Spatial estimation of herbaceous biomass using remote sensing in Southern African savannas

The Savanna biome covers around 60% of sub-Saharan Africa. The goods and services it provides are utilised and often depended upon by rural communities, commercial farmers and managers of conservation areas existing within it. The benefits derivable by these parties depend largely on vegetation structure and species composition which can show great variation within savannas. Fire has long been used as an effective means of manipulating savanna vegetation to maximise the provision of specific benefits, usually the provision of new herbaceous growth, and to a lesser extent to control woody cover. Information on the abundance and distribution of herbaceous biomass, which is the primary fuel source for savanna fires, has emerged as one of the most important inputs for savanna management planning. Although the most popular and reliable means of obtaining this information remains field-based sampling, estimation using remote sensing data is increasingly being incorporated into the process. Its increased popularity stems from the fact that it can greatly expand the extent of the areas for which herbaceous biomass estimations can be provided. Although there have been studies conducted on the performance of individual remote sensing based herbaceous biomass estimation methods, few have focused on the relative performance of available methods. Information on the accuracy of methods when applied in relatively densely wooded savannas, or those where a large amount of herbaceous material is retained between seasons is also limited. This presents a problem for savanna managers in South Africa where these conditions prevail. It was the aim of this study to compare the accuracy and precision of two different remote sensing based herbaceous biomass estimation techniques (the use of a regression model and cokriging) when applied under such conditions. To achieve this aim a large amount of herbaceous biomass data were required to form testing and training datasets. These were acquired from the Kruger National Park’s Veld Condition Assessment (VCA) datasets for the growth seasons between 2000 and 2006, which contains herbaceous biomass estimates based on disk pasture meter readings. It was suspected early on in the study that the VCA field data was not ideal for use as remote sensing (ground truthing) field data because of the limited size of the field plots relative to the pixels of the remotely sensed imagery used. It was decided to include an additional section of analysis to determine the possible contribution of this issue to the estimation error of the methods assessed. This involved measuring and comparing mean herbaceous biomass in co-located trial 60x60m VCA sites and trial 250x250m, The Moderate Resolution Imaging Spectroradiometer (MODIS) pixels. The main section of analysis involved (i) gathering and deriving the required variables for use in the two estimation methods assessed, (ii) producing the estimates and (iii) comparing their accuracy and precision. The first method assessed was the use of a linear regression model. Seven regression models were created in total, one for each year of the growth seasons occurring between 2000 and 2006, plus another using all of the data combined. The models included variables to account for vegetation production (based on MODIS EVI), tree cover and fire history. These variables were derived using data supplied by the CSIR and Kruger National Park Scientific Services. The second method assessed was cokriging performed with the VCA herbaceous biomass field estimates as the primary variable and the MODIS EVI data as a secondary variable. The regression models were unable to account for more than 46% of the variation in herbaceous biomass, usually accounting for between just 20 and 30% (R2 of between 0.2 and 0.3). Three potential methods were identified that could improve the model fits obtained in the future, namely: 1. Increasing the dimensions of the field sample plots 2. Improving the calibration of the disk pasture meter used to collect the field data 3. Using EVI from previous seasons in conjunction with fire scar data to account for the presence of dry material from previous seasons. Cokriging produced estimates that were on average 119 kg/ha more accurate than those of the regression models. However, the performance of cokriging was poorer than expected given the results of previous studies in the area. A possible explanation for this discrepancy is that the ArcGIS geostatistical analysis extension used in this study is limited in its capabilities. Even with the poorer than expected performance recorded in this study, the cokriged maps remain the best option for fire managers as they are the most accurate to date and require the fewest resources to produce. Neither method produced estimates with less than 1000 kg/ha of error (RMSE), the upper limit initially considered useful in this study. However this error limit could be considered unrealistic given the well documented high level of heterogeneity typical of southern African savannas

Remote Sensing of Environment: Current status of Landsat program, science, and applications

