Search

Background: Place of death represents an important indicator for end-of-life care policy making and is related to the quality of life of patients and their families. The aim of the paper is to analyse the place of death in the Czech Republic and Slovakia in 2011. Research questions were focused on factors influencing the place of death and specifically the likelihood of dying at home. Methods: Whole population data from death certificates for all deaths in the Czech Republic and Slovakia in 2011 were used for bivariate and multivariate analyses. Separate analysis using binary logistic regression was conducted for subpopulation of patients who died from chronic conditions. Results: The majority of population in both countries died in hospitals (58.4% the Czech Republic, 54.8% Slovakia), less than one-third died at home. In case of chronic conditions, death at home was significantly associated with underlying cause of death (cancer and heart failure), being male, age (older than 85, Slovakia only) and higher education (the Czech Republic only). Cancer and heart failure patients had higher chances to die at home than other chronic conditions. Conclusions: Czech and Slovak patients with chronic conditions are more likely to die in hospitals than in some other European Union member countries. This finding should be addressed by policy makers in promoting home hospice care services and education in palliative care for staff in nursing homes and other end-of-life settings. [ABSTRACT FROM AUTHOR]

The temperate waters of the North-Eastern Atlantic have a long history of maritime resource richness and, as a result, the European Union is endeavouring to maintain regional productivity and biodiversity. At the intersection of these aims lies potential conflict, signalling the need for integrated, cross-border management approaches. This paper focuses on the marine megafauna of the region. This guild of consumers was formerly abundant, but is now depleted and protected under various national and international legislative structures. We present a meta-analysis of available megafauna datasets using presence-only distribution models to characterise suitable habitat and identify spatially-important regions within the English Channel and southern bight of the North Sea. The integration of studies from dedicated and opportunistic observer programmes in the United Kingdom and France provide a valuable perspective on the spatial and seasonal distribution of various taxonomic groups, including large pelagic fishes and sharks, marine mammals, seabirds and marine turtles. The Western English Channel emerged as a hotspot of biodiversity for megafauna, while species richness was low in the Eastern English Channel. Spatial conservation planning is complicated by the highly mobile nature of marine megafauna, however they are important components of the marine environment and understanding their distribution is a first crucial step toward their inclusion into marine ecosystem management. [ABSTRACT FROM AUTHOR]

This paper presents a novel population genetic model and a computationally and statistically tractable framework for analyzing within-host HIV diversity based on serial samples of HIV DNA sequences. This model considers within-host HIV evolution during the chronic phase of infection and assumes that the HIV population is homogeneous at the beginning, corresponding to the time of seroconversion, and evolves according to the Wright-Fisher reproduction model with recombination and variable mutation rate across nucleotide sites. In addition, the population size and generation time vary over time as piecewise constant functions of time. Under this model I approximate the genealogical and mutational processes for serial samples of DNA sequences by a continuous coalescent-recombination process and an inhomogeneous Poisson process, respectively. Based on these derivations, an efficient algorithm is described for generating polymorphisms in serial samples of DNA sequences under the model including various substitution models. Extensions of the algorithm are also described for other demographic scenarios that can be more suitable for analyzing the dynamics of genetic diversity of other pathogens in vitro and in vivo. For the case of the infinite-sites model, I derive analytical formulas for the expected number of polymorphic sites in sample of DNA sequences, and apply the developed simulation and analytical methods to explore the fit of the model to HIV genetic diversity based on serial samples of HIV DNA sequences from 9 HIV-infected individuals. The results particularly show that the estimates of the ratio of recombination rate over mutation rate can vary over time between very high and low values, which can be considered as a consequence of the impact of selection forces. [ABSTRACT FROM AUTHOR]

The raindrop size distribution (RDSD) is defined as the relative frequency of raindrops per given diameter in a volume. This paper describes a mathematically consistent modeling of the RDSD drawing on probability theory. It is shown that this approach is simpler than the use of empirical fits and that it provides a more consistent procedure to estimate the rainfall rate ( R) from reflectivity ( Z) measurements without resorting to statistical regressions between both parameters. If the gamma distribution form is selected, the modeling expresses the integral parameters Z and R in terms of only the total number of drops per volume ( N T), the sample mean [ m = E( D)], and the sample variance [ σ2 = E( m − D)2] of the drop diameters ( D) or, alternatively, in terms of N T, E( D), and E[log( D)]. Statistical analyses indicate that ( N T, m) are independent, as are ( N T, σ2). The Z- R relationship that arises from this model is a linear R = T × Z expression (or Z = T−1 R), with T a factor depending on m and σ2 only and thus independent of N T. The Z- R so described is instantaneous, in contrast with the operational calculation of the RDSD in radar meteorology, where the Z- R arises from a regression line over a usually large number of measurements. The probabilistic approach eliminates the need of intercept parameters N0 or , which are often used in statistical approaches but lack physical meaning. The modeling presented here preserves a well-defined and consistent set of units across all the equations, also taking into account the effects of RDSD truncation. It is also shown that the rain microphysical processes such as coalescence, breakup, or evaporation can then be easily described in terms of two parameters-the sample mean and the sample variance-and that each of those processes have a straightforward translation in changes of the instantaneous Z- R relationship. [ABSTRACT FROM AUTHOR]

