Search

The SOUL systems at the Large Bincoular Telescope can be seen such as precursor for the ELT SCAO systems, combining together key technologies such as EMCCD, Pyramid WFS and adaptive telescopes. After the first light of the first upgraded system on September 2018, going through COVID and technical stops, we now have all the 4 systems working on-sky. Here, we report about some key control improvements and the system performance characterized during the commissioning. The upgrade allows us to correct more modes (500) in the bright end and increases the sky coverage providing SR(K)>20% with reference stars G$_{RP}$<17, opening to extragalcatic targets with NGS systems. Finally, we review the first astrophysical results, looking forward to the next generation instruments (SHARK-NIR, SHARK-Vis and iLocater), to be fed by the SOUL AO correction., Comment: 13 pages, 10 figures, Adaptive Optics for Extremely Large Telescopes 7th Edition, 25-30 Jun 2023 Avignon (France)

Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applications Key Features Discover the new features introduced in Elasticsearch 7 Explore techniques for distributed search, indexing, and clustering Gain hands-on knowledge of implementing Elasticsearch for your enterprise Book Description Elasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch. What you will learn Install Elasticsearch and use it to safely store data and retrieve it when needed Work with a variety of analyzers and filters Discover techniques to improve search results in Elasticsearch Understand how to perform metric and bucket aggregations Implement best practices for moving clusters and applications to production Explore various techniques to secure your Elasticsearch clusters Who this book is for This book is for software developers, engineers, data architects, system administrators, and anyone who wants to get up and running with Elasticsearch 7. No prior experience with Elasticsearch is required.

Pathophysiological damages and loss of function of dopamine neurons precede their demise and contribute to the early phases of Parkinson's disease. The presence of aberrant intracellular pathological inclusions of the protein alpha-synuclein within ventral midbrain dopaminergic neurons is one of the cardinal features of Parkinson's disease. We employed molecular biology, electrophysiology, and live-cell imaging to investigate how excessive alpha-synuclein expression alters multiple characteristics of dopaminergic neuronal dynamics and dopamine transmission in cultured dopamine neurons conditionally expressing GCaMP6f. We found that overexpression of alpha-synuclein in mouse (male and female) dopaminergic neurons altered neuronal firing properties, calcium dynamics, dopamine release, protein expression, and morphology. Moreover, prolonged exposure to the D2 receptor agonist, quinpirole, rescues many of the alterations induced by alpha-synuclein overexpression. These studies demonstrate that alpha-synuclein dysregulation of neuronal activity contributes to the vulnerability of dopaminergic neurons and that modulation of D2 receptor activity can ameliorate the pathophysiology. These findings provide mechanistic insights into the insidious changes in dopaminergic neuronal activity and neuronal loss that characterize Parkinson's disease progression with significant therapeutic implications.

Humans are adept at learning the latent structure of the relationship between abstract concepts and can build a cognitive map from limited experiences. However, examining internal representations of the cognitive map is challenging because they are unobservable and differ across individuals. Here, we introduce a behavioral training protocol designed for human participants to implicitly build a map of two-dimensional social hierarchies while making a series of binary choices and analytic tools for measuring the internal representation of this structural knowledge. For complete details on the use and execution of this protocol, please refer to Park et al. (2020a, 2020b).

Generalizing experiences to guide decision-making in novel situations is a hallmark of flexible behavior. Cognitive maps of an environment or task can theoretically afford such flexibility, but direct evidence has proven elusive. In this study, we found that discretely sampled abstract relationships between entities in an unseen two-dimensional social hierarchy are reconstructed into a unitary two-dimensional cognitive map in the hippocampus and entorhinal cortex. We further show that humans use a grid-like code in entorhinal cortex and medial prefrontal cortex for inferred direct trajectories between entities in the reconstructed abstract space during discrete decisions. These grid-like representations in the entorhinal cortex are associated with decision value computations in the medial prefrontal cortex and temporoparietal junction. Collectively, these findings show that grid-like representations are used by the human brain to infer novel solutions, even in abstract and discrete problems, and suggest a general mechanism underpinning flexible decision-making and generalization.

