Miracle-dz/UniFAR-FTUs huggingface dataset:
Degree-Based Power Control Method for Increasing Spatial Reuse in TDMA-Based Wireless Mesh Networks

Wireless Mesh Networks (WMNs) have attracted significant interest as a cost-effective wireless network infrastructure. However, the efficiency of wireless resource utilization decreases by radio interference when multiple transmissions in an interference region occur simultaneously. So decreasing radio interference is one of the major problems in wireless network.In the present paper, we propose a degree-based power control method of wireless mesh nodes to enhance spatial reuse in WMNs with TDMA MAC protocol. The proposed method is an attempt to reduce the radio interference and improve the spatial reuse of the WMN by decreasing the transmission power of mesh nodes, while maintaining the network connectivity at a certain level. Numerical evaluation results reveal that the proposed method decreases the frame length by up to 22%.
Humanizing NAO robot teleoperation using ROS

The work presented here proposes two different ROS packages to enrich the teleoperation of the robot NAO: speech-based teleoperation (in Basque) and gesture-based teleoperation together with arm control. These packages have been used and evaluated in a human mimicking experiment. The tools offered can serve as a base for many applications.
Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment

This paper describes a concept for a collision avoidance system for ships, which is based on model predictive control. A finite set of alternative control behaviors are generated by varying two parameters: offsets to the guidance course angle commanded to the autopilot and changes to the propulsion command ranging from nominal speed to full reverse. Using simulated predictions of the trajectories of the obstacles and ship, compliance with the Convention on the International Regulations for Preventing Collisions at Sea and collision hazards associated with each of the alternative control behaviors are evaluated on a finite prediction horizon, and the optimal control behavior is selected. Robustness to sensing error, predicted obstacle behavior, and environmental conditions can be ensured by evaluating multiple scenarios for each control behavior. The method is conceptually and computationally simple and yet quite versatile as it can account for the dynamics of the ship, the dynamics of the steering and propulsion system, forces due to wind and ocean current, and any number of obstacles. Simulations show that the method is effective and can manage complex scenarios with multiple dynamic obstacles and uncertainty associated with sensors and predictions.
Hydrodynamic Timescales and Temporal Structure of Gamma-Ray Bursts

We calculate the hydrodynamic timescales for a spherical ultrarelativistic shell that is decelerated by the ISM and discuss the possible relations between these timescales and the observed temporal structure in γ-ray bursts. We suggest that the bursts' duration is related to the deceleration time, the variability is related to the ISM inhomogeneities, and that precursors are related to internal shocks within the shell. Good agreement can be achieved for these quantities with reasonable, not fine-tuned, astrophysical parameters. The difference between Newtonian and relativistic reverse shocks may lead to the observed bimodal distribution of bursts' durations.
Towards Information Systems Design for Value Webs

In this paper we discuss the alignment between a business model of a value web and the information systems of the participating companies needed to implement the business model. Traditional business-IT alignment approaches focus on one single company, but in a value web we are dealing with various independent businesses. Since a value web is actually a web of services, delivered by IT systems owned by different companies, to ensure alignment we need to specify the services and their properties and then map them on the available IT support in the different companies. Such mappings have to be evaluated in terms of their impact on the profitability of participating in the value web of the different companies. We propose techniques to map services to IT support and show how to do commercial trade-offs.
Functional-Lexical Code-Mixing Patterns as Evidence for Language Dominance in Young Bilingual Children: A Minimalist Approach

In this paper we address the issue of how language is represented in the bilingual mind. We specifically investigate functional-lexical mixed utterances of the type Det + N as produced by young English/Spanish bilingual children. Functional-lexical mixings are defined here as constituents formed by a functional morpheme (either free or bound) from one language and a lexical (referential) morpheme from the other. Examples of English/Spanish Det + N mixings are given in (1) and (2).
Influence of Aerobic Training on the Reduced Vasoconstriction to Angiotensin II in Rats Exposed to Intrauterine Growth Restriction: Possible Role of Oxidative Stress and AT2 Receptor of Angiotensin II

