Miracle-dz/UniFAR-FTUs huggingface dataset:
A Pilot Study of Classroom‐Based Cognitive Skill Instruction: Effects on Cognition and Academic Performance

Cognitive skills are associated with academic performance, but little is known about how to improve these skills in the classroom. Here, we present the results of a pilot study in which teachers were trained to engage students in cognitive skill practice through playing games. Fifth-grade students at an experimental charter school were randomly assigned to receive cognitive skill instruction (CSI) or instruction in geography and typing. Students in the CSI group improved significantly more than the control group on a composite measure of cognitive skills. CSI was more effective for students with lower standardized test scores. Although there was no group effect on test scores, cognitive improvement correlated positively with test score improvement only in the CSI group. Beyond showing that cognitive skills can be improved in the classroom, this study provides lessons for the future of CSI, including changes to professional development and challenges for scalability.
Likelihood-based Clustering of Directed Graphs

In this paper, a new, stochastic approach to the clustering of directed graphs is presented. This method differs from the commonly used ones by defining the term "cluster" in an alternative way: a cluster can even be a set of vertices that don't connect to each other at all, provided that they have the same connectional preference to other vertices. First, a short overview of the current state of the art will be given. Then the underlying theory of this alternative clustering method will be explained and a possible implementation will be proposed. To support the validity of this approach, benchmark results on computer-generated graphs as well as two real applications are presented.
On the Spectrum of Lattice Massive Su ( 2 ) Yang

The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. On the basis of extended simulations, we provide some results concerning the spectrum of Massive SU(2) Yang–Mills on the lattice. We study the " time " correlator of local gauge invariant operators integrated over the remaining three dimensions. The energy gaps are measured in the isospin I = 0, 1 and internal spin J = 0, 1 channels. No correlation is found in the I = 1, J = 0 channel. In the I = 1, J = 1 channel and far from the critical mass value m c , the energy gap roughly follows the bare value m (vector mesons). In approaching the critical value m c at β fixed, there is a bifurcation of the energy gap: one branch follows the value m, while the new is much larger and it shows a more and more dominant weight. This phenomenon might be the sign of two important features: the long range correlation near the fixed point at β → ∞ implied by the low energy gap and the screening (or confining) mechanisms across the m = m c associated to the larger gap. The I = 0, J = 0, 1 gaps are of the same order of magnitude, typically larger than the I = 1, J = 1 gap (for m m c). For m ∼ m c , both I = 0 gaps have a dramatic drop with minima near the value m. This behavior might correspond to the formation of I = 0 bound states both in the J = 0 and J = 1 channels.
High-level optimization for low power consumption on microprocessor-based systems

Power consumption is an important constraint in the design of battery-operated embedded systems. The problem of minimizing power dissipation may be handled in terms of hardware or software optimizations. High-level language optimization techniques appear as an alternative to achieve low power consumption when programming embedded systems. In this work, software optimization techniques were applied to a set of code segments in a high-level language, in order to analyze the effect that source code optimizations have on the power dissipation of microprocessor-based systems. Design of experiments (DOE) techniques were used in order to reach statistical sound conclusions about the actual impact that software optimization techniques have on power consumption.
Yeast lipases: enzyme purification, biochemical properties and gene cloning

Lipases are placed only after proteases and carbohydrases in world enzyme market and share about 5% of enzyme market. They occur in plants, animals and microorganisms and are accordingly classified as plant, animal and microbial lipases. Wherever they exist, they function to catalyze hydrolysis of triglycerides to glycerol and fatty acid. Like carbohydrases and proteases, lipases of microbial origin enjoy greater industrial importance as they are more stable (compared to plant and animal lipases) and can be obtained in bulk at low cost. Majority of yeast lipases are extracelluar, monomericglycoproteins with molecular weight ranging between ~33 to ~65 kD. More than 50% reported lipases producing yeast, produce it in the forms of various isozymes. These lipase isozymes are in turn produced by various lipase encoding genes. Among many lipase producing yeasts Candida rugosa is most frequently used yeast as the source of lipase commercially. This review is aimed at compiling the information on properties of various yeast lipases and genes encoding them.
Air Traffic Control: To what extent can we predict performance based on personality?

