Miracle-dz/UniFAR-FTUs huggingface dataset:
Distinguishing Evaluation from Description in the Personality-Emotion Relationship

Personality characteristics and emotional experiences contain both descriptive and evaluative aspects. The purpose of the present study was to test whether evaluation was a mediator in two well-established personality-emotion relationships. Using structural equation modeling procedures with two samples of participants, the authors demonstrated that evaluation fully mediated the relationship between neuroticism and negative affect and partially mediated the relationship between extraversion and positive affect. The results suggest that both description and evaluation components are essential to understanding the complex relationships between personality and emotion.
A new local search algorithm providing high quality solutions to vehicle routing problems

This paper describes a new local search algorithm that provides very high quality solutions to vehicle routing problems. The method uses greedy local search, but avoids local minima by using a large neighbourhood based upon rescheduling selected customer visits using constraint programming techniques. The move operator adopted is completely generic, in that virtually any side constraint can be efﬁciently incorporated into the search process. Computational results show that a naive implementation of the method produces results bettering the best produced by competing techniques using minima-escaping methods.
Grouping Volume Renderers for Enhanced Visualization in Computational Fluid Dynamics

This paper advocates the use of a group of renderers rather than any specific rendering method. We describe a bundle containing four alternative approaches to visualizing volume data. One new approach uses realistic volumetric gas rendering techniques to produce photo-realistic images and animations. The second uses ray casting that is based on a simpler illumination model and is mainly centered around a versatile new tool for the design of transfer functions. The third method employs a simple illumination model and rapid rendering mechanisms to provide efficient preview capabilities. The last one reduces data magnitude by displaying the most visible components and exploits rendering hardware to provide real time browsing capabilities. We show that each rendering tool provides a unique service and demonstrate the combined utility of our group of volume renderers in computational fluid dynamic (CFD) visualization. While one tool allows the explorer to render rapidly for navigation through the data, another tool allows one to emphasize data features (e.g., shock waves), and yet another tool allows one to realistically render the data. We believe that only through the deployment of groups of renderers will the scientist be well served and equipped to form numerous perspectives of the same dataset, each providing different insights into the data. >
Understanding Exhaustive Pattern Learning

Pattern learning in an important problem in Natural Language Processing (NLP). Some exhaustive pattern learning (EPL) methods (Bod, 1992) were proved to be flawed (Johnson, 2002), while similar algorithms (Och and Ney, 2004) showed great advantages on other tasks, such as machine translation. In this article, we first formalize EPL, and then show that the probability given by an EPL model is constant-factor approximation of the probability given by an ensemble method that integrates exponential number of models obtained with various segmentations of the training data. This work for the first time provides theoretical justification for the widely used EPL algorithm in NLP, which was previously viewed as a flawed heuristic method. Better understanding of EPL may lead to improved pattern learning algorithms in future.
$158/GFLOPS astrophysical N-body simulation with reconfigurable add-in card and hierarchical tree algorithm

As an entry for the 2006 Gordon Bell price/performance prize, we report an astrophysical N-body simulation performed with reconfigurable computing systems and a hierarchical tree algorithm. Each of our systems consists of a host PC and a reconfigurable add-in card attached via high-speed interface, PCI Express or PCI-X. The reconfigurable add-in card houses one FPGA chip, into which we integrated 16 pipeline processors specialized for gravitational force calculation. Other operations, such as tree construction, tree traverse and time integration, are performed on the host PC. On our system, we performed a cosmological N-body simulation with 2.1 million particles, which sustained a performance of 15.39 Gflops averaged over 4.33 hours. The price of our system is $2,384 in total and, price per performance obtained is $158/Gflops, which is 44 times better than that obtained by GRAPE-5 special-purpose hardware, the 1999 Gordon Bell winner.
Bases fisiopatológicas de la epilepsia del lóbulo temporal: estudios en humanos y animales

