Colorectal Cancer Screening by a CEACAM-6 Immunosensor

The biomarker for colorectal cancer (CRC) is CEACAM-6 antigen (C6AG). Therefore, this study aims to develop a novel, simple and low-cost CEACAM-6 antigen immumosensor (C6AG-IMS), based on electrical impedance measurement, for precise determination of C6AG. A low-cost screen-printed graphite electrode was constructed and used as the sensor, with CEACAM-6 antibody (C6AB) immobilized on it. The procedures of sensor fabrication and antibody immobilization are simple and low-cost. Measurement of the electrical impedance at a definite frequency ranges (0.43 – 1.26 MHz) showed that the C6AG-IMS has an excellent linear (r2>0.9) response range (8.125 – 65 pg/mL), covering the normal physiological and pathological ranges of blood C6AG levels. Also, the C6AG-IMS has excellent reliability and validity, with the intraclass correlation coefficient being 0.97. In conclusion, a novel, simple, low-cost and reliable C6AG-IMS was designed and developed, being able to accurately determine blood C6AG levels in the range of pathological and normal physiological regions. The C6AG-IMS can provide a point-of-care and immediate screening results to the user at home.

European and International Bond Markets Integration

The concurrent era is characterised by strengthened interactions among financial markets and increased capital mobility globally. In this frames we examine the effects the international financial integration process has on the European bond markets. We perform a comparative study of the interactions of the European and international bond markets and exploit Cointegration analysis results on the elimination of stochastic trends and the decomposition of the underlying long run equilibria and short run causal relations. Our investigation provides evidence on the relation between the European integration process and that of globalisation, viewed through the bond markets- sector. Additionally the structural formulation applied, offers significant implications of the findings. All in all our analysis offers a number of answers on crucial queries towards the European bond markets integration process.

On Methodologies for Analysing Sickness Absence Data: An Insight into a New Method

Sickness absence represents a major economic and social issue. Analysis of sick leave data is a recurrent challenge to analysts because of the complexity of the data structure which is often time dependent, highly skewed and clumped at zero. Ignoring these features to make statistical inference is likely to be inefficient and misguided. Traditional approaches do not address these problems. In this study, we discuss model methodologies in terms of statistical techniques for addressing the difficulties with sick leave data. We also introduce and demonstrate a new method by performing a longitudinal assessment of long-term absenteeism using a large registration dataset as a working example available from the Helsinki Health Study for municipal employees from Finland during the period of 1990-1999. We present a comparative study on model selection and a critical analysis of the temporal trends, the occurrence and degree of long-term sickness absences among municipal employees. The strengths of this working example include the large sample size over a long follow-up period providing strong evidence in supporting of the new model. Our main goal is to propose a way to select an appropriate model and to introduce a new methodology for analysing sickness absence data as well as to demonstrate model applicability to complicated longitudinal data.

The Influence of Preprocessing Parameters on Text Categorization

Text categorization (the assignment of texts in natural language into predefined categories) is an important and extensively studied problem in Machine Learning. Currently, popular techniques developed to deal with this task include many preprocessing and learning algorithms, many of which in turn require tuning nontrivial internal parameters. Although partial studies are available, many authors fail to report values of the parameters they use in their experiments, or reasons why these values were used instead of others. The goal of this work then is to create a more thorough comparison of preprocessing parameters and their mutual influence, and report interesting observations and results.

Modeling Concave Globoidal Cam with Swinging Roller Follower : A Case Study

This paper describes a computer-aided design for design of the concave globoidal cam with cylindrical rollers and swinging follower. Four models with different modeling methods are made from the same input data. The input data are angular input and output displacements of the cam and the follower and some other geometrical parameters of the globoidal cam mechanism. The best cam model is the cam which has no interference with the rollers when their motions are simulated in assembly conditions. The angular output displacement of the follower for the best cam is also compared with that of in the input data to check errors. In this study, Pro/ENGINEER® Wildfire 2.0 is used for modeling the cam, simulating motions and checking interference and errors of the system.