Background: Data collected to inform time variations in natural population size are tainted by sampling error. Ignoring sampling error in population dynamics models induces bias in parameter estimators, e.g., density-dependence. In particular, when sampling errors are independent among populations, the classical estimator of the synchrony strength (zero-lag correlation) is biased downward. However, this bias is rarely taken into account in synchrony studies although it may lead to overemphasizing the role of intrinsic factors (e.g., dispersal) with respect to extrinsic factors (the Moran effect) in generating population synchrony as well as to underestimating the extinction risk of a metapopulation. Methodology/Principal findings: The aim of this paper was first to illustrate the extent of the bias that can be encountered in empirical studies when sampling error is neglected. Second, we presented a space-state modelling approach that explicitly accounts for sampling error when quantifying population synchrony. Third, we exemplify our approach with datasets for which sampling variance (i) has been previously estimated, and (ii) has to be jointly estimated with population synchrony. Finally, we compared our results to those of a standard approach neglecting sampling variance. We showed that ignoring sampling variance can mask a synchrony pattern whatever its true value and that the common practice of averaging few replicates of population size estimates poorly performed at decreasing the bias of the classical estimator of the synchrony strength. Conclusion/Significance: The state-space model used in this study provides a flexible way of accurately quantifying the strength of synchrony patterns from most population size data encountered in field studies, including over-dispersed count data. We provided a user-friendly R-program and a tutorial example to encourage further studies aiming at quantifying the strength of population synchrony to account for uncertainty in population size estimates. [ABSTRACT FROM AUTHOR]

The part-based method has been a fast rising framework for object detection. It is attracting more and more attention for its detection precision and partial robustness to the occlusion. However, little research has been focused on the problem of occlusion overlapping of the part regions, which can reduce the performance of the system. This paper proposes a part-based probabilistic model and the corresponding inference algorithm for the problem of the part occlusion. The model is based on the Bayesian theory integrally and aims to be robust to the large occlusion. In the stage of the model construction, all of the parts constitute the vertex set of a fully connected graph, and a binary variable is assigned to each part to indicate its occlusion status. In addition, we introduce a penalty term to regularize the argument space of the objective function. Thus, the part detection is formulated as an optimization problem, which is divided into two alternative procedures: the outer inference and the inner inference. A stochastic tentative method is employed in the outer inference to determine the occlusion status for each part. In the inner inference, the gradient descent algorithm is employed to find the optimal positions of the parts, in term of the current occlusion status. Experiments were carried out on the Caltech database. The results demonstrated that the proposed method achieves a strong robustness to the occlusion. [ABSTRACT FROM AUTHOR]

Modeling financial time series at different time scales is still an open challenge. The choice of a suitable indicator quantifying the distance between the model and the data is therefore of fundamental importance for selecting models. In this paper, we propose a multiscale model selection method based on the Jensen-Shannon distance in order to select the model that is able to better reproduce the distribution of price changes at different time scales. Specifically, we consider the problem of modeling the ultra high frequency dynamics of an asset with a large tick-to-price ratio. We study the price process at different time scales and compute the Jensen-Shannon distance between the original dataset and different models, showing that the coupling between spread and returns is important to model return distribution at different time scales of observation, ranging from the scale of single transactions to the daily time scale. [ABSTRACT FROM AUTHOR]

This paper develops an equipment failure prognostics model, in the context of Condition Based Maintenance (CBM), in order to predict the equipment's chance of survival, using Logical Analysis of Data (LAD). LAD has the advantage of not relying on any statistical theory, which enables it to overcome the conventional problems concerning the statistical properties of the datasets. LAD's main advantage is its straightforward procedure and self-explanatory results. In this paper, our main objective is to develop methods to calculate equipment's survival probability at a certain future moment, using LAD. We employ LAD's pattern generation procedure. Then, we introduce a guideline to employ the generated patterns to estimate the equipment's survival probability. The proposed methods are applied on Prognostics and Health Management Challenge dataset, a condition monitoring dataset collected from some mechanical equipment, provided by NASA Ames Prognostics Data Repository. Analysis of performance of the proposed methods reveals that the methods provide comprehensible results that are greatly beneficial to maintenance practitioners. Prognostics results obtained by the proposed methods are compared with that of Proportional Hazards Model (PHM). The comparison reveals that the proposed methods are promising tools that compare favorably to the PH Model. Since the proposed prognostics model is at its beginning phase, some future directions are presented to improve the performance of the model. [ABSTRACT FROM AUTHOR]

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses. [ABSTRACT FROM AUTHOR]

It is an effective strategy to use both genetic perturbation data and gene expression data to infer regulatory networks that aims to improve the detection accuracy of the regulatory relationships among genes. Based on both types of data, the genetic regulatory networks can be accurately modeled by Structural Equation Modeling (SEM). In this paper, a linear regression (LR) model is formulated based on the SEM, and a novel iterative scheme using Bayesian inference is proposed to estimate the parameters of the LR model (LRBI). Comparative evaluations of LRBI with other two algorithms, the Adaptive Lasso (AL-Based) and the Sparsity-aware Maximum Likelihood (SML), are also presented. Simulations show that LRBI has significantly better performance than AL-Based, and overperforms SML in terms of power of detection. Applying the LRBI algorithm to experimental data, we inferred the interactions in a network of 35 yeast genes. An open-source program of the LRBI algorithm is freely available upon request. [ABSTRACT FROM AUTHOR]

Aim This paper reports on regulated (or licensed) care providers' understanding and perceptions of feedback reports in a sample of Canadian long-term care settings using a cross-sectional survey design. Background Audit with feedback quality improvement studies have seldom targeted front-line providers in long-term care to receive feedback information. Methods Feedback reports were delivered to front-line regulated care providers in four long-term care facilities for 13 months in 2009-10. Providers completed a postfeedback survey. Results Most (78%) regulated care providers ( n = 126) understood the reports and felt they provided useful information for making changes to resident care (64%). Perceptions of the report differed, depending on the role of the regulated care provider. In multivariable logistic regression, the regulated nurses' understanding of more than half the report was negatively associated with 'usefulness of information for changing resident care', and perceiving the report as generally useful had a positive association. Conclusions Front-line regulated providers are an appropriate target for feedback reports in long-term care. Implications for nursing management Long-term care administrators should share unit-level information on care quality with unit-level managers and other professional front-line direct care providers. [ABSTRACT FROM AUTHOR]

