High-order harmonic generation by orthogonally polarized two-color (OTC) laser fields is analysed using strong-field approximation and quantum-orbit theory. Results for the field components frequency ratio of 2:1 and 3:1 are presented and compared. We have shown that, depending on the relative phase between the field components, the shape of the high-harmonic spectrum can be very different from that obtained by a monochromatic linearly polarized laser field. It is also shown that it is possible to generate elliptically polarized high-order harmonics with very high photon energies using OTC laser field with the frequency ratio of 3:1 and a long fundamental wavelength. An effective relative phase control of the harmonic emission is demonstrated. The obtained results are explained using the quantum-orbit theory.

Background: Borrelia burgdorferi and tick-borne encephalitis (TBE) virus are 2 types of tick-borne pathogens that can cause central nervous system infection. Routine diagnostics have so far included analysis of cerebrospinal fluid (CSF) cell numbers, CSF serology for Borrelia burgdorferi and serum serology for TBE virus. However, early diagnosis may be difficult based on antibody detection which takes time to analyze, and with the possibility of false negative results, thus delaying treatment. Cytokine analyses are becoming increasingly available in clinical routine care and may offer important information. Methods: Fifteen cytokines and chemokines were measured in the CSF from the diagnostic lumbar puncture of 37 children with TBE, 34 children with neuroborreliosis and 19 children without evidence of central nervous system infection, using Luminex technology. Results: Significantly higher levels of proinflammatory interleukin-6 were detected in the samples from TBE-infected children, when compared with neuroborreliosis or controls. In comparison, children with neuroborreliosis had significantly higher levels of interleukin-7, interleukin-8, interleukin-10, and interleukin-13 when compared with TBE infected or controls. Furthermore, the ratio between interleukin-6 and interleukin-10 was significantly different between the 2 types of tick-borne infections. Conclusions: The interleukin-6/interleukin-10 ratio can be used as a rapid diagnostic cue upon suspected tick-borne infection, enabling fast and correct treatment. Also, in serology-negative results, such information may strengthen a clinical suspicion.

Abstract Simultaneous adsorption of heavy metals in complex multi metal system is insufficiently explored. This research gives results of key process parameters optimization for simultaneous removal of Cd(II), Co(II), Cr(III), Cu(II), Mn(II), Ni(II) and Pb(II) from aqueous solution (batch system). New lemon peel-based biomaterial was prepared and characterized by infrared spectroscopy with Fourier transformation (FTIR), scanning electron microscopy (SEM), electron dispersive spectroscopy (EDS), while the quantification of metals was made by atomic absorption spectrometry (AAS). Simultaneous removal of seven metals ions was favorable at pH 5 with 300 mg/50 mL solid-liquid phase ratio, within 60 min at room temperature with total obtained adsorption capacity of 46.77 mg g−1. Kinetic modeling showed that pseudo-second order kinetic and Weber-Morris diffusion models best describe the adsorption mechanism of all seven heavy metals onto lemon peel.

Introduction: Patients with hip fracture are one of the most demanding groups in the health-care system. One of the most important tasks for nurses is to assess pain and ensure the patients are pain free. Pain assessment in patients with dementia is a well-known challenge for health-care professionals due to the patients’ difficulties in verbalising pain problems. Aim: The aim of this study was to explore the experience of intensive care nurses in assessment of pain in patients with hip fracture and dementia in the postoperative setting. Methods: Data were collected through five focus group discussions using open-ended questions and qualitative content analysis. Twenty-one intensive care nurses (6 men and 15 women) participated in the focus group interviews. Results: Analysis of the data resulted in three main categories: “Communication”, “Visual assessment of pain”, and “Practical issues” including a number of subcategories. Some of the factors which influence assessment of pain in patients with dementia are the lack of information and knowledge about the patients, which causes loss of time and increased stress. The different forms of communication and ways of assessing pain in these patients were other factors mentioned by nurses as hindrances regarding assessment of the pain. Conclusion: In order to improve assessment of pain, more knowledge and information about the patients are needed and better coordination between the pre- and postoperative departments regarding these patients. In this context, different intervention studies on patient’s hip fracture and dementia are needed to increase knowledge and awareness regarding this group of patients.

The paper presents the possibility of using criterion programming and neuro-fuzzy modeling in determining the value of planning technical power losses. Proposed is an optimal control in normal mode power grids which considers the value of planned technical power losses. Improved method for determining normative values of technical energy losses using the criteria programming and neuro-fuzzy modeling is presented.

