Reconstructing the free-energy landscape of Met-enkephalin using dihedral Principal Component Analysis and Well-tempered Metadynamics

Well-Tempered Metadynamics (WTmetaD) is an efficient method to enhance the reconstruction of the free-energy surface of proteins. WTmetaD guarantees a faster convergence in the long time limit in comparison with the standard metadynamics. It still suffers however from the same limitation, i.e. the non trivial choice of pertinent collective variables (CVs). To circumvent this problem, we couple WTmetaD with a set of CVs generated from a dihedral Principal Component Analysis (dPCA) on the Ramachadran dihedral angles describing the backbone structure of the protein. The dPCA provides a generic method to extract relevant CVs built from internal coordinates. We illustrate the robustness of this method in the case of the small and very diffusive Metenkephalin pentapeptide, and highlight a criterion to limit the number of CVs necessary to biased the metadynamics simulation. The free-energy landscape (FEL) of Met-enkephalin built on CVs generated from dPCA is found rugged compared with the FEL built on CVs extracted from PCA of the Cartesian coordinates of the atoms.Comment: 17 pages, 9 figures (4 in color

Two Energy Efficient Algorithms for Tracking Objects in a Sensor Network

We propose two energy efficient algorithms for locating a target object moving in an area covered by a wireless ad hoc network. The first algorithm developed conserve energy by efficiently identifying sensor nodes, as Home Nodes, and use only local messages between neighboring nodes to follow the trail of the object. Since we avoid the long-range transmission and maximize the localization, the algorithms reduce the communication cost. The dynamic nature of the second algorithm exploits the predefined parameters such as the object velocity. Our algorithm represents query shipping against the conventional data shipping as a means to reduce the amount of data being shipped across the network. Hence, it locates the objects over the network with minimal energy conservation using short-range message transmissions. The performance analysis (both experimental and theoretical) shows the effectiveness of the two algorithms in comparison to another tracking algorithm

EFFECTS OF SUBLETHAL COPPER EXPOSURE ON NUCLEIC ACID LEVELS IN FISH, OREOCHROMIS MOSSAMBICUS (PETERS)

ndustries are the major sources of heavy metal pollution and it is released into water and soil. Heavy metals cause several ill effects to aquatic organisms and environment. In the present study, Fishes were exposed to sub lethal concentrations (1/16, 1/12, 1/8 and 1/4th of 96 h LC50 value) i.e. 3mg/L, 4mg/L, 6mg/L and 12mg/L of Copper Sulphate for four different exposure durations of 10, 20, 30 and 40 days. The Nucleic acids (RNA and DNA) in different tissues such as Muscle, Liver, Gills and Kidney of Copper Sulphate (CuSO4) exposed fish, Oreochromis mossambicus has been studied. Decreased tendency was observed in RNA and an insignificant change was observed in DNA levels in all the vital tissues of fish exposed to Copper Sulphate over control. RNA content was gradually decreased with increased exposure period and the decrease was observed to be directly proportional to increased sublethal concentrations. DNA levels decreased higher concentration (12mg/L) and higher duration (40 days)

A Novel Multi-Symbol Curve Fit based CABAC Framework for Hybrid Video Codec's with Improved Coding Efficiency and Throughput

Video compression is an essential component of present-day applications and a decisive factor between the success or failure of a business model. There is an ever increasing demand to transmit larger number of superior-quality video channels into the available transmission bandwidth. Consumers are increasingly discerning about the quality and performance of video-based products and there is therefore a strong incentive for continuous improvement in video coding technology for companies to have market edge over its competitors. Even though processor speeds and network bandwidths continue to increase, a better video compression results in a more competitive product. This drive to improve video compression technology has led to a revolution in the last decade. In this thesis we addresses some of these data compression problems in a practical multimedia system that employ Hybrid video coding schemes. Typically Real life video signals show non-stationary statistical behavior. The statistics of these signals largely depend on the video content and the acquisition process. Hybrid video coding schemes like H264/AVC exploits some of the non-stationary characteristics but certainly not all of it. Moreover, higher order statistical dependencies on a syntax element level are mostly neglected in existing video coding schemes. Designing a video coding scheme for a video coder by taking into consideration these typically observed statistical properties, however, offers room for significant improvements in coding efficiency.In this thesis work a new frequency domain curve-fitting compression framework is proposed as an extension to H264 Context Adaptive Binary Arithmetic Coder (CABAC) that achieves better compression efficiency at reduced complexity. The proposed Curve-Fitting extension to H264 CABAC, henceforth called as CF-CABAC, is modularly designed to conveniently fit into existing block based H264 Hybrid video Entropy coding algorithms. Traditionally there have been many proposals in the literature to fuse surfaces/curve fitting with Block-based, Region based, Training-based (VQ, fractals) compression algorithms primarily to exploiting pixel- domain redundancies. Though the compression efficiency of these are expectantly better than DCT transform based compression, but their main drawback is the high computational demand which make the former techniques non-competitive for real-time applications over the latter. The curve fitting techniques proposed so far have been on the pixel domain. The video characteristic on the pixel domain are highly non-stationary making curve fitting techniques not very efficient in terms of video quality, compression ratio and complexity. In this thesis, we explore using curve fitting techniques to Quantized frequency domain coefficients. we fuse this powerful technique to H264 CABAC Entropy coding. Based on some predictable characteristics of Quantized DCT coefficients, a computationally in-expensive curve fitting technique is explored that fits into the existing H264 CABAC framework. Also Due to the lossy nature of video compression and the strong demand for bandwidth and computation resources in a multimedia system, one of the key design issues for video coding is to optimize trade-off among quality (distortion) vs compression (rate) vs complexity. This thesis also briefly studies the existing rate distortion (RD) optimization approaches proposed to video coding for exploring the best RD performance of a video codec. Further, we propose a graph based algorithm for Rate-distortion. optimization of quantized coefficient indices for the proposed CF-CABAC entropy coding

