3shape Trios 3口内扫描和传统硅橡胶在牙体缺损修复中的失败原因分析

目的分析并比较3shape Trios 3口内扫描和传统硅橡胶在牙体缺损修复中的失败原因,为临床取模以及口内扫描仪性能改善提供参考依据。方法回顾性分析2021年1月至2023年10月实施口腔固定修复治疗并返工的200例患者为研究对象,以取模方式将其分为口扫组(n=97)和硅橡胶组(n=103)。口扫组给予3shape Trios 3口内扫描,硅橡胶组给予传统硅橡胶。比较两组在牙体缺损修复中的失败原因。结果两组的牙体缺损修复失败分布情况比较,差异具有统计学意义(P<0.05);口扫组中,龈下缺损修复失败占比高于龈上(P<0.05)。两组的龈下缺损修复失败原因比较,差异具有统计学意义(P<0.05)。结论相较于传统硅橡胶,3shape Trios 3口内扫描在龈上缺损修复中更有优势,但在龈下缺损修复中,硅橡胶应用效果更佳。

基于性格分析DISC理论的临床带教模式对护生核心能力的影响

目的:探讨基于性格分析DISC理论的临床带教模式对护生核心能力的影响。方法:选取2022年1月-12月在江苏省某三级甲等医院全科医学科的96名实习护生为研究对象,根据实习先后顺序分为试验组48人和对照组48人。在临床带教过程中,对照组实施传统带教方法,试验组实施基于性格分析DISC理论的临床带教模式,比较两组的核心能力、理论成绩、护理技能操作成绩、带教管理质量及带教满意度。结果:干预结束后,试验组核心能力、理论成绩、护理技能操作成绩、带教管理质量总分均高于对照组(P<0.05)。结论:将性格分析DISC理论应用于临床实习带教中,有利于培养护生的核心能力和提高其理论成绩、护理技能操作成绩及带教管理质量。

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Computer vision-aided DEM study on the compaction characteristics of graded subgrade filler considering realistic coarse particle shapes

The compaction quality of subgrade filler strongly affects subgrade settlement.The main objective of this research is to analyze the macro-and micro-mechanical compaction characteristics of subgrade filler based on the real shape of coarse particles.First,an improved Viola-Jones algorithm is employed to establish a digitalized 2D particle database for coarse particle shape evaluation and discrete modeling purposes of subgrade filler.Shape indexes of 2D subgrade filler are then computed and statistically analyzed.Finally,numerical simulations are performed to quantitatively investigate the effects of the aspect ratio(AR)and interparticle friction coefficient(μ)on the macro-and micro-mechanical compaction characteristics of subgrade filler based on the discrete element method(DEM).The results show that with the increasing AR,the coarse particles are narrower,leading to the increasing movement of fine particles during compaction,which indicates that it is difficult for slender coarse particles to inhibit the migration of fine particles.Moreover,the average displacement of particles is strongly influenced by the AR,indicating that their occlusion under power relies on particle shapes.The dis-placement and velocity of fine particles are much greater than those of the coarse particles,which shows that compaction is primarily a migration of fine particles.Under the cyclic load,the interparticle friction coefficientμhas little effect on the internal structure of the sample;under the quasi-static loads,however,the increase inμwill lead to a significant increase in the porosity of the sample.This study could not only provide a novel approach to investigate the compaction mechanism but also establish a new theoretical basis for the evaluation of intelligent subgrade compaction.

