DRB1*15 and DRB1*03 extended haplotype interaction in primary Sj?gren's syndrome genetic susceptibility

OBJECTIVE: Sj?gren's syndrome (SS) is a chronic autoimmune disease with a genetic component. Among the genetic factors, the role of HLA class II genes has been suggested and a positive association with DRB1*03 allele has been described. However, there is no consensus on a unique HLA locus for this disease nor on the role of the HLA gene product in the disease. The aim of this study was to analyse prospectively MHC region involvement in the genetic susceptibility to SS by studying DRB1, DQB1, DPB1, TAP1, TAP2 genes and TNF microsatellites in a population of 45 primary SS patients. METHODS: All the polymorphisms studied were analysed at the genomic level using PCR-based methodologies. RESULTS: Concerning HLA class II alleles, the highest relative risk to develop the disease was associated with the DRB1*15-DRB1*0301 heterozygous genotype (17.8% vs 3.5% in controls - pc < 0.005, OR = 5.96). Analysing other genes located on the same region allowed us to further determine the DRB1 haplotypes at risk. For instance, the DRB1*0301 haplotype involved in the genetic susceptibility to SS was more often associated with the DPB1* 0201 and TNF-a2 alleles in SS patients than in controls. Moreover, all the DRB1*15-DRB1*0301 SS patients were TAP1-0101, TAP2-0101 homozygous, allowing us to deduce the extended genotype at risk as DRB1*15, TAP1-0101, TAP2-0101/DRB1*0301, TAP1-0101, TAP2-0101 which was carried by only 3 controls out of the 130 tested (p < 0.01, OR = 6.68). CONCLUSION: This study confirmed the role of the MHC region in the susceptibility to Sj?gren's disease, and for the first time suggests a synergistic interaction between two HLA-DRB1 extended haplotypes in the genetic mechanisms controlling the disease.     

Unpacking the black-box of students' visual attention in Mathematics and English classrooms: Empirical evidence using mini-video recording gadgets

With the technological improvements of innovative portable recording gadgets, augmented researchers' interest in exploring students' visual attention in their natural and normal occurring classrooms. The purpose of this study was to gauge students' visual attention in their Mathematics and English classrooms. This article reports on a study conducted in three schools in Santiago, Chile, where a sample of 113 randomly selected students wore a mini-video camera mounted on eyeglass in their Mathematics and English lessons. Using Google images, we automatically and objectively examined 723,600 frames from the recordings where the classroom teacher appeared in the students' visual field. The results show that students' visual attention varies depending on four factors: (a) gender of the student, (b) age of the students, whether students are low/high attainers and (d) whether students are in English or Mathematics lessons. Surprisingly, students significantly paid more visual attention in their Mathematics than in English lessons. High attainers were more visually engaged than their low attainers counterparts. Students appeared to be visually engaged differently at different stages in their education. Furthermore, girls were more visually engaged than boys. The results of this study can have enormous practical implications for teachers and teacher education, in order to be better visually engaged with students during teaching.     

Application of NN-ARX Model to Predict Groundwater Levels in the Neishaboor Plain, Iran

There is no doubt that groundwater is an important and vital source of water supply in arid and semi-arid areas. Therefore, prediction of groundwater level fluctuations is necessary for planning conjunctive use in these areas. This research was aimed to predict groundwater levels in the Neishaboor plain using Neural Network – AutoRegressive eXtra input (NN-ARX) and Static-NN models. The NN-ARX model determines a nonlinear ARX model of a dynamic system by training a hidden layer neural network with the Levenberg-Marquardt algorithm. In this model the current outputs depend not only on the current inputs, but also on the inputs and outputs at the pervious time periods. The available observation wells in the study area were clustered according to their fluctuation behavior using the “Ward” method, which resulted in six areal zones. Then, for each cluster, an observation well was selected as its representative, and for each zone, values of monthly precipitation, temperature and groundwater extraction were estimated. The best input of the Static-NN model was identified using combination of Gamma Test and Genetic Algorithm. Also, Gamma Test is applied to identify the length of the training dataset. The results showed that the NN-ARX model was suitable and more practical. The performance indicators (R ²?=?0.97, RMSE?=?0.03 m, ME?=?--0.07 m and R ²?=?0.81, RMSE?=?0.35 m, ME?=?0.60 m, respectively for the best and worst performance of model) reveals the effectiveness of this model. Moreover, these results were compared with the results of a static-NN model using t-test, which showed the superiority of the NN-ARX over the static-NN.     

Evolutionäre betriebliche Informationssysteme

This article reflects on existing and emerging future challenges arising in the area of “evolutionary business information systems”, a class of systems that demand an evolutionary software development process and which support secondary design of various conceptual layers. We place both existing contributions and future research opportunities in context by referring to an idealized, preliminary system architecture. Finally, we emphasize our pluralistic perspective on the research object and the resulting need for methodological flexibility in the sense of interdisciplinary configurations of research methods.     

