Shared parenting, law and policy: considering power within the framework of autopoietic theory

This paper uses the last few decades’ developments in the area of shared parenting to explore power within the framework of autopoietic theory. It traces how, prompted by turbulence from the political subsystem, family law has made several unsuccessful attempts to solve the perceived problem of post-separation dual-household parenting. It agrees with Luhmann and Teubner that closed autopoietic systems’ developments are limited by their normative and cognitive frameworks, and also argues that changes, which have occurred in family law, show that closed social systems do not function in total isolation. It considers power as ego’s ability to limit alter’s choices. In our functionally differentiated society, with its recent proliferation of communication, power appears more diffuse and impossible to plot into causal one-way relationships.

Testing projected wild bee distributions in agricultural habitats: predictive power depends on species traits and habitat type

Species distribution models (SDM) are increasingly used to understand the factors that regulate variation in biodiversity patterns and to help plan conservation strategies. However, these models are rarely validated with independently collected data and it is unclear whether SDM performance is maintained across distinct habitats and for species with different functional traits. Highly mobile species, such as bees, can be particularly challenging to model. Here, we use independent sets of occurrence data collected systematically in several agricultural habitats to test how the predictive performance of SDMs for wild bee species depends on species traits, habitat type, and sampling technique. We used a species distribution modeling approach parametrized for the Netherlands, with presence records from 1990 to 2010 for 193 Dutch wild bees. For each species, we built a Maxent model based on 13 climate and landscape variables. We tested the predictive performance of the SDMs with independent datasets collected from orchards and arable fields across the Netherlands from 2010 to 2013, using transect surveys or pan traps. Model predictive performance depended on species traits and habitat type. Occurrence of bee species specialized in habitat and diet was better predicted than generalist bees. Predictions of habitat suitability were also more precise for habitats that are temporally more stable (orchards) than for habitats that suffer regular alterations (arable), particularly for small, solitary bees. As a conservation tool, SDMs are best suited to modeling rarer, specialist species than more generalist and will work best in long-term stable habitats. The variability of complex, short-term habitats is difficult to capture in such models and historical land use generally has low thematic resolution. To improve SDMs’ usefulness, models require explanatory variables and collection data that include detailed landscape characteristics, for example, variability of crops and flower availability. Additionally, testing SDMs with field surveys should involve multiple collection techniques.

Basic Income, Republican Freedom, and Effective Market Power

This article examines republican arguments for a basic income that turn on a right to exit the labour market. It gives criteria for the maintenance of republican freedom in markets, arguing that a right to exit or effective market power will guarantee republican freedom in markets. The article then considers whether a basic income is either sufficient or necessary to protect republican freedom both in labour markets and elsewhere. If a basic income is necessary to protect republican freedom in the labour market, I argue it is not sufficient to protect that freedom elsewhere. If citizens lack the means to maintain their republican freedom in the labour market, then there may be other spheres of life where they are vulnerable to subordination, whether or not they have a basic income. Some sociological evidence on cultural consumption patterns is presented.

Probabilistic wind power forecasts with an inverse power curve transformation and censored regression

Forecasting wind power is an important part of a successful integration of wind power into the power grid. Forecasts with lead times longer than 6 h are generally made by using statistical methods to post-process forecasts from numerical weather prediction systems. Two major problems that complicate this approach are the non-linear relationship between wind speed and power production and the limited range of power production between zero and nominal power of the turbine. In practice, these problems are often tackled by using non-linear non-parametric regression models. However, such an approach ignores valuable and readily available information: the power curve of the turbine's manufacturer. Much of the non-linearity can be directly accounted for by transforming the observed power production into wind speed via the inverse power curve so that simpler linear regression models can be used. Furthermore, the fact that the transformed power production has a limited range can be taken care of by employing censored regression models. In this study, we evaluate quantile forecasts from a range of methods: (i) using parametric and non-parametric models, (ii) with and without the proposed inverse power curve transformation and (iii) with and without censoring. The results show that with our inverse (power-to-wind) transformation, simpler linear regression models with censoring perform equally or better than non-linear models with or without the frequently used wind-to-power transformation.

Papal power and protection in the Shebet Yehudah

The sixteenth-century Shebet Yehudah is an account of the persecutions of Jews in various countries and epochs, including their expulsion from Spain in the fifteenth century. It is not a medieval text and was written long after many of the events it describes. Yet although it cannot give us a contemporary medieval standpoint, it provides important insights into how later Jewish writers perceived Jewish–papal relations in the thirteenth, fourteenth, and fifteenth centuries. Although the extent to which Jewish communities came into contact either with the papacy as an institution or the actions of individual popes varied immensely, it is through analysis of Hebrew works such as the Shebet Yehudah that we are able to piece together a certain understanding of Jewish ideas about the medieval papacy as an institution and the policies of individual popes. This article argues that Jews knew only too well that papal protection was not unlimited, but always carefully circumscribed in accordance with Christian theology. It is hoped that it will be a scholarly contribution to our growing understanding of Jewish ideas about the papacy's spiritual and temporal power and authority in the Later Middle Ages and how this impacted on Jewish communities throughout medieval Europe.

Improving power and accuracy of genome-wide association studies via a multi-locus mixed linear model methodology

Genome-wide association studies (GWAS) have been widely used in genetic dissection of complex traits. However, common methods are all based on a fixed-SNP-effect mixed linear model (MLM) and single marker analysis, such as efficient mixed model analysis (EMMA). These methods require Bonferroni correction for multiple tests, which often is too conservative when the number of markers is extremely large. To address this concern, we proposed a random-SNP-effect MLM (RMLM) and a multi-locus RMLM (MRMLM) for GWAS. The RMLM simply treats the SNP-effect as random, but it allows a modified Bonferroni correction to be used to calculate the threshold p value for significance tests. The MRMLM is a multi-locus model including markers selected from the RMLM method with a less stringent selection criterion. Due to the multi-locus nature, no multiple test correction is needed. Simulation studies show that the MRMLM is more powerful in QTN detection and more accurate in QTN effect estimation than the RMLM, which in turn is more powerful and accurate than the EMMA. To demonstrate the new methods, we analyzed six flowering time related traits in Arabidopsis thaliana and detected more genes than previous reported using the EMMA. Therefore, the MRMLM provides an alternative for multi-locus GWAS.

Increasing thermal plant flexibility in a high renewables power system

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability. This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified.