PIELG: A Protein Interaction Extraction Systemusing a Link Grammar Parser from Biomedical Abstracts

Due to the ever growing amount of publications about protein-protein interactions, information extraction from text is increasingly recognized as one of crucial technologies in bioinformatics. This paper presents a Protein Interaction Extraction System using a Link Grammar Parser from biomedical abstracts (PIELG). PIELG uses linkage given by the Link Grammar Parser to start a case based analysis of contents of various syntactic roles as well as their linguistically significant and meaningful combinations. The system uses phrasal-prepositional verbs patterns to overcome preposition combinations problems. The recall and precision are 74.4% and 62.65%, respectively. Experimental evaluations with two other state-of-the-art extraction systems indicate that PIELG system achieves better performance. For further evaluation, the system is augmented with a graphical package (Cytoscape) for extracting protein interaction information from sequence databases. The result shows that the performance is remarkably promising.

Adsorption of H2 and CO on Iron-based Catalysts for Fischer-Tropsch Synthesis

The adsorption properties of CO and H2 on iron-based catalyst with addition of Zr and Ni were investigated using temperature programmed desorption process. It was found that on the carburized iron-based catalysts, molecular state and dissociative state CO existed together. The addition of Zr was preferential for the molecular state adsorption of CO on iron-based catalyst and the presence of Ni was beneficial to the dissociative adsorption of CO. On H2 reduced catalysts, hydrogen mainly adsorbs on the surface iron sites and surface oxide sites. On CO reduced catalysts, hydrogen probably existed as the most stable CH and OH species. The addition of Zr was not benefit to the dissociative adsorption of hydrogen on iron-based catalyst and the presence of Ni was preferential for the dissociative adsorption of hydrogen.

The Development of a Teachers- Self-Efficacy Instrument for High School Physical Education Teacher

The purpose of this study was to develop a “teachers’ self-efficacy scale for high school physical education teachers (TSES-HSPET)” in Taiwan. This scale is based on the self-efficacy theory of Bandura [1], [2]. This study used exploratory and confirmatory factor analyses to test the reliability and validity. The participants were high school physical education teachers in Taiwan. Both stratified random sampling and cluster sampling were used to sample participants for the study. 350 teachers were sampled in the first stage and 234 valid scales (male 133, female 101) returned. During the second stage, 350 teachers were sampled and 257 valid scales (male 143, female 110, 4 did not indicate gender) returned. The exploratory factor analysis was used in the first stage, and it got 60.77% of total variance for construct validity. The Cronbach’s alpha coefficient of internal consistency was 0.91 for sumscale, and subscales were 0.84 and 0.90. In the second stage, confirmatory factor analysis was used to test construct validity. The result showed that the fit index could be accepted (χ2 (75) =167.94, p

Fractal Dimension of Breast Cancer Cell Migration in a Wound Healing Assay

Migration in breast cancer cell wound healing assay had been studied using image fractal dimension analysis. The migration of MDA-MB-231 cells (highly motile) in a wound healing assay was captured using time-lapse phase contrast video microscopy and compared to MDA-MB-468 cell migration (moderately motile). The Higuchi fractal method was used to compute the fractal dimension of the image intensity fluctuation along a single pixel width region parallel to the wound. The near-wound region fractal dimension was found to decrease three times faster in the MDA-MB- 231 cells initially as compared to the less cancerous MDA-MB-468 cells. The inner region fractal dimension was found to be fairly constant for both cell types in time and suggests a wound influence range of about 15 cell layer. The box-counting fractal dimension method was also used to study region of interest (ROI). The MDAMB- 468 ROI area fractal dimension was found to decrease continuously up to 7 hours. The MDA-MB-231 ROI area fractal dimension was found to increase and is consistent with the behavior of a HGF-treated MDA-MB-231 wound healing assay posted in the public domain. A fractal dimension based capacity index has been formulated to quantify the invasiveness of the MDA-MB-231 cells in the perpendicular-to-wound direction. Our results suggest that image intensity fluctuation fractal dimension analysis can be used as a tool to quantify cell migration in terms of cancer severity and treatment responses.

Transimpedance Amplifier for Integrated 3D Ultrasound Biomicroscope Applications

This paper presents the design and implementation of a fully integrated transimpedance amplifier (TIA) as the analog frontend receiver for Capacitive Micromachined Ultrasound Transducers (CMUTs) for ultrasound biomicroscope imaging application. The amplifier is designed to amplify the received signals from 17.5MHz to 52.5MHz with a center frequency of 35MHz. The TIA was fabricated in GF 0.18μm 1P6M 30V high voltage process. The measurement results show that the designed amplifier can reach a transimpedance gain of 61.08dBΩ and operating frequency from 17.5MHz to 100MHz with 1VP-P output voltage under 6V power supply.

