Miracle-dz/UniFAR-FTUs huggingface dataset:
A New Approach to Enforcing Discrete Maximum Principles in Continuous Galerkin Methods for Convection-Dominated Transport Equations

This paper presents a set of design principles and new algorithmic tools for enforcing maximum principles and/or positivity preservation in continuous ﬁnite element approximations to convection-dominated transport problems. Using a linear ﬁrst-order advection equation as a model problem, we ad-dress the design of ﬁrst-order artiﬁcial diﬀusion operators and their higher-order counterparts at the element matrix level. The proposed methodology leads to a nonlinear high-resolution scheme capable of resolving moving fronts and internal/boundary layers as sharp localized nonoscillatory features. The amount of numerical dissipation depends on the diﬀerence between the solution value at a given node and a local maximum or minimum. The shock-capturing numerical diﬀusion coeﬃcient is designed to vanish as the nodal values approach a mass-weighted or linearity-preserving average. The uni-versal applicability and simplicity of the element-based limiting procedure makes it an attractive alternative to edge-based algebraic ﬂux correction. Additionally a Lipschitz continuous version of the limiter is presented that guarantees unique solvability of the nonlinear system associated with the steady state limit of the time-dependent problem. A grid convergence study is performed for two-dimensional test problems.
Multiresolution Computation of Conformal Structures of Surfaces

An efficient multiresolution method to compute global conformal structures of nonzero genus triangle meshes is introduced. The homology, cohomology groups of meshes are computed explicitly, then a basis of harmonic one forms and a basis of holomorphic one forms are constructed. A progressive mesh is generated to represent the original surface at different resolutions. The conformal structure is computed for the coarse level first, then used as the estimation for that of the finer level, by using conjugate gradient method it can be refined to the conformal structure of the finer level.
Sports Sentiment and Stock Returns

This paper investigates the stock market reaction to sudden changes in investor mood. Motivated by psychological evidence of a strong link between soccer outcomes and mood, we use international soccer results as our primary mood variable. We find a significant market decline after soccer losses. For example, a loss in the World Cup elimination stage leads to a next-day abnormal stock return of −49 basis points. This loss effect is stronger in small stocks and in more important games, and is robust to methodological changes. We also document a loss effect after international cricket, rugby, and basketball games. THIS PAPER EMPLOYS A NOVEL MOOD VARIABLE, international soccer results, to investigate the effect of investor sentiment on asset prices. Using a cross-section of 39 countries, we find that losses in soccer matches have an economically and statistically significant negative effect on the losing country’s stock market. For example, elimination from a major international soccer tournament is associated with a next-day return on the national stock market index that is 38 basis points lower than average. We also document a loss effect after international cricket, rugby, and basketball games. On average, the effect is smaller in magnitude for these other sports than for soccer, but is still economically and statistically significant. We find no evidence of a corresponding effect after wins for any of the sports that we study. Controlling for the pre-game expected outcome, we are able to reject the hypothesis that the loss effect after soccer games is driven by economic factors such as reduced productivity or lost revenues. We
Carbonaceous Chondrite-Like Xenoliths in Polymict Ureilites: A Large Variety of Unique Outer Solar System Materials

VARIETY OF UNIQUE OUTER SOLAR SYSTEM MATERIALS. C. A. Goodrich, M. Zolensky, I. Kohl, E. D. Young, Q. -Z. Yin, M. E. Sanborn and M. H. Shaddad. Lunar and Planetary Institute, USRA, 3600 Bay Area Blvd., Houston TX 77058 USA goodrich@lpi.usra. edu; ARES, NASA-JSC, Houston TX 77058 USA; Univ. of California at Los Angeles, Los Angeles CA 90095 USA; Univ. of California at Davis, Davis CA 95616 USA; Univ. of Khartoum, Khartoum 11115 Sudan.
Applying MapReduce Programming Model for Handling Scientific Problems

