Consumer engagement and the development, evaluation and dissemination of evidence-based parenting programs

PubMed Central

Sanders, Matthew R.; Kirby, James N.

2013-01-01

A consumer perspective can contribute much to enhancing the “ecological fit” of population level parenting interventions so they meet the needs of parents. This approach involves building relationships with consumer groups and soliciting consumer input into the relevance and acceptability of interventions, clarifying the enablers and barriers to engagement and involvement of parents, and clarifying variables that influence a parent’s program completion. The adoption of a more collaborative approach to working with consumers is important if meaningful population level change in the prevalence of serious social, emotional and behavioral problems in children and young people is to be achieved. Parents seeking assistance for their children’s behavior come from a diverse range of socioeconomic backgrounds, educational levels, cultures and languages. This paper examines consumer engagement strategies that can be employed throughout the process of program development, evaluation, training and dissemination and in “scaling up” the intervention. We argue that a multi-level public health approach to parenting intervention requires a strong consumer perspective to enable interventions to be more responsive to the preferences and needs of families and to ensure improved population reach of interventions. Examples from large scale dissemination trials are used to illustrate how consumer input can result in an increasingly differentiated suite of evidence-based parenting programs. PMID:22440062

Dual Segment Glocal Model Based Capacitive Level Sensor (CLS) for Adhesive Material and Level Detection

NASA Astrophysics Data System (ADS)

Khan, F. A.; Yousaf, A.; Reindl, L. M.

2018-04-01

This paper presents a multi segment capacitive level monitoring sensor based on distributed E-fields approach Glocal. This approach has an advantage to analyze build-up problem by the local E-fields as well the fluid level monitoring by the global E-fields. The multi segment capacitive approach presented within this work addresses the main problem of unwanted parasitic capacitance generated from Copper (Cu) strips by applying active shielding concept. Polyvinyl chloride (PVC) is used for isolation and parafilm is used for creating artificial build-up on a CLS.

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

CREATE Wellness: A multi-component behavioral intervention for patients not responding to traditional Cardiovascular disease management.

PubMed

Miller-Rosales, Chris; Sterling, Stacy A; Wood, Sabrina B; Ross, Thekla; Makki, Mojdeh; Zamudio, Cindy; Kane, Irene M; Richardson, Megan C; Samayoa, Claudia; Charvat-Aguilar, Nancy; Lu, Wendy Y; Vo, Michelle; Whelan, Kimberly; Uratsu, Connie S; Grant, Richard W

2017-12-01

Cardiovascular disease (CVD) is the leading cause of death in the US. Many patients do not benefit from traditional disease management approaches to CVD risk reduction. Here we describe the rationale, development, and implementation of a multi-component behavioral intervention targeting patients who have persistently not met goals of CVD risk factor control. Informed by published evidence, relevant theoretical frameworks, stakeholder advice, and patient input, we developed a group-based intervention (Changing Results: Engage and Activate to Enhance Wellness; "CREATE Wellness") to address the complex needs of patients with elevated or unmeasured CVD-related risk factors. We are testing this intervention in a randomized trial among patients with persistent (i.e > 2 years) sub-optimal risk factor control despite being enrolled in an advanced and highly successful CVD disease management program. The CREATE Wellness intervention is designed as a 3 session, group-based intervention combining proven elements of patient activation, health system engagement skills training, shared decision making, care planning, and identification of lifestyle change barriers. Our key learnings in designing the intervention included the value of multi-level stakeholder input and the importance of pragmatic skills training to address barriers to care. The CREATE Wellness intervention represents an evidence-based, patient-centered approach for patients not responding to traditional disease management. The trial is currently underway at three medical facilities within Kaiser Permanente Northern California and next steps include an evaluation of efficacy, adaptation for non-English speaking patient populations, and modification of the curriculum for web- or phone-based versions. NCT02302612.

Comparison of multi-subject ICA methods for analysis of fMRI data

PubMed Central

Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.

2010-01-01

Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045

VLBI-resolution radio-map algorithms: Performance analysis of different levels of data-sharing on multi-socket, multi-core architectures

NASA Astrophysics Data System (ADS)

Tabik, S.; Romero, L. F.; Mimica, P.; Plata, O.; Zapata, E. L.

2012-09-01

A broad area in astronomy focuses on simulating extragalactic objects based on Very Long Baseline Interferometry (VLBI) radio-maps. Several algorithms in this scope simulate what would be the observed radio-maps if emitted from a predefined extragalactic object. This work analyzes the performance and scaling of this kind of algorithms on multi-socket, multi-core architectures. In particular, we evaluate a sharing approach, a privatizing approach and a hybrid approach on systems with complex memory hierarchy that includes shared Last Level Cache (LLC). In addition, we investigate which manual processes can be systematized and then automated in future works. The experiments show that the data-privatizing model scales efficiently on medium scale multi-socket, multi-core systems (up to 48 cores) while regardless of algorithmic and scheduling optimizations, the sharing approach is unable to reach acceptable scalability on more than one socket. However, the hybrid model with a specific level of data-sharing provides the best scalability over all used multi-socket, multi-core systems.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Towards a comprehensive global approach to prevention and control of NCDs.

PubMed

McKee, Martin; Haines, Andy; Ebrahim, Shah; Lamptey, Peter; Barreto, Mauricio L; Matheson, Don; Walls, Helen L; Foliaki, Sunia; Miranda, J Jaime; Chimeddamba, Oyun; Garcia-Marcos, Luis; Vineis, Paolo; Pearce, Neil

2014-10-28

The "25×25" strategy to tackle the global challenge of non-communicable diseases takes a traditional approach, concentrating on a few diseases and their immediate risk factors. We propose elements of a comprehensive strategy to address NCDs that takes account of the evolving social, economic, environmental and health care contexts, while developing mechanisms to respond effectively to local patterns of disease. Principles that underpin the comprehensive strategy include: (a) a balance between measures that address health at the individual and population level; (b) the need to identify evidence-based feasible and effective approaches tailored to low and middle income countries rather than exporting questionable strategies developed in high income countries; (c) developing primary health care as a universal framework to support prevention and treatment; (d) ensuring the ability to respond in real time to the complex adaptive behaviours of the global food, tobacco, alcohol and transport industries; (e) integrating evidence-based, cost-effective, and affordable approaches within the post-2015 sustainable development agenda; (f) determination of a set of priorities based on the NCD burden within each country, taking account of what it can afford, including the level of available development assistance; and (g) change from a universal "one-size fits all" approach of relatively simple prevention oriented approaches to more comprehensive multi-sectoral and development-oriented approaches which address both health systems and the determinants of NCD risk factors. The 25×25 is approach is absolutely necessary but insufficient to tackle the the NCD disease burden of mortality and morbidity. A more comprehensive approach is recommended.

A Multi-Level Decision Fusion Strategy for Condition Based Maintenance of Composite Structures

PubMed Central

Sharif Khodaei, Zahra; Aliabadi, M.H.

2016-01-01

In this work, a multi-level decision fusion strategy is proposed which weighs the Value of Information (VoI) against the intended functions of a Structural Health Monitoring (SHM) system. This paper presents a multi-level approach for three different maintenance strategies in which the performance of the SHM systems is evaluated against its intended functions. Level 1 diagnosis results in damage existence with minimum sensors covering a large area by finding the maximum energy difference for the guided waves propagating in pristine structure and the post-impact state; Level 2 diagnosis provides damage detection and approximate localization using an approach based on Electro-Mechanical Impedance (EMI) measures, while Level 3 characterizes damage (exact location and size) in addition to its detection by utilising a Weighted Energy Arrival Method (WEAM). The proposed multi-level strategy is verified and validated experimentally by detection of Barely Visible Impact Damage (BVID) on a curved composite fuselage panel. PMID:28773910

Integration of Evidence Base into a Probabilistic Risk Assessment

NASA Technical Reports Server (NTRS)

Saile, Lyn; Lopez, Vilma; Bickham, Grandin; Kerstman, Eric; FreiredeCarvalho, Mary; Byrne, Vicky; Butler, Douglas; Myers, Jerry; Walton, Marlei

2011-01-01

INTRODUCTION: A probabilistic decision support model such as the Integrated Medical Model (IMM) utilizes an immense amount of input data that necessitates a systematic, integrated approach for data collection, and management. As a result of this approach, IMM is able to forecasts medical events, resource utilization and crew health during space flight. METHODS: Inflight data is the most desirable input for the Integrated Medical Model. Non-attributable inflight data is collected from the Lifetime Surveillance for Astronaut Health study as well as the engineers, flight surgeons, and astronauts themselves. When inflight data is unavailable cohort studies, other models and Bayesian analyses are used, in addition to subject matters experts input on occasion. To determine the quality of evidence of a medical condition, the data source is categorized and assigned a level of evidence from 1-5; the highest level is one. The collected data reside and are managed in a relational SQL database with a web-based interface for data entry and review. The database is also capable of interfacing with outside applications which expands capabilities within the database itself. Via the public interface, customers can access a formatted Clinical Findings Form (CLiFF) that outlines the model input and evidence base for each medical condition. Changes to the database are tracked using a documented Configuration Management process. DISSCUSSION: This strategic approach provides a comprehensive data management plan for IMM. The IMM Database s structure and architecture has proven to support additional usages. As seen by the resources utilization across medical conditions analysis. In addition, the IMM Database s web-based interface provides a user-friendly format for customers to browse and download the clinical information for medical conditions. It is this type of functionality that will provide Exploratory Medicine Capabilities the evidence base for their medical condition list. CONCLUSION: The IMM Database in junction with the IMM is helping NASA aerospace program improve the health care and reduce risk for the astronauts crew. Both the database and model will continue to expand to meet customer needs through its multi-disciplinary evidence based approach to managing data. Future expansion could serve as a platform for a Space Medicine Wiki of medical conditions.

Framework for the design and delivery of organized physical activity sessions for children and adolescents: rationale and description of the 'SAAFE' teaching principles.

PubMed

Lubans, David R; Lonsdale, Chris; Cohen, Kristen; Eather, Narelle; Beauchamp, Mark R; Morgan, Philip J; Sylvester, Benjamin D; Smith, Jordan J

2017-02-23

The economic burden of inactivity is substantial, with conservative estimates suggesting the global cost to health care systems is more than US$50 billion. School-based programs, including physical education and school sport, have been recommended as important components of a multi-sector, multi-system approach to address physical inactivity. Additionally, community sporting clubs and after-school programs (ASPs) offer further opportunities for young people to be physically active outside of school. Despite demonstrating promise, current evidence suggests school-based physical activity programs, community sporting clubs and ASPs are not achieving their full potential. For example, physical activity levels in physical education (PE) and ASP sessions are typically much lower than recommended. For these sessions to have the strongest effects on young people's physical activity levels and their on-going physical literacy, they need to improve in quality and should be highly active and engaging. This paper presents the Supportive, Active, Autonomous, Fair, Enjoyable (SAAFE) principles, which represent an evidence-based framework designed to guide the planning, delivery and evaluation of organized physical activity sessions in school, community sport and ASPs. In this paper we provide a narrative and integrative review of the conceptual and empirical bases that underpin this framework and highlight implications for knowledge translation and application.

Automatic multi-organ segmentation using learning-based segmentation and level set optimization.

PubMed

Kohlberger, Timo; Sofka, Michal; Zhang, Jingdan; Birkbeck, Neil; Wetzl, Jens; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

We present a novel generic segmentation system for the fully automatic multi-organ segmentation from CT medical images. Thereby we combine the advantages of learning-based approaches on point cloud-based shape representation, such a speed, robustness, point correspondences, with those of PDE-optimization-based level set approaches, such as high accuracy and the straightforward prevention of segment overlaps. In a benchmark on 10-100 annotated datasets for the liver, the lungs, and the kidneys we show that the proposed system yields segmentation accuracies of 1.17-2.89 mm average surface errors. Thereby the level set segmentation (which is initialized by the learning-based segmentations) contributes with an 20%-40% increase in accuracy.

Enhancing evidence-based diabetes and chronic disease control among local health departments: a multi-phase dissemination study with a stepped-wedge cluster randomized trial component.

PubMed

Parks, Renee G; Tabak, Rachel G; Allen, Peg; Baker, Elizabeth A; Stamatakis, Katherine A; Poehler, Allison R; Yan, Yan; Chin, Marshall H; Harris, Jenine K; Dobbins, Maureen; Brownson, Ross C

2017-10-18

The rates of diabetes and prediabetes in the USA are growing, significantly impacting the quality and length of life of those diagnosed and financially burdening society. Premature death and disability can be prevented through implementation of evidence-based programs and policies (EBPPs). Local health departments (LHDs) are uniquely positioned to implement diabetes control EBPPs because of their knowledge of, and focus on, community-level needs, contexts, and resources. There is a significant gap, however, between known diabetes control EBPPs and actual diabetes control activities conducted by LHDs. The purpose of this study is to determine how best to support the use of evidence-based public health for diabetes (and related chronic diseases) control among local-level public health practitioners. This paper describes the methods for a two-phase study with a stepped-wedge cluster randomized trial that will evaluate dissemination strategies to increase the uptake of public health knowledge and EBPPs for diabetes control among LHDs. Phase 1 includes development of measures to assess practitioner views on and organizational supports for evidence-based public health, data collection using a national online survey of LHD chronic disease practitioners, and a needs assessment of factors influencing the uptake of diabetes control EBPPs among LHDs within one state in the USA. Phase 2 involves conducting a stepped-wedge cluster randomized trial to assess effectiveness of dissemination strategies with local-level practitioners at LHDs to enhance capacity and organizational support for evidence-based diabetes prevention and control. Twelve LHDs will be selected and randomly assigned to one of the three groups that cross over from usual practice to receive the intervention (dissemination) strategies at 8-month intervals; the intervention duration for groups ranges from 8 to 24 months. Intervention (dissemination) strategies may include multi-day in-person workshops, electronic information exchange methods, technical assistance through a knowledge broker, and organizational changes to support evidence-based public health approaches. Evaluation methods comprise surveys at baseline and the three crossover time points, abstraction of local-level diabetes and chronic disease control program plans and progress reports, and social network analysis to understand the relationships and contextual issues that influence EBPP adoption. ClinicalTrial.gov, NCT03211832.

Generalist solutions to complex problems: generating practice-based evidence - the example of managing multi-morbidity

PubMed Central

2013-01-01

Background A growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet the concept of multi-morbidity (the presence of >2 diseases) is a product of the design of health care systems which define health care need on the basis of disease status. So does the solution lie in an alternative model of healthcare? Discussion Strengthening generalist practice has been proposed as part of the solution to tackling multi-morbidity. Generalism is a professional philosophy of practice, deeply known to many practitioners, and described as expertise in whole person medicine. But generalism lacks the evidence base needed by policy makers and planners to support service redesign. The challenge is to fill this practice-research gap in order to critically explore if and when generalist care offers a robust alternative to management of this complex problem. We need practice-based evidence to fill this gap. By recognising generalist practice as a ‘complex intervention’ (intervening in a complex system), we outline an approach to evaluate impact using action-research principles. We highlight the implications for those who both commission and undertake research in order to tackle this problem. Summary Answers to the complex problem of multi-morbidity won’t come from doing more of the same. We need to change systems of care, and so the systems for generating evidence to support that care. This paper contributes to that work through outlining a process for generating practice-based evidence of generalist solutions to the complex problem of person-centred care for people with multi-morbidity. PMID:23919296

Generalist solutions to complex problems: generating practice-based evidence--the example of managing multi-morbidity.

PubMed

Reeve, Joanne; Blakeman, Tom; Freeman, George K; Green, Larry A; James, Paul A; Lucassen, Peter; Martin, Carmel M; Sturmberg, Joachim P; van Weel, Chris

2013-08-07

A growing proportion of people are living with long term conditions. The majority have more than one. Dealing with multi-morbidity is a complex problem for health systems: for those designing and implementing healthcare as well as for those providing the evidence informing practice. Yet the concept of multi-morbidity (the presence of >2 diseases) is a product of the design of health care systems which define health care need on the basis of disease status. So does the solution lie in an alternative model of healthcare? Strengthening generalist practice has been proposed as part of the solution to tackling multi-morbidity. Generalism is a professional philosophy of practice, deeply known to many practitioners, and described as expertise in whole person medicine. But generalism lacks the evidence base needed by policy makers and planners to support service redesign. The challenge is to fill this practice-research gap in order to critically explore if and when generalist care offers a robust alternative to management of this complex problem. We need practice-based evidence to fill this gap. By recognising generalist practice as a 'complex intervention' (intervening in a complex system), we outline an approach to evaluate impact using action-research principles. We highlight the implications for those who both commission and undertake research in order to tackle this problem. Answers to the complex problem of multi-morbidity won't come from doing more of the same. We need to change systems of care, and so the systems for generating evidence to support that care. This paper contributes to that work through outlining a process for generating practice-based evidence of generalist solutions to the complex problem of person-centred care for people with multi-morbidity.

Developing Evidence for Public Health Policy and Practice: The Implementation of a Knowledge Translation Approach in a Staged, Multi-Methods Study in England, 2007-09

ERIC Educational Resources Information Center

South, Jane; Cattan, Mima

2014-01-01

Effective knowledge translation processes are critical for the development of evidence-based public health policy and practice. This paper reports on the design and implementation of an innovative approach to knowledge translation within a mixed methods study on lay involvement in public health programme delivery. The study design drew on…

Adaptive multi-GPU Exchange Monte Carlo for the 3D Random Field Ising Model

NASA Astrophysics Data System (ADS)

Navarro, Cristóbal A.; Huang, Wei; Deng, Youjin

2016-08-01

This work presents an adaptive multi-GPU Exchange Monte Carlo approach for the simulation of the 3D Random Field Ising Model (RFIM). The design is based on a two-level parallelization. The first level, spin-level parallelism, maps the parallel computation as optimal 3D thread-blocks that simulate blocks of spins in shared memory with minimal halo surface, assuming a constant block volume. The second level, replica-level parallelism, uses multi-GPU computation to handle the simulation of an ensemble of replicas. CUDA's concurrent kernel execution feature is used in order to fill the occupancy of each GPU with many replicas, providing a performance boost that is more notorious at the smallest values of L. In addition to the two-level parallel design, the work proposes an adaptive multi-GPU approach that dynamically builds a proper temperature set free of exchange bottlenecks. The strategy is based on mid-point insertions at the temperature gaps where the exchange rate is most compromised. The extra work generated by the insertions is balanced across the GPUs independently of where the mid-point insertions were performed. Performance results show that spin-level performance is approximately two orders of magnitude faster than a single-core CPU version and one order of magnitude faster than a parallel multi-core CPU version running on 16-cores. Multi-GPU performance is highly convenient under a weak scaling setting, reaching up to 99 % efficiency as long as the number of GPUs and L increase together. The combination of the adaptive approach with the parallel multi-GPU design has extended our possibilities of simulation to sizes of L = 32 , 64 for a workstation with two GPUs. Sizes beyond L = 64 can eventually be studied using larger multi-GPU systems.

[Systemic therapies--a contribution to psychotherapy integration].

PubMed

Schiepek, Günter

2012-06-01

Some converging lines from neuroscience, neurobiological psychotherapy research, process-outcome-research, internet-based change monitoring and the systems and complexity sciences actually allow for an open and generic definition of systemic therapies. The "family" of systemic therapies as designed here is not restricted to the field of psychotherapy. It is a scientifically founded and engaged, bio-psycho-social multi-level approach to a common or integrative psychotherapy, not restricted to a psychotherapeutic confession or exclusively to family or couples therapy. A core element of systemic therapy is the support of self-organizing processes and the use of data-driven feedback tools. The conclusion goes to a modified concept of evidence-based practice and, vice versa, practice-based evidence, to an integration of the medical model and the common factors model into a self-organization theory of human change processes, and to a list of criteria for scientifically based practice in psychotherapy. © Georg Thieme Verlag KG Stuttgart · New York.

A systematic approach to baseline assessment of nursing documentation and enterprise-wide prioritization for electronic conversion.

PubMed

Dykes, Patricia C; Spurr, Cindy; Gallagher, Joan; Li, Qi; Ives Erickson, Jeanette

2006-01-01

An important challenge associated with making the transition from paper to electronic documentation systems is achieving consensus regarding priorities for electronic conversion across diverse groups. In our work we focus on applying a systematic approach to evaluating the baseline state of nursing documentation across a large healthcare system and establishing a unified vision for electronic conversion. A review of the current state of nursing documentation across PHS was conducted using structured tools. Data from this assessment was employed to facilitate an evidence-based approach to decision-making regarding conversion to electronic documentation at local and PHS levels. In this paper we present highlights of the assessment process and the outcomes of this multi-site collaboration.

Exploring multi-level system factors facilitating educator training and implementation of evidence-based practices (EBP): a study protocol.

PubMed

Stahmer, Aubyn C; Suhrheinrich, Jessica; Schetter, Patricia L; McGee Hassrick, Elizabeth

2018-01-08

This study examines how system-wide (i.e., region, district, and school) mechanisms such as leadership support, training requirements, structure, collaboration, and education affect the use of evidence-based practices (EBPs) in schools and how this affects the outcomes for students with autism spectrum disorder (ASD). Despite growing evidence for the positive effects of EBPs for ASD, these practices are not consistently or effectively used in schools. Although special education programs are mandated to use EBPs, there are very few evidence-based methods for selecting, implementing, and sustaining EBPs. Research focuses primarily on teacher training, without attention to contextual factors (e.g., implementation climate, attitudes toward EBPs, resource allocation, and social networks) that may impact outcomes. Using an implementation science framework, this project will prospectively examine relations between system-wide factors and teachers' use of EBPs and student education outcomes. Survey data will be collected from approximately 85 regional special education directors, 170 regional program specialists, 265 district special education directors, 265 behavior specialists, 925 school principals, 3538 special education teachers, and 2700 paraprofessionals. Administrative data for the students with ASD served by participating teachers will be examined. A total of 79 regional-, district-, and school-level personnel will also participate in social network interviews. Mixed methods, including surveys, administrative data, and observational checklists, will be used to gather in-depth information about system-wide malleable factors that relate to positive teacher implementation of EBPs and student outcomes. Multi-level modeling will be used to assess system-wide malleable factors related to EBP implementation which will be linked to the trainer, teacher, and student outcomes and examined based on moderators (e.g., district size, Special Education Local Plan Area structure, teachers' ASD experience). Finally, a dynamic social network approach will be used to map EBP-related connectivity across all levels of the system for selected regions. Dynamic network analysis will be used to gauge the degree to which and ways that EBP trainings, resources, and interventions are shared (or not shared) among school staff. Results are expected to inform the development of system-wide interventions to improve the school-based implementation of EBPs for students with ASD.

Mathematical model comparing of the multi-level economics systems

NASA Astrophysics Data System (ADS)

Brykalov, S. M.; Kryanev, A. V.

2017-12-01

The mathematical model (scheme) of a multi-level comparison of the economic system, characterized by the system of indices, is worked out. In the mathematical model of the multi-level comparison of the economic systems, the indicators of peer review and forecasting of the economic system under consideration can be used. The model can take into account the uncertainty in the estimated values of the parameters or expert estimations. The model uses the multi-criteria approach based on the Pareto solutions.

Multi-level stressor analysis from the DNA/biochemical level to community levels in an urban stream and integrative health response (IHR) assessments.

PubMed

Lee, Jae Hoon; Kim, Joon Ha; Oh, Hee-Mock; An, Kwang-Guk

2013-01-01

The objectives of this study were to identify multi-level stressors at the DNA/biochemical level to the community level in fish in an urban stream and to develop an integrative health response (IHR) model for ecological health diagnosis. A pristine control site (S (c) ) and an impacted site (S (i) ) were selected from among seven pre-screened sites studied over seven years. Various chemical analyses indicated that nutrient enrichment (Nitrogen, Phosphorus) and organic pollution were significantly greater (t > 8.783, p < 0.01) at the S (i) site compared to the S (c) site. Single-cell gel electrophoresis (comet assays) of DNA-level impairment indicated significantly (t = 5.678, p < 0.01) greater tail intensity, expressed as % tail-DNA, at the S (i) site and genotoxic responses were detected in the downstream reach. Ethoxyresorufin-O-deethylase (EROD) assays, as a physiological bioindicator, were 2.8-fold higher (p < 0.05, NK-test after ANOVA) at the S (i) site. Tissue analysis using a necropsy-based health assessment index (NHAI) showed distinct internal organ disorders in three tissues, i.e., liver, kidney, and gill, at the S (i) site. Population-level analysis using the sentinel species Zacco platypus showed that the regression coefficient (b) was 3.012 for the S (i) site and 2.915 for the S (c) site, indicating population skewness in the downstream reach. Community-level health was impaired at the S (i) site based on an index of biological integrity (IBI), and physical habitat modifications were identified by a qualitative habitat evaluation index (QHEI). Overall, the model values for the integrative health response (IHR), developed using the star plot approach, were 3.22 (80.5%) at the S (c) site and 0.74 (18.5%) at the S (i) site, indicating that, overall, ecological health impairments were evident in the urban reach. Our study was based on multi-level approaches using biological organization and the results suggest that there is a pivotal point of linkage between mechanistic understanding and real ecological consequences of environmental stressors.

Multi-fidelity methods for uncertainty quantification in transport problems

NASA Astrophysics Data System (ADS)

Tartakovsky, G.; Yang, X.; Tartakovsky, A. M.; Barajas-Solano, D. A.; Scheibe, T. D.; Dai, H.; Chen, X.

2016-12-01

We compare several multi-fidelity approaches for uncertainty quantification in flow and transport simulations that have a lower computational cost than the standard Monte Carlo method. The cost reduction is achieved by combining a small number of high-resolution (high-fidelity) simulations with a large number of low-resolution (low-fidelity) simulations. We propose a new method, a re-scaled Multi Level Monte Carlo (rMLMC) method. The rMLMC is based on the idea that the statistics of quantities of interest depends on scale/resolution. We compare rMLMC with existing multi-fidelity methods such as Multi Level Monte Carlo (MLMC) and reduced basis methods and discuss advantages of each approach.

Analytic hierarchy process-based approach for selecting a Pareto-optimal solution of a multi-objective, multi-site supply-chain planning problem

NASA Astrophysics Data System (ADS)

Ayadi, Omar; Felfel, Houssem; Masmoudi, Faouzi

2017-07-01

The current manufacturing environment has changed from traditional single-plant to multi-site supply chain where multiple plants are serving customer demands. In this article, a tactical multi-objective, multi-period, multi-product, multi-site supply-chain planning problem is proposed. A corresponding optimization model aiming to simultaneously minimize the total cost, maximize product quality and maximize the customer satisfaction demand level is developed. The proposed solution approach yields to a front of Pareto-optimal solutions that represents the trade-offs among the different objectives. Subsequently, the analytic hierarchy process method is applied to select the best Pareto-optimal solution according to the preferences of the decision maker. The robustness of the solutions and the proposed approach are discussed based on a sensitivity analysis and an application to a real case from the textile and apparel industry.

Exploring Multi-Level System Factors Facilitating Educator Training and Implementation of Evidence-Based Practices (EBP): A Study Protocol

ERIC Educational Resources Information Center

Stahmer, Aubyn C.; Suhrheinrich, Jessica; Schetter, Patricia L.; Hassrick, Elizabeth McGee

2018-01-01

This study examines how system-wide (i.e., region, district, and school) mechanisms such as leadership support, training requirements, structure, collaboration, and education affect the use of evidence-based practices (EBPs) in schools and how this affects the outcomes for students with autism spectrum disorder (ASD). Despite growing evidence for…

AMULET: A MUlti-cLuE Approach to Image Forensics

DTIC Science & Technology

2014-12-31

celebrities have been substituted in the other two pictures. 3.2.5 Choice of reliability properties Let us now apply the BBA mapping approach proposed in...Jiang, and L. Ma, “Ds evidence theory based digital image trustworthiness evaluation model,” in MINES 2009, International Conference on Multimedia

Profile of Students’ Mental Model Change on Law Concepts Archimedes as Impact of Multi-Representation Approach

NASA Astrophysics Data System (ADS)

Taher, M.; Hamidah, I.; Suwarma, I. R.

2017-09-01

This paper outlined the results of an experimental study on the effects of multi-representation approach in learning Archimedes Law on students’ mental model improvement. The multi-representation techniques implemented in the study were verbal, pictorial, mathematical, and graphical representations. Students’ mental model was classified into three levels, i.e. scientific, synthetic, and initial levels, based on the students’ level of understanding. The present study employed the pre-experimental methodology, using one group pretest-posttest design. The subject of the study was 32 eleventh grade students in a Public Senior High School in Riau Province. The research instrument included model mental test on hydrostatic pressure concept, in the form of essay test judged by experts. The findings showed that there was positive change in students’ mental model, indicating that multi-representation approach was effective to improve students’ mental model.

Best practices in policy approaches to obesity prevention.

PubMed

Fox, Ashley M; Horowitz, Carol R

2013-01-01

The rapidly rising rate of obesity has prompted a variety of policy responses at national, regional, and local levels. Yet, many have expressed concern that these policy responses have a limited evidence base, are overly paternalistic, and have the potential to increase rather than shrink obesity-related disparities. The purpose of this article is to evaluate obesity policies in terms of the adequacy of evidence for action and along two ethical dimensions: their potential effect on liberty and equity. To evaluate evidence, we engage in a systematic review of reviews and rate policies in terms of the sufficiency of evidence of effectiveness at combating obesity. We then apply a libertarian-paternalist framework to assess policies in terms of their impact on liberty and inverse-equity theory to assess impact on disparities. This article provides a framework to assist decision-makers in assessing best practices in obesity using a more multi-faceted set of dimensions.

Best Practices in Policy Approaches to Obesity Prevention

PubMed Central

Fox, Ashley M.; Horowitz, Carol R.

2014-01-01

The rapidly rising rate of obesity has prompted a variety of policy responses at national, regional, and local levels. Yet, many have expressed concern that these policy responses have a limited evidence base, are overly paternalistic, and have the potential to increase rather than shrink obesity-related disparities. The purpose of this article is to evaluate obesity policies in terms of the adequacy of evidence for action and along two ethical dimensions: their potential effect on liberty and equity. To evaluate evidence, we engage in a systematic review of reviews and rate policies in terms of the sufficiency of evidence of effectiveness at combating obesity. We then apply a libertarian-paternalist framework to assess policies in terms of their impact on liberty and inverse-equity theory to assess impact on disparities. This article provides a framework to assist decision-makers in assessing best practices in obesity using a more multi-faceted set of dimensions. PMID:23727973

Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework

NASA Astrophysics Data System (ADS)

Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.

2016-03-01

A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.

3D Digital Surveying and Modelling of Cave Geometry: Application to Paleolithic Rock Art.

PubMed

González-Aguilera, Diego; Muñoz-Nieto, Angel; Gómez-Lahoz, Javier; Herrero-Pascual, Jesus; Gutierrez-Alonso, Gabriel

2009-01-01

3D digital surveying and modelling of cave geometry represents a relevant approach for research, management and preservation of our cultural and geological legacy. In this paper, a multi-sensor approach based on a terrestrial laser scanner, a high-resolution digital camera and a total station is presented. Two emblematic caves of Paleolithic human occupation and situated in northern Spain, "Las Caldas" and "Peña de Candamo", have been chosen to put in practise this approach. As a result, an integral and multi-scalable 3D model is generated which may allow other scientists, pre-historians, geologists…, to work on two different levels, integrating different Paleolithic Art datasets: (1) a basic level based on the accurate and metric support provided by the laser scanner; and (2) a advanced level using the range and image-based modelling.

Multi-Level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

ERIC Educational Resources Information Center

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-01-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective,…

Resilient workflows for computational mechanics platforms

NASA Astrophysics Data System (ADS)

Nguyên, Toàn; Trifan, Laurentiu; Désidéri, Jean-Antoine

2010-06-01

Workflow management systems have recently been the focus of much interest and many research and deployment for scientific applications worldwide [26, 27]. Their ability to abstract the applications by wrapping application codes have also stressed the usefulness of such systems for multidiscipline applications [23, 24]. When complex applications need to provide seamless interfaces hiding the technicalities of the computing infrastructures, their high-level modeling, monitoring and execution functionalities help giving production teams seamless and effective facilities [25, 31, 33]. Software integration infrastructures based on programming paradigms such as Python, Mathlab and Scilab have also provided evidence of the usefulness of such approaches for the tight coupling of multidisciplne application codes [22, 24]. Also high-performance computing based on multi-core multi-cluster infrastructures open new opportunities for more accurate, more extensive and effective robust multi-discipline simulations for the decades to come [28]. This supports the goal of full flight dynamics simulation for 3D aircraft models within the next decade, opening the way to virtual flight-tests and certification of aircraft in the future [23, 24, 29].

State of science: occupational slips, trips and falls on the same level.

PubMed

Chang, Wen-Ruey; Leclercq, Sylvie; Lockhart, Thurmon E; Haslam, Roger

2016-07-01

Occupational slips, trips and falls on the same level (STFL) result in substantial injuries worldwide. This paper summarises the state of science regarding STFL, outlining relevant aspects of epidemiology, biomechanics, psychophysics, tribology, organisational influences and injury prevention. This review reaffirms that STFL remain a major cause of workplace injury and STFL prevention is a complex problem, requiring multi-disciplinary, multi-faceted approaches. Despite progress in recent decades in understanding the mechanisms involved in STFL, especially slipping, research leading to evidence-based prevention practices remains insufficient, given the problem scale. It is concluded that there is a pressing need to develop better fall prevention strategies using systems approaches conceptualising and addressing the factors involved in STFL, with considerations of the full range of factors and their interactions. There is also an urgent need for field trials of various fall prevention strategies to assess the effectiveness of different intervention components and their interactions. Practitioner Summary: Work-related slipping, tripping and falls on the same level are a major source of occupational injury. The causes are broadly understood, although more attention is needed from a systems perspective. Research has shown preventative action to be effective, but further studies are required to understand which aspects are most beneficial.

State of science: occupational slips, trips and falls on the same level *

PubMed Central

Chang, Wen-Ruey; Leclercq, Sylvie; Lockhart, Thurmon E.; Haslam, Roger

2016-01-01

Abstract Occupational slips, trips and falls on the same level (STFL) result in substantial injuries worldwide. This paper summarises the state of science regarding STFL, outlining relevant aspects of epidemiology, biomechanics, psychophysics, tribology, organisational influences and injury prevention. This review reaffirms that STFL remain a major cause of workplace injury and STFL prevention is a complex problem, requiring multi-disciplinary, multi-faceted approaches. Despite progress in recent decades in understanding the mechanisms involved in STFL, especially slipping, research leading to evidence-based prevention practices remains insufficient, given the problem scale. It is concluded that there is a pressing need to develop better fall prevention strategies using systems approaches conceptualising and addressing the factors involved in STFL, with considerations of the full range of factors and their interactions. There is also an urgent need for field trials of various fall prevention strategies to assess the effectiveness of different intervention components and their interactions. Practitioner Summary: Work-related slipping, tripping and falls on the same level are a major source of occupational injury. The causes are broadly understood, although more attention is needed from a systems perspective. Research has shown preventative action to be effective, but further studies are required to understand which aspects are most beneficial. PMID:26903401

3D Digital Surveying and Modelling of Cave Geometry: Application to Paleolithic Rock Art

PubMed Central

González-Aguilera, Diego; Muñoz-Nieto, Angel; Gómez-Lahoz, Javier; Herrero-Pascual, Jesus; Gutierrez-Alonso, Gabriel

2009-01-01

3D digital surveying and modelling of cave geometry represents a relevant approach for research, management and preservation of our cultural and geological legacy. In this paper, a multi-sensor approach based on a terrestrial laser scanner, a high-resolution digital camera and a total station is presented. Two emblematic caves of Paleolithic human occupation and situated in northern Spain, “Las Caldas” and “Peña de Candamo”, have been chosen to put in practise this approach. As a result, an integral and multi-scalable 3D model is generated which may allow other scientists, pre-historians, geologists…, to work on two different levels, integrating different Paleolithic Art datasets: (1) a basic level based on the accurate and metric support provided by the laser scanner; and (2) a advanced level using the range and image-based modelling. PMID:22399958

Multi-disciplinary rehabilitation for acquired brain injury in adults of working age.

PubMed

Turner-Stokes, Lynne; Pick, Anton; Nair, Ajoy; Disler, Peter B; Wade, Derick T

2015-12-22

Evidence from systematic reviews demonstrates that multi-disciplinary rehabilitation is effective in the stroke population, in which older adults predominate. However, the evidence base for the effectiveness of rehabilitation following acquired brain injury (ABI) in younger adults has not been established, perhaps because this scenario presents different methodological challenges in research. To assess the effects of multi-disciplinary rehabilitation following ABI in adults 16 to 65 years of age. We ran the most recent search on 14 September 2015. We searched the Cochrane Injuries Group Specialised Register, The Cochrane Library, Ovid MEDLINE(R), Ovid MEDLINE(R) In-Process & Other Non-Indexed Citations, Ovid MEDLINE(R) Daily and Ovid OLDMEDLINE(R), Embase Classic+Embase (OvidSP), Web of Science (ISI WOS) databases, clinical trials registers, and we screened reference lists. Randomised controlled trials (RCTs) comparing multi-disciplinary rehabilitation versus routinely available local services or lower levels of intervention; or trials comparing an intervention in different settings, of different intensities or of different timing of onset. Controlled clinical trials were included, provided they met pre-defined methodological criteria. Three review authors independently selected trials and rated their methodological quality. A fourth review author would have arbitrated if consensus could not be reached by discussion, but in fact, this did not occur. As in previous versions of this review, we used the method described by Van Tulder 1997 to rate the quality of trials and to perform a 'best evidence' synthesis by attributing levels of evidence on the basis of methodological quality. Risk of bias assessments were performed in parallel using standard Cochrane methodology. However, the Van Tulder system provided a more discriminative evaluation of rehabilitation trials, so we have continued to use it for our primary synthesis of evidence. We subdivided trials in terms of severity of brain injury, setting and type and timing of rehabilitation offered. We identified a total of 19 studies involving 3480 people. Twelve studies were of good methodological quality and seven were of lower quality, according to the van Tulder scoring system. Within the subgroup of predominantly mild brain injury, 'strong evidence' suggested that most individuals made a good recovery when appropriate information was provided, without the need for additional specific interventions. For moderate to severe injury, 'strong evidence' showed benefit from formal intervention, and 'limited evidence' indicated that commencing rehabilitation early after injury results in better outcomes. For participants with moderate to severe ABI already in rehabilitation, 'strong evidence' revealed that more intensive programmes are associated with earlier functional gains, and 'moderate evidence' suggested that continued outpatient therapy could help to sustain gains made in early post-acute rehabilitation. The context of multi-disciplinary rehabilitation appears to influence outcomes. 'Strong evidence' supports the use of a milieu-oriented model for patients with severe brain injury, in which comprehensive cognitive rehabilitation takes place in a therapeutic environment and involves a peer group of patients. 'Limited evidence' shows that specialist in-patient rehabilitation and specialist multi-disciplinary community rehabilitation may provide additional functional gains, but studies serve to highlight the particular practical and ethical restraints imposed on randomisation of severely affected individuals for whom no realistic alternatives to specialist intervention are available. Problems following ABI vary. Consequently, different interventions and combinations of interventions are required to meet the needs of patients with different problems. Patients who present acutely to hospital with mild brain injury benefit from follow-up and appropriate information and advice. Those with moderate to severe brain injury benefit from routine follow-up so their needs for rehabilitation can be assessed. Intensive intervention appears to lead to earlier gains, and earlier intervention whilst still in emergency and acute care has been supported by limited evidence. The balance between intensity and cost-effectiveness has yet to be determined. Patients discharged from in-patient rehabilitation benefit from access to out-patient or community-based services appropriate to their needs. Group-based rehabilitation in a therapeutic milieu (where patients undergo neuropsychological rehabilitation in a therapeutic environment with a peer group of individuals facing similar challenges) represents an effective approach for patients requiring neuropsychological rehabilitation following severe brain injury. Not all questions in rehabilitation can be addressed by randomised controlled trials or other experimental approaches. For example, trial-based literature does not tell us which treatments work best for which patients over the long term, and which models of service represent value for money in the context of life-long care. In the future, such questions will need to be considered alongside practice-based evidence gathered from large systematic longitudinal cohort studies conducted in the context of routine clinical practice.

Enhancing the Teaching of Introductory Economics with a Team-Based, Multi-Section Competition

ERIC Educational Resources Information Center

Beaudin, Laura; Berdiev, Aziz N.; Kaminaga, Allison Shwachman; Mirmirani, Sam; Tebaldi, Edinaldo

2017-01-01

The authors describe a unique approach to enhancing student learning at the introductory economics level that utilizes a multi-section, team-based competition. The competition is structured to supplement learning throughout the entire introductory course. Student teams are presented with current economic issues, trends, or events, and use economic…

Multi-Hazard Interactions in Guatemala

NASA Astrophysics Data System (ADS)

Gill, Joel; Malamud, Bruce D.

