Topical Delivery of Thymidine Dinucleotide to Induce p53 Generation in the Skin by Elastic Liposome

Transcription factor p53 has a powerful tumor suppressing function that is associated with many cancers. However, p53 of the molecular weight was higher make the limitation across to skin or cell membrane. Thymidine dinucleotide (pTT), an oligonucleotide, can activate the p53 transcription factor. pTT is a hydrophilic and negative charge oligonucleotide, which delivery in to cell membrane need an appropriate carrier. The aim of this study was to improve the bioavailability of the nucleotide fragment, thymidine dinucleotide (pTT), using elasic liposome carriers to deliver the drug into the skin. The study demonstrate that dioleoylphosphocholine (DOPC) incorporated with sodium cholate at molar ratio 1:1 can archived the particle size about 220 nm. This elastic liposome could penetration through skin from stratum corneum to whole epidermis by confocal laser scanning microscopy (CLSM). Moreover, we observed the the slight increase in generation of p53 by western blot.

Influence of Radio Frequency Identification Technology in Logistic, Inventory Control and Supply Chain Optimization

The main aim of Supply Chain Management (SCM) is to produce, distribute, logistics and deliver goods and equipment in right location, right time, right amount to satisfy costumers, with minimum time and cost waste. So implementing techniques that reduce project time and cost, and improve productivity and performance is very important. Emerging technologies such as the Radio Frequency Identification (RFID) are now making it possible to automate supply chains in a real time manner and making them more efficient than the simple supply chain of the past for tracing and monitoring goods and products and capturing data on movements of goods and other events. This paper considers concepts, components and RFID technology characteristics by concentration of warehouse and inventories management. Additionally, utilization of RFID in the role of improving information management in supply chain is discussed. Finally, the facts of installation and this technology-s results in direction with warehouse and inventory management and business development will be presented.

Vibration Induced Fatigue Assessment in Vehicle Development Process

Improvement in CAE methods has an important role for shortening of the vehicle product development time. It is provided that validation of the design and improvements in terms of durability can be done without hardware prototype production. In recent years, several different methods have been developed in order to investigate fatigue damage of the vehicle. The intended goal among these methods is prediction of fatigue damage in a short time with reduced costs. This study developed a new fatigue damage prediction method in the automotive sector using power spectrum densities of accelerations. This study also confirmed that the weak region in vehicle can be easily detected with the method developed in this study which results were compared with conventional method.

Web Application to Profiling Scientific Institutions through Citation Mining

Recently the use of data mining to scientific bibliographic data bases has been implemented to analyze the pathways of the knowledge or the core scientific relevances of a laureated novel or a country. This specific case of data mining has been named citation mining, and it is the integration of citation bibliometrics and text mining. In this paper we present an improved WEB implementation of statistical physics algorithms to perform the text mining component of citation mining. In particular we use an entropic like distance between the compression of text as an indicator of the similarity between them. Finally, we have included the recently proposed index h to characterize the scientific production. We have used this web implementation to identify users, applications and impact of the Mexican scientific institutions located in the State of Morelos.

A Hybrid Recommender System based on Collaborative Filtering and Cloud Model

User-based Collaborative filtering (CF), one of the most prevailing and efficient recommendation techniques, provides personalized recommendations to users based on the opinions of other users. Although the CF technique has been successfully applied in various applications, it suffers from serious sparsity problems. The cloud-model approach addresses the sparsity problems by constructing the user-s global preference represented by a cloud eigenvector. The user-based CF approach works well with dense datasets while the cloud-model CF approach has a greater performance when the dataset is sparse. In this paper, we present a hybrid approach that integrates the predictions from both the user-based CF and the cloud-model CF approaches. The experimental results show that the proposed hybrid approach can ameliorate the sparsity problem and provide an improved prediction quality.

A Serializability Condition for Multi-step Transactions Accessing Ordered Data

In mobile environments, unspecified numbers of transactions arrive in continuous streams. To prove correctness of their concurrent execution a method of modelling an infinite number of transactions is needed. Standard database techniques model fixed finite schedules of transactions. Lately, techniques based on temporal logic have been proposed as suitable for modelling infinite schedules. The drawback of these techniques is that proving the basic serializability correctness condition is impractical, as encoding (the absence of) conflict cyclicity within large sets of transactions results in prohibitively large temporal logic formulae. In this paper, we show that, under certain common assumptions on the graph structure of data items accessed by the transactions, conflict cyclicity need only be checked within all possible pairs of transactions. This results in formulae of considerably reduced size in any temporal-logic-based approach to proving serializability, and scales to arbitrary numbers of transactions.