Climate prediction on subseasonal to decadal time scales is a rapidly advancing field that is synthesizing improvements in climate process understanding and modeling to improve and expand operational services worldwide. Weather and climate variations on subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus broadly remains similar, (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these area

Cognitive maps enable efficient inferences from limited experience that can guide novel decisions. We tested whether the hippocampus (HC), entorhinal cortex (EC), and ventromedial prefrontal cortex (vmPFC)/medial orbitofrontal cortex (mOFC) organize abstract and discrete relational information into a cognitive map to guide novel inferences. Subjects learned the status of people in two unseen 2D social hierarchies, with each dimension learned on a separate day. Although one dimension was behaviorally relevant, multivariate activity patterns in HC, EC, and vmPFC/mOFC were linearly related to the Euclidean distance between people in the mentally reconstructed 2D space. Hubs created unique comparisons between the hierarchies, enabling inferences between novel pairs. We found that both behavior and neural activity in EC and vmPFC/mOFC reflected the Euclidean distance to the retrieved hub, which was reinstated in HC. These findings reveal how abstract and discrete relational structures are represented, are combined, and enable novel inferences in the human brain.

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Climate prediction on subseasonal to decadal time scales is a rapidly advancing field that is synthesizing improvements in climate process understanding and modeling to improve and expand operational services worldwide. Weather and climate variations on subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus broadly remains similar, (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these area

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Climate prediction on subseasonal to decadal time scales is a rapidly advancing field that is synthesizing improvements in climate process understanding and modeling to improve and expand operational services worldwide. Weather and climate variations on subseasonal to decadal timescales can have enormous social, economic and environmental impacts, making skillful predictions on these timescales a valuable tool for decision makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) timescales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) timescales, while the focus broadly remains similar, (e.g., on precipitation, surface and upper ocean temperatures and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal and externally-forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere-ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these area, The International Conferences on Subseasonal to Decadal Prediction on which this paper is based were sponsored by: US CLIVAR, NSF, UCAR, NCAR and its Climate and Global Dynamics Laboratory (CGD), NOAA’s Climate Variability and Predictability (CVP) and Modeling, Analysis, Predictions and Projections (MAPP) Programs, Copernicus Climate Change Service, IPSL, and WWRP/WCRP’s Subseasonal-to-Seasonal (S2S) Prediction Project., Postprint (author's final draft)

Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applications Key Features Discover the new features introduced in Elasticsearch 7 Explore techniques for distributed search, indexing, and clustering Gain hands-on knowledge of implementing Elasticsearch for your enterprise Book Description Elasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch. What you will learn Install Elasticsearch and use it to safely store data and retrieve it when needed Work with a variety of analyzers and filters Discover techniques to improve search results in Elasticsearch Understand how to perform metric and bucket aggregations Implement best practices for moving clusters and applications to production Explore various techniques to secure your Elasticsearch clusters Who this book is for This book is for software developers, engineers, data architects, system administrators, and anyone who wants to get up and running with Elasticsearch 7. No prior experience with Elasticsearch is required.

Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applications Key Features Discover the new features introduced in Elasticsearch 7 Explore techniques for distributed search, indexing, and clustering Gain hands-on knowledge of implementing Elasticsearch for your enterprise Book Description Elasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch. What you will learn Install Elasticsearch and use it to safely store data and retrieve it when needed Work with a variety of analyzers and filters Discover techniques to improve search results in Elasticsearch Understand how to perform metric and bucket aggregations Implement best practices for moving clusters and applications to production Explore various techniques to secure your Elasticsearch clusters Who this book is for This book is for software developers, engineers, data architects, system administrators, and anyone who wants to get up and running with Elasticsearch 7. No prior experience with Elasticsearch is required.

Since 2014, the LBT's First Light Adaptive Optics (FLAO) system has also included a seldom used capability, known as Enhanced Seeing Mode (ESM), that can improve the angular resolution over a 4' x 4' field of view (FOV). In full AO operation, FLAO provides diffraction limited (DL) capabilities over a small (30" x 30") FOV. By comparison, ESM can achieve significantly enhanced resolution, over natural seeing, across a far larger FOV. This improves operational efficiency over standard seeing limited (SL) observations and is applicable across a broader range of scientific targets. ESM uses 11 modes of correction (including tip and tilt) to remove residual aberrations and jitter which significantly improves angular resolution over the full FOV. While this mode does not reach the DL, it can achieve uniform angular resolutions as good as 0".22 over the FOV. Furthermore, it allows for the use of multi-object spectroscopy with R~10,000 or imaging with angular resolution similar to that achieved by the Wide-Field Camera 3 infrared channel on the Hubble Space Telescope, but powered by 11.6 meters of effective aperture in binocular mode. As part of the on-going characterization of ESM, we have demonstrated that even in poor seeing conditions (1".5-2") the image quality delivered to the focal station is improved by factors of 2-3. Here, we present the first results of the characterization of ESM, including systematic tests of the delivered PSF across the FOV as a function of the brightness of, and distance from, the AO Reference Star. We present a range of galactic and extra-galactic targets showing the improvements obtained over a broad range of seeing conditions and propose ESM as a standard observational mode for near-Infrared observations., Comment: AO4ELT6 Conference Proceedings, 10 pages, 6 Figures

