Miracle-dz/UniFAR-FTUs huggingface dataset:
The spectroscopic orbit of the K-giant binary γ Canis Minoris

We have determined an improved orbit for the bright, evolved, double lined binary γ Canis Minoris. The system has an orbital period of 389.31 days and an eccentricity of 0.2586. We have revised the secondary to primary mass ratio to 0.987. The spectral types of the primary and secondary are K4 III and K1: III, respectively, and the components have a V magnitude difference of 2.2. Orbital fits to the Hipparcos astrometry are not definitive, but they suggest an orbital inclination of ∼ 66°, which produces masses of 1.88 and 1.85 M⊙ for the components. A comparison with evolutionary tracks results in an age of 1.3 Gyr. STELLA very low amplitude radial velocity residuals of the secondary indicate a period of 278 days. We interpret this as the rotation period of the secondary, detectable because of star spots rotating in and out of view. This period is nearly identical to the pseudosynchronous rotation period of the star. The primary is rotating more slowly than its pseudosynchronous rate. (© 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Increased IL-33 in Synovial Fluid and Paired Serum Is Associated with Disease Activity and Autoantibodies in Rheumatoid Arthritis

Objectives. IL-33, a newly found cytokine which is involved in joint inflammation, could be blocked by a decoy receptor—sST2. The expression and correlation of IL-33 and sST2 in rheumatoid arthritis (RA) are of great interest. Methods. Synovial fluid (SF) was obtained from 120 RA and 30 osteoarthritis (OA) patients, and paired sera were collected from 54 of these RA patients. The levels of IL-33 and sST2 were measured by ELISA. Results. SF IL-33 was significantly higher in RA than in OA, which was correlated with disease activity score 28, erythrocyte sedimentation rate, rheumatoid factor (RF)-IgM, RF-IgG, glucose phosphate isomerase (GPI), and immunoglobulin. Serum IL-33 was correlated positively with SF IL-33 in RA. Furthermore, it was correlated with RF-IgM and GPI. sST2 was partly detectable in RA (13 out of 54, 24.1%), while not in OA. Serum sST2 in RA had no significant correlation with serum IL-33 or SF IL-33. However, SFs from both RA and OA patients did not express sST2. Conclusions. This study supported that IL-33 played an important role in the local pathogenesis of RA. Considering the tight correlation between IL-33 and clinical features, it may become a new target of local treatment.
Longitudinal Impacts of Home Computer Use on Primary School Children s Reading and Mathematics Achievement

This study investigates the impact of children’s Home Computer Use (HCU), both educational and recreational, on their achievement in Reading and Mathematics during primary school. The data are taken from a longitudinal study in England called Effective Provision of Preschool, Primary and Secondary Education (EPPSE). Hierarchical linear regressions were employed to investigate the main (direct) effects, and path analyses were applied to study the mediation (indirect) effects of HCU on pupils’ school achievement. The main effect models indicated that HCU has very little ‘extra’ impact on children’s school results over and beyond their prior achievement and demographic background. By contrast, results from path analyses showed a statistically significant mediation effect, through the home learning environment and self-regulation, on children’s Reading and Mathematics scores. The implications of the findings for policy and practice are also discussed.
Photonic-enabled millimeter-wave F-band wireless link using photonic integrated circuits

Millimeter-waves (30-300 GHz) have interest due to the wide bandwidths available for carrying information, enabling broadband wireless communications. Photonics is a key technology for millimeter wave signal generation, recently demonstrating the use of photonic integration to reduce size and cost. In this paper, we present two dual-wavelength Photonic Integrated Circuit structures designed for signal generation using the optical heterodyne technique. We demonstrate a 1 Gbps data rate wireless link that does not require any stabilization scheme to lock the two wavelengths. Both integrated dual-wavelength sources are based on an Arrayed Waveguide Grating element. A novel building block-Multimode Interference Reflectors - is used to integrate on-chip one of these structures, without need of cleaved facets to define the laser cavity. This fact enables us to locate any of these structures at any location within the photonic chip.
Optimal Derivative Investment in Continuous Time

