Detecting dynamical complexity changes in time series using the base-scale entropy

Timely detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meanings. We introduce a complexity measure for time series： the base-scale entropy. The definition directly applies to arbitrary real-word data. We illustrate our method on a practical speech signal and in a theoretical chaotic system. The results show that the simple and easily calculated measure of base-scale entropy can be effectively used to detect qualitative and quantitative dynamical changes.

Outcome assessment of stroke convalescence using multiple scales based on different dimensions

BACKGROUND: Convalescence is an important stage of stroke treatment. A lot of patients have somatic and mental disorders at various degrees. The primary standard can only reflect partial conditions of somatic disorder; in addition, multiple dimensions of patients at the phase of stroke convalescence are further observed by using a lot of standards, such as signs and symptoms of traditional Chinese medicine, daily activity and psychological status. OBJECTIVE: To analyze the outcome assessments of the cases of stroke convalescence measured with different criteria consisting of various dimensions by a cross-sectional investigation of the condition of stroke convalescent patients. DESIGN: Scale evaluation. SETTING: Departments of Clinical Epidemiology Exploratory Development and Neurology, the Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine; National Center for Training of Design, Measurement and Evaluation in Clinical Research,Guangzhou University of Traditional Chinese Medicine. PARTICIPANTS: A total of 194 stroke convalescent patients treated in the Second Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine from July 26, 2000 to February 28, 2001 were taken as subjects of the study. There were 126 males and 68 females aged from 40 to 89 years, and the illness course ranged from 14 to 181 days. All patients met diagnosis-treatment criteria of stroke (the second version)[DTCS(V2.0)] and various kinds of diagnostic points of cerebrovascular diseases; moreover, all patients provided confirmed consents. METHODS: They were assessed by assessment methods including the following assessment instruments: DTCS(V2.0), self-designed scale of traditional Chinese medicine (TCM) symptoms (28 symptoms and physical signs were scored as 0, 1, 2 marks from none to severity), modified Edinburgh-Scandinavia stroke scale (a total of 45 marks, 0 to 15 marks as mild defect, 16 to 30 as moderate defect, 31 to 45 as severe defect), modified Barthel activities of daily life (ADL) index (a total of 100 marks, less than 60 marks as unable self-care), vitality and mental health (subscales derived from Health Survey Questionnaire, SF-36). The collected data from scales and inter-scale correlation were processed by the statistic methods mainly including descriptive analysis, Spearmen correlation analysis, factor analysis, etc. MAIN OUTCOME MEASURES: ① Average scores of scales and criteria; ② correlation between modified Edinburgh-Scandinavia stroke scale and other scales. RESULTS: All of the patients completed the assessment, and analyzed in the final analysis. ① The average scores of the scales and criteria: The average scores of DTCS(V2.0), self-designed scale of TCM symptoms, modified Edinburgh-Scandinavia stroke scale, modified Barthel ADL index, vitality and mental health scales were 6.51±6.29, 13.73±6.97, 7.56±7.35, 63.58±23.68, 52.79±23.32 and 62.83±22.75 respectively. ② Correlation between modified Edinburgh-Scandinavia stroke scale and other scales: The Spearman correlation coefficients (R ’) of modified Edinburgh-Scandinavia stroke scale with diagnosis-treatment criteria of stroke, scales of TCM symptoms, modified Barthel ADL index, vitality scale and mental health scale were 20.885, 0.302, -0.824, -0.294 and -0.258 respectively. CONCLUSION: The modified Edinburgh-Scandinavia stroke scale and DTCS(V2.0) shared the same assessment dimension, so they can be mutually alternated in some clinical practices. Discrepancy in measurements of health status was gained due to the diverse dimensions applied in outcome assessments. It is necessary to build up a multi-dimensional assessment criteria system, such as signs and symptoms, daily activities and psychological status, for assessing the stroke convalescent cases in a more comprehensive scope and reflecting the efficacy of TCM treatment scientifically.

A Closure for Isotropic Turbulence Based on Extended Scale Similarity Theory in Physical Space

The closure of a turbulence field is a longstanding fundamental problem, while most closure models are introduced in spectral space. Inspired by Chou＇s quasi-normal closure method in spectral space, we propose an analytical closure model for isotropic turbulence based on the extended scale similarity theory of the velocity structure function in physical space. The assumptions and certain approximations are justified with direct numerical simulation. The asymptotic scaling properties are reproduced by this new closure method, in comparison to the classical Batchelor model.