Introduccion. La epilepsia del lobulo temporal (ELT) es el tipo mas frecuente de epilepsia farmacorresistente en humanos. El tratamiento quirurgico de estos pacientes permite estudios de gran importancia para conocer los mecanismos fisiopatologicos subyacentes. Desarrollo. Se revisan algunos de los datos y teorias mas recientes sobre la fisiopatologia de la ELT, tanto en modelos animales como en humanos. Aunque existen similitudes electrofisiologicas, no hay una relacion perfecta entre los datos hallados en modelos animales y en humanos, lo que dificulta la extrapolacion de los resultados. No obstante, ambos tipos de estudios sugieren una considerable heterogeneidad en las alteraciones responsables de la epilepsia, si bien se acepta comunmente que existe una remodelacion de la excitacion glutamatergica y la inhibicion gabergica que deriva en hiperexcitabilidad. El papel de la esclerosis mesial como proceso originario de la ELT esta cada vez mas discutido. El desarrollo de estudios electrofisiologicos in vitro y la aplicacion de tecnicas con mayor poder de resolucion, como los registros con microelectrodos o nuevas herramientas matematicas, pueden aportar importantes datos al conocimiento fisiopatologico de este sindrome. Conclusiones. El estudio multidisciplinar de la fisiopatologia de la ELT en la ultima decada ha permitido aumentar el conocimiento sobre los procesos que subyacen a la genesis de las crisis, su clinica y evolucion. Este conocimiento es de gran importancia porque abre nuevas opciones terapeuticas de la ELT.
PET: a partial evaluation-based test case generation tool for Java bytecode

PET is a prototype Partial Evaluation-based Test case generation tool for a subset of Java bytecode programs. It performs white-box test generation by means of two consecutive Partial Evaluations (PE). The first PE decompiles the Java bytecode program into an equivalent CLP (Constraint Logic Programming) counterpart. The second PE generates a test-case generator from the CLP program. This generator captures interesting test coverage criteria and it is able to generate further test cases on demand. For the first PE, PET incorporates an existing tool which decompiles bytecode to CLP. The main contribution of this work is the implementation of the second PE and the proof of concept of the approach. This has required the development of a partial evaluator for CLP with appropriate control strategies to ensure the required coverage criteria and to generate test-case generators. PET can be downloaded as free software from its web site, where a repository of examples and a web interface are also provided. Though PET has to be extended to be applicable to larger programs, we argue that it provides some evidence that the approach can be of practical interest.
A unified view of non-stationary sinusoidal parameter estimation methods using signal derivatives

In this paper, we present a unified view of three non-stationary sinusoidal parameter estimation methods which are based on taking linear transforms of a signal and its derivatives. These methods, the Distribution Derivative Method (DDM), the Generalized Derivative Method (GDM), and the Generalized Reassignment Method (GRM), are shown to be subcases of a more general method which results in a system of linear equations from which we can solve for the parameter estimators. While the GDM and GRM are known to be theoretically equivalent, we show that they are also equivalent to the DDM in one special case. Matrix formulations are established for the GDM and GRM with a polynomial log-amplitude, polynomial phase sinusoidal signal model, and a bias in previous frequency slope estimators is explicitly demonstrated.
On the Efficacy of APUs for Heterogeneous Graph Computation

Accelerated Processing Units (APUs) are central processor s that feature integrated GPU cores. In this study, we show that thi s architecture is well-suited to the domain of graph analysis. O ur evaluation shows that a current-generation integrated GPU can o utperform an externally-connected discrete GPU by up to 50% for the breadth-first search and PageRank algorithms. Furthermore , by operating on data with different characteristics in unison, t he CPU and integrated GPU can halve the running time of PageRank on a scale-free dataset.
Protein A Detection Based on Quantum Dots-Antibody Bioprobe Using Fluorescence Coupled Capillary Electrophoresis

