Miracle-dz/UniFAR-FTUs huggingface dataset:
Smokers and ex‐smokers have shared differences in the neural substrates for potential monetary gains and losses

Despite an increased understanding of nicotine addiction, there is a scarcity of research comparing the neural correlates of non‐drug reward between smokers and ex‐smokers. Long‐term changes in reward‐related brain functioning for non‐drug incentives may elucidate patterns of functioning that potentially contribute to ongoing smoking behaviour in current smokers. Similarly, examining the effects of previous chronic nicotine exposure during a period of extended abstinence may reveal whether there are neural correlates responsible for non‐drug reward processing that are different from current smokers. The current study, therefore, sets out to examine the neural correlates of reward and loss anticipation, and their respective outcomes, in smokers, ex‐smokers and matched controls using a monetary incentive delay task during functional magnetic resonance imaging. Here, we report that in the absence of any significant behavioural group differences, both smokers and ex‐smokers showed a significantly greater activation change in the lateral orbitofrontal/anterior insular cortex compared with smokers when anticipating both potential monetary gains and losses. We further report that ex‐smokers showed a significantly greater activation change in the ventral putamen compared with both controls and smokers and in the caudate compared with controls during the anticipation of potential monetary losses only. The results suggest that smoking may sensitize striato‐orbitofrontal circuitry subserving motivational processes for loss avoidance and reward gain in nicotine addiction.
Analysis of Cost-Service Trade-off in Inventory Management through Evolutionary Multi-objective Optimization

Inventory management involves trade-offs between conflicting objectives such as cost minimization and service level maximization. The trade-off analysis of cycle stock investment and workload, so called the exchange curve, possibly dates back to several decades ago. These analyses seldom formulated inventory trade-offs as a multi-objective optimization problem and their solution procedures were all based on single objective optimization. To our best knowledge, there do exist some studies that propose non-classical approach to multi-objective inventory management. However, some of the objectives in earlier studies are not conflicted each other such that the multiobjective models were not properly justified. In this paper, a Inventory Management Model without redundancy is discussed first. Then a solution procedure based on evolutionary multi-objective optimization is introduced to effectively solve the fixed order model. The results show that the intrinsic multi-objective approach can find efficient policies of order size and safety factor simultaneously without estimating shortage cost or service level. Moreover, a fitted exchange curve of cost and service is useful in determining the best customer service possible for the given investment in inventory management. The cost-service trade-off can be observed in a single run of an iterative computation, so that it is more appropriate for the practice of inventory management.
Gestural mind markers in ECAs

We aim at creating expressive Embodied Conversational Agents (ECAs) able to communicate multimodally with a user or with other ECAs. In this paper we focus on the Gestural Mind Markers, that is, those gestures that convey information on the Speaker's Mind; we present the ANVIL-SCORE, a tool to analyze and classify multimodal data that is a semantically augmented version of Kipp's ANVIL [2].
Towards the identification of Idiopathic Parkinson’s Disease from the speech. New articulatory kinetic biomarkers

Although a large amount of acoustic indicators have already been proposed in the literature to evaluate the hypokinetic dysarthria of people with Parkinson’s Disease, the goal of this work is to identify and interpret new reliable and complementary articulatory biomarkers that could be applied to predict/evaluate Parkinson’s Disease from a diadochokinetic test, contributing to the possibility of a further multidimensional analysis of the speech of parkinsonian patients. The new biomarkers proposed are based on the kinetic behaviour of the envelope trace, which is directly linked with the articulatory dysfunctions introduced by the disease since the early stages. The interest of these new articulatory indicators stands on their easiness of identification and interpretation, and their potential to be translated into computer based automatic methods to screen the disease from the speech. Throughout this paper, the accuracy provided by these acoustic kinetic biomarkers is compared with the one obtained with a baseline system based on speaker identification techniques. Results show accuracies around 85% that are in line with those obtained with the complex state of the art speaker recognition techniques, but with an easier physical interpretation, which open the possibility to be transferred to a clinical setting.
Area and length minimizing flows for shape segmentation

