Contour Area Research Articles

Sarcopenia in Men With Bone-Predominant Metastatic Castration-Resistant Prostate Cancer Undergoing Ra-223 Therapy.

Osteosarcopenia is the progressive loss of musculoskeletal structure and functionality, contributing to disability and mortality. Despite complex interactions between bone and muscle, osteosarcopenia prevention and treatment in men with metastatic castration-resistant prostate cancer (mCRPC) focuses predominantly on bone health. It is unknown whether Radium-223 (Ra-223) therapy affects sarcopenia. We identified 52 patients with mCRPC who had received Ra-223 and had a baseline plus ≥1 follow-up abdominopelvic CT scan. The total contour area (TCA) and averaged Hounsfield units (HU) of the left and right psoas muscles were obtained at the inferior L3 endplate, and the psoas muscle index (PMI) was calculated therefrom. Intrapatient musculoskeletal changes were analyzed across various time points. TCA and PMI gradually declined over the study period (P = .002, P = .003, respectively), but Ra-223 therapy did not accelerate sarcopenia, nor the decline of HU compared to the pre-Ra-223 period. The median overall survival of patients with baseline sarcopenia was numerically worse (14.93 vs. 23.23 months, HR 0.612, P = .198). Ra-223 does not accelerate sarcopenia. Thus, worsening muscle parameters in men with mCRPC undergoing Ra-223 therapy are attributable to other factors. Further research is needed to determine whether baseline sarcopenia predicts poor overall survival in such patients.

GLAMPING RESORT DI KABUPATEN BENGKAYANG

The busyness that tends to be the same and the problems faced every day make people bored. You can relieve boredom by taking a vacation to natural attractions. Nature that has a varied topography such as hilly areas, beaches, valleys, and others gives rise to beautiful areas. One area that has topographic diversity is in Bengkayang Regency, West Kalimantan. One of the activities that can enjoy nature directly is camping / camping activities. Not everyone can do camping activities because the terrain is difficult to reach. Therefore, glamping (glamour camping) emerged which is a luxurious and practical camping activity as a solution. Glamping can be combined with resorts which are tourist attractions equipped with lodging facilities and produce glamping resorts that offer visitors the convenience of staying in the open. The method used is the J.C Jones method with direct data collection and based on literature studies. The aim of the design is to design a tourist area without destroying nature, to adapt to existing site conditions, and to be easy to pass. The result of the design is a tourist area that can be reached easily consisting of several masses of buildings that are placed in certain areas as facilities of the area such as glamping inns which are placed in the back area of the area and outbound which are placed scattered following the shape of the area's contours.

Calculation of normal stiffness and contact patch of ultra-low pressure tires for agricultural machinery

BACKGROUND:The impact of tires on a deformable ground surface determines not only the ability of a vehicle to move, but also the pressure on ground through the contact patch geometric characteristics. The pressure on soil is normalized and limited by the conditions for the preservation of its agrophysical properties. Therefore, when creating vehicles for various purposes for their movement or movement of their trailers on deformable ground surfaces, it is required to calculate the pressure on ground in the design process. However, currently there are no universal dependencies for calculation of the mentioned parameters of ultra-low pressure tires. This applies to both vertical and inclined tire arrangement.
 AIMS:Development and implementation of universal methods for calculation of normal stiffness and con-tact patch parameters of ultra-low-pressure tires for agricultural machinery.
 MATERIALS AND METHODS:Software products such as MS Excel, MATLAB and Curve Expert Professional were used in modeling.
 RESULTS:The universal analytical-experimental dependence has been obtained to determine the normal stiff-ness of ultra-low pressure tires, including a possible inclination of the wheel rotation axis. The dependence takes into account tire pressure, normal wheel load, an inclination angle of the rotation axis and tire geometric characteristics. The formula is obtained for determining the contact patch contour area of an ultra-low pressure tire. It helps to calculate the current pressure on ground, which should not exceed the specified value.
 CONCLUSIONS:The method for calculation of normal stiffness and contact patch parameters such as contact length, contour area and contact pressure for ultra-low pressure tires has been developed and implemented. The method is universal for all ultra-low pressure tires.

