Synthesis and characterization of radiation grafted copolymer for removal of nonionic organic contaminants

Nonionic organic contaminants such as phenol, benzene, and toluene from contaminated wastewater on laboratory scale can be effectively sorbed by cellulosic wood pulp sheet incorporated with three polar functional groups. The synthesis was carried out by graft copolymerization reaction of N,N‐dimethylaminoethylmethacrylate with methacrylic acid onto wood pulp. The preparation conditions at which the grafting process proceeds homogeneously are determined. Characterization and some selected properties of the original and grafted wood pulp were evaluated using FTIR and scanning electron microscope, also, the removal of phenol, benzene, and toluene on laboratory scale was investigated by using gas chromatography. It was found that phenol shows the highest removal percent than that of benzene and toluene. The efficiency of removal of the nonionic contaminants is found to be 97%, which shows a great promise for its applicability in the removal of organic contaminates from wastewater. © 2006 Wiley Periodicals, Inc. J Appl Polym Sci 100: 3589–3595, 2006     

Ensemble-based noise detection: noise ranking and visual performance evaluation

Noise filtering is most frequently used in data preprocessing to improve the accuracy of induced classifiers. The focus of this work is different: we aim at detecting noisy instances for improved data understanding, data cleaning and outlier identification. The paper is composed of three parts. The first part presents an ensemble-based noise ranking methodology for explicit noise and outlier identification, named Noise- Rank, which was successfully applied to a real-life medical problem as proven in domain expert evaluation. The second part is concerned with quantitative performance evaluation of noise detection algorithms on data with randomly injected noise. A methodology for visual performance evaluation of noise detection algorithms in the precision-recall space, named Viper, is presented and compared to standard evaluation practice. The third part presents the implementation of the NoiseRank and Viper methodologies in a web-based platform for composition and execution of data mining workflows. This implementation allows public accessibility of the developed approaches, repeatability and sharing of the presented experiments as well as the inclusion of web services enabling to incorporate new noise detection algorithms into the proposed noise detection and performance evaluation workflows.     

Proteomics in aortic aneurysm – What have we learnt so far?

Aortic aneurysm is a deceptively indolent disease that can cause severe complications such as aortic rupture and dissection. In the normal aorta, vascular smooth muscle cells within the medial layer produce and sustain the extracellular matrix (ECM) that provides structural support but also retains soluble growth factors and regulates their distribution. Although the ECM is an obvious target to identify molecular processes leading to structural failure within the vessel wall, an in-depth proteomics analysis of this important sub-proteome has not been performed. Most proteomics analyses of the vasculature to date used homogenized tissue devoid of spatial information. In such homogenates, quantitative proteomics comparisons are hampered by the heterogeneity of clinical samples (i.e. cellular composition) and the dynamic range limitations stemming from highly abundant cellular proteins. An unbiased proteomics discovery approach targeting the ECM instead of the cellular proteome may decipher the complex, multivalent signals that are presented to cells during aortic remodelling. A better understanding of the ECM in healthy and diseased vessels will provide important pathogenic insights and has potential to reveal novel biomarkers.     

Palladium nanoclusters-coated polyfuran as a novel sensor for catecholamine neurotransmitters and paracetamol

A promising electrochemical biosensor was developed by electrodeposition of palladium nanoclusters on polyfuran film modified platinum electrode. This biosensor electrode was used to determine some catecholamines, namely dopamine, epinephrine and norepinephrine, ascorbic acid and paracetamol. The method of formation of the polymer film and deposition of Pd particles plays a key role in the electroactivity of the resulting hybrid material. This sensor effectively resolved the overlapping anodic peaks of ascorbic acid (AA), dopamine (DA) and paracetamol (ACOP) into three well-defined voltammetric peaks in differential pulse voltammetry analysis. The detection limit of DA in the absence and presence of AA and ACOP are eventually the same which indicates that the oxidation processes of DA, AA and ACOP are independent and that the simultaneous measurements of the three analytes are possible without interference. The electrodeposition of Pd on polyfuran improved exceptionally the detection limit about four decades. Moreover, diffusion coefficient measurements confirmed the fast electron transfer kinetics of the electrochemical oxidation of the analyte molecules at the sensor/solution interface. It is very interesting to note that the electrocatalytic effect of PF/Pd composite has been increased to be sometimes 21 times that of the pristine PF which has been considered for a long time to be of low conductivity and attracted low attention as a result of the difficulty of its formation and poor conductivity.     

