The subjectivist interpretation of probability and the problem of individualisation in forensic science

This paper presents and discusses further aspects of the subjectivist interpretation of probability (also known as the 'personalist' view of probabilities) as initiated in earlier forensic and legal literature. It shows that operational devices to elicit subjective probabilities - in particular the so-called scoring rules - provide additional arguments in support of the standpoint according to which categorical claims of forensic individualisation do not follow from a formal analysis under that view of probability theory.

Combining probabilistic land-use change and tree population dynamics modelling to simulate responses in mountain forests

Altitudinal tree lines are mainly constrained by temperature, but can also be influenced by factors such as human activity, particularly in the European Alps, where centuries of agricultural use have affected the tree-line. Over the last decades this trend has been reversed due to changing agricultural practices and land-abandonment. We aimed to combine a statistical land-abandonment model with a forest dynamics model, to take into account the combined effects of climate and human land-use on the Alpine tree-line in Switzerland. Land-abandonment probability was expressed by a logistic regression function of degree-day sum, distance from forest edge, soil stoniness, slope, proportion of employees in the secondary and tertiary sectors, proportion of commuters and proportion of full-time farms. This was implemented in the TreeMig spatio-temporal forest model. Distance from forest edge and degree-day sum vary through feed-back from the dynamics part of TreeMig and climate change scenarios, while the other variables remain constant for each grid cell over time. The new model, TreeMig-LAb, was tested on theoretical landscapes, where the variables in the land-abandonment model were varied one by one. This confirmed the strong influence of distance from forest and slope on the abandonment probability. Degree-day sum has a more complex role, with opposite influences on land-abandonment and forest growth. TreeMig-LAb was also applied to a case study area in the Upper Engadine (Swiss Alps), along with a model where abandonment probability was a constant. Two scenarios were used: natural succession only (100% probability) and a probability of abandonment based on past transition proportions in that area (2.1% per decade). The former showed new forest growing in all but the highest-altitude locations. The latter was more realistic as to numbers of newly forested cells, but their location was random and the resulting landscape heterogeneous. Using the logistic regression model gave results consistent with observed patterns of land-abandonment: existing forests expanded and gaps closed, leading to an increasingly homogeneous landscape.

Perturbation expansions of multilocus fixation probabilities for frequency-dependent selection with applications to the Hill-Robertson effect and to the joint evolution of helping and punishment.

Natural populations are of finite size and organisms carry multilocus genotypes. There are, nevertheless, few results on multilocus models when both random genetic drift and natural selection affect the evolutionary dynamics. In this paper we describe a formalism to calculate systematic perturbation expansions of moments of allelic states around neutrality in populations of constant size. This allows us to evaluate multilocus fixation probabilities (long-term limits of the moments) under arbitrary strength of selection and gene action. We show that such fixation probabilities can be expressed in terms of selection coefficients weighted by mean first passages times of ancestral gene lineages within a single ancestor. These passage times extend the coalescence times that weight selection coefficients in one-locus perturbation formulas for fixation probabilities. We then apply these results to investigate the Hill-Robertson effect and the coevolution of helping and punishment. Finally, we discuss limitations and strengths of the perturbation approach. In particular, it provides accurate approximations for fixation probabilities for weak selection regimes only (Ns < or = 1), but it provides generally good prediction for the direction of selection under frequency-dependent selection.

