Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a theory of e-Learning :experiential e-Learning

E-learning is frequently technology-led rather than theory-led. In order to provide a deeper theoretical foundation for the development of e-learning, this case study uses a model developed from experiential learning theory as the practical basis for the design of an induction CD-Rom for students. In moving from a face-to-face experience to an electronic experience, video content was added to text-based induction handouts, with film and text carefully used to simulate a ‘real experience’ to engage the learners. An experiential model informed the filming sequences and script development, which was then evaluated through the use of questionnaires, interviews and reflective writing with postgraduate students. This action research, concerned with ‘what works’, had the central question: is it possible to transfer a successful face-to-face experience into an e-learning format? While the results point to the need for further research, the CD-Rom was well received by learners and was significantly advantageous to them. The experiential model provided a solid application to the design of the e-learning experience. Experiential learning closely involves the person, whereas e-learning, through its very nature, is an electronically mediated interaction. To bridge these differences, the two forms of learning are combined to introduce the concept of Colin Beard is a Teaching Fellow at the Faculty of Organisation and Management at Sheffield Hallam University. He is a National Teaching Fellow, Fellow of the Royal Society of Arts, and specialises in experiential learning. John Wilson is a researcher at the Institute of Work Psychology. He is co-author of Experiential Learning and editor of the textbook Human Resource Development: Learning and Training for Individuals and Organisations. Richard McCarter has worked for training organisations and in higher education for 27 years. His experience and expertise is mainly in video production. He supports lecturers in the use of rich media in teaching and learning at Sheffield Hallam University, and his main research interests are in the pedagogical use of video and text in multimedia. Beard, Wilson and McCarter (2007) Towards a Theory of e-Learning: Experiential e-Learning experiential e-learning (E learning). While these e-learning materials were initially developed for distance learning students who were unable to experience the face-to-face event, the ematerial is now being used by: 1) distance learning students; 2) on-site students as a reinforcement of seminars and lectures; and 3) other universities and HE institutions.
Aggregate Demand and Supply

This paper is part of a broader project that provides a microfoundation to the General Theory of J.M. Keynes. I call this project 'old Keynesian economics' to distinguish it from new-Keynesian economics, a theory that is based on the idea that to make sense of Keynes we must assume that prices are sticky. I describe a multi-good model in which I interpret the definitions of aggregate demand and supply found in the General Theory through the lens of a search theory of the labor market. I argue that Keynes' aggregate supply curve can be interpreted as the aggregate of a set of first order conditions for the optimal choice of labor and, using this interpretation, I reintroduce a diagram that was central to the textbook teaching of Keynesian economics in the immediate post-war period.
Improving search by incorporating evolution principles in parallel Tabu Search

Combinatorial optimization problems require computing efforts which grow at least exponentially with the problem dimension. Therefore, the use of the remarkable power of massively parallel systems constitutes an opportunity to be considered for solving significant applications in reasonable times. In this paper, starting from Tabu Search, a general optimization methodology, a parallel version, oriented to distributed memory multiprocessors and including evolution principles, has been introduced and discussed. The experiments have been performed on classical Traveling Salesman Problems and Quadratic Assignment Problems taken from literature. The results obtained show that the incorporation of evolution principles is very fruitful for the search strategy in terms of both convergence speed and solution precision. <<ETX>>
SSSPM J0829–1309: a new nearby L dwarf detected in SuperCOSMOS Sky Surveys

ABSTRACT The SuperCOSMOS Sky Surveys provide a complete coverage of the Southern skyin three passbands (photographic B J ,R and I) and at diﬀerent epochs (Hambly et al.2001a,b,c). These data are the basis for a new high proper motion survey which aimsat ﬁnding extremely red nearby dwarf stars and brown dwarfs. One of the ﬁrst can-didates, which is relatively bright (I = 16) but very red (R− I = 2.8,B J −R = 3.6),was detected in the equatorial zone by its large proper motion of 0.56 arcsec/yr.Spectroscopic follow-up observations with the 2.2m telescope of the Calar Alto Ob-servatory classiﬁed this object as L2 dwarf very similar to the ﬁrst free-ﬂoating Ldwarf Kelu 1 also discovered in a proper motion survey by Ruiz et al. (1997). If weassume SSSPM J0829−1309 to have the same luminosity as Kelu 1, we get a distanceestimate for the new L dwarf of about 12 pc since it is about one magnitude brighterthan Kelu 1 in the SSS I and R bands. This makes SSSPM J0829−1309 one of thenearest objects of its class, well suited for detailed investigations. We present a briefoverview of all known nearby (d < 20 pc) southern L dwarfs and give ﬁrst propermotion values for DENIS-P J0255−47 and SDSSp J1326−00 and an improved propermotion for LHS 102B.Key words: surveys – stars: distances – stars: kinematics – stars: late-type – stars:low-mass, brown dwarfs – solar neighbourhood.
Analyzing the Memory Impact of Advertising

