This manuscript aims to propose a new extension of the EDAS method, adapted for usage with single-valued neutrosophic numbers. By using single-valued neutrosophic numbers, the EDAS method can be more efficient for solving complex problems whose solution requires assessment and prediction, because truth- and falsity-membership functions can be used for expressing the level of satisfaction and dissatisfaction about an attitude. In addition, the indeterminacy-membership function can be used to point out the reliability of the information given with truth- and falsity-membership functions. Thus, the proposed extension of the EDAS method allows the use of a smaller number of complex evaluation criteria. The suitability and applicability of the proposed approach are presented through three illustrative examples.

To develop and validate new Juvenile Arthritis Disease Activity Score 10 (JADAS10) and clinical JADAS10 (cJADAS10) cutoffs to separate the states of inactive disease (ID), minimal disease activity (MiDA), moderate disease activity (MoDA), and high disease activity (HDA) in children with oligoarthritis and with rheumatoid factor–negative polyarthritis, based on subjective disease assessment by the treating pediatric rheumatologist.

Adult shipworms (Bivalvia, Teredinidae) have greatly elongate bodies, and thus, the organs have a different orientation than those of other bivalves. Studies on the anatomy of the digestive system have been carried out in a number of genera and species in the Teredinidae, but are now over 50 years old and most were carried in only a few preserved specimens. These studies contain descriptions and line drawings, but high-resolution images do not exist, except for Lyrodus pedicellatus that was recently studied using modern techniques. Thus, we present high-resolution images of fresh specimens of three teredinid species, representing three genera, to show the different features of each organ of the digestive tract and intra- and inter-specific differences. Most of our observations concur with, but some differ from previous descriptions. One observation in Teredo navalis showed, for the first time, the foot covered by a membrane with corrugated aspect, which the function is not yet understood. Another observation in the same species showed that the caecum and intestine have strikingly different colourations in specimens in overcrowded conditions when compared with those in uncrowded conditions. This may indicate that the former resort more to filter feeding to avoid the complete destruction of their habitat. In Psiloteredo megotara, the digestive gland seems to cover the caecum, as it does in Nototeredo norvagica and differing from a previous line drawing for the former species. Faecal pellets were observed in N. norvagica and P. megotara, which may indicate a more complete utilization of wood in these species.

Background Environmental exposures such as smoking are widely recognized risk factors in the emergence of lung diseases including lung cancer and acute respiratory distress syndrome (ARDS). However, the strength of environmental exposures is difficult to measure, making it challenging to understand their impacts. On the other hand, some COVID-19 patients develop ARDS in an unfavorable disease progression and smoking has been suggested as a potential risk factor among others. Yet initial studies on COVID-19 cases reported contradictory results on the effects of smoking on the disease – some suggest that smoking might have a protective effect against it while other studies report an increased risk. A better understanding of how the exposure to smoking and other environmental factors affect biological processes relevant to SARS-CoV-2 infection and unfavorable disease progression is needed. Approach In this study, we utilize mutational signatures associated with environmental factors as sensors of their exposure level. Many environmental factors including smoking are mutagenic and leave characteristic patterns of mutations, called mutational signatures, in affected genomes. We postulated that analyzing mutational signatures, combined with gene expression, can shed light on the impact of the mutagenic environmental factors to the biological processes. In particular, we utilized mutational signatures from lung adenocarcinoma (LUAD) data set collected in TCGA to investigate the role of environmental factors in COVID-19 vulnerabilities. Integrating mutational signatures with gene expression in normal tissues and using a pathway level analysis, we examined how the exposure to smoking and other mutagenic environmental factors affects the infectivity of the virus and disease progression. Results By delineating changes associated with smoking in pathway-level gene expression and cell type proportions, our study demonstrates that mutational signatures can be utilized to study the impact of exogenous mutagenic factors on them. Consistent with previous findings, our analysis showed that smoking mutational signature (SBS4) is associated with activation of cytokine-mediated signaling pathways, leading to inflammatory responses. Smoking related changes in cell composition were also observed, including the correlation of SBS4 with the expansion of goblet cells. On the other hand, increased basal cells and decreased ciliated cells in proportion were associated with the strength of a different mutational signature (SBS5), which is present abundantly but not exclusively in smokers. In addition, we found that smoking increases the expression levels of genes that are up-regulated in severe COVID-19 cases. Jointly, these results suggest an unfavorable impact of smoking on the disease progression and also provide novel findings on how smoking impacts biological processes in lung.

