Miracle-dz/UniFAR-FTUs huggingface dataset:
Drop-out Conditional Random Fields for Twitter with Huge Mined Gazetteer

In named entity recognition task especially for massive data like Twitter, having a large amount of high quality gazetteers can alleviate the problem of training data scarcity. One could collect large gazetteers from knowledge graph and phrase embeddings to obtain high coverage of gazetteers. However, large gazetteers cause a side-effect called “feature under-training”, where the gazetteer features overwhelm the context features. To resolve this problem, we propose the dropout conditional random ﬁelds, which decrease the inﬂuence of gazetteer features with a high weight. Our experiments on named entity recognition with Twitter data lead to higher F1 score of 69.38%, about 4% better than the strong baseline presented in Smith and Osborne (2006).
INTERACTIONS ENTRE PROCESSUS COGNITIFS ET PHYSIOLOGIQUES: EFFET DU NIVEAU D'EFFORT ET DU NIVEAU DE CONDITION PHYSIQUE DES SUJETS.

There has been little research on the relationship between physical exercise and cognitive performance. These studies can be classified in four categories: those finding a beneficial relationship, those finding a detrimental relationship, those finding both a beneficial and a detrimental relationship and those finding no relationship. Tomporowski and Ellis (1986) reported that these inconsistent findings were due to the failure of researchers to use a coherent methodology and, that future research should consider several points. First, exercise produced arousal and fatigue, and any at temps to analyse exercise effect has to measure exactly the physical changes brought by exercise. Second, the effect of exercise will depend on the physical fitness of the subject tested. The purpose of this present research was to examine the effect of two levels of physical fitness on the performance of a multiple choice reaction time during four aerobic workloads (20, 40, 60, 80 % Maximal Aerobic Power). Results indicated, in the two groups, that the increments in relative physical workload improved performance in the RT task. We discussed, first the difficulty to show relationship between arousal, physiologic measures and cognitive performance, second the fact that the performance was diffe- rent between the two groups when intensity was expressed as absolute workloads.
Hematopoietically-Expressed Homeobox Gene Three Widely-Evaluated Polymorphisms and Risk for Diabetes: A Meta-Analysis

Background The hematopoietically-expressed homeobox (HHEX) gene is identified as a promising candidate for type 2 diabetes by genome-wide association studies, triggering plenty of subsequent replications; however, the results are conflicting. We therefore conducted a meta-analysis of three widely-evaluated polymorphisms in HHEX gene and diabetes risk. Methodology/Principal Findings A random-effects model was adopted irrespective of heterogeneity. Data and study quality were assessed in duplicate. There were 49 studies (cases/controls: 57931/74658) for rs1111875, 18 studies (18227/30366) for rs5015480 and 26 studies (25725/30579) for rs7923837, respectively. Overall analyses indicated that rs1111875-C allele (odds ratio [OR] = 1.16; 95% confidence interval [CI]: 1.13–1.2; P<0.0005), rs5015480-C allele (OR = 1.16; 95% CI: 1.06–1.26; P = 0.001) and rs7923837-G allele (OR = 1.18; 95% CI: 1.12–1.24; P<0.0005) conferred significantly increased risk for type 2 diabetes, yet accompanying moderate to strong evidence of heterogeneity. Despite vast divergence in allele distributions, subgroup analyses by ethnicity showed comparable risk estimates between Asians and Caucasians for three examined polymorphisms. Moreover, results of studies with hospital-based controls deviated greatly from that of all qualified studies, especially for rs7923837-G allele carrying a doubled risk (OR = 1.37 versus 1.18). Furthermore, when only large studies (≥500 case-patients) were considered, risk effects were identical to the overall estimates for three examined polymorphisms. The Begg's funnel plot and Egger's test indicated low probability of publication bias. Conclusions Our results provide clarification to the significant association of rs1111875, rs5015480 and rs7923837 in HHEX gene with type 2 diabetes.
Estradiol Enhances Prostaglandin E2 Receptor Gene Expression in Luteinizing Hormone-Releasing Hormone (LHRH) Neurons and Facilitates the LHRH Response to PGE2 by Activating a Glia-to-Neuron Signaling Pathway

