Miracle-dz/UniFAR-FTUs huggingface dataset:
Data Fusion for 3D Gestures Tracking using a Camera mounted on a Robot

This article describes a multiple feature data fusion applied to an auxiliary particle filter for markerless tracking of 3D two-arm gestures by using a single camera mounted on a mobile robot. The human limbs are modelled by a set of linked degenerated quadrics which are truncated by pairs of planes also modelled as degenerated quadrics. The method relies on the projection of both the model's silhouette and local features located on the model surface, to validate the particles (associated configurations) which generate the best model-to-image fittings. Our cost metric combines robustly two imaging cues i.e. model contours and colour or texture based patches located on the model surface, subject to 3D joint limits and also non self-intersection constraints. The results show the robustness and versatility of our data fusion based approach
Gérer les paradoxes organisationnels en construisant du sens lors d’une conduite paradoxale du changement

Cette communication interroge les modalites de gestion des paradoxes organisationnels qui se manifestent dans le cadre d’une conduite de changement. Pour approfondir cette relation, nous articulons la litterature sur les paradoxes organisationnels (Smith et Lewis, 2011 ; Jarzabkoski, Le et Van de Ven, 2013), avec celle sur la conduite du changement (Hargrave et Van de Ven, 2016 ; Lusher et Lewis (2011) et la construction du sens (Weick, 1995). La mobilisation d’une recherche-intervention durant six annees destinee a accompagner le deploiement de la norme ISO 26000 dans une entreprise de taille intermediaire du secteur de l’agro-alimentaire, nous permet alors d’apprehender les paradoxes qui se cristallisent a cette occasion et d’observer les modalites de leur regulation. L’analyse des donnees (entretiens semi-directifs, observations participantes et non participantes, questionnaires, documents internes et externes) mobilise une demarche inductive, inspiree de Gioia et ses collegues (Corley et Gioia, 2004, Gioia, Corley et Hamilton, 2013, Langley et Abdallah, 2011). Notre analyse se deploie en trois temps. La premiere phase consiste a reperer les tensions organisationnelles a l’œuvre et a les qualifier dans le prolongement des travaux de Smith et Lewis (2011). Dans une deuxieme phase, nous montrons comment ces paradoxes sont geres a travers differents dispositifs de sensemaking et de sensegiving dont l’agencement permet une prise en charge globale des paradoxes organisationnels. Le troisieme temps vise a proposer un modele integre et paradoxal de conduite du changement permettant l’association des paradoxes organisationnels dans un systeme global de management articulant une dynamique de changement prescrit et construit, ainsi qu’une construction prospective et retrospective du sens. La discussion de ces resultats souligne la triple contribution de cet article. La premiere invite a depasser une approche sequentielle et une prise en charge isolee de chaque paradoxe organisationnel, en proposant un modele qui permet de manager l’ensemble des paradoxes simultanement. La seconde depasse les clivages entre changement construit et changement prescrit en proposant une conduite du changement elle-meme paradoxale, reposant sur differentes sequences de sensemaking et de sensegiving. La derniere, enfin, s’efforce de qualifier les dispositifs de sensemaking et de sensegiving venant en appui de cette conduite de changement paradoxale.
Relevance of Blood Vessel Networks in Blast-Induced Traumatic Brain Injury

Cerebral vasculature is a complex network that circulates blood through the brain. However, the role of this networking effect in brain dynamics has seldom been inspected. This work is to study the effects of blood vessel networks on dynamic responses of the brain under blast loading. Voronoi tessellations were implemented to represent the network of blood vessels in the brain. The brain dynamics in terms of maximum principal strain (MPS), shear strain (SS), and intracranial pressure (ICP) were monitored and compared. Results show that blood vessel networks significantly affected brain responses. The increased MPS and SS were observed within the brain embedded with vessel networks, which did not exist in the case without blood vessel networks. It is interesting to observe that the alternation of the ICP response was minimal. Moreover, the vessel diameter and density also affected brain dynamics in both MPS and SS measures. This work sheds light on the role of cerebral vasculature in blast-induced traumatic brain injury.
Lactic acid mediates resistance to stress through class I HDAC induction in a chronic social defeat model of depression. (c2017)