Justification of the optimal type of well completion profile based on a retrospective assessment of the technical and economic performance indicators

To date, significant foreign and domestic experience has been accumulated in the construction and operation of horizontal, multilateral and multilateral wells, as well as the restoration of an idle well stock by drilling sidetracks and sidetracks into various productive formations: low-permeability and highly dissected, with low values of effective oil-saturated thicknesses, degraded hydrodynamic connection with the contour area, etc. In this regard, it becomes extremely important to make a decision on choosing the optimal well profile in specific geological and physical conditions. The relevance of the work is also confirmed by the fact that at some development sites there is a decrease in the oil production rate of horizontal wells to the level of directional wells in the initial period of operation. Based on a significant difference in the reservoir properties of oil fields in the Perm Territory, all the analyzed objects operated by horizontal wells are combined into several groups: “northern” (N) and two “southern” (S1 and S2). The main parameter in the selection of groups was the coefficient of mobility of oil. The well-by-well technical and economic assessment performed in the article, based on the actual values of production over a long period, made it possible to identify the optimal well profile depending on the geological and physical characteristics of the reservoir. Combining the main geological characteristics that affect the technological parameters of well operation, with an economic assessment, the dependences of the net present value on the formation hydraulic conductivity were built. Dependences built for the first time make it possible to reasonably select the well profile in specific geological and physical conditions. Also in the work for a variety of geological and physical conditions, the value of the minimum profitable oil production for various well profiles is determined. Thus, the basis has been created, which is necessary for determining the profile of wells when planning production drilling.

Medical Image Segmentation with active contour and optimization Techniques: Survey

The principal aim is to improve medical diagnosis through segmented images. Thus, medical image segmentation become one of the key technologies in computer-aided diagnosis. Active contours, or snakes, have been widely used for image segmentation purposes. However, high noise sensitivity and poor performance over weak edges are the most acute issues that hinder the segmentation accuracy of these curves, particularly in medical images. To overcome these issues, a novel external force that integrates gradient vector flow (GVF) field forces and the traditional snake function is proposed in this research. In addition, a novel technique is applied to limit the boundary of the initial contour by set four initial points around the medical issue and then connecting them by polynomial curves. Moreover, the positive effect of Particle Swarm Optimization (PSO) on calculating the final active contour area and its percentage to the entire image area is proved in this work.

421 A multiparametric, stepwise in vitro approach to identify anti-dark circle and anti-puffiness ingredients

Dark circles are a cosmetic concern worldwide, often associated with tiredness or aging. Owing to its thinness, the highly vascularized eye contour area easily shows blood and lymphatic circulation disorders. Environmental stress alters skin microcirculation, endothelial barrier function and increases oxidation in the subocular area. The multifactorial nature of dark circles and puffiness represents a real challenge for in vitro efficacy testing of active ingredients. Therefore, to select an active ingredient with both anti-puffiness and anti-dark circle potentials, we have implemented a screening strategy that combined different biological models addressing relevant targets of skin microcirculation and endothelial barrier function.

Breast Ultrasound Image Segmentation Algorithm Using Adaptive Region Growing and Variation Level Sets

To address the features of strong noise, blurred boundaries, and poor imaging quality in breast ultrasound images, we propose a method for segmenting breast ultrasound images using adaptive region growing and variation level sets. First, this method builds a template layer from the difference between the marked image and the original image. Second, the Otsu algorithm is used to measure the target and background using the maximum class variance method to set the threshold. Finally, through the level set of the pixel neighborhood, the boundary points of the adaptive region growth are specified by the level set of the pixel neighborhood, and it is therefore possible to accurately determine the contour perimeter and area of the lesion region. The results demonstrate that the value of Jaccard and Dice for benign tumors is greater than 0.99. Therefore, the segmentation effect of breast images can be achieved by utilizing a breast ultrasound image segmentation approach that uses adaptive region growth and variation level sets.

