Miracle-dz/UniFAR-FTUs huggingface dataset:
Public/Private Negotiation and Strategic Co-evolution in a Biocluster

Clusters are characterized by partnership practices that lead to a high competitiveness. However some of them encounter coordination difficulties due to conflicts for the appropriation of collective gains. It is more particularly the case of bioclusters because of their sectorial particularities and because of the different public policies improved. Stemming from an analysis of conflicts at stake in a biocluster, this article aims at bringing to light how firms and institutions strategies emerge and co-evolve as their actions are characterized by divergent interests. According to an evolutionary perspective, we propose an exploratory simulation leading to an analysis of the mutual adaptation dynamics developed by the agents involved. The results show on one hand that firms adjust their bargaining strategies according to uncertainty and to their perception of the gains which might be generated at the collective level. On the other hand, the model shows that local authorities can play a regulatory part in the game. This exploratory research contributes to the comprehension of the management public modalities so as to generate cooperation and innovation within bioclusters.
Modern Scientific Visualization is More than Just Pretty Pictures

Author(s): Bethel, E Wes | Abstract: While the primary product of scientific visualization is images and movies, its primary objective is really scientific insight. Too often, the focus of visualization research is on the product, not the mission. This paper presents two case studies, both that appear in previous publications, that focus on using visualization technology to produce insight. The first applies "Query-Driven Visualization" concepts to laser wakefield simulation data to help identify and analyze the process of beam formation. The second uses topological analysis to provide a quantitative basis for (i) understanding the mixing process in hydrodynamic simulations, and (ii) performing comparative analysis of data from two different types of simulations that model hydrodynamic instability.
An iterative receiver design with CFO, SFO, channel estimation and equalization for OFDM systems over multipath fading channels

An iteration scheme is proposed to robust carrier frequency offset (CFO), sampling frequency offset (SFO) and channel impulse response (CIR) estimation for OFDM systems over synchronization errors and multipath fading channel environments. The development of the estimators involves the following procedures. First, a joint time-frequency cross-correlation scheme is proposed to estimate CFO and SFO, which can resist the multipath fading channel effect. Next, using the estimated CFO and SFO parameters, a least square (LS) algorithm with low dimensional sub-block transformed-preamble is utilized to estimate CIR. Finally, with inter-carrier interference (ICI) cancellation, the proposed estimators can provide more accurate parameters estimation. The main advantage of the proposed estimators is lower computational complexity. Computer simulation results show that the proposed estimators with ICI cancellation can obviously offer better performance and overcome the error floor problem at higher SNR scenario.
Model-Free Robust Adaptive Control for flexible rubber objects manipulation

This article addresses the control problem of robots with unknown dynamics and manipulating flexible rubber objects of unknown elasticity. The manipulated rubber object is considered to be interacting with arbitrarily-switched constraints. Such a kind of robot system is shown to have switched impedance parameters during a task execution that results in an unknown hybrid nonlinear system with arbitrarily switched signal. A Model-Free Robust Adaptive Control (MFRAC) strategy is proposed for such a robot system that is proved to guarantee global stable performance with all closed loop signals are assured to be bounded. The suggested MFRAC strategy relies on the synergy of the Adaptive Fuzzy System (AFS), the Sliding Mode Control (SMC), and the notion of Common Lyapunov Functions (CLF). The AFS relaxes the need for knowing the precise robot dynamics, the SMC adds robustness against the drift of the dynamics parameters, and the CLF accommodates the arbitrary switching of the impedance parameters. The bounds of the impedance parameters are adapted online and incorporated in the MFRAC design such that a convergent performance is achieved. Experiment is conducted on a KUKA Lightweight Robot (LWR) doing flexible rubber peg-in-hole assembly process that falls in the category of systems considered in this article. From the experimental results, excellent tracking performance is reported when using the proposed MFRAC strategy for the considered robotic system despite the dynamics anonymity and the unknown impedance parameters arbitrary switching.
Evaluation of Confidence Intervals for a Binomial Parameter and for the Ratio of Poisson Means

