国际海事组织LCA导则的应用与发展

LCA导则是船用燃料全生命周期温室气体强度评价的根本依据,燃料温室气体强度评价结果将直接影响船用燃料在船舶上的推广使用,国际海事组织、欧盟等也会基于评价结果阶段性降低燃料的温室气体强度,将评价结果应用于船舶能效法规的指标计算也会产生较大影响。介绍LCA导则的主要内容,分析LCA导则的应用及发展方向,供行业内相关方参考。

考虑广义储能和LCA碳排放的综合能源系统低碳优化运行策略

综合能源系统(IES)是当前能源转型低碳发展背景下实现“双碳”目标的关键,为了提高IES碳减排能力,需要充分利用需求侧负荷资源和传统储能设备等广义储能资源参与IES优化.首先,建立一种综合考虑可再生能源、能源转换设备、广义储能设备、能源市场交易的IES优化运行模型.然后,使用生命周期评估法(LCA)对IES中能源循环、设备循环的全过程进行碳排放量计算,并将碳排放成本纳入系统总成本.最后,利用仿真实验验证所提模型不仅有利于降低IES总调度成本,还能降低系统的碳排放量,有效促进IES的低碳发展.

基于EIO-LCA模型的江西省产业部门的隐含碳排放及碳减排潜力分析

低碳经济发展是实现可持续发展的重要途径之一。采用经济投入产出生命周期评估模型(EIO-LCA),运用42部门投入产出表及国际认可的IPCC法测算出江西省各产业部门直接碳排放量以及隐含碳排放量,并在此基础上构建碳减排潜力模型,来揭示因产业部门结构变动而引起的碳减排效应。研究结果表明:按产业部门分析,基础性工业部门的直接碳排放量都相对较高,其中位列前三的部门分别为电力、热力的生产和供应业、石油、炼焦产品和核燃料加工业与金属冶炼和压延加工品业;按整体产业结构分析,江西省直接碳排放量、隐含碳排放量和碳减排潜力较大的部门集中在重工业和能源产业。未来,江西省应当针对不同产业部门的特点实施差异化减排政策,同时优化产业结构,实现产业良性互动。

Lagrangian coherent structure analysis on transport of Acetes chinensis along coast of Lianyungang,China

Spatial heterogeneity or“patchiness”of plankton distributions in the ocean has always been an attractive and challenging scientific issue to oceanographers.We focused on the accumulation and dynamic mechanism of the Acetes chinensis in the Lianyungang nearshore licensed fishing area.The Lagrangian frame approaches including the Lagrangian coherent structures theory,Lagrangian residual current,and Lagrangian particle-tracking model were applied to find the transport pathways and aggregation characteristics of Acetes chinensis.There exist some material transport pathways for Acetes chinensis passing through the licensed fishing area,and Acetes chinensis is easy to accumulate in the licensed fishing area.The main mechanism forming this distribution pattern is the local circulation induced by the nonlinear interaction of topography and tidal flow.Both the Lagrangian coherent structure analysis and the particle trajectory tracking indicate that Acetes chinensis in the licensed fishing area come from the nearshore estuary.This work contributed to the adjustment of licensed fishing area and the efficient utilization of fishery resources.

Model reduction of fractional impedance spectra for time–frequency analysis of batteries, fuel cells, and supercapacitors

Joint time–frequency analysis is an emerging method for interpreting the underlying physics in fuel cells,batteries,and supercapacitors.To increase the reliability of time–frequency analysis,a theoretical correlation between frequency-domain stationary analysis and time-domain transient analysis is urgently required.The present work formularizes a thorough model reduction of fractional impedance spectra for electrochemical energy devices involving not only the model reduction from fractional-order models to integer-order models and from high-to low-order RC circuits but also insight into the evolution of the characteristic time constants during the whole reduction process.The following work has been carried out:(i)the model-reduction theory is addressed for typical Warburg elements and RC circuits based on the continued fraction expansion theory and the response error minimization technique,respectively;(ii)the order effect on the model reduction of typical Warburg elements is quantitatively evaluated by time–frequency analysis;(iii)the results of time–frequency analysis are confirmed to be useful to determine the reduction order in terms of the kinetic information needed to be captured;and(iv)the results of time–frequency analysis are validated for the model reduction of fractional impedance spectra for lithium-ion batteries,supercapacitors,and solid oxide fuel cells.In turn,the numerical validation has demonstrated the powerful function of the joint time–frequency analysis.The thorough model reduction of fractional impedance spectra addressed in the present work not only clarifies the relationship between time-domain transient analysis and frequency-domain stationary analysis but also enhances the reliability of the joint time–frequency analysis for electrochemical energy devices.

