Electro-copolymerisation of indene and styrene

Electroinitiated cationic copolymerisation of indene and styrene was investigated by constant potential electrolysis. Effects of copolymerisation potential and temperature on the copolymer composition and the reactivity ratios are discussed. The reactivity ratios of the monomers were calculated according to the integrated Lewis-Mayo equation.     

Study of liquid injection impact on the performance of new refrigerant mixtures

In this paper, the test results of liquid injection impact on the performance of new alternative refrigerant mixtures such as: R-410A, R-507, R-407C and R-404A are discussed, analysed and presented. The test results were obtained using an air-source heat pump set-up with enhanced surface tubing under various liquid injection ratios. Performance tests were conducted according to the ARI/ASHRAE standards. The performance data demonstrated that as liquid injection ratio increases, compressor head pressure and discharge temperature decrease. This has a positive effect in protecting the compressor. The effect of liquid injection on mixture behaviour varies from one mixture to another depending upon the mixture's composition. Furthermore, liquid injection appears to have a significant influence on R-410A behaviour compared to the other mixtures in question. Copyright © 2002 John Wiley & Sons, Ltd.     

In vitro cytotoxicity and DNA damage production in Chinese hamster ovary cells and topoisomerase II inhibition by 2-[2''-(dimethylamino)ethyl]-1, 2-dihydro-3H-dibenz[de,h]isoquinoline-1,3-diones with substitutions at the 6 and 7 positions (azonafides)

The p53 tumor suppressor gene encodes a phosphoprotein which when overexpressed can induce growth arrest at the G1 and G2/M phases of the cell cycle, promote differentiation and apoptosis. This paper demonstrates that p53 can associate with trk tyrosine kinase. Expression of a murine temperature-sensitive (ts) p53 mutant in PC12 cells overexpressing trk (a model system to analyse cellular differentiation and signal transduction induced by NGF) induces morphological changes in the absence of NGF stimulation at 32 degrees C but not at 37 degrees C. In cells differentiated by p53, trk, but not EGFr, was hyperphosphorylated on tyrosine. Furthermore trk was not phosphorylated when expressed in Saos-2 cells (human osteosarcoma cells that lack expression of both endogenous trk and p53) at either temperature. However, transfection of ts p53 into these cells induces trk phosphorylation at 32 degrees C in the absence of NGF stimulation. Association of trk and p53 can be detected in NIH3T3 and PC12 cells co-expressing trk and the ts p53 mutant, in NIH3T3 and PC12 cells transfected with trk alone, and in untransfected PC12 cells, showing that overexpressed and/or endogenous trk associates with endogenous, low levels of p53. These data suggest a novel function for p53 which involves the stimulation of signal transduction pathways (mediating morphological properties of cells), possibly through association with and hyperphosphorylation of trk.     

Fault tolerance in FFT arrays: Time redundancy approaches

Fault tolerance in VLSI/WSI FFT arrays acquires relevance when defects and run-time faults become significant, due to large dimensions of processors and arrays. Then, both restructuring to overcome end-of-production defects and reconfiguration to overcome run-time faults are required, to achieve the dual purposes of higher yield and higher reliability.Adopting as basic FFT network the two-dimensions array that directly corresponds to the FFT flow graph, the usual structure redundancy techniques tailored for two-dimensions arrays reconfiguration are not well applicable, since the limited locality of this network leads to relevant area increase due to the augmented interconnection structure.In this paper,time redundancy is suggested as a viable alternative for the two-dimensions FFT array; two different solutions are presented, one based oninter-stage reconfiguration, the other one adoptingintra-state reconfiguration, both allowing for survival to multiple faults with limited increase of network complexity and very small hard-core sections. As usual in many time redundancy methods, both approaches result in a processing speed equal to half the processing speed granted by an ideal, fault-free device.Reliability and survival ratios to multiple faults are evaluated for the two cases, taking into account also the area increments necessary for fault tolerance. The reliability evaluations allow for a direct comparison of the two solutions.     

Effect of electricity tariff on the optimum insulation-thickness in building walls as determined by a dynamic heat-transfer model

Thermal insulation is one of the most effective energy-conservation measures in buildings. Despite the widespread use of insulation materials in recent years, little is known regarding their optimum thickness under dynamic thermal conditions. Insulated concrete blocks are among the units most commonly used in the construction of building walls in Saudi Arabia. Typically, the insulation layer thickness is fixed at a value in the range 2.5–7.5 cm, regardless of the climatic conditions, type and cost of insulation material, and other economic parameters. In the present study, a numerical model based on a finite-volume, time-dependent implicit procedure, which has been previously validated, is used to compute the yearly cooling and heating transmission loads under steady periodic conditions through a typical building wall, for different insulation thicknesses. The transmission loads, calculated by using the climatic conditions of Riyadh for a west-facing wall, are fed into an economic model in order to determine the optimum thickness of insulation (L_opt). The latter corresponds to the minimum total cost, which includes the cost of insulation material and its installation plus the present value of energy consumption cost over the lifetime of the building. The optimum insulation thickness depends on the electricity tariff as well as the cost of insulation material, lifetime of the building, inflation and discount rates, and coefficient of performance of the air-conditioning equipment. In the present study, the effect of electricity tariff on the computed optimum insulation thickness is investigated. Different average electricity tariffs are considered; namely, 0.05, 0.1, 0.2, 0.3 and 0.4 SR/kWh (designated as Cases 1–5, respectively; 1 US$ = 3.75 Saudi Riyals). Results using moulded polystyrene as an insulating material show that the values of L_opt are: 4.8, 7.2, 10.9, 13.7 and 16.0 cm for Cases 1–5. Under the conditions of optimal insulation thickness for each electricity tariff, Case 1 gives the lowest total cost of 17.4 SR/m², while Case 5 gives the highest total cost of 53.1 SR/m². Corresponding thermal performance characteristics in terms of yearly total and peak transmission loads, R-value, time lag and decrement factor are presented.     