Purpose – This research looked into the validity of personality in predicting air traffic controller performance and identified which function (curvilinear or linear) was the best fit for each given relationship. Design/methodology/approach – Participants from an Air Traffic Control Provider in New Zealand completed both the OPQ Personality measure within a high stakes condition (recruitment) and low stakes condition (in the year 2014) and had managerial performance ratings completed in 2014. This data was then analysed using within sample t tests, regression and curve estimation techniques. Findings – 18 relationships were found to be significant between personality traits and the performance competencies. Of these, 10 relationships displayed evidence of a curvilinear function which adds to the growing literature supporting the introduction of a curvilinear function in the personality-performance relationship. Research Limitations/Implications – There is one minor limitations within the current study. This is that through the use of self-report data, there is a risk of response distortion occurring. Despite this, the current research provides evidence of the validity of personality in predicting performance and a platform for future research into the area. Furthermore, it provides valuable information to improve the successfulness of the selection process. Originality/value – The study adds to the minimal research on personality and air traffic control performance, and is among the first to examine the idea of a curvilinear function between personality and air traffic controller performance, as opposed to the linear function that has been the only function considered in air traffic control performance research thus far.
Clock distribution networks — A case study using multi VDD and multi threshold level converters

Clock Distribution has played a key role in designing the synchronous systems. Even with the systems moving towards Globally Asynchronous and Locally Synchronous (GALS) a need for low power clock distribution network exists as it consumes a major portion of the circuit power. In this paper we demonstrate the effect of various level converters on clock distribution networks. Also we propose a novel low to high level converter which performs better for asynchronous latch based logic circuits at relatively higher frequency where the existing level converters fail. The simulation work was carried out using Cadence Virtuoso Schematic Composer at the frequencies of 10 MHz, 100 MHz, 200 MHz, 250 MHz, 400 MHz and 500 MHz. The proposed circuit performs better in terms of level retention at higher frequencies and power consumption when intermediate frequencies are considered.
Towards portable source code representations using XML

One of the most important issues in source code analysis and software re-engineering is the representation of software code text at an abstraction level and form suitable for algorithmic processing. However, source code representation schemes must be compact, accessible by well defined application programming interfaces (APIs) and above all portable to different operating platforms and various CASE tools. This paper proposes a program representation technique that is based on language domain modes and the XML markup language. In this context, source code is represented as XML DOM trees that offer a higher level of openness and portability than custom-made tool specific abstract syntax trees. The DOM trees can be exchanged between tools in textual or binary form. Similarly the domain model allows for language entities to be associated with analysis services offered by various CASE tools, leading to an integrated software maintenance environment.
The laminar organization of the lateral geniculate body and the striate cortex in the squirrel monkey (Saimiri sciureus)

The organization of the projection from the lateral geniculate body to the striate cortex in the squirrel monkey has been re-examined using the anterograde and retrograde transport of horseradish peroxidase (HRP) and wheat germ agglutinin conjugated to HRP. The results confirm earlier findings that the projections of the magnocellular and parvocellular layers of the lateral geniculate body terminate in separate sublaminae of layer IV of striate cortex; a more superficial projection of the parvocellular layers to a narrow strip at the base of layer III (IVA in Brodmann's terminology) has also been confirmed. In addition to these well characterized pathways, our results show that the projections of the lateral geniculate body terminate in more superficial levels of layer III and sparsely in layer I of striate cortex. The projections to the upper portion of layer III terminate in distinct patches which coincide precisely with patches of cytochrome oxidase activity previously identified in this zone. The projections to the patches originate primarily from small, pale-staining cells of the “intercalated layers” which surround the magnocellular layers of the lateral geniculate body. A comparison of the organization of the geniculo-cortical projections in the squirrel monkey with that of the cat, Galago, and Tupaia suggests that, despite marked species differences in the laminar organization of the lateral geniculate body and striate cortex, there are striking similarities in the pathway which terminates in the most superficial layers of striate cortex.
Indoor navigation for an automatic guided vehicle with beacon based relative distance estimation

When an autonomous guided vehicle (AGV) rotates its direction in a narrow indoor environment, overlapped zone or dead zone may happen depending on either sensing multiple landmarks or no sensing landmark. We present a self-localization of an AGV based on artificial beacons. With this approach, the position of an AGV is determined by its relative distance to a beacon, whose location is known in advance. A promising range of acquiring the best beacon signal strength should be known to us and thus this reliable location information will be used to control the AGV more precisely.
18FDG PET imaging can quantify increased cellular metabolism in pulmonary arterial hypertension: A proof-of-principle study

