Modeling of pressure rise in SF6 GIS (Gas Insulated Switchgear) due to internal arc faults is a complex and challenging task, due to a large number of highly variable factors, which influence the whole process. This is especially the case in GIS with high rated short circuit currents, where the effects, such as material evaporation and erratic arc behavior, and consequently the pressure build-up rate, are much more pronounced. These severe conditions ultimately determine the design limits and must therefore be carefully investigated. The enhanced internal arc simulation model, presented in this paper, considers the impact of evaporation of different materials on gas properties and the pressure rise, as well as the dependence of released arc energy, thermal transfer and evaporation intensity on the state of gas. The experimental set-up and the test configuration, used to validate the calculation results, are evaluated and discussed. An evident finding, which is supported by measurements, is that the implemented improvements of the basic simulation model (introduced in the Technical Brochure 602 by the CIGRÉ working group A3.24) increase the prediction accuracy of GIS withstand performance during internal arc faults.

Introduction: The source of scientific information, methods for their evaluation, and methodology of their use are critical for serious scientific research and publishing of the scientific research results. Certain methodological principles should be inexcusably followed when designing clinical or observational research to avoid bias and presentation of results that do not reflect the truth about the phenomenon that is the object of the study. Aim: The aim of this study was to compare the methodological quality of clinical trials and observational studies published in medical journals from ex-Yugoslav countries indexed in Web of Science (WoS) and Pubmed/MEDLINE. Methods: Clinical studies published in medical journals of ex-Yugoslav countries were retrieved from the WoS and Pubmed database, and the sample for analysis was randomly chosen from the retrieved publications. The rate of the most common errors in the design of clinical/observational studies was established by a careful reading of the sampled publications and their checking against predefined criteria. Results: Number and percent of the evaluated studies that failed to meet each of the methodological criteria tested, number of the evaluated criteria not satisfied per database and number of studies that satisfied more than 4 criteria were analyzed per database. When explanatory potential of journal impact factor, number of citations, time elapsed from publication and a database where a journal is referred were tested by linear regression in regard to the number of methodological criteria satisfied per study, the linear regression model was obtained by backward deletion method and achieved R2 adjusted of 0.166 (F=13.827, df1 = 2, df2 = 127, p=0.000). The methodological quality of studies was directly related to impact factor of the journals (B = 0.976, 95% confidence interval 0.539 – 1.413, p=0.000) and inversely with the database where a journal is referred (B =–0.444, 95% confidence interval–0.824 – -0.064, p = 0.022). Each additional unit of impact factor increased number of satisfied methodological criteria for about 1, while referring a journal only in WoS decreased number of satisfied criteria for 0.45 points in comparison with journals referred in both WoS and Pubmed/MEDLINE, and for 0.9 points in comparison to journals referred only in MEDLINE. Conclusion: Methodological and scientometric quality of clinical studies published in medical journals from ex-Yugoslav region varies significantly, and the variations are higher in journals referenced only in WoS than in journals referenced in Pubmed/MEDLINE only, or in both Pubmed and Web of Science databases.

Introduction: Pseudo journals, hijacked journals, fraudulent journals, fake journals, and predatory journals waste valuable research when authors publish their studies in them. Aim: This article described novel suggested features for the identification of fraudulent journals and aimed to explain this issue to help inexperienced scientists avoid publishing in predatory journals. Methods: The articles related to this topic in were retrieved from PubMed and trustable Internet sources. Results: Unfortunately, some fake journals have made their way into reputable databases, such as PubMed, PubMed Central, MEDLINE, SCOPUS, and Web of Science; thus, the serious question has been raised regarding how we should address this problematic phenomenon. We recommended 28 suggested characteristics of predatory journals for readers to take into consideration. Conclusion: Unaware of the detrimental effects associated with publishing in disreputable journals, inexperienced researchers can fall victim to them. Together, as both readers and writers, we should completely boycott predatory journals.

Aim To determine preferable type of treatment in our clinical circumstances by following two groups of patients with critical limb ischemia (CLI), who were treated endovascularly and surgically. Methods Research was carried out in the form of a prospective study of 80 patients with CLI and Trans-Atlantic Inter-Society Consensus (TASC) C or D type of arterial disease, with American Society of Anesthesiology (ASA) class III risk, who were randomly divided in two groups as per the treatment they received, surgical and endovascular. Patients were followed during 28 months using clinical examination and Duplex Ultrasound (DUS) in accordance with prescheduled control visits. Results There was a statistical difference between surgical and endovascular group in two years patency (82.5% vs. 55%; p=0.022) but it did not result in the difference in amputation free survival (AFS) (95% vs. 85%; p=0.171) or two-year freedom from major adverse limb events (MALE) (87.5 vs. 77.5; p=0.254). Also, there was no difference in the overall survival of patients (100% vs. 97.5%; p=0.317). Conclusion Initial endovascular treatment is a preferred form of the treatment for selected patient population.