In vitro experiments have shown that isolated human gut bacteria are able to metabolise PUFA into conjugated PUFA like conjugated linoleic acids (CLA). The hypothesis of the present paper was that high-fat (HF) diet feeding and supplementation with fermentable carbohydrates that have prebiotic properties modulate the in vivo production of CLA by the mouse gut microbiota. Mice were treated for 4 weeks as follows: control (CT) groups were fed a standard diet; HF groups were fed a HF diet rich in linoleic acid (18 : 2n-6); the third groups were fed with the HF diet supplemented with either inulin-type fructans (HF-ITF) or arabinoxylans (HF-Ax). HF diet feeding increased rumenic acid (cis-9, trans-11-18 : 2 CLA) content both in the caecal and liver tissues compared with the CT groups. ITF supplementation had no major effect compared with the HF diet whereas Ax supplementation increased further rumenic acid (cis-9, trans-11-18 : 2 CLA) in the caecal tissue. These differences between both prebiotics may be linked to the high fat-binding capacity of Ax that provides more substrates for bacterial metabolism and to differential modulation of the gut microbiota (specific increase in Roseburia spp. in HF-Ax v. HF). In conclusion, these experiments supply the proof of concept that the mouse gut microbiota produces CLA in vivo, with consequences on the level of CLA in the caecal and liver tissues. We postulate that the CLA-producing bacteria could be a mediator to consider in the metabolic effects of both HF diet feeding and prebiotic supplementation. [ABSTRACT FROM PUBLISHER]

INTRODUCTION: The ageing population means prescribing for chronic illnesses in older people is expected to rise. Comorbidities and compromised organ function may complicate prescribing and increase medication-related risks. Comorbid depression in older people is highly prevalent and complicates medication prescribing decisions. AIM: To determine the prevalence of potentially inappropriate medication use in a community-dwelling population of older adults with depressive symptoms. METHODS: The medications of 191 community-dwelling older people selected because of depressive symptoms for a randomised trial were reviewed and assessed using the modified version of the Beers' Criteria. The association between inappropriate medication use and various population characteristics was assessed using Chi-square statistics and logistic regression analyses. RESULTS: The mean age was 81 (±4.3) years and 59% were women. The median number of medications used was 6 (range 1-21 medications). The most commonly prescribed potentially inappropriate medications were amitriptyline, dextropropoxyphene, quinine and benzodiazepines. Almost half (49%) of the participants were prescribed at least one potentially inappropriate medication; 2996 were considered to suffer significant depressive symptoms (Geriatric Depression Scale >5) and no differences were found in the number of inappropriate medications used between those with and without significant depressive symptoms (Chi-square 0.005 p=0.54). DISCUSSION: Potentially inappropriate medication use, as per the modified Beers' Criteria, is very common among community-dwelling older people with depressive symptoms. However, the utility of the Beers' Criteria is lessened by lack of clinical correlation. Ongoing research to examine outcomes related to apparent inappropriate medication use is needed. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Statistics is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of African Journal of Reproductive Health is the property of Women's Health & Action Research Centre and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Few trials have evaluated the metabolic effects and health outcomes of lowering dietary n-6 PUFA. The objectives of the present paper were (1) to report the methods employed to lower dietary n-6 PUFA, while either increasing or maintaining n-3 PUFA intake and (2) to validate our methods with 24 h recalls and erythrocyte fatty acid analyses. A total of sixty-seven subjects were randomised to either (1) an average-n-3 PUFA, low-n-6 PUFA (L6) intervention designed to lower linoleic acid (LA; ≤ 2·5 % of energy (en%)) and arachidonic acid ( ≤ 60 mg/d), while maintaining an average US intake of n-3 PUFA or (2) a high-n-3 PUFA, low-n-6 PUFA (H3-L6) intervention designed to lower n-6 LA, while increasing the n-3 PUFA α-linolenic acid (ALA; ≥ 1·5 en%) and EPA+DHA ( ≥ 1000 mg/d). Pre- and intra-intervention nutrient intakes were estimated with six 24 h dietary recalls per subject. Both groups achieved the targeted reductions in dietary LA to ≤ 2·5 en% (median LA 2·45 (2·1, 3·1); P< 0·001). Intakes of n-3 PUFA did not change for the L6 group. Target increases in n-3 ALA (median 1·6 en%, (1·3, 2·0), P< 0·001) and EPA+DHA (1482 mg, (374, 2558), P< 0·001) were achieved in the H3-L6 group. Dietary changes were validated by corresponding changes in erythrocyte n-6 and n-3 fatty acid composition. Dietary LA can be lowered to ≤ 2·5 en%, with or without concurrent increases in dietary n-3 PUFA, in an outpatient clinical trial setting using this integrated diet method. [ABSTRACT FROM PUBLISHER]

In this paper the ideas of three types of statistical convergence of a sequence of random variables, namely, statistical convergence in probability, statistical convergence in mean of order r and statistical convergence in distribution are introduced and the interrelation among them is investigated. Also their certain basic properties are studied. [ABSTRACT FROM AUTHOR]

The clinical serial interval of an infectious disease is the time between date of symptom onset in an index case and the date of symptom onset in one of its secondary cases. It is a quantity which is commonly collected during a pandemic and is of fundamental importance to public health policy and mathematical modelling. In this paper we present a novel method for calculating the serial interval distribution for a Markovian model of household transmission dynamics. This allows the use of Bayesian MCMC methods, with explicit evaluation of the likelihood, to fit to serial interval data and infer parameters of the underlying model. We use simulated and real data to verify the accuracy of our methodology and illustrate the importance of accounting for household size. The output of our approach can be used to produce posterior distributions of population level epidemic characteristics. [ABSTRACT FROM AUTHOR]

In this paper, a Pareto-archived estimation-of-distribution algorithm (PAEDA) is presented for the multiobjective resource-constrained project scheduling problem with makespan and resource investment criteria. First, by combining the activity list and the resource list, an encoding scheme named activity-resource list is presented. Second, a novel hybrid probability model is designed to predict the most promising activity permutation and resource capacities. Third, a new sampling and updating mechanism for the probability model is developed to track the area with promising solutions. In addition, a Pareto archive is used to store the nondominated solutions that have been explored, and another archive is used to store the solutions for updating the probability model. The evolution process of the PAEDA is visualized showing the most promising area of the search space is tracked. Extensive numerical testing results then demonstrate that the PAEDA outperforms the existing methods. [ABSTRACT FROM PUBLISHER]

