Method For Rapid Construction Research Articles

Construction of an Electrochemical Molecularly Imprinted Sensor Based on L-carnitine Doped Polypyrrole for Vibrio Parahaemolyticus Detection

This study addresses the pressing need for rapid detection of pathogenic microorganisms by designing and fabricating an L-carnitine-doped polypyrrole (L-CN/PPy) electrochemical molecularly imprinted sensor, with Vibrio parahaemolyticus as the model target. Employing L-carnitine as a dual-functional dopant and auxiliary recognition element in the electropolymerization process, the sensor not only enhances the conductive properties of polypyrrole but also significantly improves its specific recognition capability towards the target bacteria. The sensor preparation encompasses the electrochemical polymerization of L-CN/PPy composite material, immobilization and elution of template bacteria, followed by bacterial recognition and detection steps. Through systematic optimization of L-CN concentration, polymerization conditions, eluent composition, elution time, and operational parameters, the sensor's performance is maximized. Experimental results confirm the sensor's efficacy in rapidly completing template bacteria elution within just 30 minutes and achieving efficient recognition of Vibrio parahaemolyticus within 20 minutes, demonstrating high sensitivity and selectivity. Moreover, the straightforward and rapid construction method of the sensor introduces a novel technological strategy for practical microbial detection applications, highlighting extensive application prospects.

Experimental Study on Key Techniques for the Construction of High Asphalt Concrete Core Rockfill Dam under Unfavorable Geological Conditions

Asphalt concrete core dams (ACCDs) have been widely constructed in Xinjiang, yet the design of materials and structures has mainly relied on empirical knowledge without substantial theoretical grounding. In this study, we carried out a large-scale relative density test of gravel material in Bamudun dam, studied the compaction characteristics of gravel material, and determined the relative density characteristic index, in order to provide a basis for the subsequent dam material rolling test and construction quality inspection. Furthermore, in order to improve the efficiency of dam construction in narrow valleys, we optimized the connection type between asphalt concrete core wall and bedrock, and proposed a rapid construction method of paving core wall after pouring mass concrete base on bedrock. Finally, we established a three-dimensional finite element model to systematically analyze the stress and deformation patterns of the dam body, core wall, and base of the ACCD at Bamudun. The results show that the maximum compressive stress suffered by the core wall during the full storage period is 1.62 MPa, there is no tensile stress, and the risk of hydraulic splitting is small. The stress and deformation levels of each part are within the safe range. This verifies the rationality of the rapid construction method. The research findings can provide a great theoretical significance and engineering value for the safe design and construction of ACCDs.

On the resonance frequency of the irregular shaped visco-acoustic Helmholtz cavity problem

In this paper we develop a closed-form mathematical solution for the resonance frequency of the axisymmetric irregular shaped visco-acoustic Helmholtz cavity problem. The solution is based on a conformal mapping that transforms the governing visco-acoustic equations of motion for the irregular cavity geometry into a new domain described by a set of orthogonal curvilinear coordinates. These orthogonal curvilinear coordinates have an important characteristic relative to the transformation of the physical boundary: the mapped domain is constructed such that the locus of all points for the length-wise profile of the physical boundary coincides with a constant value for a (quasi radial) coordinate in the new mapped domain. In these orthogonal curvilinear coordinates we obtain an analytical solution for the visco-acoustic equations of motion and exactly satisfy the no-slip fluid boundary conditions over the irregular shaped cavity walls by matching the coefficients of an orthogonal Legendre polynomial series representation for the non-uniform velocity on the cavity walls. The mathematical solution is an approximation to the extent that the scale factors chosen for the mapping consist of strictly the mutual-coupling terms of the true scale factors. Thus we analyze some results to understand the correlation of the analytical solution frequency response spectra with numerical finite element analyses of the idealized boundary conditions with various irregular shaped cavity geometries. The results for fundamental resonance frequency were found to exhibit good correlation with the results of finite element analyses over a significant range of fluid properties with different irregular cavity geometries. As the primary motivation for the derivation stems from the lack of a rapid yet accurate alternative to computationally intensive MultiPhysics FEA in the formulation of acoustic trendlines for sensor development, the solution’s acoustic impedance was applied as dispersive loading in a simple lumped parameter model of a fluid identification sensor for comparison. The resulting acoustic trendlines of the reduced (5 DOF) model were found to exhibit good correlation with the results of the MultiPhysics FEA (>105 DOF). Thus the solution was found to enable a closed-form analytical method for rapid construction of parametric studies in the practical design of fluid analysis sensors based on complex resonant cavity geometries.

