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Acetabular cup size trends in total hip arthroplasty

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World Journal of Orthopedics 2024年第1期15卷 39-44页

作者： Daniel patrick McKenna alex p.ice Timothy McAleese Darren Dahly paul McKenna May Cleary Department of Trauma and Orthopaedics University Hospital WaterfordWaterford X91 ER8EIreland Department of Epidemiology and public Health University College CorkCork T12 XF62Ireland

BACKGROUND Total hip arthroplasty(THA)is a common procedure for end stage *** learning curve for THA is complex and *** of the most difficult skills to master is acetabular *** wish to identify if experience in arthroplasty leads to preservation of more bone *** To investigate if increasing surgeon experience will predict an ever decreasing acetabular cup *** A retrospective case series of four attending orthopaedic surgeons was *** uncemented elective total hip arthroplasties since appointment were selected for *** size of acetabular cup used was noted and logistic regression was used to identify if a trend to smaller cups *** A total of 1614 subjects were included with a mean age of 64 *** cups were on average 0.18mm smaller per year(95%confidence interval-0.25 to-0.11,pp sizes to decrease 0.27 mm/year for surgeon A,0.02 mm/year for surgeon B,0.15 mm/year for surgeon C and 0.29 mm/year for surgeon *** of the four surgeons had a more pronounced trend to smaller cups for male subjects than their female *** We found increasing surgeon experience to be associated with an ever-decreasing acetabular cup *** acetabular cup size may act as a surrogate marker of surgical proficiency by virtue of decreased acetabular reaming.

关键词： Hip Arthroplasty Acetabulum Cup Learning

Enhanced entropy generation and heat transfer characteristics of magnetic nano-encapsulated phase change materials in latent heat thermal energy storage systems

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Applied Mathematics and Mechanics(English Edition) 2024年第6期45卷 1051-1070页

作者： p.S.REDDY p.SREEDEVI Department of Mathematics Rajeev Gandhi Memorial College of Engineering and TechnologyNandyal 518501India

The objective of the current study is to investigate the importance of entropy generation and thermal radiation on the patterns of velocity,isentropic lines,and temperature contours within a thermal energy storage device filled with magnetic nanoencapsulated phase change materials(NEpCMs).The versatile finite element method(FEM)is implemented to numerically solve the governing *** effects of various parameters,including the viscosity parameter,ranging from 1 to 3,the thermal conductivity parameter,ranging from 1 to 3,the Rayleigh parameter,ranging from 102 to 3×10^(2),the radiation number,ranging from 0.1 to 0.5,the fusion temperature,ranging from 1.0 to 1.2,the volume fraction of NEpCMs,ranging from 2%to 6%,the Stefan number,ranging from 1 to 5,the magnetic number,ranging from 0.1 to 0.5,and the irreversibility parameter,ranging from 0.1 to 0.5,are examined in detail on the temperature contours,isentropic lines,heat capacity ratio,and velocity ***,the heat transfer rates at both the cold and hot walls are analyzed,and the findings are presented *** results indicate that the time taken by the NEpCMs to transition from solid to liquid is prolonged inside the chamber region as the fusion temperatureθf ***,the contours of the heat capacity ratio Cr decrease with the increase in the Stefan number Ste.

关键词： volume fraction of nano-encapsulated phase change material(NEpCM) radiation Stefan number heat capacity ratio entropy generation

A Hybrid Optimization Approach of Single point Incremental Sheet Forming of AISI 316L Stainless Steel Using Grey Relation Analysis Coupled with principal Component Analysiss

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Journal of Wuhan University of Technology(Materials Science) 2024年第1期39卷 160-166页

作者： A Visagan p Ganesh Department of production Technology Madras Institute of TechnologyChennai-600044India

We investigated the parametric optimization on incremental sheet forming of stainless steel using Grey Relational Analysis(GRA) coupled with principal Component Analysis(pCA). AISI 316L stainless steel sheets were used to develop double wall angle pyramid with aid of tungsten carbide tool. GRA coupled with pCA was used to plan the experiment conditions. Control factors such as Tool Diameter(TD), Step Depth(SD), Bottom Wall Angle(BWA), Feed Rate(FR) and Spindle Speed(SS) on Top Wall Angle(TWA) and Top Wall Angle Surface Roughness(TWASR) have been studied. Wall angle increases with increasing tool diameter due to large contact area between tool and workpiece. As the step depth, feed rate and spindle speed increase,TWASR decreases with increasing tool diameter. As the step depth increasing, the hydrostatic stress is raised causing severe cracks in the deformed surface. Hence it was concluded that the proposed hybrid method was suitable for optimizing the factors and response.