Depression is one of the most common psychiatric disorders and a leading cause of disability worldwide. Environmental factors, mainly stress, play an important role in promoting this disorder by inducing changes in gene expression that are sustained by epigenetic modifications, particularly in the hippocampal brain regions. Transcriptional profiling of the hippocampus revealed a downregulation in the BrainDerived Neurotrophic Factor (Bdnf) gene expression in animal models of stress, and this downregulation was reversed by antidepressant treatment and physical exercise. In our study, we use a chronic social defeat paradigm, a validated model of depression in mice, to study the antidepressant effect of the endogenous molecule lactate that is released after physical exercise. We used multiple behavioral tests including open field, T-maze and social interaction tests to show that lactate rescues depression phenotypes such as defeat and anxiety behavior We also report that lactate activates independent pathways to affect two separate processes: promotion of resilience to stress and protection from depression. Our results reveal an antidepressant-like activity of an endogenous molecule lactate, produced after physical exercise and known to accumulate in the hippocampal regions of the brain and illustrate a novel mechanism that can explain the positive effects of exercise on mood disorders.
Climate warming decreases the survival of the little auk (Alle alle), a high Arctic avian predator

Delayed maturity, low fecundity, and high adult survival are traits typical for species with a long-life expectancy. For such species, even a small change in adult survival can strongly affect the population dynamics and viability. We examined the effects of both regional and local climatic variability on adult survival of the little auk, a long-lived and numerous Arctic seabird species. We conducted a mark-resighting study for a period of 8 years (2006-2013) simultaneously at three little auk breeding sites that are influenced by the West Spitsbergen Current, which is the main carrier of warm, Atlantic water into the Arctic. We found that the survival of adult little auks was negatively correlated with both the North Atlantic Oscillation (NAO) index and local summer sea surface temperature (SST), with a time lag of 2 and 1 year, respectively. The effects of NAO and SST were likely mediated through a change in food quality and/or availability: (1) reproduction, growth, and development of Arctic Calanus copepods, the main prey of little auks, are negatively influenced by a reduction in sea ice, reduced ice algal production, and an earlier but shorter lasting spring bloom, all of which result from an increased NAO; (2) a high sea surface temperature shortens the reproductive period of Arctic Calanus, decreasing the number of eggs produced. A synchronous variation in survival rates at the different colonies indicates that climatic forcing was similar throughout the study area. Our findings suggest that a predicted warmer climate in the Arctic will negatively affect the population dynamics of the little auk, a high Arctic avian predator.
Towards more accurate and intelligent recommendation systems

In this paper, a comparative analysis of current Recommendation Systems (RSs) is provided. In addition, we propose a new efficient Utility-Based Filtering (UBF) and Knowledge-Based Filtering (KBF) hybrid approach for calculating the utility value of each object to be recommended. The proposed system is anticipated to be at least streamlined, straightforward, and less burdening solution for recommending variety of personalized services for the user. The purpose of this paper is to help RS designers to implement more accurate and intelligent recommendation engines as well as convince them of the benefits of our new smarter system that combines best of the UBF and KBF methods, thus resulting in one unique and effective hybrid system. Moreover, some new ideas that will be used in our future research work are proposed.
Sign language video retrieval based on trajectory

In this paper, we present a revised method to compute the similarity of traditional string edit distance. In order to compute the edit distance, a new algorithm is introduced. This algorithm is shown to work in O (m∗n∗log(n)) time and 0(n∗m) memory space for strings of lengths m and n. Content-based video retrieval is a challenging field, and most research focus on the low level features such as color histogram, texture and etc. In this paper, we solve the retrieval problem by high level features used by hand language trajectory and compare the similarity by our revised string edit distance algorithms. Trajectory based video retrieval is widely explored in recent years by many excellent researchers. Experiments in trajectory-based sign language video retrieval are presented in our paper at last, revealing that our revised edit distance algorithm consistently provide better results than classical edit distances.
Automatic analysis of semantic similarity in comparable text through syntactic tree matching