Thermal Analysis of Tibetan Vernacular Building - Case of Lhasa

Vernacular building is considered as sustainable in energy consumption and environment and its thermal performance is more and more concerned by researchers. This paper investigates the thermal property of the vernacular building in Lhasa by theoretical analysis on the aspects of building form, envelope and materials etc. The values of thermal resistance and thermal capacity of the envelope are calculated and compared with the current China building code and modern building case. And it is concluded that Lhasa vernacular building meets the current China building code of thermal standards and have better performance in some aspects, which is achieved by various passive means with close response to local climate conditions.

Development a New Model of EEVC/WG17 Lower Legform for Pedestrian Safety

Development, calibration and validation of a threedimensional model of the Legform impactor for pedestrian crash with bumper are presented. Lower limb injury is becoming an increasingly important concern in vehicle safety for both occupants and pedestrians. In order to prevent lower extremity injuries to a pedestrian when struck by a car, it is important to elucidate the loadings from car front structures on the lower extremities and the injury mechanism caused by these loadings. An impact test procedure with a legform addressing lower limb injuries in car pedestrian accidents has been proposed by EEVC/WG17. In this study a modified legform impactor is introduced and validated against EEVC/WG17 criteria. The finite element model of this legform is developed using LS-DYNA software. Total mass of legform impactor is 13.4 kg.Technical specifications including the mass and location of the center of gravity and moment of inertia about a horizontal axis through the respective centre of gravity in femur and tibia are determined. The obtained results of legform impactor static and dynamic tests are as specified in the EEVC/WG17.

Modeling of Pulping of Sugar Maple Using Advanced Neural Network Learning

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of Pulping of Sugar Maple problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified problem where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Enzymes Activity in Bovine Cervical Mucus Related to the Time of Ovulation And Insemination

Forty-five dairy cows were used to compare the enzyme activity of alkaline phosphatase (ALP), lactate dehydrogenase (LDH), α -amylase in the cervical mucus of cows during spontaneous and induced estrus using progestagen or PGF2 α and to determine whether these enzymes affect the fertility in cows with induced estrus, at the time of Al. The animals were assigned to 3 groups (no treatment, a Crestar® for 12 days, a double im injection of PGF2 α). The cows were artificially inseminated (AI). Cervical mucus samples were collected from all cows 3 to 5 min before the AI. The results are summarized as follows: ALP and α -amylase activity for spontaneous estrus were similar to those for induced estrus (P>0.05) . LDH activity levels during spontaneous and PGF2 α induced estrus was significantly lower (P < 0.001) than that in progestagene induced estrus groups. While no difference was found between the first and the third groups. Our result showed a significant difference in LDH activity levels between cows conceived with 2 or more AI and those conceived with 1 AI. The result of this study showed that the enzyme activity in cervical mucus is helpful for detection of ovulation and time of AI.

Extraction of Graphene-Titanium Contact Resistances using Transfer Length Measurement and a Curve-Fit Method

Graphene-metal contact resistance limits the performance of graphene-based electrical devices. In this work, we have fabricated both graphene field-effect transistors (GFET) and transfer length measurement (TLM) test devices with titanium contacts. The purpose of this work is to compare the contact resistances that can be numerically extracted from the GFETs and measured from the TLM structures. We also provide a brief review of the work done in the field to solve the contact resistance problem.

Development of Subjective Measures of Interestingness: From Unexpectedness to Shocking

Knowledge Discovery of Databases (KDD) is the process of extracting previously unknown but useful and significant information from large massive volume of databases. Data Mining is a stage in the entire process of KDD which applies an algorithm to extract interesting patterns. Usually, such algorithms generate huge volume of patterns. These patterns have to be evaluated by using interestingness measures to reflect the user requirements. Interestingness is defined in different ways, (i) Objective measures (ii) Subjective measures. Objective measures such as support and confidence extract meaningful patterns based on the structure of the patterns, while subjective measures such as unexpectedness and novelty reflect the user perspective. In this report, we try to brief the more widely spread and successful subjective measures and propose a new subjective measure of interestingness, i.e. shocking.

Implementation and Analysis of Elliptic Curve Cryptosystems over Polynomial basis and ONB

Polynomial bases and normal bases are both used for elliptic curve cryptosystems, but field arithmetic operations such as multiplication, inversion and doubling for each basis are implemented by different methods. In general, it is said that normal bases, especially optimal normal bases (ONB) which are special cases on normal bases, are efficient for the implementation in hardware in comparison with polynomial bases. However there seems to be more examined by implementing and analyzing these systems under similar condition. In this paper, we designed field arithmetic operators for each basis over GF(2233), which field has a polynomial basis recommended by SEC2 and a type-II ONB both, and analyzed these implementation results. And, in addition, we predicted the efficiency of two elliptic curve cryptosystems using these field arithmetic operators.