Calculation of work roll initial crown based on desired strip profile in hot rolling

The superposition of work roll initial crown, the work roll bending and flattening crown, the work roll wearing crown and the work roll thermal crown makes the final hot strip. In this paper, new models based on numerical method have been obtained to predict the roll force, the work roll wearing crown and the work roll thermal crown utilizing experimental data provided by Mobarake Steel Complex. Meanwhile, the work roll bending and flattening crown has been obtained from finite element method as well as elasticity approach. Then, a computer programing has been written to obtain the work roll initial crown in order to get desired strip profile. This program is called Initial Crown Prediction Software (ICPS). Finally, the obtained initial crowns from ICPS were applied for different stands of hot strip mill of Mobarake Steel Complex, and the strip profile shows a good agreement with the desired one for the mentioned mill.     

Global DEMs to tackle RPC biases and the overfitting phenomenon in high-resolution satellite imagery

ABSTRACT

The overfitting phenomenon and rational polynomial coefficients (RPCs) biases are two crucial issues that degrade the accuracy of geospatial products derived from high-resolution satellite images. The overfitting phenomenon is caused by both a large number of RPCs and strong correlations among them. The RPC biases arise from uncertainties in the global positioning system receivers and inertial measurement units. In this article, an innovative framework based on the genetic algorithm (GA) and the least squares (LS) algorithm, called GALS, is proposed to overcome these problems simultaneously. In this method, the GA is applied to select the optimum RPCs, while the LS algorithm is used to estimate the values of the optimally selected RPCs. The GALS method requires various sets of well-distributed ground control points (GCPs). To tackle the problem of GCP collection, we generated a large number of digital elevation model (DEM)-derived GCPs (DEMGCPs), using a global DEM (GDEM) and vendor-provided RPCs, refined by only one GCP. To evaluate the performance of this framework, four IRS-P5 data sets were used. The GALS is compared to two competing methods, L1-norm-regularized LS and ridge estimation by considering two scenarios using 50 GCPs and the DEMGCPs. The results demonstrate the superiority of GALS in both scenarios. Furthermore, GALS using DEMGCPs led to far more accurate and stable results when compared to GALS using GCPs. Compared to the vendor-provided RPCs, the results of the GALS using DEMGCPs also indicate a major improvement, single-pixel or subpixel accuracy with around 15 RPCs, and only 1 GCP, in both accuracy and reliability of georeferencing for all IRS-P5 data sets.     

Continuous strategy replicator dynamics for multi-agent Q-learning

The problem of multi-agent learning and adaptation has attracted a great deal of attention in recent years. It has been suggested that the dynamics of multi agent learning can be studied using replicator equations from population biology. Most existing studies so far have been limited to discrete strategy spaces with a small number of available actions. In many cases, however, the choices available to agents are better characterized by continuous spectra. This paper suggests a generalization of the replicator framework that allows to study the adaptive dynamics of Q-learning agents with continuous strategy spaces. Instead of probability vectors, agents’ strategies are now characterized by probability measures over continuous variables. As a result, the ordinary differential equations for the discrete case are replaced by a system of coupled integral-differential replicator equations that describe the mutual evolution of individual agent strategies. We derive a set of functional equations describing the steady state of the replicator dynamics, examine their solutions for several two-player games, and confirm our analytical results using simulations.     

Fuzzy hypothesis testing with vague data using likelihood ratio test

Hypothesis testing is one of the most significant facets of statistical inference, which like other situations in the real world is definitely affected by uncertain conditions. The aim of this paper is to develop hypothesis testing based on likelihood ratio test in fuzzy environment, where it is supposed that both hypotheses under study and sample data are fuzzy. The main idea is to employ Zadeh’s extension principle. In this regard, a pair of non-linear programming problems is exploited toward obtaining membership function of likelihood ratio test statistic. Afterwards, the membership function is compared with critical value of the test in order to assess acceptability of the fuzzy null hypothesis under consideration. In this step, two distinct procedures are applied. In the first procedure, a ranking method for fuzzy numbers is utilized to make an absolute decision about acceptability of fuzzy null hypothesis. From a different point of view, in the second procedure, membership degrees of fuzzy null hypothesis acceptance and rejection are first derived using resolution identity and then, a relative decision is made on fuzzy null hypothesis acceptance or rejection based on some arbitrary decision rules. Flexibility of the proposed approach in testing fuzzy hypothesis with vague data is presented using some numerical examples.     

Environmental and Safety Aspects of Using Tritium in Fusion

Today most current fusion research and development activity is based on the expectation that the D–T reaction will be used for the first generation of fusion reactors. This mixture is the premier candidate for a fusion fuel on account of its outstanding energy gain. Fusion reactors will produce neither the problematic emissions now experienced from fossil-fuel-burning power plants nor the long-lived fission products and transuranic elements resulting from fission reactors. Even though, tritium is a radioactive isotope of hydrogen with 12.32 years half-life that exposes beta radiation. Although its specific activity is relatively weak but because of its gaseous state, it can leak easily from its container and contaminate its surrounding. In order to improving safety and reliability of fusion reactors, research groups jointly investigate radiation hazards resulting from the release of tritium and activation products during normal operations as well as accidental conditions. In this paper, some of the most significant safety and environmental aspects of tritium is briefly discussed.