2017-04-01

In this paper, we combine physical and social science approaches to develop a multi-scale regional framework for natural hazard interactions in Guatemala. The identification and characterisation of natural hazard interactions is an important input for comprehensive multi-hazard approaches to disaster risk reduction at a regional level. We use five transdisciplinary evidence sources to organise and populate our framework: (i) internationally-accessible literature; (ii) civil protection bulletins; (iii) field observations; (iv) stakeholder interviews (hazard and civil protection professionals); and (v) stakeholder workshop results. These five evidence sources are synthesised to determine an appropriate natural hazard classification scheme for Guatemala (6 hazard groups, 19 hazard types, and 37 hazard sub-types). For a national spatial extent (Guatemala), we construct and populate a "21×21" hazard interaction matrix, identifying 49 possible interactions between 21 hazard types. For a sub-national spatial extent (Southern Highlands, Guatemala), we construct and populate a "33×33" hazard interaction matrix, identifying 112 possible interactions between 33 hazard sub-types. Evidence sources are also used to constrain anthropogenic processes that could trigger natural hazards in Guatemala, and characterise possible networks of natural hazard interactions (cascades). The outcomes of this approach are among the most comprehensive interaction frameworks for national and sub-national spatial scales in the published literature. These can be used to support disaster risk reduction and civil protection professionals in better understanding natural hazards and potential disasters at a regional scale.

Evicase: an evidence-based case structuring approach for personalized healthcare.

PubMed

Carmeli, Boaz; Casali, Paolo; Goldbraich, Anna; Goldsteen, Abigail; Kent, Carmel; Licitra, Lisa; Locatelli, Paolo; Restifo, Nicola; Rinott, Ruty; Sini, Elena; Torresani, Michele; Waks, Zeev

2012-01-01

The personalized medicine era stresses a growing need to combine evidence-based medicine with case based reasoning in order to improve the care process. To address this need we suggest a framework to generate multi-tiered statistical structures we call Evicases. Evicase integrates established medical evidence together with patient cases from the bedside. It then uses machine learning algorithms to produce statistical results and aggregators, weighted predictions, and appropriate recommendations. Designed as a stand-alone structure, Evicase can be used for a range of decision support applications including guideline adherence monitoring and personalized prognostic predictions.

Multiframe video coding for improved performance over wireless channels.

PubMed

Budagavi, M; Gibson, J D

2001-01-01

We propose and evaluate a multi-frame extension to block motion compensation (BMC) coding of videoconferencing-type video signals for wireless channels. The multi-frame BMC (MF-BMC) coder makes use of the redundancy that exists across multiple frames in typical videoconferencing sequences to achieve additional compression over that obtained by using the single frame BMC (SF-BMC) approach, such as in the base-level H.263 codec. The MF-BMC approach also has an inherent ability of overcoming some transmission errors and is thus more robust when compared to the SF-BMC approach. We model the error propagation process in MF-BMC coding as a multiple Markov chain and use Markov chain analysis to infer that the use of multiple frames in motion compensation increases robustness. The Markov chain analysis is also used to devise a simple scheme which randomizes the selection of the frame (amongst the multiple previous frames) used in BMC to achieve additional robustness. The MF-BMC coders proposed are a multi-frame extension of the base level H.263 coder and are found to be more robust than the base level H.263 coder when subjected to simulated errors commonly encountered on wireless channels.

Use of a multi-level mixed methods approach to study the effectiveness of a primary care progressive return to activity protocol after acute mild traumatic brain injury/concussion in the military.

PubMed

Gregory, Emma; West, Therese A; Cole, Wesley R; Bailie, Jason M; McCulloch, Karen L; Ettenhofer, Mark L; Cecchini, Amy; Qashu, Felicia M

2017-01-01

The large number of U.S. service members diagnosed with concussion/mild traumatic brain injury each year underscores the necessity for clear and effective clinical guidance for managing concussion. Relevant research continues to emerge supporting a gradual return to pre-injury activity levels without aggravating symptoms; however, available guidance does not provide detailed standards for this return to activity process. To fill this gap, the Defense and Veterans Brain Injury Center released a recommendation for primary care providers detailing a step-wise return to unrestricted activity during the acute phase of concussion. This guidance was developed in collaboration with an interdisciplinary group of clinical, military, and academic subject matter experts using an evidence-based approach. Systematic evaluation of the guidance is critical to ensure positive patient outcomes, to discover barriers to implementation by providers, and to identify ways to improve the recommendation. Here we describe a multi-level, mixed-methods approach to evaluate the recommendation incorporating outcomes from both patients and providers. Procedures were developed to implement the study within complex but ecologically-valid settings at multiple military treatment facilities and operational medical units. Special consideration was given to anticipated challenges such as the frequent movement of military personnel, selection of appropriate design and measures, study implementation at multiple sites, and involvement of multiple service branches (Army, Navy, and Marine Corps). We conclude by emphasizing the need to consider contemporary approaches for evaluating the effectiveness of clinical guidance. Copyright © 2016 Elsevier Inc. All rights reserved.

Balancing efficiency, equity and feasibility of HIV treatment in South Africa – development of programmatic guidance

PubMed Central

2013-01-01

South Africa, the country with the largest HIV epidemic worldwide, has been scaling up treatment since 2003 and is rapidly expanding its eligibility criteria. The HIV treatment programme has achieved significant results, and had 1.8 million people on treatment per 2011. Despite these achievements, it is now facing major concerns regarding (i) efficiency: alternative treatment policies may save more lives for the same budget; (ii) equity: there are large inequalities in who receives treatment; (iii) feasibility: still only 52% of the eligible population receives treatment. Hence, decisions on the design of the present HIV treatment programme in South Africa can be considered suboptimal. We argue there are two fundamental reasons to this. First, while there is a rapidly growing evidence-base to guide priority setting decisions on HIV treatment, its included studies typically consider only one criterion at a time and thus fail to capture the broad range of values that stakeholders have. Second, priority setting on HIV treatment is a highly political process but it seems no adequate participatory processes are in place to incorporate stakeholders’ views and evidences of all sorts. We propose an alternative approach that provides a better evidence base and outlines a fair policy process to improve priority setting in HIV treatment. The approach integrates two increasingly important frameworks on health care priority setting: accountability for reasonableness (A4R) to foster procedural fairness, and multi-criteria decision analysis (MCDA) to construct an evidence-base on the feasibility, efficiency, and equity of programme options including trade-offs. The approach provides programmatic guidance on the choice of treatment strategies at various decisions levels based on a sound conceptual framework, and holds large potential to improve HIV priority setting in South Africa. PMID:24107435

A multi-level examination of how the organizational context relates to readiness to implement prevention and evidence-based programming in community settings.

PubMed

Chilenski, Sarah M; Olson, Jonathan R; Schulte, Jill A; Perkins, Daniel F; Spoth, Richard

2015-02-01

Prior theoretical and empirical research suggests that multiple aspects of an organization's context are likely related to a number of factors, from their interest and ability to adopt new programming, to client outcomes. A limited amount of the prior research has taken a more community-wide perspective by examining factors that associate with community readiness for change, leaving how these findings generalize to community organizations that conduct prevention or positive youth development programs unknown. Thus for the current study, we examined how the organizational context of the Cooperative Extension System (CES) associates with current attitudes and practices regarding prevention and evidence-based programming. Attitudes and practices have been found in the empirical literature to be key indicators of an organization's readiness to adopt prevention and evidence-based programming. Based on multi-level mixed models, results indicate that organizational management practices distinct from program delivery may affect an organization's readiness to adopt and implement new prevention and evidence-based youth programs, thereby limiting the potential public health impact of evidence-based programs. Openness to change, openness of leadership, and communication were the strongest predictors identified within this study. An organization's morale was also found to be a strong predictor of an organization's readiness. The findings of the current study are discussed in terms of implications for prevention and intervention.

A Multi-level Examination of how the Organizational Context Relates to Readiness to Implement Prevention and Evidence-Based Programming in Community Settings

PubMed Central

Chilenski, Sarah M.; Olson, Jonathan R.; Schulte, Jill A.; Perkins, Daniel F.; Spoth, Richard

2015-01-01

Prior theoretical and empirical research suggests that multiple aspects of an organization’s context are likely related to a number of factors, from their interest and ability to adopt new programming, to client outcomes. A limited amount of the prior research has taken a more community-wide perspective by examining factors that associate with community readiness for change, leaving how these findings generalize to community organizations that conduct prevention or positive youth development programs unknown. Thus for the current study, we examined how the organizational context of the Cooperative Extension System (CES) associates with current attitudes and practices regarding prevention and evidence-based programming. Attitudes and practices have been found in the empirical literature to be key indicators of an organization’s readiness to adopt prevention and evidence-based programming. Based on multi-level mixed models, results indicate that organizational management practices distinct from program delivery may affect an organization’s readiness to adopt and implement new prevention and evidence-based youth programs, thereby limiting the potential public health impact of evidence-based programs. Openness to change, openness of leadership, and communication were the strongest predictors identified within this study. An organization’s morale was also found to be a strong predictor of an organization’s readiness. The findings of the current study are discussed in terms of implications for prevention and intervention. PMID:25463014

Multi-level and hybrid modelling approaches for systems biology.

PubMed

Bardini, R; Politano, G; Benso, A; Di Carlo, S

2017-01-01

During the last decades, high-throughput techniques allowed for the extraction of a huge amount of data from biological systems, unveiling more of their underling complexity. Biological systems encompass a wide range of space and time scales, functioning according to flexible hierarchies of mechanisms making an intertwined and dynamic interplay of regulations. This becomes particularly evident in processes such as ontogenesis, where regulative assets change according to process context and timing, making structural phenotype and architectural complexities emerge from a single cell, through local interactions. The information collected from biological systems are naturally organized according to the functional levels composing the system itself. In systems biology, biological information often comes from overlapping but different scientific domains, each one having its own way of representing phenomena under study. That is, the different parts of the system to be modelled may be described with different formalisms. For a model to have improved accuracy and capability for making a good knowledge base, it is good to comprise different system levels, suitably handling the relative formalisms. Models which are both multi-level and hybrid satisfy both these requirements, making a very useful tool in computational systems biology. This paper reviews some of the main contributions in this field.

Rationale and clinical data supporting nutritional intervention in Alzheimer's disease.

PubMed

Engelborghs, S; Gilles, C; Ivanoiu, A; Vandewoude, M

2014-01-01

Adequate nutrition plays an important role in the maintenance of cognitive function, particularly during aging. Malnutrition is amongst the risk factors for developing mild cognitive impairment (MCI) and Alzheimer's disease (AD). Epidemiological studies have associated deficiencies in some nutrients with a higher risk of cognitive dysfunction and/or AD. Cognitive decline in AD is correlated with synaptic loss and many of the components required to maintain optimal synaptic function are derived from dietary sources. As synapses are part of the neuronal membrane and are continuously being remodelled, the availability of sufficient levels of nutritional precursors (mainly uridine monophosphate, choline and omega-3 fatty acids) to make the phospholipids required to build neuronal membranes may have beneficial effects on synaptic degeneration in AD. In addition, B-vitamins, phospholipids and other micronutrients act as cofactors to enhance the supply of precursors required to make neuronal membranes and synapses. Despite this, no randomized controlled trial has hitherto provided evidence that any single nutrient has a beneficial effect on cognition or lowers the risk for AD. However, a multi-target approach using combinations of (micro)nutrients might have beneficial effects on cognitive function in neurodegenerative brain disorders like AD leading to synaptic degeneration. Here we review the clinical evidence for supplementation, based on a multi-target approach with a focus on key nutrients with a proposed role in synaptic dysfunction. Based on preclinical evidence, a nutrient mixture, Souvenaid(®) (Nutricia N.V., Zoetermeer, The Netherlands) was developed. Clinical trials with Souvenaid(®) have shown improved memory performance in patients with mild AD. Further clinical trials to evaluate the effects of nutritional intervention in MCI and early dementia due to AD are on-going.

Device Independent Layout and Style Editing Using Multi-Level Style Sheets

NASA Astrophysics Data System (ADS)

Dees, Walter

This paper describes a layout and styling framework that is based on the multi-level style sheets approach. It shows some of the techniques that can be used to add layout and style information to a UI in a device-independent manner, and how to reuse the layout and style information to create user interfaces for different devices

Citizen science applied to building healthier community environments: advancing the field through shared construct and measurement development.

PubMed

Hinckson, Erica; Schneider, Margaret; Winter, Sandra J; Stone, Emily; Puhan, Milo; Stathi, Afroditi; Porter, Michelle M; Gardiner, Paul A; Dos Santos, Daniela Lopes; Wolff, Andrea; King, Abby C

2017-09-29

Physical inactivity across the lifespan remains a public health issue for many developed countries. Inactivity has contributed considerably to the pervasiveness of lifestyle diseases. Government, national and local agencies and organizations have been unable to systematically, and in a coordinated way, translate behavioral research into practice that makes a difference at a population level. One approach for mobilizing multi-level efforts to improve the environment for physical activity is to engage in a process of citizen science. Citizen Science here is defined as a participatory research approach involving members of the public working closely with research investigators to initiate and advance scientific research projects. However, there are no common measures or protocols to guide citizen science research at the local community setting. We describe overarching categories of constructs that can be considered when designing citizen science projects expected to yield multi-level interventions, and provide an example of the citizen science approach to promoting PA. We also recommend potential measures across different levels of impact. Encouraging some consistency in measurement across studies will potentially accelerate the efficiency with which citizen science participatory research provides new insights into and solutions to the behaviorally-based public health issues that drive most of morbidity and mortality. The measures described in this paper abide by four fundamental principles specifically selected for inclusion in citizen science projects: feasibility, accuracy, propriety, and utility. The choice of measures will take into account the potential resources available for outcome and process evaluation. Our intent is to emphasize the importance for all citizen science participatory projects to follow an evidence-based approach and ensure that they incorporate an appropriate assessment protocol. We provided the rationale for and a list of contextual factors along with specific examples of measures to encourage consistency among studies that plan to use a citizen science participatory approach. The potential of this approach to promote health and wellbeing in communities is high and we hope that we have provided the tools needed to optimally promote synergistic gains in knowledge across a range of Citizen Science participatory projects.

Developing an evidence-based approach to Public Health Nutrition: translating evidence into policy.

PubMed

Margetts, B; Warm, D; Yngve, A; Sjöström, M

2001-12-01

The aim of this paper is to highlight the importance of an evidence-based approach to the development, implementation and evaluation of policies aimed at improving nutrition-related health in the population. Public Health Nutrition was established to realise a population-level approach to the prevention of the major nutrition-related health problems world-wide. The scope is broad and integrates activity from local, national, regional and international levels. The aim is to inform and develop coherent and effective policies that address the key rate-limiting steps critical to improving nutrition-related public health. This paper sets out the rationale for an evidence-based approach to Public Health Nutrition developed under the umbrella of the European Network for Public Health Nutrition.

OPREVENT2: Design of a multi-institutional intervention for obesity control and prevention for American Indian adults.

PubMed

Gittelsohn, Joel; Jock, Brittany; Redmond, Leslie; Fleischhacker, Sheila; Eckmann, Thomas; Bleich, Sara N; Loh, Hong; Ogburn, Elizabeth; Gadhoke, Preety; Swartz, Jacqueline; Pardilla, Marla; Caballero, Benjamin

2017-01-23

Obesity and other nutrition-related chronic disease rates are high in American Indian (AI) populations, and an urgent need exists to identify evidence-based strategies for prevention and treatment. Multi-level, multi-component (MLMC) interventions are needed, but there are significant knowledge gaps on how to deliver these types of interventions in low-income rural AI communities. OPREVENT2 is a MLMC intervention targeting AI adults living in six rural reservations in New Mexico and Wisconsin. Aiming to prevent and reduce obesity in adults by working at multiple levels of the food and physical activity (PA) environments, OPREVENT2 focuses on evidence-based strategies known to increase access to, demand for, and consumption of healthier foods and beverages, and increase worksite and home-based opportunities for PA. OPREVENT2 works to create systems-level change by partnering with tribal stakeholders, multiple levels of the food and PA environment (food stores, worksites, schools), and the social environment (children as change agents, families, social media). Extensive evaluation will be conducted at each level of the intervention to assess effectiveness via process and impact measures. Novel aspects of OPREVENT2 include: active engagement with stakeholders at many levels (policy, institutional, and at multiple levels of the food and PA system); use of community-based strategies to engage policymakers and other key stakeholders (community workshops, action committees); emphasis on both the built environment (intervening with retail food sources) and the social environment. This paper describes the design of the intervention and the evaluation plan of the OPREVENT2. Clinical Trial Registration: NCT02803853 (June 10, 2016).

Coupling biomechanics to a cellular level model: an approach to patient-specific image driven multi-scale and multi-physics tumor simulation.

PubMed

May, Christian P; Kolokotroni, Eleni; Stamatakos, Georgios S; Büchler, Philippe

2011-10-01

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning. Copyright © 2011 Elsevier Ltd. All rights reserved.

Biodiversity conservation in Swedish forests: ways forward for a 30-year-old multi-scaled approach.

PubMed

Gustafsson, Lena; Perhans, Karin

2010-12-01

A multi-scaled model for biodiversity conservation in forests was introduced in Sweden 30 years ago, which makes it a pioneer example of an integrated ecosystem approach. Trees are set aside for biodiversity purposes at multiple scale levels varying from individual trees to areas of thousands of hectares, with landowner responsibility at the lowest level and with increasing state involvement at higher levels. Ecological theory supports the multi-scaled approach, and retention efforts at every harvest occasion stimulate landowners' interest in conservation. We argue that the model has large advantages but that in a future with intensified forestry and global warming, development based on more progressive thinking is necessary to maintain and increase biodiversity. Suggestions for the future include joint planning for several forest owners, consideration of cost-effectiveness, accepting opportunistic work models, adjusting retention levels to stand and landscape composition, introduction of temporary reserves, creation of "receiver habitats" for species escaping climate change, and protection of young forests.

Understanding the development of minimum unit pricing of alcohol in Scotland: a qualitative study of the policy process.

PubMed

Katikireddi, Srinivasa Vittal; Hilton, Shona; Bonell, Chris; Bond, Lyndal

2014-01-01

Minimum unit pricing of alcohol is a novel public health policy with the potential to improve population health and reduce health inequalities. Theories of the policy process may help to understand the development of policy innovation and in turn identify lessons for future public health research and practice. This study aims to explain minimum unit pricing's development by taking a 'multiple-lenses' approach to understanding the policy process. In particular, we apply three perspectives of the policy process (Kingdon's multiple streams, Punctuated-Equilibrium Theory, Multi-Level Governance) to understand how and why minimum unit pricing has developed in Scotland and describe implications for efforts to develop evidence-informed policymaking. Semi-structured interviews were conducted with policy actors (politicians, civil servants, academics, advocates, industry representatives) involved in the development of MUP (n = 36). Interviewees were asked about the policy process and the role of evidence in policy development. Data from two other sources (a review of policy documents and an analysis of evidence submission documents to the Scottish Parliament) were used for triangulation. The three perspectives provide complementary understandings of the policy process. Evidence has played an important role in presenting the policy issue of alcohol as a problem requiring action. Scotland-specific data and a change in the policy 'image' to a population-based problem contributed to making alcohol-related harms a priority for action. The limited powers of Scottish Government help explain the type of price intervention pursued while distinct aspects of the Scottish political climate favoured the pursuit of price-based interventions. Evidence has played a crucial but complex role in the development of an innovative policy. Utilising different political science theories helps explain different aspects of the policy process, with Multi-Level Governance particularly useful for highlighting important lessons for the future of public health policy.

Understanding the Development of Minimum Unit Pricing of Alcohol in Scotland: A Qualitative Study of the Policy Process

PubMed Central

Katikireddi, Srinivasa Vittal; Hilton, Shona; Bonell, Chris; Bond, Lyndal

2014-01-01

Background Minimum unit pricing of alcohol is a novel public health policy with the potential to improve population health and reduce health inequalities. Theories of the policy process may help to understand the development of policy innovation and in turn identify lessons for future public health research and practice. This study aims to explain minimum unit pricing’s development by taking a ‘multiple-lenses’ approach to understanding the policy process. In particular, we apply three perspectives of the policy process (Kingdon’s multiple streams, Punctuated-Equilibrium Theory, Multi-Level Governance) to understand how and why minimum unit pricing has developed in Scotland and describe implications for efforts to develop evidence-informed policymaking. Methods Semi-structured interviews were conducted with policy actors (politicians, civil servants, academics, advocates, industry representatives) involved in the development of MUP (n = 36). Interviewees were asked about the policy process and the role of evidence in policy development. Data from two other sources (a review of policy documents and an analysis of evidence submission documents to the Scottish Parliament) were used for triangulation. Findings The three perspectives provide complementary understandings of the policy process. Evidence has played an important role in presenting the policy issue of alcohol as a problem requiring action. Scotland-specific data and a change in the policy ‘image’ to a population-based problem contributed to making alcohol-related harms a priority for action. The limited powers of Scottish Government help explain the type of price intervention pursued while distinct aspects of the Scottish political climate favoured the pursuit of price-based interventions. Conclusions Evidence has played a crucial but complex role in the development of an innovative policy. Utilising different political science theories helps explain different aspects of the policy process, with Multi-Level Governance particularly useful for highlighting important lessons for the future of public health policy. PMID:24670519

Testing use of payers to facilitate evidence-based practice adoption: protocol for a cluster-randomized trial

PubMed Central

2013-01-01

Background More effective methods are needed to implement evidence-based findings into practice. The Advancing Recovery Framework offers a multi-level approach to evidence-based practice implementation by aligning purchasing and regulatory policies at the payer level with organizational change strategies at the organizational level. Methods The Advancing Recovery Buprenorphine Implementation Study is a cluster-randomized controlled trial designed to increase use of the evidence-based practice buprenorphine medication to treat opiate addiction. Ohio Alcohol, Drug Addiction, and Mental Health Services Boards (ADAMHS), who are payers, and their addiction treatment organizations were recruited for a trial to assess the effects of payer and treatment organization changes (using the Advancing Recovery Framework) versus treatment organization changes alone on the use of buprenorphine. A matched-pair randomization, based on county characteristics, was applied, resulting in seven county ADAMHS boards and twenty-five treatment organizations in each arm. Opioid dependent patients are nested within cluster (treatment organization), and treatment organization clusters are nested within ADAMHS county board. The primary outcome is the percentage of individuals with an opioid dependence diagnosis who use buprenorphine during the 24-month intervention period and the 12-month sustainability period. The trial is currently in the baseline data collection stage. Discussion Although addiction treatment providers are under increasing pressure to implement evidence-based practices that have been proven to improve patient outcomes, adoption of these practices lags, compared to other areas of healthcare. Reasons frequently cited for the slow adoption of EBPs in addiction treatment include, regulatory issues, staff, or client resistance and lack of resources. Yet the way addiction treatment is funded, the payer’s role—has not received a lot of attention in research on EBP adoption. This research is unique because it investigates the role of payers in evidence-based practice implementation using a randomized controlled design instead of case examples. The testing of the Advancing Recovery Framework is designed to broaden the understanding of the impact payers have on evidence-based practice (EBP) adoption. Trial registration http://NCT01702142 (ClinicalTrials.gov registry, USA) PMID:23663749

A Comprehensive Prevention Approach to Reducing Assault Offenses and Assault Injuries Among Youth

PubMed Central

Heinze, Justin E.; Reischl, Thomas M.; Bai, Mengqiao; Roche, Jessica S.; Morrel-Samuels, Susan; Cunningham, Rebecca M.; Zimmerman, Marc A.

2018-01-01

Since 2011, the CDC-funded Michigan Youth Violence Prevention Center (MI-YVPC), working with community partners, has implemented a comprehensive prevention approach to reducing youth violence in Flint, MI, based on public health principles. MI-YVPC employed an intervention strategy that capitalizes on existing community resources and application of evidence-based programs using a social-ecological approach to change. We evaluated the combined effect of six programs in reducing assaults and injury among 10–24 year olds in the intervention area relative to a matched comparison community. We used generalized linear mixed models to examine change in the intervention area counts of reported assault offenses and assault injury presentation relative to the comparison area over a period six years prior- and two and a half years post-intervention. Results indicated that youth victimization and assault injuries fell in the intervention area subsequent to the initiation of the interventions and that these reductions were sustained over time. Our evaluation demonstrated that a comprehensive multi-level approach can be effective for reducing youth violence and injury. PMID:26572898

A Social-Ecological Framework of Theory, Assessment, and Prevention of Suicide

PubMed Central

Cramer, Robert J.; Kapusta, Nestor D.

2017-01-01

The juxtaposition of increasing suicide rates with continued calls for suicide prevention efforts begs for new approaches. Grounded in the Centers for Disease Control and Prevention (CDC) framework for tackling health issues, this personal views work integrates relevant suicide risk/protective factor, assessment, and intervention/prevention literatures. Based on these components of suicide risk, we articulate a Social-Ecological Suicide Prevention Model (SESPM) which provides an integration of general and population-specific risk and protective factors. We also use this multi-level perspective to provide a structured approach to understanding current theories and intervention/prevention efforts concerning suicide. Following similar multi-level prevention efforts in interpersonal violence and Human Immunodeficiency Virus (HIV) domains, we offer recommendations for social-ecologically informed suicide prevention theory, training, research, assessment, and intervention programming. Although the SESPM calls for further empirical testing, it provides a suitable backdrop for tailoring of current prevention and intervention programs to population-specific needs. Moreover, the multi-level model shows promise to move suicide risk assessment forward (e.g., development of multi-level suicide risk algorithms or structured professional judgments instruments) to overcome current limitations in the field. Finally, we articulate a set of characteristics of social-ecologically based suicide prevention programs. These include the need to address risk and protective factors with the strongest degree of empirical support at each multi-level layer, incorporate a comprehensive program evaluation strategy, and use a variety of prevention techniques across levels of prevention. PMID:29062296

Modeling and optimization of the multiobjective stochastic joint replenishment and delivery problem under supply chain environment.

PubMed

Wang, Lin; Qu, Hui; Liu, Shan; Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted.

Modeling and Optimization of the Multiobjective Stochastic Joint Replenishment and Delivery Problem under Supply Chain Environment

PubMed Central

Dun, Cai-xia

2013-01-01

As a practical inventory and transportation problem, it is important to synthesize several objectives for the joint replenishment and delivery (JRD) decision. In this paper, a new multiobjective stochastic JRD (MSJRD) of the one-warehouse and n-retailer systems considering the balance of service level and total cost simultaneously is proposed. The goal of this problem is to decide the reasonable replenishment interval, safety stock factor, and traveling routing. Secondly, two approaches are designed to handle this complex multi-objective optimization problem. Linear programming (LP) approach converts the multi-objective to single objective, while a multi-objective evolution algorithm (MOEA) solves a multi-objective problem directly. Thirdly, three intelligent optimization algorithms, differential evolution algorithm (DE), hybrid DE (HDE), and genetic algorithm (GA), are utilized in LP-based and MOEA-based approaches. Results of the MSJRD with LP-based and MOEA-based approaches are compared by a contrastive numerical example. To analyses the nondominated solution of MOEA, a metric is also used to measure the distribution of the last generation solution. Results show that HDE outperforms DE and GA whenever LP or MOEA is adopted. PMID:24302880

Multi-sensor information fusion method for vibration fault diagnosis of rolling bearing

NASA Astrophysics Data System (ADS)

Jiao, Jing; Yue, Jianhai; Pei, Di

2017-10-01

Bearing is a key element in high-speed electric multiple unit (EMU) and any defect of it can cause huge malfunctioning of EMU under high operation speed. This paper presents a new method for bearing fault diagnosis based on least square support vector machine (LS-SVM) in feature-level fusion and Dempster-Shafer (D-S) evidence theory in decision-level fusion which were used to solve the problems about low detection accuracy, difficulty in extracting sensitive characteristics and unstable diagnosis system of single-sensor in rolling bearing fault diagnosis. Wavelet de-nosing technique was used for removing the signal noises. LS-SVM was used to make pattern recognition of the bearing vibration signal, and then fusion process was made according to the D-S evidence theory, so as to realize recognition of bearing fault. The results indicated that the data fusion method improved the performance of the intelligent approach in rolling bearing fault detection significantly. Moreover, the results showed that this method can efficiently improve the accuracy of fault diagnosis.

A RE-AIM evaluation of evidence-based multi-level interventions to improve obesity-related behaviours in adults: a systematic review (the SPOTLIGHT project).

PubMed

Compernolle, Sofie; De Cocker, Katrien; Lakerveld, Jeroen; Mackenbach, Joreintje D; Nijpels, Giel; Oppert, Jean-Michel; Rutter, Harry; Teixeira, Pedro J; Cardon, Greet; De Bourdeaudhuij, Ilse

2014-12-06

This systematic literature review describes the potential public health impact of evidence-based multi-level interventions to improve obesity-related behaviours in adults, using the Reach, Efficacy, Adoption, Implementation and Maintenance (RE-AIM) framework. Electronic databases (PubMed, Embase, and The Cochrane Library) were searched to identify intervention studies published between January 2000 and October 2013. The following inclusion criteria were used: (1) the study included at least one outcome measure assessing obesity-related behaviours (i.e. diet, physical activity or sedentary behaviour), (2) the study collected data over at least one year and (3) the study's intervention targeted adults, was conducted in a specified geographical area or worksite, and was multi-level (i.e. targeting both individual and environmental level). Evidence of RE-AIM of the selected interventions was assessed. Potential public health impact of an intervention was evaluated if information was provided on at least four of the five RE-AIM dimensions. Thirty-five multi-level interventions met the inclusion criteria. RE-AIM evaluation revealed that the included interventions generally had the potential to: reach a large number of people (on average 58% of the target population was aware of the intervention); achieve the assumed goals (89% found positive outcomes); be broadly adopted (the proportion of intervention deliverers varied from 9% to 92%) and be sustained (sixteen interventions were maintained). The highest potential public health impact was found in multi-level interventions that: 1) focused on all levels at the beginning of the planning process, 2) guided the implementation process using diffusion theory, and 3) used a website to disseminate the intervention. Although most studies underreported results within the RE-AIM dimensions, the reported Reach, Effectiveness, Adoption, Implementation and Maintenance were positively evaluated. However, more information on external validity and sustainability is needed in order to take informed decisions on the choice of interventions that should be implemented in real-world settings to accomplish long-term changes in obesity-related behaviours.

Can Mindfulness Training Improve Medication Adherence? Integrative Review of the Current Evidence and Proposed Conceptual Model.

PubMed

Salmoirago-Blotcher, Elena; Carey, Michael P

Medication adherence is a complex, multi-determined behavior that is often influenced by system- (e.g., cost), drug- (e.g., regimen complexity), and patient-related (e.g., depression) factors. System-level approaches (e.g., making medications more affordable) are critically important but do not address patient-level factors that can undermine adherence. In this paper, we identify patient-level determinants of non-adherence and discuss whether mindfulness-training approaches that target these determinants can help to improve adherence to medical treatment. We highlight two chronic medical conditions (viz., heart failure and HIV) where poor adherence is a significant concern, and examine the evidence regarding the use of mindfulness interventions to improve medication adherence in these two conditions. We also discuss the theoretical underpinnings of mindfulness training with respect to medication adherence, and conclude by suggesting directions for future research. Copyright © 2018 Elsevier Inc. All rights reserved.

Multi-level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

NASA Astrophysics Data System (ADS)

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-11-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective, affords opportunities for analysts to perform a theoretically based detailed analysis of discourse events. Along with the presentation of analysis, we show and discuss how the articulation of different levels offers interpretative criteria for analyzing instructional conversations. We synthesize the results into a model for a teacher's practice and discuss the implications and possibilities of this approach for the field of discourse analysis in science classrooms. Finally, we reflect on how the development of teachers' understanding of their activity structures can contribute to forms of progressive discourse of science education.

Decision-Level Fusion of Spatially Scattered Multi-Modal Data for Nondestructive Inspection of Surface Defects

PubMed Central

Heideklang, René; Shokouhi, Parisa

2016-01-01

This article focuses on the fusion of flaw indications from multi-sensor nondestructive materials testing. Because each testing method makes use of a different physical principle, a multi-method approach has the potential of effectively differentiating actual defect indications from the many false alarms, thus enhancing detection reliability. In this study, we propose a new technique for aggregating scattered two- or three-dimensional sensory data. Using a density-based approach, the proposed method explicitly addresses localization uncertainties such as registration errors. This feature marks one of the major of advantages of this approach over pixel-based image fusion techniques. We provide guidelines on how to set all the key parameters and demonstrate the technique’s robustness. Finally, we apply our fusion approach to experimental data and demonstrate its capability to locate small defects by substantially reducing false alarms under conditions where no single-sensor method is adequate. PMID:26784200

Usability Methods for Ensuring Health Information Technology Safety: Evidence-Based Approaches. Contribution of the IMIA Working Group Health Informatics for Patient Safety.

PubMed

Borycki, E; Kushniruk, A; Nohr, C; Takeda, H; Kuwata, S; Carvalho, C; Bainbridge, M; Kannry, J

2013-01-01

Issues related to lack of system usability and potential safety hazards continue to be reported in the health information technology (HIT) literature. Usability engineering methods are increasingly used to ensure improved system usability and they are also beginning to be applied more widely for ensuring the safety of HIT applications. These methods are being used in the design and implementation of many HIT systems. In this paper we describe evidence-based approaches to applying usability engineering methods. A multi-phased approach to ensuring system usability and safety in healthcare is described. Usability inspection methods are first described including the development of evidence-based safety heuristics for HIT. Laboratory-based usability testing is then conducted under artificial conditions to test if a system has any base level usability problems that need to be corrected. Usability problems that are detected are corrected and then a new phase is initiated where the system is tested under more realistic conditions using clinical simulations. This phase may involve testing the system with simulated patients. Finally, an additional phase may be conducted, involving a naturalistic study of system use under real-world clinical conditions. The methods described have been employed in the analysis of the usability and safety of a wide range of HIT applications, including electronic health record systems, decision support systems and consumer health applications. It has been found that at least usability inspection and usability testing should be applied prior to the widespread release of HIT. However, wherever possible, additional layers of testing involving clinical simulations and a naturalistic evaluation will likely detect usability and safety issues that may not otherwise be detected prior to widespread system release. The framework presented in the paper can be applied in order to develop more usable and safer HIT, based on multiple layers of evidence.

A Multi-Faceted Approach to Successful Transition for Students with Intellectual Disabilities

ERIC Educational Resources Information Center

Dubberly, Russell G.

2011-01-01

This report summarizes the multi-faceted, dynamic instructional model implemented to increase positive transition outcomes for high school students with intellectual disabilities. This report is based on the programmatic methods implemented within a secondary-level school in an urban setting. This pedagogical model facilitates the use of…

Leveraging Citizen Science and Information Technology for Population Physical Activity Promotion.

PubMed

King, Abby C; Winter, Sandra J; Sheats, Jylana L; Rosas, Lisa G; Buman, Matthew P; Salvo, Deborah; Rodriguez, Nicole M; Seguin, Rebecca A; Moran, Mika; Garber, Randi; Broderick, Bonnie; Zieff, Susan G; Sarmiento, Olga Lucia; Gonzalez, Silvia A; Banchoff, Ann; Dommarco, Juan Rivera

2016-05-15

While technology is a major driver of many of society's comforts, conveniences, and advances, it has been responsible, in a significant way, for engineering regular physical activity and a number of other positive health behaviors out of people's daily lives. A key question concerns how to harness information and communication technologies (ICT) to bring about positive changes in the health promotion field. One such approach involves community-engaged "citizen science," in which local residents leverage the potential of ICT to foster data-driven consensus-building and mobilization efforts that advance physical activity at the individual, social, built environment, and policy levels. The history of citizen science in the research arena is briefly described and an evidence-based method that embeds citizen science in a multi-level, multi-sectoral community-based participatory research framework for physical activity promotion is presented. Several examples of this citizen science-driven community engagement framework for promoting active lifestyles, called "Our Voice", are discussed, including pilot projects from diverse communities in the U.S. as well as internationally. The opportunities and challenges involved in leveraging citizen science activities as part of a broader population approach to promoting regular physical activity are explored. The strategic engagement of citizen scientists from socio-demographically diverse communities across the globe as both assessment as well as change agents provides a promising, potentially low-cost and scalable strategy for creating more active, healthful, and equitable neighborhoods and communities worldwide.

Leveraging Citizen Science and Information Technology for Population Physical Activity Promotion

PubMed Central

King, Abby C.; Winter, Sandra J.; Sheats, Jylana L.; Rosas, Lisa G.; Buman, Matthew P.; Salvo, Deborah; Rodriguez, Nicole M.; Seguin, Rebecca A.; Moran, Mika; Garber, Randi; Broderick, Bonnie; Zieff, Susan G.; Sarmiento, Olga Lucia; Gonzalez, Silvia A.; Banchoff, Ann; Dommarco, Juan Rivera

2016-01-01

PURPOSE While technology is a major driver of many of society’s comforts, conveniences, and advances, it has been responsible, in a significant way, for engineering regular physical activity and a number of other positive health behaviors out of people’s daily lives. A key question concerns how to harness information and communication technologies (ICT) to bring about positive changes in the health promotion field. One such approach involves community-engaged “citizen science,” in which local residents leverage the potential of ICT to foster data-driven consensus-building and mobilization efforts that advance physical activity at the individual, social, built environment, and policy levels. METHOD The history of citizen science in the research arena is briefly described and an evidence-based method that embeds citizen science in a multi-level, multi-sectoral community-based participatory research framework for physical activity promotion is presented. RESULTS Several examples of this citizen science-driven community engagement framework for promoting active lifestyles, called “Our Voice”, are discussed, including pilot projects from diverse communities in the U.S. as well as internationally. CONCLUSIONS The opportunities and challenges involved in leveraging citizen science activities as part of a broader population approach to promoting regular physical activity are explored. The strategic engagement of citizen scientists from socio-demographically diverse communities across the globe as both assessment as well as change agents provides a promising, potentially low-cost and scalable strategy for creating more active, healthful, and equitable neighborhoods and communities worldwide. PMID:27525309

Technology-based self-care methods of improving antiretroviral adherence: a systematic review.

PubMed

Saberi, Parya; Johnson, Mallory O

2011-01-01

As HIV infection has shifted to a chronic condition, self-care practices have emerged as an important topic for HIV-positive individuals in maintaining an optimal level of health. Self-care refers to activities that patients undertake to maintain and improve health, such as strategies to achieve and maintain high levels of antiretroviral adherence. Technology-based methods are increasingly used to enhance antiretroviral adherence; therefore, we systematically reviewed the literature to examine technology-based self-care methods that HIV-positive individuals utilize to improve adherence. Seven electronic databases were searched from 1/1/1980 through 12/31/2010. We included quantitative and qualitative studies. Among quantitative studies, the primary outcomes included ARV adherence, viral load, and CD4+ cell count and secondary outcomes consisted of quality of life, adverse effects, and feasibility/acceptability data. For qualitative/descriptive studies, interview themes, reports of use, and perceptions of use were summarized. Thirty-six publications were included (24 quantitative and 12 qualitative/descriptive). Studies with exclusive utilization of medication reminder devices demonstrated less evidence of enhancing adherence in comparison to multi-component methods. This systematic review offers support for self-care technology-based approaches that may result in improved antiretroviral adherence. There was a clear pattern of results that favored individually-tailored, multi-function technologies, which allowed for periodic communication with health care providers rather than sole reliance on electronic reminder devices.

Improving quality of care through routine, successful implementation of evidence-based practice at the bedside: an organizational case study protocol using the Pettigrew and Whipp model of strategic change

PubMed Central

2007-01-01

Background Evidence-based practice (EBP) is an expected approach to improving the quality of patient care and service delivery in health care systems internationally that is yet to be realized. Given the current evidence-practice gap, numerous authors describe barriers to achieving EBP. One recurrently identified barrier is the setting or context of practice, which is likewise cited as a potential part of the solution to the gap. The purpose of this study is to identify key contextual elements and related strategic processes in organizations that find and use evidence at multiple levels, in an ongoing, integrated fashion, in contrast to those that do not. Methods The core theoretical framework for this multi-method explanatory case study is Pettigrew and Whipp's Content, Context, and Process model of strategic change. This framework focuses data collection on three entities: the Why of strategic change, the What of strategic change, and the How of strategic change, in this case related to implementation and normalization of EBP. The data collection plan, designed to capture relevant organizational context and related outcomes, focuses on eight interrelated factors said to characterize a receptive context. Selective, purposive sampling will provide contrasting results between two cases (departments of nursing) and three embedded units in each. Data collection methods will include quantitative tools (e.g., regarding culture) and qualitative approaches including focus groups, interviews, and documents review (e.g., regarding integration and “success”) relevant to the EBP initiative. Discussion This study should provide information regarding contextual elements and related strategic processes key to successful implementation and sustainability of EBP, specifically in terms of a pervasive pattern in an acute care hospital-based health care setting. Additionally, this study will identify key contextual elements that differentiate successful implementation and sustainability of EBP efforts, both within varying levels of a hospital-based clinical setting and across similar hospital settings interested in EBP. PMID:17266756

Breastfeeding protection, promotion, and support in the United States: a time to nudge, a time to measure.