The aim of this study was to determine the antioxidant activity, total phenolics, total flavonoid, proanthocyanidins, and anthocyanins content of eight berry species, namely serviceberry, gooseberry, blackberry, black chokeberry, bilberry, red currant, black currant, and cornelian cherry harvested in the regions of Sarajevo and Tuzla, Bosnia and Herzegovina. The antioxidant activity was determined by a battery of in vitro tests including DPPH radical assay, FRAP assay, ABTS assay, and phosphomolybdate test for total antioxidant capacity. Total phenolics, total flavonoids, and proanthocyanidins ranged from 0.834 to 6.921 mg TAE (tannic acid equivalents), 0.081–0.673 mg of quercetin, and 0.162–3.247 mg of catechin per gram of fresh fruit, respectively. The water extract of fruits had considerable levels of tested constituents and antioxidant activity, with the highest results obtained for black chokeberry. The multivariate clustering analysis showed that water extracts of analyzed species of berries belong to four distinct types in terms of their antioxidants levels and antioxidant activity. Furthermore, these results support the opinion that employment of multiple antioxidant tests is indeed required for adequate in vitro assessment of antioxidant capacity. Results also emphasized the need for a more detailed evaluation of the fruit species with good antioxidant potential (relative to standards), such as cornelian cherry and gooseberry, which are abundant yet not frequently consumed in Bosnia and Herzegovina.

This study explored how women breast cancer survivors who underwent radical mastectomy experienced stress and adversity and managed their diagnosis and treatment. This study is based on semi-structured and in-depth interviews with a convenience sample of 22 participants. Qualitative analysis and discussion groups were conducted in the participant’s homes over 18 months. Thematic analysis resulted in four overarching categories that illustrated how being a woman was challenged and restructured from the participants’ personal experiences. The participants’ coping strategies were primarily reflected in their spirituality, optimism, the embrace of healthy lifestyles, and pink ribbon activism.

BACKGROUND The Prostate Biopsy Collaborative Group risk calculator (PBCG RC) has a moderate discriminatory capability. This study aimed to create automated machine learning (AutoML) PBCG RC for predicting the probability of any-grade and high-grade prostate cancer (PCa). METHODS This retrospective, single-center study was carried out using the database with 832 patients who were subject to transrectal ultrasound-guided prostate biopsy with prostate-specific antigen (PSA) values from 2 to 50 ng/ml. Information about PBCG RC predictors was gathered for all patients. We used H2O, as an open-source platform for AutoML, where the set of 20 base learning algorithms were trained. The AutoML PBCG RC was compared in terms of discrimination, calibration, and clinical utility with the original PBCG RC. RESULTS PCa was detected in 341 (41%) men, and 159 (19.1%) of them had high-grade PCa. Our AutoML models demonstrated better discriminative ability than the original PBCG RC for detection of PCa (area under the curve [AUC]: 0.703 vs 0.628; P = 0.023) and high-grade PCa (AUC: 0.990 vs 0.717; P < 0.001). The decision curve analyses showed that AutoML models performed better. For high-grade PCa the PSA was the most important feature. CONCLUSIONS We applied ensemble techniques to create a freely available online PCa risk tool based on PBCG RC predictors and AutoML algorithms. The AutoML models drastically improved original model performance and the predictions of high-grade PCa were nearly perfect. However, new models should be used with a reserve, because external validation has not been performed yet.

This paper focuses on reviewing relevant work on autonomous ground systems for concrete bridge inspection. The current inspection of bridges is still based on visual inspection by inspectors or by using semi-destructive techniques. Current inspection practices require a large amount of time for inspection. In addition, complex scaffolding or expensive equipment is required for inaccessible areas, which also poses a risk to the safety of inspectors. These drawbacks could be overcome by using robotic systems equipped with non-destructive techniques (NDT). This paper presents the ground robotic systems that have been used in the inspection of concrete bridges, mainly for the localization of reinforcement, corrosion assessment and crack detection.

