Miracle-dz/UniFAR-FTUs huggingface dataset:
I2RNTU at SemEval-2016 Task 4: Classifier Fusion for Polarity Classification in Twitter

In this work, we apply classiﬁer fusion to tweet polarity identiﬁcation problem. The task is to predict whether the emotion hidden in a tweet is positive, neutral, or negative. An asymmetric SIMPLS (ASIMPLS) based clas-siﬁer, which was proved to be able to identify the minority class well in imbalanced classi-ﬁcation problems, is implemented. Word embedding is also employed as a new feature. For each word, we obtain three word embedding vectors on positive, neutral, and negative tweet sets respectively. These vectors are used as features in the ASIMPLS classiﬁer. Another three state-of-the-art systems are implemented also, and these four systems are fused together to further boost the performance. The fusion system achieved 59.63% accuracy on the 2016 test set of SemEval2016 Task 4, Subtask A.
Family “Bonds”: Making Meaning of Parent–Child Relationships in Estrangement Narratives

ABSTRACT Framed by relational dialectics theory, the present study takes a critical approach to the discursive navigation of the parent–child relationship. Specifically, this study explores the ways in which the parent–child relationship is constructed in 52 narrative interviews with adult children who are estranged from their parent(s). Contrapuntal analysis revealed that two discourses compete to illuminate meanings of the parent–child relationship. Three interrelated themes that emphasize biological connection, familial webs, and shared history constitute the Discourse of Relationship Endurance (DRE). Four interrelated themes that emphasize the need for relational maintenance, care/support, love, and individualism constitute the Discourse of Temporal Contingency and resist the DRE. The competition of these discourses, in the form of diachronic separation, synchronic interplay, and a discursive hybrid coalesce to making meaning of the parent–child relationship and hold implications for both theory and practice.
Quality of service capabilities for hard real-time applications on multi-core processors

Computing Worst-Case Execution Times (WCETs) for applications executed on multi-core processors is a challenging topic since possible interferences on shared resources need to be considered. Some approaches are already proposed in literature, but the problem is still not sufficiently solved. Different approaches suffer different shortcomings. For instance, the mutual analysis of multiple applications leads to great computational complexity, pessimistic assumptions on the interference between tasks causes highly overestimated WCETs and resource privatisation dissipates processor resources. In this paper we tackle the problems of overestimated WCETs due to pessimistic analysis and differences between average-case and worst-case execution timing. We introduce a new computing paradigm for safety-critical real-time systems, which enables Quality of Service (QoS) properties to increase the utilisation of multi-core processors while still guaranteeing bounds on the worst-case behavior. This paradigm is one approach to raise multi-core performance over single-core processors, even for hard real-time systems. For evaluation we use abstractions of real applications. The concepts are implemented on Freescale's P4080 multi-core processor and AbsInt's timing analysis framework aiT. The results show an increased processor core and system utilisation of up to 99.9% and 59.3% respectively, while still providing hard deadline guarantees for all applications.
Epithelial-Mesenchymal Transition Is a Critical Step in Tumorgenesis of Pancreatic Neuroendocrine Tumors

The transcription factors Snail, Slug and Twist repress E-cadherin and induce epithelial-mesenchymal transition (EMT), a process exploited by invasive cancer cells. In this study, we evaluated the role of EMT in the tumorgenesis of neuroendocrine tumors of the pancreas (PNETs) in vitro, in vivo and human tumor specimen. Expression of EMT markers was analyzed using immunohistochemistry and real-time PCR. For in vitro studies, BON-1 cells were analyzed regarding expression of EMT markers before and after transfection with siRNA against Slug or Snail, and cell aggregation assays were performed. To asses in vivo effects, Rip1Tag2 mice were treated with vehicle or the snail-inhibitor polythlylenglykol from week 5-10 of age. The resected pancreata were evaluated by weight, tumor cell proliferation and apoptosis. Snail and Twist was expressed in 61 % and 64% of PNETs. This was associated with loss of E-cadherin. RT-PCR revealed conservation of the EMT markers Slug and Snail in BON-1 cells. Transfection with siRNA against Slug was associated with upregulation of E-cadherin, enhanced cell-cell adhesion and inhibition of cell proliferation. Snail-inhibition in vivo by PEG was associated with increased apoptosis, decreased tumor cell proliferation and dramatic reduced tumor volume in Rip1Tag2 mice. The presented data show that EMT plays a key role in tumorgenesis of PNETs. The activation of Snail in a considerable subset of human PNETs and the successful effect of Snail inhibition by PEG in islet cell tumors of transgenic mice provides first evidence of Snail as a drug target in PNETs.
Effects of Warm Up Intensity on Factors Related to Subsequent Performance of Submaximal Exercise

