Miracle-dz/UniFAR-FTUs huggingface dataset:
TCP Performance Improvement with ACK Pacing during a Long Lasting Loss Period in Wireless Data Networks

Wireless data services are fundamental in ubiquitous networks. In wireless data networks, the TCP congestion mechanism can mistake a wireless channel error or blackout for congestion on the route. Several wireless TCP protocols have been proposed considering TCP performance degradation in wireless systems. However, these protocols are too complex to deploy in wireless systems. In this paper, we propose the ACK Pacing algorithm for long lasting loss periods like a hand-off or a blackout. By pacing ACK packets sending, we prevent bursty data delivery to the old path and a spurious timeout occurrence. Also, paced ACK packets trigger the route update to the new path faster. The proposed algorithm can be implemented in the wirelessnode-side which is easily applicable to wireless systems. From simulation results, ACK Pacing improves TCP performance compared with many TCP variations. The ACK Pacing algorithm shows good performance during a long lasting loss period.
Improvement of attribute-oriented induction method based on attribute correlation with target attribute

Attribute-oriented induction (AOI) is one of the classical knowledge discovery methods for a relational database query in the field of data mining. On the basis of deeply analysis on the principles of the AOI method, this paper points out some problems existing in it such as redundant attributes after generalization and the invalid rules. This paper puts forward the concept of correlation degree with target attribute, and then gives the improved algorithm according to it Removing the redundant attributes with weak correlation degree with target attribute could help the improved AOI overcome the problems existing in the classical AOI method, and thus improve its efficiency. Different approaches to calculate correlation degree with target attribute are defined to deal with different type of data. Grey relation and attribute reduction based on rough set method are induced to fulfill the above calculation. Experiments on an example demonstrate the effectiveness of the proposed method.
Real-Time Visualization of Streaming Text Data: Tasks and Challenges

Real-time visualization of text streams is crucial for different analysis scenarios and can be expected to become one of the important future research topics in the text visualization domain. Especially the complex requirements of real-time text analysis tasks lead to new visualization challenges, which will be structured and described in this paper. First, we give a definition of what we consider to be a text stream and emphasize the importance of different real-world application scenarios. Then, we summarize research challenges related to different parts of the analysis process and identify those challenges that are exclusive to real-time streaming text visualization. We review related work with respect to the question which of the challenges have been addressed in the past and what solutions have been suggested. Finally, we identify the open issues and potential future research subjects in this vibrant area. Index Terms—real-time, text streams, streaming data, dynamic visualization, visual analytics.
The Yarrowia lipolytica Gene PAY2 Encodes a 42-kDa Peroxisomal Integral Membrane Protein Essential for Matrix Protein Import and Peroxisome Enlargement but Not for Peroxisome Membrane Proliferation (*)

PAY genes are required for peroxisome assembly in the yeast Yarrowia lipolytica. Here we show that a mutant strain, pay2, is disrupted for the import of proteins targeted by either peroxisomal targeting signal-1 or −2. Electron microscopy of pay2 cells revealed the presence of small peroxisomal “ghosts,” similar to the vesicular structures found in fibroblasts of patients with the human peroxisome assembly disorder, Zellweger syndrome. Functional complementation of pay2 with a plasmid library of Y. lipolytica genomic DNA identified a gene, PAY2, that restores growth of pay2 on oleic acid, import of catalase and multifunctional enzyme into peroxisomes, and formation of wild type peroxisomes. The PAY2 gene encodes Pay2p, a hydrophobic polypeptide of 404 amino acids. An antibody raised against Pay2p recognizes a polypeptide of 42-kDa whose synthesis is induced by growth of Y. lipolytica on oleic acid. Pay2p is a peroxisomal integral membrane protein, as it localizes to carbonate-stripped peroxisomal membranes. Pay2p shows no identity to any known protein. Our results suggest that Pay2p is essential for the activity of the peroxisomal import machinery but does not affect the initial steps of peroxisomal membrane proliferation.
Effect of Immune Pressure on Hepatitis C Virus Evolution: Insights From a Single-Source Outbreak

