Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of endodontic irrigating solutions on the microhardness and roughness of root canal dentin: an in vitro study.

CONTEXT To evaluate the effect of widely used endodontic irrigating solutions on root dentin microhardness and surface roughness. MATERIALS AND METHODS One hundred twenty, non-carious extracted human permanent incisor teeth were selected. The crowns of the teeth were sectioned and the roots were separated longitudinally to get 240 specimens. These specimens were then divided into six groups according to the irrigating solutions used. The solutions used were 5% and 2.5% NaOCl solutions, 3% H2 O2 , 17% EDTA solution, 0.2% chlorhexidine gluconate, and distilled water. Then, the specimens were subjected to microhardness and roughness testing. The data were analyzed using ANOVA and Tukey's multiple comparison tests. RESULTS The results of this study indicated that all irrigation solutions, except 0.2% chlorhexidine gluconate, decreased the microhardness of root dentin, and 3% H2 O2 and 0.2% chlorhexidine gluconate had no effect on surface roughness. CONCLUSIONS Within the limitation of this study, it is concluded that 0.2% chlorhexidine gluconate seems to be an appropriate irrigation solution, because of its harmless effect on the microhardness and surface roughness of root canal dentin.
BER Performance Using 16-QAM Modulation in V-Blast MIMO System

In This paper we have tried to reduce the values of BER using different number of transmitter antenna and receiver antenna combinations. The MIMO V-Blast System came into reality to improve the gain and error rate. Here we study the V-BLAST (Vertical-Bell Laboratory Layered Space Time) MIMO with ZF (Zero- Forcing), MMSE (Minimum Mean-Square Error), and QR-Decomposition detection algorithms with 16-QAM modulation scheme and simulate the model in AWGN environment. From simulation we find that instead of using equal number of transmitter and receiver antennas, we will get better performance of BER with increased no. of receiver antennas only compared to transmitters.
College Students Attitudes toward Learning Process and Outcome of Online Instruction and Distance Learning across Learning Styles

This study uses the Learning-Style Inventory LSI (Smith & Kolb, 1985) to explore to what extent student attitudes toward learning process and outcome of online instruction and Distance Learning are affected by their cognitive styles and learning behaviors. It finds that there are not much statistically significant differences in perceptions on many learning process and outcome indicators across learning styles. However, students who learn from concrete experience and reflective experimentation/observation didnt appreciate the flexible class schedule, need instant questions and feedback, and expect more leniency from the instructor.
L 1 pred : A Sequence-Based Prediction Tool for Catalytic Residues in Enzymes with the L 1-logreg Classifier

To understand enzyme functions, identifying the catalytic residues is a usual first step. Moreover, knowledge about catalytic residues is also useful for protein engineering and drug-design. However, to experimentally identify catalytic residues remains challenging for reasons of time and cost. Therefore, computational methods have been explored to predict catalytic residues. Here, we developed a new algorithm, L1pred, for catalytic residue prediction, by using the L1-logreg classifier to integrate eight sequence-based scoring functions. We tested L1pred and compared it against several existing sequence-based methods on carefully designed datasets Data604 and Data63. With ten-fold cross-validation, L1pred showed the area under precision-recall curve (AUPR) and the area under ROC curve (AUC) of 0.2198 and 0.9494 on the training dataset, Data604, respectively. In addition, on the independent test dataset, Data63, it showed the AUPR and AUC values of 0.2636 and 0.9375, respectively. Compared with other sequence-based methods, L1pred showed the best performance on both datasets. We also analyzed the importance of each attribute in the algorithm, and found that all the scores contributed more or less equally to the L1pred performance. Citation: Dou Y, Wang J, Yang J, Zhang C (2012) L1pred: A Sequence-Based Prediction Tool for Catalytic Residues in Enzymes with the L1-logreg Classifier. PLoS ONE 7(4): e35666. doi:10.1371/journal.pone. 0035666 Editor: Iddo Friedberg, Miami University, United States of America Received January 4, 2012; Accepted March 19, 2012; Published April 27, 2012 Copyright: 2012 Dou et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Funding: This work was partially supported by the National Natural Science Foundation of China (No. 10731040), Shanghai Leading Academic Discipline Project (No. S30405) and Innovation Program of Shanghai Municipal Education Commission (No. 09zz134). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. No additional external funding received for this study. Competing Interests: The authors have declared that no competing interests exist. * E-mail: czhang5@unl.edu
Computational Properties of the Hippocampus Increase the Efficiency of Goal-Directed Foraging through Hierarchical Reinforcement Learning

