Miracle-dz/UniFAR-FTUs huggingface dataset:
Orchestrating a multi-tabletop classroom: from activity design to enactment and reflection

If multi-tabletop classrooms were available in each school, how would teachers plan and enact their activities to enhance learning and collaboration? How can they evaluate how the activities actually went compared with the plan? Teachers' effectiveness in orchestrating the classroom has a direct impact on students learning. Interactive tabletops offer the potential to support teachers by enhancing their awareness and classroom control. This paper describes our mechanisms to help a teacher orchestrate a classroom activity using multiple interactive tabletops. We analyse automatically captured interaction data to assess whether the activity design, as intended by the teacher, was actually followed during its enactment. We report on an authentic classroom study embedded in the curricula of an undergraduate Management unit. This involved 236 students across 14 sessions. The main contribution of the paper is an approach for designing a multi-tabletop classroom that can help teachers plan their learning activities; and provide data for assessment and reflection on the enactment of a series of classroom sessions.
On the performance of spatial multiplexing MIMO cellular systems with adaptive modulation and scheduling

We analyze the forward link spectral efficiency (SE) of a spatial multiplexing cellular MIMO system using adaptive modulation and scheduling (opportunistic and proportional fair). With the channel state information (CSI) available only at the receiver side, the minimum mean square error (MMSE)-based ordered successive interference cancellation is employed for detection with either forward or reverse ordering. When the channel state information (CSI) is available at the transmitter, separate channels are obtained via singular value decomposition (SVD) of the channel matrix. The post processing SNR for each stream is fed back to the transmitter to adapt the modulation level corresponding to each stream. The multi-user diversity gain due to scheeduling is observed to be very significant especially without power control. The SE gain from the SVD scheme becomes negligible in a high SNR region which would not justify the complexity of having the CSI at the transmitter. The proportional fair scheduling is a good choice to compromise SE and fairness when the average channel conditions of users are different.
Bayesian fusion of hidden Markov models for understanding bimanual movements

Understanding hand and body gestures is a part of a wide spectrum of current research in computer vision and human-computer interaction. A part of this can be the recognition of movements in which the two hands move simultaneously to do something or imply a meaning. We present a Bayesian network for fusing hidden Markov models in order to recognise a bimanual movement. A bimanual movement is tracked and segmented by a tracking algorithm. Hidden Markov models are assigned to the segments in order to learn and recognize the partial movement within each segment. A Bayesian network fuses the HMMs in order to perceive the movement of the two hands as a single entity.
Thermobonding Behaviour of Polypropylene and Other Fibres

An investigation is reported in which a new fibre-loop test, developed earlier for a flexible thermomechanical analyser (FTMA), was used with varying conditions of time, temperature, and tension to assess the thermobonding responses of three different grades of polypropylene fibre and one of copolyester fibre. Heating and cooling rates were rapid to correspond with commercial practice, and scanning electron micrographs were taken of the bonded loops. Conditions for optimum bond strength are determined.
Comprehensive assessment of pain in juvenile rheumatoid arthritis: an empirical model.

A comprehensive assessment model of variables hypothesized to influence pediatric pain perception was empirically investigated in 23 families who had a child with juvenile rheumatoid arthritis. To determine the effects of family environment, child psychological adjustment, and disease parameters on child pain perception, a developmental^ appropriate model was developed. Children between the ages of 5 and 15 were found to be reliable judges of their pain intensity. Several family environmental and child psychological factors were found to interact with specific disease parameters in determining pediatric pain perception and report. A multidimensional age-appropriate assessment model is suggested for use in the further examination of pediatric chronic and recurrent pain.
The Importance of Ideas: An A Priori Critical Juncture Framework

Abstract. This paper sets out an improved framework for examining critical junctures. This framework, while rigorous and broadly applicable and an advance on the frameworks currently employed, primarily seeks to incorporate an a priori element. Until now the frameworks utilized in examining critical junctures were entirely postdictive. Adding a predictive element to the concept will constitute a significant advance. The new framework, and its predictive element, termed the “differentiating factor,” is tested here in examining macro-economic crises and subsequent changes in macro-economic policy, in America and Sweden. Résumé. Cet article propose un cadre amélioré pour analyser les conjonctures critiques. Bien que rigoureux, largement applicable et représentant en soi une avance sur les modèles actuellement utilisés, ce cadre cherche principalement à incorporer un élément a priori. Jusqu'ici les cadres servant à l'étude des conjonctures critiques étaient entièrement fondés sur la postdiction. L'ajout d'un élément prédictif constituera une avance notable. Cet article examine la validité du nouveau cadre et de son élément prédictif, appelé “facteur de différenciation”, à la lumière des crises macro-économiques en Amérique et en Suède et des changements de politique macro-économique qu'elles ont entraînés dans leur sillon.
Validation of Binary Typing forStaphylococcus aureus Strains

