Wind Farm Layout Design Using Cuckoo Search Algorithms

Wind energy has emerged as a strong alternative to fossil fuels for power generation. To generate this energy, wind turbines are placed in a wind farm. The extraction of maximum energy from these wind farms requires optimal placement of wind turbines. Due to complex nature of micrositing of wind turbines, the wind farm layout design problem is considered a complex optimization problem. In the recent past, various techniques and algorithms have been developed for optimization of energy output from wind farms. The present study proposes an optimization approach based on the cuckoo search (CS) algorithm, which is relatively a recent technique. A variant of CS is also proposed that incorporates a heuristic-based seed solution for a better performance. The proposed CS algorithms are compared with genetic and particle swarm optimization (PSO) algorithms, which have been extensively applied to wind farm layout design. Empirical results indicate that the proposed CS algorithms outperformed the genetic and PSO algorithms for the given test scenarios in terms of yearly power output and efficiency.     

Nonlinear robust state feedback control system design for nonlinear uncertain systems

This paper presents a systematic approach to the design of a nonlinear robust dynamic state feedback controller for nonlinear uncertain systems using copies of the plant nonlinearities. The technique is based on the use of integral quadratic constraints and minimax linear quadratic regulator control, and uses a structured uncertainty representation. The approach combines a linear state feedback guaranteed cost controller and copies of the plant nonlinearities to form a robust nonlinear controller with a novel control architecture. A nonlinear state feedback controller is designed for a synchronous machine using the proposed method. The design provides improved stability and transient response in the presence of uncertainty and nonlinearity in the system and also provides a guaranteed bound on the cost function. An automatic voltage regulator to track reference terminal voltage is also provided by a state feedback equivalent robust nonlinear proportional integral controller. Copyright © 2016 John Wiley & Sons, Ltd.     

Association Mechanism and Conformational Changes in Trypsin on Its Interaction with Atrazine: A Multi- Spectroscopic and Biochemical Study with Computational Approach

Atrazine (ATR) is a herbicide globally used to eliminate undesired weeds. Herbicide usage leads to various adverse effects on human health and the environment. The primary source of herbicides in humans is the food laced with the herbicides. The ATR binding to trypsin (TYP) was investigated in this study to explore its binding potential and toxicity. In vitro interaction of ATR with TYP was studied using multi-spectroscopic methods, molecular docking, and enzyme kinetics to explore the mechanism of binding for the TYP-ATR system. The TYP-ATR complex revealed binding constants (10³ M⁻¹), suggesting a moderate binding. The free energy for the TYP-ATR complexes was negative, suggesting a spontaneous interaction. Thermodynamic parameters enthalpy (ΔH) and entropy (ΔS) obtained positive values for the TYP-ATR system suggesting hydrophobic interactions in the binding process. Micro-environmental and conformational changes in TYP molecules were induced on interaction with ATR. Reduced catalytic activity of TYP was observed after interaction with ATR owing to the changes in the secondary structure of the TYP.     

Microscopic melanoma detection and classification: A framework of pixel‐based fusion and multilevel features reduction

The numbers of diagnosed patients by melanoma are drastic and contribute more deaths annually among young peoples. An approximately 192,310 new cases of skin cancer are diagnosed in 2019, which shows the importance of automated systems for the diagnosis process. Accordingly, this article presents an automated method for skin lesions detection and recognition using pixel‐based seed segmented images fusion and multilevel features reduction. The proposed method involves four key steps: (a) mean‐based function is implemented and fed input to top‐hat and bottom‐hat filters which later fused for contrast stretching, (b) seed region growing and graph‐cut method‐based lesion segmentation and fused both segmented lesions through pixel‐based fusion, (c) multilevel features such as histogram oriented gradient (HOG), speeded up robust features (SURF), and color are extracted and simple concatenation is performed, and (d) finally variance precise entropy‐based features reduction and classification through SVM via cubic kernel function. Two different experiments are performed for the evaluation of this method. The segmentation performance is evaluated on PH2, ISBI2016, and ISIC2017 with an accuracy of 95.86, 94.79, and 94.92%, respectively. The classification performance is evaluated on PH2 and ISBI2016 dataset with an accuracy of 98.20 and 95.42%, respectively. The results of the proposed automated systems are outstanding as compared to the current techniques reported in state of art, which demonstrate the validity of the proposed method.     