Comparative Study of Phenol Biodegradation of Phenol by Free and Immobilized Cells

The objective of this project work is comparative study of the biodegradation of phenol by bacterial strain isolated from Petroleum Contaminated Soil sample and immobilized on commercial activated carbon by simultaneous adsorption and biodegradation. Biodegradation is one of the cheapest methods without any production of hazardous by-products. The biodegradation study of phenol is carried out in MSM broth where phenol is provided as a source of carbon and energy. The effect of temperature, pH and phenol concentration on the rate of phenol biodegradation by a particular strain is carried out. Activated carbons are the most broadly utilized adsorbents because of their incredible adsorption capacities for organic pollutants. The cells are immobilized on activated carbon and the effect of temperature, pH and phenol concentration on the rate of phenol biodegradation by immobilized cells is carried out. Observations uncovered that the rate of phenol biodegradation is essentially influenced by pH, temperature of incubation and phenol concentration and immobilized cells are more effective than free cells

Mechanisms of Antibody-based defense against Pneumocystis

Pneumocystis (PC) pneumonia is a life-threatening opportunistic fungal infection observed in individuals with severe immunodeficiencies, such as AIDS. This dissertation evaluates functions of antibodies and conserved fungal cell wall carbohydrate antigens in host defense against PC. We demonstrate that a novel recombinant protein consisting of the extracellular domain of the beta-glucan receptor dectin-1 fused to the constant portion of murine IgG1, binds beta-glucan and recognizes Fc-γ receptors; and functionally, impairs growth of PC in the lungs of immunocompromised mice. As an antibody-like molecule targeting a conserved fungal cell wall carbohydrate enhanced host defense against PC, we questioned whether the host produces similar antibodies. We identified natural IgM antibodies, conserved across species and not requiring microbial stimulation for production, that recognize fungal cell wall carbohydrates beta-glucan and chitosan/chitin. In mice, naïve serum containing natural antibodies impairs the growth of PC organisms in the lungs at intermediate stages of infection, while at earliest stages limits pulmonary neutrophil recruitment. Mice unable to secrete IgM, sIgM(-/-), manifest similar impairments in pathogen clearance at intermediate stages of infection. Additionally, sIgM(-/-) mice demonstrate diminished trafficking of fungal cell wall carbohydrate antigen by CD11c+ cells to draining lymph nodes, impaired production of Th2 and Th17 cytokines in lymph nodes after PC challenge, and altered adaptive antibody responses, with diminished anti-PC IgG1 (Th2 associated) while enhanced IgG2a (Th1 associated) adaptive antibody responses. Thus, sIgM, of which a significant component is natural antibody, influences PC Ag presentation at earliest stages of infection, enhancing host defense and biasing the host towards Th2 adaptive responses. Additionaly, we observe that beta-glucan and chitosan/chitin are targets of induced antibody responses. PC challenge leads to the induction of specific serum IgG, and increased quantities of multiple isotypes at the lung mucosa against these carbohydrates. Mucosal responses against beta-glucan and chitosan/chitin after PC challenge are regulated by CD4+ T cells, and we provide evidence that functional memory B cell responses against fungal wall carbohydrates are generated as a consequence of PC challenge. Collectively, these studies demonstrate the importance of conserved fungal cell wall carbohydrate antigens, and primitive antibody isotypes, in host defense responses against PC

Locating Moving Objects over Mobile Sensor Network

The purpose of our on going research would be to track entities, which enter their field of vision over the sensor network. Based on their sightings, they maintain a dynamic cache that can be queried by a base station- a stationary orfixed node. Since transmitting messages consumes a lot of energy, as against local processing and moreover the limited energy in sensor node does not allow heavy duty computing, we need to develop algorithms that will ensure efficient computing and minimal transmission without degradation of performance. and also data is stored locally, and memory is finite, the nodes must choose their cache lines carefully and need to dump the redundant data so that it could avoid cache overflow.Here we propose a class of algorithms for locating target object moving over a sensor network. the algorithms work with energy and memory limitations of the nodes. Algorithms developed conserves energy by efficiently identifying sensor nodes and use local messages between neighboring nodes to follow the trail of the object, assuming local transmission cost less compared to the long range transmission. Since, we avoid the long-range transmission and maximizing the local granularity security increases. the entire dynamic nature of the algorithm exploits the knowledge management for effective identification of objects through predefined parameters such as the object, object velocity. Hence it effectively exploits the network management for locating the objects over the network with minimal energy conservation and short range transmissions

Rooting capacity of Pelargonium cuttings with special regard to carbohydrate availability and photosynthetic performance

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SPECIFIC POWER OPTIMIZATION OF 0.1MWe CLOSED CYCLE OTEC POWER PLANT

Abstract: The search for renewable sources of energy resulted in the revival of a concept based on the utilization of the differences in temperature between the warm tropical surface waters and the cold deep ocean water available at depths of about 1000 m as the source of the thermal energy required to vaporize and condense the working fluid of a turbinegenerator system respectively. This concept is referred to as "Ocean Thermal Energy Conversion". As the temperature in the top surface is equal to the ambient temperature and the temperature in the bottom surface is much cooler when compared to the top surface, there exists a temperature difference between the layers of the ocean and this temperature difference is utilized to run an OTEC power plant. In this work, simulation of the OTEC power plant is done to optimize the specific power output by varying the intake velocities and depth. Ammonia is used as the working fluid. The maximum specific power output is obtained for a depth of 600m