Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic detection of problematic rules in Vietnamese Treebank

Vietnamese Treebank is a syntactically annotated corpus newly published in 2009. In this paper, we applied automated methods to detect errors in Vietnammese Treebank based on the concept of equivalence classes proposed by Dickinson. On this basis, we propose an improved method of error detection by transforming syntax trees based on vertical markovization. Our experimental results on Vietnamese Treebank showed that the scope of error detection was extended more than 2 times and the precision was improved more than 18.07% in comparison with the base line methods.
A statistical interpretation of Non-Local Means

Noise filtering is a common step in image processing, and is particularly effective in improving the subjective quality of images. A large number of techniques have been developed, many of which concentrate on the problem of removing noise without damaging small structures such as edges. One recent approach that demonstrates empirical merit is the non-local means (NLM) algorithm. With the increasing use of imaging in medicine and sciences it might be considered inevitable that researchers will try to apply such noise filtering schemes in quantitative analysis. In order to do this with confidence we need to develop an understanding of the noise removal process that goes beyond subjective appearance. The purpose of this paper is to develop and test a statistical basis of NLM, in order to try to understand the conditions required for its use. The theory is illustrated on synthetic data and real MR images of the brain.
The Role of Protein Arginine Methyltransferases in Inflammatory Responses

Protein arginine methyltransferases (PRMTs) mediate the methylation of a number of protein substrates of arginine residues and serve critical functions in many cellular responses, including cancer development, progression, and aggressiveness, T-lymphocyte activation, and hepatic gluconeogenesis. There are nine members of the PRMT family, which are divided into 4 types (types I–IV). Although most PRMTs do not require posttranslational modification (PTM) to be activated, fine-tuning modifications, such as interactions between cofactor proteins, subcellular compartmentalization, and regulation of RNA, via micro-RNAs, seem to be required. Inflammation is an essential defense reaction of the body to eliminate harmful stimuli, including damaged cells, irritants, or pathogens. However, chronic inflammation can eventually cause several types of diseases, including some cancers, atherosclerosis, rheumatoid arthritis, and periodontitis. Therefore, inflammation responses should be well modulated. In this review, we briefly discuss the role of PRMTs in the control of inflammation. More specifically, we review the roles of four PRMTs (CARM1, PRMT1, PRMT5, and PRMT6) in modulating inflammation responses, particularly in terms of modulating the transcriptional factors or cofactors related to inflammation. Based on the regulatory roles known so far, we propose that PRMTs should be considered one of the target molecule groups that modulate inflammatory responses.
A Novel Form of Progressive Retinal Atrophy in Swedish Vallhund Dogs

Inherited retinal degenerations, such as retinitis pigmentosa (RP) and age-related macular degeneration (AMD), represent leading causes of incurable blindness in humans. This is also true in dogs, where the term progressive retinal atrophy (PRA) is used to describe inherited photoreceptor degeneration resulting in progressive vision loss. Because of the similarities in ocular anatomy, including the presence of a cone photoreceptor-rich central retinal region, and the close genotype-phenotype correlation, canine models contribute significantly to the understanding of retinal disease mechanisms and the development of new therapies. The screening of the pure-bred dog population for new forms of PRA represents an important strategy to establish new large animal models. By examining 324 dogs of the Swedish vallhund breed in seven countries and across three continents, we were able to describe a new and unique form of PRA characterized by the multifocal appearance of red and brown discoloration of the tapetal fundus followed over time by thinning of the retina. We propose three stages of the disease based on the appearance of the ocular fundus and associated visual deficits. Electroretinography revealed a gradual loss of both rod and cone photoreceptor-mediated function in Stages 2 and 3 of the disease. In the few dogs that suffered from pronounced vision loss, night-blindness occurred first in late Stage 2, followed by decreased day-vision in Stage 3. Histologic examinations confirmed the loss of photoreceptor cells at Stage 3, which was associated with the accumulation of autofluorescent material in the adjacent retinal pigment epithelium. Pedigree analysis was suggestive of an autosomal-recessive mode of inheritance. Mutations in six known canine retinal degeneration genes as well as hypovitaminosis E were excluded as causes of the disease. The observed variability in the age of disease onset and rate of progression suggest the presence of genetic and/or environmental disease modifiers.
LCC's GISTexter at DUC 2007: Machine Reading for Update Summarization

In this paper, we describe Language Computer Corporation’s GISTEXTER question-focused and update-based multidocument summarization (MDS) systems. We show that by using a machine reading (MR) framework in order to construct representations of the knowledge inferable from a text collection, we were able to create coherent sets of iupdatei summaries that were likely to contain inewi information that could not be inferred from any previously considered document. Details of our DUC 2007 Main Task submission are provided as well.
Role of the proteasome in membrane extraction of a short‐lived ER‐transmembrane protein

