Miracle-dz/UniFAR-FTUs huggingface dataset:
Epistemology, pedagogy, assessment and learning analytics

There is a well-established literature examining the relationships between epistemology (the nature of knowledge), pedagogy (the nature of learning and teaching), and assessment. Learning Analytics (LA) is a new assessment technology and should engage with this literature since it has implications for when and why different LA tools might be deployed. This paper discusses these issues, relating them to an example construct, epistemic beliefs -- beliefs about the nature of knowledge -- for which analytics grounded in pragmatic, sociocultural theory might be well placed to explore. This example is particularly interesting given the role of epistemic beliefs in the everyday knowledge judgements students make in their information processing. Traditional psychological approaches to measuring epistemic beliefs have parallels with high stakes testing regimes; this paper outlines an alternative LA for epistemic beliefs which might be readily applied to other areas of interest. Such sociocultural approaches afford opportunity for engaging LA directly in high quality pedagogy.
The conserved C-terminal domain of the bovine papillomavirus E5 oncoprotein can associate with an alpha-adaptin-like molecule: a possible link between growth factor receptors and viral transformation

The bovine papillomavirus E5 gene encodes an oncoprotein that can independently transform rodent fibroblasts. This small 44-amino-acid protein is thought to function through the activation of growth factor receptors. E5 activation of the epidermal growth factor receptor results in an increase in the number of activated receptors at the cell surface. This finding suggests that E5 may act by inhibiting the normal down regulation of activated epidermal growth factor receptor via coated pit-mediated endocytosis. We have constructed a fusion protein consisting of glutathione S-transferase and the conserved C-terminal domain of E5 (GST-E5) in order to identify E5-associated cellular proteins that may be involved in its transforming activity. We have identified a 125-kDa cellular protein with a strong associated serine kinase activity that specifically associated with GST-E5 in the reduced form but not with GST-E5 fusions that contained changes in several conserved amino acids. Microsequence and biochemical analyses suggest that p125 is a novel member of the alpha-adaptin family. Since alpha-adaptins have previously been shown to be involved in coated pit-mediated cell surface receptor endocytosis and down regulation, these results suggest that p125 may be an alpha-adaptin-like molecule involved in growth factor receptor down regulation and that E5 may act by inhibiting its activity.
Development of 3D Vision Testbed for Shape Memory Polymer Structure Applications

As applications for shape memory polymers (SMPs) become more advanced, it is necessary to have the ability to monitor both the actuation and thermal properties of structures made of such materials. In this paper, a method of using three stereo pairs of webcams and a single thermal camera is studied for the purposes of both tracking three dimensional motion of shape memory polymers, as well as the temperature of points of interest within the SMP structure. The method used includes a stereo camera calibration with integrated local minimum tracking algorithms to locate points of interest on the material and measure their temperature through interpolation techniques. The importance of the proposed method is that it allows a means to cost effectively monitor the surface temperature of a shape memory polymer structure without having to place intrusive sensors on the samples, which would limit the performance of the shape memory effect. The ability to monitor the surface temperatures of a SMP structure allows for more complex configurations to be created while increasing the performance and durability of the material. Additionally, as compared to the previous version, both the functionalities of the testbed and the user interface have been significantly improved.
Phylodynamics without trees: estimating R0 directly from pathogen sequences

We develop a new tree-free phylodynamic method to estimate the reproduction number (R0) of a pathogen from large numbers of sequences of a pathogen. It is based on the convergence of the cherry-to-tip ratio (CTR) to a constant depending on R0 in supercritical branching trees. It is a tree-free method because tree reconstruction is not required: the number of cherries and the CTR is estimated directly from the sequences using the new computational method Cherries Without Tree (CWT). With simulations, we compare CWT to other methods currently in use. We use the new inference method to estimate R0 from simulated sequences and discuss its accuracy. We explore the potential bias arising from sub-sampling.
Performance analysis of the converted range rate and position linear Kalman filter