The mammalian brain is thought to use a version of Model-based Reinforcement Learning (MBRL) to guide “goal-directed” behavior, wherein animals consider goals and make plans to acquire desired outcomes. However, conventional MBRL algorithms do not fully explain animals' ability to rapidly adapt to environmental changes, or learn multiple complex tasks. They also require extensive computation, suggesting that goal-directed behavior is cognitively expensive. We propose here that key features of processing in the hippocampus support a flexible MBRL mechanism for spatial navigation that is computationally efficient and can adapt quickly to change. We investigate this idea by implementing a computational MBRL framework that incorporates features inspired by computational properties of the hippocampus: a hierarchical representation of space, “forward sweeps” through future spatial trajectories, and context-driven remapping of place cells. We find that a hierarchical abstraction of space greatly reduces the computational load (mental effort) required for adaptation to changing environmental conditions, and allows efficient scaling to large problems. It also allows abstract knowledge gained at high levels to guide adaptation to new obstacles. Moreover, a context-driven remapping mechanism allows learning and memory of multiple tasks. Simulating dorsal or ventral hippocampal lesions in our computational framework qualitatively reproduces behavioral deficits observed in rodents with analogous lesions. The framework may thus embody key features of how the brain organizes model-based RL to efficiently solve navigation and other difficult tasks.
Exploring Epistemologies: Social Work Action as a Reflection of Philosophical Assumptions.

Abstract Using Habermas' (1971) Grand Theory and Schaefer's (1979) notion of Theory as Fiction, two major philosophical assumptions that undergird the literature, practice and teaching of social work are reviewed. Empiricism dominates social work theory and aims at technical control. Existentialism has been an important but marginal voice and attempts to explain subjective meaning. Two newer theoretical positions also are introduced: Critical theory, which considers humanity's ability to reflect on history to be an agent of societal change; and deconstruction, which questions the validity of any structure. The article concludes with a consideration of the implications of using each position as a context for teaching.
A MULTI-AGENT BASED PRICING : A VIRTUAL STOCK MARKET SIMULATION

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Interactions between investors and information exchange during a transaction reproduce the market dynamics and organize the multi-agent based pricing.
Synthesis, structural and optical characterizations of cadmium oxide (CdO) thin films by chemical bath deposition (CBD) technique

Thin films of cadmium oxide (CdO) were synthesized and characterized using chemical bath deposition (CBD) technique. The XRD studies revealed amorphous CdO thin films which upon annealing at 623K transformed to polycrystalline structure. The optical studies showed that the CdO films have high average transmittance over 60% in the visible region and direct optical bandgaps of 2.02 ± 0.05 eV, 2.03 ± 0.05eV and 2.05 ± 0.05eV for samples X, Y, Z respectively. These characteristics make them good candidates for applications in photodiodes, phototransistors, photovoltaics, transparent electrodes, liquid crystal displays, IR detectors and anti-reflection coatings. Key words: Thin films, chemical bath method, cadmium oxide, characterizations, bandgap.
Query-based composition for large-scale language model in LVCSR

