Miracle-dz/UniFAR-FTUs huggingface dataset:
Laplacian Tensor sparse coding for image categorization

To generate the visual codebook, a step of quantization process is obligatory. Several works have proved the efficiency of sparse coding in feature quantization process of BoW based image representation. Furthermore, it is an important method which encodes the original signal in a sparse signal space. Yet, this method neglects the relationships among features. To reduce the impact of this issue, we suggest in this paper, a Laplacian Tensor sparse coding method, which will aim to profit from the relationship among the local features. Precisely, we propose to apply the similarity of tensor descriptors to create a Laplacian Tensor similarity matrix, which can better present in the same time the closeness of local features in the data space and the topological relationship among the spatially near local descriptors. Moreover, we integrate statistical analysis applied to the local features assigned to each visual word in the pooling step. Our experimental results prove that our method prevails or exceeds existing background results.
Efficient identification of coupled entities in document collections

The relentless pace at which textual data are generated on-line necessitates novel paradigms for their understanding and exploration. To this end, we introduce a methodology for discovering strong entity associations in all the slices (meta-data value restrictions) of a document collection. Since related documents mention approximately the same group of core entities (people, locations, etc.), the groups of coupled entities discovered can be used to expose themes in the document collection. We devise and evaluate algorithms capable of addressing two flavors of our core problem: algorithm THR-ENT for computing all sufficiently strong entity associations and algorithm TOP-ENT for computing the top-k strongest entity associations, for each slice of the document collection.
Generation of anti-type III pneumococcal polysaccharide hybridomas from mice with an X-linked B-lymphocyte defect

(CBA/N X BALB/c male)F1 mice bear on X-linked defect making them totally unresponsive to T-independent (TI), TI-2 antigens such as type III pneumococcal polysaccharide (SSS-III). We found that somatic cell hybrids between CB nonresponder spleen cells and NS1 plasmacytoma cells secreted antibody specific for SSS-III. The solid-phase binding of such antibody was completely inhibited by the addition of free antigen (SSS- III) and the amount of antibody detected in culture fluids ranged from 10 ng/ml to 10 micrograms/ml. Eight hybridoma clones were identified; all make antibody of the IgM class. These results indicate that the X- linked defect does not result in a deletion of a B-cell subset which responds to TI-2 antigens.
A review on the Detection of Missing Content Queries in FAQ Retrieval Systems

When developing an automated FAQ retrieval system, the information supplier constructs question candidates in advance using their own knowledge. Then they answer these question candidates to create question-answer pairs to use in the FAQ retrieval system. However, these question-answer pairs will not always satisfy the users’ information needs. When there is no relevant question–answer pair to a users’ query, such a user may submit various query reformulations browsing over the long results list and may abandon the search before their information need has been satisfied. Such users many never return to use the system again because of the inability of the system to return relevant question-answer pairs to their query. In order to alleviate this, modern automated FAQ retrieval systems use a Missing Content Query (MCQ) detection subsystem to detect those queries that do not have the relevant question–answer pair. In this article we conduct a review of the different approaches proposed in the literature for detecting these MCQs. In particular, we provide a comprehensive review of the different systems that deployed the binary classification approach, the thresholding approach and the hybrid approach in the detection of MCQs. Moreover, we describe the strength and weaknesses of each approach.
Invariant Texture Classification Using Ridgelet Packets

In this paper, we propose a novel rotation invariant texture classification technique by using ridgelet packets. Ridgelet packets provide many orthonormal bases that can effectively capture directional features present in textures. The Fourier transform is good at eliminating the texture orientation differences. By combining these two tools, a very efficient rotation invariant texture classification technique is created. Experimental results show that the proposed method achieves very high classification rates and it outperforms two state-of-the-art methods for rotation invariant texture classification under both noise-free and noisy environments
Phrase Detectives: A Web-based collaborative annotation game

Annotated corpora of the size needed for modern computational linguistics research cannot be created by small groups of hand annotators. One solution is to exploit collaborative work on the Web and one way to do this is through games like the ESP game. Applying this methodology however requires developing methods for teaching subjects the rules of the game and evaluating their contribution while maintaining the game entertainment. In addition, applying this method to linguistic annotation tasks like anaphoric annotation requires developing methods for presenting text and identifying the components of the text that need to be annotated. In this paper we present the first version of Phrase Detectives (http://www.phrasedetectives.org), to our knowledge the first game designed for collaborative linguistic annotation on the Web.
Investigating Therapies for Freezing of Gait Targeting the Cognitive, Limbic, and Sensorimotor Domains