In this report, fluorescence detection coupled capillary electrophoresis (CE-FL) was used to detect Protein A. Antibody was first labeled with Cy5 and then mixed with quantum dots (QDs) to form QDs-antibody bioprobe. Further, we observed fluorescence resonance energy transfer (FRET) from QDs donor to Cy5 acceptor. The bioprobe was formed and brought QDs and Cy5 close enough to allow FRET to occur. After adding protein A, the FRET system was broken and caused the FRET signal to decrease. Thus, a new method for the determination of protein A was proposed based on the FRET signal changes. This study provides a new trail of thought for the detection of protein.
Adaptive Feedback Control for a Class of Uncertain Nonlinear Systems with Dead-Zone

In this paper, a robust adaptive feedback controller is proposed based on backstepping method and neural network for a class of uncertain nonlinear systems with deadzone. The subsystem uncertainty is approximated using radial basis function (RBF) neural network and weight value update law is given for approximating the subsystem uncertainty. Based on the output of the neural network, the robust adaptive control scheme is presented with backstepping method. The designed controller can not only guarantee robust stability of the uncertain nonlinear system, but also make it has L2-gain performance index which less than or equal to Gt 0.
Axisymmetric galaxy models with central black holes, with an application to M32

The contour integral method of Hunter & Qian is applied to axisymmetric galaxy models in which the distribution function (DF) is of the form f=f(E,L_z), where E and L_z are the classical integrals of motion in an axisymmetric potential. A practical way to construct the unique even part of the DF for such systems is presented. It is applied to models, both oblate and prolate, in which the mass density is stratified on similar concentric spheroids. The spheroids with scale-free densities are discussed in detail. These provide useful approximations to the behaviour of more realistic models in the limit of small and large radii. The self-consistent case is treated, as well as the case in which there are additional contributions to the potential from a central black hole or dark halo. The range of axis ratios and density profile slopes is determined for which spheroidal power--law cusps with a central black hole have a physical two--integral DF. More generally, the f(E,L_z) DFs are discussed for a set of spheroidal `(alpha,beta)-models', characterized by a power-law density cusp with slope alpha at small radii, and a power-law density fall-off with slope [alpha + 2 beta] at large radii. As an application, the DF is constructed for the (alpha,beta) model with a 1.8 x 10^6 solar mass black hole used by van der Marel et al. to interpret their high spatial resolution spectroscopic data for M32. The results confirm that the model fits the observed line-of-sight velocity profiles remarkably well. The model is used to calculate predictions for future spectroscopic observations with the HST.
Agent Based Model for Call Centers Using Knowledge Management

A call center is an organizational unit where inbound calls are received or outbound calls placed for the purposes of sales, support, advice and other business transactions. By applying knowledge management solutions, we can meet call centers’ challenges and gain benefits of reduced training costs, improved call handling and greater flexibility. This paper describes a solution to agent mediated knowledge management system in call centers and new search algorithms. We introduced two agent based search algorithms for finding the expert user in system. Searching an expert is one of the most critical features which each call center system should have. Our agent based search with agent based weighted graph works well in our prototype system. Our agent model can distribute and share knowledge in whole levels of organizations and call center.
'In the blank of mere possibility' : liminal transformations in the poetry of Christina Rossetti

