Inherited retinal diseases cause severe visual deficits in children. They are classified in outer and inner retina diseases, and often cause blindness in childhood. The diagnosis for this type of illness is challenging, given the wide range of clinical and genetic causes (with over 200 causative genes). It is routinely based on a complex pattern of clinical tests, including invasive ones, not always appropriate for infants or young children. A different approach is thus needed, that exploits Chromatic Pupillometry, a technique increasingly used to assess outer and inner retina functions. This paper presents a novel Clinical Decision Support System (CDSS), based on Machine Learning using Chromatic Pupillometry in order to support diagnosis of Inherited retinal diseases in pediatric subjects. An approach that combines hardware and software is proposed: a dedicated medical equipment (pupillometer) is used with a purposely designed custom machine learning decision support system. Two distinct Support Vector Machines (SVMs), one for each eye, classify the features extracted from the pupillometric data. The designed CDSS has been used for diagnosis of Retinitis Pigmentosa in pediatric subjects. The results, obtained by combining the two SVMs in an ensemble model, show satisfactory performance of the system, that achieved 0.846 accuracy, 0.937 sensitivity and 0.786 specificity. This is the first study that applies machine learning to pupillometric data in order to diagnose a genetic disease in pediatric age.

BACKGROUND Lead and cadmium are significant environmental pollutants that cause pathophysiological responses in many organs. Heavy metal absorption into many tissues is very fast due to a pronounced affinity for metallothioneins. METHOD Japanese quail were exposed to different concentrations of metals (cadmium 0.20 mg/L and lead 0.25 and 0.50 mg/L) for 20 days. Erythrocytes (normal and hemolyzed) and lymphocytes (normal and altered) were monitored in this study. The analysis observed the percentage of normal and altered cells, as well as erythrocyte surface area. Cell counts were analyzed using light microscopy, while surface area and cytological changes in cells and nuclei were analyzed using licensed software. RESULTS Different concentrations of metals have caused erythrocyte hemolysis as well as structural and morphological alterations in lymphocytes. Destruction of cell and nucleus membrane, changes in cell size, erythrocyte denucleation and reduced erythrocyte surface area were observed. Cadmium has caused erythrocyte hemolysis (29.30 %) and lymphocyte damage (92.10 %). Higher doses of lead resulted in greater damage to lymphocytes (63 %). Also, treatment with higher dose of lead produced a higher percentage of hemolyzed erythrocytes (19.20 %) in comparison to lower dose (9.90 %). CONCLUSION The toxicity of heavy metals leads to reduced maturation of the blast, which causes the appearance of immature cells in peripheral circulation and severe destruction of blood cell membranes. Erythrocyte hemolysis can lead to anemia, while lymphocyte damage can lead to lymphocytopenia.

Purpose We examined ideas about how youth would mitigate non-medical use of prescription medications among their peers. Design/methodology/approach The National Monitoring of Adolescent Prescription Stimulants Study (N-MAPSS) interviewed 11,048 youth10-18 years of age between 2008 and 2011 from entertainment venues of 10 US urban, suburban, and rural areas. Using a mixed-methods approach, participants completed a survey culminating in open ended questions asking: 1) How should kids your age be told about prescription drugs and their effects?; 2) If you ran the world, how would you stop kids from taking other people's prescription medicines?; 3)Why do people use prescription stimulants without a prescription? Responses from a random sample of 900 children were analyzed using qualitative thematic analyses. Findings The random sample of 900 youth (52% female, 40% white, with a mean age was 15.1 years) believed they should be educated about prescription drugs and their negative effects at schools, at home by parents, through the media, and health professionals. Youth would stop kids from using other people's prescription drugs through more stringent laws that restricted use, and education about negative consequences of use. Peer pressure was the most common reason youth gave for using other's pills, though some reported using for curiosity. Originality/value This analysis shows the importance of considering youth's opinions on non-medical use of prescription medications, which are often overlooked. Studies should disseminate this data from youth to stop the illicit use of prescription drugs among teens and youth.

