Planar Thermoelectric Microgenerators in Application to Power RFID Tags.

This paper presents an innovative approach to the integration of thermoelectric microgenerators (µTEGs) based on thick-film thermopiles of planar constantan-silver (CuNi-Ag) and calcium cobaltite oxide-silver (Ca3Co4O9-Ag) thick-film thermopiles with radio frequency identification (RFID) technology. The goal was to consider using the TEG for an active or semi-passive RFID tag. The proposed implementation would allow the communication distance to be increased or even operated without changing batteries. This article discusses the principles of planar thermoelectric microgenerators (µTEGs), focusing on their ability to convert the temperature difference into electrical energy. The concept of integration with active or semi-passive tags is presented, as well as the results of energy efficiency tests, considering various environmental conditions. On the basis of the measurements, the parameters of thermopiles consisting of more thermocouples were simulated to provide the required voltage and power for cooperation with RFID tags. The conclusions of the research indicate promising prospects for the integration of planar thermoelectric microgenerators with RFID technology, opening the way to more sustainable and efficient monitoring and identification systems. Our work provides the theoretical basis and practical experimental data for the further development and implementation of this innovative technology.

Deep learning assisted distinguishing of honey seasonal changes using quadruple voltammetric electrodes.

The work presents innovative quadruple disk iridium, platinum, and iridium-platinum voltammetric electrodes with a special design, dedicated to the testing of samples with a complex organic composition. Noble metal wires are tightened in one silver rod, and therefore each of them acts as a single sensor. It was demonstrated that the signals of the iridium-platinum sensor combine the electrode responses constructed from one metal, which increases the possibilities and range of applications of this sensor, and it can be used as an electronic tongue. These single and combined noble metal electrodes were successfully verified to profile the seasonal variability of honey collected from an apiary in Malopolska (voivodeship in Poland). Data obtained by the differential pulse voltammetry, according to the principles of green chemistry, without using any reagents, were interpreted by principal component analysis, preceded by the optimized variable selection procedure. The best results in distinguishing 12 honeys were obtained using a multimetallic electrode. The classification model calculated using deep convolutional neural networks indicated the proper belonging of honeys to the groups with 100% accuracy for the training and validation set. The proposed solution proved that noble metals quadruple disk electrodes are a promising tool supporting voltammetric profiling of samples and this strategy, considering deep learning, can be developed to a large extent.

Processes discriminating adaptive and maladaptive Internet use among European adolescents highly engaged online.

Today adolescents are highly engaged online. Contrary to common concern, not all highly engaged adolescents develop maladaptive patterns of internet use. The present qualitative study explored the experiences, patterns and impact of use of 124 adolescents (M(age) = 16.0) reporting signs of internet addictive behaviors. The focus was to discern adaptive and maladaptive use patterns, which promote or interfere with adolescents' development, respectively. Semi-structured individual interviews were conducted in seven European countries (Greece, Spain, Poland, Germany, Romania, Netherlands and Iceland) and qualitatively analyzed using grounded theory. Considerable variability emerged in the way adolescents satisfied their personal needs online and offline, in the experienced impact from high online engagement and functional value ascribed to the internet, and in the self-regulatory processes underlying use. Variability in these discriminating processes was linked to adaptive or maladaptive adolescent internet use patterns. The emerged processes can provide direction for designing prevention and intervention programs promoting adaptive use.

Internet addictive behavior in adolescence: a cross-sectional study in seven European countries.

A cross-sectional school-based survey study (N=13,284; 53% females; mean age 15.8±0.7) of 14-17-year-old adolescents was conducted in seven European countries (Greece, Spain, Poland, Germany, Romania, the Netherlands, and Iceland). The aim of the study was to investigate the prevalence of Internet addictive behavior (IAB) and related psychosocial characteristics among adolescents in the participating countries. In the study, we distinguish two problematic groups: adolescents with IAB, characterized by a loss of control over their Internet use, and adolescents "at risk for IAB," showing fewer or weaker symptoms of IAB. The two groups combined form a group of adolescents with dysfunctional Internet behavior (DIB). About 1% of adolescents exhibited IAB and an additional 12.7% were at risk for IAB; thus, in total, 13.9% displayed DIB. The prevalence of DIB was significantly higher among boys than among girls (15.2% vs. 12.7%, p<0.001) and varied widely between countries, from 7.9% in Iceland to 22.8% in Spain. Frequent use of specific online activities (e.g., gambling, social networking, gaming) at least 6 days/week was associated with greater probability of displaying DIB. Multiple logistic regression analysis indicated that DIB was more frequent among adolescents with a lower educational level of the parents, earlier age at first use of the Internet, and greater use of social networking sites and gaming sites. Multiple linear regression analysis showed that externalizing (i.e., behavioral) and internalizing (i.e., emotional) problems were associated with the presence of DIB.