This thesis offers a new reading of Christina Rossetti’s poetic texts which situates them within the context of liminality. I define liminality here as a site of ambiguity, change and unfulfilment between two states, whilst emphasising its potential for transformation and transgression. I examine multiple narratives – personal and communal, linear and cyclical, spatial and temporal – which emerge from Rossetti’s complex texts, and highlight two major approaches used: layering and silencing. The range of works I analyse includes both famous and lesser known poems, secular and spiritual writing, from “Winter: My Secret” (1857) and “Goblin Market” (1859) to “The Iniquity of the Fathers Upon the Children” (1865) and ““Resurgam” (1883). With this wide range, I demonstrate that similar approaches are used throughout Rossetti’s writing from her earliest poems to her later work. I begin the thesis with a focus on the fragmentation of the poetic self into observer and observed and examine the power acquired by the speakers/protagonists through the distance and seclusion of the liminal space. This enables the liminal space to shape a new identity for the speakers/protagonists. In Rossetti’s poetry, the liminal personae become defined by the space they inhabit, or are trapped in, on visual, physical, psychological and sound levels. This positioning helps them to acquire (or re-gain) personal history, memory and a voice. I proceed to explore the conflict between the seen and the unseen, revelation and illusion, in Rossetti’s work, paralleling this with photographic experiments by Lady Hawarden. This enables me to trace the use of the threshold in both poetic and visual languages. Rossetti’s speakers are unable to cross this threshold yet they still struggle to gain control over the outside world. From visual explorations I move on to consideration of sound and suggest that rhythm and rhyme function in the same way as Rossetti’s use of tropes of sight/deprivation of sight. Rossetti introduces rhythmical lapses and repetitive constructions as a means of controlling and shaping reality. Sound repetition subverts our expectations, while sound disruptions create negative spaces which serve as markers of the apocalyptic and the threshold. This idea of negative space is closely linked to the ideas of absence and unfulfilment and is pivotal in understanding Rossetti’s poetry. I argue that Rossetti’s theology is based on negation and that this is extended to her secular poems as well. Christina Rossetti’s poems are characterised by oppositions of absence and exuberant presence on all textual levels. In the final part of my thesis, I examine the transformation of the speaker’s/narrator’s self. I read the ideas of unfulfilment against the self-recognition of the speakers and show their inner splits and subsequent alienation. In this way, unnaming and silencing work as ways of defining the boundaries of the self through negation.
Selection of a Similar Writer for Personal Handwritten Character Recognition

It becomes the diffusion period of a tablet (keyboard less) computer for electronic book and electronic publishing, and every business elite will bring a personal tablet computer. The usage of personal tablet computer includes taking memo using the touch panel display. The taking memo using the touch panel display is written by a finger or a pen. The memo includes a figure and a character written by his finger or pen. The user desires the handwritten character recognition. The useful handwritten character recognition software, however, has not developed for Japanese characters. We will develop the personal handwritten character recognition system in high accuracy using the tablet can use the trajectory of his finger or pen. In this paper, we describe the effectiveness of personal character recognition and a selection method of a similar writer in personal character recognition. We proposed two new recognition methods: “similar mean dictionary (SMD)” and “similar feature space dictionary (SFSD)” to improve the personal character recognition. These dictionaries use only one character, and they can estimate the personality of writing style using characters written by a similar writer. The similar feature space dictionary improved the character recognition rate to 91.0 % which obtains the similar accuracy with personal dictionary. It is confirmed that only one character written by a user (specific writer) is very effective for handwritten character recognition. Keywords— Handwriting, Hiragana recognition, Character recognition, Handwriting character recognition, Personal tablet computer
Effects of Extract from Mangifera indica Leaf on Monosodium Urate Crystal-Induced Gouty Arthritis in Rats

The leaves of Mangifera indica L. (Anacardiaceae) is used as a medicinal material in traditional herb medicine for a long time in India, China, and other Eastern Asian countries. Our present study investigated the therapeutic effects of the ethanol extract from Mangifera indica (EMI) in rat with monosodium urate (MSU) crystals-induced gouty arthritis. Effects of EMI (50, 100, and 200 mg/kg, p.o.) administrated for 9 days on the ankle swelling, synovial tumor necrosis factor-alpha (TNF-α), and interleukin-1beta (IL-1β) levels were assessed in MSU crystal rat. Data from our study showed that rat with gouty arthritis induced by MSU crystal demonstrated an elevation in ankle swelling, synovial TNF-α, IL-1β mRNA, and protein levels. Oral administration of 100 and 200 mg/kg EMI for 9 days reversed the abnormalities in ankle swelling, synovial TNF-α, IL-1β mRNA, and protein levels. The results indicated that the beneficial antigouty arthritis effect of EMI may be mediated, at least in part, by inhibiting TNF-α and IL-1β expression in the synovial tissues. Our study suggests that Mangifera indica and its extract may have a considerable potential for development as an anti-gouty arthritis agent for clinical application.
Adaptive Duty Cycling for Place-Centric Mobility Monitoring using Zero-Cost Information in Smartphone