Prostaglandin E2 (PGE2) mediates the stimulatory effect of norepinephrine (NE) on the secretion of luteinizing hormone-releasing hormone (LHRH), the neuropeptide controlling reproductive function. In rodents, this facilitatory effect requires previous exposure to estradiol, suggesting that the steroid affects downstream components in the cascade that leads to PGE2-induced LHRH release. Because astroglia are the predominant cell type contacting LHRH-secreting nerve terminals, we investigated the involvement of hypothalamic astrocytes in the estradiol facilitation of PGE2-induced LHRH release. A subpopulation of LHRH neurons was found to express the mRNA encoding the PGE2 receptor subtype EP1-R, which is coupled to calcium mobilization. The LHRH-producing cell line GT1–1 also contains EP1-R mRNA and, to a lesser extent, the three alternatively spliced forms of EP3-R mRNA (α, β, and γ) that encode receptors linked to inhibition and stimulation of cAMP formation. Hypothalamic astrocytes treated with estradiol produced a conditioned medium that when applied to GT1–1 cells resulted in a selective upregulation of EP1-R and EP3γ-R mRNAs. The conditioned medium also enhanced the LHRH response to EP1-R and EP3-R agonists and the cAMP response to EP3-R activation. Thus, one mechanism by which estradiol facilitates the effect of neurotransmitters acting via PGE2 to stimulate LHRH release is by enhancing the glial production of substances that upregulate PGE2 receptors on LHRH neurons. The existence of such a mechanism underscores the emerging importance of glial–neuronal communication in the control of brain neurosecretory activity.
Investigating the cost/schedule trade-off in software development

The author has studied the effects of schedule compression or stretch-out on total project cost within a much broader effort to study and predict the dynamics of the entire development process. The resulting cost/schedule tradeoffs were examined. Much of this project involved developing a comprehensive system-dynamics model. He used the model to conduct three simulation experiments. (1) He investigated the effects of different levels of schedule compression and stretch-out on total project cost in man-days and compared the results to those reported in the literature. (2) He addressed the stealthy role undersizing plays in schedule compression. (3) He investigated how different levels of managerial commitment affect the project's final cost and completion time. The results of all three experiments are presented and discussed. <<ETX>>
The archaeology of Ingaanjalwurr rockshelter in Manilikarr Country, western Arnhem Land

Abstract Archaeological excavations at Ingaanjalwurr rockshelter in western Arnhem Land, Northern Territory, have revealed evidence of human settlement on the East Alligator River floodplain from approximately 1900 years ago through to the twentieth-century. This short report summarises the results of archaeological excavations at the site, focusing on dated distributions of stone artefacts as the primary retrieved cultural material. The excavations revealed two main periods of occupation: the earlier from c. 1900 to 1300 cal. BP and the latter from c. 460-300 cal. BP to the proto-historic period. The findings from Ingaanjalwurr broadly correspond to previously proposed regional settlement trends, whereby Aboriginal settlement shifted to newly stabilised freshwater environments during the later Holocene period.
Automatic semantic annotation of images based on Web data

Image annotation is a promising approach to bridging the semantic gap between low-level features and high-level concepts, and it can avoid the heavy manual labor. Most existing automatic image annotation approaches are based on supervised learning. They often encounter several problems, such as insufficiency of training data, lack of ability in dealing with new concept, and a limited number of semantic concepts. Web images are massive, rich information, customized etc. Therefore, Web data is a potential repository to provide a sufficient source for semantic annotation. In this paper, we proposed a novel image annotation method based on Web data, which aims to utilize Web data to perform automatic image annotation. Web data, collected from several image search engine, are first preprocessed, clustered and mined to construct a concept clustering model. And then candidate annotation terms are extracted through the model for query image. Afterwards, a rank algorithm is designed to filter out noise terms. Finally, an update phase is implemented to improve the whole method. Evaluations on benchmark image datasets have indicated the effectiveness of our proposal.
Testing and Evaluating the Single Objective Intelligent Evolutionary Algorithm through a Graphic Interface

