Miracle-dz/UniFAR-FTUs huggingface dataset:
An Approach to Find Related Communities Based on Bipartite Graphs

In this paper we investigate the problem of extracting related community information from a large collection of Web-pages by performing hyperlink analysis. We consider a group of communities (say related community set) related if they have common interests on some topic. In the proposed approach, we employ dense bipartite graph (DBG) abstraction for two purposes. From the given page collection, we first extract all the communities by mathematically abstracting the community as a DBG over a set of pages. Next, our approach extracts related communities among the communities by abstracting related community set as a DBG over set of communities. We report experimental results on 10 GB TREC (Text REtrieval Conference) data collection that contains 1.7 million pages and 21.5 million links. The results demonstrate that the proposed approach extracts related community structures. Index terms Web mining; Communities; trawling; Link analysis
Feature Filtering for Instance-Specific Algorithm Configuration

Instance-Specific Algorithm Configuration (ISAC) is a novel general technique for automatically generating and tuning algorithm portfolios. The approach has been very successful in practice, but up to now it has been committed to using all the features it was provided. However, traditional feature filtering techniques are not applicable, requiring multiple computationally expensive tuning steps during the evaluation stage. To this end, we show three new evaluation functions that use precomputed runtimes of a collection of untuned solvers to quickly evaluate subsets of features. One of our proposed functions even shows how to generate such an effective collection of solvers when only one highly parameterized solver is available. Using these new functions, we show that the number of features used by ISAC can be reduced to less than a quarter of the original number while often providing significant performance gains. We present numerical results on both SAT and CP domains.
The Nonsubsampled Contourlet Transform Based Statistical Medical Image Fusion Using Generalized Gaussian Density

We propose a novel medical image fusion scheme based on the statistical dependencies between coefficients in the nonsubsampled contourlet transform (NSCT) domain, in which the probability density function of the NSCT coefficients is concisely fitted using generalized Gaussian density (GGD), as well as the similarity measurement of two subbands is accurately computed by Jensen-Shannon divergence of two GGDs. To preserve more useful information from source images, the new fusion rules are developed to combine the subbands with the varied frequencies. That is, the low frequency subbands are fused by utilizing two activity measures based on the regional standard deviation and Shannon entropy and the high frequency subbands are merged together via weight maps which are determined by the saliency values of pixels. The experimental results demonstrate that the proposed method significantly outperforms the conventional NSCT based medical image fusion approaches in both visual perception and evaluation indices.
Collaborative Artmaking for Reducing Marginalization

Research has shown that the study of children’s drawings can shed light on certain problems, allowing many invisible sides of children’s school life to emerge. Based on the results of that research, this article will study whether the use of drawings, and art in general, could lead to the reduction of social and academic marginalization and to the increased participation of children who appeared to be marginalized. This study presents the process of a collaborative artmaking in a pre-primary school class with the purpose of reducing social and academic marginalization and increasing the participation of marginalized children in the curricula, the cultures, and the societies of schools.
Face Landmark Fitting via Optimized Part Mixtures and Cascaded Deformable Model

This paper addresses the problem of facial landmark localization and tracking from a single camera. We present a two-stage cascaded deformable shape model to effectively and efficiently localize facial landmarks with large head pose variations. In initialization stage, we propose a group sparse optimized mixture model to automatically select the most salient facial landmarks. By introducing 3D face shape model, we apply procrustes analysis to provide pose-aware landmark initialization. In landmark localization stage, the first step uses mean-shift local search with constrained local model to rapidly approach the global optimum. The second step uses component-wise active contours to discriminatively refine the subtle shape variation. Our framework simultaneously handles face detection, pose-robust landmark localization and tracking in real time. Extensive experiments are conducted on both laboratory environmental databases and face-in-the-wild databases. The results reveal that our approach consistently outperforms state-of-the-art methods for face alignment and tracking.
Rule abstraction and transfer in reinforcement learning by decision tree