Impact of N-Terminal Tags on De Novo Vimentin Intermediate Filament Assembly

Vimentin, a type III intermediate filament protein, is found in most cells along with microfilaments and microtubules. It has been shown that the head domain folds back to associate with the rod domain and this association is essential for filament assembly. The N-terminally tagged vimentin has been widely used to label the cytoskeleton in live cell imaging. Although there is previous evidence that EGFP tagged vimentin fails to form filaments but is able to integrate into a pre-existing network, no study has systematically investigated or established a molecular basis for this observation. To determine whether a tag would affect de novo filament assembly, we used vimentin fused at the N-terminus with two different sized tags, AcGFP (239 residues, 27 kDa) and 3 × FLAG (22 residues; 2.4 kDa) to assemble into filaments in two vimentin-deficient epithelial cells, MCF-7 and A431. We showed that regardless of tag size, N-terminally tagged vimentin aggregated into globules with a significant proportion co-aligning with β-catenin at cell–cell junctions. However, the tagged vimentin aggregates could form filaments upon adding untagged vimentin at a ratio of 1:1 or when introduced into cells containing pre-existing filaments. The resultant filament network containing a mixture of tagged and untagged vimentin was less stable compared to that formed by only untagged vimentin. The data suggest that placing a tag at the N-terminus may create steric hinderance in case of a large tag (AcGFP) or electrostatic repulsion in case of highly charged tag (3 × FLAG) perhaps inducing a conformational change, which deleteriously affects the association between head and rod domains. Taken together our results shows that a free N-terminus is essential for filament assembly as N-terminally tagged vimentin is not only incapable of forming filaments, but it also destabilises when integrated into a pre-existing network.     

Three-dimensional Numerical Study of Laminar Confined Slot Jet Impingement Cooling using Slurry of Nano—encapsulated Phase Change Material

This Article presents a three dimensional numerical model investigating thermal performance and hydrodynamics features of the confined slot jet impingement using slurry of Nano Encapsulated Phase Change Material (NEPCM) as a coolant. The slurry is composed of water as a base fluid and n-octadecane NEPCM particles with mean diameter of 100nm suspended in it. A single phase fluid approach is employed to model the NEPCM slurry.The thermo physical properties of the NEPCM slurry are computed using modern approaches being proposed recently and governing equations are solved with a commercial Finite Volume based code. The effects of jet Reynolds number varying from 100 to 600 and particle volume fraction ranging from 0% to 28% are considered. The computed results are validated by comparing Nusselt number values at stagnation point with the previously published results with water as working fluid. It was found that adding NEPCM to the base fluid results with considerable amount of heat transfer enhancement.The highest values of heat transfer coefficients are observed at H/W=4 and C_m=0.28. However, due to the higher viscosity of slurry compared with the base fluid, the slurry can produce drastic increase in pressure drop of the system that increases with NEPCM particle loading and jet Reynolds number.     

Flow‐based electromagnetic‐type energy harvester using microplanar coil for IoT sensors application

Battery is the sole power source for Internet of thing (IoT) sensors. Due to limited shelf life, the batteries are required to be replaced intermittently. This periodic replacement of batteries is inflated in terms of both logistics and time. This article illustrates conceptual design, development, and characterization of a flow‐based electromagnetic‐type energy harvester (F‐EH) using microplanar coil for IoT sensors application. The F‐EH converts hydro energy into useful electrical energy utilizing electromagnetic transduction mechanism. The microfabrication and macrofabrication techniques adopted to manufacture harvester's components are presented. The F‐EH has been successfully characterized by laboratory scale experimental flow test loop commissioned for this work. Experimentation with associated uncertainty analysis prevails that at a matching impedance, the F‐EH can generate a 686 μW of maximum power at an operating flow rate of 12 L/min with an uncertainty of 8.1%.     

Microfluidic Tumor-on-a-Chip Model to Study Tumor Metabolic Vulnerability

Tumor-specific metabolic adaptations offer an interesting therapeutic opportunity to selectively destroy cancer cells. However, solid tumors also present gradients of nutrients and waste products across the tumor mass, forcing tumor cells to adapt their metabolism depending on nutrient availability in the surrounding microenvironment. Thus, solid tumors display a heterogenous metabolic phenotype across the tumor mass, which complicates the design of effective therapies that target all the tumor populations present. In this work, we used a microfluidic device to study tumor metabolic vulnerability to several metabolic inhibitors. The microdevice included a central chamber to culture tumor cells in a three-dimensional (3D) matrix, and a lumen in one of the chamber flanks. This design created an asymmetric nutrient distribution across the central chamber, generating gradients of cell viability. The results revealed that tumor cells located in a nutrient-enriched environment showed low to no sensitivity to metabolic inhibitors targeting glycolysis, fatty acid oxidation, or oxidative phosphorylation. Conversely, when cell density inside of the model was increased, compromising nutrient supply, the addition of these metabolic inhibitors disrupted cellular redox balance and led to tumor cell death.