The host's immune response to hepatitis C virus (HCV) can result in the selection of characteristic mutations (adaptations) that enable the virus to escape this response. The ability of the virus to mutate at these sites is dependent on the incoming virus, the fitness cost incurred by the mutation, and the benefit to the virus in escaping the response. Studies examining viral adaptation in chronic HCV infection have shown that these characteristic immune escape mutations can be observed at the population level as human leukocyte antigen (HLA)–specific viral polymorphisms. We examined 63 individuals with chronic HCV infection who were infected from a single HCV genotype 1b source. Our aim was to determine the extent to which the host's immune pressure affects HCV diversity and the ways in which the sequence of the incoming virus, including preexisting escape mutations, can influence subsequent mutations in recipients and infection outcomes. Conclusion: HCV sequences from these individuals revealed 29 significant associations between specific HLA types within the new hosts and variations within their viruses, which likely represent new viral adaptations. These associations did not overlap with previously reported adaptations for genotypes 1a and 3a and possibly reflected a combination of constraint due to the incoming virus and genetic distance between the strains. However, these sites accounted for only a portion of the sites in which viral diversity was observed in the new hosts. Furthermore, preexisting viral adaptations in the incoming (source) virus likely influenced the outcomes in the new hosts. (HEPATOLOGY 2011;53:396‐405)
The relationship between Eysenck personality characteristics and resiliency with attitude towards suicide among female students

Present study conducted to determine the relationship between the Eysenck Personality characteristics and resiliency with a look at the issue of suicide among girl students in Kermanshah. Performing the research, a sample size of 250 individuals selected among all secondary school students in Kermanshah through cluster sampling. Descriptive study was a correlative type, to analyze the data; resulted data was analyzed using Pearson correlation and regression analysis by the help of SPSS19 software. To gather data, the Eysenck Personality characteristics questionnaires, Connor and Davidson resiliency approach and attitude to committing suicide used. Results showed that there was a positive, significant correlation between personality traits psychotic mental attitudes, and attitude to committing suicide, but there was a negative correlation between extroversion and attitude towards committing suicide. In addition, results indicated that there was a negative correlation between resiliency and attitude towards committing suicide. According to the results it could be concluded that the character of a structure is associated to commit suicide.
Frame of the Human Macrophage Colony-stimulating Factor Gene Is Independently Translated and Codes for an Antigenic Peptide of 14 Amino Acids Recognized by Tumor-infiltrating CD 8 T Lymphocytes

We show that cytotoxic T lymphocytes (CTLs) infiltrating a kidney tumor recognize a peptide encoded by an alternative open reading frame (ORF) of the macrophage colony-stimulating factor (M-CSF) gene. Remarkably, this alternative ORF, which is translated in many tumors concurrently with the major ORF, is also translated in some tissues that do not produce M-CSF, such as liver and kidney. Such a dissociation of the translation of two overlapping ORFs from the same gene is unexpected. The antigenic peptide encoded by the alternative ORF is presented by human histocompatibility leukocyte antigen (HLA)-B * 3501 and has a length of 14 residues. Peptide elution indicated that tumor cells naturally present this 14 mer, which is the longest peptide known to be recognized by CTLs. Binding studies of peptide analogues suggest that it binds by its two extremities and bulges out of the HLA groove to compensate for its length.
Considerations for recruiting contributions to anonymised data sets

For the improvement and evaluation of learning management systems as well as concepts and tools for personal history, the availability of suitable data has become increasingly important. In this paper we discuss considerations for creating such a data set and report on our experiences while recruiting contributions for the Web History Repository project (WHR). We focus on measures and techniques for addressing privacy issues and strategies for motivating people to contribute. We briefly report on the outcomes of the first rounds of analysis of the data set and discuss implications for educational data mining.
Identification of Syntenin as a Protein of the Apical Early Endocytic Compartment in Madin-Darby Canine Kidney Cells*

We used flow cytometry to sort and analyze apical and basolateral endocytic vesicles from filter-grown Madin-Darby canine kidney (MDCK) cells after membrane internalization of the lipophilic fluorescent probe trimethylamino-diphenylhexatriene. Western blot analysis of sorted fractions showed enrichment of the early endosomal markers transferrin receptor and the small GTPase Rab5. Two-dimensional gel analysis indicated that the apical and basolateral early endosomes differed significantly in their protein composition. We found nine polypeptides to be specifically enriched in apical or basolateral endocytic vesicles. An apical protein identified by microsequencing was the adaptor molecule syntenin. This protein contains two PDZ domains (PSD-95, Dlg, and ZO-1 homology) that bind syndecan and ephrin-B2 cytoplasmic domains. In MDCK cells, transiently overexpressed Myc-tagged syntenin localized to both plasma membrane domains and to an intracellular vesicular compartment. Syntenin positive vesicles colocalized with internalized transferrin in the perinuclear region. In addition, syntenin colocalized in the apical supranuclear region with Rab5 and Rab11; the latter is a marker for the apical recycling endosomes in MDCK cells.
Choices of Theatre Events: p* Models for Affiliation Networks with Attributes

In this article we analyse the choice of theatre pe rformances made by theatregoers through the application of network ana lysis. We use the institution in which the events are staged and the aesthetical expectations of the theatregoers as explanations for the choice pat terns. By means of p* models, we are able to simultaneously analyse the p atterns of choice, the loyalty to an institution and the co-attendance of events, and the diversity in audience composition. Based on an audience survey i n three theatre institutions in the city of Ghent (Belgium), we sho w that theatregoers with unconventional expectations are more likely to atte nd plays of the less traditional institutions. Second, audiences are loy al to an institution irrespective of the existence of season tickets. Pe ople are more inclined to combine plays that are staged by the institutions w ith a similar programmation. Furthermore, we find that one instit ution has very similar audiences for different plays, whereas for others t he composition of the audiences differs significantly with regard to aest hetic expectations between different plays.
Federal Policy toward Human Embryonic Stem Cell Research

causing and beneating from a moral wrong might show that there are ways in which compromise on public funding of ES cell research and the therapies derived from that research might occur (Robertson 1999). Careful analysis of the relevant biology and moral reasoning could provide the bridge across the ethical chasm that now separates the different sides in this debate. References Doeroinger, R. 2002. Ditching religion and reality. American Journal of Bioethics 2(1): 31–32.
Code-Switch Language Model with Inversion Constraints for Mixed Language Speech Recognition

We propose a first ever code-switch language model for mixed language speech recognition that incorporates syntactic constraints by a code-switch boundary prediction model, a code-switch translation model, and a reconstruction model. A WFST-based decoder then recognizes speech by combining an acoustic model, a pronunciation model and the code-switch language model in an integrated approach. Our proposed approach avoids making early decisions on code-switch boundaries and is therefore more robust than previous approaches. Our proposed system using the code-switch language model outperforms a baseline of interpolated language models by a statistically significant 0.91% on a mixed language lecture speech corpus, and 1.25% on a mixed language lunch conversation corpus. Our method also outperforms a language model that permits code-switch at all word boundaries by a statistically significant 1.35% on the lecture speech corpus and 1.69% on the lunch conversation corpus.
Designing Semantic Kernels as Implicit Superconcept Expansions

Recently, there has been an increased interest in the exploitation of background knowledge in the context of text mining tasks, especially text classification. At the same time, kernel-based learning algorithms like Support Vector Machines have become a dominant paradigm in the text mining community. Amongst other reasons, this is also due to their capability to achieve more accurate learning results by replacing standard linear kernel (bag-of-words) with customized kernel functions which incorporate additional apriori knowledge. In this paper we propose a new approach to the design of ‘semantic smoothing kernels’ by means of an implicit superconcept expansion using well-known measures of term similarity. The experimental evaluation on two different datasets indicates that our approach consistently improves performance in situations where (i) training data is scarce or (ii) the bag-ofwords representation is too sparse to build stable models when using the linear kernel.
Discovery of Extreme Carbon Stars in the Large Magellanic Cloud

