Free Exercise of Religion: A Luxury Our Nation Can No Longer Afford?

Employment Division v. Smith, 110 S.Ct. 1595 (interim ed. 1990)

The emission by dust and stars of nearby galaxies in the Herschel KINGFISH survey

Using new far-infrared imaging from the Herschel Space Observatory with ancillary data from ultraviolet (UV) to submillimeter wavelengths, we estimate the total emission from dust and stars of 62 nearby galaxies in the KINGFISH survey in a way that is as empirical and model independent as possible. We collect and exploit these data in order to measure from the spectral energy distributions (SEDs) precisely how much stellar radiation is intercepted and re-radiated by dust, and how this quantity varies with galaxy properties. By including SPIRE data, we are more sensitive to emission from cold dust grains than previous analyses at shorter wavelengths, allowing for more accurate estimates of dust temperatures and masses. The dust/stellar flux ratio, which we measure by integrating the SEDs, has a range of nearly three decades (from 10(-2.2) to 10(0.5)). The inclusion of SPIRE data shows that estimates based on data not reaching these far-IR wavelengths are biased low by 17% on average. We find that the dust/stellar flux ratio varies with morphology and total infrared (IR) luminosity, with dwarf galaxies having faint luminosities, spirals having relatively high dust/stellar ratios and IR luminosities, and some early types having low dust/stellar ratios. We also find that dust/stellar flux ratios are related to gas-phase metallicity ((log(f(dust)/f(*)) over bar) = -0.66 +/- 0.08 and -0.22 +/- 0.12 for metal-poor and intermediate-metallicity galaxies, respectively), while the dust/stellar mass ratios are less so (differing by approximate to 0.2 dex); the more metal-rich galaxies span a much wider range of the flux ratios. In addition, the substantial scatter between dust/stellar flux and dust/stellar mass indicates that the former is a poor proxy of the latter. Comparing the dust/stellar flux ratios and dust temperatures, we also show that early types tend to have slightly warmer temperatures (by up to 5 K) than spiral galaxies, which may be due to more intense interstellar radiation fields, or possibly to different dust grain compositions. Finally, we show that early types and early-type spirals have a strong correlation between the dust/stellar flux ratio and specific star formation rate, which suggests that the relatively bright far-IR emission of some of these galaxies is due to ongoing (if limited) star formation as well as to the radiation field from older stars, which is heating the dust grains

Resolving the far-IR line deficit : photoelectric heating and far-IR line cooling in NGC 1097 and NGC 4559

The physical state of interstellar gas and dust is dependent on the processes which heat and cool this medium. To probe heating and cooling of the interstellar medium over a large range of infrared surface brightness, on sub-kiloparsec scales, we employ line maps of [C II] 158 mu m, [O I] 63 mu m, and [N II] 122 mu m in NGC 1097 and NGC 4559, obtained with the Photodetector Array Camera & Spectrometer on board Herschel. We matched new observations to existing Spitzer Infrared Spectrograph data that trace the total emission of polycyclic aromatic hydrocarbons (PAHs). We confirm at small scales in these galaxies that the canonical measure of photoelectric heating efficiency, ([C II] + [O I])/TIR, decreases as the far-infrared (far-IR) color, nu f(nu)(70 mu m) nu f(nu)(100 mu m), increases. In contrast, the ratio of far-IR cooling to total PAH emission, ([C II] + [O I])/PAH, is a near constant similar to 6% over a wide range of far-IR color, 0.5 , derived from models of the IR spectral energy distribution. Emission from regions that exhibit a line deficit is characterized by an intense radiation field, indicating that small grains are susceptible to ionization effects. We note that there is a shift in the 7.7/11.3 mu m PAH ratio in regions that exhibit a deficit in ([C II] + [O I])/PAH, suggesting that small grains are ionized in these environments

Gene Expression Signature of Cigarette Smoking and Its Role in Lung Adenocarcinoma Development and Survival

