767 resultados para collaborative filtering


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Even though collaborative consumption (CC) is gaining economic importance, research in CC is still in its infancy. Consumers’ reasons for participating have already been investigated but little research on consequences of participation has been conducted. This article examines whether interactions between customers in peer-to-peer CC services influence the willingness to coproduce service outcomes. Drawing on social exchange theory, it is proposed that this effect is mediated by consumers’ identification with the brand community. Furthermore, continuance intention in CC is introduced as a second stage moderator. In a cross-sectional study, customers of peer-to-peer accommodation sharing are surveyed. While customer-to-customer interactions were found to have a positive effect on brand community identification, brand community identification did not positively affect co-production intention. Surprisingly, the effect of brand community identification on co-production intention was negative. Moreover, continuance intention of customers did not moderate this relationship. Bearing in mind current challenges for researchers and companies, theoretical and managerial implications are discussed.

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Forming suitable learning groups is one of the factors that determine the efficiency of collaborative learning activities. However, only a few studies were carried out to address this problem in the mobile learning environments. In this paper, we propose a new approach for an automatic, customized, and dynamic group formation in Mobile Computer Supported Collaborative Learning (MCSCL) contexts. The proposed solution is based on the combination of three types of grouping criteria: learner’s personal characteristics, learner’s behaviours, and context information. The instructors can freely select the type, the number, and the weight of grouping criteria, together with other settings such as the number, the size, and the type of learning groups (homogeneous or heterogeneous). Apart from a grouping mechanism, the proposed approach represents a flexible tool to control each learner, and to manage the learning processes from the beginning to the end of collaborative learning activities. In order to evaluate the quality of the implemented group formation algorithm, we compare its Average Intra-cluster Distance (AID) with the one of a random group formation method. The results show a higher effectiveness of the proposed algorithm in forming homogenous and heterogeneous groups compared to the random method.

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Text classification, information filtering, semi-supervised learning, quality control

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A collaborative exercise was carried out by the European DNA Profiling Group (EDNAP) in order to evaluate the distribution of mitochondrial DNA (mtDNA) heteroplasmy amongst the hairs of an individual who displays point heteroplasmy in blood and buccal cells. A second aim of the exercise was to study reproducibility of mtDNA sequencing of hairs between laboratories using differing chemistries, further to the first mtDNA reproducibility study carried out by the EDNAP group. Laboratories were asked to type 2 sections from each of 10 hairs, such that each hair was typed by at least two laboratories. Ten laboratories participated in the study, and a total of 55 hairs were typed. The results showed that the C/T point heteroplasmy observed in blood and buccal cells at position 16234 segregated differentially between hairs, such that some hairs showed only C, others only T and the remainder, C/T heteroplasmy at varying ratios. Additionally, differential segregation of heteroplasmic variants was confirmed in independent extracts at positions 16093 and the poly(C) tract at 302-309, whilst a complete A-G transition was confirmed at position 16129 in one hair. Heteroplasmy was observed at position 16195 on both strands of a single extract from one hair segment, but was not observed in the extracts from any other segment of the same hair. Similarly, heteroplasmy at position 16304 was observed on both strands of a single extract from one hair. Additional variants at positions 73, 249 and the HVII poly(C) region were reported by one laboratory; as these were not confirmed in independent extracts, the possibility of contamination cannot be excluded. Additionally, the electrophoresis and detection equipment used by this laboratory was different to those of the other laboratories, and the discrepancies at position 249 and the HVII poly(C) region appear to be due to reading errors that may be associated with this technology. The results, and their implications for forensic mtDNA typing, are discussed in the light of the biology of hair formation.