Revisiting the Concept of Risk Analysis within the Context of Geospatial Database Design: A Collaborative Framework

The aim of this research is to design a collaborative framework that integrates risk analysis activities into the geospatial database design (GDD) process. Risk analysis is rarely undertaken iteratively as part of the present GDD methods in conformance to requirement engineering (RE) guidelines and risk standards. Accordingly, when risk analysis is performed during the GDD, some foreseeable risks may be overlooked and not reach the output specifications especially when user intentions are not systematically collected. This may lead to ill-defined requirements and ultimately in higher risks of geospatial data misuse. The adopted approach consists of 1) reviewing risk analysis process within the scope of RE and GDD, 2) analyzing the challenges of risk analysis within the context of GDD, and 3) presenting the components of a risk-based collaborative framework that improves the collection of the intended/forbidden usages of the data and helps geo-IT experts to discover implicit requirements and risks.

Satellite Data Classification Accuracy Assessment Based from Reference Dataset

In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

A Block World Problem Based Sudoku Solver

There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Supercompression for Full-HD and 4k-3D (8k)Digital TV Systems

In this work, we developed the concept of supercompression, i.e., compression above the compression standard used. In this context, both compression rates are multiplied. In fact, supercompression is based on super-resolution. That is to say, supercompression is a data compression technique that superpose spatial image compression on top of bit-per-pixel compression to achieve very high compression ratios. If the compression ratio is very high, then we use a convolutive mask inside decoder that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. Specifically, the mentio-ned mask is coded inside texture memory of a GPGPU.

Reversible, Embedded and Highly Scalable Image Compression System

In this work a new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuous-tone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different importance levels from which the bit stream will be generated. The subcomponents of each importance level are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several improvement levels.

Quasilinearization–Barycentric Approach for Numerical Investigation of the Boundary Value Fin Problem

In this paper we improve the quasilinearization method by barycentric Lagrange interpolation because of its numerical stability and computation speed to achieve a stable semi analytical solution. Then we applied the improved method for solving the Fin problem which is a nonlinear equation that occurs in the heat transferring. In the quasilinearization approach the nonlinear differential equation is treated by approximating the nonlinear terms by a sequence of linear expressions. The modified QLM is iterative but not perturbative and gives stable semi analytical solutions to nonlinear problems without depending on the existence of a smallness parameter. Comparison with some numerical solutions shows that the present solution is applicable.

A 1.2-ns16×16-Bit Binary Multiplier Using High Speed Compressors

For higher order multiplications, a huge number of adders or compressors are to be used to perform the partial product addition. We have reduced the number of adders by introducing special kind of adders that are capable to add five/six/seven bits per decade. These adders are called compressors. Binary counter property has been merged with the compressor property to develop high order compressors. Uses of these compressors permit the reduction of the vertical critical paths. A 16×16 bit multiplier has been developed using these compressors. These compressors make the multipliers faster as compared to the conventional design that have been used 4-2 compressors and 3-2 compressors.

Preemptive Possibilistic Linear Programming:Application to Aggregate Production Planning

This research proposes a Preemptive Possibilistic Linear Programming (PPLP) approach for solving multiobjective Aggregate Production Planning (APP) problem with interval demand and imprecise unit price and related operating costs. The proposed approach attempts to maximize profit and minimize changes of workforce. It transforms the total profit objective that has imprecise information to three crisp objective functions, which are maximizing the most possible value of profit, minimizing the risk of obtaining the lower profit and maximizing the opportunity of obtaining the higher profit. The change of workforce level objective is also converted. Then, the problem is solved according to objective priorities. It is easier than simultaneously solve the multiobjective problem as performed in existing approach. Possible range of interval demand is also used to increase flexibility of obtaining the better production plan. A practical application of an electronic company is illustrated to show the effectiveness of the proposed model.