Artificial neural network algorithm for pulse shape discrimination in 2πα and 2πβ particle surface emission rate measurements

To enhance the accuracy of 2πα and 2πβ particle surface emission rate measurements and address the identification issues of nuclides in conventional methods, this study introduces two artificial neural network(ANN) algorithms: back-propagation(BP) and genetic algorithm-based back-propagation(GA-BP). These algorithms classify pulse signals from distinct α and β particles. Their discrimination efficacy is assessed by simulating standard pulse signals and those produced by contaminated sources, mixing α and β particles within the detector. This study initially showcases energy spectrum measurement outcomes, subsequently tests the ANNs on the measurement and validation datasets, and contrasts the pulse shape discrimination efficacy of both algorithms. Experimental findings reveal that the proportional counter's energy resolution is not ideal, thus rendering energy analysis insufficient for distinguishing between 2πα and 2πβ particles. The BP neural network realizes approximately 99% accuracy for 2πα particles and approximately 95% for 2πβ particles, thus surpassing the GA-BP's performance. Additionally, the results suggest enhancing β particle discrimination accuracy by increasing the digital acquisition card's threshold lower limit. This study offers an advanced solution for the 2πα and 2πβ surface emission rate measurement method, presenting superior adaptability and scalability over conventional techniques.

基于改进Alpha Shape算法的点云数据岛屿边界提取

针对机载LiDAR点云的岛屿岸线提取过程复杂、附属岛屿岸线难以提取等问题,提出一种基于改进Alpha Shape算法的点云数据岛屿边界提取方法。首先利用布料模拟滤波算法剔除非岛屿点云数据,通过欧式聚类进行不同岛屿的提取,再将岛屿点云数据投影至二维平面,并根据岛屿点云构建格网。在此基础上使用自适应Alpha Shape算法,对提取出的岛屿点云进行边界提取,即可得到岛屿的岸线轮廓。选取新西兰的玛提尤/萨姆斯岛作为研究区域,并将本文算法与Alpha Shape算法进行对比,结果表明:本文算法提取岛屿边界点云的精准度为97.78%,可以准确地提取岛屿岸线,为海岛规划提供参考。

An Improved Deep Learning Framework for Automated Optic Disc Localization and Glaucoma Detection

Glaucoma disease causes irreversible damage to the optical nerve and it has the potential to cause permanent loss of vision.Glaucoma ranks as the second most prevalent cause of permanent blindness.Traditional glaucoma diagnosis requires a highly experienced specialist,costly equipment,and a lengthy wait time.For automatic glaucoma detection,state-of-the-art glaucoma detection methods include a segmentation-based method to calculate the cup-to-disc ratio.Other methods include multi-label segmentation networks and learning-based methods and rely on hand-crafted features.Localizing the optic disc(OD)is one of the key features in retinal images for detecting retinal diseases,especially for glaucoma disease detection.The approach presented in this study is based on deep classifiers for OD segmentation and glaucoma detection.First,the optic disc detection process is based on object detection using a Mask Region-Based Convolutional Neural Network(Mask-RCNN).The OD detection task was validated using the Dice score,intersection over union,and accuracy metrics.The OD region is then fed into the second stage for glaucoma detection.Therefore,considering only the OD area for glaucoma detection will reduce the number of classification artifacts by limiting the assessment to the optic disc area.For this task,VGG-16(Visual Geometry Group),Resnet-18(Residual Network),and Inception-v3 were pre-trained and fine-tuned.We also used the Support Vector Machine Classifier.The feature-based method uses region content features obtained by Histogram of Oriented Gradients(HOG)and Gabor Filters.The final decision is based on weighted fusion.A comparison of the obtained results from all classification approaches is provided.Classification metrics including accuracy and ROC curve are compared for each classification method.The novelty of this research project is the integration of automatic OD detection and glaucoma diagnosis in a global method.Moreover,the fusion-based decision system uses the glaucoma detection result obtained using several convolutional deep neural networks and the support vector machine classifier.These classification methods contribute to producing robust classification results.This method was evaluated using well-known retinal images available for research work and a combined dataset including retinal images with and without pathology.The performance of the models was tested on two public datasets and a combined dataset and was compared to similar research.The research findings show the potential of this methodology in the early detection of glaucoma,which will reduce diagnosis time and increase detection efficiency.The glaucoma assessment achieves about 98%accuracy in the classification rate,which is close to and even higher than that of state-of-the-art methods.The designed detection model may be used in telemedicine,healthcare,and computer-aided diagnosis systems.

