Miracle-dz/UniFAR-FTUs huggingface dataset:
Binary Masses as a Test for Pre-Main-Sequence Tracks

Observations of binaries have traditionally provided the means for ascertaining stellar masses. Here we use the published data on eight pre-main-sequence pairs to gauge the accuracy of our own, recently calculated, evolutionary tracks. We consider both eclipsing, double-lined spectroscopic binaries, which provide the mass of each star separately, and noneclipsing, double-lined systems, which yield only the ratio. We also analyze the visual, quadruple system GG Tau, for which the sum of the two component masses follows from observations of the circumbinary disk. In almost all cases, our theoretically derived masses or mass ratios are in good agreement with the empirical values. For two binaries (NTTS 162814-2427 and P1540), the observational results are still too uncertain for a proper comparison. We also find that the derived contraction ages within each pre-main-sequence pair are nearly equal. This result extends earlier findings regarding visual pairs and indicates that the components of all binaries form in proximity, perhaps within the same dense cloud core. Finally, our study reveals that the Trapezium star BM Ori is very young since both the star itself and its companion have contraction ages less than 105 yr.
Dust effects on snowpack melt and related ecosystem processes are secondary to those of forest canopy structure and interannual snowpack variability

Dust deposition lowers the albedo of snow and can significantly alter snowpack energy balance. Investigation of aeolian dust deposition in the mountains of the western U.S. has shown that these effects advance the timing of snowpack melt and spring runoff across much of the region. These studies have primarily focused on alpine snowpacks with little to no overstory vegetation. To evaluate the impacts of aeolian dust on ecohydrological processes in forests, we conducted a manipulative experiment in a subalpine conifer forest in Utah's Wasatch Mountains. During the spring of 2010–2012, we added dust to the snow surface in forested plots every 1 to 2 weeks, roughly doubling the natural dust loading. We then measured snowpack ablation in control and dust addition plots, along with below‐snowpack and warm season soil temperature (Tsoil), soil water content (θ), litter decomposition rate (D), soil respiration rate (Rs), and tree xylem water potential (ψ). Differences in ablation between control and dust addition plots were similar in magnitude to differences associated with the canopy structure of the forest. Seasonal patterns in Tsoil and θ were similar between dust treatments and canopy structure groups. D, Rs, and ψ varied little between dust treatments, but there were significant differences between years. During our 3‐year study, an unusual level of interannual variability in snowfall had the greatest effect on the soil environment and ecosystem processes. The effects of aeolian dust on snowpack mass and energy balance in our forest were slightly smaller than those associated with canopy structure. Copyright © 2014 John Wiley & Sons, Ltd.
Propagation of Probabilities, Means, and Variances in Mixed Graphical Association Models

Abstract A scheme is presented for modeling and local computation of exact probabilities, means, and variances for mixed qualitative and quantitative variables. The models assume that the conditional distribution of the quantitative variables, given the qualitative, is multivariate Gaussian. The computational architecture is set up by forming a tree of belief universes, and the calculations are then performed by local message passing between universes. The asymmetry between the quantitative and qualitative variables sets some additional limitations for the specification and propagation structure. Approximate methods when these are not appropriately fulfilled are sketched. It has earlier been shown how to exploit the local structure in the specification of a discrete probability model for fast and efficient computation, thereby paving the way for exploiting probability-based models as parts of realistic systems for planning and decision support. The purpose of this article is to extend this computational s.
Vector Texture Maps on the GPU

This paper presents VTMs (Vector Texture Maps), a novel representation of vector images that can be used as a texture by the GPU for real-time rendering. A VTM decomposes texture space into different regions, represented in an analytic way, by a set of implicit degree 3 polynomials. Each region can be rendered by a different fragment shading function. Accurate anti-aliasing is performed in real-time, based on an estimate of fragment coverage. As a consequence, infinite zooming can be applied without any pixel discretization artifact. Based on a hierarchical data structure, our representation has low memory requirements. Its versatility is demonstrated in various settings, including a font engine completely implemented in the GPU. CR Categories: I.3. 7 [Computer Graphics]: Three-Dimensional Graphics and Realism—Color, shading, shadowing, and texture
Body sensor networks: can we use them?