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This study introduces a novel approach for automatic temporal phase detection and inter-arm coordination estimation in front-crawl swimming using inertial measurement units (IMUs). We examined the validity of our method by comparison against a video-based system. Three waterproofed IMUs (composed of 3D accelerometer, 3D gyroscope) were placed on both forearms and the sacrum of the swimmer. We used two underwater video cameras in side and frontal views as our reference system. Two independent operators performed the video analysis. To test our methodology, seven well-trained swimmers performed three 300 m trials in a 50 m indoor pool. Each trial was in a different coordination mode quantified by the index of coordination. We detected different phases of the arm stroke by employing orientation estimation techniques and a new adaptive change detection algorithm on inertial signals. The difference of 0.2 +/- 3.9% between our estimation and video-based system in assessment of the index of coordination was comparable to experienced operators' difference (1.1 +/- 3.6%). The 95% limits of agreement of the difference between the two systems in estimation of the temporal phases were always less than 7.9% of the cycle duration. The inertial system offers an automatic easy-to-use system with timely feedback for the study of swimming.

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The present study was performed to assess the interlaboratory reproducibility of the molecular detection and identification of species of Zygomycetes from formalin-fixed paraffin-embedded kidney and brain tissues obtained from experimentally infected mice. Animals were infected with one of five species (Rhizopus oryzae, Rhizopus microsporus, Lichtheimia corymbifera, Rhizomucor pusillus, and Mucor circinelloides). Samples with 1, 10, or 30 slide cuts of the tissues were prepared from each paraffin block, the sample identities were blinded for analysis, and the samples were mailed to each of seven laboratories for the assessment of sensitivity. A protocol describing the extraction method and the PCR amplification procedure was provided. The internal transcribed spacer 1 (ITS1) region was amplified by PCR with the fungal universal primers ITS1 and ITS2 and sequenced. As negative results were obtained for 93% of the tissue specimens infected by M. circinelloides, the data for this species were excluded from the analysis. Positive PCR results were obtained for 93% (52/56), 89% (50/56), and 27% (15/56) of the samples with 30, 10, and 1 slide cuts, respectively. There were minor differences, depending on the organ tissue, fungal species, and laboratory. Correct species identification was possible for 100% (30 cuts), 98% (10 cuts), and 93% (1 cut) of the cases. With the protocol used in the present study, the interlaboratory reproducibility of ITS sequencing for the identification of major Zygomycetes species from formalin-fixed paraffin-embedded tissues can reach 100%, when enough material is available.

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There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.

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Forensic scientists working in 12 state or private laboratories participated in collaborative tests to improve the reliability of the presentation of DNA data at trial. These tests were motivated in response to the growing criticism of the power of DNA evidence. The experts' conclusions in the tests are presented and discussed in the context of the Bayesian approach to interpretation. The use of a Bayesian approach and subjective probabilities in trace evaluation permits, in an easy and intuitive manner, the integration into the decision procedure of any revision of the measure of uncertainty in the light of new information. Such an integration is especially useful with forensic evidence. Furthermore, we believe that this probabilistic model is a useful tool (a) to assist scientists in the assessment of the value of scientific evidence, (b) to help jurists in the interpretation of judicial facts and (c) to clarify the respective roles of scientists and of members of the court. Respondents to the survey were reluctant to apply this methodology in the assessment of DNA evidence.

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Errors in the inferred multiple sequence alignment may lead to false prediction of positive selection. Recently, methods for detecting unreliable alignment regions were developed and were shown to accurately identify incorrectly aligned regions. While removing unreliable alignment regions is expected to increase the accuracy of positive selection inference, such filtering may also significantly decrease the power of the test, as positively selected regions are fast evolving, and those same regions are often those that are difficult to align. Here, we used realistic simulations that mimic sequence evolution of HIV-1 genes to test the hypothesis that the performance of positive selection inference using codon models can be improved by removing unreliable alignment regions. Our study shows that the benefit of removing unreliable regions exceeds the loss of power due to the removal of some of the true positively selected sites.

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Report for the scientific sojourn at the University of California at Berkeley, USA, from september 2007 until july 2008. Communities of Learning Practice is an innovative paradigm focused on providing appropriate technological support to both formal and especially informal learning groups who are chiefly formed by non-technical people and who lack of the necessary resources to acquire such systems. Typically, students who are often separated by geography and/or time have the need to meet each other after classes in small study groups to carry out specific learning activities assigned during the formal learning process. However, the lack of suitable and available groupware applications makes it difficult for these groups of learners to collaborate and achieve their specific learning goals. In addition, the lack of democratic decision-making mechanisms is a main handicap to substitute the central authority of knowledge presented in formal learning.

