A unified framework for connectionist systems

Pattern classification using connectionist (i.e., neural network) models is viewed within a statistical framework. A connectionist network's subjective beliefs about its statistical environment are derived. This belief structure is the network's subjective probability distribution. Stimulus classification is interpreted as computing the most probable response for a given stimulus with respect to the subjective probability distribution. Given the subjective probability distribution, learning algorithms can be analyzed and designed using maximum likelihood estimation techniques, and statistical tests can be developed to evaluate and compare network architectures. The framework is applicable to many connectionist networks including those of Hopfield (1982, 1984), Cohen and Grossberg (1983), Anderson et al. (1977), and Rumelhart et al. (1986b).     

Towards a definition of living systems: A theory of ecological support for behavior

It is proposed that the Darwinian theoretical approach and account of living systems has not yet been clearly given. A first approximation to this is attempted, focussing on behavior in evolving environments. A theoretical terminology is defined emphasizing the mutuality of organism and environment and the existence of biologically theoretical entities.     

A framework for environmental decision support in cities incorporating organizational LCA

The International Journal of Life Cycle Assessment - Cities contribute to and are affected by several environmental pressures within and beyond city boundaries. Urban decision makers struggle to...     

Evaluation of a decision support system in a medical environment

This paper describes the impact of a decision support system on the quality of recorded diagnoses and the completeness of medical records. The assumption is that for quality assessment purposes enough data have to be recorded in an electronic medical record so that diagnostic decisions can be justified. The hypotheses were tested that active decision support will lead to better quality recorded diagnoses and more complete medical records. Three groups of ten GPs were presented with 10 cases each. The GPs had to enter the data about these cases in a GP information system. One group of GPs was not supported. The second group was presented with the ICHPPC-II-Defined criteria that had to be fulfilled when a diagnosis was entered. In a third group, the GPs were asked those data that were needed to justify an entered diagnosis (active support). It could be shown that the last group of GPs entered better quality diagnoses than the other two groups. These latter groups also entered so little data that most of their diagnoses could not be justified. It is concluded from the study that only active decision support will lead to better diagnoses and a more complete medical record that can be used for quality assessment.     

A proposed unified framework for biological invasions

There has been a dramatic growth in research on biological invasions over the past 20 years, but a mature understanding of the field has been hampered because invasion biologists concerned with different taxa and different environments have largely adopted different model frameworks for the invasion process, resulting in a confusing range of concepts, terms and definitions. In this review, we propose a unified framework for biological invasions that reconciles and integrates the key features of the most commonly used invasion frameworks into a single conceptual model that can be applied to all human-mediated invasions. The unified framework combines previous stage-based and barrier models, and provides a terminology and categorisation for populations at different points in the invasion process.     

A unified theory for the development of cancer

It is postulated that cancer is the result of genetic and epigenetic changes that occur mainly in stem (precursor) cells of various cell types. I propose that there are three classes of genes which are involved in the development of cancer. These are: Class I, II and III oncogenes. The classification is based on the way the oncogene acts at the cellular level to further the development of cancer. Genetic changes, that is point mutations, deletions, inversions, amplifications and chromosome translocations, gains or losses in the genes themselves or epigenetic changes in the genes (e.g. DNA hypomethylation) or in the gene products (RNA or protein) are responsible for the development of cancer. Changes of oncogene activity have a genetic or epigenetic origin or both and result in quantitative or qualitative differences in the oncogene products. These are involved in changing normal cells into the cells demonstrating a cancer phenotype (usually a form of dedifferentiated cell) in a multistep process. There are several pathways to cancer and the intermediate steps are not necessarily defined in an orderly fashion. Activation of a particular Class I or II oncogene and inactivation of a Class III oncogene could occur at any step during the development of cancer. Most benign or malignant tumors consist of a heterogeneous mixture of dedifferentiated cells arising from a single cell.     

Energy intensities in ecological and economic systems

The concept of energy intensity (the energy needed, directly and indirectly, to effect the production of a “modity” an be applied to both economic and ecological systems. Hannon (1979) and Constanza (1980) have remarked on the lack of variation of energy intensity between different commodities for an ecosystem and an economic system, respectively. T This is particularly surprising for the ecosystem, since it seems to violate the traditional pyramid view of trophic systems. I show rigorously that Hannon's result is a mathematical consequence of his assumptions which are physically unjustified. I present a similar intuitive argument for Costanza's result, which is based on controversial but not physically unacceptable assumptions. The discussion brings out common threads of input-output economics and ecosystem analysis.     

