Effects of Negation and Uncertainty Stratification on Text-Derived Patient Profile Similarity

Semantic similarity is a useful approach for comparing patient phenotypes, and holds the potential of an effective method for exploiting text-derived phenotypes for differential diagnosis, text and document classification, and outcome prediction. While approaches for context disambiguation are commonly used in text mining applications, forming a standard component of information extraction pipelines, their effects on semantic similarity calculations have not been widely explored. In this work, we evaluate how inclusion and disclusion of negated and uncertain mentions of concepts from text-derived phenotypes affects similarity of patients, and the use of those profiles to predict diagnosis. We report on the effectiveness of these approaches and report a very small, yet significant, improvement in performance when classifying primary diagnosis over MIMIC-III patient visits.

Entropy-Based Quantification of Privacy Attained Through User Profile Similarity

Location-based services refer to services that use location as primary input. But accessing user's location by an adversary invites issues of privacy breach. Instead of specific location coordinates, its surrounding area known as cloaking region is revealed in order to get the service. K anonymity technique of location privacy ensures that at least K-1 users should be included within a specific cloaked region. Researches have established that on combining K anonymity with the idea of including similar users together in a cloaked region provides stringent privacy (especially from background and heterogeneity attacks). This work quantifies the amount of privacy gain attained through, opting-for users with similar profiles instead of random users. The quantification is done by using KL divergence. Values of KL divergence of user profiles have been calculated for different cloaking regions containing similar and random users. Low KL divergence values depict privacy gains up to 33% for users with similar profiles.

Core Self-Evaluation Moderates Distinctive Similarity Preference in Ideal Partner’s Personality

This research investigated the moderation effects of core self-evaluation (CSE) on singles’ ideal partner preference, concerning distinctive similarity in personality. The data were collected from singles from three countries (i.e., China, Denmark, and US), and modelled in a multilevel profile analysis. The results show that CSE moderated distinctive profile similarity preference in that people high in CSE preferred higher distinctive profile similarity with their ideal partner. In addition, CSE moderated distinctive trait similarity preference in Emotionality, Extraversion, Agreeableness, and Conscientiousness in that people high in CSE preferred their ideal partner to share higher distinctive similarity on these four traits. Implications and limitations of the research and findings are also discussed.

Effect of Noise Adaptive Wavelet Filter on Diagnostic Performance in Stroke Perfusion

Background: Computed tomography perfusion (CTP) images include more noise than routine clinic computed tomography (CT) images. Singular value decomposition based deconvolution algorithms are widely used for obtaining several functional perfusion maps. Recently block circulant singular value decomposition algorithms become popular for its superior property of immunity to contrast bolus lag. It is well known from literature that these algorithms are very sensitive to noise. There are a lot of examples of noise reduction filters in the literature as well as commercial ones. Functional maps which help physicians in the diagnostic process can be obtained with better image quality by de-noising CTP images with adaptive noise reduction filters. Objective: In this study, the effect of a noise adaptive wavelet filtering method on diagnostic performance on CTP stroke patient images is investigated. Method: Images of acute stroke patients were de-noised by this method and their diagnostic value were evaluated by visual means, peak signal-to-noise ratio and time intensity profile metrics. An observer evaluation study was carried out in order to validate quantitative image quality metrics. The results are compared with Gaussian and a bilateral filter based filtering method called TIPS (Time Intensity Profile Similarity) on same images sets to benchmark proposed method. Results: The diagnostic value of the images obtained from noise adaptive wavelet filtering method were better than Gaussian filter method and were compatible with a wellknown time intensity profile similarity bilateral filter method. Diagnostic performance of the both observers were improved compared to both Gaussian and TIPS methods. Conclusion: The noise adaptive wavelet filter method succeeded to reduce noise while preserving details contained in the contrast bolus. Its final effect on the timeintensity profiles and generated perfusion maps are compatible with the literature and showed improvements on diagnostic performance on specificity and overall accuracy when compared to other methods.

