Polyhydramnios is a condition related to an excessive accumulation of amniotic fluid in the third trimester of pregnancy and it can be acute and chronic depending on the duration. Published data suggest that during muscle development, in the stage of late histochemical differentiation decreased mechanical loading cause decreased expression of myosin heavy chain (MHC) type 1 leading to slow-to-fast transition. In the case of chronic polyhydramnios, histochemical muscle differentiation could be affected as a consequence of permanent decreased physical loading. Most affected would be muscles which are the most active i.e., spine extensor muscles and muscles of legs. Long-lasting decreased mechanical loading on muscle should cause decreased expression of MHC type 1 leading to slow-to-fast transition, decreased number of muscle fiber type I especially in extensor muscles of spine and legs. Additionally, because MHC type 1 is present in all skeletal muscles it could lead to various degrees of hypotrophy depending on constituting a percentage of MHC type 1 in affected muscles. These changes in the case of preexisting muscle disorders have the potential to deteriorate the muscle condition additionally. Given these facts, idiopathic chronic polyhydramnios is a rare opportunity to study the influence of reduced physical loading on muscle development in the human fetus. Also, it could be a medical entity to examine the influence of micro- and hypogravity conditions on the development of the fetal muscular system during the last trimester of gestation.

This paper investigates the impact of foreign direct investment on economic growth, on a sample of three groups of countries, classified according to the criterion of economic development. The research problem that seeks to be solved is defined by the question: Do foreign direct investment affect the economic growth of targeted countries and in what way? The objectives of the research are to explain the mechanism of functioning of foreign direct investment and the implications for macroeconomic growth parameters, ceteris paribus. The results of the research show the existence of correlation and determination of the dependent variable with the variations of the independent variable. In this way, the main hypothesis of the paper was confirmed, that foreign direct investment has a stimulating effect on economic growth and the effect of investment is a priori determined by the defined economic policy and the appropriate institutional and legislative framework of the countries, ceteris paribus. The methods used in this paper are regression analysis, i.e. simple linear regression, and analysis and synthesis of previous research and theoretical findings, in order to draw conclusions by induction. The analysis of the data confirms that foreign direct investments have an impact on the economic growth of each group of countries individually, but that in certain groups this connection is present. Thus, the results of the research showed the existence of a relation between FDI and economic growth, i.e. they emphasized FDI as a significant predictor of economic growth in the targeted groups of countries ceteris paribus. The paper represents the author's contribution to economic theory and practice, and to the general public, but also to decision-makers in developing countries. Further research should be directed towards whether it is possible to influence the increase of GDP by "copying" a certain country in terms of attracting foreigners.

Artificial neural networks (ANNs) providing sophisticated, power-efficient classification are finding their way into thin-film electronics. Thin-film technologies require robust, layout-efficient devices with facile manufacturability. Here, we show how the multimodal transistor’s (MMT’s) transfer characteristic, with linear dependence in saturation, replicates the rectified linear unit (ReLU) activation function of convolutional ANNs (CNNs). Using MATLAB, we evaluate CNN performance using systematically distorted ReLU functions, then substitute measured and simulated MMT transfer characteristics as proxies for ReLU. High classification accuracy is maintained, despite large variations in geometrical and electrical parameters, as CNNs use the same activation functions for training and classification.

This paper describes comparative analysis of the biomechanical performances conducted on the external fixation devices whose frames are made out of two different material (stainless steel and composite material). Biomechanical properties were determined with experimental and FEM (finite element method) models which are used to study the movement of the fracture crack, establish stiffness of the design solutions and monitor generated stresses on the zones of interest. Geometric modeling of two fixation devices configurations B50 and C50 is used as a basis for structural analysis under the impact of axial load. Structural analysis results are confirmed with an experimental setup. Analyzed deflection values in the load and fracture zones are used to define the exact values of the stiffness for the construction design and fracture, respectively. The carbon frame device configuration has 28% lower construction stiffness than the one with the steel frame (for B50 configuration), i.e., 9% (for C50 configuration). In addition, fracture stiffness values for the composite frame application are approximately 23% lower (B50 configuration), i.e., 13% lower (C50 configuration), compared to steel frame. The carbon frame device has about 33% lower stresses at the critical zones compared to the steel frame at the control zone MM+ and, similarly, 35% lower stresses at the control zone MM-. With an exhausting analysis of the biomechanical properties of the fixation devices, it can be concluded that steel frame fixation device is superior, meaning it has better biomechanical characteristics compared to carbon frame fixation device, regarding obtained data for stresses and stiffnesses of the frame construction and fracture. Considering stresses at the critical zones of the fixation device construction, the carbon frame device has better biomechanical performances compared to steel frame devices.