基于BIM的路面LCCA与LCA方法研究综述

目前,生命周期成本分析(Life Cycle Cost Analysis,LCCA)和生命周期环境评价(Life Cycle Assessment,LCA)方法常用于评估路面在全生命周期范围内的经济和环境影响。然而,路面LCCA和LCA方法在应用过程中存在数据量大、数据类别多造成评价过程烦琐的问题。针对此类问题,部分学者尝试将BIM(Building Information Modeling)与LCCA和LCA方法相结合以优化评价流程。在路面领域,LCCA和LCA与BIM相结合的研究还处于初级阶段,缺少对其相关研究成果的总结。因此,该文通过对路面LCCA、LCA、LCCA-LCA及与BIM相结合的研究进行归纳总结,探究其存在的问题与面临的挑战。研究发现:BIM的应用能够优化LCCA和LCA过程,实现设计与评价的动态协同。但目前存在集成化程度不高、建模软件与评价软件之间统一数据格式标准的欠缺等问题,因此阻碍了其应用发展。

Mantle sources of Cenozoic volcanoes around the South China Sea revealed by geochemical and isotopic data using the principal component analysis

Principal component analysis(PCA)was employed to determine the implications of geochemical and isotopic data from Cenozoic volcanic activities in the Southeast Asian region,including China(South China Sea(SCS),Hainan Island,Fujian-Zhejiang coast,Taiwan Island),and parts of Vietnam and Thailand.We analyzed 15 trace element indicators and 5 isotopic indicators for 623 volcanic rock samples collected from the study region.Two principal components(PCs)were extracted by PCA based on the trace elements and Sr-Nd-Pb isotopic ratios,which probably indicate an enriched oceanic island basalt-type mantle plume and a depleted mid-ocean ridge basalt-type spreading ridge.The results show that the influence of the Hainan mantle plume on younger volcanic activities(<13 Ma)is stronger than that on older ones(>13 Ma)at the same location in the Southeast Asian region.PCA was employed to verify the mantle-plume-ridge interaction model of volcanic activities beneath the expansion center of SCS and refute the hypothesis that the tension of SCS is triggered by the Hainan plume.This study reveals the efficiency and applicability of PCA in discussing mantle sources of volcanic activities;thus,PCA is a suitable research method for analyzing geochemical data.

零碳目标下临时木结构建筑降碳策略与LCA碳排放研究——以2024世园会企业展园为例

以2024年世园会成都设计咨询集团企业展馆为例,探讨了基于零碳目标下小型临时木结构建筑如何采取源头减碳、过程降碳、末端消碳等三方面的低碳优化策略,并基于LCA全生命周期评估方法对其进行碳排放核算研究,得出针对小型临时建筑,建材生产与加工环节对建筑全生命周期碳排放影响最大,占比约为50.30%~69.49%,其次是运行阶段,占比约为19.33%~30.91%。通过对比分析目标建筑与同体量的轻钢结构建筑,目标建筑在采取不同的措施下可实现减碳率约36.00%~68.41%,建筑全生命周期(5年)单位面积的碳排放量可降低至382 kgCO_(2)eq/m^(2)。研究得出临时建筑各阶段融入降碳策略的重要性和运用LCA方法评估建筑碳排放的必要性,除运行阶段外,临时建筑需更加关注低碳材料的替代与拆除阶段材料的回收利用,为未来实现零碳建筑目标提供了新的思路和实践参考。

基于LCA的公路路面建设碳排放量测算探究

针对公路路面建设碳排放量问题,基于LCA理论,明确公路路面生命周期评价范围,并以西藏拉萨境内某旅游环线公路路面建设为案例,分析、核算路面建设生命周期内碳排放量占比、各建设阶段碳排放量影响因子占比,认为建设过程中减少运距、改善材料生产工艺可以达到降碳减排的目的.

