MethodsX最新文献_第3页

Bifurcation analysis and phase portraits for chiral solitons with bohm potential in quantum hall effect 量子霍尔效应中具有玻姆势的手性孤子的分岔分析和相刻画

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2025-12-11 DOI: 10.1016/j.mex.2025.103761

Lu Tang , Yakup Yildirim , Ahmed H. Arnous , Ahmed Shaker Mahmood , Ibrahim Zeghaiton Chaloob , Anjan Biswas

This paper presents a comprehensive bifurcation analysis and phase portrait investigation of chiral solitons governed by the chiral nonlinear Schrödinger equation with Bohm potential in the Quantum Hall Effect framework. The equation accounts for chirality, quantum corrections, and nonlinear interactions, making it a valuable model for soliton behavior in quantum fluids. We analyze the system’s dynamical properties, equilibrium points, and solution regimes using bifurcation theory, revealing stability transitions and structural changes in soliton solutions. Phase plane techniques visualize qualitative behaviors under varying parameters. Additionally, we derive exact optical soliton solutions, demonstrating the Bohm potential’s influence on soliton formation and evolution. These findings offer insights into nonlinear wave propagation in chiral quantum systems and have potential applications in condensed matter physics and optical fiber systems.

The paper analyzes chiral solitons using bifurcation theory and phase portraits to reveal stability transitions and dynamic behaviors.

Exact soliton solutions are derived, highlighting the effects of Bohm potential and chirality on soliton formation.

The results provide insights into nonlinear wave propagation in quantum fluids and optical fiber systems.

本文在量子霍尔效应框架下，对具有玻姆势的手性非线性Schrödinger方程控制的手性孤子进行了全面的分岔分析和相画像研究。该方程考虑了手性、量子修正和非线性相互作用，使其成为量子流体中孤子行为的一个有价值的模型。我们利用分岔理论分析了系统的动力学性质、平衡点和解状态，揭示了孤子解的稳定性转变和结构变化。相平面技术可视化在不同参数下的定性行为。此外，我们得到了精确的光学孤子解，证明了玻姆势对孤子形成和演化的影响。这些发现为研究手性量子系统中的非线性波传播提供了新的思路，并在凝聚态物理和光纤系统中具有潜在的应用前景。利用分岔理论和相画像分析手性孤子，揭示其稳定性转变和动力学行为。推导了精确的孤子解，强调了玻姆势和手性对孤子形成的影响。该结果为量子流体和光纤系统中的非线性波传播提供了见解。

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引用次数: 0

AI-powered mental health application with data privacy preservation 具有数据隐私保护功能的人工智能心理健康应用程序

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2025-12-11 DOI: 10.1016/j.mex.2025.103756

Pooja Bagane , Anushree Dahiya , Shardul Kacheria , Ansh Sehgal , Shrishti Bajpai , Obsa Amenu Jebessa

Anxiety disorders, emotional conditions, and stress are becoming an increasing tendency in modern society, which makes digital mental health technologies that provide support in these cases highly demanded. This paper focuses on proposing an AI-driven framework that combines Natural Language Processing (NLP) with privacy-protective systems to recognize emotions in the text of the user. The AES-256 encryption, Supabase authentication, and role-based access control are used to secure data security. It is presented as a multi-label problem of emotion classification, which is fine-tuned on the BERT-base-uncased and ModernBERT Large transformer. ModernBERT exhibited rapid convergence and enhanced situational sensitivity especially when it comes to sarcasm and mixed emotional states.

Key contributions include:

•
Planning an emotion feedback loop offering contextual response and customized mindfulness teaching.
•
Performing a Class imbalance analysis of emotions and trade-offs in precision and recall.
•
Illustrating privacy-first architecture that is able to integrate with digital-therapy and clinician assisted decision software.

