This study presents a practical view of dynamic programming, specifically in the context of the application of finding the optimal solutions for the polygon triangulation problem. The problem of the optimal triangulation of polygon is considered to be as a recursive substructure. The basic idea of the constructed method lies in finding to an adequate way for a rapid generation of optimal triangulations and storing - them in as small as possible memory space. The upgraded method is based on a memoization technique, and its emphasis is in storing the results of the calculated values and returning the cached result when the same values again occur. The significance of the method is in the generation of the optimal triangulation for a large number of n. All the calculated weights in the triangulation process are stored and performed in the same table. Results processing and implementation of the method was carried out in the Java environment and the experimental results were compared with the square matrix and Hurtado-Noy method.

This study presents a practical view of dynamic programming, specifically in the context of the application of finding the optimal solutions for the polygon triangulation problem. The problem of the optimal triangulation of polygon is considered to be as a recursive substructure. The basic idea of the constructed method lies in finding to an adequate way for a rapid generation of optimal triangulations and storing - them in as small as possible memory space. The upgraded method is based on a memoization technique, and its emphasis is in storing the results of the calculated values and returning the cached result when the same values again occur. The significance of the method is in the generation of the optimal triangulation for a large number of n. All the calculated weights in the triangulation process are stored and performed in the same table. Results processing and implementation of the method was carried out in the Java environment and the experimental results were compared with the square matrix and Hurtado-Noy method.

BACKGROUND To explore corellation of anxiety, depression ant type of personality in inflammatory bowel disease (IBD) and compare with peptic ulcer (PU). SUBJECTS AND METHODS In this study, prevalence of anxiety, depression and type of personality was investigated in 362 cases divided into three groups: 112 of IBD patients, 122 of peptic ulcer patients and 128 of control group who didn't have any gastrointestinal or psychic complaints. IBD and peptic ulcer diagnosis were established by standard diagnostic procedures (anamnesis, clinical manifestations, laboratory, endoscopy and biopsy in IBD and upper endoscopy in peptic ulcer). Anxiety and depression were established by Hamilton anxiety rating scale (HAM-A) and Hamilton rating test for depression (HAM-D). Type of A/B personality was established by Bortner scale and D type of personality by Denollet scale (DS14). RESULTS Anxiety was found in 47 (41.9%) and depression in 44 (38.3%) of a total of 112 IBD cases. In group with peptic ulcer anxiety was found in 40 (32.8%) and depression aalso in 40 (32.8%) of total 122 cases. In control group anxiety was diagnosed in 21 (16.4%) and depression in 20 (15.6%) of total 128 cases. Anxiety and depresson were significantly higher in both groups than in control group but anxiety and depression were significantly higher in IBD group than peptic ulcer group. D type of personality was statistically significant in peptic ulcer group. CONCLUSION Anxiety and depression in IBD and peptic ulcer cases have a greater prevalence compared to the normal population and surprisingly are higher in IBD than peptic ulcer group. D type of personality is associated with peptic ulcer.

Summary In 2015, cholesterol deficiency (CD) was reported for the first time as a new recessive defect in Holstein cattle. After GWAS mapping and identification of a disease‐associated haplotype, a causative loss‐of‐function variant in APOB was identified. CD‐clinically affected APOB homozygotes showed poor development, intermittent diarrhea and hypocholesterolemia and, consequently, a limited life expectation. Herein, we present a collection of 18 cases clinically diagnosed as CD‐affected APOB heterozygotes. CD‐clinically affected heterozygotes show reduced cholesterol and triglyceride blood concentrations. The differences in total blood cholesterol and triglycerides between nine CD‐clinically affected and 36 non‐affected heterozygotes were significant. As only some APOB heterozygotes show the clinical CD phenotype, we assume that the penetrance is reduced in heterozygotes compared to the fully penetrant effect observed in homozygotes. We conclude that APOB‐associated CD represents most likely an incomplete dominant inherited metabolic disease with incomplete penetrance in heterozygotes.

Today's HTTP adaptive streaming applications are designed to provide high levels of Quality of Experience (QoE) across a wide range of network conditions. The adaptation logic in these applications typically needs an estimate of the future network bandwidth for quality decisions. This estimation, however, is challenging in cellular networks because of the inherent variability of bandwidth and latency due to factors like signal fading, variable load, and user mobility. In this paper, we exploit machine learning (ML) techniques on a range of radio channel metrics and throughput measurements from a commercial cellular network to improve the estimation accuracy and hence, streaming quality. We propose a novel summarization approach for input raw data samples. This approach reduces the 90th percentile of absolute prediction error from 54% to 13%. We evaluate our prediction engine in a trace-driven controlled lab environment using a popular Android video player (ExoPlayer) running on a stock mobile device and also validate it in the commercial cellular network. Our results show that the three tested adaptation algorithms register improvement across all QoE metrics when using prediction, with stall reduction up to 85% and bitrate switching reduction up to 40%, while maintaining or improving video quality. Finally, prediction improves the video QoE score by up to 33%.

