Cassava starch snack formulation using functional shell fish by‐products: mechanical,sorption and geometric properties

Utilisation of by‐products of the shrimp industry, namely shrimp head protein and chitosan, could lead to a functional snack with substantial market in Asia. Produced on a cassava starch base this would lead to a product with shrimp flavour and chitosan's lipid adsorption capacity. The characteristics of such a mixture with 82% deacetylated chitosan and salt was investigated by Rapid Visco Analyser and instrumental Texture Profile Analyser using the Doehlert Uniform Shell experimental design. Polynomial models explained more than 88% of variability of responses. A significant effect of salt, shrimp head proteins and chitosan was observed on cassava starch gelling characteristics. A corresponding heat and shear stress resistance ability was observed while there was a reduction in its specific swelling power. Snacks prepared in the form of chips and extruded product confirmed their good potential for added value to snack foods in respect of their 90–94% linear expansion ratio, up to 1.1 kg maximum breaking force and up to 4.5 radial expansion ratio. Adsorption isotherm of extrudates had a maximum water content target of 115 g kg^?1 dry matter at 25 °C for a later formulation and extrusion optimisation, in order to guarantee consumer texture acceptability. Corresponding shelf‐lives of extrudates were calculated at three storage conditions. Copyright © 2005 Society of Chemical Industry     

Modeling of current-voltage characteristics of thin film solar cells

An analytical model is developed to study the current-voltage characteristics of thin film solar cells by incorporating exponential photon absorption, carrier trapping and carrier drift in the absorber layer. An analytical expression for the external voltage dependent photocurrent is derived by solving the continuity equation for both electrons and holes assuming the electric field remains uniform in the absorber layer. The analytical results are verified with the numerical self-consistent solution of the steady-state continuity equations and the Poisson’s equation. The overall load current is calculated considering the actual solar spectrum. It is found that the solar cell efficiency critically depends on the transport properties of the carriers that drift towards the bottom contact. The recombination current dominates over the ideal diode current in CdTe based solar cells. The theoretical model is fitted with the published experimental data on various thin film solar cells and shows a very good agreement.     

Gold nanoparticle induces masking of amines and some therapeutic implications

Citrate capped gold nanoparticles (GNP) are effective in masking protein amines. The extent of such masking is quantified using Fourier Transform Infra Red (FTIR) spectroscopy. A strong correlation is shown to exist between a shift of amide-II peak intensity (1600-1500 cm(-1)) caused by GNP and the number of exposed amines in a given protein. The result is validated using eight different proteins. The expected out-come of such masking is inhibition of interaction between any external ligand and such amines. The prediction is validated using a simple non-enzymatic glycation of clinically important protein like crystallin.     

Analyzing the stability of a failing rock slope for suggesting suitable mitigation measure: a case study from the Theng rockslide,Sikkim Himalayas,India

At km 87.20 near Theng on the North Sikkim Highway, India, severe rock falls and slides in recent years rendered 180 m stretch of this important road corridor in the Sikkim Himalayas risky and vulnerable to the commuters. The rockslide at Theng has, thus, been studied in detail at 24 discrete locations using the ground-based topographic, lithologic and structural data with an objective to evaluate the mechanisms of rock sliding for suggesting the most effective mitigation measure. In this study, large scale geological mapping and site-specific kinematic analyses in different spatial domains corroborated that within this 180 m stretch, despite having a competent lithology (quartzo feldspathic gneiss and quartzites), the possibility of both plane and wedge failures are high because of gentler and unfavourably oriented planar discontinuities with respect to the available steep topography. The rock slope failure analysis both at discrete locations and in a distributed manner in a Geographic Information System further revealed that unfavourable geometric disposition of discontinuities at Theng rendered multiple modes of failure at critical locations, which is also corroborated by a very low Slope Mass Rating value (4.0) determined in this area, thus, making it difficult to suggest any cost-effective surface protection measure. However, analysis suggests slope dressing or re-excavation to contain future rock sliding in such cases, but the same appears to be difficult to implement on the ground because of unfavourable kinematic conditions of the vulnerable rock discontinuities. Accordingly, after evaluating the site conditions in detail, a short road tunnel with its probable tunnel rockmass conditions is proposed to bypass this active rock sliding stretch.     

