价格支持政策对我国不同粮食作物播种面积变化的影响差异

［目的］文章评估了价格支持政策对不同粮食作物播种面积变化的平均效应与动态效应，并测度多种价格支持政策的交叉政策弹性。［方法］基于1998—2016年实施粮食价格支持政策省份面板数据，设立对照组，利用倾向得分匹配—双重差分方法（PSM DID）评估价格支持政策平均效应与动态效应，并构建粮食作物供给反应（Nerlove）模型测度价格支持政策的交叉政策弹性。［结果］（1）价格支持政策对水稻、小麦、玉米播种面积增加具有不同程度的推动作用，按大小依次为玉米>水稻>小麦，对大豆播种面积变化影响不显著； （2）价格支持政策持续时间越长，对水稻、玉米播种面积增加的推动作用越大，对小麦播种面积增加的推动作用较为稳定； （3）小麦、玉米播种面积变化主要来自自身价格支持政策，水稻播种面积变化除了受到自身价格支持政策影响外，还受到其他作物政策影响，大豆播种面积变化对玉米临储政策反应敏感，对自身价格支持政策反应不敏感。［结论］在制定粮食政策时既要区分政策及其持续性对不同粮食播种面积变化的影响差异，又要注意在同一地区实施多种粮食政策时，可能对不同作物产生交叉影响。     

COVID-19-induced layoff,survivors’ COVID-19-related stress and performance in hospitality industry: The moderating role of social support

The COVID-19 pandemic has hit the hospitality industry hard globally, resulting in millions of employees being laid off. Drawing upon the conservation of resources theory, this study aims to empirically examine how and when COVID-19-induced layoff influences employees’ in-role and extra-role performance in the hospitality industry. We tested this model by using field data collected from 302 employees and their supervisors in China across two waves. Results revealed that COVID-19-induced layoff increases survivors’ COVID-19-related stress, which in turn leads to decreased in-role and extra-role performance. The strength of these indirect effects is mitigated by perceived family support against COVID-19. Unexpectedly, perceived organizational support against COVID-19 intensifies these indirect effects. The theoretical and practical implications of this study are further discussed.     

创新驱动下中国区域高质量发展——基于平衡充分发展水平的门槛分析

创新驱动是破解中国区域不平衡不充分发展的突破口,是实现高质量发展的助推器。采用2003～2017年中国30个省市面板数据,运用全局参比Malmquist模型测度了中国区域高质量发展水平,并通过构建指标体系分别对中国各省市的平衡发展和充分发展水平进行了评价,然后通过门槛回归模型分析了在不同平衡和充分发展水平下创新驱动对于高质量发展的影响机制。结果发现：①区域高质量发展水平呈现出先下降后上升的变化趋势；②各省市平衡和充分发展水平均呈现上升趋势,但各省市之间的变化情况差异较大,有明显的空间集聚特征；③在不同的平衡及充分发展水平下,创新驱动对高质量发展的影响机制是不同的,当平衡充分发展水平较低时,创新驱动对高质量发展没有显著影响；当平衡充分发展达到一定水平时,创新驱动对高质量发展起到一定的促进作用；随着平衡充分发展水平的进一步提高,创新驱动对高质量发展的促进作用越来越大。     

Moral hazard and subsidized crop insurance

Along with adverse selection, moral hazard is one of the major hurdles that private and public insurance plans must contend with. Moral hazard occurs if risks are endogenous to a producer's behavior and if the insurer is unable to properly monitor the insured. We review the role of moral hazard in the US crop insurance program. We conduct an empirical analysis of one important aspect of the US crop insurance program—prevented planting. This provision provides indemnity payments if conditions are not suitable for planting. The program has been the subject of considerable controversy, especially during 2019, when the rate of claims is expected to be especially high. Because loss adjustors may encounter difficulties in assessing the weather conditions associated with prevented planting claims, the program is susceptible to moral hazard. We consider the extent to which prevented planting claims may be endogenous to prices. We find significant evidence of moral hazard. The likelihood of prevented planting claims increases as the expected market price decreases or as fertilizer costs increase for corn and soybeans in the Prairie Pothole Region and for grain sorghum and cotton in all states.     

一种基于Radon变换的微表情识别算法

微表情是人们处在一些与平时生活环境不同的高强度环境下试图控制和掩饰的情感表现，也是一种不曾意识到的瞬时脸部表情,持续时间短，强度弱。为了提高其准确率，提出了基于Radon变换的微表情识别算法。首先，对数据库中的视频序列进行灰度归一化、尺寸归一化和二维主成分分析法（Two-dimensional Principal Component Analysis，2DPCA）降维预处理，使用光流法对降维后图像提取运动特征；然后使用Radon变换算法对光流图像进行处理，得到对应微表情的特征值和特征图像；最后使用支持向量机进行微表情分类识别。实验结果表明，使用Radon变换后得到的微表情特征图像得到了较好的识别效果，在微表情数据集CASME和CASMEⅡ上识别率分别为81.48%和82.17%，通过与选取的其他方法对比说明了该方法具有更好的识别性能。     