A Study on the Application of TRIZ to CAD/CAM System

This study created new graphical icons and operating functions in a CAD/CAM software system by analyzing icons in some of the popular systems, such as AutoCAD, AlphaCAM, Mastercam and the 1st edition of LiteCAM. These software systems all focused on geometric design and editing, thus how to transmit messages intuitively from icon itself to users is an important function of graphical icons. The primary purpose of this study is to design innovative icons and commands for new software. This study employed the TRIZ method, an innovative design method, to generate new concepts systematically. Through literature review, it then investigated and analyzed the relationship between TRIZ and idea development. Contradiction Matrix and 40 Principles were used to develop an assisting tool suitable for icon design in software development. We first gathered icon samples from the selected CAD/CAM systems. Then grouped these icons by meaningful functions, and compared useful and harmful properties. Finally, we developed new icons for new software systems in order to avoid intellectual property problem.

Fast Object/Face Detection Using Neural Networks and Fast Fourier Transform

Recently, fast neural networks for object/face detection were presented in [1-3]. The speed up factor of these networks relies on performing cross correlation in the frequency domain between the input image and the weights of the hidden layer. But, these equations given in [1-3] for conventional and fast neural networks are not valid for many reasons presented here. In this paper, correct equations for cross correlation in the spatial and frequency domains are presented. Furthermore, correct formulas for the number of computation steps required by conventional and fast neural networks given in [1-3] are introduced. A new formula for the speed up ratio is established. Also, corrections for the equations of fast multi scale object/face detection are given. Moreover, commutative cross correlation is achieved. Simulation results show that sub-image detection based on cross correlation in the frequency domain is faster than classical neural networks.

Utilizing Virtual Worlds in Education: The Implications for Practice

Multi User Virtual Worlds are becoming a valuable educational tool. Learning experiences within these worlds focus on discovery and active experiences that both engage students and motivate them to explore new concepts. As educators, we need to explore these environments to determine how they can most effectively be used in our instructional practices. This paper explores the current application of virtual worlds to identify meaningful educational strategies that are being used to engage students and enhance teaching and learning.

The Importance of 3D Mesh Generation for Large Eddy Simulation of Gas – Solid Turbulent Flows in a Fluidized Beds

The objective of this work is to show a procedure for mesh generation in a fluidized bed using large eddy simulations (LES) of a filtered two-fluid model. The experimental data were obtained by [1] in a laboratory fluidized bed. Results show that it is possible to use mesh with less cells as compared to RANS turbulence model with granular kinetic theory flow (KTGF). Also, the numerical results validate the experimental data near wall of the bed, which cannot be predicted by RANS.model.

Fast Complex Valued Time Delay Neural Networks

Here, a new idea to speed up the operation of complex valued time delay neural networks is presented. The whole data are collected together in a long vector and then tested as a one input pattern. The proposed fast complex valued time delay neural networks uses cross correlation in the frequency domain between the tested data and the input weights of neural networks. It is proved mathematically that the number of computation steps required for the presented fast complex valued time delay neural networks is less than that needed by classical time delay neural networks. Simulation results using MATLAB confirm the theoretical computations.

The State, Local Community and Participatory Governance Practices: Prospects of Change

In policy discourse of 1990s, more inclusive spaces have been constructed for realizing full and meaningful participation of common people in education. These participatory spaces provide an alternative possibility for universalizing elementary education against the backdrop of a history of entrenched forms of social and economical exclusion; inequitable education provisions; and shrinking role of the state in today-s neo-liberal times. Drawing on case-studies of bottom-up approaches to school governance, the study examines an array of innovative ways through which poor people gained a sense of identity and agency by evolving indigenous solutions to issues regarding schooling of their children. In the process, state-s institutions and practices became more accountable and responsive to educational concerns of the marginalized people. The deliberative participation emerged as an active way of experiencing deeper forms of empowerment and democracy than its passive realization as mere bearers of citizen rights.

Simplex Method for Solving Linear Programming Problems with Fuzzy Numbers

The fuzzy set theory has been applied in many fields, such as operations research, control theory, and management sciences, etc. In particular, an application of this theory in decision making problems is linear programming problems with fuzzy numbers. In this study, we present a new method for solving fuzzy number linear programming problems, by use of linear ranking function. In fact, our method is similar to simplex method that was used for solving linear programming problems in crisp environment before.

Mechanical Behaviour Analysis of Polyester Polymer Mortars Modified with Recycled GFRP Waste Materials

In this study the effect of incorporation of recycled glass-fibre reinforced polymer (GFRP) waste materials, obtained by means of milling processes, on mechanical behaviour of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste powder and fibres, with distinct size gradings, were incorporated into polyester based mortars as sand aggregates and filler replacements. Flexural and compressive loading capacities were evaluated and found better than unmodified polymer mortars. GFRP modified polyester based mortars also show a less brittle behaviour, with retention of some loading capacity after peak load. Obtained results highlight the high potential of recycled GFRP waste materials as efficient and sustainable reinforcement and admixture for polymer concrete and mortars composites, constituting an emergent waste management solution.