Anaemia in juvenile chronic arthritis

Brush border myosin-I (BBMI) is a single-headed unconventional myosin found in the microvilli of intestinal epithelial cells, where it links the core bundle of actin filaments to the plasma membrane. An association of BBMI with anionic phospholipids has been shown to be mediated by a carboxy-terminal domain which is rich in basic amino acids. We have exploited this natural affinity of BBMI for negatively charged lipids to form two-dimensional (2D) crystals of this protein which are suitable for structural analysis by electron crystallographic techniques. The 2D crystals which we have obtained belong to one of two space groups, p22121 or p2. We present here projection maps calculated from images of negatively stained crystals for each of these crystal types to a resolution of 20 A and show that the asymmetric unit is the same in both crystal types.     

Sr2+–Mg2+-Doped SiAlON Ceramics

In the present work, multi-cation-doped (Sr²⁺–Mg²⁺) SiAlON ceramics were investigated. MgO and SrO were used in 100:0 and 50:50 molar ratios. The mixture was sintered at 1800° and 1830°C for 1 h in a gas pressure-sintering furnace. The results showed that sintered samples were composed of mainly α- and β-SiAlON phases and small amounts of some Sr-containing phases and SiAlON polytypes. According to Rietveld analysis of X-ray diffraction patterns, Mg is incorporated into the α-SiAlON structure. However, the incorporation of Sr is limited.     

Interface feature prioritization for web services: Case of online flight reservations

Acceptance, utility, and usability of system designs have become a focal interest in human–computer interaction (HCI) research, yet at present there is a lack detailed understandings of which system design features influence them. The purpose of the study is to examine the effects of five product design features; customization, adaptive behavior, memory load, content density, and speed on user preference through an experimental study by using conjoint analysis. In experimental study, instead of classical conjoint cards, prototypes were generated for products. Besides, desirability and market segments of product prototypes were identified. In line with the results, among the five product design features, speed is the most and customization is the least important features that affect user preference. Contrary to the expectations, customization has a relatively small importance value in this research. Subsequent design features that influence user preference after speed are minimal memory load, adaptive behavior, and content density, respectively. According to findings, interfaces that have high-speed, minimal memory load, adaptive behavior, low content density, and customization features are more preferable than those that do not.     

Output-associative RVM regression for dimensional and continuous emotion prediction

Many problems in machine learning and computer vision consist of predicting multi-dimensional output vectors given a specific set of input features. In many of these problems, there exist inherent temporal and spatial dependencies between the output vectors, as well as repeating output patterns and input–output associations, that can provide more robust and accurate predictors when modeled properly. With this intrinsic motivation, we propose a novel Output-Associative Relevance Vector Machine (OA-RVM) regression framework that augments the traditional RVM regression by being able to learn non-linear input and output dependencies. Instead of depending solely on the input patterns, OA-RVM models output covariances within a predefined temporal window, thus capturing past, current and future context. As a result, output patterns manifested in the training data are captured within a formal probabilistic framework, and subsequently used during inference. As a proof of concept, we target the highly challenging problem of dimensional and continuous prediction of emotions, and evaluate the proposed framework by focusing on the case of multiple nonverbal cues, namely facial expressions, shoulder movements and audio cues. We demonstrate the advantages of the proposed OA-RVM regression by performing subject-independent evaluation using the SAL database that constitutes naturalistic conversational interactions. The experimental results show that OA-RVM regression outperforms the traditional RVM and SVM regression approaches in terms of accuracy of the prediction (evaluated using the Root Mean Squared Error) and structure of the prediction (evaluated using the correlation coefficient), generating more accurate and robust prediction models.     

Prioritization methodology of dangerous substances for water quality monitoring with scarce data

Monitoring and control of dangerous substances discharged into receiving waters have attracted more attention lately. Since it is not possible to analyze every single substance, a prioritization methodology is needed for the selection of those to be monitored. Existing well-developed models require significant amount of data for reliable outcomes. This paper presents a methodology to prioritize the dangerous substances having adverse effects on freshwaters in Turkey, where data are scarce. Such a methodology will also serve as a solid model for other countries with limited background data. The adopted methodology enabled the elimination of chemicals to generate a candidate list composed of 608 substances among more than 5000 substances. Further screening and prioritization were conducted using different assessment methods (i.e., Total Hazard Value, Total Impact Value, Combined Monitoring-based, and Modelling-based Priority Setting) to obtain a proposed Final Candidate Specific Pollutants List of 150 dangerous substances. The proposed Candidate National Pollutant List of Turkey was established by combining 45 priority pollutants of the European Union with a list of candidate specific pollutants. According to the outcomes of this study, monitoring and controlling of 195 dangerous substances in freshwaters are recommended. Further detailed studies should be conducted in order to observe the actual levels of these dangerous substances in freshwaters followed by a review of the monitoring list accordingly. Moreover, further revisions might be required in the proposed list due to some possible versatile conditions in terms of sampling points (i.e., change in the location of industries).     

Defecting From the Gutenberg Legacy: Employing Images to Test Knowledge Gaps

Education‐based knowledge gaps are well‐documented across countries, media platforms, and content. Without exception, knowledge is measured through words not images. Given the centrality of sight in the natural history of Homo sapiens, the extraordinary visual acuity of humans, and the proliferation of screen‐based visual media environments in contemporary life, an experiment was conducted to test the knowledge gap visually. Participants watched 8 audiovisual news stories. Simple recognition of story details and comprehension of that information were tested in verbal and visual modalities. Results offered the first confirmation of the knowledge gap in visual terms. Yet, gaps were significantly smaller employing visual than verbal measures, pointing to the need for continued efforts to develop visual measures for future memory studies.     

Surface-modified alumina nanoparticles-filled aramid fiber-reinforced epoxy nanocomposites: preparation and mechanical properties

Iranian Polymer Journal - Surface of Al2O3 nanoparticles was modified with a silane coupling agent, and aramid fiber-reinforced epoxy nanocomposites were produced using these particles. Three...     

Effect of Deep Cryogenic Treatment on Wear Resistance of AISI 52100 Bearing Steel

In this study, the effects of deep cryogenic treatment (DCT) on the wear resistance of AISI 52100 bearing steel were investigated. For this purpose, a number of bearing steel samples were held for different times (12, 24, 36, 48, 60 h) at deep cryogenic temperatures (?145 °C). The wear experiments were carried out in a ball–disk arrangement, by applying loads of 10 and 20 N and a sliding velocity of 0.15 m/s. After conducting the experimental studies, 36 h was found to be the optimal holding time. At this holding time, the wear rate and friction coefficient were decreased, while the hardness reached to maximum values. It was observed that DCT led to significant microstructural changes, which resulted in improved tribological properties.