We determine the optimal investment in a risky asset, and in a set of derivatives written on this asset, when the underlying price process is a pure jump L evy process. Both the in nite horizon problem with intermediate consumption and the nite horizon problem with no intermediate consumption are solved in closed form for investors with HARA utility when the statistical and risk-neutral price processes are in the variance gamma (VG) class of processes. We nd that optimal derivative contracts are written on successive price relatives, paying a function of these relatives continuously through time. For statistical volatilities below risk-neutral ones, we show that the optimal derivative contract for intermediate levels of risk aversion is a collar that nances downside protection by selling o upside gain.
Embedded multi-sensors objects detection and tracking for urban autonomous driving

This paper proposes an embedded real time method for detecting and tracking of multiobjects including vehicles, pedestrians, motorbikes and bicycles in urban environment. The features of different objects are learned as a deformable object model through the combination of a latent support vector machine (LSVM) and histograms of oriented gradients (HOG). Laser depth data have been used as a priori to generate objects hypothesis regions and estimate HOG feature pyramid level to reduce the detection time of previously presented algorithm. Detected objects are tracked through a particle filter which fuses the observations from laser map and sequential images. We use the accurate laser data for state predication and use image HOG information for likelihood calculation. The likelihood finds the maximum HOG feature compatibility for both root and parts of the tracked objects to increase tracking accuracy for deformable objects such as pedestrians in crowded scenes. Extensive experiments with urban scenarios showed that the proposed method can improve the detection and tracking in urban environment.
Experiences of Hijabi Women: Finding a Way Through the Looking Glass for Muslim Americans

The purpose of this study was to describe the experiences of Muslim women who wear the hijab, their perceptions of the how wearing the hijab impacted their relationships, identity formation and cultural adaptation in the American workplace. Through the analysis of qualitative data, this exploratory phenomenological study investigated the lived experiences of Muslim women to gain an understanding of how the wearing of the hijab impacted cross-cultural interactions, how they maintained their personal and social identities, coped with stress, and perceived discrimination and feelings of isolation. Qualitative interviews with seven participants were conducted in the U.S. and the results varied.
Cost-Aware Automatic Virtual Machine Scaling in Fine Granularity for Cloud Applications

It is a tendency for enterprises to deploy their applications on Infrastructure as a Service (IaaS) platforms. Many latest IaaS service providers offer Virtual Machine (VM) instances with various capacities and prices by the minute. In this paper, based on the observation that the workload of nowaday applications fluctuates frequently, we propose a cost-aware automatic VM scaling method of fine granularity to satisfy the Service Level Agreement (SLA) and minimize the rent of VMs down to the minute. In the environment with sporadic and sharp swings of workload, our approach acts quickly to get suitable VM scaling scheme to stabilize the response time, reduce the SLA violations and save the rent of VM usage.
Efficient Query Propagation by Adaptive Bordercast Operation in Dense Ad Hoc Network

We designed the Adaptive Bordercast Resolution Protocol for efficient query propagation in a flat ad hoc network. The characteristic of Ad hoc networks like dynamic topology, network density causes asymptotic packet generation that results in degraded performance of routing protocols. The Bordercast Resolution Protocol (BRP) under Zone Routing Protocol (ZRP) outperforms flooding, albeit naive query propagation technique. We can optimize the performance of bordercast operation by setting the optimal routing zone radius. In this paper, we present and examine the characteristics of new adaptive routing protocol based on the ZRP protocol. The results show that the cost of discovering the route by adaptive bordercast is better than the native bordercast resolution protocol
Highly scalable graph search for the Graph500 benchmark

