Perceiving Physical Equation by Observing Visual Scenarios

Inferring universal laws of the environment is an important ability of human intelligence as well as a symbol of general AI. In this paper, we take a step toward this goal such that we introduce a new challenging problem of inferring invariant physical equation from visual scenarios. For instance, teaching a machine to automatically derive the gravitational acceleration formula by watching a free-falling object. To tackle this challenge, we present a novel pipeline comprised of an Observer Engine and a Physicist Engine by respectively imitating the actions of an observer and a physicist in the real world. Generally, the Observer Engine watches the visual scenarios and then extracting the physical properties of objects. The Physicist Engine analyses these data and then summarizing the inherent laws of object dynamics. Specifically, the learned laws are expressed by mathematical equations such that they are more interpretable than the results given by common probabilistic models. Experiments on synthetic videos have shown that our pipeline is able to discover physical equations on various physical worlds with different visual appearances.Comment: NIPS 2018 Workshop on Modeling the Physical Worl

Mindfulness-based interventions for people diagnosed with a current episode of an anxiety or depressive disorder: a meta-analysis of randomised controlled trials

Objective Mindfulness-based interventions (MBIs) can reduce risk of depressive relapse for people with a history of recurrent depression who are currently well. However, the cognitive, affective and motivational features of depression and anxiety might render MBIs ineffective for people experiencing current symptoms. This paper presents a meta-analysis of randomised controlled trials (RCTs) of MBIs where participants met diagnostic criteria for a current episode of an anxiety or depressive disorder. Method Post-intervention between-group Hedges g effect sizes were calculated using a random effects model. Moderator analyses of primary diagnosis, intervention type and control condition were conducted and publication bias was assessed. Results Twelve studies met inclusion criteria (n = 578). There were significant post-intervention between-group benefits of MBIs relative to control conditions on primary symptom severity (Hedges g = −0.59, 95% CI = −0.12 to −1.06). Effects were demonstrated for depressive symptom severity (Hedges g = −0.73, 95% CI = −0.09 to −1.36), but not for anxiety symptom severity (Hedges g = −0.55, 95% CI = 0.09 to −1.18), for RCTs with an inactive control (Hedges g = −1.03, 95% CI = −0.40 to −1.66), but not where there was an active control (Hedges g = 0.03, 95% CI = 0.54 to −0.48) and effects were found for MBCT (Hedges g = −0.39, 95% CI = −0.15 to −0.63) but not for MBSR (Hedges g = −0.75, 95% CI = 0.31 to −1.81). Conclusions This is the first meta-analysis of RCTs of MBIs where all studies included only participants who were diagnosed with a current episode of a depressive or anxiety disorder. Effects of MBIs on primary symptom severity were found for people with a current depressive disorder and it is recommended that MBIs might be considered as an intervention for this population

Wild-Type, but Not Mutant N296H, Human Tau Restores Aβ-Mediated Inhibition of LTP in Tau−/− mice

Microtubule associated protein tau (MAPT) is involved in the pathogenesis of Alzheimer’s disease and many forms of frontotemporal dementia (FTD). We recently reported that Aβ-mediated inhibition of hippocampal long-term potentiation (LTP) in mice requires tau. Here, we asked whether expression of human $MAPT$ can restore Aβ-mediated inhibition on a mouse $Tau−/−$ background and whether human tau with an FTD-causing mutation (N296H) can interfere with Aβ-mediated inhibition of LTP. We used transgenic mouse lines each expressing the full human $MAPT$ locus using bacterial artificial chromosome technology. These lines expressed all six human tau protein isoforms on a $Tau−/−$ background. We found that the human wild-type $MAPT$ H1 locus was able to restore Aβ$_{42}$-mediated impairment of LTP. In contrast, Aβ$_{42}$ did not reduce LTP in slices in two independently generated transgenic lines expressing tau protein with the mutation N296H associated with frontotemporal dementia (FTD). Basal phosphorylation of tau measured as the ratio of AT8/Tau5 immunoreactivity was significantly reduced in N296H mutant hippocampal slices. Our data show that human $MAPT$ is able to restore Aβ$_{42}$-mediated inhibition of LTP in $Tau−/−$ mice. These results provide further evidence that tau protein is central to Aβ-induced LTP impairment and provide a valuable tool for further analysis of the links between Aβ, human tau and impairment of synaptic function.MVC was supported by a Wellcome Trust OXION Training Fellowship and an equipment grant from Alzheimer’s Research UK. MVC is funded by the Institute for Life Sciences University of Southampton. RW-M was supported by a Wellcome Trust Research Career Development Fellowship (073141/Z/03/Z), CurePSP and the Alzheimer’s Society; FD held a Wellcome Trust DPhil in Neuroscience (075406/Z/04/A), and CMP is funded by the Gerald Kerkut Trust and IfLS. We thank Hana N. Dawson and Michael P. Vitek for Tau−/− mice. We thank Jenny Dworzak for her participation at an early phase of this project

