Effect of low-degree astigmatism on the objective visual quality

AIM:To evaluate the effect of low-degree astigmatism on objective visual quality through the Optical Quality Analysis System(OQAS).METHODS:This study enrolled 46 participants(aged 23 to 30y,90 eyes)with normal or corrected-to-normal vision.The cylindrical lenses(0,0.5,0.75,1.0,and 1.25 D)were placed at the axial direction(180°,45°,90°,and 135°)in front of the eyes with the best correction to form 16 types of regular low-degree astigmatism.OQAS was used to detect the objective visual quality,recorded as the objective scattering index(OSI),OQAS values at contrasts of 100%,20%,and 9%predictive visual acuity(OV100%,OV20%,and OV9%),modulation transfer function cut-off(MTFcut-off)and Strehl ratio(SR).The mixed effect linear model was used to compare objective visual quality differences between groups and examine associations between astigmatic magnitude and objective visual quality parameters.RESULTS:Apparent negative relationships between the magnitude of low astigmatism and objective visual quality were observed.The increase of OSI per degree of astigmatism at 180°,45°,90°,and 135°axis were 0.38(95%CI:0.35,0.42),0.50(95%CI:0.46,0.53),0.49(95%CI:0.45,0.54)and 0.37(95%CI:0.34,0.41),respectively.The decrease of MTFcut-off per degree of astigmatism at 180°,45°,90°,and 135°axis were-10.30(95%CI:-11.43,-9.16),-12.73(95%CI:-13.62,-11.86),-12.75(95%CI:-13.79,-11.70),and-9.97(95%CI:-10.92,-9.03),respectively.At the same astigmatism degree,OSI at 45°and 90°axis were higher than that at 0°and 135°axis,while MTFcut-off were lower.CONCLUSION:Low astigmatism of only 0.50 D can significantly reduce the objective visual quality.

Grindability Evaluation of Ultrasonic Assisted Grinding of Silicon Nitride Ceramic Using Minimum Quantity Lubrication Based SiO_(2)Nanofluid

Minimum quantity Lubrication(MQL)is a sustainable lubrication system that is famous in many machining systems.It involve the spray of an infinitesimal amount of mist-like lubricants during machining processes.The MQL system is affirmed to exhibit an excellent machining performance,and it is highly economical.The nanofluids are understood to exhibit excellent lubricity and heat evacuation capability,compared to pure oil-based MQL system.Studies have shown that the surface quality and amount of energy expended in the grinding operations can be reduced considerably due to the positive effect of these nanofluids.This work presents an experimental study on the tribological performance of SiO_(2)nanofluid during grinding of Si_(3)N_(4)ceramic.The effect different grinding modes and lubrication systems during the grinding operation was also analyzed.Different concentrations of the SiO_(2)nanofluid was manufactured using canola,corn and sunflower oils.The quantitative evaluation of the grinding process was done based on the amount of grinding forces,specific grinding energy,frictional coefficient,and surface integrity.It was found that the canola oil exhibits optimal lubrication performance compared to corn oil,sunflower oil,and traditional lubrication systems.Additionally,the introduction of ultrasonic vibrations with the SiO_(2)nanofluid in MQL system was found to reduce the specific grinding energy,normal grinding forces,tangential grinding forces,and surface roughness by 65%,57%,65%,and 18%respectively.Finally,regression analysis was used to obtain an optimum parameter combinations.The observations from this work will aid the smooth transition towards ecofriendly and sustainable machining of engineering ceramics.

The Effect of Mineral Composition and Quantity of Fines on the Atterberg Limits and Compaction Characteristics of Soils