According to data volumes in scientific applications have grown exponentially, new scientific methods to analyze and organize the data are required. MapReduce programming is driving Internet services and those services operation in a cloud environment. Hence it is required to efficiently provide resources for handling diverse MapReduce applications. In this paper we show the Hadoop application with map and reduce functions for the data transformation.
Inter-tile reuse optimization applied to bandwidth constrained embedded accelerators

The adoption of High-Level Synthesis (HLS) tools has significantly reduced accelerator design time. A complex scaling problem that remains is the data transfer bottleneck. To scale-up performance accelerators require huge amounts of data, and are often limited by interconnect resources. In addition, the energy spent by the accelerator is often dominated by the transfer of data, either in the form of memory references or data movement on interconnect. In this paper we drastically reduce accelerator communication by exploration of computation reordering and local buffer usage. Consequently, we present a new analytical methodology to optimize nested loops for inter-tile data reuse with loop transformations like interchange and tiling. We focus on embedded accelerators that can be used in a multi-accelerator System on Chip (SoC), so performance, area, and energy are key in this exploration. 1) On three common embedded applications in the image/video processing domain (demosaicing, block matching, object detection), we show that our methodology reduces data movement up to 2.1x compared to the best case of intra-tile optimization. 2) We demonstrate that our small accelerators (1-3% FPGA resources) can boost a simple MicroBlaze soft-core to the performance level of a high-end Intel-i7 processor.
MYCN-targeting miRNAs are predominantly downregulated during MYCN-driven neuroblastoma tumor formation

MYCN is a transcription factor that plays key roles in both normal development and cancer. In neuroblastoma, MYCN acts as a major oncogenic driver through pleiotropic effects regulated by multiple protein encoding genes as well as microRNAs (miRNAs). MYCN activity is tightly controlled at the level of transcription and protein stability through various mechanisms. Like most genes, MYCN is further controlled by miRNAs, but the full complement of all miRNAs implicated in this process has not been determined through an unbiased approach. To elucidate the role of miRNAs in regulation of MYCN, we thus explored the MYCN-miRNA interactome to establish miRNAs controlling MYCN expression levels. We combined results from an unbiased and genome-wide high-throughput miRNA target reporter screen with miRNA and mRNA expression data from patients and a murine neuroblastoma progression model. We identified 29 miRNAs targeting MYCN, of which 12 miRNAs are inversely correlated with MYCN expression or activity in neuroblastoma tumor tissue. The majority of MYCN-targeting miRNAs in neuroblastoma showed a decrease in expression during murine MYCN-driven neuroblastoma tumor development. Therefore, we provide evidence that MYCN-targeting miRNAs are preferentially downregulated in MYCN-driven neuroblastoma, suggesting that MYCN negatively controls the expression of these miRNAs, to safeguard its expression.
Abstract—eigenvector Methods Are Gaining Increasing

acceptance in the area of spectrum estimation. This paper presents a successful attempt at testing and evaluating the performance of two of the most popular types of subspace techniques in determining the parameters of multiexponential signals with real decay constants buried in noise. In particular, MUSIC (Multiple Signal Classification) and minimum-norm techniques are examined. It is shown that these methods perform almost equally well on multiexponential signals with MUSIC displaying better defined peaks.
EFFECT OF PARTIAL SUBSTITUTION OF COW MILK WITH BAMBARA GROUNDNUT MILK ON THE CHEMICAL COMPOSITION , ACCEPTABILITY AND SHELFLIFE OF YOGHURT

