Miracle-dz/UniFAR-FTUs huggingface dataset:
Binary White Dwarfs in the Supernova Ia Progenitor Survey

We report results of a systematic radial velocity survey for double degenerate (DD) binaries as potential progenitors of type Ia supernovae: SPY (ESO Supernovae Ia Progenitor surveY). More than 1000 white dwarfs (WDs) and pre-white dwarfs were observed with the VLT. The aim of SPY is to perform a statistically significant test of the DD scenario. We give an overview of the project and follow-up results. The sample is used for two tests of the contempo- rary picture of close binary evolution leading to DDs. It is shown that the SPY observations of low mass He-core WDs (HeWDs) are inconsistent with the idea that they all reside in close binary systems. We carry out a model atmosphere analysis of WDs residing in double-lined binaries and estimate individual cooling ages. For a number of systems the younger (and hotter) component is the less massive one, as expected. However, for some systems the mass ratio is inverted.
Micro-expression and Its Applications

When an emotion is concealed or repressed,the true emotion may be manifest as a micro-expression,a fleeting facial expression discordant with the expressed emotion,usually suppressed within 1/25 to 1/5 of a second,and closely related to the deception.This article is a review of all the studies reported about micro-expression.Earlier researchers focused on the measurement of abilities to recognize micro-expression.Because of the development of measurement tools,a large number of micro-expression recognition studies emerged within the clinical domain.However,only one published empirical study has explored the generation of micro-expression,and many questions are left unanswered.Further research should focus on the cross-culture validity of Micro-Expression Training Tool(METT),the generation of micro-expression,and the development of automatic micro-expression recognition tools.Micro-expression studies can provide important insights into the development of an automatic deception detection system.
A Roadmap for a Type Architecture Based Parallel Programming Language

Ever since the end of the era of single processor performance improvement, we observe proliferation of multi and many-core architectures in almost all spheres of computing. Tablets, desktop PCs, workstation clusters, and supercomputers are ripe with multi-core CPUs and/or accelerators. Although there are considerable architectural heterogeneity and scale differences present among these machine architectures, there is also significant commonality in their multi-core building blocks. This situation revives the interest for possibility of parallel programming paradigms that are both efficient and portable across environments. We have been investigating such a programming paradigm for over a year and half now. Two key aspects of our work are development of a common machine abstraction for diverse hardware platforms and a clear separation of different concerns embodied in parallel programming. This is our first paper describing the philosophy, abstraction mechanism, programming model, and early results of our ongoing project.
Improved Selection of Auxiliary Objectives Using Reinforcement Learning in Non-stationary Environment

Efficiency of evolutionary algorithms can be increased by using auxiliary objectives. The method which is called EA+RL is considered. In this method a reinforcement learning (RL) algorithm is used to select objectives in evolutionary algorithms (EA) during optimization. In earlier studies, reinforcement learning algorithms for stationary environments were used in the EA+RL method. However, if behavior of auxiliary objectives change during the optimization process, it can be better to use reinforcement learning algorithms which are specially developed for non-stationary environments. In our previous work we proposed a new reinforcement learning algorithm to be used in the EA+RL method. In this work we propose an improved version of that algorithm. The new algorithm is applied to a non-stationary problem and compared with the methods which were used in other studies. It is shown that the proposed method achieves optimal value more often and obtains higher values of the target objective than the other algorithms.
The Dark Side of String Theory: Black Holes and Black Strings

Solutions to low energy string theory describing black holes and black strings are reviewed. Many of these solutions can be obtained by applying simple solution generating transformations to the Schwarzschild metric. In a few cases, the corresponding exact conformal field theory is known. Various properties of these solutions are discussed including their global structure, singularities, and Hawking temperature. (This review is based on lectures given at the 1992 Trieste Spring School on String Theory and Quantum Gravity.)
PS Frog: a point-absorber wave energy converter working in a pitch/surge mode

In studies of wave energy, notably those made under contract to the U.K. Department of Energy, capital costs have generally been _found too high to compete with other sources It has been shown elsewhere (1) that the large structural element in these costs can be avoided by using point-absorbers reacting against an internal moving mass. This early proposal (2) suffers from the disadvantage that over most of the frequency band capture can only be a fraction of the ideal capture unless some means is adopted of modifying the dynamics to ensure 'resonance' at all frequencies and with irregular waves. Budal and Falnes (3) have used'latching',or holding the mass when it stops until the judicious moment, and have achieved excellent results with their heaving buoy, which, however, ultimately reacts against the sea bed. The authors used latching in early experiments -with a free-floating buoy reacting against an internal mass, but the results were disappointing, although in earlier work with buoys moving in surge on a cable they had had good results with latching (Flounder (4)).
Function Projective Synchronization of Chaotic Fractional Order Systems with Different Dimensions

The function projective synchronization of different dimensional fractional order chaotic systems is investigated in this letter. According to the stability theorem of linear fractional order systems, a nonlinear controller to realize the synchronization is obtained. The function projective synchronization between the fractional order chaotic and hyperchaotic Rossler systems is successfully achieved to show the feasibility of the proposed method.
Global confidence regions in parametric shape estimation

We introduce confidence region techniques for analyzing and visualizing the performance of two-dimensional parametric shape estimators. Assuming an asymptotically normal and efficient estimator for a finite parameterization of the object boundary, Cramer-Rao bounds are used to define a confidence region, centered around the true boundary. Computation of the probability that an entire boundary estimate lies within the confidence region is a challenging problem, because the estimate is a two-dimensional nonstationary random process. We derive lower bounds on this probability using level crossing statistics. The results make it possible to generate confidence regions for arbitrary prescribed probabilities. These global confidence regions conveniently display the uncertainty in various geometric parameters such as shape, size, orientation, and position of the estimated object, and facilitate geometric inferences. Numerical simulations suggest that the new bounds are quite tight.
What happens at the lesson start?

Abstract Transitional periods, such as lesson starts, are necessary steps from one activity to another, but they also compete with time for actual learning. The aim of the present study was to replicate a previous pilot study on lesson starts and explore possible disturbances. In total, 130 lesson starts in Finnish basic education in grades 1–9 were studied using systematic observation performed by 79 preservice teachers. The results corresponded with a previous pilot study indicating that lesson starts were generally orderly and teachers used effective means to manage events. However, lessons started 5 min late on average. Male teachers were evaluated to have better classroom order than female teachers. Small effects were observed based on the gender of the student and the hour of the lesson. No association was found between disturbances in the classroom and the grade level, group size or presence of a classroom assistant.
Packaging and Irradiation Effects on Lipid Oxidation and Volatiles in Cooked Pork Patties

Packaging, irradiation, and the length of storage of raw meat were important factors in lipid oxidation of cooked meat. Preventing oxygen exposure after cooking, however, was more important in preventing lipid oxidation of cooked meat than the raw meat treatments. Cooking itself did not increase thiobarbituric acidreactive substances (TBARS) values. The structural damages caused by the cooking process made it easy for oxygen to contact with membrane lipids and accelerated lipid oxidation. Propanal, pentanal, hexanal, 1-pentanol, and total volatiles were highly correlated (P<0.01) with TBARS values of cooked meat. Among the volatile components, hexanal and total volatiles content provided the best criteria for determining lipid oxidation status and off-odor production in cooked meat. However, the relationships between TBARS values and aldehydes of cooked meat from various muscles were different from each other, and the explanation for different aldehydes/TBARS values in cooked meat from different muscle types requires further study.
Online adaptation of controller parameters based on approximate dynamic programming

Controller parameter tuning is an integral part of control engineering practice. Existing tuning methods usually start with an accurate mathematical model of the controlled system, which may pose some challenges for practicing engineers dealing with real systems. As such, parameter optimization and adaptation are treated as two independent steps during tuning. To address these issues, we propose a new, online parameterized controller tuning method for a general nonlinear dynamic system. This tuning method is based on direct heuristic dynamic programming (direct HDP), a model-free algorithm in the approximated dynamic programming (ADP) family. By using a Lyapunov stability approach, we provide uniformly ultimately bounded (UUB) results under some mild conditions for controller parameters, the critic neural network weights, and the action neural network weights. Simulation studies based on the benchmark cart-pole system demonstrate adaptability and optimization capabilities of the proposed controller parameter tuning method.
Land-use Classification for High-resolution Remote Sensing Image using Collaborative Representation with a Locally Adaptive Dictionary

Sparse representation is widely applied in the field of remote sensing image classification, but sparsity-based methods are time-consuming. Unlike sparse representation, collaborative representation could improve the efficiency, accuracy, and precision of image classification algorithms. Thus, we propose a high-resolution remote sensing image classification method using collaborative representation with a locally adaptive dictionary. The proposed method includes two steps. First, we use a similarity measurement technique to separately pick out the most similar images for each test image from the total training image samples. In this step, a one-step sub-dictionary is constructed for every test image. Second, we extract the most frequent elements from all one-step sub-dictionaries of a given class. In the step, a unique two-step sub-dictionary, that is, a locally adaptive dictionary is acquired for every class. The test image samples are individually represented over the locally adaptive dictionaries of all classes. Extensive experiments (OA (%) =83.33, Kappa (%) =81.35) show that our proposed method yields competitive classification results with greater efficiency than other compared methods.
Asterias: A Parallelized Web-based Suite for the Analysis of Expression and aCGH Data

