Applying eXplainable AI Techniques to Interpret Machine Learning Predictive Models for the Analysis of Problematic Internet Use among Adolescents

This research focusses on the potential application of artificial intelligence (AI) techniques in the analysis of behavioural addictions, specifically addressing problematic Internet use among adolescents. Using tabular data from a representative sample from Serbian high schools, the authors investigated the feasibility of employing eXplainable AI (XAI) techniques, placing special emphasis on feature selection and feature importance methods. The results indicate a successful application to tabular data, with global interpretations that effectively describe predictive models. These findings align with previous research, which confirms both relevance and accuracy. Interpretations of individual predictions reveal the impact of features, especially in cases of misclassified instances, underscoring the significance of XAI techniques in error analysis and resolution. Although AI’s influence on the medical domain is substantial, the current state of XAI techniques, although useful, is not yet advanced enough for the reliable interpretation of predictions. Nevertheless, XAI techniques play a crucial role in problem identification and the validation of AI models

Lead Telluride Doped with Au as a Very Promising Material for Thermoelectric Applications

PbTe single crystals doped with monovalent Au or Cu were grown using the Bridgman method. Far infrared reflectivity spectra were measured at room temperature for all samples and plasma minima were registered. These experimental spectra were numerically analyzed and optical parameters were calculated. All the samples of PbTe doped with Au or Cu were of the “n” type. The properties of these compositions were analyzed and compared with PbTe containing other dopants. The samples of PbTe doped with only 3.3 at% Au were the best among the PbTe + Au samples having the lowest plasma frequency and the highest mobility of free carriers-electrons, while PbTe doped with Cu was the opposite. Samples with the lowest Cu concentration of 0.23 at% Cu had the best properties. Thermal diffusivity and electronic transport properties of the same PbTe doped samples were also investigated using a photoacoustic (PA) method with the transmission detection configuration. The results obtained with the far infrared and photoacoustic characterization of PbTe doped samples were compared and discussed. Both methods confirmed that when PbTe was doped with 3.3 at% Au, thermoelectric and electrical properties of this doped semiconductor were both significantly improved, so Au as a dopant in PbTe could be used as a new high quality thermoelectric material

Recent Improvements of Power Plants Management and Technology

Since first AC current high-power hydropower plant was put in operation, built by Nikola Tesla and George Westinghouse in 1895 on Niagara Falls, electrification of the world has dramatically changed. The growing power demand and energy consumption in the last decades require fundamental changes in the process, power production, and services. These requirements tend to use both conventional and nonconventional energy generation in order to have power plants economically useful and environmentally friendly to the society. The goal of this textbook is to provide an up-to-date review of this important topic with specific emphasis on the current guidelines for improving overall efficiency, lowering emissions, and using large share of renewable energy

Thermal, electron transport and far infrared properties of PbTe single crystals doped with Br

Understanding the properties of PbTe remains in focus as enhancement of thermoelectric efficiency of this material is studied extensively. In this work single crystals of PbTe, doped with less than 2 at % Br, were synthesized using the Bridgmann technique and their thermal, electron transport and far infrared properties were studied. Thermal diffusivity was determined using the photoacoustic method with a transmission detection configuration. Electron transport was determined by Seebeck coefficient measurements. IR reflectivity measurements showed that reflectivity in the region of plasma resonance was low. Measured reflectivity diagrams were numerically analyzed - enabling calculation of the carrier concentration and mobility-and compared with the values obtained by Hall measurements

Atherogenic impact of homocysteine: Can hmg-coa reductase inhibitors additionally influence hyperhomocysteinaemia?

© 2019, University of Kragujevac, Faculty of Science. All rights reserved. The strong association among the risk of coronary artery diseases (CAD), high levels of LDL-C and low levels of HDL-C is well established. Hyperhomocysteinaemia (HHcy) is an independent risk factor for cardiovascular disease (CVD) and causes endothelial dysfunction, a hallmark of atherosclerosis. In this study, we ascertained the influence of statins on the atherogenic index, as an indicator and a significant adjunct for predicting atherosclerosis in hyperhomocysteinaemic male Wistar albino rats. For 4 weeks, the animals were fed with one of the following diets (Mucedola SRL., Milan, Italy): standard rodent chow; a diet enriched in methionine with no deficiency in B vitamins or a diet enriched in methionine and deficient in B vitamins. The animals were simultaneously exposed to a pharmacology treatment with atorvastatin at dose of 3 mg/kg/day i.p. or simvastatin, at dose of 5 mg/kg/day i.p. We measured weight gain, food intake, and FER and determined the concentrations of biochemical parameters of dyslipidaemia (TC, TGs, LDL-C, VLDL-C, and HDL-C), AI, and CRR. A histopathological examination was conducted on portions of the right and left liver lobes from each animal. A connection between Hhcy and dyslipidaemia was indicated by the findings of biochemical and histological analyses, suggesting that Hhcy was a pro-atherogenic state. An improvement in the lipid profile along with a decrease in the atherogenic index by statins suggests that atorvastatin and simvastatin could be useful antiatherogenic agents, with protective activities during hyperhomocysteinaemia

Improving Education in Medical Statistics: Implementing a Blended Learning Model in the Existing Curriculum.

BACKGROUND:Although recent studies report on the benefits of blended learning in improving medical student education, there is still no empirical evidence on the relative effectiveness of blended over traditional learning approaches in medical statistics. We implemented blended along with on-site (i.e. face-to-face) learning to further assess the potential value of web-based learning in medical statistics. METHODS:This was a prospective study conducted with third year medical undergraduate students attending the Faculty of Medicine, University of Belgrade, who passed (440 of 545) the final exam of the obligatory introductory statistics course during 2013-14. Student statistics achievements were stratified based on the two methods of education delivery: blended learning and on-site learning. Blended learning included a combination of face-to-face and distance learning methodologies integrated into a single course. RESULTS:Mean exam scores for the blended learning student group were higher than for the on-site student group for both final statistics score (89.36±6.60 vs. 86.06±8.48; p = 0.001) and knowledge test score (7.88±1.30 vs. 7.51±1.36; p = 0.023) with a medium effect size. There were no differences in sex or study duration between the groups. Current grade point average (GPA) was higher in the blended group. In a multivariable regression model, current GPA and knowledge test scores were associated with the final statistics score after adjusting for study duration and learning modality (p<0.001). CONCLUSION:This study provides empirical evidence to support educator decisions to implement different learning environments for teaching medical statistics to undergraduate medical students. Blended and on-site training formats led to similar knowledge acquisition; however, students with higher GPA preferred the technology assisted learning format. Implementation of blended learning approaches can be considered an attractive, cost-effective, and efficient alternative to traditional classroom training in medical statistics