Late Diagnosis of Congenital Optic Disc Abnormalities

Purpose: To show epidemiological and imaging aspects of congenital optic disc abnormalities diagnosed late. Method: It was a retrospective study, including all patients with congenital optic disc abnormalities diagnosed at a late age between January 2020 and October 2022 at the eye center of Abass Ndao Hospital. Complete ophthalmological examination was performed with eye imaging according to the cases. Results: 09 patients (10 eyes) were diagnosed with congenital optic disc abnormalities. The mean age was 29 years, with a sex ratio of 0.8. Three patients had consulted for unilateral decreased visual acuity since childhood, two for sudden vision loss and in four cases the diagnosis was fortuitous. Visual acuity was ranged from 1/200 to 20/20. Fundus examination showed myelinated retinal nerve fibers in four eyes, optic disc pit in three eyes including two complicated by maculopathy, two cases of morning glory syndrome and a case of pseudoduplication of the optic disc. Optical coherence tomography, ocular ultrasound B and OCT-Angiography were performed according to the cases. Conclusion: Congenital optic disc abnormalities are often diagnosed late. They are potentially amblyogenic and complications are not rare, worsening the visual prognosis. Their screening should be systematic by ophthalmological examination in newborns.

J-shaped association between dietary thiamine intake and the risk of cognitive decline in cognitively healthy,older Chinese individuals

Background The prospective association of dietary thiamine intake with the risk of cognitive decline among the general older adults remains uncertain.Aims To investigate the association between dietary thiamine intake and cognitive decline in cognitively healthy,older Chinese individuals.Methods The study included a total of 3106 participants capable of completing repeated cognitive function tests.Dietary nutrient intake information was collected through 3-day dietary recalls and using a 3-day food-weighed method to assess cooking oil and condiment consumption.Cognitive decline was defined as the 5-year decline rate in global or composite cognitive scores based on a subset of items from the Telephone Interview for Cognitive Status-modified.Results The median follow-up duration was 5.9 years.There was a J-shaped relationship between dietary thiamine intake and the 5-year decline rate in global and composite cognitive scores,with an inflection point of 0.68 mg/day(95%confidence interval(Cl):0.56 to 0.80)and a minimal risk at 0.60-1.00 mg/day of dietary thiamine intake.Before the inflection point,thiamine intake was not significantly associated with cognitive decline.Beyond the inflection point,each unit increase in thiamine intake(mg/day)was associated with a significant decrease of 4.24(95%Cl:2.22 to 6.27)points in the global score and 0.49(95%Cl:0.23 to 0.76)standard units in the composite score within 5 years.A stronger positive association between thiamine intake and cognitive decline was observed in those with hypertension,obesity and those who were non-smokers(all p<0.05).Conclusions This study revealed a J-shaped association between dietary thiamine intake and cognitive decline in cognitively healthy,older Chinese individuals,with an inflection point at 0.68 mg/day and a minimal risk at 0.60-1.00 mg/day of dietary thiamine intake.

Thermal fatigue and wear of compacted graphite iron brake discs with various thermomechanical properties

The increase in payload capacity of trucks has heightened the demand for cost-effective yet high performance brake discs.In this work,the thermal fatigue and wear of compacted graphite iron brake discs were investigated,aiming to provide an experimental foundation for achieving a balance between their thermal and mechanical properties.Compacted graphite iron brake discs with different tensile strengths,macrohardnesses,specific heat capacities and thermal diffusion coefficients were produced by changing the proportion and strength of ferrite.The peak temperature,pressure load and friction coefficient of compacted graphite iron brake discs were analyzed through inertia friction tests.The morphology of thermal cracks and 3D profiles of the worn surfaces were also discussed.It is found that the thermal fatigue of compacted graphite iron discs is determined by their thermal properties.A compacted graphite iron with the highest specific heat capacity and thermal diffusion coefficient exhibits optimal thermal fatigue resistance.Oxidization of the matrix at low temperatures significantly weakens the function of alloy strengthening in hindering the propagation of thermal cracks.Despite the reduced hardness,increasing the ferrite proportion can mitigate wear loss resulting from low disc temperatures and the absence of abrasive wear.