Confidence intervals for a binomial parameter or for the ratio of Poisson means are commonly desired in high energy physics (HEP) applications such as measuring the detection efficiency of a device or algorithm, or measuring branching ratios. Due to the discreteness of the observed data, in both of these closely related problems the frequentist coverage probability unfortunately depends on the unknown parameter. Trade-offs among desiderata for sets of intervals have thus led to numerous sets of intervals in the statistics literature, while in the HEP literature one typically encounters only the classic intervals of Clopper-Pearson (central intervals with strictly no undercoverage but substantial over-coverage) or a few approximate methods which are known in the statistics literature to perform poorly. When strict coverage is relaxed, some sort of averaging is needed to compare intervals. In most of the literature, this averaging is over different values of the unknown parameter, which is conceptually problematic from the frequentist point of view in which the unknown parameter is typically fixed. In contrast, we perform an (unconditional) average over observed data in the ratio-of-Poisson-means problem. We are led to two recommendations (Clopper-Pearson intervals and intervals from inverting the likelihood ratio test) if strict coverage is desired (for central and non-central intervals, respectively), with Lancaster’s mid-P modification to either if only average coverage is desired.
Neural networks to predict ozone pollution in industrial areas

In this paper a novel approach, based on a neural network structure, is introduced in order to face with the problem of pollutant estimation in an industrial area. In particular a short-term prediction (six hours ahead) of the O3 pollutant mean value has been performed. The results obtained show the capability of such structures to model complex chemical reactions heavily dependent on the meteorological conditions and on the typical geographical characteristics.
Acquisition of Finnish derivational morphology: School-age children and young adults

The current study examined how morpho-semantic processing of derivational morphology develops from later childhood through adolescence to adulthood in Finnish. Finnish is a synthetic language rich both in derivation and inflection. It has been suggested that children gradually acquire the ability to process morphologically complex word structures. However, this development could be delayed because of the complex derivational morphology in Finnish. To assess this, three age groups of Finnish native speakers participated in a priming study, in which they made a visual lexical decision for the target words. There were three types of primes: morphologically related words, pseudowords, and unrelated words. The reaction times results showed a significant difference between all the groups, which implies that the word processing is still developing in adolescence. The error rates unveiled a similar pattern to reaction times. The prime type affected the recognition: words with morphological primes were processed faster than words with pseudoword primes, which in turn were processed faster than words with unrelated primes. Moreover, males made significantly more errors than females with morphological and pseudoword prime conditions.
Abstract 19153: Morphine Delays and Attenuates Ticagrelor Exposure and Action in Patients With Myocardial Infarction: The Randomized, Double-blind, Placebo-controlled Impression Trial

Introduction: The currently available data from observational studies and a randomized trial on clopidogrel conducted in healthy volunteers suggest existence of drug-drug interactions between morphine and oral P2Y12 inhibitors, when administered together. Hypothesis: We aimed to test the hypothesis that morfine administered intravenously excerts the negative impact on pharmacokinetics and pharmacodynamics of ticagrelor and its active metabolite (AR-C124910XX) in patients with myocardial infarction. Methods: In a single center, randomized, double-blind trial, participants were assigned in a 1:1 ratio to receive intravenously either morphine (5 mg) or placebo, followed by a 180 mg loading dose of ticagrelor. Pharmacokinetics was determined with liquid chromatography tandem mass spectrometry, while ticagrelor antiplatelet effect was measured with up to 3 different platelet function tests: vasodilator-stimulated phosphoprotein (VASP) phosphorylation assay, multiple electrode aggregometry and VerifyNow P2Y12. Results: The pharmacokinetic and pharmacodynamic assessment was performed in 70 patients (35 in each study group). Morphine administration lowered the total exposure to ticagrelor and its active metabolite by 35.6% (AUC(0-12): 6307 vs. 9791 ng·h/mL; p=0.003) and 37.1% (AUC(0-12): 1503 vs. 2388 ng·h/mL; p=0.008), respectively, with a concomitant delay in maximal plasma concentration of ticagrelor (4 vs. 2 h; p=0.002) and AR-C124910XX (6 vs. 4 h; p=0.03) in morphine-treated patients. Multiple regression analysis showed that lower AUC(0-12) values for ticagrelor were associated with morphine administration (p=0.003) and the presence of ST-segment elevation myocardial infarction (p=0.010). All three methods of platelet reactivity assessment consistently showed a stronger antiplatelet effect of ticagrelor in the placebo group as reflected by a higher prevalence of high platelet reactivity in patients receiving morphine. Conclusions: Morphine delays and attenuates ticagrelor exposure and action in patients with myocardial infarction.
Do not play God: contrasting effects of deontological guilt and pride on decision-making

