Miracle-dz/UniFAR-FTUs huggingface dataset:
Respiratory Syncytial Virus Infection of Human Airway Epithelial Cells Is Polarized, Specific to Ciliated Cells, and without Obvious Cytopathology

ABSTRACT Gene therapy for cystic fibrosis (CF) lung disease requires efficient gene transfer to airway epithelial cells after intralumenal delivery. Most gene transfer vectors so far tested have not provided the efficiency required. Although human respiratory syncytial virus (RSV), a common respiratory virus, is known to infect the respiratory epithelium, the mechanism of infection and the epithelial cell type targeted by RSV have not been determined. We have utilized human primary airway epithelial cell cultures that generate a well-differentiated pseudostratified mucociliary epithelium to investigate whether RSV infects airway epithelium via the lumenal (apical) surface. A recombinant RSV expressing green fluorescent protein (rgRSV) infected epithelial cell cultures with high gene transfer efficiency when applied to the apical surface but not after basolateral inoculation. Analyses of the cell types infected by RSV revealed that lumenal columnar cells, specifically ciliated epithelial cells, were targeted by RSV and that cultures became susceptible to infection as they differentiated into a ciliated phenotype. In addition to infection of ciliated cells via the apical membrane, RSV was shed exclusively from the apical surface and spread to neighboring ciliated cells by the motion of the cilial beat. Gross histological examination of cultures infected with RSV revealed no evidence of obvious cytopathology, suggesting that RSV infection in the absence of an immune response can be tolerated for >3 months. Therefore, rgRSV efficiently transduced the airway epithelium via the lumenal surface and specifically targeted ciliated airway epithelial cells. Since rgRSV appears to breach the lumenal barriers encountered by other gene transfer vectors in the airway, this virus may be a good candidate for the development of a gene transfer vector for CF lung disease.
The emergence of grammaticality in connectionist networks.

Linguistic theory in the generative tradition is based on a small number of simple but important observations about human languages and how they are acquired. First, the structure of language is extremely complex– so complex that it is often argued that it would be impossible to learn without prior knowledge as to its general character (Chomsky, 1965). Second, children learn languages rapidly and seemingly effortlessly. Although clearly limited with respect to other sorts of cognitive tasks, every normal child raised under normal circumstances learns the basic syntax of language within a few years of birth. Third, the world’s languages exhibit structural commonalities–so-called linguistic universals. Together, these observations have led many researchers to the conclusion that language involves domain-specific forms of knowledge that are largely innate. In the generative approach, the faculty of mind dedicated to language is called linguistic competence. A generative grammar is a formal description of this faculty, in the form of a system that generates the set of possible sentences of a given language, and thereby bestows on its possessor the ability to distinguish between grammatical and ungrammatical utterances. Grammars developed within this tradition (which we will call the standard approach) typically consist of primitives, operations, and principles intended to describe the knowledge of an idealized speaker/hearer in a homogeneous speech community. In this approach cognitive representations are hierarchically structured sets of symbols and cognitive processes are operations on them. Although the standard approach has been very successful in promoting the discovery of descriptive generalizations about linguistic structure and variation, it presents several problems when considered as the basis for a theory of how language is acquired and used. These problems arise from the competence-performance distinction that is one of the foundational assumptions of the approach. The distinction between what people know about language and what they do with that
Self‐Regulation in Health Behavior: Concepts, Theories, and Central Issues

