Structural modifications in bivoltine silk fiber under thermal treatment

The microstructural changes of semicrystalline bivoltine silk fibers annealed between 27 to 260°C were measured using positron annihilation lifetime spectroscopy (PALS). Measured lifetime and intensity as a function of temperature reveals the removal of water molecules until 60°C. Present results indicate a T_g of 140°C, which is further confirmed by differential scanning calorimetry (DSC). The structural changes like random-coil to alpha and then to beta form are observed in the crystalline and amorphous domains at 100 and 205°C, respectively. Degradation of the fibers occur around 240°C. As an extension of the present measurements, we have estimated the activation energy of 8.0 KJ/mol in the disordered domain of the fiber, based on Goldanskii's kinetic relations. © 1997 John Wiley & Sons, Inc.     

Novel statistical method for data drift detection in satellite telemetry

Autonomy is becoming a prime requirement for satellite mission control operations. Data-driven methods like Machine Learning models are playing a key role in bringing in autonomy. Health keeping data from satellite telemetry is a key ingredient in these data-driven methods. In real-world satellite operations, the health-keeping telemetry data gradually drifts due to adverse space weather effects and wear and tear of electronic and mechanical components. The key question that arises is how to detect and quantify the data drift which is generally a gradual phenomenon. This paper discusses a novel statistical method for detecting data drift occurring in satellite telemetry. For the purpose of experimental work in this paper, an actual telemetry data set of the BUS CURRENT sensor which is part of the Electrical Power System of a Low Earth Orbit Satellite was considered. Data drift detection test was carried out using this sensor data using the developed novel statistical method and with Kolmogorov Smirnov test which is a probabilistic method. Both results are analysed and compared. Thereafter novel statical method was used to check its efficacy using a synthetic data set with induced drift.     

Development of robust calibration models using support vector machines for spectroscopic monitoring of blood glucose

Sample-to-sample variability has proven to be a major challenge in achieving calibration transfer in quantitative biological Raman spectroscopy. Multiple morphological and optical parameters, such as tissue absorption and scattering, physiological glucose dynamics and skin heterogeneity, vary significantly in a human population introducing nonanalyte specific features into the calibration model. In this paper, we show that fluctuations of such parameters in human subjects introduce curved (nonlinear) effects in the relationship between the concentrations of the analyte of interest and the mixture Raman spectra. To account for these curved effects, we propose the use of support vector machines (SVM) as a nonlinear regression method over conventional linear regression techniques such as partial least-squares (PLS). Using transcutaneous blood glucose detection as an example, we demonstrate that application of SVM enables a significant improvement (at least 30%) in cross-validation accuracy over PLS when measurements from multiple human volunteers are employed in the calibration set. Furthermore, using physical tissue models with randomized analyte concentrations and varying turbidities, we show that the fluctuations in turbidity alone causes curved effects which can only be adequately modeled using nonlinear regression techniques. The enhanced levels of accuracy obtained with the SVM based calibration models opens up avenues for prospective prediction in humans and thus for clinical translation of the technology.     

Multivariate Adaptive Regression Splines Model to Predict Fracture Characteristics of High Strength and Ultra High Strength Concrete Beams

This paper presents Multivariate Adaptive Regression Splines (MARS) model to predict the fracture characteristics of high strength and ultra high strength concrete beams. Fracture characteristics include fracture energy (GF), critical stress intensity factor (KIC) and critical crack tip opening displacement (CTODc). This paper also presents the details of development of MARS model to predict failure load (Pmax) of high strength concrete (HSC) and ultra high strength concrete (UHSC) beam specimens. Characterization of mix and testing of beams of high strength and ultra strength concrete have been described. Methodologies for evaluation of fracture energy, critical stress intensity factor and critical crack tip opening displacement have been outlined. MARS model has been developed by establishing a relationship between a set of predicators and dependent variables. MARS is based on a divide and conquers strategy partitioning the training data sets into separate regions; each gets its own regression line. Four MARS models have been developed by using MATLAB software for training and prediction of fracture parameters and failure load.MARS has been trained with about 70% of the total 87 data sets and tested with about 30% of the total data sets. It is observed from the studies that the predicted values of Pmax, GF, KIC and CTODC are in good agreement with those of the experimental values.     

