Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

Deep sequencing reveals predominant expression of miR-21 amongst the small non-coding RNAs in retinal microvascular endothelial cells

The retinal vascular endothelium is essential for angiogenesis and is involved in maintaining barrier selectivity and vascular tone. The aim of this study was to identify and quantify microRNAs and other small regulatory non-coding RNAs (ncRNAs) which may regulate these crucial functions. Primary bovine retinal microvascular endothelial cells (RMECs) provide a well-characterized in vitro system for studying angiogenesis. RNA extracted from RMECs was used to prepare a small RNA library for deep sequencing (Illumina Genome Analyzer). A total of 6.8 million reads were mapped to 250 known microRNAs in miRBase (release 16). In many cases, the most frequent isomiR differed from the sequence reported in miRBase. In addition, five novel microRNAs, 13 novel bovine orthologs of known human microRNAs and multiple new members of the miR-2284/2285 family were detected. Several similar to 30 nucleotide sno-miRNAs were identified, with the most highly expressed being derived from snoRNA U78. Highly expressed microRNAs previously associated with endothelial cells included miR-126 and miR-378, but the most highly expressed was miR-21, comprising more than one-third of all mapped reads. Inhibition of miR-21 with an LNA inhibitor significantly reduced proliferation, migration, and tube-forming capacity of RMECs. The independence from prior sequence knowledge provided by deep sequencing facilitates analysis of novel microRNAs and other small RNAs. This approach also enables quantitative evaluation of microRNA expression, which has highlighted the predominance of a small number of microRNAs in RMECs. Knockdown of miR-21 suggests a role for this microRNA in regulation of angiogenesis in the retinal microvasculature. J. Cell. Biochem. 113: 20982111, 2012. (C) 2012 Wiley Periodicals, Inc.

Predictive models for deterioration of concrete structures

Permeation characteristics and fracture strength are the fundamental properties of concrete that influence the initiation and extent of damage and can form the basis by which deterioration can be predicted. The relationship between these properties and deterioration mechanisms is discussed along with the different models representing their interaction with the environment. Mehta presented a holistic model of the deterioration of concrete based on the environmental action on the microstructure of concrete. Using a similar approach, a detailed investigation on the causes of concrete deterioration is used to develop a macro-model for each mechanism relating to the physical properties of concrete. A single interaction model is then presented for all types of deterioration, emphasizing the permeation properties of concrete. Data from an in situ investigation of concrete bridges in Northern Ireland is used to validate this model. This is followed by a micro-predictive model which includes an ionic transport sub-model, a deterioration sub-model and a structural sub-model and affords quantitative prediction of the deterioration of concrete structures. The quantitative predictive capabilities of the micro-model are demonstrated with the use of reported experimental data.

Joint complex diversity coding and channel coding over space, time and frequency

This study provides a general diversity analysis for joint complex diversity coding (CDC) and channel coding-based space-time-frequency codeing is provided. The mapping designs from channel coding to CDC are crucial for efficient exploitation of the diversity potential. This study provides and proves a sufficient condition of full diversity construction with joint three-dimensional CDC and channel coding, bit-interleaved coded complex diversity coding and symbol-interleaved coded complex diversity coding. Both non-iterative and iterative detections of joint channel code and CDC transmission are investigated. The proposed minimum mean-square error-based iterative soft decoding achieves the performance of the soft sphere decoding with reduced complexity.

Predictive position and force control for shape memory alloy cylinders

In this paper, a linear lightweight electric cylinder constructed using shape memory alloy (SMA) is proposed. Spring SMA is used as the actuator to control the position and force of the cylinder rod. The model predictive control algorithm is investigated to compensate SMA hysteresis phenomenon and control the cylinder. In the predictive algorithm, the future output of the cylinder is computed based on the cylinder model, and the control signal is computed to minimize the error and power criterion. The cylinder model parameters are estimated by an online identification algorithm. Experimental results show that the SMA cylinder is able to precisely control position and force by using the predictive control strategy though the hysteresis effect existing in the actuator. The performance of the proposed controller is compared with that of a conventional PID controller

Predictive markers for colorectal cancer:current status and future prospects

Colorectal cancer (CRC) is the second leading cause of cancer death in the United States. Although there is clear evidence of the benefit of chemotherapy in adjuvant and metastatic settings, its use continues to be suboptimal because of intrinsic or acquired drug resistance. 5-Fluorouracil continues to be the mainstay of CRC therapy, and combinations with newer chemotherapeutic agents such as irinotecan and oxaliplatin have resulted in improved response rates and survival. The role of other agents including cyclooxygenase-2 inhibitors, epidermal growth factor receptor, and farnsyl transferase inhibitors remains to be elucidated. Despite these improvements, many patients undergo chemotherapy without benefit. Increased understanding of the biology of CRC has led to the identification of prognostic markers that may help identify patients who will benefit from chemotherapy. Furthermore, studies have also begun to identify markers that predict whether a tumor will respond to a particular chemotherapy. The ultimate goal of this research is to prospectively identify patients who should receive chemotherapy and, thus, to tailor treatment to the molecular profile of the tumor and patient. Such an approach has the potential to dramatically improve response rates. This review highlights potentially important prognostic and predictive factors in CRC and discusses the potential for their use in the treatment of this disease.