An Electrical and Statistical Study of Burst Noise

Burst noise is a normally undesirable phenomenon occasionally found in bipolar semiconductors and other current carrying devices. It is an electrical fluctuation which exhibits itself as one or more rectangular waveforms possessing constant amplitude but random pulse duration. The experimental portion of this study relates only to burst noise in bipolar transistors and operational amplifiers. Burst noise is not Gaussian as are the more common fluctuations in semiconductors. That fact was established by estimation of the amplitude distribution, a technique found to be sensitive in the detection of burst noise obscured by quantities of conventional noise. The amplitude of burst noise varies with the parameters of base-emitter, voltage temperature and source resistance. An exponential increase of amplitude with Vbe and a lack of dependence on collector voltage implied that the noise originates in the base-emitter junction. A noise magnitude linearly proportional to source resistance over several decades leads one to infer the equivalent circuit of a current source between base and emitter. Current amplitudes of 10-10 to nearly 10-6 ampere p-p were observed. Burst noise pulse durations were found as brief as 10 µsec and as long as some 29 hours; neither an upper nor a lower bound was established. The two noise states (high and low, in the rectangular waveform) were treated separately in the duration experiments. Careful measurements on the relative frequency with which the pulse occurred gave duration probability densities of 1/τ e -t/τ for each state. That density also applies to a single particle alternately being trapped and escaping and is consistent with the physical theory due to Mead and Whittier relating burst noise to trapping phenomena. Measurements on noise pulse durations in both states as a function of Vbe lent support to the theory and indicated both trapping and recombination-generation centers were present in samples examined. Another theory, due to Leonard and Jaskolsky, was found inconsistent with the evidence for burst noise's origin in the base-emitter junction. Duration versus temperature dependence indicated activation energies of roughly .5 eV. Although suggestions in the literature for the power spectrum of burst noise have been inconsistent, digital spectral estimation and judicious use of a wave analyzer showed the spectrum to be flat at low frequencies and to fall as 1/f2 at higher ones. Proceeding only from the measured pulse duration probability density, the power spectrum was deduced on theoretical grounds for the first time. The method entailed the derivation of burst noise's autocorrelation function which, when Fourier transformed, yielded S(w) = 2/(τ1 + τ0)[(1/τ1 + 1/τ0)2 + w2] where τ1 and τ0 are the average durations in the two noise estates. The expression proved consistent with experiment.</p

Effects of Filter Strips on Habitat Use and Home Range of Northern Bobwhites on Alligator River National Wildlife Refuge

Lack of breeding habitat for northern bobwhites (Colinus virginianus) on agricultural landscapes is a factor that limits populations. Therefore, we examined how the addition of filter strips around crop fields and along crop field drainage ditches impacted northern bobwhites. Our study focused on habitat use, home range and brood-rearing range of bobwhites, from April through September I 993-94. Two farms on Alligator River National Wildlife Refuge were sub-divided into filter strip (FS) and non-filter strip (NFS) sections. More bobwhites were found on FS sections than on NFS sections based on flush counts (4.3x more on FS areas: P = 0.02). We used log-linear analysis to examine the distribution of telemetry locations (n = 1796) of radio-marked bobwhites (n = 218) across 5, 4.6m bands parallel to drainage ditches. Bobwhite locations were skewed towards ditches, particularly on FS sections before soybeans matured to a size that was sufficient to provide canopy cover for bobwhites. Bobwhites captured on FS sections had significantly smaller breeding season ranges than those captured on NFS sections (P = 0.001). Adult and sub-adult breeding season (May-Aug) ranges (n = 23) averaged 32 ha (SE = 26) and 182 ha (SE = 41) on FS and NFS sections, respectively. Brood ranges to 14 days (n = 9) ranged from 0.8 ha to 2.2 ha depending on habitat and calculation method. Presence of filter strips shifted habitat use patterns, especially during spring and early summer, and improved crop fields as habitat for breeding bobwhites

Using NASA Remotely Sensed Data to Help Characterize Environmental Risk Factors for National Public Health Applications

NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets will be developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be disseminated to end-users for decision making through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system

Public Health Applications of Remotely-sensed Environmental Datasets for the Conterminous United States

NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics to address issues of environmental health and enhance public health decision-making using NASA remotely-sensed data and products. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid using the US Environmental Protection Agency (EPA) ground observations and NASA's MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Incoming Solar Radiation (Insolation) and heat-related products using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets were linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline, stroke and other health outcomes. These environmental datasets and the results of the public health linkage analyses will be disseminated to end-users for decision-making through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer-reviewed publications respectively. The linkage of these data with the CDC WONDER system substantially expands public access to NASA data, making their use by a wide range of decision makers feasible. By successful completion of this research, decision-making activities, including policy-making and clinical decision-making, can be positively affected through utilization of the data products and analyses provided on the CDC WONDER system

Using NASA Environmental Data to Enhance Public Health Decision Making

The Universities Space Research Association at the NASA Marshall Space Flight Center is collaborating with the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) to address issues of environmental health and enhance public health decision making by utilizing NASA remotely sensed data and products. The objectives of this collaboration are to develop high-quality spatial data sets of environmental variables, and deliver the data sets and associated analyses to local, state and federal end-user groups. These data can be linked spatially and temporally to public health data, such as mortality and disease morbidity, for further analysis and decision making. Three daily environmental data sets have been developed for the conterminous U.S. on different spatial resolutions for the time period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental data sets will be linked with public health data from the UAB REasons for Geographic And Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental datasets and public health linkage analyses will be made available to public health professionals, researchers and the general public through the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system and through peer reviewed publications. To date, two of the data sets have been released to the public in CDC WONDER, Daily Air Temperature and Heat Index for years 1979-2010, and Daily Fine Particulate Matter (PM2.5) air quality measures for years 2003-2008. These data in CDC WONDER can be aggregated to the county-level, state-level, or regional-level as per users need and downloaded in tabular, graphical, and map formats. The summary statistical output are available to web and app developers via the WONDER Application Programming Interface (API). The linkage of these data with the CDC WONDER system provides a significant addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in CDC WONDER online system. It also substantially expands public access to NASA environmental data, making their use by a wide range of decision makers feasible

Linking NASA Environmental Data with a National Public Health Cohort Study and a CDC On-Line System to Enhance Public Health Decision Making

The overall goal of this study is to address issues of environmental health and enhance public health decision making by utilizing NASA remotely-sensed data and products. This study is a collaboration between NASA Marshall Space Flight Center, Universities Space Research Association (USRA), the University of Alabama at Birmingham (UAB) School of Public Health and the Centers for Disease Control and Prevention (CDC) National Center for Public Health Informatics. The objectives of this study are to develop high-quality spatial data sets of environmental variables, link these with public health data from a national cohort study, and deliver the linked data sets and associated analyses to local, state and federal end-user groups. Three daily environmental data sets were developed for the conterminous U.S. on different spatial resolutions for the period 2003-2008: (1) spatial surfaces of estimated fine particulate matter (PM2.5) exposures on a 10-km grid utilizing the US Environmental Protection Agency (EPA) ground observations and NASA s MODerate-resolution Imaging Spectroradiometer (MODIS) data; (2) a 1-km grid of Land Surface Temperature (LST) using MODIS data; and (3) a 12-km grid of daily Solar Insolation (SI) and maximum and minimum air temperature using the North American Land Data Assimilation System (NLDAS) forcing data. These environmental datasets were linked with public health data from the UAB REasons for Geographic and Racial Differences in Stroke (REGARDS) national cohort study to determine whether exposures to these environmental risk factors are related to cognitive decline and other health outcomes. These environmental national datasets will also be made available to public health professionals, researchers and the general public via the CDC Wide-ranging Online Data for Epidemiologic Research (WONDER) system, where they can be aggregated to the county, state or regional level as per users need and downloaded in tabular, graphical, and map formats. The linkage of these data provides a useful addition to CDC WONDER, allowing public health researchers and policy makers to better include environmental exposure data in the context of other health data available in this online system. It also substantially expands public access to NASA data, making their use by a wide range of decision makers feasible