ABSTRACT Most of the DNA-based methods for genetic typing ofStaphylococcus aureus strains generate complex banding patterns. Therefore, we have developed a binary typing procedure involving strain-differentiating DNA probes which were generated on the basis of randomly amplified polymorphic DNA (RAPD) analysis. We present and validate the usefulness of 15 DNA probes, according to generally accepted performance criteria for molecular typing systems. RAPD analysis with multiple primers was performed on 376 S. aureus strains of which 97% were methicillin resistant (MRSA). Among the 1,128 RAPD patterns generated, 66 were selected which identified 124 unique DNA fragments. From these amplicons, only 12% turned out to be useful for isolate-specific binary typing. The nature of the RAPD-generated DNA fragments was investigated by partial DNA sequence analysis. Several homologies with known S. aureussequences and with genes from other species were discovered; however, 87% of the probe sequences are of previously unknown origin. The locations of most of the DNA probes on the chromosome of S. aureus NCTC 8325 were determined by hybridization. Seven fragments were randomly dispersed along the genome, five were clustered within the 2500- to 2600-kb position of the genome, and the remaining four did not recognize complementary sequences in S. aureusNCTC 8325. A total of 103 S. aureus strains (69% MRSA) were used for the validation of the binary typing technique. The 15 DNA probes provided stable epidemiological markers, both in vitro (type consistency after serial passages on culture media) and in vivo (comparison of sequential isolates recovered from cases of persistent colonization). The discriminatory power of binary typing (D = 0.998) exceeded that of pulsed-field gel electrophoresis (D = 0.966) and RAPD analysis (D = 0.949). Reproducibility, measured by analyzing multiple strains belonging to a multitude of different epidemiological clusters, was comparable to that of other genotyping techniques used. Contribution of the DNA probes to the discriminatory power of the system was analyzed by comparison of dendrograms. This study demonstrates that binary typing is a robust tool for the genetic typing of S. aureus isolates.
Neural representation of interval time

Animals can predict the time of occurrence of a forthcoming event relative to a preceding stimulus, i.e. the interval time between those two, given previous learning experience with the temporal contingency between them. Accumulating evidence suggests that a particular pattern of neural activity observed during tasks involving fixed temporal intervals might carry interval time information: the activity of some cortical and subcortical neurons ramps up slowly and linearly during the interval, like a temporal integrator, and peaks around the time at which the event is due to occur. The slope of this climbing activity, and hence the peak time, adjusts to the length of a temporal interval during repetitive experience with it. Various neural mechanisms for producing climbing activity with variable slopes, representing the length of learned intervals, are discussed.
Enabling Applications on the Grid: A Gridlab Overview

Grid technology is widely emerging. Still, there is an eminent shortage of real Grid users, mostly due to the lack of a “critical mass” of widely deployed and reliable higher-level Grid services, tailored to application needs. The GridLab project aims to provide fundamentally new capabilities for applications to exploit the power of Grid computing, thus bridging the gap between application needs and existing Grid middleware. We present an overview of GridLab, a large-scale, EU-funded Grid project spanning over a dozen groups in Europe and the US. We first outline our vision of Grid-empowered applications and then discuss GridLab’s general architecture and its Grid Application Toolkit (GAT). We illustrate how applications can be Grid-enabled with the GAT and discuss GridLab’s scheduler as an example of GAT services.
On the convergence of shifted Laplace preconditioner combined with multilevel deflation

Deflating the shifted Laplacian with geometric multigrid vectors yields speedup. To verify this claim, we investigate a simplified variant of Erlangga and Nabben presented in [Erlangga and Nabben, ETNA, 2008;31:403–424]. We derive expressions for the eigenvalues of the two‐level preconditioner for the one‐dimensional problem. These expressions show that the algorithm analyzed is not scalable. They also show that the imaginary shift can be increased without delaying the convergence of the outer Krylov acceleration. An increase of the number of grid points per wavelength results in convergence acceleration. This contrasts to the use of the shifted Laplace preconditioner. Our analysis also shows that the use of deflation results in a spectrum more favorable to the convergence of the outer Krylov acceleration. The near‐null space components are still insufficiently well resolved, and the number of iterations increases with the wavenumber. In the two‐dimensional case, the number of near‐zero eigenvalues is larger than in the one‐dimensional case. We perform numerical computations with the two‐level and multilevel versions of the algorithm on constant and nonconstant wavenumber problems. Our numerical results confirm our spectral analysis. Copyright © 2013 John Wiley & Sons, Ltd.
Leveraging archival video for building face datasets

