Unexpected Twinning and Phase-Transition of the Indentation Standards, Their Transition Energies, and Scientific Dichotomy

The general use of aluminium as an indentation standard for the iteration of contact heights for the determination of ISO-14577 hardness and elastic modulus is challenged because of as yet not appreciated phase-changes in the physical force-depth standard curve that seemed to be secured by claims from 1992. The physical and mathematical analyses with closed formulas avoid the still world-wide standardized energy-law violation by not reserving 33.33% (h2 belief) (or 20% h3/2 physical law) of the loading force and thus energy for all not depth producing events but using 100% for the depth formation is a severe violation of the energy law. The not depth producing part of the indentation work cannot be done with zero energy! Both twinning and structural phase-transition onsets and normalized phase-transition energies are now calculated without iterations but with physically correct closed arithmetic equations. These are reported for Berkovich and cubecorner indentations, including their comparison on geometric grounds and an indentation standard without mechanical twinning is proposed. Characteristic data are reported. This is the first detection of the indentation twinning of aluminium at room temperature and the mechanical twinning of fused quartz is also new. Their disqualification as indentation standards is established. Also, the again found higher load phase-transitions disqualify aluminium and fused quartz as ISO-ASTM 14577 (International Standardization Organization and American Society for Testing and Materials) standards for the contact depth “hc” iterations. The incorrect and still world-wide used black-box values for H- and Er-values (the latter are still falsely called “Young’s moduli” even though they are not directional) and all mechanical properties that depend on them. They lack relation to bulk moduli from compression experiments. Experimentally obtained and so published force vs depth parabolas always follow the linear FN = kh3/2 + Fa equation, where Fa is the axis-cut before and after the phase-transition branches (never “h2” as falsely enforced and used for H, Er and giving incorrectly calculated parameters). The regression slopes k are the precise physical hardness values, which for the first time allow for precise calculation of the mechanical qualities by indentation in relation to the geometry of the indenter tip. Exactly 20% of the applied force and thus energy is not available for the indentation depth. Only these scientific k-values must be used for AI-advises at the expense of falsely iterated indentation hardness H-values. Any incorrect H-ISO-ASTM and also the iterated Er-ISO-ASTM modulus values of technical materials in artificial intelligence will be a disaster for the daily safety. The AI must be told that these are unscientific and must therefore be replaced by physical data. Iterated data (3 and 8 free parameters!) cannot be transformed into physical data. One has to start with real experimental loading curves and an absolute ZerodurR standard that must be calibrated with standard force and standard length to create absolute indentation results. .

CONTROL CHAOS IN TRANSITION SYSTEM USING SAMPLED-DATA FEEDBACK

The method for controlling chaotic transition system was investigated using sampled- data . The output of chaotic transition system was sampled at a given sampling rate , then the sampled output was used by a feedbacks subsystem to construct a control signal for controlling chaotic transition system to the origin . Numerical simulations are presented to show the effectiveness and feasibility of the developed controller.

Transition Logic Regression Method to Identify Interactions in Binary Longitudinal Data

Logic regression is an adaptive regression method which searches for Boolean (logic) combinations of binary variables that best explain the variability in the outcome, and thus, it reveals interaction effects which are associated with the response. In this study, we extended logic regression to longitudinal data with binary response and proposed “Transition Logic Regression Method” to find interactions related to response. In this method, interaction effects over time were found by Annealing Algorithm with AIC (Akaike Information Criterion) as the score function of the model. Also, first and second orders Markov dependence were allowed to capture the correlation among successive observations of the same individual in longitudinal binary response. Performance of the method was evaluated with simulation study in various conditions. Proposed method was used to find interactions of SNPs and other risk factors related to low HDL over time in data of 329 participants of longitudinal TLGS study.