Several active contour models have been proposed to unify the curve evolution framework with classical energy minimization techniques for segmentation, such as snakes. The essential idea is to evolve a curve (in 2D) or a surface (in 3D) under constraints from image forces so that it clings to features of interest in an intensity image. Recently the evolution equation has been derived from first principles as the gradient flow that minimizes a modified length functional, tailored to features such as edges. However, because the flow may be slow to converge in practice, a constant (hyperbolic) term is added to keep the curve/surface moving in the desired direction. The authors provide a justification for this term based on the gradient flow derived from a weighted area functional, with image dependent weighting factor. When combined with the earlier modified length gradient flow they obtain a PDE which offers a number of advantages, as illustrated by several examples of shape segmentation on medical images. In many cases the weighted area flow may be used on its own, with significant computational savings.
Yandex School of Data Analysis approach to English-Turkish translation at WMT16 News Translation Task

We describe the English-Turkish and Turkish-English translation systems submitted by Yandex School of Data Analysis team to WMT16 news translation task. We successfully applied hand-crafted morphological (de-)segmentation of Turkish, syntax-based pre-ordering of English in English-Turkish and post-ordering of English in Turkish-English. We perform desegmentation using SMT and propose a simple yet efficient modification of postordering. We also show that Turkish morphology and word order can be handled in a fully-automatic manner with only a small loss of BLEU.
An internal model control-cascade Proportion-Integration-Differentiation method for manipulation of nano-quad-rotors

Nowadays, manipulation of quad-rotors faces complexity in controller parameter tuning process and system instability under uncertainties. Internal model control is featured with less controller parameters, simpler tuning process than conventional methods, good robustness and perfect capability in rejection of uncertainties. All its merits can be applied in the field of nano-quad-rotor control since its internal model is easy to be obtained and the suffered uncertainties, especially persistent ones such as model uncertainties and winds, can be rejected by the algorithm effectively. In this paper, an internal model control cascade Proportion-Integration-Differentiation (PID) method is developed to enhance the robustness and improve the capability of uncertainty rejection of nano-quad-rotors flying under persistent uncertainties. The system can be stabilized in a very easy way with all controller parameters tuned within 0 to 1. Comparison with internal model control method was carried out numerically; the results show that, in dealing with persistent uncertainties, the internal model control cascade PID-based method presents significant superiority in the maintenance of both the accuracy of trajectory tracking and the stability of attitude.
Regulation of Extracellular Chromatin Release from Neutrophils

Neutrophils use intricate mechanisms for capturing and killing invading microorganisms. One mechanism entails the release of relaxed chromatin from the cell. Microbes are trapped by the extracellular chromatin and exposed to high local concentrations of bactericidal compounds. We examine the regulation of chromatin release by testing the contribution of microtubules and the actin cytoskeleton to the deployment of neutrophil extracellular traps (NETs). Incubation of human neutrophils with nocodazole, a tubulin polymerization inhibitor, or cytochalasin D, an inhibitor of actin filamentation, severely diminished the ability of neutrophils to respond to LPS by releasing chromatin from the cells. In addition, pretreatment of neutrophils with M1/70, a monoclonal antibody to the Mac-1 integrin adhesion receptor, drastically reduced the deployment of chromatin into NETs. Analysis of histone deimination, the conversion of arginine to citrulline in 3 of the 4 core histones by peptidylarginine deiminase 4, revealed that the treatments inhibiting NET formation also reduced histone deimination. Our data indicate that NET formation requires functional tubulin and actin filaments and responds to engagement of Mac-1 integrins. Because histone deimination coincides with the release of NETs, we propose that these events represent overlapping mechanisms of neutrophil responses to infections.
Learning Semantic Patterns with Discriminant Localized Binary Projections

