Construction materials have a direct impact on the environment, on people, and their health. In addition, building insulation plays a decisive role in terms of energy consumption of buildings and regarding CO2-emissions over their whole life cycle. In order to achieve a holistic concept for green building worldwide, it is necessary to develop ecological insulating materials and to scientifically examine them in terms of their technical properties, as done with particleboards from agricultural waste presented in this article. This study aims to characterize the properties’ tensile and compressive strength, modulus of rupture (MOR), and elasticity (MOE) and thermal conductivity of particleboards affected by parameters, such as waste type (rice straw or flax shives), particleboard density, resin type, and content, as well as the use of treated rice straw. Particleboards made from flax shives had superior properties compared to the rice straw particles. The mechanical properties of the boards increase with an increasing resin content, except for the MOR and MOE, which decrease with an increasing resin content, and reach their peak value at a resin content of 10%.

This paper presents performance analysis of an adaptive peak cancellation (PC) method to reduce the high peak-to-average power ratio (PAPR) for OFDM systems, while keeping the out-of-band (OoB) power leakage as well as an in-band distortion power below the pre-determined level. In this work, the increase of adjacent leakage power ratio (ACLR) and error vector magnitude (EVM) are estimated recursively using the detected peak amplitude. We present analytical framework for OFDM-based systems with theoretical bit error rate (BER) representations and detection of optimum peak threshold based on predefined EVM and ACLR requirements. Moreover, the optimum peak detection threshold is selected based on theoretical design to maintain the pre-defined distortion level. Thus, their degradations are restricted below the pre-defined levels which correspond to target OoB radiation. We also discuss the practical design of peak-cancellation signal with target OoB radiation and in-band distortion through optimizing the windowing size of the PC signal. Numerical results show the improvements with respect to both achievable BER and PAPR with the PC method in eigen-beam space division multiplexing (E-SDM) systems under restriction of OoB power radiation. It can also be seen that the theoretical BER shows good agreements with simulation results.

Every successful health care system should be based on some general humanistic ideals. However, the nationally organized health care systems of most European countries usually suffer from a deficiency in common ethical values based on universal human principles. When transitional societies, such as that of Bosnia-Herzegovina are concerned, health care organizational models are even more dysfunctional. The sources of a dysfunction in medical care system of Bosnia-Herzegovina are manifold and mutually controversial, including a lack of shared principles, an inappropriate involvement of politicians in medical care and practice, administrative difficulties arising from superficial communication systems, as well as economic limits concerned with the financing of health care. The deficiency of a moral culture of medicine, which is correlated to a general collapse of morality is also responsible for many problems affecting various aspects of life including medical care. Hence, medical ethics from a virtue perspective is becoming an important ingredient of any improvement deigned to provide better-quality medical care. The aim of this paper is to underline the influence of humanism on the organization of health care systems and the ethics of medical interrelations in the society of Bosnia-Herzegovina. It is not intended to diagnose or resolve the problems, but to analyze them. It is also a critique of specific socio-political-economic influences on this health care system, inquiring if well-educated individuals in the virtues, which are involved in medical practice and education, would counteract them. In conclusion, humanism creates a universal ethical structure, which is based on human values such as fidelity, trust, benevolence, intellectual honesty, courage, compassion and truthfulness. These values should represent the standard around which medical care is organized. Since the health care system in Bosnia-Herzegovina is not entirely founded upon humanistic ideals, addressing the socio-political-economic conditions that constantly undermine those values is a prerequisite for any much-needed improvements of the medical care.

Artificial neural networks are notoriously power- and time-consuming when implemented on conventional von Neumann computing systems. Consequently, recent years have seen an emergence of research in machine learning hardware that strives to bring memory and computing closer together. A popular approach is to realise artificial neural networks in hardware by implementing their synaptic weights using memristive devices. However, various device- and system-level non-idealities usually prevent these physical implementations from achieving high inference accuracy. We suggest applying a well-known concept in computer science—committee machines—in the context of memristor-based neural networks. Using simulations and experimental data from three different types of memristive devices, we show that committee machines employing ensemble averaging can successfully increase inference accuracy in physically implemented neural networks that suffer from faulty devices, device-to-device variability, random telegraph noise and line resistance. Importantly, we demonstrate that the accuracy can be improved even without increasing the total number of memristors. Designing reliable and energy-efficient memristor-based artificial neural networks remains a challenge. Here, the authors demonstrate a technology-agnostic approach, committee machines, which increases the inference accuracy of memristive neural networks that suffer from device variability, faulty devices, random telegraph noise and line resistance.