Formal planning and development of what became the first Landsat satellite commenced over 50 years ago in 1967. Now, having collected earth observation data for well over four decades since the 1972 launch of Landsat- 1, the Landsat program is increasingly complex and vibrant. Critical programmatic elements are ensuring the continuity of high quality measurements for scientific and operational investigations, including ground systems, acquisition planning, data archiving and management, and provision of analysis ready data products. Free and open access to archival and new imagery has resulted in a myriad of innovative applications and novel scientific insights. The planning of future compatible satellites in the Landsat series, which maintain continuity while incorporating technological advancements, has resulted in an increased operational use of Landsat data. Governments and international agencies, among others, can now build an expectation of Landsat data into a given operational data stream. International programs and conventions (e.g., deforestation monitoring, climate change mitigation) are empowered by access to systematically collected and calibrated data with expected future continuity further contributing to the existing multi-decadal record. The increased breadth and depth of Landsat science and applications have accelerated following the launch of Landsat-8, with significant improvements in data quality. Herein, we describe the programmatic developments and institutional context for the Landsat program and the unique ability of Landsat to meet the needs of national and international programs. We then present the key trends in Landsat science that underpin many of the recent scientific and application developments and followup with more detailed thematically organized summaries. The historical context offered by archival imagery combined with new imagery allows for the development of time series algorithms that can produce information on trends and dynamics. Landsat-8 has figured prominently in these recent developments, as has the improved understanding and calibration of historical data. Following the communication of the state of Landsat science, an outlook for future launches and envisioned programmatic developments are presented. Increased linkages between satellite programs are also made possible through an expectation of future mission continuity, such as developing a virtual constellation with Sentinel-2. Successful science and applications developments create a positive feedback loop—justifying and encouraging current and future programmatic support for Landsat

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science : Seattle, WA, USA. 24-26 September 2015.