In this paper, we present a novel approach to learning semantic localized patterns with binary projections in a supervised manner. The pursuit of these binary projections is reformulated into a problem of feature clustering, which optimizes the separability of different classes by taking the members within each cluster as the nonzero entries of a projection vector. An efficient greedy procedure is proposed to incrementally combine the sub-clusters by ensuring the cardinality constraints of the projections and the increase of the objective function. Compared with other algorithms for sparse representations, our proposed algorithm, referred to as Discriminant Localized Binary Projections (dlb), has the following characteristics: 1) dlb is supervised, hence is much more effective than other unsupervised sparse algorithms like Non-negative Matrix Factorization (NMF) in terms of classification power; 2) similar to NMF, dlb can derive spatially localized sparse bases; furthermore, the sparsity of dlb is controllable, and an interesting result is that the bases have explicit semantics in human perception, like eyes and mouth; and 3) classification with dlb is extremely efficient, and only addition operations are required for dimensionality reduction. Extensive experimental results show significant improvements of dlb in sparsity and face recognition accuracy in comparison to the state-of-the-art algorithms for dimensionality reduction and sparse representations.
Hedgehog Signaling Regulation of Insulin Production By Pancreatic-Cells

Hedgehogs (Hhs) are intercellular signaling molecules that regulate tissue patterning in mammalian development. Mammalian Hhs include Sonic hedgehog (Shh), Indian hedgehog (Ihh), and Desert hedgehog (Dhh). The absence of Shh expression is required for the early development of the endocrine and exocrine pancreas, but whether Hh signaling functions in the fully developed adult endocrine pancreas is unknown. Here we report that Hhs Ihh and Dhh and their receptors patched (Ptc) and smoothened are expressed in the endocrine islets of Langerhans of the fully developed rat pancreas and in the clonal -cell line INS-1. We demonstrate the coexpression of Ptc with insulin in -cells of mouse pancreatic islets, indicating that -cells are targets of active Hh signaling. The administration of cyclopamine, a Hh signaling inhibitor, decreases both insulin secretion from and insulin content of INS-1 cells. The effects of Hh signaling on insulin production occur at the transcriptional level because activation of Hh signal transduction by ectopic expression of Shh increases rat insulin I promoter activation in a dosedependent manner in transient transfections of INS-1 and MIN6 -cell lines. In contrast, inhibition of Hh signaling with increasing concentrations of cyclopamine progressively reduces insulin promoter activity. Furthermore, the treatment of INS-1 cells with cyclopamine diminishes endogenous insulin mRNA expression. We propose that Hh signaling is not restricted to patterning in early pancreas development but also continues to signal in differentiated -cells of the endocrine pancreas in regulating insulin production. Thus, defective Hh signaling in the pancreas should be considered as a potential factor in the pathogenesis of type 2 diabetes. Diabetes 49:2039–2047, 2000
Personalized recommendation of linear content on interactive TV platforms: beating the cold start and noisy implicit user feedback

Recommender systems in TV applications mostly focus on the recommendation of video-on-demand (VOD) content, although the major part of users’ content consumption is realized on linear channel programs (live or recorded), termed EPG programs. The accurate collaborative filtering algorithms suitable for VOD recommendation cannot be directly carried over for EPG program recommendation. First, EPG program recommendation features the cold start problem; a significant part of EPG programs are new in the system. Second, and more importantly, without explicit user feedbacks (ratings) the algorithms have to model user preference based on the noisy and less directly interpretable implicit user feedbacks. In this paper, we present several approaches that overcome these difficulties, by applying pre-filtering on noisy low-level data and taking into account channel preferences of users and program metadata if available to cope with the cold start. Using time-dependent tensor factorization approaches, the temporal preferences of users are also reflected in recommendation, that also hints on the person watching the TV. Experiments were performed on a dataset of SaskTel, a Canadian IPTV service provider using Microsoft Mediaroom middleware.
Mercury transfer in a subtropical coastal lagoon food web (SE Gulf of California) under two contrasting climatic conditions

