Lipase Catalyzed Synthesis of Aromatic Esters of Sugar Alcohols

Commercially available lipases (Candida antarctica lipase B, Novozyme 435, Thermomyces lanuginosus lipase, and Lipozyme TL IM), as well as sol-gel immobilized lipases, have been screened for their ability to acylate regioselectively xylitol, sorbitol, and mannitol with a phenolic ester in a binary mixture of t-butanol and dimethylsulfoxide. HPLC and MALDI-TOF MS analysis revealed the exclusive formation of monoesters for all studied sugar alcohols. The lipases immobilized by the sol-gel entrapment method proved to be efficient catalysts, leading to high conversions (up to 60%) in the investigated acylation reactions. From a sequence of silane precursors with different nonhydrolyzable groups in their structure, the presence of octyl and i-butyl group was most beneficial for the catalytic activity of sol-gel entrapped lipases in the studied process.

Hidden State Probabilistic Modeling for Complex Wavelet Based Image Registration

This article presents a computationally tractable probabilistic model for the relation between the complex wavelet coefficients of two images of the same scene. The two images are acquisitioned at distinct moments of times, or from distinct viewpoints, or by distinct sensors. By means of the introduced probabilistic model, we argue that the similarity between the two images is controlled not by the values of the wavelet coefficients, which can be altered by many factors, but by the nature of the wavelet coefficients, that we model with the help of hidden state variables. We integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has sub-pixel accuracy and is robust to noise and to other variations like local illumination changes. We present the performance of our algorithm on various image types.

A Pairwise-Gaussian-Merging Approach: Towards Genome Segmentation for Copy Number Analysis

Segmentation, filtering out of measurement errors and identification of breakpoints are integral parts of any analysis of microarray data for the detection of copy number variation (CNV). Existing algorithms designed for these tasks have had some successes in the past, but they tend to be O(N2) in either computation time or memory requirement, or both, and the rapid advance of microarray resolution has practically rendered such algorithms useless. Here we propose an algorithm, SAD, that is much faster and much less thirsty for memory – O(N) in both computation time and memory requirement -- and offers higher accuracy. The two key ingredients of SAD are the fundamental assumption in statistics that measurement errors are normally distributed and the mathematical relation that the product of two Gaussians is another Gaussian (function). We have produced a computer program for analyzing CNV based on SAD. In addition to being fast and small it offers two important features: quantitative statistics for predictions and, with only two user-decided parameters, ease of use. Its speed shows little dependence on genomic profile. Running on an average modern computer, it completes CNV analyses for a 262 thousand-probe array in ~1 second and a 1.8 million-probe array in 9 seconds

Network Analysis in a Natural Perturbed Ecosystem

The objective of this work is to explicit knowledge on the interactions between the chlorophyll-a and nine meroplankton larvae of epibenthonic fauna. The studied case is the Arraial do Cabo upwelling system, Southeastern of Brazil, which provides different environmental conditions. To assess this information a network approach based in probability estimative was used. Comparisons among the generated graphs are made in the light of different water masses, application of Shannon biodiversity index, and the closeness and betweenness centralities measurements. Our results show the main pattern among different water masses and how the core organisms belonging to the network skeleton are correlated to the main environmental variable. We conclude that the approach of complex networks is a promising tool for environmental diagnostic.

Characterization of Carbon Based Nanometer Scale Coil Growth

The carbon based coils with the nanometer scale have the 3 dimension helix geometry. We synthesized the carbon nano-coils by the use of chemical vapor deposition technique with iron and tin as the catalysts. The fabricated coils have the external diameter of ranging few hundred nm to few thousand nm. The Scanning Electro-Microscope (SEM) and Tunneling Electro-Microscope has shown detail images of the coil-s structure. The fabrication of the carbon nano-coils can be grown on the metal and non-metal substrates, such as the stainless steel and silicon substrates. Besides growth on the flat substrate; they also can be grown on the stainless steel wires. After the synthesis of the coils, the mechanical and electro-mechanical property is measured. The experimental results were reported.

