Oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions via Prufer transformation

A class of Sturm-Liouville problems with discontinuity is studied in this paper.The oscillation properties of eigenfunctions for Sturm-Liouville problems with interface conditions are obtained.The main method used in this paper is based on Prufer transformation,which is different from the classical ones.Moreover,we give two examples to verify our main results.

Role of outdoor trees on pedestrian wind and thermal conditions around a pre-education building for sustainable energy management

Finding sustainable energy resources is essential to face the increasing energy demand.Trees are an important part of ancient architecture but are becoming rare in urban areas.Trees can control and tune the pedestrian-level wind velocity and thermal condition.In this study,a numerical investigation is employed to assess the role of trees planted in the windward direction of the building complex on the thermal and pedestrian wind velocity conditions around/inside a pre-education building located in the center of the complex.Compared to the previous studies(which considered only outside buildings),this work considers the effects of trees on microclimate change both inside/outside buildings.Effects of different parameters including the leaf area density and number of trees,number of rows,far-field velocity magnitude,and thermal condition around the main building are assessed.The results show that the flow velocity in the spacing between the first-row buildings is reduced by 30%-40% when the one-row trees with 2 m height are planted 15 m farther than the buildings.Furthermore,two rows of trees are more effective in higher velocities and reduce the maximum velocity by about 50%.The investigation shows that trees also could reduce the temperature by about 1℃around the building.

Research on shell-side heat and mass transfer with multi-component in LNG spiral-wound heat exchanger under sloshing conditions

The spiral-wound heat exchanger(SWHE) is the primary low-temperature heat exchanger for large-scale LNG plants due to its high-pressure resistance, compact structure, and high heat exchange efficiency. This paper studied the shell-side heat and mass transfer characteristics of vapor-liquid two-phase mixed refrigerants in an SWHE by combining a multi-component model in FLUENT software with a customized multicomponent mass transfer model. Besides, the mathematical model under the sloshing condition was obtained through mathematical derivation, and the corresponding UDF code was loaded into FLUENT as the momentum source term. The results under the sloshing conditions were compared with the relevant parameters under the steady-state condition. The shell-side heat and mass transfer characteristics of the SWHE were investigated by adjusting the component ratio and other working conditions. It was found that the sloshing conditions enhance the heat transfer performance and sometimes have insignificant effects. The sloshing condition is beneficial to reduce the flow resistance. The comprehensive performance of multi-component refrigerants has been improved and the improvement is more significant under sloshing conditions, considering both the heat transfer and pressure drop.These results will provide theoretical support for the research and design of multi-component heat and mass transfer enhancement of LNG SWHE under ocean sloshing conditions.

Impact of wetting-drying cycles and acidic conditions on the soil aggregate stability of yellow‒brown soil

Soil aggregate is the basic structural unit of soil,which is the foundation for supporting ecosystem functions,while its composition and stability is significantly affected by the external environment.This study was conducted to explore the effect of external environment(wetting-drying cycles and acidic conditions)on the soil aggregate distribution and stability and identify the key soil physicochemical factors that affect the soil aggregate stability.The yellow‒brown soil from the Three Gorges Reservoir area(TGRA)was used,and 8 wetting-drying conditions(0,1,2,3,4,5,10 and 15 cycles)were simulated under 4 acidic conditions(pH=3,4,5 and 7).The particle size distribution and soil aggregate stability were determined by wet sieving method,the contribution of environmental factors(acid condition,wetting-drying cycle and their combined action)to the soil aggregate stability was clarified and the key soil physicochemical factors that affect the soil aggregate stability under wetting-drying cycles and acidic conditions were determined by using the Pearson’s correlation analysis,Partial least squares path modeling(PLS‒PM)and multiple linear regression analysis.The results indicate that wetting-drying cycles and acidic conditions have significant effects on the stability of soil aggregates,the soil aggregate stability gradually decreases with increasing number of wetting-drying cycles and it obviously decreases with the increase of acidity.Moreover,the combination of wetting-drying cycles and acidic conditions aggravate the reduction in the soil aggregate stability.The wetting-drying cycles,acidic conditions and their combined effect imposes significant impact on the soil aggregate stability,and the wetting-drying cycles exert the greatest influence.The soil aggregate stability is significantly correlated with the pH,Ca^(2+),Mg^(2+),maximum disintegration index(MDI)and soil bulk density(SBD).The PLS‒PM and multiple linear regression analysis further reveal that the soil aggregate stability is primarily influenced by SBD,Ca^(2+),and MDI.These results offer a scientific basis for understanding the soil aggregate breakdown mechanism and are helpful for clarifying the coupled effect of wetting-drying cycles and acid rain on terrestrial ecosystems in the TGRA.

Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

Tailoring Classical Conditioning Behavior in TiO_(2) Nanowires:ZnO QDs-Based Optoelectronic Memristors for Neuromorphic Hardware

Neuromorphic hardware equipped with associative learn-ing capabilities presents fascinating applications in the next generation of artificial intelligence.However,research into synaptic devices exhibiting complex associative learning behaviors is still nascent.Here,an optoelec-tronic memristor based on Ag/TiO_(2) Nanowires:ZnO Quantum dots/FTO was proposed and constructed to emulate the biological associative learning behaviors.Effective implementation of synaptic behaviors,including long and short-term plasticity,and learning-forgetting-relearning behaviors,were achieved in the device through the application of light and electrical stimuli.Leveraging the optoelectronic co-modulated characteristics,a simulation of neuromorphic computing was conducted,resulting in a handwriting digit recognition accuracy of 88.9%.Furthermore,a 3×7 memristor array was constructed,confirming its application in artificial visual memory.Most importantly,complex biological associative learning behaviors were emulated by mapping the light and electrical stimuli into conditioned and unconditioned stimuli,respectively.After training through associative pairs,reflexes could be triggered solely using light stimuli.Comprehen-sively,under specific optoelectronic signal applications,the four features of classical conditioning,namely acquisition,extinction,recovery,and generalization,were elegantly emulated.This work provides an optoelectronic memristor with associative behavior capabilities,offering a pathway for advancing brain-machine interfaces,autonomous robots,and machine self-learning in the future.

Mixed D-vine copula-based conditional quantile model for stochastic monthly streamflow simulation

Copula functions have been widely used in stochastic simulation and prediction of streamflow.However,existing models are usually limited to single two-dimensional or three-dimensional copulas with the same bivariate block for all months.To address this limitation,this study developed a mixed D-vine copula-based conditional quantile model that can capture temporal correlations.This model can generate streamflow by selecting different historical streamflow variables as the conditions for different months and by exploiting the conditional quantile functions of streamflows in different months with mixed D-vine copulas.The up-to-down sequential method,which couples the maximum weight approach with the Akaike information criteria and the maximum likelihood approach,was used to determine the structures of multivariate Dvine copulas.The developed model was used in a case study to synthesize the monthly streamflow at the Tangnaihai hydrological station,the inflow control station of the Longyangxia Reservoir in the Yellow River Basin.The results showed that the developed model outperformed the commonly used bivariate copula model in terms of the performance in simulating the seasonality and interannual variability of streamflow.This model provides useful information for water-related natural hazard risk assessment and integrated water resources management and utilization.

The Impact of Physiotherapy Interventions on the Elderly Population with Mental Health Conditions at Chainama Hills College Hospital in Zambia. A Pre-Post Single Sample Study Design

Background: Physical functional decline is common among elderly individuals with mental disorders, worsening their symptoms. Physiotherapy interventions have shown some evidence in improving physical function and mental health outcomes in this population. This study aimed to assess the impact of physiotherapy interventions on the elderly with mental health conditions at Chainama Hills College Hospital in Zambia. Methods: A pre-post single sample design was used to track patient progress over six weeks, with 10 physiotherapy sessions. The study population (N = 30) comprised of all elderly individuals with mental health conditions, encompassing both men and women, who were hospitalized during the research period. The Katz Index of Activities of Daily Living and the six-minute walk test were evaluated before and after the intervention. The IBM SPSS version 26 was used to analyze data and results were presented as mean ± SD with a 95% confidence interval. The variables were described in terms of their mean, SD, and range. A significance level of 0.05 was used for a paired T-test to detect changes and multiple logistic regression was used to identify factors associated with mental health. Results: Following the intervention, the percentage of participants achieving full function and independence increased significantly to 96.7% from the initial 73.3%, supported by a 95% CI = [0.82 - 0.99]. There was also a notable decrease in the proportion of individuals experiencing moderate impairment, dropping from 26.7% to just 3.3%, with a corresponding 95% CI = [0.00 - 0.17]. Conclusion: The findings derived from this study illustrate an enhancement in the aspects of participants’ overall health and functional condition, including blood pressure, heart rate, and respiratory rate. Consequently, physiotherapy exercises can be employed as a tactic to ameliorate the functional status and physical well-being of older individuals afflicted with mental disorders in Zambia.

Existence of Entropy Solution for Degenerate Parabolic-Hyperbolic Problem Involving p(x)-Laplacian with Neumann Boundary Condition

We consider a strongly non-linear degenerate parabolic-hyperbolic problem with p(x)-Laplacian diffusion flux function. We propose an entropy formulation and prove the existence of an entropy solution.

Inverse Spectral Problem for Sturm-Liouville Operator with Boundary and Jump Conditions Dependent on the Spectral Parameter

In this paper, the inverse spectral problem of Sturm-Liouville operator with boundary conditions and jump conditions dependent on the spectral parameter is investigated. Firstly, the self-adjointness of the problem and the eigenvalue properties are given, then the asymptotic formulas of eigenvalues and eigenfunctions are presented. Finally, the uniqueness theorems of the corresponding inverse problems are given by Weyl function theory and inverse spectral data approach.

The Convergence Rate of Fréchet Distribution under the Second-Order Regular Variation Condition

In this article we consider the asymptotic behavior of extreme distribution with the extreme value index γ>0 . The rates of uniform convergence for Fréchet distribution are constructed under the second-order regular variation condition.

再生粗骨料混凝土应力-应变关系

再生粗骨料混凝土应力-应变关系是实现其材料到结构力学分析的桥梁纽带,成为再生粗骨料混凝土结构基础理论的基石。介绍了作者团队多年来在再生粗骨料混凝土应力-应变关系方面取得的研究进展:采用模型化再生粗骨料方法,研究了复杂界面过渡区对再生粗骨料混凝土破坏行为的影响,揭示了再生粗骨料混凝土细观损伤本质与演化机理;从静力作用到动力作用,系统地开展了不同工况下再生粗骨料混凝土应力-应变行为试验研究,探明了载荷条件对再生粗骨料混凝土应力与变形的影响规律并建立了相适应的力学与数学模型;进一步考虑再生粗骨料性能时空变异性,发现了再生粗骨料混凝土力学响应的概率分布特征,提出了再生粗骨料混凝土随机损伤本构关系;基于获得的本构模型,完成了再生粗骨料混凝土构件时变可靠度分析和结构动力非线性分析,为再生粗骨料混凝土在实际工程中的安全应用提供了理论支撑;提炼了相关研究结论并对未来研究工作进行了展望。

水资源-能源-粮食-生态系统耦合协调及驱动力分析

为加深对我国水资源、能源、粮食、生态系统协同演变趋势的认识,构建水资源-能源-粮食-生态多维系统指标体系,运用耦合协调度模型对我国2005—2020年水资源-能源-粮食-生态系统耦合协调度进行评价,并采用多因素归因分析法进行驱动力分析。结果表明:我国水资源-能源-粮食-生态系统耦合协调度从2005年的0.55增长到2020年的0.84,各地区耦合协调度从勉强协调发展水平过渡到中级协调发展水平,各子系统对耦合协调度上升的驱动分别经历了由粮食子系统到生态子系统再到水资源子系统主导的过程;能源子系统的贡献率虽然比较小,但是未来可能是各地区提升水资源-能源-粮食-生态系统多维系统协调发展水平的突破口。

鄂西渝东地区中-新生代构造变形及其对油气保存的制约

油气成藏跟构造息息相关,研究构造及油气保存条件在油气勘探中具有重要作用。研究了鄂西渝东地区断裂发育特征及构造样式的差异分布,划分了构造单元,描述了断裂、构造类型及演化,分析了构造对保存条件的影响。研究表明:鄂西渝东中扬子地块南部构造带西部中生代以来经历了多期盆-山耦合构造作用,构造变形强度大,发育基底卷入型和盖层滑脱型断层。提出了该复杂构造区油气保存条件评价的方法。评价认为齐岳山断层以西保存条件好于东侧,以万县复向斜的保存条件最好,其次为石柱复向斜。湘鄂西褶皱带以利川构造带保存条件最好,其次为恩施构造带,南北镇-桑植石门构造带最差。该研究成果在红星地区、宜恩地区页岩气、致密气、岩溶体油气勘探中的应用取得了较好的效果。

基于DEMATEL-ISM的水利工程EPC项目价值增值机理研究

采用设计-采购-施工(engineering-procurement-construction,EPC)总承包模式的水利工程项目日益增多,研究其价值增值机理有利于总承包方做好项目的价值管理。从水利工程EPC项目的价值链分析入手,基于文献和专家访谈得到23个价值增值影响因素。采用问卷调查方式得到各因素间的影响程度评分,用决策实验和评估实验(decision-making trial and evaluation laboratory,DEMATEL)法计算了各因素的中心度和原因度,结合解释结构模型(interpretative structural modeling,ISM)对数据进行分析,将价值增值因素划分为6类,构建了水利工程EPC项目价值增值的递阶模型,探究和揭示了项目价值增值的路径和机理。研究结果对水利工程EPC总承包方制订管理策略有一定启示作用。

二氧化碳-水-岩作用机理及微观模拟方法研究进展

系统综述CO_(2)-水-岩复杂作用机理、多孔介质反应输运(溶解、沉淀及沉淀运移)微观模拟、CO_(2)-水-岩系统微观模拟3个方面的研究进展,指出目前研究存在的主要问题并提出了关于未来研究方向的建议。CO_(2)注入储集层后,不仅存在常规渗流体系的流动和传质作用,还会产生溶解、沉淀及沉淀运移等特殊物理化学现象,其耦合作用导致多孔介质的孔渗参数变化规律复杂。孔隙尺度的微观渗流模拟,可以得到孔喉三维空间内的详细信息,且能显性观察到多孔介质流-固界面随反应的变化。目前研究主要在复杂作用机理解耦合、多矿物差异性反应表征、沉淀生成机理及表征(晶体成核和矿物脱落)、沉淀-流体相互作用模拟方法、多物理化学过程耦合渗流机制等方面存在局限。未来研究中,需要创新实验方法对“溶解—沉淀—沉淀运移”解耦合,提高矿物地球化学反应相关参数实验测试的准确度,在不同沉淀机理可靠表征的基础上,建立沉淀-流体相互作用模拟方法,并有机耦合各个物理化学过程,最终实现对CO_(2)-水-岩系统中“溶解—沉淀—沉淀运移”的耦合渗流模拟。

基于GC-IMS和GC-MS技术结合化学计量法分析干燥方式对香椿挥发性成分的影响

为研究干燥方式对香椿挥发性风味物质的影响,利用气相色谱-离子迁移谱技术(gaschromatography-ion mobility spectrometry,GC-IMS)和气相色谱-质谱联用技术(gas chromatography-mass spectrometry,GC-MS)、相对香气活性值(relative odor activity value,ROAV)对真空冷冻干燥、热泵干燥、热风干燥、微波真空干燥的香椿样品进行挥发性成分分析,并进一步结合化学计量方法主成分分析(principal component analysis,PCA)和偏最小二乘判别分析(partial least squares-discriminant analysis,PLS-DA),探究样品间挥发性成分的差异性。结果表明,通过GC-IMS检测到78个峰,鉴定出59种化合物。通过GC-MS鉴定出94种挥发性化合物,主要挥发性成分是硫化物、烯烃类和醛类。经过干燥后总挥发性化合物的含量显著降低。通过ROAV法确定了(E,Z)-二-1-丙烯基二硫化物、2-巯基-3,4-二甲基-2,3-二氢噻吩、正己醛、2-己烯醛、丁香酚等为香椿样品中关键香气化合物。PCA和PLS-DA结果表明,不同干燥方式的样品与新鲜样品有明显的分离,彼此之间也有明显的区别。鲜样和真空冷冻干燥样品为一组,其他3个干燥香椿样品为一组。根据变量投影重要性(variable importance in projection,VIP)得分共筛选出10种(VIP>1)标志挥发性化合物。干燥方式对香椿风味特性影响显著,真空冷冻干燥组与鲜样最为接近,考虑实际应用热泵干燥为香椿最适宜的脱水方式。本研究为热加工过程中风味品质控制提供一定的理论参考。

基于CFD-DEM的流-固耦合数值建模方法研究进展

随着土体渗流侵蚀研究的逐渐深入,对土颗粒流失和变形破坏机理的研究方法呈现出多尺度的特点。其中,计算流体力学-离散元耦合方法(CFD-DEM)为在细观尺度上研究流-固耦合相互作用对土体宏观力学特性的影响提供了一种行之有效的方法。针对CFD-DEM耦合方法在岩土工程领域应用现状,本文系统总结现有流-固耦合计算方法的优缺点,重点论述CFD-DEM耦合方法的建模策略,包括固相颗粒形状建模与粒间接触模型、流体相控制方程及参数计算方法,以及CFD-DEM耦合计算,并就相关问题进行深入探讨,最后提出了CFD-DEM耦合方法未来的发展方向。

老年急性脑梗死患者血清Del-1和IL-17水平变化及与梗死面积和预后的关系

目的 探究老年急性脑梗死(ACI)患者血清内皮发育调节基因-1(Del-1)、白细胞介素-17(IL-17)水平与脑梗死面积、病情严重程度及预后的关系。方法 回顾性收集2019-01-2021-12厦门大学附属东南医院收治的126例老年ACI患者(病例组)及105名健康体检者(对照组)的临床资料,根据脑梗死面积将病例组患者分为大面积梗死组(梗死最大直径>5 cm,n=14)、中面积梗死组(梗死最大直径3~5 cm,n=53)和小面积梗死组(梗死最大直径<3 cm,n=59);根据NIHSS评分分为重症组(NIHSS评分≥16分,n=13)、中症组(5分<NIHSS评分<15分,n=58)和轻症组(NIHSS评分≤5分,n=55);根据m RS评分分为预后良好组(mRS评分≤2分,n=81)和预后不良组(mRS评分>2分,n=45)。采用荧光免疫法检测血清Del-1、IL-17水平,受试者工作特征(ROC)曲线评估血清Del-1、IL-17水平预测老年ACI患者预后的价值。结果 病例组吸烟史比例、收缩压、舒张压、糖化血红蛋白、血清IL-17水平均高于对照组,血清Del-1水平低于对照组(P<0.05)。不同脑梗死面积患者血清Del-1水平比较,小面积梗死组>中面积梗死组>大面积梗死组;血清IL-17水平比较,小面积梗死组<中面积梗死组<大面积梗死组(P<0.05)。轻症组血清Del-1水平高于中症组、重症组(P<0.05),不同病情严重程度患者血清IL-17水平比较,重症组>中症组>轻症组(P<0.05)。预后良好组患者血清Del-1水平高于预后不良组,血清IL-17水平低于预后不良组(P<0.05)。ROC曲线分析显示,血清Del-1、IL-17预测ACI患者预后的AUC值分别为0.763、0.747(P<0.05)。结论 老年ACI患者血清Del-1水平较低,IL-17水平较高,二者与患者脑梗死面积、病情严重程度和预后关系密切,可作为预测老年ACI患者预后的可靠指标。

基于混合式教学的“教-学-评”一体化实验教学体系探索

实验能力是医学专业研究生的重要科研能力,实验能力的培养与实验教学的方法与质量密切相关。文章针对传统实验教学受到时间和空间限制且评价指标较为单一的现状,提出构建基于线上自主学习和现场实践相结合的“教-学-评”一体化实验教学体系,建立覆盖课前线上自主学习、课堂现场实践、课后作业提交与考核教学全过程的评价体系,以评促学,以评促教,通过评价反馈激发学生的学习热情,改进教学内容和方法,不断探索与完善实验教学体系,提高实验教学质量,以期为培养具有实践能力与创新精神的医学科研人才发挥积极作用。