Miracle-dz/UniFAR-FTUs huggingface dataset:
Phytophthora infestans RXLR-WY Effector AVR3a Associates with Dynamin-Related Protein 2 Required for Endocytosis of the Plant Pattern Recognition Receptor FLS2

Pathogens utilize effectors to suppress basal plant defense known as PTI (Pathogen-associated molecular pattern-triggered immunity). However, our knowledge of PTI suppression by filamentous plant pathogens, i.e. fungi and oomycetes, remains fragmentary. Previous work revealed that the co-receptor BAK1/SERK3 contributes to basal immunity against the potato pathogen Phytophthora infestans. Moreover BAK1/SERK3 is required for the cell death induced by P. infestans elicitin INF1, a protein with characteristics of PAMPs. The P. infestans host-translocated RXLR-WY effector AVR3a is known to supress INF1-mediated cell death by binding the plant E3 ligase CMPG1. In contrast, AVR3aKI-Y147del, a deletion mutant of the C-terminal tyrosine of AVR3a, fails to bind CMPG1 and does not suppress INF1-mediated cell death. Here, we studied the extent to which AVR3a and its variants perturb additional BAK1/SERK3-dependent PTI responses in N. benthamiana using the elicitor/receptor pair flg22/FLS2 as a model. We found that all tested variants of AVR3a suppress defense responses triggered by flg22 and reduce internalization of activated FLS2. Moreover, we discovered that AVR3a associates with the Dynamin-Related Protein 2 (DRP2), a plant GTPase implicated in receptor-mediated endocytosis. Interestingly, silencing of DRP2 impaired ligand-induced FLS2 internalization but did not affect internalization of the growth receptor BRI1. Our results suggest that AVR3a associates with a key cellular trafficking and membrane-remodeling complex involved in immune receptor-mediated endocytosis. We conclude that AVR3a is a multifunctional effector that can suppress BAK1/SERK3-mediated immunity through at least two different pathways.
Faster Clustering via Non-Backtracking Random Walks

This paper presents VEC-NBT, a variation on the unsupervised graph clustering technique VEC, which improves upon the performance of the original algorithm significantly for sparse graphs. VEC employs a novel application of the state-of-the-art word2vec model to embed a graph in Euclidean space via random walks on the nodes of the graph. In VEC-NBT, we modify the original algorithm to use a non-backtracking random walk instead of the normal backtracking random walk used in VEC. We introduce a modification to a non-backtracking random walk, which we call a begrudgingly-backtracking random walk, and show empirically that using this model of random walks for VEC-NBT requires shorter walks on the graph to obtain results with comparable or greater accuracy than VEC, especially for sparser graphs.
Critical Role of Lipopolysaccharide-Binding Protein and CD14 in Immune Responses against Gram-Negative Bacteria1

LPS-binding protein (LBP) and CD14 potentiate cell activation by LPS, contributing to lethal endotoxemia. We analyzed the contribution of LBP/CD14 in models of bacterial infection. Mice pretreated with mAbs neutralizing CD14 or LBP showed a delay in TNF-α production and died of overwhelming infection within 24 h, after a challenge with 250 CFU of virulent Klebsiella pneumoniae. Blockade of TNF-α also increased lethality, whereas pretreatment with TNF-α protected mice, even in the presence of LBP and CD14 blockade. Anti-LBP or anti-CD14 mAbs did not improve or decrease lethality with a higher inoculum (105 K. pneumoniae) and did not affect outcome following injections of low or high inocula of Escherichia coli O111. These results point to the essential role of LBP/CD14 in innate immunity against virulent bacteria.
Preparation and Properties of Cellulose Laurate (CL)/Starch Nanocrystals Acetate (SNA) Bio-nanocomposites