A BSN is a heterogeneous environment populated with different types of sensors. As such it needs a framework to abstract to applications the underlying sensor resources they need to get the information from. Such framework (a middleware), should allow applications to issue information requests with a set of requirements to be met. This would then be translated into sensor resource access(es) while trying to abide by the requirements. In this paper we describe an architecture proposal for such a middleware and an implementation overview of a first prototype. We focus on the first layer needed to provide an abstraction to the resources.
ScopeG: A Mobile Application for Exploration and Comparison of Personality Traits

The language people use on social media has been shown to provide insight into their personality characteristics. We developed a mobile system that aids the exploration and comparison of personal personality profiles with those of others. We conducted a user study to evaluate system usability, gauge user interaction of interest, and the system's performance in completing exploration and comparison tasks. Our study shows that the system is easy to use and enables users effectively explore and compare personality profiles, and users were interested in comparing their personality traits with the personality traits of friends, role models, and celebrities.
Hierarchical multiscale hyperporous block copolymer membranes via tunable dual-phase separation

A new class of amphiphilic block copolymer–based porous membranes is fabricated via tunable dual-phase separation. The rational design and realization of revolutionary porous structures have been long-standing challenges in membrane science. We demonstrate a new class of amphiphilic polystyrene-block-poly(4-vinylpyridine) block copolymer (BCP)–based porous membranes featuring hierarchical multiscale hyperporous structures. The introduction of surface energy–modifying agents and the control of major phase separation parameters (such as nonsolvent polarity and solvent drying time) enable tunable dual-phase separation of BCPs, eventually leading to macro/nanoscale porous structures and chemical functionalities far beyond those accessible with conventional approaches. Application of this BCP membrane to a lithium-ion battery separator affords exceptional improvement in electrochemical performance. The dual-phase separation–driven macro/nanopore construction strategy, owing to its simplicity and tunability, is expected to be readily applicable to a rich variety of membrane fields including molecular separation, water purification, and energy-related devices.
Intensity-based Registration versus Feature-based Registration for Neurointerventions

Registration of 2D-3D data sets can provide an important tool to help visualisation during minimal invasive neurointerventions. We have quantitatively compared two approaches to this registration problem: an intensity-based algorithm and a feature-based algorithm. The intensity-based algorithm was found to be more accurate, having an average RMS error of 1.2 mm, compared to 2.3 mm for the feature-based algorithm. However, the feature-based algorithm proved to be more reliable over a wide range of starting conditions.
Large scale mapping using submaps

The main contribution of this article the implementation of a new method for the usage of submaping algorithms, which surpasses the limitations arising from the need of statistical independence between the submaps, when mapping large scale areas. This method relies on the commonly used structure of SLAM (Simultaneous Localization and Mapping) mandatory for building submaps which share information, but stay conditionally independent. This approach is able to recover the final map, without introducing other approximations ignoring the ones already introduced by the EKF (Extended Kalman Filter), all this in a linear time. The algorithm has been tested for the case of local submaps because the effects of linearization errors are smaller in this way. The obtained maps are more accurate and consistent compared with ones obtained by EKF or EIF (Extended Information Filter) methods, which are not using local coordinates.
Neurokinin B and Dynorphin A in Kisspeptin Neurons of the Arcuate Nucleus Participate in Generation of Periodic Oscillation of Neural Activity Driving Pulsatile Gonadotropin-Releasing Hormone Secretion in the Goat

Gonadotropin-releasing hormone (GnRH) neurons in the basal forebrain are the final common pathway through which the brain regulates reproduction. GnRH secretion occurs in a pulsatile manner, and indirect evidence suggests the kisspeptin neurons in the arcuate nucleus (ARC) serve as the central pacemaker that drives pulsatile GnRH secretion. The purpose of this study was to investigate the possible coexpression of kisspeptin, neurokinin B (NKB), and dynorphin A (Dyn) in neurons of the ARC of the goat and evaluate their potential roles in generating GnRH pulses. Using double and triple labeling, we confirmed that all three neuropeptides are coexpressed in the same population of neurons. Using electrophysiological techniques to record multiple-unit activity (MUA) in the medial basal hypothalamus, we found that bursts of MUA occurred at regular intervals in ovariectomized animals and that these repetitive bursts (volleys) were invariably associated with discrete pulses of luteinizing hormone (LH) (and by inference GnRH). Moreover, the frequency of MUA volleys was reduced by gonadal steroids, suggesting that the volleys reflect the rhythmic discharge of steroid-sensitive neurons that regulate GnRH secretion. Finally, we observed that central administration of Dyn-inhibit MUA volleys and pulsatile LH secretion, whereas NKB induced MUA volleys. These observations are consistent with the hypothesis that kisspeptin neurons in the ARC drive pulsatile GnRH and LH secretion, and suggest that NKB and Dyn expressed in those neurons are involved in the process of generating the rhythmic discharge of kisspeptin.
Making Them Move: Motor Control for Animated Humans and Animals

Simulating the motion of humans and animals is a challenging problem that is of interest to various disciplines, including biomechanics, control, and robotics. A surprising amount of progress is also being made in the computer graphics community, whose ever-increasing demand for realism has led to the use of complex physically-based simulations. This is motivated by the goal of creating simulated autonomous characters equipped with basic motor skills for movement. The problem of encoding these basic motor skills is one which has seen a variety of proposed solutions in computer animation. This talk will give an overview of some of the control methods applied towards the animation of complex simulated models of humans and animals. These control methods vary in their choice of problem representation but typically rely on numerical optimization techniques. A variety of animation results will be shown.
Modeling 3 D Urban Areas from Aerial LiDAR Point Clouds : A Robust Roof Feature Based Reconstruction Approach

