Miracle-dz/UniFAR-FTUs huggingface dataset:
A Single-Amino-Acid Substitution in the NS1 Protein Changes the Pathogenicity of H5N1 Avian Influenza Viruses in Mice

ABSTRACT In this study, we explored the molecular basis determining the virulence of H5N1 avian influenza viruses in mammalian hosts by comparing two viruses, A/Duck/Guangxi/12/03 (DK/12) and A/Duck/Guangxi/27/03 (DK/27), which are genetically similar but differ in their pathogenicities in mice. To assess the genetic basis for this difference in virulence, we used reverse genetics to generate a series of reassortants and mutants of these two viruses. We found that a single-amino-acid substitution of serine for proline at position 42 (P42S) in the NS1 protein dramatically increased the virulence of the DK/12 virus in mice, whereas the substitution of proline for serine at the same position (S42P) completely attenuated the DK/27 virus. We further demonstrated that the amino acid S42 of NS1 is critical for the H5N1 influenza virus to antagonize host cell interferon induction and for the NS1 protein to prevent the double-stranded RNA-mediated activation of the NF-κB pathway and the IRF-3 pathway. Our results indicate that the NS1 protein is critical for the pathogenicity of H5N1 influenza viruses in mammalian hosts and that the amino acid S42 of NS1 plays a key role in undermining the antiviral immune response of the host cell.
A framework for exploiting collaborative traces

Any activity in a computer-supported cooperative working environment produces a set of traces. In a collaborative working context, such traces may be very voluminous and heterogeneous. They reflect all the interactive actions among the actors themselves and between the actors and the system. This paper examines what is required to exploit traces in the context of a collaborative working environment. The objective is to propose a model abstracting the exploiting process from a set of collaborative traces, according to a goal and a specific target framework. The example of the SWOT analysis is described to illustrate the approach.
Adoption Process for VoIP: The UTAUT Model

This study tests the appropriateness of the Unified Theory of Acceptance and Use of Technology UTAUT model in the context of end user consumption by means of an online survey with four hundred and seventy five respondents 24% response rate. The study shows which factors have the greatest impact on the adoption process of VoIP technology in the US market in addition to the interactions of the main variables in the model Performance Expectancy, Effort Expectancy, Social Influence, and Behavioral Intention to Adopt using Partial Least Squares PLS. The model includes four moderator variables Gender, Age, Experience, and Voluntariness of Use. The results of this study can be found further in the article.
COMPUTATIONAL FLUID DYNAMICS THROUGHOUT THE DESIGN PROCESS IN NUCLEAR APPLICATIONS

Though Computational Fluid Dynamics (CFD) is recognized as an emerging engineering tool, it is not infrequent that engineering projects make little or no use of it during the early design stages. CFD codes, if used at all, are left for the final stages in which an already finished design is tested to confirm its performance before construction. Scaled mock-ups are also used at these stages, but in many cases they are economically unaffordable. In a nuclear reactor the operational radiation dose results from coupled processes of coolant flow and species radioactive decay. Thermal-hydraulic phenomena such as stratification, stagnation and inappropriate flow pattern should thus be considered from the early design stages. In this article we want to report on an innovative experience in this direction, namely the application of CFD since the first stages of the design of some components of the reactor to be built by INVAP S. E. in Lucas Height, Australia, for the Australian National Science and Technology Organization (ANSTO). The analysis of the aforementioned components leads, sooner or later, to the need for massive threedimensional simulations which can only be performed with high performance computing techniques. This motivates a brief description of the software (PAR-GPFEP, presented in MECOM’2000) and of the hardware (Linux PC-cluster) used to successfully produce the simulations. The two case studies addressed in this presentation elaborate on the scientific, software-related and strategic aspects of CFD consulting work throughout the design process. Though the application is specific to the nuclear industry, the methodologies are applicable to many other areas of engineering design.
Recognition of Online Handwritten Mathematical Expressions

A fair amount of work has been done thus far towards automatic human handwriting recognition. Digit recognition has been well-studied using the MNIST dataset, and its classification approximates human performance [1]. Character recognition has been similarly well-studied [2]. In addition, a simple Google search yields results of small projects many have done with respectable outcomes close to perfect accuracy. Thus, character and digit recognition have been well-studied and achieved levels comparable to human performance. There have been many papers published to date on general handwriting (English words and numbers) [5]. Handwriting recognition is comprised of two general parts: offline recognition, where the text was written in a non-digital medium (e.g. a handwritten letter), and online recognition, where the text was written on a special digitzer where the sensor picks up the pen-tip movements (e.g. using a stylus to take notes on a tablet). Though offline handwriting accuracy still lags behind online handwriting accuracy, it is accurate enough now to be used in real-world systems such as interpreting handwritten postal addresses or monetary values on bank checks [5]. Online handwriting has the benefit of including additional metadata such as stroke information, which can be used by the algorithm. Less progress has been made surrounding handwritten equation recognition. The 2012 Competition on Recognition of Online Handwritten Mathematical Expressions (CROHME) [3] had 7 serious competitors. The system that was best by far, and the only system with better than 50% accuracy on all tests, was submitted by Vision Objects. Vision Objects has online demos for the handwriting and equation recognition engine [4], and there is no doubt that their technology is great. However, Vision Objects is also a privately held company with proprietary technology. Thus, we decided to tackle this problem for our 221 project.
Using Structure to Explore the Sequence Alignment Space of Remote Homologs

