Miracle-dz/UniFAR-FTUs huggingface dataset:
Good to be Bad? Distinguishing between Positive and Negative Citations in Scientific Impact

The impact of a publication is often measured by the number of citations it received, this number being taken as a proxy for the relevance of published work. However, a higher citation index does not necessarily mean that a publication necessarily had a positive feedback from citing authors, as a citation can represent a negative criticism. In order to overcome this limitation, we used sentiment analysis to rate citations as positive, neutral or negative. Adjectives are initially extracted from the citations, with the SentiWordNet lexicon being used to rate the degree of positivity and negativity for each adjective. Relevance scores were then computed to rank citations according to the sentiment expressed in the text corresponding to each citation. As expected for accurate information retrieval systems, higher precision rates were observed in the initial points of the curve. The SRC (0.6728) computed using number of raw citations is lower than the SRC (0.7397) observed by the ranking generated using sentiment scores (Table 3). Conclusion: This result indicates that child articles with higher values of relevance score were in general the ones expressing positive opinion about their parents. Therefore, the ranking generated by sentiment scores had an improved accuracy.
Modelling SO-CAL in an Inheritance-based Sentiment Analysis Framework

Sentiment analysis is the computational study of people's opinions, as expressed in text. This is an active area of research in Natural Language Processing with many applications in social media. There are two main approaches to sentiment analysis: machine learning and lexicon-based. The machine learning approach uses statistical modelling techniques, whereas the lexicon-based approach uses 'sentiment lexicons' containing explicit sentiment values for individual words to calculate sentiment scores for documents. In this paper we present a novel method for modelling lexicon-based sentiment analysis using a lexical inheritance network. Further, we present a case study of applying inheritance-based modelling to an existing sentiment analysis system as proof of concept, before developing the ideas further in future work.
Isolation and typification of histamine-producing Lactobacillus vaginalis strains 1 from cheese 2 3 4

22 23 In food, the biogenic amine (BA) histamine is mainly produced by histidine 24 decarboxylation catalyzed by microbial histidine decarboxylase. The consumption of 25 foods containing high concentrations of histamine can trigger adverse neurological, 26 gastrointestinal and respiratory reactions. Indeed, histamine is one of the most toxic of 27 all BAs, and is often detected in high concentration in cheese. However, little is known 28 about the microorganisms responsible for its accumulation in this food. In the present 29 work, 25 histamine-producing Lactobacillus vaginalis strains were isolated from a blue30 veined cheese (the first time that histamine-producing strains of this species have been 31 isolated from any food). The restriction profiles of their genomes were analysed by 32 PFGE, and seven lineages identified. The presence of the histidine decarboxylase gene 33 (hdcA) was confirmed by PCR. The nucleotide sequence and genetic organization of the 34 histamine biosynthesis gene cluster (HDC) and its flanking regions are described for a 35 representative strain (L. vaginalis IPLA11050). 36 37
Physical and functional association of the cbl protooncogen product with an src-family protein tyrosine kinase, p53/56lyn, in the B cell antigen receptor-mediated signaling

To identify novel signal transducers involved in signaling mediated by the Src-family protein tyrosine kinases (PTKs), we used a yeast two- hybrid system with a probe corresponding to the regulatory region of p56lyn, a member of Src-family PTKs. One of the isolated clones contained the COOH-terminal 470 amino acid residues of p120c-cbl, the product of the cellular homologue of the v-cbl retroviral oncogene. p120c-cbl is a cytoplasmic protein with nuclear protein-like motifs. Here we show in vivo association of p120c-cbl with p53/56lyn. After stimulation of the B cell antigen receptor (BCR), p120c-cbl was rapidly tyrosine phosphorylated. Studies with lyn- or syk-negative chicken B cells demonstrated that p53/56lyn, but not p72syk, was crucial for tyrosine phosphorylation of p120c-cbl upon stimulation of the BCR. We also show the importance of p59fyn in tyrosine phosphorylation of p120c- cbl in the T-cell receptor-mediated signaling using fyn-overexpressing T cell hybridomas and splenic T cells from fyn-deficient mice. These results suggest that p120c-cbl is an important substrate of Src-family PTKs in the intracellular signaling mediated by the antigen receptors
PERFORMANCE OF ROBUST HEDGES FOR DIGITAL DOUBLE BARRIER OPTIONS

We analyze the performance of robust hedging strategies of digital double barrier options of Cox and Obloj (2011) against that of traditional hedging methods such as delta and delta/vega hedging. Digital double barrier options are financial derivative contracts which pay out a fixed amount on the condition that the underlying asset remains within or breaks into a range defined by two distinct barrier levels. We perform the analysis in hypothetical forward markets driven by models with stochastic volatility and jumps, calibrated to the AUD/USD foreign exchange rate market. Our findings are strikingly unanimous and suggest that, in the presence of model uncertainty and/or transaction costs, robust hedging strategies typically outperform in a substantial way model-specific hedging methods.
Sleep Architecture When Sleeping at an Unusual Circadian Time and Associations with Insulin Sensitivity

