Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Combining food web and species distribution models for improved community projections

The ability to model biodiversity patterns is of prime importance in this era of severe environmental crisis. Species assemblage along environmental gradient is subject to the interplay of biotic interactions in complement to abiotic environmental filtering. Accounting for complex biotic interactions for a wide array of species remains so far challenging. Here, we propose to use food web models that can infer the potential interaction links between species as a constraint in species distribution models. Using a plant-herbivore (butterfly) interaction dataset, we demonstrate that this combined approach is able to improve both species distribution and community forecasts. Most importantly, this combined approach is very useful in rendering models of more generalist species that have multiple potential interaction links, where gap in the literature may be recurrent. Our combined approach points a promising direction forward to model the spatial variation of entire species interaction networks. Our work has implications for studies of range shifting species and invasive species biology where it may be unknown how a given biota might interact with a potential invader or in future climate.

Ecological studies on the intermediate host snails and the relevance to schistosomiasis control

A detailed knoledge of distribution patterns schistosome intermediate hsts and their populations dynamics and factors affecting these patterns will provide useful information about the possibilities and desirability of conducting snail control measures in various transmission situations. On the basis of various case studies the association between the occurence of human water contacts and the presence of schistosome intermediate hosts or infections in the intermediate hosts is illustrated. Other parameters affecting snail distribution patterns and density fluctuations are discussed. It is concluded that ecological studies on the intermediate host are extremely relevant, either to optimally apply existing control measures or to develop alternative measures of snail control, such as ecological or biological control.

Deliberative ecological economics: emergence and research issues

We discuss the recent emergence of "deliberative ecological economics", a field that highlights the potential of deliberation for improving environmental governance. We locate the emergence of this literature in the long concern in ecological economics over the policy implications of limited views of human action and its encounter with deliberative democracy scholarship and the model of communicative rationality as an alternative to utilitarianism. Considering criticisms over methods used and the focus of research in deliberative decision-making, we put forward a research agenda for deliberative ecological economics. Given the promising potential of deliberative processes for improving the effectiveness and legitimacy of environmental decision-making, work in this area could help advance both theory and practice in environmental governance.

Studies on the sandfly fauna of Samuel Ecological Station, Porto Velho Municipality, Rondônia State, Brazil

In a study of sandfly species in the Samuel Ecological Station, in Porto Velho, Rondônia State, the following species were identified: Lutzomyia brasiliensis, L. evangelistai, L. gomezi, L. anduzei, L. flaviscutellata, L. richardwardi, L. shawi, L. umbratilis, L. yuilli yuilli, L. dendrophyla, L. puctigeniculata, L. shannoni, L. amazonensis, L. ayrozai, L. carrerai carrerai, L. claustrei, L. davisi and L. lainsoni. L. richardwardi, L. umbratilis and L. c. carrerai were the predominant species captured of man forming 60.30% of the total catch. L. richarwardi was the most frequent at ground level (29.9%), while L. umbratilis predominated in the canopy (48.5%).

Dengue in Brazil - situation, transmission and control: a proposal for ecological control

This article discusses dengue in terms of its conceptual and historical aspects, epidemiological and clinical/pathological nature, and evolution up to the present situation in Brazil. The author discusses the ecological relationship in both the production of dengue and its control. Comparison is made between traditional dengue-control programs and a proposed socially-controlled program of an ecological nature without the use of insecticides. Stress is placed on interdisciplinary technical and scientific activity, broadbased participation by communities in discussing methodological aspects involving them, and prospective evaluation comparing the communities selected for intervention and control communities with regard to clinical and subclinical dengue cases and vector infestation rates in relation to climatic, socio-economic, and behavioural factors.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Decision-theoretic analysis of forensic sampling criteria using Bayesian decision networks

Sampling issues represent a topic of ongoing interest to the forensic science community essentially because of their crucial role in laboratory planning and working protocols. For this purpose, forensic literature described thorough (Bayesian) probabilistic sampling approaches. These are now widely implemented in practice. They allow, for instance, to obtain probability statements that parameters of interest (e.g., the proportion of a seizure of items that present particular features, such as an illegal substance) satisfy particular criteria (e.g., a threshold or an otherwise limiting value). Currently, there are many approaches that allow one to derive probability statements relating to a population proportion, but questions on how a forensic decision maker - typically a client of a forensic examination or a scientist acting on behalf of a client - ought actually to decide about a proportion or a sample size, remained largely unexplored to date. The research presented here intends to address methodology from decision theory that may help to cope usefully with the wide range of sampling issues typically encountered in forensic science applications. The procedures explored in this paper enable scientists to address a variety of concepts such as the (net) value of sample information, the (expected) value of sample information or the (expected) decision loss. All of these aspects directly relate to questions that are regularly encountered in casework. Besides probability theory and Bayesian inference, the proposed approach requires some additional elements from decision theory that may increase the efforts needed for practical implementation. In view of this challenge, the present paper will emphasise the merits of graphical modelling concepts, such as decision trees and Bayesian decision networks. These can support forensic scientists in applying the methodology in practice. How this may be achieved is illustrated with several examples. The graphical devices invoked here also serve the purpose of supporting the discussion of the similarities, differences and complementary aspects of existing Bayesian probabilistic sampling criteria and the decision-theoretic approach proposed throughout this paper.

The snail hosts of schistosomiasis: some evolutionary and ecological perspectives in relation to control

Despite opportunities for radiation provided by spatio-temporal isolation, the basic morphological plan of pulmonate snails has remained conservative. In consequence of the resulting dearth of morphological characters and their plasticity, there is a case for using biochemical characters such as exogenous chemicals released by the snails (e.g. amino acids) and their chemoreception niche as taxonomic aids to classify snails of medical importance. As these same chemicals are used by snails to distinguish conspecifics they could also be used as "environmental antibodies" in controlled release formulations (CRF's) designed to remove target snails in a specific, cost-effective and ecologically acceptable manner. The snails, surface-living bacteria, algae and macrophytic plants are considered as co-evolved, interactive modular systems with strong mutualistic elements. Recently, anthropogenic perturbations such as deforestation, and damming of flowing waters, have benefited these modules whereas others such as river canalization, acid deposition, accumulation of pesticide residues and eutrophication have harmed them. Research is needed to elucidate the factors which limit the growth of snails in primitive habitats, uninfluenced by man, as well as in those subject to harmful anthropogenic factors. The understanding thus gained could be applied to develop cost-effective primary health care strategies to reduce or prevent transmission of schistosomiasis and other water related diseases.

The use and mis-use of some ecological terms and concepts in epidemiology

The article discusses the current use and mis-use of ecological terms and concepts in epidemiological literature, and in special, in works dealing with zoonotic diseases. A selection of examples was taken from papers recently published on the transmission of Chagas' disease by Triatoma sordida. Proper definitions are listed, with the intent of helping non-ecologists to use those terms and concepts correctly.