Individual consistency in spatiotemporal characteristics of migratory Whimbrels in the East Asian-Australasian Flyway

Many migratory birds exhibit interannual consistency in migration schedules,routes and stopover sites.Detecting the interannual consistency in spatiotemporal characteristics helps understand the maintenance of migration and enables the implementation of targeted conservation measures.We tracked the migration of Whimbrel(Numenius phaeopus)in the East Asian-Australasian Flyway and collected spatiotemporal data from individuals that were tracked for at least two years.Wilcoxon non-parametric tests were used to compare the interannual variations in the dates of departure from and arrival at breeding/nonbreeding sites,and the inter-annual variation in the longitudes when the same individual across the same latitudes.Whimbrels exhibited a high degree of consistency in the use of breeding,nonbreeding,and stopover sites between years.The variation of arrival dates at nonbreeding sites was significantly larger than that of the departure dates from nonbreeding and breeding sites.Repeatedly used stopover sites by the same individuals in multiple years were concentrated in the Yellow Sea coast during northward migration,but were more widespread during southward migration.The stopover duration at repeatedly used sites was significantly longer than that at sites used only once.When flying across the Yellow Sea,Whimbrels breeding in Sakha(Yakutia)exhibited the highest consistency in migration routes in both autumn and spring.Moreover,the consistency in migration routes of Yakutia breeding birds was generally higher than that of birds breeding in Chukotka.Our results suggest that the northward migration schedule of the Whimbrels is mainly controlled by endogenous factors,while the southward migration schedule is less affected by endogenous factors.The repeated use of stopover sites in the Yellow Sea coast suggests this region is important for the migration of Whimbrel,and thus has high conservation value.

Differentiating consistency of meningioma based on grey-level histogram analysis of T2WI

Objective To observe the value of grey-level histogram analysis based on T2WI for differentiating consistency of meningioma.Methods Data of 109 patients with meningioma were retrospectively analyzed.The patients were divided into hard group(n=71)and soft group(n=38)according to the consistency of tumors.Tumor ROI was outlined on axial T2WI showing the largest tumor section,gray levels were extracted and histogram analysis was performed.The value of each histogram parameter were compared between groups.Then receiver operating characteristic curve was drawn,and the area under the curve(AUC)was calculated to evaluate the efficiency for differentiating soft and hard meningioma.Results P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI in soft group were all higher than those in hard group(all P<0.05),while the variance,the kurtosis and the skewness were not significantly different between groups(all P>0.05).The differentiating efficiency of P 1,P 10,P 50,P 90,P 99 and the mean grey levels on T2WI were all fine,with AUC of 0.774 to 0.833,and no significant difference was found(all P>0.05).Conclusion Parameters of grey-level histogram analysis such as P 1,P 10,P 50,P 90,P 99 and the mean values based on T2WI were all valuable for differentiating soft and hard meningioma.

Cross-Modal Consistency with Aesthetic Similarity for Multimodal False Information Detection

With the explosive growth of false information on social media platforms, the automatic detection of multimodalfalse information has received increasing attention. Recent research has significantly contributed to multimodalinformation exchange and fusion, with many methods attempting to integrate unimodal features to generatemultimodal news representations. However, they still need to fully explore the hierarchical and complex semanticcorrelations between different modal contents, severely limiting their performance detecting multimodal falseinformation. This work proposes a two-stage detection framework for multimodal false information detection,called ASMFD, which is based on image aesthetic similarity to segment and explores the consistency andinconsistency features of images and texts. Specifically, we first use the Contrastive Language-Image Pre-training(CLIP) model to learn the relationship between text and images through label awareness and train an imageaesthetic attribute scorer using an aesthetic attribute dataset. Then, we calculate the aesthetic similarity betweenthe image and related images and use this similarity as a threshold to divide the multimodal correlation matrixinto consistency and inconsistencymatrices. Finally, the fusionmodule is designed to identify essential features fordetectingmultimodal false information. In extensive experiments on four datasets, the performance of the ASMFDis superior to state-of-the-art baseline methods.

