Diversity, Trust and Conformity: a Simulation Study

Previous simulation models have found positive effects of cognitive diversity on group performance, but have not explored effects of diversity in demographics (e.g., gender, ethnicity). In this paper, we present an agent-based model that captures two empirically supported hypotheses about how demographic diversity can improve group performance. The results of our simulations suggest that, even when social identities are not associated with distinctive task-related cognitive resources, demographic diversity can, in certain circumstances, benefit collective performance by counteracting two types of conformity that can arise in homogeneous groups: those relating to group-based trust and those connected to normative expectations towards in-groups.

The effect of ENEAS application in patients with endometriosis and its influence on the level of IL-8 and MCP-1

Endometriosis is a gynecological disease that endometrial cells develop outside the uterus. This event happens when the endometrial glands grow outside the endometrium and uterine muscles, especially in the pelvis. Although endometriosis is widespread, the clinical manifestations of the disease are very different, and it is challenging to adapt to the conventional classification system to divide patients into homogeneous groups. Given the importance of endometriosis, a correct, accurate, and timely diagnosis of this disease can significantly prevent its complications. Using health-related software is one of these ways. Enhanced Endometriosis Archiving Software (ENEAS) is a web-based application based on one of the most widely used open-source database management systems (MySQL), allowing the direct link to other open-source software for data management and storage. In the current study, the effect of ENEAS application was considered in patients with endometriosis, and its influence on IL-8 and MCP-1 gene expression was evaluated. For this purpose, 100 women with endometriosis were divided into two groups of 50 patients. The first group (control group) was examined by a gynecologist and received medication and treatment. In the case group, their demographic and clinical information were entered into ENEAS software. To study the expression of the IL-8 gene and MCP-1 gene, after collecting 5 ml of blood samples in tubes containing anticoagulant, RNA extraction was performed by Total RNA Purification Kit (Cat. 17200, 37500, 17250). Then cDNA synthesis was performed for this purpose, and a Bioneer DNA synthesis kit (South Korea) was used. The results showed that the expression level of the IL-8 gene in the case group was significantly reduced compared to the control group (P = 0.035). MCP-1 gene expression was also decreased compared to the control group, but this decrease was not significant. Therefore, those who used this application for treatment had reduced expression of IL-8 and MCP-1 genes. This event indicates that this application has reduced the amount of inflammation caused by endometriosis with proper analysis.

IN-SITU MORPHOLOGICAL CHARACTERIZATION OF CASSAVA LANDRACES (MANIHOTESCULENTACRANTZ) FROM COTE DIVOIRE

Cassava provides food security for millions of people worldwide. In Cote dIvoire, it is the second most important food crop. The objective of this study is to evaluate the structure and genetic variability of certain qualitative traits in targeted cassava landracesin order to identify the most widespread cassava landraces. Thus, prospecting missions were carried out in different regions of Cote dIvoire to characterize cassavalandraces, from which 180 cassava landrace accessions were characterized using14 morphological markers. Multiple Correspondence Analysis (MCA) showed that among the 14 markers, 10 were relevant fordescribing the total variability within accessions. In addition, the Hierarchical Ascending Classification (HAC) grouped the Ivorianlandraces into five homogeneous groups and also revealed that this morphological diversity is not structured according to the landracesgeographical origin. The study highlighted 131 distinct cultivars among the 180 accessions characterized. Moreover, of the 131 distinct cultivars, four were the most widespread. These are the local cultivars: Yace, Six mois, Blêbou and Trogla. Thus, the study has definitively shown that breeders have a wide choice of parents for developing improved cassava cultivars adapted fromthe populations found in Cote dIvoire.

ON THE QUALITATIVE QUALITATIVE CHARACTERISTICS OF THE RESULT OF GROUPING ELECTRIC RADIO PRODUCTS INTO HOMOGENEOUS GROUPS

В работе представлен подход к определению меры однородности набора элементов - электрорадиоизделий, основанный на введении двух понятий: характеристики качества деления набора на группы и области качественного деления, как области значений характеристик качества деления, соответствующего разделению набора на однородные группы. This work presents an approach for determination of the homogeneity in a set of elements (semiconductor devices) based on the introducing two concepts: characteristic of the quality of dividing a set into groups and an area of qualitative division, as the range of values of characteristics of the quality of dividing, corresponding to dividing a set into homogeneous groups.

Application of the cluster analysis for assessing the savings and investment potential of the population of the siberian federal district

The article presents a multidimensional cluster analysis of the regions of the Siberian Federal Level by the level of savings and investment potential of the population. Clustering was carried out using the ACC Statistica based on the joint use of hierarchical and non-hierarchical algorithms. This approach made it possible to increase the reliability of dividing the regions of the district into homogeneous groups. As a result, the heterogeneity of the regions of the Siberian Federal District in terms of the studied potential is revealed. Three clusters with a high, medium and low level of savings and investment potential of the population were obtained. Each resulting cluster provides a tool for making effective decisions at the level of both a single region and the district as a whole. The analysis made it possible to analyze the current state and trends in the development of the level of savings and investment potential of the population in the Siberian Federal District. And also to find out the reasons for the low level of the investigated potential.

