Duhan je biljna kultura koja se ističe brzinom i količinom apsorpcije teških metala iz tla, a naročito kadmija. Konzumiranjem duhana, teški metali se akumuliraju u organizmu ljudi, bez mogućnosti da se iz njega odstrane na bilo koji način, za razliku od nekih drugih biljnih kultura (npr. rajčica) kod kojih se ti metali mogu odstraniti iz organizma putem probavnog trakta. Autohtone hercegovačke sorte duhana (Ravnjak, VH i VH32) dugo su bile tretirane kao jedne od najkvalitetnijih, a za čiji rast i razvoj su potrebni specifični agroekološki uvjeti koji su karakteristični isključivo za Hercegovinu. U ovom istraživanju se prati translokacija Cd u sustavu tlo-duhan-dimni kondenzat kod duhana koji se danas uzgajaju na području BiH. Kako ovakvo ili slično istraživanje nije nikada prije rađeno na hercegovačkim duhanima, to su dobiveni rezultati uspoređivani s rezultatima dobivenim kod sorti Virdžinija i Berlej, koje su također bile predmetom istraživanja, a za koje postoje i literaturni podaci uzeti iz predhodnih svjetskih istraživanja. Uzorci tla i duhana uzeti su s 16 lokacija s područja cijele BiH, tj. sa svih lokaliteta na kojima se danas uzgaja duhan u BiH. Od najkvalitetnijih srednjih insercija, ručno su pravljene cigarete koje su kasnije popušene na pušačkom stroju. Na sadržaj Cd ispitivani su uzorci tla, duhana i dimnog kondenzata, a iz statističke analize dobivenih rezultata, može se zaključiti da postoji značajno kretanje kadmija iz tla preko biljke u dimni kondenzat.

Thermal transport properties of solid Bi-Cu alloys have been investigated over a wide composition range and temperature range ranging from 25 to 250 °C. The flash method was used to determine thermal diffusivity. Thermal diffusivity was discovered to decrease continuously with increasing temperature and bismuth content. The indirect Archimedean method was used to determine the density of the Bi-Cu alloys at 25 °C. The obtained results show that the density of the studied alloys decreases slightly as the copper content increases. Thermal conductivity of the alloys was calculated using measured diffusivity, density, and a calculated specific heat capacity. The thermal conductivity of the studied Bi-Cu alloys decreases with increasing temperature and bismuth content, similar to thermal diffusivity. SEM with energy dispersive X-ray spectrometry (EDS) and differential scanning calorimetry (DSC) were used to examine the microstructure and melting behavior of Bi-Cu alloys, respectively. The eutectic temperature was measured to be 269.9±0.1 °C, and the measured phase transition temperatures and heat effects were compared to thermodynamic calculations using the CALPHAD method.

Principal component analysis (PCA) is perhaps the most widely used method for data dimensionality reduction. A key question in PCA is deciding how many factors to retain. This manuscript describes a new approach to automatically selecting the number of principal components based on the Bayesian minimum message length method of inductive inference. We derive a new estimate of the isotropic residual variance and demonstrate that it improves on the usual maximum likelihood approach. We also discuss extending this approach to finite mixture models of principal component analyzers.

The aim of this manuscript is to introduce the Bayesian minimum message length principle of inductive inference to a general statistical audience that may not be familiar with information theoretic statistics. We describe two key minimum message length inference approaches and demonstrate how the principle can be used to develop a new Bayesian alternative to the frequentist $t$-test as well as new approaches to hypothesis testing for the correlation coefficient. Lastly, we compare the minimum message length approach to the closely related minimum description length principle and discuss similarities and differences between both approaches to inference.

In this short note, we derive a new bias adjusted maximum likelihood estimate for the shape parameter of the Weibull distribution with complete data and type I censored data. The proposed estimate of the shape parameter is significantly less biased and more efficient than the corresponding maximum likelihood estimate, while being simple to compute using existing maximum likelihood software procedures.

The Weibull distribution, with shape parameter $k>0$ and scale parameter $\lambda>0$, is one of the most popular parametric distributions in survival analysis with complete or censored data. Although inference of the parameters of the Weibull distribution is commonly done through maximum likelihood, it is well established that the maximum likelihood estimate of the shape parameter is inadequate due to the associated large bias when the sample size is small or the proportion of censored data is large. This manuscript demonstrates how the Bayesian information-theoretic minimum message length principle coupled with a suitable choice of weakly informative prior distributions, can be used to infer Weibull distribution parameters given complete data or data with type I censoring. Empirical experiments show that the proposed minimum message length estimate of the shape parameter is superior to the maximum likelihood estimate and appears superior to other recently proposed modified maximum likelihood estimates in terms of Kullback-Leibler risk. Lastly, we derive an extension of the proposed method to data with type II censoring.