Rapid Construction Method for Bridges with Long- Span Precast Girders Made of C80/95

Rapid Construction Method for Bridges with Long- Span Precast Girders Made of C80/95

Rapid construction method of emergency material supply chain based on shared platform covering market resources

In the early stages of emergency response, access to a robust information flow and sufficient materials is the basis for ensuring the efficient operation of the emergency material supply chain. Based on a summary of the structure and operational processes of the emergency material supply chain, this paper analyses the key elements and sources of supply chain information flow and proposes a method for integrating information flow based on shared platform. First, basic disaster information and multiscale population data are combined to determine the distribution of the affected population or shelters, and the demand assessment is completed. Then, the market material supply source information is mined, the national reserve information is integrated, and the quantity and distribution of supply sources are analysed. Finally, traffic information is obtained by calling on the real-time Amap API, the supply and demand of emergency materials are matched, and a reasonable emergency material dispatching plan is proposed. This paper considers both historical and recent cases, with case applications to the Lushan County, Ya 'an City, Sichuan Province MS7.0 earthquake; and the 2023 MW7.8 and 7.5 Turkey earthquakes, among others. The results verify that the proposed method can effectively integrate and construct the information flow of the emergency material supply chain and that the rational use of market resources can compensate for material shortages. The information flow and material flow of the emergency material supply chain can thus be maximized, indirectly reducing the losses caused by disaster emergencies.

Bioinspired Skeletal Reorganization Approach for the Synthesis of Steroid Natural Products.

ConspectusSteroids, termed "keys to life" by Rupert Witzmann, have a wide variety of biological activities, including anti-inflammatory, antishock, immunosuppressive, stress-response-enhancing, and antifertility activities, and steroid research has made great contributions to drug discovery and development. According to a chart compiled by the Njardarson group at the University of Arizona, 15 of the top 200 small-molecule drugs (by retail sales in 2022) are steroid-related compounds. Therefore, synthetic and medicinal chemists have long pursued the chemical synthesis of steroid natural products (SNPs) with diverse architectures, and vital progress has been achieved, especially in the twentieth century. In fact, several chemists have been rewarded with a Nobel Prize for original contributions to the isolation of steroids, the elucidation of their structures and biosynthetic pathways, and their chemical synthesis. However, in contrast to classical steroids, which have a 6/6/6/5-tetracyclic framework, rearranged steroids (i.e., abeo-steroids and secosteroids), which are derived from classical steroids by reorganization of one or more C-C bonds of the tetracyclic skeleton, have started to gain attention from the synthetic community only in the last two decades. These unique rearranged steroids have complex frameworks with high oxidation states, are rich in stereogenic centers, and have attractive biological activities, rendering them popular yet formidable synthetic targets.Our group has a strong interest in the efficient synthesis of SNPs and, drawing inspiration from nature, we have found that bioinspired skeletal reorganization (BSR) is an efficient strategy for synthesizing challenging rearranged steroids. Using this strategy, we recently achieved concise syntheses of five different kinds of SNPs (cyclocitrinols, propindilactone G, bufospirostenin A, pinnigorgiol B, and sarocladione) with considerably rearranged skeletons; our work also enabled us to reassign the originally proposed structure of sarocladione. In this Account, we summarize the proposed biosyntheses of these SNPs and describe our BSR approach for the rapid construction of their core frameworks. In the work described herein, information gleaned from the proposed biosyntheses allowed us to develop routes for chemical synthesis. However, in several cases, the synthetic precursors that we used for our BSR approach differed substantially from the intermediates in the proposed biosyntheses, indicating the considerable challenges we encountered during this synthetic campaign. It is worth mentioning that during our pursuit of concise and scalable syntheses of these natural products, we developed two methods for accessing synthetically challenging targets: a method for rapid construction of bridged-ring molecules by means of point-to-planar chirality transfer and a method for efficient construction of macrocyclic molecules via a novel ruthenium-catalyzed endoperoxide fragmentation. Our syntheses vividly demonstrate that consideration of natural product biosynthesis can greatly facilitate chemical synthesis, and we expect that the BSR approach will find additional applications in the efficient syntheses of other structurally complex steroid and terpenoid natural products.