Recent accounts support the existence of two distinct feelings of guilt: altruistic guilt (AG), arising from the appraisal of not having been altruistic toward a victim and deontological guilt (DG), emerging from the appraisal of having violated an intuitive moral rule. Neuroimaging data has shown that the two guilt feelings trigger different neural networks, with DG selectively activating the insula, a brain area involved in the processing of disgust and self-reproach. Thus, insula activation could reflect the major involvement of self-reproach in DG rather than in AG. However, only a few studies have empirically tested whether and how DG and AG differently affect decision making and none have compared enhanced self-worth. Here we asked three groups of participants, respectively, induced with either pride, DG or AG, to participate in a third-party version of the ultimatum game in which they were asked to decide on behalf of others to accept or reject economic offers with several degrees of fairness. Results revealed that only deontological participants had higher median acceptances of Moderately Unfair offers as compared to proud participants. However fairness judgments were not different between groups, suggesting that deontological participants’ moral standards had not decreased. Crucially, a higher increase in DG was associated with an increase in the odds of accepting 30:70 offers. The opposite effects that DG and pride exert on self-worth can account for these results. Specifically, proud participants felt entitled enough to take action in order to restore equity, while deontological participants followed the “Do not play God” principle, which limited their decisional autonomy, not allowing them to decide on behalf of others.
RNA of Enterococcus faecalis Strain EC-12 Is a Major Component Inducing Interleukin-12 Production from Human Monocytic Cells

Interleukin-12 (IL-12) is an important cytokine for the immunomodulatory effects of lactic acid bacteria (LAB). Using murine immune cells, we previously reported that the RNA of Enterococcus faecalis EC-12, a LAB strain exerting probiotic-like beneficial effects, is the major IL-12-inducing immunogenic component. However, it was recently revealed that bacterial RNA can be a ligand for Toll-like receptor (TLR) 13, which is only expressed in mice. Because TLR13 is not expressed in humans, the immuno-stimulatory and -modulatory effects of LAB RNA in human cells should be augmented excluding TLR13 contribution. In experiment 1 of this study, the role of LAB RNA in IL-12 induction in human immune cells was studied using three LAB strains, E.faecalis EC-12, Lactobacillus gasseri JCM5344, and Bifidobacterium breve JCM1192. RNase A treatment of heat-killed LAB significantly decreased the IL-12 production of human peripheral blood mononuclear cells on stimulation, while RNase III treatment revealed virtually no effects. Further, IL-12 production against heat-killed E. faecalis EC-12 was abolished by depleting monocytes. These results demonstrated that single stranded RNA (ssRNA) of LAB is a strong inducer of IL-12 production from human monocytes. In experiment 2, major receptor for ssRNA of E. faecalis EC-12 was identified using THP-1 cells, a human monocytic cell line. The type of RNA molecules of E. faecalis EC-12 responsible for IL-12 induction was also identified. IL-12 production induced by the total RNA of E. faecalis EC-12 was significantly reduced by the treatment of siRNA for TLR8 but not for TLR7. Furthermore, both 23S and 16S rRNA, but not mRNA, of E. faecalis EC-12 markedly induced IL-12 production from THP-1 cells. These results suggested that the recognition of ssRNA of E. faecalis EC-12 was mediated by TLR8 and that rRNA was the RNA molecule that exhibited IL-12-inducing ability in human cells.
Numerical Investigation of Carbon Dioxide Diffusion in Indoor Hypobaric Atmosphere

