A broad pore size distribution mesoporous SnO2 as anode for lithium-ion batteries

We demonstrate here that mesoporous tin dioxide (abbreviated M-SnO2) with a broad pore size distribution can be a prospective anode in lithium-ion batteries. M-SnO2 with pore size ranging between 2 and 7.5 nm was synthesized using a hydrothermal procedure involving two different surfactants of slightly different sizes, and characterized. The irreversible capacity loss that occurs during the first discharge and charge cycle is 890 mAh g(-1), which is smaller than the 1,010-mAh g(-1) loss recorded for mesoporous SnO2 (abbreviated S-SnO2) synthesized using a single surfactant. After 50 cycles, the discharge capacity of M-SnO2 (504 mAh g(-1)) is higher than that of S-SnO2 (401 mAh g(-1)) and solid nanoparticles of SnO2 (abbreviated nano-SnO2 < 4 mAh g(-1)) and nano-SnO2. Transmission electron microscopy revealed higher disorder in the pore arrangement in M-SnO2. This, in turn imparts lower stiffness to M-SnO2 (elastic modulus, E (R) a parts per thousand aEuro parts per thousand 14.5 GPa) vis-a-vis S-SnO2 (E (R) a parts per thousand aEuro parts per thousand 20.5 GPa), as obtained using the nanoindentation technique. Thus, the superior battery performance of M-SnO2 is attributed to its intrinsic material mechanical property. The fluidity of the internal microstructure of M-SnO2 resulted in a lower degree of aggregation of Sn particles compared to S-SnO2 and nano-SnO2 structural stabilization and long-term cyclability.

MPI-based parallel synchronous vector evaluated particle swarm optimization for multi-objective design optimization of composite structures

This paper presents a decentralized/peer-to-peer architecture-based parallel version of the vector evaluated particle swarm optimization (VEPSO) algorithm for multi-objective design optimization of laminated composite plates using message passing interface (MPI). The design optimization of laminated composite plates being a combinatorially explosive constrained non-linear optimization problem (CNOP), with many design variables and a vast solution space, warrants the use of non-parametric and heuristic optimization algorithms like PSO. Optimization requires minimizing both the weight and cost of these composite plates, simultaneously, which renders the problem multi-objective. Hence VEPSO, a multi-objective variant of the PSO algorithm, is used. Despite the use of such a heuristic, the application problem, being computationally intensive, suffers from long execution times due to sequential computation. Hence, a parallel version of the PSO algorithm for the problem has been developed to run on several nodes of an IBM P720 cluster. The proposed parallel algorithm, using MPI's collective communication directives, establishes a peer-to-peer relationship between the constituent parallel processes, deviating from the more common master-slave approach, in achieving reduction of computation time by factor of up to 10. Finally we show the effectiveness of the proposed parallel algorithm by comparing it with a serial implementation of VEPSO and a parallel implementation of the vector evaluated genetic algorithm (VEGA) for the same design problem. (c) 2012 Elsevier Ltd. All rights reserved.

How Does the Spacer Length of Cationic Gemini Lipids Influence the Lipoplex Formation with Plasmid DNA? Physicochemical and Biochemical Characterizations and their Relevance in Gene Therapy

Lipoplexes formed by the pEGFP-C3 plasmid DNA (pDNA) and lipid mixtures containing cationic gemini surfactant of the 1,2-bis(hexadecyl dimethyl ammonium) Acmes family referred to as C16CnC16, where n = 2 3, 5, or 12, and the zwitterionic helper lipid, 1,2-dioleoyl-sn-glycero-3-phosphatidylethanolamine (DOPE) have been studied from a wide variety of physical, chemical, and biological standpoints. The study has been carried out using several experimental methods, such as zeta potential, gel electrophoresis, small-angle X-ray scattering (SAXS), cryo-TEM, gene transfection, cell viability/cytotoxicity, and confocal fluorescence microscopy. As reported recently in a communication (J. Am. Chem. Soc. 2011, 133, 18014), the detailed physicochemical and biological studies confirm that, in the presence of the studied series lipid mixtures, plasmid DNA is compacted with a large number of its associated Na+ counterions. This in turn yields a much lower effective negative charge, q(pDNA)(-), a value that has been experimentally obtained for each mixed lipid mixture. Consequently, the cationic lipid (CL) complexes prepared with pDNA and CL/DOPE mixtures to be used in gene transfection require significantly less amount of CL than the one estimated assuming a value of q(DNA)(-) = -2. This drives to a considerably lower cytotoxicity of the gene vector. Depending on the CL molar composition, alpha, of the lipid mixture, and the effective charge ratio of the lipoplex, rho(eff), the reported SAXS data indicate the presence of two or three structures in the same lipoplex, one in the DOPE-rich region, other in the CL-rich region, and another one present at any CL composition. Cryo-TEM and SAXS studies with C16CnC16/DOPE-pDNA lipoplexes indicate that pDNA is localized between the mixed lipid bilayers of lamellar structures within a monolayer of similar to 2 nm. This is consistent with a highly compacted supercoiled pDNA conformation compared with that of linear DNA. Transfection studies were carried out with HEK293T, HeLa, CHO, U343, and H460 cells. The alpha and rho(eff) values for each lipid mixture were optimized on HEK293T cells for transfection, and using these values, the remaining cells were also transfected in absence (-FBS-FBS) and presence (-FBS+FBS) of serum. The transfection efficiency was higher with the CLs of shorter gemini spacers (n = 2 or 3). Each formulation expressed GFP on pDNA transfection and confocal fluorescence microscopy corroborated the results. C16C2C16/DOPE mixtures were the most efficient toward transfection among all the lipid mixtures and, in presence of serum, even better than the Lipofectamine2000, a commercial transfecting agent Each lipid combination was safe and did not show any significant levels of toxicity. Probably, the presence of two coexisting lamellar structures in lipoplexes synergizes the transfection efficiency of the lipid mixtures which are plentiful in the lipoplexes formed by CLs with short spacer (n = 2, 3) than those with the long spacer (n = 5, 12).