This paper represents a solution to the problem of automatization of a web page robustness score grading. Robustness of a web page is best defined as a property of a specific web page to keep its layout and style of elements after applying different modifications. The rapid development of web pages has enabled a quick creation of numerous web pages, but the question is what is the quality of those web pages in terms of robustness. Automatic grading enables a relatively fast way of creating a metric in terms of the score that specific web pages get after being tested for the level of robustness. The research framework consists of different technologies and concepts that have been used during the implementation of a practical solution. The paper describes data structures that have been used to represent web pages as well as the machine learning methods such as neural networks, used to calculate the robustness score.

With the arrival of COVID-19 pandemic in March of 2020 the first lock-down and closing of schools and faculties occurred. Educational institutions had to find a solution overnight. To ensure the continuity of schooling was a great challenge, the strategy of the faculties has only indicated digital transformation, and a small number of faculty staff was ready to face this new situation (according to the research had already been carried out). Teachers that had already used digital technologies and e-learning found it easier to form their classes in online environment that they were already familiar with. But those teachers that have never done so, found themselves facing a great challenge. Faced with the inability to hold classes in a traditional classroom way, they were challenged to quickly transition to online environment and ensure the completion of the academic year. With the arrival of the new academic year, the return to the classic way of classes was expected, but this did not completely occur. The pandemic did not cease and again higher education institutions face closing and classes are more and more held remotely. Levels of preparation and experience of teachers and students at the University of Mostar differ greatly. This paper has a goal of presenting experiences and needs of the teachers of the Faculty of Humanities and Social Sciences and ascertaining how these experiences can be, and how much they have been used relating to the situation we find ourselves in again.

This paper deals with the development of control software for a remotely operated vehicle (ROV) as part of an automated fish cage inspection system in aquaculture. The ROV navigates autonomously around the fish cages streaming video to the topside computer that runs the algorithms for vertical rope detection. The topside computer sends back the velocity references to the ROV in real-time in order to successfully complete the inspection task. These images are also used to determine the state of net biofouling using a pre-trained convolutional neural network to help determine which nets are in need of cleaning. Robot Operating System (ROS) framework is developed to enable the topside computer to access the video stream from the ROV, process the images, and send back velocity references that would result in the complete inspection of fish cages. The inspection task is planned by following the recognizable rope segments of the outer structure of the fish cage downwards by controlling the vehicle's yaw, heave, and depth.

In today's digital age, presence on the Internet and the Web mean presence in general life. This is generally more pronounced in the context of higher education because these institutions are the primary drivers of overall social development. The quality and highly accessible website of each university is a must as these websites are generally the first contact and first impression for new potential students and also the first step for establishing cooperation with the social economy and society. For this reason, websites need to meet some of the basic standards when it comes to accessibility of the content they provide and it is essential to ensure that content on the websites can be accessed by people with disabilities. This paper deals with the analysis of websites of universities in Bosnia and Herzegovina in the context of their accessibility, from one side, and their position on the international scene in the context of the Webometrics list of universities, on the other side. Based on the obtained results and conducted analysis, recommendations were given on how to improve some of the elements on websites in order to make these websites more accessible in accordance with the standards related to this topic.

The vehicle routing problem is one of the most complex problems in the field of combinatorial optimization. Creating optimal routes leads to timely delivery of orders to end customers, which increases the efficiency of the company and enables maximum earnings. The problem of vehicle routing with a series of real-world constraints is called the rich vehicle routing problem (RVRP). The paper presents an approach to solving RVRP, where the asymmetric routing problem with a heterogeneous vehicle fleet, time windows, customer-vehicle constraints and a number of others is observed. The approach solves the problem in two phases, by dividing customers into clusters using a discrete metaheuristic Bat algorithm, and by solving the routing problem for each obtained cluster. The proposed approach has been tested for 26 days of delivery from large warehouses in Bosnia and Herzegovina. Significant savings were achieved compared to previously implemented approaches. All created routes were feasible. The approach automatically creates routes, and gives results in a shorter time than previously used approaches. Time does not increase significantly with the increase in the number of customers, which is a great advantage of the proposed approach.