Miracle-dz/UniFAR-FTUs huggingface dataset:
Telecollaborative Desktop-Videoconferencing Exchange: The Case of Mark.

This presentation is a case study of the Intercultural Communicative Competence (ICC) development of Mark, one of ten American students engaged in a desktop-videoconferencing telecollaborative exchange with a class of French students. Due in part to its inherent complexity, this context has not been widely researched. To observe ICC development, I used a combination of a priori categories based on the "Attitude" component of Byram's (1997) model, that is, the willingness to show value to one's partner or relativize one's self, and a set of emerging themes (Boyatzis, 1998) gathered from the data. The video-recorded sessions are analyzed in conjunction with data from background surveys, autobiographies, journal entries, and email exchanges. This methodology sheds light on the behavioral choices of a participant who, despite a high level of engagement and motivation, does not appear to take advantage of the exchange for the purpose of ICC development, a behavior that I noticed in other members of his class. While linguistic development can be observed, there is little display of "self-relativizing" and "valuing others" (Byram, 1997, p. 34). These results raise the question of how the methodology could be modified to better foster ICC development in students like Mark, or whether it is even possible to reach this goal within such a mediated environment.
FilmArray, an Automated Nested Multiplex PCR System for Multi-Pathogen Detection: Development and Application to Respiratory Tract Infection

The ideal clinical diagnostic system should deliver rapid, sensitive, specific and reproducible results while minimizing the requirements for specialized laboratory facilities and skilled technicians. We describe an integrated diagnostic platform, the “FilmArray”, which fully automates the detection and identification of multiple organisms from a single sample in about one hour. An unprocessed biologic/clinical sample is subjected to nucleic acid purification, reverse transcription, a high-order nested multiplex polymerase chain reaction and amplicon melt curve analysis. Biochemical reactions are enclosed in a disposable pouch, minimizing the PCR contamination risk. FilmArray has the potential to detect greater than 100 different nucleic acid targets at one time. These features make the system well-suited for molecular detection of infectious agents. Validation of the FilmArray technology was achieved through development of a panel of assays capable of identifying 21 common viral and bacterial respiratory pathogens. Initial testing of the system using both cultured organisms and clinical nasal aspirates obtained from children demonstrated an analytical and clinical sensitivity and specificity comparable to existing diagnostic platforms. We demonstrate that automated identification of pathogens from their corresponding target amplicon(s) can be accomplished by analysis of the DNA melting curve of the amplicon.
8 dyon partition function and walls of marginal stability

We construct the partition function of 1/8 BPS dyons in type II string theory on T6 from counting of microstates of a D1-D5 system in Taub-NUT space. Our analysis extends the earlier ones by Shih, Strominger and Yin and by Pioline by taking into account the walls of marginal stability on which a 1/8 BPS dyon can decay into a pair of half-BPS dyons. Across these walls the dyon spectrum changes discontinuously, and as a result the spectrum is not manifestly invariant under S-duality transformation of the charges. However the partition function is manifestly S-duality invariant and takes the same form in all domains of the moduli space separated by walls of marginal stability, the spectra in different domains being obtained by choosing different integration contours along which we carry out the Fourier transform of the partition function. The jump in the spectrum across a wall of marginal stability, calculated from the behaviour of the partition function at an appropriate pole, reproduces the expected wall crossing formula.
Active Listening and Counselor Self-Efficacy

Abstract By emphasizing active listening over the other microskills, it is hypothesized that beginning counselors will feel more efficacious and better able to hear clients, thus performing better in skill areas. In this pilot study with five Master's-level counselor trainees in their first counseling practicum, an emphasis on active listening in instruction and individual supervision resulted in increases in active listening and self-efficacy ratings, as well as performance in three skill areas (reflection of feelings, challenging, and immediacy). These results suggest the importance of attending to counselors' strengths and reducing anxiety in the first counseling experience.
Classroom assessment within the alternative assessment paradigm: revisiting the territory

Assessment reform has been on the educational agenda of many countries for at least two decades. In this article—which begins by charting what lies behind the calls for a paradigm shift in assessment and what is being proposed instead—classroom assessment is explored in detail in relation to its links with teacher and student assessment, as well as with formative and summative assessment. The emerging notion that classroom assessment embodies all forms of assessment that take place within the confines of the classroom is subsequently analysed from an ‘assessment for learning’ perspective, which is increasingly being accepted as the way forward if teaching, learning and assessment are to become fully integrated as demanded by the underlying philosophy of the new, alternative paradigm. However, noting the gross difficulties facing the translation of new policies into classroom practices, the article finally suggests what can be done to rectify this certainly frustrating, but also potentially dangerous, situation.
ChatterCrop: Reaping the benefits of online product reviews