Stability of Adult Emergence and Activity/Rest Rhythms in Fruit Flies Drosophila melanogaster under Semi-Natural Condition

Here we report the results of a study aimed at examining stability of adult emergence and activity/rest rhythms under seminatural conditions (henceforth SN), in four large outbred fruit fly Drosophila melanogaster populations, selected for emergence in a narrow window of time under laboratory (henceforth LAB) light/dark (LD) cycles. When assessed under LAB, selected flies display enhanced stability in terms of higher amplitude, synchrony and accuracy in emergence and activity rhythms compared to controls. The present study was conducted to assess whether such differences in stability between selected and control populations, persist under SN where several gradually changing time-cues are present in their strongest form. The study revealed that under SN, emergence waveform of selected flies was modified, with even more enhanced peak and narrower gate-width compared to those observed in the LAB and compared to control populations in SN. Furthermore, flies from selected populations continued to exhibit enhanced synchrony and accuracy in their emergence and activity rhythms under SN compared to controls. Further analysis of zeitgeber effects revealed that enhanced stability in the rhythmicity of selected flies under SN was primarily due to increased sensitivity to light because emergence and activity rhythms of selected flies were as stable as controls under temperature cycles. These results thus suggest that stability of circadian rhythms in fruit flies D. melanogaster, which evolved as a consequence of selection for emergence in a narrow window of time under weak zeitgeber condition of LAB, persists robustly in the face of day-to-day variations in cycling environmental factors of nature.

Simulation of Influence of Bilayer Melting on Dynamics and Thermodynamics of Interfacial Water

We investigate the effect of bilayer melting transition on thermodynamics and dynamics of interfacial water using molecular dynamics simulation with the two-phase thermodynamic model. We show that the diffusivity of interface water depicts a dynamic crossover at the chain melting transition following an Arrhenius behavior until the transition temperature. The corresponding change in the diffusion coefficient from the bulk to the interface water is comparable with experimental observations found recently for water near 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) vesicles Phys. Chem. Chem. Phys. 13, 7732 (2011)]. The entropy and potential energy of interfacial water show distinct changes at the bilayer melting transition, indicating a strong correlation in the thermodynamic state of water and the accompanying first-order phase transition of the bilayer membrane. DOI: 10.1103/PhysRevLett.110.018303

Smart Network Interface Selection for E-DTNs

We implement two energy models that accurately and comprehensively estimates the system energy cost and communication energy cost for using Bluetooth and Wi-Fi interfaces. The energy models running on a system is used to smartly pick the most energy optimal network interface so that data transfer between two end points is maximized.

An Optimal Fuzzy Logic Controller tuned with Artificial Immune System

In this paper, a method for the tuning the membership functions of a Mamdani type Fuzzy Logic Controller (FLC) using the Clonal Selection Algorithm(CSA) a model of the Artificial Immune System(AIS) paradigm is examined. FLC's are designed for two problems, firstly the linear cart centering problem and secondly the highly nonlinear inverted pendulum problem. The FLC tuned by AIS is compared with FLC tuned by GA. In order to check the robustness of the designed PLC's white noise was added to the system, further, the masses of the cart and the length and mass of the pendulum are changed. The PLC's were also tested in the presence of faulty rules. Finally, Kruskal Wallis test was performed to compare the performance of the GA and AIS. An insight into the algorithms are also given by studying the effect of the important parameters of GA and AIS.

MULTI-OBJECTIVE GENETIC ALGORITHM FOR EFFICIENT POINT MATCHING IN MULTI-SENSOR SATELLITE IMAGE

This paper investigates a new approach for point matching in multi-sensor satellite images. The feature points are matched using multi-objective optimization (angle criterion and distance condition) based on Genetic Algorithm (GA). This optimization process is more efficient as it considers both the angle criterion and distance condition to incorporate multi-objective switching in the fitness function. This optimization process helps in matching three corresponding corner points detected in the reference and sensed image and thereby using the affine transformation, the sensed image is aligned with the reference image. From the results obtained, the performance of the image registration is evaluated and it is concluded that the proposed approach is efficient.