Intrauterine growth restriction (IUGR) is associated with impaired vascular function, which contributes to the increased incidence of chronic disease. The aim of this study was to investigate whether aerobic training improves AngII-induced vasoconstriction in IUGR rats. Moreover, we assess the role of superoxide dismutase (SOD) isoforms and NADPH oxidase-derived superoxide anions in this improvement. Female Wistar rats were randomly divided into two groups on day 1 of pregnancy. A control group was fed standard chow ad libitum, and a restricted group was fed 50% of the ad libitum intake throughout gestation. At 8 weeks of age, male offspring from both groups were randomly assigned to 4 experimental groups: sedentary control (SC), trained control (TC), sedentary restricted (SRT), and trained restricted (TRT). The training protocol was performed on a treadmill and consisted of a continuous 60-min session 5 days/week for 10 weeks. Following aerobic training, concentration–response curves to AngII were obtained in endothelium-intact aortic rings. Protein expression of SOD isoforms, AngII receptors and the NADPH oxidase component p47phox was assessed by Western blot analysis. The dihydroethidium was used to evaluate the in situ superoxide levels under basal conditions or in the presence of apocynin, losartan or PD 123,319. Our results indicate that aerobic training can prevent IUGR-associated increases in AngII-dependent vasoconstriction and can restore basal superoxide levels in the aortic rings of TRT rats. Moreover, we observed that aerobic training normalized the increased p47phox protein expression and increased MnSOD and AT2 receptor protein expression in thoracic aortas of SRT rats. In summary, aerobic training can result in an upregulation of antioxidant defense by improved of MnSOD expression and attenuation of NADPH oxidase component p47phox. These effects are accompanied by increased expression of AT2 receptor, which provide positive effects against Ang II–induced superoxide generation, resulting in attenuation of AngII-induced vasoconstriction.
Facilitation of Drug Transport across the Blood–Brain Barrier with Ultrasound and Microbubbles

Medical treatment options for central nervous system (CNS) diseases are limited due to the inability of most therapeutic agents to penetrate the blood–brain barrier (BBB). Although a variety of approaches have been investigated to open the BBB for facilitation of drug delivery, none has achieved clinical applicability. Mounting evidence suggests that ultrasound in combination with microbubbles might be useful for delivery of drugs to the brain through transient opening of the BBB. This technique offers a unique non-invasive avenue to deliver a wide range of drugs to the brain and promises to provide treatments for CNS disorders with the advantage of being able to target specific brain regions without unnecessary drug exposure. If this method could be applied for a range of different drugs, new CNS therapeutic strategies could emerge at an accelerated pace that is not currently possible in the field of drug discovery and development. This article reviews both the merits and potential risks of this new approach. It assesses methods used to verify disruption of the BBB with MRI and examines the results of studies aimed at elucidating the mechanisms of opening the BBB with ultrasound and microbubbles. Possible interactions of this novel delivery method with brain disease, as well as safety aspects of BBB disruption with ultrasound and microbubbles are addressed. Initial translational research for treatment of brain tumors and Alzheimer’s disease is presented.
Fast exact shortest path and distance queries on road networks with parametrized costs

We study a scenario for route planning in road networks, where the objective to be optimized may change between every shortest path query. Since this invalidates many of the known speedup techniques for road networks that are based on preprocessing of shortest path structures, we investigate optimizations exploiting topological structures. We experimentally evaluate our technique on a large set of real-world road networks of various data sources. With lightweight preprocessing our technique answers long-distance queries across continental networks significantly faster than previous approaches towards the same problem formulation.
Towards intent-driven bidterm suggestion

In online advertising, pervasive in commercial search engines, advertisers typically bid on few terms, and the scarcity of data makes ad matching difficult. Suggesting additional bidterms can significantly improve ad clickability and conversion rates. In this paper, we present a large-scale bidterm suggestion system that models an advertiser's intent and finds new bidterms consistent with that intent. Preliminary experiments show that our system significantly increases the coverage of a state of the art production system used at Yahoo while maintaining comparable precision.
Reconstruction of cloud geometry using a scanning cloud radar

Abstract. Clouds are one of the main reasons of uncertainties in the forecasts of weather and climate. In part, this is due to limitations of remote sensing of cloud microphysics. Present approaches often use passive spectral measurements for the remote sensing of cloud microphysical parameters. Large uncertainties are introduced by three-dimensional (3-D) radiative transfer effects and cloud inhomogeneities. Such effects are largely caused by unknown orientation of cloud sides or by shadowed areas on the cloud. Passive ground-based remote sensing of cloud properties at high spatial resolution could be crucially improved with this kind of additional knowledge of cloud geometry. To this end, a method for the accurate reconstruction of 3-D cloud geometry from cloud radar measurements is developed in this work. Using a radar simulator and simulated passive measurements of model clouds based on a large eddy simulation (LES), the effects of different radar scan resolutions and varying interpolation methods are evaluated. In reality, a trade-off between scan resolution and scan duration has to be found as clouds change quickly. A reasonable choice is a scan resolution of 1 to 2\degree. The most suitable interpolation procedure identified is the barycentric interpolation method. The 3-D reconstruction method is demonstrated using radar scans of convective cloud cases with the Munich miraMACS, a 35 GHz scanning cloud radar. As a successful proof of concept, camera imagery collected at the radar location is reproduced for the observed cloud cases via 3-D volume reconstruction and 3-D radiative transfer simulation. Data sets provided by the presented reconstruction method will aid passive spectral ground-based measurements of cloud sides to retrieve microphysical parameters.
A display system for the Stellar graphics supercomputer model GS1000