Unconventional phase transition of phase-change-memory materials for optical data storage

Recent years, optically controlled phase-change memory draws intensive attention owing to some advanced applications including integrated all-optical nonvolatile memory, in-memory computing, and neuromorphic computing. The light-induced phase transition is the key for this technology. Traditional understanding on the role of light is the heating effect. Generally, the RESET operation of phase-change memory is believed to be a melt-quenching-amorphization process. However, some recent experimental and theoretical investigations have revealed that ultrafast laser can manipulate the structures of phase-change materials by non-thermal effects and induces unconventional phase transitions including solid-to-solid amorphization and order-to-order phase transitions. Compared with the conventional thermal amorphization,these transitions have potential superiors such as faster speed, better endurance, and low power consumption. This article summarizes some recent progress of experimental observations and theoretical analyses on these unconventional phase transitions. The discussions mainly focus on the physical mechanism at atomic scale to provide guidance to control the phase transitions for optical storage. Outlook on some possible applications of the non-thermal phase transition is also presented to develop new types of devices.

T_(BB) DATA-REVEALED FEATURES OF ASIAN-AUSTRALIAN MONSOON SEASONAL TRANSITION AND ASIAN SUMMER MONSOOM ESTABLISHMENT

Based on TBB data from Meteorological Institute Research of Japan, study is carried out of the features of seasonal transition of Asian-Australian monsoons and Asian summer monsoon establishment,indicating that the transition begins as early as in April, followed by abrupt change in May-June; the Asian summer monsoon situation is fully established in June. The winter convective center in Sumatra moved steadily northwestward across the "land bridge" of the maritime continent and the Indo-China Peninsula as time goes from winter to summer, thus giving rise to the change in large scale circulations that is responsible for the summer monsoon establishment over SE Asia and India; the South China Sea to the western Pacific summer monsoon onset bears a close relation to the active convection in the Indo China Peninsula and steady eastward retreat of the subtropical TBB high-value band,corresponding to the western Pacific subtropical high.

Data processing in pulse transit time measurement

PuLse transit time(FIT)is used as a noninvasive and cull-less parameter to estimate blood pressure.In this paper,we develop an algorithm to obtain FTT rapidly,which is appropriate for micro-processor and could achieve good accuracy in PTT,even in noisy measurements.The algorithm is based on finite impulse response(FIR)filter to reduce the noise and an adaptive threshold to detect the significant points of ECG and PPG.Evaluation of this method is based on the signals from our PTr-based blood pressure devices.It is shown that the method works well for PPT calculation.

Public Transit Performance Evaluation Using Data Envelopment Analysis and Possibilities of Enhancement

This study evaluates the operational performance of all routes of Sajha Bus Yatayat operating inside Kathmandu valley using Data Envelopment Analysis (DEA) in terms of efficiency and effectiveness score. This approach allows us to access the relative performance of transit system in absence of historical data and research to compare with. To explore the possibility of enhancing the performance, scenarios were created for relatively underperforming routes and long route problem by changing the most important input variable and output variables accordingly with regression model where it was relevant. Partial Least Squares (PLS) regression was used to determine the most influential input variables to the output variables. DEA was conducted to access the performance of all routes under these scenarios. Underperforming routes except the longest route under the first set of scenarios, emerge to be better performing efficiently without considerable negative deviation in effectiveness. The result of second set of scenarios for long route problem suggests that the longest route’s performance can be enhanced significantly upon proper route alignment. Scenarios development and evaluation can help lead transit companies to explore the strategies to facilitate operational performance enhancement.

Data processing in pulse transit time measurement

Pulse transit time (PTT) is used as a noninvasive and cuff-less parameter to estimate blood pressure. In this paper, we develop an algorithm to obtain PTT rapidly, which is appropriate for micro-processor and could achieve good accuracy in PTT, even in noisy measurements. The algorithm is based on finite impulse response (FIR) filter to reduce the noise and an adaptive threshold to detect the significant points of ECG and PPG. Evaluation of this method is based on the signals from our PTT-based blood pressure devices. It is shown that the method works well for PPT calculation.

基于数据融合的城市轨道交通大客流预警研究

为了降低因节假日或突发时间导致的客流拥堵,促进客运部门快速应对客流波动,提出了一种基于数据融合的城市轨道交通大客流预警方法。通过对客流参数预测信息进行融合,获得符合实际客流瓶颈点的参数信息,以完成轨道交通大客流预警。提出的方法利用动态贝叶斯网络,实现了历史数据与运输服务信息的融合。以城市假期期间五条线路每日客流量为例,通过对比实验验证了提出方法的有效性与准确性。

保供降碳目标下能源转型模式及转型时点分析

应对气候变化目标要求全球能源系统进行广泛而深刻的转型。由于资源禀赋、能源战略、技术水平等差异,各国能源转型进程呈现出明显的异质性特征。通过对主要国家能源转型特征与减煤路径的分析,归纳了4种典型模式:能效提高模式、增气减煤模式、煤炭洁净利用模式、新能源替代模式,不同模式在不同时间点上与经济社会发展交互影响形成了国际能源转型的内在驱动机制。采用面板数据模型识别了影响能源转型模式的重要因素,并利用历史趋势分析方法对我国化石能源消费“拐点”与减煤时间节点进行研究。研究表明,当人均GDP达到25500美元时,发达国家即出现化石能源减少拐点。国家创新指数和城镇化与煤炭消费占比呈负相关,第二产业增加值占比与煤炭消费占比呈正相关。我国预计减煤时间范围在2028-2035年,化石能源消费减少时点在2040年左右。考虑到我国以煤炭为主的能源资源禀赋,我国能源转型目标的实现须依赖于煤炭洁净利用为主的转型路径,大力发展低碳化现代煤基能源体系,改变传统煤炭利用理念与方式,为未来多能耦合的新型能源体系提供重要支撑。

基于改进浮动单元的城市职住平衡时间尺度估计——以广州市为例

已有研究对城市职住平衡的测度往往存在可塑性面积单元问题,且忽略了交通网络在职住联系中的媒介作用。提出一种改进的浮动单元法,构建基于道路和城市轨道交通网络的数据集,以时间为职住分析尺度生成浮动单元,运用手机信令数据对职住平衡进行测度。以广州市为例,对就业中心和居住区的职住平衡时间尺度进行估计。研究发现:广州市中心城区职住平衡时间尺度分布呈圈层式空间特征,职住平衡时间尺度从一级就业中心向外围先减小再增大;城市轨道交通缩小了就业中心的职住平衡时间尺度;一级、二级(不处于一级就业中心的辐射范围内)和三级就业中心的职住平衡时间尺度分别为32~40 min、14~28 min和10~20 min,而居住组团的职住平衡时间尺度主要依附于就业中心且受到城市轨道交通的影响。最后,提出在合适的时间尺度下对职住空间结构进行评估和优化住房和就业等资源配置,并重视城市轨道交通对职住空间结构的影响。

中国石油地球物理数据共享与数字化转型设想

地球物理数据是油气田公司的核心数据资产,是可持续挖掘的宝贵数据资源。中国石油天然气集团有限公司在几十年的油气勘探开发过程中,获取了海量地球物理数据。大数据时代数据为王,为了更好地保护地球物理数据资产,挖掘数据潜力,提高数据价值,盘活数据资产,中国石油成立了地球物理数据与软件共享中心,对地球物理数据集中统一实施异地备份和资产化共享管理,为海量数据超级计算奠定基础,促进地球物理数据共享使用,解决协同研究工作中的数据孤岛问题,助推地球物理业务实现数字化转型,更好地支撑服务油田公司上游业务发展。

OH^(+)离子14个Λ-S态和27个Ω态光谱性质的理论研究

在选择合适的活性空间和基组、考虑各种物理效应(标量相对论效应、核-价电子关联效应、完备基组极限和自旋-轨道耦合效应)的基础上,本文利用优化的icMRCI+Q方法获得了X^(3)Σ^(-)/a^(1)Δ/b^(1)Σ^(+)/A^(3)Π/c^(1)Π(OH^(+))←X^(2)Π(OH)精确的电离能、OH^(+)离子14个Λ^(-)S态和相应的27个Ω态势能曲线.利用全电子icMRCI/cc-pCV5Z+SOC理论获得了6个Ω态[X^(3)Σ_(0+)^(-),X^(3)Σ_(1)^(-)],(1)2,(2)2,(2)1和(1)0-]之间的跃迁偶极距.并且本文获得的电离能、光谱和振动-转动跃迁数据与现有的测量值符合得非常好.研究发现:1)(1)2(v′=0-6,J′=2,+)的辐射寿命随着v′的增大而逐渐缩短,辐射宽度随着v′的增大而逐渐增宽;(1)2(v′=0-6,J'=2,+)-X^(3)Σ_(1)^(-)(υ″,J″=1,-)自发辐射较弱.2)(2)2^(第一势阱)(υ′=0-2,J′=2,+),(2)1(υ′=0-9,J′=1,+)和(1)0-(v′=0-8,J′=0,+)-X^(3)Σ_(1)^(-)(v″,J″=1,-)的自发辐射很强.3)(2)2第一势阱(v′=0-2,+),(2)1(v′=0-9,+)和(1)0-(v′=0-8,+)的辐射寿命都是随着J′的增大而逐渐增长.

三维激光扫描与BIM技术融合的城市轨道交通地下建筑物三维建模方法

本文将三维激光扫描技术与BIM技术相结合,实现了城市轨道交通地下车站、隧道及附属设施的三维建模。通过激光扫描仪获取点云数据,利用点云处理软件进行预处理,包括拼接、去噪和精简等操作;然后利用特征点云提取方法结合BIM建模软件和可视化编程技术,有效解决了传统测绘方法无法获取和处理复杂地下建筑物信息及BIM模型中信息孤岛问题。本文方法对未来城市轨道交通工程建设和运维管理的信息化和三维可视化具有重要意义。

城市温室气体排放推演及其评估方法

气候变化已成为人类可持续发展面临的重大挑战。为应对这一紧迫问题,世界各国相继制定了温室气体减排计划和碳中和时间表。随着全球气候变化对城市温室气体排放管理需求的不断增加,城市温室气体排放推演及其评估方法日益受到重视。这些方法通过模拟未来城市的温室气体排放趋势,使政府、企业和各部门能够更好地了解城市如何通过低碳转型应对气候变化并推动可持续发展,从而在实现气候目标方面发挥关键作用。然而,尽管这些方法在气候行动规划中愈加重要,国际上依然缺乏统一的标准和方法论,这使得各城市在评估其气候行动计划和能源转型策略的有效性时面临挑战。为此,本文提出并探讨了一套标准化的城市温室气体排放推演与评估方法,旨在为全球城市提供统一的技术指南。该方法涵盖数据收集、模型选择、情景定义与评估指标等关键环节。通过对两个典型城市的案例研究,本文验证了该标准方法的适用性和有效性,展示了其在支持全球城市低碳转型和气候行动中的重要作用。这一标准化方法的推广将为全球城市的气候治理和可持续发展提供坚实的技术基础,为标准研制提供有力支撑。

面向爆炸压力场的体绘制自动传输函数设计

直接体绘制广泛应用于可视化领域,其中传输函数决定了最终绘制的效果。大规模爆炸数据属于复杂的时变数据,其压力场的取值范围和分布会随时间剧烈变化。为了实现对冲击波传播特征的连续跟踪,提出了一种基于标量-时间梯度(scalar-temporal gradient,STG)二维空间的自动传输函数设计方法。结合爆炸过程中的物理规律,将STG空间划分为多种状态并总结了状态之间的转移规律。将冲击波的传播特征编码为一段一定长度的状态转移链(state transitions chain,STC),称为时变特征。传输函数中的颜色以时变特征为单位,基于完全状态转移链自动分配。传输函数中的不透明度采用基于压强变化速率的分段非线性曲线,凸显压强变化剧烈的特征。选取了两类典型的大规模爆炸场景对方法进行了验证,绘制结果中都包含了丰富的明显可区分的冲击波传播特征。结果表明,生成的传输函数在整个时间维度上都能稳定、准确地捕捉冲击波的传播特征。

