Supercritical Fluid Extraction of Lutein Esters from Marigold Flowers and their Hydrolysis by Improved Saponification and Enzyme Biocatalysis

Lutein is a dietary oxycarotenoid which is found to reduce the risks of Age-related Macular Degeneration (AMD). Supercritical fluid extraction of lutein esters from marigold petals was carried out and was found to be much effective than conventional solvent extraction. The saponification of pre-concentrated lutein esters to produce free lutein was studied which showed a composition of about 88% total carotenoids (UV-VIS spectrophotometry) and 90.7% lutein (HPLC). The lipase catalyzed hydrolysis of lutein esters in conventional medium was investigated. The optimal temperature, pH, enzyme concentration and water activity were found to be 50°C, 7, 15% and 0.33 respectively and the activity loss of lipase was about 25% after 8 times re-use in at 50°C for 12 days. However, the lipase catalyzed hydrolysis of lutein esters in conventional media resulted in poor conversions (16.4%).

Turkic - Indian Lexical Parallels in the Framework of the Nostratic Language's Macrofamily

From ancient times Turkic languages have been in contact with numerous representatives of different language families. The article discusses the Turkic - Indian language contact and were shown promise and necessity of this trend for the Turkic linguistics, were given Turkic - Indian lexical parallels in the framework of the nostratic language's macro family. The research work has done on the base of lexical parallels (LP) -of Turkic (which belong to the Altaic family of languages) and Indian (including Dravidian and Indo-Aryan languages).

Effect of Impact Location upon Sub-Impacts between Beam and Block

The present investigation is concerned with sub-impacts taken placed when a rigid hemispherical-head block transversely impacts against a beam at different locations. Dynamic substructure technique for elastic-plastic impact is applied to solve numerically this problem. The time history of impact force and energy exchange between block and beam are obtained. The process of sub-impacts is analyzed from the energy exchange point of view. The results verify the influences of the impact location on impact duration, the first sub-impact and energy exchange between the beam and the block.

Protecting the Privacy and Trust of VIP Users on Social Network Sites

There is a real threat on the VIPs personal pages on the Social Network Sites (SNS). The real threats to these pages is violation of privacy and theft of identity through creating fake pages that exploit their names and pictures to attract the victims and spread of lies. In this paper, we propose a new secure architecture that improves the trusting and finds an effective solution to reduce fake pages and possibility of recognizing VIP pages on SNS. The proposed architecture works as a third party that is added to Facebook to provide the trust service to personal pages for VIPs. Through this mechanism, it works to ensure the real identity of the applicant through the electronic authentication of personal information by storing this information within content of their website. As a result, the significance of the proposed architecture is that it secures and provides trust to the VIPs personal pages. Furthermore, it can help to discover fake page, protect the privacy, reduce crimes of personality-theft, and increase the sense of trust and satisfaction by friends and admirers in interacting with SNS.

Medical Image Segmentation Using Deformable Model and Local Fitting Binary: Thoracic Aorta

This paper presents an application of level sets for the segmentation of abdominal and thoracic aortic aneurysms in CTA datasets. An important challenge in reliably detecting aortic is the need to overcome problems associated with intensity inhomogeneities. Level sets are part of an important class of methods that utilize partial differential equations (PDEs) and have been extensively applied in image segmentation. A kernel function in the level set formulation aids the suppression of noise in the extracted regions of interest and then guides the motion of the evolving contour for the detection of weak boundaries. The speed of curve evolution has been significantly improved with a resulting decrease in segmentation time compared with previous implementations of level sets, and are shown to be more effective than other approaches in coping with intensity inhomogeneities. We have applied the Courant Friedrichs Levy (CFL) condition as stability criterion for our algorithm.