Chemical composition, acceptability and shelf-life of yoghurt produced from bambara groundnut and cow milk were studied. The yoghurt was produced from cow milk partially substituted with bambara groundnut milk in different ratios (0, 10, 20, 30 and 40%). Standard methods were used to determine the chemical, sensory and shelf life properties of the yoghurt samples. Sensory results showed that there was no significant difference (p 0.05) in the aroma and consistency while there was significant difference (p 0.05) in the taste, color and overall acceptability as influenced by varying proportions of added bambara groundnut milk. The pH and total titratable acidity was found between the range of 4.30 4.90 and 1.40 1.85 respectively. Microbial analysis carried out indicated that growth of micro-organisms in the yoghurt samples was almost constant from week 0 to week 3; a decrease was noticed on the fourth week thereby leading to deterioration of the yoghurt samples and reduction in the nutritional composition with storage. The study showed that yoghurt could be kept for three weeks with no appreciable decrease in nutritional composition. There was significant difference (p 0.05) in the protein composition and iron content with increase in added bambara groundnut milk. This work showed the potential of bambara groundnut as an alternative source of milk in yoghurt making with improved nutritional values and consumer acceptability.
Successive Convex Approximations to Cardinality-Constrained Quadratic Programs: A DC Approach ✩

In this paper we consider a cardinality-constrained quadratic program that minimizes a convex quadratic function subject to a cardinality constraint and linear constraints. This class of problems have many applications including portfolio selection, subset selection and compressed sensing. We propose a successive convex approximation method for this class of problems in which the cardinality function is first approximated by a piecewise linear DC function (difference of two convex functions) and a sequence of convex subproblems are then constructed by successively linearizing the concave terms of the DC function. Under some mild assumptions, we establish that any accumulation point of the sequence generated by the method is a KKT point of the DC approximation problem. We show that the basic algorithm can be refined by adding valid inequalities in the subproblems. We report some preliminary computational results which show that our method is promising for finding good suboptimal solutions and is competitive with some other local solution methods for cardinality-constrained quadratic pro
Chirurgie bariatrique et obstétrique Bariatric surgery and obstetrics

MOTS CLÉS Grossesse ; Issues maternelles ; Obésité ; Supplémentations Résumé L’obésité présente un risque important pour les femmes en âge de procréer. La perte de poids avant la conception est la meilleure méthode pour améliorer la fertilité et réduire la morbidité de ces femmes. En cas d’échec, la chirurgie bariatrique est alors la méthode de recours la plus efficace en permettant une perte de poids importante, une amélioration nette de la fertilité et une diminution importante des complications obstétricales et de la morbidité maternelle et néonatale par rapport aux femmes obèses non opérées. L’anneau gastrique ou le bypass gastrique sont actuellement les techniques les plus utilisées en France et sont proposées aux patientes en âge de procréer présentant une obésité morbide. À l’aide d’une revue de la littérature, nous évoquerons les différentes techniques de chirurgie bariatrique et nous aborderons la grossesse après ce type de chirurgie, dont la prise en charge spécifique (surveillance, supplémentations) doit être multidisciplinaire afin d’assurer des grossesses normales et des nouveau-nés en bonne santé tout en poursuivant un contrôle du poids maternel. © 2008 Elsevier Masson SAS. Tous droits réservés.
Gaining Insight to Customer Behavior based on Time Series Data

The success of customer relationship management is dependent upon the organization's ability to truly understand the individual customer and market to them with the optimal product, message and channel. An essential component of this one-to-one marketing strategy is the creation and deployment of a robust customer segmentation system. Through the use of powerful time series data and sophisticated data mining and statistical techniques, organizations can gain valuable insight into the motivation behind customer behaviors. This shift will allow organizations to create products based on the customer's needs and desires and develop more profitable and longer-term customer relationships.
An Optimal Solution to Minimize the Energy Consumption in Wireless Sensor Networks

Wireless Sensor Network has been widely used in all the fields for the past few years. In many recent wireless sensor network applications such as environmental monitoring, medical applications and surveillance, there is a need for providing the uninterrupted coverage of a sensing field with long instant, this is one of the obvious problem attracted many researchers as well as general users. In any aspects, the sensor nodes are energized by low powered devices; it is one of the critical aspects to reduce the energy consumption to improve the lifetime to some extent. In this research, initially we concentrated on the energy consumption for the typical sensor node component by assuming the grid network with shortest path technique. Secondly, the direction is made to conserve energy in wireless sensor networks. Special focus is given over the areas which have not yet get more attention in the literature such as data aggregation along with load balancing techniques. Extensive simulations are conducted in Network Simulator-2 to test the effectiveness of the proposed load balancing scheme. The results proved that the proposed scheme achieves over 8% energy-saving per node and the throughput improves to 18.2% with data collection through multi-hop relay. The simulation results show that, our algorithm can balance the network traffic in real-time.
Design of a low return loss Planar Inverted F Antenna (PIFA) for 4G & WLAN applications loaded with Metamaterial lens

