An overview of the involvement of women in fisheries activities in Oceania

Role of women, Fisheries, Oceania,

Letting Go of “Natural Kind”: Toward a Multidimensional Framework of Nonarbitrary Classification

This article uses the case study of ethnobiological classification to develop a positive and a negative thesis about the state of natural kind debates. On the one hand, I argue that current accounts of natural kinds can be integrated in a multidimensional framework that advances understanding of classificatory practices in ethnobiology. On the other hand, I argue that such a multidimensional framework does not leave any substantial work for the notion “natural kind” and that attempts to formulate a general account of naturalness have become an obstacle to understanding classificatory practices

HATS-8b: A Low-Density Transiting Super-Neptune

HATS-8b is a low density transiting super-Neptune discovered as part of the HATSouth project. The planet orbits its solar-like G dwarf host (V=14.03 $\pm$ 0.10 and T$_{eff}$ =5679 $\pm$ 50 K) with a period of 3.5839 d. HATS-8b is the third lowest mass transiting exoplanet to be discovered from a wide-field ground based search, and with a mass of 0.138 $\pm$ 0.019 M$_J$ it is approximately half-way between the masses of Neptune and Saturn. However HATS-8b has a radius of 0.873 (+0.123,-0.075) R$_J$, resulting in a bulk density of just 0.259 $\pm$ 0.091 g.cm$^{-3}$. The metallicity of the host star is super-Solar ([Fe/H]=0.210 $\pm$ 0.080), arguing against the idea that low density exoplanets form from metal-poor environments. The low density and large radius of HATS-8b results in an atmospheric scale height of almost 1000 km, and in addition to this there is an excellent reference star of near equal magnitude at just 19 arcsecond separation on the sky. These factors make HATS-8b an exciting target for future atmospheric characterization studies, particularly for long-slit transmission spectroscopy.Comment: 11 pages, 7 figures, accepted for publication in A

HATS-1b: The First Transiting Planet Discovered by the HATSouth Survey

We report the discovery of HATS-1b, a transiting extrasolar planet orbiting the moderately bright V=12.05 G dwarf star GSC 6652-00186, and the first planet discovered by HATSouth, a global network of autonomous wide-field telescopes. HATS-1b has a period P~3.4465 d, mass Mp~1.86MJ, and radius Rp~1.30RJ. The host star has a mass of 0.99Msun, and radius of 1.04Rsun. The discovery light curve of HATS-1b has near continuous coverage over several multi-day periods, demonstrating the power of using a global network of telescopes to discover transiting planets.Comment: Submitted to AJ 10 pages, 5 figures, 6 table

Elimination of gender-related employment disparities through statistical process control

This paper proposes a novel approach that has the potential to hasten the eradication of gender disparities in employment. This approach relies upon the concept of statistical process control (SPC) to more systematically remedy disparate employment outcomes for women. SPC also serves as a new vehicle for conceptualizing the influence of industry on equal employment opportunity (EEO) outcomes. Using data from U.S. Current Population Surveys, we compare industries on EEO performance as assessed by a recently developed Systemic Gender Disparity Scorecard. The theory and practice of SPC suggest that further improvement, and by far the greater opportunity for gender-related EEO progress, necessitates fundamental changes in each industry's practices and norms that serve as barriers to gender parity. We recommend more resources to support collaboration between employers and EEO enforcement agencies.Women - Employment

Ensemble tractography

Fiber tractography uses diffusion MRI to estimate the trajectory and cortical projection zones of white matter fascicles in the living human brain. There are many different tractography algorithms and each requires the user to set several parameters, such as curvature threshold. Choosing a single algorithm with a specific parameters sets poses two challenges. First, different algorithms and parameter values produce different results. Second, the optimal choice of algorithm and parameter value may differ between different white matter regions or different fascicles, subjects, and acquisition parameters. We propose using ensemble methods to reduce algorithm and parameter dependencies. To do so we separate the processes of fascicle generation and evaluation. Specifically, we analyze the value of creating optimized connectomes by systematically combining candidate fascicles from an ensemble of algorithms (deterministic and probabilistic) and sweeping through key parameters (curvature and stopping criterion). The ensemble approach leads to optimized connectomes that provide better cross-validatedprediction error of the diffusion MRI data than optimized connectomes generated using the singlealgorithms or parameter set. Furthermore, the ensemble approach produces connectomes that contain both short- and long-range fascicles, whereas single-parameter connectomes are biased towards one or the other. In summary, a systematic ensemble tractography approach can produce connectomes that are superior to standard single parameter estimates both for predicting the diffusion measurements and estimating white matter fascicles.Fil: Takemura, Hiromasa. University of Stanford; Estados Unidos. Osaka University; JapónFil: Caiafa, César Federico. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas. Instituto Argentino de Radioastronomía. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto Argentino de Radioastronomía; ArgentinaFil: Wandell, Brian A.. University of Stanford; Estados UnidosFil: Pestilli, Franco. Indiana University; Estados Unido

Estimating moose population parameters from aerial surveys

Successful moose management depends on knowledge of population dynamics. The principal parameters required are size, rate of change, recruitment, sex composition, and mortality. Moose management in Alaska has been severely hampered by the lack of good estimates of these parameters, and unfortunately, this lack contributed to the decline of many Alaskan moose populations during the 1970s (e.g., Gasaway et al. 1983). The problems were: (1) population size not adequately estimated, (2) rapid rates of decline not acknowledged until populations were low, (3) meaningful recruitment rates were not available in the absence of good population estimates, and (4) calf and adult mortality rates were grossly underestimated. Frustration of moose managers working with inadequate data led to development of aerial survey procedures that yield minimally biased, sufficiently precise estimates of population parameters for most Alaskan moose management and research. This manual describes these procedures. Development of these procedures would have been impossible without the inspiration, support, advice, and criticism of many colleagues. We thank these colleagues for their contributions. Dale Haggstrom and Dave Kelleyhouse helped develop flight patterns, tested and improved early sampling designs, and as moose managers, put these procedures into routine use. Pilots Bill Lentsch and Pete Haggland were instrumental in developing and testing aerial surveying techniques. Their interest and dedication to improving moose management made them valuable allies. Statisticians Dana Thomas of the University of Alaska and W. Scott Overton of Oregon State University provided advice on variance approximations for the population estimator. Warren Ballard, Sterling Miller, SuzAnne Miller, Doug Larsen, and Wayne Kale tested procedures and provided valuable criticisms and suggestions. Jim Raymond initially programmed a portable calculator to make lengthy calculation simple, fast, and error-free. Angie Babcock, Lisa Ingalls, Vicky Leffingwell, and Laura McManus patiently typed several versions of this manual. John Coady and Oliver Burris provided continuous moral and financial support for a 3-year project that lasted 6 years. Joan Barnett, Rodney Boetje, Steven Peterson, and Wayne Regelin of the Alaska Department of Fish and Game provided helpful editorial suggestions in previous drafts. Finally, we thank referees David Anderson of the Utah Cooperative Wildlife Research Unit, Vincent Schultz of Washington State University, and James Peek, E. "Oz" Garton, and Mike Samuel of the University of Idaho whose comments and suggestions improved this manual. This project was funded by the Alaska Department of Fish and Game through Federal Aid in Wildlife Restoration Projects W-17-9 through W-22-1