Because of the various elements that come into play in natural soil formation, the impact of varied proportions of mineral composition and fines amount on Atterberg limits and compaction characteristics of soils is not well known. Three distinct soil samples were used in this investigation. The findings indicated the effect of varied mineral composition proportions and fines amount on the liquid limit, plastic limit, and plasticity index as assessed by the Casagrande test and hand-rolling method. The fluctuation of maximum dry density and optimal moisture content with these three soils has also been studied. Furthermore, correlations were established to indicate the compaction parameters and the amount of minerals and particles in the soil. The data show that the mineral content of the soil has a direct impact on the Atterberg limits and compaction characteristics. Soils containing larger percentages of expansive minerals, such as montmorillonite, have more flexibility and volume change capability. Mineral composition influences compaction parameters such as maximum dry density, ideal water content, axial strain, and axial stress. Soils with a larger proportion of fines, such as Soil 2 and Soil 3, have stronger flexibility and lower compaction qualities, with higher ideal water content and lower maximum dry density. Soil 1 has moderate flexibility and intermediate compaction qualities due to its low fines percentage. The effect of different mineral compositions and fines on the Atterberg limits and compaction characteristics of soils can be used to predict the behavior of compacted soils encountered in engineering practices, reducing the time and effort required to assess soil suitability for engineering use.

Objective Model Selection in Physics: Exploring the Finite Information Quantity Approach

Traditional methods for selecting models in experimental data analysis are susceptible to researcher bias, hindering exploration of alternative explanations and potentially leading to overfitting. The Finite Information Quantity (FIQ) approach offers a novel solution by acknowledging the inherent limitations in information processing capacity of physical systems. This framework facilitates the development of objective criteria for model selection (comparative uncertainty) and paves the way for a more comprehensive understanding of phenomena through exploring diverse explanations. This work presents a detailed comparison of the FIQ approach with ten established model selection methods, highlighting the advantages and limitations of each. We demonstrate the potential of FIQ to enhance the objectivity and robustness of scientific inquiry through three practical examples: selecting appropriate models for measuring fundamental constants, sound velocity, and underwater electrical discharges. Further research is warranted to explore the full applicability of FIQ across various scientific disciplines.

Low-degree toroidal modes from the Sumatra-Andaman event observed by superconducting gravimeters

The complex frequencies of the low-degree toroidal modes are helpful in constraining the mantle structure.In the early years,the traditional method to detect the low-degree toroidal modes is seismic approach,which is primarily limited by the horizontal noise of seismometers.Recently,it has been proved that gravity method is competitive.Therefore,we re-estimated or newly estimated the complex frequencies of the toroidal modes below 1.5 mHz excited by the 2004 Sumatra-Andaman event using gravity method in this paper.The results show that(1)The quality factors of0 T5-0 T9 and1 T2-1 T3 are estimated from superconducting gravity data for the first time;(2)The estimated frequencies and quality factors for0 T2-0 T9 and1 T2-1 T3 are consistent with those provided by previous publications,which verifies the correctness and effectiveness of our estimations;(3)The maximum difference of frequencies between our results and those from CPREM is on the order of 0.01 mHz and the maximum difference of quality factors is at the level of 10.

The Spectral Analysis and Application of Low-degree Modified Spheroidal Hotine Kernel

The traditional spheroidal kernel results in the spectrum leakage,and the utilization rate of the removed degrees of the measured data is low.Hence,a kind of spheroidal kernel whose high-and low-degrees are both modified is introduced in this research,which is exampled by the Hotine kernel.In addition,the low-degree modified spheroidal kernel is proposed.Either cosine or linear modification factors can be utilized.The modified kernel functions can effectively control the spectrum leakage compared with the traditional spheroidal kernel.Furthermore,the modified kernel augments the contribution rate of the measured data to height anomaly in the modified frequency domain.The experimental results show that the accuracy of the quasi-geoid by the cosine or linear low-degree modified kernel is higher than that by the traditional spheroidal kernel.And the accuracy equals the accuracy of the quasi-geoid using the spheroidal kernel with high-and low-degrees modified approximately when the low-degree modification bandwidths of these two kinds of kernels are the same.Since the computational efficiency of the low-degree modified kernel is much higher,the low-degree modified kernel behaves better in constructing the(quasi-)geoid based on Stokes-Helmert or Hotine-Helmert boundary-value theory.