In this paper, an antenna for 4G and WLAN devices is proposed. The proposed antenna is designed using Planar Inverted F Antenna (PIFA) structure. The antenna uses Rogers Duroid 5880 as a dielectric substrate and metallic ground plane. The dimensions of the top patch are 18.5 mm × 18.5 mm and thus making it a low profile antenna. The designed antenna covers WLAN (2.4-2.48 GHz) & 4G LTE (2300-2400 MHz & 2500-2690 MHz) communication standards. The overall volume occupied by the proposed antenna is 44mm × 20mm × 3.8mm. Metamaterial superstate is also analyzed which enhances the gain and bandwidth of the proposed antenna significantly. The antenna is designed and simulated using High Structure Frequency Simulator (HFSS).
Online Scaling in a Highly Available Database

An increasing number of database applications demands high availability combined with online scalability and soft real-time transaction response. This means that scaling must be done online and non-blocking. This paper extends the primary/hot standby approach to high availability with online scaling operations. The challenges are to do this without degrading the response time and throughput of transactions and to support high availability throughout the scaling period. We measure the impact of online scaling on response time and throughput using di(cid:11)erent scheduling schemes. We also show some of the recovery problems that appear in this setting
The Role of the Experimenter in HRI Research - A Case Study Evaluation of Children with Autism Interacting with a Robotic Toy

The general context of the work presented in this paper is assistive robotics with our long-term aim to support children with autism. This paper is part of an investigation into what ways and to what extent a robot can assume the role of a social mediator - encouraging autistic children to interact with the robot, with each other and with co-present adults. The article focuses on the role of the experimenter in these triadic interactions, and provides a case study evaluation of segments of trials where a robot mediated both indirect and direct interactions between children with autism and the experimenter
A new technique for performance evaluation of random access protocols

A new technique is proposed for performance evaluation of random access protocols. This technique is based on the idea that the service probability distribution of a particular random access protocol can be described by a phase-type distribution. By modeling the service probability distribution of a protocol into a phase-type distribution, the performance of the protocol can be evaluated using an equivalent continuous time Markov chain. We demonstrate the applicability of the technique to evaluate the performance of the IEEE 802.3 and the IEEE 802.11 MAC protocols. Furthermore, we provide an example of performance evaluation of a MAC protocol subject to bursty traffic models such as the Markov modulated Poisson process. The accuracy of the results is verified by simulation.
Transionospheric signal detection with chirped wavelets

Chirped wavelets are utilized to detect dispersed signals in the joint time/scale domain. Specifically, pulses that become dispersed by transmission through the ionosphere and are received by satellites as nonlinear chirps are investigated. Since the dispersion greatly lowers the signal-to-noise ratios, it is difficult to isolate the signals in the time domain. Satellite data are examined with discrete wavelet expansions. Detection is accomplished via a template matching threshold scheme. Quantitative experimental results demonstrate that the chirped wavelet detection scheme is successful in detecting the transionospheric pulses at very low signal-to-noise ratios.
RuleSN: Research and Application of Social Network Access Control Model