A New Quantile Based Fuzzy Time Series Forecasting Model

Time series models have been used to make predictions of academic enrollments, weather, road accident, casualties and stock prices, etc. Based on the concepts of quartile regression models, we have developed a simple time variant quantile based fuzzy time series forecasting method. The proposed method bases the forecast using prediction of future trend of the data. In place of actual quantiles of the data at each point, we have converted the statistical concept into fuzzy concept by using fuzzy quantiles using fuzzy membership function ensemble. We have given a fuzzy metric to use the trend forecast and calculate the future value. The proposed model is applied for TAIFEX forecasting. It is shown that proposed method work best as compared to other models when compared with respect to model complexity and forecasting accuracy.

Design of Moving Sliding Surfaces in A Variable Structure Plant and Chattering Phenomena

This paper deals with the design of a moving sliding surface in a variable structure plant for a second order system. The chattering phenomena is also dealt with during the switching process for an unstable sliding surface condition. The simulation examples considered in this paper shows the effectiveness of the sliding mode control method used for the design of the moving sliding surfaces. A simulink model of the continuous system was also developed in MATLAB-SIMULINK for the design and hence demonstrated. The phase portraits and the state plots shows the demonstration of the powerful control technique which can be applied for second order systems.

Probabilistic Modelling of Marine Bridge Deterioration

Chloride induced corrosion of steel reinforcement is the main cause of deterioration of reinforced concrete marine structures. This paper investigates the relative performance of alternative repair options with respect to the deterioration of reinforced concrete bridge elements in marine environments. Focus is placed on the initiation phase of reinforcement corrosion. A laboratory study is described which involved exposing concrete samples to accelerated chloride-ion ingress. The study examined the relative efficiencies of two repair methods, namely Ordinary Portland Cement (OPC) concrete and a concrete which utilised Ground Granulated Blastfurnace Cement (GGBS) as a partial cement replacement. The mix designs and materials utilised were identical to those implemented in the repair of a marine bridge on the South East coast of Ireland in 2007. The results of this testing regime serve to inform input variables employed in probabilistic modelling of deterioration for subsequent reliability based analysis to compare the relative performance of the studied repair options.

Modeling and FOS Feedback Based Control of SISO Intelligent Structures with Embedded Shear Sensors and Actuators

Active vibration control is an important problem in structures. The objective of active vibration control is to reduce the vibrations of a system by automatic modification of the system-s structural response. In this paper, the modeling and design of a fast output sampling feedback controller for a smart flexible beam system embedded with shear sensors and actuators for SISO system using Timoshenko beam theory is proposed. FEM theory, Timoshenko beam theory and the state space techniques are used to model the aluminum cantilever beam. For the SISO case, the beam is divided into 5 finite elements and the control actuator is placed at finite element position 1, whereas the sensor is varied from position 2 to 5, i.e., from the nearby fixed end to the free end. Controllers are designed using FOS method and the performance of the designed FOS controller is evaluated for vibration control for 4 SISO models of the same plant. The effect of placing the sensor at different locations on the beam is observed and the performance of the controller is evaluated for vibration control. Some of the limitations of the Euler-Bernoulli theory such as the neglection of shear and axial displacement are being considered here, thus giving rise to an accurate beam model. Embedded shear sensors and actuators have been considered in this paper instead of the surface mounted sensors and actuators for vibration suppression because of lot of advantages. In controlling the vibration modes, the first three dominant modes of vibration of the system are considered.

Quasi Multi-Pulse Back-to-Back Static Synchronous Compensator Employing Line Frequency Switching 2-Level GTO Inverters

Back-to-back static synchronous compensator (BtBSTATCOM) consists of two back-to-back voltage-source converters (VSC) with a common DC link in a substation. This configuration extends the capabilities of conventional STATCOM that bidirectional active power transfer from one bus to another is possible. In this paper, VSCs are designed in quasi multi-pulse form in which GTOs are triggered only once per cycle in PSCAD/EMTDC. The design details of VSCs as well as gate switching circuits and controllers are fully represented. Regulation modes of BtBSTATCOM are verified and tested on a multi-machine power system through different simulation cases. The results presented in the form of typical time responses show that practical PI controllers are almost robust and stable in case of start-up, set-point change, and line faults.

