Tumor Necrosis Factor-α Regulates Heme Oxygenase-1 Expression in Endothelial Cells via the Phosphorylation of JNK/p38

Heme oxygenase-1 (HO-1), an enzyme degrading heme to carbon monoxide, iron, and biliverdin, has been recognized as playing a crucial role in cellular defense against stressful conditions, not only related to heme release. In the present study, the effects of TNF-a on the expression of heme oxygenase-1 (HO-1) in human aortic endothelial cells (HAECs) as well as the related mechanisms were investigated. 10 ng/mL TNF-α treatment significantly increased HO-1 expression after 6h, then a further increase at 12h and declined at 24h. Treatment with 2 ng/mL of TNF-a after 12 h resulted in a significant increase in HO-1 expression, which peaked at 10 ng/mL, then declined at 20 ng/mL. TNF-α induced HO-1 expression and then HO-1 expression reduced  vascular cell adhesion molecule-1 (VCAM-1) expression. Phosphorylation studies of ERK1/2, JNK, and p38, three subgroups of mitogen-activated protein kinases (MAPKs) demonstrated TNF-α-induced ERK1/2, JNK, and p38 phosphorylation. The increase in HO-1 expression in response to TNF-α treatment was affected by pretreatment with SP600125 (a JNK inhibitor) and SB203580 (a p38 inhibitor), not with PD98059 (an ERK1/2 inhibitor). The expression of HO-1 was stronger in aortas of TNF-α-treated apo-E deficient mice when compared with control mice. These results suggest that low dose of TNF-α treatment notably induced HO-1 expression was mediated through JNK/p38 phosphorylation and may have a protective potential in cardiovascular diseases and inflammatory response through the regulation of HO-1 expression.

Early-Warning Lights Classification Management System for Industrial Parks in Taiwan

This paper presents the early-warning lights classification management system for industrial parks promoted by the Taiwan Environmental Protection Administration (EPA) since 2011, including the definition of each early-warning light, objectives, action program and accomplishments. All of the 151 industrial parks in Taiwan were classified into four early-warning lights, including red, orange, yellow and green, for carrying out respective pollution management according to the monitoring data of soil and groundwater quality, regulatory compliance, and regulatory listing of control site or remediation site. The Taiwan EPA set up a priority list for high potential polluted industrial parks and investigated their soil and groundwater qualities based on the results of the light classification and pollution potential assessment. In 2011-2013, there were 44 industrial parks selected and carried out different investigation, such as the early warning groundwater well networks establishment and pollution investigation/verification for the red and orange-light industrial parks and the environmental background survey for the yellow-light industrial parks. Among them, 22 industrial parks were newly or continuously confirmed that the concentrations of pollutants exceeded those in soil or groundwater pollution control standards. Thus, the further investigation, groundwater use restriction, listing of pollution control site or remediation site, and pollutant isolation measures were implemented by the local environmental protection and industry competent authorities; the early warning lights of those industrial parks were proposed to adjust up to orange or red-light. Up to the present, the preliminary positive effect of the soil and groundwater quality management system for industrial parks has been noticed in several aspects, such as environmental background information collection, early warning of pollution risk, pollution investigation and control, information integration and application, and inter-agency collaboration. Finally, the work and goal of self-initiated quality management of industrial parks will be carried out on the basis of the inter-agency collaboration by the classified lights system of early warning and management as well as the regular announcement of the status of each industrial park.

Infrared Camera-Based Hand Gesture Space Touch System Implementation of Smart Device Environment

This paper proposes a method to recognize the tip of a finger and space touch hand gesture using an infrared camera in a smart device environment. The proposed method estimates the tip of a finger with a curvature-based ellipse fitting algorithm, and verifies that the estimated object is indeed a finger with an ellipse fitting rectangular area. The feature extracted from the verified finger tip is used to implement the movement of a mouse and clicking gesture. The proposed algorithm was implemented with an actual smart device to test the proposed method. Empirical parameters were obtained from the keypad software and an image analysis tool for the performance optimization, and a comparative analysis with conventional research showed improved performance with the proposed method.

Clustering of Variables Based On a Probabilistic Approach Defined on the Hypersphere

We consider n individuals described by p standardized variables, represented by points of the surface of the unit hypersphere Sn-1. For a previous choice of n individuals we suppose that the set of observables variables comes from a mixture of bipolar Watson distribution defined on the hypersphere. EM and Dynamic Clusters algorithms are used for identification of such mixture. We obtain estimates of parameters for each Watson component and then a partition of the set of variables into homogeneous groups of variables. Additionally we will present a factor analysis model where unobservable factors are just the maximum likelihood estimators of Watson directional parameters, exactly the first principal component of data matrix associated to each group previously identified. Such alternative model it will yield us to directly interpretable solutions (simple structure), avoiding factors rotations.