Good health is of critical importance to many people while they are generally aware that their behavior plays an important role in achieving and maintaining physical well-being. In Western societies, it is difficult not knowing that one is, to some extent, responsible for one’s own health as people are continuously reminded of the importance of their behavior for staying healthy by both public health campaigns and medical care professionals (Brownell, 1991). Yet, even though good health is generally considered important, and many people have good intentions for health behavior, the vast majority report difficulties in consistently performing those behaviors. They may find it hard, for instance, to maintain a healthy diet or a pattern of regular exercise in the face of temptations of modern life (e.g., Rothman, Baldwin & Hertel, 2004). Changing a bad health habit seems even more difficult than maintaining a good one (Polivy & Herman, 2002; cf. Norcross, Ratzin & Payne, 1989). The proverbial road to hell does indeed seem to be paved with good intentions (cf. Powers, Koestner & Topciu, 2005). The question is: Why is it so difficult to act upon intentions or maintain attempts for changing health behavior, even for people who seem to be motivated? Only recently has the so-called ‘‘intention-behavior gap’’ started to attract substantial attention, and currently this is one of the most researched aspects of health behavior (e.g., Sheeran, 2002; Sheeran, Milne, Webb & Gollwitzer, 2005; also see Sheeran, Webb & Gollwitzer, this volume), and a crucial aspect of self-regulation. Selfregulation broadly refers to the processes of goal setting and goal striving, and includes dealing with a range of challenges that individuals may face when trying to achieve something that is important but, almost by definition, difficult to attain (Mischel, Cantor & Feldman, 1996). Important new questions arise from a self-regulation approach to health behavior, such as the following: How do people set health goals, and do they in fact
Testing concurrent programs using value schedules

Concurrent programs are difficult to debug and verify because of the nondeterministic nature of concurrent executions. A particular concurrency-related bug may only show up under certain rarely-executed thread interleavings. Therefore, commonly used debugging methodologies, such as inserting print statements, are no longer sufficient for uncovering concurrency-related bugs. However, many existing bug detection methods, such as dynamic analysis and model checking, have a very high computational cost. In this paper, we introduce a new technique for uncovering concurrency-related bugs from multithreaded Java programs. Our technique uncovers concurrency-related bugs by generating and testing read-write assignment sequences, referred to as value schedules, of a multithreaded Java program. Our value-schedule-based technique distinguishes itself in its ability to avoid exploring superfluous program state space caused by speculative permutation on transitions. Therefore, our technique can achieve a higher degree of POR (Partial Order Reduction) than existing methods. We demonstrate our technique using some programs, with an implementation built using an explicit state model checker called JPF
Application of the self-organising map to trajectory classification

This paper presents an approach to the problem of automatically classifying events detected by video surveillance systems; specifically, of detecting unusual or suspicious movements. Approaches to this problem typically involve building complex 3D-models in real-world coordinates to provide trajectory information for the classifier. We show that analysis of trajectories may be carried out in a model-free fashion, using self-organising feature map neutral networks to learn the characteristics of normal trajectories, and to detect novel ones. Trajectories are represented in 2D image coordinates. First and second order motion information is also generated, with moving-average smoothing. This allows novelty detection to be applied on a point-by-point basis in real time, and permits both instantaneous motion and whole trajectory motion to be subjected to novelty detection.
A 63-mA 112/94-dB DR IF bandpass ΔΣ modulator with direct feed-forward and double sampling

We developed a 10.7-MHz intermediate frequency (IF) bandpass discrete-time (DT) 4<sup>th</sup> -order 4-bit ΔΣ modulator for AM/FM car radio tuners. Using direct feed-forward and double sampling, we have achieved a dynamic range (DR) of 112 dB in the 3-kHz AM bandwidth (BW) and a DR of 94 dB in the 200-kHz FM BW. The modulator occupies 3 mm<sup>2</sup>, in 0.15 μm CMOS technology, and draws 63 mA of current.
A Partial Bandwidth Reservation Scheme for QoS Support in Ad Hoc Networks

With the fast development of information technology, the application environment and multimedia services in Ad Hoc networks, all of these are needed to support QoS, and bandwidth is the one of key points needed to be considered. In this paper, we propose a partial bandwidth reservation scheme adapted to reactive routing protocol. In each node, it can estimate available bandwidth in real time, and introduce access control scheme to meet services QoS metric. Simulations integrated with DSR protocol show that this partial bandwidth reservation scheme proposed has improved network capability, and provided QoS support for network services in a certain extent.
Geovisual Analytics Approach to Exploring Public Political Discourse on Twitter