In active sonar and radar applications measurements consist of range, bearing and often range rate - all nonlinear functions of the target state (usually modeled in Cartesian coordinates). The converted measurement Kalman filter (CMFK) first converts the range and bearing measurements into Cartesian coordinates to allow for the use of a linear Kalman filter. The extension of the CMKF to use range rate as a linear measurement however has been limited to cases with small bearing errors. The use of range rate as a nonlinear measurement requires the use of a nonlinear filter such as the extended Kalman filter (EKF). Due to the uncertain performance of the EKF, various modifications have been proposed, including use of a pseudo measurement, an alternative linearization of the measurement prediction function, and sequentially processing the converted position and range rate measurements (applied to the EKF and the Unscented Kalman Filter). Common to these approaches is that the measurement prediction function remains nonlinear. A measurement conversion from range, bearing and range rate to Cartesian position and velocity has recently been proposed [4]. This manuscript expands the evaluation of this new approach by comparing to the Sequential EKF, the Sequential Unscented Kalman Filter (UKF) and the posterior Cramer-Rao lower bound (PCRLB). The new method is shown to have improved mean square error performance and exhibits improved constancy over the previously proposed methods, especially in cases with poor bearing accuracy.
Detection of stable mobile communities in vehicular Ad Hoc Networks

A vehicular Ad Hoc Network (VANET) is a type of wireless network where nodes represent moving vehicles. Some VANET-based applications might require organising vehicles into groups (communities). However, the high mobility of the vehicles and their tendency to travel in clustered flows makes them a challenging subject for community detection. Communities should be formed on the fly, using only local knowledge about their neighbourhood, and evolve as vehicles move over time. The main goal of this paper is to evaluate if stable community detection is possible in highly dynamic VANETs. To do so, the SandSHARC algorithm is extended with two different stability metrics: link duration and mobility similarity. In order to evaluate the stability of the evolving mobile communities, new quantitative and qualitative metrics are proposed, and run simulations on two different VANET scenarios: highway and urban. We analyse how the two stability metrics improve the stability of the detected communities. The results demonstrate that stability depends on the mobility patterns of the underlying traffic network. The proposed method can be applied in a distributed manner and produces communities with robust communication links between members what makes it viable for VANET applications.
Universite de Montreal at TREC 2013: Experiments with Quantum Language Models in the Web Track

In TREC 2013, we focus on addressing the challenges posed by the Web track using our recently proposed Quantum Language Modeling (QLM) approach for IR [1]. QLM can be considered as a dependence model for IR for its capability of representing and integrating compound term dependencies into the scoring function. Among the main properties of the model, two of them make it stand out from the literature of existing dependence models (such as MRF [3]). First, QLM does not combine scores obtained from matching single terms and from matching compound dependencies, which makes it virtually parameterless. This is quite an appealing property for an IR system, especially when a new dataset such as ClueWeb12 is released and no previous training examples can be leveraged to fine-tune important parameters. The second peculiar feature of our model is its ability to automatically fallback onto the baseline bag-ofwords score in the case that the required dependence relationship does not hold in the document. This is expected to bring improved robustness w.r. t. the baseline ranking. In the light of these considerations, the Web Track ad-hoc and robustness task seem the perfect testbeds for our model. In what follows we briefly review some of the theoretical background of QLM before delving into the description of the submitted runs and obtained results.
Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.
A unified dynamic model and control for the voltage-sourced converter under unbalanced grid conditions

This paper introduces and develops i) a novel unified dynamic model, and ii) new control schemes for a grid-connected static energy conversion system that is based on the voltage-sourced converter (VSC) configuration. The model and the controls are applicable to both the conventional two-level and the three-level neutral point diode clamped (NPC) VSCs. The model is unified since it represents the dynamic behavior of the VSC with respect to both positiveand negative-sequence components, due to unbalanced grid conditions and disturbances. To develop the unified model, the concepts of "generalized sinusoidal pulse-width modulation (SPWM)" and "VSC sequence subsystems" are presented. Based on the negative-sequence subsystem control, a new control strategy, to either balance the ac line currents or to mitigate dc-bus voltage ripples, is introduced. Application of the developed model and the controls to a variable-speed wind-power unit is presented in the paper.
Simultaneous determination of glucoraphanin and sulforaphane in Brassica oleracea seeds by high-performance liquid chromatography with evaporative light-scattering detector

In this article, a novel and efficient analysis method is described to simultaneously and quantitatively determine glucoraphanin and its major degradation product sulforaphane by reversed-phase high-performance liquid chromatography (HPLC) coupled with an evaporative light-scattering detector (ELSD). This method was validated according to the regulatory guidelines with respect to precision, accuracy and linearity. The HPLC-ELSD method was successfully used to assess the contents of glucoraphanin and sulforaphane in varieties of Brassica oleracea seeds. The developed analytical method not only avoids the underestimation of total glucoraphanin content, but also provides a reduction in analysis time and good efficiency and sensitivity compared to with conventional HPLC methods.
Incox - A Language for XML Integrity Constraints Description

