Miracle-dz/UniFAR-FTUs huggingface dataset:
Adversarial Sub-sequence for Text Generation

Generative adversarial nets (GAN) has been successfully introduced for generating text to alleviate the exposure bias. However, discriminators in these models only evaluate the entire sequence, which causes feedback sparsity and mode collapse. To tackle these problems, we propose a novel mechanism. It first segments the entire sequence into several sub-sequences. Then these sub-sequences, together with the entire sequence, are evaluated individually by the discriminator. At last these feedback signals are all used to guide the learning of GAN. This mechanism learns the generation of both the entire sequence and the sub-sequences simultaneously. Learning to generate sub-sequences is easy and is helpful in generating an entire sequence. It is easy to improve the existing GAN-based models with this mechanism. We rebuild three previous well-designed models with our mechanism, and the experimental results on benchmark data show these models are improved significantly, the best one outperforms the state-of-the-art model. \footnote[1]{All code and data are available at this https URL
Tracking Monocytes and Macrophages in Tumors With Live Imaging

In most cancers, myeloid cells represent the major component of the immune microenvironment. Deciphering the impact of these cells on tumor growth and in response to various anti-tumor therapies is a key issue. Many studies have elucidated the role of tumor-associated monocytes and tumor-associated macrophages (TAM) in tumor development, angiogenesis, and therapeutic failure. In contrast, tumor dendritic cells (DC) are associated with tumor antigen uptake and T-cell priming. Myeloid subpopulations display differences in ontogeny, state of differentiation and distribution within the neoplastic tissue, making them difficult to study. The development of high-dimensional genomic and cytometric analyses has unveiled the large functional diversity of myeloid cells. Important fundamental insights on the biology of myeloid cells have also been provided by a boom in functional fluorescent imaging techniques, in particular for TAM. These approaches allow the tracking of cell behavior in native physiological environments, incorporating spatio-temporal dimensions in the study of their functional activity. Nevertheless, tracking myeloid cells within the TME remains a challenging process as many markers overlap between monocytes, macrophages, DC, and neutrophils. Therefore, perfect discrimination between myeloid subsets remains impossible to date. Herein we review the specific functions of myeloid cells in tumor development unveiled by image-based tracking, the limits of fluorescent reporters commonly used to accurately track specific myeloid cells, and novel combinations of myeloid-associated fluorescent reporters that better discriminate the relative contributions of these cells to tumor biology according to their origin and tissue localization.
TLR4, but Neither Dectin-1 nor Dectin-2, Participates in the Mollusk Hemocyanin-Induced Proinflammatory Effects in Antigen-Presenting Cells From Mammals

Mollusk hemocyanins have biomedical uses as carriers/adjuvants and nonspecific immunostimulants with beneficial clinical outcomes by triggering the production of proinflammatory cytokines in antigen-presenting cells (APCs) and driving immune responses toward type 1 T helper (Th1) polarization. Significant structural features of hemocyanins as a model antigen are their glycosylation patterns. Indeed, hemocyanins have a multivalent nature as highly mannosylated antigens. We have previously shown that hemocyanins are internalized by APCs through receptor-mediated endocytosis with proteins that contain C-type lectin domains, such as mannose receptor (MR). However, the contribution of other innate immune receptors to the proinflammatory signaling pathway triggered by hemocyanins is unknown. Thus, we studied the roles of Dectin-1, Dectin-2, and Toll-like receptor 4 (TLR4) in the hemocyanin activation of murine APCs, both in dendritic cells (DCs) and macrophages, using hemocyanins from Megathura crenulata (KLH), Concholepas concholepas (CCH) and Fissurella latimarginata (FLH). The results showed that these hemocyanins bound to chimeric Dectin-1 and Dectin-2 receptors in vitro; which significantly decreased when the glycoproteins were deglycosylated. However, hemocyanin-induced proinflammatory effects in APCs from Dectin-1 knock-out (KO) and Dectin-2 KO mice were independent of both receptors. Moreover, when wild-type APCs were cultured in the presence of hemocyanins, phosphorylation of Syk kinase was not detected. We further showed that KLH and FLH induced ERK1/2 phosphorylation, a key event involved in the TLR signaling pathway. We confirmed a glycan-dependent binding of hemocyanins to chimeric TLR4 in vitro. Moreover, DCs from mice deficient for MyD88-adapter-like (Mal), a downstream adapter molecule of TLR4, were partially activated by FLH, suggesting a role of the TLR pathway in hemocyanin recognition to activate APCs. The participation of TLR4 was confirmed through a decrease in IL-12p40 and IL-6 secretion induced by FLH when a TLR4 blocking antibody was used; a reduction was also observed in DCs from C3H/HeJ mice, a mouse strain with a nonfunctional mutation for this receptor. Moreover, IL-6 secretion induced by FLH was abolished in macrophages deficient for TLR4. Our data showed the involvement of TLR4 in the hemocyanin-mediated proinflammatory response in APCs, which could cooperate with MR in innate immune recognition of these glycoproteins.
Compositional Synthesis of Symbolic Models for Networks of Switched Systems