Betweenness-based algorithm for a partition scale-free graph

Many real-world networks are found to be scale-free. However, graph partition technology, as a technology capable of parallel computing, performs poorly when scale-free graphs are provided. The reason for this is that traditional partitioning algorithms are designed for random networks and regular networks, rather than for scale-free networks. Multilevel graph-partitioning algorithms are currently considered to be the state of the art and are used extensively. In this paper, we analyse the reasons why traditional multilevel graph-partitioning algorithms perform poorly and present a new multilevel graph-partitioning paradigm, top down partitioning, which derives its name from the comparison with the traditional bottom-up partitioning. A new multilevel partitioning algorithm, named betweenness-based partitioning algorithm, is also presented as an implementation of top-down partitioning paradigm. An experimental evaluation of seven different real-world scale-free networks shows that the betweenness-based partitioning algorithm significantly outperforms the existing state-of-the-art approaches.

Effect of Nursing Intervention Based on Caprini Risk Assessment Scale for Venous Thromboembolism in Perioperative Patients with Liver Cancer

Objective:To explore the effect of nursing intervention based on Caprini risk assessment scale for venous thromboembolism(VTE)in perioperative patients with liver cancer.Methods:A total of 128 hepatocellular cancer(HCC)patients who were hospitalized in our department from January 2021 to March 2022 and met the research criteria were selected.According to odd and even numbers in the order of inclusion,64 cases were divided into two groups:a control group and an observation group.The control group received routine nursing intervention during perioperative period,while the observation group received nursing intervention based on Caprini risk assessment scale for VTE.The incidence of VTE and complications were compared between the two groups.Results:The incidence of VTE and postoperative complications in the observation group were lower than those in the control group(P<0.05).Conclusion:Nursing intervention based on Caprini risk assessment scale for VTE can reduce the incidence of perioperative deep vein thrombosis and complications in patients with liver cancer;thus,it is worthy of clinical application.

The Impact of Model Based Offset Scaling Technique on the Amplitude Variation with Offset Responses from 3D Seismic Data Acquired from the Tano Basin, Offshore Ghana

Amplitudes have been found to be a function of incident angle and offset. Hence data required to test for amplitude variation with angle or offset needs to have its amplitudes for all offsets preserved and not stacked. Amplitude Variation with Offset (AVO)/Amplitude Variation with Angle (AVA) is necessary to account for information in the offset/angle parameter (mode converted S-wave and P-wave velocities). Since amplitudes are a function of the converted S- and P-waves, it is important to investigate the dependence of amplitudes on the elastic (P- and S-waves) parameters from the seismic data. By modelling these effects for different reservoir fluids via fluid substitution, various AVO geobody classes present along the well and in the entire seismic cube can be observed. AVO analysis was performed on one test well (Well_1) and 3D pre-stack angle gathers from the Tano Basin. The analysis involves creating a synthetic model to infer the effect of offset scaling techniques on amplitude responses in the Tano basin as compared to the effect of unscaled seismic data. The spectral balance process was performed to match the amplitude spectra of all angle stacks to that of the mid (26°) stack on the test lines. The process had an effect primarily on the far (34° - 40°) stacks. The frequency content of these stacks slightly increased to match that of the near and mid stacks. In offset scaling process, the root mean square (RMS) amplitude comparison between the synthetic and seismic suggests that the amplitude of the far traces should be reduced relative to the nears by up to 16%. However, the exact scaler values depend on the time window considered. This suggests that the amplitude scaling with offset delivered from seismic processing is only approximately correct and needs to be checked with well synthetics and adjusted accordingly prior to use for AVO studies. The AVO attribute volumes generated were better at resolving anomalies on spectrally balanced and offset scaled data than data delivered from conventional processing. A typical class II AVO anomaly is seen along the test well from the cross-plot analysis and AVO attribute cube which indicates an oil filled reservoir.

Factor Analytical Examination of the Evidence-Based Practice Beliefs Scale: Indications of a Two-Factor Structure

Background: Promotion of Evidence-Based Practice (EBP) in nursing appears to be developing slowly. Research indicates that nurses’ beliefs in EBP may play an even more significant role than knowledge and resources in making implementation feasible. To address this issue, measurement of nurses’ beliefs regarding EBP is paramount. Aims and objectives: This study explores the internal consistency reliability and the construct factor structure of the Norwegian version of the original Evidence-Based Practice Beliefs Scale (EBP-BS). Methods: The study has a Non-experimental exploratory survey design. A Norwegian translation of the EBP-BS was tested in a convenience sample of 118 healthcare professionals (95% nurses) attending a continuing education program at a University College in Norway. The response rate was 95% (n = 112). The internal consistency of the scale was measured by Cronbach’s alpha, and an explorative Principal Component Analysis (PCA) was used to explore the construct structure. Results: The overall internal consistency of the EBP-BS was acceptable. The PCA indicated a four-factor structure. The psychometric properties of two of the factors were too weak for expanding to a four-factor model. Based on our investigation of the EBP-BS, we suggest a two-factor structure model. The factors were named 1) General knowledge and confidence concerning EBP and 2) Task specific beliefs in EBP. This finding differs from previous results that indicated a unidimensional structure. Conclusion: As a starting point, reliable and valid measurement of nurses’ beliefs about EBP is required in order to identify possible obstacles and to optimize implementation in the individual clinical setting. Our results indicate that the EBP-BS has a two-factor structure. Further exploration of the factor structure is needed. Further empirical research may contribute to the resolving of controversies concerning basic understandings of the concept of EBP.

Surrogate-based modeling and dimension reduction techniques for multi-scale mechanics problems

Successful modeling and/or design of engineering systems often requires one to address the impact of multiple ＂design variables＂ on the prescribed outcome.There are often multiple,competing objectives based on which we assess the outcome of optimization.Since accurate,high fidelity models are typically time consuming and computationally expensive,comprehensive evaluations can be conducted only if an efficient framework is available.Furthermore,informed decisions of the model/hardware＇s overall performance rely on an adequate understanding of the global,not local,sensitivity of the individual design variables on the objectives.The surrogate-based approach,which involves approximating the objectives as continuous functions of design variables from limited data,offers a rational framework to reduce the number of important input variables,i.e.,the dimension of a design or modeling space.In this paper,we review the fundamental issues that arise in surrogate-based analysis and optimization,highlighting concepts,methods,techniques,as well as modeling implications for mechanics problems.To aid the discussions of the issues involved,we summarize recent efforts in investigating cryogenic cavitating flows,active flow control based on dielectric barrier discharge concepts,and lithium（Li）-ion batteries.It is also stressed that many multi-scale mechanics problems can naturally benefit from the surrogate approach for ＂scale bridging.＂

EFFECTS OF TRACE ELEMENTS ON THE OXIDATION OF LOW SEGREGATION Ni－Cr－Al BASED SUPERALLOYS

The oxidation behaviors of two kinds of low segregation Ht-Cr-Al based superalloys have been studied between 1000-1100℃, and compared with that of general Mt-Cr-Al based superalloys. The results indicated that the simultaneous additions of 0.1 wt% S and 0. 1 wt% Zr to low segregation alloys increase the oxidation rate of Al2O3-forming alloy and improve the scale adherence. The addition of 0.1 wt% Zr can ,minimize the negative effects of S on the adherence of Al2O3 scale. Low amounts of S(≤50 ppm wt) have no obviously negative effects on the adherence of Cr2O3 scale formed on one of the low segregation superalloys.

Isothermal oxidation behavior and mechanism of a nickel-based superalloy at 1000°C

The oxidation behavior of a nickel-based superalloy at 1000°C in air was investigated through X-ray diffraction, scanning electron microscopy, and energy-dispersive spectroscopy analysis. A series of oxides, including external oxide scales（Cr_2O_3,（TiO_2 ＋ Mn Cr_2O_4）） and internal oxides（Al_2O_3,Ti N）, were formed on the surface or sub-surface of the substrate at 1000°C in experimental still air. The oxidation resistance of the alloy was dependent on the stability of the surface oxide layer. The continuity and density of the protective Cr_2O_3 scale were affected by minor alloying elements such as Ti and Mn. The outermost oxide scale was composed of TiO_2 rutile and Mn Cr_2O_4 spinel, and the growth of TiO_2 particles was controlled by the outer diffusion of Ti ions through the pre-existing oxide layer. Severe internal oxidation occurred beneath the external oxide scale, consuming Al and Ti of the strength phase γ′（Ni_3（Al,Ti）） and thereby severely deteriorating the surface mechanical properties. The depth of the internal oxidation region was approximately 35 μm after exposure to experimental air at 1000°C for 80 h.

Optimal Tracking Controller Design for a Small Scale Helicopter

A model helicopter is more difficult to control than its full scale counterpart. This is due to its greater sensitivity to control inputs and disturbances as well as higher bandwidth of dynamics. This work is focused on designing practical tracking controller for a small scale helicopter following predefined trajectories. A tracking controller based on optimal control theory is synthesized as a part of the development of an autonomous helicopter. Some issues with regards to control constraints are addressed. The weighting between state tracking performance and control power expenditure is analyzed. Overall performance of the control design is evaluated based on its time domain histories of trajectories as well as control inputs.

Analysis on the Effect of Shading on the Characteristics of Large-scale on-grid PV System in China

Because of rich solar resource and low land cost, a lot of large-scale ground-based grid-connected PV systems have been built in Northwest China. In this paper, some shading phenomena on a grid-connected PV system inNorthwest Chinaare classified and analyzed. Through the I-V curve test of PV modules, it can be seen that dust influence system performance of the grid-connected PV system. And the experimental results have shown that shading could affect the electrical properties of PV modules. Meanwhile, same shading area on different shading positions could have different impacts on the identical PV module.

Object-based forest gaps classification using airborne LiDAR data

Object-based classification differentiates forest gaps from canopies at large regional scale by using remote sensing data. To study the segmentation and classification processes of object-based forest gaps classification at a regional scale, we sampled a natural secondary forest in northeast China at Maoershan Experimental Forest Farm.Airborne light detection and ranging(LiDAR; 3.7 points/m2) data were collected as the original data source and the canopy height model(CHM) and topographic dataset were extracted from the LiDAR data. The accuracy of objectbased forest gaps classification depends on previous segmentation. Thus our first step was to define 10 different scale parameters in CHM image segmentation. After image segmentation, the machine learning classification method was used to classify three kinds of object classes, namely,forest gaps, tree canopies, and others. The common support vector machine(SVM) classifier with the radial basis function kernel(RBF) was first adopted to test the effect of classification features(vegetation height features and some typical topographic features) on forest gap classification.Then the different classifiers(KNN, Bayes, decision tree,and SVM with linear kernel) were further adopted to compare the effect of classifiers on machine learning forest gaps classification. Segmentation accuracy and classification accuracy were evaluated by using Mo¨ller's method and confusion metrics, respectively. The scale parameter had a significant effect on object-based forest gap segmentation and classification. Classification accuracies at different scales revealed that there were two optimal scales(10 and 20) that provided similar accuracy, with the scale of 10 yielding slightly greater accuracy than 20. The accuracy of the classification by using combination of height features and SVM classifier with linear kernel was91% at the optimal scale parameter of 10, and it was highest comparing with other classification classifiers, such as SVM RBF(90%), Decision Tree(90%), Bayes(90%),or KNN(87%). The classifiers had no significant effect on forest gap classification, but the fewer parameters in the classifier equation and higher speed of operation probably lead to a higher accuracy of final classifications. Our results confirm that object-based classification can extract forest gaps at a large regional scale with appropriate classification features and classifiers using LiDAR data. We note, however, that final satisfaction of forest gap classification depends on the determination of optimal scale(s) of segmentation.

Fractal Behaviour of Atomic Scale Microstructures:an Introduction

The properties of all materials depend largely on their chemical compositions.Compositional analysis by using the atom probe suggests that it is necessary to invent new parameters to describe some aspects of microstructures.Experimental and calculation work indicates that fractal dimension can be used to describe structural aspects not readily expressible with normal parameters.The application of fractal concept in mate- rials studies will enable us to understand from a brand-new angle the ultra-fine microstructures of materials.

柴达木盆地卤水钾盐迁聚规律与找矿新突破

钾盐是我国大宗紧缺战略性“粮食”矿产,对保障国家粮食安全具有重要意义。我国钾盐资源具有需求量大、对外依存度高等特点,寻找新的钾盐矿床、形成新的大型钾盐资源基地刻不容缓。2023年,中国地质调查局组织开展青海柴达木盆地钾盐“增储保供”地质调查工作,在前期对柴达木盆地成盐聚钾规律性认识的基础上,于柴西北大浪滩—黑北凹地部署实施了“探采一体化”柴钾1井,钻获1021.95 m(井深111.54~1133.49 m)巨厚松散砂砾储卤层,全井段抽卤试验获日稳定涌水量8586 m^(3)/d、水位降深11.3 m、单位涌水量759.89 m^(3)/d·m、氯化钾平均含量为0.54%的高产工业品位“砂砾型”卤水钾矿,取得了柴达木盆地陆相深层卤水钾盐找矿新突破,为形成中国新的亿吨级大型钾盐基地夯实了资源基础。