Circadian misalignment affects total sleep time, but it may also affect sleep architecture. The objectives of this study were to examine intra-individual effects of circadian misalignment on sleep architecture and inter-individual relationships between sleep stages, cortisol levels and insulin sensitivity. Thirteen subjects (7 men, 6 women, age: 24.3±2.5 y; BMI: 23.6±1.7 kg/m2) stayed in a time blinded respiration chamber during three light-entrained circadian cycles (3x21h and 3x27h) resulting in a phase advance and a phase delay. Sleep was polysomnographically recorded. Blood and salivary samples were collected to determine glucose, insulin and cortisol concentrations. Intra-individually, a phase advance decreased rapid eye movement (REM) sleep and slow-wave sleep (SWS), increased time awake, decreased sleep and REM sleep latency compared to the 24h cycle. A phase delay increased REM sleep, decreased stage 2 sleep, increased time awake, decreased sleep and REM sleep latency compared to the 24h cycle. Moreover, circadian misalignment changed REM sleep distribution with a relatively shorter REM sleep during the second part of the night. Inter-individually, REM sleep was inversely associated with cortisol levels and HOMA-IR index. Circadian misalignment, both a phase advance and a phase delay, significantly changed sleep architecture and resulted in a shift in rem sleep. Inter-individually, shorter REM sleep during the second part of the night was associated with dysregulation of the HPA-axis and reduced insulin sensitivity. Trial Registration: International Clinical Trials Registry Platform NTR2926 http://apps.who. int/trialsearch/
Interdiction and fortification problem of supply system based on preferential attachment

Protections of facilities of supply systems have been studied for many years. With development of e-commerce and network technology and the economic globalization, modern supply systems with enormous scales are organized as distributed and multi-echelon networks, which can be recognized as a complex network system. Distributions of facilities in such supply networks are consistent with power-law distribution of complex system. In this paper, we consider interdiction and fortification problem of supply system based on preferential attachment (IFPA) which means that the demand nodes choose facility with largest satisfaction as their service supporter after interdiction. Then we formulate IFPA as a linear bi-level program and solve the IFPA model by tree search algorithm in a decentralized mode. Finally, computational experiments demonstrate the results of IFPA compared with existed models and conclusions about IFPA are discussed at last.
Per instance algorithm configuration of CMA-ES with limited budget

Per Instance Algorithm Configuration (PIAC) relies on features that describe problem instances. It builds an Empirical Performance Model (EPM) from a training set made of (instance, parameter configuration) pairs together with the corresponding performance of the algorithm at hand. This paper presents a case study in the continuous black-box optimization domain, using features proposed in the literature. The target algorithm is CMA-ES, and three of its hyper-parameters. Special care is taken to the computational cost of the features. The EPM is learned on the BBOB benchmark, but tested on independent test functions gathered from the optimization literature. The results demonstrate that the proposed approach can outperform the default setting of CMA-ES with as few as 30 or 50 time the problem dimension additional function evaluations for feature computation.
Cortical Plasticity in Amyotrophic Lateral Sclerosis: Motor Imagery and Function

Background. Cortical networks underlying motor imagery are functionally close to motor performance networks and can be activated by patients with severe motor disabilities. Objective. The aim of the study was to examine the longitudinal effect of progressive motoneuron degeneration on cortical representation of motor imagery and function in amyotrophic lateral sclerosis. Methods. The authors studied 14 amyotrophic lateral sclerosis patients and 15 healthy controls and a subgroup of 11 patients and 14 controls after 6 months with a grip force paradigm comprising imagery and execution tasks using functional magnetic resonance imaging. Results. Motor imagery activated similar neural networks as motor execution in amyotrophic lateral sclerosis patients and healthy subjects in the primary motor (BA 4), premotor, and supplementary motor (BA 6) cortex. Amyotrophic lateral sclerosis patients presented a stronger response within premotor and primary motor areas for imagery and execution compared to controls. After 6 months, these differences persisted with additional activity in the precentral gyrus in patients as well as in a frontoparietal network for motor imagery, in which activity increased with impairment. Conclusion. The findings suggest an ongoing compensatory process within the higher order motor-processing system of amyotrophic lateral sclerosis patients, probably to overcome loss of function in primary motor and motor imagery-specific networks. The increased activity in precentral and frontoparietal networks in motor imagery might be used to control brain-computer interfaces to drive communication and limb prosthetic devices in patients with loss of motor control such as severely disabled amyotrophic lateral sclerosis patients in a locked-in-like state.
(Hi)story-telling the nation: the narrative construction of Romanianism in the late 19th century

