Grandparenthood is a fascinating research area that not only brings together three generations and multiple roles in different life domains, but also echoes social contexts across historical times ...and places. Comparative research on grandparenthood, however, rarely includes non-western countries. This article seeks to answer the question of how grandparenthood differs between Western Europe and China by using comparable representative surveys of older adults. We extend the literature in two ways by showing that: 1) compared to Western Europe, becoming a grandparent occurs earlier and is virtually universal in both Urban and Rural China – the probability of being a grandparent is over 80% for Chinese by the time they are 55, while the same cannot be said for Western Europeans until they are aged between 70 and 80; and 2) the role-overlaps with grandparenthood are different for older Chinese and Western Europeans. The probability of being a working grandparent in Rural China is about twice that in Western Europe, while the rate is similar to Western Europeans for Urban Chinese. Chinese grandparents are also more likely to live with their children than Western Europeans. Conversely, as all family transitions come earlier for Chinese but life expectancy is shorter, the probabilities that grandparenthood overlaps with widowhood and filial roles are similar to that in Western Europe. Taken together, this study provides an overarching picture of the characteristics of grandparenthood in different societies that are fundamental to the meaning, performance, and impact of grandparental roles and relevant to a better understanding of grandparenthood worldwide.
Soil drainage conditions are highly important to farmers and the environment. To map drainage classes efficiently, several analytical approaches, such as decision tree classification, can be used. ...Decision tree classification can be improved by combining the predictions of several trees with boosting and bagging techniques. This study tested the relative performance of boosting and bagging for the prediction of drainage classes. Furthermore, as drainage classes form an ordered series rather than unrelated classes, differential costs for misclassification were tested in combination with each technique. Decision tree models were trained from 1135 observations of soil drainage classes and validated using leave-one-out cross validation and a hold-out validation sample with 567 observations. The best model was achieved using bagging combined with differential costs for misclassification (overall accuracy=52.0%). On the other hand, differential costs for misclassification reduced the overall accuracy of boosted decision trees from 50.8% to 49.2%. The best models obtained with boosting and bagging were used to produce maps of drainage classes on a national extent. The maps predicted the same drainage class in 81% of the study area. Finally, with boosting as well as bagging, the models had a high usage of the predictor variables wetlands, slope to channel network, clay content, land use and geology.
•Drainage classes are mapped for Denmark by means of decision tree classification.•The effect of applying of differential costs for misclassification is tested.•The best performance was achieved combining differential costs with bagging.•The performance of boosting deteriorated with differential costs implemented.
There is a drastic geographic imbalance in available global streamflow gauge and catchment property data, with additional large variations in data characteristics. As a result, models calibrated in ...one region cannot normally be migrated to another without significant modifications. Currently in these regions, non‐transferable machine learning models are habitually trained over small local data sets. Here we show that transfer learning (TL), in the senses of weight initialization and weight freezing, allows long short‐term memory (LSTM) streamflow models that were pretrained over the conterminous United States (CONUS, the source data set) to be transferred to catchments on other continents (the target regions), without the need for extensive catchment attributes available at the target location. We demonstrate this possibility for regions where data are dense (664 basins in Great Britain), moderately dense (49 basins in central Chile), and scarce with only remotely sensed attributes available (5 basins in China). In both China and Chile, the TL models showed significantly elevated performance compared to locally trained models using all basins. The benefits of TL increased with the amount of available data in the source data set, and seemed to be more pronounced with greater physiographic diversity. The benefits from TL were greater than from pretraining LSTM using the outputs from an uncalibrated hydrologic model. These results suggest hydrologic data around the world have commonalities which could be leveraged by deep learning, and synergies can be had with a simple modification of the current workflows, greatly expanding the reach of existing big data. Finally, this work diversified existing global streamflow benchmarks.
Plain Language Summary
We introduced a method to utilize available big data to better start and warm up a machine learning streamflow model that is later fine‐tuned for prediction in basins on other continents (Asia, South America and Europe). This procedure noticeably improved streamflow volume prediction for different scenarios with varying amounts of data in the target basins (in terms of time period, length of collected data, and number of basins having data). This allows thousands of basins across the world with only a few years’ worth of streamflow observations to benefit from improved modeling and accuracy resulting from the use of deep learning.
Key Points
Basins around the world can be better modeled by applying transfer learning (TL) to a deep network trained in the US, and tuning it locally
The benefits of TL increased with the amount and diversity of the source data, and were larger than from pretraining with a hydrologic model
This work greatly expands the reach of deep learning, adds to the value of existing big data, and calls for synergy of global data sets
•Main challenges in geothermal grilling.•Significance of drilling fluid rheology in drilling operations.•Factors affecting the drilling fluid rheology in geothermal drilling.•Issues associated with ...fluid rheology in geothermal drilling.•Advances in controlling drilling fluid rheology for geothermal drilling.
The harsh downhole conditions of high pressure and high temperature (HPHT) encountered in geothermal wells make the drilling operation challenging. Drilling in such environments requires a special drilling mud formulation with high thermal stability and good rheological properties to fulfill the drilling fluid functions. Therefore, great efforts should be put into selecting the suitable drilling fluid, optimize and monitor the drilling fluid properties throughout drilling operations, and predicting its performance under downhole conditions. Rheological properties significantly impact many drilling parameters such as hole cleaning, fluid and wellbore stability, wellbore hydraulics, torque and drag, and other drilling issues. This paper discusses water-based drilling fluids' flow behavior under HPHT conditions and highlights the significance of fluid rheology in geothermal drilling. The common challenges and complications related to fluid rheology encountered in geothermal drilling are addressed in this paper, such as hole cleaning, wellbore hydraulics, and drilling fluid stability. This article also reviews the recent advances in drilling mud systems, rheology enhancement, and rheological properties measurements at surface and subsurface conditions. Moreover, the rheology models of drilling fluid at elevated temperatures are reviewed to fully understand their flow behavior and establish a method for drilling engineers to optimize fluid formulations for geothermal drilling.