Graph500 is a new benchmark to rank supercomputers with a large-scale graph search problem. We found that the provided reference implementations are not scalable in a large distributed environment. We devised an optimized method based on 2D partitioning and other methods such as communication compression and vertex sorting. Our optimized implementation can handle BFS (Breadth First Search) of a large graph with 236 (68.7 billion vertices) and 240 (1.1 trillion) edges in 10.58 seconds while using 1366 nodes and 16,392 CPU cores. This performance corresponds to 103.9 GE/s. We also studied the performance characteristics of our optimized implementation and reference implementations on a large distributed memory supercomputer with a Fat-Tree-based Infiniband network.
Japanese Speakers ’ Confusion of Phonemically Contrasting English Words : A Link Between Phoneme Perception and Lexical Processing

This study examined the link between phoneme perception and lexical processing in a second language (L2) through four experiments on testing and training of word translation. Results showed that translation performance generally differed as a function of perceptual difficulty of phonemes in words. In contrast, perceptual difficulty did not always influence the translation performance during extensive laboratory training. These results suggest that the link between phoneme perception and lexical processing in L2 is stronger in longitudinal vocabulary acquisition than in the learning by short-term extensive training.
Knowledge Extraction and Consolidation from Social Media ( KECSM 2012 ) Preface

An increasing number of innovative applications use data from online social networks. In many cases data analysis tasks, like opinion mining processes, are applied on platforms such as Twitter, in order to discover what people think about various issues. In our view, selecting the proper data set is paramount for the analysis tasks to produce credible results. This direction, however, has not yet received a lot of attention. In this paper we propose and discuss in detail a platform for supporting processes such as opinion mining on Twitter data, with emphasis on the selection of the proper data set. The key point of our approach is the representation of term associations, user associations, and related attributes in a single model that also takes into account their evolution through time. This model enables flexible queries that combine complex conditions on time, terms, users, and their associations.
DETECTION OF IRREGULAR PHONATION IN SPEECH

The problem addressed here is that of detecting irregular phonation during conversational speech. While most published work tackles this problem only by focusing on the voiced regions of speech, we focus on detecting irregular phonation without assuming prior knowledge of voiced regions. In addition, we improve the pitch estimation accuracy of a current pitch tracking algorithm in regions of irregular phonation, where most pitch trackers fail to perform well. The algorithm has been tested on the TIMIT and NIST 98 databases. The detection rate for the TIMIT database is 91.8% (17.42% false detections). The detection rate for the NIST 98 database is 91.5% (12.8% false detections). The pitch detection accuracy increased from 95.4% to 98.3% for the TIMIT database, and from 94.8% to 97.4% for the NIST 98 database.
Restoration of turbulence profile from scintillation indices

An algorithm that permits to measure atmospheric turbulence by statistical analysis of light flux fluctuations in four concentric-ring apertures is described in detail. It consists of computing the scintillation indices for each aperture and pairwise aperture combination and in fitting the set of measured indices to a model with a small number of turbulent layers. The performance of this method is analyzed by means of simulations and using the real data from a Multi-Aperture Scintillation Sensor. It is shown that turbulence profile with a vertical resolution of can be reconstructed and that the errors of the measured intensities of turbulent layers are typically around 10% of the integrated intensity. The integral parameters like seeing and isoplanatic angle are measured with few percent accuracy.
An efficient dynamic auction for heterogeneous commodities

This article proposes a new dynamic design for auctioning multiple heterogeneous commodities. An auctioneer wishes to allocate K types of commodities among n bidders. The auctioneer announces a vector of current prices, bidders report quantities demanded at these prices, and the auctioneer adjusts the prices. Units are credited to bidders at the current prices as their opponents' demands decline, and the process continues until every commodity market clears. Bidders, rather than being assumed to behave as price-takers, are permitted to strategically exercise their market power. Nevertheless, the proposed auction yields Walrasian equilibrium prices and, as from a Vickrey-Clarke-Groves mechanism, an efficient allocation. (JEL D44)
Remembrance of things tagged: how tagging effort affects tag production and human memory