This paper is a study in historical socio - anthropology, focusing on the political process of Romanian nation building and its corresponding anthropological program of creating the national self. Starting from the assum ption that human being is a “storytelling animal” nested in a (hi)story - telling community pillared upon “narrative traditions,” this paper examines the stock of stories told through history schoolbooks about the Romanian past as a means of narrative constr uction of Romanian national identity. Consequently, the paper looks at the nationalizing process launched by Romanian state authorities in the wake of the political union of 1859, arguing that the political building of Romanian nation implied the narrative articulation, followed by the recursive institutional reciting within the public educational system, of a “Romanian master story” as a means of breeding national Romanians out of Orthodox peasants. After detailing the pedagogy of the nation emerged in the second half of the 19th century as establishing the norms of (hi)story telling the national past, the study concludes by highlighting the main themes, or “schematic narrative templates,” into which the Romanian master story has been poured out.
Development and Characterization of a Reverse Genetic System for Studying Dengue Virus Serotype 3 Strain Variation and Neutralization

Dengue viruses (DENV) are enveloped single-stranded positive-sense RNA viruses transmitted by Aedes spp. mosquitoes. There are four genetically distinct serotypes designated DENV-1 through DENV-4, each further subdivided into distinct genotypes. The dengue scientific community has long contended that infection with one serotype confers lifelong protection against subsequent infection with the same serotype, irrespective of virus genotype. However this hypothesis is under increased scrutiny and the role of DENV genotypic variation in protection from repeated infection is less certain. As dengue vaccine trials move increasingly into field-testing, there is an urgent need to develop tools to better define the role of genotypic variation in DENV infection and immunity. To better understand genotypic variation in DENV-3 neutralization and protection, we designed and constructed a panel of isogenic, recombinant DENV-3 infectious clones, each expressing an envelope glycoprotein from a different DENV-3 genotype; Philippines 1982 (genotype I), Thailand 1995 (genotype II), Sri Lanka 1989 and Cuba 2002 (genotype III) and Puerto Rico 1977 (genotype IV). We used the panel to explore how natural envelope variation influences DENV-polyclonal serum interactions. When the recombinant viruses were tested in neutralization assays using immune sera from primary DENV infections, neutralization titers varied by as much as ∼19-fold, depending on the expressed envelope glycoprotein. The observed variability in neutralization titers suggests that relatively few residue changes in the E glycoprotein may have significant effects on DENV specific humoral immunity and influence antibody mediated protection or disease enhancement in the setting of both natural infection and vaccination. These genotypic differences are also likely to be important in temporal and spatial microevolution of DENV-3 in the background of heterotypic neutralization. The recombinant and synthetic tools described here are valuable for testing hypotheses on genetic determinants of DENV-3 immunopathogenesis.
Adaptive Localization of Focus Point Regions via Random Patch Probabilistic Density from Whole-Slide, Ki-67-Stained Brain Tumor Tissue

Analysis of whole-slide tissue for digital pathology images has been clinically approved to provide a second opinion to pathologists. Localization of focus points from Ki-67-stained histopathology whole-slide tissue microscopic images is considered the first step in the process of proliferation rate estimation. Pathologists use eye pooling or eagle-view techniques to localize the highly stained cell-concentrated regions from the whole slide under microscope, which is called focus-point regions. This procedure leads to a high variety of interpersonal observations and time consuming, tedious work and causes inaccurate findings. The localization of focus-point regions can be addressed as a clustering problem. This paper aims to automate the localization of focus-point regions from whole-slide images using the random patch probabilistic density method. Unlike other clustering methods, random patch probabilistic density method can adaptively localize focus-point regions without predetermining the number of clusters. The proposed method was compared with the k-means and fuzzy c-means clustering methods. Our proposed method achieves a good performance, when the results were evaluated by three expert pathologists. The proposed method achieves an average false-positive rate of 0.84% for the focus-point region localization error. Moreover, regarding RPPD used to localize tissue from whole-slide images, 228 whole-slide images have been tested; 97.3% localization accuracy was achieved.
Effect of thiamine deficiency on the competence of the blood-brain barrier to albumin labeled with fluorescent dyes.

