Spatial distribution of Chlorpyrifos and Endosulfan in USA coastal waters and the Great Lakes

Between 1994 and 1997, 258 tissue and 178 sediment samples were analyzed for chlorpyrifos throughout the coastal United States and the Great Lakes. Subsequently, 95 of the 1997 tissue samples were reanalyzed for endosulfan. Tissue chlorpyrifos concentrations, which exceeded the 90th percentile, were found in coastal regions known to have high agricultural use rates but also strongly correlated with sites near high population. The highest concentrations of endosulfans in contrast, were generally limited to agricultural regions of the country. Detections of chlorpyrifos at several Alaskan sites suggest an atmospheric transport mechanism. Many Great Lakes sites had chlorpyrifos tissue concentrations above the 90th percentile which decreased with increasing distance from the Corn Belt region (Iowa, Indiana, Illinois, and Wisconsin) where most agriculturally applied chlorpyrifos is used. Correlation analysis suggests that fluvial discharge is the primary transport pathway on the Atlantic and Gulf of Mexico coasts for chlorpyrifos but not necessarily for endosulfans. (PDF contains 28 pages

Reductions in the dietary niche of southern sea otters (Enhydra lutris nereis) from the Holocene to the Anthropocene.

The sea otter (Enhydra lutris) is a marine mammal hunted to near extinction during the 1800s. Despite their well-known modern importance as a keystone species, we know little about historical sea otter ecology. Here, we characterize the ecological niche of ancient southern sea otters (E. lutris nereis) using δ13C analysis and δ15N analysis of bones recovered from archaeological sites spanning ~7,000 to 350 years before present (N = 112 individuals) at five regions along the coast of California. These data are compared with previously published data on modern animals (N = 165) and potential modern prey items. In addition, we analyze the δ15N of individual amino acids for 23 individuals to test for differences in sea otter trophic ecology through time. After correcting for tissue-specific and temporal isotopic effects, we employ nonparametric statistics and Bayesian niche models to quantify differences among ancient and modern animals. We find ancient otters occupied a larger isotopic niche than nearly all modern localities; likely reflecting broader habitat and prey use in prefur trade populations. In addition, ancient sea otters at the most southerly sites occupied an isotopic niche that was more than twice as large as ancient otters from northerly regions. This likely reflects greater invertebrate prey diversity in southern California relative to northern California. Thus, we suggest the potential dietary niche of sea otters in southern California could be larger than in central and northern California. At two sites, Año Nuevo and Monterey Bay, ancient otters had significantly higher δ15N values than modern populations. Amino acid δ15N data indicated this resulted from shifting baseline isotope values, rather than a change in sea otter trophic ecology. Our results help in better understanding the contemporary ecological role of sea otters and exemplify the strength of combing zooarchaeological and biological information to provide baseline data for conservation efforts

Connectionist Theory Refinement: Genetically Searching the Space of Network Topologies

An algorithm that learns from a set of examples should ideally be able to exploit the available resources of (a) abundant computing power and (b) domain-specific knowledge to improve its ability to generalize. Connectionist theory-refinement systems, which use background knowledge to select a neural network's topology and initial weights, have proven to be effective at exploiting domain-specific knowledge; however, most do not exploit available computing power. This weakness occurs because they lack the ability to refine the topology of the neural networks they produce, thereby limiting generalization, especially when given impoverished domain theories. We present the REGENT algorithm which uses (a) domain-specific knowledge to help create an initial population of knowledge-based neural networks and (b) genetic operators of crossover and mutation (specifically designed for knowledge-based networks) to continually search for better network topologies. Experiments on three real-world domains indicate that our new algorithm is able to significantly increase generalization compared to a standard connectionist theory-refinement system, as well as our previous algorithm for growing knowledge-based networks.Comment: See http://www.jair.org/ for any accompanying file

Multi-Element Abundance Measurements from Medium-Resolution Spectra. II. Catalog of Stars in Milky Way Dwarf Satellite Galaxies

