Upper limits on the strength of periodic gravitational waves from PSR J1939+2134

The first science run of the LIGO and GEO gravitational wave detectors presented the opportunity to test methods of searching for gravitational waves from known pulsars. Here we present new direct upper limits on the strength of waves from the pulsar PSR J1939+2134 using two independent analysis methods, one in the frequency domain using frequentist statistics and one in the time domain using Bayesian inference. Both methods show that the strain amplitude at Earth from this pulsar is less than a few times $10^{-22}$.Comment: 7 pages, 1 figure, to appear in the Proceedings of the 5th Edoardo Amaldi Conference on Gravitational Waves, Tirrenia, Pisa, Italy, 6-11 July 200

Improving the sensitivity to gravitational-wave sources by modifying the input-output optics of advanced interferometers

We study frequency dependent (FD) input-output schemes for signal-recycling interferometers, the baseline design of Advanced LIGO and the current configuration of GEO 600. Complementary to a recent proposal by Harms et al. to use FD input squeezing and ordinary homodyne detection, we explore a scheme which uses ordinary squeezed vacuum, but FD readout. Both schemes, which are sub-optimal among all possible input-output schemes, provide a global noise suppression by the power squeeze factor, while being realizable by using detuned Fabry-Perot cavities as input/output filters. At high frequencies, the two schemes are shown to be equivalent, while at low frequencies our scheme gives better performance than that of Harms et al., and is nearly fully optimal. We then study the sensitivity improvement achievable by these schemes in Advanced LIGO era (with 30-m filter cavities and current estimates of filter-mirror losses and thermal noise), for neutron star binary inspirals, and for narrowband GW sources such as low-mass X-ray binaries and known radio pulsars. Optical losses are shown to be a major obstacle for the actual implementation of these techniques in Advanced LIGO. On time scales of third-generation interferometers, like EURO/LIGO-III (~2012), with kilometer-scale filter cavities, a signal-recycling interferometer with the FD readout scheme explored in this paper can have performances comparable to existing proposals. [abridged]Comment: Figs. 9 and 12 corrected; Appendix added for narrowband data analysi

The State of the Dry Forest Zone and its Communities

94 p.The Dry Forest Zone is a region of eastern Oregon and northern California with challenging market conditions and high levels of poverty and unemployment. However, local entrepreneurship, collaboration, and commitment to integrated economic development and natural resource management in the zone are strong. In the past decade, the scope of community-based nonprofits, integrated biomass utilization businesses, and new networks has increased, fostering sustainable forest stewardship at an increasingly regional scale. The geography and climate of the zone support dry forests of pine and mixed conifer with fire regimes that are departed from their historical range of variability. These forests are prone to wildfire hazards and in need of active management to restore more diverse and variable-aged structures. As 68 percent of the land in the zone is public, the communities of this region rely on the economic and ecological productivity of these federal forests. The number of sawmills that once provided high levels of primary processing capacity and employment has shrunk to nine mills in the zone. More forest-related employment is now forestry support work, including activities such as firefighting, pest control, and thinning. Poverty and unemployment have increased, with estimated poverty levels in 2007 of over 15 percent in ten of the fifteen counties. Through the Dry Forest Zone project, we have an opportunity to build on the local strengths of this region and overcome these ecological and socioeconomic challenges.Financial support was provided the U.S. Endowment for Forestry and Communities, USDA Rural Development, and the Ford Foundation

Detektion von Apnoeereignissen aus Schnarchsignalen

Zur ambulanten Differenzierung zwischen primärem Schnarchen und obstruktiver Schlafapnoe wird eine kostengünstige und einfach durchführbare Diagnostik benötigt. Eine Quantifizierung der Schnarchlautstärke ist bisher nicht zufriedenstellend möglich, führt jedoch typischerweise den Patienten zum HNO-Arzt. Das Ziel dieser Studie war es, anhand von während des Schlafes aufgezeichneten Atemgeräuschen eine Software zu entwickeln, die Schnarchgeräusche quantifiziert und Atempausen detektiert.Auf der Basis von 89 Ganz-Nacht-Datensätzen von 49 Personen wurde ein Algorithmus entwickelt, der das gesamte Audiosignal mit speziellen Filtersystemen nach charakteristischen Atemgeräuschen durchsucht. Folgt auf eine Geräuschpause von mindestens 10 sec Länge ein typisches Öffnungsgeräusch, so wird diese Stelle als Apnoe-ähnliches Ereignis erkannt. Zur Ermittlung von Sensitivität und Spezifität der Software wurden die Ergebnisse dann mit den in der simultanen Polysomnographie gefundenen Atempausen verglichen. Das Ausmaß der Schnarchgeräusche wurde bezüglich ihrer Intensität und Häufigkeit quantifiziert.Zur Erzielung einer optimalen Apnoeerkennung waren Bandpassfilter und adaptive Schwellenwertbestimmung erforderlich. Bei einem Filterwert von 11 Sekunden wurde eine Sensitivität von 81,5% und eine Spezifität von 48,5% erreicht. Vereinfachte Hochpassfilter ergaben eine deutlich schlechtere Genauigkeit. Für die Beurteilung des Schnarchens wurde ein Index aus mittlerer Intensität und Schnarchhäufigkeit errechnet.Die Analyse von Atemgeräuschen im Schlaf kann erfolgreich zum Apnoescreening und zur Quantifizierung der Schnarchlautstärke genutzt werden. Weitere Modifikationen sind erforderlich, um die Genauigkeit des Systems noch zu verbessern.Supported by: teilweise unterstützt durch IFU GmbH, Lichtena

External validation and recalibration of an incidental meningioma prognostic model - IMPACT: protocol for an international multicentre retrospective cohort study

Introduction: Due to the increased use of CT and MRI, the prevalence of incidental findings on brain scans is increasing. Meningioma, the most common primary brain tumour, is a frequently encountered incidental finding, with an estimated prevalence of 3/1000. The management of incidental meningioma varies widely with active clinical-radiological monitoring being the most accepted method by clinicians. Duration of monitoring and time intervals for assessment, however, are not well defined. To this end, we have recently developed a statistical model of progression risk based on single-centre retrospective data. The model Incidental Meningioma: Prognostic Analysis Using Patient Comorbidity and MRI Tests (IMPACT) employs baseline clinical and imaging features to categorise the patient with an incidental meningioma into one of three risk groups: low, medium and high risk with a proposed active monitoring strategy based on the risk and temporal trajectory of progression, accounting for actuarial life expectancy. The primary aim of this study is to assess the external validity of this model. Methods and analysis: IMPACT is a retrospective multicentre study which will aim to include 1500 patients with an incidental intracranial meningioma, powered to detect a 10% progression risk. Adult patients ≥16 years diagnosed with an incidental meningioma between 1 January 2009 and 31 December 2010 will be included. Clinical and radiological data will be collected longitudinally until the patient reaches one of the study endpoints: intervention (surgery, stereotactic radiosurgery or fractionated radiotherapy), mortality or last date of follow-up. Data will be uploaded to an online Research Electronic Data Capture database with no unique identifiers. External validity of IMPACT will be tested using established statistical methods. Ethics and dissemination: Local institutional approval at each participating centre will be required. Results of the study will be reported through peer-reviewed articles and conferences and disseminated to participating centres, patients and the public using social media