Anthropometric Correlates of Balance Performance in Non-Institutionalized Elderly

Purpose: The fear of falling is a major concern among the elderly. Sixty-five percent of individuals older than 60 years of age experience loss of balance often on a daily basis. Therefore, balance assessment in the elderly deserves special attention due to its importance in functional mobility and safety. This study aimed at assessing balance performance and comparing some anthropometric parameters among a Nigerian non-institutionalized elderly population. Methods: Sixty one elderly subjects (31 males and 30 females) participated in this study. Their ages ranged between 62 and 84 years. Ability to maintain balance was assessed using Functional Reach Test (FRT) and Sharpened Romberg Test (SRT). Anthropometric data including age, weight, height, arm length, leg length, bi-acromial breadth, foot length and trunk length were also collected. Analysis was done using Pearson’s Product Moment Correlation Coefficient and Independent T-test, while level of significance was set as p

Impact of Liquidity Crunch on Interbank Network

Most empirical studies have analyzed how liquidity risks faced by individual institutions turn into systemic risk. Recent banking crisis has highlighted the importance of grasping and controlling the systemic risk, and the acceptance by Central Banks to ease their monetary policies for saving default or illiquid banks. This last point shows that banks would pay less attention to liquidity risk which, in turn, can become a new important channel of loss. The financial regulation focuses on the most important and “systemic” banks in the global network. However, to quantify the expected loss associated with liquidity risk, it is worth to analyze sensitivity to this channel for the various elements of the global bank network. A small bank is not considered as potentially systemic; however the interaction of small banks all together can become a systemic element. This paper analyzes the impact of medium and small banks interaction on a set of banks which is considered as the core of the network. The proposed method uses the structure of agent-based model in a two-class environment. In first class, the data from actual balance sheets of 22 large and systemic banks (such as BNP Paribas or Barclays) are collected. In second one, to model a network as closely as possible to actual interbank market, 578 fictitious banks smaller than the ones belonging to first class have been split into two groups of small and medium ones. All banks are active on the European interbank network and have deposit and market activity. A simulation of 12 three month periods representing a midterm time interval three years is projected. In each period, there is a set of behavioral descriptions: repayment of matured loans, liquidation of deposits, income from securities, collection of new deposits, new demands of credit, and securities sale. The last two actions are part of refunding process developed in this paper. To strengthen reliability of proposed model, random parameters dynamics are managed with stochastic equations as rates the variations of which are generated by Vasicek model. The Central Bank is considered as the lender of last resort which allows banks to borrow at REPO rate and some ejection conditions of banks from the system are introduced. Liquidity crunch due to exogenous crisis is simulated in the first class and the loss impact on other bank classes is analyzed though aggregate values representing the aggregate of loans and/or the aggregate of borrowing between classes. It is mainly shown that the three groups of European interbank network do not have the same response, and that intermediate banks are the most sensitive to liquidity risk.

Kano’s Model for Clinical Laboratory

The clinical laboratory has received considerable recognition globally due to the rapid development of advanced technology, economic demands and its role in a patient’s treatment cycle. Although various cross-domain experiments and practices with respect to clinical laboratory projects are ready for the full swing, the customer needs are still ambiguous and debatable. The purpose of this study is to apply Kano’s model and customer satisfaction matrix to categorize service quality attributes in order to see how well these attributes are able to satisfy customer needs. The result reveals that ten of the 26 service quality attributes have greater impacts on highly increasing customer’s satisfaction and should be taken in consideration firstly.

Coproduction of Fructose and Ethanol from Dates by S. cerevisiae ATCC 36859

Coproduction of fructose and ethanol from dates extract by a glucose-selective S. cerevisiae ATCC 36859 strain has been studied. Various initial sugar concentrations (i.e., 131.4, 315.3, 408.2, and 500.0 g/l) have been tested. The fermentation experiments were performed in a water shaker bath at 30°C and 120 rpm. The results showed that highest yields of fructose (95.0%) and ethanol (72.8%) were achieved for the 131.4 g/l concentration. Increasing the initial concentration to 315.3 g/l resulted in lower yields of fructose (82.2%) and ethanol (61.0%). However, further increase to 408.2 g/l increased the fructose yield (97.5%) at the expense of ethanol yield (42.0%) due to probable substrate inhibitions that resulted in lower glucose conversion. At 500 g initial sugar/l the growth rate of ATCC 36859 was highly inhibited. 

Isolation and Classification of Red Blood Cells in Anemic Microscopic Images

Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. Anemia is a lack of RBCs is characterized by its level compared to the normal hemoglobin level. In this study, a system based image processing methodology was developed to localize and extract RBCs from microscopic images. Also, the machine learning approach is adopted to classify the localized anemic RBCs images. Several textural and geometrical features are calculated for each extracted RBCs. The training set of features was analyzed using principal component analysis (PCA). With the proposed method, RBCs were isolated in 4.3secondsfrom an image containing 18 to 27 cells. The reasons behind using PCA are its low computation complexity and suitability to find the most discriminating features which can lead to accurate classification decisions. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network RBFNN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained within short time period, and the results became better when PCA was used.