A wheat canopy model for use in disease management decision support systems

A model is described which predicts those aspects of wheat canopy development and growth which are influential in determining the development of epidemics of foliar pathogens, the efficacy of foliar applied fungicides and the impact of disease on yield; specifically the emergence, expansion and senescence of upper culm leaves in relation to anthesis date. This focus on upper leaves allowed prediction of leaf emergence dates by reference to anthesis, rather than sowing. This avoided the step changes in flag leaf emergence date with temperature, reported with earlier models, without the additional complexity of a stochastic approach. The model is designed to be coupled to models of foliar disease, where the primary effect on yield is via reduction in green canopy area and hence interception of photosynthetically active radiation. Mechanisms were incorporated to allow observations of crop development during the growing season to update state variables and adjust parameters affecting future predictions. The model was calibrated using experimental data, and validated against independent observations of crop development on four wheat cultivars across seven contrasting sites in the UK. Anthesis date and upper culm leaf emergence were always predicted within one week of their observed dates.     

甘肃省生态环境与社会经济系统协调发展的耦合分析

社会经济发展与当地自然生态环境保护之间的耦合协调是可持续发展研究的热点问题。本研究以甘肃省为研究对象,构建甘肃省自然生态系统与社会经济系统耦合协调度模型及综合评价指标体系,分析甘肃省2007-2017年间社会经济发展与自然生态环境质量变化之间的耦合协调程度及演变过程。结果表明：（1）甘肃省的自然环境质量指数在2007-2017年间呈先波动下降后逐步上升的变化趋势,而甘肃省社会经济发展水平自然环境系统的综合水平在2007-2017年间整体呈现上升趋势;（2）2007-2017年,甘肃省的社会经济与自然生态环境质量的发展状态从失调阶段逐步过渡到协调阶段,说明这社会经济系统与自然生态环境系统的耦合过程正从磨合阶段向着高水平有序状态稳固发展,10年间甘肃省生态环境与社会经济发展的耦合协调性有明显改善。面向自然生态环境质量与社会经济发展速度的动态讨论可以看出：（1）甘肃省自然环境和社会经济变化速率的剪刀差的演变过程经过了差异较大但无明显制约-社会经济对生态环境压力逐步加重-社会经济发展与生态支撑能力同步回升的演变过程;（2）2007-2014年,甘肃省处于自然生态环境的发展速度小于社会经济的发展速度阶段,社会经济发展受生态环境的限制和约束,经济发展对生态环境的影响也几乎为零,但其相互胁迫程度不断增加,到2015-2017年,自然生态环境的发展速度大于社会经济的发展速度,2015-2017年自然生态环境的增速高于社会经济发展速度,产业结构优化和自然生态环境保护措施开始起效,社会经济与自然生态环境之间的耦合协调度越来越好。     

A decision-analytic framework for impact assessment part I: LCA and decision analysis

Life-cycle assessments (LCAs) are conducted to satisfy the aspiration of decision makers to consider the environment in their decision making. This paper reviews decision analysis and discusses how it can be used to structure the assessment and to integrate characterization and valuation. The decision analytic concepts of objectives (goals) and attributes (indicators of the degree to which an objective is achieved) are used to describe steps of the assessment of the entire impact chain. Decision analysis distinguishes among different types of objectives and attributes; it describes how these relate to each other. Impact indicators such as the Human Toxicity Potential are constructed attributes. A means-ends objectives network can show how the different constructed attributes relate to the objective of protecting the environment. As LCA takes disparate environmental impacts into account, it needs to assess their relative importance. Trade-off methods in decision analysis are grouped into utility theory and multicriteria decision aids; they have different advantages and disadvantages, but are all more sophisticated than simple weighting. The performance of the different trade-off methods has not yet been tested in an LCA context. In the second part of the paper, we present criteria for the development of characterization methods.     

Credit of ecological interactions: A new conceptual framework to support conservation in a defaunated world

As defaunation spreads through the world, there is an urgent need for restoring ecological interactions, thus assuring ecosystem processes. Here, we define the new concept of credit of ecological interactions, as the number of interactions that can be restored in a focal area by species colonization or reintroduction. We also define rewiring time, as the time span until all the links that build the credit of ecological interactions of a focal area have become functional again. We expect that the credit will be gradually cashed following refaunation in rates that are proportional to (1) the abundance of the reintroduced species (that is expected to increase in time since release), (2) the abundance of the local species that interact with them, and (3) the traits of reintroduced species. We illustrated this approach using a theoretical model and an empirical case study where the credit of ecological interactions was estimated. This new conceptual framework is useful for setting reintroduction priorities and for evaluating the success of conservation initiatives that aim to restore ecosystem services.     

