The Use of Molecular Dynamics Simulation Method to Quantitatively Evaluate the Affinity between HBV Antigen T Cell Epitope Peptides and HLA-A Molecules

Chronic hepatitis B virus (HBV), a potentially life-threatening liver disease, makes people vulnerable to serious diseases such as cancer. T lymphocytes play a crucial role in clearing HBV virus, while the pathway depends on the strong binding of T cell epitope peptide and HLA. However, the experimental identification of HLA-restricted HBV antigenic peptides is extremely time-consuming. In this study, we provide a novel prediction strategy based on structure to assess the affinity between the HBV antigenic peptide and HLA molecule. We used residue scanning, peptide docking and molecular dynamics methods to obtain the molecular docking model of HBV peptide and HLA, and then adopted the MM-GBSA method to calculate the binding affinity of the HBV peptide–HLA complex. Overall, we collected 59 structures of HLA-A from Protein Data Bank, and finally obtained 352 numerical affinity results to figure out the optimal bind choice between the HLA-A molecules and 45 HBV T cell epitope peptides. The results were highly consistent with the qualitative affinity level determined by the competitive peptide binding assay, which confirmed that our affinity prediction process based on an HLA structure is accurate and also proved that the homologous modeling strategy for HLA-A molecules in this study was reliable. Hence, our work highlights an effective way by which to predict and screen for HLA-peptide binding that would improve the treatment of HBV infection.     

STN7 Kinase Is Essential for Arabidopsis thaliana Fitness under Prolonged Darkness but Not under Dark-Chilling Conditions

Reversible phosphorylation of photosystem II light harvesting complexes (LHCII) is a well-established protective mechanism enabling efficient response to changing light conditions. However, changes in LHCII phosphorylation were also observed in response to abiotic stress regardless of photoperiod. This study aimed to investigate the impact of dark-chilling on LHCII phosphorylation pattern in chilling-tolerant Arabidopsis thaliana and to check whether the disturbed LHCII phosphorylation process will impact the response of Arabidopsis to the dark-chilling conditions. We analyzed the pattern of LHCII phosphorylation, the organization of chlorophyll–protein complexes, and the level of chilling tolerance by combining biochemical and spectroscopy techniques under dark-chilling and dark conditions in Arabidopsis mutants with disrupted LHCII phosphorylation. Our results show that during dark-chilling, LHCII phosphorylation decreased in all examined plant lines and that no significant differences in dark-chilling response were registered in tested lines. Interestingly, after 24 h of darkness, a high increase in LHCII phosphorylation was observed, co-occurring with a significant F_V/F_M parameter decrease. The highest drop of F_V/F_M was detected in the stn7-1 line–mutant, where the LHCII is not phosphorylated, due to the lack of STN7 kinase. Our results imply that STN7 kinase activity is important for mitigating the adverse effects of prolonged darkness.     

Video game training to improve selective visual attention in older adults

The current study investigated the effect of video game training on older adult’s useful field of view performance (the UFOV® test). Fifty-eight older adult participants were randomized to receive practice with the target action game (Medal of Honor), a placebo control arcade game (Tetris), a clinically validated UFOV training program, or into a no contact control group. Examining pretest–posttest change in selective visual attention, the UFOV improved significantly more than the game groups; all three intervention groups improved significantly more than no-contact controls. There was a lack of difference between the two game conditions, differing from findings with younger adults. Discussion considers whether games posing less challenge might still be effective interventions for elders, and whether optimal training dosages should be higher.     

Automatic word naming recognition for an on-line aphasia treatment system

One of the most common effects among aphasia patients is the difficulty to recall names or words. Typically, word retrieval problems can be treated through word naming therapeutic exercises. In fact, the frequency and the intensity of speech therapy are key factors in the recovery of lost communication functionalities. In this sense, speech and language technology can have a relevant contribution in the development of automatic therapy methods. In this work, we present an on-line system designed to behave as a virtual therapist incorporating automatic speech recognition technology that permits aphasia patients to perform word naming training exercises. We focus on the study of the automatic word naming detector module and on its utility for both global evaluation and treatment. For that purpose, a database consisting of word naming therapy sessions of aphasic Portuguese native speakers has been collected. In spite of the different patient characteristics and speech quality conditions of the collected data, encouraging results have been obtained thanks to a calibration method that makes use of the patients’ word naming ability to automatically adapt to the patients’ speech particularities.     

Similarity reasoning for the semantic web based on fuzzy concept lattices: An informal approach

Similarity Reasoning in the presence of vague information is becoming fundamental in several research areas and, in particular, in the Semantic Web. Fuzzy Formal Concept Analysis (FFCA) is a generalization of Formal Concept Analysis (FCA) for modeling uncertainty information. Although FFCA has become very interesting for supporting different activities for the development of the Semantic Web, in the literature it is usually addressed at a technical level and intended for a restricted audience. This paper proposes a similarity measure for FFCA concepts. The key notions underlying the proposed approach are presented informally, in order to reach a broad audience of readers.     