Decoding the inconsistency of six cropland maps in China

Accurate cropland information is critical for agricultural planning and production,especially in foodstressed countries like China.Although widely used medium-to-high-resolution satellite-based cropland maps have been developed from various remotely sensed data sources over the past few decades,considerable discrepancies exist among these products both in total area and in spatial distribution of croplands,impeding further applications of these datasets.The factors influencing their inconsistency are also unknown.In this study,we evaluated the consistency and accuracy of six cropland maps widely used in China in circa 2020,including three state-of-the-art 10-m products(i.e.,Google Dynamic World,ESRI Land Cover,and ESA WorldCover)and three 30-m ones(i.e.,GLC_FCS30,GlobeLand 30,and CLCD).We also investigated the effects of landscape fragmentation,climate,and agricultural management.Validation using a ground-truth sample revealed that the 10-m-resolution WorldCover provided the highest accuracy(92.3%).These maps collectively overestimated Chinese cropland area by up to 56%.Up to 37%of the land showed spatial inconsistency among the maps,concentrated mainly in mountainous regions and attributed to the varying accuracy of cropland maps,cropland fragmentation and management practices such as irrigation.Our work shed light on the promotion of future cropland mapping efforts,especially in highly inconsistent regions.

Identifying Brand Consistency by Product Differentiation Using CNN

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance variation.In Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and functions.Results show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various brands.The investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late Stage.Results show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real world.The relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style roadmaps.In addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred boundary.The study provides insights into practical problems for designers,manufacturers,and marketers in product design.It not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand consistency.Designers can use these techniques to find features that influence brand style.Then,capture these features as innovative design elements and maintain core brand values.

A Data Consistency Insurance Method for Smart Contract

As one of the major threats to the current DeFi(Decentralized Finance)ecosystem,reentrant attack induces data inconsistency of the victim smart contract,enabling attackers to steal on-chain assets from DeFi projects,which could terribly do harm to the confidence of the blockchain investors.However,protecting DeFi projects from the reentrant attack is very difficult,since generating a call loop within the highly automatic DeFi ecosystem could be very practicable.Existing researchers mainly focus on the detection of the reentrant vulnerabilities in the code testing,and no method could promise the non-existent of reentrant vulnerabilities.In this paper,we introduce the database lock mechanism to isolate the correlated smart contract states from other operations in the same contract,so that we can prevent the attackers from abusing the inconsistent smart contract state.Compared to the existing resolutions of front-running,code audit,andmodifier,our method guarantees protection resultswith better flexibility.And we further evaluate our method on a number of de facto reentrant attacks observed from Etherscan.The results prove that our method could efficiently prevent the reentrant attack with less running cost.

Asymptotic Consistency of the James-Stein Shrinkage Estimator

The study explores the asymptotic consistency of the James-Stein shrinkage estimator obtained by shrinking a maximum likelihood estimator. We use Hansen’s approach to show that the James-Stein shrinkage estimator converges asymptotically to some multivariate normal distribution with shrinkage effect values. We establish that the rate of convergence is of order and rate , hence the James-Stein shrinkage estimator is -consistent. Then visualise its consistency by studying the asymptotic behaviour using simulating plots in R for the mean squared error of the maximum likelihood estimator and the shrinkage estimator. The latter graphically shows lower mean squared error as compared to that of the maximum likelihood estimator.

Adaptive Graph Embedding With Consistency and Specificity for Domain Adaptation

Domain adaptation(DA) aims to find a subspace,where the discrepancies between the source and target domains are reduced. Based on this subspace, the classifier trained by the labeled source samples can classify unlabeled target samples well.Existing approaches leverage Graph Embedding Learning to explore such a subspace. Unfortunately, due to 1) the interaction of the consistency and specificity between samples, and 2) the joint impact of the degenerated features and incorrect labels in the samples, the existing approaches might assign unsuitable similarity, which restricts their performance. In this paper, we propose an approach called adaptive graph embedding with consistency and specificity(AGE-CS) to cope with these issues. AGE-CS consists of two methods, i.e., graph embedding with consistency and specificity(GECS), and adaptive graph embedding(AGE).GECS jointly learns the similarity of samples under the geometric distance and semantic similarity metrics, while AGE adaptively adjusts the relative importance between the geometric distance and semantic similarity during the iterations. By AGE-CS,the neighborhood samples with the same label are rewarded,while the neighborhood samples with different labels are punished. As a result, compact structures are preserved, and advanced performance is achieved. Extensive experiments on five benchmark datasets demonstrate that the proposed method performs better than other Graph Embedding methods.

