A Model of Trust, Moods, and Emotions in Multiagent Systems and its Empirical Evaluation

Abstract We study the interplay of moods, emotions, and trust in decisionmaking contexts characterized by commitments among agents. We develop a general approach representing the relationships among these concepts via a Bayesian network model. Our approach incorporates insights from the literature and provides a computational methodology for identifying improved Bayesian models. Based on observations from an empirical study, we motivate a refined Bayesian model involving the above-mentioned concepts that goes beyond the relationships known in the literature. Our findings include (1) the violation of a commitment affects trust more than its satisfaction; (2) goal satisfaction affects mood and emotion more than commitment satisfaction, but the outcome of a commitment affects trust more than the outcome of a goal; and (3) an agent's prior mood and trust affect whether it satisfies its commitments

The Relationship Between Histopathologic Findings and Body Mass Index in Sleeve Gastrectomy Materials

PubMed: 30251093Objective: For treatment of obesity, which is one of the important health problems of the present time, lifestyle modification, pharmacotherapy, behavioral treatment methods, and surgical procedures are commonly used. Sleeve gastrectomy is widely used among surgical procedures. We aimed to investigate the relationship between histopathologic findings and body mass indices (BMIs) of cases with sleeve gastrectomy in our study. Methods: Thirty-seven patients were included in our study who underwent sleeve gastrectomy and whose operation materials were examined histopathologically in our hospital. Two pathologists re-evaluated all gastrectomy materials. The relationship between BMI and the presence of gastritis, atrophy, intestinal metaplasia (IM), Helicobacter pylori (HPL), and other histopathological findings was investigated. Results: The mean age of patients included in the study was 34.7 + 9.3 years. Of patients, 70.3% were female and 29.7% were male. There was a statistically significant difference between BMI and IM among the evaluated histopathologic parameters. Moreover, IM was significantly more present in patients with type 2 diabetes. Conclusions: There is no previous study investigating the relationship between gastric histopathological findings and BMI in sleeve gastrectomy patients. We think that the statistically significant difference between BMI and IM that we found in our study may shed light on studies to be performed in the future. © 2018, Springer Science+Business Media, LLC, part of Springer Nature

The excess kurtosis of a source as a function of the relative size of the active region.

<p>A Gaussian has zero excess kurtosis. Here as in Example 2 of the original paper <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073309#pone.0073309-Daubechies1" target="_blank">[8]</a>. The four vertical lines at correspond to the relative sizes of the small box, the medium box, the large box, and a very large box corresponding to the maximal kurtosis case. Note that the medium and large box experiments have near zero excess kurtosis, <i>i.e., kurtosis value matching that of a Gaussian</i>. In addition, the pdfs of these sources are bimodal (see inset figures), ensuring that ICA algorithms designed for unimodal super-Gaussian distributions such as Infomax and FastICA with standard parameter settings, will likely fail. At the bottom of the figure are the ISI values (see Equation (2)) for the various algorithms at those four points (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0073309#pone-0073309-t001" target="_blank">Table 1</a> for full list). Also note the best separation performance of Infomax and FastICA for the maximum kurtosis case, which corresponds to almost the <i>lowest</i> level of sparsity.</p

The distribution of sources and mixtures for ().

<p>We plot (A–C) the distribution of sources, and (D) the contour plot of mixtures for the case of (). Contrary to the claim made in Daubechies et al., the sources have in fact very peaky and heavy-tailed distributions and are not at all close to a Gaussian distribution. For comparison purposes we also present Gaussian distribution curves (blue, A–B).</p