Quasi-based hierarchical clustering for land cover mapping using satellite images

This paper presents an improved hierarchical clustering algorithm for land cover mapping problem using quasi-random distribution. Initially, Niche Particle Swarm Optimization (NPSO) with pseudo/quasi-random distribution is used for splitting the data into number of cluster centers by satisfying Bayesian Information Criteria (BIC). Themain objective is to search and locate the best possible number of cluster and its centers. NPSO which highly depends on the initial distribution of particles in search space is not been exploited to its full potential. In this study, we have compared more uniformly distributed quasi-random with pseudo-random distribution with NPSO for splitting data set. Here to generate quasi-random distribution, Faure method has been used. Performance of previously proposed methods namely K-means, Mean Shift Clustering (MSC) and NPSO with pseudo-random is compared with the proposed approach - NPSO with quasi distribution(Faure). These algorithms are used on synthetic data set and multi-spectral satellite image (Landsat 7 thematic mapper). From the result obtained we conclude that use of quasi-random sequence with NPSO for hierarchical clustering algorithm results in a more accurate data classification.

Clustering using Levy Flight Cuckoo Search

In this paper, a comparative study is carried using three nature-inspired algorithms namely Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Cuckoo Search (CS) on clustering problem. Cuckoo search is used with levy flight. The heavy-tail property of levy flight is exploited here. These algorithms are used on three standard benchmark datasets and one real-time multi-spectral satellite dataset. The results are tabulated and analysed using various techniques. Finally we conclude that under the given set of parameters, cuckoo search works efficiently for majority of the dataset and levy flight plays an important role.

Spectral-spatial MODIS image analysis using swarm intelligence algorithms and region based segmentation for flood assessment

This paper discusses an approach for river mapping and flood evaluation based on multi-temporal time-series analysis of satellite images utilizing pixel spectral information for image clustering and region based segmentation for extracting water covered regions. MODIS satellite images are analyzed at two stages: before flood and during flood. Multi-temporal MODIS images are processed in two steps. In the first step, clustering algorithms such as Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are used to distinguish the water regions from the non-water based on spectral information. These algorithms are chosen since they are quite efficient in solving multi-modal optimization problems. These classified images are then segmented using spatial features of the water region to extract the river. From the results obtained, we evaluate the performance of the methods and conclude that incorporating region based image segmentation along with clustering algorithms provides accurate and reliable approach for the extraction of water covered region.

Automatic road extraction using high resolution satellite images based on Level Set and Mean Shift methods

Analysis of high resolution satellite images has been an important research topic for urban analysis. One of the important features of urban areas in urban analysis is the automatic road network extraction. Two approaches for road extraction based on Level Set and Mean Shift methods are proposed. From an original image it is difficult and computationally expensive to extract roads due to presences of other road-like features with straight edges. The image is preprocessed to improve the tolerance by reducing the noise (the buildings, parking lots, vegetation regions and other open spaces) and roads are first extracted as elongated regions, nonlinear noise segments are removed using a median filter (based on the fact that road networks constitute large number of small linear structures). Then road extraction is performed using Level Set and Mean Shift method. Finally the accuracy for the road extracted images is evaluated based on quality measures. The 1m resolution IKONOS data has been used for the experiment.

Multi-objective optimization of satellite image registration using discrete Pparticle swarm optimisation

A new multi-sensor image registration technique is proposed based on detecting the feature corner points using modified Harris Corner Detector (HDC). These feature points are matched using multi-objective optimization (distance condition and angle criterion) based on Discrete Particle Swarm Optimization (DPSO). This optimization process is more efficient as it considers both the distance and angle criteria to incorporate multi-objective switching in the fitness function. This optimization process helps in picking up three corresponding corner points detected in the sensed and base image and thereby using the affine transformation, the sensed image is aligned with the base image. Further, the results show that the new approach can provide a new dimension in solving multi-sensor image registration problems. From the obtained results, the performance of image registration is evaluated and is concluded that the proposed approach is efficient.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Self catalytic growth of SnO2 branched nanowires by thermal evaporation

For the first time, Tin oxide (SnO2) multiple branched nanowires (NWs) have been synthesized by thermal evaporation of tin (Sn) in presence of oxygen without use of metal catalysts at low substrate temperature of 500 degrees C. Synthesized product consists of multiple branched nanowires and were single crystalline in nature. Each of the nanowire capped with catalyst particle at their ends. Energy dispersive X-ray analysis on the nanowires and capped nanoparticle confirms that Sn act as catalyst for SnO2 nanowires growth. A self catalytic vapor-liquid-solid (VLS) growth mechanism was proposed to describe the SnO2 nanowires growth. (C) 2012 Elsevier B.V. All rights reserved.