Isotopically purified semiconductors potentially dissipate heat better than their natural, isotopically mixed counterparts as they have higher thermal conductivity (κ). But the benefit is low for Si at room temperature, amounting to only ∼10% higher κ for bulk ^{28}Si than for bulk natural Si (^{nat}Si). We show that in stark contrast to this bulk behavior, ^{28}Si (99.92% enriched) nanowires have up to 150% higher κ than ^{nat}Si nanowires with similar diameters and surface morphology. Using a first-principles phonon dispersion model, this giant isotope effect is attributed to a mutual enhancement of isotope scattering and surface scattering of phonons in ^{nat}Si nanowires, correlated via transmission of phonons to the native amorphous SiO_{2} shell. The Letter discovers the strongest isotope effect of κ at room temperature among all materials reported to date and inspires potential applications of isotopically enriched semiconductors in microelectronics.

Background: Patients with suspected non-ST-elevation acute coronary syndrome (NSTE-ACS) assigned to the “observe” zone of the European Society of Cardiology (ESC) 0/1-h algorithm form a heterogeneous group known to have an unfavourable prognosis. We aim to elucidate the clinical characteristics and management of these patients and generate a model that is predictive of a coronary diagnosis at index visit to the emergency department (ED). Methods: A retrospective observational cohort study, including adult patients presenting to the ED with suspected NSTE-ACS assigned to the “observe” zone of the ESC 0/1-h algorithm. Multivariable logistic regression analysis was performed for the prediction of a coronary diagnosis. Internal validation was performed using bootstrap resampling. Results: A total of 750 patients were included; mean age 66 ± 13 years, 35% women, 50% with prior history of coronary artery disease (CAD). In 372 (50%) patients a diagnosis was established within 30 days of index presentation, of whom 169 (45%) patients had a coronary-related event. Multivariable logistic regression analysis generated a 12-point risk score incorporating 5 variables for the prediction of such event, including type of angina, chest pain occurring during inspiration, prior history of CAD, ST-segment deviation on electrocardiogram, and estimated glomerular filtration rate <60. The final model had an optimism-corrected c-statistic of 0.78 (95% confidence interval [CI]: 0.74–0.82). A score <6 ruled out a coronary event in 276 (37%) patients, with a sensitivity and negative predictive value of 90% (95% CI: 84–94) and 94% (91–96), respectively. Conclusion: A score <6 identifies patients at low risk of a coronary diagnosis and can guide clinical decision-making in choosing the appropriate diagnostic test.

OBJECTIVES To estimate the incidence and describe the spectrum of inflammatory and autoimmune diseases linked to SARS-CoV-2 infection and COVID-19 vaccination in children from two neighbouring south central European countries. METHODS We performed a multi-centre prospective cohort study of children under 18 years diagnosed with inflammatory/autoimmune diseases linked to SARS-CoV-2 infection or COVID-19 vaccination, who were admitted to the paediatric tertiary care hospitals in Slovenia and Friuli Venezia Giulia, Italy, from January 1, 2020, to December 31, 2021. Disease incidence was calculated based on laboratory-confirmed cases only. RESULTS Inflammatory and autoimmune diseases linked to SARS-CoV-2 were diagnosed in 192 children (127 laboratory-confirmed), of whom 112 had multisystem inflammatory syndrome (MIS-C), followed by vasculitis, neurological and cardiac diseases. Calculated risk of MIS-C was 1 in 860 children after SARS-CoV-2 infection and cumulative incidence of MIS-C was 18.3/100,000 of all children. Fifteen children had severe COVID-19. Two patients with MIS-C and a patient with myositis presented after COVID-19 vaccination. All 3 had at presentation also a serologically proven recent SARS-CoV-2 infection. After MIS-C, nine patients were vaccinated against COVID-19 and 25 patients had a SARS-CoV-2 reinfection, without recurrence of MIS-C. CONCLUSIONS Autoimmune diseases following SARS-CoV-2 infection in children were 8.5 times as common as severe COVID-19. MIS-C was the most common manifestation and its incidence in this predominantly white population was higher than previously reported. MIS-C does not seem to recur after SARS-CoV-2 reinfection or COVID-19 vaccination. Autoimmune diseases were much more common after SARS-CoV-2 infection than after COVID-19 vaccination.

Extreme terahertz (THz) pulses can be generated via interaction of strong infrared ultrashort laser pulses with a suitable target. Inverting this scheme, we propose to use such THz pulses to control strong-laser-field-driven processes. In particular, we show that for THz-pulse-assisted strong-laser-field ionization the electron yield can be increased by one order of magnitude for some energies, and that the maximal emitted photoelectron energy can be a few times higher than that realized with the laser field alone. This can be achieved with the THz field intensity many orders of magnitude lower than that of the ionizing laser field. The only requirement is that the vector potential amplitude of the THz field, which governs the electron dynamics after the ionization by the laser field, be comparable with that of the used laser field. An important control parameter is the time delay between the THz pulse and the laser pulse. Strong-field ionization of Cs atoms is used for an illustration. The numerical results are obtained applying the improved strong-field approximation. For a physical explanation, we use quantum-orbit theory supported by the modified saddle-point method, as well as a classical model.