In the present paper, a series of totally novel bio-nanocomposite films from cellulose laurate (CL) and starch nanocrystals acetate (SNA) were fabricated, and the properties of nanocomposite films were investigated in detail. SNA was obtained by modifying starch nanocrystals (SNs) produced by sulfuric acid hydrolysis of corn starch with acetic anhydride. The favorable dispersity of SNA in chloroform made it ready to convert into nanocomposite films with CL via casting/evaporation method. The transmittance, thermal behavior, mechanical properties, barrier properties and hydrophobicity of CL/SNA nanocomposite films were investigated with UV-vis spectrophotometer, simultaneous thermal analyzer (STA), universal tensile tester/dynamic thermomechanical analysis (DMA), water vapor permeation meter/oxygen permeability tester, and contact angle tester, respectively. The transmittance of nanocomposite films decreased with the increase of SNA content. Thermogravimetric analysis (TGA) results showed that the introduction of SNA into CL matrix did not severely decrease the thermal behavior of CL/SNA nanocomposites. Moreover, non-linear and linear mechanical analysis reflected the enhancement of SNA. At lower contents of SNA (<5.0 wt%), the values of Young’s modulus, tensile strength and the elongation at break of nanocomposite films were comparable with those of neat CL. However, with the increase of SNA, the Young’s modulus and tensile strength were improved significantly and were accompanied by the decreased elongation at break. The water vapor permeability (WVP) and oxygen permeability (PO2) of CL/SNA nanocomposite films were significantly improved by the addition of SNA.
Design and Implementation of Hidden based Web Retrieval using Innovative Vision-based Segmentation

assimilate the extracted information from a conference website to acquire the clean and high superiority academic data. This research has subsequent contributors: We propose a novel vision-based page segmentation algorithm, which use DOM tree to compensate the information loss of classical vision-based segmentation algorithm. We transform the conference Web material extraction which is difficult into a classification problematic, and categorize text blocks as predefined sets permitting to vision, key disputes, text and content information. We improve the classification quality by post-processing. Our experimental results on real-world datasets shows that our method is highly effective and efficient for extracting academic information from conference pages.
Ecto 5′-Nucleotidase and Nonspecific Alkaline Phosphatase

In human airways, extracellular adenosine regulates epithelial functions supporting mucociliary clearance, an important airway defense mechanism against bacterial infection. Thus, defining the mechanisms of adenosine generation is critical for elucidating the role of this nucleoside in airway homeostasis. In this study, we identified the source of adenosine on the mucosal surface of human airway epithelia. Polarized primary cultures of human nasal or bronchial epithelial cells were assayed for transepithelial transport, cytosolic and cell surface adenosine production. Ussing chamber experiments indicated that serosal 1 μm [3H]adenosine was not transported to the mucosal compartment. Messenger RNA for the cytosolic AMP-specific 5′-nucleotidase (CN-I) was not detected in human bronchial epithelial cells, suggesting that mucosal adenosine did not originate from intracellular pools. In contrast, extracellular 0.1 mmATP was rapidly dephosphorylated into adenosine on the mucosal epithelial surface. We identified two ectonucleotidases that mediated the conversion of AMP to adenosine: ecto 5′-nucleotidase (ecto 5′-NT, CD73) and alkaline phosphatase (AP). Both mucosal and serosal epithelial surfaces displayed ecto 5′-NT activity (K m = 14 μm,V max = 0.5 nmol·min−1·cm−2), whereas AP activity was restricted to the mucosal surface (K m, high = 36 μm,V max = 1.2 nmol·min−1·cm−2;K m, low = 717 μm,V max = 2.8 nmol· min−1·cm−2). In bronchial cultures and tissues, ecto 5′-NT accounted for >80% of total activity toward 0.01 mm AMP, compared with <15% for 5 mm AMP. The proximal airway AP isoform was identified as nonspecific AP (NS AP) by levamisole sensitivity and mRNA expression. The two ectoenzymes presented opposite airway distributions, ecto 5′-NT and NS AP mRNA dominating in higher and lower airways, respectively. Collectively, these experiments support a major role for extracellular nucleotide catalysis and for ecto 5′-NT and NS AP in the regulation of adenosine concentrations on airway surfaces.
Efficient Processing of the Cube Operator