This paper describes a high performance display system that has been incorporated into the overall architecture of the Stellar Graphics Supercomputer Model GS1000. The display system is tightly coupled to the CPU, memory system and vector processing unit of this supercomputer, and is capable of rendering 150,000 shaded triangles/sec, and 600,000 short vectors/sec. The goal of the architecture is to share hardware resources between the CPU and display system and achieve a high bandwidth connection between them. This coupling of the display system and the processor, the architecture of the rendering processor, and the two ASICs that are used to implement the rendering processor are described.In addition, the display system architecture is contrasted to other approaches to high performance graphics, and design trade-offs and possible extensions are described. The implementation of popular display algorithms on the architecture is discussed, and their performance specified. The reader is advised that Stellar Computer Inc. is seeking patent protection for work described in this paper.
`What is the usefulness of your schoolwork?'

Various motivational frameworks converge to suggest that highlighting the relevance of a learning activity yields benefits for students' learning and performance. Herein, we review a set of studies grounded in self-determination theory's distinction between intrinsic and extrinsic goals, which show that the beneficial effect of a learning activity's utility value should be nuanced. Specifically, this effect depends on the particular goal that activity is thought to serve, such that intrinsic goal framing enhances learning and performance, whereas extrinsic goal framing does not. Such effects emerge regardless of students' personal goal preferences. Overall, this research suggests that teachers might do well to consider the content of the promoted goal when highlighting the utility value of a learning activity.
A preliminary investigation of cognitive appraisal and cardiovascular reactivity and recovery in Arab Americans.

BACKGROUND Arab Americans exhibit higher rates of hypertension and other cardiovascular risk factors relative to national averages. While research suggests some minorities may exhibit increased cardiovascular reactivity (CVR) to, and slowed recovery from, stress compared to Whites, which may represent a risk factor for hypertension and cardiovascular disease, this has not been studied in Arab Americans. This study examined differences between Arab Americans and Whites in cognitive appraisal, and blood pressure and heart rate (HR) reactivity and recovery to laboratory stressors. METHODS The undergraduate sample included 27 Arab Americans (16 female) and 27 gender matched Whites. Eligible participants completed two stressful laboratory tasks (mental arithmetic [MA] and stress-recall [SR]). Cognitive appraisals were assessed for each task, and physiological data were collected during baseline, each laboratory task, and recovery. Ethnicity differences in baseline cardiovascular values and cognitive appraisals were examined with t-tests, while differences in CVR and recovery were tested with ANCOVA, controlling for initial values. RESULTS Arab Americans showed lower baseline systolic blood pressure and mean arterial pressure than Whites. Arab Americans also reported greater threat and stress associated with MA, and greater threat for SR. No CVR differences were observed during MA; however during and after SR, Arab Americans evidenced lesser systolic and diastolic blood pressure reactivity and lesser HR recovery compared to Whites. CONCLUSIONS Overall, Arab Americans showed lesser reactivity than Whites, but also exhibited slower HR recovery. These results may be attributable to physiological habituation to chronic stress associated with minority status.
Distributed Searchable Symmetric Encryption

Searchable Symmetric Encryption (SSE) allows a client to store encrypted data on a storage provider in such a way, that the client is able to search and retrieve the data selectively without the storage provider learning the contents of the data or the words being searched for. Practical SSE schemes usually leak (sensitive) information during or after a query (e.g., the search pattern). Secure schemes on the other hand are not practical, namely they are neither efficient in the computational search complexity, nor scalable with large data sets. To achieve efficiency and security at the same time, we introduce the concept of distributed SSE (DSSE), which uses a query proxy in addition to the storage provider. We give a construction that combines an inverted index approach (for efficiency) with scrambling functions used in private information retrieval (PIR) (for security). The proposed scheme, which is entirely based on XOR operations and pseudo-random functions, is efficient and does not leak the search pattern. For instance, a secure search in an index over one million documents and 500 keywords is executed in less than 1 second.
Mantle Heterogeneities and the SCEC Reference Three-Dimensional Seismic Velocity Model Version 3

We determine upper mantle seismic velocity heterogeneities below Southern California from the inversion of teleseismic travel-time residuals. Teleseismic P-wave arrival times are obtained from three temporary passive experiments and Southern California Seismic Network (SCSN) stations, producing good raypath coverage. The inversion is performed using a damped least-squares conjugate gradient method (LSQR). The inversion model element spacing is 20 km. Before the inversion, the effects of crustal velocity heterogeneities represented by the Southern California Earthquake Center (SCEC) seismic velocity model version 2 are removed from the teleseismic travel times. The P-wave inversion produces a variance reduction of 43%. S-wave velocities are determined from laboratory Vp/Vs ratios. The most prominent features imaged in the results are high P-wave velocities (+3%) in the uppermost mantle beneath the northern Los Angeles basin, and the previously reported tabular high-velocity anomaly (+3%) to depths of 200 km beneath the Transverse Ranges, crosscutting the San Andreas fault. We incorporate the upper mantle seismic velocity heterogeneities into the SCEC Southern California reference seismic velocity model. The prior accounting for the crustal velocity heterogeneity demonstrates the utility of the top-down method of the SCEC seismic velocity model development.
SGameFlow framework: How to experience enjoyment in Serious Game (SG) for Motor Impaired Users (MIU)