Protein structure modeling by homology requires an accurate sequence alignment between the query protein and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that is “optimal” in terms of the DP score does not necessarily correspond to the alignment that produces the most accurate structural model. That is, the correct alignment based on structural superposition will generally have a lower score than the optimal alignment obtained from sequence. Variations of the DP algorithm have been developed that generate alternative alignments that are “suboptimal” in terms of the DP score, but these still encounter difficulties in detecting the correct structural alignment. We present here a new alternative sequence alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements and combining high-scoring fragments that pass basic tests for “modelability”, we can generate accurate alignments within a small ensemble. Our results suggest that the set of sequences that can currently be modeled by homology can be greatly extended.
Oxidative Nerve Cell Death in Alzheimers Disease and Stroke: Antioxidants as Neuroprotective Compounds

Abstract Many neurodegenerative disorders and syndromes are associated with an excessive generation of reactive oxygen species (ROS) and oxidative stress. The pathways to nerve cell death induced by diverse potential neurotoxins such as peptides, excitatory amino acids, cytokines or synthetic drugs commonly share oxidative downstream processes, which can cause either an acute oxidative destruction or activate secondary events leading to apoptosis. The pathophysiological role of ROS has been intensively studied in in vitro and in vivo models of chronic neurodegenerative diseases such as Alzheimers disease (AD) and of syndromes associated with rapid nerve cell loss as occuring in stroke. In AD, oxidative neuronal cell dysfunction and cell death caused by protofibrils and aggregates of the ADassociated amyloid β protein (Aβ) may causally contribute to pathogenesis and progression. ROS and reactive nitrogen species also take part in the complex cascade of events and the detrimental effects occuring during ischemia and reperfusion in stroke. Direct antioxidants such as chainbreaking free radical scavengers can prevent oxidative nerve cell death. Although there is ample experimental evidence demonstrating neuroprotective activities of direct antioxidants in vitro, the clinical evidence for antioxidant compounds to act as protective drugs is relatively scarce. Here, the neuroprotective potential of antioxidant phenolic structures including αtocopherol (vitamin E) and 17βestradiol (estrogen) in vitro is summarized. In addition, the antioxidant and cytoprotective activities of lipophilic tyrosine and tryptophancontaining structures are discussed. Finally, an outlook is given on the neuroprotective potential of aromatic amines and imines, which may comprise novel lead structures for antioxidant drug design.
A Framework for Path Sensitive Program Analysis

We present a framework that produces path-sensitive analyses with different tradeoffs of accuracy and efficiency. The first component is a program transformation that restructures a CFG in order to encode path-sensitivity into it. The method consists of deleting infeasible paths from the CFG while performing selective node splitting based on information captured from infeasible paths. This transformation is fully independent from the analysis and can be built offline. Our initial experiments demonstrate that the size of the resulting CFG increases by a reasonable factor and its use can produce significant accuracy gains for several analyses. The second component is a generic backward algorithm that interleaves the above process with the computation of the analysis. This synergy allows using analysis information in order to decide whether a node should be joined or not. We use the concept of witness that establishes the conditions, using some knowledge from the analysis, to ensure that a node can be joined without incurring in any loss of accuracy. We demonstrate that although more expensive this concept can be implemented producing more precise results.
Fast Odometry Integration in Local Bundle Adjustment-Based Visual SLAM

The Simultaneous Localisation And Mapping (SLAM) for a camera moving in a scene is a long term research problem. Here we improve a recent visual SLAM which applies Local Bundle Adjustments (LBA) on selected key-frames of a video: we show how to correct the scale drift observed in long monocular video sequence using an additional odometry sensor. Our method and results are interesting for several reasons: (1) the pose accuracy is improved on real examples (2) we do not sacrifice the consistency between the reconstructed 3D points and image features to fit odometry data (3) the modification of the original visual SLAM method is not difficult.
Image Aesthetic Evaluation Using Parallel Deep Convolution Neural Network