Design and Implementation of Artificial Intelligence of Things for Tea (Camellia sinensis L.) Grown in a Plant Factory

An innovative plant growth monitoring and environmental control platform is designed and implemented in this study. In addition to using multi-band artificial light sources for plant growth and development, an artificial intelligence of things (AIoT) approach is also utilised for environmental parameter monitoring, control, and the recording of plant growth traits and diseases. The five LED bands are white (5000 K), cool white (5500 K), blue (peak: 450 nm), red (660 nm), and light red (630 nm). The tea plant (Camellia sinensis f. formosana) is irradiated using lighting-emitting diodes (LED) composed of bands of different wavelengths. In addition, the number of leaves, contour area of the leaves, and leaf colour during the growth period of two varieties of tea plants (Taicha No. 18 and Taicha No. 8) under different irradiation intensities are analysed. Morphological image processing and deep learning models are simultaneously used to obtain plant growth characterization traits and diseases. The effect of the spectral distribution of the light source on the growth response of tea leaves and the effect of disease suppression are not fully understood. This study depicts how light quality affects the lighting formula changes in tea plants under controlled environments. The experimental results show that in three wavelength ranges (360–500 nm, 500–600 nm, and 600–760 nm), the light intensity ratio was 2.5:2.0:5.5 when the illuminance intensity was about 150 µmol∙m−2∙s−1 with a photoperiod of 20:4 (dark); this enabled more leaves, a smaller contour area of the leaves, and a light green colour of the leaves of the tea plant (Taicha No. 18). In addition, during the lighting treatment, when the ratio of the band with an irradiation intensity of 360–500 nm to that with an irradiation intensity of 500–600 nm was 2:1.5, it resulted in a better leaf disease inhibition effect. When the light intensity was increased to more than 400 µmol∙m−2∙s−1, it had little effect on the growth and development of the tea plants and the inhibition of diseases. The results of the study also found that there was a significant difference between the colour of the leaves and the relative chlorophyll content of the tea trees. Finally, the tea plant growth response data obtained from manual records and automatic records are compared and discussed. The accuracy rates of leaf number and disease were 94% and 87%, respectively. Compared with the results of manual measurement and recording, the errors were about 3–15%, which verified the effectiveness and practicability of the proposed solution. The innovative platform provides a data-driven crop modeling application for plant factories.

Block copolymer nanopatterns affect cell spreading: Stem versus cancer bone cells

Bone healing after a tumor removal can be promoted by biomaterials that enhance the bone regeneration and prevent the tumor relapse. Herein, we obtained several nanopatterns by self-assembly of polystyrene-block-poly-(2-vinylpyridine) (PS-b-P2VP) with different molecular weights and investigated the adhesion and morphology of human bone marrow mesenchymal stem cells (BMMSC) and osteosarcoma cell line (SaOS-2) on these patterns aiming to identify topography and chemistry that promote bone healing. We analyzed > 2000 cells per experimental condition using imaging software and different morphometric descriptors, namely area, perimeter, aspect ratio, circularity, surface/area, and fractal dimension of cellular contour (FDC). The obtained data were used as inputs for principal component analysis, which showed distinct response of BMMSC and SaOS-2 to the surface topography and chemistry. Among the studied substrates, micellar nanopatterns assembled from the copolymer with high molecular weight promote the adhesion and spreading of BMMSC and have an opposite effect on SaOS-2. This nanopattern is thus beneficial for bone regeneration after injury or pathology, e.g. bone fracture or tumor removal.