Birth Defects of the Child Optic Disc: Diagnostic Challenges and Prospects for Care

Introduction: Congenital optic disc anomalies in children refer to structural variations of the optic nerve head present from birth. These deformations involve the size, shape, color, and vessels of the optic disc. Although often asymptomatic, these anomalies can impact the visual development of the child, underscoring the importance of a thorough fundus examination for early detection and appropriate medical follow-up. We present two cases of congenital optic disc anomalies in children, illustrating the diagnostic challenges and complexity of their management. Case 1: A 3-year-old girl presented with a white spot in her left eye present since birth. Uncorrected distance visual acuity was 2/10 in the right eye, while she could perceive hand movements at 2 meters with the left eye. Normal examination in the right eye showed leukocoria, microphthalmia, and a white mass at the center of the optic disc on fundus examination in the left eye. Ocular imaging, including ultrasound and optical coherence tomography (OCT), confirmed the diagnosis of persistent hyperplastic primary vitreous (PHPV) in its mixed form in the left eye. Management included prescribing full optical correction and functional rehabilitation, without resorting to surgery. The course was marked by persistent amblyopia leading to a poor prognosis. Case 2: A 7-year-old girl consulted for vision disturbance in her right eye. Visual acuity was finger counting at 2 meters in the right eye and 10/10 in the left eye. Anterior segment examination revealed no abnormalities in both eyes. However, fundus examination highlighted a large funnel-shaped excavation associated with central glial proliferation, wheel spoke vessels, and neuroretinal ring atrophy in the right eye. Optical coherence tomography (OCT) of the right eye confirmed the diagnosis of isolated unilateral Morning Glory syndrome. Management included full optical correction and orthoptic rehabilitation. The course was marked by the absence of ocular complication and maintenance of visual stability in the right eye. The prognosis seemed favorable. Conclusion: Congenital optic disc anomalies in children exhibit great clinical variability and require an individualized diagnostic and therapeutic approach.

Shape and diffusion instabilities of two non-spherical gas bubbles under ultrasonic conditions

Ultrasonic cavitation involves dynamic oscillation processes induced by small bubbles in a liquid under the influence of ultrasonic waves. This study focuses on the investigation of shape and diffusion instabilities of two bubbles formed during cavitation. The derived equations for two non-spherical gas bubbles, based on perturbation theory and the Bernoulli equation, enable the analysis of their shape instability. Numerical simulations, utilizing the modified Keller–Miksis equation,are performed to examine the shape and diffusion instabilities. Three types of shape instabilities, namely, Rayleigh–Taylor,Rebound, and parametric instabilities, are observed. The results highlight the influence of initial radius, distance, and perturbation parameter on the shape and diffusion instabilities, as evidenced by the R_0–P_a phase diagram and the variation pattern of the equilibrium curve. This research contributes to the understanding of multiple bubble instability characteristics, which has important theoretical implications for future research in the field. Specifically, it underscores the significance of initial bubble parameters, driving pressure, and relative gas concentration in determining the shape and diffusive equilibrium instabilities of non-spherical bubbles.

Effect of granular shape on radial segregation in a two-dimensional drum

Granular segregation is widely observed in nature and industry.Most research has focused on segregation caused by differences in the size and density of spherical grains.However,due to the fact that grains typically have different shapes,the focus is shifting towards shape segregation.In this study,experiments are conducted by mixing cubic and spherical grains.The results indicate that spherical grains gather at the center and cubic grains are distributed around them,and the degree of segregation is low.Through experiments,a structured analysis of local regions is conducted to explain the inability to form stable segregation patterns with obviously different geometric shapes.Further,through simulations,the reasons for the central and peripheral distributions are explained by comparing velocities and the number of collisions of the grains in the flow layer.