Mercury (Hg) transference through an established and defined food web from an urbanized subtropical coastal lagoon (SE Gulf of California) was examined by using carbon and nitrogen stable isotope and Hg analyses. Concentrations of Hg in seawater (0.045–0.078 μg L−1), predominantly incorporated to the particulate fraction (60% of total), were lower than those found in highly contaminated coastal areas around the world (0.18–16 μg L−1). Although levels of Hg available for the biota (e.g., associated to the reactive and pyrite fractions; 0.11–0.15 μg g−1) were within of effects range‐low (ER‐L, 0.15–0.71 μg g−1) these concentrations represented from 46.6 to 67.0% of the total Hg pool that may be transferred through food web. The sequence of bio‐accumulation of Hg in studied species was according with their functional guild: tertiary consumer (0.85–1.15 μg g−1) > secondary consumers (0.084–0.168 μg g−1) > primary consumers (0.014–0.160 μg g−1) > primary producers (0.016–0.056 μg g−1). Hg concentrations increased for each successive trophic position estimate through δ15N isotopic values, although these relationships showed differences between dry and rainy seasons (R2 = 0.37 and R2 = 0.39 between δ15N vs. Hg in organisms, respectively). We concluded that Hg is being positively transferred (biomagnification factor >1) through the studied food web probably enhanced by the favorable environmental conditions for Hg‐methylation (e.g., fine sediments rich in organic matter, and environmental conditions changes of the redox, pH, and temperature) found in this urbanized coastal water, however, the study of processes methlylation and biomagnifcation of Hg need further investigations. © 2011Wiley Periodicals, Inc. Environ Toxicol, 2012.
Walnut Shell for Partial Replacement of Fine Aggregate in Concrete: Modeling and Optimization

The huge need of natural resources and the raising pollution problems from agro wastes disposal have become the top most important factors behind using agro waste in construction industry. Many agro waste materials have been recycled and reused successfully in concrete as replacement alternatives for cement, aggregate, and reinforcing materials. Kurdistan region-Iraq is the country leading producer of walnut, simultaneously; large quantities of walnut shell is disposed in landfill from agricultural, household and small scale food industries. Hence, the present study deals with using walnut shell the agro waste as partial replacement of fine aggregate in concrete for the purpose of reduction the natural resource exploitation and associated costs, minimization waste landfill, and modifying the concrete properties. A two factorial central composite design was adopted to study the effect of water/cement ratio (0.38-0.52) and walnut shell content (1.72-58.28) weight % for concrete mixes on water absorption, density and compressive strength. Control concrete samples were also investigated for comparison purpose. The experimental results were modeled and optimized using Response Surface Methodology. The response surface analysis results showed that walnut shell content has significant effect on compressive strength and density, while the quadratic effect of water/cement ratio was significant for total surface water absorption. The walnut-concrete samples seemed to have lower density, and lower initial and total surface water absorption compared to control samples. Similar findings were obtained for compressive strength. However, it was confirmed that walnut shell can be used as light replacement material instead of fine aggregate up to 30% at 0.38 water/cement ratio without adversely affecting the acceptable compressive strength for structural Portland cement concrete. The promising results indicated the potential of using walnut shell for producing structurally applicable and environmental friendly concrete.
Suppression of the LMP2A target gene, EGR‐1, protects Hodgkin's lymphoma cells from entry to the EBV lytic cycle

Hodgkin's lymphoma is unusual among B cell lymphomas, in so far as the malignant Hodgkin/Reed–Sternberg (HRS) cells lack a functional B cell receptor (BCR), as well as many of the required downstream signalling components. In Epstein–Barr virus (EBV)‐positive cases of Hodgkin's lymphoma, HRS cells express the viral latent membrane proteins (LMP)‐1 and ‐2A. LMP2A is thought to contribute to the pathogenesis of Hodgkin's lymphoma by providing a surrogate BCR‐like survival signal. However, LMP2A has also been shown to induce the virus‐replicative cycle in B cells, an event presumably incompatible with lymphomagenesis. In an attempt to resolve this apparent paradox, we compared the transcriptional changes observed in primary HRS cells with those induced by LMP2A and by BCR activation in primary human germinal centre (GC) B cells, the presumed progenitors of HRS cells. We found a subset of genes that were up‐regulated by both LMP2A expression and BCR activation but which were down‐regulated in primary HRS cells. These genes included EGR1, an immediate‐early gene that is required for BCR‐induced entry to the virus‐replicative cycle. We present data supporting a model for the pathogenesis of EBV‐positive Hodgkin's lymphoma in which LMP2A‐expressing HRS cells lacking BCR signalling functions cannot induce EGR1 and are consequently protected from entry to the virus lytic cycle. The primary microarray data are available from GEO (http://www.ncbi.nlm.nih.gov/geo/) under series Accession No 46143. Copyright © 2013 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Linux malware detection using non-parametric statistical methods

