The robustness of the institutional environment is a requisite factor for the growth and development of a firm. This study is focused on the impact of factors of institutional environment on SMEs’ acquisition and use of licensed technology from abroad. The independent variables considered as the factors of institutional environment are: financial institutions, regulatory institutions, infrastructure, and security, while the dependent variable is the use of licensed technology from abroad. Data from the manufacturing and the service sectors of the economies of Africa and the Middle East are collected from the database of the World Bank Enterprise Survey. The survey employs random sampling to select firms in each country. The firms are stratified based on the number of employees and the geographical region. Questionnaires are administered to firms from 2006 to 2018 through cross-sectional data collection method. By focusing on the scope of research on the two regions and SMEs, the sampled observations are scaled down from 136,887 to 33,977 firms in 53 countries. Although not all the Pearson correlation coefficients of the independent variables with the dependent variable are high, there are satisfactory levels of significance with p-values below 5%. The independent variables in the regression model have a statistically significant impact on the use of licensed technology from abroad. The forecasting power of the regression model, the possible implications from the test results are shown. The limitations of the research and the possible areas for future research are discussed in the last section.

Introduction: Mathematical modeling of coronavirus disease spread and computer simulations are currently one of the main tools in public health that can give important indicators for prevention planning. Based on mathematical projections and daily updates of information, the measures are either tightened or reduced, in order to protect the health of the population. Aim: The aim of this paper is to present a computer system based on an adequate mathematical model that allows frequent execution of various scenarios of spread severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in any period in the future. Also, the aim of this article is to point out the importance of measures for the prevention of coronavirus disease 2019 (COVID-19) in Bosnia and Herzegovina through examples of computer simulation models. Methods: Software solution based on the USLIRD model (Unpopulated - Susceptible - Latent - Infectious - Recovered - Deceased) was developed, with a number of variable parameters ‘reproduction number, delay period, infectivity period, hospital capacity, characteristics of population). By setting these parameters in accordance with the existing and available data, the model is brought to an optimized state with the possibility of a realistic assessment of the course of the infection curve in any future period. Data from the beginning of the pandemic are collected at the Faculty of Mechanical Engineering, University of Sarajevo and updated several times a day. The set of measures is divided into two types. 'Intervention 1' is a measure to close institutions that are at high risk for pandemics, working from home, wearing face mask, enhanced hygiene when entering facilities with a larger number of people. 'Intervention 2' presents restrictive measures that has been introduced as mandatory in Bosnia and Herzegovina. The period 01.03.2020 to 01.09.2020 was observed. Results: Without epidemiological measures, Bosnia and Herzegovina's health system would quickly collapse. Restrictive measures reduce the intensity of the spread of the infection, save human lives and keep the health system functional, but with consequences on other aspects of society - reduction of economic activities, collapse of the service industry and companies and disorders in mental health status of the population. Four different scenarios of the situation were analyzed. Scenario number three is current condition with measures that are currently in Bosnia and Herzegovina. The reintroduction of restrictive measures leads to a decrease in the number of infected population and suppression of the spread of the pandemic, which is shown in scenario 4. Conclusion: Self-discipline, adherence to measures, while trying to avoid restrictive measures should be the way to fight the COVID-19 pandemic. Whatever the consequences, the initiation of restrictive measures to preserve the health of the population should be imperative.

Engaging students as partners in university-industry collaboration (UIC) through challenge-based and real-life projects creates significant value for all participants through novel educational approaches, talent recruitment, user-driven innovation, new resources, and research-related opportunities. However, as these practices have developed iteratively over time in industrialized countries and are highly context dependent, it is unclear how they can be best transferred to emerging economy contexts. In this paper, we present a research and design process of creating an innovation intermediary to foster student-centric UIC in Nairobi, Kenya. Seen as a set of services that reside on a multilevel platform, the intermediary aims to add value to the existing ecosystem through open access knowledge sharing, promoting partnerships, and mentoring for impact in an integrative, complementary way. Through a four-step qualitative research process involving interviews and co-creation workshops with local stakeholders, we examine the ecosystem, define value creation, design the services of the intermediary, and propose a step-wise model for further diffusion. We note the importance of establishing a solid rationale for collaboration, understanding the expected value to be created, creating a neutral space for the collaboration, and planning the implementation in detail. We contribute to transferring student-centric UIC practices into emerging economy contexts.

