Miracle-dz/UniFAR-FTUs huggingface dataset:
The existence and stability of relativistic shock waves: general criteria and numerical simulations for a non-convex equation of state

A small viscosity approach to discontinuous flows is discussed in relativistic hydrodynamics with a general (possibly, non-convex) equation of state that typically occurs in the domains of phase transitions. Different forms of criteria for the existence and stability of relativistic shock waves, such as evolutionarity conditions, entropy criterion and corrugation stability conditions are compared with the requirement of the existence of shock viscous profile. The latter is shown to be most restrictive in case of a single-valued shock adiabat expressed as a function of pressure. One-dimensional numerical simulations with artificial viscosity for a simple piecewise-linear equation of state are carried out to illustrate the criteria in the case of planar and spherical shock waves. The effect of a phase transition domain on the shock amplitude in the process of a hydrodynamical spherical collapse is demonstrated.
Whole brain quantitative CBF, CBV, and MTT measurements using MRI bolus tracking: Implementation and application to data acquired from hyperacute stroke patients

A robust whole brain magnetic resonance (MR) bolus tracking technique based on indicator dilution theory, which could quantitatively calculate cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) on a regional basis, was developed and tested. T2*‐weighted gradient‐echo echoplanar imaging (EPI) volumes were acquired on 40 hyperacute stroke patients after gadolinium diethylene triamine pentaacetic acid (Gd‐DTPA) bolus injection. The thalamus, white matter (WM), infarcted area, penumbra, and mirror infarcted and penumbra regions were analyzed. The calculation of the arterial input function (AIF) needed for absolute quantification of CBF, CBV, and MTT was shown to be user independent. The CBF values (ml/min/100 g units) and CBV values (% units, in parentheses) for the thalamus, WM, infarct, mirror infarct, penumbra, and mirror penumbra (averaged over all patients) were 69.8 ± 22.2 (9.0 ± 3.0 SD); 28.1 ± 6.9 (3.9 ± 1.2); 34.4 ± 22.4 (7.1 ± 2.7); 60.3 ± 20.7 (8.2 ± 2.3); 50.2 ± 17.5 (10.4 ± 2.4); and 64.2 ± 17.0 (9.5 ± 2.3), respectively, and the corresponding MTT values (in seconds) were 8.0 ± 2.1; 8.6 ± 3.0; 16.1 ± 8.9; 8.6 ± 2.9; 13.3 ± 3.5; and 9.4 ± 3.2. The infarct and penumbra CBV values were not significantly different from their corresponding mirror values, whereas the CBF and MTT values were (P < 0.01). Quantitative measurements of CBF, CBV, and MTT were calculated on a regional basis on data acquired from hyperacute stroke patients, and the CBF and MTT values showed greater sensitivity to areas with perfusion defects than the CBV values. J. Magn. Reson. Imaging 2000;12:400–410. © 2000 Wiley‐Liss, Inc.
A Survey on Sentiment Analysis and Visualization

Online Social Networks become the medium for a plethora of applications such as targeted advertising and recommendation services, collaborative filtering, behavior modeling and pre- diction, analysis and identification of aggressive behavior, bullying and stalking, cultural trend monitoring, epidemic studies, crowd mood reading and tracking, revelation of terrorist net- works, even political deliberation. They mainly aim to promote human interaction on the Web, assist community creation, and facilitate the sharing of ideas, opinions and content. Social Networking Analysis Research has lately focused on major Online Social Networks like Face-book, Twitter and Digg [Chelmis and Prasanna, 2011]. However, research in Social Networks [Ereteo et al., 2008] has extracted underlying and often hidden social structures [Newman, 2010] from email communications [Tyler et al., 2003], structural link analysis of web blogs and personal home pages [Adamic and Adar, 2003] or recently explicit FOAF networks [Ding et al., 2005], structural link analysis of bookmarks, tags or resources in general [Mika, 2007], co-occurrence of names [Kautz et al., 1997] [Mika, 2007], and co-authorship in scientific publications references [Wasserman and Faust, 1994], and co-appearance in movies or music productions [Yin et al., 2010]. Interactive visualizations is employed by visual analytics in order to integrate users' knowledge and inference capability into numerical/algorithmic data analysis processes. It is an active research field that has applications in many sectors, such as security, finance, and business. The growing popularity of visual analytics in recent years creates the need for a broad survey that reviews and assesses the recent developments in the field. This paper reviews the state of the art of sentiment visualization field. The growing popularity of sentiment visualization systems in recent years is an active research area. In this paper, we will present a survey that reviews and assesses the recent visualization techniques and systems in the field. This report classifies and reviews the recent approaches in visual analysis. The motivations in conducting this survey are twofold. First, we aim to review the most recent research trends and developments of sentiment visualization techniques and systems and provide a precise review of the field. Second, this survey aims to provide a critical assessment of the research which can help enhance the understanding of the field.
Renormalization group scaling of the 1/m{sup 2} HQET Lagrangian