We propose to analyse semantic similarity in comparable text by matching syntactic trees and labeling the alignments according to one of five semantic similarity relations. We present a Memory-based Graph Matcher (MBGM) that performs both tasks simultaneously as a combination of exhaustive pairwise classification using a memory-based learner, followed by global optimization of the alignments using a combinatorial optimization algorithm. The method is evaluated on a monolingual treebank consisting of comparable Dutch news texts. Results show that it performs substantially above the baseline and close to the human reference.
Malignant pleural mesothelioma: history, controversy and future of a manmade epidemic

Asbestos is the term for a family of naturally occurring minerals that have been used on a small scale since ancient times. Industrialisation demanded increased mining and refining in the 20th century, and in 1960, Wagner, Sleggs and Marchand from South Africa linked asbestos to mesothelioma, paving the way to the current knowledge of the aetiology, epidemiology and biology of malignant pleural mesothelioma. Pleural mesothelioma is one of the most lethal cancers, with increasing incidence worldwide. This review will give some snapshots of the history of pleural mesothelioma discovery, and the body of epidemiological and biological research, including some of the controversies and unresolved questions. Translational research is currently unravelling novel circulating biomarkers for earlier diagnosis and novel treatment targets. Current breakthrough discoveries of clinically promising noninvasive biomarkers, such as the 13-protein signature, microRNAs and the BAP1 mesothelioma/cancer syndrome, are highlighted. The asbestos history is a lesson to not be repeated, but here we also review recent in vivo and in vitro studies showing that manmade carbon nanofibres could pose a similar danger to human health. This should be taken seriously by regulatory bodies to ensure thorough testing of novel materials before release in the society. Malignant pleural mesothelioma is a cancer with increasing death tolls due to the past and present use of asbestos http://ow.ly/DhA2y
A Framework for Simulating and Comparing Explicit Substitutions Calculi ∗

We present a framework, called SUBSEXPL, for simulating and comparing explicit substitutions calculi. This framework was developed in Ocaml, a language of the ML family, and it allows the manipulation of expressions of the λ-calculus and of several styles of explicit substitutions calculi. Applications of this framework include: the visualisation of the contractions of the λ-calculus, and of guided one-step reductions and normalisation via each of the associated substitution calculi. Many useful facilities are available: reductions can be easily recorded and stored into files, latex output and useful examples for dealing with, among other things, arithmetic operations and computational operators such as conditionals and repetitions in the λ-calculus. The current implementation of SUBSEXPL includes treatment of three different calculi of explicit substitutions: the λσ, the λse and the suspension calculus; other explicit substitutions calculi can be easily incorporated into the system due to its modular structure. An implementation of the η-reduction is provided for each of these explicit substitutions calculi. This system has been of great help for systematically comparing explicit substitutions calculi, as well as for understanding properties of explicit substitutions such as the Preservation of Strong Normalisation. In addition, it has been used for teaching basic properties of the λ-calculus such as: computational adequacy, the importance of de Bruijn’s notation and of making explicit substitutions in real implementations based on the λ-calculus.
The explicit expression of the fugacity for weakly interacting Bose and Fermi gases

In this paper, we calculate the explicit expression for the fugacity for two- and three-dimensional weakly interacting Bose and Fermi gases from their equations of state in isochoric and isobaric processes, respectively, based on the mathematical result of the boundary problem of analytic functions—the homogeneous Riemann-Hilbert problem. We also discuss the Bose-Einstein condensation phase transition of three-dimensional hard-sphere Bose gases.
Multilevel Linear Dimensionality Reduction for Data Analysis using Nearest-Neighbor Graphs ∗