ПЛОЩАДЬ КОНТАКТА ШИНЫ С ОПОРОЙ, КАК ФУНКЦИЯ ВЕРТИКАЛЬНОЙ НАГРУЗКИ И ВНУТРИШИННОГО ДАВЛЕНИЯ

A comprehensive increase in the efficiency of mobile agricultural machinery is impossible without taking into account the level of impact of its movers on the soil, while the most important target is to improve the coupling qualities of tractors and agricultural machines, including by increasing the size of the contact area of the mover with the supporting base. The dimensions of the contact surface at the soil-tire interface will determine the specific pressure of the pneumatic wheeled equipment on the soil, which in turn determines the level of environmental safety of the “mechanized vehicle – environment – crop” system. Agricultural tires, widely used in the Russian Federation, were chosen as objects of research, in total 22 options. The studies were carried out at vertical load levels from 10 to 60 kN and tire pressure from 50 to 500 kPa. As a result of the research, the authors proposed a method for determining the contour area of the contact of modern wheel propellers, with a change in external (wheel axle load) and internal (in-tire pressure) factors. The level of adequacy of the mathematical model, calculated by the Nash–Sutcliff modeling efficiency criterion, was 0.991. Simplicity and sufficient accuracy for engineering calculations make it quite suitable for practical use.

Blast-Loading Effects on Structural Redundancy of Long-Span Suspension Bridge Using a Simplified Approach

Long-span suspension bridges are typically designed against wind and earthquake loadings without considering blast loads because existing blast-resistant design guidelines for bridges are limited and in fact not detailed enough to fully explicate the consequences of a blast event. This study performed detailed dynamic analysis of a long-span suspension bridge to parametrically evaluate its structural redundancy under small to large blasts detonated at different locations. To accomplish this, the blast-structure interaction problem was solved by a simplified approach whereby the blast aspect was modeled as nodal loads by simulating the pressure contour area on the deck surface caused by the explosion; the structural aspect was modeled as a three-dimensional fishbone skeleton finite-element model. In particular, major attention was paid to the blast load effects on the main cable and hangers designed at safety factors of 2.2 and 2.5, respectively. This study concluded that the main cable and hangers show sufficient and insufficient structural redundancies, respectively under small to medium blasts, whereas a large blast was proven to be detrimental to both the main cable and hangers, which may further trigger progressive collapse of the entire suspension bridge.

Fretting wear evolution model of the metal filaments inside metal rubber

Metal rubber (MR) is a porous material which possesses macroscopic damping properties through the dry friction between the internal helical metal wires. Due to its complex topological structure, the research on the fretting wear of MR is rarely reported in the literature. In the present work, a double-body wear model of metal filaments is constructed by the master-slave composite method. The friction and wear conditions of the dynamic and static metal wires inside the MR are analyzed under different contact angles, loads, and vibration amplitudes. The results indicate that the wear area and volume of the dynamic wire under each working condition are significantly larger than those of the static wire, while the case for the wear depth is the opposite. After wear, the wires exhibit an obvious stress concentration phenomenon, which is distributed along the wire wear contour area, and the wear profile has a high sensitivity to the contact angle. In order to further investigate the difference in the wear degree of the static and dynamic wires inside the MR, the fretting amplitude is introduced to describe the wear scar area of the dynamic wire, the special wear scar area is reorganized regularly, and the wear volume of the wire is approximated by the regional combination, deriving and constructing a fretting wear evolution model suitable for MR wires. This evolution model can simultaneously predict the wear degree of dynamic and static wires, and its prediction accuracy is high. The prediction accuracy under each working condition is basically less than 10%; thus, the proposed model can be effectively applied to the fretting wear prediction of MR ultra-fine wire contact pairs. This work provides theoretical guidance for the life prediction and other aspects of MR materials.

A calculation method of phenotypic traits of soybean pods based on image processing technology