The operator mixing matrix for the dimension six operators in the heavy quark effective theory Lagrangian is computed at one loop. The results are shown to be consistent with constraints from the equations of motion, and from reparametrization invariance. {copyright} {ital 1997} {ital The American Physical Society}
Interleukin 35 Polymorphisms Are Associated with Decreased Risk of Premature Coronary Artery Disease, Metabolic Parameters, and IL-35 Levels: The Genetics of Atherosclerotic Disease (GEA) Study

Interleukin 35 (IL-35) is a heterodimeric cytokine involved in the development of atherosclerosis. The aim of the present study was to establish if the polymorphisms of IL-12A and EBI3 genes that encode the IL-35 subunits are associated with the development of premature coronary artery disease (CAD) in Mexican individuals. The IL-12A and EBI3 polymorphisms were determined in 1162 patients with premature CAD and 873 controls. Under different models, the EBI3 rs428253 (OR = 0.831, Padd = 0.036; OR = 0.614, Prec = 0.033; OR = 0.591, Pcod2 = 0.027) and IL-12A rs2243115 (OR = 0.674, Padd = 0.010; OR = 0.676, Pdom = 0.014; OR = 0.698, Phet = 0.027; OR = 0.694, Pcod1 = 0.024) polymorphisms were associated with decreased risk of developing premature CAD. Some polymorphisms were associated with clinical and metabolic parameters. Significant different levels of IL-35 were observed in EBI3 rs4740 and rs4905 genotypes only in the group of healthy controls. In summary, our study suggests that the EBI3 and IL-12A polymorphisms play an important role in decreasing the risk of developing premature CAD; it also demonstrates the relationship of the EBI3 rs4740 and rs4905 genotypes with IL-35 levels in healthy individuals.
piRNAs: from biogenesis to function

Distinguishing self from non-self plays a crucial role in safeguarding the germlines of metazoa from mobile DNA elements. Since their discovery less than a decade ago, Piwi-interacting RNAs (piRNAs) have been shown to repress transposable elements in the germline and, hence, have been at the forefront of research aimed at understanding the mechanisms that maintain germline integrity. More recently, roles for piRNAs in gene regulation have emerged. In this Review, we highlight recent advances made in understanding piRNA function, highlighting the divergent nature of piRNA biogenesis in different organisms, and discussing the mechanisms of piRNA action during transcriptional regulation and in transgenerational epigenetic inheritance.
Lighting interpolation by shadow morphing using intrinsic lumigraphs

Densely-sampled image representations such as the light field or lumigraph have been effective in enabling photorealistic image synthesis. Unfortunately, lighting interpolation with such representations has not been shown to be possible without the use of accurate 3D geometry and surface reflectance properties. In this paper we propose an approach to image-based lighting interpolation that is based on estimates of geometry and shading from relatively few images. We decompose captured light fields at different lighting conditions into intrinsic images (reflectance and illumination images), and estimate view-dependent scene geometries using multi-view stereo. We call the resulting representation an intrinsic lumigraph. In the same way that the lumigraph uses geometry to permit more accurate view interpolation, the intrinsic lumigraph uses both geometry and intrinsic images to allow high-quality interpolation at different views and lighting conditions. Joint use of geometry and intrinsic images is effective in the computation of shadow masks for shadow prediction at new lighting conditions. We illustrate our approach with images of real scenes.
Breaking Patterns of Environmentally Influenced Disease for Health Risk Reduction: Immune Perspectives