Incident Hepatitis C Virus Infections in the Swiss HIV Cohort Study : changes in treatment uptake and outcomes between 1991 and 2013

Background: The hepatitis C virus (HCV) epidemic is evolving rapidly in patients infected with human immunodeficiency virus (HIV). We aimed to describe changes in treatment uptake and outcomes of incident HCV infections before and after 2006, the time-point at which major changes in HCV epidemic became apparent. Methods.  We included all adults with an incident HCV infection before June 2012 in the Swiss HIV Cohort Study, a prospective nationwide representative cohort of individuals infected with HIV. We assessed the following outcomes by time period: the proportion of patients starting an HCV therapy, the proportion of treated patients achieving a sustained virological response (SVR), and the proportion of patients with persistent HCV infection during follow-up. Results.  Of 193 patients with an HCV seroconversion, 106 were diagnosed before and 87 after January 2006. The proportion of men who have sex with men increased from 24% before to 85% after 2006 (P < .001). Hepatitis C virus treatment uptake increased from 33% before 2006 to 77% after 2006 (P < .001). Treatment was started during early infection in 22% of patients before and 91% after 2006 (P < .001). An SVR was achieved in 78% and 29% (P = .01) of patients treated during early and chronic HCV infection. The probability of having a detectable viral load 5 years after diagnosis was 0.67 (95% confidence interval [CI], 0.58-0.77) in the group diagnosed before 2006 and 0.24 (95% CI, 0.16-0.35) in the other group (P < .001). Conclusions. In recent years, increased uptake and earlier initiation of HCV therapy among patients with incident infections significantly reduced the proportion of patients with replicating HCV.

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.

Unexpectedly late expression of intracellular CD3epsilon and TCR gammadelta proteins during adult thymus development.

During adult thymus development immature CD4(-)CD8(-) [double-negative (DN)] precursor cells pass through four phenotypically distinct stages defined by expression of CD44 and CD25: CD44(hi)CD25(-) (DN1), CD44(hi)CD25(+) (DN2), CD44(lo)CD25(+) (DN3) and CD44(lo)CD25(-) (DN4). Although it is well established that the TCR beta, gamma and delta genes are rearranged and expressed in association with the CD3 components in DN thymocytes, the precise timing of expression of the TCR and CD3 proteins has not been determined. In this report we have utilized a sensitive intracellular (ic) staining technique to analyze the expression of ic CD3epsilon, TCR beta and TCR gammadelta proteins in immature DN subsets. As expected from previous studies of TCR beta rearrangement and mRNA expression, icTCR beta(+) cells were first detected in the DN3 subset and their proportion increased thereafter. Surprisingly, however, both icCD3epsilon(+) and icTCR gammadelta(+) cells were detected at later stages of development than was predicted by molecular studies. In particular icCD3epsilon protein expression coincided with the transition from the DN2 to DN3 stage of development, whereas icTCR gammadelta protein expression was only detected in a minor subset of DN4 cells. The implications of these findings for alphabeta lineage divergence will be discussed.

Delinquency in male adolescents: the role of alexithymia and family structure

The purpose of this study was to examine the linkages between alexithymia and delinquency in male adolescents (age ranging from 14 to 18 years), and to investigate whether alexithymia was a good discriminatory factor for juvenile delinquency. Thirty-six offender adolescents and 46 non-offender control adolescents participated in the study and completed the 20-item Toronto Alexithymia Scale (TAS-20) (alexithymia), the Revised Children's Manifest Anxiety Scale (R-CMAS) (anxiety), the Liste d'Adjectifs Bipolaires et en Echelles de Likert (LABEL) (personality-Big Five) and demographic data. Findings revealed that the adolescents of the offender group scored high on alexithymia and that proportion of disrupted family structure in the offender group is higher than in the control group. Logistic regressions confirmed that alexithymia and family structure are the strongest discriminatory factors for juvenile delinquency. Limitations and clinical implications are discussed, and recommendations for future research are provided

Synchronization of EEG: bivariate and multivariate measures.

