One-chip wonders

Consumer demand for portable computing and mobile wireless communications will continue to drive development of functionally integrated, ultra-low-power systems on a chip. CMOS bulk processing is likely to emerge as the foundation of mixed-signal, ultra-low-power ICs because of its inherent advantages for low-power logic and flexibility in RF applications. To successfully meet time-to-market goals and shrink product-development cycles, computer-aided design tools must guide a design from conceptualization to physical implementation. Estimates of floorplan arrangement and interconnect and package parasitics are necessary early in the design flow, since these undesirable contributions can dominate over the intrinsic device parasitics     

Binding free energy predictions of farnesoid X receptor (FXR) agonists using a linear interaction energy (LIE) approach with reliability estimation: application to the D3R Grand Challenge 2

Computational protein binding affinity prediction can play an important role in drug research but performing efficient and accurate binding free energy calculations is still challenging. In the context of phase 2 of the Drug Design Data Resource (D3R) Grand Challenge 2 we used our automated eTOX ALLIES approach to apply the (iterative) linear interaction energy (LIE) method and we evaluated its performance in predicting binding affinities for farnesoid X receptor (FXR) agonists. Efficiency was obtained by our pre-calibrated LIE models and molecular dynamics (MD) simulations at the nanosecond scale, while predictive accuracy was obtained for a small subset of compounds. Using our recently introduced reliability estimation metrics, we could classify predictions with higher confidence by featuring an applicability domain (AD) analysis in combination with protein–ligand interaction profiling. The outcomes of and agreement between our AD and interaction-profile analyses to distinguish and rationalize the performance of our predictions highlighted the relevance of sufficiently exploring protein–ligand interactions during training and it demonstrated the possibility to quantitatively and efficiently evaluate if this is achieved by using simulation data only.     

Fabrication of PZT/CuO composite films and their photovoltaic properties

In this paper, we reported the design and preparation of a double-layer antireflective (AR) coating, which possessed relatively high transmittance at 351, 527, and 1053?nm. The refractive indices and film thicknesses of the under layer and upper layer of the simulated AR coating were determined as 1.27, 95?nm and 1.18, 106?nm, respectively. The under layer of the double-layer coating dip-coated from a mixture of base-catalyzed and acid-catalyzed silica sols had a refractive index of 1.27. The upper layer fabricated by the deposition of methylated silica nanoparticles by simply adding methyltriethoxysilane into the base-catalyzed silica sols possessed a refractive index of 1.18. The hydrophobicity of coatings could be dramatically improved with the water contact angle increasing from 23.4° to 150.0°, and the refractive indices of the pure base-catalyzed silica coatings were easily decreased from 1.20 to 1.12 through the surface treatment of silica nanoparticles. Thus, we have successfully prepared a double-layer AR coating, which had a high transmittance of 99.8%, 96.1%, and 99.7% at 351, 527, and 1053?nm, respectively.

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A hierarchy in mutation of genetic algorithm and its application to multi-objective analog/RF circuit optimization

This paper presents a multi-objective analog circuit design optimization tool using genetic algorithm based on hierarchical mutation scheme. The idea is to improve the convergence and diversity of genetic algorithm by incorporating hierarchy during polynomial mutation operation. In this regard, a theoretical framework of proposed genetic algorithm is presented using Markov chain principle. To investigate the effectiveness of hierarchy in polynomial mutation operator, the scheme is compared with six different mutation strategies. Experiments are performed for different function evaluations to evaluate the performance of hierarchical polynomial mutation operator. Further, to showcase the improvement in genetic algorithm, numerous experiments are performed on twelve different test functions and two design examples. The proposed genetic algorithm shows competitive performance over other standard optimization techniques in terms of both convergence and diversity of solutions.     

Improved VBLAST MAP: A Novel Point-to-Point Symbol Detection Algorithm for MIMO Wireless Communication Systems

Anovel point-to-point symbol detection algorithm in multiple input multiple output (MIMO) system is proposed. This algorithm is an augmentation of two popular algorithms, namely, vertical Bell laboratories layered space-time (VBLAST) and maximum a posteriori probability (MAP). Here, layers are distinguished or ordered based on the a posteriori probabilities of output symbols and not on signal-to-noise ratio (SNR). For each layer, a set of a posteriori probabilities is computed for all output symbols using all possible signal constellations. The layer corresponding to the output symbol having minimum a posteriori probability is selected first from the set of a posteriori probabilities for detection by doing the comprehensive search over all the possible signal constellations. Then, the remaining layers are detected by the conventional VBLAST MAP technique. The relationship of MIMO symbol error rate (MIMO SER) versus MIMO symbol SNR is presented using simulations for 16×16 MIMO systems and 16-QAM constellation. The results show that the proposed algorithm outperforms conventional VBLAST MAP and improved VBLAST algorithms.     

Synthesis of Cysteine-Functionalized Silver Nanoparticles Using Green Tea Extract with Application for Lipase Immobilization

The application of cysteine-capped silver nanoparticles synthesized using green tea as the reducing agent to immobilize lipase has been reported in the present work. The reducing property of green tea is due to the presence of polyphenolic compounds in its extract which are not oxidized at ambient atmospheric conditions and hence is a suitable reducing agent for green synthesis of nanoparticles. Cysteine-capped silver nanoparticles were synthesized under alkaline conditions by reducing the silver salt by green tea extract in the presence of cystine. Various parameters such as the cystine concentration, pH, temperature, and amount of reducing agent were standardized and their effect on the synthesis process has been initially evaluated by surface plasmon resonance peak analysis. Furthermore, the synthesized nanoparticles were also characterized using X-ray diffraction, Fourier transform infrared spectroscopy, and transmission electron microscopy. The particle size analysis revealed the average size of the particles to be around 20?nm. The glutaraldehyde-deactivated amino group on cysteine-capped nanoparticles was used to immobilize lipase on its surface. Both crude and immobilized lipases were checked for activity and protein content under standard assay conditions and their activity was found to be 37.7 and 24.9?U?mL^?1, respectively. The lipase nanoparticle bioconjugates exhibited a good shelf life of 60 days with a marginal decrease in activity. The bioconjugates showed 15% loss in its initial activity at the end of five reusability cycles. This immobilized reusable system has the potential to be utilized for various applications pertaining to the exploitation of lipase in various industries.