The need for heating and cooling in traditional housing is becoming increasingly disadvantageous regarding high energy costs. But what is more concerning is the impact on our environment. The main goal of this paper is studying the prospects of using renewable energy for heating and cooling houses through an integrated bio-solar system in order to solve the energy scarcity problem. For this purpose, a simulation model for a bio-solar house made from different materials (walls made of bricks with straw bales and a roof made of concrete with straw bales) was developed successively in accordance with the energy balance and renewable energies such as biogas and solar energy were applied. This approach enabled an enhancement of the main factors affecting the performance of a building in terms of saving energy. The model was able to predict the energy requirements for heating and cooling of houses, the energy gained by a solar collector and by a biogas digester as well as the energy requirement for heating the biogas digester. Also, the purpose of this paper is to validate this developed simulation model by measuring energy requirements for heating of houses and solar radiation for solar collectors. The model is a simulation model for the bio-solar house with its three main parts—a straw house, a solar collector and a biogas digester. This paper demonstrates the values of the performed measurements and compares them to the theoretical, predicted values. The comparison indicates that the predicted energy requirements for the heating of buildings were a close approximation to the measured values. Another relevant deduction of the validation was the fact that the solar collector delivered the highest heat gain on 21st of June.

We investigate global dynamics of the equation\begin{equation*}x_{n+1}=\frac{x_{n-1}+F}{ax_{n}^2+f},\text{ \ }n=0,1,2,...,\end{equation*}where the parameters $a,F$ and $f$ are positive numbers and the initial conditions $x_{-1},x_{0}$ are arbitrary nonnegative numbers such that $x_{-1}+x_{0}>0$. The existence and local stability of the unique positive equilibrium are analyzed algebraically. We characterize the global dynamics of this equation with the basins of attraction of its equilibrium point and periodic solutions.

Before choosing an intersection project design, an important step is to examine the justification of the construction on the basis of defined criteria. One of the key criteria is the analysis of capacity. Large numbers of roundabout capacity models are present in the world, most of them adapted to the conditions of the country they originate from and they need to be calibrated for local conditions. Key parameters for calibration are critical headway and follow-up headway. Follow-up headway can be measured directly in the field, while critical headway cannot be measured, but is estimated. Many critical headway estimation methods exist (over 30) and each of them provides different values. Different values of critical headway result in different capacity estimation values. This raises the question which method provides more realistic estimations under certain conditions. In this paper, four most frequently used critical headway estimation methods (Raff, Maximum likelihood method, Wu, Logit) were selected to be tested by comparison of theoretical capacity models and actual measured capacity at a small urban roundabout.

We investigate the global dynamics of the following rational difference equation of second order\begin{equation*}x_{n+1}=\frac{Ax_{n}^{2}+Ex_{n-1}}{x_{n}^{2}+f},\quad n=0,1,\ldots ,\end{equation*}where the parameters $A$ and $E$ are positive real numbers and the initial conditions $x_{-1}$ and $x_{0}$ are arbitrary non-negative real numbers such that $x_{-1}+x_{0}>0$. The transition function associated with the right-hand side of this equation is always increasing in the second variable and can be either increasing or decreasing in the first variable depending on the parametric values. The unique feature of this equation is that the second iterate of the map associated with this transition function changes from strongly competitive to strongly cooperative. Our main tool for studying the global dynamics of this equation is the theory of monotone maps while the local stability is determined by using center manifold theory in the case of the nonhyperbolic equilibrium point.

European plum cultivars (Prunus domestica L.) are hexaploid and partially self-fertile or self-sterile requiring compatible pollinizers with overlapping bloom times. Therefore, inter-planting of different pollinizer cultivars is recommended. In order to identify successful pollinizers of the plum cultivars ‘Edda’, ‘Opal’ (self-fertile), ‘Jubileum’, ‘Reeves’, ‘Mallard’, ‘Avalon’, ‘Cacanska Lepotica’ (self-fertile), and ‘Valor’, 60 fruits per cultivar were collected from nine orchards in 2017 and 2018, all of which were located in Ullensvang, western Norway. DNA extraction was subsequently conducted from the obtained embryos, followed by genetic characterization using seven microsatellite markers. Tissue samples from all possible pollinizers were collected during the summer of 2017 and the same DNA approach was conducted. Results showed that ‘Opal’ was the most successful pollinizer among the investigated plum cultivars. The main exception was ‘Cacanska Lepotica’, which consistently displayed very high level of self-pollination. The most successful foreign pollinizer of ‘Opal’ was ‘Mallard’. However, in more than two thirds of embryos extracted from ‘Opal’ fruits self-fertilization was determined. ‘Reeves’ was identified as the most successful pollinizer among embryos collected from ‘Valor’. Among the five cultivars (‘Edda’, ‘Jubileum’, ‘Reeves’, ‘Mallard’, and ‘Avalon’) that did not display self-pollination, the pollinizer success rate of ‘Opal’, ranged from 36.5% (‘Mallard’) to 93.5% (‘Edda’) in 2017, while in 2018 this rate ranged from 43.5% (‘Jubileum’ and ‘Reeves’) up to 96.5% (‘Edda’). Overall, genotyping embryos using SSRs (simple sequence repeats) proved an effective method in determining the success rate of individual pollinizers among European plum cultivars.

