Hours Restrictions and Labor Supply

This study presents a model of labor supply in which individuals may face constraints on their choice of work hours, and analyzes the sensitivity of parameter estimates and policy conclusions to the usual assumption of unrestricted choice. We set up the labor supply decision asa discrete choice problem, where each worker faces a finite number of employment opportunities, each offering fixed hours of work.The distribution from which these are drawn, as well as the number of draws, is estimated along with the behavioral parameters of individual labor supply.The standard model with unconstrained hours appears as a special case where the number of draws approaches infinity. We estimate the mean absolute difference between desired and actual work hours to be about ten hours perweek. The results strongly support the notion that hours choices are constrained, and suggest that models which ignore restrictions on hours worked may yield biased estimates of the wage elasticity of desired hours. Further, we suggest that analysis of policies such as income transfers and the flat rate tax which do not consider their effects on the distribution of hours offered may be very misleading.

Guanosine nucleotides regulate B2 kinin receptor affinity of agonists but not of antagonists: Discussion of a model proposing receptor precoupling to G protein

The effect of nucleotides on binding of the B2 kinin (BK) receptor agonist {[}H-3]BK and the antagonist {[}H-3]NPC17731 to particulate fractions of human foreskin fibroblasts was studied. At 0 degrees C, particulate fractions exhibited a single class of binding sites with a Kd of 2.3 nM for {[}H-3]BK and a K-d Of 3.8 nM for the antagonist {[}H-3]NPC17731. Incubation with radioligands at 37 degrees C for 5 min gave a reduction of agonist, as well as antagonist, binding that was between 0-40% depending on the preparation, even in the absence of guanosine nucleotides. As shown by Scatchard analysis, this reduction in specific binding was due to a shift in the affinity of at least a fraction of the receptors. The presence at 37 degrees C of the guanine nucleotides GTP, GDP and their poorly hydrolyzable analogs left {[}H-3]-NPC17731 binding unaffected, but reduced the receptor affinity for {[}H-3]BK to a K-d Of about 15 nM. The maximal number of receptors, however, was unchanged. This affinity change was strongly dependent on the presence of bivalent cations, in particular Mg2+. It was reversed by incubation at 0 degrees C, The rank order of the guanosine nucleotides for {[}H-3]BK binding reduction was GTP{[}gamma S] = Gpp{[}NH]p > GTP = GDP > GDP{[}beta S]. GMP, ATP, ADP and AMP showed no influence on agonist binding. A model for the interaction of the B2 kinin receptor with G proteins is discussed

First records of soilborne Phytophthora species in Swedish oak forests

Thirty-two oak stands in southern Sweden, 27 with predominantly declining trees and five with a higher proportion of healthy trees were investigated regarding the presence of soilborne Phytophthora species. Phytophthora quercina , an oak-specific fine root pathogen, was isolated from rhizosphere soil samples in 10 of the 27 declining stands. Additionally, P. cactorum and P. cambivora were recovered from one stand each. No Phytophthora species were isolated from the healthy oak stands. The soil conditions at the sites from which Phytophthora spp. were recovered ranged from mesic sediments to moraines, with clayey to silty textures and with soil pH (BaCl2) between 3.5 and 5.0. The results show that P. quercina is geographically widespread in oak stands in southern Sweden and indicate that this pathogen may be one of the factors involved in oak decline in Northern Europe as has already been shown for western, Central and parts of southern Europe

Incorporating double copies of a chromatin insulator into lentiviral vectors results in less viral integrants

<p>Abstract</p> <p>Background</p> <p>Lentiviral vectors hold great promise as gene transfer vectors in gene therapeutic settings. However, problems related to the risk of insertional mutagenesis, transgene silencing and positional effects have stalled the use of such vectors in the clinic. Chromatin insulators are boundary elements that can prevent enhancer-promoter interactions, if placed between these elements, and protect transgene cassettes from silencing and positional effects. It has been suggested that insulators can improve the safety and performance of lentiviral vectors. Therefore insulators have been incorporated into lentiviral vectors in order to enhance their safety profile and improve transgene expression. Commonly such insulator vectors are produced at lower titers than control vectors thus limiting their potential use.</p> <p>Results</p> <p>In this study we cloned in tandem copies of the chicken β-globin insulator (cHS4) on both sides of the transgene cassette in order to enhance the insulating effect. Our insulator vectors were produced at significantly lower titers compared to control vectors, and we show that this reduction in titer is due to a block during the transduction process that appears after reverse transcription but before integration of the viral DNA. This non-integrated viral DNA could be detected by PCR and, importantly, prevented efficient transduction of target cells.</p> <p>Conclusion</p> <p>These results have importance for the future use of insulator sequences in lentiviral vectors and might limit the use of insulators in vectors for <it>in vivo </it>use. Therefore, a careful analysis of the optimal design must be performed before insulators are included into clinical lentiviral vectors.</p

Sampling, Intervention, Prediction, Aggregation: A Generalized Framework for Model-Agnostic Interpretations

Model-agnostic interpretation techniques allow us to explain the behavior of any predictive model. Due to different notations and terminology, it is difficult to see how they are related. A unified view on these methods has been missing. We present the generalized SIPA (sampling, intervention, prediction, aggregation) framework of work stages for model-agnostic interpretations and demonstrate how several prominent methods for feature effects can be embedded into the proposed framework. Furthermore, we extend the framework to feature importance computations by pointing out how variance-based and performance-based importance measures are based on the same work stages. The SIPA framework reduces the diverse set of model-agnostic techniques to a single methodology and establishes a common terminology to discuss them in future work

Putting evolutionary biology back in the ecological theatre: a demographic framework mapping genes to communities

Question: How can we link genotypic, phenotypic, individual, population, and community levels of organization so as to illuminate general ecological and evolutionary processes and provide a framework for a quantitative, integrative evolutionary biology? Framework: We introduce an evolutionary framework that maps different levels of biological diversity onto one another. We provide (1) an overview of maps linking levels of biological organization and (2) a guideline of how to analyse the complexity of relationships from genes to population growth. Method: We specify the appropriate levels of biological organization for responses to selection, for opportunities for selection, and for selection itself. We map between them and embed these maps into an ecological setting

Fairway: A Way to Build Fair ML Software

Machine learning software is increasingly being used to make decisions that affect people's lives. But sometimes, the core part of this software (the learned model), behaves in a biased manner that gives undue advantages to a specific group of people (where those groups are determined by sex, race, etc.). This "algorithmic discrimination" in the AI software systems has become a matter of serious concern in the machine learning and software engineering community. There have been works done to find "algorithmic bias" or "ethical bias" in the software system. Once the bias is detected in the AI software system, the mitigation of bias is extremely important. In this work, we a)explain how ground-truth bias in training data affects machine learning model fairness and how to find that bias in AI software,b)propose a methodFairwaywhich combines pre-processing and in-processing approach to remove ethical bias from training data and trained model. Our results show that we can find bias and mitigate bias in a learned model, without much damaging the predictive performance of that model. We propose that (1) test-ing for bias and (2) bias mitigation should be a routine part of the machine learning software development life cycle. Fairway offers much support for these two purposes.Comment: ESEC/FSE'20: The 28th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineerin