DNA Methylation Variation Is Identified in Monozygotic Twins Discordant for Congenital Heart Diseases

Aims:Multiple genes and environmental factors are known to be involved in congenital heart disease(CHD),but epigenetic variation has received little attention.Monozygotic(MZ)twins with CHD provide a unique model for exploring this phenomenon.In order to investigate the potential role of Deoxyribonucleic Acid(DNA)methyla-tion in CHD pathogenesis,the present study examined DNA methylation variation in MZ twins discordant for CHD,especially ventricular septal defect(VSD).Methods and Results:Using genome-wide DNA methylation profiles,we identified 4004 differentially methylated regions(DMRs)in 18 MZ twin pairs discordant for CHD,and 2826 genes were identified.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)analysis revealed a list of CHD-associated pathways.To further investigate the role of DNA methylation in VSD,data from 7 pairs of MZ twins with VSD were analyzed.We identified 1614 DMRs corresponding to 1443 genes associated with arrhythmogenic right ventricular cardiomyopathy,cyclic guanosine monopho-sphate-protein kinase G(cGMP-PKG)signaling pathway by KEGG analysis,and cell-cell adhesion,calcium ion transmembrane transport by GO analysis.A proportion of DMR-associated genes were involved in calcium signaling pathways.The methylation changes of calcium signaling genes might be related to VSD pathogenesis.Conclusion:CHD is associated with differential DNA methylation in MZ twins.CHD may be etiologically linked to DNA methylation,and methylation of calcium signaling genes may be involved in the development of VSD.

Danish cohort of monozygotic inflammatory bowel disease twins: Clinical characteristics and inflammatory activity

AIM: To describe the establishment of a Danish inflammatory bowel diseases (IBD) twin cohort with focus on concordance of treatment and inflammatory markers.METHODS: We identified MZ twins, likely to be discordant or concordant for IBD, by merging information from the Danish Twin Register and the National Patient Register. The twins were asked to provide biological samples, questionnaires, and data access to patient files and public registries. Biological samples were collected via a mobile laboratory, which allowed for immediate centrifugation, fractionation, and storage of samples. The mean time from collection of samples to storage in the -80 °C mobile freezer was less than one hour. The diagnoses where validated using the Copenhagen diagnostic criteria.RESULTS: We identified 159 MZ IBD twin pairs, in a total of 62 (39%) pairs both twins agreed to participate. Of the supposed 62 IBD pairs, the IBD diagnosis could be confirmed in 54 pairs. The cohort included 10 concordant pairs, whereof some were discordant for either treatment or surgery. The 10 concordant pairs, where both pairs suffered from IBD, included eight CD/CD pairs, one UC/UC pair and one UC/IBDU pair. The discordant pairs comprised 31 UC, 5 IBDU (IBD unclassified), and 8 CD discordant pairs. In the co-twins not affected by IBD, calprotectin was above 100 μg/g in 2 participants, and above 50 μg/g in a further 5 participants.CONCLUSION: The presented IBD twin cohorts are an excellent resource for bioinformatics studies with proper adjustment for disease-associated exposures including medication and inflammatory activity in the co-twins.

Digital Twins for Wastewater Treatment:A Technical Review

The digital twins concept enhances modeling and simulation through the integration of real-time data and feedback.This review elucidates the foundational elements of digital twins,covering their concept,entities,domains,and key technologies.More specifically,we investigate the transformative potential of digital twins for the wastewater treatment engineering sector.Our discussion highlights the application of digital twins to wastewater treatment plants(WWTPs)and sewage networks,hardware(i.e.,facilities and pipes,sensors for water quality and activated sludge,hydrodynamics,and power consumption),and software(i.e.,knowledge-based and data-driven models,mechanistic models,hybrid twins,control methods,and the Internet of Things).Furthermore,two cases are provided,followed by an assessment of current challenges in and perspectives on the application of digital twins in WWTPs.This review serves as an essential primer for wastewater engineers navigating the digital paradigm shift.

