Miracle-dz/UniFAR-FTUs huggingface dataset:
UMCC_DLSI: A Probabilistic Automata for Aspect Based Sentiment Analysis

This work introduces a new approach for aspect based sentiment analysis task. Its main purpose is to automatically assign the correct polarity for the aspect term in a phrase. It is a probabilistic automata where each state consists of all the nouns, adjectives, verbs and adverbs found in an annotated corpora. Each one of them contains the number of occurrences in the annotated corpora for the four required polarities (i.e. positive, negative, neutral and conflict). Also, the transitions between states have been taken into account. These values were used to assign the predicted polarity when a pattern was found in a sentence; if a pattern cannot be applied, the probabilities of the polarities between states were computed in order to predict the right polarity. The system achieved results around 66% and 57% of recall for the restaurant and laptop domain respectively.
Skeletal Muscle Phenotypically Converts and Selectively Inhibits Metastatic Cells in Mice

Skeletal muscle is rarely a site of malignant metastasis; the molecular and cellular basis for this rarity is not understood. We report that myogenic cells exert pronounced effects upon co-culture with metastatic melanoma (B16-F10) or carcinoma (LLC1) cells including conversion to the myogenic lineage in vitro and in vivo, as well as inhibition of melanin production in melanoma cells coupled with cytotoxic and cytostatic effects. No effect is seen with non-tumorigenic cells. Tumor suppression assays reveal that the muscle-mediated tumor suppressor effects do not generate resistant clones but function through the down-regulation of the transcription factor MiTF, a master regulator of melanocyte development and a melanoma oncogene. Our findings point to skeletal muscle as a source of therapeutic agents in the treatment of metastatic cancers.
Grafting a lubricious coating onto photo-crosslinked poly(trimethylene carbonate.

For biomaterial applications that involve moving parts such as artificial joints, lubricity is an essential property. Poly (trimethylene carbonate) networks are relatively hydrophobic. To create a lubricious layer, methacrylated poly(ethylene glycol) and methoxy-poly(ethylene glycol) were grafted onto poly(trimethylene carbonate) networks by photo-crosslinking. After conditioning for 24h in water, no delamination was observed, showing that the grafted hydrophilic layers were covalently attached to the poly(trimethylene carbonate) network. The lubricating properties were assessed by means of friction experiments, and the friction coefficients with relevant biomaterials were determined. It was shown that the grafting results in a significant decrease of the friction coefficients. These results show the potential of this approach to obtain lubricious materials for application in biomedical engineering. Copyright (C) 2015 John Wiley & Sons, Ltd.
Effects of Compounding Addition of Sintering Aids on DC Bias Superposition Characteristic of NiCuZn Ferrites

NiCuZn ferrites were prepared through conventional solid-state method. The effects of the sintering aids such as Bi2O3 and glass on the DC bias superposition characteristic of NiCuZn Ferrites were investigated. It was apparently discovered that when the glass and the Bi2O3 were doped together, the grain size was distributed consistently and the DC bias superposition characteristic reached an achievement comparing to the situation when the Bi2O3 and glass were doped alone. Additionally, it was also observed that the DC bias superposition characteristic had a significant relationship with Hc and △B.
Associations of MC3R polymorphisms with physical activity in South African adolescents.

BACKGROUND There is evidence demonstrating that the contribution of sedentary behavior and effect of physical activity on metabolic phenotypes is mediated by polymorphisms in genes. METHODS The type and frequency of physical activity was assessed by means of structured questionnaires in 1555 South African school learners. Anthropometric measurements, blood pressure, fasting blood glucose and lipids were measured using standard procedures. The effect of different types and frequency of physical activity on obesity-related traits was assessed in relation to MC3R T6K and V81I genotypes in 430 of the learners. RESULTS Levels of total cholesterol were significantly lower in learners carrying the MC3R T6K and V81I minor alleles, after adjusting for age, race, gender, and each specific physical activity category. An activity-by-genotype interaction was also detected: learners heterozygous for the V81I polymorphism and performed house chores often had reduced total cholesterol. Though no association was observed between frequency of physical activity and BMI, television viewing was significantly associated with an increase in height, weight and marginally with waist circumference. CONCLUSION Our findings suggest that physical activity even in the form of house chores has a positive effect on metabolic traits and this effect is further enhanced in the presence of MC3R polymorphisms.
Motherhood and HCI