We introduce a semi-supervised method for building large, labeled datasets effaces by leveraging archival video. Specifically, we have implemented a system for labeling 11 years worth of archival footage from a television show. We have compiled a dataset of 611,770 faces, orders of magnitude larger than existing collections. It includes variation in appearance due to age, weight gain, changes in hairstyles, and other factors difficult to observe in smaller-scale collections. Face recognition in an uncontrolled setting can be difficult. We argue (and demonstrate) that there is much structure at varying timescales in the video data that make recognition much easier. At local time scales, one can use motion and tracking to group face images together - we may not know the identity, but we know a single label applies to all faces in a track. At medium time scales (say, within a scene), one can use appearance features such as hair and clothing to group tracks across shot boundaries. However, at longer timescales (say, across episodes), one can no longer use clothing as a cue. This suggests that one needs to carefully encode representations of appearance, depending on the timescale at which one intends to match. We assemble our final dataset by classifying groups of tracks in a nearest-neighbors framework. We use a face library obtained by labeling track clusters in a reference episode. We show that this classification is significantly easier when exploiting the hierarchical structure naturally present in the video sequences. From a data-collection point of view, tracking is vital because it adds non-frontal poses to our face collection. This is important because we know of no other method for collecting images of non-frontal faces "in the wild".
Breast mass segmentation on digital mammograms by a combined deterministic annealing method

Segmentation plays a vital role in digital mammographic mass detection. In this paper, we developed one breast mass segmentation scheme which is based on the concept of deterministic annealing (DA) and incorporated with a gain adaptive contrast enhancement (GACE) preprocessing technique. The probability distribution of gray levels within the region of interest(ROI) after GACE filter are estimated and a series of image partitions are obtained according to the intensity proximity as the temperature decreases. Compared with the segmentation results of DA without enhancement, and DA with histogram enhancement, the experimental results show that the combined DA and GACE segmentation scheme works more efficiently.
Dual/Primal mesh optimization for polygonized implicit surfaces

A new method for improving polygonizations of implicit surfaces with sharp features is proposed. The method is based on the observation that, given an implicit surface with sharp features, a triangle mesh whose triangles are tangent to the implicit surface at certain inner triangle points gives a better approximation of the implicit surface than the standard marching cubes mesh Lorensen(in our experiments we use VTK marching cubes VTK). First, given an initial triangle mesh, its dual mesh composed of the triangle centroids is considered. Then the dual mesh is modified such that its vertices are placed on the implicit surface and the mesh dual to the modified dual mesh is considered. Finally the vertex positions of that "double dual" mesh are optimized by minimizing a quadratic energy measuring a deviation of the mesh normals from the implicit surface normals computed at the vertices of the modified dual mesh. In order to achieve an accurate approximation of fine surface features, these basic steps are combined with adaptive mesh subdivision and curvature-weighted vertex resampling. The proposed method outperforms approaches based on the mesh evolution paradigm in speed and accuracy.
Averages of the number of points on elliptic curves

If $E$ is an elliptic curve defined over $\mathbb Q$ and $p$ is a prime of good reduction for $E$, let $E(\mathbb F_p)$ denote the set of points on the reduced curve modulo $p$. Define an arithmetic function $M_E(N)$ by setting $M_E(N):= \#\{p: \#E(\mathbb F_p)= N\}$. Recently, David and the third author studied the average of $M_E(N)$ over certain "boxes" of elliptic curves $E$. Assuming a plausible conjecture about primes in short intervals, they showed the following: for odd $N$, the average of $M_E(N)$ over a box with sufficiently large sides is $\sim \frac{K^{\ast}(N)}{\log{N}}$ for an explicitly-given function $K^{\ast}(N)$. The function $K^{\ast}(N)$ is somewhat peculiar: defined as a product over the primes dividing $N$, it resembles a multiplicative function at first glance. But further inspection reveals that it is not, and so one cannot directly investigate its properties by the usual tools of multiplicative number theory. In this paper, we overcome these difficulties and prove a number of statistical results about $K^{\ast}(N)$. For example, we determine the mean value of $K^{\ast}(N)$ over all $N$, odd $N$ and prime $N$, and we show that $K^{\ast}(N)$ has a distribution function. We also explain how our results relate to existing theorems and conjectures on the multiplicative properties of $\# E(\mathbb F_p)$, such as Koblitz's conjecture.
Applications of Vibrational Spectroscopy to Oilseeds Analysis