A digital twins enabled underwater intelligent internet vehicle path planning system via reinforcement learning and edge computing

The Autonomous Underwater Glider(AUG)is a kind of prevailing underwater intelligent internet vehicle and occupies a dominant position in industrial applications,in which path planning is an essential problem.Due to the complexity and variability of the ocean,accurate environment modeling and flexible path planning algorithms are pivotal challenges.The traditional models mainly utilize mathematical functions,which are not complete and reliable.Most existing path planning algorithms depend on the environment and lack flexibility.To overcome these challenges,we propose a path planning system for underwater intelligent internet vehicles.It applies digital twins and sensor data to map the real ocean environment to a virtual digital space,which provides a comprehensive and reliable environment for path simulation.We design a value-based reinforcement learning path planning algorithm and explore the optimal network structure parameters.The path simulation is controlled by a closed-loop model integrated into the terminal vehicle through edge computing.The integration of state input enriches the learning of neural networks and helps to improve generalization and flexibility.The task-related reward function promotes the rapid convergence of the training.The experimental results prove that our reinforcement learning based path planning algorithm has great flexibility and can effectively adapt to a variety of different ocean conditions.

Origin of nucleation and growth of extension twins in grains unsuitably oriented for twinning during deformation of Mg-1%Al

A large number of anomalous extension twins,with low or even negative twinning Schmid factors,were found to nucleate and grow in a strongly textured Mg-1Al alloy during tensile deformation along the extruded direction.The deformation mechanisms responsible for this behaviour were investigated through in-situ electron back-scattered diffraction,grain reference orientation deviation,and slip trace-modified lattice rotation.It was found that anomalous extension twins nucleated mainly at the onset of plastic deformation at or near grain boundary triple junctions.They were associated with the severe strain incompatibility between neighbour grains as a result from the differentbasal slip-induced lattice rotations.Moreover,the anomalous twins were able to grow with the applied strain due to the continuous activation ofbasal slip in different neighbour grains,which enhanced the strain incompatibility.These results reveal the complexity of the deformation mechanisms in Mg alloys at the local level when deformed along hard orientations.

Survey on digital twins for Internet of Vehicles:Fundamentals,challenges,and opportunities

As autonomous vehicles and the other supporting infrastructures(e.g.,smart cities and intelligent transportation systems)become more commonplace,the Internet of Vehicles(IoV)is getting increasingly prevalent.There have been attempts to utilize Digital Twins(DTs)to facilitate the design,evaluation,and deployment of IoV-based systems,for example by supporting high-fidelity modeling,real-time monitoring,and advanced predictive capabilities.However,the literature review undertaken in this paper suggests that integrating DTs into IoV-based system design and deployment remains an understudied topic.In addition,this paper explains how DTs can benefit IoV system designers and implementers,as well as describes several challenges and opportunities for future researchers.

Digital Twins for Engineering Asset Management:Synthesis,Analytical Framework,and Future Directions

Effective engineering asset management(EAM)is critical to economic development and improving livability in society,but its complexity often impedes optimal asset functionalities.Digital twins(DTs)could revolutionize the EAM paradigm by bidirectionally linking the physical and digital worlds in real time.There is great industrial and academic interest in DTs for EAM.However,previous review studies have predominately focused on technical aspects using limited life-cycle perspectives,failing to holistically synthesize DTs for EAM from the managerial point of view.Based on a systematic literature review,we introduce an analytical framework for describing DTs for EAM,which encompasses three levels:DT 1.0 for technical EAM,DT 2.0 for technical-human EAM,and DT 3.0 for technical-environmental EAM.Using this framework,we identify what is known,what is unknown,and future directions at each level.DT 1.0 addresses issues of asset quality,progress,and cost management,generating technical value.It lacks multi-objective self-adaptive EAM,however,and suffers from high application cost.It is imperative to enable closed-loop EAM in order to provide various functional services with affordable DT 1.0.DT 2.0 accommodates issues of human-machine symbiosis,safety,and flexibility management,generating managerial value beyond the technical performance improvement of engineering assets.However,DT 2.0 currently lacks the automation and security of human-machine interactions and the managerial value related to humans is not prominent enough.Future research needs to align technical and managerial value with highly automated and secure DT 2.0.DT 3.0 covers issues of participatory governance,organization management,sustainable development,and resilience enhancement,generating macro social value.Yet it suffers from organizational fragmentation and can only address limited social governance issues.Numerous research opportunities exist to coordinate different stakeholders.Similarly,future research opportunities exist to develop DT 3.0 in a more open and complex system.

Exploring Alternatives to Create Digital Twins from and for Process Simulation

In this work,Digital Twins based on Neural Networks for the steady state production of styrene were generated.Thus,both the Aspen Technology AI Model Builder(alternative 1)and a homemade MS Excel VBA code connected to Aspen HYSYS and Aspen Plus(alternative 2)were used with this same aim.The raw data used for generating the Digital Twins were obtained from process simulations using Aspen HYSYS and/or Aspen Plus,which were connected through a recycle-like stream via automation for solving the entire simulation flowsheet.Aspen HYSYS was used for solving the pre-heating,reaction,and stabilization sections of the process whereas Aspen Plus ensured the computing of the separation and purification columns.Both alternatives led to an excellent prediction showing the capability of creating Digital Twins from and for process simulation.

Promoting hybrid twins structure to reduce yield asymmetry of rolled AZ31 plates by combining side-rolling and torsion

In this work,an as-rolled AZ31 square bar with c-axis//ND(normal direction)texture was used.Side-rolling and reciprocating torsion were performed to treat the bar.Microstructure evolution and tensile-compressive properties were investigated in detail.Initial rolled AZ31 bar exhibits a large yield asymmetry along the rolling direction(RD).Reciprocating torsion can generate extension twins to introduce twin boundaries and twin-texture.The twin structure can reduce yield asymmetry.However,only limited regions in the rolled AZ31 bar can be twinned during torsion.Pre-side-rolling along the transverse direction(TD)can generate two texture components(c-axis//TD texture and c-axis//ND texture)by introducing profuse{10–12}twins.Such dual texture components help increase the regions which are favorable for twinning during torsion.Finally,combining side-rolling and reciprocating torsion generates hybrid{10–12}twins structure on the entire cross-section,resulting in a remarkably low yield asymmetry.The relevant mechanisms were discussed in detail.

Modeling Methods of 3D Model in Digital Twins

To understand the current application and development of 3D modeling in Digital Twins(DTs),abundant literatures on DTs and 3D modeling are investigated by means of literature review.The transition process from 3D modeling to DTs modeling is analyzed,as well as the current application of DTs modeling in various industries.The application of 3D DTs modeling in the􀀀elds of smartmanufacturing,smart ecology,smart transportation,and smart buildings in smart cities is analyzed in detail,and the current limitations are summarized.It is found that the 3D modeling technology in DTs has broad prospects for development and has a huge impact on all walks of life and even human lifestyles.At the same time,the development of DTs modeling relies on the development and support capabilities of mature technologies such as Big Data,Internet of Things,Cloud Computing,Articial Intelligence,and game technology.Therefore,although some results have been achieved,there are still limitations.This work aims to provide a good theoretical support for the further development of 3D DTs modeling.

On the strengthening and slip activity of Mg-3Al-1Zn alloy with pre-induced{1012¯}twins

{1012¯}twins were introduced into the magnesium(Mg)plate AZ31 via pre-rolling along its transverse direction.The plates,both with and without the pre-induced{1012¯}twins,were subjected to uniaxial tension along different directions.Using crystal plasticity modeling,we found that the strengthening effect of the pre-induced{1012¯}twins on the macroscopic flow stress primarily arised from the increased slip resistance caused by the boundaries,rather than the orientation hardening due to the twinning reorientation(although the latter did make its contribution in some specific loading directions).Besides,the pre-existing{1012¯}twins were found,by both experiments and simulation,to promote the activity of prismatic and pyramidal<c+a>in the parent matrix of the material.Further analysis showed that the enhanced non-basal slip activity is related to the{1012¯}twin boundaries’low micro Hall-Petch slope ratios of non-basal slips to basal slip.With the critical resolved shear stress(CRSS)obtained from crystal plasticity modeling and the orientation data from EBSD,a probability-based slip transfer model was proposed.The model predicts higher slip transfer probabilities and thus lower strain concentration tendencies at{1012¯}twin boundaries than that at grain boundaries,which agrees with the experimental observation that the strain localization was primarily associated with the latter.The present findings are helpful scientifically,in deepening our understanding of how the pre-induced{1012¯}twins affect the strength and slip activity of Mg alloys,and technologically,in guiding the design of the pre-strain protocol of Mg alloys.

Design and Implementation of Secure and Reliable Information Interaction Architecture for Digital Twins

In order to improve the comprehensive defense capability of data security in digital twins(DTs),an information security interaction architecture is proposed in this paper to solve the inadequacy of data protection and transmission mechanism at present.Firstly,based on the advanced encryption standard(AES)encryption,we use the keystore to expand the traditional key,and use the digital pointer to avoid the key transmission in a wireless channel.Secondly,the identity authentication technology is adopted to ensure the data integrity,and an automatic retransmission mechanism is added for the endogenous properties of the wireless channel.Finally,the software defined radio(SDR)platform composed of universal software radio peripheral(USRP)and GNU radio is used to simulate the data interaction between the physical entity and the virtual entity.The numerical results show that the DTs architecture can guarantee the encrypted data transmitted completely and decrypted accurately with high efficiency and reliability,thus providing a basis for intelligent and secure information interaction for DTs in the future.