Background Freezing of gait (FOG) is arguably the most disabling motor symptom experienced with Parkinson’s disease (PD), but treatments are extremely limited due to our poor understanding of the underlying mechanisms. Three cortical domains are postulated in recent research (ie, the cognitive, limbic, and sensorimotor domains), thus, treatments targeting these mechanisms of FOG may potentially be effective. Cognitive training, cognitive behavioral therapy (CBT, a well-known anxiety intervention), and proprioceptive training may address the cognitive, limbic, and sensorimotor domains, respectively. Objective To investigate whether these 3 treatments could improve functional outcomes of FOG. Methods In a single-blind, randomized crossover design, 15 individuals with PD and FOG were randomized into different, counterbalanced orders of receiving the interventions. Each consisted of eight 1-hour sessions, twice weekly for 4 weeks. FOG severity was assessed as the primary outcome using a novel gait paradigm that was aimed at evoking FOG when the cognitive, limbic, or sensorimotor domains were independently challenged. Results FOG severity significantly improved after the cognitive intervention, with strong trends toward improvement specifically in the baseline and cognitive-challenge assessment conditions. CBT, as the anxiety intervention, resulted in significantly worse FOG severity. In contrast, proprioceptive training significantly improved FOG severity, with consistent trends across all conditions. Conclusions The cognitive and proprioceptive treatments appeared to improve different aspects of FOG. Thus, either of these interventions could potentially be a viable treatment for FOG. However, although the results were statistically significant, they could be sensitive to the relatively small number of participants in the study. Considering the significant results together with nonsignificant trends in both FOG and gait measures, and given equal time for each intervention, proprioceptive training produced the most consistent indications of benefits in this study. (clinicaltrials.gov NCT03065127).
Body fat assessment in elite soccer players: cross-validation of different field methods

ABSTRACT Objective: In soccer players, body fat mass (FM) is commonly estimated by assessment methods such as skinfolds, bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA). The main aim was to cross-validate the 3 field methods for quantifying body fat against a recent model of DXA. Methods: This study involved a group of 18 international-level, elite male soccer players belonging to the squad of a Serie A club in Italy. Results: All skinfold equations (with the exception of Deuremberg) showed large-to-very large positive correlations (r from 0.61 to 0.82, p ≤ 0.01) with DXA, however, BIA %FM data showed unclear relationship. All the sum of skinfolds showed moderate-to-very large positive correlations with DXA (r from 0.46 to 0.79, p values from 0.061 to 0.000). The combination of triceps and iliac crest skinfolds selected by the stepwise procedure explained 78.6% variance in DXA total %FM. Conclusion: All different methods employed in the present study are likely to differ, which prevent their use interchangeably. Almost all the equations showed positive correlations, but with different values in comparison with a recent model of DXA. Finally, the sum of skinfolds appears to be a good alternative when limited time and budged is available.
The annotated laser data set for navigation in urban areas

In this paper, we present a challenging data set for use in a variety of mobile robotic navigation tasks. Based on the data set that we released previously, we further extend its capability by annotating the laser range data. Apart from the laser range data, the dead-reckoning trajectory and the tri-camera imagery, the true segmentation differentiating between objects and the true moving object detection (MOD) discriminating moving objects are also annotated. The data set is intended for extensive evaluation of localization, mapping and MOD by providing highly accurate relative pose, object segmentation and MOD. All data are synchronized, carefully annotated and formatted in space-delimited plaintext format. We also provide an interactive web interface to facilitate the access to the data and the annotations.
Local and Remote Growth Factor Effects after Primate Spinal Cord Injury

Primate models of spinal cord injury differ from rodent models in several respects, including the relative size and functional neuroanatomy of spinal projections. Fundamental differences in scale raise the possibility that retrograde injury signals, and treatments applied at the level of the spinal cord that exhibit efficacy in rodents, may fail to influence neurons at the far greater distances of primate systems. Thus, we examined both local and remote neuronal responses to neurotrophic factor-secreting cell grafts placed within sites of right C7 hemisection lesions in the rhesus macaque. Six months after gene delivery of brain-derived neurotrophic factor (BDNF) and neurotrophin-3 (NT-3) into C7 lesion sites, we found both local effects of growth factors on axonal growth, and remote effects of growth factors reflected in significant reductions in axotomy-induced atrophy of large pyramidal neurons within the primary motor cortex. Additional examination in a rodent model suggested that BDNF, rather than NT-3, mediated remote protection of corticospinal neurons in the brain. Thus, injured neural systems retain the ability to respond to growth signals over the extended distances of the primate CNS, promoting local axonal growth and preventing lesion-induced neuronal degeneration at a distance. Remote cortical effects of spinally administered growth factors could “prime” the neuron to respond to experimental therapies that promote axonal plasticity or regeneration.
Estimating the Price of Default Risk

