Natural convection in a cavity with undulated walls filled with water-based non-Newtonian power-law CuO–water nanofluid under the influence of the external magnetic field

Natural convection heat transfer in a square cavity (with wavy or plane wall) filled with non-Newtonian power-law nanofluid has been elucidated for several input parameters like Ra spanning from 10⁵ to 10⁶, power-law index (n) from 0.6 to 1.4, and volume fraction of CuO nanoparticles (?) from to 0 to 0.12. Effect of external magnetic field on heat transfer has been illustrated by varying the Ha from 0 to 90. In the present study, our main objective is to explore the effect of nanoparticles on heat transfer enhancement in non-Newtonian power-law fluid. It is found that the addition of nanoparticles (?) to shear thinning fluid enhances the heat transfer approximately 15% when ? increases from 0 to 0.12 for Ha less than 60 at all Ra. For a shear thickening fluid, the same thing happens for all Ha at any Ra. The average surface Nusselt number for a cavity with wavy wall is less than that of a plane wall for all cases which is not true for the case of local Nusselt number.     

Completely automated multiresolution edge snapper--a new technique for an accurate carotid ultrasound IMT measurement: clinical validation and benchmarking on a multi-institutional database

The aim of this paper is to describe a novel and completely automated technique for carotid artery (CA) recognition, far (distal) wall segmentation, and intima-media thickness (IMT) measurement, which is a strong clinical tool for risk assessment for cardiovascular diseases. The architecture of completely automated multiresolution edge snapper (CAMES) consists of the following two stages: 1) automated CA recognition based on a combination of scale-space and statistical classification in a multiresolution framework and 2) automated segmentation of lumen-intima (LI) and media-adventitia (MA) interfaces for the far (distal) wall and IMT measurement. Our database of 365 B-mode longitudinal carotid images is taken from four different institutions covering different ethnic backgrounds. The ground-truth (GT) database was the average manual segmentation from three clinical experts. The mean distance ± standard deviation of CAMES with respect to GT profiles for LI and MA interfaces were 0.081 ± 0.099 and 0.082 ± 0.197 mm, respectively. The IMT measurement error between CAMES and GT was 0.078 ± 0.112 mm. CAMES was benchmarked against a previously developed automated technique based on an integrated approach using feature-based extraction and classifier (CALEX). Although CAMES underestimated the IMT value, it had shown a strong improvement in segmentation errors against CALEX for LI and MA interfaces by 8% and 42%, respectively. The overall IMT measurement bias for CAMES improved by 36% against CALEX. Finally, this paper demonstrated that the figure-of-merit of CAMES was 95.8% compared with 87.4% for CALEX. The combination of multiresolution CA recognition and far-wall segmentation led to an automated, low-complexity, real-time, and accurate technique for carotid IMT measurement. Validation on a multiethnic/multi-institutional data set demonstrated the robustness of the technique, which can constitute a clinically valid IMT measurement for assistance in atherosclerosis disease management.     

Analysis and characterization of wind-solar-constant torque spring hybridized model

Solar and wind are the most promising renewable energy resources. But their unpredictable and varying nature prevents them from being used as the sole resource for power generation. This paper presents a model of wind and solar thermal hybrid power plant with a spring storage system which is expected to play an efficient role in combating with the drawbacks related to renewable power generation. In the proposed scheme, wind energy is harnessed by a hybrid vertical axis wind turbine, solar energy is utilized by a Stirling engine, and the surplus energy is stored in a winding spring. The paper discusses the working methodologies and analyses the performance of such 2.6 kW hybrid power plant model. It has been observed that the plant is capable of consistently generating 50% of its rated capacity irrespective of limitations in solar and wind resources.     