This paper describes a query-based composition algorithm that can integrate an ARPA format language model in the unified WFST framework, which avoids the memory and time cost of converting the language models to WFST and optimizing the WFST of language models. The proposed algorithm is applied to on-the-fly one-pass decoder and rescoring decoder. Both modified decoder require less memory during decoding on different scale of language models. What's more, query-based on-the-fly one-pass decoder nearly has the same decoding speed as standard one and query-based rescoring decoder even use less time to rescore the lattice. Because of these advantages, large-scale language models can be applied by query-based composition algorithm to improve the performance of large vocabulary continuous speech recognition.
The Turn Once Again Toward Practice-Based Teacher Education

Current work to identify the core teaching practices that should be included in teacher education curriculum is a part of a long-standing tradition of reform in American teacher education. This article situates the proposals of Hiebert and Morris and the contemporary work to which it is linked within this historical tradition and identifies several issues that need to be addressed by this current work. These include the task of developing a system that unlike performance-based systems in the past is evidence-based, manageable, and sustainable, and that does not ignore important aspects of good teaching.
TR # : ISIS-06-706 Title : OASiS : A Service-Oriented Middleware for Pervasive Ambient-Aware Sensor Networks

Heterogeneous sensor networks consisting of networked devices embedded into the physical world have a significant role in pervasive computing systems. Such sensor networks may contain wireless sensor networks that are ensembles of small, smart, and cheap sensing and computing devices that permeate the environment, as well as high-bandwidth rich sensors such as satellite imaging systems, meteorological stations, air quality stations, and security cameras. Emergency response, homeland security, and many other applications have a very real need to interconnect such diverse networks and access information in real-time. While Web service standards provide well-developed mechanisms for resource-intensive computing nodes, linking such mechanisms with wireless sensor networks is very challenging because of limited resources, volatile communication links, and often node mobility. This paper presents a service-oriented programming model and middleware for ad-hoc wireless sensor networks which permits discovery and access of Web services. Sensor network applications are realized as graphs of modular and autonomous services with well-defined interfaces that allow them to be published, discovered, and invoked over the network, providing a convenient mechanism for integrating services from heterogeneous sensor systems. Our approach provides dynamic discovery, composition, and binding of services based on an efficient localized constraint satisfaction algorithm that can be used for developing ambient-aware applications that adapt to changes in the environment. A tracking application that employs many inexpensive sensor nodes, as well as a Web service, is used to illustrate the approach. Our results demonstrate the feasibility of ambient-aware applications that interconnect wireless sensor networks and Web services. ∗ Corresponding author: Tel. : +1 615 322 8283; Fax: +1 615 343 5459. Email address: xenofon.koutsoukos@vanderbilt.edu (Xenofon Koutsoukos,).
Isolating the Effect of Virtual Reality Based Exposure Therapy for Agoraphobia: a Comparative Trial

The isolated effect of Virtual Reality Based Exposure Therapy (VRBET) for agoraphobia was analyzed through a comparative trial involving the first 10 agoraphobic participants. The participants were randomly assigned to two groups: VREBT only and VREBT combined with cognitive therapy. All the required Virtual Environments (VE) were created with an inexpensive Game Level Editor (GLE). Outcome measures supported the immersive effect of the VEs. Questionnaires, behavioral tests and physiological measures indicated a positive effect of VRBET alone. The addition of cognitive therapy to VREBT did not appear to generate any significant differences. Consequences for future research and practice are discussed.
Node Evaluation in the Chord P2P Systems

In this paper we investigate two statistical estimators for the number of nodes in the Chord peer-to-peer system and one estimator for the number of information items stored in the system. The first estimator of the number of nodes is based on the Maximum Likelihood Estimation (MLE) technology and the second is based on the Methods of Moments (MM). We compare its statistical properties, show that the MM estimator has a better properties for our purposes and we discuss how we can implement this estimators in the Chord system.Our solutions can be implemented in Chord in such a way that they do not require any additional transmissions since all necessary information can be gathered during the standard operations of checking consistency of the Chord structure.Our results can be applied not only to the Chord P2P system but can be adopted to other decentralized and structured systems.
Recent trends in stimulant medication use among U.S. children.

