Miracle-dz/UniFAR-FTUs huggingface dataset:
Chinese-Vietnamese bilingual news unsupervised sentiment classification based on word-weighted JST algorithm

Sentiment classification is an important part of text sentiment analysis. Usually sentiment classification methods are supervised models or semi-supervised models, but well-labeled corpora are often difficult to obtain. In the Chinese-Vietnamese bilingualism, the lack of emotional resources leads to the accuracy of cross-language sentiment classification is not as accurate as that in a single-language environment. Unsupervised sentiment classification can improve the accuracy of sentiment classification by constructing emotional dictionary and incorporating word weights. In this paper, the Gibbs sampling process is firstly guided by the emotional polarity of the words in the sentiment dictionary, which helps the model to predict the vocabulary emotion and subject distribution. Then this paper proposes an unsupervised sentiment classification method based on the word weighted Joint Sentiment/topic (JST) model algorithm. Through the linear combination of three kinds of weighted methods, the emotional weight was integrated into the vocabulary. This approach improves the impact of emotional words in the Gibbs sampling process, and ultimately improves the accuracy of sentiment classification. Experiments show that the word-weighted JST model combined with prior knowledge has greatly improved the accuracy of Vietnamese sentiment classification. Keywords—sentiment classification, unsupervised, emotional dictionary, weighting method, Chinese-Vietnamese
Functionally active rat S100A4 from a polymerase chain reaction-synthesized gene expressed in soluble form in Escherichia coli

S100A4 protein is associated with Ca2+-dependent regulation of intracellular activities and is significant in the invasion, growth and metastasis of cancer. In order to express rat S100A4 functionally and identify its biological activity following purification, an S100A4 gene fragment was optimized and fully synthesized via overlapping polymerase chain reaction. The gene was inserted into the prokaryotic expression vector, pBV220, with phage λ PRPL promoters following confirmation by DNA sequencing. The pBV220-S100A4 plasmid was constructed and transformed into Escherichia coli DH5α. Following temperature induction, rat S100A4 was overexpressed and the protein was observed to be located in the supernatant of the lysates, which was ~30–40% of the total protein within the host. The protein was isolated and purified by metal-chelate affinity chromatography. High purity protein (>98% purity) was obtained and in vitro western blot analysis identified that the recombinant S100A4 was able to bind to the antibody against wild-type S100A4. The bioactivity of the recombinant protein was detected via Transwell migration and invasion assays. The polyclonal antibody of rat S100A4 protein was prepared for rabbit immunization and exhibited similar efficacies when compared with commercial S100A4. Therefore, rat S100A4 was functionally expressed in E. coli; thus, the production of active recombinant S100A4 protein in E. coli may further aid with the investigation and application of S100A4.
Post‐trauma Lipitor treatment prevents endothelial dysfunction, facilitates neuroprotection, and promotes locomotor recovery following spinal cord injury

We have previously reported neuroprotection in spinal cord injury (SCI) by Lipitor [atorvastatin (AT)]‐pre‐treatment. Though informative, pre‐treatment studies find only limited clinical application as trauma occurrence is unpredictable. Therefore, this study investigates the efficacy of AT treatment post‐SCI. In a rat model of contusion‐SCI resulting in complete hindlimb paralysis, AT treatment (5 mg/kg; gavage) was begun 2, 4, or 6 h post‐SCI followed by a once daily dose thereafter for 6 weeks. While the placebo vehicle (VHC)‐SCI rats showed substantial functional deficit, AT‐SCI animals exhibited significant functional recovery. AT diminished injury‐induced blood–spinal cord barrier (BSCB) dysfunction with significantly reduced infiltration and tumor necrosis factor‐α/interleukin‐1β/inducible nitric oxide synthase expression at site of injury. BSCB protection in AT‐SCI was attributable to attenuated matrix metalloproteinase‐9 (MMP9) expression – a central player in BSCB disruption. Furthermore, endothelial MMP9 expression was found to be RhoA/ROCK pathway‐mediated and regulated by AT through an isoprenoid‐dependent mechanism. Attenuation of these early inflammatory events reduced secondary damage. Significant reduction in axonal degeneration, myelin degradation, gliosis, and neuronal apoptosis with resultant enhancement in tissue sparing was observed in AT‐SCI compared with VHC‐SCI. In summary, this novel report presenting the efficacy of post‐injury AT treatment might be of critical therapeutic value as effective treatments are currently unavailable for SCI.
Automatic assignment of reviewers in an online peer assessment task based on social interactions