Three empirical evaluations of a software reuse reference model

The contribution of this paper is three empirical evaluations of a reference model for the practice of software reuse. Our research thesis is that software development based upon a software reuse reference model improves quality of products, productivity of processes and product time‐to‐market for many software development enterprises. The definition and investigation of such a model has been carried out using three steps. First, the reference model is developed based on existing software reuse concepts. Second, this reference model is empirically evaluated using three studies: one using a survey method, one using a case studies method, and one using a legacy studies method. Third, the impact of the reference model on software development productivity, quality, and time‐to‐market is empirically derived. This revised version was published online in June 2006 with corrections to the Cover Date.     

Resistance of Listeria monocytogenes, Escherichia coli O157:H7 and Campylobacter jejuni after exposure to repetitive cycles of mild bactericidal treatments

While maintaining nutritional and sensorial attributes of fresh foods mild processing technologies generally deliver microbiologically perishable food products. Currently little information exists on possible increase in the resistance of pathogens after repetitive exposure to mild (sub-lethal) treatments. Multiple strain-cocktails of Listeria monocytogenes, Escherichia coli O157:H7 and Campylobacter jejuni were exposed to 20 consecutive cycles of sub-lethal inactivation by three different techniques. Used techniques comprised inactivation with lactic acid (LA), chlorine dioxide (ClO₂) and intense light pulses (ILP). Results showed that the selection of resistant cells was both species and technique dependent. While repetitive cycles of ClO₂ treatment did not result in increased resistance, repetitive inactivation with LA yielded L. monocytogenes culture of higher resistance in comparison to the parental culture. The increased resistance, expressed as decreased level of reduction in bacterial counts in subsequent inactivation cycles, was also observed with ILP for both L. monocytogenes and E. coli O157:H7 strains. Visual trend observations were confirmed through statistical linear regression analysis. No such effects were noted for C. jejuni which became undetectable after first 2–5 cycles. Current findings indicate the ability of foodborne pathogens to adapt to mild bactericidal treatments creating new challenges in risk assessment and more specifically in hazard analysis.     

Effect of operating conditions on current density distribution and high frequency resistance in a segmented PEM fuel cell

Understanding losses in polymer electrolyte membrane fuel cells, in the form of ohmic and mass transport, is of great importance to their commercialization. In this study, we use a spatially resolved cell consisting of 49 segments to measure the local current density distribution and high frequency resistance (HFR). A parametric study is used to investigate the effects of cell voltage, inlet relative humidity and flow rate and configuration using a three-channel serpentine flow field. We found that as the cell voltage decreased, the current density increased, while the HFR decreased. However, at a low cell voltage of 200 mV, we found the HFR to be higher than that at 500 mV. This increase is attributed to the increased electro-osmotic drag. This trend is independent of the flow configuration. Further, we found that the effect of the inlet relative humidity on the HFR highly depends on the flow configurations. Finally, a sharp decrease in the current density at some specific bend segments was observed, which correlates with lower OCV values and higher HFR values at this position.     

Analysis of medications change in Parkinson’s disease progression data

Parkinson’s disease is a neurodegenerative disorder that affects people worldwide. Careful management of patient’s condition is crucial to ensure the patient’s independence and quality of life. This is achieved by personalized treatment based on individual patient’s symptoms and medical history. The aim of this study is to determine patient groups with similar disease progression patterns coupled with patterns of medications change that lead to the improvement or decline of patients’ quality of life symptoms. To this end, this paper proposes a new methodology for clustering of short time series of patients’ symptoms and prescribed medications data, and time sequence data analysis using skip-grams to monitor disease progression. The results demonstrate that motor and autonomic symptoms are the most informative for evaluating the quality of life of Parkinson’s disease patients. We show that Parkinson’s disease patients can be divided into clusters ordered in accordance with the severity of their symptoms. By following the evolution of symptoms for each patient separately, we were able to determine patterns of medications change which can lead to the improvement or worsening of the patients’ quality of life.     

Technoeconomic study for the optimization of turbine size and wind farm layouts

A technoeconomic analysis and optimization of wind turbine size and layout are performed using WAsP software. A case study of a 100‐MW wind farm located in Egypt is considered. Wind atlas for Egypt was used as the input data of the WAsP software. Two turbine models of powers 52 and 80 MW are considered for this project. The wind turbine size and distributions are selected based on the technoeconomic optimization, namely minimum wake effect, maximum annual energy production (AEP) rate, optimum cash flow, and payback period. The future worth method is adopted in economic comparison between the two alternatives, and the cash flow diagram provided the payback period and future worth after the lifetime of the plant. The results showed that (1) the AEP dramatically decreases for a wind farm area less than 15 km²; (2) the turbine spacing, spacing‐to‐diameter ratio, and the setback distances decrease and the wind turbine density and wake losses increase with decreasing the wind turbines size; (3) the total net AEP using G52 is lower than that of using G80 by about 16%; (4) the technoeconomic analysis recommended using G80 as it has higher profit than those of G52 by about $20 million.