Urban reconstruction combining photogrammetry, remote sensing, computer vision, and computer graphic is an active research area with broad impact on several potential applications. In this work, a fast, completely automated approach to create 3D watertight building models from aerial LiDAR (Light Detection and Ranging) point clouds is presented. The developed method analyzes the scene content and generates rooftops, with complex rigorous boundaries and vertical walls, that connect rooftops to the ground. The graph cuts scheme is adopted to separate vegetative elements from the rest of the scene content, which is based on the local analysis about the implicit surface properties. The ground terrain and building rooftop footprints are then extracted based on a two-pass hierarchical Euclidean clustering. For each individual building footprint, major features on the rooftop are further detected using a region-growing algorithm with surface smoothness constraints. The principal orientation of each building rooftop is calculated using a minimum bounding box fitting technique, and is used to guide the refinement of shapes and boundaries of the rooftop parts. Boundaries for all of these features are refined for the purpose of producing strict description. Once the description of the rooftops is achieved, polygonal mesh models are generated by creating surface patches with outlines defined by detected vertices to produce triangulated mesh models. These triangulated mesh models are suitable for many applications, such as 3D mapping, urban planning and augmented reality.
Geo-Social Mobility Model for VANET Simulation

Vehicular Ad Hoc Network (VANET) can be viewed as a special case of an ad hoc network formed by moving vehicles communicating through short-to-medium range wireless transmission. This emerging wireless technology allowed for a wide range of applications varying from safety and accident avoidance to leisure and entertainment. The VANET's special features, such as high node mobility, made the design and validation of its protocols a challenging task. A realistic simulation environment is then required. Since the vehicles mobility is driven by the human mobility characteristics and is controlled by the geographical restrictions of the roads, the work presented in this paper is aimed to having a realistic mobility model that incorporates both the social aspects of human mobility together with the geographical restrictions that governs the movement of the mobile nodes. The model is based on using realistic data sets rather than randomly generated data.
Spectral Models of Advection-dominated Accretion Flows with Winds

We calculate spectral models of advection-dominated accretion flows, taking into account the possibility that significant mass may be lost to an outflow/wind. We apply the models to the soft X-ray transient V404 Cyg in quiescence, the Galactic center source Sgr A*, and the nucleus of NGC 4649. We show that there are qualitative degeneracies between the mass-loss rate in the wind and parameters characterizing the microphysics of the accretion flow; of particular importance is δ, the fraction of the turbulent energy which heats the electrons. For small δ, current observations suggest that at most 90% of the mass originating at large radii is lost to a wind, so that at least ~10% reaches the central object. For large δ ~ 0.3, however, models with significantly more mass loss are in agreement with the observations. We conclude by highlighting future observations which may clarify the importance of mass loss in sub-Eddington accretion flows.
Analysis of Decorrelation Transform Gain for Uncoded Wireless Image and Video Communication

An uncoded transmission scheme called SoftCast has recently shown great potential for wireless video transmission. Unlike conventional approaches, SoftCast processes input images only by a series of transformations and modulates the coefficients directly to a dense constellation for transmission. The transmission is uncoded and lossy in nature, with its noise level commensurate with the channel condition. This paper presents a theoretical analysis for an uncoded visual communication, focusing on developing a quantitative measurements for the efficiency of decorrelation transform in a generalized uncoded transmission framework. Our analysis reveals that the energy distribution among signal elements is critical for the efficiency of uncoded transmission. A decorrelation transform can potentially bring a significant performance gain by boosting the energy diversity in signal representation. Numerical results on Markov random process and real image and video signals are reported to evaluate the performance gain of using different transforms in uncoded transmission. The analysis presented in this paper is verified by simulated SoftCast transmissions. This provide guidelines for designing efficient uncoded video transmission schemes.
Odia transliteration engine using moses

Transliteration is an important Natural Language Processing task. Transliteration is an automatic method for converting words in one language into phonetically equivalent ones in another language. In this paper we use the popular phrase-based SMT techniques for the task of machine transliteration, for Odia-English and Odia-Hindi language pair. We have created two models for syllable based splits (Odia-English, Odia-Hindi) on 50,900 parallel entries and two models for character based splits (Odia-English, Odia-Hindi) on 1,10,000 parallel entries. SRILM is used to build statistical language models. GIZA++ is used to perform word alignments over parallel corpora. We have achieved an accuracy of 89% for Odia-English and 86% for Odia-Hindi on Syllable based split and 71% for Odia-English and 85% for Odia-Hindi on character based split.
Predictive Biomarkers and Personalized Medicine ALK Rearrangements Are Mutually Exclusive with Mutations in EGFR or KRAS : An Analysis of 1 , 683 Patients with Non – Small Cell Lung Cancer

