33 research outputs found

    How to Capture Reciprocal Communication Dynamics: Comparing Longitudinal Statistical Approaches in Order to Analyze Within- and Between-Person Effects

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    Choosing an appropriate statistical model to analyze reciprocal relations between individuals’ attitudes, beliefs, or behaviors over time can be challenging. Often, decisions for or against specific models are rather implicit and it remains unclear whether the statistical approach fits the theory of interest. For longitudinal models, this is problematic since within- and between-person processes can be confounded leading to wrong conclusions. Taking the perspective of the reinforcing spirals model (RSM) focusing on media effects and selection, we compare six statistical models that were recently used to analyze the RSM and show their ability to separate within- and between-person components. Using empirical data capturing respondents’ development during adolescence, we show that results vary across statistical models. Further, Monte Carlo simulations indicate that some approaches might lead to wrong conclusions if specific communication dynamics are present. In sum, we recommend using approaches that explicitly model and clearly separate within- and between-person effects

    A Review of the "Digital Turn" in the New Literacy Studies

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    Digital communication has transformed literacy practices and assumed great importance in the functioning of workplace, recreational, and community contexts. This article reviews a decade of empirical work of the New Literacy Studies, identifying the shift toward research of digital literacy applications. The article engages with the central theoretical, methodological, and pragmatic challenges in the tradition of New Literacy Studies, while highlighting the distinctive trends in the digital strand. It identifies common patterns across new literacy practices through cross-comparisons of ethnographic research in digital media environments. It examines ways in which this research is taking into account power and pedagogy in normative contexts of literacy learning using the new media. Recommendations are given to strengthen the links between New Literacy Studies research and literacy curriculum, assessment, and accountability in the 21st century

    The Role of Trait and State Perfectionism in Psychological Detachment From Daily Job Demands

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    Psychological detachment has been proposed to be a mediator of the relations between an individual's responses to stressful work-related experiences and mid- and long-term health. However, the number of studies that have specifically examined the role that personal characteristics play in these associations is considerably small. One personal characteristic that might specifically interfere with psychological detachment is perfectionism, which has been considered an important vulnerability factor for the development of psychological disorders. Hence, the goal of this registered report was to extend research on psychological detachment by introducing trait and state perfectionism as moderators of the aforementioned relations. We conducted an experience sampling study with three measurement occasions per day over the course of 3 working weeks (N = 158 employees; Mage = 41.6; 67% women). Multilevel path models showed that perfectionistic concerns consistently determined strain responses at between- and within-levels of analyses even after the effects of job demands (i.e., unfinished tasks and role ambiguity) and detachment were accounted for. However, we found no evidence for the proposed moderation effects. The theoretical implications for the understanding of the processes proposed in the stressor-detachment model are discussed

    Current challenges of implementing anthropogenic land-use and land-cover change in models contributing to climate change assessments

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    This is the author accepted manuscript. The final version is available from European Geosciences Union (EGU) via the DOI in this record.Land-use and land-cover change (LULCC) represents one of the key drivers of global environmental change. However, the processes and drivers of anthropogenic land-use activity are still overly simplistically implemented in terrestrial biosphere models (TBMs). The published results of these models are used in major assessments of processes and impacts of global environmental change, such as the reports of the Intergovernmental Panel on Climate Change (IPCC). Fully coupled models of climate, land use and biogeochemical cycles to explore land use-climate interactions across spatial scales are currently not available. Instead, information on land use is provided as exogenous data from the land-use change modules of integrated assessment models (IAMs) to TBMs. In this article, we discuss, based on literature review and illustrative analysis of empirical and modeled LULCC data, three major challenges of this current LULCC representation and their implications for land use-climate interaction studies: (I) provision of consistent, harmonized, land-use time series spanning from historical reconstructions to future projections while accounting for uncertainties associated with different land-use modeling approaches, (II) accounting for sub-grid processes and bidirectional changes (gross changes) across spatial scales, and (III) the allocation strategy of independent land-use data at the grid cell level in TBMs. We discuss the factors that hamper the development of improved land-use representation, which sufficiently accounts for uncertainties in the land-use modeling process. We propose that LULCC data-provider and user communities should engage in the joint development and evaluation of enhanced LULCC time series, which account for the diversity of LULCC modeling and increasingly include empirically based information about sub-grid processes and land-use transition trajectories, to improve the representation of land use in TBMs. Moreover, we suggest concentrating on the development of integrated modeling frameworks that may provide further understanding of possible land-climate-society feedbacks.The research in this paper has been supported by the European Research Council under the European Union’s Seventh Framework Programme project LUC4C (Grant No. 603542), ERC grant GLOLAND (No. 311819) and BiodivERsA project TALE (No. 832.14.006) funded by the Dutch National Science Foundation (NWO). This research contributes to the Global Land Project (www.globallandproject.org). This is paper number 26 of the Birmingham Institute of Forest Research

    Dichloroacetate reverses the hypoxic adaptation to bevacizumab and enhances its antitumor effects in mouse xenografts.