Motherhood and mothering are fundamental aspects of life, and as a consequence, every culture has knowledge, values, practices and expectations related to the role. Technologies now have an increasing role in motherhood, altering many women's experiences of pregnancy, birth, and mothering. For HCI, such a transition opens a whole host of questions relating to areas of participatory design, social connection, data sharing, identity, memory-making, emotion work, as well as offering a new lens through which to understand notions of care and wellbeing. This workshop will bring together researchers, designers, and practitioners interested in the role of motherhood, the act of mothering, and its relation to HCI and technology. We will identify a collective research agenda related to motherhood and HCI and forge connections amongst a community of researchers to support the sharing of knowledge, resources and design approaches.
Targeted overexpression of a golli–myelin basic protein isoform to oligodendrocytes results in aberrant oligodendrocyte maturation and myelination

Recently, several in vitro studies have shown that the golli–myelin basic proteins regulate Ca2+ homoeostasis in OPCs (oligodendrocyte precursor cells) and immature OLs (oligodendrocytes), and that a number of the functions of these cells are affected by cellular levels of the golli proteins. To determine the influence of golli in vivo on OL development and myelination, a transgenic mouse was generated in which the golli isoform J37 was overexpressed specifically within OLs and OPCs. The mouse, called JOE (J37-overexpressing), is severely hypomyelinated between birth and postnatal day 50. During this time, it exhibits severe intention tremors that gradually abate at later ages. After postnatal day 50, ultrastructural studies and Northern and Western blot analyses indicate that myelin accumulates in the brain, but never reaches normal levels. Several factors appear to underlie the extensive hypomyelination. In vitro and in vivo experiments indicate that golli overexpression causes a significant delay in OL maturation, with accumulation of significantly greater numbers of pre-myelinating OLs that fail to myelinate axons during the normal myelinating period. Immunohistochemical studies with cell death and myelin markers indicate that JOE OLs undergo a heightened and extended period of cell death and are unable to effectively myelinate until 2 months after birth. The results indicate that increased levels of golli in OPC/OLs delays myelination, causing significant cell death of OLs particularly in white matter tracts. The results provide in vivo evidence for a significant role of the golli proteins in the regulation of maturation of OLs and normal myelination.
The role of general and occupational stress in the relationship between workaholism and work-family/family-work conflicts

IntroductionThe purpose of this study was to analyze the role of general and occupational stress in the relationship between workaholism (recognized in two ways: as addiction and as behavioral tendency) and the intensity of work-family and family-work conflict.Materials and MethodsThe study included 178 working people. The survey was conducted at three stages — half a year before a holiday, right after the holiday and half a year after the holiday. The Excessive Work Involvement Scale (SZAP) by Golińska for the measurement of workaholism recognized as addiction; The Scale of Workaholism as Behavioral Tendencies (SWBT) by Mudrack and Naughton as adapted by Dudek et al for the measurement of workaholism as behavioral tendency; the Perceived Stress Scale by Cohen et al., as adapted by Juczyński for the measurement of general stress; the Scale of Occupational Stress by Stanton in the adaptation of Dudek and Hauk for measurement of occupational stress; the Scale of Work-Family Conflict WFC/FWC by Netemeyer et al. with the Polish adaptation of A.M. Zalewska. Workaholism was measured once — before a holiday, the explained and intervening variables (the level of conflicts and stress, respectively) were measured at three stages. To test the mediating role of general and occupational stress, hierarchical regression analysis as well as the method of bootstrapping were applied.Results and ConclusionsOur results indicate that general stress is an important mediator of the relationship between workaholism recognized as an addiction and work-family conflicts. Occupational stress turned out to be the only mediator in the relationship between workaholism (recognized as an addiction) and the work-family conflict, noted exclusively in the first stage of the study. Both general and occupational stress were not significant mediators in the relationship between workaholism recognized as a behavioral tendency and the conflicts described.
A therapeutic nanoparticle vaccine against Trypanosoma cruzi in a BALB/c mouse model of Chagas disease

ABSTRACT Chagas disease, caused by Trypanosoma cruzi, results in an acute febrile illness that progresses to chronic chagasic cardiomyopathy in 30% of patients. Current treatments have significant side effects and poor efficacy during the chronic phase; therefore, there is an urgent need for new treatment modalities. A robust TH1-mediated immune response correlates with favorable clinical outcomes. A therapeutic vaccine administered to infected individuals could bolster the immune response, thereby slowing or stopping the progression of chagasic cardiomyopathy. Prior work in mice has identified an efficacious T. cruzi DNA vaccine encoding Tc24. To elicit a similar protective cell-mediated immune response to a Tc24 recombinant protein, we utilized a poly(lactic-co-glycolic acid) nanoparticle delivery system in conjunction with CpG motif-containing oligodeoxynucleotides as an immunomodulatory adjuvant. In a BALB/c mouse model, the vaccine produced a TH1-biased immune response, as demonstrated by a significant increase in antigen-specific IFNγ-producing splenocytes, IgG2a titers, and proliferative capacity of CD8+ T cells. When tested for therapeutic efficacy, significantly reduced systemic parasitemia was seen during peak parasitemia. Additionally, there was a significant reduction in cardiac parasite burden and inflammatory cell infiltrate. This is the first study demonstrating immunogenicity and efficacy of a therapeutic Chagas vaccine using a nanoparticle delivery system.
Improving expectation maximization algorithm over stellar data

