Miracle-dz/UniFAR-FTUs huggingface dataset:
Expression analyses of some Beauveria bassiana genes in response to cuticles of four different insects

Beauveria spp. as entomopathogenic fungi have extremely diverse insect host ranges. Here, a comparative transcript analysis of a Bassiasin I (BSNI), a Dipeptidyl peptidase (DPP), a Cytochrom P450 monooxygenase (CYP52), a Mitogen activated protein kinase (MAPK), and a Neuronal calcium sensor 1 (NCS) in two isolates of Beauveria bassiana. , with low and high virulence, were carried out. For this, induction media, containing isolated cuticles from four insects, and a check medium lacking any cuticular extract were prepared and isolates were allowed to grow on them. Interestingly, upregulation of BSNI and DPP in induction media was noted in comparison to the check, following normalization with γ-ACTIN. CYP52 was up-regulated in synthetic medium in comparison to cuticular extract. MAPK expression was greater in most virulent isolate once compared with the low virulent isolate. The expression of MAPK was greater in the presence of Caliptamus italicus cuticles and synthetic medium as opposed to others. NCS expression remained on changed in all media tested and can be suggested as a reference gene in transcriptomics of Beauveria spp. genes in future.
Association between the CTLA-4 +49A/G polymorphism and Graves’ disease: A meta-analysis

The +49A/G polymorphism of the cytotoxic T-lymphocyte-associated antigen-4 gene (CTLA-4) has been associated with Graves’ disease (GD). However, results have been inconsistent. The aim of this study was to quantitatively summarize the evidence for CTLA-4 +49A/G polymorphism and GD. Electronic search of PubMed was conducted to select studies. Case-control studies containing available genotype frequencies of CTLA-4 +49 were chosen, and Odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of this association. Forty-two case-control studies including 8,288 cases and 9,372 controls were identified. Three studies were eliminated from the total 42 studies due to a p-value <0.05 (p-value for Hardy-Weinberg equilibrium in control group) in these studies which induced significant publication bias. The overall results suggested that the variant genotypes were highly associated (p<0.01) with GD risk in all genetic models (additive model: OR, 1.443; 95% CI, 1.319–1.578; p<0.001; recessive model: OR, 1.589; 95% CI, 1.396–1.808; p<0.001; dominant model: OR, 1.621; 95% CI, 1.430–1.837; p<0.001). Similarly, in the subgroup analyses for ethnicity (Caucasian, Asian), the results were positive. This meta-analysis suggests that the CTLA-4 +49A/G polymorphism is highly associated (p<0.01) with increased risk of GD, especially in Caucasians and Asians. To validate this association, further studies with larger participants worldwide are needed to examine associations between this polymorphism and GD.
Selective destruction of nerve growth factor receptor-bearing cells in vitro using a hybrid toxin composed of ricin A chain and a monoclonal antibody against the nerve growth factor receptor

A hybrid toxin composed of ricin A chain and a monoclonal antibody directed against the rat nerve growth factor (NGF) receptor (192-IgG) was prepared using the heterobifunctional cross-linking agent N- succinimidyl-3-(2-pyridyldithio)-propionate and purified by affinity chromatography. Characterization studies showed that the hybrid, 192-s- s-A, displaced bound 125I-labeled 192-IgG from rat superior cervical ganglion (SCG) membranes with an IC50 3-5 times lower than that of unconjugated 192-IgG. When incubated with cultured rat SCG neurons, 192- s-s-A inhibited protein synthesis in a concentration-dependent fashion. The effect of 192-s-s-A on these neurons was reversed by coincubation with an excess of 192-IgG. The IC50 of 192-s-s-A on protein synthesis in rat SCG neurons was 4 nM. Intact ricin and ricin A chain inhibited protein synthesis in these neurons with IC50 values of 5 pM and 500 nM, respectively. The 192-s-s-A hybrid had no effect on mouse SCG neurons or a human melanoma cell line known to have NGF receptors. This is consistent with the finding that 192-IgG recognizes only the rat NGF receptor. Also, 192-s-s-A did not inhibit protein synthesis in primary cultures of rat skeletal muscle or Vero cells, which do not have cell surface receptors for NGF. 192-s-s-A was able to inhibit protein synthesis in PC12 cells but the potency was 10-100 times less in these cells compared to rat SCG neurons. Ricin and A chain were also 10-100 times less potent in PC12 cells than neurons. Rat SCG neurons exposed to 192-s-s-A lost their refractile appearance under phase-contrast optics, showed granular degeneration of neurites, and died. Thus the decreased protein synthesis caused by the hybrid toxin correlated with the morphological destruction of the neurons. 192-s-s-A represents a potentially powerful tool by which to selectively destroy NGF receptor- bearing cells in vitro. The hybrid toxin may prove useful as an in vivo toxin.
Event Related Potentials Reveal Early Phonological and Orthographic Processing of Single Letters in Letter-Detection and Letter-Rhyme Paradigms