In this letter, we provide a compositional methodology for constructing symbolic models for networks of discrete-time switched systems. We first define a notion of so-called augmented-storage functions to relate switched subsystems and their symbolic models. Then we show that if some dissipativity type conditions are satisfied, one can establish a notion of so-called alternating simulation function as a relation between a network of symbolic models and that of switched subsystems. The alternating simulation function provides an upper bound for the mismatch between the output behavior of the interconnection of switched subsystems and that of their symbolic models. Moreover, we provide an approach to construct symbolic models for discrete-time switched subsystems under some assumptions ensuring incremental passivity of each mode of switched subsystems. Finally, we illustrate the effectiveness of our results through two examples.
Development of a Real-Time Polymerase Chain Reaction Assay for Prediction of the Uptake of Meta-[ 131 I ] iodobenzylguanidine by Neuroblastoma Tumors 1

Purpose: The suitability of neuroblastoma patients for therapy using radiolabeled meta-iodobenzylguanidine (MIBG) is determined by scintigraphy after the administration of a tracer dose of radioiodinated MIBG whose uptake is dependent upon the cellular expression of the noradrenaline transporter (NAT). As a possible alternative to gamma camera imaging, we developed a novel molecular assay of NAT expression. mRNA extracted from neuroblastoma biopsy samples, obtained retrospectively, was reverse transcribed, and NAT-specific cDNA was quantified by real-time PCR, referenced against the expression of the housekeeping gene glyceraldehyde-3-phosphate dehydrogenase. Experimental Design: Tumor specimens from 54 neuroblastoma patients were analyzed using real-time PCR, and NAT expression was compared with the corresponding diagnostic scintigrams. Results: Forty-eight of 54 (89%) of tumors showed MIBG uptake by scintigraphy. NAT expression was found to be significantly associated with MIBG uptake (P < 0.0001, Fisher’s exact test). None of the samples from the six tumors that failed to concentrate MIBG expressed detectable levels of the NAT (specificity 1.0). However, of the 48 MIBG uptake-positive tumors, only 43 (90%) expressed NAT (sensitivity 0.9). The real-time PCR test has a positive predictive value of 1.0 but a negative predictive value of 0.55. Conclusions: The results indicate that whereas this method has substantial ability to predict the capacity of neuroblastoma tumors to accumulate MIBG, confirmation is required in prospective studies to determine more accurately the predictive strength of the test and its role in the management of patients with neuroblastoma.
Quadcopter Flight Control Using a Non-invasive Multi-Modal Brain Computer Interface

