Investigation of contact behavior on a model of the dual-mobility artificial hip joint for Asians in different inner liner thicknesses

BACKGROUND The four components that make up the current dual-mobility artificial hip joint design are the femoral head,the inner liner,the outer liner as a metal cover to prevent wear,and the acetabular cup.The acetabular cup and the outer liner were constructed of 316L stainless steel.At the same time,the inner liner was made of ultra-high-molecular-weight polyethylene(UHMWPE).As this new dual-mobility artificial hip joint has not been researched extensively,more tribological research is needed to predict wear.The thickness of the inner liner is a significant component to consider when calculating the contact pressure.AIM To make use of finite element analysis to gain a better understanding of the contact behavior in various inner liner thicknesses on a new model of a dual-mobility artificial hip joint,with the ultimate objective of determining the inner liner thickness that was most suitable for this particular type of dual-mobility artificial hip joint.METHODS In this study,the size of the femoral head was compared between two diameters(28 mm and 36 mm)and eight inner liner thicknesses ranging from 5 mm to 12 mm.Using the finite element method,the contact parameters,including the maximum contact pressure and contact area,have been evaluated in light of the Hertzian contact theory.The simulation was performed statically with dissipated energy and asymmetric behavior.The types of interaction were surface-to-surface contact and normal contact behavior.RESULTS The maximum contact pressures in the inner liner(UHMWPE)at a head diameter of 28 mm and 36 mm are between 3.7-13.5 MPa and 2.7-10.4 MPa,respectively.The maximum von Mises of the inner liner,outer liner,and acetabular cup are 2.4–11.4 MPa,15.7–44.3 MPa,and 3.7–12.6 MPa,respectively,for 28 mm head.Then the maximum von Mises stresses of the 36 mm head are 1.9-8.9 MPa for the inner liner,9.9-32.8 MPa for the outer liner,and 2.6-9.9 MPa for the acetabular cup.A head with a diameter of 28 mm should have an inner liner with a thickness of 12 mm.Whereas the head diameter was 36 mm,an inner liner thickness of 8 mm was suitable.CONCLUSION The contact pressures and von Mises stresses generated during this research can potentially be exploited in estimating the wear of dual-mobility artificial hip joints in general.Contact pressure and von Mises stress reduce with an increasing head diameter and inner liner’s thickness.Present findings would become one of the references for orthopedic surgery for choosing suitable bearing geometric parameter of hip implant.

Detection of Alzheimer’s Disease Progression Using Integrated Deep Learning Approaches

Alzheimer’s disease(AD)is an intensifying disorder that causes brain cells to degenerate early and destruct.Mild cognitive impairment(MCI)is one of the early signs of AD that interferes with people’s regular functioning and daily activities.The proposed work includes a deep learning approach with a multimodal recurrent neural network(RNN)to predict whether MCI leads to Alzheimer’s or not.The gated recurrent unit(GRU)RNN classifier is trained using individual and correlated features.Feature vectors are concate-nated based on their correlation strength to improve prediction results.The feature vectors generated are given as the input to multiple different classifiers,whose decision function is used to predict the final output,which determines whether MCI progresses onto AD or not.Our findings demonstrated that,compared to individual modalities,which provided an average accuracy of 75%,our prediction model for MCI conversion to AD yielded an improve-ment in accuracy up to 96%when used with multiple concatenated modalities.Comparing the accuracy of different decision functions,such as Support Vec-tor Machine(SVM),Decision tree,Random Forest,and Ensemble techniques,it was found that that the Ensemble approach provided the highest accuracy(96%)and Decision tree provided the lowest accuracy(86%).