Reinforcement learning agents store their knowledge such as state-action value in look-up tables. However, loop-up table requires large memory space when number of states become large. Learning from look-up table is tabularasa therefore is very slow. To overcome this disadvantage, generalization methods are used to abstract knowledge. In this paper, decision tree technology is used to enable the agent to represent abstract knowledge in rule from during learning progress and form rule base for each individual task.
Improving Dialogue Annotation Reliability

Data collection and annotation represent the most significant portion of the effort involved in building statistical models of dialogue. We must be able to annotate reliably if there is any hope of building predictive statistical models. This paper describes the annotation process being used to tag the TRAINS-93 corpus with dialogue acts, and measures we have taken to improve inter-annotator reliability.
Role of a Class Dhc1b Dynein in Retrograde Transport of Ift Motors and Ift Raft Particles along Cilia, but Not Dendrites, in Chemosensory Neurons of Living Caenorhabditis elegans

The heterotrimeric motor protein, kinesin-II, and its presumptive cargo, can be observed moving anterogradely at 0.7 μm/s by intraflagellar transport (IFT) within sensory cilia of chemosensory neurons of living Caenorhabditis elegans, using a fluorescence microscope–based transport assay (Orozco, J.T., K.P. Wedaman, D. Signor, H. Brown, L. Rose, and J.M. Scholey. 1999. Nature. 398:674). Here, we report that kinesin-II, and two of its presumptive cargo molecules, OSM-1 and OSM-6, all move at ∼1.1 μm/s in the retrograde direction along cilia and dendrites, which is consistent with the hypothesis that these proteins are retrieved from the distal endings of the cilia by a retrograde transport pathway that moves them along cilia and then dendrites, back to the neuronal cell body. To test the hypothesis that the minus end–directed microtubule motor protein, cytoplasmic dynein, drives this retrograde transport pathway, we visualized movement of kinesin-II and its cargo along dendrites and cilia in a che-3 cytoplasmic dynein mutant background, and observed an inhibition of retrograde transport in cilia but not in dendrites. In contrast, anterograde IFT proceeds normally in che-3 mutants. Thus, we propose that the class DHC1b cytoplasmic dynein, CHE-3, is specifically responsible for the retrograde transport of the anterograde motor, kinesin-II, and its cargo within sensory cilia, but not within dendrites.
SonarPen: an ultrasonic pointing device for an interactive TV

An interactive TV is requiring a more advanced remote controlling method than the traditional TV due to its diverse and complex functions. Many types of input technologies and interaction styles are being tested for remote pointing for an interactive TV. We introduce the SonarPen, an ultrasonic pointing device system developed for an interactive TV. It determines a cursor position from phase differences among sinusoidal signals received by three ultrasonic receivers. A common problem with phase difference methods is phase ambiguity, but we solved this problem by exploiting the directionality of an LED and discontinuity in phase difference signals. A performance evaluation of the SonarPen in comparison with other pointing devices showed that the SonarPen has a better throughput, while it has a relatively high error rate than others.
Finding the shortest transfer sequence of sequential circuit based on simplified ROBDDs

A method of finding the shortest transfer sequence for the given set of internal states with using operations on ROBDDs is considered. Simplified ROBDDs for transition functions compositions are applied. The ROBDDs are built by using Shannon decomposition first for state and then for input variables. In the simplified ROBDD its path originated by state variables has the only prolongation among input variables. An algorithm of cutting the number of these prolongations for the ROBDD is proposed. The algorithm is based on using the decomposition tree and oriented to cut calculations on finding the shortest transfer sequence.
Local and Nonlocal Preserving Projection for Bearing Defect Classification and Performance Assessment