Augmented Reality on Android

Augmented Reality is an application which combines a live view of real-world environment and computer-generated images. This paper studies and demonstrates an efficient Augmented Reality development in the mobile Android environment with the native Java language and Android SDK. Major components include Barcode Reader, File Loader, Marker Detector, Transform Matrix Generator, and a cloud database.

An Effective Genetic Algorithm for a Complex Real-World Scheduling Problem

We address a complex scheduling problem arising in the wood panel industry with the objective of minimizing a quadratic function of job tardiness. The proposed solution strategy, which is based on an effective genetic algorithm, has been coded and implemented within a major Tunisian company, leader in the wood panel manufacturing. Preliminary experimental results indicate significant decrease of delivery times.

Investigating the Influence of Porosity on Thermal and Mechanical Properties of a C/C Composite Using Image Based FE Modelling

In this paper, 3D image based composite unit cell is constructed from high resolution tomographic images. Through-thickness thermal diffusivity and in-plane Young’s modulus are predicted for the composite unit cell. The accuracy of the image based composite unit cell is tested by comparing its results with the experimental results obtained from laser flash and tensile test. The FE predictions are in close agreement with experimental results. Through-thickness thermal diffusivity and in-plane Young’s modulus of a virgin C/C composite are predicted by replacing the properties of air (porosity) with the properties of carbon matrix. The effect of porosity was found to be more profound on thermal diffusivity than young’s modulus.

Composition Dependent Formation of Sputtered Co-Cu Film on Cr Under-Layer

Sputtered CoxCu100-x films with the different compositions of x = 57.7, 45.8, 25.5, 13.8, 8.8, 7.5 and 1.8 were deposited on Cr under-layer by RF-sputtering. SEM result reveals that the averaged thickness of Co-Cu film and Cr under-layer are 92 nm and 22nm, respectively. All Co-Cu films are composed of Co (FCC) and Cu (FCC) phases in (111) directions on BCC-Cr (110) under-layers. Magnetic properties, surface roughness and morphology of Co-Cu films are dependent on the film composition. The maximum and minimum surface roughness of 3.24 and 1.16nm are observed on the Co7.5Cu92.5 and Co45.8Cu54.2films, respectively. It can be described that the variance of surface roughness of the film because of the difference of the agglomeration rate of Co and Cu atoms on Cr under-layer. The Co57.5Cu42.3, Co45.8Cu54.2 and Co25.5Cu74.5 films shows the ferromagnetic phase whereas the rest of the film exhibits the paramagnetic phase at room temperature. The saturation magnetization, remnant magnetization and coercive field of Co-Cu films on Cr under-layer are slightly increased with increasing the Co composition. It can be concluded that the required magnetic properties and surface roughness of the Co-Cu film can be adapted by the adjustment of the film composition.

A Study of Priority Evaluation and Resource Allocation for Revitalization of Cultural Heritages in the Urban Development

Proper maintenance and preservation of significant cultural heritages or historic buildings is necessary. It can not only enhance environmental benefits and a sense of community, but also preserve a city's history and people’s memory. It allows the next generation to be able to get a glimpse of our past, and achieve the goal of sustainable preserved cultural assets. However, the management of maintenance work has not been appropriate for many designated heritages or historic buildings so far. The planning and implementation of the reuse has yet to have a breakthrough specification. It leads the heritages to a mere formality of being “reserved”, instead of the real meaning of “conservation”. For the restoration and preservation of cultural heritages study issues, it is very important due to the consideration of historical significance, symbolism, and economic benefits effects. However, the decision makers such as the officials from public sector they often encounter which heritage should be prioritized to be restored first under the available limited budgets. Only very few techniques are available today to determine the appropriately restoration priorities for the diverse historical heritages, perhaps because of a lack of systematized decision-making aids been proposed before. In the past, the discussions of management and maintenance towards cultural assets were limited to the selection of reuse alternatives instead of the allocation of resources. In view of this, this research will adopt some integrated research methods to solve the existing problems that decision-makers might encounter when allocating resources in the management and maintenance of heritages and historic buildings. The purpose of this study is to develop a sustainable decision making model for local governments to resolve these problems. We propose an alternative decision support model to prioritize restoration needs within the limited budgets. The model is constructed based on fuzzy Delphi, fuzzy analysis network process (FANP) and goal programming (GP) methods. In order to avoid misallocate resources; this research proposes a precise procedure that can take multi-stakeholders views, limited costs and resources into consideration. Also, the combination of many factors and goals has been taken into account to find the highest priority and feasible solution results. To illustrate the approach we propose in this research, seven cultural heritages in Taipei city as one example has been used as an empirical study, and the results are in depth analyzed to explain the application of our proposed approach.

