Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of the O ( 3 ) Bootstrap σ-Model with the Lattice Regularization at Low Energies

The renormalized coupling g R defined through the connected 4-point function at zero external momentum in the non-linear O(3) sigma-model in two dimensions, is computed in the continuum form factor bootstrap approach with estimated error ∼ 0.3%. New high precision data are presented for g R in the lattice regularized theory with standard action for nearly thermodynamic lattices L/ξ ∼ 7 and correlation lengths ξ up to ∼ 122 and with the fixed point action for correlation lengths up to ∼ 12. The agreement between the form factor and lattice results is within ∼ 1%. We also recompute the phase shifts at low energy by measuring the two-particle energies at finite volume, a task which was previously performed by Lüscher and Wolff using the standard action, but this time using the fixed point action. Excellent agreement with the Zamolodchikov S-matrix is found.
Emotions and prosociality: lessons for blood donation

Without volunteer blood a large proportion of healthcare delivery would not be possible. Blood donation is an archetypal altruistic and prosocial act, but like all altruism may also be motivated by selfish reasons. Key among these are the prosocial and moral emotions (e.g., gratitude, shame, guilt, anger). This chapter shows how blood donation can be used to manage negative emotions (e.g., guilt) and enhance well-being (warm-glow, pride). It also shows how negative emotions such as anger promote prosociality. It draws implications for interventions and develops a model showing how emotions and memory are linked across the donor cycle to influence behavior.
Using Modified CHI Square and Rough Set for Text Categorization with Many Redundant Features

Text categorization is a key problem of text mining. Although there are many research on this problem, the main works are focused on classification of big categories. There are very few researches on text categorization problems characterised by many redundant features. We call this kind of problem as fine-text-categorization. In this paper, we presented an algorithm based on modified CHI square feature selection and rough set to solve this problem. The features of categories are selected in a aggressive manner. The classification rules are extracted by using rough set theory. Experiments on real world corpora show that our algorithm can evidently improve classification precision, thus is promising.
The Financial Appraisal Profile (FAP) Model for Evaluation of Enterprise-Wide Information Technology: A Case Example

Enterprise-wide information systems adoption by organizations has become common place. Even with the benefits offered by such systems, there have also been many failures. One of the important reasons for these failures is inappropriate project evaluation and selection. In order to reduce the level of project failures, we introduce an innovative methodology, the financial appraisal profile (FAP) model, which seeks to address some of the issues and limitations posed by standard appraisal and evaluation approaches for strategic technologies and programs. By making the right decision in the first place and involving senior managers in the appraisal process, the organization will be better placed to achieve project success. The adoption of IGI PUBLISHING This paper appears in the publication, Modelling and Analysis of Enterprise Information Systems edited by A. Gunasekaran © 2007, IGI Global 701 E. Chocolate Avenue, Suite 200, Hershey PA 17033-1240, USA Tel: 717/533-8845; Fax 717/533-8661; URL-http://www.igi-pub.com ITB14248
Analysis of Iris Recognition Algorithms Prof

Iris recognition has been increasingly used with very satisfactory results. Presently, the challenge consists in unconstraint the image capturing conditions and enables its application to domains where the subjects’ cooperation is not expectable (e.g. criminal/terrorist seeks, missing children). In this type of use, due to variations in the image capturing distance and in the lighting conditions that determine the size of the subjects’ pupil, the area correspondent To the iris in the captured images will be highly varying too. In order to compensate this variation, common iris recognition proposals translate the segmented iris image to a double dimensionless pseudo-polar coordinate system, in a process known as the normalization stage, which can be regarded as a sampling of the original data with the inherent possibility of aliasing. In this paper we analyze the relationship between the size of the captured iris image and the overall recognition’s accuracy. Further, we identify the threshold for the sampling rate of the iris normalization process above which the error rates significantly increase.
An axial gradient of transgene methylation in murine skeletal muscle: genomic imprint of rostrocaudal position.