基于LCA的轮轨与磁悬浮方案比选研究

本文基于LCA对京沪高铁的轮轨与磁悬浮方案进行比选研究,在材料、设备、运输与施工阶段对轮轨与磁悬浮的能源消耗进行计算分析,最后对两者进行综合比选评价。从能源消耗的全生命周期评价角度为铁路在轮轨与磁悬浮两个方案的比选评价提供科学可靠的参考思路。

Application of Isogeometric Analysis Method in Three-Dimensional Gear Contact Analysis

Gears are pivotal in mechanical drives,and gear contact analysis is a typically difficult problem to solve.Emerging isogeometric analysis(IGA)methods have developed new ideas to solve this problem.In this paper,a threedimensional body parametric gear model of IGA is established,and a theoretical formula is derived to realize single-tooth contact analysis.Results were benchmarked against those obtained from commercial software utilizing the finite element analysis(FEA)method to validate the accuracy of our approach.Our findings indicate that the IGA-based contact algorithmsuccessfullymet theHertz contact test.When juxtaposed with the FEA approach,the IGAmethod demonstrated fewer node degrees of freedomand reduced computational units,all whilemaintaining comparable accuracy.Notably,the IGA method appeared to exhibit consistency in analysis accuracy irrespective of computational unit density,and also significantlymitigated non-physical oscillations in contact stress across the tooth width.This underscores the prowess of IGA in contact analysis.In conclusion,IGA emerges as a potent tool for addressing contact analysis challenges and holds significant promise for 3D gear modeling,simulation,and optimization of various mechanical components.

A Seismic Facies Analysis to Determine the Relative Age and History of the Al Idrissi Mud Volcano from Offshore Larache Located in the NW Moroccan Atlantic Margin

Formed on top of the Gulf of Cadiz, the Al Idrissi mud volcano is the shallowest and largest mud volcano in the El Arraiche mud volcano field of the northwestern Moroccan margin. The development and morphology of mud volcanoes from the El Arraiche mud volcanoes group have been studied at a large scale. However, the time interval related to their formation period still needs to be better understood. In this regard, we interpreted and analyzed the seismic facies from the 2D reflection data of the GEOMARGEN-1 campaign, which took place in 2011. The aim was to identify the seismic sequences and draw the Al Idrissi mud volcano system to determine the formation period of the Al Idriss mud volcano. And as a result, the Al Idrissi mud volcano system is made of both buried and superficial bicone and was identified along with the Upper Tortonian to Messinian-Upper Pliocene facies. As the initial mud volcano extrusive edifice, the buried bicone was formed in the Late-Messinian to Early-Pliocene period. However, the superficial bicone, as the final extrusive edifice, was included in the Late Pliocene. In this case, the timing interval between the buried and superficial bicone is equivalent to the Late-Messinian to Upper-Pliocene period. Therefore, the latter corresponds to the Al Idrissi mud volcano formation period.

Preliminary electromagnetic analysis of the COOL blanket for CFETR

The supercritical CO_(2)cOoled Lithium-Lead(COOL)blanket has been designed as one advanced blanket candidate for the Chinese Fusion Engineering Test Reactor(CFETR).This work focuses on the electromagnetic(EM)loads(Maxwell force and Lorentz force)acting on the COOL blanket,which are important mechanical loads in further structural analysis of the COOL blanket.A 3D electromagnetic analysis is performed using the ANSYS finite element method to obtain EM loads on the COOL blanket in this study.At first,the magnetic scalar potential(MSP)method is used to obtain the magnetic field and the Maxwell force on the COOL blanket.Then,the magnetic vector potential(MVP)method is performed during a plasma disruption event to get the eddy current distribution.At last,a multi-step method is adopted for the calculation of the Lorentz force and the torque.The maximum Lorentz forces of inboard and outboard blanket structural components are 5624 kN and 2360 kN respectively.

