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.

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.

临界温度下循环喷油量对柴油机冷起动和排放特性的影响

为探明循环喷油量对小型农用柴油机冷起动特性和排放性能的影响规律,同时寻求其临界温度下的最佳循环喷油量,该研究以一款直列双缸高压共轨柴油发动机为研究对象,利用环境模拟舱整机试验平台,通过多次预试验测得海拔2000 m下,该机不开启预热装置能够成功起动的临界温度为-5℃。在此工况下,采用3次喷射方式,通过改变主喷油量研究循环喷油量对该机冷起动特性和排放性能的影响。结果表明:较大或较小的循环喷油量均会导致柴油机冷起动时间增加,甚至起动失败;随着循环喷油量增大,冷起动时间先减小后增加,循环喷油量为20 mg时冷起动时间最短,且HC、CO排放峰值均最低,分别为12984和3008 mg/L;增大或减少循环喷油量均会导致HC和CO排放峰值增加。循环喷油量较大时,CO排放峰值显著增加,并且峰值出现时刻提前。改变循环喷油量对NOx排放峰值有较大影响,循环喷油量为30 mg时NOx排放峰值最小,为368 mg/L。综合考虑,海拔高度2000 m,环境温度-5℃工况下该柴油机起动的最佳循环喷油量为20 mg。研究结果可为柴油机冷起动特性和排放优化提供支撑。

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。

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。

皖南农村地区需水量特征分析及预测模型研究

需水量的准确预测对于提高农村地区水资源利用率、优化农饮水厂日常调度有着重要作用,然而现有预测算法面临农村部分地区可用历史数据少、质量差等问题,同时部分预测算法的计算负荷较高,无法有效适应农饮水厂运维环境。选取2021-2022年安徽省南部不同地区3处农饮水厂日供水量数据作为研究对象。经过特征分析发现,皖南农村地区日需水量存在季节性变化趋势明显而短期内波动较大的特点。针对该数据特点及实际计算需求,选取了使用网格搜索法优化后的ARIMA模型进行预测,并与SVR、LSTM、RF等模型进行对比分析。研究结果表明,使用网格搜索法的ARIMA模型可以更好地适应农饮水厂运维环境,利用其对于周期性、季节性数据较强的学习能力,对农饮水厂供水量变化趋势和规律进行准确预测,具有一定的普适性,且计算负荷明显优于其他方法。模型对比分析显示,ARIMA模型的预测精度最高,在3处农饮水厂测试集数据上的平均绝对百分比误差(MAPE)分别为1.827、1.454、2.714。

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。

电感耦合等离子体质谱法测定纹身贴中17种有害元素及其迁移量

建立电感耦合等离子体质谱法测定纹身贴中硼、铝、铬、锰、钴、镍、铜、锌、砷、硒、锶、镉、锡、锑、钡、汞和铅17种元素的分析方法。纹身贴样品经纯水湿润后,用刮刀取下覆在膜上的油墨,干燥后用微波消解法消解,以电感耦合等离子体质谱法测定纹身贴中17种元素含量。分别用模拟胃液和模拟汗液提取纹身贴中17种元素,以电感耦合等离子体质谱法测定17种元素的迁移量。汞元素的质量浓度在0~10μg/L范围内、其余16种元素的质量浓度在0~100μg/L范围内与质谱响应值具有良好的线性关系,相关系数均大于0.999,17种元素的检出限为0.001~0.397μg/kg,定量限为0.003~1.32μg/kg;迁移量检出限为0.0015~1.638μg/dm^(2),定量限为0.005~5.46μg/dm^(2)。纹身贴中17种有害元素及其在模拟胃液、模拟汗液中迁移量测定结果的相对标准偏差为2.9%~15.0%(n=7),样品加标回收率为80.0%~119.2%。该方法灵敏度高,适用于纹身贴中有害元素的测定。