We previously used mice bearing a myosin light chain-chloramphenicol acetyltransferase (MLC1-CAT) transgene to show that adult muscle cells bear a heritable, cell autonomous memory of their rostrocaudal position. CAT mRNA and protein are expressed in a > 100-fold rostrocaudal gradient in skeletal muscles of developing and adult MLC1-CAT mice (Donoghue, M. J., Merlie, J. P., Rosenthal, N. and Sanes, J. R. (1991). Proc. Natl. Acad. Sci. USA 88, 5847-5851; Donoghue, M. J., Alvarez, J. D. , Merlie, J. P. and Sanes, J. R. (1991). J. Cell Biol. 115, 423-434). Moreover, both in primary cultures and in myogenic cell lines prepared from individual muscles of these mice, CAT levels reflect the body position from which the myoblasts were derived (Donoghue, M.J., Morris-Valero, R., Johnson, Y.R., Merlie, J.P. and Sanes, J. R. (1992). Cell 69, 67-77). Here, we show that the methylation state of the MLC1-CAT transgene in skeletal muscles is also graded along the rostrocaudal axis: methylation levels decrease and expression levels increase in the order, jaw-->neck-->chest and forelimb-->hindlimb. Methylation levels are also approx. 10-fold higher in rostrally derived than in caudally derived myogenic cell lines, which express low and high levels of CAT, respectively. Within each cell line, undifferentiated cells (myoblasts), which do not express the transgene, and differentiated cells (myotubes), which do, are indistinguishable in methylation state. Thus, differentiation-related changes in transgene expression do not affect position-related levels of transgene methylation. On the other hand, treatment of rostrally derived lines with the demethylating agent, 5-azacytidine, decreases methylation and increases expression of the transgene. Thus, perturbation of methylation affects expression. Taken together, these results suggest that methylation provides a genomic imprint of rostrocaudal body position that may serve as a component of the positional memory that mammalian cells retain into adulthood.
Trot gait control of quadruped robot based on inclination of body

Legged robots have been expected to work at areas where conventional robots with wheels cannot move. However, control of legged locomotion is much more difficult than wheel locomotion because a legged robot is exposed to risks to stumble. In conventional studies, the Zero Moment Point (ZMP) has been considered as an important index for controlling legged locomotion. On the other hand, many studies based on strategies of locomotion of animals mainly aim to generate rhythm of the robot motion or optimize energy consumption rather than control the motion. However, controlling the robot motion may also be improved by considering the effective locomotion theory of animals. In this study, inclination of robot's body is considered as a new index of stable walk instead of the ZMP and the controller design based on the new index is proposed. The proposed controller was verified by simulation of a robot walking with quadruped locomotion.
Transcranial direct current stimulation in patients with Alzheimer’s disease: Challenges and responses

The use of transcranial direct current stimulation ( tDCS ) as a noninvasive therapeutic approach for Alzheimer’s disease (AD) has gained increasing attention. Research regarding the utility of tDCS in AD is inconsistent. In this study, we reviewed the importance of individual diversity among AD patients, starting from the uninformative mean results. We also demonstrated variation among AD patients. Highly educated patients seem to benefit more; education also seems to modulate baseline measurements and the results. Individual cortical morphology also affects the current distribution, which influences the effectiveness of stimulation. We suggest the use of structural MRI to distinguish inter-individual variability; high-resolution modeling can also be used to predict current distributions and should be combined with cognitive training (CT) along with tDCS .
Information Extraction on the Web with Credibility Guarantee

The Web became the central medium for valuable sources of information extraction applications. However, such user-generated resources are often plagued by inaccuracies and misinformation due to the inherent openness and uncertainty of the Web. In this work we study the problem of extracting structured information out of Web data with a credibility guarantee. The ultimate goal is that not only the structured information should be extracted as much as possible but also its credibility is high. To achieve this goal, we propose a learning process to optimize the parameters of a probabilistic model that captures the relationships between users, their unstructured contents, and the underlying structured information. Our evaluations on real-world datasets show that our approach outperforms the baseline up to 6 times.
Automatic Quality Assessment of SRS Text by Means of a Decision-Tree-Based Text Classifier

The success of a software project is largely dependent upon the quality of the Software Requirements Specification (SRS) document, which serves as a medium to communicate user requirements to the technical personnel responsible for developing the software. This paper addresses the problem of providing automated assistance for assessing the quality of textual requirements from an innovative point of view, namely through the use of a decision- tree-based text classifier, equipped with Natural Language Processing (NLP) tools. The objective is to apply the text classification technique to build a system for the automatic detection of ambiguity in SRS text based on the quality indicators defined in the quality model proposed in this paper. We believe that, with proper training, such a text classification system will prove to be of immense benefit in assessing SRS quality. To the authors' best knowledge, ours is the first documented attempt to apply the text classification technique for assessing the quality of software documents.
Estimating Illumination Chromaticity via Support Vector Regression

Support vector regression is applied to the problem of estimating the chromaticity of the light illuminating a scene from a color histogram of an image of the scene. Illumination estimation is fundamental to white balancing digital color images and to understanding human color constancy. Under controlled experimental conditions, the support vector method is shown to perform well. Its performance is compared to other published methods including neural network color constancy color by correlation, and shades of gray.
Innovation and Investment in Capitalist Economies, 1870–2000: Kaleckian Dynamics and Evolutionary Life Cycles

Se estudia en este trabajo, el modelo kaleckiano del ciclo de la inversion que to-ma en cuenta el doble efecto de la inversion; sobre los beneficios y sobre la misma inversion. A estos determinantes se agregan los procesos del ciclo vital de la innovacion industrial que proporcionan el estimulo para la inversion. En-lazando el ciclo vital evolutivo del desarrollo industrial con procesos innovado-res, con la reproduccion ampliada kaleckiana a traves de los procesos de volati-lidad de la inversion, pueden identificarse la inestabilidad de los ciclos y su ten-dencia creciente.
Comparing 3-D protein structures similarity by using fractal features