Abstract Given recent environmental reforms and the focus on the problem of climate change, it is necessary to evaluate whether green growth and environmental taxes can reduce CO2 emissions for countries. Even though a number of studies have analysed the ways to reduce environmental pollution, the literature lacks enough evidence for the role of green growth and environmental taxes in determining the level of carbon emissions. Therefore, the objective of the empirical analysis is to estimate the impacts on CO2 emissions of green growth and environmental taxes by including sustainable indicators for a group of 25 environmentally friendly countries from 1994 to 2018 by applying advanced panel data analysis models. By applying the novel quantile regressions on the largest amount of available data from 1994 to 2018, this article shows that the coefficients of green growth, environmental taxes, renewable energy and energy efficiency are negative at lower, medium and higher quantiles. According to the results of the quantile regression, environmental taxes, renewable energy and energy efficiency are key factors in decreasing CO2 emissions. Overall, renewable energy should be given greater priority through research supports, subsidies and government incentives while environmental taxes should be more implemented to discourage activities that promote pollution.

This convergent mixed methods study aims to compare effectiveness of using three online consultation resources entailing deductive vs. data-driven learning on learning and retention of 18 verb-noun collocations by EFL learners. The participants ( N =45) randomly assigned to treatment conditions consulted three different online resources in different orders to complete the same online error correction tasks and gap-fill exercises in three sessions. The participants were given the Vocabulary Size Test (VST), and a productive collocation translation test (CTT) as the pretest, the posttest and the retention test. A sub-set of the participants also performed think aloud protocols during the treatment. After the treatment, the participants were given the CTT and responded a rating scale and an open-ended question. The results indicated that all of the resources led to significantly higher learning and retention rates with no significant differences among the resources. It was also found that the participants rate the resources differently and go through different cognitive processes when consulting resources. The VST scores positively correlated with the posttest scores, suggesting that participants’ vocabulary sizes can be a moderating variable. The findings are discussed based on previous research and within the framework of data-driven learning

In the paper by Obradovic et al., the first name and surname of the authors have been interchanged. The correct names of the author are listed below: Slobodan Obradovic, Boris Dzudovic, Bojana Subotic, Jovan Matijasevic, Zorica Mladenovic, Aleksandar Bokan, Jadranka Trobok, Sandra Pekovic, Sonja Salinger-Martinovic, Ljiljana Jovanovic, Ljiljana Kos, Tamara Kovacevic-Preradovic, Maja Nikolic, Vladimir Miloradovic, Ana Kovacevic-Kuzmanovic, Zec Nenad, Natasa Markovic-Nikolic, Ilija Srdanovic, Zoran Gluvic, Srdjan Kafedzic, Sasa Pancevacki, Aleksandar Neskovic and Stavros Konstantinides.

There are several issues and problems that are inevitably produced by the phenomenon and the emergence of social exclusion. These are, first of all: unemployment, inadequate education, extremely poor housing and an environment characterized by high rates of corruption and crime, insufficient and inadequate care and nursing of the elderly, low level of general health, cases of family breakdown, addiction problems, and discrimination on various grounds. Therefore, the fight against poverty and social exclusion, through the promotion of integration and inclusion in the labor market and social integration, supports marginalized groups and helps their active inclusion in social flows. The inclusion in the labor market of socially excluded groups, accompanied by projects to create a supportive environment, is particularly important and represents the best approach in their social reaffirmation and fight against all forms of social exclusion. In this sense, the development and implementation of social inclusion programs that are regulated by positive legal regulations by the state are crucial. It is the state that should, on the basis of legal regulation and through financial support, encourage social inclusion since this is the only way and basis to ensure the prevention of all forms of discrimination against socially excluded groups of citizens. In this context, the development and implementation of disability education programs are key. Support for such projects increases opportunities for education and subsequent employment and reduces the risk of social exclusion and poverty of socially excluded categories. The presented case study shows that the development and implementation of targeted inclusive education programs will give excellent results in terms of strengthening this marginalized category by improving the conditions of their education without physical and mental barriers, as well as by creating conditions for improving their later employment and labor market integration.

How statistically non-significant results are reported and interpreted following null hypothesis significance testing is often criticized. This issue is important for animal cognition research because studies in the field are often underpowered to detect theoretically meaningful effect sizes, i.e., often produce non-significant p-values even when the null hypothesis is incorrect. Thus, we manually extracted and classified how researchers report and interpret non-significant p-values and examined the p-value distribution of these non-significant results across published articles in animal cognition and related fields. We found a large amount of heterogeneity in how researchers report statistically non-significant p-values in the result sections of articles, and how they interpret them in the titles and abstracts. Reporting of the non-significant results as “No Effect” was common in the titles (84%), abstracts (64%), and results sections (41%) of papers, whereas reporting of the results as “Non-Significant” was less common in the titles (0%) and abstracts (26%), but was present in the results (52%). Discussions of effect sizes were rare (<5% of articles). A p-value distribution analysis was consistent with research being performed with low power of statistical tests to detect effect sizes of interest. These findings suggest that researchers in animal cognition should pay close attention to the evidence used to support claims of absence of effects in the literature, and—in their own work—report statistically non-significant results clearly and formally correct, as well as use more formal methods of assessing evidence against theoretical predictions.

