The inheritance of germless seeds in maize

1. The character known as germless in maize is described. Data are presented on its occurrance and the manner of inheritance and linkage relations of the genetic factors causing the character, together with data on other linkage relations in group II. 2. It is shown that germless seeds commonly occur in our commercial varieties of corn. 3. Data are presented on the inheritance of two different factors, gm2 and gm1, which cause germless seeds. 4. Linkage relations of gm2 and gm1 with factors in linkage group II were determined. 5. The factor gm2 was found to be linked with R with 27.11 percent of crossing over as compared to 31 percent previously reported by Demerec (6). 6. The gm2 factor, however, did not show, in the F2 data, evidences of linkage with G or Pg1 . The lack of evidence of linkage with G is explained by assuming gm2 to be located to the left of R, while G has been shown by Lindstrom (9 and 10) to be located to the right of R with a crossover percentage of 20. The lack of evidence of linkage with Pg1 is explained in the same way after the presentation of data to show that Pg1 is also located to the right of R near G with 14.57 percent of crossing over between G and Pg1. 7. Data presented show no linkage between gm1 and r or c. 8. There is some evidence of linkage between gm1 and G but not sufficient to be conclusive. 9. Data on gm1 and Pr showed no linkage of these two factors. 10. Rather extensive data on R and Pr showed conclusively that there is no linkage between these two factors as reported by Hayes and Brewbaker (8). 11. Some data are also presented which show that there is no linkage between Pr and G. 12. Linkage data on R and G show a crossover percentage of about 20 which checks with data previously reported by Lindstrom (9 and 10). 13. The percentage of crossing over between R and Pg1 was found to be 23.39 which checks with Brunson\u27s (3) data on these two factors

Persistent Regulations: A Detailed Assessment of the Trump Administration\u27s Efforts to Repeal Federal Climate Regulations

This paper takes a critical look at what the Trump administration has actually accomplished in terms of repealing and modifying greenhouse gas emission standards and otherwise advancing its pro-fossil fuel agenda. As detailed herein and summarized in Figures 1 and 2, the scope of the efforts taken pursuant to this agenda is extremely broad – there are dozens of different deregulatory actions underway at various agencies, most notably the Environmental Protection Agency (EPA). But in most cases, the pace of these efforts has been quite slow. This is particularly true for efforts to repeal or revise major regulations like the Clean Power Plan and the motor vehicle greenhouse gas emission and fuel economy standards, as the administration must adhere to notice-and-comment procedures and must also justify any changes to these rules in light of the statutory provisions it is implementing

Further development of an improved altimeter wind speed algorithm

A previous altimeter wind speed retrieval algorithm was developed on the basis of wind speeds in the the limited range from about 4 to 14 ms¯¹. In this paper, we use a new approach which gives a wind speed model function applicable over the range 0 to 21 ms¯¹. The method is based on comparing 50 km along-track averages of the altimeter normalized radar cross section measurements with neighboring off-nadir scatterometer wind speed measurements. The scatterometer winds are constructed from 100 km binned measurements of radar cross section and are located approximately 200 km from the satellite subtrack. The new model function agrees very well with earlier versions up to wind speeds of 14 ms¯¹ but differs significantly at higher wind speeds. We discuss the relevance of these results to the Geosat altimeter launched in March 1985

Global Microwave Satellite Observations of Sea Surface Temperature for Numerical Weather Prediction and Climate Research

Obtaining global sea surface temperature (SST) fields for the ocean boundary condition in numerical weather prediction (NWP) models and for climate research has long been problematic. Historically, such fields have been constructed by a blending of in situ observations from ships and buoys and satellite infrared observations from the Advanced Very High Resolution Radiometer (AVHRR) that has been operational on NOAA satellites since November 1981. The resolution of these global SST fields is limited by the sparse coverage of in situ observations in many areas of the World Ocean and cloud contamination of AVHRR observations, which can exceed 75% over the subpolar oceans. As clouds and aerosols are essentially transparent to microwave radiation, satellite microwave observations can greatly improve the sampling and resolution of global SST fields. The Advanced Microwave Scanning Radiometer on the NASA Earth Observing System (EOS) Aqua satellite (AMSR-E) is providing the first highly accurate and global satellite microwave observations of SST. The potential for AMSR-E observations to improve the sampling, resolution, and accuracy of SST fields for NWP and climate research is demonstrated from example SST fields and from an investigation of the sensitivity of NWP models to specification of the SST boundary condition