OBJECTIVE Stimulant medications, such as methylphenidate and amphetamines, are commonly prescribed to treat attention deficit hyperactivity disorder. Stimulant use increased fourfold from 1987 (0.6%) to 1996 (2.4%) among subjects 18-year-old and younger in the U.S. The aim of this study was to determine whether pediatric use of stimulants continued to rise during the period 1997-2002. METHOD The Medical Expenditure Panel Survey (MEPS) database for the years 1997-2001 was analyzed. The MEPS is a yearly survey of a nationally representative sample of civilian, noninstitutionalized U.S. households, conducted by the U.S. Agency for Health Care Research and Quality. Previously reported estimates from the 1996 MEPS and the 1987 National Medical Expenditure Survey, the predecessor to MEPS, were also replicated to compare recent trends to changes between 1987 and 1996. RESULTS The prevalence use of stimulants among subjects under 19 years of age was 2.7% (95% C.I. 2.3-3.1) in 1997 and 2.9% (95% C.I. 2.5-3.3) in 2002, with no statistically significant change during these 6 years. Likewise, when pooling data across years and comparing the rate in 1997-1998 (2.8%) with the rate in 2001-2002 (3.0%), no statistically significant changes emerged. Use was highest among 6-12 year olds (4.8% in 2002), as compared with 3.2% among 13-19 year olds and 0.3% among children under 6. An estimated 2.2 million (95% C.I. 1.9-2.6) children received stimulant medication in 2002 as compared to 2.0 million (95% C.I. 1.7-2.3) in 1997. CONCLUSIONS The steep increase in the utilization of stimulants among children 18 years and younger that occurred over the 1987-1996 period attenuated in the following years through 2002, and has remained stable among very young children.
LEAR and XRCE's Participation to Visual Concept Detection Task - ImageCLEF 2010

In this paper we present the common effort of Lear and XRCE for the ImageCLEF Visual Concept Detection and Annotation Task. We first sought to combine our individual state-of-the-art approaches: the Fisher vector image representation, with the TagProp method for image auto-annotation. Our second motivation was to investigate the annotation performance by using extra information in the form of provided Flickr-tags. The results show that using the Flickr-tags in combination with visual features improves the results of any method using only visual features. Our winning system, an early-fusion linear-SVM classifier, trained on visual and Flickr-tags features, obtains 45.5% in mean Average Precision (mAP), almost a 5% absolute improvement compared to the best visual-only system. Our best visual-only system obtains 39.0% mAP, and is close to the best visual-only system. It is a late-fusion linear-SVM classifier, trained on two types of visual features (SIFT and colour). The performance of TagProp is close to our SVM classifiers. The methods presented in this paper, are all scalable to large datasets and/or many concepts. This is due to the fast FK framework for image representation, and due to the classifiers. The linear SVM classifier has proven to scale well for large datasets. The k-NN approach of TagProp, is interesting in this respect since it requires only 2 parameters per concept.
Sociology and the Virtual: Interactive Mirrors, Representational Thinking and Intensive Power

This article explores the role of images in the workings of contemporary power. It examines one of the central ways in which sociology has approached images as representations and proposes an alternative understanding of images through the concepts of interactivity, intensity and the virtual. Focusing on the examples of three interactive mirrors, one a piece of artwork, another designed to be located in a designer shop and the other a medical mirror for tracking ‘vital signs’, it suggests that the mirrors emphasize the screen and, in so doing, disrupt a notion of images of representations. Images are instead brought to life; intensively experienced rather than extensively read. The article engages, first, with the increasing prevalence of screens and, second, with the moves in sociology towards theorizing the value of the concept of the virtual. Arguing that images are felt and lived out, the article seeks to contribute to how sociology has dealt with, and might further develop, the concept of the virtual as a productive way of understanding the relationships between images, screens, power and life.
Auto-percepções, auto-estima, ansiedade físico-social e imagem corporal - estudo comparativo entre instrutores de fitness e praticantes de actividade física

