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.     

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     

Microalgae Chlorella as a potential bio-energy feedstock

Microalgae are promising biomass species owing to their fast growth rate and high CO₂ fixation ability as compared to terrestrial plants. Microalgae have long been recognized as potentially good source for biofuel production because of their high oil content and rapid biomass production. In this study Chlorella sp. MP-1 biomass was examined for its physical and chemical characteristics using Bomb calorimeter, TGDTA, CHN and FTIR. The proximate composition was calculated using standard ASTM methodology. Chlorella sp. MP-1 biomass shows low ash (5.93%), whereas high energy (18.59 MJ/kg), carbohydrate (19.46%), and lipid (28.82%) content. The algal de-oiled cake was characterized by FTIR spectroscopy and thermogravimetric study at 10 °C/min and 30 °C/min to investigate its feasibility for thermo-chemical conversion. The present investigation suggests that within the realm of biomass energy technologies the algal biomass can be used as feedstock for bio and thermo-chemical whereas the de-oiled cake for thermo-chemical conversion thereby serving the demand of second generation biofuels.     

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.     

Encapsulated microbubbles and echogenic liposomes for contrast ultrasound imaging and targeted drug delivery

Micron- to nanometer-sized ultrasound agents, like encapsulated microbubbles and echogenic liposomes, are being developed for diagnostic imaging and ultrasound mediated drug/gene delivery. This review provides an overview of the current state of the art of the mathematical models of the acoustic behavior of ultrasound contrast microbubbles. We also present a review of the in vitro experimental characterization of the acoustic properties of microbubble based contrast agents undertaken in our laboratory. The hierarchical two-pronged approach of modeling contrast agents we developed is demonstrated for a lipid coated (Sonazoid $^\mathrm{TM})$ and a polymer shelled (poly D-L-lactic acid) contrast microbubbles. The acoustic and drug release properties of the newly developed echogenic liposomes are discussed for their use as simultaneous imaging and drug/gene delivery agents. Although echogenicity is conclusively demonstrated in experiments, its physical mechanisms remain uncertain. Addressing questions raised here will accelerate further development and eventual clinical approval of these novel technologies.