轨道交通“网-源-储-车”协同供能技术体系

为降低轨道交通系统牵引能耗,轨道交通“网-源-储-车”协同供能技术通过可再生能源的就地消纳,构建新型协同供能技术体系,实现跨时空高效用能.针对此新型供电系统结构,本文全面分析协同供能系统的物理架构、信息架构和社会架构的基本组成及类型特征;在此基础上,围绕资产能源化的基本概念,总结“荷-源”时空匹配评估方法与优化技术,并从系统角度阐述多源融合技术、保护重构、弹性评估等重要技术体系;重点分析“网-源-储-车”协同的高效能与高弹性的能源自洽技术,并基于人工智能和信息技术构建多层级能量管控系统,实现不同能量流的高效耦合,保障系统安全稳定经济运行.本文系统性地总结了轨道交通“网-源-储-车”协同供能系统的架构特征、评估优化、安全运维及协同运行等关键技术,阐述协同供能系统的技术组成体系,为协同供能系统的工程实践提供相应参考.

考虑优化调度的微电网频率恢复分布式预测控制策略

为了解决快速频率恢复和缓慢实际功率调度之间的时间尺度分离问题,提出一种考虑优化调度的微电网频率恢复分布式预测控制策略。引入的一致性策略能够在同一时间尺度上处理优化调度和频率恢复,另外提出的实际功率调度方案分布式模型预测控制解决了通信延迟、通信中断和即插即用情景,并且将下垂、实际功率传输和相位角方程作为等式约束,从而预测每个微电网的行为。此外,终端值和不等式约束有助于确定可行解空间的界,从而减少优化时间。在4种测试情景下对控制器的动态性能进行实验评估,结果证明该控制器对负载变化和通信问题具有较强的鲁棒性,并且保证了频率快速回复与高效功率调度。

On the Principle of Consistency of Rights and Obligations in the Constitution of PRC

“The Fundamental Rights and obligations of Citizens”, the title of Chapter II of the current Constitution of PRC, and the stipulation that citizens must fulfill certain obligations while enjoying rights have triggered many debates. Considering the historical origin, constitutional philosophy, and the text and structure of the Constitution, the special provisions of the current Constitution are influenced by the principle of consistency of rights and obligations. The principle of consistency of rights and obligations in the Constitution is of complex connotation. Therefore, although the principle of consistency of rights and obligations effectively connects the public and private spheres, it ignores the diversity and differences of the interests and elements contained in the Constitution, the asymmetry of the normative status of fundamental rights and fundamental obligations,and the right of citizens to self-determination of personal interests.The principle of consistency of rights and obligations should be purposefully narrowed and concretized: In the context of public-private integration and risk society prevention, the principle of consistency of rights and obligations can be used as a supplement to the functional system of the Constitution;in the field of fundamental political obligations, the principle of consistency of rights and obligations should be in line with the requirements of the state to respect and protect human rights;in the field of fundamental social obligations, the exercise of fundamental rights by individuals is protected by the Constitution as long as they comply with the law and do not infringe upon the interests of the social community. The principle of the consistency of rights and obligations is only used as the negative constituents of the determination of rights and the basis for the effect against a third party of fundamental rights.