As a homologous organ of the leaf, the pod is an essential factor in determining the yield and quality of the grain. The physiological and ecological characteristics of pods are a critical basis for soybean breeding and yield estimation. In order to avoid time-consuming and laborious problems in the traditional manual measurement process, a fast calculation method of pod's phenotypic traits was proposed based on image processing technology. First, two varieties (Heihe 49 and Suinong 26) were taken as the research objects. The self-developed image acquisition platform was used to obtain the color images of soybean pods at different growth stages. Second, the geometric distortion of the raw image was registered by using the linear mapping equation. In addition, the edge of the pod was extracted by the Gaussian filter function and Canny detection operator. Finally, the length, width, and area of pods were calculated based on the minimum circumscribed rectangle method, the maximum inscribed circle method, and the pixel count of pod's contour area combined with the template calibration method. The shape and the number of seeds were calculated based on the interval duty cycle method, the interval duty cycle combined with the arc length of pod's convex edge. The results showed that the accuracy between the calculated values and the standard values of pod length, pod width, pod area, pod shape, and the number of seeds was 97.8%, 95.1%, 97.1%, 93.2%, and 85%, respectively. Thus, the proposed method can provide not only a rapid detection for quantitative indexes of soybean seed test and yield estimation, but also a theoretical basis and technical knowledge for soybean breeding and scientific cultivation.

Fusion Growth of Two-Dimensional Disklike Micelles via Liquid-Crystallization-Driven Self-Assembly

Liquid-crystallization-driven self-assembly (LCDSA) is an emerging strategy for constructing nanoassemblies, such as 1D cylindrical micelles with LC-like micellar cores. However, it is still unknown whether LCDSA can be applied to higher-dimensional self-assembly. Herein, we realize the growth of two-dimensional (2D) disklike micelles via LCDSA and reveal its mechanism. Disklike seeds are constructed through the self-assembly of poly(γ-benzyl l-glutamate)-block-poly(ethylene glycol) (PBLG-b-PEG) block copolymers in solution. In the micellar core, the PBLG rod blocks take a smectic LC-like packing manner. After PBLG-b-PEG unimers are added into the seed solution, they first self-assemble into small aggregates. The aggregates then fuse with the seed edges to achieve the epitaxial growth of the disklike micelles. Brownian dynamic simulations reveal that the rod blocks in the small aggregates rearrange themselves to match the LC-like structure of the seed core in the growth process. The contour area of the disklike micelles is dependent on the unimer-to-seed ratio, and the 2D growth kinetics can be well controlled to construct concentric disklike micelles. The observed growth behavior of disklike micelles extends the LCDSA from 1D to 2D and can address the challenge of the precise manipulation of 2D nanostructures.

Intelligent monitoring of photovoltaic panels based on infrared detection

With the continuously increasing application of photovoltaic (PV) panels, how to effectively manage these valuable facilities has become an issue of concern. To date, some methods have been developed to meet this purpose. However, to date, a satisfactory solution has not been achieved for managing large-scale solar PV power plants. To address this issue, a new PV panel condition monitoring and fault diagnosis technique is developed in this paper. The new technique uses a U-Net neural network and a classifier in combination to intelligently analyse the PV panel’s infrared thermal images taken by drones or other kinds of remote operating systems. The novelties of this research include: (1) a U-net neural network is developed and trained to carry out image segmentation, thereby significantly improving the efficiency of image processing; (2) the condition monitoring and fault diagnosis is based on the contour features in the ‘mask’ of true colour infrared images. As compared to the true colour images, their mask images have little interference information, the reliability and accuracy of condition monitoring and fault diagnosis based on mask images can be guaranteed to a large extent. In the research, 295 infrared images were taken first from the PV panels in different health states, and then their ‘masks’ were manually created using the software LabelMe. Secondly, enlarge the number of image samples using three image expansion methods (i.e. mirroring left and right, flipping up and down, and cropping and then zooming in) to establish the image sample database for training and testing the U-net neural network. Thirdly, use 1852 infrared images and their mask images stored in the database to train a U-Net neural network until the trained U-net neural network can create mask images as accurately as the software LabelMe does. The trained neural network will guarantee that the achieved segmentation accuracy can be as high as 95.2%. Finally, four potential criteria (i.e., Contour area, Perimeter, Aspect ratio and Ratio of contour area to the area of contour outer rectangle) are proposed to characterise the contour of mask images and then based on the calculation results of these four criteria, different types of PV panel faults are diagnosed with the aid of three kinds of classifiers. The classifiers are Decision tree, K-Nearest Neighbours algorithm (KNN), and Support-vector machine (SVM). The research results have shown that the combined use of a well-trained U-Net neural network and Decision tree can diagnose the PV panel faults with 99.8% accuracy. Therefore, it may arguably provide a promising intelligent tool for condition monitoring the PV panels.