We introduce spatial patterns of Tweets visualization (SPoTvis), a web-based geovisual analytics tool for exploring messages on Twitter (or “tweets”) collected about political discourse, and illustrate the potential of the approach with a case study focused on a set of linked political events in the United States. In October 2013, the U.S. Congressional debate over the allocation of funds to the Patient Protection and Affordable Care Act (commonly known as the ACA or “Obamacare”) culminated in a 16-day government shutdown. Meanwhile the online health insurance marketplace related to the ACA was making a public debut hampered by performance and functionality problems. Messages on Twitter during this time period included sharply divided opinions about these events, with many people angry about the shutdown and others supporting the delay of the ACA implementation. SPoTvis supports the analysis of these events using an interactive map connected dynamically to a term polarity plot; through the SPoTvis interface, users can compare the dominant subthemes of Tweets in any two states or congressional districts. Demographic attributes and political information on the display, coupled with functionality to show (dis)similar features, enrich users’ understandings of the units being compared. Relationships among places, politics and discourse on Twitter are quantified using statistical analyses and explored visually using SPoTvis. A two-part user study evaluates SPoTvis’ ability to enable insight discovery, as well as the tool’s design, functionality and applicability to other contexts.
Benefit of transferred mutations is better predicted by the fitness of recipients than by their ecological or genetic relatedness

Significance The fitness effect of many mutations depends on the genotype of the individual in which they occur. Are these dependencies predictable? Do dependencies build on existing variation between individuals to promote divergence, or do they act to favor genetic cohesion? We examine these questions by measuring the fitness effect of mutations that conferred a benefit in a laboratory-evolved population when transferred into genetically and phenotypically diverse natural isolates of the same species. We found that fitness effects were predicted by the fitness of the strain to which they were added but not by the genetic or ecological relationship of the recipient strains. This pattern extends findings that the current fitness of strain is a major predictor of its ability to adapt. The effect of a mutation depends on its interaction with the genetic background in which it is assessed. Studies in experimental systems have demonstrated that such interactions are common among beneficial mutations and often follow a pattern consistent with declining evolvability of more fit genotypes. However, these studies generally examine the consequences of interactions between a small number of focal mutations. It is not clear, therefore, that findings can be extrapolated to natural populations, where new mutations may be transferred between genetically divergent backgrounds. We build on work that examined interactions between four beneficial mutations selected in a laboratory-evolved population of Escherichia coli to test how they interact with the genomes of diverse natural isolates of the same species. We find that the fitness effect of transferred mutations depends weakly on the genetic and ecological similarity of recipient strains relative to the donor strain in which the mutations were selected. By contrast, mutation effects were strongly inversely correlated to the initial fitness of the recipient strain. That is, there was a pattern of diminishing returns whereby fit strains benefited proportionally less from an added mutation. Our results strengthen the view that the fitness of a strain can be a major determinant of its ability to adapt. They also support a role for barriers of transmission, rather than differential selection of transferred DNA, as an explanation of observed phylogenetically determined patterns of restricted recombination among E. coli strains.
ASSESSING THE POTENTIAL OF USING VALUE-ADDED ESTIMATES OF TEACHER JOB PERFORMANCE FOR MAKING TENURE DECISIONS*

Reforming teacher tenure is an idea that appears to be gaining traction with the underlying assumption being that one can infer to a reasonable degree how well a teacher will perform over her career based on estimates of her early-career effectiveness. Here we explore the potential for using value-added models to estimate performance and inform tenure decisions. We find little evidence that the variation of teacher effects change over teacher careers, but strong evidence that prior year estimates of job performance predict student achievement, even when there is a multi-year lag between the two.
Unsupervised Storyline Extraction from News Articles