The Internet-of-Things (IoT) has enabled Industry 4.0 as a new manufacturing paradigm. The envisioned future of Industry 4.0 and Smart Factories is to be highly configurable and composed mainly of the ‘Things’ that are expected to come with some, often partial, assurance guarantees. However, many factories are categorised as safety-critical, e.g. due to the use of heavy machinery or hazardous substances. As such, some of the guarantees provided by the ‘Things’, e.g. related to performance and availability, are deemed as necessary in order to ensure the safety of the manufacturing processes and the resulting products. In this paper, we explore key safety challenges posed by Industry 4.0and identify the characteristics that its safety assurance should exhibit. We propose a modular safety assurance model by combination of the different actor responsibilities, e.g. system integrators, cloud service providers and “Things” suppliers. Besides the desirable modularity of such a safety assurance approach, our model provides a basis for cooperative, on-demand and continuous reasoning in order to address the reconfigurable nature of Industry 4.0 architectures and services. We illustrate our approach based on a smart factory use case.

In order for a tourist to visit a location, it has to be attractive. Destination attractiveness can be examined in several ways. One of them is offered by this study, which has examined destination attractiveness based on resources available in certain rural settlements. Based on a case study carried out in the Brčko District of Bosnia and Herzegovina (Brčko District), a model will be developed to test for rural tourism destination attractiveness. Examination of tourist destination attractiveness in the area of the Brčko District was conducted with a decision model based on the Decision EXpert method and expert decision-making. For that purpose, six rural settlements in the area of the Brčko District were examined with respect to destination attractiveness. Results obtained using this model showed that rural settlement Bijela has a “very good” attractiveness, rural settlements Brezik, Brezovo Polje, and Gornji Zovik have “good” attractiveness, while rural settlements Ražljevo and Maoča have “middle” attractiveness. The results obtained by applying this model have shown the need for improvement of touristic offer in order to make it more attractive. In order to improve attractiveness of a tourist destination, we need to strengthen human potential in this area and improve tourist infrastructure and make more effort to preserve the environment. The application of the used model has given good results in examination of tourist destination attractiveness and it should be applied for other branches of tourism in the future studies.

Purpose: Youth represents the most vulnerable population, mainly due to their lifestyle derived from risky sexual behaviours. The aim of the study was to identify specific HPV genotypes correlating with cervical smear cytologic abnormalities, well as sociodemographic/behavioural characteristics and history of sexually transmitted diseases in Bosnian women age up to 30 years. Methods: The longitudinal study was performed at the Department of Microbiology School of Medicine University of Sarajevo and Institute for Public Health dr. Andrija Stampar, Zagreb, Croatia from June 2017 to January 2018. Thirty (30) cervical smears were taken from tested females were screened using COBAS assay for HPV DNA testing. Routine Pap screening was performed in the Public Institution Department for Health Care of Women and Maternity of Sarajevo Canton. A self-administered questionnaire was applied. Results: A total of 30 sexually active women with abnormal cytological reports were enrolled in the study. The mean age was 26 IQR (20.75, 29.0) year. The overall prevalence of HR HPV was 66.7 %. Women age of ≤25 years had a positive association with positive results of HPV testing, OR=1.91. Consummation of alcohol, cigarettes had a strong positive association with positive HPV testing. Conclusions: The data obtained from this study indicate that HPV 16 is the most common HPV type found in the cervical specimens among young Bosnian women, followed by HPV 18. HPV DNA testing using as a screening test should be considered in the development of cervical cancer prevention programs in Bosnia and Herzegovina.

For certain industrial control applications an explicit function capturing the non-trivial trade-off between competing objectives in closed loop performance is not available. In such scenarios it is common practice to use the human innate ability to implicitly learn such a relationship and manually tune the corresponding controller to achieve the desirable closed loop performance. This approach has its deficiencies because of individual variations due to experience levels and preferences in the absence of an explicit calibration metric. Moreover, as the complexity of the underlying system and/or the controller increase, in the effort to achieve better performance, so does the tuning time and the associated tuning cost. To reduce the overall tuning cost, a tuning framework is proposed herein, whereby a supervised machine learning is used to extract the human-learned cost function and an optimisation algorithm that can efficiently deal with a large number of variables, is used for optimising the extracted cost function. Given the interest in the implementation across many industrial domains and the associated high degree of freedom present in the corresponding tuning process, a Model Predictive Controller applied to air path control in a diesel engine is tuned for the purpose of demonstrating the potential of the framework.