Applicability of machine learning approaches for structural damage detection of offshore wind jacket structures based on low resolution data

Structural damage in offshore wind jacket support structures are relatively unlikely due to the precautions taken in design but it could imply dramatic consequences if undetected. This work explores the possibilities of damage detection when using low resolution data, which are available with lower costs compared to dedicated high-resolution structural health monitoring. Machine learning approaches showed to be generally feasible for detecting a structural damage based on SCADA data collected in a simulation environment. Focus is here given to investigate model uncertainties, to assess the applicability of machine learning approaches for reality. Two jacket models are utilised representing the as-designed and the as-installed system, respectively. Extensive semi-coupled simulations representing different operating load cases are conducted to generate a database of low-resolution signals serving the machine learning training and testing. The analysis shows the challenges of classification approaches, i.e. supervised learning aiming to separate healthy and damage status, in coping with the uncertainty in system dynamics. Contrarily, an unsupervised novelty detection approach shows promising results when trained with data from both, the as-designed and the as-installed system. The findings highlight the importance of investigating model uncertainties and careful selection of training data

Reliability, availability, maintainability data review for the identification of trends in offshore wind energy applications

This work presents a comprehensive review and discussion of the identification of critical components of the currently installed and next generation of offshore wind turbines. A systematic review on the reliability, availability, and maintainability data of both offshore and onshore wind turbines is initially performed, collecting the results from 24 initiatives, at system and subsystem level. Due to the scarcity of data from the offshore wind industry, the analysis is complemented with the extensive experience from onshore structures. Trends based on the deployment parameters for the influence of design characteristics and environmental conditions on the onshore wind turbines' reliability and availability are first investigated. The estimation of the operational availability for a set of offshore wind farm scenarios allowed a comparison with the recently published performance statistics and the discussion of the integrity of the data available to date. The failure statistics of the systems deployed offshore are then discussed and compared to the onshore ones, with regard to their normalised results. The availability calculations supported the hypothesis of the negative impact of the offshore environmental conditions on the reliability figures. Nonetheless, similarities in the reliability figures of the blade adjustment system and the maintainability of the power generation and the control systems are outlined. Finally, to improve the performance prediction of future offshore projects, recommendations on the effort worth putting into research and data collection are provided

Feasibility of machine learning algorithms for classifying damaged offshore jacket structures using SCADA data

The best practise for structural damage detection currently relies on the installation of structural health monitoring systems for the collection of dedicated high frequency measurements. Switching to the employment of the wind turbine's SCADA (Supervisory Control and Data Acquisition) signals and their commonly recorded low frequency statistics can lead to a reduction in the number of ad-hoc monitoring sensors and quantity of data required. In this paper, aero-hydro-servo-elastic simulations for a model of a turbine are used to assess its loads and any changes in the dynamics under healthy state and a damaged configuration case study. To prove the feasibility of the damage detection through low-resolution data, the statistics of the typically recorded signals from the SCADA and the structural monitoring systems are fed into a database for training and testing of classification algorithms. The ability of the machine learning models to generalise the classification for both stochasticity and uncertainties in the environmental conditions are tested. Decision tree-based classifiers showed the capability to capture the damage for the majority of the operating conditions considered. Though the setup of the traditional SCADA sensors had to be supplemented with an additional structural health monitoring sensor, the detection of the damage has been shown feasible by referring to low-frequency statistics only

Progress on the development of a holistic coupled model of dynamics for offshore wind farms : phase II - study on a data-driven based reduced-order model for a single wind turbine

At present, over 1500 offshore wind turbines (OWTs) are operating in the UK with a capacity of 5.4GW. Until now, the research has mainly focused on how to minimise the CAPEX, but Operation and Maintenance (O&M) can represent up to 39% of the lifetime costs of an offshore wind farm, mainly due to the assets’ high cost and the harsh environment in which they operate. Focusing on O&M, the HOME Offshore research project (www.homeoffshore.org) aims to derive an advanced interpretation of the fault mechanisms through holistic multiphysics modelling of the wind farm. With the present work, an advanced model of dynamics for a single wind turbine is developed, able to identify the couplings between aero-hydro-servo-elastic (AHSE) dynamics and drive train dynamics. The wind turbine mechanical components, modelled using an AHSE dynamic model, are coupled with a detailed representation of a variable-speed direct-drive 5MW permanent magnet synchronous generator (PMSG) and its fully rated voltage source converters (VSCs). Using the developed model for the wind turbine, several case studies are carried out for above and below rated operating conditions. Firstly, the response time histories of wind turbine degrees of freedom (DOFs) are modelled using a full-order coupled analysis. Subsequently, regression analysis is applied in order to correlate DOFs and generated rotor torque (target degree of freedom for the failure mode in analysis), quantifying the level of inherent coupling effects. Finally, the reduced-order multiphysics models for a single offshore wind turbine are derived based on the strength of the correlation coefficients. The accuracy of the proposed reduced-order models is discussed, comparing it against the full-order coupled model in terms of statistical data and spectrum. In terms of statistical results, all the reducedorder models have a good agreement with the full-order results. In terms of spectrum, all the reduced-order models have a good agreement with the full-order results if the frequencies of interest are below 0.75Hz

