Deformation structure in a Ti-24Al-11Nb alloy

A Ti-24Al-11Nb alloy has been heat-treated so as to obtain a microstructure of coarse α₂ particles (D0₁₉ structure based on Ti₃Al) in a matrix of the ordered β_o phase (B2 structure based on Ti₂AlNb). Dislocation structures generated by tensile strains of ∼2 pct at room temperature have been analyzed by transmission electron microscopy The β_o phase is shown to deform inhomogeneously on {110}, {112}, and {123} planes by α/〈211〉 slip. The slipband structure is complex, consisting of segments of heavily pinned edge dislocations with periodic cross slip of screw components on to secondary slip planes. Incompatibility stresses at α₂/β_o interfaces can generate fine α[100] slip as well. The α₂ phase deforms independently by α dislocation slip. Slipbands in the β_o phase can shear the α₂ phase by activatingc +a/2 slip on and slip planes, as well asa slip on higher order pyramidal planes, where the parallelism of the specific slip system is permitted by the Burgers relationship between the two phases.     

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     

Comparing ANN and GMM in a voice conversion framework

In this paper, we present a comparative analysis of artificial neural networks (ANNs) and Gaussian mixture models (GMMs) for design of voice conversion system using line spectral frequencies (LSFs) as feature vectors. Both the ANN and GMM based models are explored to capture nonlinear mapping functions for modifying the vocal tract characteristics of a source speaker according to a desired target speaker. The LSFs are used to represent the vocal tract transfer function of a particular speaker. Mapping of the intonation patterns (pitch contour) is carried out using a codebook based model at segmental level. The energy profile of the signal is modified using a fixed scaling factor defined between the source and target speakers at the segmental level. Two different methods for residual modification such as residual copying and residual selection methods are used to generate the target residual signal. The performance of ANN and GMM based voice conversion (VC) system are conducted using subjective and objective measures. The results indicate that the proposed ANN-based model using LSFs feature set may be used as an alternative to state-of-the-art GMM-based models used to design a voice conversion system.     

Group technology based adaptive cell formation using predator-prey genetic algorithm

In recent years, there has been a considerable growth of application of group technology in cellular manufacturing. This has led to investigation of the primary cell formation problem (CFP), both in classical and soft-computing domain. Compared to more well-known and analytical techniques like mathematical programming which have been used rigorously to solve CFPs, heuristic approaches have yet gained the same level of acceptance. In the last decade we have seen some fruitful attempts to use evolutionary techniques like genetic algorithm (GA) and Ant Colony Optimization to find solutions of the CFP. The primary aim of this study is to investigate the applicability of a fine grain variant of the predator-prey GA (PPGA) in CFPs. The algorithm has been adapted to emphasize local selection strategy and to maintain a reasonable balance between prey and predator population, while avoiding premature convergence. The results show that the algorithm is competitive in identifying machine-part clusters from the initial CFP matrix with significantly less number of iterations. The algorithm scaled efficiently for large size problems with competitive performance. Optimal cluster identification is then followed by removal of the bottleneck elements to give a final solution with minimum inter-cluster transition cost. The results give considerable impetus to study similar NP-complete combinatorial problems using fine-grain GAs in future.     

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.     

Aggregation dynamics of particles in a microchannel due to an applied magnetic field

Functionalized magnetic microspheres have promising applications in different microfluidic devices including MEMS-scale biosensors. These particles exhibit magnetic field-induced aggregation, which can be harnessed to achieve several practical tasks in microfluidic devices. For this, the particle aggregation needs to be well characterized. Herein, a numerical simulation and experimental validation of particle-chaining is presented. Simulations show that the particle aggregation time scales linearly with a group parameter. The predicted growth of one- two- and three-particle chains with time shows a similar trend as that found in the experiments. The results of the study could help predicting the performance of magnetic aggregate-based lab-on-a-chip devices.     

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.