Web 2.0 has allowed online shoppers to become not just information seekers but also information providers. Many e-commerce venues allow users to share their experiences in the form of textual product reviews. While textual product reviews represent a wealth of information for candidate buyers, finding pertinent information becomes difficult, as the number of reviews for a particular product becomes large, or if the buyer is interested in particular features of an item. We present ChatterCrop, a tool that uses text summarization. ChatterCrop condenses the information from a large set of reviews into a few sentences, and allows users to customize these summaries for feature-focused search. In a user study, subjects used ChatterCrop and a sortable list of reviews, to answer questions about two camcorder models. When looking for information about particular features, ChatterCrop outperformed the list, in terms user confidence and perceived ease in finding pertinent information. ChatterCrop's summaries also provided users with starting points to guide further research, and were particularly helpful in the early stages of sensemaking.
Hierarchical Coordinated Control Method for Unmanned Robot Applied to Automotive Test

The paper describes application of unmanned robot applied to automotive test (URAT) to save time, costs, and to improve accuracy of tests. A hierarchical coordinated control method based on fuzzy logic theory is proposed for URAT, to realize the coordinated control and the accurate speed tracking of driving test cycle during all kinds of conditions. The system structure is briefly described in the paper. Similar to a skilled human driver, a control method based on Saridis hierarchical architecture to coordinate multiple robot manipulators systems for the automotive test system is presented. The coordinated movements for throttle mechanical leg, clutch mechanical leg, brake mechanical leg are designed. On top of that, the fuzzy speed controller for URAT is used to accurately track the desired vehicle velocity under different test conditions. Experiments have been conducted by using a Ford FOCUS car. The proposed control method of URAT is experimentally proved and compared with other control methods and with human driver performances.
Analysis of Joint Call Admission Control Strategies for Heterogeneous Cellular Networks

This paper investigates three joint call admission control algorithms (JCAC) for heterogeneous cellular networks. These algorithms are random-selection-based, service-based, and load-based JCAC algorithms. Our approach is based on decomposing heterogeneous cellular networks into groups of co-located cells. We model the JCAC algorithms as a multi-dimensional Markov chain. For each of the three JCAC algorithms, new call blocking probability and handoff call probability are derived and evaluated. The performances of the three JCAC algorithms are compared and the results are presented.
Finite-scale equations for compressible fluid flow

Finite-scale equations (FSE) describe the evolution of finite volumes of fluid over time. We discuss the FSE for a one-dimensional compressible fluid, whose every point is governed by the Navier–Stokes equations. The FSE contain new momentum and internal energy transport terms. These are similar to terms added in numerical simulation for high-speed flows (e.g. artificial viscosity) and for turbulent flows (e.g. subgrid scale models). These similarities suggest that the FSE may provide new insight as a basis for computational fluid dynamics. Our analysis of the FS continuity equation leads to a physical interpretation of the new transport terms, and indicates the need to carefully distinguish between volume-averaged and mass-averaged velocities in numerical simulation. We make preliminary connections to the other recent work reformulating Navier–Stokes equations.
Edge-aware depth completion for point-cloud 3D scene visualization on an RGB-D camera

Nowadays, 3D scene reconstruction using RGB-D videos becomes more popular because of the widely-available off-the-shelf RGB-D camera. However, the depth information from current RGB-D camera still need improved in order to reconstruct the 3D scene with better quality. In this paper, an edge-aware depth completion method aims to recover more accurate depth information is proposed. There are mainly two parts in our proposed method. The first part is the edge-aware color image analysis, and the second part is depth image processing including unreliable depth pixel invalidation and filling. The depth image processing can retrieve more accurate depth information using our proposed edge-aware color image analysis. Consequently, we can not only preserve the reliable depth information, but also fill in the appropriate depth values to align edges of depth image with edges of its corresponding color image. Besides, the experimental results show that the visualization of the reconstructed point-cloud 3D scene benefits from our proposed edge-aware depth completion. Finally, the PSNR evaluation using ground truth depth information is presented.
Real-time Character Posing Using Millions of Natural Human Poses

We present intuitive interfaces for interactively posing 3D human characters. The user can create desired fullbody poses by directly dragging points, modifying bone directions, or specifying distances between two points in 2D screen space. Designing such an interface for full-body pose modeling is challenging because many unnatural poses might be consistent with the ambiguous user input. The system automatically learns a pose prior from a huge database which contains about 2.8 million prerecorded poses and uses it to remove the ambiguity. We formulate the problem in a maximum a posteriori (MAP) framework by combining the prior with user-defined constraints. Maximizing the posterior allows us to generate an optimal and natural full-body pose that satisfies the user-defined constraints. Our system runs in real time; it is also simple and easy to use. We evaluate the performance of our approach with cross validation tests and compare with alternative techniques for character posing.
Optical sensing of square lattice photonic crystal point-shifted nanocavity for protein adsorption detection

