HA/β-TCP plasma sprayed coatings on Ti substrate for biomedical applications

The present work focuses on the fabrication of βTCP (β-tricalcium phosphate) and HA/βTCP (hydroxyapatite/β-tricalcium phosphate) composite coatings by plasma spraying. The starting powders were produced via solid-state method using 2 wt% MgO to stabilize βTCP phase. The synthesized powders were preliminarily granulated to be used by the plasma spray process. Coatings obtained on titanium substrates are uniform and well adherent but due to the high temperature and cooling rate typical for plasma spraying process, βTCP phase is almost totally transformed into the α allotrope. Thermal treatment at 800 °C allows the reconversion of the phase αTCP→ βTCP. It is therefore possible to produce coatings with tuneable dissolution properties by selecting the proper initial powder mixture and the specific thermal treatment.     

A Low-Power Wide-Dynamic-Range Analog VLSI Cochlea

Low-power wide-dynamic-range systems are extremely hard to build. The biological cochlea is one of the most awesome examples of such a system: It can sense sounds over 12 orders of magnitude in intensity, with an estimated power dissipation of only a few tens of microwatts. In this paper, we describe an analog electronic cochlea that processes sounds over 6 orders of magnitude in intensity, and that dissipates 0.5 mW. This 117-stage, 100 Hz to 10 KHz cochlea has the widest dynamic range of any artificial cochlea built to date. The wide dynamic range is attained through the use of a wide-linear-range transconductance amplifier, of a low-noise filter topology, of dynamic gain control (AGC) at each cochlear stage, and of an architecture that we refer to as overlapping cochlear cascades. The operation of the cochlea is made robust through the use of automatic offset-compensation circuitry. A BiCMOS circuit approach helps us to attain nearly scale-invariant behavior and good matching at all frequencies. The synthesis and analysis of our artificial cochlea yields insight into why the human cochlea uses an active traveling-wave mechanism to sense sounds, instead of using bandpass filters. The low power, wide dynamic range, and biological realism make our cochlea well suited as a front end for cochlear implants.     

On denoising and compression of DNA microarray images

We address the problems of noise and huge data sizes in microarray images. First, we propose a mixture model for describing the statistical and structural properties of microarray images. Then, based on the microarray image model, we present methods for denoising and for compressing microarray images. The denoising method is based on a variant of the translation-invariant wavelet transform. The compression method introduces the notion of approximate contexts (rather than traditional exact contexts) in modeling the symbol probabilities in a microarray image. This inexact context modeling approach is important in dealing with the noisy nature of microarray images. Using the proposed denoising and compression methods, we describe a near-lossless compression scheme suitable for microarray images. Results on both denoising and compression are included, which show the performance of the proposed methods. Further experiments using the results of the proposed near-lossless compression scheme in gene clustering using cell-cycle microarray data for S. cerevisiae showed a general improvement in the clustering performance, when compared with using the original data. This provides an indirect validation of the effectiveness of the proposed denoising method.     

A rule-based fuzzy-logic approach for the measurement of manufacturing flexibility

Manufacturing flexibility is a difficult to quantify concept that defies universal definition. This paper presents a novel fuzzy-logic approach for measuring manufacturing flexibility that exploits linguistic variables for quantifying pertinent factors affecting commonly utilized flexibility types. Towards this end, we identify and measure the contribution of specified state variables towards the assumed flexibility types in order to compute an overall flexibility index for a generic manufacturing system. The suggested framework provides a convenient end user approach amenable to software implementation that is exemplified through the development of a prototypical software tool called “Flexibility Evaluator”.     

Design development of a static sunshade using small scale modeling technique

The rising global demand for energy has triggered emphasis on conservation of energy. Buildings are one of the important energy consuming sectors. Passive solar architecture encompasses a wide range of strategies and options resulting in energy efficient building design and increased occupant's comfort. Passive solar design, aiming at increasing direct solar gains during winter period and to avoid overheating during summer period should make use of specific shading devices over energy efficient window. The static sunshades are most effective for solar control inside the buildings.Countries like India have composite climate, which can be classified under summer, winter and rainy season. Depending on the seasonal requirements, this paper introduces a new geometry of a static sunshade, designed by calculating the sun angles for the two dates. The static sun shading design methodology is validated with the help of small scale modeling experimentation technique, carried out in Pilani, Rajasthan (India). Although insulating materials can be used as a part of a building structure, its feasibility should be checked before particular application. In the present paper, the two small-scale experimental models of actual construction material with varying static sunshades, i.e. horizontal and the proposed one have been constructed and analyzed with the models of insulating material (Polyurethane Foam [PUF]). Depending upon the solar intersection over south facade wall, sunlit area and shaded area have been correlated with temperature inside the models to decide the effectiveness of the proposed sunshade.     