Selective degradation of proteins at the endoplasmic reticulum (ER‐associated degradation) is thought to proceed largely via the cytosolic ubiquitin–proteasome pathway. Recent data have indicated that the dislocation of short‐lived integral‐membrane proteins to the cytosolic proteolytic system may require components of the Sec61 translocon. Here we show that the proteasome itself can participate in the extraction of an ER‐membrane protein from the lipid bilayer. In yeast mutants expressing functionally attenuated proteasomes, degradation of a short‐lived doubly membrane‐spanning protein proceeds rapidly through the N‐terminal cytosolic domain of the substrate, but slows down considerably when continued degradation of the molecule requires membrane extraction. Thus, proteasomes engaged in ER degradation can directly process transmembrane proteins through a mechanism in which the dislocation of the substrate and its proteolysis are coupled. We therefore propose that the retrograde transport of short‐lived substrates may be driven through the activity of the proteasome.
An approach based on Fourier descriptors and decision trees to perform presumptive diagnosis of esophagitis for educational purposes

According to World Cancer Research Fund International the esophageal cancer is the eighth most common malignancy and the sixth most common cause of cancer-related death in the world. This disease can be originated by various causes, being the Barrett's esophagus his previous stage. The Barrett's esophagus is present in several cases of patients suffering from gastric reflux. Therefore, it is fundamental to have tools able to detect the earlier stages of esophageal cancer (esophagitis). On those grounds, in this paper we propose a method that allows detecting the esophagitis using an approach based on the analysis of esophageal irregularities (the Z-line). In order to analyze these irregularities, we have applied the Fourier transform on shape signature of the Z-line. With the aim of validate the proposed method, we have used K Nearest Neighbor criterion and Random Forest on a database consisting on 26 real cases of patients (10 healthy and 16 suffering from the disease). The results are promising in terms of precision, sensitivity, and specificity (0.81, 0.86 and 0.72, respectively).
Sensation of learning analytics top prevail the software engineering education

Software pockets an indispensable role in the modern living style to make their work easy. Software engineers are the people who develop the software to comply with the user needs and make them joyful. Software engineering education is the place where the software engineers mold up academically for the society's requirement. As a result, software engineering education grabs the essence in the computer education, albeit it fall shorts to cook up the genius to meet with the industries necessity. To overcome these issues, researchers suggested number of software engineering learning/teaching methods to egg on students to acquire their profundity knowledge in software engineering. Even though the suggestions do not utterly surmount this crucial issue since the suggested approaches did not attract the maj ority of the students and touch their learning style. Learning analytics plays a vital role to improve the students learning activities. Learning style and learning engagement are the key factors for the learning analytics. This paper focuses on learning style and learning engagement of the software engineering students. This work classifies the students in line with their learning style and identifies the needs of the software engineering students using learning engagement finally proposed the model to inspire the students to overcome such issues and motivate them in gathering software engineering knowledge.
A Survey of Polyphonic Sound Event Detection Based on Non-Negative Matrix Factorization

Nowadays, sound event detection (SED) is a popular study in machine listening area. Detecting overlapping sound events, in which many sound events occur simultaneously, is challenging and interesting topic. Besides, non-negative matrix factorization (NMF) and its derived methods are suitably used to perform SED. This paper presents a survey of recent approaches in SED based on NMF methods that provides the understanding and strategies for detecting polyphonic sound events.
A scalable smooth graph learning method based on Bernoulli-Gaussian model

The graph topology is the basis of graph signal processing. This paper investigates how to learn a smooth and sparse weight matrix for an undirected graph from the signals observed on the graph. The idea is based on the locally linear embedding and Bernoulli-Gaussian model, from which a nonconvex optimization problem is derived. This paper introduces a scalable algorithm to work out a sparse and smooth graph. Compared with the L ι relaxation method, our algorithm can obtain suboptimal solution more efficiently. Numerical results illustrate the advantages of the graph constructed by the proposed method in the frequency analysis of graph signals.
Development of an intelligent object for grasp and manipulation research

In this paper we introduce a novel device, called iObject, which is equipped with tactile and motion tracking sensors that allow for the evaluation of human and robot grasping and manipulation actions. Contact location and contact force, object acceleration in space (6D) and orientation relative to the earth (3D magnetometer) are measured and transmitted wirelessly over a Bluetooth connection. By allowing human-human, human-robot and robot-robot comparisons to be made, iObject is a versatile tool for studying manual interaction. To demonstrate the efficiency and flexibility of iObject for the study of bimanual interactions, we report on a physiological experiment and evaluate the main parameters of the considered dual-handed manipulation task.
Data type based security alert dialogs

