Relationship between electrocardiogram‐based features and personality traits: Machine learning approach

Background: Based on the known relationship between the human emotion and standard surface electrocardiogram (ECG), we explored the relationship between features extracted from standard ECG recorded during relaxation and seven personality traits (Honesty/humility, Emotionality, eXtraversion, Agreeableness, Conscientiousness, Openness, and Disintegration) by using the machine learning (ML) approach which learns from the ECG-based features and predicts the appropriate personality trait by adopting an automated software algorithm. Methods: A total of 71 healthy university students participated in the study. For quantification of 62 ECG-based parameters (heart rate variability, as well as temporal and amplitude-based parameters) for each ECG record, we used computation procedures together with publicly available data and code. Among 62 parameters, 34 were segregated into separate features according to their diagnostic relevance in clinical practice. To examine the feature influence on personality trait classification and to perform classification, we used random forest ML algorithm. Results: Classification accuracy when clinically relevant ECG features were employed was high for Disintegration (81.3%) and Honesty/humility (75.0%) and moderate to high for Openness (73.3%) and Conscientiousness (70%), while it was low for Agreeableness (56.3%), eXtraversion (47.1%), and Emotionality (43.8%). When all calculated features were used, the classification accuracies were the same or lower, except for the eXtraversion (52.9%). Correlation analysis for selected features is presented. Conclusions: Results indicate that clinically relevant features might be applicable for personality traits prediction, although no remarkable differences were found among selected groups of parameters. Physiological associations of established relationships should be further explored.Ministry of Education, Science, and Technological Development, Republic of Serbia, Grant/Award Number: 179018 and TR33020; Abbott Laboratorie

Bird's-eye view on Noise-Based Logic

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as (i) What does practical determinism mean? (ii) Is noise-based logic a Turing machine? (iii) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, (iv) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.Comment: paper in pres

Diferencijacija prednjeg krila medonosne pčele iz Srbije

In this study, 12 morphological characteristics were measured on worker bee samples collected from seven different locations covering the territory of Republic Serbia. The measurement of 11 angles on the front wing and cubital index was done with stereo microscope Leica XTL-3400D, and software package IL 1009 in accordance with the standard method. The results showed significant differences between the groups of bees and investigation of angles on the forewing could be contributed to a clearer separation of groups of bees inside domestic population.U ovom istraživanju mereno je 12 morfoloških karakteristika prednjeg krila pčela radilica u skladu sa metodama Ruttner i sar. (1978). Uzorci pčela radilica su prikupljeni sa 7 različitih lokacija čime su pokriveni glavni pčelarski regioni na teritoriji Republike Srbije. Morfometrijska istraživanja pokazala su da pčele iz Zapadno Bačkog regiona u Vojvodini imaju najveću vrednost uglova B4 (113,17º), D7 (100,10º), E9 (24,28º), K19 (79,60º) i najveći kubitalni indeks (2,92). Iste pčele se na osnovu multivarijantne diskriminantne analize najviše razlikuju od grupe pčela sa Kosova. Na osnovu analize varijanse, utvrđeno je da postoji vrlo značajna razlika (P lt 0.01) u 7 morfoloških karakteristika između grupa pčela sa izabranih lokaliteta. Može se zaključiti da utvrđene vrednosti za ispitivane karaktere ukazuju na postojanje značajne varijabilnosti i impliciraju na postojanje subpopulacija uslovljenih delovanjem čoveka

Utjecaj procesa pridruživanja Europskoj uniji na organizacijsku kulturu poduzeća koja posluju u tranzicijskim zemljama

The aim of this research is to reveal the direction of change the cultural dimensions of companies in AP Vojvodina, when the Republic of Serbia – as a country in transition – was being included in the European division of labor. Foreign direct investments from EU countries are used as a method of transposing cultural patterns. The research methodology used here included the application of the Mann Whitney and the Chi square tests to compare the attitudes of the managers of these two groups of companies in AP Vojvodina. The results indicate that there is no statistically significant difference in the attitudes of managers of the two groups of companies, in terms of the questionnaire items that explore the power distance dimension. In AP Vojvodina, masculinity and individualism are still valued to a greater extent by the managers of companies with foreign capital than by those with domestic capital. Managers of the companies with foreign capital show a higher degree of uncertainty avoidance than those with domestic capital, which is contrary to authors’ expectations, though explicable in the context of the recessionary business conditions under which the research was conducted.poduzeća koja posluju u AP Vojvodini, u momentu kada se Republika Srbija – kao tranzicijska zemlja – nalazi u procesu uključivanja u Europsku podjelu rada. Inozemna izravna ulaganja iz zemalja članica EU, služe kao metoda za prenošenja kulturnih obrazaca. Metodologija istraživanja koja je ovdje korištena uključuje primjenu Mann Whitney i hi-kvadrat testova u cilju uspoređivanja stavova menadžera dviju skupina poduzeća u AP Vojvodini. Rezultati pokazuju da ne postoji statistički značajna razlika u stavovima menadžera dvije grupe poduzeća, u odnosu na pitanja koja određuju distancu moći. U AP Vojvodini, rodno muške vrijednosti i individualizam još uvijek su cijenjene u većoj mjeri od strane menadžera poduzeća koja posluju s privatnim kapitalom stranog podrijetla u odnosu na menadžere poduzeća koja posluju s privatnim kapitalom domaćega podrijetla. Menadžeri poduzeća sa stranim kapitalom pokazuju veći stupanj izbjegavanja neizvjesnosti u odnosu na menadžere poduzeća koja posluju s privatnim kapitalom domaćeg podrijetla, što je u suprotnosti s očekivanjima autora, ali se objašnjava recesijskim uvjetima poslovanja pod kojima je provedeno istraživanje

Mining protein function from text using term-based support vector machines

<p>Abstract</p> <p>Background</p> <p>Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents.</p> <p>Results</p> <p>The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent.</p> <p>Conclusion</p> <p>A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2.</p