在现代社会中，焦虑症、情绪状况和压力正成为一种日益增长的趋势，这使得在这些情况下提供支持的数字心理健康技术受到高度要求。本文的重点是提出一个人工智能驱动的框架，该框架将自然语言处理（NLP）与隐私保护系统相结合，以识别用户文本中的情绪。采用AES-256加密、Supabase认证和基于角色的访问控制，保证数据安全。它是一个多标签的情感分类问题，在bert -base-uncase和ModernBERT Large变压器上进行微调。现代伯特表现出快速收敛和增强的情境敏感性，特别是在涉及讽刺和混合情绪状态时。主要贡献包括：•规划一个情感反馈循环，提供情境反应和定制的正念教学。•执行类的不平衡分析的情绪和权衡的精度和召回。•说明了能够与数字治疗和临床医生辅助决策软件集成的隐私优先架构。

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引用次数: 0

Standardizing food web reconstruction from metabarcoding data using iterative rarefaction and trait-based trophic inference model 基于迭代稀疏和基于性状的营养推断模型的元条形码数据食物网重构标准化研究

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2026-06-03 DOI: 10.1016/j.mex.2026.103988

Víctor Lecegui , Vincent E.J. Jassey , Aaron Pérez-Haase

High-throughput metabarcoding combined with trait-based trophic inference models enables the reconstruction of food webs from community eDNA. However, uneven sequencing depth can bias inferred food web structure. Network metrics derived from unstandardized read counts may reflect sampling effort rather than ecological processes. Here, we present an objective and reproducible framework using iterative rarefaction with trait-based trophic inference to standardize food web metrics prior to ecological analysis.

Our approach links rarefaction depth to network-level properties by generating rarefaction curves based on food web metrics rather than taxonomic richness. An optimal rarefaction threshold is determined using a first derivative criterion, and rarefied networks are reconstructed repeatedly to obtain robust mean metric estimates.

We applied this method to soil protist communities assessed using 18S rRNA metabarcoding. The method reduced sequencing-depth bias and revealed environmental drivers that were masked in non-rarefied analyses.

This framework provides a standardized solution for comparing food webs derived from amplicon datasets across environmental gradients.

Integrates trait-based trophic inference with iterative rarefaction of metabarcoding communities.

Selects rarefaction thresholds using food web network properties rather than species accumulation curve.

Provides reliable estimates of food web structure independent of sequencing effort.

高通量元条形码结合基于性状的营养推断模型，可以从社区eDNA重建食物网。然而，不均匀的测序深度可能会影响推断出的食物网结构。来自非标准化读取计数的网络度量可能反映采样努力，而不是生态过程。在这里，我们提出了一个客观的、可重复的框架，使用基于性状的营养推断的迭代稀疏来标准化生态分析之前的食物网指标。我们的方法通过基于食物网指标而不是分类丰富度生成稀疏曲线，将稀疏深度与网络级属性联系起来。利用一阶导数准则确定最优稀疏阈值，并对稀疏网络进行多次重构以获得稳健的平均度量估计。我们将该方法应用于土壤原生生物群落的18S rRNA元条形码评估。该方法减少了测序深度偏差，并揭示了在非稀有分析中被掩盖的环境驱动因素。该框架提供了一个标准化的解决方案，用于比较来自不同环境梯度的扩增子数据集的食物网。整合了基于性状的营养推理与元条形码社区的迭代稀疏。利用食物网网络特性而非物种积累曲线选择稀疏阈值。提供独立于测序工作的食物网结构的可靠估计。

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引用次数: 0

Development of an inexpensive, simple purification method for ω-5 gliadin from wheat flour 一种廉价、简单的从小麦粉中提纯ω-5麦胶蛋白的方法

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 DOI: 10.1016/j.mex.2026.103979

Akihiro Maeta , Mamoru Tanaka , Kyoko Takahashi

ω-5 gliadin is a major causative allergen associated with various types of wheat allergy, including wheat-dependent exercise-induced anaphylaxis. Recently, ω-5 gliadin-deficient wheat has been developed. However, several wheat protein studies do not use standard ω-5 gliadin because its naturally derived form is expensive, and purifying it in-house is time-consuming. Therefore, we sought to develop an inexpensive, simple method for purifying ω-5 gliadin on a small scale.