The rapid construction method of the digital twin polymorphic model for discrete manufacturing workshop

The modeling process is resource-intensive, time-consuming, and expensive due to the large number and variety of production and auxiliary equipment in discrete manufacturing plants. The popular twin-model construction method based on a single type of equipment cannot meet the demand for rapid construction and high-quality model mapping in large discrete manufacturing plants. This paper proposes a strategy for developing a digital twin polymorphic model (DTPM) for discrete manufacturing workshops to meet complex manufacturing business scenarios, improve the richness of digital twin model varieties, construction efficiency and intelligence, and form an efficient equipment model construction method. The complete element information and real-time dynamic data of the minimal component unit (Functional Components, FC) of DTPM are clustered and analyzed. In addition, properties of the functional component information model are characterized from several dimensions, such as geometry, physics, and behavior. Furthermore, the FC with highly concentrated primary components is established based on the object-oriented derivation inheritance and attribute reuse hybrid drive technique. FC drastically reduces the duration of the digital twin model development process through encapsulation, inheritance, polymorphism, and other technologies. On this premise, the DTPM construction method that deeply decouples the physical structure and functional methods is proposed. DTPM integrates adaptive information interaction technology to accomplish intelligent data connection, dynamic data updating, and digitally accurate mapping of static-dynamic-virtual multidimensional models in discrete production workshops. Lastly, the method's validity is confirmed by creating a large discrete production workplace. The results indicate that the proposed technique may significantly enhance the model variety and building efficiency of large-scale digital twin workshop systems.

Inverse Determination Of Interfacial Properties of a Bonded Structure Using Lamb Waves Generated By Laser Lateral Excitation

Nondestructive testing of the adhesive bond properties of a bonded structure is essential in aviation, automotive, and other industries. In this study, a Lamb wave–based quantitative characterization method is proposed to determine the interfacial stiffness of bonded structures. A theoretical model is established, with which the dispersion relationship of Lamb waves in a bonded structure is investigated. Different interfacial states ranging from a perfect bond to a weak bond are simulated, and the numerical results show the sensitivity of Lamb waves to interfacial stiffness. A lateral excitation method is proposed to enhance the excitation of the interfacial sensitive Lamb wave modes, and laser ultrasonic experiments show the enhancement of the Lamb wave signals on aluminum-epoxy-aluminum samples generated by the lateral excitation method. Then, a rapid construction method of inversion objective function is presented to reconstruct the interfacial stiffness coefficient of a bonded structure, and its functionality is validated via finite element simulations. Finally, the interfacial properties of the samples are reconstructed using the inversion scheme.

Dual-band optical collimator based on deep-learning designed, fabrication-friendly metasurfaces

Abstract Metasurfaces, which consist of arrays of ultrathin planar nanostructures (also known as “meta-atoms”), offer immense potential for use in high-performance optical devices through the precise manipulation of electromagnetic waves with subwavelength spatial resolution. However, designing meta-atom structures that simultaneously meet multiple functional requirements (e.g., for multiband or multiangle operation) is an arduous task that poses a significant design burden. Therefore, it is essential to establish a robust method for producing intricate meta-atom structures as functional devices. To address this issue, we developed a rapid construction method for a multifunctional and fabrication-friendly meta-atom library using deep neural networks coupled with a meta-atom selector that accounts for realistic fabrication constraints. To validate the proposed method, we successfully applied the approach to experimentally demonstrate a dual-band metasurface collimator based on complex free-form meta-atoms. Our results qualify the proposed method as an efficient and reliable solution for designing complex meta-atom structures in high-performance optical device implementations.

CBR-RBR fusion based parametric rapid construction method of bridge BIM model

The development of BIM (Building Information Modeling) parametric modeling technology has improved the reusability and modeling efficiency of building information models. Aiming at the problems of too many parameters and long time in the rapid parametric construction of the bridge BIM model, we propose a novel parametric rapid construction method of bridge BIM model based on the integration of CBR (Case Based Reasoning) and RBR (Rule Based Reasoning), which is used to realize the rapid construction of bridge BIM model. Firstly, the modeling characteristics of CBR and RBR are analyzed, and a parametric modeling framework of CBR-RBR fusion is proposed. Secondly, a MHPO (Modified Hunter-Prey Optimization) algorithm is proposed to assign the weight of feature parameters to improve the accuracy of the prediction model. Then, modeling parameter reasoning rules are designed to realize the construction of parameter reasoning model. Finally, the prototype system is developed to verify the proposed method based on Revit and C#. Compared with manual modeling and traditional parametric modeling, the fusion method of CBR and RBR greatly shortens the modeling time and improves modeling efficiency and flexibility.