We propose a point-shifted D0 nanocavity formed by locally modulating four central air holes in square lattice photonic crystal for optical sensing application. Three defect modes in this nanocavity, including monopole, whispering-gallery, and dipole modes, are identified in experiments. We also apply a chemical treatment on InGaAsP surface to form a 1-octadecanethiol linking monolayer, which enables the following protein adsorption. In experiments, the wavelength shifts of lasing modes in the D0 nanocavity due to the protein adsorption are observed and agree with the simulation results. This can be a practical tool for label-free molecule detection in biomedical researches.
Departing toward Survival: Reconsidering the Language of Trauma in Cathy Caruth, Ingeborg Bachmann and W. G. Sebald

Little has been said in trauma studies about the ability or inability of traumatized characters de-picted by traumatized writers to recover accounts of self from the aseptic reiterations of a language unable to articulate the unspeakable event of trauma. This paper argues that Cathy Caruth’s recent emphasis upon a “language of ashes”—derived from a “language of the life drive” departing from a “language of the death drive”—provides a framework for examining the extent to which traumatized textualities are able to apprehend their seeming enervating repetitions of the death drive as textual constructs able to be written on and read. I posit that the literary characters in the fictions of Ingeborg Bachmann and W. G. Sebald occupy opposing ends of the ambit of the life and death drives, and aver that the contrasting ways they perform the repetitiveness of personal and/or national trauma come close to enacting, respectively, the languages of the “death drive” and the “life drive”. I demonstrate the extent to which they are able to extricate the language used from their singular historical experiences of trauma. In this way, I argue that Caruth’s attempt to identify the site within history where trauma can be creatively animated sets a productive framework for examining how trauma can either metabolize an individual into foreclosing the world, or create a continuing dialogue with loss for the unfolding of a world-in-becoming.
The Concept of Generalization in Behaviour Therapy

Several writers have been interested in the extent to which behaviour therapy techniques are derived from the principles of learning. The present paper reviews this issue with respect to stimulus generalization and response generalization in behaviour therapy. Generalization has been a problem because many therapists have reported that newly learned skills and behaviours have not transferred outside the treatment situation to settings in the patients' or clients' life. Reviewing the literature on stimulus generalization it is concluded that in research on learning theory, stimulus generalization is shown to occur along a single stimulus dimension while in the behaviour therapy literature researchers often attempt to produce generalization across many stimulus dimensions simultaneously and as a result generalization may be poor. It is suggested that subsequent therapy and research should be designed so that treatment situations and generalization situations differ on as few stimulus dimensions as possible, thus maximizing the probability of generalization. With respect to response generalization it is felt that the concept is weak as an explanation for behaviour change and it may be more useful to consider that behaviours are functionally related, so that changes in behaviour A will produce changes in behaviour B or that covert responses may account for changes in untreated behaviours. Finally, a recommendation is made that therapists be more precise about the stimulus dimensions along which they wish behaviour to generalize.
Association of SCN1A gene polymorphism with antiepileptic drug responsiveness in the population of Thrace, Greece

Introduction The aim was to examine the influence of the SCN1A gene polymorphism IVS5-91 rs3812718 G>A on the response to antiepileptic drugs (AEDs) in monotherapy or polytherapy. Material and methods Two hundred epilepsy patients and 200 healthy subjects were genotyped for SCN1A IVS5-91 rs3812718 G>A polymorphism using TaqMan assay. Patients were divided into drug-responsive and drug-resistant patients. The drug-responsive group was further studied, comparing monotherapy in maximum and minimum doses and monotherapy-responsive and -resistant groups. Results There were no statistically significant differences in the allelic frequencies and genotype distributions between patients and controls (p = 0.178). The distribution of SCN1A IVS5-91 rs3812718 G>A genotypes was similar between drug-responsive and drug-resistant patients (p = 0.463). The differences in genotype distributions (A/A or A/G vs. G/G) between monotherapy-responsive and -resistant groups were statistically significant (p = 0.021). Within the monotherapy-responsive group, patients with the A/A or A/G genotype needed higher dose AEDs than patients with the G/G genotype (p = 0.032). The relative risk for generalized epilepsy due to A-containing genotypes was of marginal statistical significance when compared with the G/G genotype (p = 0.05). Conclusions Overall, our findings demonstrate an association of SCN1A IVS5-91 rs3812718 G>A polymorphism with AED responsiveness in monotherapy without evidence of an effect on drug-resistant epilepsy.
Accurate Image Search Using the Contextual Dissimilarity Measure