Parallel processing in dynamic simulation of power systems

The dynamic behaviour of a large interconnected electric power system is characterized by a simultaneous set of nonlinear algebraic and ordinary differential equations. The solution is obtained by numerical methods and the simulation of the transient behaviour for a few seconds after a fault is the standard analytical procedure used in planning and operational studies of the system. The need for on-line simulation in near real time for more efficient operation has encouraged the search for faster solution methods and the use of parallel computers for this purpose has attracted the attention of many researchers. The success of parallelization depends on three factors: the problem structure, the computer architecture, and the algorithm that takes maximum advantage of both. In this problem, the generator equations are only coupled through the electrical network providing some parallelization in (variable) space, and a solution is needed at each time step leading to some parallelization in time (waveform relaxation). However, since the problem formulation is not completely decoupled, parallel algorithms can only be developed by trading off any relaxation with a degradation in convergence. The fastest sequential algorithm used today is the combination of implicit trapezoidal integration with a dishonest Newton solution. The Newton algorithm is not parallel at all but has the fastest convergence while a Gauss-Jacobi algorithm is completely parallel but converges very slowly. A relaxation of the Newton algorithm appears to be a good compromise. As for the parallel hardware, the coupling seems to require significant communication between processors thus favouring a data-sharing architecture over a message-passing hypercube. Special architectures to match the problem structure have also been an area of investigation. This paper elaborates on the above issues and assesses the present state-of-the-art.     

A mathematical model of single roll strip caster based on macroscopic enthalpy balances

A mathematical model, based on the overall heat balance and the growth of solidification front, has been formulated to describe the single-roll strip-casting process for steel. The model provides useful interrelationships between the rate of growth of solidifying strip and the principal process variables such as the speed of rotation of caster drum, the system geometry, the superheat of melt and the relevant heat transfer coefficients. Using these relationships it has been possible to predict the effect of process parameters on the process performance in terms of the final strip thickness and the casting rate.     

Reliability of a cascade system with normal stress and exponential strength

In this paper we study the reliability of an N-cascade system whose stress and strength follow normal and exponential distributions, respectively. In this system we can observe that reliability increases for lower values of strength parameter (λ) and stress parameter (μ). Marginal reliability rate also increases at higher values of λ. Hence we conclude that the addition of components by a cascade system gives a significant improvement.     

Automated screening of congestive heart failure using variational mode decomposition and texture features extracted from ultrasound images

Heart is an important and hardest working muscular organ of the human body. Inability of the heart to restore normal perfusion to the entire body refers to cardiac failure, which then with symptoms results in manifestation of congestive heart failure (CHF). Impairment in systolic function associated with chronic dilation of left ventricle is referred as dilated cardiomyopathy (DCM). The clinical examination, surface electrocardiogram (ECG), chest X-ray, blood markers and echocardiography play major role in the diagnosis of CHF. Though the ECG manifests chamber enlargement changes, it does not possess sensitive marker for the diagnosis of DCM, whereas echocardiographic assessment can effectively reveal the presence of asymptomatic DCM. This work proposes an automated screening method for classifying normal and CHF echocardiographic images affected due to DCM using variational mode decomposition technique. The texture features are extracted from variational mode decomposed image. These features are selected using particle swarm optimization and classified using support vector machine classifier with different kernel functions. We have validated our experiment using 300 four-chamber echocardiography images (150: normal, 150: CHF) obtained from 50 normal and 50 CHF patients. Our proposed approach yielded maximum average accuracy, sensitivity and specificity of 99.33%, 98.66% and 100%, respectively, using ten features. Thus, the developed diagnosis system can effectively detect CHF in its early stage using ultrasound images and aid the clinicians in their diagnosis.

     

Study of the potential of alternative crops by integration of multisource data using a neuro‐fuzzy technique

This work proposes a neuro‐fuzzy method for suggesting alternative crop production over a region using integrated data obtained from land‐survey maps as well as satellite imagery. The methodology proposed here uses an artificial neural network (multilayer perceptron, MLP) to predict alternative crop production. For each pixel, the MLP takes vector input comprising elevation, rainfall and goodness values of different existing crops. The first two components of the aforementioned input, that is, elevation and rainfall, are determined from contour information of land‐survey maps. The other components, such as goodness values of different existing crops, are based on the productivity estimates of soil determined by fuzzyfication and expert opinion (on soil) along with production quality by the Normalized Difference Vegetation Index (NDVI) obtained from satellite imagery. The methodology attempts to ensure that the suggested crop will also be a high productivity crop for that region.