Brain-Computer Interfaces (BCIs) translate neuronal information into commands to control external software or hardware, which can improve the quality of life for both healthy and disabled individuals. Here, a multi-modal BCI which combines motor imagery (MI) and steady-state visual evoked potential (SSVEP) is proposed to achieve stable control of a quadcopter in three-dimensional physical space. The complete information common spatial pattern (CICSP) method is used to extract two MI features to control the quadcopter to fly left-forward and right-forward, and canonical correlation analysis (CCA) is employed to perform the SSVEP classification for rise and fall. Eye blinking is designed to switch these two modes while hovering. Real-time feedback is provided to subjects by a global camera. Two flight tasks were conducted in physical space in order to certify the reliability of the BCI system. Subjects were asked to control the quadcopter to fly forward along the zig-zag pattern to pass through a gate in the relatively simple task. For the other complex task, the quadcopter was controlled to pass through two gates successively according to an S-shaped route. The performance of the BCI system is quantified using suitable metrics and subjects are able to acquire 86.5% accuracy for the complicated flight task. It is demonstrated that the multi-modal BCI has the ability to increase the accuracy rate, reduce the task burden, and improve the performance of the BCI system in the real world.
Mood Disorders and Severity of Addiction in Alcohol-Dependent Patients Could Be Mediated by Sex Differences

Background: Alcohol dependence is highly prevalent in the general population; some differences in alcohol use and dependence between women and men have been described, including outcomes and ranging from biological to social variables. This study aims to compare the severity of alcohol dependence with clinical and psychopathological characteristics between sexes. Methods: A cross-sectional descriptive study was conducted in alcohol-dependent outpatients; the recruitment period was 7 years. The assessment of these patients was carried out by obtaining sociodemographic characteristics and using the Semi-structured Clinical Interview for Axis I and II (SCID-I and SCID-II), European version of the Addiction Severity Index (EuropASI), Beck Depression Inventory (BDI), and State–Trait Anxiety Inventory (STAI) scales. Variables were compared and analyzed. Results: The sample was composed of 178 patients (74.2% males and 25.8% females) with a mean age of 46.52 ± 9.86. No sociodemographic differences were found between men and women. Females had a higher rate of suicide attempts and depression symptoms at the treatment onset. When results of EuropASI were compared, females had worse psychological and employment results than males. According to consumption variables, males had an earlier onset of alcohol use, had more regular alcohol use, and develop alcohol dependence earlier than females. Conclusions: According to results, there are sex-dependent differences (severity and other variables such as mood or suicide) in alcohol dependence. Thus, this may implicate the need of future specific research and treatment programs based on the specific necessities of each sex.
LSSD COMPATIBLE AND CONCURRENTLY TESTABLE RAM

Design-for-testability of ASICs has become complex because of embedded RAMs. This paper presents a design methodology for testing embedded RAMs. This methodology is based on scan design, but a remarkable reduction of test vectors for RAMs can be achievcd by using exhaustive random pattern for addressing and a newly designed scan register for data compression. A RAM test circuitry which realizes concurrent testing of multiple RAMs by using this new scan register is presented.
Hybrid position estimator based on high-frequency signal injection and machine learning for EV fault-tolerant control

This paper proposes a novel hybrid position estimation strategy based on merging two self-sensing techniques according to the operating speed. High-frequency (HF) signal injection algorithm is deployed for zero and low-speeds, while the Machine Learning (ML) method is adopted for medium and high speeds. The proposed position estimator is intended for the fault-tolerant control of an interior permanent-magnet-synchronous motor (IPMSM) drive that propels an electrical vehicle (EV).
Désambiguïsation et expansion de requêtes dans un SRI. Etude de l'apport des liens sémantiques

Dans cet article, nous proposons d'exploiter des liens semantiques entre concepts pour ameliorer la recherche d'information. Un thesaurus electronique de langue generale est utilise pour la reformulation des requetes utilisateurs en procedant par un processus d'« expansion prudente » en amont d'un moteur de recherche. Ce processus, transparent a l'utilisateur, exploite d'abord la notion de concepts multitermes pour desambiguiser les mots de la requete. Il s'appuie ensuite sur les relations semantiques entre concepts pour elargir la requete. Differents tests ont ete effectues pour l'evaluation de ce processus qui conduit a une amelioration significative de la pertinence des reponses retournees par le moteur. Les experimentations ont ete realisees en utilisant le moteur Mercure developpe a l'IRIT, WordNet comme base de donnees lexicales et Clef2001 comme collection de tests.
A Novel Point Variant in NTRK3, R645C, Suggests a Role of this Gene in the Pathogenesis of Hirschsprung Disease