Tribological Mechanism of Graphene and Ionic Liquid Mixed Fluid on Grinding Interface under Nanofluid Minimum Quantity Lubrication

Graphene has superhigh thermal conductivity up to 5000 W/(m·K),extremely thin thickness,superhigh mechanical strength and nano-lamellar structure with low interlayer shear strength,making it possess great potential in mini-mum quantity lubrication(MQL)grinding.Meanwhile,ionic liquids(ILs)have higher thermal conductivity and better thermal stability than vegetable oils,which are frequently used as MQL grinding fluids.And ILs have extremely low vapor pressure,thereby avoiding film boiling in grinding.These excellent properties make ILs also have immense potential in MQL grinding.However,the grinding performance of graphene and ionic liquid mixed fluid under nano-fluid minimum quantity lubrication(NMQL),and its tribological mechanism on abrasive grain/workpiece grinding interface,are still unclear.This research firstly evaluates the grinding performance of graphene and ionic liquid mixed nanofluids(graphene/IL nanofluids)under NMQL experimentally.The evaluation shows that graphene/IL nanofluids can further strengthen both the cooling and lubricating performances compared with MQL grinding using ILs only.The specific grinding energy and grinding force ratio can be reduced by over 40%at grinding depth of 10μm.Work-piece machined surface roughness can be decreased by over 10%,and grinding temperature can be lowered over 50℃at grinding depth of 30μm.Aiming at the unclear tribological mechanism of graphene/IL nanofluids,molecular dynamics simulations for abrasive grain/workpiece grinding interface are performed to explore the formation mechanism of physical adsorption film.The simulations show that the grinding interface is in a boundary lubrication state.IL molecules absorb in groove-like fractures on grain wear flat face to form boundary lubrication film,and graphene nanosheets can enter into the grinding interface to further decrease the contact area between abrasive grain and workpiece.Compared with MQL grinding,the average tangential grinding force of graphene/IL nanofluids can decrease up to 10.8%.The interlayer shear effect and low interlayer shear strength of graphene nanosheets are the principal causes of enhanced lubricating performance on the grinding interface.EDS and XPS analyses are further carried out to explore the formation mechanism of chemical reaction film.The analyses show that IL base fluid happens chemical reactions with workpiece material,producing FeF_(2),CrF_(3),and BN.The fresh machined surface of workpiece is oxidized by air,producing NiO,Cr_(2)O_(3) and Fe_(2)O_(3).The chemical reaction film is constituted by fluorides,nitrides and oxides together.The combined action of physical adsorption film and chemical reaction film make graphene/IL nano-fluids obtain excellent grinding performance.

Tribological Performance of Different Concentrations of Al_(2)O_(3)Nanofluids on Minimum Quantity Lubrication Milling

Nanofluid minimum quantity lubrication(NMQL)is a green processing technology.Cottonseed oil is suitable as base oil because of excellent lubrication performance,low freezing temperature,and high yield.Al_(2)O_(3)nanoparticles improve not only the heat transfer capacity but also the lubrication performance.The physical and chemical proper-ties of nanofluid change when Al_(2)O_(3)nanoparticles are added.However,the effects of the concentration of nanofluid on lubrication performance remain unknown.Furthermore,the mechanisms of interaction between Al_(2)O_(3)nanoparti-cles and cottonseed oil are unclear.In this research,nanofluid is prepared by adding different mass concentrations of Al_(2)O_(3)nanoparticles(0,0.2%,0.5%,1%,1.5%,and 2%wt)to cottonseed oil during minimum quantity lubrication(MQL)milling 45 steel.The tribological properties of nanofluid with different concentrations at the tool/workpiece interface are studied through macro-evaluation parameters(milling force,specific energy)and micro-evaluation parameters(surface roughness,micro morphology,contact angle).The result show that the specific energy is at the minimum(114 J/mm^(3)),and the roughness value is the lowest(1.63μm)when the concentration is 0.5 wt%.The surfaces of the chip and workpiece are the smoothest,and the contact angle is the lowest,indicating that the tribological proper-ties are the best under 0.5 wt%.This research investigates the intercoupling mechanisms of Al_(2)O_(3)nanoparticles and cottonseed base oil,and acquires the optimal Al_(2)O_(3)nanofluid concentration to receive satisfactory tribological properties.

Qualia Role-Based Quantity Relation Extraction for Solving Algebra Story Problems

A qualia role-based entity-dependency graph(EDG)is proposed to represent and extract quantity relations for solving algebra story problems stated in Chinese.Traditional neural solvers use end-to-end models to translate problem texts into math expressions,which lack quantity relation acquisition in sophisticated scenarios.To address the problem,the proposed method leverages EDG to represent quantity relations hidden in qualia roles of math objects.Algorithms were designed for EDG generation and quantity relation extraction for solving algebra story problems.Experimental result shows that the proposedmethod achieved an average accuracy of 82.2%on quantity relation extraction compared to 74.5%of baseline method.Another prompt learning result shows a 5%increase obtained in problem solving by injecting the extracted quantity relations into the baseline neural solvers.

专利权质押与企业创新

本文利用中国企业专利调查数据,在微观层面定量考察了专利权质押对企业创新的影响。研究发现,专利权质押显著提升了企业的创新能力,其积极效应不仅体现在以专利总数为代表的研发产出数量上,而且体现在以发明专利占比为代表的研发产出质量上。专利权质押显著增强了企业的研发激励,提高了企业的研发经费占比和研发人员占比。调节效应分析表明,研发职务奖励有助于扩大发明专利质押对企业创新产出的促进作用,但研发周期在一定程度上会抑制专利质押对企业创新产出的促进作用。异质性分析表明,专利权质押对不同所有制企业和不同规模企业的研发产出数量、研发产出质量和研发投入均有显著影响,但相比之下,专利权质押对国有企业和大企业创新产出数量的正面影响更大,对非国有企业和小企业研发投入和专利质量结构改善更为明显。本文研究结论为深入开展专利权质押试点和提升企业创新能力提供了一定的政策启示。

人口“数量-质量”转换、经济增长与养老金可持续性研究

党的二十大报告中强调要发展多层次、多支柱、可持续的养老保险体系,但随着人口老龄化问题加剧,劳动占比下降、老年抚养比上升等问题开始影响养老制度可持续性。本文从人口数量-质量转换视角,先建立数理模型研究人口结构变动对经济增长和养老金可持续性的影响,再通过数值模拟分析不同老龄化程度下人口结构变化的宏观经济结果,最后以2001—2022年全国30个省、直辖市、自治区的省级面板数据为样本(剔除西藏)进行实证检验。结果显示:(1)人口数量结构转变对经济增长存在显著的负向影响,人口质量结构转变对经济增长存在显著的正向影响;人口质量提高会缓解人口数量下降给经济增长带来的冲击,即人口数量-质量转换可以促进经济增长。(2)人口质量提高通过促进经济增长增强养老金可持续性。(3)人口数量-质量转换可以增强养老金可持续性。无论以教育投资为代表的人力资本水平提高是父代主动的、有意识的行为,还是行政性政策的结果,人口质量的提高都有利于促进经济增长和维持养老金收支平衡。

企业数字化转型与政府数字化治理对创新“提质增量”的协同影响机制研究

基于数字化赋能理论,以2016—2021年396家高技术制造业上市公司为样本,从微观和宏观两个维度出发探究企业数字化转型和政府数字化治理赋能企业创新“提质增量”的作用机理,并采用多项式回归、响应面分析及块变量分析技术剖析其交互协同机制,明晰数字经济推动企业创新“提质增量”的多维路径,研究结果表明:(1)企业数字化转型能促进企业创新“增量”,不能促进创新“提质”;政府数字化治理能促进企业创新“提质增量”。(2)企业数字化转型和政府数字化治理存在交互协同效应,能显著促进企业创新“提质增量”,并且在平衡状态下,二者处于双高水平时企业创新表现更好,在非平衡状态下,呈现政府数字化治理的“主导逻辑”。(3)政企之间的交互协同可以通过降低管理性交易成本,缓解信息不对称性来促进企业创新“提质增量”。研究结论丰富了数字经济与企业创新相关研究,为企业走出创新“轻质量、重数量”困境提供了新的路径,为政府部门落实数字经济政策和优化创新环境提供了新的参考。

太湖流域洪水与水量调度方案修订的认识与思考

太湖流域经济社会的快速发展对流域调度工作提出新的更高要求。回顾了《太湖流域洪水与水量调度方案》实施以来流域防洪与水量调度的实践,总结分析了方案修订背景、总体考虑以及修订的主要内容,并作出展望与思考。