Unequal Error Protection of Facial Features for Personal ID Images Coding

This paper presents an approach for an unequal error protection of facial features of personal ID images coding. We consider unequal error protection (UEP) strategies for the efficient progressive transmission of embedded image codes over noisy channels. This new method is based on the progressive image compression embedded zerotree wavelet (EZW) algorithm and UEP technique with defined region of interest (ROI). In this case is ROI equal facial features within personal ID image. ROI technique is important in applications with different parts of importance. In ROI coding, a chosen ROI is encoded with higher quality than the background (BG). Unequal error protection of image is provided by different coding techniques and encoding LL band separately. In our proposed method, image is divided into two parts (ROI, BG) that consist of more important bytes (MIB) and less important bytes (LIB). The proposed unequal error protection of image transmission has shown to be more appropriate to low bit rate applications, producing better quality output for ROI of the compresses image. The experimental results verify effectiveness of the design. The results of our method demonstrate the comparison of the UEP of image transmission with defined ROI with facial features and the equal error protection (EEP) over additive white gaussian noise (AWGN) channel.

Network Intrusion Detection Design Using Feature Selection of Soft Computing Paradigms

The network traffic data provided for the design of intrusion detection always are large with ineffective information and enclose limited and ambiguous information about users- activities. We study the problems and propose a two phases approach in our intrusion detection design. In the first phase, we develop a correlation-based feature selection algorithm to remove the worthless information from the original high dimensional database. Next, we design an intrusion detection method to solve the problems of uncertainty caused by limited and ambiguous information. In the experiments, we choose six UCI databases and DARPA KDD99 intrusion detection data set as our evaluation tools. Empirical studies indicate that our feature selection algorithm is capable of reducing the size of data set. Our intrusion detection method achieves a better performance than those of participating intrusion detectors.

Admission Control Approaches in the IMS Presence Service

In this research, we propose a weighted class based queuing (WCBQ) mechanism to provide class differentiation and to reduce the load for the IMS (IP Multimedia Subsystem) presence server (PS). The tasks of admission controller for the PS are demonstrated. Analysis and simulation models are developed to quantify the performance of WCBQ scheme. An optimized dropping time frame has been developed based on which some of the preexisting messages are dropped from the PS-buffer. Cost functions are developed and simulation comparison has been performed with FCFS (First Come First Served) scheme. The results show that the PS benefits significantly from the proposed queuing and dropping algorithm (WCBQ) during heavy traffic.

Wine Grape Residues Gasification in Supercritical Water

In this study, production possibilities of hydrogen and/or methane via SCWG from black grape residues have been investigated. For this aim, grape residues which remain as a byproduct of the wine making process have been used. Since utilization from grape residues is limited due to the high moisture content, supercritical water gasification is the most convenient method. The effect of the gasification temperature and type of catalyst on supercritical water gasification have been investigated. Gasification experiments were performed in a batch autoclave at four different temperatures 300, 400, 500 and 600°C. K2CO3 and Trona (NaHCO3.Na2CO3·2H2O) were used as catalyst. Real biomass types of black grape residues have been successfully gasified and the product gas (hydrogen, methane, carbon dioxide, carbon monoxide and a small amount of ethane and ethylene) were identified by using gas chromatography. A TOC analyzer was used to determine total organic carbon (TOC) content of aqueous phase. The amounts of carboxylic acids, aldehydes, ketones, furfurals and phenols present in the aqueous solutions were analyzed by high performance liquid chromatography. When the temperature increased from 300°C to 600°C, mol% of H2 in gas products increased. The presence of catalysts improves the hydrogen yield. Trona showed gasification activity to be similar to that of K2CO3. It may be concluded that the use of Trona instead of commercially produced catalysts, can be preferably used in the gasification of biomass in supercritical water.

3D Digitalization of the Human Body for Use in Orthotics and Prosthetics

The motivation of this work was to find a suitable 3D scanner for human body parts digitalization in the field of prosthetics and orthotics. The main project objective is to compare the three hand-held portable scanners (two optical and one laser) and two optical tripod scanners. The comparison was made with respect of scanning detail, simplicity of operation and ability to scan directly on the human body. Testing was carried out on a plaster cast of the upper limb and directly on a few volunteers. The objective monitored parameters were time of digitizing and post-processing of 3D data and resulting visual data quality. Subjectively, it was considered level of usage and handling of the scanner. The new tripod was developed to improve the face scanning conditions. The results provide an overview of the suitability of different types of scanners.

Time and Frequency Domain Analysis of Heart Rate Variability and their Correlations in Diabetes Mellitus

Diabetes mellitus (DM) is frequently characterized by autonomic nervous dysfunction. Analysis of heart rate variability (HRV) has become a popular noninvasive tool for assessing the activities of autonomic nervous system (ANS). In this paper, changes in ANS activity are quantified by means of frequency and time domain analysis of R-R interval variability. Electrocardiograms (ECG) of 16 patients suffering from DM and of 16 healthy volunteers were recorded. Frequency domain analysis of extracted normal to normal interval (NN interval) data indicates significant difference in very low frequency (VLF) power, low frequency (LF) power and high frequency (HF) power, between the DM patients and control group. Time domain measures, standard deviation of NN interval (SDNN), root mean square of successive NN interval differences (RMSSD), successive NN intervals differing more than 50 ms (NN50 Count), percentage value of NN50 count (pNN50), HRV triangular index and triangular interpolation of NN intervals (TINN) also show significant difference between the DM patients and control group.

Quality Evaluation of Cookies Produced from Blends of Sweet Potato and Fermented Soybean Flour

The study was conducted to evaluate the quality characteristics of cookies produced from sweet potato-fermented soybean flour. Cookies were subjected to proximate and sensory analysis to determine the acceptability of the product. Protein, fat and ash increased as the proportion of soybean flour increased, ranging from 13.8-21.7, 1.22-5.25 and 2.20-2.57 respectively. The crude fibre content was within the range of 3.08-4.83%. The moisture content of the cookies decreased with increase in soybean flour from 3.42- 2.13%. Cookies produced from whole sweet potato flour had the highest moisture content of 3.42% while 30% substitution had the lowest moisture content 2.13%. A nine point hedonic scale was used to evaluate the organoleptic characteristics of the cookies. The sensory analysis indicated that there was no significant difference between the cookies produced even when compared to the control 100% sweet potato cookies. The overall acceptance of the cookies was ranked to 20% soybean flour substitute.

Fast and Efficient On-Chip Interconnection Modeling for High Speed VLSI Systems

Timing driven physical design, synthesis, and optimization tools need efficient closed-form delay models for estimating the delay associated with each net in an integrated circuit (IC) design. The total number of nets in a modern IC design has increased dramatically and exceeded millions. Therefore efficient modeling of interconnection is needed for high speed IC-s. This paper presents closed–form expressions for RC and RLC interconnection trees in current mode signaling, which can be implemented in VLSI design tool. These analytical model expressions can be used for accurate calculation of delay after the design clock tree has been laid out and the design is fully routed. Evaluation of these analytical models is several orders of magnitude faster than simulation using SPICE.

Applying Autonomic Computing Concepts to Parallel Computing using Intelligent Agents

The work reported in this paper is motivated by the fact that there is a need to apply autonomic computing concepts to parallel computing systems. Advancing on prior work based on intelligent cores [36], a swarm-array computing approach, this paper focuses on 'Intelligent agents' another swarm-array computing approach in which the task to be executed on a parallel computing core is considered as a swarm of autonomous agents. A task is carried to a computing core by carrier agents and is seamlessly transferred between cores in the event of a predicted failure, thereby achieving self-ware objectives of autonomic computing. The feasibility of the proposed swarm-array computing approach is validated on a multi-agent simulator.

Characteristics of Intronic and Intergenic Human miRNAs and Features of their Interaction with mRNA

Regulatory relationships of 686 intronic miRNA and 784 intergenic miRNAs with mRNAs of 51 intronic miRNA coding genes were established. Interaction features of studied miRNAs with 5'UTR, CDS and 3'UTR of mRNA of each gene were revealed. Functional regions of mRNA were shown to be significantly heterogenous according to the number of binding sites of miRNA and to the location density of these sites.

