Aquatic Ecosystems: Conservation, Restoration and Management

Aquatic Ecosystems perform numerous valuable environmental functions. They recycle nutrients, purify water, recharge ground water, augment and maintain stream flow, and provide habitat for a wide variety of flora and fauna and recreation for people. A rapid population increase accompanied by unplanned developmental works has led to the pollution of surface waters due to residential, agricultural, commercial and industrial wastes/effluents and decline in the number of water bodies. Increased demands for drainage of wetlands have been accommodated by channelisation, resulting in further loss of stream habitat, which has led to aquatic organisms becoming extinct or imperiled in increasing numbers and to the impairment of many beneficial uses of water, including drinking, swimming and fishing. Various anthropogenic activities have altered the physical, chemical and biological processes within aquatic ecosystems. An integrated and accelerated effort toward environmental restoration and preservation is needed to stop further degradation of these fragile ecosystems. Failure to restore these ecosystems will result in sharply increased environmental costs later, in the extinction of species or ecosystem types, and in permanent ecological damage.

Electrode kinetics of a nickel/cadmium cell and failure-mode prediction. Estimation of equivalent resistance of an internal short

A quantitative expression has been obtained for the equivalent resistance of an internal short in rechargeable cells under constant voltage charging.

Texture dependent stress corrosion failure of commercial titanium sheets in bromine-methanol solution

The stress corrosion cracking (SCC) characteristics of agr-titanium sheets in a bromine-methanol solution have been studied in the annealed and cold-rolled conditions using longitudinal and transverse specimens. The times to failure for annealed longitudinal specimens were longer than those for similarly tested transverse specimens. The cold-rolled specimens developed resistance to SCC, but failed by cleavage when notched, unlike the intergranular separation in annealed titanium. The apparent activation energy was found to be texture dependent and was in the range 30 to 51 kJ mol–1 for annealed titanium, and 15kJ mol–1 for cold-rolled titanium. The dependence of SCC behaviour on the texture is related to the changes in the crack initiation times. These are caused by changes in the passivation and repassivation characteristics of the particular thickness plane. The thickness planes are identified with the help of X-ray pole figures obtained on annealed and cold-rolled material. On the basis of the activation energy and the electrochemical measurements, the mechanism of SCC in annealed titanium is identified to be the one involving stress-aided anodic dissolution. On the other hand, the results on the cold-rolled titanium are in support of the hydrogen embrittlement mechanism consisting of hydride precipitation. The cleavage planes identified from the texture data match with the reported habit planes for hydride formation.

Restoration of symmetry by radiative corrections

It is shown using an explicit model that radiative corrections can restore the symmetry of a system which may appear to be broken at the classical level. This is the reverse of the phenomenon demonstrated by Coleman and Weinberg. Our model is different from theirs, but the techniques are the same. The calculations are done up to the two-loop level and it is shown that the two-loop contribution is much smaller than the one-loop contribution, indicating good convergence of the loop expansion.

An algebraic approach to the restoration of images

Two different matrix algorithms are described for the restoration of blurred pictures. These are illustrated by numerical examples.

Optimal maintenance policy for equipment subject to random deterioration and random failure A modern control theory approach.

The stochastic version of Pontryagin's maximum principle is applied to determine an optimal maintenance policy of equipment subject to random deterioration. The deterioration of the equipment with age is modelled as a random process. Next the model is generalized to include random catastrophic failure of the equipment. The optimal maintenance policy is derived for two special probability distributions of time to failure of the equipment, namely, exponential and Weibull distributions Both the salvage value and deterioration rate of the equipment are treated as state variables and the maintenance as a control variable. The result is illustrated by an example

Conservative Design Optimization of Laminated Composite Structures Using Genetic Algorithms and Multiple Failure Criteria

This article analyzes the effect of devising a new failure envelope by the combination of the most commonly used failure criteria for the composite laminates, on the design of composite structures. The failure criteria considered for the study are maximum stress and Tsai-Wu criteria. In addition to these popular phenomenological-based failure criteria, a micromechanics-based failure criterion called failure mechanism-based failure criterion is also considered. The failure envelopes obtained by these failure criteria are superimposed over one another and a new failure envelope is constructed based on the lowest absolute values of the strengths predicted by these failure criteria. Thus, the new failure envelope so obtained is named as most conservative failure envelope. A minimum weight design of composite laminates is performed using genetic algorithms. In addition to this, the effect of stacking sequence on the minimum weight of the laminate is also studied. Results are compared for the different failure envelopes and the conservative design is evaluated, with respect to the designs obtained by using only one failure criteria. The design approach is recommended for structures where composites are the key load-carrying members such as helicopter rotor blades.