Introduction to the 3rd Biennial Conference of the Society for Implementation Research Collaboration: advancing efficient methodologies through team science and community partnerships Cara Lewis, Doyanne Darnell, Suzanne Kerns, Maria Monroe-DeVita, Sara J. Landes, Aaron R. Lyon, Cameo Stanick, Shannon Dorsey, Jill Locke, Brigid Marriott, Ajeng Puspitasari, Caitlin Dorsey, Karin Hendricks, Andria Pierson, Phil Fizur, Katherine A. Comtois A1: A behavioral economic perspective on adoption, implementation, and sustainment of evidence-based interventions Lawrence A. Palinkas A2: Towards making scale up of evidence-based practices in child welfare systems more efficient and affordable Patricia Chamberlain A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A3: Mixed method examination of strategic leadership for evidence-based practice implementation Gregory A. Aarons, Amy E. Green, Mark. G. Ehrhart, Elise M. Trott, Cathleen E. Willging A4: Implementing practice change in Federally Qualified Health Centers: Learning from leaders’ experiences Maria E. Fernandez, Nicholas H. Woolf, Shuting (Lily) Liang, Natalia I. Heredia, Michelle Kegler, Betsy Risendal, Andrea Dwyer, Vicki Young, Dayna Campbell, Michelle Carvalho, Yvonne Kellar-Guenther A5: Efficient synthesis: Using qualitative comparative analysis and the Consolidated Framework for Implementation Research across diverse studies Laura J. Damschroder, Julie C. Lowery A6: Establishing a veterans engagement group to empower patients and inform Veterans Affairs (VA) health services research Sarah S. Ono, Kathleen F. Carlson, Erika K. Cottrell, Maya E. O’Neil, Travis L. Lovejoy A7: Building patient-practitioner partnerships in community oncology settings to implement behavioral interventions for anxious and depressed cancer survivors Joanna J. Arch, Jill L. Mitchell A8: Tailoring a Cognitive Behavioral Therapy implementation protocol using mixed methods, conjoint analysis, and implementation teams Cara C. Lewis, Brigid R. Marriott, Kelli Scott A9: Wraparound Structured Assessment and Review (WrapSTAR): An efficient, yet comprehensive approach to Wraparound implementation evaluation Jennifer Schurer Coldiron, Eric J. Bruns, Alyssa N. Hook A10: Improving the efficiency of standardized patient assessment of clinician fidelity: A comparison of automated actor-based and manual clinician-based ratings Benjamin C. Graham, Katelin Jordan A11: Measuring fidelity on the cheap Rochelle F. Hanson, Angela Moreland, Benjamin E. Saunders, Heidi S. Resnick A12: Leveraging routine clinical materials to assess fidelity to an evidence-based psychotherapy Shannon Wiltsey Stirman, Cassidy A. Gutner, Jennifer Gamarra, Dawne Vogt, Michael Suvak, Jennifer Schuster Wachen, Katherine Dondanville, Jeffrey S. Yarvis, Jim Mintz, Alan L. Peterson, Elisa V. Borah, Brett T. Litz, Alma Molino, Stacey Young McCaughanPatricia A. Resick A13: The video vignette survey: An efficient process for gathering diverse community opinions to inform an intervention Nancy Pandhi, Nora Jacobson, Neftali Serrano, Armando Hernandez, Elizabeth Zeidler- Schreiter, Natalie Wietfeldt, Zaher Karp A14: Using integrated administrative data to evaluate implementation of a behavioral health and trauma screening for children and youth in foster care Michael D. Pullmann, Barbara Lucenko, Bridget Pavelle, Jacqueline A. Uomoto, Andrea Negrete, Molly Cevasco, Suzanne E. U. Kerns A15: Intermediary organizations as a vehicle to promote efficiency and speed of implementation Robert P. Franks, Christopher Bory A16: Applying the Consolidated Framework for Implementation Research constructs directly to qualitative data: The power of implementation science in action Edward J. Miech, Teresa M. Damush A17: Efficient and effective scaling-up, screening, brief interventions, and referrals to treatment (SBIRT) training: a snowball implementation model Jason Satterfield, Derek Satre, Maria Wamsley, Patrick Yuan, Patricia O’Sullivan A18: Matching models of implementation to system needs and capacities: addressing the human factor Helen Best, Susan Velasquez A19: Agency characteristics that facilitate efficient and successful implementation efforts Miya Barnett, Lauren Brookman-Frazee, Jennifer Regan, Nicole Stadnick, Alison Hamilton, Anna Lau A20: Rapid assessment process: Application to the Prevention and Early Intervention transformation in Los Angeles County Jennifer Regan, Alison Hamilton, Nicole Stadnick, Miya Barnett, Anna Lau, Lauren Brookman-Frazee A21: The development of the