Synchronization behavior of electroencephalographic (EEG) signals is important for decoding information processing in the human brain. Modern multichannel EEG allows a transition from traditional measurements of synchronization in pairs of EEG signals to whole-brain synchronization maps. The latter can be based on bivariate measures (BM) via averaging over pair-wise values or, alternatively, on multivariate measures (MM), which directly ascribe a single value to the synchronization in a group. In order to compare BM versus MM, we applied nine different estimators to simulated multivariate time series with known parameters and to real EEGs.We found widespread correlations between BM and MM, which were almost frequency-independent for all the measures except coherence. The analysis of the behavior of synchronization measures in simulated settings with variable coupling strength, connection probability, and parameter mismatch showed that some of them, including S-estimator, S-Renyi, omega, and coherence, aremore sensitive to linear interdependences,while others, like mutual information and phase locking value, are more responsive to nonlinear effects. Onemust consider these properties together with the fact thatMM are computationally less expensive and, therefore, more efficient for the large-scale data sets than BM while choosing a synchronization measure for EEG analysis.

Animal dispersal modelling: handling landscape features and related animal choices

Animal dispersal in a fragmented landscape depends on the complex interaction between landscape structure and animal behavior. To better understand how individuals disperse, it is important to explicitly represent the properties of organisms and the landscape in which they move. A common approach to modelling dispersal includes representing the landscape as a grid of equal sized cells and then simulating individual movement as a correlated random walk. This approach uses a priori scale of resolution, which limits the representation of all landscape features and how different dispersal abilities are modelled. We develop a vector-based landscape model coupled with an object-oriented model for animal dispersal. In this spatially explicit dispersal model, landscape features are defined based on their geographic and thematic properties and dispersal is modelled through consideration of an organism's behavior, movement rules and searching strategies (such as visual cues). We present the model's underlying concepts, its ability to adequately represent landscape features and provide simulation of dispersal according to different dispersal abilities. We demonstrate the potential of the model by simulating two virtual species in a real Swiss landscape. This illustrates the model's ability to simulate complex dispersal processes and provides information about dispersal such as colonization probability and spatial distribution of the organism's path.

Prefrailty and chronic morbidity in the youngest old: an insight from the Lausanne Cohort Lc65+.

OBJECTIVES: To estimate the prevalence of prefrailty, frailty, comorbidity, and disability in the youngest old and to identify chronic diseases associated with individual frailty criteria. DESIGN: Population-based cohort study of noninstitutionalized elderly adults at baseline; cross-sectional analysis. SETTING: Lausanne, Switzerland. PARTICIPANTS: One thousand two hundred eighty-three individuals with complete data on frailty, aged 65 to 70 (58.5% women). MEASUREMENTS: Frailty was assessed according to an adaptation of Fried's criteria (shrinking, weakness, exhaustion, slowness, and low activity, three criteria needed for the diagnosis of frailty, 1 to 2 for prefrailty). Other outcomes were diseases diagnosed by a doctor (≥ 2 chronic diseases: comorbidity) and limitations in activities of daily living (ADLs, basic and instrumental). RESULTS: At baseline, of 1,283 participants 71.1% were classified as nonfrail, 26.4% as prefrail, and 2.5% as frail. The proportion of women increased across these three groups (56.5%, 62.8%, and 71.9%, respectively; P = .01), as did the proportion of individuals with one or more chronic diseases (68.0%, 82.8%, and 90.6%, respectively; P < .001) and the proportion with basic or instrumental ADL disability (1.6%, 10.3%, and 59.4%, respectively; P < .001). Weakness (low grip strength) was the most frequent criterion (14.3%). Prefrail participants had significantly more comorbidity and ADL disability than nonfrail participants (P < .001). When present in isolation, weakness was associated with two to three times greater prevalence of coronary heart disease, other heart diseases, diabetes mellitus, and arthritis. Similarly, a significant association was identified between exhaustion and depression. CONCLUSION: Prefrailty is common in the youngest old. The most prevalent frailty criterion is weakness, which is associated with cardiovascular diseases. Longitudinal studies of the evolution of prefrailty should explore the role of potential interactions between individual frailty criteria and specific chronic diseases.

Inference about the number of contributors to a DNA mixture: Comparative analyses of a Bayesian network approach and the maximum allele count method.