Recent years have witnessed an explosion of multimedia traffic carried over the Internet. Video-on-demand and live streaming services are the most dominant services. To ensure growth, many streaming providers have invested considerable time and effort to keep pace with ever-increasing users' demand for better quality and stall abolition. HTTP adaptive streaming (HAS) algorithms are at the core of every major streaming provider service. Recent years have seen sustained development in HAS algorithms. Currently, to evaluate their proposed solutions, researchers need to create a framework and numerous state-of-the-art algorithms. Often, these frameworks lack flexibility and scalability, covering only a limited set of scenarios. To fill this gap, in this paper we propose DASHbed, a highly customizable real-time framework for testing HAS algorithms in a wireless environment. Due to its low memory requirement, DASHbed offers a means of running large-scale experiments with a hundred competing players. Finally, we supplement the proposed framework with a dataset consisting of results for five HAS algorithms tested in various evaluated scenarios. The dataset showcases the abilities of DASHbed and presents the adaptation metrics per segment in the generated content (such as switches, buffer-level, P. 1203.1 values, delivery rate, stall duration, etc.), which can be used as a baseline when researchers compare the output of their proposed algorithm against the state-of-the-art algorithms.

The adoption of design fiction into design research has recently been expanding within the HCI community. Design fiction workshops have fruitfully facilitated users and researchers discussing and creating future technologies by exposing differing viewpoints. Yet, most scholarship focuses on the ostensibly successful outputs of these workshops. It remains unclear exactly what sort of interaction dynamics are instigated by design fiction in collaborative design. How might design fiction affect what we consider in design, and how is this reflected in the ensuing design? To fill this gap, our study examines design fictions across five workshops where diverse participants created futuristic autobiographies, a method to elicit values, and built diegetic prototypes both individually and collaboratively. We detail their design processes and unpack three kinds of soft conflicts that arose between participants and allowed them to bring up and discuss differing values regarding technology in society. Reflecting on our workshops, we discuss their implications on how one might employ design fiction in collaborative design.

Quando queremos resolver um problema que envolva operações aritméticas, faz-se necessária uma identificação das quantidades envolvidas (contadas ou medidas), as quais chamamos de referentes. Assim, as operações de transformação de referente podem ser entendidas como uma composição de quantidades, gerando novas quantidades que podem ou não vir a ser novos referentes. Estas operações são de difícil entendimento para os alunos, e já existem algumas indicações que nos permitem dizer que o mesmo acontece com os professores. Em geral, os alu-

Abstract Subjects (n=13) did 30 workouts with their left leg on an Inertial Exercise Trainer (IET), while their right leg served as an untreated control. Before and after the 30 workouts, they underwent isokinetic strength tests (knee and ankle extensors of both legs) whose peak torque (PT), time to PT (TTPT), and rate of torque development (RTD) values were each analyzed with 2(leg)×2(time)×3(velocity) analysis of variances (ANOVAs), with repeated measures per independent variable. Peak force (PF) and total work (TW) data were measured from each IET workout, and they represent time course strength changes produced by our exercise intervention. PF and TW values for the three IET exercises that comprised each workout were each analyzed with one-way ANOVAs with time as the independent variable. Results included significant ankle and knee extensor PT increases, whereby the left leg achieved higher values at posttesting, but there were no significant TTPT changes and a time effect for ankle extensor RTD. Our data show that PF and TW each had significant increases over time, with the latter exhibiting greater gains over the 30-workout intervention. Our results imply that the IET yields strength gains over time comparable to standard resistive exercise hardware.

Background: Right ventricular dysfunction (RVD) is a well-known predictor of early death in patients with acute pulmonary embolism and thus early identification of RVD is critical in the risk stratification or management of acute pulmonary embolism (PE). Aim of this study was to investigate a useful role of cardiac biomarker NTproBNP for predicting echocardiographic right ventricular dysfunction in patients with acute pulmonary embolism. Methods: A retrospective analysis was performed in 195 consecutive adult patients with pulmonary embolism from the Serbian University Pulmonary Embolism Registry (SUPER 2015-2019) created by six university clinics: Military Medical Academy (Belgrade), Institute of Pulmonary Diseases (Sremska Kamenica), Clinical Center (Nis), University Clinic Zvezdara, Clinical Center (Kragujevac) and University Clinical Centre of Republic of Srpska (Banja Luka). All patients were divided into RVD group and non-RVD group according to whether there was increase in systolic pressure in right ventricle (>40mmHg) on echocardiography. Odds ratios (OR) and 95% confidence intervals (CI) assessing the risk factors for RVD were assessed by multivariate logistic regression. The ability of the NT proBNP in predicting the RVD was described by the Receiving Operating Curves analysis. Results: The mean age is a strong predictor of echocardiographic RVD in patients with PE. The simple measurements of this cardiac biomarker could be helpful in clinical decision-making or risk stratification in patients with PE.