BK-SWMM flood simulation framework is being proposed for urban storm flood modeling based on uncertainty parameter crowdsourcing data from a single functional region

In recent years, urban flood disasters caused by sudden heavy rains have become increasingly severe, posing a serious threat to urban public infrastructure and the life and property safety of residents. Rapid simulation and prediction of urban rain-flood events can provide timely decision-making reference for urban flood control and disaster reduction. The complex and arduous calibration process of urban rain-flood models has been identified as a major obstacle affecting the efficiency and accuracy of simulation and prediction. This study proposes a multi-scale urban rain-flood model rapid construction method framework, BK-SWMM, focusing on urban rain-flood model parameters and based on the basic architecture of Storm Water Management Model (SWMM). The framework comprises two main components: 1) constructing a SWMM uncertainty parameter sample crowdsourcing dataset and coupling Bayesian Information Criterion (BIC) and K-means clustering machine learning algorithm to discover clustering patterns of SWMM model uncertainty parameters in urban functional areas; 2) coupling BIC and K-means with SWMM model to form BK-SWMM flood simulation framework. The applicability of the proposed framework is validated by modeling three different spatial scales in the study regions based on observed rainfall-runoff data. The research findings indicate that the distribution pattern of uncertainty parameters, such as depression storage, surface Manning coefficient, infiltration rate, and attenuation coefficient. The distribution patterns of these seven parameters in urban functional zones indicate that the values are highest in the Industrial and Commercial Areas (ICA), followed by Residential Areas (RA), and lowest in Public Areas (PA). All three spatial scales' REQ, NSEQ, and RD2 indices were superior to the SWMM and less than 10%, greater than 0.80, and greater than 0.85, respectively. However, when the study area's geographical scale expands, the simulation's accuracy will decline. Further research is required on the scale dependency of urban storm flood models.

Research on asphalt materials based on machine vision and generate adversarial networks

With the rapid development of artificial intelligence and deep learning, computer vision-oriented generative models have been widely used. Among them, the generation of adversarial network has the most far-reaching influence. To solve the problem of dynamic instability in the training of generative adversarial networks, this paper proposes a rapid construction method of generative adversarial networks based on hidden layer characterization. The generation process of the adversarial network is divided into two independent generation processes to generate the representation of the experience hidden layer and the final result respectively, so as to stably generate the training dynamics of the adversarial network and capture more data patterns. This method can effectively and stably generate the training dynamics of the adversarial network. Finally, theoretical analysis proves that this method can stably generate the training dynamics of adversarial network and reduce the difficulty of adversarial training. Large-scale experiments on multiple data sets demonstrate the effectiveness of the proposed method.

Dual-particles functionalized hybrid biosorbent based on a facile etching-loading method for Pb2+ adsorption

Herein, novel cellulose-based biosorbent with dual-particles system was fabricated through a rapid and facile etching-loading method. The results shown the adsorbent exhibited efficient and stable adsorption performance which is owing to the firm embedding of functional particles without interference on the oxidized matrix. And the maximum adsorption capacity for Pb2+ reached 372.4 mg/g. The corresponding adsorption behavior was found to accord well with the pseudo-second-order kinetic model and Langmuir isotherm model, which reveals the rate-limiting phase of adsorption process is attributed to chemical adsorption type, and Pb2+ was adsorbed onto biosorbent surface by monolayer spontaneous chemical reaction. Surface physical attraction and chemical complexation bond are dominant adsorption mechanisms. And the recycling efficiency of biosorbent reached above 83% after 5 cycles. The above results indicate the hybrid functional structure by etching-loading route provided a novel method for rapid construction of promising and recyclable adsorbent for wastewater treatment.

