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.

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.

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.

Očuvanje porodice kao osnovne ćelije društva u savremenom načinu života je veliki izazov. Očuvanje i funkcionisanje porodice gdje je jedno dijete s oštećenjem sluha predstavlja ogroman pritisak roditeljima, koji moraju naučiti balansirati između djeteta koje ima teškoću i djeteta koje nema. Uočavanjem i dijagnostikovanjem teškoće kod djeteta roditelji se suočavaju sa potpuno novim načinom života. Odgajanje djeteta s teškoćama u razvoju za njih je put u nepoznato, nije rijetkost da brak zapadne u krizu, svakodnevno su izloženi stresu i brojnim obavezama. Uz nerazumijevanje šire porodice za probleme s kojima se suočavaju i društvene zajednice koja ne pruža adekvatnu podršku, moraju naučiti na koji način će odgajati i jedno i drugo dijete. Koliko će ravnopravno postupati u ophođenju prema njima je od presudnog značaja za razvijanje skladnih bratsko – sestrinskih odnosa. Adekvatnim pristupom i pravilnim odgojem, dijete s teškoćama u razvoju u porodici stvara posebne veze među članovima koji doprinose bržem sazrijevanju, većoj zrelosti, odgovornosti i samostalnosti braće i sestara.

Poslednjih decenija sve je prisutnija pojava porasta problema u ponašanju kod djece i adolescenata. Cilj istraživanja je utvrditi razlike u porodičnoj orijentaciji i strukturi porodice između adolescenata sa eksternaliziranim i internaliziranim problemima i tipično razvijenih adolescenata. Uzorak ispitanika čini 587 adolescena oba spola. Istraživanje je realizovano u petnaest osnovnih škola na području Tuzle tako što je iz svake škole uključeno po dva odjeljenja, jedno sedmog i jedno osmog razreda. Uzorak je namjerni (samo sedmi i osmi razredi), a unutar njega metodom slučaja su izabirani razredi. U istraživanju su korištena dva mjerna instrumenta: Youth Self-Report – YRS (Achenbach, 2007) i Skala porodičnog okruženja, verzija za adolescente (Family Envinoment Scale – FES, Moos, Moos, 2009). Rezultati istraživanja upućuju na postojanje razlike između adolescenata koji žive sa oba roditelja i onih koji su iz nepotpune porodice. Statistički značajne razlike uočene su na skalama Agresivno ponašanje (t = - 2,23; p < 0,00), Ponašanje kojim se krše pravila (t = -3,22; p < 0,00) i dimenziji Eksternalizacije (t = -2,82; p < 0,00). Kod porodične orijentacije je također prisutna statistička razlika. Dovodeći u vezu strukturu porodice porodice sa internaliziranim problemima uočeno je da ne postoje statistički značajne razlike.

: 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.

PURPOSE We aimed to determine the association of two of the most important functional polymorphisms of IL-8 and IL-10 with the clinical course and outcome of acute pancreatitis. METHOD Ninety-three patients with acute pancreatitis were genotyped for IL-8-251T>A and IL-10-1082G>A using PCR-RFLP. The severity of the disease was determined based on the Atlanta Classification system. RESULTS In patients treated with opioids, the odds for severe form of acute pancreatitis, its complications, and death were increased. Advanced age was associated with higher odds of organ/multiple organ failure and other systemic complications. Multivariate logistic regression analyses confirmed the observed effect of age and use of opioids, and revealed higher odds for the development of severe form of acute pancreatitis [P = 0.017, odds ratio (OR): 4.324, 95% confidence interval (CI): 1.305-14.323], its complications in general (P = 0.011, OR: 4.936, 95% CI: 1.442-16.897), pancreatic necrosis (P = 0.032, OR: 3.922, 95% CI: 1.122-13.707) and systemic inflammatory response syndrome (P = 0.037, OR: 3.838, 95% CI: 1.085-13.583) in the absence of IL-10-1082G>A variant allele. The effect of IL-8 -251T>A on acute pancreatitis severity or mortality was not detected. CONCLUSION Our study suggests the IL-10 -1082A allele as a protective factor in acute pancreatitis. Opioid analgesics treatment in acute pancreatitis is associated with severity, complications and mortality, while advanced age increases the risk of systemic complications.