The past decade has seen increased application of 18-flurodeoxyglucose positron emission tomography (18FDG-PET) imaging to help diagnose and monitor disease, particularly in oncology, vasculitis and atherosclerosis. Disordered glycolytic metabolism and infiltration of plexiform lesions by inflammatory cells has been described in idiopathic pulmonary arterial hypertension (IPAH). We hypothesized that increased 18FDG uptake may be present in the lungs, large pulmonary arteries and right ventricle of patients with pulmonary hypertension, and that this uptake would be related to markers of immune activation. We imaged the thorax of 14 patients with pulmonary hypertension (idiopathic and chronic thromboembolic) and six controls by 18FDG-PET/computed tomography (CT) and measured uptake in the lung parenchyma, large pulmonary arteries and right ventricle. 18FDG uptake in the lungs and pulmonary arteries was normalized for venous blood activity to give a target-to-background ratio (TBR). Blood was contemporaneously drawn for high-sensitivity CRP – C-reactive protein (CRP) (hsCRP), N-Terminal Probrain natriuteric peptide (NT-ProBNP) and other inflammatory cytokines. IPAH patients had significantly higher lung parenchymal TBR (P =0.034) and right ventricle FDG uptake (P=0.007) than controls. Uptake in the main pulmonary arteries was similar in chronic thromboembolic pulmonary hypertension, IPAH and controls. There were no correlations between 18FDG uptake and hsCRP or inflammatory cytokine levels. NT-ProBNP correlated with RV uptake in those with pulmonary hypertension (r=0.55, P =0.04). In this pilot study, we found increased 18FDG uptake in the lung parenchyma and right ventricle of subjects with IPAH. The lung uptake might be useful as a surrogate marker of increased cellular metabolism and immune activation as underlying mechanisms in this disease. Further evaluation of the impact of targeted therapies in treatment-naïve patients and the significance of right ventricular uptake is suggested.
Examining Searcher Perceptions of and Interactions with Sponsored Results

In this paper, we report results of an investigation into the effect of sponsored links on ecommerce information seeking on the Web. In this research, 56 participants each engaged in 6 ecommerce Web searching tasks using 60 organic and 30 sponsored Web links for each task. We extracted these tasks from the transaction log of an actual Web search engine, so these queries represent actual ecommerce searching information needs. In the study, we controlled for quality of the Web search engine results by switching organic and sponsored links on three of the six searching tasks for each participant. We counterbalanced the order of presentation among participants. We investigated the perceptions of sponsored links and the factors that influence this bias. Data included 2,453 interactions with links from result pages and 961 utterances evaluating these links. Findings include that there is a strong preference for organic links, a bias against sponsored results, and that more than 56% of the time, the title of the sponsored link was the determining factor in searcher perceived relevance. We discuss implications for sponsored links and paid search as a long-term business model.
On a Principle of Lipschitz

1. It is often desirable to be able to approximate to the number of points with integral coordinates in a closed bounded region R in n dimensional space by means of the volume V(K) of ft. The position is very simple if R depends on one parameter X, and is obtained froma fixed region r\x by uniform dilatation about the origin with linear ratio of dilatation X. Then it is immediate that the number of points with integral coordinates in ft is
The Profit Curve for Budgeted Learning : Properties and Computation

In the budgeted learning problem we experiment on a set of alternatives (given a fixed experimentation budget) with the goal of picking a single alternative with the largest possible expected payoff. The ratio index, introduced by Goel et al. [5], leads to an index-based constant factor approximation algorithm for this problem. Index-based policies have the advantage that a single number (i.e. the index) can be computed for each alternative irrespective of all other alternatives, and the alternative with the highest index is experimented upon. This value has been highlighted by the famous Gittins index for the discounted multi-armed bandit problem. In this paper, we define the profit curve for budgeted learning, which is critical to calculating the ratio index. In the process, we derive several structural properties for the profit curve with significant consequences. Among these properties, we show that the profit curve is concave and piecewise linear, which, among other things, makes calculation of the ratio index using the profit curve elementary. We also show that the policies which induce the profit curve possess a certain monotonicity property critical to the proof that a greedy algorithm for budgeted learning with respect to the ratio index is a constant factor approximation algorithm. This monotonicity property also leads directly to a proof that the profit curve and the ratio index can be computed in strongly polynomial time. Thus, the greedy algorithm can be executed in strongly polynomial time, as can an index-based approximation algorithm for a discount oblivious version of the multi-armed bandit problem. Further, the techniques we develop may also be useful for deriving strongly polynomial algorithms for other Markov Decision Problems. We conclude with a detailed algorithm for computing the profit curve. ∗Department of Management Science and Engineering, Stanford University. Research supported by NSF ITR grant 0428868. Email: null@stanford.edu . †Departments of Management Science and Engineering and (by courtesy) Computer Science, Stanford University. Research supported by NSF ITR grant 0428868, NSF CAREER award 0339262, and an Alfred P. Sloan fellowship. Email: ashishg@stanford.edu .
UJM at CLEF in Author Identification Notebook for PAN at CLEF 2014

This article describes our proposal for the Author Identification task in the PAN CLEF Challenge 2014. We adopt a machine learning approach based on several representations of the texts and on optimized decision trees which have as entry various attributes and which are learnt for every training corpus separately for this classification task. Our method ranked us at the 2nd place with an overall AUC of 70.7%, and C@1 of 68.4% and, between the 1st and the 6th place on the six corpora .
Classification of Motor Imagery EEG Signals with Support Vector Machines and Particle Swarm Optimization

Support vector machines are powerful tools used to solve the small sample and nonlinear classification problems, but their ultimate classification performance depends heavily upon the selection of appropriate kernel and penalty parameters. In this study, we propose using a particle swarm optimization algorithm to optimize the selection of both the kernel and penalty parameters in order to improve the classification performance of support vector machines. The performance of the optimized classifier was evaluated with motor imagery EEG signals in terms of both classification and prediction. Results show that the optimized classifier can significantly improve the classification accuracy of motor imagery EEG signals.
Defense Technical Information Center Compilation Part Notice ADPO 11062 TITLE : The Relevance of Patent Foramen Ovale to Type 11 DCS : An Overview of the Literature

TITLE: Operational Medical Issues in Hypo-and Hyperbaric Conditions [les Questions medicales a caractere oprationel liees aux conditions hypobares ou hyperbares] To order the complete compilation report, use: ADA395680 The component part is provided here to allow users access to individually authored sections A proceedings, annals, symposia, etc. However, the component should be considered within [he context of the overall compilation report and not as a stand-alone technical report.
Treatment for Recurrent Ovarian Cancer—At First Relapse

Recurrent ovarian cancer is a lethal disease, and few patients can be cured. Although most patients receive standardized surgery and chemotherapy, the status of recurrent disease is heterogeneous. The site of recurrence and the survival intervals after recurrence are also widely distributed. Among a number of factors, many clinical trials identified time to recurrence was the factor most related to chemosensitivity at first relapse. The current recommendation for platinum sensitive ovarian cancer is a carboplatin containing combination chemotherapy. Generally, a single agent is chosen for platinum resistant ovarian cancer. Patients with single site recurrence and a long disease free interval are candidates for secondary cytoreduction, which may provide longer survival. There are several treatment choices at first relapse, and disease status, chemotherapy-free interval, and the patient's condition play a major role in the decision making process.
External Competitiveness of EU Candidate Countries

As the current financial crisis has shown, macroeconomic imbalances such as persistent current account and trade deficits, can seriously undermine a country’s resilience to economic shocks. Maintaining and enhancing external competitiveness has thus become of increasing concern, particularly to European Union (EU) candidate countries whose economic growth models have been challenged in recent years. Drawing on previous studies, this paper assesses developments in the external competitiveness of EU candidate countries between 1999 and 2011. Taking a broad approach to the issue of competitiveness, the paper considers various indicators of both short and long-term competitiveness, including those related to domestic prices and costs, export performance, and institutional and structural issues. In the context of EU integration, comparisons are drawn with developments in the EU12. We find that, during the pre-crisis period, all candidate countries experienced robust export market growth, but also suffered losses in price and cost competitiveness. In terms of export characteristics, progress has been heterogeneous and also fairly slow when compared with the EU12. All candidate countries have increased their number of export products and trading partners, but only a few have been able to export more complex products. As regards structural issues such as corruption and bureaucratic efficiency, all countries have performed quite poorly with the exception of Iceland. JEL Classification: H3, H6, E6, G1
Stress/emotion classification using features extracted in compliance with the front-end of the ETSI ES 202 211 V1.1.1 standard

The paper presents the study and the performance results of a system for emotion classification using the architecture of a Distributed Speech Recognition System (DSR). The parameters used were extracted by the front-end ETSI Aurora eXtended of a mobile terminal in compliance with the ETSI ES 202 211 V1.1. 1 standard. On the basis of the time trend of these parameters, over 3800 statistical parameters were extracted to characterize semantic units of two different lengths (sentences and words). Using the WEKA (Waikato Environment for Knowledge Analysis) software the most significant parameters for the classification of emotional states were selected and the results of various classification techniques were analysed. The results, obtained using both the Berlin Database of Emotional Speech (EMO-DB) and the Speech Under Simulated and Actual Stress (SUSAS) corpus, showed that the best performance is achieved using a Support Vector Machine (SVM) trained with the Sequential Minimal Optimization (SMO) algorithm, after normalizing and discretizing the input statistical parameters.