An Adaptive Model for Blind Image Restoration using Bayesian Approach

Image restoration involves elimination of noise. Filtering techniques were adopted so far to restore images since last five decades. In this paper, we consider the problem of image restoration degraded by a blur function and corrupted by random noise. A method for reducing additive noise in images by explicit analysis of local image statistics is introduced and compared to other noise reduction methods. The proposed method, which makes use of an a priori noise model, has been evaluated on various types of images. Bayesian based algorithms and technique of image processing have been described and substantiated with experimentation using MATLAB.

Characterization and Development of Anthropomorphic Phantoms Liver for Use in Nuclear Medicine

The objective this study was to characterize and develop anthropomorphic liver phantoms in tomography hepatic procedures for quality control and improvement professionals in nuclear medicine. For the conformation of the anthropomorphic phantom was used in plaster and acrylic. We constructed three phantoms representing processes with liver cirrhosis. The phantoms were filled with 99mTc diluted with water to obtain the scintigraphic images. Tomography images were analyzed anterior and posterior phantom representing a body with a greater degree cirrhotic. It was noted that the phantoms allow the acquisition of images similar to real liver with cirrhosis. Simulations of hemangiomas may contribute to continued professional education of nuclear medicine, on the question of image acquisition, allowing of the study parameters such of the matrix, energy window and count statistics.

Haematological Characterization of Reproductive Status at Laying Hens by Age

Physiological activity of the pineal gland with specific responses in the reproductive territory may be interpreted by monitoring the process parameters used in poultry practice in different age batches of laying hens. As biological material were used 105 laying hens, clinically healthy, belonging to ALBO SL- 2000 hybrid, raised on ground, from which blood samples were taken at the age of 12 and 28 weeks. The haematological examinations were concerned to obtain the total number of erythrocytes and leukocytes and the main erythrocyte constant (RBC, PCV, MCV, MCH, MCHC and WBC). The results allow the interpretation of the reproductive status through the dynamics of the presented values.

A New Heuristic Approach for the Stock- Cutting Problems

This paper addresses a stock-cutting problem with rotation of items and without the guillotine cutting constraint. In order to solve the large-scale problem effectively and efficiently, we propose a simple but fast heuristic algorithm. It is shown that this heuristic outperforms the latest published algorithms for large-scale problem instances.

Design of Low Power and High Speed Digital IIR Filter in 45nm with Optimized CSA for Digital Signal Processing Applications

In this paper, a design methodology to implement low-power and high-speed 2nd order recursive digital Infinite Impulse Response (IIR) filter has been proposed. Since IIR filters suffer from a large number of constant multiplications, the proposed method replaces the constant multiplications by using addition/subtraction and shift operations. The proposed new 6T adder cell is used as the Carry-Save Adder (CSA) to implement addition/subtraction operations in the design of recursive section IIR filter to reduce the propagation delay. Furthermore, high-level algorithms designed for the optimization of the number of CSA blocks are used to reduce the complexity of the IIR filter. The DSCH3 tool is used to generate the schematic of the proposed 6T CSA based shift-adds architecture design and it is analyzed by using Microwind CAD tool to synthesize low-complexity and high-speed IIR filters. The proposed design outperforms in terms of power, propagation delay, area and throughput when compared with MUX-12T, MCIT-7T based CSA adder filter design. It is observed from the experimental results that the proposed 6T based design method can find better IIR filter designs in terms of power and delay than those obtained by using efficient general multipliers.

A New Method of Adaptation in Integrated Learning Environment

A new method of adaptation in a partially integrated learning environment that includes electronic textbook (ET) and integrated tutoring system (ITS) is described. The algorithm of adaptation is described in detail. It includes: establishment of Interconnections of operations and concepts; estimate of the concept mastering level (for all concepts); estimate of student-s non-mastering level on the current learning step of information on each page of ET; creation of a rank-order list of links to the e-manual pages containing information that require repeated work.