Background Diseases rarely, if ever, occur in isolation. Instead, most represent part of a more complex web or “pattern” of conditions that are connected via underlying biological mechanisms and processes, emerge across a lifetime, and have been identified with the aid of large medical databases. Objective We have described how an understanding of patterns of disease may be used to develop new strategies for reducing the prevalence and risk of major immune-based illnesses and diseases influenced by environmental stimuli. Findings Examples of recently defined patterns of diseases that begin in childhood include not only metabolic syndrome, with its characteristics of inflammatory dysregulation, but also allergic, autoimmune, recurrent infection, and other inflammatory patterns of disease. The recent identification of major immune-based disease patterns beginning in childhood suggests that the immune system may play an even more important role in determining health status and health care needs across a lifetime than was previously understood. Conclusions Focusing on patterns of disease, as opposed to individual conditions, offers two important venues for environmental health risk reduction. First, prevention of developmental immunotoxicity and pediatric immune dysfunction can be used to act against multiple diseases. Second, pattern-based treatment of entryway diseases can be tailored with the aim of disrupting the entire disease pattern and reducing the risk of later-life illnesses connected to underlying immune dysfunction. Disease-pattern–based evaluation, prevention, and treatment will require a change from the current approach for both immune safety testing and pediatric disease management.
Boltzmann brains and the scale-factor cutoff measure of the multiverse

To make predictions for an eternally inflating 'multiverse', one must adopt a procedure for regulating its divergent spacetime volume. Recently, a new test of such spacetime measures has emerged: normal observers - who evolve in pocket universes cooling from hot big bang conditions - must not be vastly outnumbered by 'Boltzmann brains' - freak observers that pop in and out of existence as a result of rare quantum fluctuations. If the Boltzmann brains prevail, then a randomly chosen observer would be overwhelmingly likely to be surrounded by an empty world, where all but vacuum energy has redshifted away, rather than the rich structure that we observe. Using the scale-factor cutoff measure, we calculate the ratio of Boltzmann brains to normal observers. We find the ratio to be finite, and give an expression for it in terms of Boltzmann brain nucleation rates and vacuum decay rates. We discuss the conditions that these rates must obey for the ratio to be acceptable, and we discuss estimates of the rates under a variety of assumptions.
Reversing deleterious protein aggregation with re-engineered protein disaggregases

Aberrant protein folding is severely problematic and manifests in numerous disorders, including amyotrophic lateral sclerosis (ALS), Parkinson disease (PD), Huntington disease (HD), and Alzheimer disease (AD). Patients with each of these disorders are characterized by the accumulation of mislocalized protein deposits. Treatments for these disorders remain palliative, and no available therapeutics eliminate the underlying toxic conformers. An intriguing approach to reverse deleterious protein misfolding is to upregulate chaperones to restore proteostasis. We recently reported our work to re-engineer a prion disaggregase from yeast, Hsp104, to reverse protein misfolding implicated in human disease. These potentiated Hsp104 variants suppress TDP-43, FUS, and α-synuclein toxicity in yeast, eliminate aggregates, reverse cellular mislocalization, and suppress dopaminergic neurodegeneration in an animal model of PD. Here, we discuss this work and its context, as well as approaches for further developing potentiated Hsp104 variants for application in reversing protein-misfolding disorders.
The Southern Flanking Fields of the 25 Orionis Group

The stellar group surrounding the Be (B1 Vpe) star 25 Ori was discovered to be a pre-main-sequence (PMS) population by the CIDA Variability Survey of Orion and subsequent spectroscopy. We analyze Sloan Digital Sky Survey multiepoch photometry to map the southern extent of the 25 Ori group and characterize its PMS population. We compare this group to the neighboring Orion OB1a and OB1b subassociations and to active star formation sites (NGC 2068/NGC 2071) within the LDN 1630 dark cloud. We find that the 25 Ori group has a radius of 1. °4, corresponding to 8-11 pc at the distances of Orion OB1a and OB1b. Given that the characteristic sizes of young open clusters are a few parsecs or less, this suggests that 25 Ori is an unbound association rather than an open cluster. Due to its PMS population having a low classical T Tauri star fraction (∼10%), we conclude that the 25 Ori group is of comparable age to the 11 Myr Orion OB1a subassociation.
Considering Alternate Futures to Classify Off-Task Behavior as Emotion Self-Regulation: A Supervised Learning Approach

Over the past decade, there has been growing interest in real-time assessment of student engagement and motivation during interactions with educational software. Detecting symptoms of disengagement, such as offtask behavior, has shown considerable promise for understanding students’ motivational characteristics during learning. In this paper, we investigate the affective role of off-task behavior by analyzing data from student interactions with CRYSTAL ISLAND , a narrative-centered learning environment for middle school microbiology. We observe that off-task behavior is associated with reduced student learning, but preliminary analyses of students’ affective transitions suggest that off-task behavior may also serve a productive role for some students coping with negative affective states such as frustration. Empirical findings imply that some students may use off-task behavior as a strategy for self-regulating negative emotional states during learning. Based on these observations, we introduce a supervised machine learning procedure for detecting whether students’ off-task behaviors are cases of emotion self-regulation. The method proceeds in three stages. During the first stage, a dynamic Bayesian network (DBN) is trained to model the valence of students’ emotion selfreports using collected data from interactions with the learning environment. In the second stage, a novel simulation process uses the DBN to generate alternate futures by modeling students’ affective trajectories as if they had engaged in fewer off-task behaviors than they did during their actual learning interactions. The alternate futures are compared to students’ actual traces to produce labels denoting whether students’ off-task behaviors are cases of emotion self-regulation. In the final stage, the generated emotion self-regulation labels are predicted using off-the-shelf classifiers and features that can be computed in run-time settings. Results suggest that this approach shows promise for identifying cases of off-task behavior that are emotion selfregulation. Analyses of the first two phases suggest that trained DBN models are capable of accurately modeling relationships between students’ off-task behaviors and self-reported emotional valence in CRYSTAL ISLAND . Additionally, the proposed simulation process produces emotion self-regulation labels with high levels of reliability. Preliminary analyses indicate that support vector machines, bagged trees, and random forests show promise for predicting the generated emotion self-regulation labels, but room for improvement remains. The findings underscore the methodological potential of considering alternate futures when modeling students’ emotion self-regulation processes in narrative-centered learning environments.
CC‐chemokine receptor 7 (CCR7) deficiency alters adipose tissue leukocyte populations in mice

The mechanism by which macrophages and other immune cells accumulate in adipose tissue (AT) has been an area of intense investigation over the past decade. Several different chemokines and their cognate receptors have been studied for their role as chemoattractants in promoting recruitment of immune cells to AT. However, it is also possible that chemoattractants known to promote clearance of immune cells from tissues to regional lymph nodes might be a critical component to overall AT immune homeostasis. In this study, we evaluated whether CCR7 influences AT macrophage (ATM) or T‐cell (ATT) accumulation. CCR7−/− and littermate wild‐type (WT) mice were placed on low‐fat diet (LFD) or high‐fat diet (HFD) for 16 weeks. CCR7 deficiency did not impact HFD‐induced weight gain, hepatic steatosis, or glucose intolerance. Although lean CCR7−/− mice had an increased proportion of alternatively activated ATMs, there were no differences in ATM accumulation or polarization between HFD‐fed CCR7−/− mice and their WT counterparts. However, CCR7 deficiency did lead to the preferential accumulation of CD8+ ATT cells, which was further exacerbated by HFD feeding. Finally, expression of inflammatory cytokines/chemokines, such as Tnf, Il6, Il1β, Ccl2, and Ccl3, was equally elevated in AT by HFD feeding in CCR7−/− and WT mice, while Ifng and Il18 were elevated by HFD feeding in CCR7−/− but not in WT mice. Together, these data suggest that CCR7 plays a role in CD8+ATT cell egress, but does not influence ATM accumulation or the metabolic impact of diet‐induced obesity.
Correlations in spontaneous activity and gray matter density between left and right sensoritmotor areas of pianists

Resting-state functional MRI and structural MRI were used to study correlations of spontaneous activity and gray matter density between the left and right primary sensorimotor areas in pianists and nonmusicians. Functional MRI analysis showed significant correlation of spontaneous activity between the left and right primary sensorimotor area in both groups; however, there was no between-group difference. Structural MRI analysis showed significant correlation in gray matter density between the left and right sensorimotor areas in nonmusicians (r=0.65, P=0.001), but not in pianists (r=0.07, P=0.78), with a significant between-group difference (P=0.035). The lack of correlation of gray matter density between the left and right sensorimotor areas might be the basis of bimanual coordination of the pianists.
Emotion classification of textual document using Emotion - Topic Model

The quick development of net a pair additional and additional documents are assigned by social users with feeling labels like happiness, sadness, and surprise. Such emotions will offer a replacement facet for document categorization, and so facilitate on- line users to pick out connected documents supported their emotional preferences. The quantitative relation with manual feeling labels remains terribly small comparison to the large quantity of web/enterprise documents. The connections between social feelings and emotive terms and supported that predict the social emotion from text content mechanically. A joint feeling- topic model by augmenting Latent Dirichlet Allocation with an extra layer for emotion modeling. It generates a group of latent topics from emotions, followed by generating emotive terms from every topic. Experimental results on a web news assortment show that the projected model will effectively determine substantive latent topics for every feeling. The analysis on feeling prediction any verifies the effectiveness of the projected model.
Low Complexity Synchronizer Using Common Autocorrelator for DVB-S2 System

This paper presents an efficient synchronizer architecture using a common autocorrelator for Digital Video Broadcasting via Satellite, Second generation (DVB-S2). To achieve the required performance under the worst channel condition and to implement the efficient H/W resource utilization of functional synchronization blocks, we propose a new efficient common autocorrelator structure. The proposed architecture can decrease about 92% of multipliers and 81% of adders compared with the direct implementation. Moreover, the proposed architecture has been thoroughly verified in XilinxTM Virtex IV and R&STM SFU (Signaling and Formatting Unit) broad-cast test equipment.
Phenotypic and Transcriptomic Response of Auxotrophic Mycobacterium avium Subsp. paratuberculosis leuD Mutant under Environmental Stress

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of severe gastroenteritis in cattle. To gain a better understanding of MAP virulence, we investigated the role of leuD gene in MAP metabolism and stress response. For this, we have constructed an auxotrophic strain of MAP by deleting the leuD gene using allelic exchange. The wildtype and mutant strains were then compared for metabolic phenotypic changes using Biolog phenotype microarrays. The responses of both strains to physiologically relevant stress conditions were assessed using DNA microarrays. Transcriptomic data was then analyzed in the context of cellular metabolic pathways and gene networks. Our results showed that deletion of leuD gene has a global effect on both MAP phenotypic and transcriptome response. At the metabolic level, the mutant strain lost the ability to utilize most of the carbon, nitrogen, sulphur, phosphorus and nutrient supplements as energy source. At the transcriptome level, more than 100 genes were differentially expressed in each of the stress condition tested. Systems level network analysis revealed that the differentially expressed genes were distributed throughout the gene network, thus explaining the global impact of leuD deletion in metabolic phenotype. Further, we find that leuD deletion impacted metabolic pathways associated with fatty acids. We verified this by experimentally estimating the total fatty acid content of both mutant and wildtype. The mutant strain had 30% less fatty acid content when compared to wildtype, thus supporting the results from transcriptional and computational analyses. Our results therefore reveal the intricate connection between the metabolism and virulence in MAP.