Introduction: When and where phonological processing occurs in the brain is still under some debate. Most paired-rhyme and phonological priming studies used word stimuli, which involve complex neural networks for word recognition and semantics. This study investigates early (<300 ms) and late (>300 ms) orthographic and phonological processing of letters. Methods: Fifteen participants aged 20–35 engaged in three two-forced choice experiments, one letter-detection (LetterID) and two letter-rhyme (Paired-Rhyme and Letter-Rhyme) tasks. From the EEG recordings, event related potential (ERP) differences within and across task stimuli were found. We also calculated the global field power (GFP) for each participant. Accuracies and reaction times were also measured from their button presses for each task. Results: Behavioral: Reaction times were 18 ms faster to letter than pseudoletter stimuli, and 27 ms faster to rhyme than nonrhyme stimuli. ERP/GFP: In the LetterID task, grand-mean evoked potentials (EPs) showed typical P1, N1, P2, and P3 waveform morphologies to letter and pseudoletter stimuli, with GFPs to pseudoletters being greater than letters from 160–600 ms. Across both rhyme tasks, there were greater negativities for nonrhyme than for rhyme stimuli at 145 ms and 426 ms. The P2 effect for rhyme stimuli was smaller than letter stimuli when compared across tasks. Conclusion: Differences in early processing of letters vs. pseudoletters between 130–190 ms suggest that letters are processed earlier and perhaps faster in the brain than pseudoletters. The P2 effect between letter and rhyme stimuli likely reflect sublexical phonological processing. Together, findings from our study fill in evidence for the temporal dynamics of orthographic and phonological processing of single letters.
Entropy-based network anomaly Detection

Anomaly-based Intrusion Detection is a key research topic in network security due to its ability to face unknown attacks and new security threats. In this paper we propose a novel intrusion detection system that performs anomaly detection by studying the variation in the entropy associated to the network traffic. To this aim, the traffic is first aggregated by means of random data structures (namely three-dimension reversible sketches) and then the entropy of different traffic descriptors is computed by using several definitions of entropy. The experimental results obtained over the MAWILab dataset validate the system and demonstrate the effectiveness of our proposal.
A Distributed Query Execution Method for RDF Storage Managers

A distributed query execution method for Resource Description Framework (RDF) storage managers is proposed. Method is intended for use with an RDF storage manager called big3store to enable it to perform efficient query execution over large-scale RDF data sets. The storage manager converts SPARQL queries into tree structures using RDF algebra formalism. The nodes of those tree structures are represented by independent processes that execute the query autonomously and in a highly parallel manner by sending asynchronous messages to each other. The proposed data and query distribution method decreases the amount of inter-server messages during query executions by use of the semantic properties of RDF data sets.
Abnormal tissus extraction in MRI brain medical images

This study is a comparison between two image segmentation's methods; the first method is based on normal brain's tissue recognition then tumor extraction using thresholding method. The second method is classification based on EM segmentation which is used for both brain recognition and tumor extraction. The goal of these methods is to detect, segment, extract, classify and measure properties of the brain normal and abnormal (tumor) tissues
Neural Networks Learning Improvement using the K-Means Clustering Algorithm to Detect Network Intrusions

In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a backpropagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.
Scalable Visual Hierarchy Exploration Scalable Visual Hierarchy Exploration

More and more modern computer applications, from business decision support to scientiic data analysis, utilize visualization techniques to support exploratory activities. Various tools have been proposed in the past decade to help users better interpret data using such display techniques. However, most do not scale well with regard to the size of the dataset upon which they operate. In particular, the level of cluttering on the screen is typically unacceptable and the performance is poor. To solve the problem of cluttering at the interface level, visualization tools have recently been extended to support hierarchical views of the data, with support for focusing and drilling-down using interactive brushes. To solve the scalability problem, we now investigate how best to couple such a visualization tool with a database management system without losing the real-time characteristics. This integration must be done carefully, since visual user interactions implemented as main memory operations do not map directly into eecient database operations. The main eeciency issue when doing this integration is to avoid the recursive processing required for hierarchical data retrieval. For this problem, we have develop a tree labeling method, called MinMax tree, that allows the movement of the on-line recursive processing into an oo-line precomputation step. Thus, at run time, the recursive processing operations translate into linear cost range queries. Secondly, we employ a main memory access strategy to support incremental loading of data into the main memory. The techniques have been incorporated into XmdvTool, a multidimensional visual exploration tool, in order to achieve scalability. The tool now successfully scales up to datasets of the order 10 5 {10 7 records. Lastly, 1 we report experimental results that illustrate the impact of the proposed techniques on the system's overall performance.
A hybrid PSO model in Extractive Text Summarizer

