Civil Society Meta-organizations and Legitimating Processes: the Case of the Addiction Field in France

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - To cope with the new challenges inherent to their political role, civil society organizations must convince their...     

Crawling Predicts Infants’ Understanding of Agents’ Navigation of Obstacles

We investigated whether crawling versus noncrawling infants interpret an agent's movements around an obstacle as goal‐directed. Infants (6–9 months) were habituated to a self‐propelled circle jumping over an obstacle to reach a goal. When the obstacle was removed, infants who crawled (n = 13) showed longer looking time to the familiar but now nonrational jumping path versus a novel but rational straight‐line path. Noncrawlers (n = 17) did not discriminate. Looking preference was independent of age and speed of habituation. These findings support the claim that infants’ processing of agency emerges early and applies to all agents, but stress the role of experience in the development of action interpretation.     

Functional approaches for predicting land use with the temporal evolution of coarse resolution remote sensing data

The sensor SPOT 4/Végétation gives every day satellite images of Europe with medium spatial resolution, each pixel corresponding to an area of 1 r km 2 1 r km. Such data are useful to characterize the development of the vegetation at a large scale. The pixels, named "mixed' pixels, aggregate information of different crops and thus different themes of interest (wheat, corn, forest, …). We aim at estimating the land use when observing the temporal evolution of reflectances of mixed pixels. The statistical problem is to predict proportions with longitudinal covariates. We compared two functional approaches. The first relies on varying-time regression models and the second is an extension of the multilogit model for functional data. The comparison is achieved on a small area on which the land use is known. Satellite data were collected between March and August 1998. The functional multilogit model gives better predictions and the use of composite vegetation index is more efficient.     

Varying-time random effects models for longitudinal data: unmixing and temporal interpolation of remote-sensing data

Remote sensing is a helpful tool for crop monitoring or vegetation-growth estimation at a country or regional scale. However, satellite images generally have to cope with a compromise between the time frequency of observations and their resolution (i.e. pixel size). When concerned with high temporal resolution, we have to work with information on the basis of kilometric pixels, named mixed pixels, that represent aggregated responses of multiple land cover. Disaggreggation or unmixing is then necessary to downscale from the square kilometer to the local dynamic of each theme (crop, wood, meadows, etc.).

Assuming the land use is known, that is to say the proportion of each theme within each mixed pixel, we propose to address the downscaling issue through the generalization of varying-time regression models for longitudinal data and/or functional data by introducing random individual effects. The estimators are built by expanding the mixed pixels trajectories with B-splines functions and maximizing the log-likelihood with a backfitting-ECME algorithm. A BLUP formula allows then to get the ‘best possible’ estimations of the local temporal responses of each crop when observing mixed pixels trajectories. We show that this model has many potential applications in remote sensing, and an interesting one consists of coupling high and low spatial resolution images in order to perform temporal interpolation of high spatial resolution images (20 m), increasing the knowledge on particular crops in very precise locations.

The unmixing and temporal high-resolution interpolation approaches are illustrated on remote-sensing data obtained on the South-Western France during the year 2002.     

The benefits of information communication technology use by the homeless: a narrative synthesis review

Recent studies have suggested that technologies are becoming an increasingly ubiquitous element in the lives of individuals experiencing homelessness. With both Canadian and US researchers reporting staggering levels of homelessness on both sides of the border, an understanding and synthesis of the current literature exploring how technologies are being utilized by homeless individuals and how it may impact their well-being is of relevance to policy makers and social service organizations. The study explored and synthesized literature to examine the ways in which individuals experiencing homelessness utilize information and communication technologies (ICTs), and how the use of ICTs influences the health and social outcomes of individuals experiencing homelessness. The study examined 16 peer reviewed articles using a narrative synthesis systematic review, following three elements of the narrative synthesis approach: preliminary synthesis of findings; exploration of relationships between studies; and assessment of the robustness of the synthesis. In relation to what ICTs are used for by homeless individuals, three major themes emerged: social connectedness, identity management, and instrumental purposes. Furthermore, there was some tentative evidence about a positive relationship between ICT use among individuals experiencing homelessness and health outcomes. The paper discussed limitations, future areas of research, as well as some policy directions.     