Get the most out of Elasticsearch 7's new features to build, deploy, and manage efficient applications Key Features Discover the new features introduced in Elasticsearch 7 Explore techniques for distributed search, indexing, and clustering Gain hands-on knowledge of implementing Elasticsearch for your enterprise Book Description Elasticsearch is one of the most popular tools for distributed search and analytics. This Elasticsearch book highlights the latest features of Elasticsearch 7 and helps you understand how you can use them to build your own search applications with ease. Starting with an introduction to the Elastic Stack, this book will help you quickly get up to speed with using Elasticsearch. You'll learn how to install, configure, manage, secure, and deploy Elasticsearch clusters, as well as how to use your deployment to develop powerful search and analytics solutions. As you progress, you'll also understand how to troubleshoot any issues that you may encounter along the way. Finally, the book will help you explore the inner workings of Elasticsearch and gain insights into queries, analyzers, mappings, and aggregations as you learn to work with search results. By the end of this book, you'll have a basic understanding of how to build and deploy effective search and analytics solutions using Elasticsearch. What you will learn Install Elasticsearch and use it to safely store data and retrieve it when needed Work with a variety of analyzers and filters Discover techniques to improve search results in Elasticsearch Understand how to perform metric and bucket aggregations Implement best practices for moving clusters and applications to production Explore various techniques to secure your Elasticsearch clusters Who this book is for This book is for software developers, engineers, data architects, system administrators, and anyone who wants to get up and running with Elasticsearch 7. No prior experience with Elasticsearch is required.

Since 2014, the LBT's First Light Adaptive Optics (FLAO) system has also included a seldom used capability, known as Enhanced Seeing Mode (ESM), that can improve the angular resolution over a 4' x 4' field of view (FOV). In full AO operation, FLAO provides diffraction limited (DL) capabilities over a small (30" x 30") FOV. By comparison, ESM can achieve significantly enhanced resolution, over natural seeing, across a far larger FOV. This improves operational efficiency over standard seeing limited (SL) observations and is applicable across a broader range of scientific targets. ESM uses 11 modes of correction (including tip and tilt) to remove residual aberrations and jitter which significantly improves angular resolution over the full FOV. While this mode does not reach the DL, it can achieve uniform angular resolutions as good as 0".22 over the FOV. Furthermore, it allows for the use of multi-object spectroscopy with R~10,000 or imaging with angular resolution similar to that achieved by the Wide-Field Camera 3 infrared channel on the Hubble Space Telescope, but powered by 11.6 meters of effective aperture in binocular mode. As part of the on-going characterization of ESM, we have demonstrated that even in poor seeing conditions (1".5-2") the image quality delivered to the focal station is improved by factors of 2-3. Here, we present the first results of the characterization of ESM, including systematic tests of the delivered PSF across the FOV as a function of the brightness of, and distance from, the AO Reference Star. We present a range of galactic and extra-galactic targets showing the improvements obtained over a broad range of seeing conditions and propose ESM as a standard observational mode for near-Infrared observations., Comment: AO4ELT6 Conference Proceedings, 10 pages, 6 Figures

We investigate the effects of automobile congestion on ambient air pollution and local infant mortality rates using data from California spanning 2002 to 2007. Constructing instrumental variables (IV) using the relationship of traffic, weather conditions, and pollutants, we show that particulate matter, even at modern levels, has large marginal effects on weekly infant mortality rates, especially for premature or low birthweight infants. We also find suggestive evidence of large effects for carbon monoxide, though results are imprecise. Finally, we check estimate sensitivity to nonclassical measurement error in local pollution and show that our IV results are robust to such concerns., University of California Energy Institute, University of California, Davis. Institute of Transportation Studies