结合新型模糊支持向量机和证据理论的多传感器水质数据融合

在多传感器水质数据融合领域，证据理论是有效的数据融合方法之一，但基本概率分配一般不易确定，从而使数据融合能力难以有效发挥。支持向量机是统计学习理论之上的高级分类算法，具有普适性和全局优化等特点，但输出的基本概率分配有待进一步提高。提出了一种基于证据理论和新型模糊支持向量机相结合的数据融合方法，通过建立基于分类超平面距离的模糊隶属度，训练模糊支持向量机提高传统支持向量机的基本概率分配，并结合证据理论进行海河水质数据融合。通过证据理论分别结合支持向量机和模糊综合评价法与上述方法进行对比实验，经精度、平均绝对百分误差、均方根误差等指标验证，精度提高10.5%，表明所提方法是一种可靠的多传感器的水质融合方法，较其他方法具有更高的融合精度。     

一种利用机器学习优化MIMO窃听信道天线选择的方法

为保障多输入多输出窃听信道系统中信息传输的保密性，提出了一种基于机器学习的天线选择方案。首先利用机器学习解决分类问题准确率高、处理大数据高效这一优势，设计了基于奇异值分解的特征值提取、基于信干噪比的标签赋值方案，建立了k最近邻分类器和逻辑回归分类器选择最优天线最大化保密性能（可达保密速率和保密中断概率）。与传统天线选择方案相比，所提方案获得了几乎一致的保密性能，并且大幅降低了系统的选择复杂度和误比特率。     

Community supported agriculture membership: The benefits of spousal involvement

Fresh vegetables originating from alternative food networks (AFNs) are an increasingly popular choice all over the world. Being part of an AFN frequently redefines consumption and participation of family members in food‐related activities. Community Supported Agriculture (CSA) is a type of AFN, providing increased access to produce in a form of risk‐sharing model between farmers and consumers, which at the same time influences organization of household resources. Thus, not only the given member of a CSA, but also his/her spousal activities in household processes should be taken in account. It is clear that entering into CSA significantly affects lifestyles and frequently requires a great deal of adaptation, possibly leading to a crisis of whether to stay within the CSA or cease membership. The objective of this study was to reveal how spouses influence CSA membership. Using an explorative design, this study has identified three emerging patterns of spousal influence: coherent, integrative and neutral/antagonistic. The spousal influence on CSA membership may represent partner activities regarding food issues but also has an effect on food preparation and culinary choices at home. Our findings suggest that membership in CSA presents challenges and thus spousal support is crucial in the long term. As a consequence, spousal influence should be examined in relation to CSA participation. Inconveniences associated with CSA membership could be avoided by providing more information about the importance of spousal support.     

A cellular automata-based land-use model as an integrated spatial decision support system for urban planning in developing cities: The case of the Bogotá region

Bogotá and the 17 neighboring municipalities make up one of the biggest metropolitan areas in Latin America. However, despite strong functional interactions within the area, there is no official government body at this level in charge of coordinating authorities and providing solutions to the wide variety of issues arising in the regional urban land system. Aiming at providing an insight on future land-use developments linked to new transport infrastructures and at offering a tool to support territorial decision-making, this paper presents a cellular automata-based (CA) model based in Metronamica® software, that allows testing different scenarios based on potential land-use policies, environmental suitability and transport alternatives.There has not been, so far, an urban planning tool that accounts for the complexities of this region. CA-based land-use simulations constitute a useful approach to understanding the impacts of urban planning policies and regulations. This tool can help to improve inter-territorial and inter-institutional coordination, which through planning and management policies seek a spatially integrated development, with a long-term perspective.The CA-based model proposed was calibrated to reproduce land-use changes between 2007 and 2016 using different methods and indicators. The model was used to simulate and analyze eight scenarios with different policy directions of transport infrastructure in the future of the region. The results of the simulations reflect the dynamics of territorial occupation. The calibration indices in the experiment indicate a high degree of suitability for the CA Bogotá model, proving its effectiveness and potential as a useful tool for decision-making. The results show that occupation scenarios with restricted developable zones within the city, tend to have the greater dispersion rate in the study area, compared to scenarios where land development plans are promoted in Bogotá, which representing a more compact development.     

Separate waste collection in mountain municipalities. A case study in Campania

This paper aims to analyse the impact of land characteristics (i.e. altimetry and housing dispersion) on separate waste collection, with a focus on mountain municipalities. The high spatial heterogeneity of the driving factors of separate waste collection allows traditional techniques, such as OLS, to offer only a partial depiction of the situation, missing important information. In this view, we perform the Geographically Weighted Regression (GWR), which allows to control for the local determinants of waste management. Our data cover 550 municipalities of Campania, in Southern Italy. We control for a set of morphological and socio-economic variables, drawn from official records for 2012. Our results show that the relationships between land characteristics and separate waste collection are not constant over space. Moreover, they suggest that in the presence of non-modifiable factors (such as land characteristics) local governments should act on citizen motivations, promoting awareness on environmental issues, and should implement time-saving collection methods.