I present a viable two leptoquark model based on $SU(5)$ gauge symmetry that addresses the $B$-physics anomalies. The entire low-energy flavour structure of the set-up originates from two $SU(5)$ operators that relate Yukawa couplings of the two leptoquarks. The proposed scenario accommodates all measured lepton flavour universality ratios in $B$-meson decays, is consistent with related flavour observables, and is compatible with direct searches at the LHC. The model is self-consistently perturbative, provides gauge coupling unification, and predicts several yet-to-be-measured flavour observables. I also outline prospects for future discoveries of the two leptoquarks at the LHC.

Aim of this paper is to give insight in Covid 19 data and to try to predict whether individual person will recover from this virus. Furthermore, this paper aims to give some answers how information like the country, the age, and the gender of the patient, the number of cases in their country and whether they’re from or have visited Wuhan can be used to make that prediction. Study uses Novel Corona Virus (COVID-19) epidemiological dataset. Logistic regression model and Random Forest algorithm are used in order to make prediction, and the Chi-Square test of independence is used to determine if there is a significant relationship between two nominal (categorical) variables. Paper reveals that recovery/survival is supposed to depend on the age of the patient, gender and country from which patient come. Information whether the patient is from Wuhan or has visited Wuhan does not affect recovery/survival of patient.

The Spectrophotometric method is one of the most suitable analytical techniques for testing the activity of enzymes under the influence of various factors. The effect of H1-antihistamines of loratadine and calcium ions on enzyme catalase under in vitro conditions was investigated in this paper. It has been shown that loratadine is a partial inhibitor of catalase, but this effect is diminished in the presence of calcium ions. Calcium as well as other cations are important for many biological and cellular functions. The kidneys play a central role in the homeostasis of these ions. The activity of the catalase enzyme under the given conditions, the type of inhibition, and the kinetic parameters of the enzyme reaction were determined. We concluded that loratadine is a partially competitive inhibitor.

Massive multiple-input multiple-output (M-MIMO) is one of the main 5G-enabling technologies that promise to increase cell throughput and reduce multiuser interference. However, these abilities rely on exploiting the channel state information (CSI) feedback at base stations (BSs). One critical challenge is that the user equipment (UE) needs to return a large amount of channel information to the base station, creating a large signaling overhead. In this letter, we propose a framework based on deep learning, which is able to efficiently compress and recover the feedback CSI. The encoder learns the most suitable compressed codeword corresponding to the CSI. The decoder decompresses this codeword at the receiving BS end using a Generative Adversarial Network (GAN). A novel objective function is proposed and used to train the Deep Convolutional Generative Adversarial Network (DCGAN) to improve the performance of our proposed framework. Simulation results demonstrate that the proposed framework outperforms traditional compressive sensing-based methods and provides remarkably robust performance for the outdoor channels.

This paper presents the design, fabrication, experimental results and related discussion of a portable bending enhancing silicone mold structure for biomedical applications in which a high-sensitive but low-cost force measurement structure with a large-dynamic range is required. Proposed system is composed of a replaceable parts like graphite coated Strathmore® 400 series Bristol paper and cheap RTV-2 silicone molds. The results shows that low-cost, portable and high-sensitive force and strain sensor systems can be realized for point-of-care biomedical applications in the future.

This paper proposes a novel disposable linear absolute encoder system and its peripheral electronic readout circuitry to be used for the localization of force in a continuum media such as a flexible robotic arm. The proposed structure relies on the design of graphite layers on a flexible surface that shows varying resistance based on the applied strain. The proposed topology can localize the force applied on a continuous paper based sensor having the geometry of an absolute encoder system. The successful results obtained from the experiments prove the efficacy of the proposed system while opening new paradigms for the possibility of contact force localization in flexible structures like soft robots.

In a previous article (10.1007/s00701-019-03888-3), preliminary results of a survey, aiming to shed light on the number of surgical procedures performed and assisted during neurosurgery residency in Europe were reported. We here present the final results and extend the analyses. Board-certified neurosurgeons of European Association of Neurosurgical Societies (EANS) member countries were asked to review their residency case logs and participate in a 31-question electronic survey (SurveyMonkey Inc., San Mateo, CA). The responses received between April 25, 2018, and April 25, 2020, were considered. We excluded responses that were incomplete, from non-EANS member countries, or from respondents that have not yet completed their residency. Of 430 responses, 168 were considered for analysis after checking in- and exclusion criteria. Survey responders had a mean age of 42.7 ± 8.8 years, and 88.8% were male. Responses mainly came from surgeons employed at university/teaching hospitals (85.1%) in Germany (22.0%), France (12.5%), the United Kingdom (UK; 8.3%), Switzerland (7.7%), and Greece (7.1%). Most responders graduated in the years between 2011 and 2019 (57.7%). Thirty-eight responders (22.6%) graduated before and 130 responders (77.4%) after the European WTD 2003/88/EC came into effect. The mean number of surgical procedures performed independently, supervised or assisted throughout residency was 540 (95% CI 424–657), 482 (95% CI 398–568), and 579 (95% CI 441–717), respectively. Detailed numbers for cranial, spinal, adult, and pediatric subgroups are presented in the article. There was an annual decrease of about 33 cases in total caseload between 1976 and 2019 (coeff. − 33, 95% CI − 62 to − 4, p = 0.025). Variables associated with lesser total caseload during residency were training abroad (1210 vs. 1747, p = 0.083) and female sex by trend (947 vs. 1671, p = 0.111), whereas case numbers were comparable across the EANS countries (p = 0.443). The final results of this survey largely confirm the previously reported numbers. They provide an opportunity for current trainees to compare their own case logs with. Again, we confirm a significant decline in surgical exposure during training between 1976 and 2019. In addition, the current analysis reveals that female sex and training abroad may be variables associated with lesser case numbers during residency.

Background: Immunization is a key step in preventing the occupational risk of acquiring hepatitis B infection for healthcare workers (HCWs). Objective: The aim of the study was determination the hepatitis B vaccine (HepB) coverage rate among HCWs and support staff and immune response 10 years after primary vaccination.Methods: A retrospective study was conducted in the Public Institution Health Centre of Sarajevo Canton in Bosnia and Herzegovina. Second-generation vaccines Euvax (Sanofi Pasteur, Thailand/LG Life Sciences Ltd, Korea) and Engerix B (GlaxoSmithKline, Belgium) were applied. A level of ≥ 10 IU/L anti-HBs was set as a cut-off value indicating the presence of protective immunity against new HBV infections and successful vaccination. Results: In total, 1541 (75.80%) were fully vaccinated, out of 1126 (73.07%) were females. The median age of participans was 50.5 ± 9.4 years. Control measurement of the anti-HBs level was performed for 409 (26.54%) HCWs. During the research, 37 booster doses were administered. Of the 23 retested participants, anti-HBs ≥10 IU/L were observed in 19 (82.16%). Three non-reactors subject were revealed.Conclusions: A satisfying HepB coverage rate and a high protective rate against hepatitis B infection among HCWs and support staff was achived. These results indicate the active engagement of the institution in the implementation of preventive measures and the high level of awareness regarding the significance of immunization. Our results demonstrated the effectiveness of booster doses. A low prevalence of non-reactors was revealed. Additional research with a focus on occupational risk factors in dental service is advised.

: T his paper provides a simple estimation of the Long Term Evolution (LTE) physical and Medium Access Control (MAC) layer peak transmission performanc e-the irr educible Block - Error - Rate (BLER) that determines the Hybrid Automatic Repeat Request (HARQ) residual channel available to higher - layer protocols. With this regard, the general pre - HARQ BLER prediction is developed for the redundancy version 0 (RV0) codeword transmission, expressed by the Bit - Error - Rate (BER)), considering the cyclic prefix protection against inter - symbol interference sufficient to prevent long error bursts. This implies only sporadic bit error occurrences, exhibiting moderate mutual interdependence that we modelled considering errored bits of each block of data as a sample without replacement and consequently describing it with the hypergeometric distribution instead of the mostly used binomial one. The HARQ BLER estimation model is verified by both problem - dedicated Monte - Carlo simulations and industry - standard LTE software simulation tool, specifically for the LTE FDD downlink channel environment, as the test results exhibit excellent matching with the residual BLER prediction.

: T ime series data of GNSS point positioning are considerably used for the purpose of geophysical research. The velocity estimates and their uncertainties deriv e from time series data of GNSS point positioning affected by seasonal signals and the stochastic noise, contained in the series. D ata cleaning of GNSS time series is a prerequisite for the noise characterization and analysing. In this article one point positioning of time series was analysed in four different periods during the five year interval. The noise characteristics were estimated for all periods. By applying Lomb - Scargle algorithm the comparable results were also provided. Lomb - Scargle algorithm used to estimate the spectral strength density of unequal sampled data is a typical tool for this kind of analysis. S pectral indices have been estimated before cleaning data and after removing linear, annual and semi - annual signals and outliers. T he spectral indices estimated from time series data of GNSS point positioning were located in the area of fractional Gaussian noises , and stationary stochastic process was described for the whole research time period.