Artificial neural networks (ANNs) are notoriously power- and time-consuming when implemented on conventional von Neumann computing systems. Recent years have seen an emergence of research in hardware that strives to break the bottleneck of von Neumann architecture and optimise the data flow; namely to bring memory and computing closer together. One of the most often suggested solutions is the physical implementation of ANNs in which their synaptic weights are realised with analogue resistive devices, such as resistive random-access memory (RRAM). However, various device- and system-level non-idealities usually prevent these physical implementations from achieving high inference accuracy. We suggest applying a well-known concept in computer science -- committee machine (CM) -- in the context of RRAM-based neural networks. Using simulations and experimental data from three different types of RRAM devices, we show that CMs employing ensemble averaging can successfully increase inference accuracy in physically implemented neural networks that suffer from faulty devices, programming non-linearities, random telegraph noise, cycle-to-cycle variability and line resistance. Importantly, we show that the accuracy can be improved even without increasing the number of devices.

Single nucleotide polymorphisms (SNPs) in genes encoding mitotic kinases could influence development and progression of gastric cancer (GC). Case-control study of nine SNPs in mitotic genes was conducted using qPCR. The study included 116 GC patients and 203 controls. In silico analysis was performed to evaluate the effects of polymorphisms on transcription factors binding sites. The AURKA rs1047972 genotypes (CT vs. CC: OR, 1.96; 95% CI, 1.05–3.65; p = 0.033; CC + TT vs. CT: OR, 1.94; 95% CI, 1.04–3.60; p = 0.036) and rs911160 (CC vs. GG: OR, 5.56; 95% CI, 1.24–24.81; p = 0.025; GG + CG vs. CC: OR, 5.26; 95% CI, 1.19–23.22; p = 0.028), were associated with increased GC risk, whereas certain rs8173 genotypes (CG vs. CC: OR, 0.60; 95% CI, 0.36–0.99; p = 0.049; GG vs. CC: OR, 0.38; 95% CI, 0.18–0.79; p = 0.010; CC + CG vs. GG: OR, 0.49; 95% CI, 0.25–0.98; p = 0.043) were protective. Association with increased GC risk was demonstrated for AURKB rs2241909 (GG + AG vs. AA: OR, 1.61; 95% CI, 1.01–2.56; p = 0.041) and rs2289590 (AC vs. AA: OR, 2.41; 95% CI, 1.47–3.98; p = 0.001; CC vs. AA: OR, 6.77; 95% CI, 2.24–20.47; p = 0.001; AA+AC vs. CC: OR, 4.23; 95% CI, 1.44–12.40; p = 0.009). Furthermore, AURKC rs11084490 (GG + CG vs. CC: OR, 1.71; 95% CI, 1.04–2.81; p = 0.033) was associated with increased GC risk. A combined analysis of five SNPs, associated with an increased GC risk, detected polymorphism profiles where all the combinations contribute to the higher GC risk, with an OR increased 1.51-fold for the rs1047972(CT)/rs11084490(CG + GG) to 2.29-fold for the rs1047972(CT)/rs911160(CC) combinations. In silico analysis for rs911160 and rs2289590 demonstrated that different transcription factors preferentially bind to polymorphic sites, indicating that AURKA and AURKB could be regulated differently depending on the presence of particular allele. Our results revealed that AURKA (rs1047972 and rs911160), AURKB (rs2241909 and rs2289590) and AURKC (rs11084490) are associated with a higher risk of GC susceptibility. Our findings also showed that the combined effect of these SNPs may influence GC risk, thus indicating the significance of assessing multiple polymorphisms, jointly. The study was conducted on a less numerous but ethnically homogeneous Bosnian population, therefore further investigations in larger and multiethnic groups and the assessment of functional impact of the results are needed to strengthen the findings.

