等。不同的研究者或管理者由于对恢复其生态系统服务功能的需求存在差异,评价退化生态系统恢复的角度也不一样。恢复评价可以从特殊种群到整个生态系统的不同层次进行。在深刻理解森林退化定义的基础上,建立现实的目标和正确地选择参照系是恢复评价的前提。     

干旱内陆流域河道外生态需水量评价——以黑河流域为例

河道外生态系统需水量的合理评价是干旱区水资源合理配置与管理、生态环境保护与建设中最为关键的科学问题。基于不同植被蒸散发潜力估算模型,依据不同生态系统及同一生态系统在不同气候与地理区域具有不同生态需水规律的特点,提出了可模拟和评价不同时期生态系统需水量的方法,不仅能体现生态系统需水量的年际变化,也能反映年内不同时间段(月、季节甚至每日)的需水量变化,并提出干旱区生态适宜需水量在不同时期是一个区间。以黑河流域中下游地区为研究区域分析其生态需水量,结果表明:黑河中游地区年平均生态需水量(11.16±2.67)×108m3,其中绿洲生态系统需水(9.13±2.29)×108m3;下游地区生态需水量(16.16±4.04)×108m3,现状绿洲生态体系需水(11.06±2.77)×108m3,现阶段实施的下游分水9.7亿m3/年的方案,可以促使现有绿洲生态系统有一个良好的结构与功能,并给出了不同典型年不同月份的生态需水量及其变化。     

基于多目标的杨树速生丰产林主伐决策分析

经济效益综合评价是产业决策研究的重要内容.从系统工程观点来看,经济效益综合评价本质上是一个有限方案多目标决策问题.因此,本文采用多目标决策法对杨树速生丰产林的主伐决策进行研究,以年均净现值、内部收益率、土地期望价、效益成本比、成本利润率为指标,提出用熵技术法确定评价指标权重,结合"理想点"法、TOPSIS法和线性加权和法三种方法对决策方案进行排序择优,得到不同排序结果,最后用平均值法得到最终综合评价结果.结果表明,对所研究的密度为10×10m~2、8×8m~2、6×8m~2、5×6m~2的杨速生丰产林进行分析得到综合评价结果,其最优主伐龄分别为:13年、10年、9年、9年.随着密度的增大,经济成熟龄提前.本研究表明该方法对杨树速生丰产林的主伐决策研究是有效可行的.     

Mapping indicator models: From intuitive problem structuring to quantified decision-making in sustainable forest management

Most commonly, sustainability indicator sets presented as lists do not take into account interactions among indicators in a systematic manner. Vice versa, existing environmental indicator systems do not provide a formalized approach for problem structuring and quantitative decision support. In this paper, techniques for considering indicator relationships are highlighted and a coupled approach between a qualitative and a quantitative method is analysed. Cognitive mapping (CM) is used for structuring indicators and three different causal maps are derived based on established sustainability concepts: (a) criteria and indicators (C&I hierarchy), (b) indicator network, and (c) Driving Force-Pressure-State-Impact-Response (DPSIR) system. These maps are transferred to the Analytic Network Process (ANP) to allow their application in multi-criteria decision analysis (MCDA).In an application example, Pan-European indicators for sustainable forest management (SFM) are utilized in an ANP-based assessment. The effects of the model structure on the overall evaluation result are demonstrated by means of three reporting periods on Austrian forestry.In a comparative analysis of CM and ANP it is tested whether their measures of indicator significance do correspond. Both centrality in CM and single limited priorities in ANP have been reported to identify key indicators that play an important role in networks. We found out that the correspondence between CM and ANP is the stronger the more rigidly cause-effect relationships are interpreted, which is the case for the DPSIR system of SFM indicators.It is demonstrated that using indicator sets without consideration of the indicator interactions will cause shortcomings for evaluation and assessment procedures in SFM. Given strict and consistent definition of causal indicator relationships, a coupled use of CM and ANP is recommendable for both enhancing the process of problem structuring as well as supporting preference-based evaluation of decision alternatives.     

预测物种潜在分布区——比较SVM与GARP

 物种分布与环境因子之间存在着紧密的联系,因此利用环境因子作为预测物种分布模型的变量是当前最普遍的建模思路,但是绝大多数物种分 布预测模型都遇到了难以解决的“高维小样本"问题。该研究通过理论和实践证明,基于结构风险最小化原理的支持向量机(Support vector machine, SVM)算法非常适合“高维小样本"的分类问题。以20种杜鹃花属(Rhododendron)中国特有种为检验对象,利用标本数据和11个1 km×1 km的栅格环境数据层作为模型变量,预测其在中国的潜在分布区,并通过全面的模型评估——专家评估,受试者工作特征(Receiver operator characteristic, ROC)曲线和曲线下方面积(Area under the curve, AUC)——来比较模型的性能。我们实现了以SVM为核心的物种分布预测 系统,并且通过试验证明其无论在计算速度还是预测效果上都远远优于当前广泛使用的规则集合预测的遗传算法(Algorithm for rule-set prediction, GARP)预测系统。