Benefiting from the popularity of computer game, Serious Game (SG) has been reaching a wide range of users. However, research on user interface design factors in SG for the Motor Impaired User (MIU) is still narrow, especially for the enjoyment experience context. This paper is aimed to proposed user interface design factors framework (SGameFlow) that makes MIU experience enjoyment when playing SG. This study is based on GameFlow Model to develop a rigorous user interface design factors that makes MIU experience enjoyment when playing SG. We make use of certain original model's factors together with three new factors (learning opportunities, accessibility and adaptivity) to predict user interface design factors of MIU enjoyment experience in SG.
Fuzzy Inference Based Adaptive Result Verification Scheme in Desktop Grids

A result verification procedure is required to guarantee the correctness of task results executed by any unspecified resource in desktop grids. Voting-based and trust-based schemes have typically been used for desktop grid. However, these schemes can encounter two problems: waste of resources, due to redundant replications of each task, and increased turnaround time, due to the inability to deal with a dynamic changeable execution environment. To overcome these problems, we propose a fuzzy inference-based replication scheme that can adaptively determine the number of replications per task needed for result verification. Simulation results indicate that our scheme is superior to others in terms of turnaround time of entire tasks, quantity of resources consumed, and number of reallocations per task.
REGION-BASED RELEVANCE FEEDBACK IN CONCEPT-BASED IMAGE RETRIEVAL

The image retrieval approach described in this paper combines two layers, the conceptual and the featurebased. It works at the region or visual object level and uses a thesaurus to explore associations between text and image content and enable concept-level queries. The solution described uses relevance feedback both at the query session level and to discover new associations between text and image. Particular emphasis is given in the paper to the limitation of the typical relevance feedback solutions presented and to the benefits of using the relevance feedback in conjunction with the two-layer model presented. Some preliminary results are reported using the prototype VOIR Visual Object Information Retrieval system.
Finding Folksonomy Experts for Taxonomy Construction

In folksonomy, different users perform diverse tagging behaviors. Although many works have been reported on folksonomy based taxonomy construction, few attentions have been paid to the data preparation for the construction from the behavior perspective. To ensure constructing taxonomy with qualified folksonomy, a method is proposed in the paper to find representative tagging users, so called folksonomy experts, tending to perform representative tagging behaviors. The evaluation confirms that the proposed method is capable of finding folksonomy experts. The method proposed can be utilized to select qualified representative data for the existing folksonomy based taxonomy construction algorithms.
Simulation of intersecting black brane solutions

A family of spherically symmetric solutions with horizon in the model with multi-component anisotropic fluid (MCAF) is obtained. The metric of any solution contains n-1 Ricci-flat ``internal space'' metrics and for certain equations of state (p_i = \pm \rho) coincides with the metric of intersecting black brane solution in the model with antisymmetric forms. Examples of simulation of intersecting M2 and M5 black branes are considered. The post-Newtonian parameters beta and gamma corresponding to the 4-dimensional section of the metric are calculated.
Predicting domain adaptivity: redo or recycle?

Over the years, the academic researchers have contributed various visual concept classifiers. Nevertheless, given a new dataset, most researchers still prefer to develop large number of classifiers from scratch despite expensive labeling efforts and limited computing resources. A valid question is why not multimedia community ``embrace the green" and recycle off-the-shelf classifiers for new dataset. The difficulty originates from the domain gap that there are many different factors that govern the development of a classifier and eventually drive its performance to emphasize certain aspects of dataset. Reapplying a classifier to an unseen dataset may end up GIGO (garbage in, garbage out) and the performance could be much worse than re-developing a new classifier with very few training examples. In this paper, we explore different parameters, including shift of data distribution, visual and context diversities, that may hinder or otherwise encourage the recycling of old classifiers for new dataset. Particularly, we give empirical insights of when to recycle available resources, and when to redo from scratch by completely forgetting the past and train a brand new classifier. Based on these analysis, we further propose an approach for predicting the negative transfer of a concept classifier to a different domain given the observed parameters. Experimental results show that the prediction accuracy of over 75\% can be achieved when transferring concept classifiers learnt from LSCOM (news video domain), ImageNet (Web image domain) and Flickr-SF (weakly tagged Web image domain), respectively, to TRECVID 2011 dataset (Web video domain).