Purpose: Anaplastic lymphoma kinase (ALK) gene rearrangements define a distinct molecular subset of non–small cell lung cancer (NSCLC). Recently, several case reports and small series have reported that ALK rearrangements can overlap with other oncogenic drivers in NSCLC in crizotinib-na€ ve and crizotinib-
The Effects of Applying Increasing Precision In Knowledge of Results When Practicing a Novel Motor Skill

The purpose of this study was to determine whether increasing the precision of augmented feedback affected motor learning. The primary hypothesis was that the group that received only directional feedback would perform with higher accuracy scores during the transfer and retention tests compared to participants that received both directional and magnitude of error feedback. Participants in the study (N=36) were randomly assigned to conditions and all participants performed a total of 50 practice trials. The task required participants to toss a hacky sack, blindfolded, with their dominant arm to a target that was placed on the ground three meters away After every trial, participants in the " KR " group received KR consisting of either " Hit " or " Miss, the " KR-precision 1 " group received " Hit " or " Missed " as well as direction of error feedback, and the " KR-precision 2 " group received " Hit " or " Missed " plus the direction and magnitude of error feedback. All participants returned after 24-hours and performed a 10-trial retention test and a 10-trial transfer test without KR. Retention test results revealed that the KR-precision 2 group was significantly more accurate on the retention test compared to the KR-precision 1 group. Transfer test results suggest that there were no significant differences between any of the groups. This result suggests that the precision of the feedback provided during practice did not influence the participant's ability to adapt to different performance characteristics.
R connectomics : Principles and challenges

MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. eywords:
Mobile Robot Planning using Action Language BC with Hierarchical Domain Abstractions

Action languageBC provides an elegant way of formalizing robotic domains which need to be expressed using default logic as well as indirec t and recursive action effects. However, generating plans efficiently for la rge domains usingBC can be challenging, even when state-of-the-art answer set solvers a re used. In this paper, we investigate the computational gains achieved by de scribing task planning domains at different abstraction levels using BC, where lower levels describe more domain details by adding fluentsnot included in higher levels and actions at different levels are formalized independently. Two alg orithms are presented to efficiently calculate the near-optimal short and low-cos t plans respectively. We present a case study where at least an order of magn itude speedup was achieved in a robot mail collection task using hierarchical domain abs tractions.
All-laser-driven, MeV-energy X-ray source for detection of SNM

A quasi-monoenergetic MeV X-ray source based on laser-driven electron acceleration and Thomson scattering is under development at the Extreme Light Laboratory at the University of Nebraska, Lincoln. Reported are experimental results on the generation of high- brightness, nearly monoenergetic 300-MeV energy electron beams with the high power, short-pulse DIOCLES laser system. The laser system produces > 100 TW of maximum peak power per pulse. The maximum pulse energy is 3.5 J with a temporal duration of 30 fs. Energetic electron beams are produced by focusing a laser pulse with 40-50-TW peak-power on a supersonic helium nozzle to drive a relativistic plasma wave (laser wakefield). Electron beams with energies of 320 + 2.0 MeV are accelerated over a distance of 3 mm. The beam has an angular spread of 5 mrad with a charge of 100 pC. The use of a stable and well-characterized laser system - in conjunction with high temporal contrast and adaptive optics correction on the amplified beam (to obtain ideal focal spots) - has enabled generation of very reproducible electron beams, both in terms of energy and pointing stability. It is found that electron acceleration is most efficient, beam brightness is highest and reproducibility is best in the resonant regime, where the temporal duration of the laser pulse equals the plasma period. A beamsplitter is used after compression to generate two pulses in the ratio of 80% to 20%. The higher power pulse drives the laser wakefield to produce the energetic electron beams while the lower power pulse is transported through an independent line and focused on the electron beam to generate X-rays. Experiments are currently in progress to observe and characterize the X-ray beam. Theoretical predictions indicate that 1~2 plusmn 10% - MeV X-ray photons can be produced in a well-collimated beam. The expected photon flux is 10 photons per laser shot. Characterization of such a high-flux high energy X-ray beam is in progress. Quasi-monoenergetic X-rays offer significant advantages for the detection of sensitive nuclear materials using techniques such as nuclear resonance fluorescence. A systematic effort is also in progress to further improve the characteristics of laser produced electron beams with regard to monochromaticity, divergence and stability and also permit easy tunability of the X-ray source. The design of a compact system capable of being deployed in the field will also be discussed as part of a long-term solution to the critical requirement for an efficient cargo-scanning system.