This paper presents a part of the doctoral work with the theme: “The impact of sorted reading from UB-trees on relational database systems”. Based on [Mar99] this doctoral work deals with the problems of the efficient implementation and analysis of sorted reading (UB-Cache [Bay97b], Tetris -Algorithm [MB98], [MZB99]) and its effect on query-processing and query optimization in relational databases and especially in the field of data warehousing (DW) and data-mining. In our days, the B-Tree [BM72] is a de facto standard in relational database systems for onedimensional data. Based on the B-Tree a new data structure for multidimensional data, the UB-Tree, was invented by [Bay96]. This data structure utilizes a space-filling curve to partition a multidimensional universe into disjoint regions while preserving multidimensional clustering. A space-filling curve (e.g., Z-curve) maps a ddimensional universe to a one-dimensional universe. Therefore algorithms for point queries, insertion, and multidimensional range queries can be efficiently handled by a normal B*-tree, which is available in any commercial relational database system. In our prototype implementation we use the Z-curve. A Z-address Z(x) is the ordinal number of a tuple x on the Z-curve which is used a key for the B*-Tree [Mar99].
Dissipation of Solitary Wave Due To Mangrove Forest: A Numerical Study by Using Non-Dispersive Wave Model

In this paper, we study a dissipation of solitary wave due to mangrove forest by using numerical simulation. Here, the solitary wave is chosen to represent tsunami wave form. To simulate the wave dynamic, we use the non-dispersive Nonlinear Shallow Water Equations (NSWE). The model is implemented numerically by using finite volume method in a momentum conservative staggered grid. By using the proposed numerical scheme, the numerical code is able to simulate solitary wave breaking phenomenon. Wave dissipation due to mangrove forest is modelled as bottom roughness with an approximate value of manning roughness, which is derived from the classical Morisson’s formula. To test the modelled dissipation by mangrove forest, we reconstruct a physical experiment in hydrodynamic laboratory where a solitary wave propagates above a sloping bottom, which has a parameterized mangrove in the shallower part. Two cases are performed to test the performance of the numerical implementation, i.e. the non-breaking and breaking solitary waves. Results of simulation agree quite well with the measurement data. The results of simulation are also analyzed quantitatively by calculating errors as well as correlation with the measurement data. Moreover, to investigate effects of wave steepness on solitary wave, to the reduction of wave energy, we perform numerical investigation. Various solitary waves with different wave steepness are simulated to see their effects on amplitude and energy reduction due to mangrove forest.
Brutal Cops , News Coverage , and Public Perceptions of Law Enforcement : An Experimental Investigation of Reality Construction

This research examines the relationship between newspaper coverage of police brutality, the public construction of law enforcement reality, and the predictive capacity of exemplification theory. Two randomly selected subsamples were assigned to either a control or test condition in a posttest only experiment. Those in the test group were exposed to six newspaper accounts recounting incidents of police brutality. A negative construction of reality associated with policecitizen interaction followed exposure. It is clear that public faith in law enforcement is eroded by extra legal police behavior, and that police-citizen relationships are contaminated, as a consequence. Further research is called for, involving more ethnically and racially diverse populations, a more representative age demographic, and media other than newspapers, both print and electronic.
A Content-Based Music Similarity Function

We present a method to compare songs based solely on their audio content. Our technique forms a signature for each song based on K-means clustering of spectral features. The signatures can then be compared using the Earth Mover’s Distance [14] which allows comparison of histograms with disparate bins. Preliminary objective and subjective results on a database of over 8000 songs are encouraging. For 20 songs judged by two users, on average 2.5 out of the top 5 songs returned were judged similar. We also found that our measure is robust to simple corruption of the audio signal and that meaningful visualizations of the data are possible using this similarity measure. Author email: Beth.Logan@compaq.com, asalomon@mit.edu c Compaq Computer Corporation, 2001 This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonprofit educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of the Cambridge Research Laboratory of Compaq Computer Corporation in Cambridge, Massachusetts; an acknowledgment of the authors and individual contributors to the work; and all applicable portions of the copyright notice. Copying, reproducing, or republishing for any other purpose shall require a license with payment of fee to the Cambridge Research Laboratory. All rights reserved. CRL Technical reports are available on the CRL’s web page at http://crl.research. compaq.com. Compaq Computer Corporation Cambridge Research Laboratory One Cambridge Center Cambridge, Massachusetts 02142 USA
Language Models and Reranking for Machine Translation

