The estimated percentage of individuals with COVID-19 due to infection with SARS-CoV-2 in need of hospitalization mostly increases proportionally with age, reaching almost 10% for those older than 60 years. Among hospitalized patients, one-fifth require treatment in the intensive care unit (ICU) due to acute respiratory distress syndrome, multiorgan failure, or hypoxemic respiratory insufficiency. Patients with moderate and severe COVID-19 who were hospitalized during the early stages of the pandemic and who continue to be hospitalized report fatigue, muscle weakness, joint stiffness, reduced mobility, increased risk of falls, and impaired quality of life. Physiotherapy is recognized to be important in the rehabilitation of COVID-19 patients requiring hospitalization. The current physiotherapy guidelines and recommendations for individuals with COVID-19, which include treatment methods and outcome measures for evaluation of the effects on respiratory and physical function and quality of life, are those established from the pre-COVID-19 era. The available extant scientific literature mainly reported the effect of physiotherapy in patients with COVID-19 in the acute, hospitalization courses of the disease, while there is a lack of quality primary, experimental studies on the effects of physiotherapy in rehabilitation of post-COVID-19 patients after hospitalization. This review aims to present an update on the effects of physiotherapy on rehabilitation and quality of life in patients hospitalized for COVID-19 and the findings from key studies published between 2020 and 2022.

disciplines and research areas that rely on participants’ self-reports to accrue data on participants’ true preferences are faced with the

In this work, we adopt the analysis of a heterogeneous cellular network by means of stochastic geometry, to estimate energy and spectral network efficiency. More specifically, it has been the widely spread experience that practical field assessment of the Signal-to-Noise and Interference Ratio (SINR), being the key physical-layer performance indicator, involves quite sophisticated test instrumentation that is not always available outside the lab environment. So, in this regard, we present here a simpler test model coming out of the much easier-to-measure Bit Error Rate (BER), as the latter can deteriorate due to various impairments regarded here as equivalent with additive white Gaussian noise (AWGN) abstracting (in terms of equal BER degradation) any actual non-AWGN impairment. We validated the derived analytical model for heterogeneous two-tier networks by means of an ns3 simulator, as it provided the test results that fit well to the analytically estimated corresponding ones, both indicating that small cells enable better energy and spectral efficiencies than the larger-cell networks.

This paper presents the results of a two-year study of six selected soybean genotypes with the aim of examining which of the genotypes in the given production conditions give the best results in regards with the amount and quality of seed yield. All genotypes belong to a zero-maturity group. The correlation between the grain yield per plant and other studied traits was tested through linear (simple) correlations. The testing showed that the following traits had a positive highly significant impact on seed yield: the number of seeds per plant (0.917**), seed germination energy (0.897**), seed moisture content (0.803**), plant height (0.802**), seed germination (0.789**), the number of seeds in pods (0.696**), the number of harvested plants per m-2 (0.590**), the number of plants (phenophase 1-3 in the three-leaf stage) per m2 (0.550**), 1000 seed mass (0.471**), and the height to the first node (0.412**).

Malware traffic classification (MTC) is a key technology for anomaly and intrusion detection in secure Industrial Internet of Things (IIoT). Traditional MTC methods based on port, payload, and statistic depend on the manual-designed features, which have low accuracy. Recently, deep-learning methods have attracted a significant attention due to their high accuracy in terms of classification. However, in practical application scenarios, deep-learning methods require a large amount of labeled samples for training, while the available labeled samples for training are very rare. Furthermore, the preparation of a large amount of labeled samples requires a lot of labor costs. To solve these problems, this article proposes three methods based on semisupervised learning (SSL), transfer learning (TL), and domain adaptive (DA), respectively. Our proposed methods use a large amount of unlabeled data collected in the Internet traffic, which can greatly improve the classification accuracy with few labeled samples. Then, we use the DA method to solve the mismatch problem between the source domain and the target domain in the TL process. The proposed method is not only applicable to the shallow network but also to the deep neural network structure, and can achieve better classification results. Experimental results show that our proposed methods can satisfy the requirement of MTC in the case of few labeled samples in IIoT. The source code for all the experiments is available at GitHub.The code of this article can be downloaded from GitHub link: https://github.com/yzjh/Keras-MTC-DA-Ladder.

