Farmers' preferences for adopting on-farm concentration of raw milk: Results from a discrete choice experiment in Germany

Milk concentrates are used in the manufacturing of dairy products such as yogurt and cheese or are processed into milk powder. Processes for the nonthermal separation of water and valuable milk ingredients are becoming increasingly widespread at farm level. The technical barriers to using farm-manufactured milk concentrate in dairies are minimal, hence the suspicion that the practice of on-farm raw milk concentration is still fairly uncommon for economic reasons. This study, therefore, set out to investigate farmers' potential willingness to adopt a raw milk concentration plant. The empirical analysis was based on discrete choice experiments with 75 German dairy farmers to identify preferences and the possible adoption of on-farm raw milk concentration. The results showed that, in particular, farmers who deemed the current milk price to be insufficient viewed on-farm concentration using membrane technology as an option for diversifying their milk sales. We found no indication that adoption would be impeded by a lack of trustworthy information on milk processing technologies or capital.     

Probabilistic learning on manifolds (PLoM) with partition

The probabilistic learning on manifolds (PLoM) introduced in 2016 has solved difficult supervised problems for the “small data” limit where the number N of points in the training set is small. Many extensions have since been proposed, making it possible to deal with increasingly complex cases. However, the performance limit has been observed and explained for applications for which N is very small and for which the dimension of the diffusion-map basis is close to N. For these cases, we propose a novel extension based on the introduction of a partition in independent random vectors. We take advantage of this development to present improvements of the PLoM such as a simplified algorithm for constructing the diffusion-map basis and a new mathematical result for quantifying the concentration of the probability measure in terms of a probability upper bound. The analysis of the efficiency of this extension is presented through two applications.     

一种新的密码本原:棘轮密钥交换的定义、模型及构造

在传统密码学应用中,人们总假定终端是安全的,并且敌手只存在于通信信道上。然而,主流的恶意软件和系统漏洞给终端安全带来了严重和直接的威胁和挑战,例如容易遭受存储内容被病毒破坏、随机数发生器被腐化等各种攻击。更糟糕的是,协议会话通常有较长的生存期,因此需要在较长的时间内存储与会话相关的秘密信息。在这种情况下,有必要设计高强度的安全协议,以对抗可以暴露存储内容和中间计算结果(包括随机数)的敌手。棘轮密钥交换是解决这一问题的一个基本工具。文中综述了密码本原——棘轮密钥交换,包括单向、半双向和双向等棘轮密钥交换的定义、模型及构造,并展望了棘轮密钥交换的未来发展趋势。     

电商平台产品共同购买网络的影响因素研究

共同购买网络的推荐系统应用越加广泛，仅基于网络内生结构变量研究其共同购买链接的经济意义已有局限，故加入网络口碑这一外生变量，进行更全面的分析。采用了社会网络方法中指数随机图模型进行建模，主要围绕产品销售量、产品入度、差评率和评论数4个方面因素，探究其对共同购买网络中共同购买链接形成的影响。结果显示，销售量、产品入度和评论数对共同购买链接形成的影响呈正比关系，而差评率则会显著地降低产品共同购买的几率。该指数随机图构建出的共同购买网络为在线电商平台管理网络口碑和推荐系统优化设计提供有益参考。     

普通食用油检验关键点分析

以实际案例和文献资料收集为基础,主要围绕食用油检测从采样到结果判定一系列过程中可能涉及的操作风险点进行分析,并对部分典型检验指标(苯并(a)芘、塑化剂、抗氧化剂、残留溶剂、过氧化值、酸价、辣椒素、黄曲霉毒素B1)进行分析,介绍了分析过程中实验室环境、接触器具、试剂、样本本底、特殊基质干扰、指标稳定性等对实验结果有关键影响的因素,并针对具体问题提出解决措施,旨在为食用油检验风险防控提供技术支撑。     

HACCP在浓香菜籽油生产中的应用

为了保障浓香菜籽油的产品质量安全,采用HACCP体系对浓香菜籽油生产全过程进行生物、物理、化学的危害分析,确定关键控制点,制定预防措施,并对生产环节进行有效监控,制定纠偏措施,做好记录管理,为浓香菜籽油的安全生产提供借鉴。     