MXenes and heterostructures-based electrocatalysts for hydrogen evolution reaction:Recent developments and future outlook

The increasing focus on electrocatalysis for sustainable hydrogen(H_(2))production has prompted significant interest in MXenes,a class of two-dimensional(2D)materials comprising metal carbides,carbonitrides,and nitrides.These materials exhibit intriguing chemical and physical properties,including excellent electrical conductivity and a large surface area,making them attractive candidates for the hydrogen evolution reaction(HER).This scientific review explores recent advancements in MXene-based electrocatalysts for HER kinetics.It discusses various compositions,functionalities,and explicit design principles while providing a comprehensive overview of synthesis methods,exceptional properties,and electro-catalytic approaches for H_(2) production via electrochemical reactions.Furthermore,challenges and future prospects in designing MXenes-based electrocatalysts with enhanced kinetics are highlighted,emphasizing the potential of incorporating different metals to expand the scope of electrochemical reactions.This review suggests possible efforts for developing advanced MXenes-based electrocatalysts,particularly for efficient H_(2) generation through electrochemical water-splitting reactions..

Catharanthus roseus:a natural source for the synthesis of silver nanoparticles

Objective:To develop a simple rapid procedure for bioreduction of silver nanoparticles(AgNPs)using aqueous leaves extracts of Catharanthus roseus(C.roseus).Methods:Characterization were determined by using UV-Vis spectrophotometry,scanning electron microscopy(SEM),energy dispersive X-ray and X-ray diffraction.Results:SEM showed the formation of silver nanoparticles with an average size of 67 nm to 48 nm.X-ray diffraction analysis showed that the particles were crystalline in nature with face centered cubic geometry.Conclusions:C.roseus demonstrates strong potential for synthesis of silver nanoparticles by rapid reduction of silver ions(Ag^+ to Ag^0).This study provides evidence for developing large scale commercial production of value-added products for biomedical/nanotechnology-based industries.

Vertically Aligned Silicon Carbide Nanowires/Boron Nitride Cellulose Aerogel Networks Enhanced Thermal Conductivity and Electromagnetic Absorbing of Epoxy Composites

With the innovation of microelectronics technology, the heat dissipation problem inside the device will face a severe test. In this work, cellulose aerogel(CA) with highly enhanced thermal conductivity(TC) in vertical planes was successfully obtained by constructing a vertically aligned silicon carbide nanowires(SiC NWs)/boron nitride(BN) network via the ice template-assisted strategy. The unique network structure of SiC NWs connected to BN ensures that the TC of the composite in the vertical direction reaches 2.21 W m^(-1) K^(-1) at a low hybrid filler loading of 16.69 wt%, which was increased by 890% compared to pure epoxy(EP). In addition, relying on unique porous network structure of CA, EP-based composite also showed higher TC than other comparative samples in the horizontal direction. Meanwhile, the composite exhibits good electrically insulating with a volume electrical resistivity about 2.35 × 10^(11) Ω cm and displays excellent electromagnetic wave absorption performance with a minimum reflection loss of-21.5 dB and a wide effective absorption bandwidth(<-10 dB) from 8.8 to 11.6 GHz. Therefore, this work provides a new strategy for manufacturing polymer-based composites with excellent multifunctional performances in microelectronic packaging applications.

An Intelligent Predictive Model-Based Multi-Response Optimization of EDM Process

Electrical Discharge Machining(EDM)is a popular non-traditional machining process that is widely used due to its ability to machine hard and brittle materials.It does not require a cutting tool and can machine complex geometries easily.However,it suffers from drawbacks like a poor rate of machining and excessive tool wear.In this research,an attempt is made to address these issues by using an intelligent predictive model coupled global optimization approach to predict suitable combinations of input parameters(current,pulse on-time and pulse off-time)that would effectively increase the material removal rate and minimize the tool wear.The predictive models,which are based on the symbolic regression approach exploit the machine intelligence of Genetic Programming(GP).As compared to traditional polynomial response surface(PRS)predictive models,the GP predictive models show compactness as well as better prediction capability.The developed GP predictive models are deployed in conjunction with NSGA-II to predict Pareto optimal solutions.