Hirschsprung disease (HSCR) is a developmental disorder characterized by the absence of ganglion cells in the myenteric and submucosal plexuses due to a defect in the migration process of neural crest neuroblasts. Manifestation of the disease has been linked to the dysfunction of two principal signalling pathways involved in the enteric nervous system (ENS) formation: the RET‐GDNF and the EDN3‐EDNRB receptor systems. However, the NTF3/NTRK3 signalling pathway plays an essential role in the development of the ENS suggesting a potential role for those genes in the pathogenesis of HSCR. We have sought to evaluate the candidature of the NTRK3 gene, which encodes the TrkC receptor, as a susceptibility gene for Hirschsprung disease. Using dHPLC technology we have screened the NTRK3 coding region in 143 Spanish HSCR patients. A total of four previously described polymorphisms and 12 novel sequence variants were detected. Of note, the novel R645C mutation was detected in 2 affected siblings of a HSCR family also carrying a RET splicing mutation. Using bioinformatics tools we observed that the presence of an additional cysteine residue might implicate structural alterations in the mutated protein. We propose haploinsufficiency as the most probable mechanism for the NTRK3 R645C mutation. NTRK3 and RET mutations in this family only appear together in the HSCR patients, suggesting that they per se are necessary but not sufficient to produce the phenotype. In addition, it is quite probable that the contribution of other still unidentified modifier genes, may be responsible for the different phenotypes (length of aganglionosis) in the two affected members.
Trigrams'n'Tags for Lexical Knowledge Acquisition

In this paper we propose a novel approach that combines syntactic and context information to identify lexical semantic relationships. We compiled semi-automatically and manually created training data and a test set for evaluation with the first sentences from the German version of Wikipedia. We trained the Trigrams’n’Tags Tagger by Brants (Brants, 2000) with a semantically enhanced tagset. The experiments showed that the cleanliness of the data is far more important than the amount of the same. Furthermore, it was shown that bootstrapping is a viable approach to ameliorate the results. Our approach outperformed the competitive lexico-syntactic patterns by 7% leading to an F1-measure of . 91.
The Effect of Coaching Leadership and Subordinate Psychological Capital on the Employee Voice Behavior

Based on the theory of emotional contagion and similar attraction paradigm, this research explored the psychological mechanism of coaching leadership promoting employee voice behavior. The results showed that subordinate psychological capital mediated the relationship between coaching leadership and employee voice behavior. Moreover, supervisor employee dyadic tenure significantly moderated the positive relationships between coaching leadership and voice behavior. Research findings enrich theory and practice of coaching leadership.
Asymmetric Distribution of GFAP in Glioma Multipotent Cells

Asymmetric division (AD) is a fundamental mechanism whereby unequal inheritance of various cellular compounds during mitosis generates unequal fate in the two daughter cells. Unequal repartitions of transcription factors, receptors as well as mRNA have been abundantly described in AD. In contrast, the involvement of intermediate filaments in this process is still largely unknown. AD occurs in stem cells during development but was also recently observed in cancer stem cells. Here, we demonstrate the asymmetric distribution of the main astrocytic intermediate filament, namely the glial fibrillary acid protein (GFAP), in mitotic glioma multipotent cells isolated from glioblastoma (GBM), the most frequent type of brain tumor. Unequal mitotic repartition of GFAP was also observed in mice non-tumoral neural stem cells indicating that this process occurs across species and is not restricted to cancerous cells. Immunofluorescence and videomicroscopy were used to capture these rare and transient events. Considering the role of intermediate filaments in cytoplasm organization and cell signaling, we propose that asymmetric distribution of GFAP could possibly participate in the regulation of normal and cancerous neural stem cell fate.
Model evidence from nonequilibrium simulations