Using Spitzer IRAC and MIPS observations of the Large Magellanic Cloud, we have identified 13 objects that have extremely red mid-IR colors. Follow-up Spitzer IRS observations of seven of these sources reveal varying amounts of SiC and C2H2 absorption as well as the presence of a broad MgS feature in at least two cases, indicating that these are extreme carbon stars. Preliminary estimates find these objects have luminosities of (4-11) × 103 L☉ and preliminary model fitting gives mass-loss rates between 4 × 10−5 and 2 × 10−4 M☉ yr−1, higher than any known carbon-rich AGB star in the LMC. These spectral and physical properties require careful reconsideration of dust condensation and mass-loss processes for carbon stars in low-metallicity environments.
Pragmatic Functions of Interpreters’ Own Discourse Markers in Simultaneous Interpreting: A Case Study of the 2012 Chinese Spring Festival Gala

Taking authentic data from the simultaneous interpreting of the Chinese 2012 Spring Festival Gala as the corpus of this study, the present paper summarizes two kinds of pragmatic functions with regard to the discourse markers used in the corpus, namely passive markers and proactive markers. The discourse markers discussed here are used by the interpreters, not those they translated. The paper then discusses their functions with some examples. Finally, the reasons for using discourse markers are investigated. It is hoped that the research findings can shed some light on the success of simultaneous interpreters in use of discourse markers.
Interaction of Nascent Chains with the Ribosomal Tunnel Proteins Rpl4, Rpl17, and Rpl39 of Saccharomyces cerevisiae *

Background: Rpl4, Rpl17, and Rpl39 expose patch-like domains to the empty ribosomal polypeptide tunnel. Results: Rpl4 contacts various nascent chain residues, even far from its patch-like domain. Rpl17 contacts only hydrophobic α-helical segments, other nearby nascent chain segments are excluded. Conclusion: The tunnel topology of Rpl4 and Rpl17 must be flexible. Significance: The amino acid sequence of nascent chains affects the topology of Rpl4 and Rpl17. As translation proceeds, nascent polypeptides pass through an exit tunnel that traverses the large ribosomal subunit. Three ribosomal proteins, termed Rpl4, Rpl17, and Rpl39 expose domains to the interior of the exit tunnel of eukaryotic ribosomes. Here we generated ribosome-bound nascent chains in a homologous yeast translation system to analyze contacts between the tunnel proteins and nascent chains. As model proteins we employed Dap2, which contains a hydrophobic signal anchor (SA) segment, and the chimera Dap2α, in which the SA was replaced with a hydrophilic segment, with the propensity to form an α-helix. Employing a newly developed FLAG exposure assay, we find that the nascent SA segment but not the hydrophilic segment adopted a stable, α-helical structure within the tunnel when the most C-terminal SA residue was separated by 14 residues from the peptidyl transferase center. Using UV cross-linking, antibodies specifically recognizing Rpl17 or Rpl39, and a His6-tagged version of Rpl4, we established that all three tunnel proteins of yeast contact the SA, whereas only Rpl4 and Rpl39 also contact the hydrophilic segment. Consistent with the localization of the tunnel exposed domains of Rpl17 and Rpl39, the SA was in contact with Rpl17 in the middle region and with Rpl39 in the exit region of the tunnel. In contrast, Rpl4 was in contact with nascent chain residues throughout the ribosomal tunnel.
Image retrieval and perceptual similarity

Simple, low-level visual features are extensively used for content-based image retrieval. Our goal was to evaluate an image-indexing system based on some of the known properties of the early stages of human vision. We quantitatively measured the relationship between the similarity order induced by the indexes and perceived similarity. In contrast to previous evaluation approaches, we objectively measured similarity both for the few best-matching images and also for relatively distinct images. The results show that, to a large degree, the rank orders induced by the indexes predict the perceived similarity between images. The highest index concordance employing a single index was obtained using the chromaticity histogram. Combining different information sources substantially improved the correspondence with the observers. We conclude that image-indexing systems can provide useful measures for perceptual image similarity. The methods presented here can be used to evaluate and compare different image-retrieval systems.
Population Decoding in Rat Barrel Cortex: Optimizing the Linear Readout of Correlated Population Responses