对偶性在线性规划预处理中的应用分析

在当今大数据背景下,从实际应用中抽象出来的线性规划问题的规模越来越大,复杂性越来越高,因此数据预处理技术在线性规划问题求解中的重要性日渐突显。对偶性不仅有助于原始问题的算法（如对偶单纯形法）求解,而且是进行算法求解前的预处理步的重要组成部分。针对后者,本文基于有上下界的线性规划模型,详细分析总结了将对偶性应用于预处理中的两种方法：优先列和比例列的处理,并利用无效约束的概念证明了弱优先列的性质,最后应用C语言将预处理方法进行编程实现,以国际通用题库中变量个数大于1500的标准线性规划问题为实例进行测试。实例测试结果表明：（1）对于一般线性规划问题而言,对偶性在预处理中的应用能够有效减小问题规模,一方面体现在直接减少问题的变量数和非零元数,另一方面通过影响其他预处理方法间接减少问题的约束个数;（2）从减小问题规模的角度,对大部分问题而言比例列的预处理效果优于优先列。     

Queering the Language? A Roundtable on Jargon in Queer Studies

Within colleges and universities, and academic circles generally, as in other fields, a certain jargon or distinguishable language has developed. There are those who assert that this academic jargon is used to add precision in the transmission of ideas, or to provide a certain degree of legitimacy to a comparatively young academic discipline, while others contend that this “academise” is needlessly dense and exclusionary setting up a hierarchy of knowledge. Three individuals with varying relationships to the “academy” discuss this ongoing controversy within queer studies. The discussants include Paul B. Franklin, a doctoral candidate in the Fine Arts Department at Harvard University. He is currently writing a dissertation on the place of homosexuality in modern art. Adrien Saks is a Boston activist, writer, and publicist. He is the coeditor of Revelations: Gay Men’s Coming Out Stories and the former Marketing Director of Alyson Publications. This is his third year on the planning committee of OutWrite: The National Lesbian, Gay, Bisexual and Transgender Writing Conference. Amanda Udis-Kessler is a bisexual sociologist with an interest in race, class, and gender inequality. Her work has appeared in eight books and a number of journals. An acquisitions editor for the journal Empathy, she is currently writing a social history of the bisexual movement/identity.     

A three-phased local search approach for the clique partitioning problem

This paper presents a three-phased local search heuristic CPP-P\(^{3}\) for solving the Clique Partitioning Problem (CPP). CPP-P\(^{3}\) iterates a descent search, an exploration search and a directed perturbation. We also define the Top Move of a vertex, in order to build a restricted and focused neighborhood. The exploration search is ensured by a tabu procedure, while the directed perturbation uses a GRASP-like method. To assess the performance of the proposed approach, we carry out extensive experiments on benchmark instances of the literature as well as newly generated instances. We demonstrate the effectiveness of our approach with respect to the current best performing algorithms both in terms of solution quality and computation efficiency. We present improved best solutions for a number of benchmark instances. Additional analyses are shown to highlight the critical role of the Top Move-based neighborhood for the performance of our algorithm and the relation between instance hardness and algorithm behavior.     

Field and remotely sensed measures of soil and vegetation carbon and nitrogen across an urbanization gradient in the Boston metropolitan area

Understanding the impact of urbanization on terrestrial biogeochemistry is critical for addressing society’s grand challenge of global environmental change. We used field observations and remotely sensed data to quantify the effects of urbanization on vegetation and soils across a 100-km urbanization gradient extending from Boston to Harvard Forest and Worcester, MA. At the field-plot scale, the normalized difference vegetation index (NDVI) was positively correlated with aboveground biomass (AGB) and foliar nitrogen (N) content and negatively correlated with impervious surface fraction. Unlike previous studies, we found no significant relationship between NDVI or impervious surface area (ISA) fraction and foliar N concentration. Patterns in foliar N appeared to be driven more strongly by changes in species composition rather than phenotypic plasticity across the urbanization gradient. For forest and non-residential development, soil nitrogen content increased with urban intensity. In contrast, residential land had consistently high soil N content across the gradient of urbanization. When field observations were scaled-up to the Boston Metropolitan Statistical Area (MSA), we found that soil and vegetation N content were negatively correlated with ISA fraction, an indicator of urban intensity. Our results demonstrated the importance of accounting for the influence of impervious surfaces when scaling field data across urban ecosystems. The combination of field data with remote sensing holds promise for disentangling the complex interactions that drive biogeochemical cycling in urbanizing landscapes. Empirical data that accurately characterize variations in urban biogeochemistry are critical to gain a mechanistic understanding of urban ecosystem function and to guide policy makers and planners in developing ecologically sensitive development strategies.     

A Cause-of-Death Decomposition of Young Adult Excess Mortality

We propose a method to decompose the young adult mortality hump by cause of death. This method is based on a flexible shape decomposition of mortality rates that separates cause-of-death contributions to the hump from senescent mortality. We apply the method to U.S. males and females from 1959 to 2015. Results show divergence between time trends of hump and observed deaths, both for all-cause and cause-specific mortality. The study of the hump shape reveals age, period, and cohort effects, suggesting that it is formed by a complex combination of different forces of biological and socioeconomic nature. Male and female humps share some traits in all-cause shape and trend, but they also differ by their overall magnitude and cause-specific contributions. Notably, among males, the contributions of traffic and other accidents were progressively replaced by those of suicides, homicides, and poisonings; among females, traffic accidents remained the major contributor to the hump.