Selective Sulfidation of Copper, Zinc and Nickelin Plating Wastewater using Calcium Sulfide

The present work is concerned with sulfidation of Cu, Zn and Ni containing plating wastewater with CaS. The sulfidation experiments were carried out at a room temperature by adding solid CaS to simulated metal solution containing either single-metal of Ni, Zn and Cu, or Ni-Zn-Cu mixture. At first, the experiments were conducted without pH adjustment and it was found that the complete sulfidation of Zn and Ni was achieved at an equimolar ratio of CaS to a particular metal. However, in the case of Cu, a complete copper sulfidation was achieved at CaS to Cu molar ratio of about 2. In the case of the selective sulfidation, a simulated plating solution containing Cu, Zn and Ni at the concentration of 100 mg/dm3 was treated with CaS under various pH conditions. As a result, selective precipitation of metal sulfides was achieved by a sulfidation treatment at different pH values. Further, the precipitation agents of NaOH, Na2S and CaS were compared in terms of the average specific filtration resistance and compressibility coefficients of metal sulfide slurry. Consequently, based on the lowest filtration parameters of the produced metal sulfides, it was concluded that CaS was the most effective precipitation agent for separation and recovery of Cu, Zn and Ni.

Oxidation of Carbon Monoxide in a Monolithic Reactor

Solution for the complete removal of carbon monoxide from the exhaust gases still poses a challenge to the researchers and this problem is still under development. Modeling for reduction of carbon monoxide is carried out using heterogeneous reaction using low cost non-noble metal based catalysts for the purpose of controlling emissions released to the atmosphere. A simple one-dimensional model was developed for the monolith using hopcalite catalyst. The converter is assumed to be an adiabatic monolith operating under warm-up conditions. The effect of inlet gas temperatures and catalyst loading on carbon monoxide reduction during cold start period in the converter is analysed.

Extended Dynamic Source Routing Protocol for the Non Co-Operating Nodes in Mobile Adhoc Networks

In this paper, a new approach based on the extent of friendship between the nodes is proposed which makes the nodes to co-operate in an ad hoc environment. The extended DSR protocol is tested under different scenarios by varying the number of malicious nodes and node moving speed. It is also tested varying the number of nodes in simulation used. The result indicates the achieved throughput by extended DSR is greater than the standard DSR and indicates the percentage of malicious drops over total drops are less in the case of extended DSR than the standard DSR.

Multi-Context Recurrent Neural Network for Time Series Applications

this paper presents a multi-context recurrent network for time series analysis. While simple recurrent network (SRN) are very popular among recurrent neural networks, they still have some shortcomings in terms of learning speed and accuracy that need to be addressed. To solve these problems, we proposed a multi-context recurrent network (MCRN) with three different learning algorithms. The performance of this network is evaluated on some real-world application such as handwriting recognition and energy load forecasting. We study the performance of this network and we compared it to a very well established SRN. The experimental results showed that MCRN is very efficient and very well suited to time series analysis and its applications.

Study of Characteristics of Multi-Layer Piezoelectric Transformers by using 3-D Finite Element Method

Piezoelectric transformers are electronic devices made from piezoelectric materials. The piezoelectric transformers as the name implied are used for changing voltage signals from one level to another. Electrical energy carried with signals is transferred by means of mechanical vibration. Characterizing in both electrical and mechanical properties leads to extensively use and efficiency enhancement of piezoelectric transformers in various applications. In this paper, study and analysis of electrical and mechanical properties of multi-layer piezoelectric transformers in forms of potential and displacement distribution throughout the volume, respectively. This paper proposes a set of quasi-static mathematical model of electromechanical coupling for piezoelectric transformer by using a set of partial differential equations. Computer-based simulation utilizing the three-dimensional finite element method (3-D FEM) is exploited as a tool for visualizing potentials and displacements distribution within the multi-layer piezoelectric transformer. This simulation was conducted by varying a number of layers. In this paper 3, 5 and 7 of the circular ring type were used. The computer simulation based on the use of the FEM has been developed in MATLAB programming environment.