This paper demonstrates how recursive least squares (RLS) can be used to estimate the parameters of remote environment contact force which can be used to render a virtual environment on the operator side in a bilateral teleoperation system. Proper and fast estimation of the remote environment impedance plays a crucial role in the realization of local force controllers for time delayed teleoperation systems. Addressing that challenge, in this paper, three variants of RLS estimators are implemented and compared against three different impedance models. The algorithms are tested in the simulation environment making use of a recorded real experiment data set. The force reconstruction performances are compared to evaluate the implemented models and estimators. Based on the simulation results, one of the estimators and one of the models are selected for experimental validation on a single degree of freedom motion control system. The results obtained from the experiments confirm how the estimated forces match with that of the actual force responses and provide promising potential for further application in local force controllers of the teleoperation systems.

This paper proposes a navigation algorithm for indoor mobile robots in unknown and unstructured environments using a modified Artificial Potential Fields (APF) approach. The proposed algorithm takes into consideration the well-known drawbacks of the APF such as local minima, U-Shaped traps, box canyon and the goal non-reachable with obstacles nearby (GNRON) and implies certain modifications to address those problems. The proposed method is tested in a series of simulations performed on actual lidar measurement data and taking into consideration the problems mentioned above. The results of the simulations confirm the performance of the proposed method yielding a robust and fast algorithm for indoor localization and navigation of mobile robots.

The quality of output or decision-making depends on high-quality input data, their adequate evaluation, the application of adequate approaches, and accurate calculation. In this paper, an objective criticism of applying the fuzzy SWARA (step-wise weight assessment ratio analysis) method based on the Chang TFN (triangular fuzzy number) scale is performed. Through research, it has been noticed that a large number of studies use this approach and, as an epilogue, there are wrong decisions based on inconsistent values in relation to the initial assessment of decision-makers (DMs). Seven representative studies (logistics, construction industry, financial performance management, and supply chain) with different parameter structures and decision matrix sizes have been singled out. The main hypothesis has been set, which implies that the application of this approach leads to wrong decisions because the weight values of the criteria are incorrect. A comparative analysis with the improved fuzzy SWARA (IMF SWARA) method has been created and a number of negative conclusions has been reached on using the fuzzy SWARA method and the Chang scale: Primarily, that using such an approach is impossible for two or more criteria to have equal value, that allocating TFN (1,1,1) leads to criteria values that are inconsistent with expert evaluation, that the last-ranked criteria in the fuzzy SWARA method have no influential value on the ranking of alternatives, that there is a great gap between the most significant and last-ranked criteria, and that the most significant criterion has a huge impact on the evaluation of alternative solutions and decision making. As a general conclusion, it is given that this approach is not adequate for application in problems of multi-criteria decision making because it produces inadequate management of processes and activities in various spheres.

BACKGROUND The 4S-AF scheme includes: stroke risk, symptoms, severity of burden, and substrate severity domain. AIM Our aim was to assess the adherence to 4S-AF scheme in patients classified according to stroke risk in post-hoc analysis of the BALKAN-AF dataset. METHODS A 14-week prospective enrolment of consecutive patients with electrocardiographically documented atrial fibrillation (AF) was performed in seven Balkan countries from 2014 to 2015. RESULTS Low stroke risk (CHA₂DS₂-VASc score, 0 in males or 1 in females) was present in 162 (6.0%) of the patients. 2,099 (77.4%) of patients had CHA₂DS₂-VASc score ≥3 in females or ≥2 in males (high stroke risk) and 613 (22.6%) had CHA₂DS₂-VASc score <3 in females or <2 in males. 75 (46.3%) of patients with low stroke risk and 1555 (74.1%) of patients with high stroke risk were prescribed oral anticoagulants (OAC). 2677 (98.6%) had data on European Heart Rhythm Association (EHRA) class. Among 2099 patients with high stroke risk, 703 (33.4%) had EHRA class ≥3. 207 (29.4%) of patients with EHRA class ≥3 and high stroke risk were offered rhythm control; 620 (55.2%) of individuals with first-diagnosed or paroxysmal AF with high stroke risk were offered rhythm control. Two or more comorbidities occurred in 1927 (91.8%) of patients with high stroke risk. CONCLUSIONS OAC overuse was observed in patients with low stroke risk, whilst OAC underuse was evident in those with high risk of stroke. The percentage of highly symptomatic patients with high risk of stroke who were offered rhythm control strategy was low.