BackgroundThe effectiveness trial “Stress echo (SE) 2020” evaluates novel applications of SE in and beyond coronary artery disease. The core protocol also includes 4-site simplified scan of B-lines by lung ultrasound, useful to assess pulmonary congestion.PurposeTo provide web-based upstream quality control and harmonization of B-lines reading criteria.Methods60 readers (all previously accredited for regional wall motion, 53 B-lines naive) from 52 centers of 16 countries of SE 2020 network read a set of 20 lung ultrasound video-clips selected by the Pisa lab serving as reference standard, after taking an obligatory web-based learning 2-h module (http://se2020.altervista.org). Each test clip was scored for B-lines from 0 (black lung, A-lines, no B-lines) to 10 (white lung, coalescing B-lines). The diagnostic gold standard was the concordant assessment of two experienced readers of the Pisa lab. The answer of the reader was considered correct if concordant with reference standard reading ±1 (for instance, reference standard reading of 5 B-lines; correct answer 4, 5, or 6). The a priori determined pass threshold was 18/20 (≥ 90%) with R value (intra-class correlation coefficient) between reference standard and recruiting center) > 0.90. Inter-observer agreement was assessed with intra-class correlation coefficient statistics.ResultsAll 60 readers were successfully accredited: 26 (43%) on first, 24 (40%) on second, and 10 (17%) on third attempt. The average diagnostic accuracy of the 60 accredited readers was 95%, with R value of 0.95 compared to reference standard reading. The 53 B-lines naive scored similarly to the 7 B-lines expert on first attempt (90 versus 95%, p = NS). Compared to the step-1 of quality control for regional wall motion abnormalities, the mean reading time per attempt was shorter (17 ± 3 vs 29 ± 12 min, p < .01), the first attempt success rate was higher (43 vs 28%, p < 0.01), and the drop-out of readers smaller (0 vs 28%, p < .01).ConclusionsWeb-based learning is highly effective for teaching and harmonizing B-lines reading. Echocardiographers without previous experience with B-lines learn quickly.

Abstract Meningiomas are the second most common neoplasm in the cerebellopontine angle (CPA), and are challenging lesions to treat surgically. With significant refinements in surgical techniques, operative morbidity, and mortality have been substantially reduced. Total or near-total surgical resection can be accomplished in the majority of cases via appropriately selected approaches, and with acceptable morbidity. In this video, we present a 51-year-old woman, who had a 2-year history of vertigo with symptoms that progressed over time. She presented with blurry vision, sensorineural hearing loss, tinnitus, left-sided facial numbness, and double vision. Magnetic resonance imaging (MRI) showed a left-sided homogeneously enhancing mass at CPA with a supratentorial extension. MRI appearance was consistent with a CPA meningioma with supratentorial extension. The patient underwent surgical resection via a retrosigmoid approach. Suprameatal drilling and tentorial sectioning were necessary to achieve gross total resection. The surgery and postoperative course were uneventful. The histopathology was a WHO (world health organization) grade I meningioma. MRI showed gross total resection of the tumor. After a 1.5-year follow-up, the patient is continuing to do well with no residual or recurrent disease. In this video, microsurgical techniques and important steps for the resection of this challenging meningioma of the cerebellopontine angle are demonstrated. The link to the video can be found at: https://youtu.be/CDto52GxrG4.

Background/Aim: Pulmonary function tests are used for screening respiratory insufficiency in patients with myotonic dystrophy (DM). We analysed the agreement between two different approaches in assessment of abnormal findings of forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), maximal inspiratory pressure (MIP) and maximal expiratory pressure (MEP), in DM patients. Methods: We used Cohen’s κ- and Bangdiwala’s B- statistic to compare the agreement between different cut-off values recommended by experts (ENMC) and the cut-off values based on the reference range (RR). We further analysed their sensitivity (Sn) and specificity (Sp) in detecting symptoms associated with respiratory insufficiency. Results: The observed agreement was: 1) for FVC: κ= –0.002, B = 0.406; 2) for FEV1: κ= 0.944, B = 0.946; 3) for MIP: κ= 0.625, B = 0.674; and 4) for MEP: κ= 0.241, B = 0.373. Overall, RR cut-off values showed higher sensitivity, whereas the ENMC values showed higher specificity in detecting symptoms of respiratory involvement. Conclusions: The two approaches showed perfect agreement in assessment of FEV1, substantial agreement for MIP, and weak agreement for FVC and MEP. RR is an established method of assessment for spirometry and should be favoured because it takes variability within the population into account. Further development and validation of regression equations for RR calculations of predicted maximal respiratory pressures, with corresponding lower limits of normal, is required. The B statistic is more robust in assessing agreement between two diagnostic methods, resolving the issue of the κ paradox.

Biomaterial strategies focused on designing scaffolds with physiologically relevant gradients provide a promising means for elucidating 3D vascular cell responses to spatial and temporal variations in matrix properties. In this study, we present a photopolymerization approach, ascending photofrontal free-radical polymerization, to generate proteolytically degradable hydrogel scaffolds of poly(ethylene) glycol with tunable continuous gradients of (1) elastic modulus (slope of 80 Pa/mm) and uniform immobilized RGD concentration (2.06 ± 0.12 mM) and (2) immobilized concentration of the RGD cell-adhesion peptide ligand (slope of 58.8 μM/mm) and uniform elastic modulus (597 ± 22 Pa). Using a coculture model of vascular sprouting, scaffolds embedded with gradients of elastic modulus induced increases in the number of vascular sprouts in the opposing gradient direction, whereas RGD gradient scaffolds promoted increases in the length of vascular sprouts toward the gradient. Furthermore, increases in vascular sprout length were found to be prominent in regions containing higher immobilized RGD concentration.