The sensitivity of various physical features that are characteristics of bearing performance may vary significantly under different working conditions. Thus, it is critical to extract the most effective information from the original physical features generated from vibration signals for bearing defect classification and performance degradation assessment. This paper proposes a local and nonlocal preserving projection (LNPP)-based feature extraction algorithm, which is different from principal component analysis that aims to discover the global structure of Euclidean space and regular manifold learning algorithms that attempt to preserve local structure in data. LNPP is capable of discovering both local and nonlocal structures of data manifold. This may enable LNPP to find the meaningful low-dimensional information hidden in the high-dimensional feature set and then to serve as a preprocessor for defect classification. Furthermore, an LNPP-based quantification index is proposed for the assessment of bearing performance degradation. An LNPP-based contribution plot for feature selection is developed to improve the degradation detection sensitiveness and to reduce false alarms. A dynamic LNPP for bearing performance assessment is further developed to consider inherent autocorrelation existing in vibration data. Detailed results are very promising and are reported in this paper. This paper will provide guidance for the applications of manifold learning algorithms (e.g., LNPP) in machine fault diagnosis and performance prognostics.
FMM and H-matrices: A Short Introduction to the Basic Idea

The aim of this paper is a short introduction to a fundamental algorithm for the fast multiplication of vectors with fully populated, special matrices arising in various applications. The basic idea is known as fast multipole method, fast multiplication by H-matrices or by mosaic-skeleton matrices. We prefer a linear algebraic approach which may serve as a basis for student seminars in Mathematics, Computer Science or Engineering. Our introduction is accompanied by a broad, but far away from complete, list of references, where the reader may find more sophisticated material.
Unsupervised Spatio-Temporal Multi-Human Detection and Recognition in Complex Scene

An algorithm for multi-human detection and recognition in complex scene is proposed. It executes multi- human detection and recognition from spatial domain and time domain. In spatial domain, it establishes the Gaussian mixture background model to obtain target windows by the background difference and the foreground connection judgment. Based on target detection, a new target size estimation method is carried out through the computation of depth of field in the scene. Each target eigenvector is extracted from its contour to input into support vector machine (SVM) to judge the target was human or not. In time domain, a new three-layer bidirectional min-distance data association is proposed. It finds out the forerunner and successor associations of target data in some image sequences based on target position, target size and target gray. It gives each target chain human or unhuman property to assist in completing human recognition. Finally, a spatio-temporal union mechanism is proposed. It presents good result on multi-human detection and recognition.
Mechanical design of a portable knee-ankle-foot robot

We are developing an intelligent compact and modular knee-ankle-foot robot gait rehabilitation at outpatient and home settings. The robot is designed with a novel compact compliant force controllable actuator. We adopt a modular design for the knee and ankle joint so that the robot can assist patients with different conditions of gait impairments. The light-weight anthropomorphic structure designed based on biomechanical studies is built with advanced composite materials to achieve portability. A prototype of the robot has been built for testing. In this paper, we present the mechanical design of the robot with focus on the actuator and mechanism design and analysis, with testing results to demonstrate the performance of the actuator.
Underestimation of vasodilator effects of nitroglycerin by upper limb blood pressure.

To determine why upper limb blood pressure measurement underestimates the vasodilator effects of nitroglycerin on lowering ascending aortic systolic pressure, we studied 24 patients (58 +/- 11 years, mean +/- SD). Ascending aortic pressure and radial artery pulse calibrated by cuff blood pressure measurement at the brachial artery were recorded simultaneously before and 5 minutes after sublingual administration of 0.3 mg nitroglycerin. Waves were analyzed by a signal processor, and the fourth derivative wave was used to find the early (S1) and late (S2) systolic shoulders (S1 corresponds to the second zero crossing and S2 to the third zero crossing). Before nitroglycerin administration, maximal systolic pressure in the ascending aorta (141 +/- 21 mm Hg) coincided with the late systolic peak in all patients, and in most patients (21 of 24) maximal systolic pressure in the radial artery (140 +/- 19 mm Hg) coincided with the early systolic peak. Maximal systolic pressure decreased more in the ascending aorta than in the radial artery (22 +/- 13 and 11 +/- 11 mm Hg, respectively; P < .001). However, the reduction in the shoulder of late systolic pressure in the radial artery (24 +/- 13 mm Hg) clearly indicated the reduction in maximal systolic pressure (late systolic peak) in the ascending aorta. The augmentation index of the ratio of the height of late systolic pressure to early systolic pressure fell proportionally (r = .74, P < .001) in the radial artery (from 0.88 +/- 0.13 to 0.60 +/- 0.11) and in the ascending aorta (from 1.57 +/- 0.25 to 1.26 +/- 0.24), which indicated the reduction in late systolic pressures. (ABSTRACT TRUNCATED AT 250 WORDS)
Composition multilingue de sentiments