PubMed

Pérez-Escamilla, Rafael; Chapman, Donna J

2012-05-01

Strong evidence-based advocacy efforts have now translated into high level political support and concrete goals for improving breastfeeding outcomes among women in the United States. In spite of this, major challenge remain for promoting, supporting and especially for protecting breastfeeding in the country. The goals of this commentary are to argue in favor of: A) Changes in the default social and environmental systems, that would allow women to implement their right to breastfeed their infants, B) A multi-level and comprehensive monitoring system to measure process and outcomes indicators in the country. Evidence-based commentary. Breastfeeding rates in the United States can improve based on a well coordinated social marketing framework. This approach calls for innovative promotion through mass media, appropriate facility based and community based support (e.g., Baby Friendly Hospital Initiative, WIC-coordinated community based peer counseling), and adequate protection for working women (e.g., longer paid maternity leave, breastfeeding or breast milk extraction breaks during the working day) and women at large by adhering and enforcing the WHO ethics Code for the Marketing of Breast Milk Substitutes. Sound infant feeding practices monitoring systems, which include WIC administrative food package data, are needed. Given the current high level of political support to improve breastfeeding in the United States, a window of opportunity has been opened. Establishing breastfeeding as the social norm in the USA will take time, but the global experience indicates that it can be done.

The Implementation and Impact of Evidence-Based Mathematics Reforms in High-Poverty Middle Schools: A Multi-Site, Multi-Year Study

ERIC Educational Resources Information Center

Balfanz, Robert; Mac Iver, Douglas J.; Byrnes, Vaughan

2006-01-01

This article reports on the first 4 years of an effort to develop comprehensive and sustainable mathematics education reforms in high poverty middle schools. In four related analyses, we examine the levels of implementation achieved and impact of the reforms on various measures of achievement in the first 3 schools to implement the Talent…

Evidence-based policymaking is not like evidence-based medicine, so how far should you go to bridge the divide between evidence and policy?

PubMed

Cairney, Paul; Oliver, Kathryn

2017-04-26

There is extensive health and public health literature on the 'evidence-policy gap', exploring the frustrating experiences of scientists trying to secure a response to the problems and solutions they raise and identifying the need for better evidence to reduce policymaker uncertainty. We offer a new perspective by using policy theory to propose research with greater impact, identifying the need to use persuasion to reduce ambiguity, and to adapt to multi-level policymaking systems.We identify insights from secondary data, namely systematic reviews, critical analysis and policy theories relevant to evidence-based policymaking. The studies are drawn primarily from countries such as the United States, United Kingdom, Canada, Australia and New Zealand. We combine empirical and normative elements to identify the ways in which scientists can, do and could influence policy.We identify two important dilemmas, for scientists and researchers, that arise from our initial advice. First, effective actors combine evidence with manipulative emotional appeals to influence the policy agenda - should scientists do the same, or would the reputational costs outweigh the policy benefits? Second, when adapting to multi-level policymaking, should scientists prioritise 'evidence-based' policymaking above other factors? The latter includes governance principles such the 'co-production' of policy between local public bodies, interest groups and service users. This process may be based primarily on values and involve actors with no commitment to a hierarchy of evidence.We conclude that successful engagement in 'evidence-based policymaking' requires pragmatism, combining scientific evidence with governance principles, and persuasion to translate complex evidence into simple stories. To maximise the use of scientific evidence in health and public health policy, researchers should recognise the tendency of policymakers to base judgements on their beliefs, and shortcuts based on their emotions and familiarity with information; learn 'where the action is', and be prepared to engage in long-term strategies to be able to influence policy; and, in both cases, decide how far you are willing to go to persuade policymakers to act and secure a hierarchy of evidence underpinning policy. These are value-driven and political, not just 'evidence-based', choices.

Evidencing Learning Outcomes: A Multi-Level, Multi-Dimensional Course Alignment Model

ERIC Educational Resources Information Center

Sridharan, Bhavani; Leitch, Shona; Watty, Kim

2015-01-01

This conceptual framework proposes a multi-level, multi-dimensional course alignment model to implement a contextualised constructive alignment of rubric design that authentically evidences and assesses learning outcomes. By embedding quality control mechanisms at each level for each dimension, this model facilitates the development of an aligned…

Second-Year Results of an Obesity Prevention Program at The Dow Chemical Company

PubMed Central

Roemer, Enid C.; Pei, Xiaofei; Short, Meghan E.; Tabrizi, Maryam J.; Wilson, Mark G.; DeJoy, David M.; Craun, Beth A.; Tully, Karen J.; White, John M.; Baase, Catherine M.

2010-01-01

Objective Evaluate innovative, evidence-based approaches to organizational/supportive environmental interventions aimed at reducing the prevalence of obesity among Dow employees after two years of implementation. Methods A quasi-experimental study design compared outcomes for two levels of intervention intensity to a control group. Propensity scores were used to weight baseline differences between intervention and control subjects. Difference-in-differences methods and multi-level modeling were used to control for individual and site-level confounders. Results Intervention participants maintained their weight and BMI while control participants gained 1.3 pounds and increased their BMI values by 0.2 over two years. Significant differences in blood pressure and cholesterol values were observed when comparing intervention employees to controls. At higher intensity sites, improvements were more pronounced. Conclusions Environmental interventions at the workplace can support weight management and risk reduction after two years. PMID:20190646

A functional language approach in high-speed digital simulation

NASA Technical Reports Server (NTRS)

Ercegovac, M. D.; Lu, S.-L.

1983-01-01

A functional programming approach for a multi-microprocessor architecture is presented. The language, based on Backus FP, its intermediate form and the translation process are discussed and illustrated with an example. The approach allows performance analysis to be performed at a high level as an aid in program partitioning.

Addressing Chronic Malnutrition through Multi-Sectoral, Sustainable Approaches: A Review of the Causes and Consequences

PubMed Central

Reinhardt, Kristina; Fanzo, Jessica

2014-01-01

Chronic malnutrition, including stunting, is an important example of a global challenge that spans multiple sectors, specifically health, agriculture, and the environment. The objective of this paper is to review current knowledge on the causes and consequences of chronic malnutrition and their relationship with multiple sectors. Understanding the causes includes approaching chronic malnutrition from the basic, underlying, and immediate levels. The causes reach from macro-level environmental influences to specific micronutrient intake. In order to effectively address stunting, it is important to understand the timing of stunting and the ability of individuals to catch up in terms of linear growth, cognitive ability, and immune function. The consequences of chronic malnutrition are transgenerational and they have an impact at the individual, community, and national level in the short- and long-term. There are still many gaps in knowledge regarding both the causes and consequences of chronic malnutrition, particularly when it comes to the interaction with agriculture and the environment, and understanding these gaps is important to addressing the burden of chronic malnutrition through evidence-based interventions. PMID:25988116

Confidence level estimation in multi-target classification problems

NASA Astrophysics Data System (ADS)

Chang, Shi; Isaacs, Jason; Fu, Bo; Shin, Jaejeong; Zhu, Pingping; Ferrari, Silvia

2018-04-01

This paper presents an approach for estimating the confidence level in automatic multi-target classification performed by an imaging sensor on an unmanned vehicle. An automatic target recognition algorithm comprised of a deep convolutional neural network in series with a support vector machine classifier detects and classifies targets based on the image matrix. The joint posterior probability mass function of target class, features, and classification estimates is learned from labeled data, and recursively updated as additional images become available. Based on the learned joint probability mass function, the approach presented in this paper predicts the expected confidence level of future target classifications, prior to obtaining new images. The proposed approach is tested with a set of simulated sonar image data. The numerical results show that the estimated confidence level provides a close approximation to the actual confidence level value determined a posteriori, i.e. after the new image is obtained by the on-board sensor. Therefore, the expected confidence level function presented in this paper can be used to adaptively plan the path of the unmanned vehicle so as to optimize the expected confidence levels and ensure that all targets are classified with satisfactory confidence after the path is executed.

Promoting Physical Activity Among Native American Youth: a Systematic Review of the Methodology and Current Evidence of Physical Activity Interventions and Community-wide Initiatives.

PubMed

Fleischhacker, Sheila; Roberts, Erica; Camplain, Ricky; Evenson, Kelly R; Gittelsohn, Joel

2016-12-01

Promoting physical activity using environmental, policy, and systems approaches could potentially address persistent health disparities faced by American Indian and Alaska Native children and adolescents. To address research gaps and help inform tribally led community changes that promote physical activity, this review examined the methodology and current evidence of physical activity interventions and community-wide initiatives among Native youth. A keyword-guided search was conducted in multiple databases to identify peer-reviewed research articles that reported on physical activity among Native youth. Ultimately, 20 unique interventions (described in 76 articles) and 13 unique community-wide initiatives (described in 16 articles) met the study criteria. Four interventions noted positive changes in knowledge and attitude relating to physical activity but none of the interventions examined reported statistically significant improvements on weight-related outcomes. Only six interventions reported implementing environmental, policy, and system approaches relating to promoting physical activity and generally only shared anecdotal information about the approaches tried. Using community-based participatory research or tribally driven research models strengthened the tribal-research partnerships and improved the cultural and contextual sensitivity of the intervention or community-wide initiative. Few interventions or community-wide initiatives examined multi-level, multi-sector interventions to promote physical activity among Native youth, families, and communities. More research is needed to measure and monitor physical activity within this understudied, high risk group. Future research could also focus on the unique authority and opportunity of tribal leaders and other key stakeholders to use environmental, policy, and systems approaches to raise a healthier generation of Native youth.

Promoting physical activity among Native American youth: A systematic review of the methodology and current evidence of physical activity interventions and community-wide initiatives

PubMed Central

Roberts, Erica; Camplain, Ricky; Evenson, Kelly R.; Gittelsohn, Joel

2015-01-01

Promoting physical activity using environmental, policy, and systems approaches could potentially address persistent health disparities faced by American Indian and Alaska Native children and adolescents. To address research gaps and help inform tribally-led community changes that promote physical activity, this review examined the methodology and current evidence of physical activity interventions and community-wide initiatives among Native youth. A keyword guided search was conducted in multiple databases to identify peer-reviewed research articles that reported on physical activity among Native youth. Ultimately, 20 unique interventions (described in 76 articles) and 13 unique community-wide initiatives (described in 16 articles) met the study criteria. Four interventions noted positive changes in knowledge and attitude relating to physical activity but none of the interventions examined reported statistically significant improvements on weight-related outcomes. Only six interventions reported implementing environmental, policy, and system approaches relating to promoting physical activity and generally only shared anecdotal information about the approaches tried. Using community-based participatory research or tribally-driven research models strengthened the tribal-research partnerships and improved the cultural and contextual sensitivity of the intervention or community-wide initiative. Few interventions or community-wide initiatives examined multi-level, multi-sector interventions to promote physical activity among Native youth, families and communities. More research is needed to measure and monitor physical activity within this understudied, high risk group. Future research could also focus on the unique authority and opportunity of tribal leaders and other key stakeholders to use environmental, policy, and systems approaches to raise a healthier generation of Native youth. PMID:27294756

Optimized swimmer tracking system based on a novel multi-related-targets approach

NASA Astrophysics Data System (ADS)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2017-02-01

Robust tracking is a crucial step in automatic swimmer evaluation from video sequences. We designed a robust swimmer tracking system using a new multi-related-targets approach. The main idea is to consider the swimmer as a bloc of connected subtargets that advance at the same speed. If one of the subtargets is partially or totally occluded, it can be localized by knowing the position of the others. In this paper, we first introduce the two-dimensional direct linear transformation technique that we used to calibrate the videos. Then, we present the classical tracking approach based on dynamic fusion. Next, we highlight the main contribution of our work, which is the multi-related-targets tracking approach. This approach, the classical head-only approach and the ground truth are then compared, through testing on a database of high-level swimmers in training, national and international competitions (French National Championships, Limoges 2015, and World Championships, Kazan 2015). Tracking percentage and the accuracy of the instantaneous speed are evaluated and the findings show that our new appraoach is significantly more accurate than the classical approach.

Multi-country health surveys: are the analyses misleading?

PubMed

Masood, Mohd; Reidpath, Daniel D

2014-05-01

The aim of this paper was to review the types of approaches currently utilized in the analysis of multi-country survey data, specifically focusing on design and modeling issues with a focus on analyses of significant multi-country surveys published in 2010. A systematic search strategy was used to identify the 10 multi-country surveys and the articles published from them in 2010. The surveys were selected to reflect diverse topics and foci; and provide an insight into analytic approaches across research themes. The search identified 159 articles appropriate for full text review and data extraction. The analyses adopted in the multi-country surveys can be broadly classified as: univariate/bivariate analyses, and multivariate/multivariable analyses. Multivariate/multivariable analyses may be further divided into design- and model-based analyses. Of the 159 articles reviewed, 129 articles used model-based analysis, 30 articles used design-based analyses. Similar patterns could be seen in all the individual surveys. While there is general agreement among survey statisticians that complex surveys are most appropriately analyzed using design-based analyses, most researchers continued to use the more common model-based approaches. Recent developments in design-based multi-level analysis may be one approach to include all the survey design characteristics. This is a relatively new area, however, and there remains statistical, as well as applied analytic research required. An important limitation of this study relates to the selection of the surveys used and the choice of year for the analysis, i.e., year 2010 only. There is, however, no strong reason to believe that analytic strategies have changed radically in the past few years, and 2010 provides a credible snapshot of current practice.

The neural basis of visual word form processing: a multivariate investigation.

PubMed

Nestor, Adrian; Behrmann, Marlene; Plaut, David C

2013-07-01

Current research on the neurobiological bases of reading points to the privileged role of a ventral cortical network in visual word processing. However, the properties of this network and, in particular, its selectivity for orthographic stimuli such as words and pseudowords remain topics of significant debate. Here, we approached this issue from a novel perspective by applying pattern-based analyses to functional magnetic resonance imaging data. Specifically, we examined whether, where and how, orthographic stimuli elicit distinct patterns of activation in the human cortex. First, at the category level, multivariate mapping found extensive sensitivity throughout the ventral cortex for words relative to false-font strings. Secondly, at the identity level, the multi-voxel pattern classification provided direct evidence that different pseudowords are encoded by distinct neural patterns. Thirdly, a comparison of pseudoword and face identification revealed that both stimulus types exploit common neural resources within the ventral cortical network. These results provide novel evidence regarding the involvement of the left ventral cortex in orthographic stimulus processing and shed light on its selectivity and discriminability profile. In particular, our findings support the existence of sublexical orthographic representations within the left ventral cortex while arguing for the continuity of reading with other visual recognition skills.

A multi-level approach of evaluating crew resource management training: a laboratory-based study examining communication skills as a function of team congruence.

PubMed

Sauer, J; Darioly, A; Mast, M Schmid; Schmid, P C; Bischof, N

2010-11-01

The article proposes a multi-level approach for evaluating communication skills training (CST) as an important element of crew resource management (CRM) training. Within this methodological framework, the present work examined the effectiveness of CST in matching or mismatching team compositions with regard to hierarchical status and competence. There is little experimental research that evaluated the effectiveness of CRM training at multiple levels (i.e. reaction, learning, behaviour) and in teams composed of members of different status and competence. An experiment with a two (CST: with vs. without) by two (competence/hierarchical status: congruent vs. incongruent) design was carried out. A total of 64 participants were trained for 2.5 h on a simulated process control environment, with the experimental group being given 45 min of training on receptiveness and influencing skills. Prior to the 1-h experimental session, participants were assigned to two-person teams. The results showed overall support for the use of such a multi-level approach of training evaluation. Stronger positive effects of CST were found for subjective measures than for objective performance measures. STATEMENT OF RELEVANCE: This work provides some guidance for the use of a multi-level evaluation of CRM training. It also emphasises the need to collect objective performance data for training evaluation in addition to subjective measures with a view to gain a more accurate picture of the benefits of such training approaches.

An Exploration of the Interaction between Global Education Policy Orthodoxies and National Education Practices in Cambodia, Illuminated through the Voices of Local Teacher Educators

ERIC Educational Resources Information Center

Courtney, Jane

2017-01-01

This research is based on a multi-disciplinary and multi-levelled analysis of evidence to present the case that education reform needs to be contextualised far more widely than is currently practised. It focuses on the voices of Cambodian local teacher trainers through interviews over a five-year period. Interview data is triangulated against…

An Adaptive Multi-Sensor Data Fusion Method Based on Deep Convolutional Neural Networks for Fault Diagnosis of Planetary Gearbox

PubMed Central

Jing, Luyang; Wang, Taiyong; Zhao, Ming; Wang, Peng

2017-01-01

A fault diagnosis approach based on multi-sensor data fusion is a promising tool to deal with complicated damage detection problems of mechanical systems. Nevertheless, this approach suffers from two challenges, which are (1) the feature extraction from various types of sensory data and (2) the selection of a suitable fusion level. It is usually difficult to choose an optimal feature or fusion level for a specific fault diagnosis task, and extensive domain expertise and human labor are also highly required during these selections. To address these two challenges, we propose an adaptive multi-sensor data fusion method based on deep convolutional neural networks (DCNN) for fault diagnosis. The proposed method can learn features from raw data and optimize a combination of different fusion levels adaptively to satisfy the requirements of any fault diagnosis task. The proposed method is tested through a planetary gearbox test rig. Handcraft features, manual-selected fusion levels, single sensory data, and two traditional intelligent models, back-propagation neural networks (BPNN) and a support vector machine (SVM), are used as comparisons in the experiment. The results demonstrate that the proposed method is able to detect the conditions of the planetary gearbox effectively with the best diagnosis accuracy among all comparative methods in the experiment. PMID:28230767

Understanding the Art and Science of Implementation in the SAAF Efficacy Trial

ERIC Educational Resources Information Center

Berkel, Cady; Murry, Velma McBride; Roulston, Kathryn J.; Brody, Gene H.

2013-01-01

Purpose: The purpose of this paper is to demonstrate the importance of considering both fidelity and adaptation in assessing the implementation of evidence-based programs. Design/methodology/approach: The current study employs a multi-method strategy to understand two dimensions of implementation (fidelity and adaptation) in the Strong African…

Perturbational treatment of spin-orbit coupling for generally applicable high-level multi-reference methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mai, Sebastian; Marquetand, Philipp; González, Leticia

2014-08-21

An efficient perturbational treatment of spin-orbit coupling within the framework of high-level multi-reference techniques has been implemented in the most recent version of the COLUMBUS quantum chemistry package, extending the existing fully variational two-component (2c) multi-reference configuration interaction singles and doubles (MRCISD) method. The proposed scheme follows related implementations of quasi-degenerate perturbation theory (QDPT) model space techniques. Our model space is built either from uncontracted, large-scale scalar relativistic MRCISD wavefunctions or based on the scalar-relativistic solutions of the linear-response-theory-based multi-configurational averaged quadratic coupled cluster method (LRT-MRAQCC). The latter approach allows for a consistent, approximatively size-consistent and size-extensive treatment of spin-orbitmore » coupling. The approach is described in detail and compared to a number of related techniques. The inherent accuracy of the QDPT approach is validated by comparing cuts of the potential energy surfaces of acrolein and its S, Se, and Te analoga with the corresponding data obtained from matching fully variational spin-orbit MRCISD calculations. The conceptual availability of approximate analytic gradients with respect to geometrical displacements is an attractive feature of the 2c-QDPT-MRCISD and 2c-QDPT-LRT-MRAQCC methods for structure optimization and ab inito molecular dynamics simulations.« less

Essential Resources for Implementation and Sustainability of Evidence-Based Health Promotion Programs: A Mixed Methods Multi-Site Case Study.

PubMed

Dattalo, M; Wise, M; Ford Ii, J H; Abramson, B; Mahoney, J

2017-04-01

As of October 2016, use of federal Older Americans Act funds for health promotion and disease prevention will be restricted to the Administration on Aging's criteria for high-level evidence-based health promotion programs. Dissemination of these programs to rural communities remains limited. Therefore a strong need exists to identify strategies that facilitate program implementation and sustainability. The objective of this study was to compare organizational readiness and implementation strategies used by rural communities that achieved varying levels of success in sustaining evidence-based health promotion programs for older adults. We utilized a qualitative multi-site case study design to analyze the longitudinal experiences of eight rural sites working to implement evidence-based health promotion program over 3 years (8/2012-7/2015). Multiple sources of data (interviews, documents, reports, surveys) from each site informed the analysis. We used conventional content analysis to conduct a cross-case comparison to identify common features of rural counties that successfully implemented and sustained their target evidence-based health promotion program. Readiness to implement evidence-based programs as low at baseline as all site leaders described needing to secure additional resources for program implementation. Sites that successfully utilized six essential resources implemented and sustained greater numbers of workshops: (1) External Partnerships, (2) Agency Leadership Commitment, (3) Ongoing Source of Workshop Leaders, (4) Health Promotion Coordination Tasks Assigned to Specific Staff, (5) Organizational Stability, and (6) Change Team Engagement. The six essential resources described in this study can help rural communities assess their readiness to implement health promotion programs and work secure the resources necessary for successful implementation.

The Impact of Response to Intervention on Learning Disability Identification: School Based Practices

ERIC Educational Resources Information Center

Smith, Tina B.

2017-01-01

The "Response to Intervention Guidance for New York State School Districts" (2010) document indicates Response to Intervention (RTI) is a mandated general education process intended to provide early interventions to struggling at-risk students. The multi-level RTI framework is structured to include targeted evidence-based interventions…

An integrated strategy of knowledge application for optimal e-health implementation: A multi-method study protocol

PubMed Central

Gagnon, Marie-Pierre; Légaré, France; Fortin, Jean-Paul; Lamothe, Lise; Labrecque, Michel; Duplantie, Julie

2008-01-01

Background E-health is increasingly valued for supporting: 1) access to quality health care services for all citizens; 2) information flow and exchange; 3) integrated health care services and 4) interprofessional collaboration. Nevertheless, several questions remain on the factors allowing an optimal integration of e-health in health care policies, organisations and practices. An evidence-based integrated strategy would maximise the efficacy and efficiency of e-health implementation. However, decisions regarding e-health applications are usually not evidence-based, which can lead to a sub-optimal use of these technologies. This study aims at understanding factors influencing the application of scientific knowledge for an optimal implementation of e-health in the health care system. Methods A three-year multi-method study is being conducted in the Province of Quebec (Canada). Decision-making at each decisional level (political, organisational and clinical) are analysed based on specific approaches. At the political level, critical incidents analysis is being used. This method will identify how decisions regarding the implementation of e-health could be influenced or not by scientific knowledge. Then, interviews with key-decision-makers will look at how knowledge was actually used to support their decisions, and what factors influenced its use. At the organisational level, e-health projects are being analysed as case studies in order to explore the use of scientific knowledge to support decision-making during the implementation of the technology. Interviews with promoters, managers and clinicians will be carried out in order to identify factors influencing the production and application of scientific knowledge. At the clinical level, questionnaires are being distributed to clinicians involved in e-health projects in order to analyse factors influencing knowledge application in their decision-making. Finally, a triangulation of the results will be done using mixed methodologies to allow a transversal analysis of the results at each of the decisional levels. Results This study will identify factors influencing the use of scientific evidence and other types of knowledge by decision-makers involved in planning, financing, implementing and evaluating e-health projects. Conclusion These results will be highly relevant to inform decision-makers who wish to optimise the implementation of e-health in the Quebec health care system. This study is extremely relevant given the context of major transformations in the health care system where e-health becomes a must. PMID:18435853

Intra-dialytic exercise training: a pragmatic approach.

PubMed

Greenwood, Sharlene A; Naish, Patrick; Clark, Rachel; O'Connor, Ellen; Pursey, Victoria A; Macdougall, Iain C; Mercer, Thomas H; Koufaki, Pelagia

2014-09-01

This continuing education paper outlines the skills and knowledge required to plan, implement and evaluate a pragmatic approach to intra-dialytic exercise training. The aim of this continuing education article is to enable the nephrology multi-disciplinary team (MDT) to plan, implement and evaluate the provision of intra-dialytic exercise training for patients receiving haemodialysis therapy. After reading this article the reader should be able to: Appreciate the level of evidence base for the clinical effectiveness of renal exercise rehabilitation and locate credible sources of research and educational information Understand and consider the need for appropriate evaluation and assessment outcomes as part of a renal rehabilitation plan Understand the components of exercise programming and prescription as part of an integrated renal rehabilitation plan Develop a sustainable longer term exercise and physical activity plan. © 2014 The Authors Journal of Renal Care published by John Wiley & Sons Ltd on behalf of European Dialysis & Transplant Nurses Association/European Renal Care Association.

Electron spin resonance and spin-valley physics in a silicon double quantum dot.

PubMed

Hao, Xiaojie; Ruskov, Rusko; Xiao, Ming; Tahan, Charles; Jiang, HongWen

2014-05-14

Silicon quantum dots are a leading approach for solid-state quantum bits. However, developing this technology is complicated by the multi-valley nature of silicon. Here we observe transport of individual electrons in a silicon CMOS-based double quantum dot under electron spin resonance. An anticrossing of the driven dot energy levels is observed when the Zeeman and valley splittings coincide. A detected anticrossing splitting of 60 MHz is interpreted as a direct measure of spin and valley mixing, facilitated by spin-orbit interaction in the presence of non-ideal interfaces. A lower bound of spin dephasing time of 63 ns is extracted. We also describe a possible experimental evidence of an unconventional spin-valley blockade, despite the assumption of non-ideal interfaces. This understanding of silicon spin-valley physics should enable better control and read-out techniques for the spin qubits in an all CMOS silicon approach.

An Intrusion Detection System Based on Multi-Level Clustering for Hierarchical Wireless Sensor Networks

PubMed Central

Butun, Ismail; Ra, In-Ho; Sankar, Ravi

2015-01-01

In this work, an intrusion detection system (IDS) framework based on multi-level clustering for hierarchical wireless sensor networks is proposed. The framework employs two types of intrusion detection approaches: (1) “downward-IDS (D-IDS)” to detect the abnormal behavior (intrusion) of the subordinate (member) nodes; and (2) “upward-IDS (U-IDS)” to detect the abnormal behavior of the cluster heads. By using analytical calculations, the optimum parameters for the D-IDS (number of maximum hops) and U-IDS (monitoring group size) of the framework are evaluated and presented. PMID:26593915

Reported Systems Changes and Sustainability Perceptions of Three State Departments of Health Implementing Multi-Faceted Evidence-Based Fall Prevention Efforts.

PubMed

Smith, Matthew Lee; Schneider, Ellen C; Byers, Imani N; Shubert, Tiffany E; Wilson, Ashley D; Towne, Samuel D; Ory, Marcia G

2017-01-01

Although the concepts of systems change and sustainability are not new, little is known about the factors associated with systems change sustaining multi-state, multi-level fall prevention efforts. This exploratory study focuses on three State Departments of Health (DOH) that were awarded 5-year funding from the Centers for Disease Control and Prevention to simultaneously implement four separate yet related evidence-based fall prevention initiatives at the clinical, community, and policy level. The purpose of this study was to examine changes in partnerships and collaborative activities that occurred to accomplish project goals (examining changes in the context of "before funding" and "after funding was received"). Additionally, this study explored changes in State DOH perceptions about action related to sustainability indicators in the context of "during funding" and "after funding ends." Findings from this study document the partnership and activity changes necessary to achieve defined fall prevention goals after funding is received, and that the importance of sustainability indicator documentation is seen as relevant during funding, but less so after the funding ends. Findings from this study have practice and research implications that can inform future funded efforts in terms of sector and stakeholder engagement necessary for initiating, implementing, and sustaining community- and clinical-based fall prevention interventions.

Empirically Examining the Performance of Approaches to Multi-Level Matching to Study the Effect of School-Level Interventions

ERIC Educational Resources Information Center

Hallberg, Kelly; Cook, Thomas D.; Figlio, David

2013-01-01

The goal of this paper is to provide guidance for applied education researchers in using multi-level data to study the effects of interventions implemented at the school level. Two primary approaches are currently employed in observational studies of the effect of school-level interventions. One approach employs intact school matching: matching…

Family, Community and Clinic Collaboration to Treat Overweight and Obese Children: Stanford GOALS -- a Randomized Controlled Trial of a Three-Year, Multi-Component, Multi-Level, Multi-Setting Intervention

PubMed Central

Robinson, Thomas N.; Matheson, Donna; Desai, Manisha; Wilson, Darrell M.; Weintraub, Dana L.; Haskell, William L.; McClain, Arianna; McClure, Samuel; Banda, Jorge; Sanders, Lee M.; Haydel, K. Farish; Killen, Joel D.

2013-01-01

Objective To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Design Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Participants Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Interventions Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Main Outcome Measure Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. Conclusions The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families. PMID:24028942

Family, community and clinic collaboration to treat overweight and obese children: Stanford GOALS-A randomized controlled trial of a three-year, multi-component, multi-level, multi-setting intervention.

PubMed

Robinson, Thomas N; Matheson, Donna; Desai, Manisha; Wilson, Darrell M; Weintraub, Dana L; Haskell, William L; McClain, Arianna; McClure, Samuel; Banda, Jorge A; Sanders, Lee M; Haydel, K Farish; Killen, Joel D

2013-11-01

To test the effects of a three-year, community-based, multi-component, multi-level, multi-setting (MMM) approach for treating overweight and obese children. Two-arm, parallel group, randomized controlled trial with measures at baseline, 12, 24, and 36 months after randomization. Seven through eleven year old, overweight and obese children (BMI ≥ 85th percentile) and their parents/caregivers recruited from community locations in low-income, primarily Latino neighborhoods in Northern California. Families are randomized to the MMM intervention versus a community health education active-placebo comparison intervention. Interventions last for three years for each participant. The MMM intervention includes a community-based after school team sports program designed specifically for overweight and obese children, a home-based family intervention to reduce screen time, alter the home food/eating environment, and promote self-regulatory skills for eating and activity behavior change, and a primary care behavioral counseling intervention linked to the community and home interventions. The active-placebo comparison intervention includes semi-annual health education home visits, monthly health education newsletters for children and for parents/guardians, and a series of community-based health education events for families. Body mass index trajectory over the three-year study. Secondary outcome measures include waist circumference, triceps skinfold thickness, accelerometer-measured physical activity, 24-hour dietary recalls, screen time and other sedentary behaviors, blood pressure, fasting lipids, glucose, insulin, hemoglobin A1c, C-reactive protein, alanine aminotransferase, and psychosocial measures. The Stanford GOALS trial is testing the efficacy of a novel community-based multi-component, multi-level, multi-setting treatment for childhood overweight and obesity in low-income, Latino families. © 2013 Elsevier Inc. All rights reserved.

Multivariate pattern recognition for diagnosis and prognosis in clinical neuroimaging: state of the art, current challenges and future trends.

PubMed

Haller, Sven; Lovblad, Karl-Olof; Giannakopoulos, Panteleimon; Van De Ville, Dimitri

2014-05-01

Many diseases are associated with systematic modifications in brain morphometry and function. These alterations may be subtle, in particular at early stages of the disease progress, and thus not evident by visual inspection alone. Group-level statistical comparisons have dominated neuroimaging studies for many years, proving fascinating insight into brain regions involved in various diseases. However, such group-level results do not warrant diagnostic value for individual patients. Recently, pattern recognition approaches have led to a fundamental shift in paradigm, bringing multivariate analysis and predictive results, notably for the early diagnosis of individual patients. We review the state-of-the-art fundamentals of pattern recognition including feature selection, cross-validation and classification techniques, as well as limitations including inter-individual variation in normal brain anatomy and neurocognitive reserve. We conclude with the discussion of future trends including multi-modal pattern recognition, multi-center approaches with data-sharing and cloud-computing.

School Funding and Resource Allocation: How It Impacts Instructional Practices at the School Level

ERIC Educational Resources Information Center

Wall, Shelly R.

2012-01-01

In the 2006-2007 school year, the State of Wyoming adopted an evidenced-based school funding model. The Wyoming funding model reviewed in this study is considered an evidence-based approach, utilizing expert judgment to determine educational funding. In an evidence-based approach, educational strategies are identified and a dollar figure is…

Multi-model comparison highlights consistency in predicted effect of warming on a semi-arid shrub

USGS Publications Warehouse

Renwick, Katherine M.; Curtis, Caroline; Kleinhesselink, Andrew R.; Schlaepfer, Daniel R.; Bradley, Bethany A.; Aldridge, Cameron L.; Poulter, Benjamin; Adler, Peter B.

2018-01-01

A number of modeling approaches have been developed to predict the impacts of climate change on species distributions, performance, and abundance. The stronger the agreement from models that represent different processes and are based on distinct and independent sources of information, the greater the confidence we can have in their predictions. Evaluating the level of confidence is particularly important when predictions are used to guide conservation or restoration decisions. We used a multi-model approach to predict climate change impacts on big sagebrush (Artemisia tridentata), the dominant plant species on roughly 43 million hectares in the western United States and a key resource for many endemic wildlife species. To evaluate the climate sensitivity of A. tridentata, we developed four predictive models, two based on empirically derived spatial and temporal relationships, and two that applied mechanistic approaches to simulate sagebrush recruitment and growth. This approach enabled us to produce an aggregate index of climate change vulnerability and uncertainty based on the level of agreement between models. Despite large differences in model structure, predictions of sagebrush response to climate change were largely consistent. Performance, as measured by change in cover, growth, or recruitment, was predicted to decrease at the warmest sites, but increase throughout the cooler portions of sagebrush's range. A sensitivity analysis indicated that sagebrush performance responds more strongly to changes in temperature than precipitation. Most of the uncertainty in model predictions reflected variation among the ecological models, raising questions about the reliability of forecasts based on a single modeling approach. Our results highlight the value of a multi-model approach in forecasting climate change impacts and uncertainties and should help land managers to maximize the value of conservation investments.

Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

PubMed

Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

Multi-atlas and label fusion approach for patient-specific MRI based skull estimation.

PubMed

Torrado-Carvajal, Angel; Herraiz, Joaquin L; Hernandez-Tamames, Juan A; San Jose-Estepar, Raul; Eryaman, Yigitcan; Rozenholc, Yves; Adalsteinsson, Elfar; Wald, Lawrence L; Malpica, Norberto

2016-04-01

MRI-based skull segmentation is a useful procedure for many imaging applications. This study describes a methodology for automatic segmentation of the complete skull from a single T1-weighted volume. The skull is estimated using a multi-atlas segmentation approach. Using a whole head computed tomography (CT) scan database, the skull in a new MRI volume is detected by nonrigid image registration of the volume to every CT, and combination of the individual segmentations by label-fusion. We have compared Majority Voting, Simultaneous Truth and Performance Level Estimation (STAPLE), Shape Based Averaging (SBA), and the Selective and Iterative Method for Performance Level Estimation (SIMPLE) algorithms. The pipeline has been evaluated quantitatively using images from the Retrospective Image Registration Evaluation database (reaching an overlap of 72.46 ± 6.99%), a clinical CT-MR dataset (maximum overlap of 78.31 ± 6.97%), and a whole head CT-MRI pair (maximum overlap 78.68%). A qualitative evaluation has also been performed on MRI acquisition of volunteers. It is possible to automatically segment the complete skull from MRI data using a multi-atlas and label fusion approach. This will allow the creation of complete MRI-based tissue models that can be used in electromagnetic dosimetry applications and attenuation correction in PET/MR. © 2015 Wiley Periodicals, Inc.

Morphing Wing Weight Predictors and Their Application in a Template-Based Morphing Aircraft Sizing Environment II. Part 2; Morphing Aircraft Sizing via Multi-level Optimization

NASA Technical Reports Server (NTRS)

Skillen, Michael D.; Crossley, William A.

2008-01-01

This report presents an approach for sizing of a morphing aircraft based upon a multi-level design optimization approach. For this effort, a morphing wing is one whose planform can make significant shape changes in flight - increasing wing area by 50% or more from the lowest possible area, changing sweep 30 or more, and/or increasing aspect ratio by as much as 200% from the lowest possible value. The top-level optimization problem seeks to minimize the gross weight of the aircraft by determining a set of "baseline" variables - these are common aircraft sizing variables, along with a set of "morphing limit" variables - these describe the maximum shape change for a particular morphing strategy. The sub-level optimization problems represent each segment in the morphing aircraft's design mission; here, each sub-level optimizer minimizes fuel consumed during each mission segment by changing the wing planform within the bounds set by the baseline and morphing limit variables from the top-level problem.

An Expanded Multi-scale Monte Carlo Simulation Method for Personalized Radiobiological Effect Estimation in Radiotherapy: a feasibility study

NASA Astrophysics Data System (ADS)

Zhang, Ying; Feng, Yuanming; Wang, Wei; Yang, Chengwen; Wang, Ping

2017-03-01

A novel and versatile “bottom-up” approach is developed to estimate the radiobiological effect of clinic radiotherapy. The model consists of multi-scale Monte Carlo simulations from organ to cell levels. At cellular level, accumulated damages are computed using a spectrum-based accumulation algorithm and predefined cellular damage database. The damage repair mechanism is modeled by an expanded reaction-rate two-lesion kinetic model, which were calibrated through replicating a radiobiological experiment. Multi-scale modeling is then performed on a lung cancer patient under conventional fractionated irradiation. The cell killing effects of two representative voxels (isocenter and peripheral voxel of the tumor) are computed and compared. At microscopic level, the nucleus dose and damage yields vary among all nucleuses within the voxels. Slightly larger percentage of cDSB yield is observed for the peripheral voxel (55.0%) compared to the isocenter one (52.5%). For isocenter voxel, survival fraction increase monotonically at reduced oxygen environment. Under an extreme anoxic condition (0.001%), survival fraction is calculated to be 80% and the hypoxia reduction factor reaches a maximum value of 2.24. In conclusion, with biological-related variations, the proposed multi-scale approach is more versatile than the existing approaches for evaluating personalized radiobiological effects in radiotherapy.

Resource atlases for multi-atlas brain segmentations with multiple ontology levels based on T1-weighted MRI.

PubMed

Wu, Dan; Ma, Ting; Ceritoglu, Can; Li, Yue; Chotiyanonta, Jill; Hou, Zhipeng; Hsu, John; Xu, Xin; Brown, Timothy; Miller, Michael I; Mori, Susumu

2016-01-15

Technologies for multi-atlas brain segmentation of T1-weighted MRI images have rapidly progressed in recent years, with highly promising results. This approach, however, relies on a large number of atlases with accurate and consistent structural identifications. Here, we introduce our atlas inventories (n=90), which cover ages 4-82years with unique hierarchical structural definitions (286 structures at the finest level). This multi-atlas library resource provides the flexibility to choose appropriate atlases for various studies with different age ranges and structure-definition criteria. In this paper, we describe the details of the atlas resources and demonstrate the improved accuracy achievable with a dynamic age-matching approach, in which atlases that most closely match the subject's age are dynamically selected. The advanced atlas creation strategy, together with atlas pre-selection principles, is expected to support the further development of multi-atlas image segmentation. Copyright © 2015 Elsevier Inc. All rights reserved.

Caring for patients with kidney disease: shifting the paradigm from evidence-based medicine to patient-centered care

PubMed Central

O'Hare, Ann M.; Rodriguez, Rudolph A.; Bowling, Christopher Barrett

2016-01-01

The last several decades have witnessed the emergence of evidence-based medicine as the dominant paradigm for medical teaching, research and practice. Under an evidence-based approach, populations rather than individuals become the primary focus of investigation. Treatment priorities are largely shaped by the availability, relevance and quality of evidence and study outcomes and results are assumed to have more or less universal significance based on their implications at the population level. However, population-level treatment goals do not always align with what matters the most to individual patients—who may weigh the risks, benefits and harms of recommended treatments quite differently. In this article we describe the rise of evidence-based medicine in historical context. We discuss limitations of this approach for supporting real-world treatment decisions—especially in older adults with confluent comorbidity, functional impairment and/or limited life expectancy—and we describe the emergence of more patient-centered paradigms to address these limitations. We explain how the principles of evidence-based medicine have helped to shape contemporary approaches to defining, classifying and managing patients with chronic kidney disease. We discuss the limitations of this approach and the potential value of a more patient-centered paradigm, with a particular focus on the care of older adults with this condition. We conclude by outlining ways in which the evidence-base might be reconfigured to better support real-world treatment decisions in individual patients and summarize relevant ongoing initiatives. PMID:25637639

Evidence-based practice beliefs and behaviors of nurses providing cancer pain management: a mixed-methods approach.

PubMed

Eaton, Linda H; Meins, Alexa R; Mitchell, Pamela H; Voss, Joachim; Doorenbos, Ardith Z

2015-03-01

To describe evidence-based practice (EBP) beliefs and behaviors of nurses who provide cancer pain management. Descriptive, cross-sectional with a mixed-methods approach. Two inpatient oncology units in the Pacific Northwest. 40 RNs.
 Data collected by interviews and web-based surveys. EBP beliefs, EBP implementation, evidence-based pain management. Nurses agreed with the positive aspects of EBP and their implementation ability, although implementation level was low. They were satisfied with their pain management practices. Oncology nursing certification was associated with innovativeness, and innovativeness was associated with EBP beliefs. Themes identified were (a) limited definition of EBP, (b) varied evidence-based pain management decision making, (c) limited identification of evidence-based pain management practices, and (d) integration of nonpharmacologic interventions into patient care. Nurses' low level of EBP implementation in the context of pain management was explained by their trust that standards of care and medical orders were evidence-based. Nurses' EBP beliefs and behaviors should be considered when developing strategies for sustaining evidence-based pain management practices. Implementation of the EBP process by nurses may not be realistic in the inpatient setting; therefore, hospital pain management policies need to be evidence-based and reinforced with nurses.

[Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

PubMed

Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

2011-12-01

Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

Toward a multi-country monitoring system of reproductive health in the context of endocrine disrupting chemical exposure.