The marginal likelihood, or model evidence, is a key quantity in Bayesian parameter estimation and model comparison. For many probabilistic models, computation of the marginal likelihood is challenging, because it involves a sum or integral over an enormous parameter space. Markov chain Monte Carlo (MCMC) is a powerful approach to compute marginal likelihoods. Various MCMC algorithms and evidence estimators have been proposed in the literature. Here we discuss the use of nonequilibrium techniques for estimating the marginal likelihood. Nonequilibrium estimators build on recent developments in statistical physics and are known as annealed importance sampling (AIS) and reverse AIS in probabilistic machine learning. We introduce estimators for the model evidence that combine forward and backward simulations and show for various challenging models that the evidence estimators outperform forward and reverse AIS.
Generation of Large Random Models for Benchmarking

Since model driven engineering (MDE) is applied to larger and more complex system, the memory and execution time performance of model processing tools and frameworks has become important. Benchmarks are a valuable tool to evaluate performance and hence assess scalability. But, benchmarks rely on reasonably large models that are unbiased, can be shaped to distinct use-case scenarios, and are ”real” enough (e.g. non-uniform) to cause real-world behavior (especially when mechanisms that exploit repetitive patterns like caching, compression, JIT-compilation, etc. are involved). Creating large models is expensive and erroneous, and neither existing models nor uniform synthetic models cover all three of the wanted properties. In this paper, we use randomness to generate unbiased, non-uniform models. Furthermore, we use distributions and parametrization to shape these models to simulate different use-case scenarios. We present a meta-model-based framework that allows us to describe and create randomly generated models based on a meta-model and a description written in a specifically developed generator DSL. We use a random code generator for an object-oriented programming language as case study and compare our result to non-randomly and synthetically created code, as well as to existing Java-code.
SLAM (CD150)-Independent Measles Virus Entry as Revealed by Recombinant Virus Expressing Green Fluorescent Protein

ABSTRACT Wild-type measles virus (MV) strains use human signaling lymphocyte activation molecule (SLAM) as a cellular receptor, while vaccine strains such as the Edmonston strain can use both SLAM and CD46 as receptors. Although the expression of SLAM is restricted to cells of the immune system (lymphocytes, dendritic cells, and monocytes), histopathological studies with humans and experimentally infected monkeys have shown that MV also infects SLAM-negative cells, including epithelial, endothelial, and neuronal cells. In an attempt to explain these findings, we produced the enhanced green fluorescent protein (EGFP)-expressing recombinant MV (IC323-EGFP) based on the wild-type IC-B strain. IC323-EGFP showed almost the same growth kinetics as the parental recombinant MV and produced large syncytia exhibiting green autofluorescence in SLAM-positive cells. Interestingly, all SLAM-negative cell lines examined also showed green autofluorescence after infection with IC323-EGFP, although the virus hardly spread from the originally infected individual cells and thus did not induce syncytia. When the number of EGFP-expressing cells after infection was taken as an indicator, the infectivities of IC323-EGFP for SLAM-negative cells were 2 to 3 logs lower than those for SLAM-positive cells. Anti-MV hemagglutinin antibody or fusion block peptide, but not anti-CD46 antibody, blocked IC323-EGFP infection of SLAM-negative cells. This infection occurred under conditions in which entry via endocytosis was inhibited. These results indicate that MV can infect a variety of cells, albeit with a low efficiency, by using an as yet unidentified receptor(s) other than SLAM or CD46, in part explaining the observed MV infection of SLAM-negative cells in vivo.
Optimal Performance of Inverted Files

Many managerial users of information systems require access to data based upon nonunique data record qualifications or classifications. A class of computer file organizations, called inverted files, has been devised to efficiently support such data retrieval. Fundamental to the use of such a file or database organization is the selection of data elements or keys for creation of nonunique key indexes. These indexes provide rapid access to data records which are qualified by logical key expressions. This paper formulates this selection problem as a zero-one, nonlinear programming problem with constraints and describes an optimization algorithm. The model recognizes both known and ad hoc uses of data; complex, Boolean key queries; and index storage capacity and query response time constraints. Computational experience is similar to previous algorithms, which consider more restricted problem formulations.