The human evolutionary model is an intelligent global optimization method conceived to perform single and multiple objective optimization, this general method is still in development, especially the multi objective (MO) part is being improved. The single objective (SO) part has demonstrated that outperforms several algorithms that are in the state of the art, for example differential evolution (DE), particle swarm optimizer, and others, we called this part single objective intelligent evolutionary algorithm (SO-IEA). The SO-IEA uses mediative fuzzy logic (MFL) for handling doubtful and contradictory information from experts to calculate the appropriated amount of individuals to create and/or to eliminate. MFL is an extension of traditional fuzzy logic and includes intuitionistic fuzzy logic (IFL) in the Atanassov sense. In this work, we are presenting the algorithm's architecture, experimental results, and a graphical interface that will help to handle the required parameters to use the SO-IEA.
Self-Management Strategies to Support Students With ASD

T EA C H IN G E xc ep ti on al C hi ld re n , V ol . 48 , N o. 5 , pp . 22 5 – 23 1. C op yr ig ht 2 01 6 T he A ut ho r( s) . D O I: 1 0. 11 77 /0 04 00 59 91 66 40 75 9 Ms. Madden, a fourth-grade teacher at Sunset Elementary, has some concerns about one of her students. Olivia is a student with autism spectrum disorder (ASD), and she is part of a population of students that is increasingly being served primarily in general education classrooms (de Bruin, Deppeler, Moore, & Diamond, 2013; Dorminy, Luscre, & Gast, 2009). Students with ASD often struggle with deficits in executive functioning skills, leading to problems with sustaining attention, inhibiting responses, setting and pursuing goals, and planning (Dorminy et al., 2009; Zingerevich & LaVesser, 2009). Consequently, teachers and other classroom staff often are responsible for taking the time to ensure students with ASD engage in appropriate classroom behaviors, such as completing and turning in work and staying on task (Dorminy et al., 2009). Olivia is very intelligent but struggles with staying on task during math, which she has reported is her least favorite subject. This is particularly true during the independent work period, when students are expected to complete a certain number of problems from their textbooks following the whole-group lesson. Ms. Madden has found that she is constantly redirecting Olivia—who will talk to other peers, doodle on her paper, or stare off into space—to focus back on her work. Ms. Madden is frustrated with the amount of time and effort it is taking to prompt Olivia to finish her assignment each day, especially given that there are 30 other students in the class who also need attention. Mr. Rodriguez, a special education teacher, spends 2 hours per week in Ms. Madden’s classroom to provide organizational assistance and behavior support to Olivia, but Olivia requires consistent help to stay on task when he is not there. Ms. Madden and Mr. Rodriguez are looking for a solution to help Olivia stay on task independently. Given her difficulty with sustaining attention during this period of the day, Olivia may be a good candidate for a self-management procedure to help her stay focused and complete her independent math work. Mr. Rodriguez wants to support Ms. Madden in developing a selfmanagement system that will help keep Olivia on task during her math block.
Improved Mechanical and Tribological Properties of Metal-Matrix Composites Dispersion-Strengthened by Nanoparticles

Co- and Fe-based alloys produced by powder technology are being widely used as a matrix for diamond-containing composites in cutting, drilling, grinding pplications, etc. The severe service conditions demand that the mechanical and tribological properties of these alloys be improved. Development of metal-matrix composites (MMCs) and alloys reinforced with nanoparticles is a promising way to resolve this problem. In this work, we have investigated the effect of nano-sized WC, ZrO2, Al2O3, and Si3N4 additives on the properties of sintered dispersion-strengthened Co- and Fe-based MMCs. The results show an increase in the hardness (up to 10 HRB), bending strength (up to 50%), wear resistance (by a factor of 2–10) and a decrease in the friction coefficient (up to 4-fold) of the dispersion-strengthened materials. The use of designed alloys as a binder of cutting diamond tools gave a 4-fold increment in the service life, without reduction in their cutting speed.
Emotional Intelligence and Agents: Survey and Possible Applications