We developed a low-effort interaction method called Click2Tag for social bookmarking. Information foraging theory predicts that the production of tags will increase as the effort required to do so is lowered, while the amount of time invested decreases. However, models of human memory suggest that changes in the tagging process may affect subsequent human memory for the tagged material. We compared (1) low-effort tagging by mouse-clicking (Click2Tag), (2) traditional tagging by typing (type-to-tag), and (3) baseline, no tagging conditions. Our results suggest that (a) Click2Tag increases tagging rates, (b) Click2Tag improves recognition of facts from the tagged text when compared to type-to-tag, and (c) Click2Tag is comparable to the no-tagging baseline condition on recall measures. Results suggest that tagging by clicking strengthens the memory traces by repeated readings of relevant words in the text and, thus, improves recognition.
Adaptive Linear Filtering Compression on realtime sensor networks

We present a lightweight lossless compression algorithm for realtime sensor networks. Our proposed Adaptive Linear Filtering Compression (ALFC) algorithm performs predictive compression, using adaptive linear filtering to predict sample values followed by entropy coding of prediction residuals, encoding a variable number of samples into fixed-length packets. Adaptive prediction eliminates the need to determine prediction coefficients a priori and, more importantly, allows compression to dynamically adjust to a changing source. The algorithm requires only integer arithmetic operations and thus is compatible with sensor platforms that do not support floating-point operations. Significant robustness to packets losses is provided by including small but sufficient overhead data to allow samples in each packet to be independently decoded. Real-world evaluations on seismic data from a wireless sensor network testbed show that ALFC provides more effective compression and uses less resources than some other lossless compression approaches such as S-LZW. Experiments in a multi-hop sensor network also show that ALFC can significantly improve raw data throughput and energy efficiency.
Optimal design of high performance repetitive controller for shunt active filters using Strength Pareto multi-objective optimization approach

In this paper an algorithm for optimal design of active power filters using Strength Pareto multi-objective optimization approach is proposed. Some parameters of the repetitive current controller together with the inverter's DC bus voltage have been considered as design variables. Different optimizing pairs of objective functions including THD of the line currents and the transient response of the filter have been considered and discussed. The proposed methodology gives a wider horizon to the controller design task for active power filters. The simulation and experimental results prove the effectiveness of the proposed design methodology.
Neuromechanics of Multifunctionality during Rejection in Aplysia californica

How are the same muscles and neurons used to generate qualitatively different behaviors? We studied this question by analyzing the biomechanical and neural mechanisms of rejection responses in the marine mollusk Aplysia californica and compared these mechanisms with those used to generate swallowing responses (Ye et al., 2006). During rejection, the central grasper of the feeding structure closes to push inedible food out of the buccal cavity. This contrasts with swallowing, during which the grasper is open as it moves toward the jaws (protracts). We examined how the shape change of the grasper during rejection mechanically reconfigured the surrounding musculature. Grasper shape change increased the effectiveness of protractor muscle I2. The closed grasper alters the function of another muscle, the hinge, which becomes capable of inducing ventral rotations of rejected material. In contrast, during large-amplitude swallows, the hinge muscle mediates dorsal rotations of ingested material. Finally, after the grasper opens, its change in shape induces a delay in the activation of other surrounding muscles, the I1/I3/jaw complex, whose premature activation would close the halves of the grasper and induce it to pull inedible material back inward. The delay in activation of the I1/I3/jaw complex is partially attributable to identified multiaction neurons B4/B5. The results suggest that multifunctionality emerges from a periphery in which flexible coalitions of muscles may perform different functions in different mechanical contexts and in which neural circuitry is capable of reorganizing to exploit these coalitions by changes in phasing, duration, and intensity of motor neuronal activation.
A Study On The Relationship Between Attachment Styles, Self Esteem And Loneliness Amongst Adolescents