Biometric security is a major emerging concern in the field of data security. In recent years, research initiatives in the field of biometrics have grown at an exponential rate. The multimodal biometric technique with enhanced accuracy and recognition rate for smart cities is still a challenging issue. This paper proposes an enhanced multimodal biometric technique for a smart city that is based on score-level fusion. Specifically, the proposed approach provides a solution to the existing challenges by providing a multimodal fusion technique with an optimized fuzzy genetic algorithm providing enhanced performance. Experiments with different biometric environments reveal significant improvements over existing strategies. The result analysis shows that the proposed approach provides better performance in terms of the false acceptance rate, false rejection rate, equal error rate, precision, recall, and accuracy. The proposed scheme provides a higher accuracy rate of 99.88% and a lower equal error rate of 0.18%. The vital part of this approach is the inclusion of a fuzzy strategy with soft computing techniques known as an optimized fuzzy genetic algorithm.

Surrogate neural network-based models have been lately trained and used in a variety of science and engineering applications where the number of evaluations of a target function is limited by execution time. In cell phone camera systems, various errors, such as interferences at the lens-barrel and lens-lens interfaces and axial, radial, and tilt misalignments, accumulate and alter profile of the lenses in a stochastic manner which ultimately changes optical focusing properties. Nonlinear finite element analysis of the stochastic mechanical behavior of lenses due to the interference fits is used on high-performance computing (HPC) to generate sufficient training and testing data for subsequent deep learning. Once properly trained and validated, the surrogate neural network model enabled accurate and almost instant evaluations of millions of function evaluations providing the final lens profiles. This computational model, enhanced by artificial intelligence, enabled us to efficiently perform Monte-Carlo analysis for sensitivity and uncertainty quantification of the final lens profile to various interferences. It can be further coupled with an optical analysis to perform ray tracing and analyze the focal properties of the lens module. Moreover, it can provide a valuable tool for optimizing tolerance design and intelligent components matching for many similar press-fit assembly processes.

Background and objective Tobacco tax evasion undermines the goal of tobacco taxes as a tobacco control measure to make tobacco products less affordable, increases the health risks for those who smoke and decreases the government revenue. This paper analyses the tobacco tax evasion in six Western Balkan (WB) countries: Albania, Bosnia and Herzegovina, Kosovo, Montenegro, North Macedonia and Serbia. The aim of this research is to estimate the size of the illicit market and identify the main determinants of tax evasion activities in the Southeastern European region. Data and methods Data from 2019 Survey on Tobacco Consumption in Southeastern Europe (STC-SEE) are used. STC-SEE provides uniquely comparable nationally representative data on smoking behaviour for adult (18–85 years old) population for each country. Tax evasion is defined on the basis of available information on tax stamps, health warnings, price and the place of purchase, in accordance with the previous research on tax evasion. In order to estimate the determinants of illicit purchases we use binary choice model of tax evasion. Results The study finds that 20.4% of all current smokers in WB countries evade taxes on tobacco products, with evasion being much more frequent for hand-rolled (HR) tobacco (86.7%) than for the manufactured cigarettes (MC) (8.6%). While HR is predominantly illicit in all six countries, MC evasion varies significantly, with evasion being significantly higher in Montenegro and Bosnia and Herzegovina. Results further suggest that tax evasion is higher in the statistical regions where institutional capacities to tackle illicit trade are lower, in municipalities bordering countries with high MC evasion, as well as among smokers with low income, women and elderly. We also provide evidence that higher tobacco taxes and prices do not increase illicit consumption. Conclusion The findings from the research suggest that in order to decrease tax evasion, governments should put additional effort to strengthen institutional capacities to tackle illicit tobacco markets. Furthermore, improving regional coordination in development and implementation of tobacco control policies, including the prevention of illicit market, is essential in lowering evasion in all WB countries. Finally, WB countries should regulate and enforce excise tax stamp requirements on the HR tobacco market to a much higher degree.