Making users aware of insecure situations and behavior while browsing the Internet is a highly discussed and still difficult task. Both, passive and active warnings have their own specific disadvantages. While active warnings interrupt the current task and annoy the user, passive approaches often fail since they go unnoticed. In this work, we present first results of a concept displaying data type based alert dialogs whenever a user enters critical information into an online form. Such contextual dialogs appear right in the users' field of view representing a hybrid approach between active and passive warnings. An initial user study was conducted that showed a significant improvement of security awareness by participants that used the tool.
ASIC Design Implementation of Memory Efficient Infinite Impulse Response UWB Equalizer

Channel Equalization plays an important role in reducing distortion and Inter-Symbol Interference (ISI) to improve the quality of transmission in Ultra-Wide Band (UWB) channel. Many equalization techniques have been proposed in the past but the proposed techniques in this paper describes Infinite Impulse Response (IIR) equalizer architecture which halves the memory requirement of conventional IIR equalizers. This is achieved by exploiting the aperiodically repeated clusters of negative-exponentially decaying segments of Channel Impulse Response (CIR) and hence by providing a single delayline between the input and output of the equalizer. Further this architecture is realized by implementing on Application Specific Integrated Circuit (ASIC) using Mentor Graphics IC Design tools. Mathematical modeling gives suitable parameters of the IIR Filter, followed by Register Transfer Level (RTL) Design using Very High Descriptive Language (VHDL), ASIC synthesis to TSMC 0.35um process technology, physical modeling using advanced layout techniques. The IIR equalization filter is designed using 8758 Metal Oxide Semi-conductor (MOS) transistors with core cell area of 0.406mm2. Streszczenie. W artykule zaproponowano architekturę ekwalizera NOI, która zmniejsza wymagania pamięci przy transmisji szerokopasmowej w układach ASIC. Zaprezentowano układ w technologii 35 nm z tranzystorami MOS przy powierzchni celki jądra 0.406 mm2. (Projekt szerokopasmowego ekwalizera NOI w układach ASIC)
Evidence for Two Independent Accretion Flows in Galactic Black-Hole Candidates

We discuss the results of long-term hard x-ray monitoring of Galactic blackhole candidates 1E 1740.7–2942, GRS 1758–258, Cyg X–1, GX 339–4, and Cyg X–3 with the Rossi X-Ray Timing Explorer (RXTE). The objects divide into two classes. In the first class, exemplified by Cyg X–1, luminosity and spectral hardness evolve simultaneously. In the second class, the relation is complicated and shows hysteresis: e.g., the softest spectra occur while the count rate is dropping. Most models of accretion, generally tailored to Cyg X–1, cannot explain the second sort of behavior. It can be explained qualitatively by a simple model with two simultaneous, independent accretion flows: a thin disk and a hot halo. The time delay between changes in luminosity and spectrum is due to the viscous delay in the thin disk: changes in the mass input from the companion propagate through the halo immediately but can take up to several weeks to propagate through the disk. This picture is strongly supported by the observation that those sources which show delays ( 1E 1740.7–2942, GRS 1758–258, and GX 339–4) are expected to have low-mass companions, and those which do not (Cyg X–1, Cyg X–3) are known or thought to have high-mass companions. Low-mass companions imply accretion by Roche-lobe overflow, with a high specific angular momentum in the accreting material, and therefore a large disk with a long viscous timescale. Wind accretion from massive companions is expected to result in a much smaller disk, and thus little viscous delay. Subject headings: accretion, accretion disks — black hole physics — x-rays:stars — stars,individual:(1E 1740.7-2942) — stars,individual:(GRS 1758-258) — stars,individual:(GX 339-4) — stars,individual:(Cyg X-1) — stars,individual:(Cyg X-3) Space Sciences Laboratory, University of California Berkeley, Berkeley, CA 94720 Center for Astrophysics and Space Sciences, Code 0424, University of California San Diego, La Jolla, CA 92093 NASA Goddard Space Flight Center, Code 666, Greenbelt, MD 20771
Random Discrete Morse Theory and a New Library of Triangulations

We introduce random discrete Morse theory as a computational scheme to measure the complexity of a triangulation. The idea is to try to quantify the frequency of discrete Morse matchings with few critical cells. Our measure will depend on the topology of the space, but also on how nicely the space is triangulated. The scheme we propose looks for optimal discrete Morse functions with an elementary random heuristic. Despite its naiveté, this approach turns out to be very successful even in the case of huge inputs. In our view, the existing libraries of examples in computational topology are “too easy” for testing algorithms based on discrete Morse theory. We propose a new library containing more complicated (and thus more meaningful) test examples.
Multichannel diffuse optical Raman tomography for bone characterization in vivo: a phantom study