Finding feasible mold parting directions using graphics hardware

We present new programmable graphics hardware accelerated algorithms to test the 2-moldability of geometric parts and assist with part redesign. These algorithms efficiently identify and graphically display undercuts as well as minimum and insufficient draft angles. Their running times grow only linearly with respect to the number of facets in the solid model, making them efficient subroutines for our algorithms that test whether a tessellated CAD model can be manufactured in a two-part mold. We have developed and implemented two such algorithms to choose candidate directions to test for 2-moldability using accessibility analysis and Gauss maps. The efficiency of these algorithms lies in the fact that they identify groups of candidate directions such that if any one direction in the group is undercut-free, all are, or if any one is not undercut-free, none are. We examine trade-offs between the algorithms' speed, accuracy, and whether they guarantee that an undercut-free direction will be found for a part if one exists.     

Rate-distortion optimized tree-structured compression algorithms for piecewise polynomial images.

This paper presents novel coding algorithms based on tree-structured segmentation, which achieve the correct asymptotic rate-distortion (R-D) behavior for a simple class of signals, known as piecewise polynomials, by using an R-D based prune and join scheme. For the one-dimensional case, our scheme is based on binary-tree segmentation of the signal. This scheme approximates the signal segments using polynomial models and utilizes an R-D optimal bit allocation strategy among the different signal segments. The scheme further encodes similar neighbors jointly to achieve the correct exponentially decaying R-D behavior (D(R) - c(o)2(-c1R)), thus improving over classic wavelet schemes. We also prove that the computational complexity of the scheme is of O(N log N). We then show the extension of this scheme to the two-dimensional case using a quadtree. This quadtree-coding scheme also achieves an exponentially decaying R-D behavior, for the polygonal image model composed of a white polygon-shaped object against a uniform black background, with low computational cost of O(N log N). Again, the key is an R-D optimized prune and join strategy. Finally, we conclude with numerical results, which show that the proposed quadtree-coding scheme outperforms JPEG2000 by about 1 dB for real images, like cameraman, at low rates of around 0.15 bpp.     

Correction to: EDVWDD: Event‑Driven Virtual Wheel‑based Data Dissemination for Mobile Sink‑Enabled Wireless Sensor Networks

The Journal of Supercomputing - A correction to this paper has been published: https://doi.org/10.1007/s11227-021-03790-9     

On the sizing of a solar thermal electricity plant for multiple objectives using evolutionary optimization

Design, implementation and operation of solar thermal electricity plants are no more an academic task, rather they have become a necessity. In this paper, we work with power industries to formulate a multi-objective optimization model and attempt to solve the resulting problem using classical as well as evolutionary optimization techniques. On a set of four objectives having complex trade-offs, our proposed procedure first finds a set of trade-off solutions showing the entire range of optimal solutions. Thereafter, the evolutionary optimization procedure is combined with a multiple criterion decision making (MCDM) approach to focus on preferred regions of the trade-off frontier. Obtained solutions are compared with a classical generating method. Eventually, a decision-maker is involved in the process and a single preferred solution is obtained in a systematic manner. Starting with generating a wide spectrum of trade-off solutions to have a global understanding of feasible solutions, then concentrating on specific preferred regions for having a more detailed understanding of preferred solutions, and then zeroing on a single preferred solution with the help of a decision-maker demonstrates the use of multi-objective optimization and decision making methodologies in practice. As a by-product, useful properties among decision variables that are common to the obtained solutions are gathered as vital knowledge for the problem. The procedures used in this paper are ready to be used to other similar real-world problem solving tasks.     

CRISPR/Cas9-Mediated Generation of Pathogen-Resistant Tomato against Tomato Yellow Leaf Curl Virus and Powdery Mildew

Tomato is one of the major vegetable crops consumed worldwide. Tomato yellow leaf curl virus (TYLCV) and fungal Oidium sp. are devastating pathogens causing yellow leaf curl disease and powdery mildew. Such viral and fungal pathogens reduce tomato crop yields and cause substantial economic losses every year. Several commercial tomato varieties include Ty-5 (SlPelo) and Mildew resistance locus o 1 (SlMlo1) locus that carries the susceptibility (S-gene) factors for TYLCV and powdery mildew, respectively. The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein (Cas) is a valuable genome editing tool to develop disease-resistant crop varieties. In this regard, targeting susceptibility factors encoded by the host plant genome instead of the viral genome is a promising approach to achieve pathogen resistance without the need for stable inheritance of CRISPR components. In this study, the CRISPR/Cas9 system was employed to target the SlPelo and SlMlo1 for trait introgression in elite tomato cultivar BN-86 to confer host-mediated immunity against pathogens. SlPelo-knockout lines were successfully generated, carrying the biallelic indel mutations. The pathogen resistance assays in SlPelo mutant lines confirmed the suppressed accumulation of TYLCV and restricted the spread to non-inoculated plant parts. Generated knockout lines for the SlMlo1 showed complete resistance to powdery mildew fungus. Overall, our results demonstrate the efficiency of the CRISPR/Cas9 system to introduce targeted mutagenesis for the rapid development of pathogen-resistant varieties in tomato.