The analysis of expression and CGH arrays plays a central role in the study of complex diseases, especially cancer, including finding markers for early diagnosis and prognosis, choosing an optimal therapy, or increasing our understanding of cancer development and metastasis. Asterias (http://www.asterias.info) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parallel computing (via MPI) and run on a server with 60 CPUs for computation; compared to a desktop or server-based but not parallelized application, parallelization provides speed ups of factors up to 50. Most of our applications allow the user to obtain additional information for user-selected genes (chromosomal location, PubMed ids, Gene Ontology terms, etc.) by using clickable links in tables and/or figures. Our tools include: normalization of expression and aCGH data (DNMAD); converting between different types of gene/clone and protein identifiers (IDconverter/IDClight); filtering and imputation (preP); finding differentially expressed genes related to patient class and survival data (Pomelo II); searching for models of class prediction (Tnasas); using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity (GeneSrF); searching for molecular signatures and predictive genes with survival data (SignS); detecting regions of genomic DNA gain or loss (ADaCGH). The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications.
Perceptions of Engineers Regarding Successful Engineering Team Design

The perceptions of engineers and scientists at NASA Langley Research Center toward engineering design teams were evaluated. A sample of 49 engineers and scientists rated 60 team behaviors in terms of their relative importance for team success. They also completed a profile of their own perceptions of their strengths and weaknesses as team members. Behaviors related to team success are discussed in terms of those involving the organizational culture and commitment to the team and those dealing with internal team dynamics. The latter behaviors focused on team issues occurring during the early stages of a team''s existence. They included the level and extent of debate and discussion regarding methods for completing the team task and the efficient use of team time to explore and discuss methodologies critical to the problem. The discussion includes a comparison of engineering teams with the prototypical business team portrayed in the literature.
Hybrid Processing of Beliefs and Constraints

This paper explores algorithms for processing probabilistic and deterministic information when the former is represented as a belief network and the latter as a set of boolean clauses. The motivating tasks are 1. evaluating belief networks having a large number of deterministic relationships and 2. evaluating probabilities of complex boolean queries or complex evidence information over a belief network. We present and analyze a variable elimination algorithm that exploits both types of information, and provide empirical evaluation demonstrating its computational benefits.
Multiphysics Numerical Simulation on Bone Scaffolds under Fully Coupled Fluid-Solid-Thermo Model

We obtained the bone scaffolds general constitutive and seepage governing equations based on conservation of energy and Darcy’s laws under fluid-solid-thermo multi-physics fields. Furthermore, we have also established the full coupling mathematical models of bone scaffolds under fluid-solid-thermo multi-physics fields. Based on these formulae in the COMSOL finite element platform, we have analyzed the stress, strain, fluid seepage velocity and the density under different external boundary and initial conditions. Through analyzing these computing results and comparing with the real experiments data of references, we think this methodology is feasible to guild bone scaffolds and porous medium design under the fluid-solid-thermo full coupling multi-physics fields. Lastly, we can find some rules of interstitial nutrition flow and scaffolds solid material movement and biodegradation in fluid-solid-thermo full coupling multiphysics.
The regular accent in Chinese sentences

The regular focus accent is determined by the syntactic structure of a sentence. In general, the distribution of the regular focus accent is regular in simple sentences. Some linguists had proposed some rules on the distribution of regular focus accent, but no experimental test yet. To improve the naturalness of the TTS system, it is very important to prove the rules of focus distribution and apply them in TTS system. The research verified rules of the distribution of the regular accent, and investigated the stressed degree to the different kinds of accents —regular accent and emphatic accent by using psycho-phonetic experiment. The results support all of the rules. The results show that the two kinds of accents are perceptually different in emphatic degree, and that the stressed degree of regular accent is situated between that of emphatic accent and that of non-accent. The acoustic cues of regular accent and emphatic accent are very similar.
Fuzzy control of configuration of web anonymization using TOR

