Neuro-Genetic Optimization of the Diffuser Elements for Applications in a Valveless Diaphragm Micropumps System

In this study, a hybridized neuro-genetic optimization methodology realized by embedding numerical simulations trained artificial neural networks (ANN) into a genetic algorithm (GA) is used to optimize the flow rectification efficiency of the diffuser element for a valveless diaphragm micropump application. A higher efficiency ratio of the diffuser element consequently yields a higher flow rate for the micropump. For that purpose, optimization of the diffuser element is essential to determine the maximum pumping rate that the micropump is able to generate. Numerical simulations are initially carried out using CoventorWare® to analyze the effects of varying parameters such as diffuser angle, Reynolds number and aspect ratio on the volumetric flow rate of the micropump. A limited range of simulation results will then be used to train the neural network via back-propagation algorithm and optimization process commence subsequently by embedding the trained ANN results as a fitness function into GA. The objective of the optimization is to maximize the efficiency ratio of the diffuser element for the range of parameters investigated. The optimized efficiency ratio obtained from the neuro-genetic optimization is 1.38, which is higher than any of the maximum efficiency ratio attained from the overall parametric studies, establishing the superiority of the optimization method

Highly-sensitive graphene-based flexible pressure sensor platform

In this work, graphene has been utilized as the sensing material for the development of a highly-sensitive flexible pressure sensor platform. It has been demonstrated that a graphene-based pressure sensor platform that is able to measure pressure change of up to 3 psi with a sensitivity of 0.042 psi-1 and a non-linearity of less than 1% has been accomplished. The developed device, which resides on a flexible platform, will be applicable for integration in continuous wearables health-care monitoring system for the measurement of blood pressure

Effects of Stimulus Enhancement and Provided Mediators on Paired Associate Learning in Learning Disabled and Educable Mentally Retarded Children

Educational Psycholog

Continuous Monitoring of Distributed Data Streams over a Time-based Sliding Window

The past decade has witnessed many interesting algorithms for maintaining statistics over a data stream. This paper initiates a theoretical study of algorithms for monitoring distributed data streams over a time-based sliding window (which contains a variable number of items and possibly out-of-order items). The concern is how to minimize the communication between individual streams and the root, while allowing the root, at any time, to be able to report the global statistics of all streams within a given error bound. This paper presents communication-efficient algorithms for three classical statistics, namely, basic counting, frequent items and quantiles. The worst-case communication cost over a window is $O(\frac{k} {\epsilon} \log \frac{\epsilon N}{k})$ bits for basic counting and $O(\frac{k}{\epsilon} \log \frac{N}{k})$ words for the remainings, where $k$ is the number of distributed data streams, $N$ is the total number of items in the streams that arrive or expire in the window, and $\epsilon < 1$ is the desired error bound. Matching and nearly matching lower bounds are also obtained.Comment: 12 pages, to appear in the 27th International Symposium on Theoretical Aspects of Computer Science (STACS), 201

Investigation of Low-Pressure Bimetallic Cobalt-Iron Catalyst-Grown Multiwalled Carbon Nanotubes and Their Electrical Properties

A bimetallic cobalt-iron catalyst was utilized to demonstrate the growth of multiwalled carbon nanotubes (CNTs) at low gas pressure through thermal chemical vapor deposition. The characteristics of multiwalled CNTs were investigated based on the effects of catalyst thickness and gas pressure variation. The results revealed that the average diameter of nanotubes increased with increasing catalyst thickness, which can be correlated to the increase in particle size. The growth rate of the nanotubes also increased significantly by ~2.5 times with further increment of gas pressure from 0.5 Torr to 1.0 Torr. Rapid growth rate of nanotubes was observed at a catalyst thickness of 6 nm, but it decreased with the increase in catalyst thickness. The higher composition of 50% cobalt in the cobalt-iron catalyst showed improvement in the growth rate of nanotubes and the quality of nanotube structures compared with that of 20% cobalt. For the electrical properties, the measured sheet resistance decreased with the increase in the height of nanotubes because of higher growth rate. This behavior is likely due to the larger contact area of nanotubes, which improved electron hopping from one localized tube to another

SOAP3-dp: Fast, Accurate and Sensitive GPU-based Short Read Aligner

To tackle the exponentially increasing throughput of Next-Generation Sequencing (NGS), most of the existing short-read aligners can be configured to favor speed in trade of accuracy and sensitivity. SOAP3-dp, through leveraging the computational power of both CPU and GPU with optimized algorithms, delivers high speed and sensitivity simultaneously. Compared with widely adopted aligners including BWA, Bowtie2, SeqAlto, GEM and GPU-based aligners including BarraCUDA and CUSHAW, SOAP3-dp is two to tens of times faster, while maintaining the highest sensitivity and lowest false discovery rate (FDR) on Illumina reads with different lengths. Transcending its predecessor SOAP3, which does not allow gapped alignment, SOAP3-dp by default tolerates alignment similarity as low as 60 percent. Real data evaluation using human genome demonstrates SOAP3-dp's power to enable more authentic variants and longer Indels to be discovered. Fosmid sequencing shows a 9.1 percent FDR on newly discovered deletions. SOAP3-dp natively supports BAM file format and provides a scoring scheme same as BWA, which enables it to be integrated into existing analysis pipelines. SOAP3-dp has been deployed on Amazon-EC2, NIH-Biowulf and Tianhe-1A.Comment: 21 pages, 6 figures, submitted to PLoS ONE, additional files available at "https://www.dropbox.com/sh/bhclhxpoiubh371/O5CO_CkXQE". Comments most welcom

ITGAM is associated with disease susceptibility and renal nephritis of systemic lupus erythematosus in Hong Kong Chinese and Thai

ITGAM was recently found to be associated with systemic lupus erythematosus (SLE) in populations of not only European ancestry, but also in Hispanic- and African-Americans, Mexicans and Colombians. The risk alleles in the gene, however, were found to be monomorphic in two Asian populations examined: Japanese and Korean. In this study, using a collection of 910 SLE patients and 2360 controls from Chinese living in Hong Kong, analyzed by both genome-wide association and direct sequencing, we confirmed the association of the same risk alleles in ITGAM with the disease. These findings were further replicated in the Thai population with 278 patients and 383 ethnicity- and geography-matched controls. Subphenotype stratification analyses showed significantly more involvement of the gene in patients with renal nephritis and neurological disorders. Although our results support a pivotal role by rs1143679 (R77H) in disease association, our data also suggests an additional contribution from rs1143683, another non-synonymous polymorphism in this gene (A858V). Therefore, despite the low-allele frequencies of the risk alleles of the gene in our two Asian populations, ITGAM was confirmed to be a risk factor related to disease susceptibility and probably severe manifestations of SLE

Selective formation of tungsten nanowires

We report on a process for fabricating self-aligned tungsten (W) nanowires with polycrystalline silicon core. Tungsten nanowires as thin as 10 nm were formed by utilizing polysilicon sidewall transfer technology followed by selective deposition of tungsten by chemical vapor deposition (CVD) using WF6 as the precursor. With selective CVD, the process is self-limiting whereby the tungsten formation is confined to the polysilicon regions; hence, the nanowires are formed without the need for lithography or for additional processing. The fabricated tungsten nanowires were observed to be perfectly aligned, showing 100% selectivity to polysilicon and can be made to be electrically isolated from one another. The electrical conductivity of the nanowires was characterized to determine the effect of its physical dimensions. The conductivity for the tungsten nanowires were found to be 40% higher when compared to doped polysilicon nanowires of similar dimensions