Identifying at-risk students is a crucial step in different learning settings. Predictive modeling technique can be used to create an early warning system which predicts students’ success in courses and informs both the teacher and the student of their performance. In this paper we describe a course-specific model for prediction of at-risk students. The proposed model uses the case-based reasoning (CBR) methodology to predict at-risk students at three specific points in time during the first half of the semester. In general, CBR is an approach of solving new problems based on solutions of similar previously experienced problem situation encoded in the form of cases. The proposed model classifies students as at-risk based on the most similar past cases retrieved from the casebase by using the k-NN algorithm. According to the experimental evaluation of the model accuracy, CBR model that is being developed for a specific course showed potential for an early prediction of at-risk students. Although the presented CBR model has been applied for one specific course, the key elements of predictive model can be easily reused by other courses.

The paper presents an approach aimed at automatically deriving the conceptual database model from a set of business process models. The approach proposes the incremental synthesis of the target model by iteratively composing the partial conceptual database models that are derived from the models contained in the source set. The approach is implemented by the AMADEOS tool, which is the first online web-based tool enabling the automatic derivation of the conceptual database model from a set of business process models.

Background: Oral premalignant lesions (OPLs) represent the most common oral precancerous conditions. One of the major challenges in this field is the identification of OPLs at higher risk for oral squamous cell cancer (OSCC) development, by discovering molecular pathways deregulated in the early steps of malignant transformation. Analysis of deregulated levels of single genes and pathways has been successfully applied to head and neck squamous cell cancers (HNSCC) and OSCC with prognostic/predictive implications. Exploiting the availability of gene expression profile and clinical follow-up information of a well-characterized cohort of OPL patients, we aim to dissect tissue OPL gene expression to identify molecular clusters/signatures associated with oral cancer free survival (OCFS). Materials and methods: The gene expression data of 86 OPL patients were challenged with: an HNSCC specific 6 molecular subtypes model (Immune related: HPV related, Defense Response and Immunoreactive; Mesenchymal, Hypoxia and Classical); one OSCC-specific signature (13 genes); two metabolism-related signatures (3 genes and signatures raised from 6 metabolic pathways associated with prognosis in HNSCC and OSCC, respectively); a hypoxia gene signature. The molecular stratification and high versus low expression of the signatures were correlated with OCFS by Kaplan–Meier analyses. The association of gene expression profiles among the tested biological models and clinical covariates was tested through variance partition analysis. Results: Patients with Mesenchymal, Hypoxia and Classical clusters showed an higher risk of malignant transformation in comparison with immune-related ones (log-rank test, p = 0.0052) and they expressed four enriched hallmarks: “TGF beta signaling” “angiogenesis”, “unfolded protein response”, “apical junction”. Overall, 54 cases entered in the immune related clusters, while the remaining 32 cases belonged to the other clusters. No other signatures showed association with OCFS. Our variance partition analysis proved that clinical and molecular features are able to explain only 21% of gene expression data variability, while the remaining 79% refers to residuals independent of known parameters. Conclusions: Applying the existing signatures derived from HNSCC to OPL, we identified only a protective effect for immune-related signatures. Other gene expression profiles derived from overt cancers were not able to identify the risk of malignant transformation, possibly because they are linked to later stages of cancer progression. The availability of a new well-characterized set of OPL patients and further research is needed to improve the identification of adequate prognosticators in OPLs.

The combination of 5G and Multi-access Edge Computing (MEC) technologies can bring significant benefits to vehicular networks, providing means for achieving enhanced Quality of Service (QoS), and Quality of Experience (QoE) of wide variety of vehicular applications. Although beneficial in terms of latency reduction, the edge of the architecture for communication networks produces enormous heterogeneity of network services and resources. This challenge becomes even more severe when different administration domains are taken into consideration. Thus, efficient network Management and Orchestration (MANO) of network resources and services are inevitable. As ETSI provided guidelines and standardization for NFV MANO components, the MEC platform can be used to host network services, while MANO systems are in charge of network service management and orchestration. In this paper, we focus on the specific impact that the Virtualized Infrastructure Manager (VIM) has on the performance of the whole MANO system, used for management and orchestration of MEC services and resources in vehicular networks by enabling the on-demand service instantiation, and service teardown. In our testbed-based evaluation, we measured the network service instantiation and termination delays when evaluating: a) OpenStack and Amazon Web Services (AWS) as VIMs for Open Source MANO (OSM), and b) OpenStack and Docker in case of Open Baton. Such performance analysis with a strong experimental component can serve as a baseline for researchers and industry towards exploiting the opportunities that existing MANO solutions provide.

This paper discusses the problem of powering a remote rural mobile base station using a standalone hybrid renewable energy system. A wind turbine and photovoltaic system are employed as the complementary power generation technologies, while the diesel generator serves as a backup power supply. A battery is required to reduce the impact of intermittency of renewable sources. On the consumption side, along with telecommunication electronic equipment, the consumption of cooling devices as a result of the ambient temperature, is also taken into account. The behavior of the base station in electrical and thermal terms is tested using the sequential Monte Carlo simulation. Adequate models have been used to generate wind, irradiance, and temperature input series, using the monthly averages for calibration, as the statistic information that is widely available in meteorological atlases, even for remote rural locations. The developed software provides all the variables of interest either in the form of chronological diagrams or probability histograms. The simulation platform can also be incorporated as a module of an algorithm for selection of optimal capacity of the generating system elements and for the optimal control of the cooling devices.