Flux of atmospheric muons: Comparison between AIRES simulations and CAPRICE98 data

We report on a comparison between the flux of muons in the atmosphere measured by the CAPRICE98 experiment and simulations performed with the air shower simulation program AIRES. To reduce systematic uncertainties we have used as input the primary fluxes of protons and helium nuclei also measured by the CAPRICE98 experiment. Heavy nuclei are also taken into account in the primary flux, and their contribution to the muon flux is discussed. The results of the simulations show a very good agreement with the experimental data, at all altitudes and for all muon momenta. With the exception of a few isolated points, the relative differences between measured data and simulations are smaller than 20 %; and in all cases compatible with zero within two standard deviations. The influence of the input cosmic ray flux on the results of the simulations is also discussed. This report includes also an extensive analysis of the characteristics of the simulated fluxes.Comment: Accepted for publication in Physical Review

53BP1 expression is a modifier of the prognostic value of lymph node ratio and CA 19–9 in pancreatic adenocarcinoma

BACKGROUND: 53BP1 binds to the tumor suppressor p53 and has a key role in DNA damage response and repair. Low 53BP1 expression has been associated with decreased survival in breast cancer and has been shown to interact with several prognostic factors in non-small cell lung cancer. The role of 53BP1 in pancreatic ductal adenocarcinoma (PDAC) has yet to be determined. We aimed to investigate whether 53BP1 levels interact with established prognostic factors in PDAC. METHODS: 106 patients for whom there was tissue available at time of surgical resection for PDAC were included. A tissue microarray was constructed using surgical specimens, stained with antibodies to 53BP1, and scored for expression intensity. Univariate and multivariate statistical analyses were performed to investigate the association between 53BP1 and patient survival with known prognostic factors for survival. RESULTS: The association of 53BP1 with several established prognostic factors was examined, including stage, tumor grade, surgical margin, peripancreatic extension, lymph node ratio (LNR), and CA 19–9. We found that 53BP1 modified the effects of known prognostic variables including LNR and CA 19–9 on survival outcomes. When 53BP1 intensity was low, increased LNR was associated with decreased OS (HR 4.84, 95% CI (2.26, 10.37), p<0.001) and high CA19-9 was associated with decreased OS (HR 1.72, 95% CI (1.18, 2.51), p=0.005). When 53BP1 intensity was high, LNR and CA19-9 were no longer associated with OS (p=0.958 and p=0.606, respectively). CONCLUSIONS: In this study, 53BP1, a key player in DNA damage response and repair, was found to modify the prognostic value of two established prognostic factors, LNR and CA 19–9, suggesting 53BP1 may alter tumor behavior and ultimately impact how we interpret the value of other prognostic factors

Simulation of Atmospheric Muon and Neutrino Fluxes with CORSIKA

The fluxes of atmospheric muons and neutrinos are calculated by a three dimensional Monte Carlo simulation with the air shower code CORSIKA using the hadronic interaction models DPMJET, VENUS, GHEISHA, and UrQMD. For the simulation of low energy primary particles the original CORSIKA has been extended by a parametrization of the solar modulation and a microscopic calculation of the directional dependence of the geomagnetic cut-off functions. An accurate description for the geography of the Earth has been included by a digital elevation model, tables for the local magnetic field in the atmosphere, and various atmospheric models for different geographic latitudes and annual seasons. CORSIKA is used to calculate atmospheric muon fluxes for different locations and the neutrino fluxes for Kamioka. The results of CORSIKA for the muon fluxes are verified by an extensive comparison with recent measurements. The obtained neutrino fluxes are compared with other calculations and the influence of the hadronic interaction model, the geomagnetic cut-off and the local magnetic field on the neutrino fluxes is investigated.Comment: revtex, 19 pages, 19 Postscript figures, submitted to Phys. Rev.