Racial and ethnic disparities in access to minimally invasive mitral valve surgery

IMPORTANCE: Whether people from racial and ethnic minority groups experience disparities in access to minimally invasive mitral valve surgery (MIMVS) is not known. OBJECTIVE: To investigate racial and ethnic disparities in the utilization of MIMVS. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the Society of Thoracic Surgeons Database for patients who underwent mitral valve surgery between 2014 and 2019. Statistical analysis was performed from January 24 to August 11, 2022. EXPOSURES: Patients were categorized as non-Hispanic White, non-Hispanic Black, and Hispanic individuals. MAIN OUTCOMES AND MEASURES: The association between MIMVS (vs full sternotomy) and race and ethnicity were evaluated using logistic regression. RESULTS: Among the 103 753 patients undergoing mitral valve surgery (mean [SD] age, 62 [13] years; 47 886 female individuals [46.2%]), 10 404 (10.0%) were non-Hispanic Black individuals, 89 013 (85.8%) were non-Hispanic White individuals, and 4336 (4.2%) were Hispanic individuals. Non-Hispanic Black individuals were more likely to have Medicaid insurance (odds ratio [OR], 2.21; 95% CI, 1.64-2.98; P \u3c .001) and to receive care from a low-volume surgeon (OR, 4.45; 95% CI, 4.01-4.93; P \u3c .001) compared with non-Hispanic White individuals. Non-Hispanic Black individuals were less likely to undergo MIMVS (OR, 0.65; 95% CI, 0.58-0.73; P \u3c .001), whereas Hispanic individuals were not less likely to undergo MIMVS compared with non-Hispanic White individuals (OR, 1.08; 95% CI, 0.67-1.75; P = .74). Patients with commercial insurance had 2.35-fold higher odds of undergoing MIMVS (OR, 2.35; 95% CI, 2.06-2.68; P \u3c .001) than those with Medicaid insurance. Patients operated by very-high volume surgeons (300 or more cases) had 20.7-fold higher odds (OR, 20.70; 95% CI, 12.7-33.9; P \u3c .001) of undergoing MIMVS compared with patients treated by low-volume surgeons (less than 20 cases). After adjusting for patient risk, non-Hispanic Black individuals were still less likely to undergo MIMVS (adjusted OR [aOR], 0.88; 95% CI, 0.78-0.99; P = .04) and were more likely to die or experience a major complication (aOR, 1.25; 95% CI, 1.16-1.35; P \u3c .001) compared with non-Hispanic White individuals. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, non-Hispanic Black patients were less likely to undergo MIMVS and more likely to die or experience a major complication than non-Hispanic White patients. These findings suggest that efforts to reduce inequity in cardiovascular medicine may need to include increasing access to private insurance and high-volume surgeons

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

Crop changes from the XVI century to the present in a hill/mountain area of eastern Liguria (Italy)

<p>Abstract</p> <p>Background</p> <p>Chronological information on the composition and structure of agrocenoses and detailed features of land cover referring to specific areas are uncommon in ethnobotanical studies, especially for periods before the XIX century. The aim of this study was to analyse the type of crop or the characteristics of soil cover from the XVI century to the present.</p> <p>Methods</p> <p>This diachronic analysis was accomplished through archival research on the inventories of the Parish of St. Mary and those of the Municipality of Pignone and from recent surveys conducted in an area of eastern Liguria (Italy).</p> <p>Results</p> <p>Archival data revealed that in study area the primary means of subsistence during the last five centuries, until the first half of the XX century, was chestnuts. In the XVIII and XIX centuries, crop diversification strongly increased in comparison with previous and subsequent periods. In more recent times, the abandonment of agricultural practices has favoured the re-colonisation of mixed woodland or cluster-pine woodland.</p> <p>Conclusion</p> <p>Ancient documents in the ecclesiastic or municipal inventories can be a very useful tool for enhancing the knowledge of agricultural practice, as well as of subsistence methods favoured by local populations during a particular time and for reconstructing land use change over time.</p

Evidence-based Kernels: Fundamental Units of Behavioral Influence

This paper describes evidence-based kernels, fundamental units of behavioral influence that appear to underlie effective prevention and treatment for children, adults, and families. A kernel is a behavior–influence procedure shown through experimental analysis to affect a specific behavior and that is indivisible in the sense that removing any of its components would render it inert. Existing evidence shows that a variety of kernels can influence behavior in context, and some evidence suggests that frequent use or sufficient use of some kernels may produce longer lasting behavioral shifts. The analysis of kernels could contribute to an empirically based theory of behavioral influence, augment existing prevention or treatment efforts, facilitate the dissemination of effective prevention and treatment practices, clarify the active ingredients in existing interventions, and contribute to efficiently developing interventions that are more effective. Kernels involve one or more of the following mechanisms of behavior influence: reinforcement, altering antecedents, changing verbal relational responding, or changing physiological states directly. The paper describes 52 of these kernels, and details practical, theoretical, and research implications, including calling for a national database of kernels that influence human behavior