Design of Fully Automatic Specification Selection System for Resistance Welding Equipment

A system for fully automatic selection of welding specifications in resistance welding equipment has been developed to address the problem of workers frequently choosing the wrong specifications during manual welding of multiple parts on a single machine in automobile factories. The system incorporates an automatic recognition system for different workpiece materials using the added machine fixture,visual detection system for nuts and bolts,and secondary graphical confirmation to ensure the correctness of specification calling. This system achieves reliable,fully automatic selection of welding specifications in resistance welding equipment and has shown significant effects in improving welding quality for massproduced workpieces,while solving the problem of specification calling errors that can occur with traditional methods involving process charts and code adjustments. This system is particularly suitable for promoting applications in manual welding of multiple parts on a single machine in automobile factories,ensuring correct specification calling and welding quality.

Product Specification Analysis for Modular Product Design Using Big Sales Data

Big data on product sales are an emerging resource for supporting modular product design to meet diversified customers’requirements of product specification combinations.To better facilitate decision-making of modular product design,correlations among specifications and components originated from customers’conscious and subconscious preferences can be investigated by using big data on product sales.This study proposes a framework and the associated methods for supporting modular product design decisions based on correlation analysis of product specifications and components using big sales data.The correlations of the product specifications are determined by analyzing the collected product sales data.By building the relations between the product components and specifications,a matrix for measuring the correlation among product components is formed for component clustering.Six rules for supporting the decision making of modular product design are proposed based on the frequency analysis of the specification values per component cluster.A case study of electric vehicles illustrates the application of the proposed method.

Enhancing Relational Triple Extraction in Specific Domains:Semantic Enhancement and Synergy of Large Language Models and Small Pre-Trained Language Models

In the process of constructing domain-specific knowledge graphs,the task of relational triple extraction plays a critical role in transforming unstructured text into structured information.Existing relational triple extraction models facemultiple challenges when processing domain-specific data,including insufficient utilization of semantic interaction information between entities and relations,difficulties in handling challenging samples,and the scarcity of domain-specific datasets.To address these issues,our study introduces three innovative components:Relation semantic enhancement,data augmentation,and a voting strategy,all designed to significantly improve the model’s performance in tackling domain-specific relational triple extraction tasks.We first propose an innovative attention interaction module.This method significantly enhances the semantic interaction capabilities between entities and relations by integrating semantic information fromrelation labels.Second,we propose a voting strategy that effectively combines the strengths of large languagemodels(LLMs)and fine-tuned small pre-trained language models(SLMs)to reevaluate challenging samples,thereby improving the model’s adaptability in specific domains.Additionally,we explore the use of LLMs for data augmentation,aiming to generate domain-specific datasets to alleviate the scarcity of domain data.Experiments conducted on three domain-specific datasets demonstrate that our model outperforms existing comparative models in several aspects,with F1 scores exceeding the State of the Art models by 2%,1.6%,and 0.6%,respectively,validating the effectiveness and generalizability of our approach.

Comparative Analysis of Statistical Thickness Models for the Determination of the External Specific Surface and the Surface of the Micropores of Materials: The Case of a Clay Concrete Stabilized Using Sugar Cane Molasses

In this work, four empirical models of statistical thickness, namely the models of Harkins and Jura, Hasley, Carbon Black and Jaroniec, were compared in order to determine the textural properties (external surface and surface of micropores) of a clay concrete without molasses and clay concretes stabilized with 8%, 12% and 16% molasses. The results obtained show that Hasley’s model can be used to obtain the external surfaces. However, it does not allow the surface of the micropores to be obtained, and is not suitable for the case of simple clay concrete (without molasses) and for clay concretes stabilized with molasses. The Carbon Black, Jaroniec and Harkins and Jura models can be used for clay concrete and stabilized clay concrete. However, the Carbon Black model is the most relevant for clay concrete and the Harkins and Jura model is for molasses-stabilized clay concrete. These last two models augur well for future research.

Development of donor specific antibodies after SARS-CoV-2 vaccination:What do we know so far?