INTRODUCTION: Athletes often warm up (WU) prior to exercise to improve performance. However, there are no clear directives regarding the intensity of the WU that is most effective in improving physiological responses related to enhanced aerobic performance. METHODS: Nine college-aged men (age, ht, mass, 20.6 yr, 1.7 m, 84.8 kg, respectively) performed WU of varying intensities, 60% ventilatory threshold (VT), 100%VT, and 120%VT prior to performing 5 min of steady state exercise at 80%VT on a cycle ergometer. O2 deficit, RPE, steady state heart rate (HRss), and steady state VO2 (VO2ss) were measured during the exercise bout. RESULTS: There was a significant decrease in O2 deficit as WU intensity increased ((2,9)= 9.15, p = . 002, η2=0.53) with the deficit being lowest after WU at 120%VT. RPE were significantly lower after WU at 120%VT than both 60% and 100%VT (F=(2,9)=6.88, p=. 007, η2=0.46). However, WU intensity did not significantly affect either HRss (F(2,9)=0.48, p=0.63) or VO2ss (F(2,9)=1.10, p=0.36) during the exercise bout. CONCLUSION: The findings suggest that a higher intensity WU improves factors related to improved aerobic performance, i.e. decreased O2 deficit and RPE, without adversely affecting factors that could lead to a decline in performance, i.e. increased HRss and VO2ss.
CD45RB Is a Novel Molecular Therapeutic Target to Inhibit Aβ Peptide-Induced Microglial MAPK Activation

Background Microglial activation, characterized by p38 MAPK or p44/42 MAPK pathway signal transduction, occurs in Alzheimer's disease (AD). Our previous studies demonstrated CD45, a membrane-bound protein tyrosine phosphatase (PTP), opposed β-amyloid (Aβ) peptide-induced microglial activation via inhibition of p44/42 MAPK. Additionally we have shown agonism of the RB isoform of CD45 (CD45RB) abrogates lipopolysaccharide (LPS)-induced microglial activation. Methodology and Results In this study, CD45RB modulation of Aβ peptide or LPS-activated primary cultured microglial cells was further investigated. Microglial cells were co-treated with “aged” FITC-Aβ1–42 and multiple CD45 isoform agonist antibodies. Data revealed cross-linking of CD45, particularly the CD45RB isoform, enhances microglial phagocytosis of Aβ1–42 peptide and inhibits LPS-induced activation of p44/42 and p38 pathways. Co-treatment of microglial cells with agonist CD45 antibodies results in significant inhibition of LPS-induced microglial TNF-α and IL-6 release through p44/42 and/or p38 pathways. Moreover, inhibition of either of these pathways augmented CD45RB cross-linking induced microglial phagocytosis of Aβ1–42 peptide. To investigate the mechanism(s) involved, microglial cells were co-treated with a PTP inhibitor (potassium bisperoxo [1,10-phenanthroline oxovanadate; Phen]) and Aβ1–42 peptides. Data showed synergistic induction of microglial activation as evidenced by TNF-α and IL-6 release; both of which are demonstrated to be dependent on increased p44/42 and/or p38 activation. Finally, it was observed that cross-linking of CD45RB in the presence of Aβ1–42 peptide, inhibits co-localization of microglial MHC class II and Aβ peptide; suggesting CD45 activation inhibits the antigen presenting phenotype of microglial cells. Conclusion In summary, p38 MAPK is another novel signaling pathway, besides p44/42, in which CD45RB cross-linking negatively regulates microglial Aβ phagocytosis while increasing potentially neurotoxic inflammation. Therefore, agonism of CD45RB PTP activity may be an effective therapeutic target for novel agents to treat AD due to its Aβ lowering, and inflammation reducing, properties that are particularly targeted at microglial cells. Such treatments may be more effective with less potential to produce systemic side-effects than therapeutics which induce non-specific, systemic down-regulation of inflammation.
K-Means-Type Algorithms on Distributed Memory Computer

