153 resultados para Informal Hiring Networks


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The genetic characterization of unbalanced mixed stains remains an important area where improvement is imperative. In fact, with current methods for DNA analysis (Polymerase Chain Reaction with the SGM Plus™ multiplex kit), it is generally not possible to obtain a conventional autosomal DNA profile of the minor contributor if the ratio between the two contributors in a mixture is smaller than 1:10. This is a consequence of the fact that the major contributor's profile 'masks' that of the minor contributor. Besides known remedies to this problem, such as Y-STR analysis, a new compound genetic marker that consists of a Deletion/Insertion Polymorphism (DIP), linked to a Short Tandem Repeat (STR) polymorphism, has recently been developed and proposed elsewhere in literature [1]. The present paper reports on the derivation of an approach for the probabilistic evaluation of DIP-STR profiling results obtained from unbalanced DNA mixtures. The procedure is based on object-oriented Bayesian networks (OOBNs) and uses the likelihood ratio as an expression of the probative value. OOBNs are retained in this paper because they allow one to provide a clear description of the genotypic configuration observed for the mixed stain as well as for the various potential contributors (e.g., victim and suspect). These models also allow one to depict the assumed relevance relationships and perform the necessary probabilistic computations.

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Using optimized voxel-based morphometry, we performed grey matter density analyses on 59 age-, sex- and intelligence-matched young adults with three distinct, progressive levels of musical training intensity or expertise. Structural brain adaptations in musicians have been repeatedly demonstrated in areas involved in auditory perception and motor skills. However, musical activities are not confined to auditory perception and motor performance, but are entangled with higher-order cognitive processes. In consequence, neuronal systems involved in such higher-order processing may also be shaped by experience-driven plasticity. We modelled expertise as a three-level regressor to study possible linear relationships of expertise with grey matter density. The key finding of this study resides in a functional dissimilarity between areas exhibiting increase versus decrease of grey matter as a function of musical expertise. Grey matter density increased with expertise in areas known for their involvement in higher-order cognitive processing: right fusiform gyrus (visual pattern recognition), right mid orbital gyrus (tonal sensitivity), left inferior frontal gyrus (syntactic processing, executive function, working memory), left intraparietal sulcus (visuo-motor coordination) and bilateral posterior cerebellar Crus II (executive function, working memory) and in auditory processing: left Heschl's gyrus. Conversely, grey matter density decreased with expertise in bilateral perirolandic and striatal areas that are related to sensorimotor function, possibly reflecting high automation of motor skills. Moreover, a multiple regression analysis evidenced that grey matter density in the right mid orbital area and the inferior frontal gyrus predicted accuracy in detecting fine-grained incongruities in tonal music.

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OBJECTIVES: Mindfulness is a concept of growing impact on psychotherapy and has been shown to be effective for stress reduction and to improve psychological well-being. Existential Behavioural Therapy (EBT) was developed to support relatives of palliative care (PC) patients to cope with their situation during caregiving and bereavement. Mindfulness training was a core element of the intervention. We investigated the relationship between mindfulness, mental distress, and psychological well-being in informal caregivers, and evaluated if the effects of the intervention were mediated by mindfulness. METHODS: Relatives of PC inpatients took part in a randomized-controlled EBT trial and completed the Cognitive and Affective Mindfulness Scale-Revised, items from the Five Facets of Mindfulness as well as the Brief Symptom Inventory, the Satisfaction with Life Scale, the WHOQOL-BREF, a numerical rating scale on quality of life (range 0-10), and the Schedule for Meaning in Life Evaluation at pre- and post-intervention, and a 3- and 12-months follow-up. RESULTS: One-hundred-and-thirty carers were included, most of them (71.6%) recently being bereaved at the beginning of the intervention. High correlations between mindfulness and mental distress (r = -0.51, p < 0.001) as well as life satisfaction (r = 0.52, p < 0.001) were found. Mindfulness was a significant predictor of improvement in psychological distress, meaning in life and quality of life three months after the intervention. The EBT effects were partly mediated by mindfulness. SIGNIFICANCE OF RESULTS: Mindfulness seems to be a promising concept in supporting informal caregivers of PC patients. Further research is needed to identify the required format and intensity of mindfulness practice necessary for improvement.

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Functional magnetic resonance imaging studies have indicated that efficient feature search (FS) and inefficient conjunction search (CS) activate partially distinct frontoparietal cortical networks. However, it remains a matter of debate whether the differences in these networks reflect differences in the early processing during FS and CS. In addition, the relationship between the differences in the networks and spatial shifts of attention also remains unknown. We examined these issues by applying a spatio-temporal analysis method to high-resolution visual event-related potentials (ERPs) and investigated how spatio-temporal activation patterns differ for FS and CS tasks. Within the first 450 msec after stimulus onset, scalp potential distributions (ERP maps) revealed 7 different electric field configurations for each search task. Configuration changes occurred simultaneously in the two tasks, suggesting that contributing processes were not significantly delayed in one task compared to the other. Despite this high spatial and temporal correlation, two ERP maps (120-190 and 250-300 msec) differed between the FS and CS. Lateralized distributions were observed only in the ERP map at 250-300 msec for the FS. This distribution corresponds to that previously described as the N2pc component (a negativity in the time range of the N2 complex over posterior electrodes of the hemisphere contralateral to the target hemifield), which has been associated with the focusing of attention onto potential target items in the search display. Thus, our results indicate that the cortical networks involved in feature and conjunction searching partially differ as early as 120 msec after stimulus onset and that the differences between the networks employed during the early stages of FS and CS are not necessarily caused by spatial attention shifts.