Dimension reduction techniques can be time-consuming when the data set is large. This paper presents a multilevel framework to reduce the size of the data set, prior to performing dimension reduction. The algorithm exploits nearestneighbor graphs. It recursively coarsens the data by finding a maximal matching level by level. Once the coarse graph is available, the coarsened data is projected at the lowest level using a known linear dimensionality reduction method. To obtain the projected data at the highest level, the same linear mapping as that of the lowest level is performed on the original data set, and on any new test data. The methods are illustrated on three applications: manifold mapping, face recognition, and text mining. Experimental results indicate that the multilevel techniques presented in this paper offer a very appealing cost to quality ratio.
Cytoplasmic Male Sterility of Rice with Boro II Cytoplasm Is Caused by a Cytotoxic Peptide and Is Restored by Two Related PPR Motif Genes via Distinct Modes of mRNA Silencing[W]

Cytoplasmic male sterility (CMS) and nucleus-controlled fertility restoration are widespread plant reproductive features that provide useful tools to exploit heterosis in crops. However, the molecular mechanism underlying this kind of cytoplasmic–nuclear interaction remains unclear. Here, we show in rice (Oryza sativa) with Boro II cytoplasm that an abnormal mitochondrial open reading frame, orf79, is cotranscribed with a duplicated atp6 (B-atp6) gene and encodes a cytotoxic peptide. Expression of orf79 in CMS lines and transgenic rice plants caused gametophytic male sterility. Immunoblot analysis showed that the ORF79 protein accumulates specifically in microspores. Two fertility restorer genes, Rf1a and Rf1b, were identified at the classical locus Rf-1 as members of a multigene cluster that encode pentatricopeptide repeat proteins. RF1A and RF1B are both targeted to mitochondria and can restore male fertility by blocking ORF79 production via endonucleolytic cleavage (RF1A) or degradation (RF1B) of dicistronic B-atp6/orf79 mRNA. In the presence of both restorers, RF1A was epistatic over RF1B in the mRNA processing. We have also shown that RF1A plays an additional role in promoting the editing of atp6 mRNAs, independent of its cleavage function.
An analytical model to exploit memory task scheduling

Memory Wall has been a well-known obstacle to processor performance improvement. The dawn of many-core processors will further exaggerate the problem. As a result, efficient memory task scheduling has been one important means to sustaining the performance growth. In this paper, we first develop an analytical model to capture the essence of on-chip compute and off-chip communication as shown in the stream programming model. It estimates the potential speedup that can be achieved by restricting the number of simultaneous memory tasks to reduce memory bandwidth contention. We then corroborate the analytical model with experimental results from task scheduling on real hardware. Correlation between the analytical and experimental results offers both insight into the benchmarks running on the hardware and opportunities to extend the analytical model. Our results show that restricting the number of simultaneous memory tasks achieves up to 60% performance improvement with a pool of synthetic workloads.
Boosting a Weak Learning Algorithm by Majority to Be Published in Information and Computation

We present an algorithm for improving the accuracy of algorithms for learning binary concepts. The improvement is achieved by combining a large number of hypotheses , each of which is generated by training the given learning algorithm on a diierent set of examples. Our algorithm is based on ideas presented by Schapire in his paper \The strength of weak learnability", and represents an improvement over his results. The analysis of our algorithm provides general upper bounds on the resources required for learning in Valiant's polynomial PAC learning framework, which are the best general upper bounds known today. We show that the number of hypotheses that are combined by our algorithm is the smallest number possible. Other outcomes of our analysis are results regarding the representational power of threshold circuits, the relation between learnability and compression, and a method for parallelizing PAC learning algorithms. We provide extensions of our algorithms to cases in which the concepts are not binary and to the case where the accuracy of the learning algorithm depends on the distribution of the instances.
An evaluation of UK risky money: an artificial intelligence approach