PubMed

Le Moal, Joëlle; Sharpe, Richard M; Jϕrgensen, Niels; Levine, Hagai; Jurewicz, Joanna; Mendiola, Jaime; Swan, Shanna H; Virtanen, Helena; Christin-Maître, Sophie; Cordier, Sylvaine; Toppari, Jorma; Hanke, Wojciech

2016-02-01

Worrying trends regarding human reproductive endpoints (e.g. semen quality, reproductive cancers) have been reported and there is growing circumstantial evidence for a possible causal link between these trends and exposure to endocrine disrupting chemicals (EDCs). However, there is a striking lack of human data to fill the current knowledge gaps. To answer the crucial questions raised on human reproductive health, there is an urgent need for a reproductive surveillance system to be shared across countries. A multidisciplinary network named HUman Reproductive health and Global ENvironment Network (HURGENT) was created aiming at designing a European monitoring system for reproductive health indicators. Collaborative work allowed setting up the available knowledge to design such a system. Furthermore we conducted an overview of 23 potential indicators, based upon a weight of evidence (WoE) approach according to their potential relation with EDC exposure. The framework and purposes of the surveillance system are settled as well as the approach to select suitable reproductive indicators. The indicators found with the highest scores according to the WoE approach are prostate and breast cancer incidence, sex ratio, endometriosis and uterine fibroid incidence, indicators related to the testicular dysgenesis syndrome, precocious puberty incidence and reproductive hormone levels. Not only sentinel health endpoints, but also diseases with high burdens in public health are highlighted as prior indicators in the context of EDC exposure. Our work can serve as a basis to construct, as soon as possible, the first multi-country reproductive monitoring system. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Surviving sepsis: a trust-wide approach. A multi-disciplinary team approach to implementing evidence-based guidelines.

PubMed

Gerber, Karin

2010-01-01

To share an experience of examining the true extent of the number of patients with severe sepsis being admitted, and the overall compliance with existing treatment guidelines in a district general hospital (DGH). Because of its aggressive, multi-factorial nature, sepsis is a rapid killer. Mortality associated with severe sepsis remains unacceptably high: 30-50%. When shock is present, mortality is reported to be even higher: 50-60%. The rapid diagnosis and management of sepsis is vital to successful treatment. The International Surviving Sepsis Campaign (SSC) was developed to help meet the challenges of sepsis and to improve its management, diagnosis and treatment. The overall aim is to reduce mortality from sepsis by 25% by 2009. Data on the number of patients admitted with severe sepsis to the DGH were previously unknown. The aim of the baseline audits was to determine the true extent of the problem and baseline mortality rates, resulting in an action plan to provide evidence-based care to patients with sepsis regardless of where in the hospital they were located. It was found that 11% of the patients audited presented with signs of severe sepsis and demonstrated elements of poor compliance with some elements of existing treatment guidelines as set out by the resuscitation component of the Surviving Sepsis Care Bundle. As an international campaign introduced predominantly within critical care, within this DGH the SSC teams' innovative approach has resulted in: * Better educated staff; * Objectives agreed within multi-disciplinary teams; * The appropriate assessment of resources; * Standardization of practice in terms of patients presenting with severe sepsis.

Assessment of Material Solutions of Multi-level Garage Structure Within Integrated Life Cycle Design Process

NASA Astrophysics Data System (ADS)

Wałach, Daniel; Sagan, Joanna; Gicala, Magdalena

2017-10-01

The paper presents an environmental and economic analysis of the material solutions of multi-level garage. The construction project approach considered reinforced concrete structure under conditions of use of ordinary concrete and high-performance concrete (HPC). Using of HPC allowed to significant reduction of reinforcement steel, mainly in compression elements (columns) in the construction of the object. The analysis includes elements of the methodology of integrated lice cycle design (ILCD). By making multi-criteria analysis based on established weight of the economic and environmental parameters, three solutions have been evaluated and compared within phase of material production (information modules A1-A3).

Single-mode glass waveguide technology for optical interchip communication on board level

NASA Astrophysics Data System (ADS)

Brusberg, Lars; Neitz, Marcel; Schröder, Henning

2012-01-01

The large bandwidth demand in long-distance telecom networks lead to single-mode fiber interconnects as result of low dispersion, low loss and dense wavelength multiplexing possibilities. In contrast, multi-mode interconnects are suitable for much shorter lengths up to 300 meters and are promising for optical links between racks and on board level. Active optical cables based on multi-mode fiber links are at the market and research in multi-mode waveguide integration on board level is still going on. Compared to multi-mode, a single-mode waveguide has much more integration potential because of core diameters of around 20% of a multi-mode waveguide by a much larger bandwidth. But light coupling in single-mode waveguides is much more challenging because of lower coupling tolerances. Together with the silicon photonics technology, a single-mode waveguide technology on board-level will be the straight forward development goal for chip-to-chip optical interconnects integration. Such a hybrid packaging platform providing 3D optical single-mode links bridges the gap between novel photonic integrated circuits and the glass fiber based long-distance telecom networks. Following we introduce our 3D photonic packaging approach based on thin glass substrates with planar integrated optical single-mode waveguides for fiber-to-chip and chip-to-chip interconnects. This novel packaging approach merges micro-system packaging and glass integrated optics. It consists of a thin glass substrate with planar integrated singlemode waveguide circuits, optical mirrors and lenses providing an integration platform for photonic IC assembly and optical fiber interconnect. Thin glass is commercially available in panel and wafer formats and characterizes excellent optical and high-frequency properties. That makes it perfect for microsystem packaging. The paper presents recent results in single-mode waveguide technology on wafer level and waveguide characterization. Furthermore the integration in a hybrid packaging process and design issues are discussed.

Evidence for the use of Levomepromazine for symptom control in the palliative care setting: a systematic review

PubMed Central

2013-01-01

Background Levomepromazine is an antipsychotic drug that is used clinically for a variety of distressing symptoms in palliative and end-of-life care. We undertook a systematic review based on the question “What is the published evidence for the use of levomepromazine in palliative symptom control?”. Methods To determine the level of evidence for the use of levomepromazine in palliative symptom control, and to discover gaps in evidence, relevant studies were identified using a detailed, multi-step search strategy. Emerging data was then scrutinized using appropriate assessment tools, and the strength of evidence systematically graded in accordance with the Oxford Centre for Evidence-Based Medicine’s ‘levels of evidence’ tool. The electronic databases Medline, Embase, Cochrane, PsychInfo and Ovid Nursing, together with hand-searching and cross-referencing provided the full research platform on which the review is based. Results 33 articles including 9 systematic reviews met the inclusion criteria: 15 on palliative sedation, 8 regarding nausea and three on delirium and restlessness, one on pain and six with other foci. The studies varied greatly in both design and sample size. Levels of evidence ranged from level 2b to level 5, with the majority being level 3 (non-randomized, non-consecutive or cohort studies n = 22), with the quality of reporting for the included studies being only low to medium. Conclusion Levomepromazine is widely used in palliative care as antipsychotic, anxiolytic, antiemetic and sedative drug. However, the supporting evidence is limited to open series and case reports. Thus prospective randomized trials are needed to support evidence-based guidelines. PMID:23331515

Addressing non-communicable diseases in the Seychelles: towards a comprehensive plan of action.

PubMed

Bovet, Pascal; Viswanathan, Bharathi; Shamlaye, Conrad; Romain, Sarah; Gedeon, Jude

2010-06-01

This article reviews the different steps taken during the past 20 years for the prevention and control of non-communicable diseases (NCDs) in the Seychelles. National surveys revealed high levels of several cardiovascular risk factors and prompted an organized response, starting with the creation of an NCD unit in the Ministry of Health. Information campaigns and nationwide activities raised awareness and rallied increasingly broad and high-level support. Significant policy was developed including comprehensive tobacco legislation and a School Nutrition Policy that bans soft drinks in schools. NCD guidelines were developed and specialized 'NCD nurses' were trained to complement doctors in district health centers. Decreasing smoking prevalence is evidence of success, but the raising so-called diabesity epidemic calls for an integrated multi-sector policy to mould an environment conducive to healthy behaviors. Essential components of these efforts include: effective surveillance mechanisms supplemented by focused research; generating broad interest and consensus; mobilizing leadership and commitment at all levels; involving local and international expertise; building on existing efforts; and seeking integrated, multi-disciplinary and multi-sector approaches.

Understanding the Diffusion of Non-Evidence-Based Health Interventions: The Role of Experiential Evidence

ERIC Educational Resources Information Center

Evans, Rhiannon; Murphy, Simon; Scourfield, Jonathan; Turley, Ruth

2017-01-01

Objective: The utilisation of evidence-based health interventions remains a challenge in educational settings. Although driving forward the scientific evidence-base may contribute to the diffusion of such approaches, abstract notions of population-level impact may not be seen as priorities in local. This paper considers the alternative forms of…

Tunable complex-valued multi-tap microwave photonic filter based on single silicon-on-insulator microring resonator.

PubMed

Lloret, Juan; Sancho, Juan; Pu, Minhao; Gasulla, Ivana; Yvind, Kresten; Sales, Salvador; Capmany, José

2011-06-20

A complex-valued multi-tap tunable microwave photonic filter based on single silicon-on-insulator microring resonator is presented. The degree of tunability of the approach involving two, three and four taps is theoretical and experimentally characterized, respectively. The constraints of exploiting the optical phase transfer function of a microring resonator aiming at implementing complex-valued multi-tap filtering schemes are also reported. The trade-off between the degree of tunability without changing the free spectral range and the number of taps is studied in-depth. Different window based scenarios are evaluated for improving the filter performance in terms of the side-lobe level.

Health professionals' decision-making in wound management: a grounded theory.

PubMed

Gillespie, Brigid M; Chaboyer, Wendy; St John, Winsome; Morley, Nicola; Nieuwenhoven, Paul

2015-06-01

To develop a conceptual understanding of the decision-making processes used by healthcare professionals in wound care practice. With the global move towards using an evidence-base in standardizing wound care practices and the need to reduce hospital wound care costs, it is important to understand health professionals' decision-making in this important yet under-researched area. A grounded theory approach was used to explore clinical decision-making of healthcare professionals in wound care practice. Interviews were conducted with 20 multi-disciplinary participants from nursing, surgery, infection control and wound care who worked at a metropolitan hospital in Australia. Data were collected during 2012-2013. Constant comparative analysis underpinned by Strauss and Corbin's framework was used to identify clinical decision-making processes. The core category was 'balancing practice-based knowledge with evidence-based knowledge'. Participants' clinical practice and actions embedded the following processes: 'utilizing the best available information', 'using a consistent approach in wound assessment' and 'using a multidisciplinary approach'. The substantive theory explains how practice and evidence knowledge was balanced and the variation in use of intuitive practice-based knowledge versus evidence-based knowledge. Participants considered patients' needs and preferences, costs, outcomes, technologies, others' expertise and established practices. Participants' decision-making tended to be more heavily weighted towards intuitive practice-based processes. These findings offer a better understanding of the processes used by health professionals' in their decision-making in wound care. Such an understanding may inform the development of evidence-based interventions that lead to better patient outcomes. © 2014 John Wiley & Sons Ltd.

Evidence-based tick acaricide resistance intervention strategy in Uganda: Concept and feedback of farmers and stakeholders.

PubMed

Vudriko, Patrick; Okwee-Acai, James; Byaruhanga, Joseph; Tayebwa, Dickson Stuart; Omara, Robert; Muhindo, Jeanne Bukeka; Lagu, Charles; Umemiya-Shirafuji, Rika; Xuan, Xuenan; Suzuki, Hiroshi

2018-02-01

The emergence of multi-acaricide resistant ticks has led to unprecedented level of acaricide failure in central and western Uganda. In the absence of a national acaricide resistance management strategy, the country's dairy sector is threatened by upsurge of ticks and tick-borne diseases. In this study, we developed a short-to-medium-term intervention approach called Evidence-Based Acaricide Tick Control (EBATIC): Identify, Test, Intervene and Eradicate (IT-IE). Furthermore, the perception of 199 farmers and extension workers, 12 key informants in four districts and 47 stakeholders in the animal industry in Uganda were assessed using semi-structured questionnaires. We report that the establishment of a specialized laboratory is pivotal in identifying and testing (IT) acaricide resistant ticks for prompt intervention and eradication (IE). The laboratory test results and the farm tick control gaps identified are very important in guiding acaricide resistance management strategies such as evidence-based acaricide rotation, development and dissemination of extension materials, training of farmers and extension workers, and stakeholders' engagement towards finding sustainable solutions. All the 47 stakeholders and 91.0% (181/199) of the farmers and extension workers reported that the EBATIC approach will help in solving the tick acaricide resistance crisis in Uganda. Similarly, all the 12 key informants and 92.5% (184/199) of the farmers and extension workers suggested that the EBATIC approach should be sustained and rolled out to other districts. The EBATIC stakeholders' dialogue generated both short-to-medium and long-term strategies for sustainable management of tick acaricide resistance in the country. Overall, the positive feedback from farmers, district veterinarians and stakeholders in the animal industry suggest that the EBATIC approach is a useful proof-of-concept on scalable intervention pathway against tick acaricide resistance in Uganda with possibility of adoption in other African countries. Copyright © 2017 Elsevier GmbH. All rights reserved.

A Multi-Informant Approach to Measuring Depressive Symptoms in Clinical Assessments of Adolescent Social Anxiety Using the Beck Depression Inventory-II: Convergent, Incremental, and Criterion-Related Validity

ERIC Educational Resources Information Center

Rausch, Erica; Racz, Sarah J.; Augenstein, Tara M.; Keeley, Lauren; Lipton, Melanie F.; Szollos, Sebastian; Riffle, James; Moriarity, Daniel; Kromash, Rachelle; De Los Reyes, Andres

2017-01-01

Background: Among adolescents, depressive symptoms commonly co-occur with social anxiety, with social anxiety often developmentally preceding depressive symptoms. Thus, evidence-based assessments of adolescent social anxiety should be augmented with assessments of depressive symptoms using measures that can be administered across developmental…

Evidence-Based Medicine in Facial Trauma.

PubMed

Dougherty, William M; Christophel, John Jared; Park, Stephen S

2017-11-01

This article provides the reader with a comprehensive review of high-level evidence-based medicine in facial trauma and highlights areas devoid of high-level evidence. The article is organized in the order one might approach a clinical problem: starting with the workup, followed by treatment considerations, operative decisions, and postoperative treatments. Individual injuries are discussed within each section, with an overview of the available high-level clinical evidence. This article not only provides a quick reference for the facial traumatologist, but also allows the reader to identify areas that lack high-level evidence, perhaps motivating future endeavors. Copyright © 2017 Elsevier Inc. All rights reserved.

Deep Visual Attention Prediction

NASA Astrophysics Data System (ADS)

Wang, Wenguan; Shen, Jianbing

2018-05-01

In this work, we aim to predict human eye fixation with view-free scenes based on an end-to-end deep learning architecture. Although Convolutional Neural Networks (CNNs) have made substantial improvement on human attention prediction, it is still needed to improve CNN based attention models by efficiently leveraging multi-scale features. Our visual attention network is proposed to capture hierarchical saliency information from deep, coarse layers with global saliency information to shallow, fine layers with local saliency response. Our model is based on a skip-layer network structure, which predicts human attention from multiple convolutional layers with various reception fields. Final saliency prediction is achieved via the cooperation of those global and local predictions. Our model is learned in a deep supervision manner, where supervision is directly fed into multi-level layers, instead of previous approaches of providing supervision only at the output layer and propagating this supervision back to earlier layers. Our model thus incorporates multi-level saliency predictions within a single network, which significantly decreases the redundancy of previous approaches of learning multiple network streams with different input scales. Extensive experimental analysis on various challenging benchmark datasets demonstrate our method yields state-of-the-art performance with competitive inference time.

Measuring sustainable development using a multi-criteria model: a case study.

PubMed

Boggia, Antonio; Cortina, Carla

2010-11-01

This paper shows how Multi-criteria Decision Analysis (MCDA) can help in a complex process such as the assessment of the level of sustainability of a certain area. The paper presents the results of a study in which a model for measuring sustainability was implemented to better aid public policy decisions regarding sustainability. In order to assess sustainability in specific areas, a methodological approach based on multi-criteria analysis has been developed. The aim is to rank areas in order to understand the specific technical and/or financial support that they need to develop sustainable growth. The case study presented is an assessment of the level of sustainability in different areas of an Italian Region using the MCDA approach. Our results show that MCDA is a proper approach for sustainability assessment. The results are easy to understand and the evaluation path is clear and transparent. This is what decision makers need for having support to their decisions. The multi-criteria model for evaluation has been developed respecting the sustainable development economic theory, so that final results can have a clear meaning in terms of sustainability. Copyright 2010 Elsevier Ltd. All rights reserved.

Update on diagnosis and management of childhood epilepsies.

PubMed

Zuberi, Sameer M; Symonds, Joseph D

2015-01-01

To review the current evidence base for the diagnosis and management of the childhood epilepsies and to draw attention to the current gaps in this evidence base. The focus will be on therapeutic aspects. Current International League Against Epilepsy (ILAE) terminology will be described and used throughout the discussion. The review will draw attention to recent advances that have been made in both our understanding and treatment of the childhood epilepsies. Potential future directions for research and treatment options will be discussed. Original articles relevant to the subject were obtained from the MedLine database using pertinent MeSH terms. Relevant papers were read and assimilated. Citation searching was used. Epilepsy is a major cause of global disease burden. Childhood epilepsies are a heterogeneous group of conditions. A multi-axial diagnostic approach should be taken prior to making treatment and management decisions for any individual patient. For the majority of patients, successful control of seizures can be achieved with a single medication. However, a significant minority develops refractory disease. Epilepsy surgery can provide cure for a carefully selected group of these cases. There remain significant gaps the evidence base for treatment in several areas of childhood epilepsy. Concerted multi-center efforts should be made to try to close these gaps. A personalized medicine approach may help to reduce the proportion of refractory cases of childhood epilepsy in future. Copyright © 2015 Sociedade Brasileira de Pediatria. Published by Elsevier Editora Ltda. All rights reserved.

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction

PubMed Central

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Objective Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Methods Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Results Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Conclusions Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. PMID:25002459

Knowledge boosting: a graph-based integration approach with multi-omics data and genomic knowledge for cancer clinical outcome prediction.

PubMed

Kim, Dokyoon; Joung, Je-Gun; Sohn, Kyung-Ah; Shin, Hyunjung; Park, Yu Rang; Ritchie, Marylyn D; Kim, Ju Han

2015-01-01

Cancer can involve gene dysregulation via multiple mechanisms, so no single level of genomic data fully elucidates tumor behavior due to the presence of numerous genomic variations within or between levels in a biological system. We have previously proposed a graph-based integration approach that combines multi-omics data including copy number alteration, methylation, miRNA, and gene expression data for predicting clinical outcome in cancer. However, genomic features likely interact with other genomic features in complex signaling or regulatory networks, since cancer is caused by alterations in pathways or complete processes. Here we propose a new graph-based framework for integrating multi-omics data and genomic knowledge to improve power in predicting clinical outcomes and elucidate interplay between different levels. To highlight the validity of our proposed framework, we used an ovarian cancer dataset from The Cancer Genome Atlas for predicting stage, grade, and survival outcomes. Integrating multi-omics data with genomic knowledge to construct pre-defined features resulted in higher performance in clinical outcome prediction and higher stability. For the grade outcome, the model with gene expression data produced an area under the receiver operating characteristic curve (AUC) of 0.7866. However, models of the integration with pathway, Gene Ontology, chromosomal gene set, and motif gene set consistently outperformed the model with genomic data only, attaining AUCs of 0.7873, 0.8433, 0.8254, and 0.8179, respectively. Integrating multi-omics data and genomic knowledge to improve understanding of molecular pathogenesis and underlying biology in cancer should improve diagnostic and prognostic indicators and the effectiveness of therapies. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association.

A fuzzy MCDM framework based on fuzzy measure and fuzzy integral for agile supplier evaluation

NASA Astrophysics Data System (ADS)

Dursun, Mehtap

2017-06-01

Supply chains need to be agile in order to response quickly to the changes in today's competitive environment. The success of an agile supply chain depends on the firm's ability to select the most appropriate suppliers. This study proposes a multi-criteria decision making technique for conducting an analysis based on multi-level hierarchical structure and fuzzy logic for the evaluation of agile suppliers. The ideal and anti-ideal solutions are taken into consideration simultaneously in the developed approach. The proposed decision approach enables the decision-makers to use linguistic terms, and thus, reduce their cognitive burden in the evaluation process. Furthermore, a hierarchy of evaluation criteria and their related sub-criteria is employed in the presented approach in order to conduct a more effective analysis.

Why we need multi-level health workforce governance: Case studies from nursing and medicine in Germany.

PubMed

Kuhlmann, Ellen; Larsen, Christa

2015-12-01

Health workforce needs have moved up on the reform agendas, but policymaking often remains 'piece-meal work' and does not respond to the complexity of health workforce challenges. This article argues for innovation in healthcare governance as a key to greater sustainability of health human resources. The aim is to develop a multi-level approach that helps to identify gaps in governance and improve policy interventions. Pilot research into nursing and medicine in Germany, carried out between 2013 and 2015 using a qualitative methodology, serves to illustrate systems-based governance weaknesses. Three explorative cases address major responses to health workforce shortages, comprising migration/mobility of nurses, reform of nursing education, and gender-sensitive work management of hospital doctors. The findings illustrate a lack of connections between transnational/EU and organizational governance, between national and local levels, occupational and sector governance, and organizations/hospital management and professional development. Consequently, innovations in the health workforce need a multi-level governance approach to get transformative potential and help closing the existing gaps in governance. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

PubMed

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Climate change impacts: The challenge of quantifying multi-factor causation, multi-component responses, and leveraging from extremes

NASA Astrophysics Data System (ADS)

Field, C. B.

2012-12-01

Modeling climate change impacts is challenging for a variety of reasons. Some of these are related to causation. A weather or climate event is rarely the sole cause of an impact, and, for many impacts, social, economic, cultural, or ecological factors may play a larger role than climate. Other challenges are related to outcomes. Consequences of an event are often most severe when several kinds of responses interact, typically in unexpected ways. Many kinds of consequences are difficult to quantify, especially when they include a mix of market, cultural, personal, and ecological values. In addition, scale can be tremendously important. Modest impacts over large areas present very different challenges than severe but very local impacts. Finally, impacts may respond non-linearly to forcing, with behavior that changes qualitatively at one or more thresholds and with unexpected outcomes in extremes. Modeling these potentially complex interactions between drivers and impacts presents one set of challenges. Evaluating the models presents another. At least five kinds of approaches can contribute to the evaluation of impact models designed to provide insights in multi-driver, multi-responder, multi-scale, and extreme-driven contexts, even though none of these approaches is a complete or "silver-bullet" solution. The starting point for much of the evaluation in this space is case studies. Case studies can help illustrate links between processes and scales. They can highlight factors that amplify or suppress sensitivity to climate drivers, and they can suggest the consequences of intervening at different points. While case studies rarely provide concrete evidence about mechanisms, they can help move a mechanistic case from circumstantial to sound. Novel approaches to data collection, including crowd sourcing, can potentially provide tools and the number of relevant examples to develop case studies as statistically robust data sources. A critical condition for progress in this area is the ability to utilize data of uneven quality and standards. Novel approaches to meta-analysis provide other options for taking advantage of diverse case studies. Techniques for summarizing responses across impacts, drivers, and scales can play a huge role in increasing the value of information from case studies. In some cases, expert elicitation may provide alternatives for identifying mechanisms or for interpreting multi-factor drivers or responses. Especially when designed to focus on a well-defined set of observations, a sophisticated elicitation can establish formal confidence limits on responses that are otherwise difficult to constrain. A final possible approach involves a focus on the mechanisms contributing to an impact, rather than the impact itself. Approaches based on quantified mechanisms are especially appealing in the context of models where the number of interactions makes it difficult to intuitively understand the chain of connections from cause to effect, when actors differ in goals or sensitivities, or when scale affects parts of the system differently. With all of these approaches, useful evidence may not conform to traditional levels of statistical confidence. Some of the biggest challenges in taking advantage of the potential tools will involve defining what constitutes a meaningful evaluation.

Evaluating Partnerships to Enhance Disaster Risk Management using Multi-Criteria Analysis: An Application at the Pan-European Level

NASA Astrophysics Data System (ADS)

Hochrainer-Stigler, Stefan; Lorant, Anna

2018-01-01

Disaster risk is increasingly recognized as a major development challenge. Recent calls emphasize the need to proactively engage in disaster risk reduction, as well as to establish new partnerships between private and public sector entities in order to decrease current and future risks. Very often such potential partnerships have to meet different objectives reflecting on the priorities of stakeholders involved. Consequently, potential partnerships need to be assessed on multiple criteria to determine weakest links and greatest threats in collaboration. This paper takes a supranational multi-sector partnership perspective, and considers possible ways to enhance disaster risk management in the European Union by better coordination between the European Union Solidarity Fund, risk reduction efforts, and insurance mechanisms. Based on flood risk estimates we employ a risk-layer approach to determine set of options for new partnerships and test them in a high-level workshop via a novel cardinal ranking based multi-criteria approach. Whilst transformative changes receive good overall scores, we also find that the incorporation of risk into budget planning is an essential condition for successful partnerships.

RTI Scheduling Processes for Middle Schools. Information Brief

ERIC Educational Resources Information Center

Prewett, Sara; Mellard, Daryl; Lieske-Lupo, Jessica

2011-01-01

Response to intervention integrates assessment and intervention within a multi-level prevention system to maximize student achievement and to reduce behavior problems. With RTI, schools identify students at risk for poor learning outcomes, monitor student progress, provide evidence-based interventions and adjust the intensity and nature of those…

Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

NASA Astrophysics Data System (ADS)

Mallick, Rajnish; Ganguli, Ranjan; Seetharama Bhat, M.

2015-09-01

The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.

Development of a model for integrated care at the end of life in advanced dementia: A whole systems UK-wide approach

PubMed Central

Jones, Louise; Candy, Bridget; Davis, Sarah; Elliott, Margaret; Gola, Anna; Harrington, Jane; Kupeli, Nuriye; Lord, Kathryn; Moore, Kirsten; Scott, Sharon; Vickerstaff, Victoria; Omar, Rumana Z; King, Michael; Leavey, Gerard; Nazareth, Irwin; Sampson, Elizabeth L

2015-01-01

Background: The prevalence of dementia is rising worldwide and many people will die with the disease. Symptoms towards the end of life may be inadequately managed and informal and professional carers poorly supported. There are few evidence-based interventions to improve end-of-life care in advanced dementia. Aim: To develop an integrated, whole systems, evidence-based intervention that is pragmatic and feasible to improve end-of-life care for people with advanced dementia and support those close to them. Design: A realist-based approach in which qualitative and quantitative data assisted the development of statements. These were incorporated into the RAND/UCLA appropriateness method to achieve consensus on intervention components. Components were mapped to underlying theory of whole systems change and the intervention described in a detailed manual. Setting/participants: Data were collected from people with dementia, carers and health and social care professionals in England, from expert opinion and existing literature. Professional stakeholders in all four countries of the United Kingdom contributed to the RAND/UCLA appropriateness method process. Results: A total of 29 statements were agreed and mapped to individual, group, organisational and economic/political levels of healthcare systems. The resulting main intervention components are as follows: (1) influencing local service organisation through facilitation of integrated multi-disciplinary care, (2) providing training and support for formal and informal carers and (3) influencing local healthcare commissioning and priorities of service providers. Conclusion: Use of in-depth data, consensus methods and theoretical understanding of the intervention components produced an evidence-based intervention for further testing in end-of-life care in advanced dementia. PMID:26354388

Information theoretic partitioning and confidence based weight assignment for multi-classifier decision level fusion in hyperspectral target recognition applications

NASA Astrophysics Data System (ADS)

Prasad, S.; Bruce, L. M.

2007-04-01

There is a growing interest in using multiple sources for automatic target recognition (ATR) applications. One approach is to take multiple, independent observations of a phenomenon and perform a feature level or a decision level fusion for ATR. This paper proposes a method to utilize these types of multi-source fusion techniques to exploit hyperspectral data when only a small number of training pixels are available. Conventional hyperspectral image based ATR techniques project the high dimensional reflectance signature onto a lower dimensional subspace using techniques such as Principal Components Analysis (PCA), Fisher's linear discriminant analysis (LDA), subspace LDA and stepwise LDA. While some of these techniques attempt to solve the curse of dimensionality, or small sample size problem, these are not necessarily optimal projections. In this paper, we present a divide and conquer approach to address the small sample size problem. The hyperspectral space is partitioned into contiguous subspaces such that the discriminative information within each subspace is maximized, and the statistical dependence between subspaces is minimized. We then treat each subspace as a separate source in a multi-source multi-classifier setup and test various decision fusion schemes to determine their efficacy. Unlike previous approaches which use correlation between variables for band grouping, we study the efficacy of higher order statistical information (using average mutual information) for a bottom up band grouping. We also propose a confidence measure based decision fusion technique, where the weights associated with various classifiers are based on their confidence in recognizing the training data. To this end, training accuracies of all classifiers are used for weight assignment in the fusion process of test pixels. The proposed methods are tested using hyperspectral data with known ground truth, such that the efficacy can be quantitatively measured in terms of target recognition accuracies.

Optimization as a Tool for Consistency Maintenance in Multi-Resolution Simulation

NASA Technical Reports Server (NTRS)

Drewry, Darren T; Reynolds, Jr , Paul F; Emanuel, William R

2006-01-01

The need for new approaches to the consistent simulation of related phenomena at multiple levels of resolution is great. While many fields of application would benefit from a complete and approachable solution to this problem, such solutions have proven extremely difficult. We present a multi-resolution simulation methodology that uses numerical optimization as a tool for maintaining external consistency between models of the same phenomena operating at different levels of temporal and/or spatial resolution. Our approach follows from previous work in the disparate fields of inverse modeling and spacetime constraint-based animation. As a case study, our methodology is applied to two environmental models of forest canopy processes that make overlapping predictions under unique sets of operating assumptions, and which execute at different temporal resolutions. Experimental results are presented and future directions are addressed.

Orion Flight Test 1 Architecture: Observed Benefits of a Model Based Engineering Approach

NASA Technical Reports Server (NTRS)

Simpson, Kimberly A.; Sindiy, Oleg V.; McVittie, Thomas I.

2012-01-01

This paper details how a NASA-led team is using a model-based systems engineering approach to capture, analyze and communicate the end-to-end information system architecture supporting the first unmanned orbital flight of the Orion Multi-Purpose Crew Exploration Vehicle. Along with a brief overview of the approach and its products, the paper focuses on the observed program-level benefits, challenges, and lessons learned; all of which may be applied to improve system engineering tasks for characteristically similarly challenges

Assessing intervention fidelity in a multi-level, multi-component, multi-site program: the Children's Healthy Living (CHL) program.

PubMed

Butel, Jean; Braun, Kathryn L; Novotny, Rachel; Acosta, Mark; Castro, Rose; Fleming, Travis; Powers, Julianne; Nigg, Claudio R

2015-12-01

Addressing complex chronic disease prevention, like childhood obesity, requires a multi-level, multi-component culturally relevant approach with broad reach. Models are lacking to guide fidelity monitoring across multiple levels, components, and sites engaged in such interventions. The aim of this study is to describe the fidelity-monitoring approach of The Children's Healthy Living (CHL) Program, a multi-level multi-component intervention in five Pacific jurisdictions. A fidelity-monitoring rubric was developed. About halfway during the intervention, community partners were randomly selected and interviewed independently by local CHL staff and by Coordinating Center representatives to assess treatment fidelity. Ratings were compared and discussed by local and Coordinating Center staff. There was good agreement between the teams (Kappa = 0.50, p < 0.001), and intervention improvement opportunities were identified through data review and group discussion. Fidelity for the multi-level, multi-component, multi-site CHL intervention was successfully assessed, identifying adaptations as well as ways to improve intervention delivery prior to the end of the intervention.

Accounting for correlation in network meta-analysis with multi-arm trials.

PubMed

Franchini, A J; Dias, S; Ades, A E; Jansen, J P; Welton, N J

2012-06-01

Multi-arm trials (trials with more than two arms) are particularly valuable forms of evidence for network meta-analysis (NMA). Trial results are available either as arm-level summaries, where effect measures are reported for each arm, or as contrast-level summaries, where the differences in effect between arms compare with the control arm chosen for the trial. We show that likelihood-based inference in both contrast-level and arm-level formats is identical if there are only two-arm trials, but that if there are multi-arm trials, results from the contrast-level format will be incorrect unless correlations are accounted for in the likelihood. We review Bayesian and frequentist software for NMA with multi-arm trials that can account for this correlation and give an illustrative example of the difference in estimates that can be introduced if the correlations are not incorporated. We discuss methods of imputing correlations when they cannot be derived from the reported results and urge trialists to report the standard error for the control arm even if only contrast-level summaries are reported. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.

Multilevel analysis of the Be Active Eat Well intervention: environmental and behavioural influences on reductions in child obesity risk.

PubMed

Johnson, B A; Kremer, P J; Swinburn, B A; de Silva-Sanigorski, A M

2012-07-01

The Be Active Eat Well (BAEW) community-based child obesity prevention intervention was successful in modestly reducing unhealthy weight gain in primary school children using a multi-strategy and multi-setting approach. To (1) examine the relationship between changes in obesity-related individual, household and school factors and changes in standardised child body mass index (zBMI), and (2) determine if the BAEW intervention moderated these effects. The longitudinal relationships between changes in individual, household and school variables and changes in zBMI were explored using multilevel modelling, with measurement time (baseline and follow-up) at level 1, individual (behaviours, n = 1812) at level 2 and households (n = 1318) and schools (n = 18) as higher levels (environments). The effect of the intervention was tested while controlling for child age, gender and maternal education level. This study confirmed that the BAEW intervention lowered child zBMI compared with the comparison group (-0.085 units, P = 0.03). The variation between household environments was found to be a large contributor to the percentage of unexplained change in child zBMI (59%), compared with contributions from the individual (23%) and school levels (1%). Across both groups, screen time (P = 0.03), sweet drink consumption (P = 0.03) and lack of household rules for television (TV) viewing (P = 0.05) were associated with increased zBMI, whereas there was a non-significant association with the frequency the TV was on during evening meals (P = 0.07). The moderating effect of the intervention was only evident for the relationship between the frequency of TV on during meals and zBMI, however, this effect was modest (P = 0.04). The development of childhood obesity involves multi-factorial and multi-level influences, some of which are amenable to change. Obesity prevention strategies should not only target individual behaviours but also the household environment and family practices. Although zBMI changes were modest, these findings are encouraging as small reductions can have population level impacts on childhood obesity levels.

Are hotspots of evolutionary potential adequately protected in southern California?

USGS Publications Warehouse

Vandergast, A.G.; Bohonak, A.J.; Hathaway, S.A.; Boys, J.; Fisher, R.N.

2008-01-01

Reserves are often designed to protect rare habitats, or "typical" exemplars of ecoregions and geomorphic provinces. This approach focuses on current patterns of organismal and ecosystem-level biodiversity, but typically ignores the evolutionary processes that control the gain and loss of biodiversity at these and other levels (e.g., genetic, ecological). In order to include evolutionary processes in conservation planning efforts, their spatial components must first be identified and mapped. We describe a GIS-based approach for explicitly mapping patterns of genetic divergence and diversity for multiple species (a "multi-species genetic landscape"). Using this approach, we analyzed mitochondrial DNA datasets from 21 vertebrate and invertebrate species in southern California to identify areas with common phylogeographic breaks and high intrapopulation diversity. The result is an evolutionary framework for southern California within which patterns of genetic diversity can be analyzed in the context of historical processes, future evolutionary potential and current reserve design. Our multi-species genetic landscapes pinpoint six hotspots where interpopulation genetic divergence is consistently high, five evolutionary hotspots within which genetic connectivity is high, and three hotspots where intrapopulation genetic diversity is high. These 14 hotspots can be grouped into eight geographic areas, of which five largely are unprotected at this time. The multi-species genetic landscape approach may provide an avenue to readily incorporate measures of evolutionary process into GIS-based systematic conservation assessment and land-use planning.

Moving Evidence into Practice: Cost Analysis and Assessment of Macaques’ Sustained Behavioral Engagement with Videogames and Foraging Devices

PubMed Central

Bennett, Allyson J.; Perkins, Chaney M.; Tenpas, Parker D.; Reinebach, Alma L.; Pierre, Peter J.

2017-01-01

Environmental enrichment plans for captive nonhuman primates often include provision of foraging devices. The rationale for using foraging devices is to promote species-typical activity patterns that encourage physical engagement and provide multi-sensory stimulation. However, these devices have been shown to be ineffective at sustaining manipulation over long periods of time, and often produce minimal cognitive engagement. Here we use an evidence-based approach to directly compare the amount of object-directed behavior with a foraging device and a computer-based videogame system. We recorded 11adult male rhesus monkeys’ interactions with a foraging device and two tasks within a joystick videogame cognitive test battery. Both techniques successfully produced high levels of engagement during the initial 20-min of observation. After 1-hr the monkeys manipulated the foraging device significantly less than the joystick, F(2,10)= 43.93, p < .0001. Subsequent testing showed that the monkeys engaged in videogame play for the majority of a 5-hr period, provided that they received a 94mg chow pellet upon successful completion of trials. Using a model approach we developed previously as a basis for standardized cost:benefit analysis to inform facility decisions, we calculated the comprehensive cost of incorporating a videogame system as an enrichment strategy. The videogame system has a higher initial cost compared to widely-used foraging devices however, the ongoing labor and supply costs are relatively low. Our findings add to two decades of empirical studies by a number of laboratories that have demonstrated the successful use of videogame-based systems to promote sustained non-social cognitive engagement for macaques. The broader significance of the work lies in the application of a systematic approach to compare and contrast enrichment strategies and encourage evidence-based decision making when choosing an enrichment strategy in a manner that promotes meaningful cognitive enrichment to the animals. PMID:27404766

Moving evidence into practice: cost analysis and assessment of macaques' sustained behavioral engagement with videogames and foraging devices.

PubMed

Bennett, Allyson J; Perkins, Chaney M; Tenpas, Parker D; Reinebach, Alma L; Pierre, Peter J

2016-12-01

Environmental enrichment plans for captive nonhuman primates often include provision of foraging devices. The rationale for using foraging devices is to promote species-typical activity patterns that encourage physical engagement and provide multi-sensory stimulation. However, these devices have been shown to be ineffective at sustaining manipulation over long periods of time, and often produce minimal cognitive engagement. Here we use an evidence-based approach to directly compare the amount of object-directed behavior with a foraging device and a computer-based videogame system. We recorded 11 adult male rhesus monkeys' interactions with a foraging device and two tasks within a joystick videogame cognitive test battery. Both techniques successfully produced high levels of engagement during the initial 20 min of observation. After 1 hr the monkeys manipulated the foraging device significantly less than the joystick, F(2,10) = 43.93, P < 0.0001. Subsequent testing showed that the monkeys engaged in videogame play for the majority of a 5 hr period, provided that they received a 94 mg chow pellet upon successful completion of trials. Using a model approach, we developed previously as a basis for standardized cost:benefit analysis to inform facility decisions, we calculated the comprehensive cost of incorporating a videogame system as an enrichment strategy. The videogame system has a higher initial cost compared to widely-used foraging devices, however, the ongoing labor and supply costs are relatively low. Our findings add to two decades of empirical studies by a number of laboratories that have demonstrated the successful use of videogame-based systems to promote sustained non-social cognitive engagement for macaques. The broader significance of the work lies in the application of a systematic approach to compare and contrast enrichment strategies and encourage evidence-based decision making when choosing an enrichment strategy in a manner that promotes meaningful cognitive enrichment to the animals. © 2016 Wiley Periodicals, Inc.

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare.

PubMed

Dolan, James G

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers.Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine "hard data" with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings.The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP).

Multi-criteria clinical decision support: A primer on the use of multiple criteria decision making methods to promote evidence-based, patient-centered healthcare

PubMed Central

Dolan, James G.

2010-01-01

Current models of healthcare quality recommend that patient management decisions be evidence-based and patient-centered. Evidence-based decisions require a thorough understanding of current information regarding the natural history of disease and the anticipated outcomes of different management options. Patient-centered decisions incorporate patient preferences, values, and unique personal circumstances into the decision making process and actively involve both patients along with health care providers as much as possible. Fundamentally, therefore, evidence-based, patient-centered decisions are multi-dimensional and typically involve multiple decision makers. Advances in the decision sciences have led to the development of a number of multiple criteria decision making methods. These multi-criteria methods are designed to help people make better choices when faced with complex decisions involving several dimensions. They are especially helpful when there is a need to combine “hard data” with subjective preferences, to make trade-offs between desired outcomes, and to involve multiple decision makers. Evidence-based, patient-centered clinical decision making has all of these characteristics. This close match suggests that clinical decision support systems based on multi-criteria decision making techniques have the potential to enable patients and providers to carry out the tasks required to implement evidence-based, patient-centered care effectively and efficiently in clinical settings. The goal of this paper is to give readers a general introduction to the range of multi-criteria methods available and show how they could be used to support clinical decision-making. Methods discussed include the balance sheet, the even swap method, ordinal ranking methods, direct weighting methods, multi-attribute decision analysis, and the analytic hierarchy process (AHP) PMID:21394218

Occupational therapy in India: focus on functional recovery and need for empowerment

PubMed Central

Samuel, Reema; Jacob, K. S.