Partitioning a set of objects into homogeneous clusters is a fundamental operation in data mining. The k-means-type algorithm is best suited for implementing this operation because of its efficiency in clustering large numerical and categorical data sets. An efficient parallel k-means-type algorithm for clustering data sets on a distributed share-nothing parallel system is considered. It has a simple communication scheme which performs only one round of information exchange in every iteration. We show that the speedup of our algorithm is asymptotically linear when the number of objects is sufficiently large. We implement the parallel k-means-type algorithm on an IBM SP2 parallel machine. The performance studies show that the algorithm has nice parallelism in experiments.
Source Association, DOA, and Fading Coefficients Estimation for Multipath Signals

This paper addresses the source association (SA), direction of arrival (DOA), and fading coefficients (FCs) estimation problem in multipath environment. First, we establish a rank reduction property for a multipath signal model with the existence of multiple groups of coherent signals. Subsequently, based on this property, effective algorithms for SA, DOA, and FCs estimation have been developed. The proposed DOA and FCs estimation methods exploit the multipath structure information to achieve improved accuracy. The new DOA estimation methods work well even in the case that the DOAs of the multipath signals associated with different sources are (nearly) overlapped. Meanwhile, the new methods are applicable to arbitrary array geometry while without decreasing the effective array aperture. Then, the stochastic Cramér–Rao bound on DOA and FCs estimation of multipath model (MCRB) exploiting the multipath structure information is derived in closed form. Numerical simulations have been provided to demonstrate the effectiveness of the proposed methods.
Description of Himalayan Mosquito Pupae III, Ochlerotatus albolateralis and Ochlerotatus deccanus

Abstract The pupae of Ochlerotatus albolateralis and Oc. deccanus are described and illustrated for the first time from specimens collected in the Himalayan Mountains in Nepal, breeding in tree holes and bamboo stumps. Chaetotaxal tables and illustrations show the morphology of their setae. Characters to recognize each species are explained.
Direct T Cell Activation via CD40 Ligand Generates High Avidity CD8+ T Cells Capable of Breaking Immunological Tolerance for the Control of Tumors

CD40 and CD40 ligand (CD40L) are costimulatory molecules that play a pivotal role in the proinflammatory immune response. Primarily expressed by activated CD4+ T cells, CD40L binds to CD40 on antigen presenting cells (APCs), thereby inducing APC activation. APCs, in turn, prime cytotoxic T lymphocytes (CTLs). Here, two tumor-associated antigen (TAA) animal models, p53-based and GP100-based, were utilized to examine the ability of CD40-CD40L to improve antigen-specific CTL-mediated antitumor immune responses. Although p53 and GP100 are self-antigens that generate low affinity antigen-specific CD8+ T cells, studies have shown that their functional avidity can be improved with CD40L-expressing APCs. Therefore, in the current study, we immunized mice with a DNA construct encoding a TAA in conjunction with another construct encoding CD40L via intramuscular injection followed by electroporation. We observed a significant increase in the antigen-specific CTL-mediated immune responses as well as the potent antitumor effects in both models. Antibody depletion experiments demonstrated that CD8+ T cells play a crucial role in eliciting antitumor effects in vaccinated mice. Furthermore, we showed that in vitro stimulation with irradiated tumor cells expressing both TAA and CD40L improved the functional avidity of antigen-specific CD8+ T cells. Thus, our data show that vaccination with TAA/CD40L DNA can induce potent antitumor effects against TAA-expressing tumors through the generation of better functioning antigen-specific CD8+ T cells. Our study serves as an important foundation for future clinical translation.
Photolithography and Its Impact on Microfluidics