RECENT ULTRAsrRUCTLuuL sruDIES have emphasized the fact that intracellular edema, notably involving glial cells and their perivascular processes, is a conspicuous earlv change in the brainstem lesions of experimental thiamine deficiencv in rats. -'2 Later, frank necrosis, often hemorrhagic, supervenes, and at this stage there is marked expansion of the extracellular space as well.3Since the earlyr edema is intracellular, and since it occurs in the absence of morphologic e'vidence of parenchvmal or vascular necrosis, it was suggested that it might represent a defect of transport directlv related to the deficiencv state. In contrast, edema occurring during the necrotic phase could be analogous to the reactive increase in capillary permeabilitv known to occur in relation to mechanical,6 heating,7 freezing,8_o severe anoxic,l neoplastic, '123 and inflammatorv 14 lesions associated with tissue destruction and termed txasogenic edema bv Klatzo. '5 This experiment was designed to test the hypothesis that the bloodbrain barrier remains intact with respect to plasma proteins in the early edematous lesion, but becomes permeable to protein in the necrotic stage. This demonstration was considered essential for subsequentlv evaluating transport of and barriers to other substances in the pathogenesis of lesions in thiamine deficiency.
Tampere University of Technology Sound event detection using spatial features and convolutional recurrent neural network

This paper proposes to use low-level spatial features extracted from multichannel audio for sound event detection. We extend the convolutional recurrent neural network to handle more than one type of these multichannel features by learning from each of them separately in the initial stages. We show that instead of concatenating the features of each channel into a single feature vector the network learns sound events in multichannel audio better when they are presented as separate layers of a volume. Using the proposed spatial features over monaural features on the same network gives an absolute F-score improvement of 6.1% on the publicly available TUT-SED 2016 dataset and 2.7% on the TUT-SED 2009 dataset that is fifteen times larger.
Effect of vibrational stress and spaceflight on regulation of heat shock proteins hsp70 and hsp27 in human lymphocytes (Jurkat)

Heat shock protein levels are increased in cells as a result of exposure to stress. To determine whether heat shock protein regulation could be used to evaluate stress in cells during spaceflight, the response of Jurkat cells to spaceflight and simulated space shuttle launch vibration was investigated by evaluating hsp70 and hsp27 gene expression. Gene expression was assessed by reverse transcription‐polymerase chain reaction using mRNA extracted from vibrated, nonvibrated, space‐flown, and ground control cells. Results indicate that mechanical stresses of vibration and low gravity do not up‐regulate the mRNA for hsp70, although the gene encoding hsp27 is up‐regulated by spaceflight but not by vibration. In ground controls, the mRNA for hsp70 and hsp27 increased with time in culture. We conclude that hsp70 gene expression is a useful indicator of stress related to culture density but is not an indicator of the stresses of launch vibration or microgravity. Up‐regulation of hsp27 gene expression in microgravity is a new finding.
Deep Hashing for Scalable Image Search

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.
Human Metapneumovirus Infection in Japanese Children

ABSTRACT Human metapneumovirus (hMPV) has been recently discovered as an etiological agent of acute respiratory infections. Our purpose was to asses the virological and clinical features of children with respiratory infections caused by hMPV. We examined 658 nasopharyngeal swab samples obtained from 637 children with respiratory infections for hMPV by using reverse transcription-PCR (RT-PCR). A total of 268 samples from 637 children were inoculated onto tertiary monkey kidney cells. A total of 36 serum samples (26 in the acute phase and 10 in the convalescent phase) from the 26 hMPV-positive children were tested for immunoglobulin G (IgG) and IgM antibodies to hMPV by using an indirect immunofluorescence assay. We detected hMPV in 57 (8.9%) of the 637 samples by using RT-PCR and isolated 7 (2.6%) hMPV strains of the 268 samples in cell cultures. A total of 12 (46.2%) of 26 hMPV-positive children were suspected to have primary infection with hMPV as determined by an indirect immunofluorescence assay. The infected children were diagnosed as having wheezy bronchitis (36.8%), upper respiratory tract infection (26.3%), bronchitis (22.8%), and pneumonia (14.0%). We showed that two hMPV groups were circulating in different regions during the same period and that reinfection with hMPV frequently occurs in childhood. The RT-PCR test is the most sensitive test for detection of hMPV, and a serological test may be useful to differentiate between primary infection and reinfection with hMPV.
A Context-aware Recommendation System using smartphone sensors

Nowadays, the ubiquity of mobile devices (such as smartphones and tablets) has encouraged the development of context-aware and personalized computation to filter the query results and provide recommendations based on different situations of a user. On the other hand, global positioning system (GPS) technology along with microelectromechanical system (MEMS) sensors enables location sensing on mobile devices. Context-aware computation can provide customized services in different contexts - where context is related to the user's location, activity and historical information. Our main focus in this paper, the Context-aware Recommendation System (Co-ARS), is one of the major applications that has been refined over the years due to the evolving geospatial technologies and data mining. The proposed Co-ARS application achieves the list of recommendations by utilizing the user's context information (such as location and preferred transportation mode), item's context information (such as restaurant ratings and types), and personalized preference information (based on individuals past behavior). In this paper, we have described the application of such a system in the City of Calgary using android smartphones. The implemented system used various data filtering and management techniques to provide beneficial and accurate recommendation results to the users.