Photoacoustic and photothermal deflection studies on certain selected photonic materials“

The emergence of lasers in the early sixties has not only revolutionized the field of optics and communication but also paved new ways in the field of material characterization. Material studies using photothermal techniques possess certain unique characteristics and advantages over conventional methods. The most important aspect of photothennal techniques is their ability to perform noncontact and nondestructive measurement. Photoacoustics, photothermal deflection, thermal lens, photothermal radiometry and photopyroelectric methods are some of the commonly used and powerful techniques for the thermal and optical characterization of materials using lasers. In this thesis the applications of photoacoustic and photothermal deflection techniques for the thermal and optical characterization of different photonic materials, namely, semiconductors, liquid crystals and dye-doped polymers are discussed

Application of chitosan and PASS for the removal of turbidity and colour from water

The most common and conventional method for removing turbidity from water is by coagulating with alum or iron salts, and settling the precipitate in suitably designed clarifiers followed by filtration. But the sludge produced is bulky, difficult to dewater and accumulates in the dumping grounds causing environmental problems. Synthetic polymers such as polyacrylamide and polyethyleneoxide have been investigated for their ability to remove turbidity. They overcome many of the disadvantages of conventional methods, but are cost—effective only when rapid flocculation and reduction in sludge volume are demanded. Considering the aforementioned situation, it was felt that more easily available and eco-friendly materials must be developed for removing turbidity from water. The results of our studies in this direction are presented in this thesis. The thesis comprises of nine chapters, with a common bibliography at the end. Chapter 1 gives an introduction to the nature of turbidity and colour usually present in water. Chapter 2 discusses the nature and availability of the principal material used in these studies, namely chitosan. Chapters 3 to 8, which deal with the actual experimental work, are further subdivided into (a) introduction, (b) materials and methods, (c) results and discussion and (d) conclusions. Chapter 9 summarises the entire work so as to put the results and conclusions into proper perspective.

Waste Water Treatment Using Low Cost Natural Adsorbents

Heavy metals are major toxic pollutants with severe health effects on humans. They are released into the environment from a variety of industrial activities. Cadmium, lead, zinc, chromium and copper are the most toxic metals of widespread use in industries such as tanning, electroplating, electronic equipment manufacturing and chemical processing plants. Heavy metals contribute to a variety of adverse health environmental effects due to their acute and chronic exposure through air, water and food chain. Conventional treatment methods of metal removal are often limited by their cost and ineffectiveness at low concentrations. Adsorption, the use of inactivated biomass as adsorbents offers an attractive potential alternative to their conventional methods. Mango peel and Alisma plantago aquatica are naturally occurring and abundant biomass can offer an economical solution for metal removal.The Cd(II), Pb(II), Zn(II), Cr(III) and Cu(II) adsorption by milled adsorbents of mango peel and Alisma plantago aquatica were evaluated in batches.

A Faster 2D Technique for the design of Combinational Digital Circuits Using Genetic Algorithm

Combinational digital circuits can be evolved automatically using Genetic Algorithms (GA). Until recently this technique used linear chromosomes and and one dimensional crossover and mutation operators. In this paper, a new method for representing combinational digital circuits as 2 Dimensional (2D) chromosomes and suitable 2D crossover and mutation techniques has been proposed. By using this method, the convergence speed of GA can be increased significantly compared to the conventional methods. Moreover, the 2D representation and crossover operation provides the designer with better visualization of the evolved circuits. In addition to this, a technique to display automatically the evolved circuits has been developed with the help of MATLAB

The protective and attractive covering of a vegetated embankment using coir geotextiles

This paper presents the results of a field experiment conducted in Kerala, South India, to test the effectiveness of coir geotextiles for embankment protection. The results reveal that treatment with geotextile in combination with grass is an effective eco-hydrological measure to protect steep slopes from erosion. In the context of sustainable watershed management, coir is a cheap and locally available material that can be used to strengthen traditional earthen bunds or protect the banks of village ponds from erosion. Particularly in developing countries, where coir is abundantly available and textiles can be produced by small-scale industry, this is an attractive alternative for conventional methods. This paper analyses the performance of coir geotextile in different treatments with respect to soil moisture content, protection against erosion and biomass production

Experimental study using coir geotextiles in watershed management

This paper presents the results of a field experiment conducted in Kerala, South India, to test the effectiveness of coir geotextiles for embankment protection. In the context of sustainable watershed management, coir is a cheap and locally available material 5 that can be used to strengthen traditional earthen bunds or protect the banks of village ponds from erosion. Particularly in developing countries, where coir is abundantly available and textiles can be produced by small-scale industry, this is an attractive alternative for conventional methods

Interactive comment on “Experimental study using coir geotextiles in watershed management

This paper presents the results of a field experiment conducted in Kerala, South India, to test the effectiveness of coir geotextiles for embankment protection. The results reveal that treatment with geotextile in combination with grass is an effective eco-hydrological measure to protect steep slopes from erosion. In the context of sustainable watershed management, coir is a cheap and locally available material that can be used to strengthen traditional earthen bunds or protect the banks of village ponds from erosion. Particularly in developing countries, where coir is abundantly available and textiles can be produced by small-scale industry, this is an attractive alternative for conventional methods. The paper analyses the performance of different treatments with regard to soil moisture content, protection against erosion and biomass production