This paper introduces the contextual dissimilarity measure, which significantly improves the accuracy of bag-of-features-based image search. Our measure takes into account the local distribution of the vectors and iteratively estimates distance update terms in the spirit of Sinkhorn's scaling algorithm, thereby modifying the neighborhood structure. Experimental results show that our approach gives significantly better results than a standard distance and outperforms the state of the art in terms of accuracy on the Nisteacuter-Steweacutenius and Lola data sets. This paper also evaluates the impact of a large number of parameters, including the number of descriptors, the clustering method, the visual vocabulary size, and the distance measure. The optimal parameter choice is shown to be quite context-dependent. In particular, using a large number of descriptors is interesting only when using our dissimilarity measure. We have also evaluated two novel variants: multiple assignment and rank aggregation. They are shown to further improve accuracy at the cost of higher memory usage and lower efficiency.
Comparative Kinetic Studies and Performance Evaluation of Biofilm and Biomass Characteristics of Pseudomonas fluorescens in Degrading Synthetic Phenolic Effluent in Inverse Fluidized Bed Biofilm Reactor

The bioremediation potential of Pseudomonas fluorescens was studied in an Inverse Fluidized Bed Biofilm Reactor under batch recirculation conditions using synthetic phenolic effluent of various concentrations (400, 600, 800, 1000 and 1200 mg/l). The performance of the reactor was investigated and the characteristics of biomass and biofilm were determined by evaluating biofilm dry density and thickness, bioparticle density, suspended and attached biomass concentration, chemical oxygen demand and phenol removal efficiency. Biodegradation kinetics had been studied for suspended biomass culture and biofilm systems with respect to its specific growth and substrate consumption rates. Suspended biomass followed substrate inhibition kinetics and the experimental data fitted well with the Haldane model. The degradation kinetic behavior of biofilm revealed that a well adapted biofilm system with effective control of biofilm thickness in an inverse fluidized bed biofilm reactor overcomes substrate inhibition effects by tolerating higher phenol concentration and fitted well to the Monod model.
Quantitative proteomics and biomarker discovery in human cancer

“Early diagnosis and prevention is a key factor in reducing the mortality and morbidity of cancer. However, currently available screening tools lack enough sensitivity for early diagnosis. It is important to develop noninvasive techniques and methods that can screen and identify asymptomatic patients who have cancer. Biomarkers of cancer status can also serve as powerful tools in monitoring the course of cancer, and in determining the efficacy and safety of novel therapies. Thus, discovery of novel specific biomarkers are needed that may provide informative clues for early diagnosis and treatment of cancer. Recently, remarkable progress has been made in the development of new proteomics technology. The progress that has been made in this field is helpful in identifying biomarkers that can be used for early diagnosis of cancer and improving the understanding of the molecular etiological mechanism of cancer. This article describes the current state of the art in this field. ”
Robust Clustering for Tracking Noisy Evolving Data Streams

We present a new approach for tracking evolving and noisy data streams by estimating clusters based on density, while taking into account the possibility of the presence of an unknown amount of outliers, the emergence of new patterns, and the forgetting of old patterns. keywords: evolving data streams, robust clustering, dynamic clustering, stream clustering, scalable clustering
Social Stratification in Recreational Fishing Participation: Research and Policy Implications

Using the multiple stratification hierarchy perspective, this study examined the combined effects of age, race and ethnicity, gender, and socioeconomic status on recreational fishing. Sample data from 3,000 Texas residents were used to develop logistic regression models corresponding to three dependent variables for fishing participation. The dependent variables were measures of participation ever, in the past 5 years, and in the past 12 months. Gender, race/ethnicity, and age were the most consistent predictors across the three dependent variables. Gender and age exhibited a negative effect on fishing participation across the three models. Results for race/ethnicity were mixed. An analysis of predicted probabilities did not reveal strong evidence of a multiple stratification hierarchy in recreational fishing. The article concludes with implications associated with angler recruitment.
Simulating gaze attention behaviors for crowds

Crowd animation is a topic of high interest which offers many challenges. One of the most important is the trade‐off between rich, realistic behaviors, and computational costs. To this end, much effort has been put into creating variety in character representation and animation. Nevertheless, one aspect still lacking realism in virtual crowd characters resides in their attention behaviors. In this paper, we propose a framework to add gaze attention behaviors to crowd animations. First, we automatically extract interest points from character or object trajectories in pre‐ existing animations. For a given character, we assign a set of elementary scores based on parameters such as distance or speed to all other characters or objects in the scene. We then combine these subscores in an overall scoring function. The scores obtained from this function form a set of gaze constraints that determine where and when each character should look. We finally enforce these constraints with an optimized dedicated gaze Inverse Kinematics (IK) solver. It first computes the displacement maps for the constraints to be satisfied. It then smoothly propagates these displacements over an automatically defined number of frames. We demonstrate the efficiency of our method and our visually convincing results through various examples. Copyright © 2009 John Wiley & Sons, Ltd.