Improved Robust Stability Criteria of a Class of Neutral Lur’e Systems with Interval Time-Varying Delays

This paper addresses the robust stability problem of a class of delayed neutral Lur’e systems. Combined with the property of convex function and double integral Jensen inequality, a new tripe integral Lyapunov functional is constructed to derive some new stability criteria. Compared with some related results, the new criteria established in this paper are less conservative. Finally, two numerical examples are presented to illustrate the validity of the main results.

Comparison of Two Types of Preconditioners for Stokes and Linearized Navier-Stokes Equations

To solve saddle point systems efficiently, several preconditioners have been published. There are many methods for constructing preconditioners for linear systems from saddle point problems, for instance, the relaxed dimensional factorization (RDF) preconditioner and the augmented Lagrangian (AL) preconditioner are used for both steady and unsteady Navier-Stokes equations. In this paper we compare the RDF preconditioner with the modified AL (MAL) preconditioner to show which is more effective to solve Navier-Stokes equations. Numerical experiments indicate that the MAL preconditioner is more efficient and robust, especially, for moderate viscosities and stretched grids in steady problems. For unsteady cases, the convergence rate of the RDF preconditioner is slightly faster than the MAL perconditioner in some circumstances, but the parameter of the RDF preconditioner is more sensitive than the MAL preconditioner. Moreover the convergence rate of the MAL preconditioner is still quite acceptable. Therefore we conclude that the MAL preconditioner is more competitive than the RDF preconditioner. These experiments are implemented with IFISS package. 

A Study of Removing SUVA and Trihalomethanes by Biological Activated Carbon

SUVA (equivalent to UV254/DOC) value in raw water is a precursor for the formation of trihalomethane during chlorination at a water treatment plant. This study collected rapidly filtered water from an advanced water treatment plant for use in experiments on raw water. The removal rate of treating the trihalomethanes formation potential (THMFP) was conducted by using a biological activated carbon. The hydraulic retention time and SUVA loading were major factors in biological degradation tests. The results showed that biological powder-activated carbon (BPAC) lowered the average concentration of UV254 and value of SUVA in raw water. A removal efficiency of THMFP was present in the treatment of the three primary organic carbon items. These results highlighted the importance of the BPAC had an excellent treatment efficiency on THMFP.

The Implementation of the Multi-Agent Classification System (MACS) in Compliance with FIPA Specifications

The paper discusses the implementation of the MultiAgent classification System (MACS) and utilizing it to provide an automated and accurate classification of end users developing applications in the spreadsheet domain. However, different technologies have been brought together to build MACS. The strength of the system is the integration of the agent technology with the FIPA specifications together with other technologies, which are the .NET widows service based agents, the Windows Communication Foundation (WCF) services, the Service Oriented Architecture (SOA), and Oracle Data Mining (ODM). The Microsoft's .NET widows service based agents were utilized to develop the monitoring agents of MACS, the .NET WCF services together with SOA approach allowed the distribution and communication between agents over the WWW. The Monitoring Agents (MAs) were configured to execute automatically to monitor excel spreadsheets development activities by content. Data gathered by the Monitoring Agents from various resources over a period of time was collected and filtered by a Database Updater Agent (DUA) residing in the .NET client application of the system. This agent then transfers and stores the data in Oracle server database via Oracle stored procedures for further processing that leads to the classification of the end user developers.

Using Multi-Linguistic Techniques for Thailand Herb and Traditional Medicine Registration Systems

Thailand has evolved many unique culture and knowledge, and the leading is the Thai traditional medicine (TTM). Recently, a number of researchers have tried to save this indigenous knowledge. However, the system to do so has still been scant. To preserve this ancient knowledge, we therefore invented and integrated multi-linguistic techniques to create the system of the collected all of recipes. This application extracted the medical recipes from antique scriptures then normalized antiquarian words, primitive grammar and antiquated measurement of them to the modern ones. Then, we applied ingredient-duplication-calculation, proportion-similarity-calculation and score-ranking to examine duplicate recipes. We collected the questionnaires from registrants and people to investigate the users’ satisfaction. The satisfactory results were found. This application assists not only registrants to validating the copyright violation in TTM registration process but also people to cure their illness that aids both Thai people and all mankind to fight for intractable diseases.

Almost Periodicity in a Harvesting Lotka-Volterra Recurrent Neural Networks with Time-Varying Delays

By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of positive almost periodic solution in a delayed Lotka-Volterra recurrent neural networks with harvesting terms. To a certain extent, our work in this paper corrects some result in recent years. Finally, an example is given to illustrate the feasibility and effectiveness of the main result.