555 research outputs found
A reduced-uncertainty hybrid evolutionary algorithm for solving dynamic shortest-path routing problem
The need for effective packet transmission to deliver advanced performance in wireless networks creates the need to find shortest network paths efficiently and quickly. This paper addresses a Reduced Uncertainty Based Hybrid Evolutionary Algorithm (RUBHEA) to solve Dynamic Shortest Path Routing Problem (DSPRP) effectively and rapidly. Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are integrated as a hybrid algorithm to find the best solution within the search space of dynamically changing networks. Both GA and PSO share context of individuals to reduce uncertainty in RUBHEA. Various regions of search space are explored and learned by RUBHEA. By employing a modified priority encoding method, each individual in both GA and PSO are represented as a potential solution for DSPRP. A Complete statistical analysis has been performed to compare the performance of RUBHEA with various state-of-the-art algorithms. It shows that RUBHEA is considerably superior (reducing the failure rate by up to 50%) to similar approaches with increasing number of nodes encountered in the networks
One-Dimensional Modeling of the Potential Impacts of a Hypothetical Uranium Tailings Dam Failure on Banister River and Kerr Reservoir in Virginia
Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv
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Quantification of gait parameters in freely walking wild type and sensory deprived Drosophila melanogaster
Coordinated walking in vertebrates and multi-legged invertebrates such as Drosophila melanogaster requires a complex neural network coupled to sensory feedback. An understanding of this network will benefit from systems such as Drosophila that have the ability to genetically manipulate neural activities. However, the fly's small size makes it challenging to analyze walking in this system. In order to overcome this limitation, we developed an optical method coupled with high-speed imaging that allows the tracking and quantification of gait parameters in freely walking flies with high temporal and spatial resolution. Using this method, we present a comprehensive description of many locomotion parameters, such as gait, tarsal positioning, and intersegmental and left-right coordination for wild type fruit flies. Surprisingly, we find that inactivation of sensory neurons in the fly's legs, to block proprioceptive feedback, led to deficient step precision, but interleg coordination and the ability to execute a tripod gait were unaffected. - See more at: http://elife.elifesciences.org/content/2/e00231#sthash.6OwrygKl.dpu
Study of potential Impacts of Radioactive Contamination on Drinking Water Qualityin Two Collinear Reservoirs Using CCHE2D Model
Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv
Approximation properties of multivariate exponential sampling series
In this paper, we generalize the family of exponential sampling series for functions of variables and study their pointwise and uniform convergence as well as the rate of convergence for the functions belonging to space of -uniformly continuous functions. Furthermore, we state and prove the generalized Mellin-Taylor's expansion of multivariate functions. Using this expansion we establish pointwise asymptotic behaviour of the series by means of Voronovskaja type theorem
Green Currents for Meromorphic Maps of Compact K\"ahler Manifolds
We consider the dynamics of meromorphic maps of compact K\"ahler manifolds.
In this work, our goal is to locate the non-nef locus of invariant classes and
provide necessary and sufficient conditions for existence of Green currents in
codimension one.Comment: Statement of Theorem 1.5 is slightly improved. Proposition 5.2 and
Theorem 5.3 are adde
An aquaporin 4 antisense oligonucleotide loaded, brain targeted nanoparticulate system design
Aquaporins (AQPs), members of the water-channel protein family, are highly expressed in brain tissue especially in astrocytic end-feet. They are important players for water hemostasis during development of cytotoxic as well as vasogenic edema. Increased expression of AQPs is important in pathophysiology of neurological diseases such as neuroinflammation and ischemia. Unfortunately, there are a few pharmacological inhibitors of AQP4 with several side effects limiting their translation as a drug for use in clinical conditions. Another therapeutic approach is using antisense oligonucleotides (ASOs) to block AQP4 activity. These are short, synthetic, modified nucleic acids that bind RNA to modulate its function. However, they cannot pass the blood brain barrier (BBB). To overcome this obstacle we designed a nanoparticulate system made up of chitosan nanoparticles surface modified with PEG and conjugated with monoclonal anti transferrin receptor-1 antibody via streptavidin-biotin binding. The nanocarrier system could be targeted to the transferrin receptor-1 at the brain endothelial capillaries through monoclonal antibodies. It is hypothesized that the nanoparticles could pass the BBB via receptor mediated transcytosis and reach brain parenchyma. Particle size, zeta potential, loading capacity and release profiles of nanoparticles were investigated. It was observed that all types of chitosau (CS) nanoparticles had positive zeta potential values and nanoparticle particle size distribution varied between 100 and 800 nm. The association efficiency of ASOs into the nanoparticles was between 80–97% and the release profiles of the nanoparticles exhibited an initial burst effect followed by a controlled release. The results showed that the designed chitosan based nanocarriers could be a promising carrier system to transport nucleic acid based drugs to brain parenchymaThis study is supported by The Scientific and Technological Research Council of Turkey (TUBITAK, Project Number: 110S460)S
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