Stellar data, only a few years ago, measured in the . 1M of objects. Now, sets are routinely 1M. With the launch of ESA's Gaia in 2013, we expect 1000M stellar objects measured more precisely and with more measurements. Without question, astronomy is about Big Data and clustering is a very common task over astronomy domain. The expectation-maximization algorithm is among the top 10 data mining algorithms used in scientific and industrial applications, however, we observe that astronomical community does not make use of it as a clustering algorithm. In this work, we cluster ∼ 1M stellar objects (simulated Galactic spectral data) via the traditional expectation-maximization algorithm for clustering (EM-T) and our extended EM-T algorithm that we call EM∗ and present the experimental results.
Maximal Voluntary Force Strengthened by the Enhancement of Motor System State through Barely Visible Priming Words with Reward

The topic of unconscious influences on behaviour has long been explored as a means of understanding human performance and the neurobiological correlates of intention, motivation, and action. However, what is relatively unknown is whether subconsciously delivered priming stimuli, with or without rewards, can affect individuals’ maximum level of force produced with their best effort. We demonstrated using transcranial magnetic stimulation that barely visible priming of an action concept, when combined with a reward in the form of a consciously visible positive stimulus, could alter the state of the motor system. In accordance with this neurophysiological alteration, the prime-plus-reward stimuli significantly increased the hand-grip force level of maximum voluntary contraction with little conscious awareness. This is the first objective evidence that the barely conscious presence of a behavioral goal can influence the state of the motor system and arouse latent ability for human force exertion.
Triangular Similarity Metric Learning: a Siamese Architecture Approach. ( L'apprentissage de similarité triangulaire en utilisant des réseaux siamois)

In many machine learning and pattern recognition tasks, there is always a need for appropriate metric functions to measure pairwise distance or similarity between data, where a metric function is a function that defines a distance or similarity between each pair of elements of a set. In this thesis, we propose Triangular Similarity Metric Learning (TSML) for automatically specifying a metric from data. A TSML system is loaded in a siamese architecture which consists of two identical sub-systems sharing the same set of parameters. Each sub-system processes a single data sample and thus the whole system receives a pair of data as the input. The TSML system includes a cost function parameterizing the pairwise relationship between data and a mapping function allowing the system to learn high-level features from the training data. In terms of the cost function, we first propose the Triangular Similarity, a novel similarity metric which is equivalent to the well-known Cosine Similarity in measuring a data pair. Based on a simplified version of the Triangular Similarity, we further develop the triangular loss function in order to perform metric learning, i.e. to increase the similarity between two vectors in the same class and to decrease the similarity between two vectors of different classes. Compared with other distance or similarity metrics, the triangular loss and its gradient naturally offer us an intuitive and interesting geometrical interpretation of the metric learning objective. In terms of the mapping function, we introduce three different options: a linear mapping realized by a simple transformation matrix, a nonlinear mapping realized by Multi-layer Perceptrons (MLP) and a deep nonlinear mapping realized by Convolutional Neural Networks (CNN). With these mapping functions, we present three different TSML systems for various applications, namely, pairwise verification, object identification, dimensionality reduction and data visualization. For each application, we carry out extensive experiments on popular benchmarks and datasets to demonstrate the effectiveness of the proposed systems.
Text Type Structure and Logical Document Structure

Most research on automated categorization of documents has concentrated on the assignment of one or many categories to a whole text. However, new applications, e.g. in the area of the Semantic Web, require a richer and more fine-grained annotation of documents, such as detailed thematic information about the parts of a document. Hence we investigate the automatic categorization of text segments of scientific articles with XML markup into 16 topic types from a text type structure schema. A corpus of 47 linguistic articles was provided with XML markup on different annotation layers representing text type structure, logical document structure, and grammatical categories. Six different feature extraction strategies were applied to this corpus and combined in various parametrizations in different classifiers. The aim was to explore the contribution of each type of information, in particular the logical structure features, to the classification accuracy. The results suggest that some of the topic types of our hierarchy are successfully learnable, while the features from the logical structure layer had no particular impact on the results.
Loop-Star and Loop-Tree Decompositions: Analysis and Efficient Algorithms

A new analysis of the spectral properties of Loop-Star and Loop-Tree decompositions is presented in this work. The analysis will shed light on the behavior of these decompositions when used with regular operators such as the magnetic field and the Calderón preconditioned electric field integral operators. This work will explain the ill-conditioning problems reported in literature and will provide a family of efficient algorithms to solve the ill-conditioning and regularizing several Loop-Star/Tree decomposed equations of interest for applications. The theory will be corroborated by numerical results that will show the practical impact of the theoretical developments.
Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young At‐Risk Individuals