Marketers are making increasing use of very brief messages that mention just a brand name or a brand name with a short headline, as in event sponsorship and program endorsements. There has been debate over the effectiveness of these "advertising fragments. " This paper introduces an approach for controlled testing of the effects of advertising fragments. Using a reaction-time based procedure, we show that a key effect of advertising fragments is to revive established brand associations, even though these associations are not explicitly communicated. This reactivation occurs not only when these names receive focal attention, but also when they receive nonfocal attention.
Spectral Clustering with Reverse Soft K-Nearest Neighbor Density Estimation

Spectral Clustering (SC) is a kernel method to cluster data objects using eigenvectors derived from the data. One fundamental issue that cause poor cuts in SC is its sensitivity to outliers. Another fundamental problem is how to determine the kernel bandwidth from the data. In fact, these two problems are also closely related. One cannot be solved before solving the other. The answer lies in robust and nonparametric estimators of the data density. We propose Reverse Soft K-Nearest Neighbor Density Estimation (RSKNN) that determines the density around a data sample, thus this sample's potential (other used terms are weight or entropy), using all the other samples' nearest neighbors' scatter properties on the contrary to the common practice of using the nearest neighbors of a sample itself to determine its own density. The basic idea behind this can be summarized as “every sample have k neighbors that are the nearest but not every point can be in many points' k-nearest neighborhood”. To demonstrate the use of it, we apply it to SC. Our package to use in SC consists of using RSKNN for estimating the density and the samples with high potential to be cluster centers helps in: 1) spectral decomposition phase to improve the generalization of the spectral cut criterion, 2) robust calculation of covariance matrix to be used in distance calculations, and 3) automatically determining the kernel bandwidth.
High-speed coherent WDM PON for next-generation access network

The wavelength-division-multiplexed passive optical network (WDM PON) is very attractive for the future broadband access network due to its capability of providing practically unlimited bandwidth to each subscriber. However, for the massive commercial deployment, its competitiveness is yet to be improved. In particular, we need to increase its operating speed and maximum reach, and, at the same time, enhance its cost-effectiveness. For these objectives, we have developed the high-speed WDM PON operating at per-wavelength speed of > 10 Gb/s by using reflective semiconductor optical amplifiers (RSOAs) and the digital coherent detection technique. We also evaluated the maximum operable speed of the RSOA-based WDM PON by using the classical Shannon theorem. This paper reviews these progresses achieved at KAIST.
Object detection and tracking in an open and dynamic world

A motion detection and tracking algorithm is presented for monitoring the pedestrians in an outdoor scene from a fixed camera. A mixture of Gaussians is used to model each pixel of the background image and thus adaptive to the dynamic scene. Colour chromaticity is used as the image representation, which results in the ill umination-invariant change detection in a daylit environment. To correctly interpret those objects that are occluded, merged, split or exit from the scene, a scene model is created and the motion of each object is predicted. A Bayesian network is constructed to reason about the uncertainty in the tracking. The results for detecting and tracking the moving objects in the PETS sequences are demonstrated.
Operating System Extensions to Support Host Based Virtual Machines

This paper presents two new operating system extensions that facilitate the fast execution of host based virtual machines: KTrace and MMA. KTrace provides a convenient and efficient mechanism for writing kernel modules that control the execution of user-level processes. MMA exposes more detail of the underlying memory management hardware, providing applications with access to high performance intraaddress space protection and address space overloading functionality. These extensions are applied to UMLinux, an x86 virtual machine that implements Linux as a user-mode process. As a result, overhead for UMLinux is reduced from 33% for a CPU bound workload and 819% 1240% for system call and I/O intensive workloads, to 6% and 49% 24% respectively.
Data Balancing using SVM as PreProcessor

Computational intelligence techniques are proved to be outperforming compared to standard statistical techniques, specifically when dealing with large, unbalanced and high dimensional data. In this paper we present Support Vector Machine as a pre-processor and decision tree is evaluated as a classifier. The proposed approach modifies the training data by replacing the actual target values with the predictions of the trained SVM. This modified training data is then used to train decision tree and the classification is done. The dataset analysed during this research study is COIL dataset which is highly unbalanced with 94:6 class distribution ratio. Extensive experimentation is done including various sampling techniques also to balance the data. Based on sensitivity measure, it is implied that preprocessing using SVM would balance the data well without compromising on the accuracy achieved by the classifier used for classification.
Testing the Accuracy of Synthetic Stellar Libraries