Online peer assessment tasks are very popular and have unique characteristics that improve learning and encourage social interactions in a distance education environment. Unfortunately, social factors have usually been ignored in the process of selecting reviewers for online peer assessment tasks. We hypothesise that this fact could have some influence on the lack of engagement and participation by some learners. For this reason, we propose an approach in which social network analysis techniques, expert criteria, and Bayesian reasoning are applied to select reviewers with the objective of increasing participation in peer review tasks. The approach is divided into two elements. On the one hand, we have developed an influence diagram template that structures a set of proposed social network analysis variables in accordance with expert criteria. This influence diagram template can be easily updated for any course simply by eliciting a minimal set of parameters. On the other hand, we have instantiated the proposed influence diagram template to produce an influence diagram network to quantify the quality of reviewer assignment for an online peer assessment task. In an online experiment, we verified that the consideration of social factors can increase participation in a peer assessment task.
Swiss-Chocolate: Sentiment Detection using Sparse SVMs and Part-Of-Speech n-Grams

We describe a classifier to predict the message-level sentiment of English microblog messages from Twitter. This paper describes the classifier submitted to the SemEval-2014 competition (Task 9B). Our approach was to build up on the system of the last year’s winning approach by NRC Canada 2013 (Mohammad et al., 2013), with some modifications and additions of features, and additional sentiment lexicons. Furthermore, we used a sparse (‘1-regularized) SVM, instead of the more commonly used ‘2-regularization, resulting in a very sparse linear classifier.
Analysis of Sequential Tasks in Use Context of Mobile Apps

Most of the work on context-aware systems has focused on the context of time, location, and activity. Previous studies on the context flow have been primarily conducted on a qualitative basis. This paper proposes a new approach from a quantitative perspective. We gathered the data from automated task service, "If This Then That (IFTTT)", and analyzed the sequential tasks in terms of event occurrence in smart devices through association rule mining. We found out three consecutive tasks in cross-applications. The results of analysis have potential to find hidden use patterns as telling what kinds of services and channels are associated with each other. The findings provide some insights on the development of design guidelines for context-aware services.
The spinal cord ventral root: an afferent pathway of the hind‐limb pressor reflex in cats.

1. In anaesthetized cats the sciatic nerve was cut and the central end was stimulated at a high frequency and voltage. This caused an increase in arterial blood pressure and a rise in heart rate. The pressure response was diminished by dorsal root section but not completely eliminated until ventral root section (L4‐S3). The tachycardia response was abolished by dorsal root section alone. 2. In other cats capsaicin was injected intra‐arterially into the hind limb, causing elevations in both blood pressure and heart rate. Similar to the sciatic nerve stimulation experiments, the pressor response was principally reduced by dorsal root section but was further significantly decreased by ventral root section (L1‐S3). The rise in heart rate was prevented by dorsal root section alone. 3. It is concluded that, in cats, the afferent pathway of the pressor response to sciatic nerve stimulation and to hind‐limb capsaicin injection are conducted principally in the dorsal roots but also to a small extent in the ventral roots of the spinal cord. Although the tachycardia response appears to be conducted only through the dorsal roots, it is possible that at lower resting heart rates and by stimulation of a large population of the unmyelinated skeletal muscle afferents, the ventral root is a functional pathway.
Production of 1,3-propanediol from glycerol by the recombinant bacteria expressing recombinant diol dehydratase