Tobacco smoking is responsible for over 90% of lung cancer cases, and yet the precise molecular alterations induced by smoking in lung that develop into cancer and impact survival have remained obscure.We performed gene expression analysis using HG-U133A Affymetrix chips on 135 fresh frozen tissue samples of adenocarcinoma and paired noninvolved lung tissue from current, former and never smokers, with biochemically validated smoking information. ANOVA analysis adjusted for potential confounders, multiple testing procedure, Gene Set Enrichment Analysis, and GO-functional classification were conducted for gene selection. Results were confirmed in independent adenocarcinoma and non-tumor tissues from two studies. We identified a gene expression signature characteristic of smoking that includes cell cycle genes, particularly those involved in the mitotic spindle formation (e.g., NEK2, TTK, PRC1). Expression of these genes strongly differentiated both smokers from non-smokers in lung tumors and early stage tumor tissue from non-tumor tissue (p<0.001 and fold-change >1.5, for each comparison), consistent with an important role for this pathway in lung carcinogenesis induced by smoking. These changes persisted many years after smoking cessation. NEK2 (p<0.001) and TTK (p = 0.002) expression in the noninvolved lung tissue was also associated with a 3-fold increased risk of mortality from lung adenocarcinoma in smokers.Our work provides insight into the smoking-related mechanisms of lung neoplasia, and shows that the very mitotic genes known to be involved in cancer development are induced by smoking and affect survival. These genes are candidate targets for chemoprevention and treatment of lung cancer in smokers

Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Davis, G. E., Baumgartner, M. F., Corkeron, P. J., Bell, J., Berchok, C., Bonnell, J. M., Thornton, J. B., Brault, S., Buchanan, G. A., Cholewiak, D. M., Clark, C. W., Delarue, J., Hatch, L. T., Klinck, H., Kraus, S. D., Martin, B., Mellinger, D. K., Moors-Murphy, H., Nieukirk, S., Nowacek, D. P., Parks, S. E., Parry, D., Pegg, N., Read, A. J., Rice, A. N., Risch, D., Scott, A., Soldevilla, M. S., Stafford, K. M., Stanistreet, J. E., Summers, E., Todd, S., & Van Parijs, S. M. Exploring movement patterns and changing distributions of baleen whales in the western North Atlantic using a decade of passive acoustic data. Global Change Biology, (2020): 1-30, doi:10.1111/gcb.15191.Six baleen whale species are found in the temperate western North Atlantic Ocean, with limited information existing on the distribution and movement patterns for most. There is mounting evidence of distributional shifts in many species, including marine mammals, likely because of climate‐driven changes in ocean temperature and circulation. Previous acoustic studies examined the occurrence of minke (Balaenoptera acutorostrata ) and North Atlantic right whales (NARW; Eubalaena glacialis ). This study assesses the acoustic presence of humpback (Megaptera novaeangliae ), sei (B. borealis ), fin (B. physalus ), and blue whales (B. musculus ) over a decade, based on daily detections of their vocalizations. Data collected from 2004 to 2014 on 281 bottom‐mounted recorders, totaling 35,033 days, were processed using automated detection software and screened for each species' presence. A published study on NARW acoustics revealed significant changes in occurrence patterns between the periods of 2004–2010 and 2011–2014; therefore, these same time periods were examined here. All four species were present from the Southeast United States to Greenland; humpback whales were also present in the Caribbean. All species occurred throughout all regions in the winter, suggesting that baleen whales are widely distributed during these months. Each of the species showed significant changes in acoustic occurrence after 2010. Similar to NARWs, sei whales had higher acoustic occurrence in mid‐Atlantic regions after 2010. Fin, blue, and sei whales were more frequently detected in the northern latitudes of the study area after 2010. Despite this general northward shift, all four species were detected less on the Scotian Shelf area after 2010, matching documented shifts in prey availability in this region. A decade of acoustic observations have shown important distributional changes over the range of baleen whales, mirroring known climatic shifts and identifying new habitats that will require further protection from anthropogenic threats like fixed fishing gear, shipping, and noise pollution.We thank Chris Pelkie, David Wiley, Michael Thompson, Chris Tessaglia‐Hymes, Eric Matzen, Chris Tremblay, Lance Garrison, Anurag Kumar, John Hildebrand, Lynne Hodge, Russell Charif, Kathleen Dudzinski, and Ann Warde for help with project planning, field work support, and data management. For all the support and advice, thanks to the NEFSC Protected Species Branch, especially the passive acoustics group, Josh Hatch, and Leah Crowe. We thank the field and crew teams on all the ships that helped in the numerous deployments and recoveries. This research was funded and supported by many organizations, specified by projects as follows: data recordings from region 1 were provided by K. Stafford (funding: National Science Foundation #NSF‐ARC 0532611). Region 2 data: D. K. Mellinger and S. Nieukirk, National Oceanic and Atmospheric Administration (NOAA) PMEL contribution #5055 (funding: NOAA and the Office of Naval Research #N00014–03–1–0099, NOAA #NA06OAR4600100, US Navy #N00244‐08‐1‐0029, N00244‐09‐1‐0079, and N00244‐10‐1‐0047). Region 3A data: D. Risch (funding: NOAA and Navy N45 programs). Region 3 data: H. Moors‐Murphy and Fisheries and Oceans Canada (2005–2014 data), and the Whitehead Lab of Dalhousie University (eastern Scotian Shelf data; logistical support by A. Cogswell, J. Bartholette, A. Hartling, and vessel CCGS Hudson crew). Emerald Basin and Roseway Basin Guardbuoy data, deployment, and funding: Akoostix Inc. Region 3 Emerald Bank and Roseway Basin 2004 data: D. K. Mellinger and S. Nieukirk, NOAA PMEL contribution #5055 (funding: NOAA). Region 4 data: S. Parks (funding: NOAA and Cornell University) and E. Summers, S. Todd, J. Bort Thornton, A. N. Rice, and C. W. Clark (funding: Maine Department of Marine Resources, NOAA #NA09NMF4520418, and #NA10NMF4520291). Region 5 data: S. M. Van Parijs, D. Cholewiak, L. Hatch, C. W. Clark, D. Risch, and D. Wiley (funding: National Oceanic Partnership Program (NOPP), NOAA, and Navy N45). Region 6 data: S. M. Van Parijs and D. Cholewiak (funding: Navy N45 and Bureau of Ocean and Energy Management (BOEM) Atlantic Marine Assessment Program for Protected Species [AMAPPS] program). Region 7 data: A. N. Rice, H. Klinck, A. Warde, B. Martin, J. Delarue, and S. Kraus (funding: New York State Department of Environmental Conservation, Massachusetts Clean Energy Center, and BOEM). Region 8 data: G. Buchanan, and K. Dudzinski (funding: New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund) and A. N. Rice, C. W. Clark, and H. Klinck (funding: Center for Conservation Bioacoustics at Cornell University and BOEM). Region 9 data: J. E. Stanistreet, J. Bell, D. P. Nowacek, A. J. Read, and S. M. Van Parijs (funding: NOAA and US Fleet Forces Command). Region 10 data: L. Garrison, M. Soldevilla, C. W. Clark, R. A. Chariff, A. N. Rice, H. Klinck, J. Bell, D. P. Nowacek, A. J. Read, J. Hildebrand, A. Kumar, L. Hodge, and J. E. Stanistreet (funding: US Fleet Forces Command, BOEM, NOAA, and NOPP). Region 11 data: C. Berchok as part of a collaborative project led by the Fundacion Dominicana de Estudios Marinos, Inc. (Dr. Idelisa Bonnelly de Calventi; funding: The Nature Conservancy [Elianny Dominguez]) and D. Risch (funding: World Wildlife Fund, NOAA, and Dutch Ministry of Economic Affairs)

