Predicting Distribution of Aedes Aegypti and Culex Pipiens Complex, Potential Vectors of Rift Valley Fever Virus in Relation to Disease Epidemics in East Africa.

The East African region has experienced several Rift Valley fever (RVF) outbreaks since the 1930s. The objective of this study was to identify distributions of potential disease vectors in relation to disease epidemics. Understanding disease vector potential distributions is a major concern for disease transmission dynamics. DIVERSE ECOLOGICAL NICHE MODELLING TECHNIQUES HAVE BEEN DEVELOPED FOR THIS PURPOSE: we present a maximum entropy (Maxent) approach for estimating distributions of potential RVF vectors in un-sampled areas in East Africa. We modelled the distribution of two species of mosquitoes (Aedes aegypti and Culex pipiens complex) responsible for potential maintenance and amplification of the virus, respectively. Predicted distributions of environmentally suitable areas in East Africa were based on the presence-only occurrence data derived from our entomological study in Ngorongoro District in northern Tanzania. Our model predicted potential suitable areas with high success rates of 90.9% for A. aegypti and 91.6% for C. pipiens complex. Model performance was statistically significantly better than random for both species. Most suitable sites for the two vectors were predicted in central and northwestern Tanzania with previous disease epidemics. Other important risk areas include western Lake Victoria, northern parts of Lake Malawi, and the Rift Valley region of Kenya. Findings from this study show distributions of vectors had biological and epidemiological significance in relation to disease outbreak hotspots, and hence provide guidance for the selection of sampling areas for RVF vectors during inter-epidemic periods

Proficiency Evaluation of NDE Personnel Utilizing the Ultrasonic Methodology

The measure by which the capability of a nondestructive testing (NDT) inspector can be assessed is based upon the proficiency by which that particular individual can perform an evaluation of a given set of test specimens in a reasonable length of time with a good probability of detection at a high confidence level. This criteria is governed by parameters based upon the training and experience of the technician, as well as the technical orders and procedures under which he/she must perform inspections. This is the philosophy which governed the NDT proficiency program discussed in this paper. The proficiency test was administered by the Nondestructive Testing laboratory at the San Antonio Air Logistics Center (SA-ALC), Kelly AFB, Texas. The subjects were NDT technicians of the Structural Assessment Testing (SAT) Facility located in the Engine Division of the SA-ALC

Reliability and Validity of the KIPPPI: An Early Detection Tool for Psychosocial Problems in Toddlers

Background: The KIPPPI (Brief Instrument Psychological and Pedagogical Problem Inventory) is a Dutch questionnaire that measures psychosocial and pedagogical problems in 2-year olds and consists of a KIPPPI Total score, Wellbeing scale, Competence scale, and Autonomy scale. This study examined the reliability, validity, screening accuracy and clinical application of the KIPPPI. Methods: Parents of 5959 2-year-old children in the Rotterdam area, the Netherlands, were invited to participate in the study. Parents of 3164 children (53.1% of all invited parents) completed the questionnaire. The internal consistency was evaluated and in subsamples the test-retest reliability and concurrent validity with regard to the Child Behavioral Checklist (CBCL). Discriminative validity was evaluated by comparing scores of parents who worried about their child's upbringing and parent's that did not. Screening accuracy of the KIPPPI was evaluated against the CBCL by calculating the Receiver Operating Characteristic (ROC) curves. The clinical application was evaluated by the relation between KIPPPI scores and the clinical decision made by the child health professionals. Results: Psychometric properties of the KIPPPI Total score, Wellbeing scale, Competence scale and Autonomy scale were respectively: Cronbach's alphas: 0.88, 0.86, 0.83, 0.58. Test-rete

Four theorems on the psychometric function

In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, Δx. This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull "slope" parameter, β, can be approximated by [Formula: see text], where [Formula: see text] is the β of the Weibull function that fits best to the cumulative noise distribution, and [Formula: see text] depends on the transducer. We derive general expressions for [Formula: see text] and [Formula: see text], from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when [Formula: see text], [Formula: see text]. We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4-0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull β reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of β for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian

Quantitative predictions of peptide binding to any HLA-DR molecule of known sequence: NetMHCIIpan

CD4 positive T helper cells control many aspects of specific immunity. These cells are specific for peptides derived from protein antigens and presented by molecules of the extremely polymorphic major histocompatibility complex (MHC) class II system. The identification of peptides that bind to MHC class II molecules is therefore of pivotal importance for rational discovery of immune epitopes. HLA-DR is a prominent example of a human MHC class II. Here, we present a method, NetMHCIIpan, that allows for pan-specific predictions of peptide binding to any HLA-DR molecule of known sequence. The method is derived from a large compilation of quantitative HLA-DR binding events covering 14 of the more than 500 known HLA-DR alleles. Taking both peptide and HLA sequence information into account, the method can generalize and predict peptide binding also for HLA-DR molecules where experimental data is absent. Validation of the method includes identification of endogenously derived HLA class II ligands, cross-validation, leave-one-molecule-out, and binding motif identification for hitherto uncharacterized HLA-DR molecules. The validation shows that the method can successfully predict binding for HLA-DR molecules-even in the absence of specific data for the particular molecule in question. Moreover, when compared to TEPITOPE, currently the only other publicly available prediction method aiming at providing broad HLA-DR allelic coverage, NetMHCIIpan performs equivalently for alleles included in the training of TEPITOPE while outperforming TEPITOPE on novel alleles. We propose that the method can be used to identify those hitherto uncharacterized alleles, which should be addressed experimentally in future updates of the method to cover the polymorphism of HLA-DR most efficiently. We thus conclude that the presented method meets the challenge of keeping up with the MHC polymorphism discovery rate and that it can be used to sample the MHC "space," enabling a highly efficient iterative process for improving MHC class II binding predictions