One of the main ingredients of stellar population synthesis models is a library of stellar spectra. Both empirical and theoretical libraries are used for this purpose, and the question about which one is preferable is still debated in the literature. Empirical and theoretical libraries are being improved significantly over the years, and many libraries have become available lately. However, it is not clear in the literature what are the advantages of using each of these new libraries, and how far behind models are compared to observations. Here we compare in detail some of the major theoretical libraries available in the literature with observations, aiming at detecting weaknesses and strengths from the stellar population modelling point of view. Our test is twofold: we compared model predictions and observations for broad-band colours and for high-resolution spectral features. Concerning the broad-band colours, we measured the stellar colour given by three recent sets of model atmospheres and flux distributions, and compared them with a recent UBVRIJHK calibration which is mostly based on empirical data. We found that the models can reproduce with reasonable accuracy the stellar colours for a fair interval in effective temperatures and gravities. The exceptions are (1) the U - B colour, where the models are typically redder than the observations, and (2) the very cool stars in general (V -K ≥ 3). Castelli & Kurucz is the set of models that best reproduce the bluest colours (U - B, B - V) while Gustafsson et al. and Brott & Hauschildt more accurately predict the visual colours. The three sets of models perform in a similar way for the infrared colours. Concerning the high-resolution spectral features, we measured 35 spectral indices defined in the literature on three high-resolution synthetic libraries, and compared them with the observed measurements given by three empirical libraries. The measured indices cover the wavelength range from ∼3500 to ∼8700 A. We found that the direct comparison between models and observations is not a simple task, given the uncertainties in parameter determinations of empirical libraries. Taking that aside, we found that in general the three libraries present similar behaviours and systematic deviations. For stars with T eff ≤ 7000K, the library by Coelho et al.is the one with best average performance. We detect that lists of atomic and molecular line opacities still need improvement, specially in the blue region of the spectrum, and for the cool stars (T eff ≤ 4500 K).
Multi-core Parallelization of Abstracted Abstract Machines ∗

It is straightforward to derive well-known higher-order flow analyses as abstract interpretations of well-known abstract machines. In this paper, we explore multi-core parallel evaluation of one such abstract abstract machine, the CES machine. The CES machine is a variant of CESK machines that runs Continuation Passing Style (CPS) λ-calculus. Using k-CFA, the concrete semantics for a CES machine can be turned into abstract semantics. Analyzing a program for this machine is a state graph walk, which can be run in parallel to increase performance.
Designing polymorphic circuits with polymorphic gates: a general design approach

A general design approach to design polymorphic circuits with polymorphic gates is proposed. These polymorphic circuits can adaptively adjust their functionalities with the changes of the electrical characteristics of components induced by the change of environment. The single function circuits that can work correctly and maintain their functionalities in different environments can be regarded as a special kind of polymorphic circuits. The general design approach for these circuits is proposed, and based on this approach, the general design approach to designing polymorphic circuits is also proposed. It is proved that a polymorphic circuit with any two different functions in two different environments can be implemented with a complete polymorphic gate set, and a definition on the gate set is given and the completeness is also discussed. Finally, these general design approaches are analysed and some experiments are performed to demonstrate their efficiency.
Video Pause Detection Using Wavelets

As the volume of digital video captured and stored continuesto increase, research efforts have focused on contentmanagement systems for video indexing and retrieval applications.A first step in generic video processing is shot boundary detection. This paper addresses a novel algorithm for abrupt shot (cut/pause) detection - especially on frames with similar statistics - based on the wavelet transformand content entropy. The algorithm has been successfullytested on some video categories including sport and live videos. Its quantitative performance has been comparedto other known methods including pixel, histogram, frequency domain and statistics difference. In each test, the proposed wavelet method outperforms the others.
Speech Enhancement by Adaptive Noise Cancellation in the Wavelet Domain

Adaptive filtering has been used for speech denoising in the time domain. During the last decade, wavelet transform has been developed for speech enhancement. In this paper we are proposing to use adaptive filtering in the wavelet transform domain. We propose a hybrid method of using adaptive filters on the lower scales of a wavelet transformed speech together with the conventional methods (thresholding, spectral subtraction, and Wiener filtering) on the higher scale coefficients. Experimental results demonstrate that the suggested approach is computationally efficient and has a good performance
Towards a compiler/runtime synergy to predict the scalability of parallel loops

Large classes of applications fail to scale well in CMPs due to contention in the memory subsystem. Assigning full core capacity to such applications is a clear resource waste. To support efficient and power-aware resource allocation policies, we need a prediction mechanism to provide information about the potential scalability of an application. In this paper we take an initial step towards building a scalability predictor, based on the utilization of information collected both during compile and runtime. Our approach is applied separately to each parallel-for region in the program and calculates an on-chip to off-chip activity ratio Sr, which then is associated to the scalability of the region (maximum speedup) with linear regression. Experimental results on two architectures using the Polybench suite demonstrate that our prediction model exhibits a good accuracy in predicting the scalability of various parallel-for regions.
The effect of obesity on the contractile performance of isolated mouse soleus, EDL, and diaphragm muscles.