Auxin-brassinosteroid crosstalk:Regulating rice plant architecture and grain shape

Rice(Oryza sativa)plant architecture and grain shape,which determine grain quality and yield,are modulatedby auxin and brassinosteroid via regulation of cell elongation and proliferation.We review the signaltransduction of these hormones and the crosstalk between their signals on the regulation of rice plantarchitecture and grain shape.

A Dual Closed-Loop Digital Twin Construction Method for Optimizing the Copper Disc Casting Process

The copper disc casting machine is core equipment for producing copper anode plates in the copper metallurgy industry.The copper disc casting machine casting package motion curve(CPMC) is significant for precise casting and efficient production.However,the lack of exact casting modeling and real-time simulation information severely restricts dynamic CPMC optimization.To this end,a liquid copper droplet model describes the casting package copper flow pattern in the casting process.Furthermore,a CPMC optimization model is proposed for the first time.On top of this,a digital twin dual closed-loop self-optimization application framework(DT-DCS) is constructed for optimizing the copper disc casting process to achieve self-optimization of the CPMC and closed-loop feedback of manufacturing information during the casting process.Finally,a case study is carried out based on the proposed methods in the industrial field.

The interaction between a shaped charge jet and a single moving plate

Reactive armour is a very efficient add-on armour against shaped charge threats.Explosive reactive armour consists of one or several plates that are accelerated by an explosive.Similar but less violent acceleration of plates can also be achieved in a completely inert reactive armour.To be efficient against elongated jets,the motion of the plates needs to be inclined against the jet such that a sliding contact between the jet and the plates is established.This sliding contact causes a deflection and thinning of the jet.Under certain circumstances,the contact will become unstable,leading to severe disturbances on the jet.These disturbances will drastically reduce the jet penetration performance and it is therefore of interest to study the conditions that leads to an unstable contact.Previous studies on the interaction between shaped charge jets and flyer plates have shown that it is mainly the forward moving plate in an explosive reactive armour that is effective in disturbing the jet.This is usually attributed to the higher plate-to-jet mass flux ratio involved in the collision of the forward moving plate compared to the backward moving plate.For slow moving plates,as occurs in inert reactive armour,the difference in mass flux for the forward and backward moving plate is much lesser,and it is therefore of interest to study if other factors than the mass flux influences on the protection capability.In this work,experiments have been performed where a plate is accelerated along its length,interacting with a shaped charge jet that is fired at an oblique angle to the plate’s normal,either against or along the plate’s velocity.The arrangement corresponds to a jet interacting with a flyer plate from a reactive armour,with the exception that the collision velocity is the same for both types of obliquities in these experiments.The experiments show that disturbances on the jet are different in the two cases even though the collision velocities are the same.Numerical simulations of the interaction support the observation.The difference is attributed to the character of the contact pressure in the interaction region.For a backward moving plate,the maximum contact pressure is obtained at the beginning of the interaction zone and the contact pressure is therefore higher upstream than downstream of the jet while the opposite is true for a forward moving plate.A negative interface pressure gradient with respect to the jet motion results in a more stable flow than a positive,which means that the jet-plate contact is more stable for a backward moving plate than for a forward moving plate.A forward moving plate is thus more effective in disturbing the jet than a backward moving plate,not only because of the higher jet to plate mass flux ratio but also because of the character of the contact with the jet.