Bulk scale production of carbon nanofibers in an economical way

An economical route for the scalable production of carbon nanofibers (CNFs) on a sodium chloride support has been developed. CNFs have been synthesized by chemical vapor deposition (CVD) method by using metal formate as catalyst precursors at 680°C. Products were characterized by SEM, TEM, Raman spectroscopy and XRD method. By thermal analysis, the purity of the as grown products and purified products were determined. This method avoids calcination and reduction process which was employed in commercial catalysts such as metal oxide or nitrate. The problems such as detrimental effect, environmental and even cost have been overcome by using sodium chloride as support. The yield of CNFs up to 7800 wt.% relative to the nickel catalyst has been achieved in the growth time of 15 min. The advantage of this synthesis technique is the simplicity and use of easily available low cost precursors.     

Targeting Efficiency and Biodistribution of Zoledronate Conjugated Docetaxel Loaded Pegylated PBCA Nanoparticles for Bone Metastasis

In an attempt to improve tumor localization of docetaxel (DTX)‐loaded nanoparticles (NPs), zoledronic acid (ZOL) is used as a ligand to target bone metastasis. DTX‐loaded ZOL‐conjugated polyethylene glycol (PEG)ylated polybutyl cyanoacrylate (PBCA) NPs are prepared using an anionic polymerization technique. PBCA‐PEG‐ZOL NPs are subjected to cytotoxic assay in both BO2 and MCF‐7 cell lines. Cell cycle arrest and apoptosis induced by the PBCA‐PEG‐ZOL NPs are studied. Quantitative cellular uptake, NP uptake route characterization, confocal microscopy and IPP/ApppI levels are performed. PBCA‐PEG‐ZOL NPs show an enhanced cytotoxic effect in both BO2 as well as MCF‐7 cell lines due to higher uptake following ZOL‐mediated endocytosis. The molecular basis of apoptosis reveals the involvement of a cytoplasmic protein in activating the programmed cell death pathway. Route characterization studies reveal that PBCA‐PEG‐ZOL NPs uptake is not completely blocked even by using both inhibitors (genistein and phenyl arsinoxide) simultaneously, conferring that uptake is not entirely based upon clathrin or caveolae. PBCA‐PEG‐ZOL NPs showed 7 and 5.3 times increase in IPP and ApppI production, in comparison to ZOL treatment, and 138 times higher than the control group in MCF‐7 cell line. In BO2 cell line, after treatment with NPs, IPP was 5.35 times higher than ZOL solution. No ApppI in BO2 cell line after treatment with NPs and ZOL solution was found. NP distribution in tumor infected bone is also significantly high in comparison to the normal bone at any time point. It is concluded that ZOL‐conjugated NPs provide an efficient and targeted delivery of DTX, with synergistic effects. Thus, these NPs present a promising treatment in the near future, by actively targeting metastatic tumor.     

Buckling and Postbuckling Behavior of Cross-Ply Composite Plate Subjected to Nonuniform In-Plane Loads

This paper presents a study of buckling and postbuckling behaviour of simply supported composite plates subjected to nonuniform in-plane loading. The mathematical model is based on higher order shear deformation theory incorporating von Kármán nonlinear strain displacement relations. Because the applied in-plane edge load is nonuniform, in the first step the plane elasticity problem is solved to evaluate the stress distribution within the prebuckling range. Using these stress distributions, the governing equations for postbuckling analysis of composite plates are obtained through the theorem of minimum potential energy. Adopting Galerkin’s approximation, the governing nonlinear partial differential equations are reduced into a set of nonlinear algebraic equations in the case of postbuckling analysis, and homogeneous linear algebraic equations in the case of buckling analysis. The critical buckling load is obtained from the solution of associated linear eigenvalue problem. Postbuckling equilibrium paths are obtained by solving nonlinear algebraic equations employing the Newton-Raphson iterative scheme. Explicit expressions for the plate in-plane stress distributions within the prebuckling range are reported for isotropic and composite plates subjected to parabolic in-plane edge loading. Buckling loads are determined for three plate aspect ratios (a/b = 0.5, 1, 1.5) and three different types of in-plane load distributions. The effect of shear deformation on the buckling loads of composite plate is reported. The present buckling results are compared with previously published results wherever possible.     