Regional Economic Development Trend Prediction Method Based on Digital Twins and Time Series Network

At present,the interpretation of regional economic development(RED)has changed from a simple evaluation of economic growth to a focus on economic growth and the optimization of economic structure,the improvement of economic relations,and the change of institutional innovation.This article uses the RED trend as the research object and constructs the RED index to conduct the theoretical analysis.Then this paper uses the attention mechanism based on digital twins and the time series network model to verify the actual data.Finally,the regional economy is predicted according to the theoretical model.The specific research work mainly includes the following aspects:1)This paper introduced the development status of research on time series networks and economic forecasting at home and abroad.2)This paper introduces the basic principles and structures of long and short-term memory(LSTM)and convolutional neural network(CNN),constructs an improved CNN-LSTM model combined with the attention mechanism,and then constructs a regional economic prediction index system.3)The best parameters of the model are selected through experiments,and the trained model is used for simulation experiment prediction.The results show that the CNN-LSTM model based on the attentionmechanism proposed in this paper has high accuracy in predicting regional economies.

Robustness optimization for rapid prototyping of functional artifacts based on visualized computing digital twins

This study presents a robustness optimization method for rapid prototyping(RP)of functional artifacts based on visualized computing digital twins(VCDT).A generalized multiobjective robustness optimization model for RP of scheme design prototype was first built,where thermal,structural,and multidisciplinary knowledge could be integrated for visualization.To implement visualized computing,the membership function of fuzzy decision-making was optimized using a genetic algorithm.Transient thermodynamic,structural statics,and flow field analyses were conducted,especially for glass fiber composite materials,which have the characteristics of high strength,corrosion resistance,temperature resistance,dimensional stability,and electrical insulation.An electrothermal experiment was performed by measuring the temperature and changes in temperature during RP.Infrared thermographs were obtained using thermal field measurements to determine the temperature distribution.A numerical analysis of a lightweight ribbed ergonomic artifact is presented to illustrate the VCDT.Moreover,manufacturability was verified based on a thermal-solid coupled finite element analysis.The physical experiment and practice proved that the proposed VCDT provided a robust design paradigm for a layered RP between the steady balance of electrothermal regulation and manufacturing efficacy under hybrid uncertainties.

A spatiotemporal intelligent framework and experimental platform for urban digital twins

Backgrounds This work emphasizes the current research status of the urban Digital Twins to establish an intelligent spatiotemporal framework.A Geospatial Artificial Intelligent(GeoAI)system is developed based on the Geographic Information System and Artificial Intelligence.It integrates multi-video technology and Virtual City in urban Digital Twins.Methods Besides,an improved small object detection model is proposed:YOLOv5-Pyramid,and Siamese network video tracking models,namely MPSiam and FSSiamese,are established.Finally,an experimental platform is built to verify the georeferencing correction scheme of video images.Result The MultiplyAccumulate value of MPSiam is 0.5B,and that of ResNet50-Siam is 4.5B.Besides,the model is compressed by 4.8times.The inference speed has increased by 3.3 times,reaching 83 Frames Per Second.3%of the Average Expectation Overlap is lost.Therefore,the urban Digital Twins-oriented GeoAI framework established here has excellent performance for video georeferencing and target detection problems.

Embryo-to-lamella transition of grain boundary twins in magnesium

A combined experimental and computational analysis is performed to investigate the less commonly studied embryo-to-lamella transition of deformation twins in magnesium. This work aims to understand the structural variables controlling the embryo-to-lamella transition from grain boundaries. Statistical analysis of hundreds of early-stage twins in the lightly deformed microstructure reveals a prevailing wedge shape,with a much thicker base along the grain boundary(GB) where they originate and a thinner tip terminating in the crystal. The analysis also shows that the GB base is super thick and identifies a minimum GB twin thickness among all early-stage twins that is about one micron. A crystal plasticity-based full-field model is employed to calculate the driving forces to migrate the boundary of a three-dimensional GB twin embryo. The stress analysis, considering a full range of embryo shapes and neighboring grain orientations, indicate that the twin embryo is most likely going to form a wedge shape when it first propagates. The calculations predict that the thickness of the embryo at the GB needs to be significantly larger than its length into the crystal in order to propagate into the crystal. The analysis finds that the more aligned the twin embryo variant is with basal slip in the neighboring grain, the thinner the twin embryo needed for propagation.