Aging of Chinese bony orbit: automatic calculation based on UNet++ and connected component analysis.

PurposeCurrent research on the aging of bony orbit is usually done manually, which is inefficient and has a large error. In this paper, automatic segmentation of bony orbit based on deep learning and automatic calculation of the parameters of the segmented orbital contour (area and height of bony orbit) are presented.MethodsThe craniofacial CT scanning data of 595 Chinese were used to carry out three-dimensional reconstruction and output the craniofacial images. The orbital contour images are obtained automatically by UNet++ segmentation network, and then the bony orbital area and height were calculated automatically by connected component analysis.ResultsThe automatic segmentation method has an Intersection of Union of 95.41% in craniofacial CT images. During the aging, the bony orbital area of males increased with age, while that of females decreased, and the area in male was larger than that in female (P < 0.05). The distance from equal points 10 and 40–90 to the supraorbital rim was significantly larger (P < 0.05). Except for the equal point 90, the distance from equal points to the inferior orbital rim was obviously larger (P < 0.05). In the females, the distance from equal points 50–70 to inferior orbital rim was significantly lower (P < 0.05).ConclusionThe method proposed here can automatically and accurately study image dataset of large-scale bony orbital CT imaging. UNet++ can achieve high-precision segmentation of bony orbital contours. The bony orbital area of Chinese changes with aging, and the bony orbital height changes different between males and females, which may be caused by the different position and degree of orbital bone resorption of males and females in the process of aging.

Evaluation of the effectiveness of interventional treatment of ventricular arrhythmias of rare localizations using non-invasive mapping

Background. Atypical localization of the focus of ventricular arrhythmias is a rather difficult group for invasive mapping and subsequent radiofrequency ablation. Invasive electroanatomical mapping, multipolar electrophysiological electrodes in combination with electrophysiological study for searching an early zone of arrhythmia focus, and substrate mapping, are aimed to identifying critical areas of the arrhythmia contour. However, there are still situations in which arrhythmia cannot be eliminated, despite the use of these systems. The method of superficial non-invasive mapping of the heart seems to be relevant, which makes it possible to estimate the volume of surgery and select the necessary technology to eliminate arrhythmias.Aim. To compare the effectiveness of interventional treatment of patients with ventricular arrhythmias of atypical localization with and without the use of superficial non-invasive mapping.Methods. The study included 40 patients with ventricular arrhythmias of rare localization. The patients were divided into two groups. Group I included 21 patients who underwent non-invasive superficial and invasive electrophysiological cardiac mapping. Group II included 19 patients who underwent invasive electrophysiological cardiac mapping.Results. Over a follow-up period of 12 months, the freedom from arrhythmia in group I was 76%, in group II — 61%. The total operation time, duration and dose of fluoroscopy were less in group I compared to the group II.Conclusion. The study results demonstrated that the method of non-invasive surface mapping of the heart is highly effective in ventricular arrhythmias of atypical localization. The time of radiofrequency ablation, interventional intervention, fluoroscopy is lower with the use of superficial non-invasive mapping, compared with the control group. Received 13 July 2021. Revised 20 October 2021. Accepted 9 December 2021. Funding: This work is supported by a grant of the Russian Science Foundation (project No. 19-15-00406). Conflict of interest: The authors declare no conflict of interest. Contribution of the authorsConception and study design: E.A. Artyukhina, A.Sh. RevishviliData collection and analysis: E.A. Artyukhina, M.V. Yashkov, E.V. Dedukh, I.A. Taymasova, A.Sh. RevishviliStatistical analysis: M.V. YashkovDrafting the article: E.A. Artyukhina, M.V. YashkovCritical revision of the article: E.A. Artyukhina, M.V. Yashkov, A.Sh. RevishviliFinal approval of the version to be published: E.A. Artyukhina, M.V. Yashkov, E.V. Dedukh, I.A. Taymasova, A.Sh. Revishvili