关键词： single point incremental forming AISI 316L taguchi grey relation analysis principal component analysis surface roughness scanning electron microscopy

Cryogenic and conventional milling of AZ91 magnesium alloy

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Journal of Magnesium and Alloys 2024年第6期12卷 2503-2519页

作者： Vikas Marakini Srinivasa pai p Gururaj Bolar Bhaskara p Achar Department of Mechanical Engineering Nitte(Deemed to be University)NMAM Institute of Technology(NMAMIT)Nitte 574110India Department of Mechanical and Industrial Engineering Manipal Institute of TechnologyManipal Academy of Higher EducationManipal 576104India

Use of magnesium is the need of the hour due to its low density as well as its high strength-to-weight and stiffness-to-weight ratio *** study focuses on the effectiveness of liquid nitrogen(LN_(2))assisted cryogenic machining on the surface integrity(SI)characteristics of AZ91 magnesium *** milling using uncoated carbide inserts have been performed under liquid nitrogen(LN_(2))assisted cryogenic condition and compared with conventional(dry)*** are performed using machining parameters in terms of cutting speeds of 325,475,625 m/min,feed rates of 0.05,0.1,0.15 mm/teeth and depth of cuts of 0.5,1,1.5 mm *** significant surface integrity characteristics such as surface roughness,microhardness,microstructure,and residual stresses have been *** of SI characteristics with respect to milling parameters have been identified using statistical technique such as ANOVA and signal-to-noise(S/N)ratio ***,the multi criteria decision making(MCDM)techniques such as additive ratio assessment method(ARAS)and complex proportional assessment(COpRAS)have been utilized to identify the optimal conditions for milling AZ91 magnesium alloy under both dry and cryogenic *** of LN_(2)during machining,resulted in reduction in machining temperature by upto 29%with a temperature drop from 251.2℃under dry condition to 178.5℃in cryogenic *** showed the advantage of performing cryogenic milling in improving the surface integrity to a significant *** machining considerably minimized the roughness by upto 28%and maximised the microhardness by upto 23%,when compared to dry *** speed has caused significant impact on surface roughness(95.33%-dry,92.92%-cryogenic)and surface microhardness(80.33%-dry,82.15%-cryogenic).Due to the reduction in machining temperature,cryogenic condition resulted in compressive residual stresses(maximumσ║=-113 Mpa)on the alloy *** indicate no

关键词： Magnesium alloy Cryogenic machining Roughness Microhardness Microstructure Residual stress Multi criteria decision making

On the functions of astrocyte-mediated neuronal slow inward currents

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Neural Regeneration Research 2024年第12期19卷 2602-2612页

作者： Balázs pál Department of physiology Faculty of MedicineUniversity of DebrecenDebrecenHungary

Slow inward currents are known as neuronal excitatory currents mediated by glutamate release and activation of neuronal extra synaptic N-met hyl-D-aspartate receptors with the contribution of *** events are significantly slower than the excitatory postsynaptic *** of slow inward currents are determined by seve ral factors including the mechanisms of astrocytic activation and glutamate release,as well as the diffusion pathways from the release site towards the extra synaptic recepto *** are stimulated by neuronal network activity,which in turn excite neurons,forming an astrocyte-neuron feedback *** as a consequence of brain edema,astrocytic swelling can also induce slow inward currents under pathological *** is a growing body of evidence on the roles of slow inward currents on a single neuron or local network *** events often occur in synchro ny on neurons located in the same astrocytic *** synchronization of neuronal excitability,slow inward currents also set synaptic strength via eliciting timing-dependent synaptic *** addition,slow inward currents are also subject to non-synaptic plasticity triggered by long-la sting stimulation of the excitatory *** note,there might be important regionspecific differences in the roles and actions triggering slow inward *** greater networks,the pathophysiological roles of slow inward currents can be better understood than physiological *** inward currents are identified in the pathophysiological background of autism,as slow inward currents drive early hypersynchrony of the neural *** inward currents are significant contributors to paroxysmal depolarizational shifts/interictal *** events are related to epilepsy,but also found in Alzheimer's disease,parkinson's disease,and stroke,leading to the decline of cognitive *** with features overlapping with slow inward currents(excitatory,N-methyl-Dasp

关键词： astrocyte cortical spreading depolarization gliotransmission glutamate neural synchronization NMDA receptor paroxysmal depolarizational shift slow inward current

An Efficient Approach to Escalate the Speed of Training Convolution Neural Networks

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China Communications 2024年第2期21卷 258-269页

作者： p pabitha Anusha Jayasimhan Department of Computer Technology Anna UniversityMadras Institute of Technology CampusChennai 600044India

Deep neural networks excel at image identification and computer vision applications such as visual product search, facial recognition, medical image analysis, object detection, semantic segmentation,instance segmentation, and many others. In image and video recognition applications, convolutional neural networks(CNNs) are widely employed. These networks provide better performance but at a higher cost of computation. With the advent of big data, the growing scale of datasets has made processing and model training a time-consuming operation, resulting in longer training times. Moreover, these large scale datasets contain redundant data points that have minimum impact on the final outcome of the model. To address these issues, an accelerated CNN system is proposed for speeding up training by eliminating the noncritical data points during training alongwith a model compression method. Furthermore, the identification of the critical input data is performed by aggregating the data points at two levels of granularity which are used for evaluating the impact on the model *** experiments are conducted using the proposed method on CIFAR-10 dataset on ResNet models giving a 40% reduction in number of FLOps with a degradation of just 0.11% accuracy.

关键词： CNN deep learning image classification model compression