The accuracy of velocity measurements made using a monopole acoustic logging-while-drilling (ALWD) measurement tool is influenced by the eccentering of the tool due to complex drill string movements. We have used the velocity of collar flexural mode (at the source frequency range) as a reference and classified the fast formations into (1) fast-fast (FF) formations with compressional velocity far larger than the collar flexural velocity and (2) slow-fast (SF) formations with compressional velocity approaching that of the collar flexural velocity. We use a 3D finite-difference method to simulate the response of an eccentered monopole ALWD tool with different eccentering magnitudes (offsets) for the two types of formations to facilitate better interpretation of velocity measurements made in an actual drilling environment. We find that the collar extensional mode, existing in the centralized and eccentered tool cases, only affects the formation P-wave measurement and can be eliminated by using an isolator. The collar flexural mode, which is a shear motion in the collar and can only be excited in a centralized tool by a dipole source, is also excited when a monopole tool is eccentered, and it significantly affects the measurement of the compressional velocity in the SF formation and that of the shear velocity in the FF formation, even for small eccentering offsets. Thus, the uncorrected monopole ALWD tool provides unreliable formation velocities (either the compressional or shear velocities) in fast formations because of the significant influence of the tool offsets on the measurement. To minimize the influence of tool offset on the measurements, we compared the differences between the waveforms collected for different azimuths and tool offsets and the centralized monopole waveforms. Keywords: borehole geophysics; logging; measurement-while-drilling; P-wave; S-wave

In the paper “A numerical investigation of the acoustic mode waves in a deviated borehole penetrating a transversely isotropic formation” by Liu et al. [1] numerical experiments are reported for a dipole sonic logging scenario with a deviated borehole penetrating a VTI anisotropic medium. In such a situation it is important to clearly define the meaning of group and phase velocities as this has led to much confusion in the literature as discussed by Miller, Horne and Walsh [2].

There is a serious lack of demographic and socioeconomic data about Asian Americans living in distressed areas. The approach suggested to address this problem is community development with professional and academics to provide updated information on many issues such as poverty, educational attainment pertinent to these disadvantaged AA communities. The article discusses the selection criteria employed to choose the fourteen distressed communities that is analyzed. Details describing demographic characteristics, such as most AA communities are racially diverse, are supplemented with statistics to provide concrete data. Unemployment and poverty go hand-in-hand and in distressed AA communities these problems are occurring in higher frequency than other communities. The typical depiction of an AA community as a rich ethnic-enclave is debunked. The dominant problems in these communities are also representative of the problems most immigrants face today. The motivation for this analysis is to compel policy-makers to develop further research into these communities to understand their problems in order to make policies effectively addressing their needs.

This technical supplement provides the tables and maps upon which the analysis included in the report for the Economic Development Administration of the U.S. Department of Commerce, "Economic Needs of Asian Americans and Pacific Islander in Distressed Areas” was based. contains detailed neighborhood profiles and maps of low-income APA areas in the following MSAs: Chicago, Long Beach (Little Phnom Pen), Los Angeles (Koreatown), Lowell, New Orleans, New York City (Chinatown), New York City (Jackson Heights), Orange County (Little Saigon), Sacramento, Saint Paul, San Francisco (Chinatown), Seattle, Stockton (Cambodian), Stockton (Filipino), Hawaii Study Area, Oahu, Hawaii Study Area, Molokai and San Francisco (Samoan).

This technical supplement provides the tables and maps upon which the analysis included in the report for the Economic Development Administration of the U.S. Department of Commerce, "Economic Needs of Asian Americans and Pacific Islander in Distressed Areas” was based. contains detailed neighborhood profiles and maps of low-income APA areas in the following MSAs: Chicago, Long Beach (Little Phnom Pen), Los Angeles (Koreatown), Lowell, New Orleans, New York City (Chinatown), New York City (Jackson Heights), Orange County (Little Saigon), Sacramento, Saint Paul, San Francisco (Chinatown), Seattle, Stockton (Cambodian), Stockton (Filipino), Hawaii Study Area, Oahu, Hawaii Study Area, Molokai and San Francisco (Samoan).

This technical supplement provides the tables and maps upon which the analysis included in the report for the Economic Development Administration of the U.S. Department of Commerce, "Economic Needs of Asian Americans and Pacific Islander in Distressed Areas” was based. contains detailed neighborhood profiles and maps of low-income APA areas in the following MSAs: Chicago, Long Beach (Little Phnom Pen), Los Angeles (Koreatown), Lowell, New Orleans, New York City (Chinatown), New York City (Jackson Heights), Orange County (Little Saigon), Sacramento, Saint Paul, San Francisco (Chinatown), Seattle, Stockton (Cambodian), Stockton (Filipino), Hawaii Study Area, Oahu, Hawaii Study Area, Molokai and San Francisco (Samoan).