Evidence-Based Practice-Concordant Care Assessment: An assessment tool to examine treatment strategies across practices Nicole Stadnick, Anna Lau, Miya Barnett, Jennifer Regan, Scott Roesch, Lauren Brookman-Frazee A22: Refining a compilation of discrete implementation strategies and determining their importance and feasibility Byron J. Powell, Thomas J. Waltz, Matthew J. Chinman, Laura Damschroder, Jeffrey L. Smith, Monica M. Matthieu, Enola K. Proctor, JoAnn E. Kirchner A23: Structuring complex recommendations: Methods and general findings Thomas J. Waltz, Byron J. Powell, Matthew J. Chinman, Laura J. Damschroder, Jeffrey L. Smith, Monica J. Matthieu, Enola K. Proctor, JoAnn E. Kirchner A24: Implementing prolonged exposure for post-traumatic stress disorder in the Department of Veterans Affairs: Expert recommendations from the Expert Recommendations for Implementing Change (ERIC) project Monica M. Matthieu, Craig S. Rosen, Thomas J. Waltz, Byron J. Powell, Matthew J. Chinman, Laura J. Damschroder, Jeffrey L. Smith, Enola K. Proctor, JoAnn E. Kirchner A25: When readiness is a luxury: Co-designing a risk assessment and quality assurance process with violence prevention frontline workers in Seattle, WA Sarah C. Walker, Asia S. Bishop, Mariko Lockhart A26: Implementation potential of structured recidivism risk assessments with justice- involved veterans: Qualitative perspectives from providers Allison L. Rodriguez, Luisa Manfredi, Andrea Nevedal, Joel Rosenthal, Daniel M. Blonigen A27: Developing empirically informed readiness measures for providers and agencies for the Family Check-Up using a mixed methods approach Anne M. Mauricio, Thomas D. Dishion, Jenna Rudo-Stern, Justin D. Smith A28: Pebbles, rocks, and boulders: The implementation of a school-based social engagement intervention for children with autism Jill Locke, Courtney Benjamin Wolk, Colleen Harker, Anne Olsen, Travis Shingledecker, Frances Barg, David Mandell, Rinad S. Beidas A29: Problem Solving Teletherapy (PST.Net): A stakeholder analysis examining the feasibility and acceptability of teletherapy in community based aging services Marissa C. Hansen, Maria P. Aranda, Isabel Torres-Vigil A30: A case of collaborative intervention design eventuating in behavior therapy sustainment and diffusion Bryan Hartzler A31: Implementation of suicide risk prevention in an integrated delivery system: Mental health specialty services Bradley Steinfeld, Tory Gildred, Zandrea Harlin, Fredric Shephard A32: Implementation team, checklist, evaluation, and feedback (ICED): A step-by-step approach to Dialectical Behavior Therapy program implementation Matthew S. Ditty, Andrea Doyle, John A. Bickel III, Katharine Cristaudo A33: The challenges in implementing muliple evidence-based practices in a community mental health setting Dan Fox, Sonia Combs A34: Using electronic health record technology to promote and support evidence-based practice assessment and treatment intervention David H. Lischner A35: Are existing frameworks adequate for measuring implementation outcomes? Results from a new simulation methodology Richard A. Van Dorn, Stephen J. Tueller, Jesse M. Hinde, Georgia T. Karuntzos A36: Taking global local: Evaluating training of Washington State clinicians in a modularized cogntive behavioral therapy approach designed for low-resource settings Maria Monroe-DeVita, Roselyn Peterson, Doyanne Darnell, Lucy Berliner, Shannon Dorsey, Laura K. Murray A37: Attitudes toward evidence-based practices across therapeutic orientations Yevgeny Botanov, Beverly Kikuta, Tianying Chen, Marivi Navarro-Haro, Anthony DuBose, Kathryn E. Korslund, Marsha M. Linehan A38: Predicting the use of an evidence-based intervention for autism in birth-to-three programs Colleen M. Harker, Elizabeth A. Karp, Sarah R. Edmunds, Lisa V. Ibañez, Wendy L. Stone A39: Supervision practices and improved fidelity across evidence-based practices: A literature review Mimi Choy-Brown A40: Beyond symptom tracking: clinician perceptions of a hybrid measurement feedback system for monitoring treatment fidelity and client progress Jack H. Andrews, Benjamin D. Johnides, Estee M. Hausman, Kristin M. Hawley A41: A guideline decision support tool: From creation to implementation Beth Prusaczyk, Alex Ramsey, Ana Baumann, Graham Colditz, Enola K. Proctor A42: Dabblers, bedazzlers, or total makeovers: Clinician modification of a common elements cognitive behavioral therapy approach Rosemary D. Meza, Shannon Dorsey, Shannon Wiltsey-Stirman, Georganna Sedlar, Leah Lucid