Integron study, molecular typing and characterization of Salmonella serotypes isolated from seafood and poultry

The primary habitat of Salmonella is the gastrointestinal tract of animals and they are discharged into the water bodies through the feces. Aquatic animals act as asymptomatic reservoirs of a wide range of Salmonella serotypes. The inevitable delay in the detection of Salmonella contamination and the low sensitivity of the conventional methods is a serious issue in the seafood industry. Due to the indiscriminate use, the antibiotics are finally accumulated in the aquatic environment which provides the required antibiotic stress for the emergence of more and more antibiotic resistant phenotypes ofSalmonella. Several genetic determinants like integrons, genomic islands etc. play their role in acquisition and reshuffling of antibiotic resistance genes. A large number of virulence determinants are required for Salmonella pathogenicity. The virulence potential of Salmonella is determined, to some extent, by the presence of phages or phage mediated genes in the bacterial genome. There is much intra-serotype polymorphism in Salmonella and epidemiological studies rely on genetic resemblance of the isolated strains. Proper identification of the strain employing the traditional and molecular techniques is a prerequisite for accurate epidemiological studies (Soto et al., 2000). In this context, a study was undertaken to determine the prevalence of different Salmonella serotypes in seafood and to characterize them

Understanding Subsystems in Biology through Dimensionality Reduction, Graph Partitioning and Analytical Modeling

Biological systems exhibit rich and complex behavior through the orchestrated interplay of a large array of components. It is hypothesized that separable subsystems with some degree of functional autonomy exist; deciphering their independent behavior and functionality would greatly facilitate understanding the system as a whole. Discovering and analyzing such subsystems are hence pivotal problems in the quest to gain a quantitative understanding of complex biological systems. In this work, using approaches from machine learning, physics and graph theory, methods for the identification and analysis of such subsystems were developed. A novel methodology, based on a recent machine learning algorithm known as non-negative matrix factorization (NMF), was developed to discover such subsystems in a set of large-scale gene expression data. This set of subsystems was then used to predict functional relationships between genes, and this approach was shown to score significantly higher than conventional methods when benchmarking them against existing databases. Moreover, a mathematical treatment was developed to treat simple network subsystems based only on their topology (independent of particular parameter values). Application to a problem of experimental interest demonstrated the need for extentions to the conventional model to fully explain the experimental data. Finally, the notion of a subsystem was evaluated from a topological perspective. A number of different protein networks were examined to analyze their topological properties with respect to separability, seeking to find separable subsystems. These networks were shown to exhibit separability in a nonintuitive fashion, while the separable subsystems were of strong biological significance. It was demonstrated that the separability property found was not due to incomplete or biased data, but is likely to reflect biological structure.

Pre-Attentive Segmentation in the Primary Visual Cortex

Stimuli outside classical receptive fields have been shown to exert significant influence over the activities of neurons in primary visual cortexWe propose that contextual influences are used for pre-attentive visual segmentation, in a new framework called segmentation without classification. This means that segmentation of an image into regions occurs without classification of features within a region or comparison of features between regions. This segmentation framework is simpler than previous computational approaches, making it implementable by V1 mechanisms, though higher leve l visual mechanisms are needed to refine its output. However, it easily handles a class of segmentation problems that are tricky in conventional methods. The cortex computes global region boundaries by detecting the breakdown of homogeneity or translation invariance in the input, using local intra-cortical interactions mediated by the horizontal connections. The difference between contextual influences near and far from region boundaries makes neural activities near region boundaries higher than elsewhere, making boundaries more salient for perceptual pop-out. This proposal is implemented in a biologically based model of V1, and demonstrated using examples of texture segmentation and figure-ground segregation. The model performs segmentation in exactly the same neural circuit that solves the dual problem of the enhancement of contours, as is suggested by experimental observations. Its behavior is compared with psychophysical and physiological data on segmentation, contour enhancement, and contextual influences. We discuss the implications of segmentation without classification and the predictions of our V1 model, and relate it to other phenomena such as asymmetry in visual search.