UV-triggered fast assembly of a high-performing stable enzyme@MOF composite membrane for efficient aquatic micropollutants removal

As conventional water purification technologies are inefficient, they put us at risk of exposure to emerging micropollutants. Here, we report a two-step method for rapid construction of a stable enzyme@MOF biomimetic membrane comprising enzyme-embedded metal–organic framework-based biocomposites for continuous and efficient removal of micropollutants from water. We first prepared a horseradish peroxidase@zeolitic imidazolate framework-8 (HRP@ZIF-8) biocomposite via ball-milling method, capable of preserving structural integrity and the entrapped enzyme bioactivity under different denaturing environments. The second step involves biocomposite membrane synthesis via stimulation of polydopamine (PDA) polymerization with UV light after successively dispersing the dopamine and HRP@ZIF-8 biocomposite molecules in a neutral pH Tris-HCl system. Accompanied by the clever codeposition with PDA, the HRP@ZIF-8 biocomposite can be “sandwiched” between the PDA layers to create a stable HRP@ZIF-8-composite membrane (HRP@ZIF-8-CM). HRP@ZIF-8-CM synergistically integrates MOF adsorption, enzyme catalysis, and membrane separation functions. The calculated encapsulation rate of the HRP@ZIF-8 biocomposite is ≤ 98.2 %. The enzyme@MOF composite membrane has a catalytic degradation efficiency of 98 % for bisphenol A (1 mg/L), membrane water flux of 32.3 L/m2 h bar, outstanding stability, and high efficiency after 7 cycles of use. Surprisingly, the bisphenol A removal rate of the enzyme@MOF composite membrane remained stable under varying denaturing conditions, including wide pH and temperature ranges and proteolytic enzymes, indicating that HRP enzyme activity is well preserved, probably owing to the bio-inertness of ZIF-8. In conclusion, we propose a new, simple, and fast method for the constructing enzyme@MOF composite membranes, which can significantly improve water purification.

Analysis of Human Clinical Mutations of Mitochondrial ND1 in a Bacterial Model System for Complex I.

The most common causes of mitochondrial dysfunction and disease include mutations in subunits and assembly factors of Complex I. Numerous mutations in the mitochondrial gene ND1 have been identified in humans. Currently, a bacterial model system provides the only method for rapid construction and analysis of mutations in homologs of human ND1. In this report, we have identified nine mutations in human ND1 that are reported to be pathogenic and are located at subunit interfaces. Our hypothesis was that these mutations would disrupt Complex I assembly. Seventeen mutations were constructed in the homologous nuoH gene in an E. coli model system. In addition to the clinical mutations, alanine substitutions were constructed in order to distinguish between a deleterious effect from the introduction of the mutant residue and the loss of the original residue. The mutations were moved to an expression vector containing all thirteen genes of the E. coli nuo operon coding for Complex I. Membrane vesicles were prepared and rates of deamino-NADH oxidase activity and proton translocation were measured. Samples were also tested for assembly by native gel electrophoresis and for expression of NuoH by immunoblotting. A range of outcomes was observed: Mutations at four of the sites allow normal assembly with moderate activity (50−76% of wild type). Mutations at the other sites disrupt assembly and/or activity, and in some cases the outcomes depend upon the amino acid introduced. In general, the outcomes are consistent with the proposed pathogenicity in humans.

Construction of a Versatile, Programmable RNA-Binding Protein Using Designer PPR Proteins and Its Application for Splicing Control in Mammalian Cells.

RNAs play many essential roles in gene expression and are involved in various human diseases. Although genome editing technologies have been established, the engineering of sequence-specific RNA-binding proteins that manipulate particular cellular RNA molecules is immature, in contrast to nucleotide-based RNA manipulation technology, such as siRNA- and RNA-targeting CRISPR/Cas. Here, we demonstrate a versatile RNA manipulation technology using pentatricopeptide-repeat (PPR)-motif-containing proteins. First, we developed a rapid construction and evaluation method for PPR-based designer sequence-specific RNA-binding proteins. This system has enabled the steady construction of dozens of functional designer PPR proteins targeting long 18 nt RNA, which targets a single specific RNA in the mammalian transcriptome. Furthermore, the cellular functionality of the designer PPR proteins was first demonstrated by the control of alternative splicing of either a reporter gene or an endogenous CHK1 mRNA. Our results present a versatile protein-based RNA manipulation technology using PPR proteins that facilitates the understanding of unknown RNA functions and the creation of gene circuits and has potential for use in future therapeutics.

Alternative Design of Post-Earthquake Permanent Housing in Indonesia using Cold Formed Steel

This article informs about permanent housing 2-story necessity for the Earthquake victim’s refugees in Indonesia. Continuing about the temporary housing (Huntara 1.0) which has been studied previously. In this article, an alternative earthquake resistant design of permanent housing using Cold-Formed Steel is proposed. Same as previous research, the loading estimation used assumption that the buildings are located in Yogyakarta as one of the cities that has the highest value of PGA. Another assumption of loading is based on available Indonesia Building Code, including the calculation of structural ability and design. Stress ratio check is automatically done using AISI LRFD 96, then manually checked using Indonesia’s code. The model also accommodates stiffness of masonry panel using Holmes equation. Overall, a new alternative design of post-earthquake permanent housing is presented in this article with relatively economic in budget and rapid construction method.