We present a catalog of Fe, Mg, Si, Ca, and Ti abundances for 2961 red giant stars that are likely members of eight dwarf satellite galaxies of the Milky Way (MW): Sculptor, Fornax, Leo I, Sextans, Leo II, Canes Venatici I, Ursa Minor, and Draco. For the purposes of validating our measurements, we also observed 445 red giants in MW globular clusters and 21 field red giants in the MW halo. The measurements are based on Keck/DEIMOS medium-resolution spectroscopy combined with spectral synthesis. We estimate uncertainties in [Fe/H] by quantifying the dispersion of [Fe/H] measurements in a sample of stars in monometallic globular clusters. We estimate uncertainties in Mg, Si, Ca, and Ti abundances by comparing our medium-resolution spectroscopic measurements to high-resolution spectroscopic abundances of the same stars. For this purpose, our DEIMOS sample included 132 red giants with published high-resolution spectroscopy in globular clusters, the MW halo field, and dwarf galaxies. The standard deviations of the differences in [Fe/H] and [alpha/Fe] (the average of [Mg/Fe], [Si/Fe], [Ca/Fe], and [Ti/Fe]) between the two samples is 0.15 and 0.16, respectively. This catalog represents the largest sample of multi-element abundances in dwarf galaxies to date. The next papers in this series draw conclusions on the chemical evolution, gas dynamics, and star formation histories from the catalog presented here. The wide range of dwarf galaxy luminosity reveals the dependence of dwarf galaxy chemical evolution on galaxy stellar mass.Comment: 26 pages, 22 figures, 4 machine-readable tables (available in the source file; click "Other formats"); accepted for publication in ApJ Supplements; updated acknowledgments in v

Santa Clara Magazine, Volume 33 Number 4, Summer 1991

12 - GEORGE BUSH AND THE QUESTION OF STYLE The president\u27s campaign strategists have had Bush play up the victory in the Persian Gulf and avoid talk of much else. By Rita Beamish \u2774 17 - MIND OVER MONEY Challenging accepted notions about how to make money in the stock market through research on the psychology of investing. By Kathryn Bold \u2781 20 - STRESS: THE DEMOCRATIC AILMENT From bricklayers to stock brokers, everyone is susceptible to stress. By Elizabeth Fernandez \u2779 24 - CHARLES LAMPKIN: ON THE LONG ROAD Remembering the actor and music man who was SCU\u27s artist-inresidence from 1969- 1981. By James Torrens, S.J. 26 - HISPANIC CALIFORNIANS AND CATHOLIC HIGHER EDUCATION A look at the personal diaries of a Hispanic student who attended Santa Clara from 1857- 1864. By Gerald McKevin, S.J.https://scholarcommons.scu.edu/sc_mag/1044/thumbnail.jp

Coyote (Canis latrans) use of marine resources in coastal California: A new behavior relative to their recent ancestors

Coyotes ( Canis latrans) are known to consume marine foods, but the importance and persistence of marine subsidies to coyotes is unknown. Recent access to a marine subsidy, especially if gained following apex predator loss, may facilitate coyote expansion along coastal routes and amplify the effects of mesopredator release. Our goal was to quantify and contextualize past and present marine resource use by coyotes on the central coast of California via stable isotope analysis. We measured δ13C and δ15N values in coyotes, their competitors, and their food resources at two modern sites, seven archaeological sites spanning in age from ~3000 to 750 BP, and from historical (AD 1893–1992) coyote and grizzly bear hair and bone sourced from coastal counties. We found evidence for marine resource use by modern coastal California coyotes at one site, Año Nuevo, which hosts a mainland northern elephant seal ( Mirounga angustirostris) breeding colony. Seals and sea lions account for ~20% of Año Nuevo coyote diet throughout the year and this marine subsidy likely positively impacts coyote population size. Isotopic data suggest that neither historic nor prehistoric coyotes consumed marine-derived foods, even at sites near ancient mainland seal rookeries. Marine resource use by some contemporary California coyotes is a novel behavior relative to their recent ancestors. We hypothesize that human alteration of the environment through extirpation of the California grizzly bear and the more recent protection of marine mammals likely enabled this behavioral shift