Automation of immunohistochemical evaluation in breast cancer using image analysis

AIM:To automate breast cancer diagnosis and to study the inter-observer and intra-observer variations in the manual evaluations.METHODS:Breast tissue specimens from sixty cases were stained separately for estrogen receptor(ER),progesterone receptor(PR)and human epidermal growth factor receptor-2(HER-2/neu).All cases were assessed by manual grading as well as image analysis.The manual grading was performed by an experienced expert pathologist.To study inter-observer and intra-observer variations,we obtained readings from another pathologist as the second observer from a different laboratory who has a little less experience than the first observer.We also took a second reading from the second observer to study intra-observer variations.Image analysis was carried out using in-house developed software(TissueQuant).A comparison of the results from image analysis and manual scoring of ER,PR and HER-2/neu was also carried out.RESULTS:The performance of the automated analysis in the case of ER,PR and HER-2/neu expressions was compared with the manual evaluations.The performance of the automated system was found to correlate well with the manual evaluations.The inter-observer variations were measured using Spearman correlation coefficient r and 95%confidence interval.In the case of ER expression,Spearman correlation r=0.53,in the case of PR expression,r=0.63,and in the case of HER-2/neu expression,r=0.68.Similarly,intra-observer variations were also measured.In the case of ER,PR and HER-2/neu expressions,r=0.46,0.66 and 0.70,respectively.CONCLUSION:The automation of breast cancer diagnosis from immunohistochemically stained specimens is very useful for providing objective and repeatable evaluations.

Fluid-Structure Interaction in Problems of Patient Specific Transcatheter Aortic Valve Implantation with and Without Paravalvular Leakage Complication

Paravalvular Leakage(PVL)has been recognized as one of the most dangerous complications in relation to Transcathether Aortic Valve Implantation(TAVI)activities.However,data available in the literature about Fluid Structure Interaction(FSI)for this specific problem are relatively limited.In the present study,the fluid and structure responses of the hemodynamics along the patient aorta model and the aortic wall deformation are studied with the aid of numerical simulation taking into account PVL and 100%TAVI valve opening.In particular,the aorta without valve(AWoV)is assumed as the normal condition,whereas an aorta with TAVI 26 mm for 100%Geometrical Orifice Area(GOA)is considered as the patient aorta with PVL complication.A 3D patient-specific aorta model is elaborated using the MIMICS software.Implantation of the identical TAVI valve of Edward SAPIEN XT 26(Edwards Lifes ciences,Irvine,California)is considered.An undersized 26 mm TAVI valve with 100%valve opening is selected to mimic the presence of PVL at the aortic annulus.The present research indicates that the existence of PVL can increase the blood velocity,pressure drop and WSS in comparison to normal conditions,thereby paving the way to the development of recirculation flow,thrombus formation,aorta wall collapse,aortic rupture and damage of endothelium.

Investigation of Coronavirus Deposition in Realistic Human Nasal Cavity and Impact of Social Distancing to Contain COVID-19:A Computational Fluid Dynamic Approach

The novel coronavirus responsible for COVID-19 has spread to several countries within a considerably short period.The virus gets deposited in the human nasal cavity and moves to the lungs that might be fatal.As per safety guidelines by theWorld Health Organization(WHO),social distancing has emerged as one of the major factors to avoid the spread of infection.However,different guidelines are being followed across the countries with regards to what should be the safe distance.Thus,the current work is an attempt to understand the virus deposition pattern in the realistic human nasal cavity and also to find the impact of distance that could be termed as a safety measure.This study is performed usingComputationalFluid Dynamics as a solution tool to investigate the impact of COVID-19 deposition(i)On a realistic 3D human upper airway model and(ii)2D social distancing protocol for a distance of 0.6,1.2,1.8,and 2.4 m.The results revealed that the regional deposition flux within the nasal cavity was predominantly observed in the external nasal cavity and nasopharyngeal section.Frequent flushing of these regions with saltwater substitutes can limit contamination in healthy individuals.The safe distancing limit estimated with 1 m/s airflow was about 1.8 m.The extensive deposition was observed for distances less than 1.8 m in this study,emphasizing the fact that social distancing advisories are not useful and do not take into account the external dynamics associated with airflow.