A firm's instantaneous probability of default is modeled as a square-root diffusion process. The parameters of these processes are estimated for 188 firms, using both the time series and cross-sectional (term structure) properties of the individual firms' bond prices. Although the estimated models are moderately successful at bond pricing, there is strong evidence of misspecification. The results indicate that single factor models of instantaneous default risk face a significant challenge in matching certain key features of actual corporate bond yield spreads. In particular, such models have difficulty generating both relatively flat yield spreads when firms have low credit risk and steeper yield spreads when firms have higher credit risk.
Analysis of 2 D Color Spaces for Highlight Elimination in 3 D Shape Reconstruction

We develop a method to separate matte and specular reflection components in color images using the dichromatic reflection model. Three-dimensional color descriptors are transformed to a pair of two-dimensional descriptors. This representation allows to perform the reflection analysis for multi-colored objects in a fast and robust manner. Further, it enables us to consider multiple dichromatic clusters in a single dichromatic plane. The method suggests that a pure color space analysis is sufficient in most situations. The matte reflection component is applied to a fast three-dimensional surface reconstruction scheme. Applying the proposed method it is not necessary to know reflection parameters such as matte and specular albedo or roughness values for surface recovery in advance.
Planning with Extended Goals and Partial Observability

Planning in nondeterministic domains with temporally extended goals under partial observability is one of the most challenging problems in planning. Simpler subsets of this problem have been already addressed in the literature, but the general combination of extended goals and partial observability is, to the best of our knowledge, still an open problem. In this paper we present a first attempt to solve the problem, namely, we define an algorithm that builds plans in the general setting of planning with extended goals and partial observability. The algorithm builds on the top of the techniques developed in the planning with model checking framework for the restricted problems of extended goals and of partial observability.
Uncertainty Aversion and Equilibrium Existence in Games with Incomplete Information

We consider games with incomplete information a la Harsanyi, where the payoff of a player depends on an unknown state of nature as well as on the profile of chosen actions. As opposed to the standard model, players' preferences over state--contingent utility vectors are represented by arbitrary functionals. The definitions of Nash and Bayes equilibria naturally extend to this generalized setting. We characterize equilibrium existence in terms of the preferences of the participating players. It turns out that, given continuity and monotonicity of the preferences, equilibrium exists in every game if and only if all players are averse to uncertainty (i.e., all the functionals are quasi--concave). We further show that if the functionals are either homogeneous or translation invariant then equilibrium existence is equivalent to concavity of the functionals.
Micro Pattern Fault-Proneness

One of the goals of Software Engineering is to reduce, or at least to try to control, the defectiveness of software systems during the development phase. The aim of our study is to analyze the relationship between micro patterns (introduced by Gil and Maman) and faults in a software system. Micro patterns are similar to design patterns, but their characteristic is that they can be identified automatically, and are at a lower level of abstraction with respect to design patterns. Our study aims to show, through empirical studies of open source software systems, which categories of micro patterns are more correlated to faults. Gil and Maman demonstrated, and subsequent studies confirmed, that 75% of the classes of a software system are covered by micro patterns. In our study we also analyze the relationship between faults and the remaining 25% of classes that do not match with any micro pattern. We found that these classes are more likely to be fault-prone than the others. We also studied the correlation among all the micro patterns of the catalog, in order to verify the existence of relationships between them.
Discovery of Pandoraea pnomenusa RB38 N-acyl homoserine Lactone Synthase (PpnI) and its Complete Genome Sequence Analysis

In this study, we sequenced the genome of P. pnomenusa RB38 and reported the finding of a pair of cognate luxI/R homologs which we firstly coined as ppnI, which is found adjacent to a luxR homolog, ppnR. An additional orphan luxR homolog, ppnR2 was also discovered. Multiple sequence alignment revealed that PpnI is a distinct cluster of AHL synthase compared to those of its nearest phylogenetic neighbor, Burkholderia spp. When expressed heterologously and analysed using high resolution tandem mass spectrometry, PpnI directs the synthesis of N-octanoylhomoserine lactone (C8-HSL). To our knowledge, this is the first documentation of the luxI/R homologs of the genus of Pandoraea.
Missing Data in Hierarchical Classification, a study with personality development data

Missing Data in Hierarchical Classification – a study with Personality developpment data Ana Lorga da Silva, Helena Bacelar-Nicolau, Gilbert Saporta, Manuel Geada ISEG, Universidade Tecnica de Lisboa e-mail:aigcls@iseg.utl. pt LEAD-FPCE, Universidade de Lisboa e-mail:hbacelar@fpce.ul. pt Chaire de Statistique Appliquee Conservatoire National des Arts et Metiers, Paris, France e-mail:saporta@cnam.fr FPCE, Universidade de Lisboa e-mail:geadamlc@fpce.ul. pt
Predictors of a new depression diagnosis among older adults admitted to complex continuing care: implications for the depression rating scale (DRS).