In this chapter applications of Raman, mid-infrared and near-infrared spectroscopy to oilseed analysis is presented. The methods can be successfully used to determine fats, proteins, carbohydrates, and numerous other secondary plant substances occurring in agricultural products. The spectroscopic methods have the potential to supplement existing standard procedures presently used for plant analysis (mainly chromatographic and NMR techniques). In addition, a great advantage of FT-Raman spectroscopy is shown as a nondestructive method used for analysis of an intact fresh plant tissue without the necessity to perform any sample cleanup preparation. Keywords: Raman; mid-infrared; IR; near-infrared; NIR; oil crops; oilseeds; fats; proteins; in situ identification; quantification
Geo-partitioning of MEC Resources

Mobile Edge Computing (MEC) is an emerging technology that aims at pushing applications and content close to the users (e.g. at base stations, access points, aggregation networks) to reduce latency, improve quality of experience, and ensure highly efficient network operation and service delivery It principally relies on virtualization-enabled MEC servers with limited capacity at the edge of the network. One key issue is to dimension such systems in terms of server size, server number and server operation area to meet MEC goals. In this paper, we propose a graph-based algorithm that, taking into account a maximum MEC server capacity, provides a partition of MEC clusters, which consolidates as many communications as possible at the edge. We use a dataset of mobile communications to evaluate it with real world spatio-temporal human dynamics. In addition to quantifying macroscopic MEC benefits, the evaluation shows that our algorithm provides MEC area partitions that largely offload the core, thus pushing the load at the edge (e.g., with 10 small MEC servers around 55% of the traffic stay at the edge), and that are well balanced through time.
Gibberellins Producing Endophytic Fungus Porostereum spadiceum AGH786 Rescues Growth of Salt Affected Soybean

In the pursuit of sustainable agriculture through environment and human health friendly practices, we evaluated the potential of a novel gibberellins (GAs) producing basidiomycetous endophytic fungus Porostereum spadiceum AGH786, for alleviating salt stress and promoting health benefits of soybean. Soybean seedlings exposed to different levels of NaCl stress (70 and 140 mM) under greenhouse conditions, were inoculated with the AGH786 strain. Levels of phytohormones including GAs, JA and ABA, and isoflavones were compared in control and the inoculated seedlings to understand the mechanism through which the stress is alleviated. Gibberellins producing endophytic fungi have been vital for promoting plant growth under normal and stress conditions. We report P. spadiceum AGH786 as the ever first GAs producing basidiomycetous fungus capable of producing six types of GAs. In comparison to the so for most efficient GAs producing Gibberella fujikuroi, AGH786 produced significantly higher amount of the bioactive GA3. Salt-stressed phenotype of soybean seedlings was characterized by low content of GAs and high amount of ABA and JA with reduced shoot length, biomass, leaf area, chlorophyll contents, and rate of photosynthesis. Mitigation of salt stress by AGH786 was always accompanied by high GAs, and low ABA and JA, suggesting that this endophytic fungus reduces the effect of salinity by modulating endogenous phytohormones of the seedlings. Additionally, this strain also enhanced the endogenous level of two isoflavones including daidzen and genistein in soybean seedlings under normal as well as salt stress conditions as compared to their respective controls. P. spadiceum AGH786 boosted the NaCl stress tolerance and growth in soybean, by modulating seedlings endogenous phytohormones and isoflavones suggesting a valuable contribution of this potent fungal biofertilizer in sustainable agriculture in salt affected soils.
Dialogue Systems for Virtual Environments

We present an on-going research project carried out at the Universidad Nacional de Cordoba in Argentina. This project investigates theoretical and practical research questions related to the development of a dialogue system situated in a virtual environment. We describe the PLN research group in which this project is being developed and, in particular, we spell out the areas of expertise of the authors. Moreover, we discuss relevant past, current and future collaborations of the research group.
Review of personalized recommendation techniques for learners in e-learning systems

With the rapidly increasing learning materials and learning resources, either offline or online, it is quite difficult to find suitable materials based on learner's need. Recommender systems help learners find the appropriate learning materials in which they would need to learn. This paper discusses about the personalized recommendation systems in e-learning and compares their recommendation techniques. Two concepts are the main discussion topics in this research. The first one is about the learner's requirement and the second one in about the personalized recommendation technique. Finally, this study proposes the knowledge based recommendation system as suitable recommendation technique. This recommendation aims to recommend to the learner, some materials based on the learner's need. By using the semantic relationship between learning materials and the learner's need, system can select the suitable materials as a recommendation to the learner. To develop the proposed knowledge based recommendation system is the next work for the future.