Obesity affects the major metabolic and cellular processes involved in skeletal muscle contractility. Surprisingly, the effect of obesity on isolated skeletal muscle performance remains unresolved. The present study is the first to examine the muscle-specific changes in contractility following dietary-induced obesity using an isolated muscle work-loop (WL) model that more closely represents in vivo muscle performance. Following 16-wk high-calorific feeding, soleus (SOL), extensor digitorum longus (EDL), and diaphragm (DIA) were isolated from female (CD-1) mice, and contractile performance was compared against a lean control group. Obese SOL produced greater isometric force; however, isometric stress (force per unit muscle area), absolute WL power, and normalized WL power (watts per kilogram muscle mass) were unaffected. Maximal isometric force and absolute WL power of the EDL were similar between groups. For both EDL and DIA, isometric stress and normalized WL power were reduced in the obese groups. Obesity caused a significant reduction in fatigue resistance in all cases. Our findings demonstrate a muscle-specific reduction in contractile performance and muscle quality that is likely related to in vivo mechanical role, fiber type, and metabolic profile, which may in part be related to changes in myosin heavy chain expression and AMP-activated protein kinase activity. These results infer that, beyond the additional requirement of moving a larger body mass, functional performance and quality of life may be further limited by poor muscle function in obese individuals. As such, a reduction in muscle performance may be a substantial contributor to the negative cycle of obesity. NEW & NOTEWORTHY The effect of obesity on isolated muscle function is surprisingly underresearched. The present study is the first to examine the effects of obesity on isolated muscle performance using a method that more closely represents real-world muscle function. This work uniquely establishes a muscle-specific profile of mechanical changes in relation to underpinning mechanisms. These findings may be important to understanding the negative cycle of obesity and in designing interventions for improving weight status.
Dramatic reduction of sequence artefacts from DNA isolated from formalin-fixed cancer biopsies by treatment with uracil-DNA glycosylase

Non-reproducible sequence artefacts are frequently detected in DNA from formalin-fixed and paraffin-embedded (FFPE) tissues. However, no rational strategy has been developed for reduction of sequence artefacts from FFPE DNA as the underlying causes of the artefacts are poorly understood. As cytosine deamination to uracil is a common form of DNA damage in ancient DNA, we set out to examine whether treatment of FFPE DNA with uracil-DNA glycosylase (UDG) would lead to the reduction of C>T (and G>A) sequence artefacts. Heteroduplex formation in high resolution melting (HRM)-based assays was used for the detection of sequence variants in FFPE DNA samples. A set of samples that gave false positive HRM results for screening of the E17K mutation in exon 4 of the AKT1 gene were chosen for analysis. Sequencing of these samples showed multiple non-reproducible C:G>T:A artefacts. Treatment of the FFPE DNA with UDG prior to PCR amplification led to a very marked reduction of the sequence artefacts as indicated by both HRM and sequencing analysis. Similar results were shown for the BRAFV600 region in the same sample set and EGFR exon 19 in another sample set. UDG treatment specifically suppressed the formation of artefacts in FFPE DNA as it did not affect the detection of true KRAS codon 12 and true EGFR exon 19 and 20 mutations. We conclude that uracil in FFPE DNA leads to a significant proportion of sequence artefacts. These can be minimised by a simple UDG pre-treatment, which can be readily carried out in the same tube as the PCR, immediately prior to commencing thermal cycling. HRM is a convenient way of monitoring both the degree of damage and the effectiveness of the UDG treatment. These findings have immediate and important implications for cancer diagnostics where FFPE DNA is used as the primary genetic material for mutational studies guiding personalised medicine strategies and where simple effective strategies to detect mutations are required.
Pediatric adherence as a multidimensional and dynamic construct, involving a triadic partnership.

OBJECTIVE The aim of this paper is to integrate and draw attention to research findings that support our conceptualization of adherence as being multidimensional, dynamic, and involving a triadic partnership. METHODS A review of relevant articles found in Medline, PsychLit, and reference lists provided in pertinent articles was performed. RESULTS Significant progress has been made in identifying disease-related and psychosocial correlates of pediatric adherence and in developing intervention programs to promote adherence. Both lines of work have proceeded without a unifying framework for conceptualizing and measuring pediatric adherence. We offer a model that views adherence as comprising three defining aspects: (a) multidimensional, in support of the complexity and interrelatedness of treatment components, (b) a triadic partnership, as in mutually influential exchanges within and among the caregiver-medical team, child-medical team, and caregiver-child relationships, and (c) dynamic in relation to the notion of changes in developmental adaptive capacity, contextual characteristics, and disease course. CONCLUSIONS Much work has yet to be done to validate, refine, and extend our model of adherence. Recommendations are offered for assessing each defining aspect, and a group-based methodology that accommodates longitudinal, prospective data is described.