Complex Language Models cannot be easily integrated in the first pass decoding of a Statistical Machine Translation system -- the decoder queries the LM a very large number of times; the search process in the decoding builds the hypotheses incrementally and cannot make use of LMs that analyze the whole sentence. We present in this paper the Language Computer's system for WMT06 that employs LM-powered reranking on hypotheses generated by phrase-based SMT systems.
Association between Upper Digestive Tract Microbiota and Cancer-Predisposing States in the Esophagus and Stomach

Background: The human upper digestive tract microbial community (microbiota) is not well characterized and few studies have explored how it relates to human health. We examined the relationship between upper digestive tract microbiota and two cancer-predisposing states, serum pepsinogen I/pepsinogen II ratio (PGI/II; predictor of gastric cancer risk) and esophageal squamous dysplasia (ESD; the precursor lesion of esophageal squamous cell carcinoma; ESCC) in a cross-sectional design. Methods: The Human Oral Microbe Identification Microarray was used to test for the presence of 272 bacterial species in 333 upper digestive tract samples from a Chinese cancer screening cohort. Serum PGI and PGII were determined by ELISA. ESD was determined by chromoendoscopy with biopsy. Results: Lower microbial richness (number of bacterial genera per sample) was significantly associated with lower PGI/II ratio (P = 0.034) and the presence of ESD (P = 0.018). We conducted principal component (PC) analysis on a β-diversity matrix (pairwise difference in microbiota), and observed significant correlations between PC1, PC3, and PGI/II (P = 0.004 and 0.009, respectively), and between PC1 and ESD (P = 0.003). Conclusions: Lower microbial richness in upper digestive tract was independently associated with both cancer-predisposing states in the esophagus and stomach (presence of ESD and lower PGI/II). Impact: These novel findings suggest that the upper digestive tract microbiota may play a role in the etiology of chronic atrophic gastritis and ESD, and therefore in the development of gastric and esophageal cancers. Cancer Epidemiol Biomarkers Prev; 23(5); 735–41. ©2014 AACR.
Delta storage for arbitrary non-text files

The storage of different versions of documents is an essential part of each software version and configuration control tool. To achieve this goal without wasting an enormous amount of disk space, delta storage is a commonly-used technique. At the time being, most of the existing version control tools offer delta storage for text files only. As not all files of a software project are plain text files, delta storage should be supported for arbitrary non-text files too. This paper deals with a technique for generating deltas between arbitrary files without any presumptions about the file structure. After a brief discussion of commonly-used delta techniques for line-structured text files, the algorithm to generate deltas between arbitrary non-text files is presented. Measurements of exwution time and the size of resulting delta scripts conclude the paper.
Adapting to Change: Studying Undergraduate Research in the Current Education Environment.

Given that science and science education are undergoing a climate change, the author suggests a re-envisioning of undergraduate research assessment. He argues that continuation of research into the processes and benefits of undergraduate research opportunities for undergraduates will need to decrease focus on student dispositions and increase attention to the external validity of programs. Common dispositional terms such as persistence and identity should give way to the study of student decision making, judgment
Online head motion tracking applied to the patient registration problem.

Image-guided systems for surgical procedures in the region of the head require a method to correlate the diagnostic image data with the corresponding site of pathology in the patient. Considering that patient movement can occur, detection and correction of such movement errors during the acquisition of images is a basic prerequisite for accurate treatment. For this reason, we developed a new registration method based upon on-line tracking of the patient's head to solve the problem of registration in the presence of head motion. The method provides non-invasive active patient registration for correction of movements during imaging and continuous update of the patient's head position during surgery. The patient motion correction applies the rigid body model to register the images using feature correspondence. The new registration method is described, and results of experiments that were performed to evaluate its accuracy and reliability in a plastic skull model and in patients are presented. The error analysis resulted in a final target registration error of 0.90 mm +/- 0.16 mm using experimental model data and 1.58 mm +/- 0.26 mm using clinical patient data. In addition, the residual registration error is modeled as a function of the measured and predicted head motion in order to determine the error that is introduced by motion tracking during image data acquisition. Furthermore, the clinical application of the method is demonstrated for oto-, rhino-, and neurosurgical procedures in the region of the head.
Comparative Evaluation of the Diagenode Multiplex PCR Assay on the BD Max System versus a Routine In-House Assay for Detection of Bordetella pertussis