Nous présentons ici PolArt, un outil multilingue pour l’analyse de sentiments qui aborde la composition des sentiments en appliquant des transducteurs en cascade. La compositionnalité est assurée au moyen de polarités préalables extraites d’un lexique et des règles de composition appliquées de manière incrémentielle.
Is Orienting of Attention Selectively Impaired After Sleep Loss? The Role of Disengagement

Research on the effects of sleep deprivation on covert orienting of attention have produced evidence indicating either a negative or a null impact of sleep loss. Moreover, it is still unclear whether, following sleep deprivation, there is a general impairment of orienting processes or a selective one. Aim of the present study is highlighting the effects of sleep deprivation on the three subcomponents of orienting of attention: disengagement, moving and engagement (Posner and Raichle, 1994). The ANT-R (Fan et al., 2009) was administered following two sleep conditions: Baseline a regular night of uninterrupted sleep, and Deprivation 24 hours of total sleep deprivation. We have found a significant slowing down of the disengagement component, while engagement and shift components were virtually unaffected by sleep deprivation. Our data show that sleep deprivation selectively affects the three subcomponents underlying covert orienting of attention. Hence, they suggest that performance deficits following sleep curtailment should no longer be accounted for in terms of a general reduction of alertness or global attentional deficits.
A 1.25 V FGMOS filter using translinear circuits

This paper presents a new low voltage/low power filter design based on Floating-Gate MOS (FGMOS) transistors. FGMOS transistors are used as primitives to design linear and non-linear (/spl radic/x) circuits. This technique enables a voltage reduction in strong inversion mode, and gives a new vision of the translinear principle, suitable for low voltage applications. Experimental results for 0.8 /spl mu/m low-pass and band-pass filter prototypes are reported.
Watch-n-Patch: Unsupervised Learning of Actions and Relations

There is a large variation in the activities that humans perform in their everyday lives. We consider modeling these composite human activities which comprises multiple basic level actions in a completely unsupervised setting. Our model learns high-level co-occurrence and temporal relations between the actions. We consider the video as a sequence of short-term action clips, which contains human-words and object-words. An activity is about a set of action-topics and object-topics indicating which actions are present and which objects are interacting with. We then propose a new probabilistic model relating the words and the topics. It allows us to model long-range action relations that commonly exist in the composite activities, which is challenging in previous works. We apply our model to the unsupervised action segmentation and clustering, and to a novel application that detects forgotten actions, which we call action patching. For evaluation, we contribute a new challenging RGB-D activity video dataset recorded by the new Kinect v2, which contains several human daily activities as compositions of multiple actions interacting with different objects. Moreover, we develop a robotic system that watches and reminds people using our action patching algorithm. Our robotic setup can be easily deployed on any assistive robots.
Tobacco Mosaic Virus Movement Protein Associates with the Cytoskeleton in Tobacco Cells 8