Background: Attachment styles, self esteem and social relationships are inextricably linked. It is well known that adolescence is a period where self esteem depends on a number of factors like family, upbringing, loneliness and peers. The following study was carried to assess the relationship between self esteem,, attachment styles and loneliness in college students. Methods: 40 girls and 40 boys aged 18-21 years studying in colleges across Mumbai were subjects for the study. The subjects were administered the Rosenberg self esteem scale, the UCLA loneliness scale and the Adult attachment scale. The scores on all scales were compared for boys and girls and Pearson‟s correlation was carried across all scales. Results: No differences between boys and girls were observed in any of the scales administered. A negative correlation between self esteem and loneliness was observed. Similar negative correlations were observed between self esteem and anxiety as well as avoidant attachment styles. A positive correlation was observed between loneliness and anxiety as well as avoidant attachment styles. Conclusion: Self esteem is linked to attachment styles and loneliness in college going students. Further studies in larger samples are warranted.
THE ANALYSIS OF CAUSAL FACTOR ON STUDENT SPEAKING ANXIETY

This article examines the analysis of causal factor on student speaking anxiety. This study is to explain what factors affecting the students speaking anxiety. Moreover, the research data are taken from the second semester students of English Education Study Program, Muhammadiyah University of Metro. This is a descriptive qualitative study and some instruments such as documentation, interview, observation are used in order to collect the data. The data is then analyzed by some steps, like data collection in which writer gathers all of the data that will be used to complete the research. After collecting the data, the writer sorts the data by summarizing and choosing the specific category, displaying the data, verifying the data analysis, and making a conclusion from the finding data. The result of this research shows the students speaking anxiety causal factors in the second semester. Most of the students feel anxious when speaking English in the class. Eventually, some suggestions are discussed in order to help students reduce anxiety and become more confident to speak English in oral language classrooms.
Understanding Signal Theory through play

Many undergraduate students find it difficult to learn, understand and conceptualize some of the the basic topics of signal processing and analysis theory such as: analog and digital signals, frequency domain, Fourier Transform, Discrete Fourier Transform, Nyquist-Shannon sampling theorem, aliasing etc. This paper presents an effective method to introduce some of the most important topics in an introductory Signal Theory course. A set of laboratory exercises is developed, where students experiment with several basic and advanced signal analysis and processing techniques, almost through game and play. The results of a poll show that students find considerable improvement in course organisation and greater usefulness of laboratory exercises in understanding course material.
Global Locator, Local Locator, and Identifier Split (GLI-Split)

The locator/identifier split is an approach for a new addressing and routing architecture to make routing in the core of the Internet more scalable. Based on this principle, we developed the GLI-Split framework, which separates the functionality of current IP addresses into a stable identifier and two independent locators, one for routing in the Internet core and one for edge networks. This makes routing in the Internet more stable and provides more flexibility for edge networks. GLI-Split can be incrementally deployed and it is backward-compatible with the IPv6 Internet. We describe its architecture, compare it to other approaches, present its benefits, and finally present a proof-of-concept implementation of GLI-Split.
Two-phase zero-voltage switching boost converter for medium power applications

A novel two-phase zero-voltage switching boost power converter is proposed. The proposed converter overcomes some limitations of the DC/DC resonant-type converter, such as high circulating energy, limited ZVS load range and complex transformer. The turn-on instant of the switches comes after zero-voltage detection of the voltage across them and there is no load limitation for soft switching. The possibility of using large resonant capacitors results in a considerable turn-off loss reduction. Dividing the power among the two identical 180/spl deg/ shifted phases of the converter contributes to reduced input and output current ripple and results in lower ratings for the switches and passive components. Steady state and dynamic analysis of the power converter are presented for design purposes. The new converter is attractive at medium-power DC/DC applications with output/input voltages ratio between 2 and about 6, where IGBTs are predominantly used as power switches. The principle of operation, features and design considerations of the proposed power converter are described and verified on a 6 kW, IGBT-based experimental circuit.