Beneficial effects of prebiotics like inulin and fructo-oligosaccharides (FOS) have been proven in health and nutrition. Yacon (Smallanthus sonchifolius), an Andean crop, contains FOS (50–70 % of its dry weight) and, therefore, is considered a prebiotic. Commercial FOS can up-regulate total secretory IgA (S-IgA) in infant mice, prevent infection with Salmonella in swine or enhance immune response for Salmonella vaccine in a mouse model. Previously, we found that administration of yacon root flour regulates gut microbiota balance and has immunomodulatory effects without inflammatory responses. The aim of the present paper is to analyse if yacon prevents enteric infection caused by a strain of Salmonella enteritidis serovar Typhimurium (S. Typhimurium) in a mouse model. BALB/c mice were supplemented with yacon flour (45 d), challenged with S. Typhimurium and killed to study pathogen translocation, total and specific IgA production by ELISA, presence of IgA and other cytokines and Toll-like receptor 4 (TLR4) and clustor of differentiation 206 (CD206) receptors positive cells by immunofluorescence and histological changes. Yacon flour administration had a protective effect from 15 to 30 d of treatment. We found a peak of total S-IgA production without translocation of the pathogen for these periods. At 30 d, there was an increase in IL-6 and macrophage inflammatory proteins-1α+ cells and expression of the receptors CD206 and TLR4. Yacon flour did not have incidence in pathogen-specific S-IgA production. Longer periods (45 d) of administration had no protective effect. Therefore, yacon can prevent enteric infection caused by S. Typhimurium when given up to 30 d; this effect would be mediated by enhancing non-specific immunity, such as total S-IgA, that improves the immunological intestinal barrier. [ABSTRACT FROM PUBLISHER]

Several contributions have reported an altered expression of pseudoneglect in psychiatric disorders, highlighting the existence of an anomalous brain lateralization in affected subjects. Surprisingly, no studies have yet investigated pseudoneglect in first-degree relatives (FdR) of psychiatric patients. We investigated performance on “paper and pencil” line bisection (LB) tasks in 68 schizophrenic patients (SCZ), 42 unaffected FdR, 41 unipolar depressive patients (UP), and 103 healthy subjects (HS). A subgroup of 20 SCZ and 16 HS underwent computerized LB and mental number line bisection (MNL) tasks requiring judgment of prebisected lines and numerical intervals. Moreover, we evaluated, in a subgroup of 15 SCZ, performance on LB and MNL before and after parietal transcranial direct current stimulation (tDCS). In comparison to HS and UP, SCZ showed a systematic rightward bias on LB, partially corrected by selective right posterior parietal tDCS. Interestingly, even FdR showed a lack of pseudoneglect on LB, expressing a mean error lying in the middle between those of HS and SCZ. On the other hand, our results showed no significant difference between the performance of SCZ and HS on MNL. Both groups showed a comparable leftward bias that could not be significantly altered after left or right parietal tDCS. These findings confirm the existence of reduced lateralization in SCZ, suggesting specific impaired functioning of the right parietal lobule. Notably, we report a lack of pseudoneglect not only in SCZ but also in FdR, raising the hypothesis that an inverted laterality pattern may be considered a concrete marker of schizotypal traits. [ABSTRACT FROM PUBLISHER]

Possessing sufficient nutritional knowledge is a necessary component in the prevention and treatment of obesity. A solid understanding of nutrition can help people make appropriate food selections and can also help correct irrational ideas or myths people may believe about food. It is a challenge to provide this information to children in ways that are exciting. Thus, we propose an online video game platform to deliver the information. The objective of this study was to study the efficacy and acceptability of an online game called ‘ETIOBE Mates’ that was designed to improve children’s nutritional knowledge; furthermore, we compare it with the traditional paper–pencil mode of information delivery. A sample of 228 children participated in the study. Participants were divided into two groups: an experimental group (who used ETIOBE Mates) and a control group (who were given a pamphlet). Both groups increased their scores for nutritional knowledge. The interaction between group × time was also statistically significant; it indicated that acquisition of nutritional knowledge was superior in the experimental group. The children considered the serious games platform to be a useful medium for improving their nutritional knowledge. Online games can be an effective method of delivery for preventive and treatment tasks that are otherwise tedious for children. [ABSTRACT FROM PUBLISHER]

The application of Preventive Maintenance (PM) and Statistical Process Control (SPC) are important practices to achieve high product quality, small frequency of failures, and cost reduction in a production process. However there are some points that have not been explored in depth about its joint application. First, most SPC is performed with the X-bar control chart which does not fully consider the variability of the production process. Second, many studies of design of control charts consider just the economic aspect while statistical restrictions must be considered to achieve charts with low probabilities of false detection of failures. Third, the effect of PM on processes with different failure probability distributions has not been studied. Hence, this paper covers these points, presenting the Economic Statistical Design (ESD) of joint X-bar-S control charts with a cost model that integrates PM with general failure distribution. Experiments showed statistically significant reductions in costs when PM is performed on processes with high failure rates and reductions in the sampling frequency of units for testing under SPC. [ABSTRACT FROM AUTHOR]

Typical data visualizations result from linear pipelines that start by characterizing data using a model or algorithm to reduce the dimension and summarize structure, and end by displaying the data in a reduced dimensional form. Sensemaking may take place at the end of the pipeline when users have an opportunity to observe, digest, and internalize any information displayed. However, some visualizations mask meaningful data structures when model or algorithm constraints (e.g., parameter specifications) contradict information in the data. Yet, due to the linearity of the pipeline, users do not have a natural means to adjust the displays. In this paper, we present a framework for creating dynamic data displays that rely on both mechanistic data summaries and expert judgement. The key is that we develop both the theory and methods of a new human-data interaction to which we refer as “ Visual to Parametric Interaction” (V2PI). With V2PI, the pipeline becomes bi-directional in that users are embedded in the pipeline; users learn from visualizations and the visualizations adjust to expert judgement. We demonstrate the utility of V2PI and a bi-directional pipeline with two examples. [ABSTRACT FROM AUTHOR]