SFGA-CPA: A Novel Screening Correlation Power Analysis Framework Based on Genetic Algorithm

Correlation power analysis(CPA)combined with genetic algorithms(GA)now achieves greater attack efficiency and can recover all subkeys simultaneously.However,two issues in GA-based CPA still need to be addressed:key degeneration and slow evolution within populations.These challenges significantly hinder key recovery efforts.This paper proposes a screening correlation power analysis framework combined with a genetic algorithm,named SFGA-CPA,to address these issues.SFGA-CPA introduces three operations designed to exploit CPA characteris-tics:propagative operation,constrained crossover,and constrained mutation.Firstly,the propagative operation accelerates population evolution by maximizing the number of correct bytes in each individual.Secondly,the constrained crossover and mutation operations effectively address key degeneration by preventing the compromise of correct bytes.Finally,an intelligent search method is proposed to identify optimal parameters,further improving attack efficiency.Experiments were conducted on both simulated environments and real power traces collected from the SAKURA-G platform.In the case of simulation,SFGA-CPA reduces the number of traces by 27.3%and 60%compared to CPA based on multiple screening methods(MS-CPA)and CPA based on simple GA method(SGA-CPA)when the success rate reaches 90%.Moreover,real experimental results on the SAKURA-G platform demonstrate that our approach outperforms other methods.

Geometric prior guided hybrid deep neural network for facial beauty analysis

Facial beauty analysis is an important topic in human society.It may be used as a guidance for face beautification applications such as cosmetic surgery.Deep neural networks(DNNs)have recently been adopted for facial beauty analysis and have achieved remarkable performance.However,most existing DNN-based models regard facial beauty analysis as a normal classification task.They ignore important prior knowledge in traditional machine learning models which illustrate the significant contribution of the geometric features in facial beauty analysis.To be specific,landmarks of the whole face and facial organs are introduced to extract geometric features to make the decision.Inspired by this,we introduce a novel dual-branch network for facial beauty analysis:one branch takes the Swin Transformer as the backbone to model the full face and global patterns,and another branch focuses on the masked facial organs with the residual network to model the local patterns of certain facial parts.Additionally,the designed multi-scale feature fusion module can further facilitate our network to learn complementary semantic information between the two branches.In model optimisation,we propose a hybrid loss function,where especially geometric regulation is introduced by regressing the facial landmarks and it can force the extracted features to convey facial geometric features.Experiments performed on the SCUT-FBP5500 dataset and the SCUT-FBP dataset demonstrate that our model outperforms the state-of-the-art convolutional neural networks models,which proves the effectiveness of the proposed geometric regularisation and dual-branch structure with the hybrid network.To the best of our knowledge,this is the first study to introduce a Vision Transformer into the facial beauty analysis task.

Automatic area estimation of algal blooms in water bodies from UAV images using texture analysis

Algal blooms,the spread of algae on the surface of water bodies,have adverse effects not only on aquatic ecosystems but also on human life.The adverse effects of harmful algal blooms(HABs)necessitate a convenient solution for detection and monitoring.Unmanned aerial vehicles(UAVs)have recently emerged as a tool for algal bloom detection,efficiently providing on-demand images at high spatiotemporal resolutions.This study developed an image processing method for algal bloom area estimation from the aerial images(obtained from the internet)captured using UAVs.As a remote sensing method of HAB detection,analysis,and monitoring,a combination of histogram and texture analyses was used to efficiently estimate the area of HABs.Statistical features like entropy(using the Kullback-Leibler method)were emphasized with the aid of a gray-level co-occurrence matrix.The results showed that the orthogonal images demonstrated fewer errors,and the morphological filter best detected algal blooms in real time,with a precision of 80%.This study provided efficient image processing approaches using on-board UAVs for HAB monitoring.