This technical supplement provides the tables and maps upon which the analysis included in the report for the Economic Development Administration of the U.S. Department of Commerce, "Economic Needs of Asian Americans and Pacific Islander in Distressed Areas” was based. contains detailed neighborhood profiles and maps of low-income APA areas in the following MSAs: Chicago, Long Beach (Little Phnom Pen), Los Angeles (Koreatown), Lowell, New Orleans, New York City (Chinatown), New York City (Jackson Heights), Orange County (Little Saigon), Sacramento, Saint Paul, San Francisco (Chinatown), Seattle, Stockton (Cambodian), Stockton (Filipino), Hawaii Study Area, Oahu, Hawaii Study Area, Molokai and San Francisco (Samoan).

Glass fiber reinforced composites (GFRC) are used in a wide variety of applications within the U.S. Navy. With a potential increase in arctic operations in the Navy’s future, it is important to understand how GFRCs will react at arctic temperatures. Previous research has shown that material properties of GFRC at cold temperatures are dependent on the reaction between the fiber and the resin, but little research has been conducted that was geared toward naval applications at arctic temperatures. This thesis focuses on the tensile properties of GFRC, resin, and glass fiber used in previous NPS-related composite research. The properties of the individual components are compared to assist in the design of composite structures, and provide a baseline to assess the need to re-conduct previous composite experiments at arctic temperatures.

Telomeres distinguish chromosome ends from double-strand breaks (DSBs) and prevent chromosome fusion. However, telomeres can also interfere with DNA repair, as shown by a deficiency in nonhomologous end joining (NHEJ) and an increase in large deletions at telomeric DSBs. The sensitivity of telomeric regions to DSBs is important in the cellular response to ionizing radiation and oncogene-induced replication stress, either by preventing cell division in normal cells, or by promoting chromosome instability in cancer cells. We have previously proposed that the telomeric protein TRF2 causes the sensitivity of telomeric regions to DSBs, either through its inhibition of ATM, or by promoting the processing of DSBs as though they are telomeres, which is independent of ATM. Our current study addresses the mechanism responsible for the deficiency in repair of DSBs near telomeres by combining assays for large deletions, NHEJ, small deletions, and gross chromosome rearrangements (GCRs) to compare the types of events resulting from DSBs at interstitial and telomeric DSBs. Our results confirm the sensitivity of telomeric regions to DSBs by demonstrating that the frequency of GCRs is greatly increased at DSBs near telomeres and that the role of ATM in DSB repair is very different at interstitial and telomeric DSBs. Unlike at interstitial DSBs, a deficiency in ATM decreases NHEJ and small deletions at telomeric DSBs, while it increases large deletions. These results strongly suggest that ATM is functional near telomeres and is involved in end protection at telomeric DSBs, but is not required for the extensive resection at telomeric DSBs. The results support our model in which the deficiency in DSB repair near telomeres is a result of ATM-independent processing of DSBs as though they are telomeres, leading to extensive resection, telomere loss, and GCRs involving alternative NHEJ.

The use of mesoscale models to provide an accurate representation of what the atmosphere is likely to do in the near future is one of the tools forecasters utilize to predict atmospheric variables. Because of the large amount of time and computer resources necessary to provide detailed forecasts on the mesoscale, this study looked at forecasting winds utilizing a simple diagnostic model and compared its results to a full physics model. Winds from the Fifth Generation Mesoscale Model (MM5), were run at fairly coarse grid spacings of 81, 27, and 9 kilometers and at a finer grid spacing of three kilometers. The MM5 9 kilometer results were input into the Winds On Critical Streamline Surfaces (WOOSS) model, which is a scaled down physics model designed to adjust winds to fine scale topography. A comparison of how the WOCSS model winds compared against each of the MM5 grid spacings was evaluated for an event during the period 4-7 August 1997 in the SOCAL bight region to determine if the results of the scaled down physics model were comparable to the full physics model. This experiment showed encouraging results for forecasting fine scale winds on complex topography using the simple dia nostic model, http://archive.org/details/forecastingmesos1094526555, NA, U.S. Navy (U.S.N.) author.