Specification of structural-tectonic configuration and geological risks in the estimation of reserves in Darvin kupesi field

Based on the newly drilled wells, the paper specifies structural-tectonic properties of Darvin kupesi field. Despite the long-term development of the field, numerous improvements have been revealed. New wells have been drilled during last years, on the basis of which geological structure of the field has been defined. Correlation schemes and geological profiles have been developed by means of new wells. Stratigraphic borders have been specified based on the correlation schemes. The structural map has been developed, the sites and forms of faults defined and the reserves by Girmaki suite and Lower Girmaki horizons calculated as well. The main objects are Girmaki and Lower Girmaki suites, which, in their turn, are divided into several horizons. Water-oil contour and oil area have been defined for both formations. Oil reserves by blocks have been estimated via С1 and С2 categories. The risk bar graphs and diagrams of sensitivity analysis have been developed for field reserves. For conducting analysis, at first the values of input parameters have been entered. As a result, a graph of distribution of oil reserves has been specified and Р 90, Р 50, Р 10 marks obtained. Sensitivity analysis has been carried out for definition of parameters, which will significantly affect the process of field development. The affect percentage of all parameters impacting the reserves has been specified, the parameters with high effect level selected.

Research on Three-Dimensional Morphological Characteristics Evaluation Method and Processing Quality of Coarse Aggregate

The size, shape, gradation and appearance of aggregate have a significant impact on the road performance of asphalt mixtures, which is directly related to the deformation characteristics and fatigue resistance of asphalt mixtures. In order to be able to design a long-life asphalt pavement, the aggregate must have reasonable morphology and morphological characteristics. In order to quantitatively analyze the shape characteristics of the road coarse aggregate, a high-precision three-dimensional scanner is used to obtain the characteristic lattice of the aggregate surface, and the solid model of the coarse aggregate particles is established. The two-dimensional and three-dimensional morphological indicators of the aggregate are analyzed and discussed. Meanwhile, aggregates processed by typical quarries in Guangdong Province are collected, and the influence of different processing techniques on the morphology of aggregates are analyzed. The results show that the difference between the perimeter and projected area of the aggregate contour under different viewing angles is relatively large, which is closely related to the flatness index of the aggregate. It can better characterize the three-dimensional shape of the aggregate. The closer the aggregate is to the cubic state, the greater the sphericity value; the ellipsoid index calculated based on the three-dimensional circumscribed ellipsoid can better characterize the angularity of the aggregate. The worse the angularity of the aggregate, the larger the corresponding ellipsoid value. The sphericity of the aggregate processed by counter-breaking is lower, and the angularity is better. The sphericity of the aggregate processed by the shaping process is the best, but the angularity is lower. According to actual needs, different processing techniques can be combined and blended to obtain aggregate finished products with a more balanced grain shape and angularity. The richer the angularity of the coarse aggregate, the better the high-temperature stability and fatigue resistance of the asphalt mixture. However, the stability of performance indicators will become worse. In practical engineering applications, it is recommended to further combine the screening efficiency of the hot material screen of the mixing plant with the stability of the hot material gradation and the uniformity of construction quality to select a suitable aggregate processing technology.

Inflammation in Remote Myocardium and Left Ventricular Remodeling After Acute Myocardial Infarction: A Pilot Study Using T2 Mapping

LGE and T2 Mapping Images of Representative Cases. On LGE Images (A for Animals and C for Human), Infarcted Myocardium Demonstrated the Area with High Intensity; On T2 Maps (B for Animals and D for Human), The High Ntensity of Infarcted Myocardium Decreases from 3 Days to 3 Months Following MI. The Measurement of Remote T2 is Performed within the Defined White Contour Area. LGE: Late Gadolinium Enhancement; MR = Magnetic Resonance; MI = Myocardial Infarction; STEMI = ST†Elevated Myocardial Infarction. BY Yang et al. (555‐564) image