Loss-size and Reliability Trade-offs Amongst Diverse Redundant Binary Classifiers

Many applications involve the use of binary classifiers, including applications where safety and security are critical. The quantitative assessment of such classifiers typically involves receiver operator characteristic (ROC) methods and the estimation of sensitivity/specificity. But such techniques have their limitations. For safety/security critical applications, more relevant measures of reliability and risk should be estimated. Moreover, ROC techniques do not explicitly account for: 1) inherent uncertainties one faces during assessments, 2) reliability evidence other than the observed failure behaviour of the classifier, and 3) how this observed failure behaviour alters one's uncertainty about classifier reliability. We address these limitations using conservative Bayesian inference (CBI) methods, producing statistically principled, conservative values for risk/reliability measures of interest. Our analyses reveals trade-offs amongst all binary classifiers with the same expected loss { the most reliable classifiers are those most likely to experience high impact failures. This trade-off is harnessed by using diverse redundant binary classifiers

Projected Range Contractions of European Protected Oceanic Montane Plant Communities: Focus on Climate Change Impacts Is Essential for Their Future Conservation

Global climate is rapidly changing and while many studies have investigated the potential impacts of this on the distribution of montane plant species and communities, few have focused on those with oceanic montane affinities. In Europe, highly sensitive bryophyte species reach their optimum occurrence, highest diversity and abundance in the northwest hyperoceanic regions, while a number of montane vascular plant species occur here at the edge of their range. This study evaluates the potential impact of climate change on the distribution of these species and assesses the implications for EU Habitats Directive-protected oceanic montane plant communities. We applied an ensemble of species distribution modelling techniques, using atlas data of 30 vascular plant and bryophyte species, to calculate range changes under projected future climate change. The future effectiveness of the protected area network to conserve these species was evaluated using gap analysis. We found that the majority of these montane species are projected to lose suitable climate space, primarily at lower altitudes, or that areas of suitable climate will principally shift northwards. In particular, rare oceanic montane bryophytes have poor dispersal capacity and are likely to be especially vulnerable to contractions in their current climate space. Significantly different projected range change responses were found between 1) oceanic montane bryophytes and vascular plants; 2) species belonging to different montane plant communities; 3) species categorised according to different biomes and eastern limit classifications. The inclusion of topographical variables in addition to climate, significantly improved the statistical and spatial performance of models. The current protected area network is projected to become less effective, especially for specialised arctic-montane species, posing a challenge to conserving oceanic montane plant communities. Conservation management plans need significantly greater focus on potential climate change impacts, including models with higher-resolution species distribution and environmental data, to aid these communities’ long-term survival

The five-item Brief-Symptom Rating Scale as a suicide ideation screening instrument for psychiatric inpatients and community residents

<p>Abstract</p> <p>Background</p> <p>An efficient screening instrument which can be used in diverse settings to predict suicide in different populations is vital. The aim of this study was to use the five-item Brief Symptom Rating Scale (BSRS-5) as a screening instrument for the prediction of suicide ideation in psychiatric, community and general medical settings.</p> <p>Methods</p> <p>Five hundred and one psychiatric, 1,040 community and 969 general medical participants were recruited. The community participants completed a structured telephone interview, and the other two groups completed the self-report BSRS-5 questionnaire.</p> <p>Results</p> <p>The logistic regression analysis showed that the predictors of suicide ideation for the psychiatric group were depression, hostility and inferiority (<it>p </it>< 0.001, <it>p </it>= 0.016, <it>p </it>= 0.011), for the community group, inferiority, hostility and insomnia (<it>p </it>< 0.001, <it>p </it>< 0.001, <it>p </it>= 0.003), and for the general medical group, inferiority, hostility, depression and insomnia (<it>p </it>< 0.001, <it>p </it>= 0.001, <it>p </it>= 0.020, <it>p </it>= 0.008). The structural equation model showed the same symptom domains that predicted suicide ideation for all three groups. The receiver operating characteristic curve using the significant symptom domains from logistic regression showed that for the psychiatric group, the optimal cut-off point was 4/5 for the total of the significant dimensions (positive predictive value [PPV] = 78.01%, negative predictive value [NPV] = 79.05%), for the community group, 7/8 (PPV = 68.75%, NPV = 96.09%), and for the general medical group, 12/13 (PPV = 92.86%, NPV = 88.48%).</p> <p>Conclusion</p> <p>The BSRS-5 is an efficient tool for the screening of suicide ideation-prone psychiatric inpatients, general medical patients, and community residents. Understanding the discriminative symptom domains for different groups and the relationship between them can help health care professionals in their preventative programs and clinical treatment.</p

Test Data Sets for Evaluating Data Visualization Techniques

In this paper we take a step toward addressing a pressing general problem in the development of data visualization systems — how to measure their effectiveness. The step we take is to define a model for specifying the generation of test data that can be em-ployed for standardized and quantitative testing of a system’s per-formance. These test data sets, in conjunction with appropriate testing procedures, can provide a basis for certifying the effective-ness of a visualization system and for conducting comparative studies to steer system development