基于旋转黏度的SBS改性沥青黏温特性及流体行为分析

采用3种基质沥青制备相应的SBS改性沥青,测试了不同温度和剪切速率下的黏度。根据Andrada方程计算了6种沥青的黏流活化能(E_(a));根据幂律方程,分别计算了6种沥青的非牛顿指数(ζ)和稠度系数(μ),分析了改性沥青的流体特性以及黏度对剪切速率的依赖性。结果表明,Andrada方程能够较好地描述沥青及改性沥青的黏温关系,E_(a)能够反映黏度对温度的敏感性,SBS改性可以显著提升沥青的黏度,但不同改性沥青的温度敏感性存在差异。SBS改性沥青的ζ值均小于1,沥青由牛顿流体向非牛顿流体转化,不同类型沥青之间非牛顿性的相对强弱随温度的变化呈现出复杂性,稠度系数(μ)随温度的升高而减小。

基于改进模拟退火遗传算法的高速公路服务区自洽能源系统高能效优化

针对高速公路自洽能源系统高能效优化的问题,基于改进模拟退火遗传算法(SA-GA),提出了一种综合考虑经济目标和环保目标的自洽能源系统高能效优化运行策略。首先根据高速公路服务区自洽能源系统中各电力单元特性,建立一种综合考虑系统经济性和环保性的能效目标函数;其次根据高速公路服务区自洽能源系统的分类,建立了不同类型系统对应的约束条件;为避免遗传算法易陷入局部最优的缺陷,引入模拟退火算法,对改进后的SA-GA算法采用降温函数,寻找全局最优解;利用新疆某高速公路服务区自洽能源系统发电和负荷数据,并在传统服务区负荷的基础上进一步考虑新能源汽车充电站的影响。测试函数测试结果表明:SA-GA算法在求解速度和稳定性方面有明显提升,改进SA-GA算法对夏季、冬季典型日能效优化的结果,相较于遗传算法,在寻优精度提升约为20.33%。

造纸高浓度磨浆机浓度控制系统设计

造纸工业中的高浓度磨浆机是一个关键的工艺设备,其性能和控制直接影响到纸张的最终质量和生产效率。基于此,从高浓度磨浆机的结构和工作原理入手分析,关注浓度控制系统的设计和关键组成部分,研究数据采集、处理和分析的方法,此外探讨多目标优化控制模型以及力学能耗模型,以确保磨浆机在不同工况下能够实现最佳性能,进而实现可持续和高效的造纸生产过程。

企业诚信建设与注册会计师审计意见

在全社会强调传承诚信文化的背景下,已有文献研究了诚信建设带给企业的诸多后果,却鲜有研究从审计市场角度分析企业诚信的影响。本文基于诚信的三个基础因素“言”“行”和“言行不一致”,利用年报文本和监管处罚数据构建了企业诚信指标,分析了企业诚信对审计意见的影响与机制。研究发现,企业诚信降低了注册会计师出具非标意见的可能性,该现象在非国有企业中更加突出。企业诚信通过减少财务报告错报、抑制盈余操纵和加强内部控制的方式,最终影响了其对审计意见的判断。进一步地,当客户的应收账款和存货占比越高、客户越重要时,企业诚信更能减少非标审计意见出具。本研究有助于促进企业从审计市场角度理解诚信建设的重要性。

基于改进势场和一致性的无人机编队避障方法

针对无人机编队在执行任务时存在的机间碰撞、与障碍物碰撞及编队通信等问题,将无人机动力学方程视为二阶积分模型,提出一种人工势场法和一致性理论相结合的协同避障控制策略。首先建立变增益函数来降低超调和稳态误差,并由此设计虚拟领航结构下的无人机编队一致性控制方法;然后应用分段思想,增加回环力、机间防碰撞力等来改进传统人工势场法,以解决局部最优和编队安全问题,从而实现编队避碰和避障;最后将一致性控制方法和改进后的人工势场法相结合,提出编队协同避障控制律,并利用小增益定理对其进行稳定收敛性分析。仿真结果表明,无人机编队可以实现精准避障后恢复预期编队队形,最终稳定到达目标位置。

考虑光储协调的配电网多阶段就地-分布式电压控制策略

针对高渗透率光伏并网点附近线路的电压越限问题,基于对含分布式电源配电网的功率调压原理的分析,提出了考虑光储协调的多阶段电压控制方法。采用切比雪夫多项式滤波方法改进基于一致性原理迭代的分布式控制方式,有效加快了分布式控制的收敛速度;提出了多阶段就地-分布式电压控制策略,包括光伏逆变器就地无功补偿的阶段Ⅰ调压、全网光伏逆变器分布式无功调节的阶段Ⅱ调压、全网储能一致性分布式有功调节的阶段Ⅲ调压。以改进的某实际55节点中压配电系统为算例进行仿真,验证了所提多阶段就地-分布式电压控制策略的有效性和优越性。