Sub-sentential alignment is the process by which multi-word translation units are extracted from sentence-aligned multilingual parallel texts. This process is required, for instance, in the course of training statistical machine translation systems. Standard approaches typically rely on the estimation of several probabilistic models of increasing complexity and on the use of various heuristics, that make it possible to align, first isolated words, then, by extension, groups of words. In this paper, we explore an alternative approach which relies on a much simpler principle: the comparison of occurrence profiles in sub-corpora obtained by sampling. After analyzing the strengths and weaknesses of this approach, we show how to improve the detection of multi-word translation units and evaluate these improvements on machine translation tasks. [ABSTRACT FROM AUTHOR]

Our objective was to assess how exposure to secondhand tobacco smoke occurs in Hungarian homes, particularly among non-smokers, and to examine the effectiveness of home smoking bans in eliminating exposure to secondhand smoke at home. In 2009, 2286 non-smokers and smokers aged 16–70 years, who were selected randomly from a nationally representative sample of 48 Hungarian settlements, completed paper-and-pencil self-administered questionnaires addressing tobacco-related attitudes, opinions and behaviors. Chi-square tests, one-way analysis of variance and multivariate logistic regression models were used to assess the effect of demographics, socio-economic characteristics and home smoking policies on the risk of exposure to secondhand tobacco smoke at home. Significantly higher risk of exposure was found among younger, lower educated and poorer people and among those having no or partial home smoking restrictions. There was a significant interaction between education level and home smoking policies: the effect of a smoking ban on exposure to secondhand tobacco smoke was stronger for the lower educated group than the higher educated group. The results suggest that Hungarians are making good progress in implementing home smoking bans, and that in the majority of population these bans are working. More can be done to promote the uptake of home smoking bans among poorer and less educated subpopulations. [ABSTRACT FROM PUBLISHER]

This paper develops a Bayesian approach for probabilistic site characterization (i.e., on both stratigraphy and soil properties) using cone penetration tests (CPTs). The available site information prior to the project (e.g., existing geological maps, geotechnical reports, and local experience) is used in the Bayesian approach as prior knowledge, and it is integrated systematically with results of CPTs that are performed deliberately for the project. The inherent spatial variability of soil is modeled explicitly by random field theory. The proposed approach contains two major components: a Bayesian model class selection method to identify the most probable number of statistically homogenous layers of soil and a Bayesian system identification method to estimate the most probable layer thicknesses and soil properties probabilistically. Equations are derived for the Bayesian approach, and the proposed approach is illustrated using a set of real CPT data obtained from a site in Netherlands. It has been shown that the proposed approach correctly identifies the number and thicknesses/boundaries of the statistically homogenous layers of soil and provides proper probabilistic characterization of soil properties. The Bayesian approach provides a means to identify the statistically homogenous layers progressively by gradually zooming into local differences with improved resolution, and it also contains a mechanism to determine when to stop such zooming. In addition, a sensitivity study is performed to explore the effect of prior knowledge. [ABSTRACT FROM AUTHOR]

Error bounds for nonlinear filtering are very important for performance evaluation and sensor management. This paper presents a comparative study of three error bounds for tracking filtering, when the detection probability is less than unity. One of these bounds is the random finite set (RFS) bound, which is deduced within the framework of finite set statistics. The others, which are the information reduction factor (IRF) posterior Cramer-Rao lower bound (PCRLB) and enumeration method (ENUM) PCRLB are introduced within the framework of finite vector statistics. In this paper, we deduce two propositions and prove that the RFS bound is equal to the ENUM PCRLB, while it is tighter than the IRF PCRLB, when the target exists from the beginning to the end. Considering the disappearance of existing targets and the appearance of new targets, the RFS bound is tighter than both IRF PCRLB and ENUM PCRLB with time, by introducing the uncertainty of target existence. The theory is illustrated by two nonlinear tracking applications: ballistic object tracking and bearings-only tracking. The simulation studies confirm the theory and reveal the relationship among the three bounds. [ABSTRACT FROM AUTHOR]

SUMMARY This paper evaluates a forecasting procedure, which was based on the data for the period 1926-1993, in and around Japan. The period of the experiment is from 1994 to April 2011. According to the procedure, the probability that the first earthquake will be a foreshock varies in a range between 1 and 10-odd per cent, depending on its location. This location-dependent forecasting performed significantly better than the unconditional foreshock probability (3.7 per cent average) throughout the Japan region. Furthermore, when multiple earthquakes were observed as a cluster, the foreshock forecast probabilities varied in a much wider range, depending on the space-time distances and magnitude increments, between the earthquakes. Such forecasts performed better than the average foreshock probability, and the forecast probabilities were basically consistent with the outcomes. The improvements of the forecasts were objectively evaluated by using the log likelihood score. It is also shown that the forecasting procedure was robust enough and can be adopted for automatically determined earthquakes in real-time. [ABSTRACT FROM AUTHOR]

Estimation of the ratio of probability densities has attracted a great deal of attention since it can be used for addressing various statistical paradigms. A naive approach to density-ratio approximation is to first estimate numerator and denominator densities separately and then take their ratio. However, this two-step approach does not perform well in practice, and methods for directly estimating density ratios without density estimation have been explored. In this paper, we first give a comprehensive review of existing density-ratio estimation methods and discuss their pros and cons. Then we propose a new framework of density-ratio estimation in which a density-ratio model is fitted to the true density-ratio under the Bregman divergence. Our new framework includes existing approaches as special cases, and is substantially more general. Finally, we develop a robust density-ratio estimation method under the power divergence, which is a novel instance in our framework. [ABSTRACT FROM AUTHOR]