Ce3+-induced Fluorescence Amplification of Copper Nanoclusters Based on Aggregation-induced Emission for Specific Sensing 2,6-pyridine Dicarboxylic Acid.

A straightforward, cost-effective and biocompatible reduction approach was applied to fabricate soluble but non-luminous glutathione-stabilized copper nanocluster (GSH-CuNCs). Surprisingly, as high as 1 × 103 times fluorescence enhancement was acquired when Ce3+ was injected at an extremely low concentration of only 18µM. Ce3+ outperformed other rare-earth metal ions in terms of inducing fluorescence amplification of the non-luminous GSH-CuNCs. Furthermore, Ce3+ was employed as inducer for aggregation-induce emission (AIE) effect as well as reactant to coordinate with target of 2,6-pyridine dicarboxylic acid (DPA) due to the stronger coordination ability between Ce3+ and DPA than that of Ce3+ and GSH. As a result, the Ce3+/GSH-CuNCs ensemble was developed as a novel sensor to detect DPA in the "on-off" mode. When DPA was introduced into the sensor, Ce3+ failed to interact with GSH and detached from the surface of GSH-CuNCs, leading to fluorescence quenching. In addition, static quenching process and internal filtration effect (IFE) between Ce3+/GSH-CuNCs and DPA were also responsible for fluorescence quenching effect. A good linear relationship was obtained from 0.3µM to 18µM, with a limit of detection (LOD) of 0.19µM. The as-proposed probe displayed high specificity to DPA and provided a simple, fast rapid and cheap method for construction this type of ensemble sensors to detect other targets.

INDOOR AND OUTDOOR STRUCTURED MONOMER RECONSTRUCTION OF CITY 3D REAL SCENE BASED ON NONLINEAR OPTIMIZATION AND INTEGRATION OF MULTI-SOURCE AND MULTI-MODAL DATA

Abstract. 3D Real Scene is an important part of new infrastructure construction, which provides a unified spatial base for economic and social development and informatization of various departments. According to the demand of real 3D Real Scene digital construction, this paper aims to study the method of indoor and outdoor structured monomer reconstruction of city 3D Real Scene, develop digital twin platform, and strive to lead the development of 3D Real Scene. The main research contents of this paper are as follows: 1) Spatio-temporal-spectral-angular remote sensing observation system and data fusion model; 2) Rapid construction method of vector monomer 3D model of indoor and outdoor entity object; 3) 3D structural reconstruction technology of urban component level based on vector images; 4) A universal digital twins platform, LuojiaDT. The technologies we have developed have been widely used in the national 3D Real Scene construction of China, including smart city, smart transportation, cultural heritage protection, public security and police, urban underground pipe network, indoor and outdoor location service. This research will promote the continuous development of digital twins technology.

The rapid construction method of human body model for virtual try-on on mobile terminal based on MDD-Net

Traditional anthropometric evaluation needs professional measuring tools and operations, and it is time-consuming, expensive, and not suitable for virtual try-on. As the mobile internet develops, the issue of human body reconstruction toward virtual try-on needs to be tackled. This paper proposes a rapid human body reconstruction method for virtual try-on based on multidimensional dense net (MDD-Net) on mobile terminal. MDD-Net takes fusion features as input and predicts 3D human body model. The acquisition of fusion features and the display of 3D human body are implemented on mobile toward virtual try-on. In the learning fuzzy anthropometric feature module, the example-guided fuzzy anthropometric feature matrix is acquired and default coding elements are interpolated. In the learning multi-perspective silhouette feature module, the fine human body shape features are learned based on DenseNet201. A related fusion feature data set is generated for the training and testing of MDD-Net. Compared to shape pose estimation models, the shape representation spaces of HMR and SMPLify are only 20.34% and 7.59% of our method, and their prediction accuracies are approximately 50% of our method. Compared to accurate shape estimation models, our method is more robust against the pose and perspective noise. The prediction accuracies of our method are improved by 13.34%, 55.77%, 34.6%, and 43.4%, 37.2% 9.0% on four test sets. Extensive experiments have demonstrated the superiority of our method for human body shape estimation toward virtual try-on.