Linux is the most renowned open source operating system. In recent years, the number of malware targeting Linux OS has been increased and the traditional defence mechanisms seems to be futile. We propose a novel non-parametric statistical approach using machine learning techniques for identifying previously unknown malicious Executable Linkable Files (ELF). The system calls employed as features extracted dynamically within a controlled environment. The proposed approach ranks and determine the prominent features by using non-parametric statistical methods like Kruskal-Wallis ranking test (KW), Deviation From Poisson (DFP). Three learning algorithms (J48, Adaboost and Random Forest) are applied to generate prediction model, from a minimal set of features extracted from the system call traces. Optimal feature vector resulted in over all classification accuracy of 97.30% to identify unknown malicious specimens.
Preparation of acrylic silicon dioxide nanoparticles as a binder for leather finishing

Polyacrylic resin, methyl methacrylate and 2‐ethyl hexylacrylate, was prepared via microemulsion polymerization with ratio 2:1, and then modified with silicon dioxide nanoparticles (SiO2) prepared by sol–gel process. Different ratios of these nanoparticles combined with acrylic resins were then coated on leather surface. The physical, chemical, and mechanical properties of coated leather were evaluated through various instrumental analysis as nuclear magnetic resonance, Fourier transmission infrared, dynamic light scattering, thermal gravimetric analysis, energy‐dispersive X‐ray spectroscopy, and transmission electron microscope. Water vapor permeability was improved with increase in the percentage of the nanoparticles. Tensile, tear strength, and elongation percentage were increased up to 3% of SiO2 nanoparticles followed by decreasing behavior. The acrylate water‐based SiO2 nanoparticles exhibited good eco‐friendly leather finishing system.
Temperature dependency of mechanical properties for crystalline cellulose added to silicone elastomer

A chemical cross-linked transparent film was got by a silicon compound to crystalline cellulose. Temperature dependency for the elasticity modulus of a provided film was measured. The shear elastic modulus was obtained the value of 2 x 106 [Pa] at room temperature. The sample decreases in 190 [deg. C] for the elasticity modulus at the room temperature as 60%, but approximately 10% recover when temperature rises up to 200 [deg. C] or more.
Pulmonary exacerbations are associated with subsequent FEV1 decline in both adults and children with cystic fibrosis

Patients with cystic fibrosis (CF) frequently experience pulmonary exacerbations that may lead to a faster subsequent decline in pulmonary function; however, this relationship has not been clearly established. The purpose of this study was to determine the association between the frequency of pulmonary exacerbations and subsequent forced expiratory volume in 1 sec (FEV1) decline in adults and children with CF.
Ontology Building using Parallel Enumerative Structures

The semantics of a text is carried by both the natural language it contains and its layout. As ontology building processes have so far taken only plain text into consideration, our aim is to elicit its textual structure. We focus here on parallel enumerative structures because they bear implicit or explicit hierarchical relations, they have salient visual properties, and they are frequently found in corpora. We have defined a process which identifies them in a text, translates them into ontology structures and finally links such structures to the concepts of an existing ontology. We have assessed this process on Wikipedia encyclopaedic articles as they are rich in definitions and statements, and contain many enumerations. The many ontology structures we have obtained are thus used to enrich an ontology which we had automatically built from database specification documents.