Genes from bacteria known to have a diol dehydratase enzyme that degrades (57) Abstract: 1,2-propanediol, was cloned into a bacterial host, growing the host in the presence of glycerol, bioconversion method of the 1,3-propanediol glycerol is provided. Expression of foreign genes in host cells is to promote the enzymatic conversion to 1,3-propanediol, glycerol, 1,3-propanediol is isolated from the culture.
Charge-Based Compact Model for Bias-Dependent Variability of 1/ $f$ Noise in MOSFETs

Variability of low frequency noise (LFN) in MOSFETs is bias-dependent. Moderate-to-large-sized transistors commonly used in analog/RF applications show 1/f-like noise spectra, resulting from the superposition of random telegraph noise. Carrier number and mobility fluctuations are considered as the main causes of LFN. While their effect on the bias-dependence of LFN has been well investigated, the way these noise mechanisms contribute to the bias-dependence of variability of LFN has been less well understood. LFN variability has been shown to be maximized in weak inversion (subthreshold), while increased drain bias also increases LFN variability. However, no compact model has been proposed to explain this bias-dependence in detail. In combination with the charge-based formulation of LFN, this paper proposes a new model for bias-dependence of LFN variability. Comparison with experimental data from moderately sized nMOS and pMOS transistors at all bias conditions provides insight into how carrier number and mobility fluctuation mechanisms impact the bias-dependence of LFN variability.
Effects of Growth Parameters on the Analysis of Aspergillus flavus Volatile Metabolites

Aspergillus flavus produces dangerous secondary metabolites known as aflatoxins, which are toxic and carcinogenic, and their contamination of agricultural products results in health issues and economic hardships in the U.S. and around the world. Early identification of aflatoxigenic isolates of A. flavus is the key in the management of these fungi. An emerging detection method for specific fungi identification involves the analysis of microbial volatile organic compounds (MVOCs) released by the fungi. Complicating this approach is the understanding that many factors influence metabolic production, including growth parameters, such as growth media, temperature, spore counts and oxidation stress. In addition, analytical and data analysis methods can also influence the results. Several growth and analysis methods were evaluated and optimized in order to better understand the effect of the methods on fungi MVOC signatures. The results indicate that carboxen/polydimethylsiloxane (CAR/PDMS) has the best extraction efficiency for the MVOCs emitted by A. flavus. Both chemical defined agar (CDA) and chemical defined liquid (CDL) are suitable growth media for MVOC emission studies. The highest MVOC production was found at 30 °C. Log transformation was considered one of the best data pretreatment methods when analyzing MVOC data and resulted in the best principal component analysis (PCA) clustering in the experiments with different growth media. This study aims to elucidate fungal volatile organic compounds (VOCs) differences due to variations in growth parameters as a first step in the development of an analytical method for the monitoring of aflatoxigenic A. flavus contamination in crop storage facilities.
Synchronization of delayed neural networks with hybrid coupling via impulsive control

The synchronization problem of coupled neural networks via impulsive control is investigated in the present paper. Based on a time varying Lyapunov functional associated with the impulsive time sequence, the delay-dependent criteria in terms of linear matrix inequalities are derived to guarantee the synchronization of the coupled neural networks. The obtained criteria are closely related to both the lower and the upper bound of the adjacent impulsive instant difference. By solving the corresponding linear matrix inequalities, the synchronization criteria can be used to estimate the upper bound of both transmission delay and distributed-delay. The low-dimensional criteria also are obtained for the coupled neural networks with identical nodes. Finally, two examples are given to illustrate the validity of the proposed hybrid control.
Testing marker‐based estimates of heritability in the wild

Marker‐based estimates of heritability are an attractive alternative to pedigree‐based methods for estimating quantitative genetic parameters in field studies where it is difficult or impossible to determine relationships and pedigrees. Here I test the ability of the marker‐based method to estimate heritability of a suite of traits in a wild population of bighorn sheep (Ovis canadensis) using marker data from 32 microsatellite loci. I compared marker‐based estimates with estimates obtained using a pedigree and the animal model. Marker‐based estimates of heritability were imprecise and downwardly biased. The high degree of uncertainty in marker‐based estimates suggests that the method may be sufficient to detect the presence of genetic variance for highly heritable traits, but not sufficiently reliable to estimate genetic parameters.
A potent nonpeptide antagonist of the substance P (NK1) receptor.