Assessing the Effect of Thermodynamic, Hydrodynamic and Geometric of an Air Cooled Condenser on COP of Vapor Compression Cycle

In this paper, the effects of thermodynamic, hydrodynamic and geometric of an air cooled condenser on COP of vapor compression cycle are investigated for a fixed condenser facing surface area. The system is utilized with a scroll compressor, modeled based on thermodynamic and heat transfer equations employing Matlab software. The working refrigerant is R134a whose thermodynamic properties are called from Engineering Equation Software. This simulation shows that vapor compression cycle can be designed by different configurations and COPs, economical and optimum working condition can be obtained via considering these parameters.

Dimensioning of Subsynchronous Cascade for Speed Regulation of Two-Motors 6kv Conveyer Drives

One way for optimum loading of overdimensioning conveyers is speed (capacity) decrement, with attention for production capabilities and demands. At conveyers which drives with three phase slip-ring induction motor, technically reasonable solution for conveyer (driving motors) speed regulation is using constant torque subsynchronous cascade with static semiconductor converter and transformer for energy reversion to the power network. In the paper is described mathematical model for parameter calculation of two-motors 6 kV subsynchronous cascade. It is also demonstrated that applying of this cascade gave several good properties, foremost in electrical energy saving, also in improving of other energy indexes, and finally that results in cost reduction of complete electrical motor drive.

Density, Strength, Thermal Conductivity and Leachate Characteristics of Light-Weight Fired Clay Bricks Incorporating Cigarette Butts

Several trillion cigarettes produced worldwide annually lead to many thousands of kilograms of toxic waste. Cigarette butts (CBs) accumulate in the environment due to the poor biodegradability of the cellulose acetate filters. This paper presents some of the results from a continuing study on recycling CBs into fired clay bricks. Physico-mechanical properties of fired clay bricks manufactured with different percentages of CBs are reported and discussed. The results show that the density of fired bricks was reduced by up to 30 %, depending on the percentage of CBs incorporated into the raw materials. Similarly, the compressive strength of bricks tested decreased according to the percentage of CBs included in the mix. The thermal conductivity performance of bricks was improved by 51 and 58 % for 5 and 10 % CBs content respectively. Leaching tests were carried out to investigate the levels of possible leachates of heavy metals from the manufactured clay-CB bricks. The results revealed trace amounts of heavy metals.

Nonlinear Modeling and Analysis of AAC infilled Sandwich Panels for out of Plane Loads

Sandwich panels are widely used in the construction industry for their ease of assembly, light weight and efficient thermal performance. They are composed of two RC thin outer layers separated by an insulating inner layer. In this research the inner insulating layer is made of lightweight Autoclaved Aerated Concrete (AAC) blocks which has good thermal insulation properties and yet possess reasonable mechanical strength. The shear strength of the AAC infill is relied upon to replace the traditionally used insulating foam and to provide the shear capacity of the panel. A comprehensive experimental program was conducted on full scale sandwich panels subjected to bending. In this paper, detailed numerical modeling of the tested sandwich panels is reported. Nonlinear 3-D finite element modeling of the composite action of the sandwich panel is developed using ANSYS. Solid elements with different crashing and cracking capabilities and different constitutive laws were selected for the concrete and the AAC. Contact interface elements are used in this research to adequately model the shear transfer at the interface between the different layers. The numerical results showed good correlation with the experimental ones indicating the adequacy of the model in estimating the loading capacity of panels.

The Evaluation and Application of FMEA in Sepahan Oil Co

Failure modes and effects analysis (FMEA) is an effective technique for preventing potential problems and actions needed to error cause removal. On the other hand, the oil producing companies paly a critical role in the oil industry of Iran as a developing country out of which, Sepahan Oil Co. has a considerable contribution. The aim of this research is to show how FMEA could be applied and improve the quality of products at Sepahan Oil Co. For this purpose, the four liter production line of the company has been selected for investigation. The findings imply that the application of FMEA has reduced the scraps from 50000 ppm to 5000 ppm and has resulted in a 0.92 percent decrease of the oil waste.

Object Detection based Weighted-Center Surround Difference

Intelligent traffic surveillance technology is an issue in the field of traffic data analysis. Therefore, we need the technology to detect moving objects in real-time while there are variations in background and natural light. In this paper, we proposed a Weighted-Center Surround Difference method for object detection in outdoor environments. The proposed system detects objects using the saliency map that is obtained by analyzing the weight of each layers of Gaussian pyramid. In order to validate the effectiveness of our system, we implemented the proposed method using a digital signal processor, TMS320DM6437. Experimental results show that blurred noisy around objects was effectively eliminated and the object detection accuracy is improved.