Abstract Lesser mole-rats (Nannospalax leucodon) are members of the Rodentia order’s Spalacidae family, and they are found in Northeastern Africa, the Balkans, Southeastern Europe, Central Asia, the Middle East, and Caucasia. The shape of the skull has a significant impact on the phenotypic appearance of animal heads, and although many domestic species have been studied, there is a lack of evidence on the macro-anatomical characteristics of the skeletal system in mole-rats. The current research was focused on the morphological, morphometric, and radiographic properties of lesser mole-rats skull in Bosnia and Herzegovina. The research was conducted on five lesser mole-rats from Bjelasnica Mountain, Bosnia and Herzegovina. We compared the results of the previously published studies, and we found a lot of similarities between Nannospalax leucodon in Bosnia and Herzegovina and Nannospalax ehrenbergi in North Iraq, as well as the Nannospalax nehringi from Eastern Anatolia.

Key Points • Rondaptivon pegol is a first-in-class prohemostatic molecule that prolongs the half-life of both endogenous FVIII and substituted FVIII.• Rondaptivon pegol could be used to enable once-weekly substitution therapy in severe hemophilia A or as prophylaxis in nonsevere hemophilia A.

We propose a certainty-equivalence scheme for adaptive control of scalar linear systems subject to additive, i.i.d. Gaussian disturbances and bounded control input constraints, without requiring prior knowledge of the bounds of the system parameters, nor the control direction. Assuming that the system is at-worst marginally stable, mean square boundedness of the closed-loop system states is proven. Lastly, numerical examples are presented to illustrate our results.

PurposeThe study provides the emergence and evolution of the socioemotional wealth (SEW) concept in the family business field from 2007 (the inception date) until 2021. To provide a better overview of this notion, the study unfolds a deeper understanding of this term throughout the systematic literature review (SLR).Design/methodology/approachThe study applies a systematic literature review (SLR) by analyzing the sample of 185SEW articles extracted from the Scopus database. To identify all relevant studies, the article selection process was carefully designed and divided into two phases with clear steps: identification of studies via databases and identification of studies via previous studies' reference lists. Selected studies were analyzed using the Bibliometrix R-tool, resulting in an analysis of the evolution of the trends in the SEW literature, citation analysis, and network analysis. Finally, this SLR included the content analysis of the 25 most-cited SEW articles.FindingsThe study provides a relevant and comprehensive overview facilitating empirical and theoretical research in this field and paving the way to develop new themes. The bottom line of the important findings is that the SEW concept is relatively new, alluding to a wealthy venue for future works. Other results and implications are discussed on the family business and SEW theme. Additionally, the study provides suggestions which could be used for future works in this area.Originality/valueThis is the first article related to the SEW concept in the family business. It portrays a clear picture of this field, providing relevant information on what has been done, as well as what the future possibilities are that might bode the future horizons in family businesses.

Cyber-physical systems (CPSs) are often complex and safety-critical, making it both challenging and crucial to ensure that the system’s specifications are met. Simulation-based falsification is a practical testing technique for increasing confidence in a CPS’s correctness, as it only requires that the system be simulated. Reducing the number of computationally intensive simulations needed for falsification is a key concern. In this study, we investigate Bayesian optimization (BO), a sample-efficient approach that learns a surrogate model to capture the relationship between input signal parameterization and specification evaluation. We propose two enhancements to the basic BO for improving falsification: (1) leveraging local surrogate models, and (2) utilizing the user’s prior knowledge. Additionally, we address the formulation of acquisition functions for falsification by proposing and evaluating various alternatives. Our benchmark evaluation demonstrates significant improvements when using local surrogate models in BO for falsifying challenging benchmark examples. Incorporating prior knowledge is found to be especially beneficial when the simulation budget is constrained. For some benchmark problems, the choice of acquisition function noticeably impacts the number of simulations required for successful falsification.