Distributed Edge Cooperation and Data Collection for Digital Twins of Wide-Areas

Digital twins for wide-areas(DT-WA)can model and predict the physical world with high fidelity by incorporating an artificial intelligence(AI)model.However,the AI model requires an energy-consuming updating process to keep pace with the dynamic environment,where studies are still in infancy.To reduce the updating energy,this paper proposes a distributed edge cooperation and data collection scheme.The AI model is partitioned into multiple sub-models deployed on different edge servers(ESs)co-located with access points across wide-area,to update distributively using local sensor data.To reduce the updating energy,ESs can choose to become either updating helpers or recipients of their neighboring ESs,based on sensor quantities and basic updating convergencies.Helpers would share their updated sub-model parameters with neighboring recipients,so as to reduce the latter updating workload.To minimize system energy under updating convergency and latency constraints,we further propose an algorithm to let ESs distributively optimize their cooperation identities,collect sensor data,and allocate wireless and computing resources.It comprises several constraint-release approaches,where two child optimization problems are solved,and designs a largescale multi-agent deep reinforcement learning algorithm.Simulation shows that the proposed scheme can efficiently reduce updating energy compared with the baselines.

Integration of Digital Twins and Artificial Intelligence for Classifying Cardiac Ischemia

Despite advances in intelligent medical care,difficulties remain.Due to its complicated governance,designing,planning,improving,and managing the cardiac system remains difficult.Oversight,including intelligent monitoring,feedback systems,and management practises,is unsuccessful.Current platforms cannot deliver lifelong personal health management services.Insufficient accuracy in patient crisis warning programmes.No frequent,direct interaction between healthcare workers and patients is visible.Physical medical systems and intelligent information systems are not integrated.This study introduces the Advanced Cardiac Twin(ACT)model integrated with Artificial Neural Network(ANN)to handle real-time monitoring,decision-making,and crisis prediction.THINGSPEAK is used to create an IoT platform that accepts patient sensor data.Importing these data sets into MATLAB allows display and analysis.A myocardial ischemia research examined Health Condition Tracking’s(HCT’s)potential.In the case study,75%of the training sets(Xt),15%of the verified data,and 10%of the test data were used.Training set feature values(Xt)were given with the data.Training,Validation,and Testing accuracy rates were 99.9%,99.9%,and 99.9%,respectively.General research accuracy was 99.9%.The proposed HCT system and Artificial Neural Network(ANN)model gather historical and real-time data to manage and anticipate cardiac issues.

A generic framework for qualifications of digital twins in maintenance

Digital twins have emerged as a promising technology for maintenance applications,enabling organizations to simulate and monitor physical assets to improve their performance.In Operation and Maintenance(O&M),digital twin facilitates the diagnosis and prognosis of critical assets,forming the basis for smart maintenance planning and reducing downtime.However,there is a lack of standardized approaches for the qualifications of digital twins in maintenance,leading to low trustworthiness and limiting its application.This paper proposes a novel framework for the qualifications of digital twins in maintenance based on five pillars,namely fidelity,smartness,timeliness,integration,and standard compliance.We demonstrate the effectiveness of the framework through two case studies,showing how it can be implemented on digital twins for preventive maintenance and condition-based maintenance.Our proposed framework can help organizations across different industrial domains develop and implement digital twins in maintenance more effectively and efficiently,leading to significant benefits in terms of cost reduction,performance improvement,and sustainability.

m^(6)AmTwins:基于深度学习和Twins网络的m^(6)A_(m)位点预测

N6,2′-O-二甲基腺苷(m^(6)Am)是一种常见的RNA分子的可逆修饰。部分研究已经说明m^(6)Am对mRNA的影响,但现阶段对m^(6)Am的生物学功能探索仍不够。所以我们提出了m^(6)AmTwins,一种新的端到端双胞胎网络,将Transformer(自动编码器)和双向门控循环单元(Bi-GRU)有机结合,简单利用RNA序列得到RNA的检测性。相比于现有的算法,本文亮点在于利用对比学习,构建新的损失函数来训练m^(6)AmTwins模型,提高了模型的泛化能力。基于Twins网络和简单编码方案,在两组正负比为1∶10的非平衡数据集下,其独立测试集上均取得了较好的结果,马修斯相关系数(MCC)分别得到0.53和0.545。同时,为增强m^(6)AmTwins模型的鲁棒性(robustness),本文在训练集上还进行了10折交叉验证,其MCC结果分别为0.562和0.567,说明该模型具有良好的泛化能力,可为生物医学在m^(6)Am上的研究提供一定的价值。