A43: Characterization of context and its role in implementation: The impact of structure, infrastructure, and metastructure Caitlin Dorsey, Brigid Marriott, Nelson Zounlome, Cara Lewis A44: Effects of consultation method on implementation of cognitive processing therapy for post-traumatic stress disorder Cassidy A. Gutner, Candice M. Monson, Norman Shields, Marta Mastlej, Meredith SH Landy, Jeanine Lane, Shannon Wiltsey Stirman A45: Cross-validation of the Implementation Leadership Scale factor structure in child welfare service organizations Natalie K. Finn, Elisa M. Torres, Mark. G. Ehrhart, Gregory A. Aarons A46: Sustainability of integrated smoking cessation care in Veterans Affairs posttraumatic stress disorder clinics: A qualitative analysis of focus group data from learning collaborative participants Carol A. Malte, Aline Lott, Andrew J. Saxon A47: Key characteristics of effective mental health trainers: The creation of the Measure of Effective Attributes of Trainers (MEAT) Meredith Boyd, Kelli Scott, Cara C. Lewis A48: Coaching to improve teacher implementation of evidence-based practices (EBPs) Jennifer D. Pierce A49: Factors influencing the implementation of peer-led health promotion programs targeting seniors: A literature review Agathe Lorthios-Guilledroit, Lucie Richard, Johanne Filiatrault A50: Developing treatment fidelity rating systems for psychotherapy research: Recommendations and lessons learned Kevin Hallgren, Shirley Crotwell, Rosa Muñoz, Becky Gius, Benjamin Ladd, Barbara McCrady, Elizabeth Epstein A51: Rapid translation of alcohol prevention science John D. Clapp, Danielle E. Ruderman A52: Factors implicated in successful implementation: evidence to inform improved implementation from high and low-income countries Melanie Barwick, Raluca Barac, Stanley Zlotkin, Laila Salim, Marnie Davidson A53: Tracking implementation strategies prospectively: A practical approach Alicia C. Bunger, Byron J. Powell, Hillary A. Robertson A54: Trained but not implementing: the need for effective implementation planning tools Christopher Botsko A55: Evidence, context, and facilitation variables related to implementation of Dialectical Behavior Therapy: Qualitative results from a mixed methods inquiry in the Department of Veterans Affairs Sara J. Landes, Brandy N. Smith, Allison L. Rodriguez, Lindsay R. Trent, Monica M. Matthieu A56: Learning from implementation as usual in children’s mental health Byron J. Powell, Enola K. Proctor A57: Rates and predictors of implementation after Dialectical Behavior Therapy Intensive Training Melanie S. Harned, Marivi Navarro-Haro, Kathryn E. Korslund, Tianying Chen, Anthony DuBose, André Ivanoff, Marsha M. Linehan A58: Socio-contextual determinants of research evidence use in public-youth systems of care Antonio R. Garcia, Minseop Kim, Lawrence A. Palinkas, Lonnie Snowden, John Landsverk A59: Community resource mapping to integrate evidence-based depression treatment in primary care in Brazil: A pilot project Annika C. Sweetland, Maria Jose Fernandes, Edilson Santos, Cristiane Duarte, Afrânio Kritski, Noa Krawczyk, Caitlin Nelligan, Milton L. Wainberg A60: The use of concept mapping to efficiently identify determinants of implementation in the National Institute of Health--President’s Emergent Plan for AIDS Relief Prevention of Mother to Child HIV Transmission Implementation Science Alliance Gregory A. Aarons, David H. Sommerfeld, Benjamin Chi, Echezona Ezeanolue, Rachel Sturke, Lydia Kline, Laura Guay, George Siberry A61: Longitudinal remote consultation for implementing collaborative care for depression Ian M. Bennett, Rinad Beidas, Rachel Gold, Johnny Mao, Diane Powers, Mindy Vredevoogd, Jurgen Unutzer A62: Integrating a peer coach model to support program implementation and ensure long- term sustainability of the Incredible Years in community-based settings Jennifer Schroeder, Lane Volpe, Julie Steffen A63: Efficient sustainability: Existing community based supervisors as evidence-based treatment supports Shannon Dorsey, Michael D Pullmann, Suzanne E. U. Kerns, Nathaniel Jungbluth, Lucy Berliner, Kelly Thompson, Eliza Segell A64: Establishment of a national practice-based implementation network to accelerate adoption of evidence-based and best practices Pearl McGee-Vincent, Nancy Liu, Robyn Walser, Jennifer Runnals, R. Keith Shaw, Sara J. Landes, Craig Rosen, Janet Schmidt, Patrick Calhoun A65: Facilitation as a mechanism of implementation in a practice-based implementation network: Improving care in a