We propose a new method for finding similarity in 3-D protein structure comparison. Different from the other existing methods, our method is grounded in the theory of fractal geometry. The proposed feature vectors of protein structures are simple to implement. The method is very fast because it requires neither alignment of the chains nor any chain-chain comparison. We calculate the fractal features of a set of 200 protein structures selected from PDB(Protein Data Bank). The experimental result shows that our method is very effective in classification of 3-D protein structures.
Religion and Spirituality: Benefits for Latino Adolescents Exposed to Community Violence

Using data from 223 Latino adolescents residing in poor, urban neighborhoods, we investigate whether spirituality, religious importance at home, and religious involvement moderate the relation between community violence exposure and psychological well-being. Results showed significant interaction effects between community violence exposure and spirituality/religiosity. Specifically, personal victimization and witnessing violence were associated with higher depression and posttraumatic stress disorder (PTSD) symptoms at low and average levels of spirituality, but not at high levels of spirituality. Witnessing violence was associated with higher PTSD symptoms at low and average levels of religious importance at home, but not at high levels of religious importance at home. Finally, witnessing violence was associated with higher depressive symptoms at low and average levels of religious involvement, but not at high levels of religious involvement. We discuss the potential benefits of supporting spiritual and religious development in Latino youth exposed to community violence.
Genetics and Environmental Stress Factor Contributions to Anterior Segment Malformations and Glaucoma

Glaucoma is one of the leading causes of irreversible blindness worldwide [1]. A gradual loss of retinal ganglion cells (RGCs) result in degeneration of the optic nerve head and visual field loss. Glaucoma is an age-related disease with a strong genetic basis. The risk of developing glaucoma significantly increases after age 40 [2,3]. An estimated 79.6 million people worldwide will have glaucoma by 2020 [1]. Patients with mutations in glaucoma-associated genes are more likely to develop juvenile-onset and early adult-onset glaucoma. In any case, early detection of glaucoma is essential to effectively manage the progression of the disease by preventing further loss of RGCs. Despite many years of research in this field, the precise cause(s) of RGC death remain unknown. The pathophysiology of glaucoma is complicated as environmental, genetic, and even stochastic factors all contribute to the pathology of glaucoma. Also, both the posterior segment, where the RGCs are located, and the anterior segment of the eye play key roles in the disease.
MK4MDD: A Multi-Level Knowledge Base and Analysis Platform for Major Depressive Disorder

Background Major depressive disorder (MDD) is a complex neuropsychiatric syndrome with high heterogeneity. There are different levels of biological components that underlie MDD and interact with each other. To uncover the disease mechanism, large numbers of studies at different levels have been conducted. There is a growing need to integrate data from multiple levels of research into a database to provide a systematic review of current research results. The cross level integration will also help bridge gaps of different research levels for further understanding on MDD. So far, there has been no such effort for MDD. Descriptions We offer researchers a Multi-level Knowledge base for MDD (MK4MDD) to study the interesting interplay of components in the pathophysiological cascade of MDD from genetic variations to diagnostic syndrome. MK4MDD contains 2,341 components and 5,206 relationships between components based on reported experimental results obtained by diligent literature reading with manual curation. All components were well classified with careful curation and supplementary annotation. The powerful search and visualization tools make all data in MK4MDD form a cross-linked network to be applied to a broad range of both basic and applied research. Conclusions MK4MDD aims to provide researchers with a central knowledge base and analysis platform for MDD etiological and pathophysiological mechanisms research. MK4MDD is freely available at http://mdd.psych.ac.cn.
Bounds on a Fair Policy with Near Optimal Performance

Providing fairness and providing good response times are often viewed as conflicting goals in scheduling. Scheduling policies that provide low response times, such as Shortest Remaining Processing Time (SRPT), are sometimes not fair, while fair policies like Processor Sharing (PS) provide response times far worse than SRPT. This seemingly inevitable tension between providing fairness and providing good response times was eliminated at last year's ACM Sigmetrics conference with the introduction of a new scheduling policy, Fair Sojourn Protocol (FSP), that appears to provide both [9]. The FSP policy is provably fair, as seen directly from its definition, and simulations show that FSP has a very low mean response time, close to that of SRPT in many cases [9]. Unfortunately, analyzing the mean response time of the FSP policy has proven to be difficult, and thus the queueing performance of FSP has only be assessed via simulation. In this work, we present the first queueing analysis of FSP. This analysis yields close upper and lower bounds on the mean response time and mean slowdown of the M/GI/1/FSP queue. Our upper bound shows that the improvement of FSP over PS is substantial: for all job size distributions, the mean response time and mean slowdown under FSP are a fraction (1 — £) of that under PS, where p is the system load. For distributions with decreasing failure rate the improvement is even greater. We also prove that the mean response time of SRPT and FSP are quite close. Lastly, our bounds reveal that FSP has yet another desirable property: similarly to PS, the FSP policy is largely insensitive to the variability of the job size distribution.
Increasing Accountability Through User-Interface Design Artifacts: A New Approach to Addressing the Problem of Access-Policy Violations