Background: The aim of the present randomized, crossover study was to determine the physiological and cognitive function responses while wearing a facemask during a maximal running aerobic fitness test. Methods: Fourteen healthy, nonsmoking physical education students (age = 17.5 years, height = 1.72 m, body mass = 70.4 kg) volunteered to participate in this study. They carried out a 20 m multistage fitness test (MSFT) while wearing or not a cloth facemask on two separate occasions performed in random order. The “Rating of Perceived Exertion” (RPE) and the d2 test for visual attention were administered and assessed before and immediately after the MSFT for both conditions (with or without a facemask). Results: When wearing the facemask, the participants exhibited lower maximal aerobic speed (p = 0.039), VO2max (p = 0.039), distance covered during the MSFT (p = 0.057), and concentration performance (p < 0.001), when compared with the control situation (without facemask). Moreover, they made more errors compared with the control condition (p = 0.021). The use of a cloth facemask during maximal endurance running tests (such as the MSFT) reduced VO2max, and measures of cognitive performance as assessed by the test of focused visual attention (the d2 test). This data suggests avoiding using a cloth facemask during maximal aerobic fitness tests, and before any tasks that require a high level of visual attention.

Radiology is integral to cancer care. Compared to molecular assays, imaging has its advantages. Imaging as a noninvasive tool can assess the entirety of tumor unbiased by sampling error and is routinely acquired at multiple time points in oncological practice. Imaging data can be digitally post-processed for quantitative assessment. The ever-increasing application of Artificial intelligence (AI) to clinical imaging is challenging radiology to become a discipline with competence in data science, which plays an important role in modern oncology. Beyond streamlining certain clinical tasks, the power of AI lies in its ability to reveal previously undetected or even imperceptible radiographic patterns that may be difficult to ascertain by the human sensory system. Here, we provide a narrative review of the emerging AI applications relevant to the oncological imaging spectrum and elaborate on emerging paradigms and opportunities. We envision that these technical advances will change radiology in the coming years, leading to the optimization of imaging acquisition and discovery of clinically relevant biomarkers for cancer diagnosis, staging, and treatment monitoring. Together, they pave the road for future clinical translation in precision oncology.

The Weibull distribution, with shape parameter $k>0$ and scale parameter $\lambda>0$, is one of the most popular parametric distributions in survival analysis with complete or censored data. Although inference of the parameters of the Weibull distribution is commonly done through maximum likelihood, it is well established that the maximum likelihood estimate of the shape parameter is inadequate due to the associated large bias when the sample size is small or the proportion of censored data is large. This manuscript demonstrates how the Bayesian information-theoretic minimum message length principle coupled with a suitable choice of weakly informative prior distributions, can be used to infer Weibull distribution parameters given complete data or data with type I censoring. Empirical experiments show that the proposed minimum message length estimate of the shape parameter is superior to the maximum likelihood estimate and appears superior to other recently proposed modified maximum likelihood estimates in terms of Kullback-Leibler risk. Lastly, we derive an extension of the proposed method to data with type II censoring.

Grazing-incidence small-angle X-ray scattering (GISAXS) is a powerful method for the structural analysis of ordered arrays of nanoparticles, quantum dots, or similar objects. However, for the correct interpretation of the measured GISAXS intensity distributions, a proper data analysis, including a suitable model, is required. Here, we demonstrate a software platform, GisaxStudio, aimed at the analysis and simulation of 2D GISAXS intensity distributions from ordered lattices of different nanoparticles. It contains several models that satisfactorily describe the GISAXS from 3D lattices or crystals of nanoparticles prepared by the self-assembly processes, pre-pattering, or ion-beam interaction with the material within their tracks. It also supports different shapes of nanoparticles, including core-shell structure with the center of core possibly displaced from the center of the shell. The software is very useful for fast and accurate GISAXS data analysis.