UBVRI Light Curves of 44 Type Ia Supernovae

We present UBVRI photometry of 44 type-Ia supernovae (SN Ia) observed from 1997 to 2001 as part of a continuing monitoring campaign at the Fred Lawrence Whipple Observatory of the Harvard-Smithsonian Center for Astrophysics. The data set comprises 2190 observations and is the largest homogeneously observed and reduced sample of SN Ia to date, nearly doubling the number of well-observed, nearby SN Ia with published multicolor CCD light curves. The large sample of U-band photometry is a unique addition, with important connections to SN Ia observed at high redshift. The decline rate of SN Ia U-band light curves correlates well with the decline rate in other bands, as does the U-B color at maximum light. However, the U-band peak magnitudes show an increased dispersion relative to other bands even after accounting for extinction and decline rate, amounting to an additional ~40% intrinsic scatter compared to B-band.Comment: 84 authors, 71 pages, 51 tables, 10 figures. Accepted for publication in the Astronomical Journal. Version with high-res figures and electronic data at http://astron.berkeley.edu/~saurabh/cfa2snIa

Assessing the accuracy of an inter-institutional automated patient-specific health problem list

<p>Abstract</p> <p>Background</p> <p>Health problem lists are a key component of electronic health records and are instrumental in the development of decision-support systems that encourage best practices and optimal patient safety. Most health problem lists require initial clinical information to be entered manually and few integrate information across care providers and institutions. This study assesses the accuracy of a novel approach to create an inter-institutional automated health problem list in a computerized medical record (MOXXI) that integrates three sources of information for an individual patient: diagnostic codes from medical services claims from all treating physicians, therapeutic indications from electronic prescriptions, and single-indication drugs.</p> <p>Methods</p> <p>Data for this study were obtained from 121 general practitioners and all medical services provided for 22,248 of their patients. At the opening of a patient's file, all health problems detected through medical service utilization or single-indication drug use were flagged to the physician in the MOXXI system. Each new arising health problem were presented as 'potential' and physicians were prompted to specify if the health problem was valid (Y) or not (N) or if they preferred to reassess its validity at a later time.</p> <p>Results</p> <p>A total of 263,527 health problems, representing 891 unique problems, were identified for the group of 22,248 patients. Medical services claims contributed to the majority of problems identified (77%), followed by therapeutic indications from electronic prescriptions (14%), and single-indication drugs (9%). Physicians actively chose to assess 41.7% (n = 106,950) of health problems. Overall, 73% of the problems assessed were considered valid; 42% originated from medical service diagnostic codes, 11% from single indication drugs, and 47% from prescription indications. Twelve percent of problems identified through other treating physicians were considered valid compared to 28% identified through study physician claims.</p> <p>Conclusion</p> <p>Automation of an inter-institutional problem list added over half of all validated problems to the health problem list of which 12% were generated by conditions treated by other physicians. Automating the integration of existing information sources provides timely access to accurate and relevant health problem information. It may also accelerate the uptake and use of electronic medical record systems.</p

A ruthenium polypyridyl intercalator stalls DNA replication forks, radiosensitizes human cancer cells and is enhanced by Chk1 inhibition

Ruthenium(II) polypyridyl complexes can intercalate DNA with high affinity and prevent cell proliferation; however, the direct impact of ruthenium-based intercalation on cellular DNA replication remains unknown. Here we show the multi-intercalator [Ru(dppz)2(PIP)]2+ (dppz = dipyridophenazine, PIP = 2-(phenyl)imidazo[4,5-f][1,10]phenanthroline) immediately stalls replication fork progression in HeLa human cervical cancer cells. In response to this replication blockade, the DNA damage response (DDR) cell signalling network is activated, with checkpoint kinase 1 (Chk1) activation indicating prolonged replication-associated DNA damage, and cell proliferation is inhibited by G1-S cell-cycle arrest. Co-incubation with a Chk1 inhibitor achieves synergistic apoptosis in cancer cells, with a significant increase in phospho(Ser139) histone H2AX (γ- H2AX) levels and foci indicating increased conversion of stalled replication forks to double-strand breaks (DSBs). Normal human epithelial cells remain unaffected by this concurrent treatment. Furthermore, pre-treatment of HeLa cells with [Ru(dppz)2(PIP)]2+ before external beam ionising radiation results in a supra-additive decrease in cell survival accompanied by increased γ-H2AX expression, indicating the compound functions as a radiosensitizer. Together, these results indicate ruthenium-based intercalation can block replication fork progression and demonstrate how these DNA-binding agents may be combined with DDR inhibitors or ionising radiation to achieve more efficient cancer cell killing