Compact DSOP and Partial DSOP Forms

Given a Boolean function f on n variables, a Disjoint Sum-of-Products (DSOP) of f is a set of products (ANDs) of subsets of literals whose sum (OR) equals f, such that no two products cover the same minterm of f. DSOP forms are a special instance of partial DSOPs, i.e. the general case where a subset of minterms must be covered exactly once and the other minterms (typically corresponding to don’t care conditions of f) can be covered any number of times. We discuss finding DSOPs and partial DSOPs with a minimal number of products, a problem theoretically connected with various properties of Boolean functions and practically relevant in the synthesis of digital circuits. Finding an absolute minimum is hard, in fact we prove that the problem of absolute minimization of partial DSOPs is NP-hard. Therefore it is crucial to devise a polynomial time heuristic that compares favorably with the known minimization tools. To this end we develop a further piece of theory starting from the definition of the weight of a cube c as a functions of the number of fragments induced on other cubes by the selection of c, and show how cube weights can be exploited for building a class of minimization heuristics for DSOP and partial DSOP synthesis. A set of experiments conducted on major benchmark functions show that our method, with a family of variants, always generates better results than the ones of previous heuristics, including the method based on a BDD representation of f.     

Nonlinear model identification and see-through cancelation from recto–verso data

The problem of see-through cancelation in digital images of double-sided documents is addressed. We show that a nonlinear convolutional data model proposed elsewhere for moderate show-through can also be effective on strong back-to-front interferences, provided that the recto and verso pure patterns are estimated jointly. To this end, we propose a restoration algorithm that does not need any classification of the pixels. The see-through PSFs are estimated off-line, and an iterative procedure is then employed for a joint estimation of the pure patterns. This simple and fast algorithm can be used on both grayscale and color images and has proved to be very effective in real-world cases. The experimental results we report in this paper demonstrate that our algorithm outperforms the ones based on linear models with no need to tune free parameters and remains computationally inexpensive despite the nonlinear model and the iterative solution adopted. Strategies to overcome some of the residual difficulties are also envisaged.     

Triennial 1951: Post-War Reconstruction and “Divine Proportion”

This research centres on the conference dedicated to the theme “Divina Proporzione” organised on the occasion of the 1951 Milano Triennale. Participating in the meeting were some of the most important art historians, architects, engineers, mathematicians and artists of the day: from a very young James Ackerman to Pier Luigi Nervi, from Le Corbusier to Carlo Mollino, from Lucio Fontana to Ernesto Rogers. That historic moment, even given the plurality of voices and approaches, represented the synthesis of a reflection that was as urgent as it was rich in implications, since it brought the concept of “proportion” into the very heart of post-war reconstruction.     

SESAME-S: Semantic Smart Home System for Energy Efficiency

As the urgent need for efficient and sustainable energy usage becomes ever more apparent, interest in Smart Homes is on the rise. The SESAME-S project (SEmantic SmArt Metering – Services for Energy Efficient Houses) uses semantically linked data to actively assist end-consumers in making well-informed decisions and controlling their energy consumption. By integrating smart metering and home automation functionality, SESAME-S works to effectively address the potential mass market of end-consumers with an easily customizable solution that can be widely implemented in domestic or business environments, with expected savings of over 20?% from the total energy bill. The developed system is a basis for conceptualizing, demonstrating, and evaluating a variety of innovative end-consumer services and their user interface paradigms. In this paper, we present the SESAME-S system as a whole and discuss the semantically enabled services, demonstrating that such systems may have broad acceptance in the future. The data obtained through such systems will be invaluable for future global energy-efficiency strategies and businesses.     

Influence new-to-old concrete interface qualities on the behaviour of support zones of composite concrete beams

The paper describes the investigations of concrete composite units consisting of two concrete parts. In each test series the interface was differently arranged and characterised by different strength parameters. They were: non-reinforced interface with existing adhesion, reinforced interface with existing adhesion and reinforced interface with broken adhesion. Simply-supported beams were subjected to four point bending. The failure of all beams was the result of exceeding the shear resistance of the support zones, but the cracks pattern in each series was different. The paper presents the results of the tests, in particular: deflection, stresses in the longitudinal and transverse reinforcement and strains of concrete. The distribution of strains along the height of the beam and the slip between the connected parts are also described.On the basis of these data a classification of failure mechanisms of concrete composite beams is proposed, as well as the analytical criteria allowing to predict failure manner of a composite beam.