The goal of the state estimation (SE) algorithm is to estimate complex bus voltages as state variables based on the available set of measurements in the power system. Because phasor measurement units (PMUs) are increasingly being used in transmission power systems, there is a need for a fast SE solver that can take advantage of high sampling rates of PMUs. This paper proposes training a graph neural network (GNN) to learn the estimates given the PMU voltage and current measurements as inputs, with the intent of obtaining fast and accurate predictions during the evaluation phase. GNN is trained using synthetic datasets, created by randomly sampling sets of measurements in the power system and labelling them with a solution obtained using a linear SE with PMUs solver. The presented results display the accuracy of GNN predictions in various test scenarios and tackle the sensitivity of the predictions to the missing input data.

Introduction: In this study we aimed to perform the first research on the current state of compulsory basic and clinical courses in genetics for medical students offered at medical faculties in six Balkan countries with Slavic languages (Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia, Serbia, and Slovenia). Materials and Methods: The study was conducted from June to September 2021. One representative from each country was invited to collect and interpret the data for all medical faculties in their respective country. All representatives filled a questionnaire, which consisted of two sets of questions. The first set of questions was factual and contained specific questions about medical faculties and design of compulsory courses, whereas the second set of questions was more subjective and inquired the opinion of the representatives about mandatory education in clinical medical genetics in their countries and internationally. In addition, full course syllabi were analysed for course aims, learning outcomes, course content, methods for student evaluation and literature. Results: Detailed analysis was performed for a total of 22 medical faculties in Bosnia and Herzegovina (6), Croatia (4), Montenegro (1), North Macedonia (3), Serbia (6), and Slovenia (2). All but the two medical faculties in Slovenia offer either compulsory courses in basic education in human genetics (16 faculties/courses) or clinical education in medical genetics (3 faculties/courses). On the other hand, only the medical faculty in Montenegro offers both types of education, including one course in basic education in human genetics and one in clinical education in medical genetics. Most of the basic courses in human genetics have similar aims, learning outcomes and content. Conversely, clinical courses in medical genetics are similar concerning study year position, number of contact hours, ECTS (European Credit Transfer and Accumulation System) and contents, but vary considerably regarding aims, learning outcomes, ratio of types of classes, teaching methods and student evaluation. Conclusion: Our results emphasise the need for future collaboration in reaching a consensus on medical genetics education in Balkan countries with Slavic languages. Further research warrants the analysis of performance of basic courses, as well as introducing clinical courses in medical genetics to higher years of study across Balkan countries.

ABSTRACT Background Deployment of modern assistive technologies is one of the major trends. The main objective is the provisioning of the effectiveness and cost-estimation model for deploying assistive technology solutions in elderly care intended for evaluation and showing specificity to the costs and associated benefits of providing smart technological solutions for seniors. Methods The model uses demographic projections taken from Eurostat for EU countries and the disability incidence from the annual report of the Ministry of Labour and Social Affairs of the Czech Republic as an input. The model was implemented in the software Stella Professional dedicated to system dynamics modelling. Results In relation to the combination of five assistive devices for the elderly the optimal solution the cost savings are 37.8% or182 billion CZK, cumulatively in the simulated time period 2021–2060. The model allows adjustments regarding price levels of various countries through the caregivers’ wage. Obtained results showed robustness of the model to this uncertainty as percentage savings varied only from 37.6% to 39.8%, a mere 2.2% difference. Conclusion With respect to the ongoing demographic transition, the need to employ smart device solutions should further increase and their price could decline. The highest savings will come from countries with higher wages for carers.

The subject of this paper is design, testing and implementation of voltage control of buck power electronics converter using programmable logic controller (PLC) which is based on Beckhoff technology. The proposed control structure is first modelled in the Matlab/Simulink software environment. The built Simulink model is then integrated and transferred to the TwinCAT 3 software which converts personal computer (PC)/laptop into the real-time PLC. This paper proposes an experimental platform consisting of the following components: laptop computer used as the PLC, Beckhoff input/output (I/O) interface, power electronics converter with gate driver module, and electronic modules for measuring and adjusting the signals between the converter and the Beckhoff PLC. In this paper, the control is implemented on the example of the buck converter. However, the proposed modular experimental platform can be used for any type of the converter. Thanks to the integration of the Matlab/Simulink and TwinCAT 3 software environments and the modularity of the platform, the proposed experimental platform is suitable for rapid prototyping of different control structures of power electronics converters, which is especially useful for educational and research purposes. The given experimental results validate excellent performances of the proposed platform.