Traditional image aesthetic evaluation method usually involves the extraction of a set of relevant image aesthetic features and classification by a classifier trained on the set of features. The system's performance greatly depends on the effectiveness of the features. However, most of these features are carefully hand-crafted for specific datasets and assumed strong prior knowledge. Therefore, these features would not be optimal for general image aesthetic evaluation. The deep convolution neural network (DCNN) has the ability to automatically learn aesthetic features, and network structure of different complexity can learn aesthetic features at different scales and different point of views. Moreover, traditional image features, such as edge and saliency map, can be used as auxiliary information for the DCNN. Therefore, a Network-Paralleled and Data-Paralleled DCNN (NP-DP-DCNN) structure is proposed. The Network-Paralleled DCNN fuses networks of different complexity and the Data-Paralleled DCNN fuses original image data and derived feature maps to learn the aesthetic features from different scales and different point of views. Experimental results show that the proposed NP-DP-DCNN structure is able to achieve better classification performance than many existing methods.
Biological Control of Crown Gall on Peach and Cherry Rootstock Colt by Native Agrobacterium radiobacter Isolates

Crown gall caused by Agrobacterium tumefaciens is the major limiting factor in raising healthy stone fruit plants in nurseries. The incidence of crown gall varies from 4 to 97.5 per cent at different locations resulting in out right rejection of an average of 30 per cent stone fruit plants in nurseries. Agrobacterium radiobacter strain K-84 has been re- ported to provide nearly complete control of this disease, however this strain is not available in India. Therefore, the pre- sent work was aimed to evaluate the antagonistic activity of twelve native A. radiobacter isolates from peach cv. Redhaven, July Elberta and cherry cv. Stella rhizosphere soil against A. tumefaciens. Agrocin production was detected in three isolates of A. radiobacter UHFBA-8, UHFBA-11 and UHFBA-12, and in cross inoculation test against A. tumefa- ciens, all the three isolates completely inhibited gall formation into tomato stems, whereas inoculation of pAg - variants of UHFBA-8 and UHFBA-11 resulted in 87.6 per cent less number of galls per wound and 96 per cent reduced gall size into inoculated tomato stems. Root dip treatment of peach plants with isolate UHFBA-11 resulted in 5.37 per cent incidence of crown gall in contrast to more than 54 per cent galled plants that had not received the treatment. In cherry rootstock Colt, isolate UHFBA-8 as root dip minimized crown gall incidence to 22.22 per cent as compared to 71.11 per cent incidence in untreated plants. Rifampicin resistant mutants of A. radiobacter isolate viz., UHFBA-8 and 11 efficiently colonized the root system of peach and Colt and their populations remained in the tissues of treated plants throughout the growing sea- son. The data suggest that other mechanisms such as efficient colonization of root system, binding and physical blockage of infection sites are involved in biological control by A. radiobacter in addition to production of agrocin.
Association and linkage studies of Huntington's chorea in relation to fifteen genetic markers.

A search for association and linkage was made between Huntington's chorea and the following marker systems: ABO, MN, Rh, P, K, Fy, Jk, Se, AcP, AK, PGM1, 6-PGD, Tf, Hp and Gc. An association was found between Huntington's chorea and the blood group phenotype Fy(a+). Preliminary analysis of the data did not indicate the presence of close linkage, but in view of the uncertainty of the final diagnosis of some healthy siblings it was deemed desirable to re-analyse the data in about 10 to 15 years time.
Recovering scenes by polarization analysis

We devise a computer vision approach which removes degradation effects in optical underwater imaging. It exploits natural illumination. By analysis of the physical effects of visibility degradation, we associate natural backscatter with partial polarization of light. This is contrary to prior studies which have associated polarization with light emanating from the objects, rather than the backscatter. Our algorithm takes advantage of this aspect to invert the image formation process. In this paper we show that our method achieves a much better visibility recovery, compared to prior methods. This is demonstrated in underwater experimentation in the sea. In addition, the physics-based analysis of the polarization filtered images recovers a range-map of the scene. This allows 3D rendering of the scene from various viewpoints
Collection and Analyses of WSJ-CSR Data at MIT

Recently, the DARPA community started a new data collection initiative in the Wall Street Journal (WSJ) domain to support research and development of very large vocabulary continuous speech recognition (CSR) systems. Since August 1991, our group has actively participated in the development of the WSJ-CSR corpus. The purpose of this paper is to document our involvement in this process, from recording and transcription to analyses and distribution. We will also present the results of an experiment investigating the preprocessing of the prompt text.
Cardiomyocyte Microvesicles Contain DNA/RNA and Convey Biological Messages to Target Cells