2017-01-01

While there have been significant advances in treatments for mental disorders over the past century, cure for many mental disorders remains elusive. The complex problems of mental illness require a multi-sectoral, multi-disciplinary and multi-dimensional approach to care. The need for focus on biopsychosocial model rather than on biomedical practise, client-centred rather than physician-oriented care, personal rather than clinical recovery, are often preached but rarely practiced. The lack of emphasis on functioning and the limited workforce and evidence base complicate issues related to the care of people with chronic mental illness in India. The role of occupational therapy in bridging the gap between symptomatic improvement and functional recovery is discussed. PMID:28827877

HIV Prevention Among Transgender Populations: Knowledge Gaps and Evidence for Action.

PubMed

Poteat, Tonia; Malik, Mannat; Scheim, Ayden; Elliott, Ayana

2017-08-01

The purpose of this review is to summarize the available evidence-based HIV prevention interventions tailored for transgender people. A limited number of evidence-based HIV prevention interventions have been tested with transgender populations. Most existing interventions target behavior change among transgender women, with only one HIV prevention program evaluated for transgender men. Studies addressing biomedical interventions for transgender women are ongoing. Few interventions address social and structural barriers to HIV prevention, such as stigma, discrimination, and poverty. Evidence-based multi-level interventions that address the structural, biomedical, and behavioral risks for HIV among transgender populations, including transgender men, are needed to address disparities in HIV prevalence. Future research should address not only pre-exposure prophylaxis uptake and condom use but also structural barriers that limit access to these prevention strategies.

Experimental evidence for excess entropy discontinuities in glass-forming solutions.

PubMed

Lienhard, Daniel M; Zobrist, Bernhard; Zuend, Andreas; Krieger, Ulrich K; Peter, Thomas

2012-02-21

Glass transition temperatures T(g) are investigated in aqueous binary and multi-component solutions consisting of citric acid, calcium nitrate (Ca(NO(3))(2)), malonic acid, raffinose, and ammonium bisulfate (NH(4)HSO(4)) using a differential scanning calorimeter. Based on measured glass transition temperatures of binary aqueous mixtures and fitted binary coefficients, the T(g) of multi-component systems can be predicted using mixing rules. However, the experimentally observed T(g) in multi-component solutions show considerable deviations from two theoretical approaches considered. The deviations from these predictions are explained in terms of the molar excess mixing entropy difference between the supercooled liquid and glassy state at T(g). The multi-component mixtures involve contributions to these excess mixing entropies that the mixing rules do not take into account. © 2012 American Institute of Physics

A Comprehensive Approach in Dissemination of Evidence Based Care for PTSD

DTIC Science & Technology

2010-09-01

evaluate their practices’ capacity to provide evidence-based care and identify potential gaps in the assessment and treatment of PTSD and depression...Project participants will use the PIP tools to evaluate their practices’ capacity to provide evidence-based care and identify potential gaps in the...PIP tools can inform improvement efforts at the clinician-, practice- or systems-level, facilitate detection of potential gaps in evidence-based care

Civilisation on the Couch: Theorising Multi-Levelled Psychoanalytical Arts Practice

ERIC Educational Resources Information Center

Benjamin, Garfield

2014-01-01

This paper combines two psychological approaches to art to theorise a both subjective and cultural methodology for practice-based arts research. The first psychoanalytical approach will follow the work of Deleuze and Guattari's Schizoanalysis, considering the role of the artist in order to assess their work in relation to society from an…

Together We STRIDE: A quasi-experimental trial testing the effectiveness of a multi-level obesity intervention for Hispanic children in rural communities.

PubMed

Ko, Linda K; Rillamas-Sun, Eileen; Bishop, Sonia; Cisneros, Oralia; Holte, Sarah; Thompson, Beti

2018-04-01

Hispanic children are disproportionally overweight and obese compared to their non-Hispanic white counterparts in the US. Community-wide, multi-level interventions have been successful to promote healthier nutrition, increased physical activity (PA), and weight loss. Using community-based participatory approach (CBPR) that engages community members in rural Hispanic communities is a promising way to promote behavior change, and ultimately weight loss among Hispanic children. Led by a community-academic partnership, the Together We STRIDE (Strategizing Together Relevant Interventions for Diet and Exercise) aims to test the effectiveness of a community-wide, multi-level intervention to promote healthier diets, increased PA, and weight loss among Hispanic children. The Together We STRIDE is a parallel quasi-experimental trial with a goal of recruiting 900 children aged 8-12 years nested within two communities (one intervention and one comparison). Children will be recruited from their respective elementary schools. Components of the 2-year multi-level intervention include comic books (individual-level), multi-generational nutrition and PA classes (family-level), teacher-led PA breaks and media literacy education (school-level), family nights, a farmer's market and a community PA event (known as ciclovia) at the community-level. Children from the comparison community will receive two newsletters. Height and weight measures will be collected from children in both communities at three time points (baseline, 6-months, and 18-months). The Together We STRIDE study aims to promote healthier diet and increased PA to produce healthy weight among Hispanic children. The use of CBPR approach and the engagement of the community will springboard strategies for intervention' sustainability. Clinical Trials Registration Number: NCT02982759 Retrospectively registered. Copyright © 2018 Elsevier Inc. All rights reserved.

Towards an Evidence-Based Approach to Tackling Health Inequalities: The English Experience

ERIC Educational Resources Information Center

Killoran, Amanda; Kelly, Michael

2004-01-01

This short paper considers the development of an evidence-based approach to tackling health inequalities. Inequalities in health in England at the beginning of the 21st century have widened and are stark. Despite overall improvements in death rates, the growing gap between social groups means that now some parts of England have the same levels of…

A hybrid solution approach for a multi-objective closed-loop logistics network under uncertainty

NASA Astrophysics Data System (ADS)

Mehrbod, Mehrdad; Tu, Nan; Miao, Lixin

2015-06-01

The design of closed-loop logistics (forward and reverse logistics) has attracted growing attention with the stringent pressures of customer expectations, environmental concerns and economic factors. This paper considers a multi-product, multi-period and multi-objective closed-loop logistics network model with regard to facility expansion as a facility location-allocation problem, which more closely approximates real-world conditions. A multi-objective mixed integer nonlinear programming formulation is linearized by defining new variables and adding new constraints to the model. By considering the aforementioned model under uncertainty, this paper develops a hybrid solution approach by combining an interactive fuzzy goal programming approach and robust counterpart optimization based on three well-known robust counterpart optimization formulations. Finally, this paper compares the results of the three formulations using different test scenarios and parameter-sensitive analysis in terms of the quality of the final solution, CPU time, the level of conservatism, the degree of closeness to the ideal solution, the degree of balance involved in developing a compromise solution, and satisfaction degree.

Neurogenic bowel management after spinal cord injury: A systematic review of the evidence

PubMed Central

Krassioukov, Andrei; Eng, Janice J.; Claxton, Geri; Sakakibara, Brodie M.; Shum, Serena

2011-01-01

OBJECTIVE To systematically review evidence for the management of neurogenic bowel in individuals with spinal cord injuries (SCI). DATA SOURCES Literature searches were conducted for relevant articles, as well as practice guidelines, using numerous electronic databases. Manual searches of retrieved articles from 1950 to July 2009 were also conducted to identify literature. STUDY SELECTION Randomized controlled trials, prospective cohort, case-control, and pre-post studies, and case reports that assessed pharmacological and non-pharmacological intervention for the management of the neurogenic bowel in SCI were included. DATA EXTRACTION Two independent reviewers evaluated each study’s quality, using the PEDro scale for RCTs and the Downs & Black scale for all other studies. Results were tabulated and levels of evidence assigned. DATA SYNTHESIS 2956 studies were found as a result of the literature search. Upon review of the titles and abstracts, 52 studies met the inclusion criteria. Multi-faceted programs are the first approach to neurogenic bowel and are supported by lower levels of evidence. Of the non-pharmacological (conservative and non-surgical) interventions, transanal irrigation is a promising treatment to reduce constipation and fecal incontinence. When conservative management is not effective, pharmacological interventions (e.g., prokinetic agents) are supported by strong evidence for the treatment of chronic constipation. When conservative and pharmacological treatments are not effective, surgical interventions may be considered and are supported by lower levels of evidence in reducing complications. CONCLUSIONS Often, more than one procedure is necessary to develop an effective bowel routine. Evidence is low for non-pharmacological approaches and high for pharmacological interventions. PMID:20212501

Enhancing evidence informed policymaking in complex health systems: lessons from multi-site collaborative approaches.

PubMed

Langlois, Etienne V; Becerril Montekio, Victor; Young, Taryn; Song, Kayla; Alcalde-Rabanal, Jacqueline; Tran, Nhan

2016-03-17

There is an increasing interest worldwide to ensure evidence-informed health policymaking as a means to improve health systems performance. There is a need to engage policymakers in collaborative approaches to generate and use knowledge in real world settings. To address this gap, we implemented two interventions based on iterative exchanges between researchers and policymakers/implementers. This article aims to reflect on the implementation and impact of these multi-site evidence-to-policy approaches implemented in low-resource settings. The first approach was implemented in Mexico and Nicaragua and focused on implementation research facilitated by communities of practice (CoP) among maternal health stakeholders. We conducted a process evaluation of the CoPs and assessed the professionals' abilities to acquire, analyse, adapt and apply research. The second approach, called the Policy BUilding Demand for evidence in Decision making through Interaction and Enhancing Skills (Policy BUDDIES), was implemented in South Africa and Cameroon. The intervention put forth a 'buddying' process to enhance demand and use of systematic reviews by sub-national policymakers. The Policy BUDDIES initiative was assessed using a mixed-methods realist evaluation design. In Mexico, the implementation research supported by CoPs triggered monitoring by local health organizations of the quality of maternal healthcare programs. Health programme personnel involved in CoPs in Mexico and Nicaragua reported improved capacities to identify and use evidence in solving implementation problems. In South Africa, Policy BUDDIES informed a policy framework for medication adherence for chronic diseases, including both HIV and non-communicable diseases. Policymakers engaged in the buddying process reported an enhanced recognition of the value of research, and greater demand for policy-relevant knowledge. The collaborative evidence-to-policy approaches underline the importance of iterations and continuity in the engagement of researchers and policymakers/programme managers, in order to account for swift evolutions in health policy planning and implementation. In developing and supporting evidence-to-policy interventions, due consideration should be given to fit-for-purpose approaches, as different needs in policymaking cycles require adapted processes and knowledge. Greater consideration should be provided to approaches embedding the use of research in real-world policymaking, better suited to the complex adaptive nature of health systems.

An innovative clinical practicum to teach evidence-based practice.

PubMed

Brancato, Vera C

2006-01-01

A clinical practicum was successfully implemented for RN to BSN students to apply evidence-based practice to actual clinical problems affecting nursing practice. The author describes how this practicum was implemented and the requisite resources and support systems. This senior-level capstone course enabled students to understand and value a lifelong learning approach to evidence-based practice.

Nutrient supplementation approaches in the treatment of ADHD.

PubMed

Rucklidge, Julia J; Johnstone, Jeanette; Kaplan, Bonnie J

2009-04-01

Attention-deficit/hyperactivity disorder (ADHD) is a chronic, debilitating psychiatric illness that often co-occurs with other common psychiatric problems. Although empirical evidence supports pharmacological and behavioral treatments, side effects, concerns regarding safety and fears about long-term use all contribute to families searching for alternative methods of treating the symptoms of ADHD. This review presents the published evidence on supplementation, including single ingredients (e.g., minerals, vitamins, amino acids and essential fatty acids), botanicals and multi-ingredient formulas in the treatment of ADHD symptoms. In most cases, evidence is sparse, mixed and lacking information. Of those supplements where we found published studies, the evidence is best for zinc (two positive randomized, controlled trials); there is mixed evidence for carnitine, pycnogenol and essential fatty acids, and more research is needed before drawing conclusions about vitamins, magnesium, iron, SAM-e, tryptophan and Ginkgo biloba with ginseng. To date, there is no evidence to support the use of St John's wort, tyrosine or phenylalanine in the treatment of ADHD symptoms. Multi-ingredient approaches are an intriguing yet under-researched area; we discuss the benefits of this approach considering the heterogeneous nature of ADHD.

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

PubMed

Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo

2018-05-10

Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.

Brain tissue segmentation based on DTI data

PubMed Central

Liu, Tianming; Li, Hai; Wong, Kelvin; Tarokh, Ashley; Guo, Lei; Wong, Stephen T.C.

2008-01-01

We present a method for automated brain tissue segmentation based on the multi-channel fusion of diffusion tensor imaging (DTI) data. The method is motivated by the evidence that independent tissue segmentation based on DTI parametric images provides complementary information of tissue contrast to the tissue segmentation based on structural MRI data. This has important applications in defining accurate tissue maps when fusing structural data with diffusion data. In the absence of structural data, tissue segmentation based on DTI data provides an alternative means to obtain brain tissue segmentation. Our approach to the tissue segmentation based on DTI data is to classify the brain into two compartments by utilizing the tissue contrast existing in a single channel. Specifically, because the apparent diffusion coefficient (ADC) values in the cerebrospinal fluid (CSF) are more than twice that of gray matter (GM) and white matter (WM), we use ADC images to distinguish CSF and non-CSF tissues. Additionally, fractional anisotropy (FA) images are used to separate WM from non-WM tissues, as highly directional white matter structures have much larger fractional anisotropy values. Moreover, other channels to separate tissue are explored, such as eigenvalues of the tensor, relative anisotropy (RA), and volume ratio (VR). We developed an approach based on the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm that combines these two-class maps to obtain a complete tissue segmentation map of CSF, GM, and WM. Evaluations are provided to demonstrate the performance of our approach. Experimental results of applying this approach to brain tissue segmentation and deformable registration of DTI data and spoiled gradient-echo (SPGR) data are also provided. PMID:17804258

Envisaging the use of evidence-based practice (EBP): how nurse academics facilitate EBP use in theory and practice across Australian undergraduate programmes.

PubMed

Malik, Gulzar; McKenna, Lisa; Griffiths, Debra

2017-09-01

This paper is drawn from a grounded theory study that aimed to investigate processes undertaken by academics when integrating evidence-based practice into undergraduate curricula. This paper focuses on how nurse academics facilitated students to apply evidence-based practice in theory and practice. Facilitating undergraduate nursing students to develop skills within an evidence-based practice framework is vital to achieving evidence-based care. Studies on evidence-based practice conducted globally suggests that there is a need to investigate approaches used by nurse academics in facilitating students' understanding and use of evidence-based practice during their nurse education. Employing constructivist grounded theory approach, 23 nurse academics across Australian universities were interviewed and nine observed during their teaching. Some study participants shared their unit guides to enrich analysis. Data analysis was performed by following Charmaz's approach of coding procedures; as a result, four categories were constructed. This paper focuses on the category conceptualised as Envisaging the use of evidence-based practice. Findings revealed that most academics-assisted students to use evidence in academic-related activities. Recognising the importance of evidence-based practice in practice, some also expected students to apply evidence-based practice during clinical experiences. However, the level of students' appreciation for evidence-based practice during clinical experiences was unknown to participants and was influenced by practice-related barriers. Acknowledging these challenges, academics were engaged in dialogue with students and suggested the need for academia-practice collaboration in combating the cited barriers. Ensuring academics are supported to emphasise clinical application of evidence-based practice requires strategies at school and practice levels. Faculty development, engagement of clinical nurses with evidence-based practice, supportive culture for nurses and students to apply evidence-based practice principles, and collaboration between academia and practice will make facilitation by academics practical and meaningful for students. Findings from this study point to a number of initiatives for clinical leadership to provide infrastructure and support for academics, practising nurses and undergraduate students to adopt evidence-based practice in practice settings, thereby influencing practice outcomes. © 2016 John Wiley & Sons Ltd.

Modular Approach to Therapy for Anxiety, Depression, Trauma, or Conduct Problems in outpatient child and adolescent mental health services in New Zealand: study protocol for a randomized controlled trial.

PubMed

Lucassen, Mathijs F G; Stasiak, Karolina; Crengle, Sue; Weisz, John R; Frampton, Christopher M A; Bearman, Sarah Kate; Ugueto, Ana M; Herren, Jennifer; Cribb-Su'a, Ainsleigh; Faleafa, Monique; Kingi-'Ulu'ave, Denise; Loy, Jik; Scott, Rebecca M; Hartdegen, Morgyn; Merry, Sally N

2015-10-12

Mental health disorders are common and disabling for young people because of the potential to disrupt key developmental tasks. Implementation of evidence-based psychosocial therapies in New Zealand is limited, owing to the inaccessibility, length, and cost of training in these therapies. Furthermore, most therapies address one problem area at a time, although comorbidity and changing clinical needs commonly occur in practice. A more flexible approach is needed. The Modular Approach to Therapy for Children with Anxiety, Depression, Trauma, or Conduct Problems (MATCH-ADTC) is designed to overcome these challenges; it provides a range of treatment modules addressing different problems, within a single training program. A clinical trial of MATCH-ADTC in the USA showed that MATCH-ADTC outperformed usual care and standard evidence-based treatment on several clinical measures. We aim to replicate these findings and evaluate the impact of providing training and supervision in MATCH-ADTC to: (1) improve clinical outcomes for youth attending mental health services; (2) increase the amount of evidence-based therapy content; (3) increase the efficiency of service delivery. This is an assessor-blinded multi-site effectiveness randomized controlled trial. Randomization occurs at two levels: (1) clinicians (≥60) are randomized to intervention or usual care; (2) youth participants (7-14 years old) accepted for treatment in child and adolescent mental health services (with a primary disorder that includes anxiety, depression, trauma-related symptoms, or disruptive behavior) are randomly allocated to receive MATCH-ADTC or usual care. Youth participants are recruited from 'mainstream', Māori-specific, and Pacific-specific child and adolescent mental health services. We originally planned to recruit 400 youth participants, but this has been revised to 200 participants. Centralized computer randomization ensures allocation concealment. The primary outcome measures are: (i) the difference in trajectory of change of clinical severity between groups (using the parent-rated Brief Problem Monitor); (ii) clinicians' use of evidence-based treatment procedures during therapy sessions; (iii) total time spent by clinicians delivering therapy. If MATCH-ADTC demonstrates effectiveness it could offer a practical efficient method to increase access to evidence-based therapies, and improve outcomes for youth attending secondary care services. Australian and New Zealand Clinical Trials Registry ACTRN12614000297628 .

Probabilistic Approaches for Multi-Hazard Risk Assessment of Structures and Systems

NASA Astrophysics Data System (ADS)

Kwag, Shinyoung

Performance assessment of structures, systems, and components for multi-hazard scenarios has received significant attention in recent years. However, the concept of multi-hazard analysis is quite broad in nature and the focus of existing literature varies across a wide range of problems. In some cases, such studies focus on hazards that either occur simultaneously or are closely correlated with each other. For example, seismically induced flooding or seismically induced fires. In other cases, multi-hazard studies relate to hazards that are not dependent or correlated but have strong likelihood of occurrence at different times during the lifetime of a structure. The current approaches for risk assessment need enhancement to account for multi-hazard risks. It must be able to account for uncertainty propagation in a systems-level analysis, consider correlation among events or failure modes, and allow integration of newly available information from continually evolving simulation models, experimental observations, and field measurements. This dissertation presents a detailed study that proposes enhancements by incorporating Bayesian networks and Bayesian updating within a performance-based probabilistic framework. The performance-based framework allows propagation of risk as well as uncertainties in the risk estimates within a systems analysis. Unlike conventional risk assessment techniques such as a fault-tree analysis, a Bayesian network can account for statistical dependencies and correlations among events/hazards. The proposed approach is extended to develop a risk-informed framework for quantitative validation and verification of high fidelity system-level simulation tools. Validation of such simulations can be quite formidable within the context of a multi-hazard risk assessment in nuclear power plants. The efficiency of this approach lies in identification of critical events, components, and systems that contribute to the overall risk. Validation of any event or component on the critical path is relatively more important in a risk-informed environment. Significance of multi-hazard risk is also illustrated for uncorrelated hazards of earthquakes and high winds which may result in competing design objectives. It is also illustrated that the number of computationally intensive nonlinear simulations needed in performance-based risk assessment for external hazards can be significantly reduced by using the power of Bayesian updating in conjunction with the concept of equivalent limit-state.

Elastic all-optical multi-hop interconnection in data centers with adaptive spectrum allocation

NASA Astrophysics Data System (ADS)

Hong, Yuanyuan; Hong, Xuezhi; Chen, Jiajia; He, Sailing

2017-01-01

In this paper, a novel flex-grid all-optical interconnect scheme that supports transparent multi-hop connections in data centers is proposed. An inter-rack all-optical multi-hop connection is realized with an optical loop employed at flex-grid wavelength selective switches (WSSs) in an intermediate rack rather than by relaying through optical-electric-optical (O-E-O) conversions. Compared with the conventional O-E-O based approach, the proposed all-optical scheme is able to off-load the traffic at intermediate racks, leading to a reduction of the power consumption and cost. The transmission performance of the proposed flex-grid multi-hop all-optical interconnect scheme with various modulation formats, including both coherently detected and directly detected approaches, are investigated by Monte-Carlo simulations. To enhance the spectrum efficiency (SE), number-of-hop adaptive bandwidth allocation is introduced. Numerical results show that the SE can be improved by up to 33.3% at 40 Gbps, and by up to 25% at 100 Gbps. The impact of parameters, such as targeted bit error rate (BER) level and insertion loss of components, on the transmission performance of the proposed approach are also explored. The results show that the maximum SE improvement of the adaptive approach over the non-adaptive one is enhanced with the decrease of the targeted BER levels and the component insertion loss.

Laser Measurements Based for Volumetric Accuracy Improvement of Multi-axis Systems

NASA Astrophysics Data System (ADS)

Vladimir, Sokolov; Konstantin, Basalaev

The paper describes a new developed approach to CNC-controlled multi-axis systems geometric errors compensation based on optimal error correction strategy. Multi-axis CNC-controlled systems - machine-tools and CMM's are the basis of modern engineering industry. Similar design principles of both technological and measurement equipment allow usage of similar approaches to precision management. The approach based on geometric errors compensation are widely used at present time. The paper describes a system for compensation of geometric errors of multi-axis equipment based on the new approach. The hardware basis of the developed system is a multi-function laser interferometer. The principles of system's implementation, results of measurements and system's functioning simulation are described. The effectiveness of application of described principles to multi-axis equipment of different sizes and purposes for different machining directions and zones within workspace is presented. The concepts of optimal correction strategy is introduced and dynamic accuracy control is proposed.

Using a multi-state Learning Community as an implementation strategy for immediate postpartum long-acting reversible contraception.

PubMed

DeSisto, Carla L; Estrich, Cameron; Kroelinger, Charlan D; Goodman, David A; Pliska, Ellen; Mackie, Christine N; Waddell, Lisa F; Rankin, Kristin M

2017-11-21

Implementation strategies are imperative for the successful adoption and sustainability of complex evidence-based public health practices. Creating a learning collaborative is one strategy that was part of a recently published compilation of implementation strategy terms and definitions. In partnership with the Centers for Disease Control and Prevention and other partner agencies, the Association of State and Territorial Health Officials recently convened a multi-state Learning Community to support cross-state collaboration and provide technical assistance for improving state capacity to increase access to long-acting reversible contraception (LARC) in the immediate postpartum period, an evidence-based practice with the potential for reducing unintended pregnancy and improving maternal and child health outcomes. During 2015-2016, the Learning Community included multi-disciplinary, multi-agency teams of state health officials, payers, clinicians, and health department staff from 13 states. This qualitative study was conducted to better understand the successes, challenges, and strategies that the 13 US states in the Learning Community used for increasing access to immediate postpartum LARC. We conducted telephone interviews with each team in the Learning Community. Interviews were semi-structured and organized by the eight domains of the Learning Community. We coded transcribed interviews for facilitators, barriers, and implementation strategies, using a recent compilation of expert-defined implementation strategies as a foundation for coding the latter. Data analysis showed three ways that the activities of the Learning Community helped in policy implementation work: structure and accountability, validity, and preparing for potential challenges and opportunities. Further, the qualitative data demonstrated that the Learning Community integrated six other implementation strategies from the literature: organize clinician implementation team meetings, conduct educational meetings, facilitation, promote network weaving, provide ongoing consultation, and distribute educational materials. Convening a multi-state learning collaborative is a promising approach for facilitating the implementation of new reimbursement policies for evidence-based practices complicated by systems challenges. By integrating several implementation strategies, the Learning Community serves as a meta-strategy for supporting implementation.

Operational considerations for the application of remotely sensed forest data from LANDSAT or other airborne platforms

NASA Technical Reports Server (NTRS)

Baker, G. R.; Fethe, T. P.

1975-01-01

Research in the application of remotely sensed data from LANDSAT or other airborne platforms to the efficient management of a large timber based forest industry was divided into three phases: (1) establishment of a photo/ground sample correlation, (2) investigation of techniques for multi-spectral digital analysis, and (3) development of a semi-automated multi-level sampling system. To properly verify results, three distinct test areas were selected: (1) Jacksonville Mill Region, Lower Coastal Plain, Flatwoods, (2) Pensacola Mill Region, Middle Coastal Plain, and (3) Mississippi Mill Region, Middle Coastal Plain. The following conclusions were reached: (1) the probability of establishing an information base suitable for management requirements through a photo/ground double sampling procedure, alleviating the ground sampling effort, is encouraging, (2) known classification techniques must be investigated to ascertain the level of precision possible in separating the many densities involved, and (3) the multi-level approach must be related to an information system that is executable and feasible.

Improving survey response rates from parents in school-based research using a multi-level approach.

PubMed

Schilpzand, Elizabeth J; Sciberras, Emma; Efron, Daryl; Anderson, Vicki; Nicholson, Jan M

2015-01-01

While schools can provide a comprehensive sampling frame for community-based studies of children and their families, recruitment is challenging. Multi-level approaches which engage multiple school stakeholders have been recommended but few studies have documented their effects. This paper compares the impact of a standard versus enhanced engagement approach on multiple indicators of recruitment: parent response rates, response times, reminders required and sample characteristics. Parents and teachers were distributed a brief screening questionnaire as a first step for recruitment to a longitudinal study, with two cohorts recruited in consecutive years (cohort 1 2011, cohort 2 2012). For cohort 2, additional engagement strategies included the use of pre-notification postcards, improved study materials, and recruitment progress graphs provided to school staff. Chi-square and t-tests were used to examine cohort differences. Compared to cohort 1, a higher proportion of cohort 2 parents responded to the survey (76% versus 69%; p < 0.001), consented to participate (71% versus 56%; p < 0.001), agreed to teacher participation (90% versus 82%; p < 0.001) and agreed to follow-up contact (91% versus 80%; p < 0.001). Fewer cohort 2 parents required reminders (52% versus 63%; p < 0.001), and cohort 2 parents responded more promptly than cohort 1 parents (mean difference: 19.4 days, 95% CI: 18.0 to 20.9, p < 0.001). These results illustrate the value of investing in a relatively simple multi-level strategy to maximise parent response rates, and potentially reduce recruitment time and costs.

Caring for patients with kidney disease: shifting the paradigm from evidence-based medicine to patient-centered care.

PubMed

O'Hare, Ann M; Rodriguez, Rudolph A; Bowling, Christopher Barrett

2016-03-01

The last several decades have witnessed the emergence of evidence-based medicine as the dominant paradigm for medical teaching, research and practice. Under an evidence-based approach, populations rather than individuals become the primary focus of investigation. Treatment priorities are largely shaped by the availability, relevance and quality of evidence and study outcomes and results are assumed to have more or less universal significance based on their implications at the population level. However, population-level treatment goals do not always align with what matters the most to individual patients-who may weigh the risks, benefits and harms of recommended treatments quite differently. In this article we describe the rise of evidence-based medicine in historical context. We discuss limitations of this approach for supporting real-world treatment decisions-especially in older adults with confluent comorbidity, functional impairment and/or limited life expectancy-and we describe the emergence of more patient-centered paradigms to address these limitations. We explain how the principles of evidence-based medicine have helped to shape contemporary approaches to defining, classifying and managing patients with chronic kidney disease. We discuss the limitations of this approach and the potential value of a more patient-centered paradigm, with a particular focus on the care of older adults with this condition. We conclude by outlining ways in which the evidence-base might be reconfigured to better support real-world treatment decisions in individual patients and summarize relevant ongoing initiatives. Published by Oxford University Press on behalf of ERA-EDTA 2015. This work is written by (a) US Government employee(s) and is in the public domain in the US.

A Comprehensive Approach in Dissemination of Evidence-Based Care for PTSD

DTIC Science & Technology

2011-09-01

facilitate practice evaluation and identification of potential gaps in care. APIRE staff have met with key clinical staff from select behavioral health...provide evidence-based care and identify potential gaps in care. Finally, strategies to implement the PCL-C, PHQ-9, and AUDIT-C for routine screening and...systems-level, facilitate detection of potential gaps in evidence-based care, and speed the adoption of evidence-based care into clinical practice

Foundations of modelling of nonequilibrium low-temperature plasmas

NASA Astrophysics Data System (ADS)

Alves, L. L.; Bogaerts, A.; Guerra, V.; Turner, M. M.

2018-02-01

This work explains the need for plasma models, introduces arguments for choosing the type of model that better fits the purpose of each study, and presents the basics of the most common nonequilibrium low-temperature plasma models and the information available from each one, along with an extensive list of references for complementary in-depth reading. The paper presents the following models, organised according to the level of multi-dimensional description of the plasma: kinetic models, based on either a statistical particle-in-cell/Monte-Carlo approach or the solution to the Boltzmann equation (in the latter case, special focus is given to the description of the electron kinetics); multi-fluid models, based on the solution to the hydrodynamic equations; global (spatially-average) models, based on the solution to the particle and energy rate-balance equations for the main plasma species, usually including a very complete reaction chemistry; mesoscopic models for plasma-surface interaction, adopting either a deterministic approach or a stochastic dynamical Monte-Carlo approach. For each plasma model, the paper puts forward the physics context, introduces the fundamental equations, presents advantages and limitations, also from a numerical perspective, and illustrates its application with some examples. Whenever pertinent, the interconnection between models is also discussed, in view of multi-scale hybrid approaches.

Communicating risk and promoting disease mitigation measures in epidemics and emerging disease settings

PubMed Central

Schiavo, Renata; Leung, May May; Brown, Mason

2014-01-01

Objective This review aims to identify and assess evidence on interventions to communicate risk and promote disease mitigation measures in epidemics and emerging disease outbreak settings. The study focuses on data that are relevant to low and middle-income country (LMIC) settings. Methods We conducted a comprehensive literature search using five major electronic databases (Pubmed Medline, Biomed Central, EMBASE, Science of Citation Index, and Cochrane Library) and other sources to identify relevant studies published from January 2002 to July 2013. The review was guided by the socio-ecological model/perspective of public health and the ideation theory and focused on interventions at the community, healthcare, and multi-sectoral settings, which also reflect key intervention levels of the Ottawa Charter for Health Promotion. Eligible quantitative studies were selected according to specific study criteria and assessed using the Critical Appraisal Skills Program (CASP) framework. Conversely, qualitative studies, reviews, case studies, and editorials were not included. Studies were selected by two independent reviewers. Results Twenty-nine relevant studies from 16 countries were included. Most studies focused on a single intervention or intervention level, rather than multi-sectoral interventions. The majority of the evidence relates to programs aimed at behavioral and social results (or relevant intermediate steps) within a specific population group. Two studies included implications for improvements in health service delivery, two studies examined the intervention’s impact on health systems-related outcomes, and three had also implications for environmental health outcomes. Cost- and health equity-related implications for select evidence were also discussed. Conclusions The paucity of well-designed quantitative evaluations of interventions to communicate health risk and promote disease control measures in LMICs does not allow for any definitive conclusions. Yet, the review identified several promising interventions and areas for future investigation. Among them, community-based and participatory interventions seemed to be central within epidemic and emerging disease settings, particularly in low-resource settings. Yet, evidence on their effectiveness is not conclusive and needs to be explored by future studies. Other promising areas for future investigation include multi-component and multi-sectoral approaches to intervention design. Major research gaps referred to any evaluation of the impact of these kinds of interventions on health policy adoption and/or implementation, and social determinants of health. Research on cost-effectiveness also needs to be strengthened. This review identified several research gaps and questions, and discusses potential future directions for increasing capacity for future and more rigorous assessments. PMID:24649867

Communicating risk and promoting disease mitigation measures in epidemics and emerging disease settings.

PubMed

Schiavo, Renata; May Leung, May; Brown, Mason

2014-03-01

This review aims to identify and assess evidence on interventions to communicate risk and promote disease mitigation measures in epidemics and emerging disease outbreak settings. The study focuses on data that are relevant to low and middle-income country (LMIC) settings. We conducted a comprehensive literature search using five major electronic databases (Pubmed Medline, Biomed Central, EMBASE, Science of Citation Index, and Cochrane Library) and other sources to identify relevant studies published from January 2002 to July 2013. The review was guided by the socio-ecological model/perspective of public health and the ideation theory and focused on interventions at the community, healthcare, and multi-sectoral settings, which also reflect key intervention levels of the Ottawa Charter for Health Promotion. Eligible quantitative studies were selected according to specific study criteria and assessed using the Critical Appraisal Skills Program (CASP) framework. Conversely, qualitative studies, reviews, case studies, and editorials were not included. Studies were selected by two independent reviewers. Twenty-nine relevant studies from 16 countries were included. Most studies focused on a single intervention or intervention level, rather than multi-sectoral interventions. The majority of the evidence relates to programs aimed at behavioral and social results (or relevant intermediate steps) within a specific population group. Two studies included implications for improvements in health service delivery, two studies examined the intervention's impact on health systems-related outcomes, and three had also implications for environmental health outcomes. Cost- and health equity-related implications for select evidence were also discussed. The paucity of well-designed quantitative evaluations of interventions to communicate health risk and promote disease control measures in LMICs does not allow for any definitive conclusions. Yet, the review identified several promising interventions and areas for future investigation. Among them, community-based and participatory interventions seemed to be central within epidemic and emerging disease settings, particularly in low-resource settings. Yet, evidence on their effectiveness is not conclusive and needs to be explored by future studies. Other promising areas for future investigation include multi-component and multi-sectoral approaches to intervention design. Major research gaps referred to any evaluation of the impact of these kinds of interventions on health policy adoption and/or implementation, and social determinants of health. Research on cost-effectiveness also needs to be strengthened. This review identified several research gaps and questions, and discusses potential future directions for increasing capacity for future and more rigorous assessments.

"Staying safe" - a narrative review of falls prevention in people with Parkinson's - "PDSAFE".

PubMed

Hulbert, Sophia; Rochester, Lynn; Nieuwboer, Alice; Goodwin, Vicki; Fitton, Carolyn; Chivers-Seymour, Kim; Ashburn, Ann

2018-05-18

Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms. Falling is common and disabling. Current medical management shows minimal impact to reduce falls or fall-related risk factors, such as deficits in gait, strength, and postural instability. Despite evidence supporting rehabilitation in reducing fall risk factors, the most appropriate intervention to reduce overall fall rate remains inconclusive. This article aims to 1) synthesise current evidence and conceptual models of falls rehabilitation in Parkinson's in a narrative review; and based on this evidence, 2) introduce the treatment protocol used in the falls prevention and multi-centre clinical trial "PDSAFE". Search of four bibliographic databases using the terms "Parkinson*" and "Fall*" combined with each of the following; "Rehab*, Balanc*, Strength*, Strateg*and Exercis*" and a framework for narrative review was followed. A total of 3557 papers were identified, 416 were selected for review. The majority report the impact of rehabilitation on isolated fall risk factors. Twelve directly measure the impact on overall fall rate. Results were used to construct a narrative review with conceptual discussion based on the "International Classification of Functioning", leading to presentation of the "PDSAFE" intervention protocol. Evidence suggests training single, fall risk factors may not affect overall fall rate. Combining with behavioural and strategy training in a functional, personalised multi-dimensional model, addressing all components of the "International Classification of Functioning" is likely to provide a greater influence on falls reduction. "PDSAFE" is a multi-dimensional, physiotherapist delivered, individually tailored, progressive, home-based programme. It is designed with a strong evidence-based approach and illustrates a model for the clinical delivery of the conceptual theory discussed. Implications for Rehabilitation Parkinson's disease demonstrates a spectrum of motor and non-motor symptoms, where falling is common and disabling. Current medical and surgical management have minimal impact on falls, rehabilitation of falls risk factors has strong evidence but the most appropriate intervention to reduce overall fall rate remains inconclusive. Addressing all components of the International Classification of Function in a multifactorial model when designing falls rehabilitation interventions may be more effective at reducing fall rates in people with Parkinson's than treating isolated risk factors. The clinical model for falls rehabilitation in people with Parkinson's should be multi-dimensional.

What China's experiment in community building can tell us about tackling health disparities: community building and mental health in mid-life and older life: evidence from China.

PubMed

Muennig, Peter

2014-04-01

Disparities in physical and mental health between advantaged and disadvantaged communities are among the largest threats to population health worldwide. These disparities appear to be growing, probably in part because we do not understand how to address their underlying causes. Many believe the underlying causes are thought to arise directly or indirectly from the psychosocial problems underlying poverty, such as hunger, poor housing, drug use, or crime. One logical solution is therefore to provide more community services targeted at addressing these problems within the most disadvantaged communities. However, to date, data on the efficacy of this approach is lacking. China serves as a possible laboratory for studying the efficacy of community-based programs. This is because the extensive community-based programs present prior to economic reforms in 1978 were removed, and then later re-instated in a quasi-experimental manner. In this issue, Yuying Shen uses multi-level models to explore the impact of this experiment on community mental health in a multi-level associational study. She finds that the quantity (but not their length of time in the community) of such services is positively associated with mental health. This study opens the door to more rigorous analyses that might motivate formal social experiments at the community level worldwide. If successful, such experiments might not only transform what we currently know not just about improving health in disadvantaged communities, but also prove transformative for health policy as a discipline. Copyright © 2014 Elsevier Ltd. All rights reserved.

Developing an Evidence Base for Policies and Interventions to Address Health Inequalities: The Analysis of “Public Health Regimes”

PubMed Central

Asthana, Sheena; Halliday, Joyce

2006-01-01

Systematic reviews have become an important methodology in the United Kingdom by which research informs health policy, and their use now extends beyond evidence-based medicine to evidence-based public health and, particularly, health inequalities policies. This article reviews the limitations of systematic reviews as stand-alone tools for this purpose and suggests a complementary approach to make better use of the evidence. That is, systematic reviews and other sources of evidence should be incorporated into a wider analytical framework, the public health regime (defined here as the specific legislative, social, political, and economic structures that have an impact on both public health and the appropriateness and effectiveness of public health interventions adopted). At the national level this approach would facilitate analysis at all levels of the policy framework, countering the current focus on individual interventions. It could also differentiate at the international level between those policies and interventions that are effective in different contexts and are therefore potentially generalizable and those that depend on particular conditions for success. PMID:16953811

Biomarker responses to environmental contamination in estuaries: A comparative multi-taxa approach.

PubMed

Duarte, Irina A; Reis-Santos, Patrick; França, Susana; Cabral, Henrique; Fonseca, Vanessa F

2017-08-01

Estuaries are highly productive ecosystems subjected to numerous anthropogenic pressures with consequent environmental quality degradation. In this study, multiple biomarker responses [superoxide dismutase (SOD), catalase (CAT), ethoxyresorufin O-deethylase (EROD) and glutathione S-transferase (GST) activities, as well as lipid peroxidation (LPO) and DNA damage (DNAd)] were determined in two fish (Dicentrarchus labrax and Pomatoschistus microps) and four macroinvertebrate species (Carcinus maenas, Crangon crangon, Hediste diversicolor and Scrobicularia plana) from the Ria de Aveiro and Tejo estuaries over distinct months. Two sites per estuarine system were selected based on anthropogenic pressures and magnitude of environmental contamination. Antioxidant enzyme activities in fish species suggested a ubiquitous response to oxidative stress, while biotransformation and effect biomarkers exhibited higher spatial and temporal variation. In invertebrate species, biotransformation enzyme activity was clearly less variable than in fish evidencing lower xenobiotic transformation capability. Overall, largest biomarker responses were found in the most contaminated sites (Tejo), yet species-specific patterns were evident. These should be factored in multi-taxa approaches, considering that the differential functional traits of species, such as habitat use, life-stage, feeding or physiology can influence exposure routes and biomarker responses. The Integrated Biomarker Response index highlighted patterns in biomarker responses which were not immediately evident when analyzing biomarkers individually. Overall, results provided insights into the complexity of species responses to contamination in naturally varying estuarine environments. Ultimately, multi-taxa and multi-biomarker approaches provide a comprehensive and complementary view of ecosystem health, encompassing diverse forms of biological integration and exposure routes, and allow the validation of results among markers and species. Copyright © 2017 Elsevier B.V. All rights reserved.

Discovering disease-disease associations by fusing systems-level molecular data

PubMed Central

Žitnik, Marinka; Janjić, Vuk; Larminie, Chris; Zupan, Blaž; Pržulj, Nataša

2013-01-01

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion. PMID:24232732

Discovering disease-disease associations by fusing systems-level molecular data.