The World Wide Web has caused an information explosion. Readers are often drowned in information while starved of knowledge. Readers are bombarded with too many lengthy documents where shorter summarized texts would be preferable. This paper presents a hybrid Harmony Particle Swarm Optimization (PSO) framework in an Extractive Text Summarizer to tackle the information overload problem. Particle Swarm Optimization is a suitable technique for solving complex problems due to its simplicity and fast computational convergence. However, it could be trapped in a local minimal search space in the midst of searching for the optimal solutions. The objective of this research is to investigate whether the proposed hybrid harmony PSO model is capable of condensing original electronic documents into shorter summarized texts more efficiently and accurately than the alternative models. Empirical results show that the proposed hybrid PSO model improves the efficiency and accuracy of composing summarized text.
Indoor Scene Recognition Based on the Weighting Spatial Information Fusion

Scene recognition is high level image understanding in machine vision field. It is usually difficult to recognize variety indoor scene of which the characteristics between many classes are changing significantly. This paper proposes an indoor home scene recognition model based on Weighting Spatial Information Fusion of PLSA (WSIF_PLSA), build many PLSA models and SVM classifiers using spatial information of indoor scene and fuse the recognition result with weight. So it is considering not only global visual characteristic but also local visual characteristic. The experiment constructs a database of IHSD which is for indoor home scene recognition and the results shows the higher recognition efficiency with this method.
A Research of Distance Transform Based Peeling Algorithm for Overlapped Fibers Separation

Overlapped fiber separation is one of main procedures in cross-sectional fiber analysis. In the proposed distance transform based peeling algorithm, a separation point is determined by removing points with the least distance. The overlapped fibers in cross-section are separated by the separation point. Experiments show that the proposed algorithm precisely separates overlapped fibers of various shapes. Keywords-overlapped fibers; cross-section; distance transform; peeling algorithm; fiber separation
Geometrical Building Modeling and Its Application to the Ortho-Rectification for Aerial Images

Due to the huge demand and the importance of 3-D city models, an effective solution for geometrical building modeling is indispensable. From the application point of view, an interactive system for geometrical building modeling based on a semi-automatic approach is presented. A true-orthophoto rectification scheme based on the generated building models is also proposed. The data used in the proposed system are 3-D visible roof-edges that have been manually measured from a stereo-model, or the 3-D building outlines from a digital topographic map. The core technology is called the”Split-Merge-Shape”(SMS) method. The SPLIT and MERGE steps are the two main procedures for topology reconstruction from non-related roof-edges. The SHAPE step uses the available roof-edge height information to define an appropriate rooftop. With the SMS method, the topographic mapping of buildings, and geometric building modeling, can be seamlessly integrated into a unified procedure. In a conventional ortho-rectification procedure using a digital terrain model, the correction of relief displacement due to buildings is not considered. In order to restore the most complete information and to correct the relief displacement of buildings, a rigorous true-orthophoto rectification scheme is proposed. In the proposed scheme, 3-D building models, multi-view aerial images, digital terrain models, and the sun's orientation are all utilized. Terrain and building relief displacement corrections as well as hidden area compensation, seamless mosaicking, and shadowed area enhancement are integrated into one procedure. In this paper, the SMS method is presented, including an evaluation of its feasibility, robustness, efficiency and accuracy. Finally, the generated building models are applied to true-orthophoto generation and 3-D GIS querying.
Horizontal and vertical five-branes in heterotic/F-theory duality

We consider the heterotic string on an elliptic Calabi-Yau three-fold with five-branes wrapping curves in the base (`horizontal' curves) of the Calabi-Yau as well as some elliptic fibers (`vertical' curves). We show that in this generalized set-up, where the association of the heterotic side with the F-theory side is changed relative to the purely vertical situation, the number of five-branes wrapping the elliptic fibers still matches the corresponding number of F-theory three-branes.
The robot that can achieve card magic

We succeeded in developing a robot that can play a card magic for the first time in the world. The robot can complete a magic by quickly switching the first-card-dealing and the-second-card-dealing. This paper is composed of three parts where one is the design of the robot by referring human motion, the second is the mechanics of the card manipulation by utilizing a simplified model, and a magic actually done by the robot. We would note that as far as the card dealing is concerned, the developed robot is even faster than human magician.
Expression Profiler: next generation - an online platform for analysis of microarray data