Condition monitoring is a fundamental technology that enables predictive maintenance of automation systems. However, as automation systems increase in complexity, the development of condition monitoring software becomes a challenging task that requires extensive knowledge from multiple engineering disciplines. In this context, the identification and specification of condition monitoring software requirements play a key role. Neglecting these tasks often results in costly problems during later stages of systems development. Currently, means to support interdisciplinary requirements engineering within condition monitoring software development are missing. In particular, there is a need for a systematic process that supports modeling condition monitoring requirements. In this paper, we present our solution - a profile based on the extension of the SysML, which is commonly used to engineer requirements in automation systems. The profile allows specification of condition monitoring software requirements and thus enables a more domain-specific requirements engineering approach. We illustrate this approach on a heat exchanger condition monitoring system, explain the particular modeling steps, and present lessons learned.

Aim To investigate quality of life and exposure to lifestyle risk factors of cancer patients in Bosnia and Herzegovina and a correlation of cancer type with lifestyle risk factors. Methods This was a cross-sectional study conducted on 200 cancer patients from the Clinical Centre of the University of Sarajevo. The respondents completed an anonymous questionnaire consisting of seven sections: basic patient information, physical activity, dietary habits including alternative medicine, tobacco use, alcohol consumption, anxiety, and comorbidities. Results A total of 150 (75%) patients were overweight with 113 (56%) of them being less physically active after the confirmed diagnosis. After the diagnosis, 79 (40%) patients ate less food, and 154 (77%) healthier; 130 (65%) reported consumption of alternative medicine and food supplements, 39 (30%) spent >1/4 of average monthly salary on these products. Majority never consumed alcohol, 135 (68%) and 101 (51%) patients reported history of tobacco use. Being obese was an independent predictor for colorectal carcinoma; being less obese was linked to a decreased risk of breast cancer diagnosis. Physical activity was linked to a decreased risk of lung cancer diagnosis. Many patients (122; 61%) reported having chronic comorbidities, mostly hypertension, while 44 (22%) patients were proven to be clinically anxious. Conclusion Our data suggest lack of public awareness of the consequences of unhealthy lifestyles. Risk factors such as alcohol consumption and tobacco use differed from other European countries. Significance of lifestyle changes after the diagnosis for reducing mortality and cancer recurrence requires further research. Prevention programs and more data are needed.

Aim To examine whether preoperative tumour size may serve as a biomarker for the occurrence of lymphovascular invasion (LVI) in centrally and peripherally located lung adenocarcinoma. Method The study included 261 patients surgically treated for diagnosed lung adenocarcinoma. A ROC curve was used to determine the biomarker potential of tumour size relative to the occurrence of LVI. Binary logistic regression was used to show changes of tumour size impact on the status of LVI. Result Tumour prevalence according to localization had no statistical significance (p=0.464), while the presence of LVI in central, as well as peripheral positions, was statistically significantly different (p<0.001). The area under the curve of 0.978 highlights the fact that tumour size is an excellent marker of the presence of LVI in centrally located adenocarcinomas of the lung. A similar finding was confirmed in peripherally located lung adenocarcinomas with an area below the curve of 0.943. Binary logistical regression showed that in centrally localized adenocarcinomas of the lung, each additional centimetre of tumour growth represents an increase in the likelihood of LVI+ by 17.14 times. In peripherally located adenocarcinomas of the lung, this increase in likelihood of LVI for each centimetre of growth was 5.46 times. Conclusion With a high degree of sensitivity and specificity, preoperative tumour size may serve as an important biomarker and positive predictor of the presence of LVI in lung adenocarcinoma of any location.

In this short demo paper, we introduce godash 2.0 godash is a headless HTTP adaptive streaming (HAS) video streaming platform written in the Google programming language GO. godash has been extensively rewritten for this release so as to provide ease of use, and a host of new features. godash includes options for eight different state of the art adaptive algorithms, five HAS profiles, four video codecs, the ability to stream audio and video segments, two transport protocols (TCP and QUIC), realtime output from five Quality of Experience (QoE) models, as well as a collaborative framework for the evaluation of cooperative HAS streaming. In this demo, we will introduce each of the options available in the godash configuration file, and illustrate examples of how to use the collaborative players using both godash on a native machine as well as godash within godashbed. godashbed is an integrated large-scale testbed framework for the evaluation of HAS streaming, which uses a virtual environment to serve video content locally (which allows setting security certificates) through the Mininet virtual emulation tool. In this manner, godash provides a framework for rapid deployment and testing of new HAS algorithms, QoE models and transport protocols.