Baló's concentric sclerosis is a primary inflammatory central nervous system demyelinating disease that is considered a rare, radiographically and pathologically distinct variant of multiple sclerosis. Baló's concentric sclerosis is characterized by alternating rings of demyelinated and myelinated axons, and it is most frequently diagnosed postmortem by autopsy or, more recently, by magnetic resonance imaging without pathologic verification. This report is of a case of Baló's concentric sclerosis in which the patient presented with left-sided focal sensorimotor deficits. The patient's lesion demonstrated characteristics of Baló's concentric sclerosis by magnetic resonance imaging, but since a neoplastic process was also suspected initially, the patient underwent a surgical biopsy. This pathology sample now provides the opportunity to correlate the tissue diagnosis of demyelination with characteristic magnetic resonance imaging findings; this comparison is infrequently found in the literature.

Babar A Khan,1–3 Mark O Farber,1 Noll Campbell,2–5 Anthony Perkins,2,3 Nagendra K Prasad,6 Siu L Hui,1–3 Douglas K Miller,1–3 Enrique Calvo-Ayala,1 John D Buckley,1 Ruxandra Ionescu,1 Anantha Shekhar,1 E Wesley Ely,7,8 Malaz A Boustani1–3 1Indiana University School of Medicine, 2Indiana University Center for Aging Research, 3Regenstrief Institute, Inc., 4Wishard Health Services, Indianapolis, 5Department of Pharmacy Practice, Purdue University College of Pharmacy, West Lafayette, 6Indiana University Melvin and Bren Simon Cancer Center, Indianapolis, IN, 7Vanderbilt University School of Medicine, 8VA Tennessee Valley Geriatric Research Education Clinical Center (GRECC), Nashville, TN, USA Background: Currently, there are no valid and reliable biomarkers to identify delirious patients predisposed to longer delirium duration. We investigated the hypothesis that elevated S100 calcium binding protein B (S100β) levels will be associated with longer delirium duration in critically ill patients. Methods: A prospective observational cohort study was performed in the medical, surgical, and progressive intensive care units (ICUs) of a tertiary care, university affiliated, and urban hospital. Sixty-three delirious patients were selected for the analysis, with two samples of S100β collected on days 1 and 8 of enrollment. The main outcome measure was delirium duration. Using the cutoff of <0.1 ng/mL and $0.1 ng/mL as normal and abnormal levels of S100β, respectively, on day 1 and day 8, four exposure groups were created: Group A, normal S100β levels on day 1 and day 8; Group B, normal S100β level on day 1 and abnormal S100β level on day 8; Group C, abnormal S100β level on day 1 and normal on day 8; and Group D, abnormal S100β levels on both day 1 and day 8. Results: Patients with abnormal levels of S100β showed a trend towards higher delirium d

As the only directly imaged multiple planet system, HR 8799 provides a unique opportunity to study the physical properties of several planets in parallel. In this paper, we image all four of the HR 8799 planets at H-band and 3.3 microns with the new LBT adaptive optics system, PISCES, and LBTI/LMIRCam. Our images offer an unprecedented view of the system, allowing us to obtain H and 3.3$ micron photometry of the innermost planet (for the first time) and put strong upper-limits on the presence of a hypothetical fifth companion. We find that all four planets are unexpectedly bright at 3.3 microns compared to the equilibrium chemistry models used for field brown dwarfs, which predict that planets should be faint at 3.3 microns due to CH4 opacity. We attempt to model the planets with thick-cloudy, non-equilibrium chemistry atmospheres, but find that removing CH4 to fit the 3.3 micron photometry increases the predicted L' (3.8 microns) flux enough that it is inconsistent with observations. In an effort to fit the SED of the HR 8799 planets, we construct mixtures of cloudy atmospheres, which are intended to represent planets covered by clouds of varying opacity. In this scenario, regions with low opacity look hot and bright, while regions with high opacity look faint, similar to the patchy cloud structures on Jupiter and L/T transition brown-dwarfs. Our mixed cloud models reproduce all of the available data, but self-consistent models are still necessary to demonstrate their viability., Comment: Accepted to ApJ