Development and machinability evaluation of MgO doped Y-ZTA ceramic inserts for high-speed machining of steel

ABSTRACT

In current high productivity manufacturing era, it is necessary to develop non-conventional newer tool materials. Here, an attempt has been made for developing MgO doped zirconia-toughened alumina (Mg-ZTA) using powder metallurgy process route. The 3 mol% yttria stabilized zirconia (YSZ) (10 wt%), alumina (Al₂O₃) (90 wt%) with varying percentage of magnesium oxide (MgO) (0–1 wt%) are mixed to study the phase transformation and uniaxially pressed into square inserts with 0.8 mm nose radius and sintered at 1,600ºC for 1 h in pressure less condition. The maximum hardness of 17.04 GPa, fracture toughness of 5.09 MPa m^1/2 and flexural strength of 502 MPa, respectively, has been reached at 0.6 wt% of MgO due to more metastable tetragonal phase. The performance of the insert has been evaluated by machining AISI 4340 steel (radius 75 mm) in lathe. The performance with respect to flank wear, cutting force and surface roughness is quite impressive at different cutting speed even after 20 min of machining. It can be inferred that MgO doped ZTA insert can be used for medium to high-speed machining in current manufacturing scenario and is very promising to replace carbide or coated carbide inserts in coming days.     

Inhibition of sickle beta-chain (betaS)-dependent polymerization by nonhuman alpha-chains. A superinhibitory mouse-horse chimeric alpha-chain

Horse alpha-chain inhibits sickle beta-chain-dependent polymerization; however, its inhibitory potential is not as high as that of mouse alpha-chain. Horse alpha-(1-30) and alpha-(31-141) segments make, respectively, minor and major contributions to the inhibitory potential of horse alpha-chain. The sum of the inhibitory potential of the two segments does not account for the inhibitory potential of the full-length horse alpha-chain. Although the polymerization inhibitory potential of horse alpha-chain is lower than mouse alpha-chain, the inhibitory potential of horse alpha-(31-141) is comparable to that of mouse alpha-(31-141). When mouse alpha-(1-30) is stitched to horse alpha-(31-141), the product is a chimeric alpha-chain with an inhibitory potential greater than mouse alpha-chain. In contrast, the stitching of horse alpha-(1-30) with mouse alpha-(31-141) had no additional inhibitory potential. Molecular modeling studies of HbS containing the mouse-horse chimeric alpha-chain indicate altered side-chain interactions at the alpha1beta1 interface when compared with HbS. In addition, the AB/GH corner perturbations facilitate a different stereochemistry for the interaction of the epsilon-amino group of Lys-16(alpha) with the beta-carboxyl group of Asp-116(alpha), resulting in a decrease in the accessibility of the side chain of Lys-16(alpha) to the solvent. Based on molecular modeling, we speculate that these perturbations by themselves, or in synergy with the altered conformational aspects of the alpha1beta1 interactions, represent the molecular basis of the superinhibitory potential of the mouse-horse chimeric alpha-chains.     

Bacteria foraging optimization in antenna engineering: An application to array fault finding

Finding fault elements in linear antenna arrays using bacteria foraging optimization (BFO) is presented. One of the better options of array diagnosis is to perform it by measuring the radiated field, because in this case, removal of the array from its working site is not required and thereby not interrupting its normal operation. This task of fault finding from far‐field data is designed as an optimization problem where the difference between the far‐field power pattern obtained for a given configuration of failed element(s) and the measured one is minimized w. r. t. the excitations of the array elements. This set of excitations on comparison with the excitations of the original array gives the idea of the fault position and their type, such as either complete fault or partial fault. BFO being relatively new to microwave community when compared with other soft‐computing techniques, its performance was observed w. r. t. time of computation and convergence of the iterative process. Possibility of finding the faults from random sample points and use of minimum number of sample points for array fault finding are the novelties of the present work. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.     

Multiperson interaction recognition in images: A body keypoint based feature image analysis

Most interaction recognition approaches have been limited to single‐person action classification in videos. However, for still images where motion information is not available, the task becomes more complex. Aiming to this point, we propose an approach for multiperson human interaction recognition in images with keypoint‐based feature image analysis. Proposed method is a three‐stage framework. In the first stage, we propose feature‐based neural network (FCNN) for action recognition trained with feature images. Feature images are body features, that is, effective distances between a set of body part pairs and angular relation between body part triplets, rearranged in 2D gray‐scale image to learn effective representation of complex actions. In the later stage, we propose a voting‐based method for direction encoding to anticipate probable motion in steady images. Finally, our multiperson interaction recognition algorithm identifies which human pairs are interacting with each other using an interaction parameter. We evaluate our approach on two real‐world data sets, that is, UT‐interaction and SBU kinect interaction. The empirical experiments show that results are better than the state‐of‐the‐art methods with recognition accuracy of 95.83% on UT‐I set 1, 92.5% on UT‐I set 2, and 94.28% on SBU clean data set.