Análisis de frameworks de nube: Microsoft Azure y Amazon Web Services, mediante versiones privadas de prueba en entornos educativos

En la presente investigación nos dedicamos a indagar sobre las peculiaridades de dos plataformas de Cloud Computing. Es el caso de Microsoft Azure y Amazon Web Services, haciendo uso de versiones privadas de prueba en entornos educativos. Teniendo en cuenta sus características principales, se procede a realizar una comparación de las plataformas mencionadas, con la finalidad de elaborar una Tabla comparativa de los frameworks mencionados para presentar una serie de recomendaciones acerca de las características de las plataformas más seguras y adecuadas a la hora de decidir por una u otra. Con el fin de alcanzar el objetivo de este trabajo que resulta ser el de indagar y adquirir conocimientos teóricos sobre marcos de trabajo de plataformas de Cloud Computing que permitan alojar imágenes médicas con inserción de Marcas de Agua en los EHRs. Posteriormente elaborar una comparación cuantitativa y cualitativa de sus características principales, y recomendar cuáles son las plataformas más seguras y adecuadas. Para garantizar de algún modo que las imágenes médicas se puedan almacenar y distribuir en forma segura preservándolas de cualquier intento de distorsión.Eje: Seguridad informática.Red de Universidades con Carreras en Informátic

Análisis de frameworks de nubes: Azure y Amazon Web para alojar imágenes médicas

A través de la telemedicina, que representa un vertiginoso adelanto en el campo de las telecomunicaciones, los médicos pueden transferir y compartir, de manera remota, registros digitales que contienen información de los pacientes, con el objeto de emitir un diagnóstico definitivo. En estos días, los datos de carácter médico que usualmente se almacenaban en el centro de salud se suben a la nube. Hay que garantizar de algún modo que las imágenes médicas se puedan almacenar y distribuir en forma segura preservándolas de cualquier inteto de distorsión. En la presente investigación nos dedicamos a indagar sobre las peculiaridades de dos plataformas de Cloud Computing privadas en la actualidad como son Amazon y Azure para alojar las imágenes médicas. A partir de los datos obtenidos en este trabajo de investigación, elaboramos una tabla comparativa de los frameworks mencionados para presentar una serie de recomendaciones acerca de las características de las plataformas más seguras y adecuadas para alojar imágenes médicas.Ibero-American Science and Technology Education Consortiu

Análisis de frameworks de nubes: Azure y Amazon Web para alojar imágenes médicas

A través de la telemedicina, que representa un vertiginoso adelanto en el campo de las telecomunicaciones, los médicos pueden transferir y compartir, de manera remota, registros digitales que contienen información de los pacientes, con el objeto de emitir un diagnóstico definitivo. En estos días, los datos de carácter médico que usualmente se almacenaban en el centro de salud se suben a la nube. Hay que garantizar de algún modo que las imágenes médicas se puedan almacenar y distribuir en forma segura preservándolas de cualquier inteto de distorsión. En la presente investigación nos dedicamos a indagar sobre las peculiaridades de dos plataformas de Cloud Computing privadas en la actualidad como son Amazon y Azure para alojar las imágenes médicas. A partir de los datos obtenidos en este trabajo de investigación, elaboramos una tabla comparativa de los frameworks mencionados para presentar una serie de recomendaciones acerca de las características de las plataformas más seguras y adecuadas para alojar imágenes médicas.Ibero-American Science and Technology Education Consortiu