Vaccination against Coronavirus disease-19(COVID-19)was pivotal to limit spread,morbidity and mortality.Our aim is to find out whether vaccines against COVID-19 lead to an immunological response stimulating the production of de novo donor specific antibodies(DSAs)or increase in mean fluorescence intensity(MFI)of pre-existing DSAs in kidney transplant recipients(KTRs).This study involved a detailed literature search through December 2nd,2023 using PubMed as the primary database.The search strategy incorporated a combination of relevant Medical Subject Headings terms and keywords:"COVID-19","SARS-CoV-2 Vaccination","Kidney,Renal Transplant",and"Donor specific antibodies".The results from related studies were collated and analyzed.A total of 6 studies were identified,encompassing 460 KTRs vaccinated against COVID-19.Immunological responses were detected in 8 KTRs of which 5 had increased MFIs,1 had de novo DSA,and 2 were categorized as either having de novo DSA or increased MFI.There were 48 KTRs with pre-existing DSAs prior to vaccination,but one study(Massa et al)did not report whether pre-existing DSAs were associated with post vaccination outcomes.Of the remaining 5 studies,35 KTRs with pre-existing DSAs were identified of which 7 KTRs(20%)developed de novo DSAs or increased MFIs.Overall,no immunological response was detected in 452(98.3%)KTRs.Our study affirms prior reports that COVID-19 vaccination is safe for KTRs,especially if there are no pre-existing DSAs.However,if KTRs have pre-existing DSAs,then an increased immunological risk may be present.These findings need to be taken cautiously as they are based on a limited number of patients so further studies are still needed for confirmation.

Genetic regulation of cell type-specific chromatin accessibility shapes brain disease etiology

Nucleotide variants in cell type-specific gene regulatory elements in the human brain are risk factors for human disease.We measured chromatin accessibility in 1932 aliquots of sorted neurons and non-neurons from 616 human postmortem brains and identified 34,539 open chromatin regions with chromatin accessibility quantitative trait loci(caQTLs).Only 10.4%of caQTLs are shared between neurons and non-neurons,which supports cell type-specific genetic regulation of the brain regulome.Incorporating allele-specific chromatin accessibility improves statistical fine-mapping and refines molecular mechanisms that underlie disease risk.Using massively parallel reporter assays in induced excitatory neurons,we screened 19,893 brain QTLs and identified the functional impact of 476 regulatory variants.Combined,this comprehensive resource captures variation in the human brain regulome and provides insights into disease etiology.

渐近平均伪轨跟踪性质、弱specification性质和分布混沌

证明了有渐近平均伪轨跟踪性质的非平凡紧致动力系统具有一致分布混沌或者按序列分布混沌。此外,在具有渐近平均伪轨跟踪性质系统中的分布混沌在测度中心是一致和稠密的,即有一个不可数的一致分布混沌集是由这样的点组成,它们的轨道闭包包含测度中心。作为一个推论,具有弱specification性质的系统也有类似的结果。

关于弱Specification性质的一个注记

该文证明具有弱specification性质的系统在其测度中心的限制系统也具有弱specification性质,并且其逆不真.作为推论得到在未有满射的假设下,弱specification性质蕴含渐近平均跟踪性质.最后证明具有弱specification性质的满射系统是一致分布混沌的.

弱Specification和逆极限空间上移位映射(英文)

对度量空间上连续自映射引进弱Ｓｐｅｃｉｆｉｃａｔｉｏｎ概念，研究了它与浑沌和拓扑熵的联系，此外还讨论了逆极限空间上移位映射的弱Ｓｐｅｃｉｆｉｃａｔｉｏｎ性质。

连续映射的弱specification性质与混沌

specification性质是一种重要的动力性质,对连续的区间映射和树映射,该性质与拓扑混合等价。对紧致度量空间,满足POTP性质的拓扑混合映射具有specification性质。文章对紧致度量空间上连续自映射,研究了弱specification性质与各种混沌之间的关系,证明了具有弱specification性质的系统是Li-Yorke意义下混沌的,是Ruelle-Takens意义下混沌的,是处处混沌的,并且具有性质P。

弱Specification性质与不变概率测度

对紧致度量空间上连续自映射,研究了弱Specification性质与不变概率测度之间的关系,证明了具有弱Specification性质的系统一定存在f:X→X的不变概率测度m,使得Suppm=X,并且f:X→X有满测度中心,即M(f)=X.