Department of Veterans Affairs post-traumatic stress disorder outpatient clinic Ruth L. Varkovitzky, Sara J. Landes A66: The ACT SMART Toolkit: An implementation strategy for community-based organizations providing services to children with autism spectrum disorder Amy Drahota, Jonathan I. Martinez, Brigitte Brikho, Rosemary Meza, Aubyn C. Stahmer, Gregory A. Aarons A67: Supporting Policy In Health with Research: An intervention trial (SPIRIT) - protocol and early findings Anna Williamson A68: From evidence based practice initiatives to infrastructure: Lessons learned from a public behavioral health system’s efforts to promote evidence based practices Ronnie M. Rubin, Byron J. Powell, Matthew O. Hurford, Shawna L. Weaver, Rinad S. Beidas, David S. Mandell, Arthur C. Evans A69: Applying the policy ecology model to Philadelphia’s behavioral health transformation efforts Byron J. Powell, Rinad S. Beidas, Ronnie M. Rubin, Rebecca E. Stewart, Courtney Benjamin Wolk, Samantha L. Matlin, Shawna Weaver, Matthew O. Hurford, Arthur C. Evans, Trevor R. Hadley, David S. Mandell A70: A model for providing methodological expertise to advance dissemination and implementation of health discoveries in Clinical and Translational Science Award institutions Donald R. Gerke, Beth Prusaczyk, Ana Baumann, Ericka M. Lewis, Enola K. Proctor A71: Establishing a research agenda for the Triple P Implementation Framework Jenna McWilliam, Jacquie Brown, Michelle Tucker A72: Cheap and fast, but what is “best?”: Examining implementation outcomes across sites in a state-wide scaled-up evidence-based walking program, Walk With Ease Kathleen P Conte A73: Measurement feedback systems in mental health: Initial review of capabilities and characteristics Aaron R. Lyon, Meredith Boyd, Abigail Melvin, Cara C. Lewis, Freda Liu, Nathaniel Jungbluth A74: A qualitative investigation of case managers’ attitudes toward implementation of a measurement feedback system in a public mental health system for youth Amelia Kotte, Kaitlin A. Hill, Albert C. Mah, Priya A. Korathu-Larson, Janelle R. Au, Sonia Izmirian, Scott Keir, Brad J. Nakamura, Charmaine K. Higa-McMillan A75: Multiple pathways to sustainability: Using Qualitative Comparative Analysis to uncover the necessary and sufficient conditions for successful community-based implementation Brittany Rhoades Cooper, Angie Funaiole, Eleanor Dizon A76: Prescribers’ perspectives on opioids and benzodiazepines and medication alerts to reduce co-prescribing of these medications Eric J. Hawkins, Carol A. Malte, Hildi J. Hagedorn, Douglas Berger, Anissa Frank, Aline Lott, Carol E. Achtmeyer, Anthony J. Mariano, Andrew J. Saxon A77: Adaptation of Coordinated Anxiety Learning and Management for comorbid anxiety and substance use disorders: Delivery of evidence-based treatment for anxiety in addictions treatment centers Kate Wolitzky-Taylor, Richard Rawson, Richard Ries, Peter Roy-Byrne, Michelle Craske A78: Opportunities and challenges of measuring program implementation with online surveys Dena Simmons, Catalina Torrente, Lori Nathanson, Grace Carroll A79: Observational assessment of fidelity to a family-centered prevention program: Effectiveness and efficiency Justin D. Smith, Kimbree Brown, Karina Ramos, Nicole Thornton, Thomas J. Dishion, Elizabeth A. Stormshak, Daniel S. Shaw, Melvin N. Wilson A80: Strategies and challenges in housing first fidelity: A multistate qualitative analysis Mimi Choy-Brown, Emmy Tiderington, Bikki Tran Smith, Deborah K. Padgett A81: Procurement and contracting as an implementation strategy: Getting To Outcomes® contracting Ronnie M. Rubin, Marilyn L. Ray, Abraham Wandersman, Andrea Lamont, Gordon Hannah, Kassandra A. Alia, Matthew O. Hurford, Arthur C. Evans A82: Web-based feedback to aid successful implementation: The interactive Stages of Implementation Completion (SIC)TM tool Lisa Saldana, Holle Schaper, Mark Campbell, Patricia Chamberlain A83: Efficient methodologies for monitoring fidelity in routine implementation: Lessons from the Allentown Social Emotional Learning Initiative Valerie B. Shapiro, B.K. Elizabeth Kim, Jennifer L. Fleming, Paul A. LeBuffe A84: The Society for Implementation Research Collaboration (SIRC) implementation development workshop: Results from a new methodology for enhancing implementation science proposals Sara J. Landes, Cara C. Lewis, Allison L. Rodriguez, Brigid R. Marriott, Katherine Anne Comtois A85: An update on the Society for Implementation Research Collaboration (SIRC) Instrument Review Projec