Sensory information is encoded in the response of neuronal populations. How might this information be decoded by downstream neurons? Here we analyzed the responses of simultaneously recorded barrel cortex neurons to sinusoidal vibrations of varying amplitudes preceded by three adapting stimuli of 0, 6 and 12 µm in amplitude. Using the framework of signal detection theory, we quantified the performance of a linear decoder which sums the responses of neurons after applying an optimum set of weights. Optimum weights were found by the analytical solution that maximized the average signal-to-noise ratio based on Fisher linear discriminant analysis. This provided a biologically plausible decoder that took into account the neuronal variability, covariability, and signal correlations. The optimal decoder achieved consistent improvement in discrimination performance over simple pooling. Decorrelating neuronal responses by trial shuffling revealed that, unlike pooling, the performance of the optimal decoder was minimally affected by noise correlation. In the non-adapted state, noise correlation enhanced the performance of the optimal decoder for some populations. Under adaptation, however, noise correlation always degraded the performance of the optimal decoder. Nonetheless, sensory adaptation improved the performance of the optimal decoder mainly by increasing signal correlation more than noise correlation. Adaptation induced little systematic change in the relative direction of signal and noise. Thus, a decoder which was optimized under the non-adapted state generalized well across states of adaptation.
Enhancing Digital Book Clustering by LDAC Model

In Digital Library (DL) applications, digital book clustering is an important and urgent research task. However, it is difficult to conduct effectively because of the great length of digital books. To do the correct clustering for digital books, a novel method based on probabilistic topic model is proposed. Firstly, we build a topic model named LDAC. The main goal of LDAC topic modeling is to effectively extract topics from digital books. Subsequently, Gibbs sampling is applied for parameter inference. Once the model parameters are learned, each book is assigned to the cluster which maximizes the posterior probability. Experimental results demonstrate that our approach based on LDAC is able to achieve significant improvement as compared to the related methods.
Parallel Sub-structuring Methods for Solving Sparse Linear Systems on a Cluster of GPUs

The main objective of this work consists in analyzing sub-structuring method for the parallel solution of sparse linear systems with matrices arising from the discretization of partial differential equations such as finite element, finite volume and finite difference. With the success encountered by the general-purpose processing on graphics processing units (GPGPU), we develop an hybrid multi GPUs and CPUs sub-structuring algorithm. GPU computing, with CUDA, is used to accelerate the operations performed on each processor. Numerical experiments have been performed on a set of matrices arising from engineering problems. We compare C+MPI implementation on classical CPU cluster with C+MPI+CUDA on a cluster of GPU. The performance comparison shows a speed-up for the sub-structuring method up to 19 times in double precision by using CUDA.
Impact of Antenna Pattern and Link Model on Directional Neighbor Discovery in 60 GHz Networks

60 GHz radio is a very attractive technology for short-range wireless communication due to its capability to provide Gbps data rate. To address the neighbor discovery (ND) problem in 60 GHz networks, we propose a novel analytical framework to investigate the ND performance. The main difficulty in modeling the ND process in a 60 GHz network is the involvement of the directional antennas with gain differences between the antenna's main lobe and side lobes. Different antenna modes - directional or omni-directional - coupled with different ND mechanisms make the analytical study demanding. In this article, we propose a comprehensive theoretical model to demonstrate the performance of ND processes using one-way ND and handshake-based ND mechanisms. Moreover, we combine them with different antenna modes, i.e., directional transmitting with omni-directional listening (DO) and directional transmitting with directional listening (DD) modes. The impact of antenna modes on the ND process is analyzed. Since 60 GHz radio is prone to co-channel interference, we examine a realistic interference-aware link model and antenna pattern via simulation studies. Our work is specifically beneficial to provide guidelines for applying directional neighbor discovery process within 60 GHz wireless networks.