Causal Effects of Paternity Leave on Children and Parents

In this paper we use a parental leave reform directed towards fathers to identify the causal effects of paternity leave on children’s and parents’ outcomes. We document that paternity leave causes fathers to become more important for children’s cognitive skills. School performance at age 16 increases for children whose father is relatively higher educated than the mother. We find no evidence that fathers’ earnings and work hours are affected by paternity leave. Contrary to expectation, mothers’ labor market outcomes are adversely affected by paternity leave. Our findings do therefore not suggest that paternity leave shifts the gender balance at home in a way that increases mothers’ time and/or effort spent at market work.parental leave, labor supply, child development

Causal effects of paternity leave on children and parents

In this paper we use a parental leave reform directed towards fathers to identify the causal effects of paternity leave on children's and parents' outcomes. We document that paternity leave causes fathers to become more important for children's cognitive skills. School performance at age 16 increases for children whose father is relatively higher educated than the mother. We find no evidence that fathers' earnings and work hours are affected by paternity leave. Contrary to expectation, mothers' labor market outcomes are adversely affected by paternity leave. Our findings do therefore not suggest that paternity leave shifts the gender balance at home in a way that increases mothers' time and/or effort spent at market work

Constraints on the evolution of azole resistance in plant pathogenic fungi

The durability of azole fungicides in controlling agriculturally important pathogenic fungi is unique amongst modern single site fungicides. Today, azoles are still relied on to control pathogens of many crops including cereals, fruits and vegetables, canola and soybeans. Significantly, this widespread use continues despite many reports of azole-resistant fungal strains. In this review, recent reports of azole resistance and the mechanisms associated with resistant phenotypes are discussed. The example of the complex evolution of the azole target sterol 14-demethylase (CYP51) enzyme in modern European populations of the wheat pathogen Mycosphaerella graminicola is used to describe the quantitative and epistatic effects on fungicide sensitivity and enzyme function of target site mutations, and to explore the hypothesis that constraints on CYP51 evolution have ensured the longevity of azoles. In addition, the threats posed by alternative resistance mechanisms causing cross-resistance to all azoles or even unrelated fungicides are discussed, and postulations are made on how using new genomic technologies to gain a greater understanding of azole resistance evolution should enhance the ability to control azole-resistant strains of plant pathogenic fungi in the future

Human Substantia Nigra Neurons Encode Unexpected Financial Rewards

The brain's sensitivity to unexpected outcomes plays a fundamental role in an organism's ability to adapt and learn new behaviors. Emerging research suggests that midbrain dopaminergic neurons encode these unexpected outcomes. We used microelectrode recordings during deep brain stimulation surgery to study neuronal activity in the human substantia nigra (SN) while patients with Parkinson's disease engaged in a probabilistic learning task motivated by virtual financial rewards. Based on a model of the participants' expected reward, we divided trial outcomes into expected and unexpected gains and losses. SN neurons exhibited significantly higher firing rates after unexpected gains than unexpected losses. No such differences were observed after expected gains and losses. This result provides critical support for the hypothesized role of the SN in human reinforcement learning

Application of quasi-Monte Carlo methods to PDEs with random coefficients -- an overview and tutorial

This article provides a high-level overview of some recent works on the application of quasi-Monte Carlo (QMC) methods to PDEs with random coefficients. It is based on an in-depth survey of a similar title by the same authors, with an accompanying software package which is also briefly discussed here. Embedded in this article is a step-by-step tutorial of the required analysis for the setting known as the uniform case with first order QMC rules. The aim of this article is to provide an easy entry point for QMC experts wanting to start research in this direction and for PDE analysts and practitioners wanting to tap into contemporary QMC theory and methods.Comment: arXiv admin note: text overlap with arXiv:1606.0661

Hot new directions for quasi-Monte Carlo research in step with applications

This article provides an overview of some interfaces between the theory of quasi-Monte Carlo (QMC) methods and applications. We summarize three QMC theoretical settings: first order QMC methods in the unit cube $[0,1]^s$ and in $\mathbb{R}^s$, and higher order QMC methods in the unit cube. One important feature is that their error bounds can be independent of the dimension $s$ under appropriate conditions on the function spaces. Another important feature is that good parameters for these QMC methods can be obtained by fast efficient algorithms even when $s$ is large. We outline three different applications and explain how they can tap into the different QMC theory. We also discuss three cost saving strategies that can be combined with QMC in these applications. Many of these recent QMC theory and methods are developed not in isolation, but in close connection with applications

Cost-Effectiveness of Cranberry Capsules to Prevent Urinary Tract Infection in Long-Term Care Facilities: Economic Evaluation with a Randomized Controlled Trial

Analysis and support of clinical decision makin