High-risk human papillomaviruses (high-risk HPVs) have been recently reported to be co-present with Epstein–Barr virus (EBV) in different types of human cancers including head and neck (HN), where they can cooperate in the initiation and/or progression of this cancer. Accordingly, we herein explored the prevalence of high-risk HPVs and EBV in 80 HN cancer tissues from the Syrian population using polymerase chain reaction, immunohistochemistry, and tissue microarray methodologies. We report that high-risk HPVs and EBV are present in 35/80 (43.7%) and 41/80 (51.2%) of our samples, respectively, and the most frequent HPV types are 33, 16, 18, 45, 52, 58, 35, 51, and 31, in this order. More significantly, our data reveal that 25/80 (31.2%) of cancer cases are positive for high-risk HPVs as well as EBV, and their co-presence is associated with high/intermediate-grade squamous cell carcinomas. These data confirm the co-presence of high-risk HPVs and EBV in HN cancers in the Syrian population of the Middle East and demonstrate that their co-incidence is linked to a more aggressive cancer phenotype. Thus, future studies are required to confirm these data and elucidate the exact role of high-risk and EBV cooperation in human HN carcinogenesis.

Abstract With an incidence of 350.000 new cases per year, cancer of the oral cavity ranks among the 10 most common solid organ cancers. Most of these cancers are squamous cell carcinomas. Five‐year survival is about 50%. It has been shown that clear resection margins (>5 mm healthy tissue surrounding the resected tumor) have a significant positive effect on locoregional control and survival. It is not uncommon that the resection margins of oral tumors are inadequate. However, when providing the surgeon with intraoperative feedback on the resection margin status, it is expected that obtaining adequate resection margins is improved. In this respect, it has been shown that specimen‐driven intraoperative assessment of resection margins is superior to defect‐driven intraoperative assessment of resection margins. In this concise report, it is described how a specimen‐driven approach can increase the rate of adequate resections of oral cavity squamous cell carcinoma as well as that it is discussed how intraoperative assessment can be further improved with regard to the surgical treatment of oral cavity squamous cell carcinoma.

Department of Clinical Microbiology, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina Department of Epidemiology, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina Autoimmune Diseases Department, Vasculitis Research Unit, IDIBAPS, CELLEX 4B, Hospital Clinic Barcelona, Spain Department of Chemistry Diagnostics, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina Department for Epizootiology, Institute for Health and Food Safety Zenica, Fra Ivana Jukića 2, 72000 Zenica, Bosnia and Herzegovina

We propose to create a secondary beam of neutral kaons in Hall D at Jefferson Lab to be used with the GlueX experimental setup for strange hadron spectroscopy. The superior CEBAF electron beam will enable a flux on the order of $1\times 10^4~K_L/sec$, which exceeds the flux of that previously attained at SLAC by three orders of magnitude. The use of a deuteron target will provide first measurements ever with neutral kaons on neutrons. The experiment will measure both differential cross sections and self-analyzed polarizations of the produced $\Lambda$, $\Sigma$, $\Xi$, and $\Omega$ hyperons using the GlueX detector at the Jefferson Lab Hall D. The measurements will span CM $\cos\theta$ from $-0.95$ to 0.95 in the range W = 1490 MeV to 2500 MeV. The new data will significantly constrain the partial wave analyses and reduce model-dependent uncertainties in the extraction of the properties and pole positions of the strange hyperon resonances, and establish the orbitally excited multiplets in the spectra of the $\Xi$ and $\Omega$ hyperons. Comparison with the corresponding multiplets in the spectra of the charm and bottom hyperons will provide insight into he accuracy of QCD-based calculations over a large range of masses. The proposed facility will have a defining impact in the strange meson sector through measurements of the final state $K\pi$ system up to 2 GeV invariant mass. This will allow the determination of pole positions and widths of all relevant $K^\ast(K\pi)$ $S$-,$P$-,$D$-,$F$-, and $G$-wave resonances, settle the question of the existence or nonexistence of scalar meson $\kappa/K_0^\ast(700)$ and improve the constrains on their pole parameters. Subsequently improving our knowledge of the low-lying scalar nonet in general.

We propose to create a secondary beam of neutral kaons in Hall D at Jefferson Lab to be used with the GlueX experimental setup for strange hadron spectroscopy. The superior CEBAF electron beam will enable a flux on the order of $1\times 10^4~K_L/sec$, which exceeds the flux of that previously attained at SLAC by three orders of magnitude. The use of a deuteron target will provide first measurements ever with neutral kaons on neutrons. The experiment will measure both differential cross sections and self-analyzed polarizations of the produced $\Lambda$, $\Sigma$, $\Xi$, and $\Omega$ hyperons using the GlueX detector at the Jefferson Lab Hall D. The measurements will span CM $\cos\theta$ from $-0.95$ to 0.95 in the range W = 1490 MeV to 2500 MeV. The new data will significantly constrain the partial wave analyses and reduce model-dependent uncertainties in the extraction of the properties and pole positions of the strange hyperon resonances, and establish the orbitally excited multiplets in the spectra of the $\Xi$ and $\Omega$ hyperons. Comparison with the corresponding multiplets in the spectra of the charm and bottom hyperons will provide insight into he accuracy of QCD-based calculations over a large range of masses. The proposed facility will have a defining impact in the strange meson sector through measurements of the final state $K\pi$ system up to 2 GeV invariant mass. This will allow the determination of pole positions and widths of all relevant $K^\ast(K\pi)$ $S$-,$P$-,$D$-,$F$-, and $G$-wave resonances, settle the question of the existence or nonexistence of scalar meson $\kappa/K_0^\ast(700)$ and improve the constrains on their pole parameters. Subsequently improving our knowledge of the low-lying scalar nonet in general.

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.

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.

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.

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.

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.

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.

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.