Expression Profiler (EP, http://www.ebi.ac.uk/expressionprofiler) is a web-based platform for microarray gene expression and other functional genomics-related data analysis. The new architecture, Expression Profiler: next generation (EP:NG), modularizes the original design and allows individual analysis-task-related components to be developed by different groups and yet still seamlessly to work together and share the same user interface look and feel. Data analysis components for gene expression data preprocessing, missing value imputation, filtering, clustering methods, visualization, significant gene finding, between group analysis and other statistical components are available from the EBI (European Bioinformatics Institute) web site. The web-based design of Expression Profiler supports data sharing and collaborative analysis in a secure environment. Developed tools are integrated with the microarray gene expression database ArrayExpress and form the exploratory analytical front-end to those data. EP:NG is an open-source project, encouraging broad distribution and further extensions from the scientific community.
Calculation of Circulating Bearing Currents in Machines of Inverter-Based Drive Systems

The high-frequency circulating bearing current that may occur in machines of inverter-based drive systems can be described by an eddy-current model. The parameters of an equivalent circuit are derived from the model. The ratio between bearing current and common-mode current amplitudes for different machines is calculated. The theoretical maximum ratio is about 0.35. Copper loops applied for bearing current measurement may decrease the circulating bearing currents up to almost 40%
Program “Mindful Parenting” untuk Meningkatkan Kesejahteraan Subjektif Ibu yang Memiliki Anak Retardasi Mental

Parenting child with intellectual disability is associated with physical and psychological problems that influence mother’s subjective well-being. The evidence is show that mindfulness based intervention can increase of life satisfaction, elicit positive affect, dan minimize negative affect, so that it can increase subjective well-being. The aim of this study is to examine the effectiveness of “Mindful parenting” program in increasing subjective well-being mother who has child with intellectual disability. This study uses a one-group pretest-posttesttt design using a double pretest. “Mindful Parenting” program was administered to ten mothers of children with intellectual disability. Participant attend 8 sessions of “Mindful parenting” program in four meeting. Analysis using Friedman test showed significance result (F r(2) = 11.13, p< 0.05). It conclude that there was significant effect of “Mindful parenting” program on promotes subjective well-being of mothers of children with intellectual disability.
Combinatorial R Matrices for a Family of Crystals: B(1)n, D(1)n, A(2)2n, and D(2)n + 1 Cases☆

Abstract For coherent families of crystals of affine Lie algebras of type B (1) n , D (1) n , A (2) 2 n , and D (2) n + 1 we describe the combinatorial R matrix using column insertion algorithms for B , C , D Young tableaux. This is a continuation of previous work by the authors (2000, in “Physical Combinatorics” (M. Kashiwara and T. Miwa, Eds.), Birkhauser, Boston).
Use of keyword hierarchies to interpret gene expression patterns

MOTIVATION High-density microarray technology permits the quantitative and simultaneous monitoring of thousands of genes. The interpretation challenge is to extract relevant information from this large amount of data. A growing variety of statistical analysis approaches are available to identify clusters of genes that share common expression characteristics, but provide no information regarding the biological similarities of genes within clusters. The published literature provides a potential source of information to assist in interpretation of clustering results. RESULTS We describe a data mining method that uses indexing terms ('keywords') from the published literature linked to specific genes to present a view of the conceptual similarity of genes within a cluster or group of interest. The method takes advantage of the hierarchical nature of Medical Subject Headings used to index citations in the MEDLINE database, and the registry numbers applied to enzymes.
GeoIP clustering: Solving replica server placement problem in content delivery networks by clustering users according to their physical locations

Content delivery networks have emerged to conquer massive requests problem in popular web services. One of the major issues in CDNs is the replica server placement problem. If the replica servers are geographically closer to the users, overall bandwidth consumption and the users' perceived latency will be reduced significantly. In this paper we have used IP geolocation services to achieve the users' locations in terms of latitude and longitude. Then we have clustered users according to their coordinates. Locating servers around the cluster centers, provides better performance of CDN.
A Sparse Hybrid Map for Vision-Guided Mobile Robots

This paper introduces a minimalistic approach to produce a visual hybrid map of a mobile robot’s working environment. The proposed system uses omnidirectional images along with odometry information to build an initial dense posegraph map. Then a two level hybrid map is extracted from the dense graph. The hybrid map consists of global and local levels. The global level contains a sparse topological map extracted from the initial graph using a dual clustering approach. The local level contains a spherical view stored at each node of the global level. The spherical views provide both an appearance signature for the nodes, which the robot uses to localize itself in the environment, and heading information when the robot uses the map for visual navigation. In order to show the usefulness of the map, an experiment was conducted where the map was used for multiple visual navigation tasks inside an office workplace.