Recently, research on emotional intelligence has advanced significantly from its theoretical basis, analytical studies and processing technology to exploratory application. The main intention of this paper is twofold. First, it will give an overview of the state-of-the-art in emotional intelligence research. Then, it will suggest a systematic order of research activities and steps with the idea of proposing an adequate framework for real-life applications. We recognize that it is necessary to apply specific methods for dynamic data analysis and pattern mining/recognition in order to identify and discover new knowledge from available emotional information and data sets. Finally, the paper will propose research activities in order to design an agent-based architecture, in which agents are capable of reasoning about and displaying some kind of emotions based on emotions detected in human speech, as well as online documents. This kind of virtual emotional agent could be employed in intelligent human-computer interaction, within areas such as tourism, education, and virtual cultural exhibitions.
An UML-based approach to software development cost estimation

CONTEXT: Resource and time estimation is a critical activity in software projects. In literature, various techniques have been proposed, but it's often difficult to perform them, because of data scarcity in the early stages of a project. We studied this issue in the context of a business unit that develops automotive infotainment systems. GOAL: The purpose of this paper is finding a system to estimate effort and duration for complex embedded software projects, using UML design and a hierarchical "divide and conquer" paradigm. METHOD: At first, we analyzed and compared estimation methodologies that are available in literature. We found in COCOMO II the model which fitted more our circumstances. By comparing the theoretical estimate model with the actual production process, we produced an UML profile, still based on COCOMO II rationale, but extended and modified, in order to adhere better to our case. The resulting model comes out from a flexible approach, which allows to evaluate effort more thoroughly as we have more detailed information on the estimated project. After model design, we implemented a tool to extract data from the selected UML designer software, and transfer them to a precompiled Excel workbook, conceived specifically for the calculation of project costs using COCOMO II formulae. RESULTS: The solution has been validated against a completed project. The results are fair in terms of total effort estimate, whereas duration estimate diverges significantly from the actual value. This suggests that the model of effort distribution over time needs to be improved. CONCLUSIONS: The results suggest that the proposed approach could be a valid option for algorithmic estimation in contexts like the one indicated, at least for total effort assessment. However, the presented solution is far from mature. In the future works, several enhancements could be added to both the model and the tool.
The Histone Deacetylase Inhibitor LBH589 (Panobinostat) Modulates the Crosstalk of Lymphocytes with Hodgkin Lymphoma Cell Lines

Epigenetic changes have been implicated in the malignant phenotype of Hodgkin Reed Sternberg (HRS) cells in Hodgkin lymphoma (HL), where HRS survival and proliferation depends on the microenvironment. The histone-deacetylase (HDAC) inhibitor LBH589 (panobinostat) showed clinical efficacy but its impact on the HRS microenvironment is unclear. Hence, we analysed the effects of LBH589 on lymphocytes and also potential combination therapies. In lymphocyte-target cell killing assays, LBH589-treatment triggered an enhanced lymphocyte-dependent lysis of HL cells despite of mild lymphocytopenic effects. In co-culture experiments of lymphocytes with HL cells, LBH589 suppressed the IFNgamma-release but increased the TNFalpha secretion. Recombinant TNFalpha boosted the lymphocyte-dependent lysis of HL target cells. In HL cell lines, LBH589 induced cell death, autophagy, and an increase of MICA/B that are ligands to natural killer cell receptors. The combination of LBH589 with Brentuximab Vedotin was inefficient due to down-regulation of CD30 as a target. Combination with gemcitabine revealed highly significant effects, suggesting a potential combination for future therapy. Based on these data we suggest that LBH589 favourably modulates the cytokine network and lymphocyte activity in the HL microenvironment.
Pseudo-boolean Optimization Pseudo-boolean Optimization

This survey examines the state of the art of a variety of problems related to pseudo-Boolean optimization, i.e. to the optimization of set functions represented by closed algebraic expressions. The main parts of the survey examine general pseudo-Boolean optimization, the specially important case of quadratic pseudo-Boolean optimization (to which every pseudo-Boolean optimization can be reduced), several other important special classes, and approximation algorithms.
An efficient QRS detection method for ECG signal captured from fingers