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This paper presents and discusses the use of Bayesian procedures - introduced through the use of Bayesian networks in Part I of this series of papers - for 'learning' probabilities from data. The discussion will relate to a set of real data on characteristics of black toners commonly used in printing and copying devices. Particular attention is drawn to the incorporation of the proposed procedures as an integral part in probabilistic inference schemes (notably in the form of Bayesian networks) that are intended to address uncertainties related to particular propositions of interest (e.g., whether or not a sample originates from a particular source). The conceptual tenets of the proposed methodologies are presented along with aspects of their practical implementation using currently available Bayesian network software.

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We consider electroencephalograms (EEGs) of healthy individuals and compare the properties of the brain functional networks found through two methods: unpartialized and partialized cross-correlations. The networks obtained by partial correlations are fundamentally different from those constructed through unpartial correlations in terms of graph metrics. In particular, they have completely different connection efficiency, clustering coefficient, assortativity, degree variability, and synchronization properties. Unpartial correlations are simple to compute and they can be easily applied to large-scale systems, yet they cannot prevent the prediction of non-direct edges. In contrast, partial correlations, which are often expensive to compute, reduce predicting such edges. We suggest combining these alternative methods in order to have complementary information on brain functional networks.

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The scenario considered here is one where brain connectivity is represented as a network and an experimenter wishes to assess the evidence for an experimental effect at each of the typically thousands of connections comprising the network. To do this, a univariate model is independently fitted to each connection. It would be unwise to declare significance based on an uncorrected threshold of α=0.05, since the expected number of false positives for a network comprising N=90 nodes and N(N-1)/2=4005 connections would be 200. Control of Type I errors over all connections is therefore necessary. The network-based statistic (NBS) and spatial pairwise clustering (SPC) are two distinct methods that have been used to control family-wise errors when assessing the evidence for an experimental effect with mass univariate testing. The basic principle of the NBS and SPC is the same as supra-threshold voxel clustering. Unlike voxel clustering, where the definition of a voxel cluster is unambiguous, 'clusters' formed among supra-threshold connections can be defined in different ways. The NBS defines clusters using the graph theoretical concept of connected components. SPC on the other hand uses a more stringent pairwise clustering concept. The purpose of this article is to compare the pros and cons of the NBS and SPC, provide some guidelines on their practical use and demonstrate their utility using a case study involving neuroimaging data.

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BACKGROUND: Existential behavioural therapy (EBT) was developed to support informal caregivers of palliative patients in the last stage of life and during bereavement as a manualised group psychotherapy comprising six sessions. We tested the effectiveness of EBT on mental stress and quality of life (QOL). METHODS: Informal caregivers were randomly assigned (1:1) to EBT or a treatment-as-usual control group using computer-generated numbers in blocks of 10. Primary outcomes were assessed with the Brief Symptom Inventory (subscales somatisation, anxiety and depression), the Satisfaction with Life Scale (SWLS), the WHOQOL-BREF and a numeric rating scale for QOL (QOL-NRS, range 0-10). Data were collected at baseline, pre-treatment, post-treatment and follow-ups after 3 and 12âeuro0/00months. Treatment effects were assessed with a multivariate analysis of covariance. RESULTS: Out of 160 relatives, 81 were assigned to EBT and 79 to the control group. Participants were 54.5âeuro0/00±âeuro0/0013.2âeuro0/00years old; 69.9% were female. The multivariate model was significant for the pre-/post-comparison (pâeuro0/00=âeuro0/000.005) and the pre-/12-month comparison (pâeuro0/00=âeuro0/000.05) but not for the pre-/3-month comparison. Medium to large effects on anxiety and QOL (SWLS, WHOQOL-BREF, QOL-NRS) were found at post-treatment; medium effects on depression and QOL (QOL-NRS) emerged in the 12-month follow-up. No adverse effects of the intervention were observed. CONCLUSION: Existential behavioural therapy appears to exert beneficial effects on distress and QOL of informal caregivers of palliative patients. Further longitudinal evidence is needed to confirm these findings. Copyright © 2013 John Wiley & Sons, Ltd.

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This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.

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We examine the relationship between structural social capital, resource assembly, and firm performance of entrepreneurs in Africa. We posit that social capital primarily composed of kinship or family ties helps the entrepreneur to raise resources, but it does so at a cost. Using data drawn from small firms in Kampala, Uganda, we explore how shared identity among the entrepreneur's social network moderates this relationship. A large network contributed a higher quantity of resources raised, but at a higher cost when shared identity was high. We discuss the implications of these findings for the role of family ties and social capital in resource assembly, with an emphasis on developing economies.