PubMed

Žitnik, Marinka; Janjić, Vuk; Larminie, Chris; Zupan, Blaž; Pržulj, Nataša

2013-11-15

The advent of genome-scale genetic and genomic studies allows new insight into disease classification. Recently, a shift was made from linking diseases simply based on their shared genes towards systems-level integration of molecular data. Here, we aim to find relationships between diseases based on evidence from fusing all available molecular interaction and ontology data. We propose a multi-level hierarchy of disease classes that significantly overlaps with existing disease classification. In it, we find 14 disease-disease associations currently not present in Disease Ontology and provide evidence for their relationships through comorbidity data and literature curation. Interestingly, even though the number of known human genetic interactions is currently very small, we find they are the most important predictor of a link between diseases. Finally, we show that omission of any one of the included data sources reduces prediction quality, further highlighting the importance in the paradigm shift towards systems-level data fusion.

A Multi-Cultural Transformative Approach to Learning: Assessing Attitude Change in Doctoral Students following an Online Diversity Course

ERIC Educational Resources Information Center

Enger, Kathy; Lajimodiere, Denise

2011-01-01

Purpose: The purpose of this paper is to examine the attitudes of students following the completion of an online doctoral level multicultural diversity course at a university in the Midwestern USA based on Banks' transformative approach to learning in an effort to determine if the online environment could successfully intervene to change student…

MLP: A Parallel Programming Alternative to MPI for New Shared Memory Parallel Systems

NASA Technical Reports Server (NTRS)

Taft, James R.

1999-01-01

Recent developments at the NASA AMES Research Center's NAS Division have demonstrated that the new generation of NUMA based Symmetric Multi-Processing systems (SMPs), such as the Silicon Graphics Origin 2000, can successfully execute legacy vector oriented CFD production codes at sustained rates far exceeding processing rates possible on dedicated 16 CPU Cray C90 systems. This high level of performance is achieved via shared memory based Multi-Level Parallelism (MLP). This programming approach, developed at NAS and outlined below, is distinct from the message passing paradigm of MPI. It offers parallelism at both the fine and coarse grained level, with communication latencies that are approximately 50-100 times lower than typical MPI implementations on the same platform. Such latency reductions offer the promise of performance scaling to very large CPU counts. The method draws on, but is also distinct from, the newly defined OpenMP specification, which uses compiler directives to support a limited subset of multi-level parallel operations. The NAS MLP method is general, and applicable to a large class of NASA CFD codes.

Multi-level molecular modelling for plasma medicine

NASA Astrophysics Data System (ADS)

Bogaerts, Annemie; Khosravian, Narjes; Van der Paal, Jonas; Verlackt, Christof C. W.; Yusupov, Maksudbek; Kamaraj, Balu; Neyts, Erik C.

2016-02-01

Modelling at the molecular or atomic scale can be very useful for obtaining a better insight in plasma medicine. This paper gives an overview of different atomic/molecular scale modelling approaches that can be used to study the direct interaction of plasma species with biomolecules or the consequences of these interactions for the biomolecules on a somewhat longer time-scale. These approaches include density functional theory (DFT), density functional based tight binding (DFTB), classical reactive and non-reactive molecular dynamics (MD) and united-atom or coarse-grained MD, as well as hybrid quantum mechanics/molecular mechanics (QM/MM) methods. Specific examples will be given for three important types of biomolecules, present in human cells, i.e. proteins, DNA and phospholipids found in the cell membrane. The results show that each of these modelling approaches has its specific strengths and limitations, and is particularly useful for certain applications. A multi-level approach is therefore most suitable for obtaining a global picture of the plasma-biomolecule interactions.

A Model-Based Approach to Predicting Graduate-Level Performance Using Indicators of Undergraduate-Level Performance

ERIC Educational Resources Information Center

Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M.

2015-01-01

The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…

Multi-Dimensional Deprivation in India during and after the Reforms: Do the Household Expenditure and the Family Health Surveys Present Consistent Evidence?

ERIC Educational Resources Information Center

Mishra, Ankita; Ray, Ranjan

2013-01-01

This paper uses the recent approach of multidimensional deprivation measures to provide a comprehensive and wide ranging assessment of changes to living standards in India during the period, 1992/93-2004/5. This covers the reforms and the immediate post reforms time periods. The study is the first to be based on the simultaneous use of two…

Applicability and feasibility of systematic review for performing evidence-based risk assessment in food and feed safety.

PubMed

Aiassa, E; Higgins, J P T; Frampton, G K; Greiner, M; Afonso, A; Amzal, B; Deeks, J; Dorne, J-L; Glanville, J; Lövei, G L; Nienstedt, K; O'connor, A M; Pullin, A S; Rajić, A; Verloo, D

2015-01-01

Food and feed safety risk assessment uses multi-parameter models to evaluate the likelihood of adverse events associated with exposure to hazards in human health, plant health, animal health, animal welfare, and the environment. Systematic review and meta-analysis are established methods for answering questions in health care, and can be implemented to minimize biases in food and feed safety risk assessment. However, no methodological frameworks exist for refining risk assessment multi-parameter models into questions suitable for systematic review, and use of meta-analysis to estimate all parameters required by a risk model may not be always feasible. This paper describes novel approaches for determining question suitability and for prioritizing questions for systematic review in this area. Risk assessment questions that aim to estimate a parameter are likely to be suitable for systematic review. Such questions can be structured by their "key elements" [e.g., for intervention questions, the population(s), intervention(s), comparator(s), and outcome(s)]. Prioritization of questions to be addressed by systematic review relies on the likely impact and related uncertainty of individual parameters in the risk model. This approach to planning and prioritizing systematic review seems to have useful implications for producing evidence-based food and feed safety risk assessment.

Efficacy of a modern neuroscience approach versus usual care evidence-based physiotherapy on pain, disability and brain characteristics in chronic spinal pain patients: protocol of a randomized clinical trial

PubMed Central

2014-01-01

Background Among the multiple conservative modalities, physiotherapy is a commonly utilized treatment modality in managing chronic non-specific spinal pain. Despite the scientific progresses with regard to pain and motor control neuroscience, treatment of chronic spinal pain (CSP) often tends to stick to a peripheral biomechanical model, without targeting brain mechanisms. With a view to enhance clinical efficacy of existing physiotherapeutic treatments for CSP, the development of clinical strategies targeted at ‘training the brain’ is to be pursued. Promising proof-of-principle results have been reported for the effectiveness of a modern neuroscience approach to CSP when compared to usual care, but confirmation is required in a larger, multi-center trial with appropriate evidence-based control intervention and long-term follow-up. The aim of this study is to assess the effectiveness of a modern neuroscience approach, compared to usual care evidence-based physiotherapy, for reducing pain and improving functioning in patients with CSP. A secondary objective entails examining the effectiveness of the modern neuroscience approach versus usual care physiotherapy for normalizing brain gray matter in patients with CSP. Methods/Design The study is a multi-center, triple-blind, two-arm (1:1) randomized clinical trial with 1-year follow-up. 120 CSP patients will be randomly allocated to either the experimental (receiving pain neuroscience education followed by cognition-targeted motor control training) or the control group (receiving usual care physiotherapy), each comprising of 3 months treatment. The main outcome measures are pain (including symptoms and indices of central sensitization) and self-reported disability. Secondary outcome measures include brain gray matter structure, motor control, muscle properties, and psychosocial correlates. Clinical assessment and brain imaging will be performed at baseline, post-treatment and at 1-year follow-up. Web-based questionnaires will be completed at baseline, after the first 3 treatment sessions, post-treatment, and at 6 and 12-months follow-up. Discussion Findings may provide empirical evidence on: (1) the effectiveness of a modern neuroscience approach to CSP for reducing pain and improving functioning, (2) the effectiveness of a modern neuroscience approach for normalizing brain gray matter in CSP patients, and (3) factors associated with therapy success. Hence, this trial might contribute towards refining guidelines for good clinical practice and might be used as a basis for health authorities’ recommendations. Trial registration ClinicalTrials.gov Identifier: NCT02098005. PMID:24885889

Probabilistic performance-based design for high performance control systems

NASA Astrophysics Data System (ADS)

Micheli, Laura; Cao, Liang; Gong, Yongqiang; Cancelli, Alessandro; Laflamme, Simon; Alipour, Alice

2017-04-01

High performance control systems (HPCS) are advanced damping systems capable of high damping performance over a wide frequency bandwidth, ideal for mitigation of multi-hazards. They include active, semi-active, and hybrid damping systems. However, HPCS are more expensive than typical passive mitigation systems, rely on power and hardware (e.g., sensors, actuators) to operate, and require maintenance. In this paper, a life cycle cost analysis (LCA) approach is proposed to estimate the economic benefit these systems over the entire life of the structure. The novelty resides in the life cycle cost analysis in the performance based design (PBD) tailored to multi-level wind hazards. This yields a probabilistic performance-based design approach for HPCS. Numerical simulations are conducted on a building located in Boston, MA. LCA are conducted for passive control systems and HPCS, and the concept of controller robustness is demonstrated. Results highlight the promise of the proposed performance-based design procedure.

A decentralised multi-agent approach to enhance the stability of smart microgrids with renewable energy

NASA Astrophysics Data System (ADS)

Rahman, M. S.; Pota, H. R.; Mahmud, M. A.; Hossain, M. J.

2016-05-01

This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.

Practical approach to the gastrointestinal manifestations of cystic fibrosis.

PubMed

Bolia, Rishi; Ooi, Chee Y; Lewindon, Peter; Bishop, Jonathan; Ranganathan, Sarath; Harrison, Jo; Ford, Kristyn; van der Haak, Natalie; Oliver, Mark R

2018-05-16

Cystic fibrosis (CF) is the most common, life-shortening, genetic illness affecting children in Australia and New Zealand. The genetic abnormality results in abnormal anion transport across the apical membrane of epithelial cells in a number of organs, including the lungs, gastrointestinal tract, liver and genito-urinary tract. Thus, CF is a multi-system disorder that requires a multi-disciplinary approach. Respiratory disease is the predominant cause of both morbidity and mortality in patients with CF. However, there are significant and clinically relevant gastrointestinal, liver, pancreatic and nutritional manifestations that must be detected and managed in a timely and structured manner. The aim of this review is to provide evidence-based information and clinical algorithms to guide the nutritional and gastrointestinal management of patients with CF. © 2018 Paediatrics and Child Health Division (The Royal Australasian College of Physicians).

Hierarchical graphical-based human pose estimation via local multi-resolution convolutional neural network

NASA Astrophysics Data System (ADS)

Zhu, Aichun; Wang, Tian; Snoussi, Hichem

2018-03-01

This paper addresses the problems of the graphical-based human pose estimation in still images, including the diversity of appearances and confounding background clutter. We present a new architecture for estimating human pose using a Convolutional Neural Network (CNN). Firstly, a Relative Mixture Deformable Model (RMDM) is defined by each pair of connected parts to compute the relative spatial information in the graphical model. Secondly, a Local Multi-Resolution Convolutional Neural Network (LMR-CNN) is proposed to train and learn the multi-scale representation of each body parts by combining different levels of part context. Thirdly, a LMR-CNN based hierarchical model is defined to explore the context information of limb parts. Finally, the experimental results demonstrate the effectiveness of the proposed deep learning approach for human pose estimation.

Multi-Decadal Coastal Behavioural States From A Fusion Of Geohistorical Conceptual Modelling With 2-D Morphodynamic Modelling

NASA Astrophysics Data System (ADS)

Goodwin, I. D.; Mortlock, T.

2016-02-01

Geohistorical archives of shoreline and foredune planform geometry provides a unique evidence-based record of the time integral response to coupled directional wave climate and sediment supply variability on annual to multi-decadal time scales. We develop conceptual shoreline modelling from the geohistorical shoreline archive using a novel combination of methods, including: LIDAR DEM and field mapping of coastal geology; a decadal-scale climate reconstruction of sea-level pressure, marine windfields, and paleo-storm synoptic type and frequency, and historical bathymetry. The conceptual modelling allows for the discrimination of directional wave climate shifts and the relative contributions of cross-shore and along-shore sand supply rates at multi-decadal resolution. We present regional examples from south-eastern Australia over a large latitudinal gradient from subtropical Queensland (S 25°) to mid-latitude Bass Strait (S 40°) that illustrate the morphodynamic evolution and reorganization to wave climate change. We then use the conceptual modeling to inform a two-dimensional coupled spectral wave-hydrodynamic-morphodynamic model to investigate the shoreface response to paleo-directional wind and wave climates. Unlike one-line shoreline modelling, this fully dynamical approach allows for the investigation of cumulative and spatial bathymetric change due to wave-induced currents, as well as proxy-shoreline change. The fusion of the two modeling approaches allows for: (i) the identification of the natural range of coastal planform geometries in response to wave climate shifts; and, (ii) the decomposition of the multidecadal coastal change into the cross-shore and along-shore sand supply drivers, according to the best-matching planforms.

The incorporation of emotion-regulation skills into couple- and family-based treatments for post-traumatic stress disorder.

PubMed

Perlick, Deborah A; Sautter, Frederic J; Becker-Cretu, Julia J; Schultz, Danielle; Grier, Savannah C; Libin, Alexander V; Schladen, Manon Maitland; Glynn, Shirley M

2017-01-01

Post-traumatic stress disorder (PTSD) is a disabling, potentially chronic disorder that is characterized by re-experience and hyperarousal symptoms as well as the avoidance of trauma-related stimuli. The distress experienced by many veterans of the Vietnam War and their partners prompted a strong interest in developing conjoint interventions that could both alleviate the core symptoms of PTSD and strengthen family bonds. We review the evolution of and evidence base for conjoint PTSD treatments from the Vietnam era through the post-911 era. Our review is particularly focused on the use of treatment strategies that are designed to address the emotions that are generated by the core symptoms of the disorder to reduce their adverse impact on veterans, their partners and the relationship. We present a rationale and evidence to support the direct incorporation of emotion-regulation skills training into conjoint interventions for PTSD. We begin by reviewing emerging evidence suggesting that high levels of emotion dysregulation are characteristic of and predict the severity of both PTSD symptoms and the level of interpersonal/marital difficulties reported by veterans with PTSD and their family members. In doing so, we present a compelling rationale for the inclusion of formal skills training in emotional regulation in couple-/family-based PTSD treatments. We further argue that increased exposure to trauma-related memories and emotions in treatments based on learning theory requires veterans and their partners to learn to manage the uncomfortable emotions that they previously avoided. Conjoint treatments that were developed in the last 30 years all acknowledge the importance of emotions in PTSD but vary widely in their relative emphasis on helping participants to acquire strategies to modulate them compared to other therapeutic tasks such as learning about the disorder or disclosing the trauma to a loved one. We conclude our review by describing two recent innovative treatments for PTSD that incorporate a special emphasis on emotion-regulation skills training in the dyadic context: structured approach therapy (SAT) and multi-family group for military couples (MFG-MC). Although the incorporation of emotion-regulation skills into conjoint PTSD therapies appears promising, replication and comparison to cognitive-behavioral approaches is needed to refine our understanding of which symptoms and veterans might be more responsive to one approach versus others.

Implementation of a multi-professional standardized care plan in electronic health records for the care of stroke patients.

PubMed

Pöder, Ulrika; Fogelberg-Dahm, Marie; Wadensten, Barbro

2011-09-01

To compare staff opinions about standardized care plans and self-reported habits with regard to documentation, and their perceived knowledge about the evidence-based guidelines in stroke care before and after implementation of an evidence-based-standardized care plan (EB-SCP) and quality standard for stroke care. The aim was also to describe staff opinions about, and their use of, the implemented EB-SCP. To facilitate evidence-based practice (EBP), a multi-professional EB-SCP and quality standard for stroke care was implemented in the electronic health record (EHR). Quantitative, descriptive and comparative, based on questionnaires completed before and after implementation. Perceived knowledge about evidence-based guidelines in stroke care increased after implementation of the EB-SCP. The majority agreed that the EB-SCP is useful and facilitates their work. There was no change between before and after implementation with regard to opinions about standardized care plans, self-reported documentation habits or time spent on documentation. An evidence-based SCP seems to be useful in patient care and improves perceived knowledge about evidence-based guidelines in stroke care. For nursing managers, introduction of evidence-based SCP in the EHR may improve the prerequisites for promoting high-quality EBP in multi-professional care. 2011 Blackwell Publishing Ltd.

A scale-based approach to interdisciplinary research and expertise in sports.

PubMed

Ibáñez-Gijón, Jorge; Buekers, Martinus; Morice, Antoine; Rao, Guillaume; Mascret, Nicolas; Laurin, Jérome; Montagne, Gilles

2017-02-01

After more than 20 years since the introduction of ecological and dynamical approaches in sports research, their promising opportunity for interdisciplinary research has not been fulfilled yet. The complexity of the research process and the theoretical and empirical difficulties associated with an integrated ecological-dynamical approach have been the major factors hindering the generalisation of interdisciplinary projects in sports sciences. To facilitate this generalisation, we integrate the major concepts from the ecological and dynamical approaches to study behaviour as a multi-scale process. Our integration gravitates around the distinction between functional (ecological) and execution (organic) scales, and their reciprocal intra- and inter-scale constraints. We propose an (epistemological) scale-based definition of constraints that accounts for the concept of synergies as emergent coordinative structures. To illustrate how we can operationalise the notion of multi-scale synergies we use an interdisciplinary model of locomotor pointing. To conclude, we show the value of this approach for interdisciplinary research in sport sciences, as we discuss two examples of task-specific dimensionality reduction techniques in the context of an ongoing project that aims to unveil the determinants of expertise in basketball free throw shooting. These techniques provide relevant empirical evidence to help bootstrap the challenging modelling efforts required in sport sciences.

Multi-day activity scheduling reactions to planned activities and future events in a dynamic model of activity-travel behavior

NASA Astrophysics Data System (ADS)

Nijland, Linda; Arentze, Theo; Timmermans, Harry

2014-01-01

Modeling multi-day planning has received scarce attention in activity-based transport demand modeling so far. However, new dynamic activity-based approaches are being developed at the current moment. The frequency and inflexibility of planned activities and events in activity schedules of individuals indicate the importance of incorporating those pre-planned activities in the new generation of dynamic travel demand models. Elaborating and combining previous work on event-driven activity generation, the aim of this paper is to develop and illustrate an extension of a need-based model of activity generation that takes into account possible influences of pre-planned activities and events. This paper describes the theory and shows the results of simulations of the extension. The simulation was conducted for six different activities, and the parameter values used were consistent with an earlier estimation study. The results show that the model works well and that the influences of the parameters are consistent, logical, and have clear interpretations. These findings offer further evidence of face and construct validity to the suggested modeling approach.

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

Uddin, Shahadat

2016-02-04

A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE Office of Scientific and Technical Information (OSTI.GOV)

He, Xu; Tuo, Rui; Jeff Wu, C. F.

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

Optimization of Multi-Fidelity Computer Experiments via the EQIE Criterion

DOE PAGES

He, Xu; Tuo, Rui; Jeff Wu, C. F.

2017-01-31

Computer experiments based on mathematical models are powerful tools for understanding physical processes. This article addresses the problem of kriging-based optimization for deterministic computer experiments with tunable accuracy. Our approach is to use multi- delity computer experiments with increasing accuracy levels and a nonstationary Gaussian process model. We propose an optimization scheme that sequentially adds new computer runs by following two criteria. The first criterion, called EQI, scores candidate inputs with given level of accuracy, and the second criterion, called EQIE, scores candidate combinations of inputs and accuracy. Here, from simulation results and a real example using finite element analysis,more » our method out-performs the expected improvement (EI) criterion which works for single-accuracy experiments.« less

An evidence-based public health approach to climate change adaptation.

PubMed

Hess, Jeremy J; Eidson, Millicent; Tlumak, Jennifer E; Raab, Kristin K; Luber, George

2014-11-01

Public health is committed to evidence-based practice, yet there has been minimal discussion of how to apply an evidence-based practice framework to climate change adaptation. Our goal was to review the literature on evidence-based public health (EBPH), to determine whether it can be applied to climate change adaptation, and to consider how emphasizing evidence-based practice may influence research and practice decisions related to public health adaptation to climate change. We conducted a substantive review of EBPH, identified a consensus EBPH framework, and modified it to support an EBPH approach to climate change adaptation. We applied the framework to an example and considered implications for stakeholders. A modified EBPH framework can accommodate the wide range of exposures, outcomes, and modes of inquiry associated with climate change adaptation and the variety of settings in which adaptation activities will be pursued. Several factors currently limit application of the framework, including a lack of higher-level evidence of intervention efficacy and a lack of guidelines for reporting climate change health impact projections. To enhance the evidence base, there must be increased attention to designing, evaluating, and reporting adaptation interventions; standardized health impact projection reporting; and increased attention to knowledge translation. This approach has implications for funders, researchers, journal editors, practitioners, and policy makers. The current approach to EBPH can, with modifications, support climate change adaptation activities, but there is little evidence regarding interventions and knowledge translation, and guidelines for projecting health impacts are lacking. Realizing the goal of an evidence-based approach will require systematic, coordinated efforts among various stakeholders.

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

PubMed Central

Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan

2010-01-01

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939

Multi-parametric analysis of phagocyte antimicrobial responses using imaging flow cytometry.

PubMed

Havixbeck, Jeffrey J; Wong, Michael E; More Bayona, Juan A; Barreda, Daniel R

2015-08-01

We feature a multi-parametric approach based on an imaging flow cytometry platform for examining phagocyte antimicrobial responses against the gram-negative bacterium Aeromonas veronii. This pathogen is known to induce strong inflammatory responses across a broad range of animal species, including humans. We examined the contribution of A. veronii to the induction of early phagocyte inflammatory processes in RAW 264.7 murine macrophages in vitro. We found that A. veronii, both in live or heat-killed forms, induced similar levels of macrophage activation based on NF-κB translocation. Although these macrophages maintained high levels of viability following heat-killed or live challenges with A. veronii, we identified inhibition of macrophage proliferation as early as 1h post in vitro challenge. The characterization of phagocytic responses showed a time-dependent increase in phagocytosis upon A. veronii challenge, which was paired with a robust induction of intracellular respiratory burst responses. Interestingly, despite the overall increase in the production of reactive oxygen species (ROS) among RAW 264.7 macrophages, we found a significant reduction in the production of ROS among the macrophage subset that had bound A. veronii. Phagocytic uptake of the pathogen further decreased ROS production levels, even beyond those of unstimulated controls. Overall, this multi-parametric imaging flow cytometry-based approach allowed for segregation of unique phagocyte sub-populations and examination of their downstream antimicrobial responses, and should contribute to improved understanding of phagocyte responses against Aeromonas and other pathogens. Copyright © 2015 Elsevier B.V. All rights reserved.

Evidence for integrating eye health into primary health care in Africa: a health systems strengthening approach

PubMed Central

2013-01-01

Background The impact of unmet eye care needs in sub-Saharan Africa is compounded by barriers to accessing eye care, limited engagement with communities, a shortage of appropriately skilled health personnel, and inadequate support from health systems. The renewed focus on primary health care has led to support for greater integration of eye health into national health systems. The aim of this paper is to demonstrate available evidence of integration of eye health into primary health care in sub-Saharan Africa from a health systems strengthening perspective. Methods A scoping review method was used to gather and assess information from published literature, reviews, WHO policy documents and examples of eye and health care interventions in sub-Saharan Africa. Findings were compiled using a health systems strengthening framework. Results Limited information is available about eye health from a health systems strengthening approach. Particular components of the health systems framework lacking evidence are service delivery, equipment and supplies, financing, leadership and governance. There is some information to support interventions to strengthen human resources at all levels, partnerships and community participation; but little evidence showing their successful application to improve quality of care and access to comprehensive eye health services at the primary health level, and referral to other levels for specialist eye care. Conclusion Evidence of integration of eye health into primary health care is currently weak, particularly when applying a health systems framework. A realignment of eye health in the primary health care agenda will require context specific planning and a holistic approach, with careful attention to each of the health system components and to the public health system as a whole. Documentation and evaluation of existing projects are required, as are pilot projects of systematic approaches to interventions and application of best practices. Multi-national research may provide guidance about how to scale up eye health interventions that are integrated into primary health systems. PMID:23506686

Systems for grading the quality of evidence and the strength of recommendations I: Critical appraisal of existing approaches The GRADE Working Group

PubMed Central

Atkins, David; Eccles, Martin; Flottorp, Signe; Guyatt, Gordon H; Henry, David; Hill, Suzanne; Liberati, Alessandro; O'Connell, Dianne; Oxman, Andrew D; Phillips, Bob; Schünemann, Holger; Edejer, Tessa Tan-Torres; Vist, Gunn E; Williams, John W

2004-01-01

Background A number of approaches have been used to grade levels of evidence and the strength of recommendations. The use of many different approaches detracts from one of the main reasons for having explicit approaches: to concisely characterise and communicate this information so that it can easily be understood and thereby help people make well-informed decisions. Our objective was to critically appraise six prominent systems for grading levels of evidence and the strength of recommendations as a basis for agreeing on characteristics of a common, sensible approach to grading levels of evidence and the strength of recommendations. Methods Six prominent systems for grading levels of evidence and strength of recommendations were selected and someone familiar with each system prepared a description of each of these. Twelve assessors independently evaluated each system based on twelve criteria to assess the sensibility of the different approaches. Systems used by 51 organisations were compared with these six approaches. Results There was poor agreement about the sensibility of the six systems. Only one of the systems was suitable for all four types of questions we considered (effectiveness, harm, diagnosis and prognosis). None of the systems was considered usable for all of the target groups we considered (professionals, patients and policy makers). The raters found low reproducibility of judgements made using all six systems. Systems used by 51 organisations that sponsor clinical practice guidelines included a number of minor variations of the six systems that we critically appraised. Conclusions All of the currently used approaches to grading levels of evidence and the strength of recommendations have important shortcomings. PMID:15615589

Practice-driven evaluation of a multi-layered psychosocial care package for children in areas of armed conflict.

PubMed

Jordans, M J D; Komproe, I H; Tol, W A; Susanty, D; Vallipuram, A; Ntamatumba, P; Lasuba, A C; De Jong, J T V M

2011-06-01

Psychosocial and mental health service delivery frameworks for children in low-income countries are scarce. This paper presents a practice-driven evaluation of a multi-layered community-based care package in Burundi, Indonesia, Sri Lanka and Sudan, through a set of indicators; (a) perceived treatment gains; (b) treatment satisfaction; (c) therapist burden; (d) access to care; (e) care package costs. Across four settings (n = 29,292 children), beneficiaries reported high levels of client satisfaction and moderate post-treatment problem reductions. Service providers reported significant levels of distress related to service delivery. Cost analyses demonstrated mean cost per service user to vary from 3.46 to 17.32 depending on country and specification of costs. The results suggest a multi-layered psychosocial care package appears feasible and satisfactory in reaching out to substantial populations of distressed children through different levels of care. Future replication should address therapist burden, cost reductions to increase sustainability and increase evidence for treatment efficacy.

Assessing the Primary Schools--A Multi-Dimensional Approach: A School Level Analysis Based on Indian Data

ERIC Educational Resources Information Center

Sengupta, Atanu; Pal, Naibedya Prasun

2012-01-01

Primary education is essential for the economic development in any country. Most studies give more emphasis to the final output (such as literacy, enrolment etc.) rather than the delivery of the entire primary education system. In this paper, we study the school level data from an Indian district, collected under the official DISE statistics. We…

Educating change agents: a qualitative descriptive study of graduates of a Master's program in evidence-based practice.

PubMed

Hole, Grete Oline; Brenna, Sissel Johansson; Graverholt, Birgitte; Ciliska, Donna; Nortvedt, Monica Wammen

2016-02-25

Health care professionals are expected to build decisions upon evidence. This implies decisions based on the best available, current, valid and relevant evidence, informed by clinical expertise and patient values. A multi-professional master's program in evidence-based practice was developed and offered. The aims of this study were to explore how students in this program viewed their ability to apply evidence-based practice and their perceptions of what constitute necessary conditions to implement evidence-based practice in health care organizations, one year after graduation. A qualitative descriptive design was chosen to examine the graduates' experiences. All students in the first two cohorts of the program were invited to participate. Six focus-group interviews, with a total of 21 participants, and a telephone interview of one participant were conducted. The data was analyzed thematically, using the themes from the interview guide as the starting point. The graduates reported that an overall necessary condition for evidence-based practice to occur is the existence of a "readiness for change" both at an individual level and at the organizational level. They described that they gained personal knowledge and skills to be "change-agents" with "self-efficacy, "analytic competence" and "tools" to implement evidence based practice in clinical care. An organizational culture of a "learning organization" was also required, where leaders have an "awareness of evidence- based practice", and see the need for creating "evidence-based networks". One year after graduation the participants saw themselves as "change agents" prepared to improve clinical care within a learning organization. The results of this study provides useful information for facilitating the implementation of EBP both from educational and health care organizational perspectives.

Implementing evidence-based medicine in general practice: a focus group based study

PubMed Central

Hannes, Karin; Leys, Marcus; Vermeire, Etienne; Aertgeerts, Bert; Buntinx, Frank; Depoorter, Anne-Marie

2005-01-01

Background Over the past years concerns are rising about the use of Evidence-Based Medicine (EBM) in health care. The calls for an increase in the practice of EBM, seem to be obstructed by many barriers preventing the implementation of evidence-based thinking and acting in general practice. This study aims to explore the barriers of Flemish GPs (General Practitioners) to the implementation of EBM in routine clinical work and to identify possible strategies for integrating EBM in daily work. Methods We used a qualitative research strategy to gather and analyse data. We organised focus groups between September 2002 and April 2003. The focus group data were analysed using a combined strategy of 'between-case' analysis and 'grounded theory approach'. Thirty-one general practitioners participated in four focus groups. Purposeful sampling was used to recruit participants. Results A basic classification model documents the influencing factors and actors on a micro-, meso- as well as macro-level. Patients, colleagues, competences, logistics and time were identified on the micro-level (the GPs' individual practice), commercial and consumer organisations on the meso-level (institutions, organisations) and health care policy, media and specific characteristics of evidence on the macro-level (policy level and international scientific community). Existing barriers and possible strategies to overcome these barriers were described. Conclusion In order to implement EBM in routine general practice, an integrated approach on different levels needs to be developed. PMID:16153300

Exploring Wellness Interventions in Progressive Multiple Sclerosis: an Evidence-Based Review.

PubMed

Venasse, Myriam; Edwards, Thomas; Pilutti, Lara A

2018-04-10

There has been recent interest in the role of lifestyle and wellness-based approaches in the treatment and management of multiple sclerosis (MS). These approaches may be particularly relevant for patients with progressive MS, considering limited therapeutic options currently available. The purpose of this review is to examine the role of wellness-based interventions including exercise training, emotional well-being therapies, and dietary modification in patients with progressive MS. We conducted a literature search on the efficacy of wellness-based interventions in patients with progressive MS published between 1985 and July 2017. The level of evidence for each trial was evaluated using the American Academy of Neurology criteria. Overall, 21 articles reporting on 16 wellness-based interventions were identified: ten trials involved exercise training, three involved emotional wellness therapies, two involved dietary modification, and one was a combined wellness intervention. There is level C evidence (possibly effective; one class II study) for the efficacy of aerobic exercise training on cardiorespiratory fitness in patients with progressive MS. There is level B evidence (probably effective; one class I study) for the efficacy of mindfulness training on psychological distress, depression, anxiety, pain, and quality of life in patients with progressive MS. There is inadequate evidence (level U) for efficacy of dietary modification (one class III study and one class IV study) and combined wellness interventions involving exercise training, meditation, and dietary modification (one class IV study). High-quality research is needed to provide evidence-based recommendations for wellness behaviors and lifestyle change in patients with progressive MS.

Design of a multi-agent hydroeconomic model to simulate a complex human-water system: Early insights from the Jordan Water Project

NASA Astrophysics Data System (ADS)

Yoon, J.; Klassert, C. J. A.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Rajsekhar, D.; Tilmant, A.; Avisse, N.; Harou, J. J.; Gawel, E.; Klauer, B.; Mustafa, D.; Talozi, S.; Sigel, K.

2015-12-01

Our work focuses on development of a multi-agent, hydroeconomic model for purposes of water policy evaluation in Jordan. The model adopts a modular approach, integrating biophysical modules that simulate natural and engineered phenomena with human modules that represent behavior at multiple levels of decision making. The hydrologic modules are developed using spatially-distributed groundwater and surface water models, which are translated into compact simulators for efficient integration into the multi-agent model. For the groundwater model, we adopt a response matrix method approach in which a 3-dimensional MODFLOW model of a complex regional groundwater system is converted into a linear simulator of groundwater response by pre-processing drawdown results from several hundred numerical simulation runs. Surface water models for each major surface water basin in the country are developed in SWAT and similarly translated into simple rainfall-runoff functions for integration with the multi-agent model. The approach balances physically-based, spatially-explicit representation of hydrologic systems with the efficiency required for integration into a complex multi-agent model that is computationally amenable to robust scenario analysis. For the multi-agent model, we explicitly represent human agency at multiple levels of decision making, with agents representing riparian, management, supplier, and water user groups. The agents' decision making models incorporate both rule-based heuristics as well as economic optimization. The model is programmed in Python using Pynsim, a generalizable, open-source object-oriented code framework for modeling network-based water resource systems. The Jordan model is one of the first applications of Pynsim to a real-world water management case study. Preliminary results from a tanker market scenario run through year 2050 are presented in which several salient features of the water system are investigated: competition between urban and private farmer agents, the emergence of a private tanker market, disparities in economic wellbeing to different user groups caused by unique supply conditions, and response of the complex system to various policy interventions.

From single cells to tissue architecture-a bottom-up approach to modelling the spatio-temporal organisation of complex multi-cellular systems.

PubMed

Galle, J; Hoffmann, M; Aust, G

2009-01-01

Collective phenomena in multi-cellular assemblies can be approached on different levels of complexity. Here, we discuss a number of mathematical models which consider the dynamics of each individual cell, so-called agent-based or individual-based models (IBMs). As a special feature, these models allow to account for intracellular decision processes which are triggered by biomechanical cell-cell or cell-matrix interactions. We discuss their impact on the growth and homeostasis of multi-cellular systems as simulated by lattice-free models. Our results demonstrate that cell polarisation subsequent to cell-cell contact formation can be a source of stability in epithelial monolayers. Stroma contact-dependent regulation of tumour cell proliferation and migration is shown to result in invasion dynamics in accordance with the migrating cancer stem cell hypothesis. However, we demonstrate that different regulation mechanisms can equally well comply with present experimental results. Thus, we suggest a panel of experimental studies for the in-depth validation of the model assumptions.

Energy Efficient Image/Video Data Transmission on Commercial Multi-Core Processors

PubMed Central

Lee, Sungju; Kim, Heegon; Chung, Yongwha; Park, Daihee

2012-01-01

In transmitting image/video data over Video Sensor Networks (VSNs), energy consumption must be minimized while maintaining high image/video quality. Although image/video compression is well known for its efficiency and usefulness in VSNs, the excessive costs associated with encoding computation and complexity still hinder its adoption for practical use. However, it is anticipated that high-performance handheld multi-core devices will be used as VSN processing nodes in the near future. In this paper, we propose a way to improve the energy efficiency of image and video compression with multi-core processors while maintaining the image/video quality. We improve the compression efficiency at the algorithmic level or derive the optimal parameters for the combination of a machine and compression based on the tradeoff between the energy consumption and the image/video quality. Based on experimental results, we confirm that the proposed approach can improve the energy efficiency of the straightforward approach by a factor of 2∼5 without compromising image/video quality. PMID:23202181

Generating demand and community support for sexual and reproductive health services for young people: A review of the Literature and Programs.

PubMed

Kesterton, Amy J; Cabral de Mello, Meena

2010-09-24

This review investigates the effectiveness of interventions aimed at generating demand for and use of sexual and reproductive health (SRH) services by young people; and interventions aimed at generating wider community support for their use. Reports and publications were found in the peer-reviewed and grey literature through academic search engines; web searches; the bibliographies of known conference proceedings and papers; and consultation with experts. The studies were reviewed against a set of inclusion criteria and those that met these were explored in more depth. The evidence-base for interventions aimed at both generating demand and community support for SRH services for young people was found under-developed and many available studies do not provide strong evidence. However, the potential of several methods to increase youth uptake has been demonstrated, this includes the linking of school education programs with youth friendly services, life skills approaches and social marketing and franchising. There is also evidence that the involvement of key community gatekeepers such as parents and religious leaders is vital to generating wider community support. In general a combined multi-component approach seems most promising with several success stories to build on. Many areas for further research have been highlighted and there is a great need for more rigorous evaluation of programmes in this area. In particular, further evaluation of individual components within a multi-component approach is needed to elucidate the most effective interventions.

Generating demand and community support for sexual and reproductive health services for young people: A review of the Literature and Programs

PubMed Central

2010-01-01

Background This review investigates the effectiveness of interventions aimed at generating demand for and use of sexual and reproductive health (SRH) services by young people; and interventions aimed at generating wider community support for their use. Methods Reports and publications were found in the peer-reviewed and grey literature through academic search engines; web searches; the bibliographies of known conference proceedings and papers; and consultation with experts. The studies were reviewed against a set of inclusion criteria and those that met these were explored in more depth. Results The evidence-base for interventions aimed at both generating demand and community support for SRH services for young people was found under-developed and many available studies do not provide strong evidence. However, the potential of several methods to increase youth uptake has been demonstrated, this includes the linking of school education programs with youth friendly services, life skills approaches and social marketing and franchising. There is also evidence that the involvement of key community gatekeepers such as parents and religious leaders is vital to generating wider community support. In general a combined multi-component approach seems most promising with several success stories to build on. Conclusions Many areas for further research have been highlighted and there is a great need for more rigorous evaluation of programmes in this area. In particular, further evaluation of individual components within a multi-component approach is needed to elucidate the most effective interventions. PMID:20863411

A Systematic Review of Montessori-Based Activities for Persons With Dementia.

PubMed

Sheppard, Christine L; McArthur, Caitlin; Hitzig, Sander L

2016-02-01

Montessori-based activities are becoming a popular approach for the care of older adults living with dementia. The aim of this study was to systematically assess the quality of the research examining the benefits of Montessori-based activities for persons with dementia. Six peer-reviewed databases were systematically searched for all relevant articles published until April 2015. Included articles were peer-reviewed studies published in English that employed Montessori-based activities with persons with dementia. Methodological quality was assessed by 2 independent raters using the Physiotherapy Evidence Database Scale or the Downs and Black evaluation tool. Levels of evidence were assigned to the study design using a modified Sackett scale. One hundred fifty articles were identified, and 14 were selected for inclusion. Level-2 evidence examining the impact of Montessori-based activities on eating behaviors suggested that difficulties with eating could be reduced with Montessori training. There was limited level-4 evidence for the benefits of Montessori-based activities on cognition, wherein benefits appeared to be specific to lower-level cognitive abilities including memory and attention. Finally, there is level-1 (n = 1), level-2 (n = 3), and level-4 (n = 6) evidence for the benefits of Montessori-based activities on engagement and affect, whereby constructive engagement and positive affect were heightened. Overall, there is a strong level of evidence for the benefits of Montessori-based activities on eating behaviors and weak evidence for the benefits on cognition. Evidence for the benefits of Montessori-based activities on engagement and affect are mixed. Future research is needed to examine the long-term benefits of Montessori-based activities. Copyright © 2016 AMDA – The Society for Post-Acute and Long-Term Care Medicine. Published by Elsevier Inc. All rights reserved.

EAP-based critical incident stress management: utilization of a practice-based assessment of incident severity level in responding to workplace trauma.

PubMed

DeFraia, Gary S

2013-01-01

Central to the field of trauma psychology is assessment of the impact of critical incidents on individuals, as measured by individual symptoms of stress. Accordingly, the trauma literature reflects a proliferation of clinical impact of event scales. Workplace incidents however, affect not only individual employees, but also work organizations, requiring a multi-level response. Critical incident stress management (CISM) is the most prevalent multi-level incident response strategy utilized by organizations, often through specialized CISM units operating within their employee assistance programs (EAPs). While EAP-based CISM units seeks to support both individuals and organizations, studies focused on individual stress dominate the literature, mirroring assessment scales that tend to emphasize clinical as opposed to organizational practice. This research contributes to less-prevalent studies exploring incident characteristics as disruptive to organizations, rather than clinical symptoms as disruptive to individuals. To measure incident disruption, an EAP-based CISM unit developed a critical incident severity scale. By analyzing this unit's extensive practice database, this exploratory study examines how critical incident severity level varies among various types of incidents. Employing the methodology of clinical data mining, this practice-based research generates evidence-informed practice recommendations in the areas of EAP-based CISM intake assessment, organizational consultation and incident response planning.

Prevention of Serious Conduct Problems in Youth with Attention Deficit/Hyperactivity Disorder

PubMed Central

Villodas, Miguel T.; Pfiffner, Linda J.; McBurnett, Keith

2013-01-01

The purpose of this review is to discuss issues in the prevention of serious conduct problems among children and adolescents with Attention Deficit/Hyperactivity Disorder (ADHD). We begin by reviewing research on the common genetic and environmental etiological factors, developmental trajectories, characteristics, and impairments associated with ADHD and comorbid Oppositional Defiant and Conduct Disorders. Next, we present empirically-based models for intervention with children and adolescents with ADHD that are at risk of developing serious conduct problems and detail the evidence supporting these models. Researchers have demonstrated the utility of medication and psychosocial intervention approaches to treat youth with these problems, but current evidence appears to support the superiority of multi-modal treatments that include both approaches. Future directions for researchers are discussed. PMID:23082741

An adaptive multi-level simulation algorithm for stochastic biological systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lester, C., E-mail: lesterc@maths.ox.ac.uk; Giles, M. B.; Baker, R. E.