Presently, there is no specialized language for complex integrity constraints description in XML documents. In this paper we present a language that combines first-order logic together with XPath language to achieve needed expressive power. Standard quantifiers of first-order logic were extended to allow us to specify (either by count or by percentage) how many elements of the selected set must hold given constraint. The proposed language can be used in conjunction with any XML schema language. The Incox validator supports both plain-text and XML variants of constraint specification. While the first one is easily understandable for humans, the latter meets requirements of machine processing.
International Journal of Innovative Research in Computer and Communication Engineering Detection of Pre-skin Cancer Using Automatic Cell Segmentation Technique

Biopsy procedure needs invasive tissue removal from a living subject to determine the occurrence or extent of the diseases. It is complicated and time consuming processes. Third Harmonic Generated Microscopy is a new exemplar for non-invasive in vivo virtual biopsy which has the ability to obtain tissue images without removing tissues. The aim of this paper is to discuss about various virtual biopsy microscopic modalities and also about automatic cell segmentation approaches such as watershed transform and convergence index filter, which provides high accuracy for non-invasive analysis of cell Nuclear-to-cytoplasm ratio (NC ratio). NC ratio plays a vital role in identifying or detecting early disease symptoms such as skin cancers during medical imaging analysis.
The projective equation of a circle and its application in camera calibration

In this article, we present the projective equation of a circle in a perspective view, which naturally encodes such important geometric entities as the projected circle center, the vanishing point of the normal direction of the circlepsilas supporting plane and the degenerate conic envelope spanned by the image of circular points (ICPs). Based on this projective equation, we propose an easy technique to calibrate the focal length and the extrinsic parameters of a camera merely by using one perspective view of two arbitrary coplanar circles. Unlike existing optimization algorithm, our method offers a closed form solution through simple matrix manipulation. Experimental results verify the correctness and efficiency of our proposed technique.
Surface micromachined capacitive ultrasonic transducers

The current state of novel technology, surface microfabricated ultrasonic transducers, is reported. Experiments demonstrating both air and water transmission are presented. Air-coupled longitudinal wave transmission through aluminum is demonstrated, implying a 110 dB dynamic range for transducers at 2.3 MHz in air. Water transmission experiments from 1 to 20 MHz are performed, with a measured 60 dB SNR at 3 MHz. A theoretical model is proposed that agrees well with observed transducer behavior. Most significantly, the model is used to demonstrate that microfabricated ultrasonic transducers constitute an attractive alternative to piezoelectric transducers in many applications.
Overexpression of the NaK-ATPase 2-subunit improves lung liquid clearance during ventilation-induced lung injury

Yochai Adir, Lynn C. Welch, Vidas Dumasius, Phillip Factor, Jacob I. Sznajder, and Karen M. Ridge Division of Pulmonary and Critical Care Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois; Division of Pulmonary Medicine, Carmel Medical Center, Rappaport Family Institute for Research in the Medical Sciences, Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel; Department of Medicine, Columbia University College of Physicians and Surgeons, New York, New York; and Jesse Brown Veterans Administration Medical Center-Lakeside Division, Chicago, Illinois
On Embedding Synfire Chains in a Balanced Network

We investigate the formation of synfire waves in a balanced network of integrate-and-fire neurons. The synaptic connectivity of this network embodies synfire chains within a sparse random connectivity. This network can exhibit global oscillations but can also operate in an asynchronous activity mode. We analyze the correlations of two neurons in a pool as convenient indicators for the state of the network. We find, using different models, that these indicators depend on a scaling variable. Beyond a critical point, strong correlations and large network oscillations are obtained. We looked for the conditions under which a synfire wave could be propagated on top of an otherwise asynchronous state of the network. This condition was found to be highly restrictive, requiring a large number of neurons for its implementation in our network. The results are based on analytic derivations and simulations.
The Si* Modeling Framework: Metamodel and Applications