In this paper we compare the performance of three indices in an inflation forecasting experiment. The evidence not only suggests that an evolved neural network is superior to traditionally trained networks in the majority of cases, but also that a risky money index performs at least as well as the Bank of England Divisia index when combined with interest rate information. Notably, the provision of long-term interest rates improves the out-of-sample forecasting performance of the Bank of England Divisia index in all cases examined.
Weighted passive nearest neighbor algorithm: A newly-developed supervised classifier

K nearest neighbor algorithm (k-NN) is an instance-based lazy classifier that does not need to delineate the entire boundaries between classes. Thus some classification tasks that constantly need a training procedure may favor k-NN if high efficiency is needed. However, k-NN is prone to be affected by the variation of datum densities among different classes. In this paper, we define a new neighborhood relationship, called passive nearest neighbor relationship, which is demonstrated to be able to counteract with the variation of datum densities. Based on which we develop a new classifier called weighted passive nearest neighbor algorithm (WPNNA). The classifier is evaluated by 10-fold cross-validation on 10 randomly chosen benchmark datasets. The experimental results show that WPNNA performs better than other classifiers on some benchmark datasets, indicating that WPNNA is at least a good complement to the current state-of-the-art of classification.
Practical Issues with TLS Client Certificate Authentication

—The most widely used secure Internet communication standard TLS (Transport Layer Security) has an optional client certiﬁcate authentication feature that in theory has signiﬁcant security advantages over HTML form-based password authentication. In this paper we discuss practical security and usability issues related to TLS client certiﬁcate authentication stemming from the server-side and browser implementations. In particular, we analyze Apache’s mod_ssl implementation on the server side and the most popular browsers – Mozilla Firefox, Google Chrome and Microsoft Internet Explorer on the client side. We complement our paper with a measurement study performed in Estonia where TLS client certiﬁcate authentication is widely used. We present our recommendations to improve the security and usability of TLS client certiﬁcate authentication.
CBR-based Knowledge-focusing for Training in Decisionmaking within Project Management Processes

A project manager is expected to have a broad knowledge of his project when making decisions such as work activity formulation, resource allocation, staffing and risk confrontation. Because of the variegated nature of project decisionmaking, the knowledge required must span numerous issues. Thus a primary concern when training novice project managers is for them to learn how to focus knowledge to support decisionmaking. We present a hierarchical networked architecture based upon the PMBOK typology of project knowledge, issues related to project management processes, and paths connecting multiple issues and cases found to impact decisions made in the past. The caseand path-based reasoning structure guides the trainee in searching for relevant issues and cases and interconnections between them, in order to build up a knowledge focus implied by a given decision scenario. The trainee's perspective of the problem can then be compared to that of an experienced project manager.
Complementarity Analysis of Affine Region Detectors

Complementarity benefiting from combination of affine region detectors for image matching is examined closely. Possible combinations of five types of representative affine region detectors are integrated into the test. The complementary features and region sizes are analyzed by the means of specific instances for the first time. To objectively compare the performance of combination detectors, the matching score is used as an evaluation criterion, which reflects not only the number of correct matches, but also the ratio between correct matches and mismatches. GLOH descriptor is used for all combinations. It is observed that HA+HE, E+HE, HE+M and M+E outperform other combinational detectors in most cases.
Semantics of the Temporal Adjunct Construction and Time Congruency

The following paper deals with the grammatical construction of the temporal adverbs yesterday, today and tomorrow, highlighting their semantic characteristics. For this, and following the Construction Grammar framework developed by Fillmore, I revise critically the grammatical construction proposed by this author for the previous temporal adverbs. Sustaining this semantic description on the cognitive notions of target and landmark, the adjuncts yesterday, today and tomorrow are explained in relation to the Calendar Unit of day, where the adverbs precede, equal or follow the reference time or landmark. Nevertheless, Fillmore's approach turns out to be incomplete, since it is only concerned with the inherent semantic features of these time adjuncts. Consequently, another section is devoted to some characteristics of the interaction between time adverbs and the other elements of the clause, this time resting on the semantic notion of Time Congruency, which will yield significant syntactic consequences