Factors influencing the transferability of medical decision support systems

Transferability is a key issue in the development and implementation of medical decision support systems. Such systems have up to now tended to be confined to the development site. Transferability represents the integrated effect of several more basic attributes of Decision Support Systems. These attributes can be considered to belong to two main groups: those concerned with the Medical Domain (of the system) and those concerned with the Information Technology by which the System functions. Among the Domain issues the most important are: Epidemiology, Terminology and Methodology. Concerning the Information Technology issues the most important are: Knowledge Acquisition and Representation methods, Database design and integration with inference mechanism. The effect of each of the individual factors is considered by illustrations from the literature and by studying the results of recent experiments where databases and decision support systems from different countries are interchanged. This exercise allows some planning in the design of future systems with the aim of improving overall transferability and therefore applicability.     

A conceptual framework for the evolution of ecological specialisation

Ecology Letters (2011) 14: 841-851 ABSTRACT: Ecological specialisation concerns all species and underlies many major ecological and evolutionary patterns. Yet its status as a unifying concept is not always appreciated because of its similarity to concepts of the niche, the many levels of biological phenomena to which it applies, and the complexity of the mechanisms influencing it. The evolution of specialisation requires the coupling of constraints on adaptive evolution with covariation of genotype and environmental performance. This covariation itself depends upon organismal properties such as dispersal behaviour and life history and complexity in the environment stemming from factors such as species interactions and spatio-temporal heterogeneity in resources. Here, we develop a view on specialisation that integrates across the range of biological phenomena with the goal of developing a more predictive conceptual framework that specifically accounts for the importance of biotic complexity and coevolutionary events.     

A unified framework of life cycle assessment

The International Journal of Life Cycle Assessment - The dichotomy between the attributional approach and the consequential approach is one of the major unsettled questions in life cycle...     

A foliar disease model for use in wheat disease management decision support systems

A model of winter wheat foliar disease is described, parameterised and tested for Septoria tritici (leaf blotch), Puccinia striiformis (yellow rust), Erysiphe graminis (powdery mildew) and Puccinia triticina (brown rust). The model estimates disease‐induced green area loss, and can be coupled with a wheat canopy model, in order to estimate remaining light‐intercepting green tissue and hence the capacity for resource capture. The model differs from those reported by other workers in three respects. First, variables (such as weather, host resistance and inoculum pressure) that affect disease risk are integrated in their effect on disease progress. The agronomic and meteorological data called for are restricted to those commonly available to growers by their own observations and from meteorological service networks. Second, field observations during the growing season can be used both to correct current estimates of disease severity and to modify parameters that determine predicted severity. Third, pathogen growth and symptom expression are modelled to allow the effects of fungicides to be accounted for as protectant activity (reducing infections that occur postapplication) and eradicant activity (reducing growth of presymptomatic infections). The model was tested against data from a wide range of sites and varieties and was shown to predict the expected level of disease sufficiently accurately to support fungicide treatment decisions.     

A unified framework for diversity gradients: the adaptive trait continuum

Aim Adaptive trait continua are axes of covariation observed in multivariate trait data for a given taxonomic group. These continua quantify and summarize life‐history variation at the inter‐specific level in multi‐specific assemblages. Here we examine whether trait continua can provide a useful framework to link life‐history variation with demographic and evolutionary processes in species richness gradients. Taking an altitudinal species richness gradient for Mediterranean butterflies as a study case, we examined a suite of traits (larval diet breadth, adult phenology, dispersal capacity and wing length) and species‐specific habitat measures (temperature and aridity breadth). We tested whether traits and species‐specific habitat measures tend to co‐vary, whether they are phylogenetically conserved, and whether they are able to explain species distributions and spatial genetic variation in a large number of butterfly assemblages. Location Catalonia, Spain. Methods We formulated predictions associated with species richness gradients and adaptive trait continua. We applied principal components analyses (PCAs), structural equation modelling and phylogenetic generalized least squares models. Results We found that traits and species‐specific habitat measures covaried along a main PCA axis, ranging from multivoltine trophic generalists with high dispersal capacity to univoltine (i.e. one generation per year), trophic specialist species with low dispersal capacity. This trait continuum was closely associated with the observed distributions along the altitudinal gradient and predicted inter‐specific differences in patterns of spatial genetic variability (F_ST and genetic distances), population responses to the impacts of global change and local turnover dynamics. Main conclusions The adaptive trait continuum of Mediterranean butterflies provides an integrative and mechanistic framework to: (1) analyse geographical gradients in species richness, (2) explain inter‐specific differences in population abundances, spatial distributions and demographic trends, (3) explain inter‐specific differences in patterns of genetic variation (F_ST and genetic distances), and (4) study specialist–generalist life‐history transitions frequently involved in butterfly diversification processes.