Tempest in the Andes? Part 2: Peasant Organization and Development Agencies in Cotopaxi (Ecuador)

This paper, published in two parts, is an analysis of the links between the ‘agrarian question’ in the Ecuadorian Andes and the creation of a network of indigenous‐peasant organizations that became the backbone of the national indigenous movement. I explore the relations between agrarian change and social change, drawing on a monographic study carried out in Cotopaxi Province, in the central sierra of Ecuador, from the 1960s to the beginning of the twenty‐first century. In the first part, I emphasized how the transformations unleashed by the crisis of the hacienda regime marked a rupture that consolidated the dense organizational scaffolding in the rural milieu. In this second part, I examine how development agencies, especially non‐governmental organizations (NGOs), played a fundamental role in strengthening those structures (1980s and 1990s). The history of the Union of Peasant Organizations of Northern Cotopaxi (UNOCANC) is one such example: born from the struggle for haciendas, inputs from the development apparatus enabled the rise of local elites who turned the organization into one of the most militant in the country. In this paper, I draw attention to aspects seldom mentioned in the specialized bibliography, namely a detailed study of how peasant differentiation, the origins of which lay in hacienda hierarchies, and which was upheld in turn by the agrarian distribution, was accelerated by the actions of NGOs, which continued to favour those indigenous peasants with more power and economic resources. Thus, divergences were consolidated and internal fissures opened up in organizations that are at the root of the crisis of representation experienced by ethnic platforms in the Ecuadorian Andes today.     

土壤水盐分运移规律研究进展

近年来,土壤水盐的运移规律已引起人们极大的兴趣。本文首先综述了土壤水的提取方法,然后介绍了影响土壤水盐分变化的主要因素,进而综述了土壤水盐运移规律研究现状,并且土壤水盐分含量特征在研究土壤水运移规律及不同水体补给关系方面亦得到了一定的应用。     

煤矸石倾倒过程中的运动特征对矸石山非均质性的影响研究

本文研究煤矸石倾倒过程中的运动特征对矸石山非均质性特征的影响。分析表明,当煤矸石密度相同时,煤矸石在坡面上的运动位移与矸石山高度、初始速度、粒径、球度和磨圆度成正比,这就使煤矸石随矸石山高度的变化粒径分布不均匀,进而造成了矸石山的非均质性。     

Empirical Study of Scapegoat Theory Paradigm in the Exchange Rate Variable in the ASEAN 5

This paper attempts to explain empirically the effect of order flow as an unobserved variable on the exchange rate movements based on the theory of scapegoat. The theory of scapegoat appears as the answer to the imbalance in the relationship between macroeconomic fundamentals and the exchange rate. To analyze the validity of this theory in Indonesia, the Philippines, Malaysia, Singapore, and Thailand (ASEAN 5), we apply the two-stage least squares method. The empirical testing generates a fact that the paradigm of scapegoat theory works for four countries, namely Indonesia, Malaysia, Singapore, and Thailand. Another finding is that the theory of scapegoat does not work for the Philippines. The implication of policy based on the results is the emphasis of policy that enables intervention in the foreign exchange market, the enhancement of monetary policy transparency in each country, as well as the management of capital flows more efficiently.     

采用STFT幅度值的长信号相位恢复算法

针对以往基于短时傅里叶变换(STFT)幅度值的相位恢复（STFTMPR）算法仅能处理一组较短的信号,并且信号的STFT幅度测量值的长度只能是质数的情况,提出了一种基于STFT幅度值的长信号相位恢复（LS-STFTMPR）算法。把一组长信号变化成几组较短的数组信号,通过改进的最小二乘（LS）法获取梯度下降（GD）法的迭代初始值,然后最小化各数组信号的非凸损失函数,并最终收敛到全局最小值。实验结果表明,在恢复一组较长信号的时候,所提算法的性能明显优于STFTMPR算法,并且具有较强的抗噪声能力。     

恩格尔系数改进模型回归分析

恩格尔系数是衡量民众生活水平和经济发展程度的统计指标之一。在当前我国经济和社会发展条件下应用恩格尔系数存在局限性。利用我国31个省市的横截面数据建立的修正后的恩格尔系数回归模型所得出的恩格尔系数计算式,能更好地衡量居民生活水平和质量;计算部分农村省市修正后的恩格尔系数,能为政府工作人员制定发展政策提供理论依据。     

加强宗教活动场所财务管理

加强宗教活动场所财务管理,有利于规范其会计基础工作,维护公众和信教群众的合法权益.通过对福清市多所宗教活动场所进行调研,针对现行宗教活动场所财务管理的问题,结合实际情况,提出具体的解决措施.     

油田污水中含油量测定结果的评定

依据SY／T 5329-94《碎屑岩油藏注水水质推荐指标及分析方法》标准中含油量的测定方法,用最小二乘法的原理回归油田污水中含油量标准曲线,并用概率论和数理统计的方法检验含油量标准曲线的相关性：最后,预测了在一定置信概率水平下的测定结果区间。     

Distributed ARIMA models for ultra-long time series

Providing forecasts for ultra-long time series plays a vital role in various activities, such as investment decisions, industrial production arrangements, and farm management. This paper develops a novel distributed forecasting framework to tackle the challenges of forecasting ultra-long time series using the industry-standard MapReduce framework. The proposed model combination approach retains the local time dependency. It utilizes a straightforward splitting across samples to facilitate distributed forecasting by combining the local estimators of time series models delivered from worker nodes and minimizing a global loss function. Instead of unrealistically assuming the data generating process (DGP) of an ultra-long time series stays invariant, we only make assumptions on the DGP of subseries spanning shorter time periods. We investigate the performance of the proposed approach with AutoRegressive Integrated Moving Average (ARIMA) models using the real data application as well as numerical simulations. Our approach improves forecasting accuracy and computational efficiency in point forecasts and prediction intervals, especially for longer forecast horizons, compared to directly fitting the whole data with ARIMA models. Moreover, we explore some potential factors that may affect the forecasting performance of our approach.