▪
We compared ω-5 gliadin-deficient wheat with normal wheat and screened for ω-5 gliadin bands using acid-polyacrylamide gel electrophoresis (A-PAGE) on a mini-slab electrophoresis apparatus.
▪
The ω-5 gliadin band was excised and sealed in dialysis tubing, and the protein was electroeluted using agarose gel electrophoresis. After electroelution, the eluted solution was filtered, dialyzed, and then freeze-dried.
▪
The main band of collected proteins migrated at approximately 55 kDa in SDS-PAGE, and the most intense band was identified as ω-5 gliadin using nano-LC-MS/MS.

ω-5麦胶蛋白是与多种小麦过敏相关的主要致敏原，包括小麦依赖性运动致过敏反应。近年来，ω-5麦胶蛋白缺乏小麦已被开发出来。然而，一些小麦蛋白研究没有使用标准的ω-5麦胶蛋白，因为它的自然衍生形式是昂贵的，并且在内部纯化它是耗时的。因此，我们寻求一种廉价、简单的方法来小范围提纯ω-5麦胶蛋白。▪我们将ω-5麦胶蛋白缺乏的小麦与正常小麦进行比较，并在微型平板电泳仪上使用酸-聚丙烯酰胺凝胶电泳（a - page）筛选ω-5麦胶蛋白带。▪切除ω-5麦胶蛋白带，在透析管中密封，琼脂糖凝胶电泳电泳蛋白。电洗脱后，将洗脱液过滤，透析，然后冷冻干燥。▪收集到的蛋白主带在SDS-PAGE中迁移约55 kDa，并通过纳米lc -MS/MS鉴定为ω-5麦胶蛋白。

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引用次数: 0

Enhancing grape disease detection: A comparative analysis of hybrid CNN-LSTM and CNN methods 增强葡萄病害检测：CNN- lstm与CNN杂交方法的比较分析

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2026-06-02 DOI: 10.1016/j.mex.2026.103983

Vinod Mulik , Vinod Patil

Crop disease detection is crucial for maintaining high agricultural productivity and minimizing the financial losses of farmers.

•
This study compares the performance of a hybrid method based on integrating the Long Short-Term Memory algorithm (LSTM) and Convolutional Neural Network (CNN) with a standalone CNN method for grape crop disease detection and classification.
•
The proposed methods are trained and tested on a comprehensive balanced and imbalanced grape leaf dataset with 4000 and 4062 images, respectively. The imbalanced dataset has 423 images of the healthy class, 1383 of ESCA, 1076 of leaf blight, and 1180 images of the black rot class, while the balanced dataset has 1000 images in each class
•
The LSTM-CNN method achieved 100%, and the CNN method achieved 99.47% accuracy on the balanced dataset. Also, in the case of the imbalanced dataset, 100% and 97.89%, respectively.

Among these two methods implemented, the proposed LSTM-CNN method has achieved excellent results in terms of performance metrics. This study presents a deep learning-based system for automated leaf disease classification. The model is designed for end-user deployment, where users can upload a leaf image and receive an immediate prediction of the disease without requiring model retraining or technical expertise.

作物病害检测对于保持高农业生产力和尽量减少农民的经济损失至关重要。•本研究比较了一种基于长短期记忆算法（LSTM）和卷积神经网络（CNN）的混合方法与一种独立的CNN方法在葡萄作物病害检测和分类中的性能。•提出的方法分别在包含4000张和4062张图像的综合平衡和不平衡葡萄叶数据集上进行了训练和测试。不平衡数据集中健康类图像423张，ESCA类图像1383张，叶枯病类图像1076张，黑腐病类图像1180张，而平衡数据集中每个类图像1000张。LSTM-CNN方法在平衡数据集中准确率达到100%，CNN方法在平衡数据集中准确率达到99.47%。同样，在不平衡数据集的情况下，分别为100%和97.89%。在这两种方法中，提出的LSTM-CNN方法在性能指标方面取得了优异的成绩。本研究提出了一种基于深度学习的叶片病害自动分类系统。该模型是为最终用户部署而设计的，用户可以上传叶子图像并立即获得疾病预测，而无需对模型进行再培训或专业技术知识。

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引用次数: 0

Artificial neural network based predictive modeling of viscosity of an oil based hybrid nanofluid 基于人工神经网络的油基混合纳米流体粘度预测建模