The regulation of functions such as respiratory or heart rate in human body as well as the control of motor movements are under the control of nervous system. As these actions and correlated tasks are directly influenced by the brain, the brain monitoring gives the possibility to differentiate the tasks, enabling at the same time the prediction of further actions. In this contribution, publicly available electroencephalography (EEG) datasets are analyzed with respect to the detection of epileptic seizure occurrence and BCI-related actions (here: cued motor imagery). For these purposes, timefrequency- based feature extraction alongside different classification methods is used. To perform the classification, Artificial Neural Network (ANN) and Support Vector Machine (SVM) are utilized and compared with previously obtained results. The feasibility of particular features for the detection of epileptic seizures and BCI-related tasks is discussed. Four different feature vectors per analyzed problem are identified. Acceptable accuracy of classification using ANN- and SVMbased classifiers is achieved using identified feature vectors.

BACKGROUND: AFP serum levels are considered as diagnostic and specific for hepatocellular carcinoma (HCC) in patients with liver cirrhosis (LC). AIM: This study aimed to examine the diagnostic value of AFP in the distinguishing of patients with HCC from patients with LC, and to analyse the potential correlation between AFP levels and liver disease stages. MATERIAL AND METHODS: Fifty patients with LC and fifty patients with HCC were included in this study. The majority of the patients were males, while the HBV aetiology was dominant. RESULTS: Significant differences between LC and HCC patients were detected for AST, ALT, GGT, bilirubin, AFP and AP. Patients with HCC had higher AFP values compared to LC. There was no significant correlation between the size of the tumour lesion and serum AFP levels. A positive correlation between AFP concentration and GGT activity was determined, as was the negative correlation between AFP and age of the subjects. The AFP value of 23.34 ng/m showed high sensitivity (84%) and specificity (82%). CONCLUSION: The size of the surface below the ROC curve (AUC) was 0.877 (0.80-0.95), which makes AFP a good biomarker and this diagnostic test is sufficient to separate patients with HCC and LC.

Methods and metrics for studying interactions between automated vehicles and other road users in their vicinity, such as pedestrians, cyclists and non-automated vehicles, are not established yet. This workshop focuses on identifying the strengths and weaknesses of various methodologies that could potentially be used to study such interactions. The objective lies in determining the proper experimental design, sensitivity of metrics for measuring user behavior, ecological validity, generalizability of findings, extraction of insights regarding how findings can be translated into actionable requirements, and the alternatives for conducting longitudinal field studies. It will be of an interactive nature and involve hands-on activities. The workshop will consolidate existing knowledge, identify recurring issues, and explore the path towards resolving these issues. The outcome will be compiled into a paper to share this valuable knowledge with a broader research community.

Queuing systems (QS) represent everyday life in all business and economic systems. On the one hand, and there is a tendency for their time and cost optimization, but on the other hand, they have not been sufficiently explored. This especially applies to logistics systems, where a large number of transportation and storage units appear. Therefore, the aim of this paper is to develop an ANFIS (Adaptive neuro-fuzzy inference system) model in a warehouse system with two servers for defining QS optimization parameters. The research was conducted in a company for the manufacturing of brown paper located in the territory of Bosnia and Herzegovina, which represents a significant share of the total export production of the country. In this paper, the optimization criterion is the time spent in the system, which is important both from the aspect of all customers of the system, and from that of the owner of the company. The time criterion directly affects the efficiency of the system, but also the overall costs that this system causes. The developed ANFIS model was compared with a mathematical model through a sensitivity analysis. The mathematical model showed outstanding results, which justifies its development and application.

School of Medicine, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Department of Pathology, Clinical Center, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Department of Radiology, Clinical Center, University of Sarajevo, Sarajevo, Bosnia and Herzegovina Department of Oncology, Clinical Center, University of Sarajevo, Sarajevo, Bosnia and Herzegovina College of Medicine, Qatar University, Doha, Qatar

This paper studies the behavior of singularly perturbed nonlinear differential equations with boundary-layer solutions that do not necessarily converge to an equilibrium. Using the average of the fast variable and assuming the boundary layer solutions converge to a bounded set, results on the closeness of solutions of the singularly perturbed system to the solutions of the reduced average and boundary layer systems over a finite time interval are presented. The closeness of solutions error is shown to be of order $\mathcal{O} (\sqrt{\varepsilon})$, where $\varepsilon$ is the perturbation parameter.

Organizations can improve efficiency of process execution through a correct resource allocation, as well as increase income, improve client satisfaction, and so on. This work presents a novel approach for solving problems of resource allocation in business processes which combines process mining, statistical techniques, and metaheuristic algorithms for optimization. In order to get more reliable results of the simulation, in this paper, we use process mining analysis and statistical techniques for building a simulation model. For finding optimal human resource allocation in business processes, we use the improved differential evolution algorithm with population adaptation. Because of the use of a stochastic simulation model, noise appears in the output of the model. The differential evolution algorithm is modified in order to include uncertainty in the fitness function. In the end, validation of the model was done on three different data sets in order to demonstrate the generality of the approach, and the comparison with the standard approach from the literature was done. The results have shown that this novel approach gives solutions which are better than the existing model from literature.