Shoplifting in Riyadh, Saudi Arabia

the research was conducted using the self report of shoplifters who apprehended in the supermarket while stealing. 943 shoplifters in three years were interviewed right after the stealing act and before calling the police. The aim of the study is to know the shoplifting characteristics in Saudi Arabia, including the trait of shoplifters and the situation of the supermarkets where the stealing takes place. The analysis based on the written information about each thief as the documentary research method. Descriptive statistics as well as some inferential statistics were employed. The result shows that there are differences between genders, age groups, occupations, time of the day, days of the week, months, way of stealing, individual or group of thieves and other supermarket situations in the type of items stolen, total price and the count of items. The result and the recommendation will serve as a guide for retailers where, when and who to look at to prevent shoplifting.

pH-Responsiveness Properties of a Biodigradable Hydrogels Based on Carrageenan-g-poly(NaAA-co-NIPAM)

A novel thermo-sensitive superabsorbent hydrogel with salt- and pH-responsiveness properties was obtained by grafting of mixtures of acrylic acid (AA) and N-isopropylacrylamide (NIPAM) monomers onto kappa-carrageenan, kC, using ammonium persulfate (APS) as a free radical initiator in the presence of methylene bisacrylamide (MBA) as a crosslinker. Infrared spectroscopy was carried out to confirm the chemical structure of the hydrogel. Moreover, morphology of the samples was examined by scanning electron microscopy (SEM). The effect of MBA concentration and AA/NIPAM weight ratio on the water absorbency capacity has been investigated. The swelling variations of hydrogels were explained according to swelling theory based on the hydrogel chemical structure. The hydrogels exhibited salt-sensitivity and cation exchange properties. The temperature- and pH-reversibility properties of the hydrogels make the intelligent polymers as good candidates for considering as potential carriers for bioactive agents, e.g. drugs.

Reliability Analysis of Underground Pipelines Using Subset Simulation

An advanced Monte Carlo simulation method, called Subset Simulation (SS) for the time-dependent reliability prediction for underground pipelines has been presented in this paper. The SS can provide better resolution for low failure probability level with efficient investigating of rare failure events which are commonly encountered in pipeline engineering applications. In SS method, random samples leading to progressive failure are generated efficiently and used for computing probabilistic performance by statistical variables. SS gains its efficiency as small probability event as a product of a sequence of intermediate events with larger conditional probabilities. The efficiency of SS has been demonstrated by numerical studies and attention in this work is devoted to scrutinise the robustness of the SS application in pipe reliability assessment. It is hoped that the development work can promote the use of SS tools for uncertainty propagation in the decision-making process of underground pipelines network reliability prediction.

Mode III Interlaminar Fracture in Woven Glass/Epoxy Composite Laminates

In the present study, fracture behavior of woven fabric-reinforced glass/epoxy composite laminates under mode III crack growth was experimentally investigated and numerically modeled. Two methods were used for the calculation of the strain energy release rate: the experimental compliance calibration (CC) method and the Virtual Crack Closure Technique (VCCT). To achieve this aim ECT (Edge Crack Torsion) was used to evaluate fracture toughness in mode III loading (out of plane-shear) at different crack lengths. Load–displacement and associated energy release rates were obtained for various case of interest. To calculate fracture toughness JIII, two criteria were considered including non-linearity and maximum points in load-displacement curve and it is observed that JIII increases with the crack length increase. Both the experimental compliance method and the virtual crack closure technique proved applicable for the interpretation of the fracture mechanics data of woven glass/epoxy laminates in mode III.

Visualisation and Navigation in Large Scale P2P Service Networks

In Peer-to-Peer service networks, where peers offer any kind of publicly available services or applications, intuitive navigation through all services in the network becomes more difficult as the number of services increases. In this article, a concept is discussed that enables users to intuitively browse and use large scale P2P service networks. The concept extends the idea of creating virtual 3D-environments solely based on Peer-to-Peer technologies. Aside from browsing, users shall have the possibility to emphasize services of interest using their own semantic criteria. The appearance of the virtual world shall intuitively reflect network properties that may be of interest for the user. Additionally, the concept comprises options for load- and traffic-balancing. In this article, the requirements concerning the underlying infrastructure and the graphical user interface are defined. First impressions of the appearance of future systems are presented and the next steps towards a prototypical implementation are discussed.