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2025-12-04 DOI: 10.1016/j.mex.2025.103748

Muhammad Furqan , Fahim Raees , Muhammad Khalid

In many industries like micro-electronics, mechanical engines, transportation, manufacturing and nuclear reactors cooling characteristics which is a crucial challenge can optimize using nanofluid. Nanofluids are also used for better energy transfer and storage in many devices. In the current study the viscosity variation studied by the impact of input variables solid volume fraction and temperature. Sol-gel auto-combustion was used to prepare nickel ferrite (NiFe₂O₄) nano-particles. The structure of the NiFe₂O₄ was obtained using an X-ray diffraction method. The Fourier transform infrared spectrum provided evidence of NiFe₂O₄ presence. In order to better understand the surface morphology of nickel ferrite nano-particles, scanning electron microscopy (SEM) was employed. AT the various concentrations of nanofluid 0, 0.25, 0.50, 0.75, and 1 % were prepared. The viscosity was calculated at temperatures ranges 40 to 80 °C. The experimental results showed that the viscosity of nanofluid (µ_nf) falls as the volume fraction(φ) increases and as the temperature rises. RSM and ANN predicted data have R² values of 0.9987 and 0.9999 respectively.. ANN accuracy can also be seen by MSE value. ANN shows less MSE value (0.00001) as compare to RSM that has MSE 0.0002. Which shows the ANN accuracy over RSM.

Predictive modelling for viscosity of Oil-Based Hybrid Nanofluid.

Artificial Neural Network and Response surface methodology methods were used for correlation.

Results were correlated with experimental data.

在微电子、机械发动机、交通运输、制造业和核反应堆等许多行业中，利用纳米流体可以优化冷却特性是一个至关重要的挑战。在许多设备中，纳米流体也用于更好的能量传递和存储。在目前的研究中，粘度的变化主要受固体体积分数和温度等输入变量的影响。采用溶胶-凝胶自燃烧法制备了纳米铁酸镍（NiFe2O4）。用x射线衍射法得到了NiFe2O4的结构。傅里叶变换红外光谱提供了NiFe2O4存在的证据。为了更好地了解纳米铁酸镍颗粒的表面形貌，采用扫描电子显微镜（SEM）进行了研究。分别制备了浓度为0、0.25、0.50、0.75、1%的纳米流体。在40 ~ 80℃的温度范围内计算了粘度。实验结果表明，随着体积分数（φ）的增大和温度的升高，纳米流体的粘度（µnf）减小。RSM和ANN预测数据的R2值分别为0.9987和0.9999。通过MSE值也可以看出人工神经网络的准确性。与MSE为0.0002的RSM相比，ANN的MSE值（0.00001）更小。这显示了人工神经网络在RSM上的精度。油基混合纳米流体粘度预测模型。采用人工神经网络和响应面方法进行相关性分析。结果与实验数据相吻合。

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引用次数: 0

Data-driven 1D design model for monotonic lateral loading of monopile foundations 单桩基础单调侧向荷载的一维数据驱动设计模型

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2025-11-26 DOI: 10.1016/j.mex.2025.103738

Ioannis Kamas , Stephen K. Suryasentana , Harvey J. Burd , Byron W. Byrne

Monopiles are a widely-used foundation system for offshore wind turbine support structures. In current practice, design calculations typically employ one-dimensional (1D) models in which the monopile is represented as an embedded beam. The current study presents a data-driven 1D design model for the analysis of offshore monopiles subjected to monotonic lateral load and moment loading. The method is based on the PISA design model framework; enhancements are incorporated in the model to improve its accuracy, scalability and to facilitate applications to a wide range of geotechnical conditions. The data-driven model incorporates a spline-based parametrisation of the soil reaction curves combined with machine learning techniques. The model is calibrated using a database of previously-published three-dimensional finite element calibration analyses. The method described in the current paper is concerned with:

•
Modifications to the PISA design model framework to develop a data-driven 1D design model.
•
Calibration of the data-driven 1D model for ground conditions comprising: (i) offshore glacial tills with varying strength–stiffness properties, and (ii) sands with a wide range of relative densities.
•
Validation of the proposed method by comparing 1D model predictions for monopiles in homogeneous and layered soils with detailed 3D finite element analyses.