基于项目的学习法联合慕课在医学统计学教学中的应用与思考

医学统计学课程教学团队从研究生医学统计学课程教学现状和存在问题出发,提出基于项目的学习法(project-based learning,PBL)联合大规模开放在线课程(massive open online courses,MOOC),即慕课的教学模式。本文对这种新型教学模式在研究生医学统计学课程的操作实施过程进行详细阐述,并对教学效果进行比较分析。结果表明PBL联合MOOC教学模式在提高学生的学习兴趣和动力、拓展学习资源和学习路径等方面具有优势,与传统教学模式相互补充和融合是解决当前研究生医学统计学课程学习瓶颈的有效途径,为当前医学院校研究生课程的教学改革与实践提供新思路。

数字化转型背景下大规模考试机考体系的构建

数字化转型是教育考试顺应时代发展的必由之路,机考以其独特的优势成为大规模考试数字化转型的有效途径。专业考试机构应该结合人工智能、大数据等先进技术,深入探索大规模考试机考的实施策略,利用现代信息技术搭建大规模考试机考体系,改进命题工作方式,提高组考工作效率,优化考试智能评分系统,提升考试评价价值。同时,积极破解数字化转型中机考的数据安全、技术保障、试卷等值等难题,提升大规模考试综合管理的质效,以满足现代考试的需要。

青少年体育家庭促进因素量表的编制与检验

目的:基于生态系统理论,开发一份适用于我国青少年体育家庭促进因素量表,并对其信度和效度进行验证。方法:利用区域抽样法,对华东、华中、华南、西南及西北地区的20名10至18岁青少年样本进行访谈。利用扎根理论对访谈资料进行三级编码,初步构建青少年体育家庭促进因素的结构维度,设计出30个初始题项。最后,对1371名青少年进行问卷测试,筛选有效问卷后,随机分为两组进行探索性和验证性因子分析。研究结果:探索性因子分析揭示量表包含行为习惯、父母体育支持、家庭运动价值观、资源投入四个维度,共13个题项。验证性因子分析证实了模型结构的有效性,各项拟合指标均满足接受标准(χ^(2)/df=2.490,GFI=0.962,CFI=0.981,IFI=0.981,AGFI=0.952,RMSEA=0.052)。此外,总量表及各维度α系数为0.832~0.922,折半信度为0.840~0.884,平均提取方差(AVE)为0.624~0.721,组合信度(CR)为0.838~0.963,且均达到显著性水平。研究结论:青少年体育家庭促进因素量表具有良好的信、效度。本研究为未来相关定量研究提供了一种有效测量工具。

混合碳四全加氢镍系催化剂的制备与性能评价

使用共沉淀法和挤条成型工艺小试制备了混合碳四全加氢镍系催化剂,考察了反应压力、体积空速、氢烃体积比等加氢工艺条件对催化剂性能的影响;采用打片成型工艺进行催化剂中试放大制备,并对其性能进行了评价。结果表明:在入口温度为室温,反应压力为2.0 MPa,氢烃体积比为300,进料体积空速为2.0 h^(-1)的优化加氢工艺条件下,小试催化剂可以将混合碳四原料中单烯烃质量分数降低至1.0%以下;与小试催化剂相比,中试放大催化剂堆积密度和径向抗压碎力分别提高73%,302%;中试放大催化剂与进口钯系催化剂在789 h评价周期内的不饱和烃转化率分别为94.26%,89.72%,前者比后者具有更优的低温加氢活性和加氢稳定性。

南岭成矿规律与百年勘查成果及新一轮找矿建议——《中国矿产地质志·南岭卷》研编

南岭成矿带是华南乃至全国最为重要且独具特色的成矿带之一,对其成矿规律的探索研究虽然历史悠久但每一次的成果总结都会推进新一轮找矿突破。笔者等在前人大量研究资料的基础上,对南岭成矿带的能源矿产(煤矿和铀矿)、有色金属矿产(钨、锡、钼、铋、铜、铅锌等)、贵金属矿产(金矿和银矿)、稀有金属和稀土金属矿产、非金属矿产(萤石)的成矿特征、时空分布规律进行了总结,并将南岭成矿带矿产按前寒武、加里东旋回、华力西旋回、印支旋回、燕山旋回及喜马拉雅旋回6个旋回厘定出21个矿床成矿系列和23个矿床成矿亚系列,为区域矿产勘查工作部署及成矿预测奠定了理论基础。为了保障能源资源安全,笔者等提出了南岭成矿带区块出让的原则性意见和柿竹园、香花岭、崇余犹、富贺钟、坪宝、三南等15个大型资源基地找矿的建议,为新一轮找矿突破战略行动提供了科学指导。