Background Shedding microvesicles are membrane released vesicles derived directly from the plasma membrane. Exosomes are released membrane vesicles of late endosomal origin that share structural and biochemical characteristics with prostasomes. Microvesicles/exosomes can mediate messages between cells and affect various cell-related processes in their target cells. We describe newly detected microvesicles/exosomes from cardiomyocytes and depict some of their biological functions. Methodology/Principal Findings Microvesicles/exosomes from media of cultured cardiomyocytes derived from adult mouse heart were isolated by differential centrifugation including preparative ultracentrifugation and identified by transmission electron microscopy and flow cytometry. They were surrounded by a bilayered membrane and flow cytometry revealed presence of both caveolin-3 and flotillin-1 while clathrin and annexin-2 were not detected. Microvesicle/exosome mRNA was identified and out of 1520 detected mRNA, 423 could be directly connected in a biological network. Furthermore, by a specific technique involving TDT polymerase, 343 different chromosomal DNA sequences were identified in the microvesicles/exosomes. Microvesicle/exosomal DNA transfer was possible into target fibroblasts, where exosomes stained for DNA were seen in the fibroblast cytosol and even in the nuclei. The gene expression was affected in fibroblasts transfected by microvesicles/exosomes and among 333 gene expression changes there were 175 upregulations and 158 downregulations compared with controls. Conclusions/Significance Our study suggests that microvesicles/exosomes released from cardiomyocytes, where we propose that exosomes derived from cardiomyocytes could be denoted “cardiosomes”, can be involved in a metabolic course of events in target cells by facilitating an array of metabolism-related processes including gene expression changes.
stx1c Is the Most Common Shiga Toxin 1 Subtype among Shiga Toxin-Producing Escherichia coli Isolates from Sheep but Not among Isolates from Cattle

ABSTRACT Unlike Shiga toxin 2 (stx2) genes, most nucleotide sequences of Shiga toxin 1 (stx1) genes from Shiga toxin-producing Escherichia coli (STEC), Shigella dysenteriae, and several bacteriophages (H19B, 933J, and H30) are highly conserved. Consequently, there has been little incentive to investigate variants of stx1 among STEC isolates derived from human or animal sources. However stx1OX3, originally identified in an OX3:H8 isolate from a healthy sheep in Germany, differs from other stx1 subtypes by 43 nucleotides, resulting in changes to 12 amino acid residues, and has been renamed stx1c. In this study we describe the development of a PCR-restriction fragment length polymorphism (RFLP) assay that distinguishes stx1c from other stx1 subtypes. The PCR-RFLP assay was used to study 378 stx1-containing STEC isolates. Of these, 207 were isolated from sheep, 104 from cattle, 45 from humans, 11 from meat, 5 from swine, 5 from unknown sources, and 1 from a cattle water trough. Three hundred fifty-five of the 378 isolates (93.9%) also possessed at least one other associated virulence gene (ehxA, eaeA, and/or stx2); the combination stx1, stx2, and ehxA was the most common (175 of 355 [49.3%]), and 90 of 355 (25.4%) isolates possessed eaeA. One hundred thirty-six of 207 (65.7%) ovine isolates possessed stx1c alone and belonged to 41 serotypes. Seventy-one of 136 (52.2%) comprised the common ovine serotypes O5:H−, O128:H2, and O123:H−. Fifty-two of 207 isolates (25.1%) possessed an stx1 subtype; 27 (51.9%) of these belonged to serotype O91:H−. Nineteen of 207 isolates (9.2%) contained both stx1c and stx1 subtypes, and 14 belonged to serotype O75:H8. In marked contrast, 97 of 104 (93.3%) bovine isolates comprising 44 serotypes possessed an stx1 subtype, 6 isolates possessed stx1c, and the remaining isolate possessed both stx1c and stx1 subtypes. Ten of 11 (91%) isolates cultured from meat in New Zealand possessed stx1c (serotypes O5:H−, O75:H8/H40, O81:H26, O88:H25, O104:H−/H7, O123:H−/H10, and O128:H2); most of these serotypes are commonly recovered from the feces of healthy sheep. Serotypes containing stx1 recovered from cattle rarely were the same as those isolated from sheep. Although an stx1c subtype was never associated with the typical enterohemorrhagic E. coli serogroups O26, O103, O111, O113, and O157, 13 human isolates possessed stx1c. Of these, six isolates with serotype O128:H2 (from patients with diarrhea), four O5:H− isolates (from patients with hemolytic-uremic syndrome), and three isolates with serotypes O123:H− (diarrhea), OX3:H8 (hemolytic-uremic syndrome), and O81:H6 (unknown health status) represent serotypes that are commonly isolated from sheep.
Advances in Proteome Analysis by Mass Spectrometry*

Proteome characterization using mass spectrometry is essential for the systematic investigation of biological systems and for the study of gene function. Recent advances in this multifaceted field have occurred in four general areas: protein and peptide separation methodologies; selective labeling chemistries for quantitative measurement of peptide and protein abundances; characterization of post-translational protein modifications; and instrumentation.