The concept of inclusivity involved an understanding of people, programmes and places, embedded with complex issues. 21 student designers took part in a first-of-its-kind five-day codesign programme to develop solutions for inclusive and engaged communities with residents. This quasi-experimental study aimed to develop a value-based approach using likelihood ratio table and a Naïve Bayes classifier method to assess the success of a codesign programme, in comparison to past programmes with different design challenges. Methodology proposed a systematic investigation to evaluate this programme holistically. Students discussed with stakeholders to uncover the complexities of human and environmental factors in design at early stage of ideation, and semi-structured participants’ observation tasks were considered instead of researcher's observations in the method of assessment. Selected teams were introduced to two new design methods to empathise better with seniors, i.e., Care Circle and See and Shoot. Findings revealed that these teams showed greater levels of critical inquiry when overcoming three key challenges, i.e., (1) identifying key personas, (2) examining potential use environment, and (3) access to market.

This paper raises methodological issues of radiocarbon (14C) dating of historical events based on data obtained during the excavations of the Russian medieval city of Yaroslavl. The city is of special interest to our study because of the precise time of its destruction by troops of Batu Khan mentioned in chronicles—the winter of 1238. To date in Yaroslavl, researchers have discovered 9 mass burials of citizens and domestic animals buried sometime after the massacre by the Mongols. Mass burials of people alongside animals in a common grave and outside of the cemetery, in violation of Christian traditions, are not typical of medieval Russia and are a sign of a military catastrophe. To test this hypothesis, we dated a total of 65 samples representing all 9 mass burials. A Bayesian chronological model of the accelerator mass spectrometry (AMS) dates narrowed the interval to the range of 1197–1280 cal AD, with the mean age of 1239 AD, consistent with the hypothesis that the studied mass burials of citizens and livestock are related to the capture of the city by the army of Batu Khan.

The aim of our study was to describe and to investigate the factors associated with glycopeptide-resistant enterococci (GRE) acquisition during a single-strain outbreak which occurred in several wards of hospital from September 2013 to January 2014. We designed a case–control study. Analyses were performed using Bayesian methods. Univariate logistic regressions with informative priors from published studies were conducted. A multivariate model was build including variables with a probability of odd-ratio exceeding one (Pr) >85% or <15%. Thirteen cases and 52 controls were recruited. The description of this outbreak highlighted the importance to quickly detect patients at risk of GRE carriage in order to implement the isolation measures and to transfer to dedicated department if they are effectively carriers. Following multivariate analysis, antibiotics during hospitalisation (Pr = 0.968), number of hospitalisation days in the year (Pr = 0.964), antacids intake (Pr = 0.878) (with a risk increase), immunosuppression (Pr = 0.026) and isolation measures (Pr = 0.003) (both with protective effect) were associated with GRE acquisition. The use of Bayesian statistics was useful because of our study's small population size and prior information availability.

Dietary fatty acid (FA) composition has an impact on human health. There is an increasing request from consumers for healthier food and pork industry must respond to it without worsening performance and the technological properties of pork products. The inclusion of genetic markers for carcass FA composition in pig selection schemes could be a useful tool to reach the right balance between unsaturated and saturated FAs to satisfy market demands. With the aim of finding genomic regions associated with porcine backfat FA composition, a genome-wide association study was performed on 798 Italian Large White pigs genotyped using Illumina PorcineSNP60 k. The strongest associations with backfat contents of palmitic, palmitoleic, oleic, medium-chain and long-chain FAs were found for the Sus scrofa chromosome (SSC) 8 region located at 119 to 122 Mb, where the gene ELOVL FA elongase 6 is mapped. Palmitic, palmitoleic, stearic and oleic acid contents were also found associated with SSC14, in particular with the genomic region at 121 to 124 Mb, where stearoyl-CoA desaturase Δ9 gene lies. On the other hand, the genomic regions associated with backfat contents of arachidic, arachidonic, n-6 and n-3 FAs showed to harbour mainly genes involved in dietary lipids and carbohydrates digestion, absorption and utilisation. To our knowledge, this is the first study performed in Large White pigs identifying markers and genomic regions associated with backfat FA composition. The results validate in Large White some associations previously detected in other pig breeds and indicate the involvement of distinct metabolic pathways in the deposition pattern of essential and non-essential FAs.

In 2013, one of Sweden’s largest archaeological excavations started in association with the building of the European Spallation Source (ESS) multidisciplinary research center in Lund. The 160 radiocarbon dates that were produced for the project represent the most exhaustive dating program for a Scandinavian site so far and provide evidence for the human impact and activities on the site from the Mesolithic to the Iron Age. This article presents the results within a Bayesian statistical framework for the 70 14C dates from the Early Neolithic settlement (object 1) and a burial site with dolmens and wooden façades. For the first time, a highly precise chronology provides deeper insight into the Neolithization processes and the early settlement strategies in southern Scandinavia from ~3800 cal BC onwards.