BACKGROUND depression is a major disabling condition among older adults, where it may be under-diagnosed for a number of reasons, including a different presentation for younger people with depression. The Minimum Data Set 2.0 (MDS 2.0) assessment system provides a measurement scale for depression, the Depression Rating Scale (DRS), in addition to other items that may represent depressive phenomenology. OBJECTIVE the ability of the DRS to predict the presence of new depression diagnoses at follow-up, among hospitalised older adults admitted without depression, is examined. METHODS the study sample consists of all persons aged 65 years or more admitted between 1996 and 2003 to a complex continuing care (CCC) bed in Ontario without a recorded depression diagnosis. The sample was restricted to those who remained in hospital for about 3 months (n = 7,818) in order to obtain follow-up assessment information. Logistic regression was used to explore the relationship between admission characteristics (i.e. DRS scale items, other MDS 2.0 items related to DSM-IV criteria for depression) and receipt of a depression diagnosis on the follow-up assessment. RESULTS a new depression diagnosis at follow-up was present in 7.5% of the individuals. The multivariate model predicting depression diagnosis included only the DRS scale, sadness over past roles, and withdrawal from activities. CONCLUSIONS the DRS score at admission was predictive of receiving a depression diagnosis on a follow-up assessment among older adults admitted to the CCC. Further, the predictive ability of the DRS is only modestly improved by the addition of other items related to DSM-IV criteria.
Verifying parameterized networks

This article describes a technique based on network grammars and abstraction to verify families of state-transition systems. The family of state-transition systems is represented by a context-free network grammar. Using the structure of the network grammar our technique constructs a process invariant that simulates all the state-transition systems in the family. A novel idea introduced in this article is the use of regular languages to express state properties. We have implemented our techniques and verified two nontrivial examples.
Predicting Tongue Positions from Acoustics and Facial Features

We test the hypothesis that adding information regarding the positions of electromagnetic articulograph (EMA) sensors on the lips and jaw can improve the results of a typical acoustic-toEMA mapping system, based on support vector regression, that targets the tongue sensors. Our initial motivation is to use such asystem inthecontext of adding atongue animation toatalking head built on the basis of concatenating bimodal acoustic-visual units. For completeness, we also train a system that maps only jaw and lip information to tongue information. Index Terms :a coustic-to-articulator ym apping, facial features, electromagnetic articulography
Automatic trachea segmentation and evaluation from MRI data using intensity pre-clustering and graph cuts

A high amount of magnetic resonance imaging (MRI) data is processed in modern epidemiological studies. Reliable and fast automatic segmentation algorithms are required to assist in data analysis. In our project, tracheal dimensions in living patients are studied. We present a fully automated segmentation method for trachea extraction based on intensity pre-clustering and narrow band graph cuts, where the clustering results are used for initialization. The volume of the extracted trachea is evaluated and its size is analyzed using anterior-posterior and lateral diameters. The method was evaluated qualitatively using 10 data sets by measuring volume fraction, volume error, and the Dice's coefficient. It produced sufficiently good results and showed potential to be integrated in clinical routine for processing thousands of participants.
HPM-Based Dynamic Sparse Grid Approach for Perona-Malik Equation

The Perona-Malik equation is a famous image edge-preserved denoising model, which is represented as a nonlinear 2-dimension partial differential equation. Based on the homotopy perturbation method (HPM) and the multiscale interpolation theory, a dynamic sparse grid method for Perona-Malik was constructed in this paper. Compared with the traditional multiscale numerical techniques, the proposed method is independent of the basis function. In this method, a dynamic choice scheme of external grid points is proposed to eliminate the artifacts introduced by the partitioning technique. In order to decrease the calculation amount introduced by the change of the external grid points, the Newton interpolation technique is employed instead of the traditional Lagrange interpolation operator, and the condition number of the discretized matrix different equations is taken into account of the choice of the external grid points. Using the new numerical scheme, the time complexity of the sparse grid method for the image denoising is decreased to O(4J+2j) from O(43J), (j ≪ J). The experiment results show that the dynamic choice scheme of the external gird points can eliminate the boundary effect effectively and the efficiency can also be improved greatly comparing with the classical interval wavelets numerical methods.
Insights from the aphasia project: designing technology for and with people who have aphasia

This paper explores a number of HCI research issues in the context of the Aphasia Project, a recently established project on the design of assistive technology for aphasic individuals. Key issues include the problems of achieving effective design and evaluation for a user population with an extremely high degree of variance, and user-centered design for a user population with significant communication impairments. We describe the Aphasia Project and our initial approaches to dealing with these issues. Similar issues arise in many areas of assistive technology, so we expect our paper to be of general interest to the research community.