超精密气体静压系统节流器法向随机微振动研究

以无气腔平面节流器为研究对象,对节流器流固耦合法向随机微振动进行了理论仿真和实验研究。受限于节流器厚度与气膜厚度尺寸的差异和输入初始边界条件,建立了节流器的COMSOL仿真简化模型,对节流器-气膜微流场进行双向流固耦合数值模拟。仿真结果表明,节流器的法向随机微振动幅值关于节流器中心对称,且由中心向边缘逐渐增大;微振动幅值随气体入口流速的增大而增大。实验采用纳米级激光测振仪,依次测量供气压力为0.1,0.2,…,0.5 MPa时尺寸为75 mm×50 mm×14 mm的HEXAGON双环联结型节流器多个不同位置的法向振动,实验结果表明,法向随机微振动幅值分布特性与仿真结果一致,关于节流器中心对称,且由中心向边缘逐渐增大,验证了节流器法向微振动的"跷跷板"振动形式;在0.5 MPa供气压力下,边缘振动幅值超过1 nm。对实验数据进行功率谱密度分析,结果表明不同供气压力下法向随机微振动均在9.4 kHz和10.6 kHz处产生较大功率,可认为与节流器-气膜流固耦合系统的固有频率有关。研究结果有效地揭示了节流器法向随机微振动的特性,为气体静压系统避开随机共振区、优化气体静压系统的设计提供了理论指导。     

Stochastic collocation-based nonlinear analysis of concrete bridges with uncertain parameters

This paper focuses on the stochastic response of concrete bridges considering uncertainty in bearing and abutment stiffness. A multi-span simply supported bridge with concrete girders is selected. A 3D-dimensional model is prepared, and nonlinear response history analyses are performed. For the numerical dynamic simulation, the non-sampling stochastic method based on generalized polynomial chaos (gPC) expansion is utilised. The uncertain parameters include the vertical and shear stiffness of bearings and the lateral stiffness of abutments are presented by the truncated gPC expansions. Furthermore, the system response such as base shear, acceleration, velocity and displacement in different columns is presented by gPC expansion with unknown deterministic coefficients. The stochastic Galerkin projection is employed to calculate a set of deterministic equations. A non-intrusive solution, as a set of collocation points, determines the unknown gPC coefficients of the system response and the results are compared with Monte Carlo simulations. The key advantage of spectral discretization is the combination of the mentioned method with the spatial discretization, e.g. finite element model. This study also emphasises the accuracy in results and time efficiency of the proposed non-sampling method for uncertainty quantification of stochastic systems comparing to sampling procedure (e.g. Monte Carlo simulation).     

采动覆岩卸荷膨胀累积效应

地下煤层开采引起的岩层运动是一系列安全和环境问题的根源,研究采动岩层运动规律是安全、高效、绿色开采的重要基础。通过对岩层运动过程的研究,揭示了采动覆岩卸荷膨胀累积效应及其对岩层运动规律的影响机制。研究表明:采动覆岩经历了卸荷膨胀与再压实的动态过程。受关键层结构控制,上覆岩层由下向上成组破断运动,关键层破断前,阻断了上覆载荷向下方岩层的传递,导致其因卸荷而产生膨胀,包括碎胀与弹性膨胀。随着关键层破断高度增加,覆岩卸荷高度同步增大,因卸荷而膨胀的岩层总厚度不断增大;同时卸荷煤岩也受到已破断关键层载荷的压实作用,从而造成覆岩卸荷膨胀总量的不断变化。将这种覆岩卸荷膨胀总量随覆岩卸荷高度动态变化的现象定义为采动覆岩卸荷膨胀累积效应,进而建立了理论模型,并通过淮北海孜煤矿巨厚火成岩下采煤覆岩裂隙实测进行了验证。结果表明,采动覆岩卸荷膨胀累积效应对采动岩层运动规律产生了重要影响,如影响覆岩关键层下离层量,影响覆岩关键层贯通破断的高度,影响不同开采条件的地表下沉系数等。采动覆岩卸荷膨胀累积效应改变了对离层存在形式的传统认识,该效应的存在导致关键层下最大离层量一般小于采高的10%,覆岩可注浆充填空间并非传统认识上的“离层区”,而主要是注浆充填压力“压实”作用下将覆岩卸荷累积膨胀所转化出的那部分空间,该发现指导了覆岩隔离注浆充填绿色开采技术的创新研发及其在建筑物压煤开采中的成功实践。