Raman spectroscopy is used to gather information on the mineral and organic components of bone tissue to analyze their composition. By measuring the Raman signal of bone through spatially offset Raman spectroscopy the health of the bone can be determined. We’ve customized a system with 8 collection channels that consist of individual fibers, which are coupled to separate spectrometers and cooled CCDs. This parallel detection system was used to scan gelatin phantoms with Teflon inclusions of two sizes. Raman signals were decoupled from the autofluorescence background using channel specific polynomial fitting. Images with high contrast to background ratios of Raman yield and accurate spatial resolution were recovered using a model-based diffuse tomography approach.
A Data Delivery Approach Based on Location and Velocity Vector for Delay Tolerant Mobile Sensor Networks

Delay Tolerant Mobile Sensor Networks (DTMSN) has the enormous potential to expand its applications in many previously impossible fields. Because of its intermittent link and limited network resources, this network needs an effective data forwarding algorithm to ensure valid data forwarding and highly delivery ratio. Recent approaches have drawbacks of computing nodes' delivery probability, because they only paid attention to partial factors. In this paper, a Location and Velocity vector based data Delivery approach (LVD) was proposed, which gives an in-depth description of nodes' motion state, and more accurately calculates the delivery probability based on the location and velocity vector. Simulation results show that this approach cannot only improve the message delivery rate with lower transmission overhead, but also reduce data transmission delay.
A User Guided Iterative Alignment Approach for Ontology Mapping

The future of the Semantic Web envisions an interconnected network of data and systems where software agents can communicate seamlessly to perform complicated tasks with limited human intervention or input. One of the biggest obstacles germane to this vision, however, is the ability of systems to align ontologies correctly to translate and merge disparate but similar domains of knowledge into a single perspective. If ontologies are correctly aligned, the ability to organize and integrate separate data sources enables human or software agents to draw conclusions and gain insight that otherwise would be difficult or impossible. In this paper we concentrate on the ontology alignment problem by presenting a tool called Ontrapro—the Ontology Translation Protocol, which allows users to apply the Similarity Flooding algorithm to the ontology alignment problem in an iterative fashion. Alignment results are presented for the user to modify and guide the ontology alignment process until an acceptable result set is determined. Our scenario demonstrates how Ontrapro and its toolset will result in more reliable ontology mappings, further enabling the possibility of semantic interoperability and taking us one step closer towards the original vision of the Semantic Web.
A Sociodemographic and Neuropsychological Characterization of an Illiterate Population

The objectives of this article are to characterize the performance and to discuss the performance differences between literate and illiterate participants in a well-defined study population. We describe the participant-selection procedure used to investigate this population. Three groups with similar sociocultural backgrounds living in a relatively homogeneous fishing community in southern Portugal were characterized in terms of socioeconomic and sociocultural background variables and compared on a simple neuropsychological test battery; specifically, a literate group with more than 4 years of education (n = 9), a literate group with 4 years of education (n = 26), and an illiterate group (n = 31) were included in this study. We compare and discuss our results with other similar studies on the effects of literacy and illiteracy. The results indicate that naming and identification of real objects, verbal fluency using ecologically relevant semantic criteria, verbal memory, and orientation are not affected by literacy or level of formal education. In contrast, verbal working memory assessed with digit span, verbal abstraction, long-term semantic memory, and calculation (i.e., multiplication) are significantly affected by the level of literacy. We indicate that it is possible, with proper participant-selection procedures, to exclude general cognitive impairment and to control important sociocultural factors that potentially could introduce bias when studying the specific effects of literacy and level of formal education on cognitive brain function.
Simulating the covariance risk of consumer debt portfolios

Consumer loan risk is hard to predict, since loans are heterogeneous, have no measurable prices in financial markets and may be significantly correlated with macro events. This work proposes a heterogeneous agents’model of household credit risk, with shocks to both labor income and credit access. Using the Chilean Household Finance Survey I simulate the default conditions of different households over distinct macro scenarios. I show that banks’ loan portfolios have very different Covariance risk in relation to macro events, with some banks being prone to high risk during recessions. JEL Classification: E21; E24; E32; E51; G01; G21.
SRT Division: Architectures, Models, and Implementations

SRT dividers are common in modern floating point units. Higher division performance is achieved by retiring more quotient bits in each cycle. Previous research has shown that realistic stages are limited to radix-2 and radix-4. Higher radix dividers are therefore formed by a combination of low-radix stages. In this paper, we present an analysis of the effects of radix-2 and radix-4 SRT divider architectures and circuit families on divider area and performance. Using analytical modeling and simulation, we evaluate the performance and area of a wide variety of divider architectures and implementations. We conclude that divider performance is only weakly sensitive to reasonable choices of architecture but is significantly improved by aggressive circuit techniques.