Study on the tunnel shape and soil-lining interaction influencing the lining behavior under seismic loading

The response of tunnels subjected to seismic loading is a complex mechanism and depends not only on the seismic nature but also on tunnel structure and surrounding soil properties.The individual behavior of circular,rectangular,and sub-rectangular tunnels subjected to seismic loadings has already been studied in the literature.In the present research,two case scenarios of circular,rectangular tunnels and four sub-rectangular shaped tunnels,with similar cross-section areas,were adopted to perform a comprehensive numerical investigation.The purpose of the study was to determine the mechanical behavior of tunnels of different shapes,depending upon seismic conditions.Analyses were performed by considering the influence of soil-lining interaction,soil parameters,and lining thickness,as well as lining rigidity.Computations were performed for no-slip and full-slip conditions.The results indicate that the tunnel shape design is of great importance when regarding the mechanical behavior of the surrounding soil.This concerns no-slip as well as full-slip soil-lining interaction,especially when the lining is subjected to seismic loading.Moreover,it is shown that changes in incremental bending moments for circular,rectangular and sub-rectangular tunnels that depend upon the soil-lining interaction conditions differ significantly.

A Deep Learning Approach to Shape Optimization Problems for Flexoelectric Materials Using the Isogeometric Finite Element Method

A new approach for flexoelectricmaterial shape optimization is proposed in this study.In this work,a proxymodel based on artificial neural network(ANN)is used to solve the parameter optimization and shape optimization problems.To improve the fitting ability of the neural network,we use the idea of pre-training to determine the structure of the neural network and combine different optimizers for training.The isogeometric analysis-finite element method(IGA-FEM)is used to discretize the flexural theoretical formulas and obtain samples,which helps ANN to build a proxy model from the model shape to the target value.The effectiveness of the proposed method is verified through two numerical examples of parameter optimization and one numerical example of shape optimization.

Single atom Cu-N-C catalysts for the electro-reduction of CO_(2) to CO assessed by rotating ring-disc electrode

The electrochemical CO_(2) reduction reaction(CO_(2)RR) to controllable chemicals is considered as a promising pathway to store intermittent renewable energy. Herein, a set of catalysts based on copper-nitrogendoped carbon xerogel(Cu-N-C) are successfully developed varying the copper amount and the nature of the copper precursor, for the efficient CO_(2)RR. The electrocatalytic performance of Cu-N-C materials is assessed by a rotating ring-disc electrode(RRDE), technique still rarely explored for CO_(2)RR. For comparison, products are also characterized by online gas chromatography in a H-cell. The as-synthesized Cu-NC catalysts are found to be active and highly CO selective at low overpotentials(from -0.6 to -0.8 V vs.RHE) in 0.1 M KHCO_(3), while H_(2) from the competitive water reduction appears at larger overpotentials(-0.9 V vs. RHE). The optimum copper acetate-derived catalyst containing Cu-N_(4) moieties exhibits a CO_(2)-to-CO turnover frequency of 997 h^(-1) at -0.9 V vs. RHE with a H_(2)/CO ratio of 1.8. These results demonstrate that RRDE configuration can be used as a feasible approach for identifying electrolysis products from CO_(2)RR.

Effect of Quadrat Shape on Spatial Point Pattern Performance of Haloxylon ammodendron

In this study, we investigated the natural growth of Haloxylon ammodendron forest in Moso Bay, southwest of Gurbantunggut Desert. Random sample analysis was used to analyze the spatial point pattern performance of Haloxylon ammodendron population. ArcGIS software was used to summarize and analyze the spatial point pattern response of Haloxylon ammodendron population. The results showed that: 1) There were significant differences in the performance of point pattern analysis among different random quadrants. The paired t-test for variance mean ratio showed that the P values were 0.048, 0.004 and 0.301 respectively, indicating that the influence of quadrat shape on the performance of point pattern analysis was significant under the condition of the same optimal quadrat area. 2) The comparative analysis of square shapes shows that circular square is the best, square and regular hexagonal square are the second, and there is no significant difference between square and regular hexagonal square. 3) The number of samples plays a decisive role in spatial point pattern analysis. Insufficient sample size will lead to unstable results. With the increase of the number of samples to more than 120, the V value and P value curves will eventually stabilize. That is, stable spatial point pattern analysis results are closely related to the increase of the number of samples in random sample square analysis.