The human respiratory syncytial virus (RSV) is a major cause of severe lower respiratory tract infections in infants, possibly due to the specific features of the immature neonatal pulmonary immune system. Using the newborn lamb, a classical model of human lung development and a state-of-the-art model of RSV infection, we aimed to explore the role of cell-mediated immunity in RSV disease during early life. Remarkably, in healthy conditions, the developing T cell compartment of the neonatal lung showed major differences to that seen in the mature adult lung. The most striking observation being a high baseline frequency of bronchoalveolar IL-4-producing CD4 and CD8 T cells, which declined progressively over developmental age. RSV infection exacerbated this pro-type 2 environment in the bronchoalveolar space, rather than inducing a type 2 response per se. Moreover, regulatory T cell suppressive functions occurred very early to dampen this pro-type 2 environment, rather than shutting them down afterwards, while γδ T cells dropped and failed to produce IL-17. Importantly, RSV disease severity was related to the magnitude of those unconventional bronchoalveolar T cell responses. These findings provide novel insights in the mechanisms of RSV immunopathogenesis in early life, and constitute a major step for the understanding of RSV disease severity. AUTHOR SUMMARY By using a state-of-the-art translational model with full accessibility to the small airways at defined early life periods, we provide an unpreceded characterization of the developing T cell compartment in the distal lungs of healthy and RSV-infected neonates. This process is highly dynamic and tightly regulated, characterized by colonizing T-cell subsets that synergize towards a narrow pro-tolerogenic immunological window. We believe our work constitutes a solid basis to clarify the age dependency of RSV immunopathogenesis, and should be considered in vaccine design, which remains challenging after five decades of effort.

Rationale: Respiratory syncytial virus (RSV) is a major cause of lower respiratory tract infection in infancy, potentially aided by an inappropriate immune response. Sparse information is available for the distal lung, mostly because data arose from non-invasive samplings of peripheral blood and nasal aspirates. Objectives: To determine the neonatal immune response to RSV in the bronchoalveolar space and better understand why neonates are at greater risk of developing severe disease. Methods: We used the newborn lamb, a state-of-the-art translational model of human RSV infection, offering ease sampling and full accessibility to lower airways. Using a multiparameter flow cytometry assay, we evaluated the frequency and activation/maturation state of the major subsets of the developing T-cell compartment. Measurements and Main Results: The T-cell compartment of the healthy developing lung was very distinct to that seen in adults. We observed a high frequency of type 2 CD4+ (Th2) and CD8+ (Tc2) T-cells, both being a large source of IL-4, which declined progressively over time. Remarkably, RSV infection exacerbated this pro-type 2 environment, rather than inducing a type 2 response per se. Neonatal regulatory T-cell (Treg) suppressive functions occurred very early to dampen those Th2 and Tc2 responses, while γδ T-cells dropped and failed to produce IL-17. The disease severity was related to the magnitude of these T-cell responses. Conclusion: The atypical neonatal immune response to RSV consists of distinct T-cell subsets that tightly cooperate, namely a combined bronchoalveolar influx of Treg, Th2 and Tc2 cells, associated with a depletion of γδ T-cells.

We have investigated the self-assembly of a strong dipolar molecule (LDipCC) on the semiconducting Si(111)-B surface with scanning tunneling microscopy (STM), density functional theory (DFT) calculations and STM simulations. Although the formation of an extended two-dimensional network was clearly revealed by STM under ultra-high vacuum, the assignment of a specific STM signature to the different terminal groups from the LDipCC molecular unit required a complete analysis by numerical simulations. The overall observed assembly is explained in terms of STM contrasts associated with the molecular structure of LDipCC and the molecule-surface interactions. To distinguish the relative arrangement of the dipolar molecules within the assembly, a rational combination of experimental results and electronic structure calculations allows us to identify a single adsorbed LDipCC phase in which the molecular dipoles are homogeneously arranged into a parallel fashion on the Si(111)-B surface.