Anonymization of any Internet traffic usually hides the details of the request originator from its target computer. Such a hiding might be required in some situations, especially in the case of web browsing. Anonymization of web traffic is not a part of the http specification, however, it can be achieved using a certain extra tool, either commercial or public one. Significant deceleration of anonymized traffic compared to normal traffic is inevitable but it can be controlled as this article suggests. The study focuses on measuring the parameters of such deceleration in terms of response time, transmission speed and latency and proposing the way how to control it. This study focuses on TOR solely as recent studies have concluded that other tools (like I2P and JAP) provide worse service. Sets of 30 web pages and 14 file locations have been formed and the latency, response time and transmission speed during the page or file download have been measured repeatedly both with TOR active in various configurations and without TOR. The main result presented here comprises several ways how to improve the TOR anonymization efficiency and the proposal for its automatic control. In spite of the fact that efficiency still remains too low compared to normal web traffic for ordinary use, its automatic control could make TOR a useful tool in some special cases.
Adaptive Control of Nonlinear Underwater Robotic

The problem of controlling underwater mobile robots in 6 degrees of freedom (DOF) is addressed. Uncertainties in the input matrix due to partly known nonlinear thruster characteristics are modelled as multiplicative input uncertainty. This paper proposes two methods to compensate for the model uncertainties: (1) an adaptive passivity-based control scheme and (2) deriving a hybrid (adaptive and sliding) controller. The hybrid controller consists of a switching term which compensates for uncertainties in the input matrix and an on-line parameter estimation algorithm. Global stability is ensured by applying Barbalat's Lyapunov-like lemma. The hybrid controller is simulated for the horizontal motion of the Norwegian Experimental Remotely Operated Vehicle (NEROV).
Fault Diagnosis and Reconfigurable Control of Singularly Perturbed Systems using GIMC Structure

paper proposes the extension of generalized internal model control (GIMC) based diagnosis and fault tolerant control to singularly perturbed system. This control method consists of two parts: a controller which guaranties nominal performance and works in the fault free case and a robustness controller to compensate the fault when a sensor failure is detected. This work describes the way to design such controllers for singularly perturbed systems so that the performance with the nominal controller may be guaranteed in the case of sensor failure.
Restoration of multiple images with motion blur in different directions

Images degraded by motion blur can be restored when several blurred images are given, and the direction of motion blur in each image is different. Given two motion blurred images, best restoration is obtained when the directions of motion blur in the two images are orthogonal. Motion blur at different directions is common, for example, in the case of small hand-held digital cameras due to fast hand trembling and the light weight of the camera. Restoration examples are given on simulated data as well as on images with real motion blur.
Three-Dimensional agent-based model of fish collective behaviour using topological interaction

This paper presents a novel 3D agent-based model of fish collective behaviour based on topological interaction. To the best of our knowledge, it is the first 3D model that implements topological interaction. Despite the fact that the topological interaction was proposed based on the observation of collective behaviour of bird flock [1], simulations show that our model also displays realistic collective patterns of fish school as seen in nature. We also observe the automatic transition of different collective patterns, which is a natural phenomenon but failed to show in many previous agent-based fish school models. Keywords-agent-based modelling; fish school; collective behaviour; swarm; topological interaction
Extreme Requirements (XR)

This paper builds upon the work of Kent Beck on Extreme Programming. Here we advance some ideas on how requirements engineering research can improve Extreme Programming and how the managerial common sense exposed by Beck can improve requirements management. The ideas expressed in the paper are anchored on Becks book and on my long experience in Software Engineering. The main argument is that a family of processes, called XR, can provide more quality to Extreme Programming projects.
Assessing the Dimension of Magnitude in Computer Self-efficacy: An Empirical Comparison of Task-Based and Levels of Assistance-Based Methodologies

Computer Self-efficacy (CSE) has been used in many studies as a predictor of individual competence or performance, usage behavior, and a variety of attitudes. Although CSE has been effective in explaining a variety of human computing interactions, there have been a number of studies in which the relationship was weak or nonexistent. One reason for such findings concerns how CSE is operationalized in extant instruments. Many (if not most) leading cognitive theorists (Bandura, 1997; Gist & Mitchell, 1992; Marakas et al., 1998) rather emphatically state that actual tasks must be used to most accurately determine an individual’s perception of ability (i.e., self-efficacy) for some task or domain. They suggest that using tasks, of incremental difficulty level within the intended domain, most accurately presents an individual’s self-efficacy and leads to stronger relationships with outcomes such as competence or performance. Yet one of the most utilized measures of self-efficacy uses levels of assistance (GCSE of Compeau & Higgins, 1995a), and not specific tasks. This study examines which methodology provides a stronger relationship with competence and performance. Using a sample of 610, self-efficacy (using both