Erratum to:Vibration analysis of a gear-rotor-bearing system with outer-ring spalling and misalignment

Because of an unfortunate mistake during the production of this article,Figure 13 was wrongly inserted.The corrected Figure 13 is shown as follows.

Advances in microfluidic-based DNA methylation analysis

DNA methylation has been extensively investigated in recent years,not least because of its known relationship with various diseases.Progress in analytical methods can greatly increase the relevance of DNA methylation studies to both clinical medicine and scientific research.Microflu-idic chips are excellent carriers for molecular analysis,and their use can provide improvements from multiple aspects.On-chip molecular analysis has received extensive attention owing to its advantages of portability,high throughput,low cost,and high efficiency.In recent years,the use of novel microfluidic chips for DNA methylation analysis has been widely reported and has shown obvious superiority to conventional methods.In this review,wefirst focus on DNA methylation and its applications.Then,we discuss advanced microfluidic-based methods for DNA methylation analysis and describe the great progress that has been made in recent years.Finally,we summarize the advantages that microfluidic technology brings to DNA methylation analysis and describe several challenges and perspectives for on-chip DNA methylation analysis.This review should help researchers improve their understanding and make progress in developing microfluidic-based methods for DNA methylation analysis.

Multi-omics analysis of human tendon adhesion reveals that ACKR1-regulated macrophage migration is involved in regeneration

Tendon adhesion is a common complication after tendon injury with the development of accumulated fibrotic tissues without effective anti-fibrotic therapies,resulting in severe disability.Macrophages are widely recognized as a fibrotic trigger during peritendinous adhesion formation.However,different clusters of macrophages have various functions and receive multiple regulation,which are both still unknown.In our current study,multi-omics analysis including single-cell RNA sequencing and proteomics was performed on both human and mouse tendon adhesion tissue at different stages after tendon injury.The transcriptomes of over 74000 human single cells were profiled.As results,we found that SPP1^(+)macrophages,RGCC^(+)endothelial cells,ACKR1^(+)endothelial cells and ADAM12^(+)fibroblasts participated in tendon adhesion formation.Interestingly,despite specific fibrotic clusters in tendon adhesion,FOLR2^(+)macrophages were identified as an antifibrotic cluster by in vitro experiments using human cells.Furthermore,ACKR1 was verified to regulate FOLR2^(+)macrophages migration at the injured peritendinous site by transplantation of bone marrow from Lysm-Cre;R26R^(tdTomato) mice to lethally irradiated Ackr1^(-/-)mice(Ackr1^(-/-)chimeras;deficient in ACKR1)and control mice(WT chimeras).Compared with WT chimeras,the decline of FOLR2^(+)macrophages was also observed,indicating that ACKR1 was specifically involved in FOLR2^(+)macrophages migration.Taken together,our study not only characterized the fibrosis microenvironment landscape of tendon adhesion by multi-omics analysis,but also uncovered a novel antifibrotic cluster of macrophages and their origin.These results provide potential therapeutic targets against human tendon adhesion.

Stability Analysis of Inverse Lax-Wendroff Procedure for a High order Compact Finite Difference Schemes

This paper considers the finite difference(FD)approximations of diffusion operators and the boundary treatments for different boundary conditions.The proposed schemes have the compact form and could achieve arbitrary even order of accuracy.The main idea is to make use of the lower order compact schemes recursively,so as to obtain the high order compact schemes formally.Moreover,the schemes can be implemented efficiently by solving a series of tridiagonal systems recursively or the fast Fourier transform(FFT).With mathematical induction,the eigenvalues of the proposed differencing operators are shown to be bounded away from zero,which indicates the positive definiteness of the operators.To obtain numerical boundary conditions for the high order schemes,the simplified inverse Lax-Wendroff(SILW)procedure is adopted and the stability analysis is performed by the Godunov-Ryabenkii method and the eigenvalue spectrum visualization method.Various numerical experiments are provided to demonstrate the effectiveness and robustness of our algorithms.