The Large Binocular Telescope (LBT) is a unique telescope featuring two co-mounted optical trains with 8.4m primary mirrors. The telescope Adaptive Optics (AO) system uses two innovative key components, namely an adaptive secondary mirror with 672 actuators and a high-order pyramid wave-front sensor. During the on-sky commissioning such a system reached performances never achieved before on large ground-based optical telescopes. Images with 40mas resolution and Strehl Ratios higher than 80% have been acquired in H band (1.6 micron). Such images showed a contrast as high as 10e-4. Based on these results, we compare the performances offered by a Natural Guide Star (NGS) system upgraded with the state-of-the-art technology and those delivered by existing Laser Guide Star (LGS) systems. The comparison, in terms of sky coverage and performances, suggests rethinking the current role ascribed to NGS and LGS in the next generation of AO systems for the 8-10 meter class telescopes and Extremely Large Telescopes (ELTs)., Comment: 10 pages, 9 figures, Preented at SSPIE Optics + Photonics 2011, San Diego 20-25 August 2011

On 13 February 2001, an explosive cyclone made landfall in Southern California. This system was responsible for storm force winds and heavy precipitation in the Los Angeles area. This storm is interesting because it was handled poorly by the numerical models and developed in an unusual area. Analysis of this storm revealed double circulation centers and multiple baroclinic zones. Due to weak static stability, air-sea fluxes were contributory in developing the baroclinic zone from which this cyclone originated as well as enhancing its development rate. Evidence suggests that the system may have had a warm core, similar to other intense extratropical cyclones. The models did not properly forecast this system due to weak cold air advection over the Eastern Pacific Ocean and due to blending the subpolar and subtropical jets into a single feature. Data assimilation is suspected to have played a role in the mishandling of these key features., http://archive.org/details/examinationoffeb109456008, Lieutenant Commander, United States Navy, Approved for public release; distribution is unlimited.

Correctly identifying a weapon system as "friend" or "foe" is vital to the success of the Army mission. Incorrect identification can leave the enemy to fight another day or cause a fratricide event. A current threat identification training method is to use Army Field Manual (FM) 1-402, which has not been updated since 1984, and is difficult to tailor towards specific and evolving threat training and mission requirements. This thesis, therefore, has two main purposes: development of a modifiable computer-based program that individual units can easily tailor to meet their current threat training requirements, and a statistical analysis to deteriine if Computer-Based Training (CET) is suitable for individual soldier threat identification training. The CBT application developed for this thesis is dynamically linked to image and text files maintained by the unit-training officer, thus allowing for modification and updates as required. Experimental results indicate that using this CBT application can be a suitable, and in some aspects better, training tool than FM 1A02. After a 20-minute study period, experiment participants using the CBT had an average nomenclature final test score increase of 38.4 percent over a similarly experienced control-group, http://archive.org/details/designimplementa109458223, Captain, United States Army, Approved for public release; distribution is unlimited.

This study evaluates the latest Navy Operational Global Atmospheric Prediction System (NOGAPS) version 4.0 with a comparison to data collected during the Surface Heat Budget of the Arctic (SHEBA) project from October 1997 to October 1998. In particular, three periods from this year long study were the focus and included, a winter, spring, and summer case. For each of these cases the first 24-hour period of the forecasts were analyzed for any bias and root mean square difference from the SHEBA data. NOGAPS had no significant biases in pressure and wind speed. During the winter case, the NOPGAPS surface temperature remained near -28 C while observed temperature varied in response to cloud cover changes and was lower by 5.3 C on the average. During the spring the NOGAPS temperatures had a steady increase from -11 C until reaching the melt season temperature of 0 C 11 days earlier than observed. As a result of too warm a surface and less downwelling longwave radiation, the net longwave flux cooling was greater than observed, by an average of -12.4 Wm-2. The NOGAPS net shortwave radiation was greater than observed by an average of 62 Wm-2 for spring and 22.6 Wm-2 for summer., http://archive.org/details/anssessmentofnog109451391, Lieutenant, United States Navy, Approved for public release; distribution is unlimited.

Mesoscale models are important, useful tools for analyzing and forecasting snail-scale atmospheric phenomena. Ideally, finer grid-point resolution should make a model more likely to capture realistic small-scale structure. Because these models work to resolve phenomena that exist on very fine spatial- and time-scales, they are subject to high variability. Accurate initialization of mesoscale models is crucial to skillful short-term forecasting. This study exercises four different initialization and model physics experiments of four nested MM5 forecast domains and examines their respective short-term (f03, f06, f09, f12) forecasts. The exceptionally rich meteorological data set taken from the Southern Coast Ozone Study of 1997 (SCOS97) provides the basis for our model verification. We show that 3km and 9k resolutions produce better forecasts than the 27km resolution model, however, differences between the 3km and 9km resolution forecasts are essentially insignificant. We also show that different model initializations and physics schemes have an insignificant impact on improving the absolute accuracy of the numerical forecasts produced by a non-hydrostatic mesoscale model, http://archive.org/details/annalysisofshort109457629