Predicting distress in European banks Betz, Frank; Oprică, Silviu; Peltonen, Tuomas A. ...
Journal of banking & finance,
08/2014, Volume:
45
Journal Article
Peer reviewed
Open access
•The paper introduces an early-warning model for bank distress.•It introduces a novel dataset for bank distress in Europe.•The model is calibrated to policymakers’ preferences between type I and II ...errors.•The model can also be calibrated taking into account systemic relevance of a bank.•The model yields useful out-of-sample predictions of bank distress during the current financial crisis.
The paper develops an early-warning model for predicting vulnerabilities leading to distress in European banks using both bank and country-level data. As outright bank failures have been rare in Europe, the paper introduces a novel dataset that complements bankruptcies and defaults with state interventions and mergers in distress. The signals of the early-warning model are calibrated not only according to the policymaker’s preferences between type I and II errors, but also to take into account the potential systemic relevance of each individual financial institution. The key findings of the paper are that complementing bank-specific vulnerabilities with indicators for macro-financial imbalances and banking sector vulnerabilities improves model performance and yields useful out-of-sample predictions of bank distress during the current financial crisis.
Democracy is under threat today and scholars agree that the main challenge is not sudden regime breakdown, but rather the gradual erosion of key institutions and norms because of growing public ...support to political forces with illiberal tendencies. In the case of Western Europe, the major threat comes from the populist radical right. Although it is true that the latter has been gaining votes in Western Europe, scholars have not analysed the extent to which a sizeable share of the electorate dislikes this party family. Nevertheless, recent studies reveal that it is important to consider both those who feel close to and those who reject political parties, i.e. positive and negative partisanship. To address this research gap, in this contribution we rely on original survey data for 10 Western European countries to examine negative partisanship towards the populist radical right. The empirical analysis reveals that a large section of the Western European electorate has an aversion to this party family and this finding should be seen as an important sign of democratic resilience. In fact, those who dislike the populist radical right are strong supporters of both democracy per se and the liberal democratic regime.
This paper investigates notable examples of sustainable lifestyles in relation to food systems. It explores the surprisingly neglected case of widely practised and environmentally sustainable food ...self-provisioning in post-socialist Central and Eastern Europe. Our argument is rooted in qualitative and quantitative data gathered over a seven-year period (2005–2011). The research considers the extent of and motivations for these practices in Poland and Czechia. The very high rates compared to Western Europe and North America have generally been explained in terms of an ‘urban peasantry’ meeting essential needs. After reviewing and rejecting those accounts we present evidence for these as socially and environmentally beneficial practices, and explore how the motivations derive from a range of feelings about food, quality, capability and family and/or friendship. Rather than relate these practices to temporal signals of quality and sustainability in food ('slow' and 'fast'), or presenting them as 'alternative food networks' we suggest that they represent 'quiet sustainability'. This novel concept summarises widespread practices that result in beneficial environmental or social outcomes and that do not relate directly or indirectly to market transactions, but are not represented by their practitioners as relating directly to environmental or sustainability goals. These practices represent exuberant, appealing and socially inclusive, but also unforced, forms of sustainability. This case further demonstrates the severe limitations of decision makers' focus on economics and behaviour change, and their neglect of other dimensions of social life and change in developing environmental policies.
•High levels of food self-provisioning continue in Central and Eastern Europe.•It is practised equally across all social groups, and in both urban and rural areas.•These behaviours aren't motivated by need or explicit environmental or social goals.•Market focused sustainability policies ignore food self-provisioning to their cost.•‘Quiet sustainability’ revises and complements sustainability discourses.
The price of EU allowances (EUAs) in the EU Emissions Trading Scheme (EU ETS) fell from almost 30€/tCO2 in mid-2008 to less than 5€/tCO2 in mid-2013. The sharp and persistent price decline has ...sparked intense debates both in academia and among policy-makers about the decisive allowance price drivers. In this paper we examine whether and to what extent the EUA price drop can be justified by three commonly identified explanatory factors: the economic recession, renewable policies and the use of international credits. Capitalizing on marginal abatement cost theory and a broadly extended data set, we find that only variations in economic activity and the growth of wind and solar electricity production are robustly explaining EUA price dynamics. Contrary to simulation-based analyses, our results point to moderate interaction effects between the overlapping EU ETS and renewable policies. The bottom line, however, is that 90% of the variations of EUA price changes remains unexplained by the abatement-related fundamentals. Together, our findings do not support the widely-held view that negative demand shocks are the main cause of the weak carbon price signal. In view of the new evidence, we evaluate the EU ETS reform options which are currently discussed.
•We examine whether abatement-related fundamentals justify the EU ETS price drop.•90% of the variations of EUA price changes remain unexplained.•Variations in economic activity are robustly explaining EUA price dynamics.•Price impact of renewable deployment and international credit use remains moderate.•Reform options are evaluated in the light of the new findings.
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