Análisis de frameworks de nubes: Azure y Amazon Web para alojar imágenes médicas

A través de la telemedicina, que representa un vertiginoso adelanto en el campo de las telecomunicaciones, los médicos pueden transferir y compartir, de manera remota, registros digitales que contienen información de los pacientes, con el objeto de emitir un diagnóstico definitivo. En estos días, los datos de carácter médico que usualmente se almacenaban en el centro de salud se suben a la nube. Hay que garantizar de algún modo que las imágenes médicas se puedan almacenar y distribuir en forma segura preservándolas de cualquier inteto de distorsión. En la presente investigación nos dedicamos a indagar sobre las peculiaridades de dos plataformas de Cloud Computing privadas en la actualidad como son Amazon y Azure para alojar las imágenes médicas. A partir de los datos obtenidos en este trabajo de investigación, elaboramos una tabla comparativa de los frameworks mencionados para presentar una serie de recomendaciones acerca de las características de las plataformas más seguras y adecuadas para alojar imágenes médicas.Ibero-American Science and Technology Education Consortiu

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

Seguridad en la nube: almacenamiento de imágenes médicas y watermarking

En los últimos años, se desarrollaron muchas aplicaciones acompañando el rápido avance de las telecomunicaciones. Una de ellas es la telemedicina por medio de la cual los médicos pueden transferir y compartir los datos digitales de los pacientes en forma remota para determinar un diagnóstico definitivo. Actualmente, la información médica que se almacenaba en el centro de salud se lleva a la nube. Por lo tanto, es esencial proteger los datos médicos intercambiados, especialmente cuando se utiliza una plataforma de Cloud Computing donde la seguridad es un problema importante. Hay que garantizar que las imágenes médicas se puedan compartir en forma segura preservándolas de cualquier intento de distorsión. Como así también proporcionar privacidad en las cadenas de datos de los Registros Electrónicos de los Pacientes o Electronic Health Records (EHR). En este trabajo, nos dedicamos a explorar y obtener conocimientos teóricos sobre marcos de trabajo de plataformas de Health Cloud Computing que permitan alojar imágenes médicas con inserción de Marcas de Agua en los EHRs. La finalidad de este trabajo de campo es seleccionar y probar plataformas de Health Cloud Computing. Posteriormente elaborar una comparación cuantitativa y cualitativa de sus características principales, y recomendar cuáles son las plataformas más seguras y adecuadas.Eje: Seguridad Informática.Red de Universidades con Carreras en Informátic

Seguridad en la nube: almacenamiento de imágenes médicas y watermarking

En los últimos años, se desarrollaron muchas aplicaciones acompañando el rápido avance de las telecomunicaciones. Una de ellas es la telemedicina por medio de la cual los médicos pueden transferir y compartir los datos digitales de los pacientes en forma remota para determinar un diagnóstico definitivo. Actualmente, la información médica que se almacenaba en el centro de salud se lleva a la nube. Por lo tanto, es esencial proteger los datos médicos intercambiados, especialmente cuando se utiliza una plataforma de Cloud Computing donde la seguridad es un problema importante. Hay que garantizar que las imágenes médicas se puedan compartir en forma segura preservándolas de cualquier intento de distorsión. Como así también proporcionar privacidad en las cadenas de datos de los Registros Electrónicos de los Pacientes o Electronic Health Records (EHR). En este trabajo, nos dedicamos a explorar y obtener conocimientos teóricos sobre marcos de trabajo de plataformas de Health Cloud Computing que permitan alojar imágenes médicas con inserción de Marcas de Agua en los EHRs. La finalidad de este trabajo de campo es seleccionar y probar plataformas de Health Cloud Computing. Posteriormente elaborar una comparación cuantitativa y cualitativa de sus características principales, y recomendar cuáles son las plataformas más seguras y adecuadas.Eje: Seguridad Informática.Red de Universidades con Carreras en Informátic