弱Specification和伪移位不变集(英文)

研究了弱Specification性质与紧致度量空间上连续映射的伪移位不变集的联系 ,得到的主要结果是 :设f∶X→X是紧致度量空间连续自映射 ,若f具有弱Specification性质 ,则存在正整数M ,使得fM具有伪移位不变集。

逐点回归映射与弱Specification(英文)

重点证明了紧致度量空间上的逐点回归映射不满足弱Specification性质。

一些紧致系统的拓扑序列熵和广义specification性质

研究了紧致度量空间上的连续满射f:X→X和逆极限空间上移位映射σf:Xf→Xf的拓扑序列熵的性质和逆极限空间上移位映射的广义spec ification性质.

为SOFL Specification自动生成消息序列(MSC)

形式化方法以其精确的描述能力,可验证性,和自动化潜力而得到了人们的关注。特别是在一些对安全性要求非常高的领域,已经有了很多成功的案例。但他始终没有在业界得到推广。原因之一就是基于数学符号的形式化语法十分晦涩难懂,这给开发人员之间,开发人员和客户之间的交流造成了巨大的障碍。我们认为要解决这一问题,就需要为形式化规范提供更直观,更为大家所熟悉的行为表现方式。文章介绍如何自动生成MSC(messagesequencechart)来描述SOFL(StructuredObjectorientedFormalLanguage)[12]specification的行为。通过用MSC来动态模拟规范的行为的执行过程,可以很好地帮助人们理解规范内容,这对于规范校验(specificationvalidation)有重要的意义。此外,我们为支持这一MSC自动生成过程编写的一款工具原形,也会在文中作简要介绍。

具有specification性质的连续流

研究了具有specification性质连续流的动力性质。主要结论是:(1)具有specmcation性质的连续流是混沌的,且其拓扑熵大于零;(2)specmcation性质在扭扩及逆极限下是不变的。

Monte Carlo Method for the Uncertainty Evaluation of Spatial Straightness Error Based on New Generation Geometrical Product Specification

Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product speeifieation（GPS） requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on ＂The Guide to the Expression of Uncertainty in Measurement（GUM）＂. In order to compute spatial straightness error（SSE） accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization（QPSO） is proposed to solve the minimum zone SSE and Monte Carlo Method（MCM） is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function（PDF） for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine（CMM） is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.

SHADOWING,EXPANSIVENESS AND SPECIFICATION FOR C^1-CONSERVATIVE SYSTEMS

We prove that a Cl-generic volume-preserving dynamical system （diffeomor- phism or flow） has the shadowing property or is expansive or has the weak specification property if and only if it is Anosov. Finally, as in [10, 27], we prove that the Cl-robustness, within the volume-preserving context, of the expansiveness property and the weak specifica- tion property, imply that the dynamical system （diffeomorphism or flow） is Anosov.

Improvement of the Assay Method for Steviol Glycosides in the JECFA Specifications

Steviol glycosides are natural sweetener constituents found in the leaves of Stevia rebaudiana Bertoni (Asteraceae). The specifications for steviol glycosides were established by the Joint FAO/WHO Expert Committee on Food Additives (JECFA) in 2008, although there was a call in the following year for the modification of this assay method to enable the determination of nine steviol glycosides rather than just seven. In response, based on a proposed method by the Japan Stevia Association, we developed an improved method by changing the HPLC conditions and including the use of an octadecylsilyl column instead of an amino-bonded column to enable the rapid and reliable determination of the nine steviol glycosides by an isocratic HPLC-UV method. With the developed method, the nine steviol glycosides can be separately determined, and identified using individual reference chemicals as standards, unlike the previous identification method, which was based on the relative retention times. In addition, the single stevioside quantification standard was replaced with both stevioside and rebaudioside A quantification standards. Importantly, the validation of the developed method was successful. The limits of quantification for the nine steviol glycosides were between 0.2% and 0.6%. The developed assay method for the nine steviol glycosides was proposed to JECFA and adopted as the revised assay method for the steviol glycosides specifications at its 73rd meeting in 2010.

Survivability Specification Framework for Dependability-Functionality Codesign of ERTS

In ordet to maintain the dependability of system and meet the functional needof users dtsire, this paper introduces a survivability mechanism into embedded real-time system,and proposes a general comprehensive, approach based on a rigorous definition of survivability. Thisapproach permits a trade-off between the function and the cost of system development. It emphasizesthe ultradependable implementation of crucial function without demanding that of entire system.