Influence of postural changes on haemodynamics in internal carotid artery bifurcation aneurysm using numerical methods

Cerebral intracranial aneurysms are serious problems that can lead to stroke,coma,and even death.The effect of blood flow on cerebral aneurysms and their relationship with rupture are unknown.In addition,postural changes and their relevance to haemodynamics of blood flow are difficult to measure in vivo using clinical imaging alone.Computational simulations investigating the detailed haemodynamics in cerebral aneurysms have been developed in recent times not only to understand the progression and rupture but also for clinical evaluation and treatment.In the present study,the haemodynamics of a patient-specific case of a large aneurysm on the left side internal carotid bifurcation(LICA)and no aneurysm on the right side internal carotid bifurcation(RICA)was investigated.The simulation of these patient-specific models using fluid–structure interaction provides a valuable comparison of flow behavior between normal and aneurysm models.The influences of postural changes were investigated during standing,sleeping,and head-down(HD)position.Significant changes in flow were observed during the HD position and quit high arterial blood pressure in the internal carotid artery(ICA)aneurysm model was established when compared to the normal ICA model.The velocity increased abruptly during the HD position by more than four times(LICA and RICA)and wall shear stress by four times(LICA)to ten times(RICA).The complex spiral flow and higher pressures prevailing within the dome increase the risk of aneurysm rupture.

Hybrid Metamodel—NSGA-III—EDAS Based Optimal Design of Thin Film Coatings

In this work,diamond-like carbon(DLC)thin film coatings are deposited on silicon substrates by using plasma-enhanced chemical vapour deposition(PECVD)technique.By varying the hydrogen(H2)flow rate,CH4−Argon(Ar)flow rate and deposition temperature(Td)as per a Box-Behnken experimental design(BBD),15 DLC deposition experiments are carried out.The Young’s modulus(E)and the coefficient of friction(COF)for the DLCs are measured.By using a second-order polynomial regression approach,two metamodels are built for E and COF,that establish them as functions of H2 flow rate,CH4-Ar flow rate and Td.A non-dominated sorting genetic algorithm(NSGA-III)is used to obtain a set of Pareto solutions for the multi-objective optimization of E maximization and COF minimization.According to various practical scenarios,evaluation based on distance from average solution(EDAS)approach is used to identify the most feasible solutions out of the Pareto solution set.Confirmation experiments are conducted which shows the efficacy of the polynomial regression—NSGA-III—EDAS hybrid approach.The surface morphology of the DLCs deposited as per the optimal predictions is also studied by using atomic force microscopy.

Erosion corrosion control of 6061 aluminum alloy in multi-phase jet impingement conditions with eco-friendly green inhibitor

Erosion corrosion performance of 6061 aluminum alloy in simulated sea water slurry was investigated under multi-phase jet impingement conditions. The main objective of the work is to study erosion–corrosion of a material with engineering application and mitigate it using eco-friendly green inhibitor. Experiments were performed with the sand concentration of 0.3% and 0.3 μm size. The effect of temperature and flow rate on the performance of inhibitor was explored. Electrochemical methods were adopted for erosion-corrosion measurements. Experiments revealed that starch could mitigate erosion-corrosion with a maximum reduction efficiency of 58% at temperature of 303 K and flow rate of 4 L·min–1. Inhibition efficiency decreased with increase in flowrate and temperature. EIS spectrum demonstrated that the corrosion process in the presence on inhibitor was both charge transfer and mass transfer controlled. A key role of hydrodynamics in the performance of corrosion inhibitor was confirmed by the present study.