Effects of Xylanase and Cellulase Production during Composting of EFB and POME using Fungi

Empty Fruit Bunches (EFB) and Palm Oil Mill Effluent (POME) are two main wastes from oil palm industries which contain rich lignocellulose. Degradation of EFB and POME by microorganisms will produce hydrolytic enzyme which will degrade cellulose and hemicellulose during composting process. However, normal composting takes about four to six months to reach maturity. Hence, application of fungi into compost can shorten the period of composting. This study identifies the effect of xylanase and cellulase produced by Aspergillus niger and Trichoderma virens on composting process using EFB and POME. The degradation of EFB and POME indicates the lignocellulolytic capacity of Aspergillus niger and Trichoderma virens with more than 7% decrease in hemicellulose and more than 25% decrease in cellulose for both inoculated compost. Inoculation of Aspergillus niger and Trichoderma virens also increased the enzyme activities during the composting period compared to the control compost by 21% for both xylanase and cellulase. Rapid rise in the activities of cellulase and xylanase was observed by Aspergillus niger with the highest activities of 14.41 FPU/mg and 3.89 IU/mg, respectively. Increased activities of cellulase and xylanase also occurred in inoculation of Trichoderma virens with the highest activities obtained at 13.21 FPU/mg and 4.43 IU/mg, respectively. Therefore, it is evident that the inoculation of fungi can increase the enzyme activities hence effectively degrading the EFB and POME.

Position Awareness Mechanisms for Wireless Sensor Networks

A Wireless sensor network (WSN) consists of a set of battery-powered nodes, which collaborate to perform sensing tasks in a given environment. Each node in WSN should be capable to act for long periods of time with scrimpy or no external management. One requirement for this independent is: in the presence of adverse positions, the sensor nodes must be capable to configure themselves. Hence, the nodes for determine the existence of unusual events in their surroundings should make use of position awareness mechanisms. This work approaches the problem by considering the possible unusual events as diseases, thus making it possible to diagnose them through their symptoms, namely, their side effects. Considering these awareness mechanisms as a foundation for highlevel monitoring services, this paper also shows how these mechanisms are included in the primal plan of an intrusion detection system.

Rigorous Modeling of Fixed-Bed Reactors Containing Finite Hollow Cylindrical Catalyst with Michaelis-Menten Type of Kinetics

A large number of chemical, bio-chemical and pollution-control processes use heterogeneous fixed-bed reactors. The use of finite hollow cylindrical catalyst pellets can enhance conversion levels in such reactors. The absence of the pellet core can significantly lower the diffusional resistance associated with the solid phase. This leads to a better utilization of the catalytic material, which is reflected in the higher values for the effectiveness factor, leading ultimately to an enhanced conversion level in the reactor. It is however important to develop a rigorous heterogeneous model for the reactor incorporating the two-dimensional feature of the solid phase owing to the presence of the finite hollow cylindrical catalyst pellet. Presently, heterogeneous models reported in the literature invariably employ one-dimension solid phase models meant for spherical catalyst pellets. The objective of the paper is to present a rigorous model of the fixed-bed reactors containing finite hollow cylindrical catalyst pellets. The reaction kinetics considered here is the widely used Michaelis–Menten kinetics for the liquid-phase bio-chemical reactions. The reaction parameters used here are for the enzymatic degradation of urea. Results indicate that increasing the height to diameter ratio helps to improve the conversion level. On the other hand, decreasing the thickness is apparently not as effective. This could however be explained in terms of the higher void fraction of the bed that causes a smaller amount of the solid phase to be packed in the fixed-bed bio-chemical reactor.

A Single-chip Proportional to Absolute Temperature Sensor Using CMOS Technology

Nowadays it is a trend for electronic circuit designers to integrate all system components on a single-chip. This paper proposed the design of a single-chip proportional to absolute temperature (PTAT) sensor including a voltage reference circuit using CEDEC 0.18m CMOS Technology. It is a challenge to design asingle-chip wide range linear response temperature sensor for many applications. The channel widths between the compensation transistor and the reference transistor are critical to design the PTAT temperature sensor circuit. The designed temperature sensor shows excellent linearity between -100°C to 200° and the sensitivity is about 0.05mV/°C. The chip is designed to operate with a single voltage source of 1.6V.

IVE: Virtual Humans’ AI Prototyping Toolkit

IVE toolkit has been created for facilitating research,education and development in the field of virtual storytelling and computer games. Primarily, the toolkit is intended for modelling action selection mechanisms of virtual humans, investigating level-of-detail AI techniques for large virtual environments, and for exploring joint behaviour and role-passing technique (Sec. V). Additionally, the toolkit can be used as an AI middleware without any changes. The main facility of IVE is that it serves for prototyping both the AI and virtual worlds themselves. The purpose of this paper is to describe IVE's features in general and to present our current work - including an educational game - on this platform.