As the first robotics journal offered by ACM, the Transactions on Human-Robot Interaction (ACM THRI) made considerable progress to advance the field of HRI since its inaugural offering in 2018. ACM THRI remains the flagship journal for leading research in the burgeoning area of Human-Robot Interaction (HRI). The interdisciplinary field of HRI aims to understand and advance our knowledge of human-robot systems towards advancing usable and useful robotic technology. ACM THRI features leading thought into how people interact with robots and robotic technologies, how to improve these interactions and make new kinds of interaction possible, and the effects of such interactions on organizations or society. HRI brings together researchers and practitioners with diverse expertise, including but not limited to robotics, artificial intelligence, human factors, psychology, design, haptics, and mechatronics. We officially began our term in January 2017 as Editors-in-Chief of the Journal of Human-Robot Interaction, the predecessor to ACM THRI. We were fortunate to build on the foundation of JHRI provided by its founding editors, Profs. Sara Kiesler and Michael Goodrich. Our leadership of ACM THRI would not be possible without the tremendous effort and dedication of our core editorial team, including our amazing Managing Editor (Prof. James Young), Journal Administrator (Gita Delsing) and Information Director (Dr. Daniel Rea) as well as their predecessors (Prof. David FeilSeifer, Ms. Jeanie Lyubelsky, and Prof. Monica Anderson). Although it has presented unique challenges and new opportunities, we remain grateful for the opportunity to lead the transition of JHRI to ACM ownership and further extend ACM THRI. Our focus as Editors-in-Chief has been to establish commitment to excellence, sustainability, and inclusion in the scholarship and review processes of ACM THRI, which has proved successful to this point. As stated in our introductory editorial, our primary aims for the Journal have been three fold: (1) increase the sustainability and impact of HRI as a field (both quantitatively and qualitatively), (2) enable timely and productive review feedback, and (3) cultivate new and leading ideas in both robotics and the human-centered sciences. ACM THRI has remained true to this scope and made significant strides towards realizing these values across the practices of the journal. For our review processes, our goal has been to provide useful feedback to our authors that enables them to improve their work and make contributions worthy of intellectual leadership. We aim to return substantive review feedback to authors within 105 days of the date of submission, and 70 days for revisions. The total average for ACM THRI returning decisions for submitted manuscripts is currently 142 days in 2021, 122 days from April 2020 to December 2020, 114.7 days in the first three months of 2020 (submissions just prior to the COVID-19 pandemic), and 99 days in 2019. Our review process includes significant deliberation and discussion among our editorial board of every manuscript and decision, which occurs during our weekly editorial teleconferences. A summary of our editorial consensus with a reasoned and supported argument is provided with

Sensory integration represents the organization of the senses for their use. It is a neuro-biological activity that allows the reception and processing of sensory information, which in arrive from the senses in huge quantities into the brain, at any time. The ability of the brain to successfully process tactile information allows the child to feel safe and develop a connection with those around it. An autistic child is not able to register many stimuli from their environment, so insufficient or poor sensory processing can contribute to the image of autism. Children with autism spectrum difficulties have specific difficulties in touch perception. The aim of the study was to examine the prevalence of sensory integration difficulties of the tactile sensory system of children with autism spectrum disorders, and to establish the statistical significance of differences in relation to children without developmental difficulties. The total sample of subjects (N=30) consisted of two subsamples. The first subsample of subjects (N=15) consisted of children with difficulties from the autism spectrum, and the second subsample of subjects (N=15) consisted of children without developmental difficulties. The measurement instrument was the „Questionnaire for testing tactile sensory sensitivity“ with 11 variables and the offered answers of possible sensory response was applied. The Mann-Whitney U test and the Wilcoxon W test at the level of statistical significance of p<0.05 were used to examine the statistical significance of the differences between the subsamples of the subjects. The results of the study showed that 86.67 % of children with autism have difficulties in sensory integration of the tactile sensory system. The hypersensitive type of sensory response has 26.67 %, and the hyposensitive sensory response 20 % of children with autism. 40.00 % of children with autism have a mixed type of tactile sensory. There is a statistically significant difference between children with autism and children without developmental difficulties on 4 variables.