Aims: Determination of the biochemical properties of β-glucosidase in peppermint, which is rich in aromatic compounds. Study Design: β-glucosidase was purified from mint, and biochemical characterization of the purified enzyme was performed. Place and Duration of Study: This study was carried out in the Faculty of Arts and Sciences Biochemistry laboratory. Methodology: Enzyme purification was performed by hydrophobic interaction chromatography using a Sepharose 4B-L-tyrosine-1-naphthylamine gel. Optimum pH, temperature, and substrate specificity of the purified enzyme were determined. The effects of glucose, δ-gluconolactone and some heavy metals on the enzyme activity were investigated. Results: The enzyme was purified with 8-fold and 28% yield. The purified protein from mint was visualized at 65 kDa on SDS-PAGE. The substrate specificity of the purified β-glucosidase from mint was determined against para- and ortho-nitrophenyl β-D-glucopyranoside (p/o-NPG) substrates. The Km values were 0.4 and 0.9 mM, and the Vmax values were 102.2 EU and 96.6 EU, respectively. While the optimum pH for the purified enzyme was 6, the optimum temperature was 35°C. Effects of heavy metals Ag+2, Fe+3, Zn+2, Cu+2, and Pb+2 on the purified enzyme activity were investigated. Relative activities of heavy metals were introduced into the reaction medium as 0.75 mM samples without any known inhibitors in the environment. Fe+3 increased the enzyme activity, and Ag+2, Pb+2, Cu+2, and Zn+2 inhibited the enzyme, and their relative activities were 78, 76, 22, and 31%, respectively. Glucose and δ-gluconolactone competitively inhibited the enzyme activity when p-NPG was the substrate. Ki values of glucose and δ-gluconolactone were determined as 0.034±0.001 and 0.038±0.002 mM, respectively. Conclusion: Determination of the biochemical properties of β-glucosidase from mint, which has commercial and pharmacological importance due to the phenolic substances it contains, will contribute to studies on improving food quality.

This work presents experimental results concerning the radon concentration from different building materials used for construction of houses in the municipality of Bihac. The passive technique using nuclear track detectors C-39 was used for a period for three months. The highest and lowest radon concentration was found in concrete brick buildings 280±5 Bqm-3 and in stone buildings 122±1 Bqm-3. It depends on the radioactive content of the materials, emanation coefficient and diffusion coefficient of radon in that material, porosity and density of the material. The mean annual effective dose was 3.26 mSv/y. The results obtained also give a correlation between indoor radon levels and the associated level of risk.

Amaranthaceae Juss. family encompasses many edible plants with prominent biological activity. This investigation tested the bioactive properties of ethanolic and methanolic extract of three well-known species: spinach (Spinacia oleracea L.), chard (Beta vulgaris L. subsp. vulgaris), and orache (Atriplex hortensis L.) through the determination of total phenolic and flavonoid content, antioxidant activity, and antibacterial properties. The particular goal was to evaluate the antibiofilm potential of extracts and to demarcate concentration-depending changes in the biofilm-forming category of included bacterial strains. The mass of the chard and orache methanolic extracts gained by maceration are lower in comparison to the mass of ethanolic extracts obtained by the Soxhlet method. In the case of spinach, the results are the opposite. All extracts have an antiradical activity that can be attributed to the established amounts of phenols and flavonoids. Total phenolics in dry leaves ranged from 0.09 to 0.44 mg GAE/g dw, and total flavonoids from 0.42 to 1.9 mg RTE/g dw. All investigated extracts performed inhibitory potential in terms of bacterial growth, while there was no bactericidal effect observed. Values of the minimum inhibitory concentration ranged from 125 µg/ml to 500 µg/ml. Overall results suggested orache extracts as the strongest inhibitory agents. Antibiofilm assays showed that examined extracts of spinach, chard, and orache caused changes in the biofilm-forming capacity of investigated bacterial pathogens. Fluctuations in observed biofilm-forming categories after application of extracts were concentration-dependent.