Recent studies have revealed the polygenic nature of bipolar disorder (BP), and identified common risk variants associated with illness. However, the role of common polygenic risk in multiplex families has not previously been examined. The present study examined 249 European‐ancestry families from the NIMH Genetics Initiative sample, comparing subjects with narrowly defined BP (excluding bipolar II and recurrent unipolar depression; n = 601) and their adult relatives without BP (n = 695). Unrelated adult controls (n = 266) were from the NIMH TGEN control dataset. We also examined a prospective cohort of young (12–30 years) offspring and siblings of individuals with BPI and BPII disorder (at risk; n = 367) and psychiatrically screened controls (n = 229), ascertained from five sites in the US and Australia and assessed with standardized clinical protocols. Thirty‐two disease‐associated SNPs from the PGC‐BP Working Group report (2011) were genotyped and additive polygenic risk scores (PRS) derived. We show increased PRS in adult cases compared to unrelated controls (P = 3.4 × 10−5, AUC = 0.60). In families with a high‐polygenic load (PRS score ≥32 in two or more subjects), PRS distinguished cases with BPI/SAB from other relatives (P = 0.014, RR = 1.32). Secondly, a higher PRS was observed in at‐risk youth, regardless of affected status, compared to unrelated controls (GEE‐χ2 = 5.15, P = 0.012). This report is the first to explore common polygenic risk in multiplex families, albeit using only a small number of robustly associated risk variants. We show that individuals with BP have a higher load of common disease‐associated variants than unrelated controls and first‐degree relatives, and illustrate the potential utility of PRS assessment in a family context. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.
Knowing Together, Learning Apart: A Proposed Framework for Supporting Individual Learning Through Collaborative Knowledge Building Tools

Learning theories and their supporting learning technologies fall into two broad categories: those that support individual learning and those that support communal knowledge building. This research in progress describes a hybrid framework that integrates these two categories and proposes the development of a comprehensive learning technology that encompasses both models. The system would support the cognitive processes necessary for collaborative knowledge building while simultaneously scaffolding the activities of individual exploration, understanding and internalization of knowledge. This paper describes the preliminary foundations for this hybrid framework, providing descriptions of existing learning theories and technologies and describing cognitive processes supported during various tasks in the proposed
Understanding what controls the spatial distribution of fish populations using a multi-model approach

Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology. The spatial distribution of fish populations observed in the wild results from the complex interactions of multiple controls both external or internal to the fish populations. Whilst species distribution models (SDMs) have been mostly concerned with static description of species distribution as a function of environmental constraints, models of animal movements (MAMs) have focussed on the dynamic nature of spatial distribution of groups of individuals under a number of constraints external and internal to the population. Besides SDMs and MAMs, modelling the spatial distribution of fish populations can be achieved by models that are fundamentally static (like SDMs) but can also incorporate many hypotheses on the control of fish spatial distribution (like MAMs). The hypotheses underlying these models need to make sense at the population level - rather than at the individual or species level –we term these ‘population distribution models’ (PDMs). PDMs are statistical models that rely on several hypotheses, which include: (i) control through geographical attachment, (ii) environmental conditions, (iii) density-dependent habitat selection, (iv) spatial dependency, (v) population demographic structure, (vi) species interactions and (vii) population memory. We review the basis behind each of these conceptual models and we examine corresponding numerical applications. We argue that the conceptual models are complementary rather than competing, that existing numerical applications are still rarely compared and combined, and that PDMs can offer a statistical framework to achieve this. We recommend that the numerical models associated with different hypotheses be constructed within such a common general framework. This will permit evaluation, comparison and combination of the multiple hypotheses on fish spatial distribution. It will ultimately lead to a more comprehensive understanding of the factors controlling the spatial distribution of fish populations and to more accurate predictions in which model uncertainty is accounted for.
All-terminal reliability evaluation through a Monte Carlo simulation based on an MPI implementation

All-terminal reliability (ATR), defined as the probability that every node in a network can communicate with every other node, is an important problem in research areas such as mobile ad-hoc wireless networks, grid computing systems, and telecommunications. The assessment of ATR has also been part of related problems like the reliability allocation problem. However, the exact calculation of ATR is a NP-hard problem. To obtain this probability, there are approaches based on analytic methods for small networks or estimation through Monte Carlo simulation (MCS). In this paper, a parallel MCS implementation, based on the Message Passing Interface (MPI) standard is presented. The implementation can take advantage of the existence of multiprocessor thus reducing the time required for the ATR assessment. Three examples related to real network illustrate the benefits.