Predicted soil organic carbon stocks and changes in Jordan between 2000 and 2030 made using the GEFSOC modelling system

Estimates of soil organic carbon (SOC) stocks and changes under different land use systems can help determine vulnerability to land degradation. Such information is important for countries in and areas with high susceptibility to desertification. SOC stocks, and predicted changes between 2000 and 2030, were determined at the national scale for Jordan using The Global Environment Facility Soil Organic Carbon (GEFSOC) Modelling System. For the purpose of this study, Jordan was divided into three natural regions (The Jordan Valley, the Uplands and the Badia) and three developmental regions (North, Middle and South). Based on this division, Jordan was divided into five zones (based on the dominant land use): the Jordan Valley, the North Uplands, the Middle Uplands, the South Uplands and the Badia. This information was merged using GIS, along with a map of rainfall isohyets, to produce a map with 498 polygons. Each of these was given a unique ID, a land management unit identifier and was characterized in terms of its dominant soil type. Historical land use data, current land use and future land use change scenarios were also assembled, forming major inputs of the modelling system. The GEFSOC Modelling System was then run to produce C stocks in Jordan for the years 1990, 2000 and 2030. The results were compared with conventional methods of estimating carbon stocks, such as the mapping based SOTER method. The results of these comparisons showed that the model runs are acceptable, taking into consideration the limited availability of long-term experimental soil data that can be used to validate them. The main findings of this research show that between 2000 and 2030, SOC may increase in heavily used areas under irrigation and will likely decrease in grazed rangelands that cover most of Jordan giving an overall decrease in total SOC over time if the land is indeed used under the estimated forms of land use. (C) 2007 Elsevier B.V. All rights reserved.

Remote sensing of tidal networks and their relation to vegetation

The study of the morphology of tidal networks and their relation to salt marsh vegetation is currently an active area of research, and a number of theories have been developed which require validation using extensive observations. Conventional methods of measuring networks and associated vegetation can be cumbersome and subjective. Recent advances in remote sensing techniques mean that these can now often reduce measurement effort whilst at the same time increasing measurement scale. The status of remote sensing of tidal networks and their relation to vegetation is reviewed. The measurement of network planforms and their associated variables is possible to sufficient resolution using digital aerial photography and airborne scanning laser altimetry (LiDAR), with LiDAR also being able to measure channel depths. A multi-level knowledge-based technique is described to extract networks from LiDAR in a semi-automated fashion. This allows objective and detailed geomorphological information on networks to be obtained over large areas of the inter-tidal zone. It is illustrated using LIDAR data of the River Ems, Germany, the Venice lagoon, and Carnforth Marsh, Morecambe Bay, UK. Examples of geomorphological variables of networks extracted from LiDAR data are given. Associated marsh vegetation can be classified into its component species using airborne hyperspectral and satellite multispectral data. Other potential applications of remote sensing for network studies include determining spatial relationships between networks and vegetation, measuring marsh platform vegetation roughness, in-channel velocities and sediment processes, studying salt pans, and for marsh restoration schemes.

A practical approach to a multi-level analysis with a sparse binary outcome within a large surgical trial

Objectives: To assess the potential source of variation that surgeon may add to patient outcome in a clinical trial of surgical procedures. Methods: Two large (n = 1380) parallel multicentre randomized surgical trials were undertaken to compare laparoscopically assisted hysterectomy with conventional methods of abdominal and vaginal hysterectomy; involving 43 surgeons. The primary end point of the trial was the occurrence of at least one major complication. Patients were nested within surgeons giving the data set a hierarchical structure. A total of 10% of patients had at least one major complication, that is, a sparse binary outcome variable. A linear mixed logistic regression model (with logit link function) was used to model the probability of a major complication, with surgeon fitted as a random effect. Models were fitted using the method of maximum likelihood in SAS((R)). Results: There were many convergence problems. These were resolved using a variety of approaches including; treating all effects as fixed for the initial model building; modelling the variance of a parameter on a logarithmic scale and centring of continuous covariates. The initial model building process indicated no significant 'type of operation' across surgeon interaction effect in either trial, the 'type of operation' term was highly significant in the abdominal trial, and the 'surgeon' term was not significant in either trial. Conclusions: The analysis did not find a surgeon effect but it is difficult to conclude that there was not a difference between surgeons. The statistical test may have lacked sufficient power, the variance estimates were small with large standard errors, indicating that the precision of the variance estimates may be questionable.

Optical sensors for monitoring water uptake in plants

The monitoring of water uptake in plants is becoming increasingly important. Optical sensors offer considerable advantages over conventional methods and several sensors have been developed including an optical potometer that monitors water uptake from individual roots, the detection of xylem cavitation using audio acoustic emissions with an interferometric force feedback microphone, and an optical fiber displacement transducer that detects changes in leaf thickness in relation to leaf-water potential.

Natural caprine whey oligosaccharides separated by membrane technology and profile evaluation by capillary electrophoresis

The functional food market is growing rapidly and membrane processing offers several advantages over conventional methods for separation, fractionation and recovery of bioactive components. The aim of the present study was to select a process that could be implemented easily on an industrial scale for the isolation of natural lactose-derived oligosaccharides (OS) from caprine whey, enabling the development of functional foods for clinical and infant nutrition. The most efficient process was the combination of a pre-treatment to eliminate proteins and fat, using an ultrafiltration (UF) membrane of 25 kDa molecular weight cut off (MWCO), followed by a tighter UF membrane with 1 kDa MWCO. Circa 90% of the carbohydrates recovered in the final retentate were OS. Capillary electrophoresis was used to evaluate the OS profile in this retentate. The combined membrane-processing system is thus a promising technique for obtaining natural concentrated OS from whey. Powered