We propose a novel QRS detection method for ECG signal captured from fingers (briefly finger-ECG). In this work, we use curvature as an estimation of energy of ECG signal. We need only three computationally simple steps for the detection of QRSs. A single threshold is used to determine QRSs from local minima of energy making the method linear i.e. O(n) in computational time which is O(n2) for slope based methods for a signal of n samples. The method is tested on 224 records of finger-ECG signal, and we have obtained superior performance than the state-of-the-arts slope-based method. Average time error of detection is also significantly lower by this method. This method has a single parameter of adaptive threshold, which required no tuning for our database whereas the slope based method required tuning of parameters. This method is potentially suitable for real time applications of finger-ECG in e-health and biometrics.
A data mining based system supporting tactical decisions

We present a decision support system based on data mining algorithms to be used for tactical decisions. The system has been developed and engineered to solve a typical problem involving strategic decisions: supporting a trainer of a basketball team in making technical/tactical decisions. The experiments conducted on this application domain proved the effectiveness of the system and its underlying algorithms. The basketball domain stressed several aspects of decision making, proving that the used approach is suitable for other domains involving tactical decisions.
Stability of Retrieved Memory: Inverse Correlation with Trace Dominance

In memory consolidation, the memory trace stabilizes and becomes resistant to certain amnesic agents. The textbook account is that for any memorized item, consolidation starts and ends just once. However, evidence has accumulated that upon activation in retrieval, the trace may reconsolidate. Whereas some authors reported transient renewed susceptibility of retrieved memories to consolidation blockers, others could not detect it. Here, we report that in both conditioned taste aversion in the rat and fear conditioning in the medaka fish, the stability of retrieved memory is inversely correlated with the control of behavior by that memory. This result may explain some conflicting findings on reconsolidation of activated memories.
Issues in Multimedia Task Scheduling I Introduction

Computational support for multimedia applications has been subject of considerable research. Much attention has been paid to communication media protocols in distributed multimedia systems. However, properly de ning a share of CPU time for the tasks that will manipulate continuous stream data is fundamental to multimedia applications. This paper focuses in basic concepts of multimedia task scheduling and surveys some approaches to solve this prob-
Knowledge Curation and Knowledge Fusion: Challenges, Models and Applications

Large-scale knowledge repositories are becoming increasingly important as a foundation for enabling a wide variety of complex applications. In turn, building high-quality knowledge repositories critically depends on the technologies of knowledge curation and knowledge fusion, which share many similar goals with data integration, while facing even more challenges in extracting knowledge from both structured and unstructured data, across a large variety of domains, and in multiple languages. Our tutorial highlights the similarities and differences between knowledge management and data integration, and has two goals. First, we introduce the Database community to the techniques proposed for the problems of entity linkage and relation extraction by the Knowledge Management, Natural Language Processing, and Machine Learning communities. Second, we give a detailed survey of the work done by these communities in knowledge fusion, which is critical to discover and clean errors present in sources and the many mistakes made in the process of knowledge extraction from sources. Our tutorial is example driven and hopes to build bridges between the Database community and other disciplines to advance research in this important area.
Phonon-induced artificial magnetic fields in optical lattices

We investigate the effect of a rotating Bose-Einstein condensate on a system of immersed impurity atoms trapped by an optical lattice. We analytically show that for a one-dimensional, ring-shaped setup the coupling of the impurities to the Bogoliubov phonons of the condensate leads to a non-trivial phase in the impurity hopping. The presence of this phase can be tested by observing a drift in the transport properties of the impurities. These results are quantitatively confirmed by a numerically exact simulation of a two-mode Bose-Hubbard model. We also give analytical expressions for the occurring phase terms for a two-dimensional setup. The phase realises an artificial magnetic field and can, for instance, be used for the simulation of the quantum Hall effect using atoms in an optical lattice.