A Multi Objective Optimization Approach to Optimize Vehicle Ride and Handling Characteristics

Vehicle suspension design must fulfill some conflicting criteria. Among those is ride comfort which is attained by minimizing the acceleration transmitted to the sprung mass, via suspension spring and damper. Also good handling of a vehicle is a desirable property which requires stiff suspension and therefore is in contrast with a vehicle with good ride. Among the other desirable features of a suspension is the minimization of the maximum travel of suspension. This travel which is called suspension working space in vehicle dynamics literature is also a design constraint and it favors good ride. In this research a full car 8 degrees of freedom model has been developed and the three above mentioned criteria, namely: ride, handling and working space has been adopted as objective functions. The Multi Objective Programming (MOP) discipline has been used to find the Pareto Front and some reasoning used to chose a design point between these non dominated points of Pareto Front.

A New Approach for Prioritization of Failure Modes in Design FMEA using ANOVA

The traditional Failure Mode and Effects Analysis (FMEA) uses Risk Priority Number (RPN) to evaluate the risk level of a component or process. The RPN index is determined by calculating the product of severity, occurrence and detection indexes. The most critically debated disadvantage of this approach is that various sets of these three indexes may produce an identical value of RPN. This research paper seeks to address the drawbacks in traditional FMEA and to propose a new approach to overcome these shortcomings. The Risk Priority Code (RPC) is used to prioritize failure modes, when two or more failure modes have the same RPN. A new method is proposed to prioritize failure modes, when there is a disagreement in ranking scale for severity, occurrence and detection. An Analysis of Variance (ANOVA) is used to compare means of RPN values. SPSS (Statistical Package for the Social Sciences) statistical analysis package is used to analyze the data. The results presented are based on two case studies. It is found that the proposed new methodology/approach resolves the limitations of traditional FMEA approach.

Development of a Simple laser-based 2D Compensating System for the Contouring Accuracy of Machine Tools

The dynamical contouring error is a critical element for the accuracy of machine tools. The contouring error is defined as the difference between the processing actual path and commanded path, which is implemented by following the command curves from feeding driving system in machine tools. The contouring error is resulted from various factors, such as the external loads, friction, inertia moment, feed rate, speed control, servo control, and etc. Thus, the study proposes a 2D compensating system for the contouring accuracy of machine tools. Optical method is adopted by using stable frequency laser diode and the high precision position sensor detector (PSD) to performno-contact measurement. Results show the related accuracy of position sensor detector (PSD) of 2D contouring accuracy compensating system was ±1.5 μm for a calculated range of ±3 mm, and improvement accuracy is over 80% at high-speed feed rate.

Multiple Moving Talker Tracking by Integration of Two Successive Algorithms

In this paper, an estimation accuracy of multiple moving talker tracking using a microphone array is improved. The tracking can be achieved by the adaptive method in which two algorithms are integrated, namely, the PAST (Projection Approximation Subspace Tracking) algorithm and the IPLS (Interior Point Least Square) algorithm. When either talker begins to speak again after a silent period, an appropriate feasible region for an evaluation function of the IPLS algorithm might not be set. Then, the tracking fails due to the incorrect updating. Therefore, if an increment of the number of active talkers is detected, the feasible region must be reset. Then, a low cost realization is required for the high speed tracking and a high accuracy realization is desired for the precise tracking. In this paper, the directions roughly estimated using the delayed-sum-array method are used for the resetting. Several results of experiments performed in an actual room environment show the effectiveness of the proposed method.

A Study of the Damages to Historical Monuments due to Climatic Factors and Air Pollution and Offering Solutions

Historical monuments as architectural heritage are, economically and culturally, considered one of the key aspects for modern communities. Cultural heritage represents a country-s national identity and pride and maintains and enriches that country-s culture. Therefore, conservation of the monuments remained from our ancestors requires everybody-s serious and unremitting effort. Conservation, renewal, restoration, and technical study of cultural and historical matters are issues which have a special status among various forms of art and science in the present century and this is due to two reasons: firstly, progress of humankind in this century has created a factor called environmental pollution which not only has caused new destructive processes of cultural/historical monuments but also has accelerated the previous destructive processes by several times, and secondly, the rapid advance of various sciences, especially chemistry, has lead to the contribution of new methods and materials to this significant issue.