ABSTRACT This study looked at 128 nasopharyngeal aspirates (NPA) and 162 throat swabs (TS) tested with the Diagenode multiplex assay on the BD Max system versus our in-house Bordetella pertussis PCR. Sensitivity and specificity were 97.3% and 100% for NPA and 88.3% and 98% for TS, respectively. Of positive NPA, 42.1% were coinfected with respiratory viruses.
Predictive representations for sequential decision making under uncertainty

The problem of making decisions is ubiquitous in life. This problem becomes even more complex when the decisions should be made sequentially. In fact, the execution of an action at a given time leads to a change in the environment of the problem, and this change cannot be predicted with certainty. The aim of a decision-making process is to optimally select actions in an uncertain environment. To this end, the environment is often modeled as a dynamical system with multiple states, and the actions are executed so that the system evolves toward a desirable state. In this thesis, we proposed a family of stochastic models and algorithms in order to improve the quality of of the decision-making process. The proposed models are alternative to Markov Decision Processes, a largely used framework for this type of problems. In particular, we showed that the state of a dynamical system can be represented more compactly if it is described in terms of predictions of certain future events. We also showed that even the cognitive process of selecting actions, known as policy, can be seen as a dynamical system. Starting from this observation, we proposed a panoply of algorithms, all based on predictive policy representations, in order to solve different problems of decision-making, such as decentralized planning, reinforcement learning, or imitation learning. We also analytically and empirically demonstrated that the proposed approaches lead to a decrease in the computational complexity and an increase in the quality of the decisions, compared to standard approaches for planning and learning under uncertainty.
Selecting Landmark Points for Sparse Manifold Learning

There has been a surge of interest in learning non-linear manifold models to approximate high-dimensional data. Both for computational complexity reasons and for generalization capability, sparsity is a desired feature in such models. This usually means dimensionality reduction, which naturally implies estimating the intrinsic dimension, but it can also mean selecting a subset of the data to use as landmarks, which is especially important because many existing algorithms have quadratic complexity in the number of observations. This paper presents an algorithm for selecting landmarks, based on LASSO regression, which is well known to favor sparse approximations because it uses regularization with an l1 norm. As an added benefit, a continuous manifold parameterization, based on the landmarks, is also found. Experimental results with synthetic and real data illustrate the algorithm.
MODEL SPASIAL FAKTOR RISIKO KEJADIAN DEMAM BERDARAH DENGUE DI PROVINSI JAWA TIMUR TAHUN 2014

Indonesia is the high suitability country for transmission of dengue. One of provinces with high incidence rate of dengue fever is East Java province which was about 36 per 100,000 populationin 2013. DHF is so easy to spread from person to person and even from one area to another, so that the incidence of dengue is increasing and widespread. Analysis is needed to see the role of factors, spatial factors, which influence the incidence of dengue fever in East Java by performing spatial modeling. This research used a quantitative research approach with ecological study design to determine the correlation between the disease and the factors that are of interest in research. This study took administrative regions throughout East Javaprovince as unit of analysis. The data was secondary data which was collected through the study of documents in several institutions. The results showed that rainfall (0,0014), percentage of healty-practice house (0,0104), healthy house percentage (0,000) and health facilities per 100.000 population (0,0456) influenced the incidence of dengue fever in East Java with R square 0,4334 or 43,34%. The best model for the incidence of dengue fever in East Java province was spatial regression modeling using spatial error model (R2= 0,4334) when compared with the spatial lag regression model (R2 = 0,1858). East Java Provincial Health Office needs to anticipate the high rainfall on the incidence of dengue, provides equitable health facilities for communities, promote health practice at home and healthy home. Keywords: dengue, spatial, regression, east Java