En-Face Optical Coherence Tomography Combined with Fluorescence in Material Defects Investigations for Ceramic Fixed Partial Dentures

Optical Coherence Tomography (OCT) combined with the Confocal Microscopy, as a noninvasive method, permits the determinations of materials defects in the ceramic layers depth. For this study 256 anterior and posterior metal and integral ceramic fixed partial dentures were used, made with Empress (Ivoclar), Wollceram and CAD/CAM (Wieland) technology. For each investigate area 350 slices were obtain and a 3D reconstruction was perform from each stuck. The Optical Coherent Tomography, as a noninvasive method, can be used as a control technique in integral ceramic technology, before placing those fixed partial dentures in the oral cavity. The purpose of this study is to evaluate the capability of En face Optical Coherence Tomography (OCT) combined with a fluorescent method in detection and analysis of possible material defects in metalceramic and integral ceramic fixed partial dentures. As a conclusion, it is important to have a non invasive method to investigate fixed partial prostheses before their insertion in the oral cavity in order to satisfy the high stress requirements and the esthetic function.

Investigation of Layer Thickness and Surface Roughness on Aerodynamic Coefficients of Wind Tunnel RP Models

Traditional wind tunnel models are meticulously machined from metal in a process that can take several months. While very precise, the manufacturing process is too slow to assess a new design's feasibility quickly. Rapid prototyping technology makes this concurrent study of air vehicle concepts via computer simulation and in the wind tunnel possible. This paper described the Affects layer thickness models product with rapid prototyping on Aerodynamic Coefficients for Constructed wind tunnel testing models. Three models were evaluated. The first model was a 0.05mm layer thickness and Horizontal plane 0.1μm (Ra) second model was a 0.125mm layer thickness and Horizontal plane 0.22μm (Ra) third model was a 0.15mm layer thickness and Horizontal plane 4.6μm (Ra). These models were fabricated from somos 18420 by a stereolithography (SLA). A wing-body-tail configuration was chosen for the actual study. Testing covered the Mach range of Mach 0.3 to Mach 0.9 at an angle-of-attack range of -2° to +12° at zero sideslip. Coefficients of normal force, axial force, pitching moment, and lift over drag are shown at each of these Mach numbers. Results from this study show that layer thickness does have an effect on the aerodynamic characteristics in general; the data differ between the three models by fewer than 5%. The layer thickness does have more effect on the aerodynamic characteristics when Mach number is decreased and had most effect on the aerodynamic characteristics of axial force and its derivative coefficients.

A Neural Network Approach in Predicting the Blood Glucose Level for Diabetic Patients

Diabetes Mellitus is a chronic metabolic disorder, where the improper management of the blood glucose level in the diabetic patients will lead to the risk of heart attack, kidney disease and renal failure. This paper attempts to enhance the diagnostic accuracy of the advancing blood glucose levels of the diabetic patients, by combining principal component analysis and wavelet neural network. The proposed system makes separate blood glucose prediction in the morning, afternoon, evening and night intervals, using dataset from one patient covering a period of 77 days. Comparisons of the diagnostic accuracy with other neural network models, which use the same dataset are made. The comparison results showed overall improved accuracy, which indicates the effectiveness of this proposed system.

Multi-Criteria Decision Analysis in Planning of Asbestos-Containing Waste Management

Environmental decision making, particularly about hazardous waste management, is inherently exposed to a high potential conflict, principally because of the trade-off between sociopolitical, environmental, health and economic factors. The need to plan complex contexts has led to an increasing request for decision analytic techniques as support for the decision process. In this work, alternative systems of asbestos-containing waste management (ACW) in Puglia (Southern Italy) were explored by a multi-criteria decision analysis. In particular, through Analytic Hierarchy Process five alternatives management have been compared and ranked according to their performance and efficiency, taking into account environmental, health and socio-economic aspects. A separated valuation has been performed for different temporal scale. For short period results showed a narrow deviation between the disposal alternatives “mono-material landfill in public quarry" and “dedicate cells in existing landfill", with the best performance of the first one. While for long period “treatment plant to eliminate hazard from asbestos-containing waste" was prevalent, although high energy demand required to achieve the change of crystalline structure. A comparison with results from a participative approach in valuation process might be considered as future development of method application to ACW management.