An ecofriendly approach for corrosion control of 6061 Al-15%(v)SiC(P)composite and its base alloy

Corrosion inhibition characteristics of bio polymer dextran was studied for the corrosion control of 6061 Al-15%_((v)) SiC_((P)) composite and its base alloy in 1 mol·L^(-1) HCl. Standard electrochemical techniques such as potentiodynamic polarization(PDP) measurements and electrochemical impedance spectroscopy(EIS) method were adopted for corrosion rate measurement. Surface morphology was studied by scanning electron microscopy(SEM) and elemental mapping was done by energy dispersive X-ray(EDX) analysis. Suitable mechanism was proposed for corrosion and inhibition process. Results indicated that dextran acts as an excellent anticorrosive agent for the corrosion control of 6061 Al-15%_((v)) SiC_((P)) composite, with maximum inhibition efficiency of 91% for the concentration of 0.4 g·L^(-1) at 303 K. Dextran acted as a mixed type of inhibitor, and got physically adsorbed both on composite and base alloy by obeying Langmuir adsorption isotherm. Dextran is proved to be a green inhibitor with environmental and economic benefits.

Steam as coolant and lubricant in turning of metal matrix composites

Green cutting has become focus of attention in ecological and environmental protection. Steam is cheap, pollu-tion-free and eco-friendly, and then is a good and economical coolant and lubricant. Steam generator and steam feeding system were developed to generate and feed steam. Comparative experiments were carried out in cutting AA6061-15 vol.% SiC (25 μm particle size), with cubic boron nitride (CBN) insert KB-90 grade under the conditions of compressed air, oil water emulsion, steam as coolant and lubricant, and dry cutting, respectively. The experimental results show that, with steam as coolant and lu-bricant, gradual reduction in the cutting force, friction coefficient, surface roughness and cutting temperature values were observed. Further, there was reduction in built up edge formation. It is proved that use of water steam as coolant and lubricant is environ-mentally friendly.

Entrance Region Flow of Herschel-Bulkley Fluid in an Annular Cylinder

The entrance region flow of a Herschel-Bulkley fluid in an annular cylinder has been investigated numerically without making prior assumptions on the form of velocity profile within the boundary layer region. This velocity distribution is determined as part of the procedure by cross sectional integration of the momentum differential equation for a given distance z from the channel entrance. Using the macroscopic mass and momentum balance equation, the entrance length at each cross section of the entrance region of the annuli and pressure distribution have been calculated for specific values of Herschel-Bulkley number and various values of aspect ratio and flow behavior index. The effects of non-Newtonian characteristics and channel width on the velocity profile, pressure distribution and the entrance length have been discussed.

An AW-HARIS Based Automated Segmentation of Human Liver Using CT Images

In the digestion of amino acids,carbohydrates,and lipids,as well as protein synthesis from the consumed food,the liver has many diverse responsibilities and functions that are to be performed.Liver disease may impact the hormonal and nutritional balance in the human body.The earlier diagnosis of such critical conditions may help to treat the patient effectively.A computationally efficient AW-HARIS algorithm is used in this paper to perform automated segmentation of CT scan images to identify abnormalities in the human liver.The proposed approach can recognize the abnormalities with better accuracy without training,unlike in supervisory procedures requiring considerable computational efforts for training.In the earlier stages,the CT images are pre-processed through an Adaptive Multiscale Data Condensation Kernel to normalize the underlying noise and enhance the image’s contrast for better segmentation.Then,the preliminary phase’s outcome is being fed as the input for the Anisotropic Weighted—Heuristic Algorithm for Real-time Image Segmentation algorithm that uses texture-related information,which has resulted in precise outcome with acceptable computational latency when compared to that of its counterparts.It is observed that the proposed approach has outperformed in the majority of the cases with an accuracy of 78%.The smart diagnosis approach would help the medical staff accurately predict the abnormality and disease progression in earlier ailment stages.