2015-01-14

Discrete-state, continuous-time Markov models are widely used in the modeling of biochemical reaction networks. Their complexity often precludes analytic solution, and we rely on stochastic simulation algorithms (SSA) to estimate system statistics. The Gillespie algorithm is exact, but computationally costly as it simulates every single reaction. As such, approximate stochastic simulation algorithms such as the tau-leap algorithm are often used. Potentially computationally more efficient, the system statistics generated suffer from significant bias unless tau is relatively small, in which case the computational time can be comparable to that of the Gillespie algorithm. The multi-level method [Anderson and Higham, “Multi-level Montemore » Carlo for continuous time Markov chains, with applications in biochemical kinetics,” SIAM Multiscale Model. Simul. 10(1), 146–179 (2012)] tackles this problem. A base estimator is computed using many (cheap) sample paths at low accuracy. The bias inherent in this estimator is then reduced using a number of corrections. Each correction term is estimated using a collection of paired sample paths where one path of each pair is generated at a higher accuracy compared to the other (and so more expensive). By sharing random variables between these paired paths, the variance of each correction estimator can be reduced. This renders the multi-level method very efficient as only a relatively small number of paired paths are required to calculate each correction term. In the original multi-level method, each sample path is simulated using the tau-leap algorithm with a fixed value of τ. This approach can result in poor performance when the reaction activity of a system changes substantially over the timescale of interest. By introducing a novel adaptive time-stepping approach where τ is chosen according to the stochastic behaviour of each sample path, we extend the applicability of the multi-level method to such cases. We demonstrate the efficiency of our method using a number of examples.« less

Identification of immiscible NAPL contaminant sources in aquifers by a modified two-level saturation based imperialist competitive algorithm

NASA Astrophysics Data System (ADS)

Ghafouri, H. R.; Mosharaf-Dehkordi, M.; Afzalan, B.

2017-07-01

A simulation-optimization model is proposed for identifying the characteristics of local immiscible NAPL contaminant sources inside aquifers. This model employs the UTCHEM 9.0 software as its simulator for solving the governing equations associated with the multi-phase flow in porous media. As the optimization model, a novel two-level saturation based Imperialist Competitive Algorithm (ICA) is proposed to estimate the parameters of contaminant sources. The first level consists of three parallel independent ICAs and plays as a pre-conditioner for the second level which is a single modified ICA. The ICA in the second level is modified by dividing each country into a number of provinces (smaller parts). Similar to countries in the classical ICA, these provinces are optimized by the assimilation, competition, and revolution steps in the ICA. To increase the diversity of populations, a new approach named knock the base method is proposed. The performance and accuracy of the simulation-optimization model is assessed by solving a set of two and three-dimensional problems considering the effects of different parameters such as the grid size, rock heterogeneity and designated monitoring networks. The obtained numerical results indicate that using this simulation-optimization model provides accurate results at a less number of iterations when compared with the model employing the classical one-level ICA. A model is proposed to identify characteristics of immiscible NAPL contaminant sources. The contaminant is immiscible in water and multi-phase flow is simulated. The model is a multi-level saturation-based optimization algorithm based on ICA. Each answer string in second level is divided into a set of provinces. Each ICA is modified by incorporating a new knock the base model.

Current approaches to challenging scenarios in myeloproliferative neoplasms.

PubMed

Zimran, Eran; Hoffman, Ronald; Kremyanskaya, Marina

2018-06-01

The Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) including polycythemia vera, essential thrombocythemia and primary myelofibrosis are clonal hematological malignancies that originate at the level of the hematopoietic stem cell, and are characterized by excessive proliferation of cells belonging to one or more of the myeloid lineages. Central to the pathogenesis of the MPNs is constitutive activation of the JAK/STAT signaling pathway due to a family of driver mutations affecting JAK2, CALR or MPL. These disorders share common clinical and laboratory features, a significant burden of systemic symptoms, increased risk of developing arterial and venous thrombotic events, and the potential to progress to myelofibrosis and acute leukemia. Areas covered: We identified four clinical situations which represent challenging management dilemmas for patients with MPNs. Our conclusions and recommendations are based on a literature search using MEDLINE and recent meeting abstracts using the keywords, focusing on publications directly addressing these scenarios and on recent contributions to the field. Expert commentary: Multi-center efforts to study large cohorts of MPN patients have led to more uniform and evidence-based approaches to key aspects in MPN management. However, treatment strategies to deal with specific clinical scenarios are lacking.

A systematic community-based participatory approach to refining an evidence-based community-level intervention: The HOLA intervention for Latino men who have sex with men

PubMed Central

Rhodes, Scott D.; Daniel, Jason; Alonzo, Jorge; Duck, Stacy; Garcia, Manuel; Downs, Mario; Hergenrather, Kenneth C.; Alegria-Ortega, Jose; Miller, AAS, Cindy; Boeving Allen, Alex; Gilbert, Paul A.; Marsiglia, Flavio F.

2014-01-01

Our community-based participatory research (CBPR) partnership engaged in a multi-step process to refine a culturally congruent intervention that builds on existing community strengths to promote sexual health among immigrant Latino men who have sex with men (MSM). The steps were: (1) increase Latino MSM participation in the existing partnership; (2) establish an Intervention Team; (3) review the existing sexual health literature; (4) explore needs and priorities of Latino MSM; (5) narrow priorities based on what is important and changeable; (6) blend health behavior theory with Latino MSM’s lived experiences; (7) design an intervention conceptual model; (8) develop training modules and (9) resource materials; and (10) pretest and (11) revise the intervention. The developed intervention contains four modules to train Latino MSM to serve as lay health advisors (LHAs) known as “Navegantes”. These modules synthesize locally collected data with other local and national data; blend health behavior theory, the lived experiences, and cultural values of immigrant Latino MSM; and harness the informal social support Latino MSM provide one another. This community-level intervention is designed to meet the expressed sexual health priorities of Latino MSM. It frames disease prevention within sexual health promotion. PMID:23075504

[Some reflections on evidenced-based medicine, precision medicine, and big data-based research].

PubMed

Tang, J L; Li, L M

2018-01-10

Evidence-based medicine remains the best paradigm for medical practice. However, evidence alone is not decisions; decisions must also consider resources available and the values of people. Evidence shows that most of those treated with blood pressure-lowering, cholesterol-lowering, glucose-lowering and anti-cancer drugs do not benefit from preventing severe complications such as cardiovascular events and deaths. This implies that diagnosis and treatment in modern medicine in many circumstances is imprecise. It has become a dream to identify and treat only those few who can respond to the treatment. Precision medicine has thus come into being. Precision medicine is however not a new idea and cannot rely solely on gene sequencing as it was initially proposed. Neither is the large cohort and multi-factorial approach a new idea; in fact it has been used widely since 1950s. Since its very beginning, medicine has never stopped in searching for more precise diagnostic and therapeutic methods and already made achievements at various levels of our understanding and knowledge, such as vaccine, blood transfusion, imaging, and cataract surgery. Genetic biotechnology is not the only path to precision but merely a new method. Most genes are found only weakly associated with disease and are thus unlikely to lead to great improvement in diagnostic and therapeutic precision. The traditional multi-factorial approach by embracing big data and incorporating genetic factors is probably the most realistic way ahead for precision medicine. Big data boasts of possession of the total population and large sample size and claims correlation can displace causation. They are serious misleading concepts. Science has never had to observe the totality in order to draw a valid conclusion; a large sample size is required only when the anticipated effect is small and clinically less meaningful; emphasis on correlation over causation is equivalent to rejection of the scientific principles and methods in epidemiology and a call to give up the assurance for validity in scientific research, which will inevitably lead to futile interventions. Furthermore, in proving the effectiveness of intervention, analyses of real-world big data cannot displace the role of randomized controlled trial. We expressed doubts and critiques in this article on precision medicine and big data, merely hoping to stimulate discussing on the true potentials of precision medicine and big data.

Thrombolysis ImPlementation in Stroke (TIPS): evaluating the effectiveness of a strategy to increase the adoption of best evidence practice – protocol for a cluster randomised controlled trial in acute stroke care

PubMed Central

2014-01-01

Background Stroke is a leading cause of death and disability internationally. One of the three effective interventions in the acute phase of stroke care is thrombolytic therapy with tissue plasminogen activator (tPA), if given within 4.5 hours of onset to appropriate cases of ischaemic stroke. Objectives To test the effectiveness of a multi-component multidisciplinary collaborative approach compared to usual care as a strategy for increasing thrombolysis rates for all stroke patients at intervention hospitals, while maintaining accepted benchmarks for low rates of intracranial haemorrhage and high rates of functional outcomes for both groups at three months. Methods and design A cluster randomised controlled trial of 20 hospitals across 3 Australian states with 2 groups: multi- component multidisciplinary collaborative intervention as the experimental group and usual care as the control group. The intervention is based on behavioural theory and analysis of the steps, roles and barriers relating to rapid assessment for thrombolysis eligibility; it involves a comprehensive range of strategies addressing individual-level and system-level change at each site. The primary outcome is the difference in tPA rates between the two groups post-intervention. The secondary outcome is the proportion of tPA treated patients in both groups with good functional outcomes (modified Rankin Score (mRS <2) and the proportion with intracranial haemorrhage (mRS ≥2), compared to international benchmarks. Discussion TIPS will trial a comprehensive, multi-component and multidisciplinary collaborative approach to improving thrombolysis rates at multiple sites. The trial has the potential to identify methods for optimal care which can be implemented for stroke patients during the acute phase. Study findings will include barriers and solutions to effective thrombolysis implementation and trial outcomes will be published whether significant or not. Trial registration Australian New Zealand Clinical Trials Registry: ACTRN12613000939796 PMID:24666591

A practical approach to evidence-based dentistry: How to search for evidence to inform clinical decisions.

PubMed

Brignardello-Petersen, Romina; Carrasco-Labra, Alonso; Booth, H Austin; Glick, Michael; Guyatt, Gordon H; Azarpazhooh, Amir; Agoritsas, Thomas

2014-12-01

Knowing how to search for evidence that can inform clinical decisions is a fundamental skill for the practice of evidence-based dentistry. There are many available types of evidence-based resources, characterized by their degrees of coverage of preappraised or summarized evidence at varying levels of processing, from primary studies to systematic reviews and clinical guidelines. The practice of evidence-based dentistry requires familiarity with these resources. In this article, the authors describe the process of searching for evidence: defining the question, identifying the question's nature and main components, and selecting the study design that best addresses the question.

Development of Decision Support System for Remote Monitoring of PIP Corn

EPA Science Inventory

The EPA is developing a multi-level approach that utilizes satellite and airborne remote sensing to locate and monitor genetically modified corn in the agricultural landscape and pest infestation. The current status of the EPA IRM monitoring program based on remote sensed imager...

An Evidence-Based Public Health Approach to Climate Change Adaptation

PubMed Central

Eidson, Millicent; Tlumak, Jennifer E.; Raab, Kristin K.; Luber, George

2014-01-01

Background: Public health is committed to evidence-based practice, yet there has been minimal discussion of how to apply an evidence-based practice framework to climate change adaptation. Objectives: Our goal was to review the literature on evidence-based public health (EBPH), to determine whether it can be applied to climate change adaptation, and to consider how emphasizing evidence-based practice may influence research and practice decisions related to public health adaptation to climate change. Methods: We conducted a substantive review of EBPH, identified a consensus EBPH framework, and modified it to support an EBPH approach to climate change adaptation. We applied the framework to an example and considered implications for stakeholders. Discussion: A modified EBPH framework can accommodate the wide range of exposures, outcomes, and modes of inquiry associated with climate change adaptation and the variety of settings in which adaptation activities will be pursued. Several factors currently limit application of the framework, including a lack of higher-level evidence of intervention efficacy and a lack of guidelines for reporting climate change health impact projections. To enhance the evidence base, there must be increased attention to designing, evaluating, and reporting adaptation interventions; standardized health impact projection reporting; and increased attention to knowledge translation. This approach has implications for funders, researchers, journal editors, practitioners, and policy makers. Conclusions: The current approach to EBPH can, with modifications, support climate change adaptation activities, but there is little evidence regarding interventions and knowledge translation, and guidelines for projecting health impacts are lacking. Realizing the goal of an evidence-based approach will require systematic, coordinated efforts among various stakeholders. Citation: Hess JJ, Eidson M, Tlumak JE, Raab KK, Luber G. 2014. An evidence-based public health approach to climate change adaptation. Environ Health Perspect 122:1177–1186; http://dx.doi.org/10.1289/ehp.1307396 PMID:25003495

Experimental evidence of hot carriers solar cell operation in multi-quantum wells heterostructures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodière, Jean; Lombez, Laurent, E-mail: laurent.lombez@chimie-paristech.fr; Le Corre, Alain

We investigated a semiconductor heterostructure based on InGaAsP multi quantum wells (QWs) using optical characterizations and demonstrate its potential to work as a hot carrier cell absorber. By analyzing photoluminescence spectra, the quasi Fermi level splitting Δμ and the carrier temperature are quantitatively measured as a function of the excitation power. Moreover, both thermodynamics values are measured at the QWs and the barrier emission energy. High values of Δμ are found for both transition, and high carrier temperature values in the QWs. Remarkably, the quasi Fermi level splitting measured at the barrier energy exceeds the absorption threshold of the QWs.more » This indicates a working condition beyond the classical Shockley-Queisser limit.« less

A Comprehensive Approach in Dissemination of Evidence-Based Care for PTSD

DTIC Science & Technology

2012-09-01

been published, to provide evidence-based resources to facilitate practice evaluation and identification of potential gaps in care. In order to...practice’s capacity to provide evidence-based care and identify potential gaps in care as targets for improvement. Finally, strategies to implement...existing patients, the PIP tools can inform improvement efforts at the clinician-, practice-or systems-level, facilitate detection of potential gaps in

Developing "My Asthma Diary": a process exemplar of a patient-driven arts-based knowledge translation tool.

PubMed

Archibald, Mandy M; Hartling, Lisa; Ali, Samina; Caine, Vera; Scott, Shannon D

2018-06-05

Although it is well established that family-centered education is critical to managing childhood asthma, the information needs of parents of children with asthma are not being met through current educational approaches. Patient-driven educational materials that leverage the power of the storytelling and the arts show promise in communicating health information and assisting in illness self-management. However, such arts-based knowledge translation approaches are in their infancy, and little is known about how to develop such tools for parents. This paper reports on the development of "My Asthma Diary" - an innovative knowledge translation tool based on rigorous research evidence and tailored to parents' asthma-related information needs. We used a multi-stage process to develop four eBook prototypes of "My Asthma Diary." We conducted formative research on parents' information needs and identified high quality research evidence on childhood asthma, and used these data to inform the development of the asthma eBooks. We established interdisciplinary consulting teams with health researchers, practitioners, and artists to help iteratively create the knowledge translation tools. We describe the iterative, transdisciplinary process of developing asthma eBooks which incorporates: (I) parents' preferences and information needs on childhood asthma, (II) quality evidence on childhood asthma and its management, and (III) the engaging and informative powers of storytelling and visual art as methods to communicate complex health information to parents. We identified four dominant methodological and procedural challenges encountered during this process: (I) working within an inter-disciplinary team, (II) quantity and ordering of information, (III) creating a composite narrative, and (IV) balancing actual and ideal management scenarios. We describe a replicable and rigorous multi-staged approach to developing a patient-driven, creative knowledge translation tool, which can be adapted for use with different populations and contexts. We identified specific procedural and methodological challenges that others conducting comparable work should consider, particularly as creative, patient-driven knowledge translation strategies continue to emerge across health disciplines.

Counselor Attitudes toward the Use of Buprenorphine in Substance Abuse Treatment: A Multi-level Modeling Approach

PubMed Central

Kovas, Anne E.; McFarland, Bentson H.; Abraham, Amanda J.

2012-01-01

In spite of evidence that buprenorphine is effective, safe, and offers greater access as compared with methadone, implementation for treatment of opiate dependence continues to be weak. Research indicates that legal and regulatory factors, state policies, and organizational and provider variables affect adoption of buprenorphine. This study uses hierarchical linear modeling (HLM) to examine National Treatment Center Study (NTCS) data to identify counselor characteristics (attitudes, training, beliefs) and organizational factors (accreditation, caseload, access to buprenorphine and other evidence-based practices) that influence implementation of buprenorphine for treatment of opiate dependence. Analyses showed that provider training about buprenorphine, higher prevalence of opiate dependent clients, and less treatment program emphasis on a 12-step model predicted greater counselor acceptance and perceived effectiveness of buprenorphine. Results also indicate that program use of buprenorphine for any treatment purpose (detoxification, maintenance, and/or pain management) and time (calendar year in data collection) were associated with increased diffusion of knowledge about buprenorphine among counselors and with more favorable counselor attitudes toward buprenorphine. PMID:21821379

Data Parallel Bin-Based Indexing for Answering Queries on Multi-Core Architectures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gosink, Luke; Wu, Kesheng; Bethel, E. Wes

2009-06-02

The multi-core trend in CPUs and general purpose graphics processing units (GPUs) offers new opportunities for the database community. The increase of cores at exponential rates is likely to affect virtually every server and client in the coming decade, and presents database management systems with a huge, compelling disruption that will radically change how processing is done. This paper presents a new parallel indexing data structure for answering queries that takes full advantage of the increasing thread-level parallelism emerging in multi-core architectures. In our approach, our Data Parallel Bin-based Index Strategy (DP-BIS) first bins the base data, and then partitionsmore » and stores the values in each bin as a separate, bin-based data cluster. In answering a query, the procedures for examining the bin numbers and the bin-based data clusters offer the maximum possible level of concurrency; each record is evaluated by a single thread and all threads are processed simultaneously in parallel. We implement and demonstrate the effectiveness of DP-BIS on two multi-core architectures: a multi-core CPU and a GPU. The concurrency afforded by DP-BIS allows us to fully utilize the thread-level parallelism provided by each architecture--for example, our GPU-based DP-BIS implementation simultaneously evaluates over 12,000 records with an equivalent number of concurrently executing threads. In comparing DP-BIS's performance across these architectures, we show that the GPU-based DP-BIS implementation requires significantly less computation time to answer a query than the CPU-based implementation. We also demonstrate in our analysis that DP-BIS provides better overall performance than the commonly utilized CPU and GPU-based projection index. Finally, due to data encoding, we show that DP-BIS accesses significantly smaller amounts of data than index strategies that operate solely on a column's base data; this smaller data footprint is critical for parallel processors that possess limited memory resources (e.g., GPUs).« less

Stakeholder conceptualisation of multi-level HIV and AIDS determinants in a Black epicentre.

PubMed

Brawner, Bridgette M; Reason, Janaiya L; Hanlon, Kelsey; Guthrie, Barbara; Schensul, Jean J

2017-09-01

HIV has reached epidemic proportions among African Americans in the USA but certain urban contexts appear to experience a disproportionate disease burden. Geographic information systems mapping in Philadelphia indicates increased HIV incidence and prevalence in predominantly Black census tracts, with major differences across adjacent communities. What factors shape these geographic HIV disparities among Black Philadelphians? This descriptive study was designed to refine and validate a conceptual model developed to better understand multi-level determinants of HIV-related risk among Black Philadelphians. We used an expanded ecological approach to elicit reflective perceptions from administrators, direct service providers and community members about individual, social and structural factors that interact to protect against or increase the risk for acquiring HIV within their community. Gender equity, social capital and positive cultural mores (e.g., monogamy, abstinence) were seen as the main protective factors. Historical negative contributory influences of racial residential segregation, poverty and incarceration were among the most salient risk factors. This study was a critical next step toward initiating theory-based, multi-level community-based HIV prevention initiatives.

Multi-criteria objective based climate change impact assessment for multi-purpose multi-reservoir systems

NASA Astrophysics Data System (ADS)

Müller, Ruben; Schütze, Niels

2014-05-01

Water resources systems with reservoirs are expected to be sensitive to climate change. Assessment studies that analyze the impact of climate change on the performance of reservoirs can be divided in two groups: (1) Studies that simulate the operation under projected inflows with the current set of operational rules. Due to non adapted operational rules the future performance of these reservoirs can be underestimated and the impact overestimated. (2) Studies that optimize the operational rules for best adaption of the system to the projected conditions before the assessment of the impact. The latter allows for estimating more realistically future performance and adaption strategies based on new operation rules are available if required. Multi-purpose reservoirs serve various, often conflicting functions. If all functions cannot be served simultaneously at a maximum level, an effective compromise between multiple objectives of the reservoir operation has to be provided. Yet under climate change the historically preferenced compromise may no longer be the most suitable compromise in the future. Therefore a multi-objective based climate change impact assessment approach for multi-purpose multi-reservoir systems is proposed in the study. Projected inflows are provided in a first step using a physically based rainfall-runoff model. In a second step, a time series model is applied to generate long-term inflow time series. Finally, the long-term inflow series are used as driving variables for a simulation-based multi-objective optimization of the reservoir system in order to derive optimal operation rules. As a result, the adapted Pareto-optimal set of diverse best compromise solutions can be presented to the decision maker in order to assist him in assessing climate change adaption measures with respect to the future performance of the multi-purpose reservoir system. The approach is tested on a multi-purpose multi-reservoir system in a mountainous catchment in Germany. A climate change assessment is performed for climate change scenarios based on the SRES emission scenarios A1B, B1 and A2 for a set of statistically downscaled meteorological data. The future performance of the multi-purpose multi-reservoir system is quantified and possible intensifications of trade-offs between management goals or reservoir utilizations are shown.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging.

PubMed

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research.

Neural Substrate of Group Mental Health: Insights from Multi-Brain Reference Frame in Functional Neuroimaging

PubMed Central

Ray, Dipanjan; Roy, Dipanjan; Sindhu, Brahmdeep; Sharan, Pratap; Banerjee, Arpan

2017-01-01

Contemporary mental health practice primarily centers around the neurobiological and psychological processes at the individual level. However, a more careful consideration of interpersonal and other group-level attributes (e.g., interpersonal relationship, mutual trust/hostility, interdependence, and cooperation) and a better grasp of their pathology can add a crucial dimension to our understanding of mental health problems. A few recent studies have delved into the interpersonal behavioral processes in the context of different psychiatric abnormalities. Neuroimaging can supplement these approaches by providing insight into the neurobiology of interpersonal functioning. Keeping this view in mind, we discuss a recently developed approach in functional neuroimaging that calls for a shift from a focus on neural information contained within brain space to a multi-brain framework exploring degree of similarity/dissimilarity of neural signals between multiple interacting brains. We hypothesize novel applications of quantitative neuroimaging markers like inter-subject correlation that might be able to evaluate the role of interpersonal attributes affecting an individual or a group. Empirical evidences of the usage of these markers in understanding the neurobiology of social interactions are provided to argue for their application in future mental health research. PMID:29033866

Improved optical flow motion estimation for digital image stabilization

NASA Astrophysics Data System (ADS)

Lai, Lijun; Xu, Zhiyong; Zhang, Xuyao

2015-11-01

Optical flow is the instantaneous motion vector at each pixel in the image frame at a time instant. The gradient-based approach for optical flow computation can't work well when the video motion is too large. To alleviate such problem, we incorporate this algorithm into a pyramid multi-resolution coarse-to-fine search strategy. Using pyramid strategy to obtain multi-resolution images; Using iterative relationship from the highest level to the lowest level to obtain inter-frames' affine parameters; Subsequence frames compensate back to the first frame to obtain stabilized sequence. The experiment results demonstrate that the promoted method has good performance in global motion estimation.

Evidence and evidence gaps in the treatment of Eustachian tube dysfunction and otitis media

PubMed Central

Teschner, Magnus

2016-01-01

Evidence-based medicine is an approach to medical treatment intended to optimize patient-oriented decision-making on the basis of empirically proven effectiveness. For this purpose, a classification system has been established to categorize studies – and hence therapy options – in respect of associated evidence according to defined criteria. The Eustachian tube connects the nasopharynx with the middle ear cavity. Its key function is to ensure middle ear ventilation. Compromised ventilation results in inflammatory middle ear disorders. Numerous evidence-based therapy options are available for the treatment of impaired middle ear ventilation and otitis media, the main therapeutic approach being antibiotic treatment. More recent procedures such as balloon dilation of the Eustachian tube have also shown initial success but must undergo further evaluation with regard to evidence. There is, as yet, no evidence for some of the other long-established procedures. Owing to the multitude of variables, the classification of evidence levels for various treatment approaches calls for highly diversified assessment. Numerous evidence-based studies are therefore necessary in order to evaluate the evidence pertaining to existing and future therapy solutions for impaired middle ear ventilation and otitis media. If this need is addressed, a wealth of implications can be expected for therapeutic approaches in the years to come. PMID:28025605

Mediterranean Diet and Multi-Ingredient-Based Interventions for the Management of Non-Alcoholic Fatty Liver Disease

PubMed Central

Suárez, Manuel; Boqué, Noemí; del Bas, Josep M.; Arola, Lluís; Caimari, Antoni

2017-01-01

Non-alcoholic fatty liver disease (NAFLD) comprises a wide spectrum of hepatic disorders, from simple steatosis to hepatic necro-inflammation leading to non-alcoholic steatohepatitis (NASH). Although the prevalence of these multifactorial pathologies is continuously increasing in the population, there is still not an established methodology for their treatment other than weight loss and a change in lifestyle habits, such as a hypocaloric diet and physical exercise. In this framework, there is increasing evidence that several food bioactives and dietary patterns are effective for reversing and preventing the onset of these pathologies. Some studies have claimed that better responses are obtained when treatments are performed under a multifaceted approach, using different bioactive compounds that act against complementary targets. Thus, in this work, current strategies for treating NAFLD and NASH based on multi-ingredient-based supplements or the Mediterranean diet, a dietary pattern rich in bioactive compounds, are reviewed. Furthermore, the usefulness of omics techniques to design effective multi-ingredient nutritional interventions and to predict and monitor their response against these disorders is also discussed. PMID:28937599

Application of fuzzy logic and fuzzy AHP to mineral prospectivity mapping of porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang, NW China

NASA Astrophysics Data System (ADS)

Zhang, Nannan; Zhou, Kefa; Du, Xishihui

2017-04-01

Mineral prospectivity mapping (MPM) is a multi-step process that ranks promising target areas for further exploration. Fuzzy logic and fuzzy analytical hierarchy process (AHP) are knowledge-driven MPM approaches. In this study, both approaches were used for data processing, based on which MPM was performed for porphyry and hydrothermal vein copper deposits in the Dananhu-Tousuquan island arc, Xinjiang. The results of the two methods were then compared. The two methods combined expert experience and the Studentized contrast (S(C)) values of the weights-of-evidence approach to calculate the weights of 15 layers, and these layers were then integrated by the gamma operator (γ). Through prediction-area (P-A) plot analysis, the optimal γ for fuzzy logic and fuzzy AHP was determined as 0.95 and 0.93, respectively. The thresholds corresponding to different levels of metallogenic probability were defined via concentration-area (C-A) fractal analysis. The prediction performances of the two methods were compared on this basis. The results showed that in MPM based on fuzzy logic, the area under the receiver operating characteristic (ROC) curve was 0.806 and 81.48% of the known deposits were predicted, whereas in MPM based on fuzzy AHP, the area under the ROC curve was 0.862 and 92.59% of the known deposits were predicted. Therefore, prediction based on fuzzy AHP is more accurate and can provide directions for future prospecting.

Application of best practice approaches for designing decision support tools: The preparatory education about clinical trials (PRE-ACT) study

PubMed Central

Fleisher, Linda; Ruggieri, Dominique G.; Miller, Suzanne M.; Manne, Sharon; Albrecht, Terrance; Buzaglo, Joanne; Collins, Michael A.; Katz, Michael; Kinzy, Tyler G.; Liu, Tasnuva; Manning, Cheri; Charap, Ellen Specker; Millard, Jennifer; Miller, Dawn M.; Poole, David; Raivitch, Stephanie; Roach, Nancy; Ross, Eric A.; Meropol, Neal J.

2014-01-01

Objective This article describes the rigorous development process and initial feedback of the PRE-ACT (Preparatory Education About Clinical Trials) web-based- intervention designed to improve preparation for decision making in cancer clinical trials. Methods The multi-step process included stakeholder input, formative research, user testing and feedback. Diverse teams (researchers, advocates and developers) participated including content refinement, identification of actors, and development of video scripts. Patient feedback was provided in the final production period and through a vanguard group (N = 100) from the randomized trial. Results Patients/advocates confirmed barriers to cancer clinical trial participation, including lack of awareness and knowledge, fear of side effects, logistical concerns, and mistrust. Patients indicated they liked the tool’s user-friendly nature, the organized and comprehensive presentation of the subject matter, and the clarity of the videos. Conclusion The development process serves as an example of operationalizing best practice approaches and highlights the value of a multi-disciplinary team to develop a theory-based, sophisticated tool that patients found useful in their decision making process. Practice implications Best practice approaches can be addressed and are important to ensure evidence-based tools that are of value to patients and supports the usefulness of a process map in the development of e-health tools. PMID:24813474

Improving Access and Systems of Care for Evidence-Based Childhood Obesity Treatment: Conference Key Findings and Next Steps

PubMed Central

Wilfley, Denise E.; Staiano, Amanda E.; Altman, Myra; Lindros, Jeanne; Lima, Angela; Hassink, Sandra G.; Dietz, William H.; Cook, Stephen

2017-01-01

Objectives To improve systems of care to advance implementation of the U.S. Preventive Services Task Force recommendations for childhood obesity treatment (i.e. clinicians offer/refer children with obesity to intensive, multicomponent behavioral interventions of >25 hours over 6–12 months to improve weight status) and to expand payment for these services. Methods In July 2015, forty-three cross-sector stakeholders attended a conference supported by the Agency for Healthcare Research and Quality, American Academy of Pediatrics Institute for Healthy Childhood Weight, and The Obesity Society. Plenary sessions presenting scientific evidence and clinical and payment practices were interspersed with breakout sessions to identify consensus recommendations. Results Consensus recommendations for childhood obesity treatment included: family-based multicomponent behavioral therapy; integrated care model; and multi-disciplinary care team. The use of evidence-based protocols, a well-trained healthcare team, medical oversight, and treatment at or above the minimum dose (e.g. >25 hours) are critical components to ensure effective delivery of high-quality care and to achieve clinically meaningful weight loss. Approaches to secure reimbursement for evidence-based obesity treatment within payment models were recommended. Conclusion Continued cross-sector collaboration is crucial to ensure a unified approach to increase payment and access for childhood obesity treatment and to scale-up training to ensure quality of care. PMID:27925451

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records.

PubMed

Peissig, Peggy L; Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries.

A Two-Stage Multi-Agent Based Assessment Approach to Enhance Students' Learning Motivation through Negotiated Skills Assessment

ERIC Educational Resources Information Center

Chadli, Abdelhafid; Bendella, Fatima; Tranvouez, Erwan

2015-01-01

In this paper we present an Agent-based evaluation approach in a context of Multi-agent simulation learning systems. Our evaluation model is based on a two stage assessment approach: (1) a Distributed skill evaluation combining agents and fuzzy sets theory; and (2) a Negotiation based evaluation of students' performance during a training…

Evidence-Based Program Service Deserts: A Geographic Information Systems (GIS) Approach to Identifying Service Gaps for State-Level Implementation Planning.

PubMed

Walker, Sarah Cusworth; Hurvitz, Philip M; Leith, Jessica; Rodriguez, Felix I; Endler, Gregory C

2016-11-01

The long term effects of untreated mental health need for individuals, families and society has prompted a number of federal policy statements encouraging the use of evidence-based programs (EBP) in children's healthcare. However, among other challenges of evidence-based practice implementation, states often do not know where to make investments based on population need. In this paper we present the use of a Geographic Information System approach to undertake a mental health needs assessment for Washington State. Our study found that this technology can be beneficially applied to conducting needs assessment for EBP implementation, and we provide recommendations for future applications.

Strengthening the evidence and action on multi-sectoral partnerships in public health: an action research initiative

PubMed Central

Willis, C. D.; Greene, J. K.; Abramowicz, A.; Riley, B. L.

2016-01-01

Abstract Introduction: The Public Health Agency of Canada’s Multi-sectoral Partnerships Initiative, administered by the Centre for Chronic Disease Prevention (CCDP), brings together diverse partners to design, implement and advance innovative approaches for improving population health. This article describes the development and initial priorities of an action research project (a learning and improvement strategy) that aims to facilitate continuous improvement of the CCDP’s partnership initiative and contribute to the evidence on multi-sectoral partnerships. Methods: The learning and improvement strategy for the CCDP’s multi-sectoral partnership initiative was informed by (1) consultations with CCDP staff and senior management, and (2) a review of conceptual frameworks to do with multi-sectoral partnerships. Consultations explored the development of the multi-sectoral initiative, barriers and facilitators to success, and markers of effectiveness. Published and grey literature was reviewed using a systematic search strategy with findings synthesized using a narrative approach. Results: Consultations and the review highlighted the importance of understanding partnership impacts, developing a shared vision, implementing a shared measurement system and creating opportunities for knowledge exchange. With that in mind, we propose a six-component learning and improvement strategy that involves (1) prioritizing learning needs, (2) mapping needs to evidence, (3) using relevant data-collection methods, (4) analyzing and synthesizing data, (5) feeding data back to CCDP staff and teams and (6) taking action. Initial learning needs include investigating partnership reach and the unanticipated effects of multi-sectoral partnerships for individuals, groups, organizations or communities. Conclusion: While the CCDP is the primary audience for the learning and improvement strategy, it may prove useful for a range of audiences, including other government departments and external organizations interested in capturing and sharing new knowledge generated from multi-sectoral partnerships. PMID:27284702

A subjective framework for seat comfort based on a heuristic multi criteria decision making technique and anthropometry.

PubMed

Fazlollahtabar, Hamed

2010-12-01

Consumer expectations for automobile seat comfort continue to rise. With this said, it is evident that the current automobile seat comfort development process, which is only sporadically successful, needs to change. In this context, there has been growing recognition of the need for establishing theoretical and methodological automobile seat comfort. On the other hand, seat producer need to know the costumer's required comfort to produce based on their interests. The current research methodologies apply qualitative approaches due to anthropometric specifications. The most significant weakness of these approaches is the inexact extracted inferences. Despite the qualitative nature of the consumer's preferences there are some methods to transform the qualitative parameters into numerical value which could help seat producer to improve or enhance their products. Nonetheless this approach would help the automobile manufacturer to provide their seats from the best producer regarding to the consumers idea. In this paper, a heuristic multi criteria decision making technique is applied to make consumers preferences in the numeric value. This Technique is combination of Analytical Hierarchy Procedure (AHP), Entropy method, and Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS). A case study is conducted to illustrate the applicability and the effectiveness of the proposed heuristic approach. Copyright © 2010 Elsevier Ltd. All rights reserved.

UWALK: the development of a multi-strategy, community-wide physical activity program.

PubMed

Jennings, Cally A; Berry, Tanya R; Carson, Valerie; Culos-Reed, S Nicole; Duncan, Mitch J; Loitz, Christina C; McCormack, Gavin R; McHugh, Tara-Leigh F; Spence, John C; Vallance, Jeff K; Mummery, W Kerry

2017-03-01

UWALK is a multi-strategy, multi-sector, theory-informed, community-wide approach using e and mHealth to promote physical activity in Alberta, Canada. The aim of UWALK is to promote physical activity, primarily via the accumulation of steps and flights of stairs, through a single over-arching brand. This paper describes the development of the UWALK program. A social ecological model and the social cognitive theory guided the development of key strategies, including the marketing and communication activities, establishing partnerships with key stakeholders, and e and mHealth programs. The program promotes the use of physical activity monitoring devices to self-monitor physical activity. This includes pedometers, electronic devices, and smartphone applications. In addition to entering physical activity data manually, the e and mHealth program provides the function for objective data to be automatically uploaded from select electronic devices (Fitbit®, Garmin and the smartphone application Moves) The RE-AIM framework is used to guide the evaluation of UWALK. Funding for the program commenced in February 2013. The UWALK brand was introduced on April 12, 2013 with the official launch, including the UWALK website on September 20, 2013. This paper describes the development and evaluation framework of a physical activity promotion program. This program has the potential for population level dissemination and uptake of an ecologically valid physical activity promotion program that is evidence-based and theoretically framed.

A variational approach to multi-phase motion of gas, liquid and solid based on the level set method

NASA Astrophysics Data System (ADS)

Yokoi, Kensuke

2009-07-01

We propose a simple and robust numerical algorithm to deal with multi-phase motion of gas, liquid and solid based on the level set method [S. Osher, J.A. Sethian, Front propagating with curvature-dependent speed: Algorithms based on Hamilton-Jacobi formulation, J. Comput. Phys. 79 (1988) 12; M. Sussman, P. Smereka, S. Osher, A level set approach for capturing solution to incompressible two-phase flow, J. Comput. Phys. 114 (1994) 146; J.A. Sethian, Level Set Methods and Fast Marching Methods, Cambridge University Press, 1999; S. Osher, R. Fedkiw, Level Set Methods and Dynamics Implicit Surface, Applied Mathematical Sciences, vol. 153, Springer, 2003]. In Eulerian framework, to simulate interaction between a moving solid object and an interfacial flow, we need to define at least two functions (level set functions) to distinguish three materials. In such simulations, in general two functions overlap and/or disagree due to numerical errors such as numerical diffusion. In this paper, we resolved the problem using the idea of the active contour model [M. Kass, A. Witkin, D. Terzopoulos, Snakes: active contour models, International Journal of Computer Vision 1 (1988) 321; V. Caselles, R. Kimmel, G. Sapiro, Geodesic active contours, International Journal of Computer Vision 22 (1997) 61; G. Sapiro, Geometric Partial Differential Equations and Image Analysis, Cambridge University Press, 2001; R. Kimmel, Numerical Geometry of Images: Theory, Algorithms, and Applications, Springer-Verlag, 2003] introduced in the field of image processing.

Familia Adelante: A Multi-Risk Prevention Intervention for Latino Families

PubMed Central

Cervantes, Richard; Goldbach, Jeremy; Santos, Susana M.

2011-01-01

A comprehensive approach for providing behavioral health services to youth is becoming increasingly emphasized (IOM, 2009). Latino youth are at increased risk for substance abuse, mental health concerns, unsafe sexual practices and HIV (Prado et al., 2006), and these outcomes have been empirically connected to individual, family and community-based stress (IOM, 2009). Despite this knowledge, there is a lack of evidence-based approaches that target these negative outcomes by reducing stress in Latino families in a culturally relevant manner (Cervantes, Kappos, Duenas & Arellano, 2003). The current study examined the use of research-based strategies for reducing multiple risk behaviors in a predominantly Mexican American sample of families. Through a modular approach, participants engaged in a psycho-educational curriculum to enhance communication and psychosocial coping, increase substance abuse and HIV knowledge and perception of harm, and improve school behavior. Over 12 sessions, the curriculum aimed to achieve these outcomes through an overall decrease in family and community-based stress by focusing on acculturative stress. Findings indicate that communication and perception of substance use harm were significantly enhanced, while social norms regarding sexual behavior, HIV anxiety and past use of marijuana and other illegal drugs were significantly reduced. While many of measures were reliable (α > .80), further changes are necessary to improve the accuracy of future studies. Despite these limitations, Familia Adelante improves many areas of participant’s family life, and points toward the feasibility of multi-risk reduction behavioral health prevention approaches. PMID:21822979

Suicide Prevention Strategies for Improving Population Health.

PubMed

Wilcox, Holly C; Wyman, Peter A

2016-04-01

Suicide is a public health problem that accounts for more than 1 million deaths annually worldwide. This article addresses evidence-based and promising youth suicide prevention approaches at the primary, secondary, and tertiary levels. Coordinated, developmentally timed, evidence-based suicide prevention approaches at all intervention levels are likely to reduce youth suicide. For most youth who die by suicide, there are opportunities for intervention before imminent risk develops. Current research in suicide prevention points to the value of investing in "upstream" universal interventions that build skills and resilience as well as policies that enable access to care and protection from lethal means. Copyright © 2016 Elsevier Inc. All rights reserved.

Evidence-based fitness promotion in an afterschool setting: implementation fidelity and its policy implications.

PubMed

Thaw, Jean M; Villa, Manuela; Reitman, David; DeLucia, Christian; Gonzalez, Vanessa; Hanson, K Lori

2014-01-01

Little is known about how the adoption of evidence-based physical activity (PA) curricula by out-of-school time (OST) programs affects children's physical fitness, and there are no clear guidelines of what constitutes reasonable gains given the types of PA instruction currently offered in these programs. Using a three-wave, quasi-experimental, naturalistic observation design, this study evaluated the implementation of an evidence-based PA instruction curriculum (Sports, Play, and Active Recreation for Kids [SPARK]) and examined whether the potential health benefits of evidence-based PA instruction can be replicated in this context when compared to OST programs that do not use evidence-based PA curricula. Quality of PA instruction and SPARK implementation fidelity were also assessed. Results indicated that children in the non-evidence-based/standard PA instruction programs engaged in higher levels of moderate-to-vigorous PA (MVPA) and showed greater improvements in fitness levels over time. The findings from this chapter suggest that while it is generally accepted that evidence-based approaches yield higher levels of PA when implemented by researchers under controlled conditions, findings are inconsistent when evidence-based PA instruction is implemented in the field, under presumably less controlled conditions. It appears that when it comes to PA instruction in afterschool, either less structured activities or well-implemented evidence-based practices could be the key to promoting higher PA levels and greater health and fitness for school-aged children. © 2014 WILEY PERIODICALS, INC.