基于点分配法、全一致性法、灰色关联分析的科技人才分类评价研究

科技人才评价是一种多准则决策问题,不同方法导致评估存在不确定性,已有相关评价方法在实践中存在一定的局限性。为解决这一问题,针对创新活动不同阶段对科技人才评价的差异化要求,立足于“破四唯”和“立新标”并举的思路,将科技人才分为基础研究类、应用研究和技术开发类以及科技管理服务类,基于政策文件和文献的关键词提取法构建科技人才分类评价指标体系,通过充分考虑不同方法导致评估存在的不确定性,结合点分配法(PA)和全一致性法(FUCOM)构建灰数组合权重,将灰数权重和不同决策者针对评价对象的评估分数作为灰数输入,提出PA-FUCOM灰色关联分析法;并以陕西省某研究院的4位应用研究和技术开发类人才为例进行实证分析,以验证评价结果的有效和准确性。结果表明:基于PA-FUCOM灰色关联分析法的科技人才评价指标体系,对基础研究人才整体上各类指标相对较为均衡但侧重人才价值和学科背景,对应用研究和技术开发类人才在成果价值和转化效益上拥有更大的权重,对科技管理服务类人才整体指标相对均衡但在成果价值上的权重相对更大;灰色系统理论有助于解决科技人才评价过程存在的不确定性,点分配法在实际评估中简单可行,FUCOM由于计算量小、一致性更高从而为混合指标权重计算提供了新的可能,因此PA-FUCOM组合权重计算方法在评价结果区分度、评价结果的一致性上都有较好的表现.

MMCSC:一种跨模态的假新闻检测方法

目前基于新闻内容的假新闻检测方法没有考虑到不同模态更高层的语义关联,缺少可以依据的信息对新闻进行判断,从而缺乏对有重要辨别特征的新闻的社交网络信息进行有效使用.针对这个问题,提出了基于新闻内容的假新闻检测方法,通过提取文本、图像和视频等多模态新闻的高层语义特征,分析不同模态高层语义信息,设计跨模态主题一致性和跨模态情感一致性计算方法.在此基础上,设计了一种跨模态内容语义一致性的假新闻检测模型MMCSC(multi-modal feature content semantic consistency).实验证明,相比于传统方法,所提出的MMCSC有较好的检测效果.

基于一致性图的权重自适应多视角谱聚类算法

随着移动设备和互联网的普及,多视角数据的采集和分享变得更加容易,其可以从多个视角更准确地描述数据。目前,一些多视角聚类算法忽略了不同视角间的一致性潜在知识和不同视角的重要性。针对该问题,提出一种平衡视角间一致性信息的多视角聚类算法。首先通过调节视角权重学习视角间一致的共享相似度矩阵,提升共享矩阵的一致性,其中相关性强的视角具有的一致性信息更多,视角权重越大,在一致性学习中发挥的作用越大,而差异性大的视角其权重越小,在学习中发挥的作用越小。其次学习视角间的一致性样本嵌入以及不同视角的特征嵌入,并将特征嵌入中包含的多样性特征信息迁移到样本嵌入中,以此促进样本嵌入的一致性表达。在不同视角特征中包含多样性信息,可补充上述共享相似度矩阵学习中单一样本关系的不足。因此,采用二部图协同聚类,通过建立样本数据、样本嵌入和特征嵌入的关系图,学习样本的特征嵌入,并将其迁移到样本嵌入中。最后将图学习、谱聚类和特征嵌入学习整合到统一的框架中进行联合优化,得到最优的样本嵌入。实验结果表明,通过对样本嵌入进行K-means聚类,将该算法运行于5个真实数据集并与7种聚类算法对比,其中在3-Sources、Yale、MRSCV1数据集上的正确率均高于对比算法5%以上,验证了该算法的有效性。