The path probability method: An atomistic technique of diffusion

The path probability method (PPM) of irreversible statistical mechanics has been successfully applied to various diffusion problems. The major advantage of this atomistic treatment over the phenomenological approach of irreversible thermodynamics is that all Onsager matrix coefficients can be derived analytically so that relations among measurable quantities can be clearly understood in terms of microscopic parameters. This review article attempts to present the PPM in the simplest possible form. The importance of the PPM as an atomistic technique is illustrated using a simple example. The applicability and limitations of the technique are also emphasized.     

Photocatalytic degradation of methyl tert‐butyl ether (MTBE) in contaminated water by ZnO nanoparticles

BACKGROUND: Over the past several decades methyl tert‐butyl ether (MTBE) as additive to gasoline, intended to either boost ratings of fuel or to reduce air pollution, has been accepted worldwide. Since MTBE has high water solubility, the occurrence of fuel spills or leaks from underground storage tanks or transferring pipeline has led to the contamination of natural waters. In this study the degradation of aqueous MTBE at relatively high concentrations was investigated by a UV‐visible/ZnO/H₂O₂ photocatalytic process. The effects of important operational parameters such as pH, amount of H₂O₂, catalyst loading and irradiation time were also investigated. Concentration of MTBE and intermediates such as tert‐butyl formate and tert‐butyl alcohol were measured. RESULTS: Time required for complete degradation increased from 20 to 150 min when the initial concentration was increased from 10 to 500 mg L^?1. The first‐order rate constants for degradation of MTBE were estimated to be 0.183–0.022 min^?1 as the concentration increased from 10 to 500 mg L^?1. Study of the overall mineralization monitored by total organic carbon analysis showed that at an initial concentration of 100 mg L^?1 MTBE complete mineralization was obtained after 100 min under UV‐visible/ZnO/H₂O₂ photocatalysis. CONCLUSION: The data presented in this paper clearly indicated that UV‐visible/ZnO/O₂ as an advanced oxidation process provides an efficient treatment alternative for the remediation of MTBE‐contaminated waters. Copyright © 2008 Society of Chemical Industry     

Enhancement of endogenous cyclic AMP signal: a new approach to allow for cold preservation of rat livers from non-heart-beating donors?

BACKGROUND: The organ donor shortage has led to a reconsideration of the use of non-heart-beating donors (NHBDs). However, graft injury due to warm ischemia in NHBD livers strongly affects posttransplant outcome. The present study was aimed at investigating the role of the cellular cyclic (c)AMP second messenger signal with regard to hepatic viability after cold preservation of NHBD livers. METHODS: Cardiac arrest was induced in Wistar rats by frenotomy of the anesthetized nonheparinized animal. After 30 min, the livers were excised and flushed with 20 ml of heparinized saline solution, rinsed with 10 ml of University of Wisconsin (UW) solution, and stored submerged in UW solution at 4 degrees C for 24 hr. In half of the experiments, UW solution was supplemented with glucagon (0.5 microg/ml) to increase the cAMP signal in the liver. Reperfusion was carried out in vitro after all livers were incubated at 25 degrees C in saline solution to replicate the period of slow rewarming during surgical implantation in vivo. RESULTS: Hepatic levels of cAMP (nmol/g dry weight) declined from 1.21+/-0.05 to 0.53+/-0.03 (P<0.01) at 30 min after cardiac arrest. Subsequent storage in UW solution resulted in a further decline to 0.35+/-0.04 after 24 hr in group A, whereas glucagon treatment enhanced cellular cAMP signal to 0.64+/-0.06 (P<0.01). Upon reperfusion, liver integrity was significantly improved after glucagon administration, with 66% reduction in alanine aminotransferase release and a threefold increase in hepatic bile production as compared with untreated livers. Moreover, liver ATP tissue levels were restored to only 2.19+/-0.51 micromol/g in the untreated group but reached 4.97+/-0.41 micromol/g (P<0.05) after treatment with glucagon. CONCLUSIONS: Posthoc conditioning of predamaged livers by glucagon enhances cAMP tissue levels during ischemic preservation and improves hepatic integrity upon reperfusion. This may represent a promising approach for the use of livers from non-heart-beating donors in clinical transplantation.     