Kelvin-Helmholtz Instability in a Fluid Layer Bounded Above by a Porous Layer and Below by a Rigid Surface in Presence of Magnetic Field

We study the stability of an interface between two fluids of different densities flowing parallel to each other in the presence of a transverse magnetic field. A simple theory based on fully developed flow approximations is used to de-rive the dispersion relation for the growth rate of KHI. We replace the effect of boundary layer with Beavers and Joseph slip condition. The dispersion relation is derived using suitable boundary and surface conditions and results are discussed graphically. The magnetic field is found to be stabilizing and the influence of the various parameters of the problem on the interface stability is thoroughly analyzed. These are favorable to control the surface instabilities in many practical applications discussed in this paper.

Effect of Magnetic Field on Kelvin-Helmholtz Instability in a Couple-Stress Fluid Layer Bounded Above by a Porous Layer and Below by a Rigid Surface

Kelvin-Helmholtz instability (KHI) appears in stratified two-fluid flow at surface. When the relative velocity is higher than the critical relative velocity, the growth of waves occurs. It is found that magnetic field has a stabilization effect whereas the buoyancy force has a destabilization effect on the KHI in the presence of sharp inter-face. The RT instability increases with wave number and flow shear, and acts much like a KHI when destabilizing effect of sheared flow dominates. It is shown that both of ablation velocity and magnetic field have stabilization effect on RT instability in the presence of continued interface. In this paper, we study the effect of magnetic field on Kelvin-Helmholtz instability (KHI) in a Couple-stress fluid layer above by a porous layer and below by a rigid surface. A simple theory based on fully developed flow approximations is used to derive the dispersion relation for the growth rate of KHI. We replace the effect of boundary layer with Beavers and Joseph slip condition at the rigid surface. The dispersion relation is derived using suitable boundary and surface conditions and results are discussed graphically. The stabilization effect of magnetic field takes place for whole waveband and becomes more significant for the short wavelength. The growth rate decreases as the density scale length increases. The stabilization effect of magnetic field is more significant for the short density scale length.

Performance Comparison of a QoS Aware Routing Protocol for Wireless Sensor Networks

Quality of Service (QoS) in Wireless Sensor Networks (WSNs) is a challenging area of research because of the limited availability of resources in WSNs. The resources in WSNs are processing power, memory, bandwidth, energy, communication capacity, etc. Delay is an important QoS parameter for delivery of delay sensitive data in a time constraint sensor network environment. In this paper, an extended version of a delay aware routing protocol for WSNs is presented along with its performance comparison with different deployment scenarios of sensor nodes, taking IEEE802.15.4 as the underlying MAC protocol. The performance evaluation of the protocol is done by simulation using ns-2 simulator.

Chaotic Flower Pollination with Deep Learning Based COVID-19 Classification Model

The Coronavirus Disease(COVID-19)pandemic has exposed the vulnerabilities of medical services across the globe,especially in underdeveloped nations.In the aftermath of the COVID-19 outbreak,a strong demand exists for developing novel computer-assisted diagnostic tools to execute rapid and cost-effective screenings in locations where many screenings cannot be executed using conventional methods.Medical imaging has become a crucial component in the disease diagnosis process,whereas X-rays and Computed Tomography(CT)scan imaging are employed in a deep network to diagnose the diseases.In general,four steps are followed in image-based diagnostics and disease classification processes by making use of the neural networks,such as network training,feature extraction,model performance testing and optimal feature selection.The current research article devises a Chaotic Flower Pollination Algorithm with a Deep Learning-Driven Fusion(CFPADLDF)approach for detecting and classifying COVID-19.The presented CFPA-DLDF model is developed by integrating two DL models to recognize COVID-19 in medical images.Initially,the proposed CFPA-DLDF technique employs the Gabor Filtering(GF)approach to pre-process the input images.In addition,a weighted voting-based ensemble model is employed for feature extraction,in which both VGG-19 and the MixNet models are included.Finally,the CFPA with Recurrent Neural Network(RNN)model is utilized for classification,showing the work’s novelty.A comparative analysis was conducted to demonstrate the enhanced performance of the proposed CFPADLDF model,and the results established the supremacy of the proposed CFPA-DLDF model over recent approaches.