On the ability of space-based passive and active remote sensing observations of CO2 to detect flux perturbations to the carbon cycle

Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Atmospheres 123 (2018): 1460–1477, doi:10.1002/2017JD027836.Space-borne observations of CO2 are vital to gaining understanding of the carbon cycle in regions of the world that are difficult to measure directly, such as the tropical terrestrial biosphere, the high northern and southern latitudes, and in developing nations such as China. Measurements from passive instruments such as GOSAT and OCO-2, however, are constrained by solar zenith angle limitations as well as sensitivity to the presence of clouds and aerosols. Active measurements such as those in development for the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS) mission show strong potential for making measurements in the high-latitude winter and in cloudy regions. In this work we examine the enhanced flux constraint provided by the improved coverage from an active measurement such as ASCENDS. The simulation studies presented here show that with sufficient precision, ASCENDS will detect permafrost thaw and fossil fuel emissions shifts at annual and seasonal time scales, even in the presence of transport errors, representativeness errors, and biogenic flux errors. While OCO-2 can detect some of these perturbations at the annual scale, the seasonal sampling provided by ASCENDS provides the stronger constraint.NASA Grant Numbers: NNX15AJ27G, NNX15AH13G2018-07-2

Open Sequence Initiative: a part submission standard to complement modern DNA assembly techniques

The discipline of synthetic biology emphasizes the application of engineering principles such as standardization, abstraction, modularity, and rational design to complex biological systems. The archetypical example of such standardization is BioBrick RFC[10], introduced in 2003 by Tom Knight at MIT. BioBricks are stored on a standard plasmid, pSB1C3, which contains prefix and suffix sequences flanking the DNA sequence specifying a biological part. The prefix and suffix sequences contain two pairs of 6 base-pair (bp) restriction enzyme sites (EcoRI+XbaI and SpeI+PstI), which can be used for both part assembly and quality control. BioBricks are intended to be well- characterized biological parts, such as genes or promoters, that function in a predictable fashion and can be readily combined to make complex systems. The rules of the RFC[10] BioBrick assembly method require that none of the restriction sites used in the prefix and suffix be present in the parts themselves. This requirement can be an onerous imposition for iGEM teams developing large, novel parts, such as genes or entire operons that are obtained by amplifying DNA sequences from environmental samples or microorganisms. While iGEM teams may use methods such as site-directed mutagenesis to remove illegal restriction sites from a part's sequence, it is certainly possible that this mutation will alter the functionality of the part – a very undesirable outcome. In addition, the mutagenesis of illegal restriction sites is an unnecessary burden on teams, given the limited time and resources available to teams during each year’s iGEM competition. Efforts spent mutagenizing sites would be better spent characterizing and improving parts. This RFC proposes an alternative submission standard to eliminate these problems

ESD Reviews: Model dependence in multi-model climate ensembles: weighting, sub-selection and out-of-sample testing

The rationale for using multi-model ensembles in climate change projections and impacts research is often based on the expectation that different models constitute independent estimates; therefore, a range of models allows a better characterisation of the uncertainties in the representation of the climate system than a single model. However, it is known that research groups share literature, ideas for representations of processes, parameterisations, evaluation data sets and even sections of model code. Thus, nominally different models might have similar biases because of similarities in the way they represent a subset of processes, or even be near-duplicates of others, weakening the assumption that they constitute independent estimates. If there are near-replicates of some models, then treating all models equally is likely to bias the inferences made using these ensembles. The challenge is to establish the degree to which this might be true for any given application. While this issue is recognised by many in the community, quantifying and accounting for model dependence in anything other than an ad-hoc way is challenging. Here we present a synthesis of the range of disparate attempts to define, quantify and address model dependence in multi-model climate ensembles in a common conceptual framework, and provide guidance on how users can test the efficacy of approaches that move beyond the equally weighted ensemble. In the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6), several new models that are closely related to existing models are anticipated, as well as large ensembles from some models. We argue that quantitatively accounting for dependence in addition to model performance, and thoroughly testing the effectiveness of the approach used will be key to a sound interpretation of the CMIP ensembles in future scientific studies.</p

The Role of I Region Gene Products in Macrophage - T Lymphocyte Interaction

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73965/1/j.1600-065X.1978.tb00400.x.pd

Genetic analysis of an H-2 mutant, B6.C-H-2 ba , using cell-mediated lympholysis: T- and B-cell dictionaries for histocompatibility determinants are different

B6.C-H-2 ba [H (z1)] is a mutant derived from C57BL/6. The two strains mutually reject their skingrafts and are incompatible in the mixed leucocyte reaction (MLR) and in cell-mediated lympholysis (CML) assays. They are serologically indistinguishable.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46732/1/251_2005_Article_BF01564084.pd