智慧城市建设对企业绿色创新的影响——基于准自然实验的实证研究

基于2007—2020年A股上市公司与地级市的年度面板数据,运用多期双重差分法实证检验智慧城市试点政策对企业绿色创新的影响,研究发现:(1)智慧城市试点政策显著提升了企业绿色创新数量和绿色创新质量,且该结论经过PSM-DID及安慰剂等一系列稳健性检验后依然成立;(2)智慧城市试点政策通过增强城市财政支持、缓解企业融资约束进而促进企业绿色创新的“增量提质”;(3)微观层面异质性分析结果表明,智慧城市试点政策对成长期、非重污染企业绿色创新的“增量提质”作用更显著;宏观层面表明,试点政策对企业绿色创新的“增量提质”效应在低市场化进程、东中部地区企业中更加明显。

秸秆覆盖量和施氮量对陇中春小麦的产量效应模拟

为量化分析秸秆覆盖量和施氮量对旱地春小麦的产量效应和协同作用,在APSIM模型中,设置秸秆覆盖量和施氮量2因素5个变化梯度,组合交叉设计25个处理,利用模型模拟25个处理的春小麦产量;于2016—2018年在甘肃省定西市安定区开展小麦大田试验,得到早播(ESW)、正常播(NSW)、晚播(LSW)春小麦产量的实测值,利用APSIM模型模拟2016—2018年春小麦的产量,将模拟值与实测值进行对比,对模型的适用性和模拟精度进行分析;对春小麦产量与秸秆覆盖量、施氮量的耦合关系进行二次多项回归和通径分析,利用Matlab计算春小麦的最大产量及对应的秸秆覆盖量和施氮量。结果表明:不同处理下产量的模拟值与实测值均位于15%置信带内,模型模拟精度较高,归一化均方根误差值为4.64%~12.22%,表明该模型在研究区具有良好的适用性;秸秆覆盖量和施氮量的增长对春小麦的产量效应为正效应,相应关系表现为开口向下的二次抛物线变化关系;ESW、NSW和LSW模拟情景下,春小麦最大产量分别为3548.64、3149.59、2507.58 kg/hm^(2);ESW模式下,最佳秸秆覆盖量和施氮量分别为7062.04、194.91 kg/hm^(2);NSW模式下,最佳秸秆覆盖量和施氮量分别为8211.31、218.81 kg/hm^(2);LSW模式下,最佳秸秆覆盖量和施氮量分别为6215.15、162.01 kg/hm^(2)。

育龄收入、子女人力资本与代际经济支持——基于子女“数量—质量替代”视角

中国家庭中子女数量下降伴随着子女人力资本提升,即子女“数量—质量替代”效应,为改善家庭养老经济支持提供了新契机。使用中国家庭追踪调查数据,结合中介效应模型和两阶段最小二乘法,研究以子女“数量—质量替代”为机制,老年父母的育龄收入对子女经济支持数额的影响。研究发现:(1)家庭中子女数量向质量的转换有利于子女经济支持数额的提高;(2)增加父母育龄收入有利于促进子女数量向质量转换,从而提高子女经济支持数额;(3)对于没有参加养老保险、子女数量较少和来自城市的家庭,在子女“数量—质量替代”机制的作用下,育龄收入的增加提高子女经济支持数额的效应更强。因此,畅通并促进子女数量向质量的转换机制是改善家庭养老经济支持水平、缓解社会养老压力的有效途径;更合理的收入分配制度对完善家庭养老功能、促进中国养老事业可持续发展和提升老年人福祉具有重要意义。