Smartphones enable the collection of mobility data using various sensors. The key challenge in the collection of continuous data is to overcome the limited battery capacity of the device. While extensive research has been conducted to solve energy issues in continuous mobility learning, we argue that previous works have not reached optimal performance. In this paper, we propose an energy-efficient mobility monitoring system, FreeTrack, to collect place-centric mobility data with minimum energy consumption in everyday life. We first analyzed the regularity of life patterns, cellular connection patterns, and battery charging behaviors of 94 smartphone users to examine important features related to human mobility. Based on our findings, we design an adaptive duty cycling scheme that uses zero-cost information (i.e., regular mobility, cell connection, and battery state) as low-level sensing to infer location change without the need to activate sensors. We model the location inference on the Hidden Markov Model and optimize the sensing schedule of individual smartphones for real-time operation. Our extensive experiment with 48 smartphone users shows that the proposed system achieves an energy saving of about 68% over previous works, yet still correctly traces 97% of mobility with 0.2±0.5 places misses in a day.
Cross-language compiler benchmarking: are we fast yet?

Comparing the performance of programming languages is difficult because they differ in many aspects including preferred programming abstractions, available frameworks, and their runtime systems. Nonetheless, the question about relative performance comes up repeatedly in the research community, industry, and wider audience of enthusiasts. This paper presents 14 benchmarks and a novel methodology to assess the compiler effectiveness across language implementations. Using a set of common language abstractions, the benchmarks are implemented in Java, JavaScript, Ruby, Crystal, Newspeak, and Smalltalk. We show that the benchmarks exhibit a wide range of characteristics using language-agnostic metrics. Using four different languages on top of the same compiler, we show that the benchmarks perform similarly and therefore allow for a comparison of compiler effectiveness across languages. Based on anecdotes, we argue that these benchmarks help language implementers to identify performance bugs and optimization potential by comparing to other language implementations.
Recovering thin structures via nonlocal-means regularization with application to depth from defocus

We propose a novel scheme to recover depth maps containing thin structures based on nonlocal-means filtering regularization. The scheme imposes a distributed smoothness constraint by relying on the assumption that pixels with similar colors are likely to belong to the same surface, and therefore can be used jointly to obtain a robust estimate of their depth. This scheme can be used to solve shape-from-X problems and we demonstrate its use in the case of depth from defocus. We cast the problem in a variational framework and solve it by linearizing the corresponding Euler-Lagrange equations. The linearized system is then inverted by using efficient numerical methods such as successive overrelaxations or more general methods such as conjugate gradient when the system is not diagonally dominant. One of the main benefits of this formulation is that it can handle the regularization of highly fragmented surfaces, which require large neighborhood structures typically difficult to solve efficiently with graph-based methods. We compare the performance of the proposed algorithm with methods recently proposed in the literature that are analogous to neighborhood filters. Finally, experimental results are shown on synthetic and real data.
Toward Assessing Vulnerability and Risk of Sensor Networks under Node Compromise

It is important to assess vulnerability of network and information system to countermeasure against a variety of attack in effective and efficient way. But vulnerability and risk assessment methodology for network and information systems could not be directly applied to sensor networks because sensor networks have different properties compared to traditional network and information system. This paper proposes a vulnerability assessment framework for cluster based sensor networks. The vulnerability assessment for sensor networks is presented. Finally, the case study in cluster based sensor networks is described to show possibility of the framework.