Social capital, or a sense of partnership leading to shared goals, provides a means for addressing today’s public health workforce challenges. This concept is particularly important in underserved rural areas, though efforts to intentionally generate social capital have been limited.Within the rural state of Kansas, the Kansas Public Health Leadership Institute (KPHLI) has implemented a social capital pre/post assessment to quantify the impact of KPHLI training on social capital within the state’s decentralized public health system. This paper discusses 38 assessment items related to bonding, bridging and linking social capital.The assessment was completed pre and post training by 130 of 148 scholars (87.8%) in six KPHLI training cycles. Data were analyzed using Wilcoxon paired t-tests in SPSS. Thirty-five of 38 items demonstrated statistically significant increases at post-test, across all 10 sub-domains.Leadership training by the KPHLI fosters quantifiable increases in characteristics of social capital, which are essential for public health systems to cope with increased workforce demands and prepare for accreditation. This study represents a key first step in examining the deliberate generation of social capital within a decentralized rural environment. [ABSTRACT FROM PUBLISHER]

This paper describes development of a decision support system for diagnosis of malaria using color image analysis. A hematologist has to study around 100 to 300 microscopic views of Giemsa-stained thin blood smear images to detect malaria parasites, evaluate the extent of infection and to identify the species of the parasite. The proposed algorithm picks up the suspicious regions and detects the parasites in images of all the views. The subimages representing all these parasites are put together to form a composite image which can be sent over a communication channel to obtain the opinion of a remote expert for accurate diagnosis and treatment. We demonstrate the use of the proposed technique for use as a decision support system by developing an android application which facilitates the communication with a remote expert for the final confirmation on the decision for treatment of malaria. Our algorithm detects around 96% of the parasites with a false positive rate of 20%. The Spearman correlation r was 0.88 with a confidence interval of 0.838 to 0.923, p < 0.0001. [ABSTRACT FROM AUTHOR]

The years 1910-1911 are auspicious years in Chinese mathematics with the births of Pao-Lu Hsu, Luo-Keng Hua and Shiing-Shen Chem. These three began the development of modern mathematics in China: Hsu in probability and statistics, Hua in number theory, and Chern in differential geometry. We here review some facts about the life of P.-L. Hsu which have been uncovered recently, and then discuss some of his contributions. We have drawn heavily on three papers in the 1979 Annals of Statistics (volume 7, pages 467-483) by T. W. Anderson, K. L. Chung and E. L. Lehmann, as well as an article by Jiang Ze-Han and Duan Xue-Fu in Hsu's collected papers. [ABSTRACT FROM AUTHOR]

It is pointed out that the two beta-type distributions introduced by Tardon et al have been known before in the statistics literature. [ABSTRACT FROM AUTHOR]

Promising approaches to the promotion of healthier eating among children in primary school settings include the opportunity to practise practical cooking and growing, promoting the take up of healthier school meals and nutritional education. However, less is known about the potential for strategies that integrate approaches through a focus on food sustainability issues—such as the promotion of awareness about local, seasonal, organic, fair trade and higher animal welfare foods. This paper presents an evaluation of the Food for Life Partnership, a multi-component programme that sought to address both the health and sustainability aspects of food. The study consisted of a two-stage cross-sectional survey of Years 5 and 6 students (ages 9–11) in 30 primary schools at enrolment and after 18–24 months, combined with an analysis of programme delivery. Higher self-reported fruit and vegetable consumption in the second stage survey was associated with a range of indicators of school participation in the programme. These included the reform of school meal procurement and preparation; experiential food growing, cooking and farm-based education and improved opportunities for stakeholder engagement. The study therefore develops a case for multilevel programmes that incorporate sustainability issues alongside experiential food education in primary school settings. [ABSTRACT FROM PUBLISHER]

In this paper we examine an Information-Theoretic method for solving noisy linear inverse estimation problems which encompasses under a single framework a whole class of estimation methods. Under this framework, the prior information about the unknown parameters (when such information exists), and constraints on the parameters can be incorporated in the statement of the problem. The method builds on the basics of the maximum entropy principle and consists of transforming the original problem into an estimation of a probability density on an appropriate space naturally associated with the statement of the problem. This estimation method is generic in the sense that it provides a framework for analyzing non-normal models, it is easy to implement and is suitable for all types of inverse problems such as small and or ill-conditioned, noisy data. First order approximation, large sample properties and convergence in distribution are developed as well. Analytical examples, statistics for model comparisons and evaluations, that are inherent to this method, are discussed and complemented with explicit examples. [ABSTRACT FROM AUTHOR]

koivu a., saarinen pi. & hyrkas k. (2012) Journal of Nursing Management 20, 401-413 Does clinical supervision promote medical-surgical nurses' well-being at work? A quasi-experimental 4-year follow-up study Aim The aim of the present paper is to report results of a quasi-experimental study exploring the effects of clinical supervision (CS) on the development of medical-surgical nurses' well-being at work over a 4-year period. Background Effective workplace interventions are needed to prevent stress and burnout. More robust scientific evidence is needed to confirm the restorative effects of CS in nursing. Methods A questionnaire survey on the perceptions of work and health was conducted in 2003 and 2007 on 14 units of a Finnish university hospital where 19 CS group processes had been completed between 2004 and 2007. Results Improvement in job resources as well as reduction in professional inefficacy and psychological distress were found among nurses who received effective CS ( n = 41), but were not present among the nurses who found their CS less effective ( n = 43) or who did not attend CS ( n = 82). Conclusions The results provide robust evidence for the positive effects of CS on medical-surgical nurses' well-being at work. Implications for nursing management Stress is a developmental challenge in the professional growth of individual nurses. One option for management to sustain nurses' well-being at work is to develop a learning organization in the workplace making use of CS. [ABSTRACT FROM AUTHOR]