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。

工业机器人、人力资本与就业——以纺织产业为例

工业机器人深度应用与就业协同发展成为产业高质量发展的重要内容。为探究如何以数智化转型带动高质量就业,本文基于2007—2019年中国31个省级行政区面板数据,构建固定效应模型,实证研究纺织产业工业机器人应用对就业的影响。结果显示,工业机器人应用一方面对就业数量产生了替代效应,另一方面提高了就业质量,人力资本水平的提升同时弱化了这两方面的作用。异质性检验显示,工业机器人应用对纺织产业平稳型和提高型发展省份、男性或低技能劳动者的就业数量替代效应更大;2013年以前工业机器人应用对就业数量的替代效应和2013年以后对就业质量的提升效应更显著。

不同化学添加剂对青贮玉米营养成分、发酵品质及微生物数量的影响

文章旨在研究不同化学添加剂对青贮玉米营养成分、发酵品质及微生物数量的影响。试验选取同批次收获的玉米秸秆,铡碎为1~2 cm。试验共分为4组,其中对照组喷洒清水,其余3组分别喷洒8 mL/kg的等量发酵抑制剂(盐酸、甲酸、乙酸),并记为盐酸组、甲酸组、乙酸组。常温真空青贮30 d后,分别取3份青贮玉米中间部位小样待测。结果 :(1)与对照组相比,盐酸组、甲酸组、乙酸组青贮玉米的粗蛋白质含量显著提高(P <0.05),乙酸组青贮玉米的酸性洗涤纤维含量显著降低(P <0.05)。(2)与对照组相比,盐酸组、甲酸组、乙酸组青贮玉米的pH值、氨态氮含量显著降低(P <0.05),乳酸含量显著提高(P <0.05),乙酸组青贮玉米的乙酸含量显著提高(P <0.05)。(3)与对照组相比,盐酸组、甲酸组、乙酸组青贮玉米的乳酸菌数量显著提高(P <0.05),酵母菌数量显著降低(P <0.05),乙酸组青贮玉米的好气性细菌数量显著降低(P <0.05)。结论 :在本试验条件下,不同化学添加剂均能改善青贮玉米的营养成分、发酵品质及微生物结构,其中以等量乙酸作为发酵抑制剂,效果最佳。

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。

城市群规划实施效果评估研究——以长株潭城市群为例

长株潭城市群经济发展对于湖南省以及中国中西部地区的发展至关重要,且该城市群规划实施的效果对其他城市群有重要借鉴意义。基于此,文章根据2000-2017年地级市面板数据,采用合成控制法,评估长株潭城市群规划实施后对城镇化和环境质量的影响。评估分析表明,长株潭城市群规划的实施推动了城市群城乡融合,在一定程度上促进了城镇化的进程,但对环境造成了一定的负面影响,其原因在于长株潭城市群内城市之间的非均衡发展。因此,城市群应着眼于制定合理规划,促进城市均衡发展,重点落实城乡融合和生态文明;各级政府应加强公共治理,强化监督和治理责任,以更好地实现城市群规划的既定目标。

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。

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)。

推动经济实现质的有效提升和量的合理增长的逻辑与路径

推动经济高质量发展,既需要实现质的有效提升,又需要实现量的合理增长。经济发展数量和质量是“一枚硬币的两面”,两者相互表征、相互反馈、相互转换,最终实现量质协同演化的高质量发展。从量质协同关系的角度观察中国经济发展实践,笔者发现:在经济加速阶段,中国经济发展数量和质量均有效提升,但是并未形成量质协同的正反馈机制;在经济减速阶段,中国经济发展数量和质量均面临下行压力,同时量质协同的负反馈机制逐渐显现;在转型发展阶段,面临经济转型与外生冲击的双重压力,宏观经济政策面临目标多元化难题,加剧了经济发展量质转型难度。推动经济实现质的有效提升和量的合理增长需要:优化宏观政策,推动实现质量效益型发展;深化供给侧结构性改革,提高供给质量;完善分配方式,提高消费需求质量;坚持“两个毫不动摇”,激发各类经营主体的内生动力和创新活力;增强国家能力,加快构建高水平社会主义市场经济体制。