A Phenotyping of Diastolic Function by Machine Learning Improves Prediction of Clinical Outcomes in Heart Failure

Background: Discriminating between different patterns of diastolic dysfunction in heart failure (HF) is still challenging. We tested the hypothesis that an unsupervised machine learning algorithm would detect heterogeneity in diastolic function and improve risk stratification compared with recommended consensus criteria.Methods: This study included 279 consecutive patients aged 24–97 years old with clinically stable HF referred for echocardiographic assessment, in whom diastolic variables were measured according to the current guidelines. Cluster analysis was undertaken to identify homogeneous groups of patients with similar profiles of the variables. Sequential Cox models were used to compare cluster-based classification with guidelines-based classification for predicting clinical outcomes. The primary endpoint was hospitalization for worsening HF.Results: The analysis identified three clusters with distinct properties of diastolic function that shared similarities with guidelines-based classification. The clusters were associated with brain natriuretic peptide level (p < 0.001), hemoglobin concentration (p = 0.017) and estimated glomerular filtration rate (p = 0.001). During a mean follow-up period of 2.6 ± 2.0 years, 62 patients (22%) experienced the primary endpoint. Cluster-based classification predicted events with a hazard ratio 1.68 (p = 0.019) that was independent from and incremental to the Meta-analysis Global Group in Chronic Heart Failure (MAGGIC) risk score for HF, and from left ventricular end-diastolic volume and global longitudinal strain, whereas guidelines-based classification did not retain its independent prognostic value (hazard ratio = 1.25, p = 0.202).Conclusion: Machine learning can identify patterns of diastolic function that better stratify the risk for decompensation than the current consensus recommendations in HF. Integrating this data-driven phenotyping may help in refining prognostication and optimizing treatment.

Demand Aggregation as a Strategy for Untapping Buildings’ Energy Renovation Potential: Diagnosis and Prioritization Methodology and Case Study from the Basque Country

Energy renovation of post-World War II private multifamily residential buildings has been identified to have a great deal of energy-saving potential but faces a great challenge across Europe, and especially in South Europe, due to fragmented property structures and longer return periods in energy efficiency investments. However, there is great deal of potential in activating demand aggregation in areas with homogeneous typologies. Local authorities play a key role in leading district-scale renovation but lack adequate methods for analysing and prioritizing areas from an integrated perspective, including social aspects. The methodology presented in this paper aims to support local authorities by providing a tool for the diagnosis and prioritization of homogeneous groups of residential buildings to address their renovation based on an analysis of their needs and opportunity factors. First, the methodology sets the universe of analysis; second, based on indicators, it provides comparative information within the municipality, which leads to a prioritization of areas for building renovations according to the state of the building and to the socio-economic profile of the residents; lastly, a detailed diagnosis of selected groups is performed, providing information to design the Renovation Action Plans accordingly. The application of the methodology in Basauri is presented in this paper.

REGIONAL FEATURES OF INNOVATIVE DEVELOPMENT AND DIFFERENTIATION OF DIRECTIONS OF INNOVATION POLICY OF RUSSIA

In our manuscript we have made an attempt to study specific sides of Russian Federation’s innovative development, analyze its impact in economy growth and provide main ways of innovative policy realization in different types of regions. The method is based on partial abstraction from the unique properties of each region, thereby uniting them into homogeneous groups using k-means method. Further analysis of the determination of the main factor at the level of country was carried out using decision trees functions with the subsequent collection of OOB errors. Group analysis was carried out using regression analysis. As a result, the authors obtained five types of regions (with a high, above average, average, below average, low level of innovative development), provided an individual characteristic for each group regarding the innovation development and identified prerogative innovative factors that can be considered by the state as a criterion for differentiating state policy and regulation of the development of innovation policy.

Hemp Seed Cake as a Novel Ingredient for Dog's Diet

In the last few years, the popularity of industrial hemp and its products is increased. From a nutritional point of view, hemp and its products are rich in protein, polyunsaturated fatty acids, vitamins, and useful minerals. Nowadays, the European Commission authorizes the use of hempseed and hempseed oil co-products in animal nutrition. This study is aimed to evaluate the use of hempseed cake in dogs' nutrition, comparing the effect of the supplementation of two lipid sources: swine tallow (T-diet) and hempseed cake (H-diet). A double-blind nutritional trial was performed at a municipal kennel located in Naples. Eight crossbreed neutered dogs recognized in good health were recruited and divided into two homogeneous groups (T- vs. H-group). Both diets were analyzed for chemical composition and fatty acid profile. Blood count and biochemical profile were evaluated at recruitment (T0) and the end of the trial (T30). Oleic, palmitic, and stearic acids were the most representative fatty acids in both diets; however, the H-diet contains more than double concentration of linoleic and α-linoleic acids compared to the T-diet (p < 0.01). The H-diet has shown significantly (p < 0.01) higher peroxidation index as the only negative aspect, which could compromise its shelf-life. After 30 days of administration, the H-group has shown a significant (p < 0.01 and p < 0.05) reduction of liver and renal markers [aspartate transferase (AST), alanine transaminase (ALT), and creatinine] and cholesterol, due to the healthier fatty acid profile. Hempseed cake seems a suggestable source of polyunsaturated fatty acids for dogs considering these preliminary results.

Regional variation in British English voice quality

This study considers regional variation of voice quality in two varieties of British English – Southern Standard British English and West Yorkshire English. A comparison of voice quality profiles for three closely related but not identical northern varieties within West Yorkshire is also considered. Our findings do not contradict the small subset of previous research which explored regional and/or social variation in voice quality in British English insofar as regionality may play a small role in a speaker’s voice quality profile. However, factors such as social standing and identity could perhaps be even more relevant. Even when considering homogeneous groups of speakers, it is not the case that there is a cohesive voice quality profile that can be attached to every speaker within the group. The reason for this, we argue, is the speaker-specificity inherent in voice quality.