In the forensic examination of DNA mixtures, the question of how to set the total number of contributors (N) presents a topic of ongoing interest. Part of the discussion gravitates around issues of bias, in particular when assessments of the number of contributors are not made prior to considering the genotypic configuration of potential donors. Further complication may stem from the observation that, in some cases, there may be numbers of contributors that are incompatible with the set of alleles seen in the profile of a mixed crime stain, given the genotype of a potential contributor. In such situations, procedures that take a single and fixed number contributors as their output can lead to inferential impasses. Assessing the number of contributors within a probabilistic framework can help avoiding such complication. Using elements of decision theory, this paper analyses two strategies for inference on the number of contributors. One procedure is deterministic and focuses on the minimum number of contributors required to 'explain' an observed set of alleles. The other procedure is probabilistic using Bayes' theorem and provides a probability distribution for a set of numbers of contributors, based on the set of observed alleles as well as their respective rates of occurrence. The discussion concentrates on mixed stains of varying quality (i.e., different numbers of loci for which genotyping information is available). A so-called qualitative interpretation is pursued since quantitative information such as peak area and height data are not taken into account. The competing procedures are compared using a standard scoring rule that penalizes the degree of divergence between a given agreed value for N, that is the number of contributors, and the actual value taken by N. Using only modest assumptions and a discussion with reference to a casework example, this paper reports on analyses using simulation techniques and graphical models (i.e., Bayesian networks) to point out that setting the number of contributors to a mixed crime stain in probabilistic terms is, for the conditions assumed in this study, preferable to a decision policy that uses categoric assumptions about N.

Developmental, metabolic and immunological costs of flea infestation in the common vole

Parasites use resources from their hosts, which can indirectly affect a number of host functions because of trade-offs in resource allocation. In order to get a comprehensive view of the costs imposed by blood sucking parasites to their hosts, it is important to monitor multiple components of the development and physiology of parasitized hosts over long time periods. The effect of infestation by fleas on body mass, body length growth, haematocrit, resistance to oxidative stress, resting metabolic rate and humoral immune response were experimentally evaluated. During a 3-month period, male common voles, Microtus arvalis, were either parasitized by rat fleas (Nosopsyllus fasciatus), which are naturally occurring generalist ectoparasites of voles, or reared without fleas. Then voles were challenged twice by injecting Keyhole Limpet Haemocyanin (KLH) to assess whether the presence of fleas affects the ability of voles to produce antibodies against a novel antigen. During the immune challenge we measured the evolution of body mass, haematocrit, resistance to oxidative stress and antibody production. Flea infestation negatively influenced the growth of voles. Moreover, parasitized voles had reduced haematocrit, higher resting metabolic rate and lower production of antibodies against the KLH. Resistance to oxidative stress was not influenced by the presence of fleas. During the immune challenge with KLH, body mass decreased in both groups, while the resistance to oxidative stress remained stable. In contrast, the haematocrit decreased only in parasitized voles. Our experiment shows that infestation by a haematophageous parasite negatively affects multiple traits like growth, energy consumption and immune response. Fleas may severely reduce the survival probability and reproductive success of their host in natural conditions.

The political economy of childcare in OECD countries : Explaining cross-national variation in spending and coverage rates

If childcare policy has become topical in most OECD countries over the last ten years or so, actual developments display huge cross-national variations. Countries like Sweden and Denmark spend around 2 per cent of GDP on this service, and provide affordable childcare places to most children below school age. At the other extreme, in Southern Europe, only around 10 per cent of this age group has access to formal daycare. Against this background, this article aims to account for cross-national variations in childcare services. It distinguishes two dependent variables: the coverage rate and the proportion of GDP spent subsidising childcare services. Using a mix of cross-sectional and pooled times-series methods, it tests a series of hypotheses concerning the determinants of the development of this policy. Its main conclusion for the coverage rate is that key factors are public spending and wage dispersion (both positive). For spending, key factors are the proportion of women in parliaments (positive) and spending on age-related policies (negative).