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    Inhibition of vascular endothelial growth factor increases response rates to chemotherapy and progression-free survival in glioblastoma. However, resistance invariably occurs, prompting the urgent need for identification of synergizing agents. One possible strategy is to understand tumor adaptation to microenvironmental changes induced by antiangiogenic drugs and test agents that exploit this process. We used an in vivo glioblastoma-derived xenograft model of tumor escape in presence of continuous treatment with bevacizumab. U87-MG or U118-MG cells were subcutaneously implanted into either BALB/c SCID or athymic nude mice. Bevacizumab was given by intraperitoneal injection every 3 days (2.5 mg/kg/dose) and/or dichloroacetate (DCA) was administered by oral gavage twice daily (50 mg/kg/dose) when tumor volumes reached 0.3 cm(3) and continued until tumors reached approximately 1.5-2.0 cm(3). Microarray analysis of resistant U87 tumors revealed coordinated changes at the level of metabolic genes, in particular, a widening gap between glycolysis and mitochondrial respiration. There was a highly significant difference between U87-MG-implanted athymic nude mice 1 week after drug treatment. By 2 weeks of treatment, bevacizumab and DCA together dramatically blocked tumor growth compared to either drug alone. Similar results were seen in athymic nude mice implanted with U118-MG cells. We demonstrate for the first time that reversal of the bevacizumab-induced shift in metabolism using DCA is detrimental to neoplastic growth in vivo. As DCA is viewed as a promising agent targeting tumor metabolism, our data establish the timely proof of concept that combining it with antiangiogenic therapy represents a potent antineoplastic strategy

    Estimating the Global Distribution of Field Size using Crowdsourcing

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    There is increasing evidence that smallholder farms contribute substantially to food production globally yet spatially explicit data on agricultural field sizes are currently lacking. Automated field size delineation using remote sensing or the estimation of average farm size at subnational level using census data are two approaches that have been used. However, both have limitations, e.g. automatic field size delineation using remote sensing has not yet been implemented at a global scale while the spatial resolution is very coarse when using census data. This paper demonstrates a unique approach to quantifying and mapping agricultural field size globally using crowdsourcing. A campaign was run in June 2017 where participants were asked to visually interpret very high resolution satellite imagery from Google Maps and Bing using the Geo-Wiki application. During the campaign, participants collected field size data for 130K unique locations around the globe. Using this sample, we have produced the most accurate global field size map to date and estimated the percentage of different field sizes, ranging from very small to very large, in agricultural areas at global, continental and national levels. The results show that smallholder farms occupy up to 40% of agricultural areas globally, which means that, potentially, there are many more smallholder farms in comparison with the two different current global estimates of 12% and 24%. The global field size map and the crowdsourced data set are openly available and can be used for integrated assessment modelling, comparative studies of agricultural dynamics across different contexts, for training and validation of remote sensing field size delineation, and potential contributions to the Sustainable Development Goal of Ending hunger, achieve food security and improved nutrition and promote sustainable agriculture

    Northward shift of the agricultural climate zone under 21st-century global climate change

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    As agricultural regions are threatened by climate change, warming of high latitude regions and increasing food demands may lead to northward expansion of global agriculture. While socio-economic demands and edaphic conditions may govern the expansion, climate is a key limiting factor. Extant literature on future crop projections considers established agricultural regions and is mainly temperature based. We employed growing degree days (GDD), as the physiological link between temperature and crop growth, to assess the global northward shift of agricultural climate zones under 21st-century climate change. Using ClimGen scenarios for seven global climate models (GCMs), based on greenhouse gas (GHG) emissions and transient GHGs, we delineated the future extent of GDD areas, feasible for small cereals, and assessed the projected changes in rainfall and potential evapotranspiration. By 2099, roughly 76% (55% to 89%) of the boreal region might reach crop feasible GDD conditions, compared to the current 32%. The leading edge of the feasible GDD will shift northwards up to 1200 km by 2099 while the altitudinal shift remains marginal. However, most of the newly gained areas are associated with highly seasonal and monthly variations in climatic water balances, a critical component of any future land-use and management decisions
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