Neuromorphic analogue VLSI

Neuromorphic systems emulate the organization and function of nervous systems. They are usually composed of analogue electronic circuits that are fabricated in the complementary metal-oxide-semiconductor (CMOS) medium using very large-scale integration (VLSI) technology. However, these neuromorphic systems are not another kind of digital computer in which abstract neural networks are simulated symbolically in terms of their mathematical behavior. Instead, they directly embody, in the physics of their CMOS circuits, analogues of the physical processes that underlie the computations of neural systems. The significance of neuromorphic systems is that they offer a method of exploring neural computation in a medium whose physical behavior is analogous to that of biological nervous systems and that operates in real time irrespective of size. The implications of this approach are both scientific and practical. The study of neuromorphic systems provides a bridge between levels of understanding. For example, it provides a link between the physical processes of neurons and their computational significance. In addition, the synthesis of neuromorphic systems transposes our knowledge of neuroscience into practical devices that can interact directly with the real world in the same way that biological nervous systems do

A practical Bayesian framework for backpropagation networks

A quantitative and practical Bayesian framework is described for learning of mappings in feedforward networks. The framework makes possible (1) objective comparisons between solutions using alternative network architectures, (2) objective stopping rules for network pruning or growing procedures, (3) objective choice of magnitude and type of weight decay terms or additive regularizers (for penalizing large weights, etc.), (4) a measure of the effective number of well-determined parameters in a model, (5) quantified estimates of the error bars on network parameters and on network output, and (6) objective comparisons with alternative learning and interpolation models such as splines and radial basis functions. The Bayesian "evidence" automatically embodies "Occam's razor," penalizing overflexible and overcomplex models. The Bayesian approach helps detect poor underlying assumptions in learning models. For learning models well matched to a problem, a good correlation between generalization ability and the Bayesian evidence is obtained

Recent changes in breast cancer incidence and risk factor prevalence in San Francisco Bay area and California women: 1988 to 2004

IntroductionHistorically, the incidence rate of breast cancer among non-Hispanic white women living in the San Francisco Bay area (SFBA) of California has been among the highest in the world. Substantial declines in breast cancer incidence rates have been documented in the United States and elsewhere during recent years. In light of these reports, we examined recent changes in breast cancer incidence and risk factor prevalence among non-Hispanic white women in the SFBA and other regions of California.MethodsAnnual age-adjusted breast cancer incidence and mortality rates (1988 to 2004) were obtained from the California Cancer Registry and analyzed using Joinpoint regression. Population-based risk factor prevalences were calculated using two data sources: control subjects from four case-control studies (1989 to 1999) and the 2001 and 2003 California Health Interview Surveys.ResultsIn the SFBA, incidence rates of invasive breast cancer increased 1.3% per year (95% confidence interval [CI], 0.7% to 2.0%) in 1988-1999 and decreased 3.6% per year (95% CI, 1.6% to 5.6%) in 1999-2004. In other regions of California, incidence rates of invasive breast cancer increased 0.8% per year (95% CI, 0.4% to 1.1%) in 1988-2001 and decreased 4.4% per year (95% CI, 1.4% to 7.3%) in 2001-2004. In both regions, recent (2000-2001 to 2003-2004) decreases in invasive breast cancer occurred only in women 40 years old or older and in women with all histologic subtypes and tumor sizes, hormone receptor-defined types, and all stages except distant disease. Mortality rates declined 2.2% per year (95% CI, 1.8% to 2.6%) from 1988 to 2004 in the SFBA and the rest of California. Use of estrogen-progestin hormone therapy decreased significantly from 2001 to 2003 in both regions. In 2003-2004, invasive breast cancer incidence remained higher (4.2%) in the SFBA than in the rest of California, consistent with the higher distributions of many established risk factors, including advanced education, nulliparity, late age at first birth, and alcohol consumption.ConclusionOngoing surveillance of breast cancer occurrence patterns in this high-risk population informs breast cancer etiology through comparison of trends with lower-risk populations and by highlighting the importance of examining how broad migration patterns influence the geographic distribution of risk factors