An FEC scheme combined with weighted scheduling to reduce multicast packet loss in IPTV over PON

Congestion is one of the most important challenges in optical networks. In a Passive Optical Network (PON), the Optical Line Terminal (OLT) is a bottleneck and congestion prone. In this paper, a framework is proposed with Forward Error Correction (FEC) at the IP layer combined with Weighted Round Robin (WRR) at the scheduling level to overcome packet-loss due to congestion in the OLT in order to achieve efficient video multicasting over PON. In the FEC scheme, Reed-Solomon (RS(n,k)) with erasure coding is used, where (n−k) erroneous symbols per n symbol blocks can be corrected. In our framework, an Internet Protocol TeleVision (IPTV) service provider uses the mentioned RS coding and generates redundant packets from regular IPTV packets in such a way that an Optical Network Unit (ONU) can recover lost packets from received packets, thus resulting in a better video quality. Simulation results show that using the proposed framework, an ONU can recover many lost packets and achieve better video quality under different traffic loads for its users. For instance, the proposed method can reduce packet loss rate by almost 55% and 10% under traffic load 0.9, respectively, compared with the Round Robin (RR) and WRR methods under symmetric traffic load. When High Receivers Queue (HRQ) traffic (i.e., traffic received by many users) is twice Low Receivers Queue (LRQ) traffic (i.e., traffic received by a small number of users), this reduction is almost 86% and 30% under traffic load 0.9. Finally, when LRQ traffic is twice HRQ traffic, the reduction in packet loss rate is almost 70% and 91% at traffic load 0.5.     

Relating Sediment Yield Estimations to the Wet Front Term Using Rainfall Simulator Field Experiments

Water Resources Management - Depth to wet front is generally considered as the amount of water that penetrates into soil and wets the internal soil layer. This is an important variable especially...     

Low-power high-speed interconnection networks in NOC using multi-valued current-mode techniques

With the fast developments and growth of electronic applications and a great demand for increasing the speed of processors, VLSI circuits and on-chip interconnections the ＂Networks-On-Chip＂ （NOC） is the best solution for ＂System-On-Chip＂ （SOC）. The most fundamental part of networks On-Chip is the On-Chip interconnection. The model presented in this article describes the method of sending data on On-Chip interconnection by using a current-mode multi-valued logic instead of voltage-mode in order to increase speed and reduce the number of interconnection wires.     

On the Efficiency of Runs Rules Schemes for Process Monitoring

There are two main types of variations, namely, common and special causes leading to in‐control and out‐of‐control states, respectively. Control charts are popular tools used to differentiate between these two states of a process. Implementation of runs rules schemes with control charts is an attractive approach for process monitoring. This study is designed to describe the methodology of runs rules schemes and discuss their implementation for different types of control charts. We have considered memory‐less charts, namely, , S, and R charts for our study purposes. It is examined that the efficiency gain depends on the number of decision points utilized to implement a given rule. Moreover, superiority of runs rules schemes may vary for different types of location and dispersion charts. An application example using a dataset is also included in the study for practical considerations. Copyright © 2015 John Wiley & Sons, Ltd.     

A genetic programming model to generate risk-adjusted technical trading rules in stock markets

Technical trading rules can be generated from historical data for decision making in stock markets. Genetic programming (GP) as an artificial intelligence technique is a valuable method to automatically generate such technical trading rules. In this paper, GP has been applied for generating risk-adjusted trading rules on individual stocks. Among many risk measures in the literature, conditional Sharpe ratio has been selected for this study because it uses conditional value at risk (CVaR) as an optimal coherent risk measure. In our proposed GP model, binary trading rules have been also extended to more realistic rules which are called trinary rules using three signals of buy, sell and no trade. Additionally we have included transaction costs, dividend and splits in our GP model for calculating more accurate returns in the generated rules. Our proposed model has been applied for 10 Iranian companies listed in Tehran Stock Exchange (TSE). The numerical results showed that our extended GP model could generate profitable trading rules in comparison with buy and hold strategy especially in the case of risk adjusted basis.     

Analysis and forecasting of IPO underpricing

Probability of withdrawal is a feature of initial public offering (IPOs), which can be an important parameter in decisions of investors and issuers. Considering the probability of offering withdrawal facilitates more precise estimation of underpricing. In this paper, the effective factors on probability of IPO withdrawal and underpricing in Tehran Stock Exchange have been characterized using regression, and then neural network is applied to estimate the probability of IPO withdrawal and underpricing. To evaluate the performance of our applied method, fuzzy regression is employed and compared with neural network. According to the obtained empirical results, neural network demonstrates better accuracy than fuzzy regression. The results indicate that there is a meaningful relationship between underpricing and probability of withdrawal, and the probability of IPO withdrawal plays an important role in precise evaluation of underpricing.