Security Requirements Engineering is emerging spurred by the realization that security must be dealt from the early phases of the system development process. Modeling languages in this field are challenging as they must provide concepts appropriate in order to talk about security within an organization. In previous work we introduced the SI* modeling language tailored to capture security aspects of socio-technical systems. SI* is founded on four main notions, namely supervision, permission, delegation, and trust. In this paper, we present the SI* metamodel. We also present some frameworks and methodologies founded on this modeling language for the analysis of security and dependability requirements as well as the exploration of design alternatives and the generation of skeletons of secure business processes. The paper also presents a development environment that uses the SI* metamodel as its basis core.
Simultaneous facial action tracking and expression recognition using a particle filter

The recognition of facial gestures and expressions in image sequences is an important and challenging problem. Most of the existing methods adopt the following paradigm. First, facial actions/features are retrieved from the imag es, and then facial expressions are recognized based on the retrieved temporal parameters. Unlike this main stream, this paper introduces a new approach allowing the simultaneous recovery of facial actions and expression using a particle filter adopting multi-class dynamics that are conditioned o n the expression. For each frame in the video sequence, our approach is split in two consecutive stages. In the first stag e, the 3D head pose is recovered using a deterministic registration technique based on Online Appearance Models. In the second stage, the facial actions as well as the facial expression are simultaneously recovered using the stochasti c framework with mixed states. The proposed fast scheme is either as robust as existing ones or more robust with respect to many regards. Experimental results show the feasibility and robustness of the proposed approach.
Spectral Shifts of Nonadiabatic High-Order Harmonic Generation

High-order harmonic generation (HHG) is a nonlinear nonperturbative process in ultrashort intense laser-matter interaction. It is the main source of coherent attosecond (1 as = 10−18 s) laser pulses to investigate ultrafast electron dynamics. HHG has become an important table-top source covering a spectral range from infrared to extreme ultraviolet (XUV). One way to extend the cutoff energy of HHG is to increase the intensity of the laser pulses. A consequence of HHG in such intense short laser fields is the characteristic nonadiabatic red and blue shifts of the spectrum, which are reviewed in the present work. An example of this nonperturbative light-matter interaction is presented for the one-electron nonsymmetric molecular ion HeH2+, as molecular systems allow for the study of the laser-molecule orientation dependence of such new effects including a four-step model of MHOHG (Molecular High-order Harmonic Generation).
Effects of Lifetime Unemployment Experience and Job Insecurity on Two-Year Risk of Physician-Diagnosed Incident Depression in the German Working Population

Unemployment and job insecurity have been reported to be associated with a higher risk of depression. The purpose of this study was to evaluate the separate and combined effects of lifetime unemployment experience and job insecurity on the incidence of depression in an unselected working population in Germany. Data from the German Socio-Economic Panel (GSOEP) study were used, as was a final sample of those currently employed, with complete data at baseline (2009) and follow-up (2011) restricted to those free of depression in 2009 (n = 7073). Poisson regression analysis was applied to test the prospective associations between unemployment, job insecurity, and a two-year incident of depression. Results showed that the experience of unemployment and perceived job insecurity were significantly associated with a higher risk of depression during the two-year follow-up (risk ratios 1.64; 95% confidence intervals (1.16, 2.31) and risk ratios 1.48; 95% confidence intervals (1.13, 1.92), respectively). Notably, the strongest risk was observed among participants with insecure jobs and past long-term unemployment (risk ratios 2.15; 95% confidence intervals (1.32; 3.52)). In conclusion, even during employment, the experience of lifetime unemployment led to a higher risk of depression. The combination of previous unemployment experience and anticipated job insecurity increased the risk of developing depression. Results support health promotion with special emphasis on unemployment and precarious working conditions.
Video completion using gray level co-occurrence matrix and object update

Reconstructing and repairing damaged parts after object removal of digital video is an important trend in artwork restoration. Video completion is an active subject in video processing, which deals with the recovery of the original data. Most previous video completion approaches consume more time in extensive search to find the best patch to restore the damaged frames. In addition to that, visual artifacts appear when the damaged area is large. This paper presents a video completion method without the extensive search process. The proposed framework consists of a segmentation stage based on low resolution version and background subtraction, a tracking stage based on Gray Level Co-occurrence Matrix (GLCM), and a completion stage based on object prior position and object update. The proposed method reduces the completion time to a few seconds and maintains the spatial and temporal consistency. It works well when the background has clutter or fake motion, and it can handle changes in object size and in posture.