Transient effects on microchannel electrokinetic filtering with an ion-permselective membrane

The electrokinetics and hydrodynamics in a hybrid microfluidic/nanofluidic pore network configuration and its effect on the concentration enrichment of charged analytes are described. A hydrogel microplug, photopolymerized in a microfluidic channel, with negative surface charge serves as a nanoporous membrane and dictates the electrokinetic behavior within the adjoining microchannel compartments. The nanoporous hydrogel with a mean pore size on the order of the electrical double layer thickness imparts ion-permselectivity (cation-selectivity) to the migration of ionic species which, under the influence of an applied electrical field, drives concentration polarization in bulk solution near the interfaces between the two microchannel compartments and the hydrogel-based nanopores. The concentration enrichment efficiency for charged analytes depends on this concentration polarization, which strongly affects the distribution of local electrical field strength. In addition, electroosmotic flow in the device plays a critical role in determining the location of the analyte enrichment zone. A theoretical model and simulations are presented to explain the interplay of concentration polarization and electroosmotic flow with respect to the observed concentration enrichment of negatively charged analytes at the cathodic hydrogel plug-microchannel solution interface.     

Efficient prediction of drug–drug interaction using deep learning models

A drug–drug interaction or drug synergy is extensively utilised for cancer treatment. However, prediction of drug–drug interaction is defined as an ill‐posed problem, because manual testing is only implementable on small group of drugs. Predicting the drug–drug interaction score has been a popular research topic recently. Recently many machine learning models have proposed in the literature to predict the drug–drug interaction score efficiently. However, these models suffer from the over‐fitting issue. Therefore, these models are not so‐effective for predicting the drug–drug interaction score. In this work, an integrated convolutional mixture density recurrent neural network is proposed and implemented. The proposed model integrates convolutional neural networks, recurrent neural networks and mixture density networks. Extensive comparative analysis reveals that the proposed model significantly outperforms the competitive models.Inspec keywords: cancer, learning (artificial intelligence), drugs, recurrent neural nets, convolutional neural nets, drug delivery systemsOther keywords: drug synergy, drug–drug interaction score, drug–drug interaction prediction, deep learning, cancer treatment, machine learning, convolutional mixture density recurrent neural network     

When false recognition is unopposed by true recognition: Gist-based memory distortion in Alzheimer's disease.

The authors examined false recognition of semantic associates in patients with probable Alzheimer's disease (AD), older adults, and young adults using a paradigm that provided rates of false recognition after single and multiple exposures to word lists. Using corrected false recognition scores to control for unrelated false alarms, the authors found that (a) the level of false recognition after a single list exposure was lower in AD patients than in controls; (b) across 5 trials, false recognition increased in AD patients, decreased in young adults, and showed a fluctuating pattern in older adults; and (c) all groups showed an increase in true recognition over the 5 trials. Analyses suggested that AD patients built up semantic gist across trials, whereas both control groups were able to use increased item-specific recollection and more conservative response criteria to suppress gist-based false alarms. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Low-Power, Battery-Free Tag for Body Sensor Networks

The authors describe a low-power, battery-free tag for use in pervasive sensing applications such as wearable patient-monitoring systems and body sensor networks. The tag consists of a custom integrated circuit, an antenna for RF energy harvesting, and several sensors for monitoring important physiological parameters and generating alarms when necessary. They also describe experimental results with phonocardiogram and photoplethysmogram signals and demonstrate tag localization within 0.6 m by using an audio localization scheme.     

Applications of Genetic Algorithm in Polymer Science and Engineering

In the last several years, genetic algorithm (GA) has gained wide acceptance as a robust optimization algorithm in almost all areas of science and engineering. Polymer science and engineering is no exception. Researchers in this field have devoted considerable attention to the optimization of polymer productionusing objective functions and constraints that lead to products having desired material properties. Multiple-objective functions have been optimized simultaneously. An example is the minimization of the reaction time in a reactor (lower costs) while simultaneously minimizing the concentration of side products (that affect the properties of the product adversely). Several end-point constraints (equality or inequality) may also be present, as, e.g., obtaining polymer of a desired molecular weight. Again, this requirement stems from producing polymer having desired strength. Solving such problems usually result in Pareto sets. A variety of adaptations of GA have been developed to obtain optimal solutions for such complex problems. These adaptations can be used to advantage in other fields too. The applications of GA in areas of polymer science and engineering other than polymerization systems are few and far between, but this field is now maturing, and it is hoped that the future will see several newer applications.     

在双镶嵌铜互联中O.13微米器件生成用的基于PVD和ALD阻挡层的先进技术

1. Introduction The requirement of minimal bottom coverageand thick sidewall coverage for PVD-based films forlow via resistance and improved stress migration isnot easy to achieve with traditional depositionmethods. Modern I-PVD techniques give high bot-tom coverage, due to the ionized component of thedeposition flux. Sidewall coverage tends to be low,which is mainly due to off-normal deposition fluxand a less than unity sticking coefficient.     

Studies of spinodal decomposition in a ternary polymer‐solvent‐nonsolvent system

Much of the work in modeling and computer simulation of spinodal decomposition has been done for binary systems. This work attempts to carry out the analysis of spinodal decomposition in ternary polymer‐solvent‐nonsolvent systems, where the solvent is the monomer used to produce the polymer and the nonsolvent is the major component. Various experimental methods are used to determine values of the parameters of the ternary version of the Cahn‐Hilliard equation of spinodal decomposition, such as cloudpoint experiments, time‐resolved light scattering in the ternary system, and morphological development of polymer membranes formed during the early stages spinodal decomposition. The combination of these experimental methods and computer simulation work shows the validity of the assumptions made in characterizing spinodal decomposition in ternary polymer systems of interest.     

Structures and Images of Novel Derivatives of Carbon Nanotubes, Fullerenes and Related New Carbon Forms

In the light of the finding that carbon nanotubes get functionalized on reaction with acid and other oxidizing agents, the structures and shapes of nanotube derivatives resulting from possible reaction between functionalized nanotubes, are obtained by an energy minimization procedure and the structures, so obtained, are compared with the observed microscopic images. The shapes of fullerene -like and nanotupe - like structures containing seven - membered rings, in addition to six and five - membered rings, are depicted along with the structures of bent nanotubes containing similar ring systems. Diamond - graphite hybrid structures which constitute an important class of carbon materials are also investigated.     

Carbon electrode fabrication from pyrolyzed parylene C

Carbon electrodes coupled with electrochemical detection have been used extensively for the investigation of biogenic amines. Herein we report the fabrication and characterization of carbonaceous electrodes prepared from pyrolyzed parylene C (PPC) films. High-aspect ratio carbonaceous microelectrodes have been prepared by masking PPC coated pipets with an insulating parylene C film. PPC thin film electrodes were characterized electrochemically, spectroscopically, and with electron microscopy. The procedures described here offer a route to fabrication of thin film carbon electrodes that can be patterned and produced in parallel. These electrodes are similar to carbon electrodes derived from pyrolyzed photoresist films but do not require spin-coating or lithography and can readily coat three-dimensional surfaces.