单桩是一种广泛应用于海上风电机组支撑结构的基础体系。在目前的实践中，设计计算通常采用一维（1D）模型，其中单桩表示为嵌入梁。目前的研究提出了一种数据驱动的一维设计模型，用于分析受单调侧向荷载和弯矩荷载作用的海上单桩。该方法基于PISA设计模型框架；在模型中加入了增强功能，以提高其准确性，可扩展性，并促进应用于广泛的岩土条件。数据驱动模型结合了基于样条的土壤反应曲线参数化与机器学习技术。该模型使用先前发表的三维有限元校准分析数据库进行校准。本文中描述的方法涉及：•修改PISA设计模型框架，以开发数据驱动的一维设计模型。•校准数据驱动的一维模型，用于地面条件，包括：(i)具有不同强度-刚度特性的近海冰川丘，以及（ii）具有广泛相对密度的砂。•通过比较均匀和分层土壤中单桩的1D模型预测与详细的3D有限元分析，验证所提出的方法。

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引用次数: 0

Health policies in long-term care facilities for older adults: A systematic review of textual evidence 老年人长期护理机构的卫生政策：文本证据的系统回顾

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2026-01-13 DOI: 10.1016/j.mex.2026.103798

Florbela Bia , Matheus Kirton dos Anjos , Zaida Charepe , Cristina Marques-Vieira

Background

Health polices in residential care settings for older adults are essential to align housing and care provision with the needs of ageing populations, ensuring safety, participation, and quality of life. Despite their importance, evidence regarding policy implementation in long-term care (LTC) facilities remains fragmented and inconsistent.

Objective

This protocol describes an original method for synthesizing health policy documents using the Joanna Briggs Institute (JBI) framework for textual evidence. It aims to identify, analyze, and integrate policy evidence related to LTC facilities for older adults.

Methods

Following JBI methodological guidance for systematic reviews of text and opinion, this protocol employs the PICo framework to define inclusion criteria and a three-step search strategy. Searches will be conducted in MEDLINE, CINAHL Complete®, and the Virtual Health Library (BVS). Eligible documents include laws, regulations, policy frameworks, and technical guidelines addressing long-term care within publicly regulated systems. Data extraction and quality appraisal will be independently performed by two reviewers using JBI instruments.

Expected Results

The review will synthesize existing polices, highlighting their characteristics, implementation strategies, and outcomes. By applying a transparent and replicable JBI-based method, this protocol supports the production of high-quality evidence to inform equitable and effective governance in LTC facilities

背景：老年人住宿护理机构的卫生政策对于使住房和护理服务与老龄化人口的需求保持一致，确保安全、参与和生活质量至关重要。尽管它们很重要，但关于长期护理（LTC）设施政策实施的证据仍然零散且不一致。目的本协议描述了一种使用乔安娜布里格斯研究所（JBI）文本证据框架合成卫生政策文件的原始方法。它旨在识别、分析和整合与老年人长期服务中心设施相关的政策证据。方法遵循JBI对文本和观点进行系统综述的方法学指导，本协议采用PICo框架定义纳入标准和三步搜索策略。检索将在MEDLINE、CINAHL Complete®和虚拟健康图书馆（BVS）中进行。符合条件的文件包括法律、法规、政策框架和技术指南，涉及公共监管系统内的长期护理。数据提取和质量评估将由两名审稿人使用JBI仪器独立完成。评估将综合现有政策，突出其特点、实施策略和成果。通过采用透明和可复制的基于jbi的方法，该协议支持产生高质量的证据，为LTC设施的公平和有效治理提供信息

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引用次数: 0

Reconciled multiplicative relational two-stage network data envelopment analysis 调和乘法关系两阶段网络数据包络分析

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2025-12-11 DOI: 10.1016/j.mex.2025.103758

M. Burak Erturan

Relational two-stage network DEA (data envelopment analysis) is an approach for two-stage systems, where all input, output and the intermediate products have same weights regardless of which process they are related. One of the main approaches to relational model is the multiplicative relational approach where main process efficiency is the product of two sub-process efficiencies. A shortcoming of the relational model is that the solution of the sub-process efficiencies may not be unique. Researchers have developed some models to overcome this problem, like prioritizing one sub-process to the other or assessing the sub-process efficiencies first and then the main process efficiency. In this study, a novel methodology is presented for a fairer efficiency assessment, where none of the processes is prioritized.