Within a neonatal vitamin A supplementation (VAS) trial, we investigated the effect of VAS on TNF-α, IL-10, IL-5 and IL-13 production after lipopolysaccharide, purified protein derivative (PPD) of Mycobacterium tuberculosis and phytohaemagglutinin stimulation using a whole blood culture protocol. We found that VAS recipients had lower unstimulated TNF-α concentrations than placebo recipients. In the present paper, we investigated whether the SNP TNF-α − 308, TNF-α − 238, IL-10 − 592, IL-10 − 1082 and toll-like receptor 4 (TLR4)+896 modified the effect of VAS on cytokine production. DNA and cytokine concentrations were available from 291 children. We found a significant interaction between TNF-α − 308 genotype and VAS for the unstimulated TNF-α production (Pinteraction = 0·04); among G homozygotes, TNF-α concentrations were significantly lower after VAS compared with placebo, whereas for A carriers, VAS did not appear to have any effect. For TNF-α − 238, there was a tendency towards an increase in PPD-stimulated TNF-α production after VAS for the G homozygotes, but the opposite tendency for A allele carriers (Pinteraction = 0·07). Stratification by sex revealed a significant VAS–genotype interaction for boys for TNF-α − 238. There was a borderline-significant three-way interaction (P = 0·05) between sex, VAS and TLR4+896 genotype. Although the present study had very limited representation of the genetic variation with potential for modification of the response to VAS, it adds to the efforts of untangling the diverse effects and impact of VAS. [ABSTRACT FROM PUBLISHER]

Abstract: This paper studies large and moderate deviation properties of a realized volatility statistic of high frequency financial data. We establish a large deviation principle for the realized volatility when the number of high frequency observations in a fixed time interval increases to infinity. Our large deviation result can be used to evaluate tail probabilities of the realized volatility. We also derive a moderate deviation rate function for a standardized realized volatility statistic. The moderate deviation result is useful for assessing the validity of normal approximations based on the central limit theorem. In particular, it clarifies that there exists a trade-off between the accuracy of the normal approximations and the path regularity of an underlying volatility process. Our large and moderate deviation results complement the existing asymptotic theory on high frequency data. In addition, the paper contributes to the literature of large deviation theory in that the theory is extended to a high frequency data environment. [Copyright &y& Elsevier]

The aim of this paper was to describe and test a social cognitive model of physical activity tailored for adolescent girls. Participants were 1518 girls (aged 13.6 ± 0.02 years) from 24 secondary schools in New South Wales, Australia. Useable accelerometer (≥10 hours day−1 on at least 3 days) and questionnaire data were obtained from 68% of this sample (N = 1035). Participants completed questionnaires assessing psychological, behavioural, social and environmental correlates of activity. The theoretical model was tested using structural equation modelling in AMOS. The model explaining accelerometer counts per minute was an adequate-to-good fit to the data (Tucker–Lewis Index = 0.89, the comparative fit index = 0.97 and the root mean square of approximation = 0.098; 90% confidence interval = 0.075–0.122) but explained only 5% of the variance in activity. There were significant model pathways from self-efficacy (r = 0.11, P = 0.01), school environment (r = 0.07, P = 0.02) and physical self-worth (r = 0.07, P = 0.04) to accelerometer counts. Although the proposed model provided an adequate-to-good fit to the data, it explained a small portion of the variance. Shared method variance may explain the larger portions of variance explained in previous studies. Future studies are encouraged to evaluate theories of physical activity behaviour change using objective measures of physical activity. [ABSTRACT FROM PUBLISHER]

This paper proposes a stochastic shortest path approach to find an optimal sequence of tests to confirm or discard a disease, for any prescribed optimality criterion. The idea is to select the best sequence in which to apply a series of available tests, with a view at reaching a diagnosis with minimum expenditure of resources. The proposed approach derives an optimal policy whereby the decision maker is provided with a test strategy for each a priori probability of disease, aiming to reach posterior probabilities that warrant either immediate treatment or a not-ill diagnosis. [ABSTRACT FROM AUTHOR]

To address increasing rates of overweight and obesity, a population-based telephone intervention was introduced in New South Wales, Australia. The Get Healthy Information and Coaching Service® (GHS) offered participants a 6-month coaching program or detailed self-help information. Determining the population reach of GHS is of public health importance to ensure that the program reaches disadvantaged groups. This paper describes the socio-demographic and risk profile of participants (n = 4828) in the first 18 months of operations, determines how representative they are of the population, assesses changes in participants’ socio-demographic profile and compares ‘information-only’ and ‘coaching’ participants. The results show that GHS users are representative of the adult population in relation to education, employment status, Aboriginal status, fruit and vegetable consumption and alcohol use. However, more female, middle-aged, English-speaking, rural and socially disadvantaged adults participated in GHS. Coaching Participants were more likely to be overweight and to be ex-smokers than the general population. There was substantial variability in GHS recruitment, when mass-reach television advertising was used, participants enrolled from a major city and from more disadvantaged communities. The GHS has broader population reach than many local interventions, but further efforts are needed to increase reach by Aboriginal communities, other minorities and men. [ABSTRACT FROM PUBLISHER]

GEL methods that generalize and extend previous contributions are defined and analyzed for moment condition models specified in terms of weakly dependent data. These procedures offer alternative one-step estimators and tests that are asymptotically equivalent to their efficient two-step GMM counterparts. The basis for GEL estimation is via a smoothed version of the moment indicators using kernel function weights that incorporate a bandwidth parameter. Examples for the choice of bandwidth parameter and kernel function are provided. Efficient moment estimators based on implied probabilities derived from the GEL method are proposed, a special case of which is estimation of the stationary distribution of the data. The paper also presents a unified set of test statistics for overidentifying moment restrictions and combinations of parametric and moment restriction hypotheses. [ABSTRACT FROM AUTHOR]