The pandemic of COVID-19 has brought many changes in health care systems at all levels of health care. The increase in the number of cases of COVID-19 has led to overuse and misuse of antibiotics.The aim of this study was to compare the consumption of antibiotics for systemic use in outpatients in the Republic of Srpska (RS), before and during the first year of the COVID-19 pandemic, as well as the association between antibiotic consumption and the rate of incidence and mortality of COVID-19. The total consumption of the antibiotics for systemic use (J01) in outpatients in the Republic of Srpska during 2019 was 19.40 DDD/TID, with an increase to 30.80 DDD/TID in 2020.Significantly higher use of penicillin (10.58 ± 11.01 DDD/TID in 2019 vs. 17.10 ± 13.63 DDD/TID in 2020), cephalosporins (2.68 ± 1.90 DDD/TID in 2019 vs. 5.93 ± 2.77 DDD/TID in 2020) and macrolides (2.14 ± 2.22 DDD/TID in 2019 vs. 3.40 ± 3.44 DDD/TID in 2020) was observed during the pandemic period. It is necessary to improve the prescribing practice of antibiotics at the primary health care level, public awareness about rational use of antibiotics, as well as the current antibiotic stewardship programs and control their implementation.

Antibiotics are often misused, especially for the treatment of upper respiratory tract infections (URTIs) in children, where their use is unnecessary and leads to antimicrobial resistance. This study sought to explore the knowledge, attitudes and practices (KAP) of parents and pediatricians on the use of antibiotics among children and whether the level of education of parents has an impact on their KAP. The research was carried out among 1459 parents of children under 6 years of age and among 18 pediatricians. Sixty percent of pediatricians (61.1%) were prescribed antibiotics daily in their practice. Most of the surveyed parents (98.4%) state that doctors are their main source of information when deciding on the use of antibiotics in the treatment of their children. Parents with a higher level of education use television less often as a source of information when making this decision compared to parents with a lower level of education (p = 0.039, i.e., p = 0.003). The majority of parents (80.7%) knew that Panklav (amoxicillin/clavulanic acid) is an antibiotic, while 52.5% identified Pancef (cefixime) as an antibiotic. Parents with a higher level of education correctly identified antibiotics significantly more often (p < 0.001). This study shows that in the Republic of Srpska, parents have adequate knowledge about antibiotics, especially those with a higher level of education, who show better KAP when it comes to antibiotic use.

The rule of law is one of the key concepts in the 21st century. The idea of the rule of law exists to the extent that there are reflections on the state and law, and a relationship between these two concepts. The aim of this paper is to show in one place the development of the idea of the rule of law through history. In this sense, the authors look at the thoughts of philosophers who have largely determined the direction of development of the idea of the rule of law. Of course, not all philosophers who have contemplated the rule of law are listed in the paper, but it nevertheless attempts to show in chronological order how the rule of law as an idea developed from Plato to its modern theorists.

Objective To establish optimised diffusion weightings (‘ b -values’) for acquisition of whole-body diffusion-weighted MRI (WB-DWI) for estimation of the apparent diffusion coefficient (ADC) in patients with metastatic melanoma (MM). Existing recommendations for WB-DWI have not been optimised for the tumour properties in MM; therefore, evaluation of acquisition parameters is essential before embarking on larger studies. Methods Retrospective clinical data and phantom experiments were used. Clinical data comprised 125 lesions from 14 examinations in 11 patients with multifocal MM, imaged before and/or after treatment with immunotherapy at a single institution. ADC estimates from these data were applied to a model to estimate the optimum b -value. A large non-diffusing phantom was used to assess eddy current–induced geometric distortion. Results Considering all tumour sites from pre- and post-treatment examinations together, metastases exhibited a large range of mean ADC values, [0.67–1.49] × 10^−3 mm^2/s, and the optimum high b -value ( b _high) for ADC estimation was 1100 (10th–90th percentile: 740–1790) s/mm^2. At higher b -values, geometric distortion increased, and longer echo times were required, leading to reduced signal. Conclusions Theoretical optimisation gave an optimum b _high of 1100 (10th–90th percentile: 740–1790) s/mm^2 for ADC estimation in MM, with the large range of optimum b -values reflecting the wide range of ADC values in these tumours. Geometric distortion and minimum echo time increase at higher b -values and are not included in the theoretical optimisation; b _high in the range 750–1100 s/mm^2 should be adopted to maintain acceptable image quality but performance should be evaluated for a specific scanner. Key Points • Theoretical optimisation gave an optimum high b-value of 1100 (10th–90th percentile: 740–1790) s/mm ^ 2 for ADC estimation in metastatic melanoma. • Considering geometric distortion and minimum echo time (TE), a b-value in the range 750–1100 s/mm ^ 2 is recommended. • Sites should evaluate the performance of specific scanners to assess the effect of geometric distortion and minimum TE.