Current rapid increasing implementations in data diversity, autonomy and dynamic privilege management, fine-grained access control in social networks have resulted in various challenges in applying existing access control models. We focus on this issue and propose a new social network access control model, RuleSN, using logical authorization language. The model provides high performance of authorization expressiveness and flexibility that can perfectly describe relations of User to User (U2U), User to Resource (U2R), Resource to Resource (R2R) and attributes of users and resources. First, this paper elaborates the formal definitions of the RuleSN model. Second, we describe the model's authorization specification and verification policies and explain the syntax and semantics of the authorization language. Finally, the implementation, application and expressiveness of the model discussed by examples.
Dynactin is required for bidirectional organelle transport

Kinesin II is a heterotrimeric plus end–directed microtubule motor responsible for the anterograde movement of organelles in various cell types. Despite substantial literature concerning the types of organelles that kinesin II transports, the question of how this motor associates with cargo organelles remains unanswered. To address this question, we have used Xenopus laevis melanophores as a model system. Through analysis of kinesin II–mediated melanosome motility, we have determined that the dynactin complex, known as an anchor for cytoplasmic dynein, also links kinesin II to organelles. Biochemical data demonstrates that the putative cargo-binding subunit of Xenopus kinesin II, Xenopus kinesin II–associated protein (XKAP), binds directly to the p150Glued subunit of dynactin. This interaction occurs through aa 530–793 of XKAP and aa 600–811 of p150Glued. These results reveal that dynactin is required for transport activity of microtubule motors of opposite polarity, cytoplasmic dynein and kinesin II, and may provide a new mechanism to coordinate their activities.
Automatic creation of semantic data about football transfer in sport news

The semantic annotation of textual content is important for the success of many information integration systems. In this paper, we present a method for generating semantic annotations about transfer in football news. Semantic web technologies are applied to extend the knowledge base of KIM platform so that named entities in this specific domain could be recognized. We study and define language models to recognize the semantic relation for football transfers. At the same time, we propose a pronoun recognition method using extraction rules to improve the relation recognition process. The experiment showed promising results on the data set built from Sky Sports news [27]. The precisions achieved in both cases, with and without integration of the pronoun recognition method, are both over 80%. In particular, the latter helps increase the recall value to around 10%.
Change detection from very high resolution satellite time series with variable off-nadir angle

Very high resolution (VHR) satellite images have the potential for revealing changes occurred overtime with a superior level of detail. However, their use for metric purposes requires accurate geo-localization with ancillary DEMs and GCPs to achieve sub-pixel terrain correction, in order to obtain images useful for mapping applications. Change detection with a time series of VHS images is not a simple task because images acquired with different off-nadir angles have a lack of pixel-to-pixel image correspondence, even after accurate geo-correction. This paper presents a procedure for automatic change detection able to deal with variable off-nadir angles. The case study concerns the identification of damaged buildings from pre- and post-event images acquired on the historic center of L’Aquila (Italy), which was struck by an earthquake in April 2009. The developed procedure is a multi-step approach where (i) classes are assigned to both images via object-based classification, (ii) an initial alignment is provided with an automated tile-based rubber sheeting interpolation on the extracted layers, and (iii) change detection is carried out removing residual mis-registration issues resulting in elongated features close to building edges. The method is fully automated except for some thresholds that can be interactively set to improve the visualization of the damaged buildings. The experimental results proved that damages can be automatically found without additional information, such as digital surface models, SAR data, or thematic vector layers.
Differentiation without Distancing. Explaining Bi-Polarization of Opinions without Negative Influence

Explanations of opinion bi-polarization hinge on the assumption of negative influence, individuals’ striving to amplify differences to disliked others. However, empirical evidence for negative influence is inconclusive, which motivated us to search for an alternative explanation. Here, we demonstrate that bi-polarization can be explained without negative influence, drawing on theories that emphasize the communication of arguments as central mechanism of influence. Due to homophily, actors interact mainly with others whose arguments will intensify existing tendencies for or against the issue at stake. We develop an agent-based model of this theory and compare its implications to those of existing social-influence models, deriving testable hypotheses about the conditions of bi-polarization. Hypotheses were tested with a group-discussion experiment (N = 96). Results demonstrate that argument exchange can entail bi-polarization even when there is no negative influence.