基于马尔可夫转移场和轻量级网络的非侵入式负荷识别

负荷识别是非侵入式负荷监测(non-intrusive loadmonitoring,NILM)的关键一步。针对目前识别方法存在网络参数量大、识别率低的局限性,提出了一种基于马尔可夫转移场(Markov transition field,MTF)和轻量级网络的非侵入式负荷识别方法。首先,利用归一化后的电压电流计算马尔可夫状态转移矩阵,在时域上排列每个状态转移概率构建MTF。其次,对MTF降采样以适应神经网络的学习,利用伪彩色编码技术得到RGB彩色图像。最后,在轻量级网络Shuffle Net V2中加入SimAM无参注意力模块作为特征提取网络,以较少的参数量实现负荷分类识别。使用公共数据集PLAID和WHITED对所提方法进行实验,结果表明,SimAM-ShuffleNetV2在两个数据集的识别准确率分别达到了98.99%和99.22%,参数量分别为0.37 M和0.41 M,比现有的方法具有更高的识别准确率和更少的参数量,验证了所提方法的有效性和优越性。

基于零信任安全模型的轨道交通数据隐私保护

为解决轨道交通网络数据传输杂乱的问题,提升数据样本的安全性,研究基于零信任安全模型的轨道交通数据隐私保护方法。在零信任安全模型的基础上,分别定义公钥密码与私钥密码模板,建立完整的轨道交通数据隐私链路标签。完善数据样本验证机制以提升数据安全性,通过求解交互认证系数的方式辨别隐私数据样本,结合敏感度指标实现轨道交通数据隐私保护。实验结果表明,在轨道交通网络中应用零信任安全模型,可在保证正序数据传输速率的同时将乱序数据传输速率限制在3.52 Mb/ms以下,能够满足轨道交通数据隐私保护的应用需求。

大都市区耕地非农化的时空跃迁特征分析--以天津市为例

基于天津1992—2022年4期数据,运用重心模型、探索性时空数据分析等方法,分析了大都市区耕地非农化时空跃迁特征。结果表明:天津耕地非农化主要以转为建设用地、水域为主;天津耕地非农化地域差异明显,中心城区耕地非农化规模较小,而东南各区规模较大;天津耕地非农化重心先向西北后向东北方向迁移,总体呈“V”型走势;天津耕地非农化有明显的空间集聚特点,但聚集水平不断下降,“高—高”聚集区主要分布于东部及南部区域,“低—低”聚集区主要分布于中心城区;北部、东部和南部地区的耕地非农化空间结构有较强的动态性,北辰区、东丽区等中心城区周边区对临近区有更强空间依赖;天津耕地非农化在空间格局演化上具有较强的空间整合性,正向协同增长的有7个区,主要分布在中北部地区,负向协同增长的有3个区,主要分布在中心城区周边区域;天津耕地非农化的不同空间结构类型间较少发生跃迁,具有较强的转移惰性。

精益数字创新体系下的数据中台解构与实践

[目的]为进一步挖掘数据价值,充分利用企业发展的重要战略资源——数据,基于现场精益管理体系的建设与经验,引入数据中台,结合一线部门的特点,建立精益数字创新体系。[方法]介绍了精益管理体系的内涵和数据中台的作用;介绍上海轨道交通隆德路站数字化管理发展历程;结合隆德路站实际应用情况,结构了数据中台的功能及其在数据挖掘中的作用。[结果及结论]将精益管理体系与数据中台有机结合,采用多种质量管理工具与数据分析工具,能够进行设备状态评估、人员能力识别及生产模式优化。通过精益管理赋能数据中台,并持续改进,能够提高决策水平和设备故障处置效率。