Microfluidics is the science and technology of systems that process or manipulate small amounts (microto picoliters) of fluids, using channels with dimensions of tens to hundreds of micrometers (Whitesides, 2006). Microfluidics offers several advantages in a variety of fields including fuel cells (Dyer, 2002; Jankowski et al., 2002; Erdler et al., 2006; Nguyen et al., 2006; Morse, 2007; Kuriyama et al., 2008; Kjeang et al., 2009), forensics (Verpoorte, 2002), clinical diagnostics (Figeys et al., 2000; Mitchell, 2001; Verpoorte, 2002; Andersson et al., 2003; Verpoorte et al., 2003; Chung et al., 2007), biotechnology (Craighead, 2006), and drug discovery (Weigl et al., 2003; Dittrich and Manz, 2006). An insight into the origin, the present, and the future of this exciting field has been presented by Whitesides (2006). Other excellent reviews are those by Verpoorte et al. (2003), Gravesen et al. (1993), Reyes et al. (2002), Auroux et al. (2002), Dittrich et al. (2006), and Vilkner et al. (2004). The physics and scaling laws in fluidics have been detailed by Beebe et al. (2002), Hu et al. (2007), Janasek et al. (2006), Mijatovic et al. (2005), and Stone et al. (2004). A treatise on the different CONTENTS
Comparison of reverse-transcription real-time PCR and immunohistochemistry for the detection of canine distemper virus infection in raccoons in Ontario, Canada

Canine distemper virus (CDV) is a widespread morbillivirus that causes subclinical to fatal infections in domestic and wild carnivores. Raccoons (Procyon lotor) are CDV reservoirs and suffer from associated disease. Aspects of pathogenesis may lead to difficulty in the interpretation of commonly used testing modalities, such as reverse-transcription real-time (RT-rt)PCR and immunohistochemistry (IHC). The reliance upon such tests is greater for wildlife, which are often submitted as carcasses with no clinical history. We compared CDV RT-rtPCR results to immunohistochemistry (the gold standard) in tissues from 74 raccoons. These tests had high kappa agreement (lymph node: 0.9335; lung: 0.8671) and a negative correlation between IHC score and threshold cycle (Ct) value for lymph node and lung (Spearman rank correlation coefficient [rs] = −0.8555 and −0.8179, respectively; p < 0.00001). An RT-rtPCR Ct value of 30 in lung and lymph node with sensitivity and specificity of 92.3 and 92.6% and 86.8 and 96.4%, respectively, was suitable for determining CDV involvement. Conjunctival swabs provide an alternative for distemper diagnosis, as there was a strong correlation between Ct values of conjunctival swabs and tissues (rs = −0.8498, p < 0.00001, n = 46). This information will aid in more efficient and accurate diagnoses in individuals, small-scale outbreaks, and epidemiologic investigations in wildlife.
Boundary-Aware Multidomain Subspace Deformation

In this paper, we propose a novel framework for multidomain subspace deformation using node-wise corotational elasticity. With the proper construction of subspaces based on the knowledge of the boundary deformation, we can use the Lagrange multiplier technique to impose coupling constraints at the boundary without overconstraining. In our deformation algorithm, the number of constraint equations to couple two neighboring domains is not related to the number of the nodes on the boundary but is the same as the number of the selected boundary deformation modes. The crack artifact is not present in our simulation result, and the domain decomposition with loops can be easily handled. Experimental results show that the single-core implementation of our algorithm can achieve real-time performance in simulating deformable objects with around quarter million tetrahedral elements.
Nonlinear model predictive control of an upper extremity rehabilitation robot using a two-dimensional human-robot interaction model

Stroke rehabilitation technologies have focused on reducing treatment cost while improving effectiveness. Rehabilitation robots are generally developed for home and clinical usage to: 1) deliver repetitive practice to post-stroke patients, 2) minimize therapist interventions, and 3) increase the number of patients per therapist, thereby decreasing the associated cost. The control of rehabilitation robots is often limited to black-or gray-box approaches; thus, safety issues regarding the human-robot interaction are not easily considered. To overcome this issue, controllers working with physics-based models gain more importance. In this study, we have developed an efficient two dimensional (2D) human-robot interaction model to implement a model-based controller on a planar end-effector-type rehabilitation robot. The developed model was used within a nonlinear model predictive control (NMPC) structure to control the rehabilitation robot. The GPOPS-II optimal control package was used to implement the proposed NMPC structure. The controller performance was evaluated by simulating the human-robot rehabilitation system, modeled in MapleSim®. In this system, a musculoskeletal model of the arm interacting with the robot is used to predict movement and muscle activation patterns, which are used by the controller to provide optimal assistance to the patient. In simulations, the controller achieved desired performance and predicted muscular activities of the dysfunctional subject with a good accuracy. In our future work, a structure exploiting the NMPC framework will be developed for the real-time control of the rehabilitation robot.
Gesture and motor skill in relation to language in children with language impairment.