Flux pattern and fouling of membranes during ultrafiltration of some dairy products

The flux pattern of milk (whole milk, skimmed milk and buttermilk) showed a distinct contrast to whey (sweet whey and acid casein whey) systems during ultrafiltration (UF) at constant composition. For milk systems, the initial flux was lower than for whey systems, but the flux stabilised within a few minutes of operation. However, for both acid and sweet whey, the flux continued to fall with time for nearly 1 h. The fouling coefficient (FC) for buttermilk was 0.6 after 5 min, rising to 0.68 after 60 min. During this time flux did not decline, suggesting that concentration polarisation (CP), rather than fouling, was controlling the flux rate. In contrast, the FC for whey was 0.5 after 5 min with a progressive rise over the next 55 min, but the flux also fell throughout this period suggesting that flux was controlled by fouling rather than CP. The higher concentration of protein in milk systems appeared to be responsible for CP, rather than fouling, being the controlling mechanism.     

Quercetin alleviates activities of intestinal and renal disaccharidases in streptozotocin-induced diabetic rats

Specific activities of both intestinal and renal dissacharidases, such as sucrase, maltase, and lactase, were altered in diabetic rats. Our study was focused to evaluate the effect of feeding quercetin - a bioflavanoid on intestinal and renal dissacharidases in streptozotocin-induced diabetic rats. The rats were fed with 0.1% quercetin in diet. A reduction in intestinal maltase and sucrase, activities in quercetin-fed diabetic rats was observed in contrast to the increased activities in the starch-fed diabetic rats. A significant amelioration in renal dissacharidase activities in quercetin-fed diabetic rats was observed when compared to decreased activity in starch-fed diabetic rats.     

RIEP: Regional integrated energy plan

The energy planning endeavours for a particular region involves the finding of a set of sources and conversion devices so as to meet the energy requirement/demand of all the tasks in an optimal manner. This optimality depends on the objective to minimise the total annual cost of energy and the dependence on non-local resources or maximise the overall system efficiency. Factors such as availability of resources in the region and task energy requirements impose constraints on the regional energy planning exercise. Thus, regional energy planning turns out to be a constrained optimisation problem. This paper describes an optimum energy allocation using integrated energy planning approaches for Uttara Kannada district and makes a satisfying energy allocation plan for the years 2005, 2010 and 2015. Integrated energy planning gives an optimal mix of new/conventional energy sources and is developed based on decision support systems (DSS) approach.The central theme of the energy planning at decentralised level would be to prepare regional energy plans to meet energy needs and development of alternate energy sources at least- cost to the economy and environment. Regional integrated energy planning (RIEP) mechanism takes into account various available resources and demands in a region. This implies that the assessment of the demand supply and its intervention in the energy system, which may appear desirable due to such exercises, must be at a similar geographic scale. Regional energy planning exercises need to be flexible (to cope with rapidly changing energy systems) and easy to use. The application of DSS is a new approach to this problem. Towards the goal of implementing analytical methods for integrated planning, computerised decision-system provides useful assistance in the analyses of available information, the projection of future conditions, and the evaluation of alternative scenarios. Some of the features of DSS found particularly useful in regional energy planning are: (i) flexible structure—allows appropriate feasible levels of disaggregation, (ii) integrated nature—promotes a better overall understanding of many processes and concepts involved in planning, allowing planners to concentrate on specific energy subsectors, and (iii) iterative nature and easy scenario testing features—provide guidance in optimising data collection activities. Regional integrated energy plan (RIEP) is a computer-assisted accounting and simulation tool being developed to assist policy makers and planners at district and state level in evaluating energy policies and develop ecologically sound, sustainable energy plans. Energy availability and demand situation are projected for various scenarios (base case scenario, high-energy intensity, and transformation, state-growth scenarios) in order to get a glimpse of future patterns and assess the likely impacts of energy policies.The application of DSS for Uttara Kananda district energy planning focuses on renewable resources that could be harnessed for energy, land use database, sectorwise energy demand database and optimal allocation of energy resources for various tasks, and then explore the energy use consequences of alternative scenarios, such as, base case scenarios, high-energy intensity and improved end use efficiency options. Linear programming formulation for optimum allocation based on the cost minimisation objective shows that there is substantial savings of about 19.19% in energy and 36.24% cost reduction in overall energy system. Cost per unit (kWh) of energy with optimal allocation of energy is Rs. 0.31/kWh (as against Rs. 0.39/kWh without optimisation). Optimisation carried out with the objective of maximisation of efficiency of ‘ijk’ combination for all combinations shows energy saving of 19.98% and cost of energy as Rs. 0.34/kWh. The scenario analyses reveal that relatively vigorous growth in energy demand in Uttara Kannada district can be accomplished without exceeding available resources.