Storyline extraction from news streams aims to extract events under a certain news topic and reveal how those events evolve over time. It requires algorithms capable of accurately extracting events from news articles published in different time periods and linking these extracted events into coherent stories. The two tasks are often solved separately, which might suffer from the problem of error propagation. Existing unified approaches often consider events as topics, ignoring their structured representations. In this paper, we propose a non-parametric generative model to extract structured representations and evolution patterns of storylines simultaneously. In the model, each storyline is modelled as a joint distribution over some locations, organizations, persons, keywords and a set of topics. We further combine this model with the Chinese restaurant process so that the number of storylines can be determined automatically without human intervention. Moreover, per-token Metropolis-Hastings sampler based on light latent Dirichlet allocation is employed to reduce sampling complexity. The proposed model has been evaluated on three news corpora and the experimental results show that it outperforms several baseline approaches.
Transistor abstraction for the functional verification of FPGAs

This paper discusses the use of transistor abstraction to enable the functional verification of FPGA fabrics with RTL models. It first describes the multiplexer structures that are used on a massive scale in FPGAs and the specific challenges that they pose to transistor abstraction tools. It then reviews previous approaches and shows that the cone model of the DESB system is particularly well suited to abstract FPGA logic because it makes pass-gate branches in multiplexer structures well apparent. Based on this model, methods are described to isolate multiplexer structures, take into account logic correlation between signals, and generate RTL models that are both simulation efficient and highly readable. Finally, Altera's ABX tool that implements these concepts is briefly described
Point spread function calibration requirements for dark energy from cosmic shear

Context. The control of systematic effects when measuring background galaxy shapes is one of the main challenges for cosmic shear analyses. Aims. Study the fundamental limitations on shear accuracy due to the measurement of the point spread function (PSF) from the finite number of stars that are available. We translate the accuracy required for cosmological parameter estimation to the minimum number of stars over which the PSF must be calibrated. Methods. We characterise the error made in the shear arising from errors on the PSF. We consider different PSF models, from a simple elliptical Gaussian to various shapelet parametrisations. First we derive our results analytically in the case of infinitely small pixels (i.e. infinitely high resolution), then image simulations are used to validate these results and investigate the effect of finite pixel size in the case of the elliptical Gaussian PSF. Results. Our results are expressed in terms of the minimum number of stars required to calibrate the PSF in order to ensure that systematic errors are smaller than statistical errors when estimating the cosmological parameters. On scales smaller than the area containing this minimum number of stars, there is not enough information to model the PSF. This means that these small scales should not be used to constrain cosmology unless the instrument and the observing strategy are optimised to make this variability extremely small. The minimum number of stars varies with the square of the star Signal-to-Noise Ratio, with the complexity of the PSF and with the pixel size. In the case of an elliptical Gaussian PSF and in the absence of dithering, 2 pixels per PSF full width at half maximum (FWHM) implies a 20% increase of the minimum number of stars compared to the ideal case of infinitely small pixels; 0.9 pixels per PSF FWHM implies a factor 100 increase. Conclusions. In the case of a good resolution and a typical Signal-to-Noise Ratio distribution of stars, we find that current surveys need the PSF to be calibrated over a few stars, which may explain residual systematics on scales smaller than a few arcmins. Future all-sky cosmic shear surveys require the PSF to be calibrated over a region containing about 50 stars. Due to the simplicity of our models these results should be interpreted as optimistic and therefore provide a measure of a systematic “floor’ intrinsic to shape measurements.
Role of the CCAAT-Binding Protein NFY in SCA17 Pathogenesis