Tobacco mosaic virus movement protein P30 complexes with genomic viral RNA for transport through plasmodesmata, the plant intercellular connections. Although most research with P30 focuses on its targeting to and gating of plasmodesmata, the mechanisms of P30 intracellular movement to plasmodesmata have not been defined. To examine P30 intracellular localization, we used tobacco protoplasts, which lack plasmodesmata, for transfection with plasmids carrying P30 coding sequences under a constitutive promoter and for infection with tobacco mosaic virus particles. In both systems, P30 appears as filaments that colocalize primarily with microtubules. To a lesser extent, P30 filaments colocalize with actin filaments, and in vitro experiments suggested that P30 can bind directly to actin and tubulin. This association of P30 with cytoskeletal elements may play a critical role in intracellular transport of the P30-vira1 RNA complex through the cytoplasm to and possibly through plasmodesmata.
Salsalate attenuates diet induced non‐alcoholic steatohepatitis in mice by decreasing lipogenic and inflammatory processes

Salsalate (salicylsalicylic acid) is an anti‐inflammatory drug that was recently found to exert beneficial metabolic effects on glucose and lipid metabolism. Although its utility in the prevention and management of a wide range of vascular disorders, including type 2 diabetes and metabolic syndrome has been suggested before, the potential of salsalate to protect against non‐alcoholic steatohepatitis (NASH) remains unclear. The aim of the present study was therefore to ascertain the effects of salsalate on the development of NASH.
Transcriptomic landscape of prophase I sunflower male meiocytes

Meiosis is a form of specialized cell division that generates gametes, allowing recombination of alleles and halving the chromosome number. Arabidopsis and maize are the plant models that have been most extensively studied to determine the genes involved in meiosis. Here we present an RNA-seq study in which gene expression in male meiocytes isolated during prophase I was compared to that in somatic tissues of the sunflower HA89 line. We sampled more than 490 million gene tags from these libraries, assembled them de novo into a sunflower transcriptome. We obtained expression data for 36,304 sunflower genes, of which 19,574 (54%) were differentially expressed (DE) between meiocytes and somatic tissue. We also determined the functional categories and metabolic pathways that are DE in these libraries. As expected, we found large differences between the meiotic and somatic transcriptomes, which is in accordance with previous studies in Arabidopsis and maize. Furthermore, most of the previously implicated meiotic genes were abundantly and DE in meiocytes and a large repertoire of transcription factors (TF) and genes related to silencing are expressed in the sunflower meiocytes. We detected TFs which appear to be exclusively expressed in meiocytes. Our results allow for a better understanding of the conservation and differences in the meiotic transcriptome of plants.
Critical Period of Nonpromoter DNA Methylation Acquisition during Prenatal Male Germ Cell Development

The prenatal period of germ cell development is a key time of epigenetic programming in the male, a window of development that has been shown to be influenced by maternal factors such as dietary methyl donor supply. DNA methylation occurring outside of promoter regions differs significantly between sperm and somatic tissues and has recently been linked with the regulation of gene expression during development as well as successful germline development. We examined DNA methylation at nonpromoter, intergenic sequences in purified prenatal and postnatal germ cells isolated from wildtype mice and mice deficient in the DNA methyltransferase cofactor DNMT3L. Erasure of the parental DNA methylation pattern occurred by 13.5 days post coitum (dpc) with the exception of approximately 8% of loci demonstrating incomplete erasure. For most loci, DNA methylation acquisition occurred between embryonic day 13.5 to 16.5 indicating that the key phase of epigenetic pattern establishment for intergenic sequences in male germ cells occurs prior to birth. In DNMT3L-deficient germ cells at 16.5 dpc, average DNA methylation levels were low, about 30% of wildtype levels; however, by postnatal day 6, about half of the DNMT3L deficiency-specific hypomethylated loci had acquired normal methylation levels. Those loci normally methylated earliest in the prenatal period were the least affected in the DNMT3L-deficient mice, suggesting that some loci may be more susceptible than others to perturbations occurring prenatally. These results indicate that the critical period of DNA methylation programming of nonpromoter, intergenic sequences occurs in male germline progenitor cells in the prenatal period, a time when external perturbations of epigenetic patterns could result in diminished fertility.