Introduction: Although many predictive tools have already been developed, efforts are still proceeding to identify a reliable biomarker to predict the prognosis of the patients with acute heart disorders. Objectives: The aim was to evaluate the role of renal injury biomarkers (serum cystatin C, serum and urine interleukin-18, IL-18) and heart failure biomarkers (plasma B-type natriuretic peptide, BNP) in the prediction of the postdischarge requirement of renal replacement therapy (RRT) and/or 6-month mortality in patients with acute heart disorders. Patients and Methods: In patients diagnosed with acute heart disorders (acute heart failure [AHF] and/or acute coronary syndrome [ACS]) and admitted to the intensive care units, baseline clinical parameters, renal and cardiac biomarkers were determined. Patients were followed up for 6 months. The composite outcome was the postdischarge requirement of RRT and/or 6-month mortality. Results: Of 120 patients, 5.8% continued RRT after discharge. The 6-month mortality was 20%. Cox logistic regression analysis showed that urine IL-18 (P=0.021), plasma BNP (P=0.046), Acute Physiology and Chronic Health Evaluation (APACHE) II score (P=0.002), and left ventricular diastolic dysfunction (P=0.045) were independent predictors of the postdischarge requirement of RRT and/or 6-month mortality. For predicting RRT and/or 6-month mortality, using urine IL-18 cutoff value of 29.1 pg/mL showed 66.7% sensitivity and 67.7% specificity (area under the curve, AUC 0.70, P=0.003), while using plasma BNP cutoff value of 881.6 pg/mL showed 66.7% sensitivity and 70.8% specificity (AUC 0.76, P<0.001). Conclusion: Urine IL-18 and plasma BNP are independently predictive for the postdischarge requirement of RRT and/or 6-month mortality in patients with acute heart disorders.

Objective – The aim of this article is to present a case of POTS, which was diagnosed quickly with Holter ECG and whose symptoms improved promptly and dramatically with non-pharmacological therapy. Case Presentation – A 15-year-old female patient mother was admitted because of unusual episodes of dizziness, syncope with spontaneous recovery and palpitations. Most of these symptoms occurred fairly frequently on standing. The Holter ECG was done with recommendation to perform some activities during recording, such as to stand for ten minutes in the presence of another person and to write symptoms. It was noticed on the Holter ECG that she had increase in heart rate more than 60 beats per minute during these ten minutes followed by symptoms. The patient was diagnosed with POTS and nonpharmacological therapy was advised which was successful. Conclusion – POTS is a disabling condition with heterogeneous and atypical symptoms which mostly affects the young females. Sometimes, a long period of time is necessary to diagnose POTS. Therefore, it is important to diagnose quickly and to start with appropriate therapy which is unique for every POTS patient. Delay in diagnosis and treatment can lead to further disability in patients affected by POTS and their poor quality of life.

We show how to couple phase-oscillators on a graph so that collective dynamics "searches" for the coloring of that graph as it relaxes toward the dynamical equilibrium. This translates a combinatorial optimization problem (graph coloring) into a functional optimization problem (finding and evaluating the global minimum of dynamical non-equilibrium potential, done by the natural system's evolution). Using a sample of graphs, we show that our method can serve as a viable alternative to the traditional combinatorial algorithms. Moreover, we show that, with the same computational cost, our method efficiently solves the harder problem of improper coloring of weighed graphs.

In this paper, we investigate the energy-efficient resource allocation problem in an uplink non-orthogonal multiple access (NOMA) millimeter wave system, where the fully-connected-based sparse radio frequency chain antenna structure is applied at the base station (BS). To relieve the pilot overhead for channel estimation, we propose a codebook-based analog beam design scheme, which only requires to obtain the equivalent channel gain. On this basis, users belonging to the same analog beam are served via NOMA. Meanwhile, an advanced NOMA decoding scheme is proposed by exploiting the global information available at the BS. Under predefined minimum rate and maximum transmit power constraints for each user, we formulate a max-min user energy efficiency (EE) optimization problem by jointly optimizing the detection matrix at the BS and transmit power at the users. We first transform the original fractional objective function into a subtractive one. Then, we propose a two-loop iterative algorithm to solve the reformulated problem. Specifically, the inner loop updates the detection matrix and transmit power iteratively, while the outer loop adopts the bi-section method. Meanwhile, to decrease the complexity of the inner loop, we propose a zero-forcing (ZF)-based iterative algorithm, where the detection matrix is designed via the ZF technique. Finally, simulation results show that the proposed schemes obtain a better performance in terms of spectral efficiency and EE than the conventional schemes.