A novel approach to predict shear strength of tilted angle connectors using artificial intelligence techniques

Shear connectors play a prominent role in the design of steel-concrete composite systems. The behavior of shear connectors is generally determined through conducting push-out tests. However, these tests are costly and require plenty of time. As an alternative approach, soft computing (SC) can be used to eliminate the need for conducting push-out tests. This study aims to investigate the application of artificial intelligence (AI) techniques, as sub-branches of SC methods, in the behavior prediction of an innovative type of C-shaped shear connectors, called Tilted Angle Connectors. For this purpose, several push-out tests are conducted on these connectors and the required data for the AI models are collected. Then, an adaptive neuro-fuzzy inference system (ANFIS) is developed to identify the most influencing parameters on the shear strength of the tilted angle connectors. Totally, six different models are created based on the ANFIS results. Finally, AI techniques such as an artificial neural network (ANN), an extreme learning machine (ELM), and another ANFIS are employed to predict the shear strength of the connectors in each of the six models. The results of the paper show that slip is the most influential factor in the shear strength of tilted connectors and after that, the inclination angle is the most effective one. Moreover, it is deducted that considering only four parameters in the predictive models is enough to have a very accurate prediction. It is also demonstrated that ELM needs less time and it can reach slightly better performance indices than those of ANN and ANFIS.

     

Incorporation of a Regularization Term to Control Negative Correlation in Mixture of Experts

Combining accurate neural networks (NN) in the ensemble with negative error correlation greatly improves the generalization ability. Mixture of experts (ME) is a popular combining method which employs special error function for the simultaneous training of NN experts to produce negatively correlated NN experts. Although ME can produce negatively correlated experts, it does not include a control parameter like negative correlation learning (NCL) method to adjust this parameter explicitly. In this study, an approach is proposed to introduce this advantage of NCL into the training algorithm of ME, i.e., mixture of negatively correlated experts (MNCE). In this proposed method, the capability of a control parameter for NCL is incorporated in the error function of ME, which enables its training algorithm to establish better balance in bias-variance-covariance trade-off and thus improves the generalization ability. The proposed hybrid ensemble method, MNCE, is compared with their constituent methods, ME and NCL, in solving several benchmark problems. The experimental results show that our proposed ensemble method significantly improves the performance over the original ensemble methods.     

Performance evaluation of an importance sampling technique in a Jackson network

Importance sampling is a technique that is commonly used to speed up Monte Carlo simulation of rare events. However, little is known regarding the design of efficient importance sampling algorithms in the context of queueing networks. The standard approach, which simulates the system using an a priori fixed change of measure suggested by large deviation analysis, has been shown to fail in even the simplest network settings. Estimating probabilities associated with rare events has been a topic of great importance in queueing theory, and in applied probability at large. In this article, we analyse the performance of an importance sampling estimator for a rare event probability in a Jackson network. This article carries out strict deadlines to a two-node Jackson network with feedback whose arrival and service rates are modulated by an exogenous finite state Markov process. We have estimated the probability of network blocking for various sets of parameters, and also the probability of missing the deadline of customers for different loads and deadlines. We have finally shown that the probability of total population overflow may be affected by various deadline values, service rates and arrival rates.     

Analysis of impersonation attacks on systems using RF fingerprinting and low-end receivers

Recently, physical layer security commonly known as Radio Frequency (RF) fingerprinting has been proposed to provide an additional layer of security for wireless devices. A unique RF fingerprint can be used to establish the identity of a specific wireless device in order to prevent masquerading/impersonation attacks. In the literature, the performance of RF fingerprinting techniques is typically assessed using high-end (expensive) receiver hardware. However, in most practical situations receivers will not be high-end and will suffer from device specific impairments which affect the RF fingerprinting process. This paper evaluates the accuracy of RF fingerprinting employing low-end receivers. The vulnerability to an impersonation attack is assessed for a modulation-based RF fingerprinting system employing low-end commodity hardware (by legitimate and malicious users alike). Our results suggest that receiver impairment effectively decreases the success rate of impersonation attack on RF fingerprinting. In addition, the success rate of impersonation attack is receiver dependent.