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Introduction: Mirtazapine is a noradrenergic and serotonergic antidepressant mainly acting through blockade of presynaptic alpha-2 receptors. Published data on pregnancy outcome after exposure to mirtazapine are scarce. This study addresses the risk associated with exposure to mirtazapine during pregnancy. Patients (or Materials) and Methods: Multicenter (n = 11), observational prospective cohort study comparing pregnancy outcomes after exposure to mirtazapine with 2 matched control groups: exposure to any selective serotonin reuptake inhibitor (SSRI) as a diseasematched control group, and general controls with no exposure to medication known to be teratogenic or to any antidepressant. Data were collected by members of the European Network of Teratology Information Services (ENTIS) during individual risk counseling between 1995 and 2011. Standardized procedures for data collection were used in each center. Results: A total of 357 pregnant women exposed to mirtazapine at any time during pregnancy were included in the study and compared with 357 pregnancies from each control group. The rate of major birth defects between the mirtazapine and the SSRI group did not differ significantly (4.5% vs 4.2%; unadjusted odds ratio, 1.1; 95% confidence interval, 0.5-2.3, P = 0.9). A trend toward a higher rate of birth defects in the mirtazapine group compared with general controls did not reach statistical significance (4.2% vs 1.9%; OR, 2.4; 95% CI, 0.9-6.3; P = 0.08). The crude rate of spontaneous abortions did not differ significantly between the mirtazapine, the SSRI, and the general control groups (9.5% vs 10.4% vs 8.4%; P = 0.67), neither did the rate of deliveries resulting in live births (79.6% vs 84.3% in both control groups; P = 0.15). However, a higher rate of elective pregnancy-termination was observed in the mirtazapine group compared with SSRI and general controls (7.8% vs 3.4% vs 5.6%; P = 0.03). Premature birth (< 37 weeks) (10.6% vs 10.1% vs 7.5%; P = 0.38), gestational age at birth (median, 39 weeks; interquartile range (IQR), 38-40 in all groups; P = 0.29), and birth weight (median, 3320 g; IQR, 2979-3636 vs 3230 g; IQR, 2910-3629 vs 3338 g; IQR, 2967-3650; P = 0.34) did not differ significantly between the groups. Conclusion: This study did not observe a statistically significant difference in the rate of major birth defects between mirtazapine, SSRI-exposed, and nonexposed pregnancies. A slightly higher rate of birth defects was, however, observed in the mirtazapine and SSRI groups compared with the low rate of birth defects in our general controls. Overall, the pregnancy outcome after mirtazapine exposure in this study is very similar to that of the SSRI-exposed control group.

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Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

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Bipolar disorder has a genetic component, but the mode of inheritance remains unclear. A previous genome scan conducted in 70 European families led to detect eight regions linked to bipolar disease. Here, we present an investigation of whether the phenotypic heterogeneity of the disorder corresponds to genetic heterogeneity in these regions using additional markers and an extended sample of families. The MLS statistic was used for linkage analyses. The predivided sample test and the maximum likelihood binomial methods were used to test genetic homogeneity between early-onset bipolar type I (cut-off of 22 years) and other types of the disorder (later onset of bipolar type I and early-onset bipolar type II), using a total of 138 independent bipolar-affected sib-pairs. Analysis of the extended sample of families supports linkage in four regions (2q14, 3p14, 16p23, and 20p12) of the eight regions of linkage suggested by our previous genome scan. Heterogeneity testing revealed genetic heterogeneity between early and late-onset bipolar type I in the 2q14 region (P = 0.0001). Only the early form of the bipolar disorder but not the late form appeared to be linked to this region. This region may therefore include a genetic factor either specifically involved in the early-onset bipolar type I or only influencing the age at onset (AAO). Our findings illustrate that stratification according to AAO may be valuable for the identification of genetic vulnerability polymorphisms.