More Similar, Better Belonging: Effect of Organizational Citizenship Behavior Profile Similarity on Ostracism

As positive nontask behavior, organizational citizenship behavior (OCB) is a well-known concept that has been investigated by numerous studies. However, weakness in the research stream is viewing this concept from the perspective of the actor. In this study, OCB is considered as a social activity that assists actors’ survival in their organizations, and how OCB affects ostracism that effectively reflects belonging in the organization is investigated. Moreover, to identify the relationship in detail, three different independent variables are used, including OCB, OCB aggregate gap, and OCB profile similarity, using social exchange theory and similarity attraction theory. The analysis is conducted using samples from 210 employees who work for Korean companies. The results indicate that OCB profile similarity has a stronger effect on reducing ostracism than the absolute level of OCB and the OCB aggregate gap.

Mineral Composition of Cereal and Cereal-Free Dry Dog Foods versus Nutritional Guidelines

The aims of the present work are to estimate the nutritional value and to evaluate and compare the levels of macroelements (Ca, P, K, Na, Mg), microelements (Fe, Zn, Mn, Cu), heavy metals (Co, Cd, Pb, Mo, Cr, Ni), and their ratios in extruded complete foods for adult dogs, their compatibility with nutritional guidelines, as well as food profile similarity. Basic composition was determined according to Association of Official Analytical Chemists (AOAC). Analyses for elements were performed using an atomic absorption spectrometer. All the evaluated dry dog foods met the minimum recommended levels for protein and fat. Eighteen tested dog foods (60%) did not meet at least one recommendation of nutritional guidelines. Four dog foods exceeded the legal limit of Fe and five foods exceeded the legal limit of Zn; in one of them, Zn level was almost twice higher. Dog foods with insect protein exceeded the legal limit for Mn content. Eight dog foods had an inappropriate Ca:P ratio. Heavy metals were below detection limit in all analyzed dog foods. The results seem to show the need for regular feed analyses of the elemental composition in raw materials before introducing supplementation and for the monitoring of the mineral composition of finished pet food.

A Test of Three Sadism Measures

The aim of this study was to evaluate psychometric properties of three sadism scales: Short Sadistic Impulse Scale (SSIS), Varieties of Sadistic Tendencies (VAST, which measures direct and vicarious sadism), and Assessment of Sadistic Personality (ASP). Sample included 443 participants (50.1% men) from the general population. Reliability based on internal consistency of all scales was good, and results of Confirmatory Factor Analysis (CFA) showed that all three scales had acceptable fit indices for the proposed structure. Results of Item Response Theory (IRT) analysis showed that all three scales had higher measurement precision (information) in above-average scores. Validity of the scales was supported through moderate to high positive correlations with the Dark Triad traits, especially psychopathy, as well as positive correlations with aggressiveness and negative with Honesty-Humility. Moreover, results of hierarchical regression analysis showed that all three measures of direct, but not vicarious sadism, contributed significantly above and beyond other Dark Triad traits to the prediction of increased positive attitudes toward dangerous social groups. The profile similarity index showed that the SSIS and the ASP were highly overlapping, while vicarious sadism seems distinct from other sadism scales.

Benchmarking orthology methods using phylogenetic patterns defined at the base of Eukaryotes

Insights into the evolution of ancestral complexes and pathways are generally achieved through careful and time-intensive manual analysis often using phylogenetic profiles of the constituent proteins. This manual analysis limits the possibility of including more protein-complex components, repeating the analyses for updated genome sets or expanding the analyses to larger scales. Automated orthology inference should allow such large-scale analyses, but substantial differences between orthologous groups generated by different approaches are observed. We evaluate orthology methods for their ability to recapitulate a number of observations that have been made with regard to genome evolution in eukaryotes. Specifically, we investigate phylogenetic profile similarity (co-occurrence of complexes), the last eukaryotic common ancestor’s gene content, pervasiveness of gene loss and the overlap with manually determined orthologous groups. Moreover, we compare the inferred orthologies to each other. We find that most orthology methods reconstruct a large last eukaryotic common ancestor, with substantial gene loss, and can predict interacting proteins reasonably well when applying phylogenetic co-occurrence. At the same time, derived orthologous groups show imperfect overlap with manually curated orthologous groups. There is no strong indication of which orthology method performs better than another on individual or all of these aspects. Counterintuitively, despite the orthology methods behaving similarly regarding large-scale evaluation, the obtained orthologous groups differ vastly from one another. Availability and implementation The data and code underlying this article are available in github and/or upon reasonable request to the corresponding author: https://github.com/ESDeutekom/ComparingOrthologies.