Mechanism of failure in a free-standing Pt-aluminide bond coat during tensile testing at room temperature

The room temperature (RT) tensile behaviour of a free-standing high activity Pt-aluminide bond coat has been evaluated by microtensile testing technique. The coating had a typical three-layer microstructure. The stress-strain plot for the free-standing coating was linear, indicating the coating to be brittle at RT. Different fracture features were observed across the coating layers, namely quasi-cleavage in the outer layer and inner interdiffusion zone, and cleavage in the intermediate layer. By employing interrupted tensile test and observing the cross-sectional microstructure of the tested specimens, it was determined that failure of the microtensile samples occurred by the initiation of a single crack in the intermediate layer of the coating and its subsequent inside-out propagation. Such a mechanism of failure has been explained in terms of the fracture features observed across the sample thickness. This mechanism of failure is consistent with fracture toughness values of the individual coating layers. (C) 2009 Elsevier B.V. All rights reserved.

Characterization of Failure Modes in CFRP Composites - An ANN Approach

Carbon fiber reinforced polymer (CFRP) composite specimens with different thickness, geometry, and stacking sequences were subjected to fatigue spectrum loading in stages. Another set of specimens was subjected to static compression load. On-line acoustic Emission (AE) monitoring was carried out during these tests. Two artificial neural networks, Kohonen-self organizing feature map (KSOM), and multi-layer perceptron (MLP) have been developed for AE signal analysis. AE signals from specimens were clustered using the unsupervised learning KSOM. These clusters were correlated to the failure modes using available a priori information such as AE signal amplitude distributions, time of occurrence of signals, ultrasonic imaging, design of the laminates (stacking sequences, orientation of fibers), and AE parametric plots. Thereafter, AE signals generated from the rest of the specimens were classified by supervised learning MLP. The network developed is made suitable for on-line monitoring of AE signals in the presence of noise, which can be used for detection and identification of failure modes and their growth. The results indicate that the characteristics of AE signals from different failure modes in CFRP remain largely unaffected by the type of load, fiber orientation, and stacking sequences, they being representatives of the type of failure phenomena. The type of loading can have effect only on the extent of damage allowed before the specimens fail and hence on the number of AE signals during the test. The artificial neural networks (ANN) developed and the methods and procedures adopted show significant success in AE signal characterization under noisy environment (detection and identification of failure modes and their growth).

Line removal and restoration of handwritten strokes

In document images, we often find printed lines over-lapping with hand written elements especially in case of signatures. Typical examples of such images are bank cheques and payment slips. Although the detection and removal of the horizontal lines has been addressed, the restoration of the handwritten area after removal of lines, persists to be a problem of interest. lit this paper, we propose a method for line removal and restoration of the erased areas of the handwritten elements. Subjective evaluation of the results have been conducted to analyze the effectiveness of the proposed method. The results are promising with an accuracy of 86.33%. The entire Process takes less than half a second for completion on a 2.4 GHz 512 MB RAM Pentium IV PC for a document image.

Quantitation and characterization of glutathionyl haemoglobin as an oxidative stress marker in chronic renal failure by mass spectrometry