One of the major problems with a Limited Area Model is the introduction of error from the lateral boundaries. The boundary condition provides a source of forcing to the interior of the model. This forcing typically originates from a global model such as NOGAPS. The transition at the boundary from one model to another invariably produces errors. Traditionally, the way to minimize boundary error is to move the boundary as far away from the area of interest as possible. In this way, the errors do not have time to infest the LAM with "bad" information. Moving the boundary far away from the area of interest increases the computational forecast load and decreases its timeliness. This study looks at how close the lateral boundary can be to minimize computational time and still maintain a forecast that is useful. It was found that when the entire inner COAMPS nest was analyzed, the differences between the control forecast and the test forecast where within the natural variability of the control grid. It was also found that there where localized areas within the model domain that differed between the control domain and the test domain by up to 20 mb for the sea level pressure after a six day forecast., http://archive.org/details/analysisoflatera109451414, Lieutenant, United States Navy, Approved for public release; distribution is unlimited.

The Large Binocular Telescope (LBT) is a unique telescope featuring two co-mounted optical trains with 8.4m primary mirrors. The telescope Adaptive Optics (AO) system uses two innovative key components, namely an adaptive secondary mirror with 672 actuators and a high-order pyramid wave-front sensor. During the on-sky commissioning such a system reached performances never achieved before on large ground-based optical telescopes. Images with 40mas resolution and Strehl Ratios higher than 80% have been acquired in H band (1.6 micron). Such images showed a contrast as high as 10e-4. Based on these results, we compare the performances offered by a Natural Guide Star (NGS) system upgraded with the state-of-the-art technology and those delivered by existing Laser Guide Star (LGS) systems. The comparison, in terms of sky coverage and performances, suggests rethinking the current role ascribed to NGS and LGS in the next generation of AO systems for the 8-10 meter class telescopes and Extremely Large Telescopes (ELTs)., Comment: 10 pages, 9 figures, Preented at SSPIE Optics + Photonics 2011, San Diego 20-25 August 2011

As the only directly imaged multiple planet system, HR 8799 provides a unique opportunity to study the physical properties of several planets in parallel. In this paper, we image all four of the HR 8799 planets at H-band and 3.3 microns with the new LBT adaptive optics system, PISCES, and LBTI/LMIRCam. Our images offer an unprecedented view of the system, allowing us to obtain H and 3.3$ micron photometry of the innermost planet (for the first time) and put strong upper-limits on the presence of a hypothetical fifth companion. We find that all four planets are unexpectedly bright at 3.3 microns compared to the equilibrium chemistry models used for field brown dwarfs, which predict that planets should be faint at 3.3 microns due to CH4 opacity. We attempt to model the planets with thick-cloudy, non-equilibrium chemistry atmospheres, but find that removing CH4 to fit the 3.3 micron photometry increases the predicted L' (3.8 microns) flux enough that it is inconsistent with observations. In an effort to fit the SED of the HR 8799 planets, we construct mixtures of cloudy atmospheres, which are intended to represent planets covered by clouds of varying opacity. In this scenario, regions with low opacity look hot and bright, while regions with high opacity look faint, similar to the patchy cloud structures on Jupiter and L/T transition brown-dwarfs. Our mixed cloud models reproduce all of the available data, but self-consistent models are still necessary to demonstrate their viability., Comment: Accepted to ApJ

Since the Clean Air Act Amendments of 1990 (CAAA), atmospheric concentration of local pollutants has fallen drastically. A natural question is whether further reductions will yield additional health benefits. We further this research by addressing two related research questions: (1) what is the impact of automobile driving (and especially congestion) on ambient air pollution levels, and (2) what is the impact of modern air pollution levels on infant health? Our setting is California (with a focus on the Central Valley and Southern California) in the years 2002-2007. Using an instrumental variables approach that exploits the relationship between traffic, ambient weather conditions, and various pollutants, our findings suggest that ambient pollution levels, specifically particulate matter, still have large impacts on weekly infant mortality rates. Our results also illustrate the importance of weather controls in measuring pollution’s impact on infant mortality., University of California Energy Institute and UC Davis Institute of Transportation Studies. UC Davis Institute of Governmental Affairs, the UC Davis Institute of Transportation Studies, and the TSR&TP through the Atmospheric Aerosols and Health (AAH) Lead Campus program.