The cultural heritage image classification represents one of the most important tasks in the process of digitalization. In this paper, a deep learning neural network was applied in order to classify images of architectural heritage belonging to ten categories, in particular: (i) bell tower, (ii) stained glass, (iii) vault, (iv) column, (v) outer dome, (vi) altar, (vii) apse, (viii) inner dome, (ix) flying buttress, and (x) gargoyle. The Convolutional neural network was used for image classification, with the same architecture applied on two sets of the data: the full dataset consisting of 10 categories as well as dataset with 5 different image categories. The results show that both architectures performed well and obtained accuracy of up to 90%.

Summary Background/Aim: Dental caries is the most common chronic disease affecting children worldwide today and represents a serious public health problem. Since pediatricians are the first health professionals whom children visit, they can be considered as a reliable source of information regarding the recognition of potential health problems and suggesting their solution, so they have a key role in primary health prevention. The aim of this study is to determine the position of pediatricians in the prevention of oral health of children in Montenegro through the assessment of their knowledge, attitude, and practice of primary professional preventive measures. Material and Methods: A cross-sectional survey was undertaken among the 84 pediatricians employed in Montenegro Community health services. Self-addressed reply envelope survey consisted questionnaire of 60 questions divided into 5 modules, was used as an instrument for the research. Results: Response rate was 86%, while 68,3% pediatricians think that gender is a risk factor for dental caries. Fact that cavity-causing bacteria can be transmitted from the mother was confirmed by 69% of respondents. Only 45% of them practice the current guidelines on the recommendation of the first dental examination up to 12 months of life. Conclusions: It can be concluded that pediatricians in Montenegro have positive attitudes about prevention and believe they have the responsibility to prevent caries but have shown insufficient knowledge about caries and risk factors for the oral diseases.

Abstract The main objective of this investigation was to determine and summarize the economic burden of severe COPD exacerbations that required hospitalization and the difference in the costs of treatment between patients with frequent (at least two exacerbations in one year) and infrequent exacerbation. Our results suggested that significantly more resources had to be spent to treat patients with at least two hospitalizations during the study related to the use of medications primarily affecting the respiratory system (corticosteroids, p = 0.013, theophylline, p = 0.007) and total hospital stay (31336.68 ± 19140 RSD/517.53 ± 316.1 EUR versus 23650.15 ± 14956.0 RSD/390.59 ± 247 EUR, p=0.002) compared to patients who stayed in a semi-intensive care unit (12875.35 ± 20742.54 RSD versus 4310.62 ± 9779.78 RSD/ 212.64 ± 342.57 EUR versus 71.19 ± 161.51 EUR, p=0.006). Based on the total number of days in the hospital, the costs of the drugs, the materials used and services provided, patients from the frequent exacerbation group had significantly higher costs (80034.1 ± 36823.7 RSD/1321.78 ± 608.15 EUR versus 69425.5 ± 34083.1 RSD/1146.58 ± 562.89 EUR) comparedthan patients in the infrequent exacerbation group (p=0.039). Our results indicate that significantly more funds will be spent treating the deterioration of patients who stay longer in the hospital or in the semi-intensive care unit. Their condition will require a significantly greater use of drugs that are primarily used to treat the respiratory system and, therefore, will utiliseutilize significantly more resources.

The highly dynamic wireless communication environment poses a challenge for many applications (e.g., adaptive multimedia streaming services). Providing accurate TP can significantly improve performance of these applications. The scheduling algorithms in cellular networks consider various PHY metrics, (e.g., CQI) and throughput history when assigning resources for each user. This article explains how AI can be leveraged for accurate TP in cellular networks using PHY and application layer metrics. We present key architectural components and implementation options, illustrating their advantages and limitations. We also highlight key design choices and investigate their impact on prediction accuracy using real data. We believe this is the first study that examines the impact of integrating network-level data and applying a deep learning technique (on PHY and application data) for TP in cellular systems. Using video streaming as a use case, we illustrate how accurate TP improves the end user's QoE. Furthermore, we identify open questions and research challenges in the area of AI-driven TP. Finally, we report on lessons learned and provide conclusions that we believe will be useful to network practitioners seeking to apply AI.

The rapid development of financial markets results in data variability and unpredictability. Anomaly detection in financial data is a very important issue. Finding anomalies can result in error reduction and corrections in due time. The main aim of this research was to find anomalies in general ledgers of a real company in Bosnia and Herzegovina. Anomalies are defined as input errors of accountants. Main concepts of anomaly detection are defined, a summary of the current progress is given, and challenges of future work are presented. Cluster-based and histogram-based anomaly detections were performed on a real-life dataset of a microcredit organization. Results of algorithms were presented, as well as results achieved using synthetic data.

Fast, accurate and noninvasive methods for a High Voltage Circuit Breaker (HVCB) condition assessment are hot topics since the first breaker has been utilized in the electrical power grid. The HVCB is the key to the stable power system, so its fault diagnosis is of great significance. The vibration signal obtained during the operation of the HVCB contains valuable information on its mechanical and structural integrity. Based on these premises, the paper present method for noninvasive HVCB condition assessment based on the vibration signature measurement. The proposed method is suitable for offline as well as online or monitoring based measurement systems. The core of the assessment method consists of variational mode decomposition and Higuchi fractal dimension estimation.

High-voltage circuit breakers (HVCB), as well as power transformers, as a part of substations, undergo numerous tests during their lifetime. The first test is performed in the factory. The following is the acceptance test performed at a customer site after the delivery. The most numerous are maintenance tests performed during equipment services. All the mentioned tests require an appropriate connection between a test device and a test object, usually utilizing a large number of cables. This can be very time consuming and imposes an additional risk of obtaining appropriate measurement and assessment indices. This paper presents the potential of the wiring replacement by the wireless connection between the test object and test equipment, which would simplify, improve make the test preparation procedure and packing test equipment more convenient and faster.

Healthcare information systems store a huge amount of patient data, so the trend of the use of data mining in healthcare is on the rise. Heart and blood vessel diseases are a leading cause of mortality both worldwide and here in Bosnia and Herzegovina, and prevention, surveillance and treatment are of great public health importance. Based on data on patients with cardiovascular disease, collected from 2011 to 2017 at Mostar Hospital, models for mortality prediction using techniques for data tree mining, neural network and logistic regression are presented. The aim of this research is to compare the effectiveness of these methods in modeling the effectiveness of predicting mortality in patients with cardiovascular disease.

Abstract I theorize that the idea of knowledge and education has shifted in Islam from an inclusive and rational search for all knowledge to a narrowed focus on religious knowledge, void of rationality. By synthesizing literature on education and knowledge in Islam, this study identifies three shifts in the cultural history of Islamic education. I argue that those shifts in what was deemed valuable knowledge have played a significant role in the emergence of radicalization today. The study shows that once the social world of Islam destabilized, the sense of belonging and sense making became inward and less reflexive as compared to that of early Muslims. Belief became privileged over the rationality mechanisms that had previously formed Islamic endeavors. I demonstrate that a decline in intellectual and scientific production followed, allowing extremists to skew Islam’s narrative by putting forward an idealized version of the Islamic caliphate divorced from rationality.

Simple Summary The recognition of the role of food in the improvement and preservation of health is receiving more and more attention among consumers, especially in developed countries. Fats from red meats are considered quite unhealthy because of their high levels of cholesterol and saturated fatty acids. Healthier lipid profiles of red meats can be achieved by a proper feed composition of animals, but other factors, such as breed, sex, and live weight, are able to affect the nutritional properties of meats. This investigation aimed to evaluate the effect of breed (Bergamasca, Italian Merino, and Sopravissana) on the fatty acid composition of invisible (intramuscular) and visible (subcutaneous) fats of light lambs reared in Central Italy transhumant farms. They recently gained a Protected Geographical Indication label (European Union, Commission Implementing Regulation No. 475/2013), as ”Agnello del Centro Italia”. It is an income opportunity for local farms that passes through the nutritional valorization of lamb meat. The indices of nutritional quality of fats have showed that the meat of Italian Merino and Sopravissana lambs had better nutritional quality than the Bergamasca breed. Abstract Lamb meat is the main product of Central Italy transhumant farms, where lambs are traditionally reared with their mothers on pastures and are supplemented with concentrates and/or hay from day 20–30 until slaughter. However, few data are available on the fatty acid (FA) composition of unweaned lambs reared by extensive systems in Central Italy. The study aimed to evaluate the effect of breed (Bergamasca, Italian Merino, and Sopravissana) on the FA composition of intramuscular (longissimus lumborum, LL) and subcutaneous (SC) fats of light lambs. Statistical analysis showed that breed had effect only on some FAs in LL muscle fat (C18:0, C20:0, C14:1, C16:1, C17:1, C18:3 n-3, trans and conjugated linoleic acid isomers) and in SC adipose tissue (C21:0, C16:1, C18:1, C20:4 n-6, C20:5 n-3, C18:1 trans isomers). Gas chromatography data in combination with a chemometric approach could have some potential to discriminate among breeds. Indices of nutritional quality of the lipids suggested that the meat of Italian Merino and Sopravissana lambs might have better nutritional quality than Bergamasca; further studies, involving a greater number of animals, are needed to confirm these early results.