PURPOSE To examine gesture and motor abilities in relation to language in children with language impairment (LI). METHOD Eleven children with LI (aged 2;7 to 6;1 [years;months]) and 16 typically developing (TD) children of similar chronological ages completed 2 picture narration tasks, and their language (rate of verbal utterances, mean length of utterance, and number of different words) and gestures (coded for type, co-occurrence with language, and informational relationship to language) were examined. Fine and gross motor items from the Battelle Developmental Screening Inventory (J. Newborg, J. R. Stock, L. Wneck, J. Guidubaldi, & J. Suinick, 1994) and the Child Development Inventory (H. R. Ireton, 1992) were administered. RESULTS Relative to TD peers, children with LI used gestures at a higher rate and produced greater proportions of gesture-only communications, conventional gestures, and gestures that added unique information to co-occurring language. However, they performed more poorly on measures of fine and gross motor abilities. Regression analyses indicated that within the LI but not the TD group, poorer expressive language was related to more frequent gesture production. CONCLUSIONS When language is impaired, difficulties are also apparent in motor abilities, but gesture assumes a compensatory role. These findings underscore the utility of including spontaneous gesture and motor abilities in clinical assessment of and intervention for preschool children with language concerns.
Thrombin neutralizes plasminogen activator inhibitor 1 (PAI-1) that is complexed with vitronectin in the endothelial cell matrix

Vitronectin endows plasminogen activator inhibitor 1 (PAI-1), the fast- acting inhibitor of both tissue-type plasminogen activator (t-PA) and urokinase-type plasminogen activator (u-PA), with additional thrombin inhibitory properties. In view of the apparent association between PAI- 1 and vitronectin in the endothelial cell matrix (ECM), we analyzed the interaction between PAI-1 and thrombin in this environment. Upon incubating 125I-labeled alpha-thrombin with endothelial cell matrix (ECM), the protease formed SDS-stable complexes exclusively with PAI-1, with subsequent release of these complexes into the supernatant. Vitronectin was required as a cofactor for the association between PAI- 1 and thrombin in ECM. Metabolic labeling of endothelial cell proteins, followed by incubation of ECM with t-PA, u-PA, or thrombin, indicated that all three proteases depleted PAI-1 from ECM by complex formation and proteolytic cleavage. Proteolytically inactive thrombin as well as anticoagulant thrombin, i.e., thrombin in complex with its endothelial cell surface receptor thrombomodulin, did not neutralize PAI-1, emphasizing that the procoagulant moiety of thrombin is required for a functional interaction with PAI-1. A physiological implication of our findings may be related to the mutual neutralization of both PAI-1 and thrombin, providing a new link between plasminogen activation and the coagulation system. Evidence is provided that in ECM, procoagulant thrombin may promote plasminogen activator activity by inactivating PAI- 1.
Contribution à l'apprentissage statistique à base de modèles génératifs pour données complexes.

Ce memoire synthetise les activites de recherche que j'ai menees de 2005 a 2012, sur la thematique de l'apprentissage statistique des donnees complexes, abordee par le biais de modeles probabilistes parametriques generatifs. Plusieurs types de donnees complexes sont considerees. Les donnees issues de populations differentes ont ete abordees en proposant des modeles de lien parametriques entre populations, permettant d'adapter les modeles statistiques d'une population vers l'autre, en evitant une lourde collecte de nouvelles donnees. Les donnees de rang, definissant un classement d'objets selon un ordre de preference, les donnees ordinales, qui sont des donnees qualitatives ayant des modalites ordonnees, et les donnees fonctionnelles, ou l'observation statistique consiste en une ou plusieurs courbes, ont egalement ete etudies. Pour ces trois types de donnees, des modeles generatifs probabilistes ont ete definis et utilises en classification automatique de donnees multivariees. Enfin les donnees de grande dimension, que l'on rencontre lorsque le nombre de variables du probleme depasse celui des observations, ont ete etudiees dans un cadre de regression. Deux approches, fruits de deux theses de doctorat que je co-encadre, sont proposes: l'une utilisant des algorithmes d'optimisation combinatoire pour explorer de facon efficace l'espace des variables, et l'autre definissant un modele de regression regroupant ensemble les variables ayant un effet similaire.