Using machine learning algorithms and techniques for defining the impact of affective temperament types, content search and activities on the internet on the development of problematic internet use in adolescents' population.

Background: By using algorithms and Machine Learning - ML techniques, the aim of this research was to determine the impact of the following factors on the development of Problematic Internet Use (PIU): sociodemographic factors, the intensity of using the Internet, different contents accessed on the Internet by adolescents, adolescents' online activities, life habits and different affective temperament types. Methods: Sample included 2,113 adolescents. The following instruments were used: questionnaire about: socio-demographic characteristics, intensity of the Internet use, content categories and online activities on the Internet; Facebook (FB) usage and life habits; The Internet Use Disorder Scale (IUDS). Based on their scores on the scale, subjects were divided into two groups - with or without PIU; Temperament Evaluation of Memphis, Pisa, Paris, and San Diego scale for adolescents (A-TEMPS-A). Results: Various ML classification models on our data set were trained. Binary classification models were created (class-label attribute was PIU value). Models hyperparameters were optimized using grid search method and models were validated using k-fold cross-validation technique. Random forest was the model with the best overall results and the time spent on FB and the cyclothymic temperament were variables of highest importance for these model. We also applied the ML techniques Lasso and ElasticNet. The three most important variables for the development of PIU with both techniques were: cyclothymic temperament, the longer use of the Internet and the desire to use the Internet more than at present time. Group of variables having a protective effect (regarding the prevention of the development of PIU) was found with both techniques. The three most important were: achievement, search for contents related to art and culture and hyperthymic temperament. Next, 34 important variables that explain 0.76% of variance were detected using the genetic algorithms. Finally, the binary classification model (with or without PIU) with the best characteristics was trained using artificial neural network. Conclusion: Variables related to the temporal determinants of Internet usage, cyclothymic temperament, the desire for increased Internet usage, anxious and irritable temperament, on line gaming, pornography, and some variables related to FB usage consistently appear as important variables for the development of PIU.

BioMThermDB 1.0: Thermophysical Database of Proteins in Solutions.

We present here a freely available web-based database, called BioMThermDB 1.0, of thermophysical and dynamic properties of various proteins and their aqueous solutions. It contains the hydrodynamic radius, electrophoretic mobility, zeta potential, self-diffusion coefficient, solution viscosity, and cloud-point temperature, as well as the conditions for those determinations and details of the experimental method. It can facilitate the meta-analysis and visualization of data, can enable comparisons, and may be useful for comparing theoretical model predictions with experiments.

Factors contributing to communication skills development in cochlear implanted children.

BACKGROUND/AIM: Over the last 10 years more than 300 persons received cochlear implant in Serbia and more than 90% of the recipients were children under 10 years of age. The program of cochlear implantation includes postoperative rehabilitation in which cognitive, integrative and developmental methods are used. The study was conducted to reveal factors affecting communication performance (CP) of cochlear implanted (Cl) children. Special attention was focused on the influence of the duration and intensity of rehabilitation and hearing age on further development of communication skills. METHODS: A group of 30 CI children (13 boys and 17 girls) aged 2 to 5 years was enrolled in the study. All of the children had average intelligence and no other developmental disorder. They lived in families and attended rehabilitative seances 3 to 5 times a week. Their parents/caregivers answered structured questionnaire about functioning after pediatric cochlear implantation (FAPCI) and the results were the subject of detailed statistical analysis. RESULTS: Analysis of variance did not show any difference between the boys and the girls regarding FAPCI achievements (F(1, 28) = 2.909; p = 0.099) and age aberration in CP score (F(1,28) = 0.114, p = 0.738). Correlation analysis showed a statistically significant difference in FAPCI scores related to hearing age and duration of rehabilitation. Regression analysis (enter method) showed that model consisting of indipendent variables significantly contributed to prediction of overall FAPCI scores and Adjusted R2 value could explain 32% difference in communication skills of participants in this study. CONCLUSION: Communication skills of CI children evaluated by FAPCI are falling behind normatives for normal hearing children 18.6 months on the average. Hearing age, duration and intensity of rehabilitation have positive predictive value for communication skills development. Later identification of hearing loss and later cochlear implantation lead to delayed development of communication skills.