Access-policy violations are a growing problem with substantial costs for organizations. Although training programs and sanctions have been suggested as a means of reducing these violations, evidence shows the problem persists. It is thus imperative to identify additional ways to reduce access-policy violations, especially for systems providing broad access to data. We use accountability theory to develop four user-interface (UI) design artifacts that raise users' accountability perceptions within systems and in turn decrease access-policy violations. To test our model, we uniquely applied the scenario-based factorial survey method to various graphical manipulations of a records system containing sensitive information at a large organization with over 300 end users who use the system daily. We show that the UI design artifacts corresponding to four submanipulations of accountability can raise accountability and reduce access policy violation intentions. Our findings have several theoretical and practical implications for increasing accountability using UI design. Moreover, we are the first to extend the scenario-based factorial survey method to test design artifacts. This method provides the ability to use more design manipulations and to test with fewer users than is required in traditional experimentation and research on human--computer interaction. We also provide bootstrapping tests of mediation and moderation and demonstrate how to analyze fixed and random effects within the factorial survey method optimally.
Reorientation and Landmark-Guided Search by Young Children

Disoriented 4-year-old children use a distinctive container to locate a hidden object, but do they reorient by this information? We addressed this question by testing children's search for objects in a circular room containing one distinctive and two identical containers. Children's search patterns provided evidence that the distinctive container served as a direct cue to a hidden object's location, but not as a directional signal guiding reorientation. The findings suggest that disoriented children's search behavior depends on two distinct processes: a modular reorientation process attuned to the geometry of the surface layout and an associative process linking landmarks to specific locations.
Atomistic simulations of kinks in 1 Õ 2 a Š 111 ‹ screw dislocations in bcc tantalum

Two types of equilibrium core structures ~denoted symmetric and asymmetric! for 1/2a^111& screw dislocations in bcc metals have been found in atomistic simulations. In asymmetric ~or polarized! cores, the central three atoms simultaneously translate along the Burgers vector direction. This collective displacement of core atoms is called polarization. In contrast, symmetric ~nonpolarized! cores have zero core polarization. To examine the possible role of dislocation core in kink-pair formation process, we studied the multiplicity, structural features, and formation energies of 1/3a^112& kinks in 1/2a^111& screw dislocations with different core structures. To do this we used a family of embedded atom model potentials for tantalum ~Ta! all of which reproduce bulk properties ~density, cohesive energy, and elastic constants! from quantum mechanics calculations but differ in the resulting polarization of 1/2a^111& screw dislocations. For dislocations with asymmetric core, there are two energy equivalent core configurations @with positive ~P! and negative ~N! polarization#, leading to 2 types of ~polarization! flips, 8 kinds of isolated kinks, and 16 combinations of kink pairs. We find there are only two elementary kinks, while the others are composites of elementary kinks and flips. In contrast, for screw dislocations with symmetric core, there are only two types of isolated kinks and one kind of kink pair. We find that the equilibrium dislocation core structure of 1/2a^111& screw dislocations is an important factor in determining the kink-pair formation energy.
Understanding physicians' imaging test use in low back pain care: the role of focus groups.

OBJECTIVE To gain understanding about why a controlled intervention to reduce variability in lumbar spine imaging test use rates for low back pain patients was ineffective among internal medicine and family practice physicians in a large US health maintenance organization. DESIGN We retrospectively analyzed data from focus groups that had been conducted prior to the implementation of the intervention. The physicians were asked about the factors that influence their decisions to order such tests. STUDY PARTICIPANTS Internal medicine and family practice physicians in the intervention group. MAIN STUDY FINDINGS: Most of the variability in physicians' imaging test ordering appeared to occur in the care of patients with back pain of non-traumatic origin who had no radicular symptoms. Within that clinical context, nonclinical factors such as patient age and work status, time constraints, access problems and ambiguity about internal referral processes were important factors in physicians' decisions. Especially relevant were tensions and conflicts the physicians face as they attempted to meet conflicting role obligations in the health maintenance organization. These tensions raised issues of patient trust in their physicians and in medical care organizations, and it appeared that imaging test orders sometimes served social and symbolic functions in resolving them. CONCLUSION Our findings suggest that gaining information from focus groups prior to designing physician behavior change interventions may aid the design of more effective interventions.