Quantum state preparation and macroscopic entanglement in gravitational-wave detectors

Long-baseline laser-interferometer gravitational-wave detectors are operating at a factor of 10 (in amplitude) above the standard quantum limit (SQL) within a broad frequency band. Such a low classical noise budget has already allowed the creation of a controlled 2.7 kg macroscopic oscillator with an effective eigenfrequency of 150 Hz and an occupation number of 200. This result, along with the prospect for further improvements, heralds the new possibility of experimentally probing macroscopic quantum mechanics (MQM) - quantum mechanical behavior of objects in the realm of everyday experience - using gravitational-wave detectors. In this paper, we provide the mathematical foundation for the first step of a MQM experiment: the preparation of a macroscopic test mass into a nearly minimum-Heisenberg-limited Gaussian quantum state, which is possible if the interferometer's classical noise beats the SQL in a broad frequency band. Our formalism, based on Wiener filtering, allows a straightforward conversion from the classical noise budget of a laser interferometer, in terms of noise spectra, into the strategy for quantum state preparation, and the quality of the prepared state. Using this formalism, we consider how Gaussian entanglement can be built among two macroscopic test masses, and the performance of the planned Advanced LIGO interferometers in quantum-state preparation

Searching for a Stochastic Background of Gravitational Waves with LIGO

The Laser Interferometer Gravitational-wave Observatory (LIGO) has performed the fourth science run, S4, with significantly improved interferometer sensitivities with respect to previous runs. Using data acquired during this science run, we place a limit on the amplitude of a stochastic background of gravitational waves. For a frequency independent spectrum, the new limit is $\Omega_{\rm GW} < 6.5 \times 10^{-5}$. This is currently the most sensitive result in the frequency range 51-150 Hz, with a factor of 13 improvement over the previous LIGO result. We discuss complementarity of the new result with other constraints on a stochastic background of gravitational waves, and we investigate implications of the new result for different models of this background.Comment: 37 pages, 16 figure

Mapping diphtheria-pertussis-tetanus vaccine coverage in Africa, 2000-2016: a spatial and temporal modelling study.

BACKGROUND: Routine childhood vaccination is among the most cost-effective, successful public health interventions available. Amid substantial investments to expand vaccine delivery throughout Africa and strengthen administrative reporting systems, most countries still require robust measures of local routine vaccine coverage and changes in geographical inequalities over time. METHODS: This analysis drew from 183 surveys done between 2000 and 2016, including data from 881 268 children in 49 African countries. We used a Bayesian geostatistical model calibrated to results from the Global Burden of Diseases, Injuries, and Risk Factors Study 2017, to produce annual estimates with high-spatial resolution (5 ×    5 km) of diphtheria-pertussis-tetanus (DPT) vaccine coverage and dropout for children aged 12-23 months in 52 African countries from 2000 to 2016. FINDINGS: Estimated third-dose (DPT3) coverage increased in 72·3% (95% uncertainty interval [UI] 64·6-80·3) of second-level administrative units in Africa from 2000 to 2016, but substantial geographical inequalities in DPT coverage remained across and within African countries. In 2016, DPT3 coverage at the second administrative (ie, district) level varied by more than 25% in 29 of 52 countries, with only two (Morocco and Rwanda) of 52 countries meeting the Global Vaccine Action Plan target of 80% DPT3 coverage or higher in all second-level administrative units with high confidence (posterior probability ≥95%). Large areas of low DPT3 coverage (≤50%) were identified in the Sahel, Somalia, eastern Ethiopia, and in Angola. Low first-dose (DPT1) coverage (≤50%) and high relative dropout (≥30%) together drove low DPT3 coverage across the Sahel, Somalia, eastern Ethiopia, Guinea, and Angola. INTERPRETATION: Despite substantial progress in Africa, marked national and subnational inequalities in DPT coverage persist throughout the continent. These results can help identify areas of low coverage and vaccine delivery system vulnerabilities and can ultimately support more precise targeting of resources to improve vaccine coverage and health outcomes for African children. FUNDING: Bill & Melinda Gates Foundation

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Upper limit map of a background of gravitational waves

We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table

Upper limit map of a background of gravitational waves

We searched for an anisotropic background of gravitational waves using data from the LIGO S4 science run and a method that is optimized for point sources. This is appropriate if, for example, the gravitational wave background is dominated by a small number of distinct astrophysical sources. No signal was seen. Upper limit maps were produced assuming two different power laws for the source strain power spectrum. For an f^-3 power law and using the 50 Hz to 1.8 kHz band the upper limits on the source strain power spectrum vary between 1.2e-48 Hz^-1 (100 Hz/f)^3 and 1.2e-47 Hz^-1 (100 Hz /f)^3, depending on the position in the sky. Similarly, in the case of constant strain power spectrum, the upper limits vary between 8.5e-49 Hz^-1 and 6.1e-48 Hz^-1. As a side product a limit on an isotropic background of gravitational waves was also obtained. All limits are at the 90% confidence level. Finally, as an application, we focused on the direction of Sco-X1, the closest low-mass X-ray binary. We compare the upper limit on strain amplitude obtained by this method to expectations based on the X-ray luminosity of Sco-X1.Comment: 11 pages, 9 figures, 2 table