The hypo baric atmosphere at high altitude has very negative effects on human's physiology and health. In the present paper, by considering human's respiration capacity and component, the RNG k-ε turbulent model was developed to study the heat transfer and CO2 diffusion of indoor air in the hypo baric atmosphere. The results show that as the pressure decreases, the CO2 diffusion tends to be weak, leading to an increasing CO2 concentration. But raising the supplied air flow speed helps to improve the CO2 diffusion and hence indoor air quality.
An approach for a component-based visualization of heterogeneous manufacturing data sources

The analysis of modern production environments requires a clear and understandable uniform visualization of the information from all levels of the production. This visualization has to be on the one hand light weight to avoid cognitive overload of the users and on the other hand rich enough to provide information about all production information sources. To solve this issue we propose to use a unified component-based visualization where single items can be exchanged to fulfill the informational needs of the users from heterogeneous data sources.
Automatic semantic acquisition through text mining techniques

Data mining theories, research, and formalizations, having emerged from ever faster computers and growing databases in the early 1990’s, is today a mature ﬁeld in its own right, heavily employed in industries where customer relationship management is critical. Only now is it beginning to be embraced by the scientiﬁc community. Existing expert systems fail in that they require either pre-programmed rules to make decisions. On the other hand, a system capable of grasping textual semantics can learn world knowledge facts, and a system capable of learning world knowledge facts can infer other facts and predict future trends and events. This paper presents preliminary re-sults of automated semantic acquisition.
Fast Localization in Large-Scale Environments Using Supervised Indexing of Binary Features

The essence of image-based localization lies in matching 2D key points in the query image and 3D points in the database. State-of-the-art methods mostly employ sophisticated key point detectors and feature descriptors, e.g., Difference of Gaussian (DoG) and Scale Invariant Feature Transform (SIFT), to ensure robust matching. While a high registration rate is attained, the registration speed is impeded by the expensive key point detection and the descriptor extraction. In this paper, we propose to use efficient key point detectors along with binary feature descriptors, since the extraction of such binary features is extremely fast. The naive usage of binary features, however, does not lend itself to significant speedup of localization, since existing indexing approaches, such as hierarchical clustering trees and locality sensitive hashing, are not efficient enough in indexing binary features and matching binary features turns out to be much slower than matching SIFT features. To overcome this, we propose a much more efficient indexing approach for approximate nearest neighbor search of binary features. This approach resorts to randomized trees that are constructed in a supervised training process by exploiting the label information derived from that multiple features correspond to a common 3D point. In the tree construction process, node tests are selected in a way such that trees have uniform leaf sizes and low error rates, which are two desired properties for efficient approximate nearest neighbor search. To further improve the search efficiency, a probabilistic priority search strategy is adopted. Apart from the label information, this strategy also uses non-binary pixel intensity differences available in descriptor extraction. By using the proposed indexing approach, matching binary features is no longer much slower but slightly faster than matching SIFT features. Consequently, the overall localization speed is significantly improved due to the much faster key point detection and descriptor extraction. It is empirically demonstrated that the localization speed is improved by an order of magnitude as compared with state-of-the-art methods, while comparable registration rate and localization accuracy are still maintained.
Chronic Insomnia: Clinical and Research Challenges – An Agenda