•
Reconciled Multiplicative Relational (RMR) model presented in this study uses data reconciliation method to determine maximum efficiency values for all processes simultaneously within the relational constraints.
•
RMR model has unique efficiency assessment solution, which solves the non-uniqueness problem and useful where none of the DMUs are preferred to another or there is no previous information in that matter.

关系两阶段网络DEA（数据包络分析）是一种针对两阶段系统的方法，其中所有的输入、输出和中间产品无论与哪个过程相关都具有相同的权重。关系模型的主要方法之一是乘法关系方法，其中主流程效率是两个子流程效率的乘积。关系模型的一个缺点是子流程效率的解决方案可能不是唯一的。研究人员已经开发了一些模型来克服这一问题，比如将一个子过程优先于另一个子过程，或者先评估子过程的效率，然后再评估主过程的效率。在这项研究中，提出了一种新的方法来进行更公平的效率评估，其中没有一个过程是优先考虑的。•本研究提出的调和乘法关系（RMR）模型使用数据调和方法在关系约束下同时确定所有流程的最大效率值。•RMR模型具有独特的效率评估方案，解决了非唯一性问题，在没有一个dmu优先于另一个dmu或在该事项中没有先前信息的情况下非常有用。

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引用次数: 0

The Rapid Initial Community Builder (RICB) V1.1 for LANDIS-II 用于LANDIS-II的快速初始社区构建器（RICB） V1.1

IF 1.9 Q2 MULTIDISCIPLINARY SCIENCES

MethodsX

Pub Date : 2026-06-01 Epub Date: 2025-12-13 DOI: 10.1016/j.mex.2025.103765

Steven A Flanagan , Zachary J. Robbins , Mac A. Callaham Jr , J. Kevin Hiers , Brian R. Miranda , Joseph J. O’Brien , Robert M. Scheller , E. Louise Loudermilk

Forest succession, or ecosystem process models, can aid in many land management decisions as they inherently incorporate ecological processes to predict how disturbances impact the resilience of the forest and its potential future structure. The landscape class of ecosystem process models are often ideal for management goals as they simulate individual tree species interactions through time at the landscape scale and offer a robust assortment of disturbance extensions. However, broad implementation and adoption are often limited as users must rebuild the landscape models for every new site of interest. Creation of the initial forest communities that all model simulations depend on, can be particularly time consuming. To address this issue, we created the Rapid Initial Community Builder (RICB) that:

•
Starts with high resolution CONtinental United States (CONUS) forest coverage and type data.
•
Makes modifications to the data for use in the landscape class ecosystem process model LANDIS-II.
•
Packages everything in an executable file that eliminates coding language or version barriers.

Thus, greatly reducing the initialization time often associated with the intensive data assimilation techniques commonly used to generate initial communities.

森林演替或生态系统过程模型可以帮助许多土地管理决策，因为它们本质上包含生态过程，以预测干扰如何影响森林的恢复能力及其潜在的未来结构。景观类生态系统过程模型通常是理想的管理目标，因为它们模拟了景观尺度上单个树种随时间的相互作用，并提供了各种各样的干扰扩展。然而，广泛的实施和采用往往受到限制，因为用户必须为每个感兴趣的新站点重新构建景观模型。所有模型模拟所依赖的原始森林群落的创建可能特别耗时。为了解决这个问题，我们创建了快速初始社区构建器（RICB），它：•从高分辨率美国大陆（CONUS）森林覆盖率和类型数据开始。•对用于景观级生态系统过程模型LANDIS-II的数据进行修改。•将所有内容打包到可执行文件中，从而消除编码语言或版本障碍。因此，大大减少初始化时间通常与用于生成初始社区的密集数据同化技术相关。

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引用次数: 0