CP-96,345 [(2S, 3S)-cis-2-(diphenylmethyl)-N-[(2-methoxyphenyl)- methyl]-1-azabicyclo[2.2. 2]octan-3-amine] is a potent nonpeptide antagonist of the substance P (NK1) receptor. CP-96,345 inhibited 3H-labeled substance P binding and was a classical competitive antagonist in the NK1 monoreceptor dog carotid artery preparation. CP-96,345 inhibited substance P-induced salivation in the rat, a classical in vivo bioassay, but did not inhibit NK2, NK3, or numerous other receptors; it is thus a selective NK1 antagonist. This compound may prove to be a powerful tool for investigation of the physiological properties of substance P and exploration of its role in diseases.
Universal capture: image-based facial animation for "The Matrix Reloaded"

The VFX R&D stage for The Matrix Reloaded was kicked off in January 2000 with the challenge to create realistic human faces. We believed that traditional facial animation approaches like muscle deformers or blend shapes would simply never work, both because of the richness of facial movement and because of the human viewer’s extreme sensitivity to facial nuances. Our task was further complicated as we had to recreate familiar actors such as Keanu Reeves and Lawrence Fishburne. Our team had been very successful at applying image-based techniques for photorealistic film set/location rendering, so we decided to approach the problem from the image-based side again. We wanted to produce a 3-d recording of the real actor's performance and be able to play it back from different angles and under different lighting conditions. Just as we can extract geometry, texture, or light from images, we are now able to extract movement. Universal Capture combines two powerful computer vision techniques: optical flow and photogrammetry.
Soil Lead Spatial Prediction Using a Fuzzy Soil-landscape Model

Soil lead pollution does great harm to the environment. The relation between soil lead and environmental covariates, however, is complicated. A fuzzy logic approach with expert knowledge has proven to be successful in mapping spatial variation of soil lead. The reasons are the limited availability of expert knowledge and the ignorance of soil type and land use of the non-soil area when predicting soil lead in current fuzzy clustering methodology. This paper incorporates the soil type map, the land use map and the DEM data to construct a soil\'96\'6 landscape model for soil lead prediction. It compares a fuzzy C-means classifier that includes expert judgment with conditional regressive model. Prediction efficiency was evaluated in the Three Gorges area of China using the root mean square error (RMSE) and the agreement coefficient (AC) of predictions at validation points. The result indicates that the soil-landscape model constructed by the fuzzy membership functions with fuzzy c-means method and the conventional soil map were able to produce good quality soil lead spatial information.
Marble Pieces in the Romanesque Portal of Glory of the Santiago de Compostela Cathedral. New Data through a Multi-Analytical Approach

ABSTRACT Probably the most important Romanesque artwork in Spain, the Portal of Glory of Santiago de Compostela is essentially made in granite, the most abundant stone in the NW of Iberia, with the only exception of five marble pieces. Different hypothesis on the origin of these marbles have previously been proposed based on visual assessment or by directly assuming a local source. To shed light on their quarry provenance, a multi-analytical study was performed combining polarized-light optical microscopy, cathodoluminescence microscopy, XRPD, SEM-EDS and stable C and O isotopes. The comparison of the results with the available databases reveals the use of marbles from the Estremoz Anticline (Portugal) in the three exquisitely carved columns strategically placed in the central arcade, whereas the other two pieces are local marbles, illustrating a more complex consumption of this noble material than that initially expected.
Fast Multi-Scaled Texture Generation and Rendering

The multi-scaled model for stochastic texture representation and the method providing real -time rendering of textur es formalized by this model are introduced. Both “abstract” and “natural -like” textures can be generated. Being much simpler then existing stochastic texture models it satisfies the requirements of real time texture mapping: compact data representation, sc alability, random pixel access. The rendering algorithm is simple enough to be implemented in hardware.
Differential expression of GAS5 in rapamycin‐induced reversion of glucocorticoid resistance