Physical Parameters of the Multiplanet Systems HD 106315 and GJ 9827

HD 106315 and GJ 9827 are two bright, nearby stars that host multiple super-Earths and sub-Neptunes discovered by K2 that are well suited for atmospheric characterization. We refined the planets' ephemerides through Spitzer transits, enabling accurate transit prediction required for future atmospheric characterization through transmission spectroscopy. Through a multiyear high-cadence observing campaign with Keck/High Resolution Echelle Spectrometer and Magellan/Planet Finder Spectrograph, we improved the planets' mass measurements in anticipation of Hubble Space Telescope transmission spectroscopy. For GJ 9827, we modeled activity-induced radial velocity signals with a Gaussian process informed by the Calcium II H&K lines in order to more accurately model the effect of stellar noise on our data. We measured planet masses of M_b = 4.87 ± 0.37 M_⊕, M_c = 1.92 ± 0.49 M_⊕, and M_d = 3.42 ± 0.62 M_⊕. For HD 106315, we found that such activity radial velocity decorrelation was not effective due to the reduced presence of spots and speculate that this may extend to other hot stars as well (T_(eff) > 6200 K). We measured planet masses of M_b = 10.5 ± 3.1 M_⊕ and M_c = 12.0 ± 3.8 M_⊕. We investigated all of the planets' compositions through comparison of their masses and radii to a range of interior models. GJ 9827 b and GJ 9827 c are both consistent with a 50/50 rock-iron composition, GJ 9827 d and HD 106315 b both require additional volatiles and are consistent with moderate amounts of water or hydrogen/helium, and HD 106315 c is consistent with a ~10% hydrogen/helium envelope surrounding an Earth-like rock and iron core