Spinocerebellar ataxia 17 (SCA17) is caused by expansion of the polyglutamine (polyQ) tract in human TATA-box binding protein (TBP) that is ubiquitously expressed in both central nervous system and peripheral tissues. The spectrum of SCA17 clinical presentation is broad. The precise pathogenic mechanism in SCA17 remains unclear. Previously proteomics study using a cellular model of SCA17 has revealed reduced expression of heat shock 70 kDa protein 5 (HSPA5) and heat shock 70 kDa protein 8 (HSPA8), suggesting that impaired protein folding may contribute to the cell dysfunction of SCA17 (Lee et al., 2009). In lymphoblastoid cells, HSPA5 and HSPA8 expression levels in cells with mutant TBP were also significantly lower than that of the control cells (Chen et al., 2010). As nuclear transcription factor Y (NFY) has been reported to regulate HSPA5 transcription, we focused on if NFY activity and HSPA5 expression in SCA17 cells are altered. Here, we show that TBP interacts with NFY subunit A (NFYA) in HEK-293 cells and NFYA incorporated into mutant TBP aggregates. In both HEK-293 and SH-SY5Y cells expressing TBP/Q(61~79), the level of soluble NFYA was significantly reduced. In vitro binding assay revealed that the interaction between TBP and NFYA is direct. HSPA5 luciferase reporter assay and endogenous HSPA5 expression analysis in NFYA cDNA and siRNA transfection cells further clarified the important role of NFYA in regulating HSPA5 transcription. In SCA17 cells, HSPA5 promoter activity was activated as a compensatory response before aggregate formation. NFYA dysfunction was indicated in SCA17 cells as HSPA5 promoter activity reduced along with TBP aggregate formation. Because essential roles of HSPA5 in protection from neuronal apoptosis have been shown in a mouse model, NFYA could be a target of mutant TBP in SCA17.
Matrix Covariance Estimation methods for robust Security Speech Recognition with under-resourced conditions

The long term goal of our project is the development of robust Security Speech Recognition systems are based on Automatic Speech Recognition methodologies. The development of ASR systems involves dealing with issues such as Acoustic Phonetic Decoding (APD), Language Modelling (LM) or the development of appropriated Language Resources (LR). Thus these applications are generally very language-dependent and require very large resources. This work is focused to the selection of appropriated sub-word units with under-resourced and noisy conditions oriented to security tasks. The work has been carried out with a trilingual internet radio database. Thus, in order to decrease the negative impact that the lack of resources has in this issue we apply several data optimization methodologies based on Matrix Covariance Estimation and Ontology-based approaches.
Weibull Statistical Reliability Analysis of Mechanical and Magnetic Properties of FeCuNbxSiB Amorphous Fibers

Glass-coated Fe76.5−xCu1NbxSi13.5B9 (x = 0, 1, 2, 3, 3.5) fibers were successfully fabricated by a modified Taylor method. The fibers showed circular morphology and smooth surface with different diameters. The mechanical properties of the fibers were evaluated and the Weibull statistical analysis has been introduced to characterize the strength reliability of the fibers, with the modulus m of the amorphous fibers reaching above 20. The magnetic properties were also studied. Lower coercivity was found for the fibers with amorphous, nanocrystalline, and microcrystalline structures rather than that for the coarse crystalline ones. The glass-coated FeCuNbSiB amorphous fibers have excellent comprehensive performance compared with the other kind of fibers.
Relationship Between Systems Coaching and Problem-Solving Implementation Fidelity in a Response-to-Intervention Model

ABSTRACT The literature on RTI has indicated that professional development and coaching are critical to facilitating problem-solving implementation with fidelity. This study examined the extent to which systems coaching related to the fidelity of problem-solving implementation in 31 schools from six districts. Schools participated in three years of a state-level professional development initiative to implement RTI practices. Each school received ongoing coaching through job-embedded training, technical assistance, and evaluation support. Data on quality of coaching received, continuity of coaching (i.e., coaching provided by the same individual over time), changes in educator beliefs and perceived skills, and problem-solving implementation fidelity were examined through multilevel modeling (MLM) procedures. Results indicated that coaching continuity positively related to RtI implementation fidelity. Implications for systems coaching practices to support problem-solving and RTI implementation are discussed.