This study evaluates the association between the long noncoding RNA GAS5 levels and the anti‐proliferative effect of the glucocorticoid (GC) methylprednisolone (MP) alone and in combination with rapamycin in peripheral blood mononuclear cells (PBMCs) obtained from healthy donors. The effect of MP, rapamycin, and MP plus rapamycin was determined in 17 healthy donors by labelling metabolically active cells with [methyl‐3H] thymidine and the expression levels of GAS5 gene were evaluated by real‐time RT‐PCR TaqMan analysis. We confirmed a role for GAS5 in modulating GC response: poor responders presented higher levels of GAS5 in comparison with good responders. Interestingly, when PBMCs were treated with the combination of rapamycin plus MP, the high levels of GAS5 observed for each drug in the MP poor responders group decreased in comparison with rapamycin (P value = 0.0134) or MP alone (P value = 0.0193). GAS5 is involved in GC resistance and co‐treatment of rapamycin with GCs restores GC effectiveness in poor responders through the downregulation of the long noncoding RNA. GAS5 could be considered a biomarker to personalize therapy and a novel therapeutic target useful for the development of new pharmacological approaches to restore GC sensitivity.
Ontology interaction with a patient electronic health record

The XIMSA system (extented interactive multimedia system for auto-medication) aims to propose information and services to patients on mild clinical signs and associated treatments, a domain usually called self-medication. An important number of XIMSA's services benefit from inferences which are the results of collaborations between a self-medication knowledge base (ontology and concept instances), drug and symptom databases and a patient simplified electronic health record. This paper focuses on the electronic health record/knowledge base interactions which enable to validate drug consumption considering a patient profile but also to design usable and user-friendly graphical user interfaces.
THE IMPACT OF RUNTIME METRICSCOLLECTION ON ADAPTIVE MOBILE APPLICATIONS

This thesis proposes, implements, and evaluates in terms of correctness and performance, an online metrics collection strategy to assist mobile application adaptation with the support of a mobile object framework. The solution is based upon an abstract representation of the system, which holds containers aggregating metrics for each specific component comprising a mobile object framework, including host mangers, runtimes and mobile objects. A key feature of the solution is the specification of multiple configurable criteria to control the propagation of metrics through the system, thereby reducing collection overhead. The MobJeX platform was used as the basis for implementation and synthetic applications were evaluated in order to provide an initial performance benchmark in terms of metrics collection overhead for a subset of a recently published suite of metrics. Preliminary findings demonstrate that even with simple collection criteria it should be possible to achieve positive adaptation outcomes that offset the overhead of the metrics collection process.
Alteration of Sarcoplasmic Reticulum Ca2+ Release in Skeletal Muscle from Calpain 3-Deficient Mice

Mutations of Ca2+-activated proteases (calpains) cause muscular dystrophies. Nevertheless, the specific role of calpains in Ca2+ signalling during the onset of dystrophies remains unclear. We investigated Ca2+ handling in skeletal cells from calpain 3-deficient mice. [Ca2+]i responses to caffeine, a ryanodine receptor (RyR) agonist, were decreased in −/− myotubes and absent in −/− myoblasts. The −/− myotubes displayed smaller amplitudes of the Ca2+ transients induced by cyclopiazonic acid in comparison to wild type cells. Inhibition of L-type Ca2+ channels (LCC) suppressed the caffeine-induced [Ca2+]i responses in −/− myotubes. Hence, the absence of calpain 3 modifies the sarcoplasmic reticulum (SR) Ca2+ release, by a decrease of the SR content, an impairment of RyR signalling, and an increase of LCC activity. We propose that calpain 3-dependent proteolysis plays a role in activating support proteins of intracellular Ca2+ signalling at a stage of cellular differentiation which is crucial for skeletal muscle regeneration.