Objectives: Glutathionyl haemoglobin (GS-Hb) belonging to the class of glutathionylated proteins has been investigated as a possible marker of oxidative stress in different chronic diseases. The purpose of this study was to examine whether glutathionyl haemoglobin can serve as an oxidative stress marker in non-diabetic chronic renal failure patients on different renal replacement therapies (RRT) through its quantitation, and characterization of the specific binding site of glutathione in haemoglobin molecule by mass spectrometric analysis. Design and methods: The study group consisted of non-diabetic chronic renal failure patients on renal replacement therapy (RRT): hemodialysis (HD), continuous ambulatory peritoneal dialysis (CAPD) and renal allograft transplant (Txp) patients. Haemoglobin samples of these subjects were analyzed by liquid chromatography electrospray ionization mass spectrometry for GS-Hb quantitation. Characterization of GS-Hb was done by tandem mass spectrometry. Levels of erythrocyte glutathione (GSH) and lipid peroxidation (as thiobarbituric acid reacting substances) were measured spectrophotometrically, while glycated baernoglobin (HbA1c) was measured by HPLC. Results: GS-Hb levels were markedly elevated in the dialysis group and marginally in the transplant group as compared to the controls. GS-Hb levels correlated positively with lipid peroxidation and negatively with the erythrocyte glutathione levels in RRT groups indicating enhanced oxidative stress. De novo sequencing of the chymotryptic fragment of GS-Hb established that glutathione is attached to Cys-93 of the beta globin chain. Mass spectrometric quantitation of total glycated haemoglobin showed good agreement with HbA1c estimation by conventional HPLC method. Conclusions: Glutathionyl haemoglobin can serve as a clinical marker of oxidative stress in chronic debilitating therapies like RRT. Mass spectrometry provides a reliable analytical tool for quantitation and residue level characterization of different post-translational modifications of haemoglobin. (c) 2007 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Design of a FIR filter for image restoration using principal component neural networks

The neural network finds its application in many image denoising applications because of its inherent characteristics such as nonlinear mapping and self-adaptiveness. The design of filters largely depends on the a-priori knowledge about the type of noise. Due to this, standard filters are application and image specific. Widely used filtering algorithms reduce noisy artifacts by smoothing. However, this operation normally results in smoothing of the edges as well. On the other hand, sharpening filters enhance the high frequency details making the image non-smooth. An integrated general approach to design a finite impulse response filter based on principal component neural network (PCNN) is proposed in this study for image filtering, optimized in the sense of visual inspection and error metric. This algorithm exploits the inter-pixel correlation by iteratively updating the filter coefficients using PCNN. This algorithm performs optimal smoothing of the noisy image by preserving high and low frequency features. Evaluation results show that the proposed filter is robust under various noise distributions. Further, the number of unknown parameters is very few and most of these parameters are adaptively obtained from the processed image.

A new FIR filter for image restoration

Image filtering techniques have potential applications in biomedical image processing such as image restoration and image enhancement. The potential of traditional filters largely depends on the apriori knowledge about the type of noise corrupting the image. This makes the standard filters to be application specific. For example, the well-known median filter and its variants can remove the salt-and-pepper (or impulse) noise at low noise levels. Each of these methods has its own advantages and disadvantages. In this paper, we have introduced a new finite impulse response (FIR) filter for image restoration where, the filter undergoes a learning procedure. The filter coefficients are adaptively updated based on correlated Hebbian learning. This algorithm exploits the inter pixel correlation in the form of Hebbian learning and hence performs optimal smoothening of the noisy images. The application of the proposed filter on images corrupted with Gaussian noise, results in restorations which are better in quality compared to those restored by average and Wiener filters. The restored image is found to be visually appealing and artifact-free

Deformation and failure of a film/substrate system subjected to spherical indentation: Part 1. Experimental validation of stresses and strains derived using Hankel transform technique in an elastic film/substrate system

Our concern here is to rationalize experimental observations of failure modes brought about by indentation of hard thin ceramic films deposited on metallic substrates. By undertaking this exercise, we would like to evolve an analytical framework that can be used for designs of coatings. In Part I of the paper we develop an algorithm and test it for a model system. Using this analytical framework we address the issue of failure of columnar TiN films in Part II [J. Mater. Res. 21, 783 (2006)] of the paper. In this part, we used a previously derived Hankel transform procedure to derive stress and strain in a birefringent polymer film glued to a strong substrate and subjected to spherical indentation. We measure surface radial strains using strain gauges and bulk film stresses using photo elastic technique (stress freezing). For a boundary condition based on Hertzian traction with no film interface constraint and assuming the substrate constraint to be a function of the imposed strain, the theory describes the stress distributions well. The variation in peak stresses also demonstrates the usefulness of depositing even a soft film to protect an underlying substrate.