胱抑素C冰冻人血清国家标准品的建立及溯源性研究

目的:对胱抑素C进行量值溯源性研究,研制胱抑素C冰冻人血清国家标准品,建立用于胱抑素C检测试剂盒准确度评价的质量评价标准,提升检验检测水平。方法:以人血清样本为原料进行无菌分装、制备胱抑素C冰冻人血清国家标准品,采用多实验室联合赋值的方法对胱抑素C国家标准品候选品进行赋值、标定,建立可溯源至国际标准物质ERM-DA471/IFCC的溯源链,并采用免疫比浊的方法对其均匀性、稳定性进行验证。结果:建立了包含2个水平量值的胱抑素C冰冻人血清国家标准品,水平1为(0.94±0.03)mg·L^(-1)(k=2),水平2为(3.52±0.09)mg·L^(-1)(k=2)。该国家标准品均匀性和稳定性良好。30天短期稳定性研究结果显示,室温条件下,国家标准品(水平1和水平2)可稳定5天;2~8℃条件下,水平1可稳定10天,水平2可稳定20天;-20℃条件下,水平1和水平2均至少可稳定30天。溯源准确性采用血清参考盘和临床血清样本进行验证,研究结果显示,该国家标准品和国际标准品ERM-DA471/IFCC具有良好的溯源性。结论:通过对胱抑素C进行量值溯源性研究,研制出胱抑素C冰冻人血清国家标准品(360046-202001),并获得批准向社会提供,可用于人血清中胱抑素C检测试剂盒正确度评价及临床实验室检测系统量值准确性评价。

人民币汇率变动与企业创新的“质”与“量”——基于产业链溢出效应

本文利用2000~2014年的中国工业企业数据库、海关贸易数据库、企业专利数据库以及2007年中国投入产出表,基于产业链视角验证了人民币升值对制造业企业创新的影响。研究结果表明,人民币升值能显著提高企业创新能力,并且产业链在其中发挥着异质性效果:企业会因其所处产业链位置表现出创新“量”与“质”的差异。人民币升值对上游企业创新质量的促进作用更强,而对创新数量的影响并不明显。机制分析发现:人民币升值带来的进口中间品增加会在产业链中形成行业间技术溢出效应以及行业内竞争效应,均对企业创新模式产生重要影响;上游企业在全产业链中表现出“质量引领效应”。本研究为企业在“双循环”发展格局下利用行业生产网络效应提高自身创新提供建设性方向。

初次和重复献血不足量特征及原因分析

目的:分析初次和重复不足量献血者的人群特征和相关影响因素,为进一步降低献血不足量的发生率提供依据。方法:回顾性调查2020年1月1日—2021年12月31日某市全血不足量献血者的献血资料,统计不足量献血者相关数据,比较初次和重复献血者不足量的原因。结果:本站全血献血者不足量发生率为1.03%,初次献血者发生率为1.52%,高于重复献血者0.59%,差异有统计学意义(χ^(2)=363.69,P<0.05);在初次献血者中年龄18~25岁不足量发生率为2.40%高于其他年龄组的1.22%、0.94%、0.89%、0,差异有统计学意义(χ^(2)=222.786,P<0.05);体重≤55 kg的发生率为1.89%高于体重>55 kg的发生率为1.40%,差异有统计学意义(χ^(2)=24.291,P<0.05);高校和集体献血不足量发生率最高,分别为2.81%和1.61%,差异有统计学意义(χ^(2)=176.890、12.693,P<0.05);目标献血量400 mL发生率为1.84%高于300 mL发生率为1.41%,差异有统计学意义(χ^(2)=18.916,P<0.05);初次与重复献血者发生不足量的原因由高到低排列顺序是一致的,主要原因是精神紧张和血流不畅,差异有统计学意义(χ^(2)=107.916、48.822,P<0.05)。结论:初次和重复献血者发生不足量的主要原因是精神紧张,重点关注初次献血者中年龄18~25岁、体重≤55 kg、目标血量400 mL的高校群体,应采取针对性预防措施,预防献血不足量的发生,减少血液报废和保障献血者安全。

基于语义分割的带式输送机煤料运输区域检测算法

针对煤炭运输过程中,经常无法保持煤炭在带式输送机上的运量均匀,使得带式输送机长时间全速运转而造成电能浪费和设备无效磨损的问题,提出一种基于语义分割的带式输送机煤料运输区域检测算法。该算法在DeeplabV3+的基础上,根据特征通道之间的相互依赖关系,引入注意力机制,使用不同扩张率的卷积核获得多种尺度的语义信息,来精确分割出煤炭在带式输送机的运输区域。实验结果表明,该算法平均交并比(Mean Intersection over Union,MIoU)相比于DeeplabV3+算法提高1.24百分点,能够有效精准地分割出煤料的运输区域,为煤量估计工作提供有效的保障。