O instrutor de fitness e constantemente confrontado, nas suas aulas, com a sua imagem corporal, auto-conceito, auto-estima e com a apreciacao da mesma pelo proprio e pela classe. Assim, o modo como o instrutor se auto-percepciona e como este pensa como os outros o percepcionam tem vindo a ser um tema ainda por responder. O proposito de examinar o modo como o Autoconceito, a Auto-estima e a Imagem Corporal se reflecte na vida profissional do instrutor de fitness podera, de alguma forma, cooperar na procura dessa resposta.
Parametrizable behavioral IP module for a data-localized low-power FFT

FFTs are important modules in embedded telecom systems, many of which require low-power real-time implementations. This paper describes a technique for aggressively localizing data accesses in a (inverse) fast Fourier transformation at the source code level. The global I/O functionality is not modified and neither is the bit-true arithmetic behavior. Typically 20 to 50% of the background memory accesses can be saved. A heavily parametrizable solution is proposed which leads to a family of power optimized algorithm codes. Moreover, efficient coding details for specific instances are shown.
A novel co-evolutionary approach to automatic software bug fixing

Many tasks in software engineering are very expensive, and that has led the investigation to how to automate them. In particular, software testing can take up to half of the resources of the development of new software. Although there has been a lot of work on automating the testing phase, fixing a bug after its presence has been discovered is still a duty of the programmers. In this paper we propose an evolutionary approach to automate the task of fixing bugs. This novel evolutionary approach is based on co-evolution, in which programs and test cases co-evolve, influencing each other with the aim of fixing the bugs of the programs. This competitive co-evolution is similar to what happens in nature for predators and prey. The user needs only to provide a buggy program and a formal specification of it. No other information is required. Hence, the approach may work for any implementable software. We show some preliminary experiments in which bugs in an implementation of a sorting algorithm are automatically fixed.
Assessment of gait recovery in children after traumatic brain injury

Objective: The aims were: (1) to quantify the functional limitation of children at the beginning of recovery of independent ambulation after Traumatic Brain Injury (TBI), using clinical-functional scales; (2) to evaluate the changes in gait pattern during rehabilitation (about 5 months later), using 3D Gait Analysis (GA) in post-acute phase; (3) to investigate the presence of correlation among parameters obtained by 3DGA, clinical assessment and measures connected with the trauma. Methods: Fourteen children with hemiplegia after severe TBI were evaluated at independent gait recovery (S0) and 5.5 months later (S1) by clinical assessment (GOS, DRS, WeeFIM and GMFM) and 3D GA (spatio-temporal parameters, kinematics and kinetics). Results: At S1 all clinical measures had improved. Regarding spatio-temporal parameters, velocity and step length improved. Significant progress was evident at the ankle joint, while an unchanged condition appeared at pelvis and hip in sagittal plane with a worsening of hip rotation which increased its internal rotation. Significant correlations were found between motor performance, clinical assessment and trauma-related measures. Conclusions: Repeated GA and clinical evaluations were useful in quantifying the motor recovery of children with TBI during rehabilitation underpinning the role of GA in quantifying these modifications in an objective and non-invasive way.
Arithmetic optimization using carry-save-adders

Carry-save-adder (CSA) is the most often used type of operation In Implementing a fast computation of arithmetics of register-transfer level design in industry. This paper establishes a relationship between the properties of arithmetic computations and several optimizing transformations using CSAs to derive consistently better qualities of results than those of manual implementations. In particular, we introduce two important concepts, operation-duplication and operation-split, which are the main driving techniques of our algorithm for achieving an extensive utilization of CSAs. Experimental results from a set of typical arithmetic computations found in industry designs indicate that automating CSA optimization with our algorithm produces designs with significantly faster timing and less area.