Chronic insomnia afflicts up to 10% of the population in Western industrialized countries. It is characterized by delayed sleep onset, problems in maintaining sleep, early morning awakening or the feeling of non-restorative sleep coupled with significant daytime impairments on an emotional, social or professional level. It can occur as a co-morbid condition in any other medical or mental disorder, but also as a primary condition. Within the last decade new diagnostic and differential diagnostic approaches have been suggested that enhance diagnostic precision. Epidemiological data and data relating to the health care and cost situation of chronic insomnia suggest a huge burden for society. Chronic insomnia leads to a clear-cut increased risk for psychopathology (i. e., affective disorders) and probably also for cardiovascular and metabolic dysfunction. The pathophysiology of the condition is still poorly understood and will profit from integrating modern neuroscientific approaches (animal studies, molecular biology, neuroimaging, neurophysiology, etc.). Current treatment strategies are mainly based on cognitive behavioural interventions (CBT-I) and hypnotic treatment with benzodiazepine receptor agonists and sedating antidepressants. Although the effectiveness of these treatments has been clearly demonstrated, a substantial proportion of patients proves to be treatment-resistant or profits only poorly. The question of long-term pharmaceutical treatment of chronic insomnia, at least in Europe, is unresolved and urgently needs answers. Novel rational treatment avenues require clues on causes and mechanisms from integrated neuroscientific approaches. The important issues concerning insomnia treatment in the future especially in Europe will be reviewed and discussed critically.
Evidence for a role of CaMKIV in the development of opioid analgesic tolerance

cAMP response‐element binding protein (CREB), a transcription factor involved in learning, memory and drug addiction, is phosphorylated by calcium–calmodulin‐dependent protein kinase IV (CaMKIV). Here, we show that CaMKIV‐knockout (KO) mice developed less analgesic tolerance after chronic morphine administration with no alteration in physical dependence or acute morphine‐induced analgesia. The increase in phosphorylated CREB expression observed in wild‐type mice after chronic morphine was absent in CaMKIV‐KO mice, while there was no difference in the expression or phosphorylation of the µ‐opioid receptor between groups. Morphine‐treated CaMKIV‐KO mice showed less G‐protein uncoupling from the µ‐opioid receptor than did wild‐type mice, while uncoupling was similar in control wild‐type and KO mice. In addition, morphine reduced inhibitory transmission to a greater degree in CaMKIV‐KO mice than in controls after chronic morphine exposure. Our results provide novel evidence for the role of CaMKIV in the development of opioid analgesic tolerance but not physical dependence.
Quantum Gauge Field Theory in Cohesive Homotopy Type Theory

We implement in the formal language of homotopy type theory a new set of axioms called cohesion. Then we indicate how the resulting cohesive homotopy type theory naturally serves as a formal foundation for central concepts in quantum gauge field theory. This is a brief survey of work by the authors developed in detail elsewhere.
Pinpointing Failure Inducing Event Orderings

A new method is designed to pinpoint failure inducing event orderings in Event Based Systems. Sequence Covering Arrays are used as test suites for systems under test which have only deterministic type of failures. After testing all test cases of SCA to get full coverage on event orderings of length 2 and 3, new test cases are generated using a new method inspired from Delta Debugging Algorithm. Suspicious set of event orderings which are most likely failures, are constructed for each failure type, and this sets are narrowed down adaptively with the result of newly generated test cases. Experiments are carried out with different fault scenarios. Our results suggest that proposed algorithm can detect all failure inducing event orderings using small number of extra test cases.
Extreme value theory based text binarization in documents and natural scenes

This paper presents a novel image binarization method that can deal with degradations such as shadows, non-uniform illumination, low-contrast, large signal-dependent noise, smear and strain. A pre-processing procedure based on morphological operations is first applied to suppress light/dark structures connected to image border. A novel binarization concept based on difference of gamma functions is presented. Next Generalized Extreme Value Distribution (GEVD) is used to find proper threshold for binarization with a significance level. Proposed method emphasizes on region of interest (with the help of morphological operations) and generates less noisy artifacts (due to GEVD). It is much simpler than other methods and works better on degraded documents and natural scene images