We perform a Bayesian analysis of pulsar-timing residuals from the NANOGrav pulsar-timing array to search for a specific form of stochastic narrow-band signal produced by oscillating gravitational potential (Gravitational Potential Background) in the Galactic halo. Such oscillations arise in models of warm dark matter composed of an ultralight massive scalar field (m ≃ 10−23 eV). The propagation of an electromagnetic signal from a pulsar through the time-dependent spacetime will leave an imprint in the pulsar timing, much like a gravitational wave. From the physical point of view, this is the classical Sachs-Wolfe effect. A distinctive feature of the pulsar-timing residuals due to GBP produced by a variable scalar field is that the amplitude of the TOA residuals should be independent of the pulsar location in the sky. In the monochromatic approximation, the stringent upper limit (95% C.L.) on the variable gravitational potential amplitude is found to be (Ψc<1.14 × 10−15), corresponding to the characteristic strain hc = 2$\sqrt{3}$Ψc < 4 × 10−15 at f=1.75 × 10−8 Hz. In the narrow-band approximation, the upper limit of this background energy density is ΩGPB < 1.27 × 10−9 at f=1.75 × 10−8 Hz. These limits are an order of magnitude higher than the expected signal amplitude assuming all Galactic dark matter is made of such scalar particles. The applied analysis of the pulsar-timing residuals can be used to search for any narrow-band stochastic signals with different correlation properties. As a by-product, parameters of the red noise present in four NANOGrav pulsars were found.

The Bayesian approach is a stochastic method, allowing to establish trend studies on thebehavior of materials between two periods or after a break in the life of these materials.It naturally integrates the inclusion of the information partially uncertain to support inmodeling problem. The method is therefore particularly suitable for the analysis of thereliability tests, especially for equipment and organs whose different tests are costly.Bayesian techniques are used to reduce the size of estimation tests, improving theevaluation of the parameters of product reliability by the integration of the past (dataavailable on the product concerned) and process, the case “zero” failure observed,difficult to treat with conventional statistical approach. This study will concern thereduction in the number of tests on electronic or mechanical components installed in amechanical lift knowing their a priori behavior in order to determine their a posterioribehavior.

This paper focuses on applications of Bayesian approaches to acoustic modeling for speech recognition and related speech-processing applications. Bayesian approaches have been widely studied in the fields of statistics and machine learning, and one of their advantages is that their generalization capability is better than that of conventional approaches (e.g., maximum likelihood). On the other hand, since inference in Bayesian approaches involves integrals and expectations that are mathematically intractable in most cases and require heavy numerical computations, it is generally difficult to apply them to practical speech recognition problems. However, there have been many such attempts, and this paper aims to summarize these attempts to encourage further progress on Bayesian approaches in the speech-processing field. This paper describes various applications of Bayesian approaches to speech processing in terms of the four typical ways of approximating Bayesian inferences, i.e., maximum a posteriori approximation, model complexity control using a Bayesian information criterion based on asymptotic approximation, variational approximation, and Markov chain Monte Carlo-based sampling techniques.

This paper presents a Bayesian approach using Markov chain Monte Carlo methods and the generalized-t (GT) distribution to predict loss reserves for the insurance companies. Existing models and methods cannot cope with irregular and extreme claims and hence do not offer an accurate prediction of loss reserves. To develop a more robust model for irregular claims, this paper extends the conventional normal error distribution to the GT distribution which nests several heavy-tailed distributions including the Student-t and exponential power distributions. It is shown that the GT distribution can be expressed as a scale mixture of uniforms (SMU) distribution which facilitates model implementation and detection of outliers by using mixing parameters. Different models for the mean function, including the log-ANOVA, log-ANCOVA, state space and threshold models, are adopted to analyze real loss reserves data. Finally, the best model is selected according to the deviance information criterion (DIC).

This study addresses three issues: spatial downscaling, calibration, and combination of seasonal predictions produced by different coupled ocean-atmosphere climate models. It examines the feasibility of using a Bayesian procedure for producing combined, well-calibrated downscaled seasonal rainfall forecasts for two regions in South America and river flow forecasts for the Paraná river in the south of Brazil and the Tocantins river in the north of Brazil. These forecasts are important for national electricity generation management and planning. A Bayesian procedure, referred to here as forecast assimilation, is used to combine and calibrate the rainfall predictions produced by three climate models. Forecast assimilation is able to improve the skill of 3-month lead November-December-January multi-model rainfall predictions over the two South American regions. Improvements are noted in forecast seasonal mean values and uncertainty estimates. River flow forecasts are less skilful than rainfall forecasts. This is partially because natural river flow is a derived quantity that is sensitive to hydrological as well as meteorological processes, and to human intervention in the form of reservoir management.

Fertility, generally considered as a trait of the two parents, is perhaps best defined as the interaction between the male and female gametes in the production of a viable zygote. Although zygote development and hatchability are traits of the embryo influenced by maternal effects, in most previous studies they have been considered to be female reproductive traits. The aim of this work was to study the influence of sire on fertility and hatchability traits and to estimate the (co)variance components of direct and maternal genetic effects under a Bayesian setting via Gibbs sampling. We measured the fertility of 6396 eggs and the hatchability of 5393 embryos on an individual basis. In addition, egg weight from 42 to 63 weeks of age (EW63) was recorded on an individual egg basis. The sire accounted for a significant amount of the variation infertility and hatchability. For direct heritability, the marginal posterior mean, for fertility and hatchability were almost equal (0·24). The maternal heritabilities for fertility and hatchability were 0·20 and 0·18, respectively. The direct heritability value for the egg weight trait was high. The direct-direct genetic correlation between egg weight and hatchability was negative and significant. The genetic correlations between the direct effect of the egg weight trait and maternal effects for fertility and hatchability were low, with variable signs, and were not significant. On the other hand, significant negative genetic correlations between direct and maternal effects of fertility and hatchability were obtained (the posterior means were –0·56 for FE and –0·55 for HC).

A statistical index is proposed in order to determine twin zygosity based on weight and height measures and a Bayesian test of hypotheses. Some Roman twin data are analyzed on the basis of the Euclidean distance index, which appears to be the best for an easy calculation and for its genetic interpretation based on the formulation of genetic distance.