This article distinguishes two different senses of information-theoretic approaches to statistical mechanics that are often conflated in the literature: those relating to the thermodynamic cost of computational processes and those that offer an interpretation of statistical mechanics where the probabilities are treated as epistemic. This distinction is then investigated through Earman and Norton’s ([1999]) ‘sound’ and ‘profound’ dilemma for information-theoretic exorcisms of Maxwell’s demon. It is argued that Earman and Norton fail to countenance a ‘sound’ information-theoretic interpretation and this paper describes how the latter inferential interpretations can escape the criticisms of Earman and Norton ([1999]) and Norton ([2005]) by adopting this ‘sound’ horn. This article considers a standard model of Maxwell’s demon to illustrate how one might adopt an information-theoretic approach to statistical mechanics without a reliance on Landauer’s principle, where the incompressibility of the probability distribution due to Liouville’s theorem is taken as the central feature of such an interpretation. 1 Introduction2 Information-Theoretic SM3 A Dilemma?4 Maxwell’s Demon5 The Cogency of the IT Account6 Does Landauer’s Principle Save the Second Law?7 Conclusion [ABSTRACT FROM PUBLISHER]

The Canary Islands are an active volcanic region densely populated and visited by several millions of tourists every year. Nearly twenty eruptions have been reported through written chronicles in the last 600 yr, suggesting that the probability of a new eruption in the near future is far from zero. This shows the importance of assessing and monitoring the volcanic hazard of the region in order to reduce and manage its potential volcanic risk, and ultimately contribute to the design of appropriate preparedness plans. Hence, the probabilistic analysis of the volcanic eruption time series for the Canary Islands is an essential step for the assessment of volcanic hazard and risk in the area. Such a series describes complex processes involving different types of eruptions over different time scales. Here we propose a statistical method for calculating the probabilities of future eruptions which is most appropriate given the nature of the documented historical eruptive data. We first characterize the eruptions by their magnitudes, and then carry out a preliminary analysis of the data to establish the requirements for the statistical method. Past studies in eruptive time series used conventional statistics and treated the series as an homogeneous process. In this paper, we will use a method that accounts for the time-dependence of the series and includes rare or extreme events, in the form of few data of large eruptions, since these data require special methods of analysis. Hence, we will use a statistical method from extreme value theory. In particular, we will apply a non-homogeneous Poisson process to the historical eruptive data of the Canary Islands to estimate the probability of having at least one volcanic event of a magnitude greater than one in the upcoming years. This is done in three steps: First, we analyze the historical eruptive series to assess independence and homogeneity of the process. Second, we perform a Weibull analysis of the distribution of repose time between successive eruptions. Third, we analyze the non-homogeneous Poisson process with a generalized Pareto distribution as the intensity function. [ABSTRACT FROM AUTHOR]

Lesion segmentation, which is a critical step in computer-aided diagnosis system, is a challenging task as lesion boundaries are usually obscured, irregular, and low contrast. In this paper, an accurate and robust algorithm for the automatic segmentation of breast lesions in mammograms is proposed. The traditional watershed transformation is applied to the smoothed (by the morphological reconstruction) morphological gradient image to obtain the lesion boundary in the belt between the internal and external markers. To automatically determine the internal and external markers, the rough region of the lesion is identified by a template matching and a thresholding method. Then, the internal marker is determined by performing a distance transform and the external marker by morphological dilation. The proposed algorithm is quantitatively compared to the dynamic programming boundary tracing method and the plane fitting and dynamic programming method on a set of 363 lesions (size range, 5-42 mm in diameter; mean, 15 mm), using the area overlap metric (AOM), Hausdorff distance (HD), and average minimum Euclidean distance (AMED). The mean ± SD of the values of AOM, HD, and AMED for our method were respectively 0.72 ± 0.13, 5.69 ± 2.85 mm, and 1.76 ± 1.04 mm, which is a better performance than two other proposed segmentation methods. The results also confirm the potential of the proposed algorithm to allow reliable segmentation and quantification of breast lesion in mammograms. [ABSTRACT FROM AUTHOR]

Abstract: This paper deals with the assessment of settlements of soft columnar inclusions when uncertainties in soil properties and geometric features are considered. Two common design methods, the analytical homogenisation method and the finite element method, are then combined with Monte Carlo simulations in order to find, using probability distributions of soil and geometrical characteristics, the probability of settlements exceeding a given value. The results show that length and modulus of granular piles are the two major sources of uncertainty and that the model uncertainty obtained from the interpretation of relevant sensitivities is smaller with the finite element model. From the outcome, this paper demonstrates that when geotechnical uncertainties and their effects on soil responses are appropriately accounted for, they can lead to an improved understanding and modelling of a practical geotechnical problem such as the ground improvement by columnar inclusions. [Copyright &y& Elsevier]

Copyright of International Statistical Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of International Statistical Review is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, the authors describe different instrumental variable (IV) estimators of causal risk ratios and odds ratios with particular attention to methods that can handle continuously measured exposures. The authors present this discussion in the context of a Mendelian randomization analysis of the effect of body mass index (BMI; weight (kg)/height (m)2) on the risk of asthma at age 7 years (Avon Longitudinal Study of Parents and Children, 1991–1992). The authors show that the multiplicative structural mean model (MSMM) and the multiplicative generalized method of moments (MGMM) estimator produce identical estimates of the causal risk ratio. In the example, MSMM and MGMM estimates suggested an inverse relation between BMI and asthma but other IV estimates suggested a positive relation, although all estimates had wide confidence intervals. An interaction between the associations of BMI and fat mass and obesity-associated (FTO) genotype with asthma explained the different directions of the different estimates, and a simulation study supported the observation that MSMM/MGMM estimators are negatively correlated with the other estimators when such an interaction is present. The authors conclude that point estimates from various IV methods can differ in practical applications. Based on the theoretical properties of the estimators, structural mean models make weaker assumptions than other IV estimators and can therefore be expected to be consistent in a wider range of situations. [ABSTRACT FROM PUBLISHER]