In situ multi-length scale approach to understand the mechanics of soft and rigid binder in composite lithium ion battery electrodes

NASA Astrophysics Data System (ADS)

Jäckel, Nicolas; Dargel, Vadim; Shpigel, Netanel; Sigalov, Sergey; Levi, Mikhael D.; Daikhin, Leonid; Aurbach, Doron; Presser, Volker

2017-12-01

Intercalation-induced dimensional changes of composite battery electrodes containing either a stiff or a soft polymeric binder is one of the many factors determining the cycling performance and ageing. Herein, we report dimensional changes in bulk composite electrodes by in situ electrochemical dilatometry (eD) combined with electrochemical quartz-crystal microbalance with dissipation monitoring (EQCM-D). The latter tracks the mechanical properties on the level of the electrode particle size. Lithium iron phosphate (LiFePO4, LFP) electrodes with a stiff binder (PVdF) and a soft binder (NaCMC) were investigated by cycling in lithium sulfate (Li2SO4) aqueous solution. The electrochemical and mechanical electrode performances depend on the electrode cycling history. Based on combined eD and EQCM-D measurements we provide evidence which properties are preferred for a binder used for a composite Li-ion battery electrode.

Coarse-grained component concurrency in Earth system modeling: parallelizing atmospheric radiative transfer in the GFDL AM3 model using the Flexible Modeling System coupling framework

NASA Astrophysics Data System (ADS)

Balaji, V.; Benson, Rusty; Wyman, Bruce; Held, Isaac

2016-10-01

Climate models represent a large variety of processes on a variety of timescales and space scales, a canonical example of multi-physics multi-scale modeling. Current hardware trends, such as Graphical Processing Units (GPUs) and Many Integrated Core (MIC) chips, are based on, at best, marginal increases in clock speed, coupled with vast increases in concurrency, particularly at the fine grain. Multi-physics codes face particular challenges in achieving fine-grained concurrency, as different physics and dynamics components have different computational profiles, and universal solutions are hard to come by. We propose here one approach for multi-physics codes. These codes are typically structured as components interacting via software frameworks. The component structure of a typical Earth system model consists of a hierarchical and recursive tree of components, each representing a different climate process or dynamical system. This recursive structure generally encompasses a modest level of concurrency at the highest level (e.g., atmosphere and ocean on different processor sets) with serial organization underneath. We propose to extend concurrency much further by running more and more lower- and higher-level components in parallel with each other. Each component can further be parallelized on the fine grain, potentially offering a major increase in the scalability of Earth system models. We present here first results from this approach, called coarse-grained component concurrency, or CCC. Within the Geophysical Fluid Dynamics Laboratory (GFDL) Flexible Modeling System (FMS), the atmospheric radiative transfer component has been configured to run in parallel with a composite component consisting of every other atmospheric component, including the atmospheric dynamics and all other atmospheric physics components. We will explore the algorithmic challenges involved in such an approach, and present results from such simulations. Plans to achieve even greater levels of coarse-grained concurrency by extending this approach within other components, such as the ocean, will be discussed.

EEG source space analysis of the supervised factor analytic approach for the classification of multi-directional arm movement

NASA Astrophysics Data System (ADS)

Shenoy Handiru, Vikram; Vinod, A. P.; Guan, Cuntai

2017-08-01

Objective. In electroencephalography (EEG)-based brain-computer interface (BCI) systems for motor control tasks the conventional practice is to decode motor intentions by using scalp EEG. However, scalp EEG only reveals certain limited information about the complex tasks of movement with a higher degree of freedom. Therefore, our objective is to investigate the effectiveness of source-space EEG in extracting relevant features that discriminate arm movement in multiple directions. Approach. We have proposed a novel feature extraction algorithm based on supervised factor analysis that models the data from source-space EEG. To this end, we computed the features from the source dipoles confined to Brodmann areas of interest (BA4a, BA4p and BA6). Further, we embedded class-wise labels of multi-direction (multi-class) source-space EEG to an unsupervised factor analysis to make it into a supervised learning method. Main Results. Our approach provided an average decoding accuracy of 71% for the classification of hand movement in four orthogonal directions, that is significantly higher (>10%) than the classification accuracy obtained using state-of-the-art spatial pattern features in sensor space. Also, the group analysis on the spectral characteristics of source-space EEG indicates that the slow cortical potentials from a set of cortical source dipoles reveal discriminative information regarding the movement parameter, direction. Significance. This study presents evidence that low-frequency components in the source space play an important role in movement kinematics, and thus it may lead to new strategies for BCI-based neurorehabilitation.

Multisensor data fusion for IED threat detection

NASA Astrophysics Data System (ADS)

Mees, Wim; Heremans, Roel

2012-10-01

In this paper we present the multi-sensor registration and fusion algorithms that were developed for a force protection research project in order to detect threats against military patrol vehicles. The fusion is performed at object level, using a hierarchical evidence aggregation approach. It first uses expert domain knowledge about the features used to characterize the detected threats, that is implemented in the form of a fuzzy expert system. The next level consists in fusing intra-sensor and inter-sensor information. Here an ordered weighted averaging operator is used. The object level fusion between candidate threats that are detected asynchronously on a moving vehicle by sensors with different imaging geometries, requires an accurate sensor to world coordinate transformation. This image registration will also be discussed in this paper.

When complexity science meets implementation science: a theoretical and empirical analysis of systems change.

PubMed

Braithwaite, Jeffrey; Churruca, Kate; Long, Janet C; Ellis, Louise A; Herkes, Jessica

2018-04-30

Implementation science has a core aim - to get evidence into practice. Early in the evidence-based medicine movement, this task was construed in linear terms, wherein the knowledge pipeline moved from evidence created in the laboratory through to clinical trials and, finally, via new tests, drugs, equipment, or procedures, into clinical practice. We now know that this straight-line thinking was naïve at best, and little more than an idealization, with multiple fractures appearing in the pipeline. The knowledge pipeline derives from a mechanistic and linear approach to science, which, while delivering huge advances in medicine over the last two centuries, is limited in its application to complex social systems such as healthcare. Instead, complexity science, a theoretical approach to understanding interconnections among agents and how they give rise to emergent, dynamic, systems-level behaviors, represents an increasingly useful conceptual framework for change. Herein, we discuss what implementation science can learn from complexity science, and tease out some of the properties of healthcare systems that enable or constrain the goals we have for better, more effective, more evidence-based care. Two Australian examples, one largely top-down, predicated on applying new standards across the country, and the other largely bottom-up, adopting medical emergency teams in over 200 hospitals, provide empirical support for a complexity-informed approach to implementation. The key lessons are that change can be stimulated in many ways, but a triggering mechanism is needed, such as legislation or widespread stakeholder agreement; that feedback loops are crucial to continue change momentum; that extended sweeps of time are involved, typically much longer than believed at the outset; and that taking a systems-informed, complexity approach, having regard for existing networks and socio-technical characteristics, is beneficial. Construing healthcare as a complex adaptive system implies that getting evidence into routine practice through a step-by-step model is not feasible. Complexity science forces us to consider the dynamic properties of systems and the varying characteristics that are deeply enmeshed in social practices, whilst indicating that multiple forces, variables, and influences must be factored into any change process, and that unpredictability and uncertainty are normal properties of multi-part, intricate systems.

Multi-atlas segmentation enables robust multi-contrast MRI spleen segmentation for splenomegaly

NASA Astrophysics Data System (ADS)

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L.; Assad, Albert; Abramson, Richard G.; Landman, Bennett A.

2017-02-01

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≍1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Multi-atlas Segmentation Enables Robust Multi-contrast MRI Spleen Segmentation for Splenomegaly.

PubMed

Huo, Yuankai; Liu, Jiaqi; Xu, Zhoubing; Harrigan, Robert L; Assad, Albert; Abramson, Richard G; Landman, Bennett A

2017-02-11

Non-invasive spleen volume estimation is essential in detecting splenomegaly. Magnetic resonance imaging (MRI) has been used to facilitate splenomegaly diagnosis in vivo. However, achieving accurate spleen volume estimation from MR images is challenging given the great inter-subject variance of human abdomens and wide variety of clinical images/modalities. Multi-atlas segmentation has been shown to be a promising approach to handle heterogeneous data and difficult anatomical scenarios. In this paper, we propose to use multi-atlas segmentation frameworks for MRI spleen segmentation for splenomegaly. To the best of our knowledge, this is the first work that integrates multi-atlas segmentation for splenomegaly as seen on MRI. To address the particular concerns of spleen MRI, automated and novel semi-automated atlas selection approaches are introduced. The automated approach interactively selects a subset of atlases using selective and iterative method for performance level estimation (SIMPLE) approach. To further control the outliers, semi-automated craniocaudal length based SIMPLE atlas selection (L-SIMPLE) is proposed to introduce a spatial prior in a fashion to guide the iterative atlas selection. A dataset from a clinical trial containing 55 MRI volumes (28 T1 weighted and 27 T2 weighted) was used to evaluate different methods. Both automated and semi-automated methods achieved median DSC > 0.9. The outliers were alleviated by the L-SIMPLE (≈1 min manual efforts per scan), which achieved 0.9713 Pearson correlation compared with the manual segmentation. The results demonstrated that the multi-atlas segmentation is able to achieve accurate spleen segmentation from the multi-contrast splenomegaly MRI scans.

Active Ottumwa: Adapting Evidence-Based Recommendations to Promote Physical Activity in a Micropolitan New Destination Community

PubMed Central

Baquero, Barbara; Ashida, Sato; Daniel-Ulloa, Jason; Laroche, Helena H.; Haines, Heidi; Bucklin, Rebecca; Maldonado, Adriana; Coronado Garcia, Mayra; Berto, Sandy; Sewell, Dan; Janz, Kathleen; Gates, Claudia; Parker, Edith A.

2018-01-01

Background: Evidence-based interventions have been developed and tested to promote physical activity, but fewer studies have focused on identifying effective intervention strategies for mid-size rural communities, especially new immigrant destinations. We report here on the design and implementation of Active Ottumwa, a community-wide intervention using a lay health advisor approach to increase physical activity in a micropolitan new destination community in the rural state of Iowa. Methods: The Active Ottumwa study is part of a community-academic partnership in Ottumwa, IA. Evidence-based strategies recommended by the Community Guide for Preventive Services guided study implementation and included behavioral and social, campaign and informational, and environmental and policy approaches. Evaluation methods for this study are multi-faceted and include a cross-sectional community survey, longitudinal cohort assessment, observational data, key informant interviews, and project records. Results: We are currently in our second year of intervention implementation, with 45 lay health advisors (termed physical activity leaders here) trained to carry out behavioral and social intervention approaches, including walking groups, tai chi, and yoga. We have completed a communication and informational campaign utilizing five channels. Our longitudinal cohort has been recruited, with baseline and 12-month data collection completed. Conclusions: This study will assess the effectiveness and impact of a community-wide intervention to support physical activity. PMID:29734709

Active Ottumwa: Adapting Evidence-Based Recommendations to Promote Physical Activity in a Micropolitan New Destination Community.

PubMed

Baquero, Barbara; Kava, Christine M; Ashida, Sato; Daniel-Ulloa, Jason; Laroche, Helena H; Haines, Heidi; Bucklin, Rebecca; Maldonado, Adriana; Coronado Garcia, Mayra; Berto, Sandy; Sewell, Dan; Novak, Nicole; Janz, Kathleen; Gates, Claudia; Parker, Edith A

2018-05-04

Background : Evidence-based interventions have been developed and tested to promote physical activity, but fewer studies have focused on identifying effective intervention strategies for mid-size rural communities, especially new immigrant destinations. We report here on the design and implementation of Active Ottumwa, a community-wide intervention using a lay health advisor approach to increase physical activity in a micropolitan new destination community in the rural state of Iowa. Methods : The Active Ottumwa study is part of a community-academic partnership in Ottumwa, IA. Evidence-based strategies recommended by the Community Guide for Preventive Services guided study implementation and included behavioral and social, campaign and informational, and environmental and policy approaches. Evaluation methods for this study are multi-faceted and include a cross-sectional community survey, longitudinal cohort assessment, observational data, key informant interviews, and project records. Results : We are currently in our second year of intervention implementation, with 45 lay health advisors (termed physical activity leaders here) trained to carry out behavioral and social intervention approaches, including walking groups, tai chi, and yoga. We have completed a communication and informational campaign utilizing five channels. Our longitudinal cohort has been recruited, with baseline and 12-month data collection completed. Conclusions : This study will assess the effectiveness and impact of a community-wide intervention to support physical activity.

Future Directions in Vulnerability to Depression among Youth: Integrating Risk Factors and Processes across Multiple Levels of Analysis

PubMed Central

Hankin, Benjamin L.

2014-01-01

Depression is a developmental phenomenon. Considerable progress has been made in describing the syndrome, establishing its prevalence and features, providing clues as to its etiology, and developing evidence-based treatment and prevention options. Despite considerable headway in distinct lines of vulnerability research, there is an explanatory gap in the field ability to more comprehensively explain and predict who is likely to become depressed, when, and why. Still, despite clear success in predicting moderate variance for future depression, especially with empirically rigorous methods and designs, the heterogeneous and multi-determined nature of depression suggests that additional etiologies need to be included to advance knowledge on developmental pathways to depression. This paper advocates for a multiple levels of analysis approach to investigating vulnerability to depression across the lifespan and providing a more comprehensive understanding of its etiology. One example of a multiple levels of analysis model of vulnerabilities to depression is provided that integrates the most accessible, observable factors (e.g., cognitive and temperament risks), intermediate processes and endophenotypes (e.g., information processing biases, biological stress physiology, and neural activation and connectivity), and genetic influences (e.g., candidate genes and epigenetics). Evidence for each of these factors as well as their cross-level integration is provided. Methodological and conceptual considerations important for conducting integrative, multiple levels of depression vulnerability research are discussed. Finally, translational implications for how a multiple levels of analysis perspective may confer additional leverage to reduce the global burden of depression and improve care are considered. PMID:22900513

Health behavior change models for HIV prevention and AIDS care: practical recommendations for a multi-level approach.

PubMed

Kaufman, Michelle R; Cornish, Flora; Zimmerman, Rick S; Johnson, Blair T

2014-08-15

Despite increasing recent emphasis on the social and structural determinants of HIV-related behavior, empirical research and interventions lag behind, partly because of the complexity of social-structural approaches. This article provides a comprehensive and practical review of the diverse literature on multi-level approaches to HIV-related behavior change in the interest of contributing to the ongoing shift to more holistic theory, research, and practice. It has the following specific aims: (1) to provide a comprehensive list of relevant variables/factors related to behavior change at all points on the individual-structural spectrum, (2) to map out and compare the characteristics of important recent multi-level models, (3) to reflect on the challenges of operating with such complex theoretical tools, and (4) to identify next steps and make actionable recommendations. Using a multi-level approach implies incorporating increasing numbers of variables and increasingly context-specific mechanisms, overall producing greater intricacies. We conclude with recommendations on how best to respond to this complexity, which include: using formative research and interdisciplinary collaboration to select the most appropriate levels and variables in a given context; measuring social and institutional variables at the appropriate level to ensure meaningful assessments of multiple levels are made; and conceptualizing intervention and research with reference to theoretical models and mechanisms to facilitate transferability, sustainability, and scalability.

An integrative framework for sensor-based measurement of teamwork in healthcare

PubMed Central

Rosen, Michael A; Dietz, Aaron S; Yang, Ting; Priebe, Carey E; Pronovost, Peter J

2015-01-01

There is a strong link between teamwork and patient safety. Emerging evidence supports the efficacy of teamwork improvement interventions. However, the availability of reliable, valid, and practical measurement tools and strategies is commonly cited as a barrier to long-term sustainment and spread of these teamwork interventions. This article describes the potential value of sensor-based technology as a methodology to measure and evaluate teamwork in healthcare. The article summarizes the teamwork literature within healthcare, including team improvement interventions and measurement. Current applications of sensor-based measurement of teamwork are reviewed to assess the feasibility of employing this approach in healthcare. The article concludes with a discussion highlighting current application needs and gaps and relevant analytical techniques to overcome the challenges to implementation. Compelling studies exist documenting the feasibility of capturing a broad array of team input, process, and output variables with sensor-based methods. Implications of this research are summarized in a framework for development of multi-method team performance measurement systems. Sensor-based measurement within healthcare can unobtrusively capture information related to social networks, conversational patterns, physical activity, and an array of other meaningful information without having to directly observe or periodically survey clinicians. However, trust and privacy concerns present challenges that need to be overcome through engagement of end users in healthcare. Initial evidence exists to support the feasibility of sensor-based measurement to drive feedback and learning across individual, team, unit, and organizational levels. Future research is needed to refine methods, technologies, theory, and analytical strategies. PMID:25053579

Multi-Level Building Reconstruction for Automatic Enhancement of High Resolution Dsms

NASA Astrophysics Data System (ADS)

Arefi, H.; Reinartz, P.

2012-07-01

In this article a multi-level approach is proposed for reconstruction-based improvement of high resolution Digital Surface Models (DSMs). The concept of Levels of Detail (LOD) defined by CityGML standard has been considered as basis for abstraction levels of building roof structures. Here, the LOD1 and LOD2 which are related to prismatic and parametric roof shapes are reconstructed. Besides proposing a new approach for automatic LOD1 and LOD2 generation from high resolution DSMs, the algorithm contains two generalization levels namely horizontal and vertical. Both generalization levels are applied to prismatic model of buildings. The horizontal generalization allows controlling the approximation level of building footprints which is similar to cartographic generalization concept of the urban maps. In vertical generalization, the prismatic model is formed using an individual building height and continuous to included all flat structures locating in different height levels. The concept of LOD1 generation is based on approximation of the building footprints into rectangular or non-rectangular polygons. For a rectangular building containing one main orientation a method based on Minimum Bounding Rectangle (MBR) in employed. In contrast, a Combined Minimum Bounding Rectangle (CMBR) approach is proposed for regularization of non-rectilinear polygons, i.e. buildings without perpendicular edge directions. Both MBRand CMBR-based approaches are iteratively employed on building segments to reduce the original building footprints to a minimum number of nodes with maximum similarity to original shapes. A model driven approach based on the analysis of the 3D points of DSMs in a 2D projection plane is proposed for LOD2 generation. Accordingly, a building block is divided into smaller parts according to the direction and number of existing ridge lines. The 3D model is derived for each building part and finally, a complete parametric model is formed by merging all the 3D models of the individual parts and adjusting the nodes after the merging step. In order to provide an enhanced DSM, a surface model is provided for each building by interpolation of the internal points of the generated models. All interpolated models are situated on a Digital Terrain Model (DTM) of corresponding area to shape the enhanced DSM. Proposed DSM enhancement approach has been tested on a dataset from Munich central area. The original DSM is created using robust stereo matching of Worldview-2 stereo images. A quantitative assessment of the new DSM by comparing the heights of the ridges and eaves shows a standard deviation of better than 50cm.

Recalibrating Baseline Evidence in Burundi, Malawi, Senegal and Uganda: Exploring the Potential of Multi-Site, National-Level Stakeholder Engagement in Participatory Evaluation

ERIC Educational Resources Information Center

Edge, Karen; Marphatia, Akanksha A.

2015-01-01

This paper details our collaborative work on the Improving Learning Outcomes in Primary Schools (ILOPS) project in Burundi, Malawi, Uganda and Senegal. ILOPS set out to establish an innovative template for multi-stakeholder, multinational participatory evaluation (PE) and examine the fundamental roles, relationships and evidence that underpin the…

Using a knowledge translation framework to implement asthma clinical practice guidelines in primary care.

PubMed

Licskai, Christopher; Sands, Todd; Ong, Michael; Paolatto, Lisa; Nicoletti, Ivan

2012-10-01

Quality problem International guidelines establish evidence-based standards for asthma care; however, recommendations are often not implemented and many patients do not meet control targets. Initial assessment Regional pilot data demonstrated a knowledge-to-practice gap. Choice of solutions We engineered health system change in a multi-step approach described by the Canadian Institutes of Health Research knowledge translation framework. Implementation Knowledge translation occurred at multiple levels: patient, practice and local health system. A regional administrative infrastructure and inter-disciplinary care teams were developed. The key project deliverable was a guideline-based interdisciplinary asthma management program. Six community organizations, 33 primary care physicians and 519 patients participated. The program operating cost was $290/patient. Evaluation Six guideline-based care elements were implemented, including spirometry measurement, asthma controller therapy, a written self-management action plan and general asthma education, including the inhaler device technique, role of medications and environmental control strategies in 93, 95, 86, 100, 97 and 87% of patients, respectively. Of the total patients 66% were adults, 61% were female, the mean age was 35.7 (SD = ± 24.2) years. At baseline 42% had two or more symptoms beyond acceptable limits vs. 17% (P< 0.001) post-intervention; 71% reported urgent/emergent healthcare visits at baseline (2.94 visits/year) vs. 45% (1.45 visits/year) (P< 0.001); 39% reported absenteeism (5.0 days/year) vs. 19% (3.0 days/year) (P< 0.001). The mean follow-up interval was 22 (SD = ± 7) months. Lessons learned A knowledge-translation framework can guide multi-level organizational change, facilitate asthma guideline implementation, and improve health outcomes in community primary care practices. Program costs are similar to those of diabetes programs. Program savings offset costs in a ratio of 2.1:1.

Using a knowledge translation framework to implement asthma clinical practice guidelines in primary care

PubMed Central

Licskai, Christopher; Sands, Todd; Ong, Michael; Paolatto, Lisa; Nicoletti, Ivan

2012-01-01

Quality problem International guidelines establish evidence-based standards for asthma care; however, recommendations are often not implemented and many patients do not meet control targets. Initial assessment Regional pilot data demonstrated a knowledge-to-practice gap. Choice of solutions We engineered health system change in a multi-step approach described by the Canadian Institutes of Health Research knowledge translation framework. Implementation Knowledge translation occurred at multiple levels: patient, practice and local health system. A regional administrative infrastructure and inter-disciplinary care teams were developed. The key project deliverable was a guideline-based interdisciplinary asthma management program. Six community organizations, 33 primary care physicians and 519 patients participated. The program operating cost was $290/patient. Evaluation Six guideline-based care elements were implemented, including spirometry measurement, asthma controller therapy, a written self-management action plan and general asthma education, including the inhaler device technique, role of medications and environmental control strategies in 93, 95, 86, 100, 97 and 87% of patients, respectively. Of the total patients 66% were adults, 61% were female, the mean age was 35.7 (SD = ±24.2) years. At baseline 42% had two or more symptoms beyond acceptable limits vs. 17% (P< 0.001) post-intervention; 71% reported urgent/emergent healthcare visits at baseline (2.94 visits/year) vs. 45% (1.45 visits/year) (P< 0.001); 39% reported absenteeism (5.0 days/year) vs. 19% (3.0 days/year) (P< 0.001). The mean follow-up interval was 22 (SD = ±7) months. Lessons learned A knowledge-translation framework can guide multi-level organizational change, facilitate asthma guideline implementation, and improve health outcomes in community primary care practices. Program costs are similar to those of diabetes programs. Program savings offset costs in a ratio of 2.1:1 PMID:22893665

A numerical multi-scale model to predict macroscopic material anisotropy of multi-phase steels from crystal plasticity material definitions

NASA Astrophysics Data System (ADS)

Ravi, Sathish Kumar; Gawad, Jerzy; Seefeldt, Marc; Van Bael, Albert; Roose, Dirk

2017-10-01

A numerical multi-scale model is being developed to predict the anisotropic macroscopic material response of multi-phase steel. The embedded microstructure is given by a meso-scale Representative Volume Element (RVE), which holds the most relevant features like phase distribution, grain orientation, morphology etc., in sufficient detail to describe the multi-phase behavior of the material. A Finite Element (FE) mesh of the RVE is constructed using statistical information from individual phases such as grain size distribution and ODF. The material response of the RVE is obtained for selected loading/deformation modes through numerical FE simulations in Abaqus. For the elasto-plastic response of the individual grains, single crystal plasticity based plastic potential functions are proposed as Abaqus material definitions. The plastic potential functions are derived using the Facet method for individual phases in the microstructure at the level of single grains. The proposed method is a new modeling framework and the results presented in terms of macroscopic flow curves are based on the building blocks of the approach, while the model would eventually facilitate the construction of an anisotropic yield locus of the underlying multi-phase microstructure derived from a crystal plasticity based framework.

A multi-image approach to CADx of breast cancer with integration into PACS

NASA Astrophysics Data System (ADS)

Elter, Matthias; Wittenberg, Thomas; Schulz-Wendtland, Rüdiger; Deserno, Thomas M.

2009-02-01

While screening mammography is accepted as the most adequate technique for the early detection of breast cancer, its low positive predictive value leads to many breast biopsies performed on benign lesions. Therefore, we have previously developed a knowledge-based system for computer-aided diagnosis (CADx) of mammographic lesions. It supports the radiologist in the discrimination of benign and malignant lesions. So far, our approach operates on the lesion level and employs the paradigm of content-based image retrieval (CBIR). Similar lesions with known diagnosis are retrieved automatically from a library of references. However, radiologists base their diagnostic decisions on additional resources, such as related mammographic projections, other modalities (e.g. ultrasound, MRI), and clinical data. Nonetheless, most CADx systems disregard the relation between the craniocaudal (CC) and mediolateral-oblique (MLO) views of conventional mammography. Therefore, we extend our approach to the full case level: (i) Multi-frame features are developed that jointly describe a lesion in different views of mammography. Taking into account the geometric relation between different images, these features can also be extracted from multi-modal data; (ii) the CADx system architecture is extended appropriately; (iii) the CADx system is integrated into the radiology information system (RIS) and the picture archiving and communication system (PACS). Here, the framework for image retrieval in medical applications (IRMA) is used to support access to the patient's health care record. Of particular interest is the application of the proposed CADx system to digital breast tomosynthesis (DBT), which has the potential to succeed digital mammography as the standard technique for breast cancer screening. The proposed system is a natural extension of CADx approaches that integrate only two modalities. However, we are still collecting a large enough database of breast lesions with images from multiple modalities to evaluate the benefits of the proposed approach on.

Application of machine learning classification for structural brain MRI in mood disorders: Critical review from a clinical perspective.

PubMed

Kim, Yong-Ku; Na, Kyoung-Sae

2018-01-03

Mood disorders are a highly prevalent group of mental disorders causing substantial socioeconomic burden. There are various methodological approaches for identifying the underlying mechanisms of the etiology, symptomatology, and therapeutics of mood disorders; however, neuroimaging studies have provided the most direct evidence for mood disorder neural substrates by visualizing the brains of living individuals. The prefrontal cortex, hippocampus, amygdala, thalamus, ventral striatum, and corpus callosum are associated with depression and bipolar disorder. Identifying the distinct and common contributions of these anatomical regions to depression and bipolar disorder have broadened and deepened our understanding of mood disorders. However, the extent to which neuroimaging research findings contribute to clinical practice in the real-world setting is unclear. As traditional or non-machine learning MRI studies have analyzed group-level differences, it is not possible to directly translate findings from research to clinical practice; the knowledge gained pertains to the disorder, but not to individuals. On the other hand, a machine learning approach makes it possible to provide individual-level classifications. For the past two decades, many studies have reported on the classification accuracy of machine learning-based neuroimaging studies from the perspective of diagnosis and treatment response. However, for the application of a machine learning-based brain MRI approach in real world clinical settings, several major issues should be considered. Secondary changes due to illness duration and medication, clinical subtypes and heterogeneity, comorbidities, and cost-effectiveness restrict the generalization of the current machine learning findings. Sophisticated classification of clinical and diagnostic subtypes is needed. Additionally, as the approach is inevitably limited by sample size, multi-site participation and data-sharing are needed in the future. Copyright © 2017 Elsevier Inc. All rights reserved.

Anxiety, not anger, induces inflammatory activity: An avoidance/approach model of immune system activation.

PubMed

Moons, Wesley G; Shields, Grant S

2015-08-01

Psychological stressors reliably trigger systemic inflammatory activity as indexed by levels of proinflammatory cytokines. This experiment demonstrates that one's specific emotional reaction to a stressor may be a significant determinant of whether an inflammatory reaction occurs in response to that stressor. Based on extant correlational evidence and theory, a causal approach was used to determine whether an avoidant emotion (anxiety) triggers more inflammatory activity than an approach emotion (anger). In an experimental design (N = 40), a 3-way Emotion Condition × Time × Analyte interaction revealed that a writing-based anxiety induction, but not a writing-based anger induction, increased mean levels of interferon-γ (IFN- γ) and interleukin-1β (IL-1β), but not interleukin-6 (IL-6) in oral mucous, F(2, 54) = 4.64, p = .01, ηp(²) = .15. Further, self-reported state anxiety predicted elevated levels of proinflammatory cytokines, all ΔR(²) >.06, ps <.04, but self-reported state anger did not. These results constitute the first evidence to our knowledge that specific negative emotions can differentially cause inflammatory activity and support a theoretical model explaining these effects based on the avoidance or approach motivations associated with emotions. (c) 2015 APA, all rights reserved).

Intelligent microchip networks: an agent-on-chip synthesis framework for the design of smart and robust sensor networks

NASA Astrophysics Data System (ADS)

Bosse, Stefan

2013-05-01

Sensorial materials consisting of high-density, miniaturized, and embedded sensor networks require new robust and reliable data processing and communication approaches. Structural health monitoring is one major field of application for sensorial materials. Each sensor node provides some kind of sensor, electronics, data processing, and communication with a strong focus on microchip-level implementation to meet the goals of miniaturization and low-power energy environments, a prerequisite for autonomous behaviour and operation. Reliability requires robustness of the entire system in the presence of node, link, data processing, and communication failures. Interaction between nodes is required to manage and distribute information. One common interaction model is the mobile agent. An agent approach provides stronger autonomy than a traditional object or remote-procedure-call based approach. Agents can decide for themselves, which actions are performed, and they are capable of flexible behaviour, reacting on the environment and other agents, providing some degree of robustness. Traditionally multi-agent systems are abstract programming models which are implemented in software and executed on program controlled computer architectures. This approach does not well scale to micro-chip level and requires full equipped computers and communication structures, and the hardware architecture does not consider and reflect the requirements for agent processing and interaction. We propose and demonstrate a novel design paradigm for reliable distributed data processing systems and a synthesis methodology and framework for multi-agent systems implementable entirely on microchip-level with resource and power constrained digital logic supporting Agent-On-Chip architectures (AoC). The agent behaviour and mobility is fully integrated on the micro-chip using pipelined communicating processes implemented with finite-state machines and register-transfer logic. The agent behaviour, interaction (communication), and mobility features are modelled and specified on a machine-independent abstract programming level using a state-based agent behaviour language (APL). With this APL a high-level agent compiler is able to synthesize a hardware model (RTL, VHDL), a software model (C, ML), or a simulation model (XML) suitable to simulate a multi-agent system using the SeSAm simulator framework. Agent communication is provided by a simple tuple-space database implemented on node level providing fault tolerant access of global data. A novel synthesis development kit (SynDK) based on a graph-structured database approach is introduced to support the rapid development of compilers and synthesis tools, used for example for the design and implementation of the APL compiler.

Multi-level Operational C2 Holonic Reference Architecture Modeling for MHQ with MOC

DTIC Science & Technology

2009-06-01

x), x(k), uj(k)) is defined as the task success probability, based on the asset allocation and task execution activities at the tactical level...on outcomes of asset- task allocation at the tactical level. We employ semi-Markov decision process (SMDP) approach to decide on missions to be...AGA) graph for addressing the mission monitoring/ planning issues related to task sequencing and asset allocation at the OLC-TLC layer (coordination

Automated diagnosis of Alzheimer's disease with multi-atlas based whole brain segmentations

NASA Astrophysics Data System (ADS)

Luo, Yuan; Tang, Xiaoying

2017-03-01

Voxel-based analysis is widely used in quantitative analysis of structural brain magnetic resonance imaging (MRI) and automated disease detection, such as Alzheimer's disease (AD). However, noise at the voxel level may cause low sensitivity to AD-induced structural abnormalities. This can be addressed with the use of a whole brain structural segmentation approach which greatly reduces the dimension of features (the number of voxels). In this paper, we propose an automatic AD diagnosis system that combines such whole brain segmen- tations with advanced machine learning methods. We used a multi-atlas segmentation technique to parcellate T1-weighted images into 54 distinct brain regions and extract their structural volumes to serve as the features for principal-component-analysis-based dimension reduction and support-vector-machine-based classification. The relationship between the number of retained principal components (PCs) and the diagnosis accuracy was systematically evaluated, in a leave-one-out fashion, based on 28 AD subjects and 23 age-matched healthy subjects. Our approach yielded pretty good classification results with 96.08% overall accuracy being achieved using the three foremost PCs. In addition, our approach yielded 96.43% specificity, 100% sensitivity, and 0.9891 area under the receiver operating characteristic curve.

Worker productivity outcome measures: OMERACT filter evidence and agenda for future research.

PubMed

Tang, Kenneth; Boonen, Annelies; Verstappen, Suzanne M M; Escorpizo, Reuben; Luime, Jolanda J; Lacaille, Diane; Fautrel, Bruno; Bosworth, Ailsa; Cifaldi, Mary; Gignac, Monique A M; Hofstetter, Cathy; Leong, Amye; Montie, Pam; Petersson, Ingemar F; Purcaru, Oana; Bombardier, Claire; Tugwell, Peter S; Beaton, Dorcas E

2014-01-01

The objective of the Outcome Measures in Rheumatology (OMERACT) Worker Productivity working group is to identify worker productivity outcome measures that meet the requirements of the OMERACT filter. At the OMERACT 11 Workshop, we focused on the at-work limitations/productivity component of worker productivity (i.e., presenteeism) - an area with diverse conceptualization and instrumentation approaches. Various approaches to quantify at-work limitations/productivity (e.g., single-item global and multi-item measures) were examined, and available evidence pertaining to OMERACT truth, discrimination, and feasibility were presented to conference participants. Four candidate global measures of presenteeism were put forth for a plenary vote to determine whether current evidence meets the OMERACT filter requirements. Presenteeism globals from the Work Productivity and Activity Impairment Questionnaire (72% support) and Rheumatoid Arthritis-specific Work Productivity Survey (71% support) were endorsed by conference participants; however, neither the presenteeism global item from the Health and Work Performance Questionnaire nor the Quantity and Quality method achieved the level of support required for endorsement at the present time. The plenary was also asked whether the central item from the Work Ability Index should also be considered as a candidate measure for potential endorsement in the future. Of participants at the plenary, 70% supported this presenteeism global measure. Progress was also made in other areas through discussions at individual breakout sessions. Topics examined include the merits of various multi-item measures of at-work limitations/productivity, methodological issues related to interpretability of outcome scores, and approaches to appraise and classify contextual factors of worker productivity. Feedback gathered from conference participants will inform the future research agenda of the working group.

Towards a Unified Approach to Information Integration - A review paper on data/information fusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitney, Paul D.; Posse, Christian; Lei, Xingye C.

2005-10-14

Information or data fusion of data from different sources are ubiquitous in many applications, from epidemiology, medical, biological, political, and intelligence to military applications. Data fusion involves integration of spectral, imaging, text, and many other sensor data. For example, in epidemiology, information is often obtained based on many studies conducted by different researchers at different regions with different protocols. In the medical field, the diagnosis of a disease is often based on imaging (MRI, X-Ray, CT), clinical examination, and lab results. In the biological field, information is obtained based on studies conducted on many different species. In military field, informationmore » is obtained based on data from radar sensors, text messages, chemical biological sensor, acoustic sensor, optical warning and many other sources. Many methodologies are used in the data integration process, from classical, Bayesian, to evidence based expert systems. The implementation of the data integration ranges from pure software design to a mixture of software and hardware. In this review we summarize the methodologies and implementations of data fusion process, and illustrate in more detail the methodologies involved in three examples. We propose a unified multi-stage and multi-path mapping approach to the data fusion process, and point out future prospects and challenges.« less

Super-resolved Parallel MRI by Spatiotemporal Encoding

PubMed Central

Schmidt, Rita; Baishya, Bikash; Ben-Eliezer, Noam; Seginer, Amir; Frydman, Lucio

2016-01-01

Recent studies described an alternative “ultrafast” scanning method based on spatiotemporal (SPEN) principles. SPEN demonstrates numerous potential advantages over EPI-based alternatives, at no additional expense in experimental complexity. An important aspect that SPEN still needs to achieve for providing a competitive acquisition alternative entails exploiting parallel imaging algorithms, without compromising its proven capabilities. The present work introduces a combination of multi-band frequency-swept pulses simultaneously encoding multiple, partial fields-of-view; together with a new algorithm merging a Super-Resolved SPEN image reconstruction and SENSE multiple-receiving methods. The ensuing approach enables one to reduce both the excitation and acquisition times of ultrafast SPEN acquisitions by the customary acceleration factor R, without compromises in either the ensuing spatial resolution, SAR deposition, or the capability to operate in multi-slice mode. The performance of these new single-shot imaging sequences and their ancillary algorithms were explored on phantoms and human volunteers at 3T. The gains of the parallelized approach were particularly evident when dealing with heterogeneous systems subject to major T2/T2* effects, as is the case upon single-scan imaging near tissue/air interfaces. PMID:24120293

Sustainable prevention of obesity through integrated strategies: The SPOTLIGHT project's conceptual framework and design.

PubMed

Lakerveld, Jeroen; Brug, Johannes; Bot, Sandra; Teixeira, Pedro J; Rutter, Harry; Woodward, Euan; Samdal, Oddrun; Stockley, Lynn; De Bourdeaudhuij, Ilse; van Assema, Patricia; Robertson, Aileen; Lobstein, Tim; Oppert, Jean-Michel; Adány, Róza; Nijpels, Giel

2012-09-17

The prevalence of overweight and obesity in Europe is high. It is a major cause of the overall rates of many of the main chronic (or non communicable) diseases in this region and is characterized by an unequal socio-economic distribution within the population. Obesity is largely determined by modifiable lifestyle behaviours such as low physical activity levels, sedentary behaviour and consumption of energy dense diets. It is increasingly being recognised that effective responses must go beyond interventions that only focus on a specific individual, social or environmental level and instead embrace system-based multi-level intervention approaches that address both the individual and environment. The EU-funded project "sustainable prevention of obesity through integrated strategies" (SPOTLIGHT) aims to increase and combine knowledge on the wide range of determinants of obesity in a systematic way, and to identify multi-level intervention approaches that are strong in terms of Reach, Efficacy, Adoption, Implementation and Maintenance (RE-AIM). SPOTLIGHT comprises a series of systematic reviews on: individual-level predictors of success in behaviour change obesity interventions; social and physical environmental determinants of obesity; and on the RE-AIM of multi-level interventions. An interactive web-atlas of currently running multi-level interventions will be developed, and enhancing and impeding factors for implementation will be described. At the neighbourhood level, these elements will inform the development of methods to assess obesogenicity of diverse environments, using remote imaging techniques linked to geographic information systems. The validity of these methods will be evaluated using data from surveys of health and lifestyles of adults residing in the neighbourhoods surveyed. At both the micro- and macro-levels (national and international) the different physical, economical, political and socio-cultural elements will be assessed. SPOTLIGHT offers the potential to develop approaches that combine an understanding of the obesogenicity of environments in Europe, and thus how they can be improved, with an appreciation of the individual factors that explain why people respond differently to such environments. Its findings will inform governmental authorities and professionals, academics, NGOs and private sector stakeholders engaged in the development and implementation of policies to tackle the obesity epidemic in Europe.

Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making.

PubMed

Johnston, Jill; MacDonald Gibson, Jacqueline

2015-11-27

At hazardous waste sites, volatile chemicals can migrate through groundwater and soil into buildings, a process known as vapor intrusion. Due to increasing recognition of vapor intrusion as a potential indoor air pollution source, in 2015 the U.S. Environmental Protection Agency (EPA) released a new vapor intrusion guidance document. The guidance specifies two conditions for demonstrating that remediation is needed: (1) proof of a vapor intrusion pathway; and (2) evidence that human health risks exceed established thresholds (for example, one excess cancer among 10,000 exposed people). However, the guidance lacks details on methods for demonstrating these conditions. We review current evidence suggesting that monitoring and modeling approaches commonly employed at vapor intrusion sites do not adequately characterize long-term exposure and in many cases may underestimate risks. On the basis of this evidence, we recommend specific approaches to monitoring and modeling to account for these uncertainties. We propose a value of information approach to integrate the lines of evidence at a site and determine if more information is needed before deciding whether the two conditions specified in the vapor intrusion guidance are satisfied. To facilitate data collection and decision-making, we recommend a multi-directional community engagement strategy and consideration of environment justice concerns.

Indoor Air Contamination from Hazardous Waste Sites: Improving the Evidence Base for Decision-Making

PubMed Central

Johnston, Jill; MacDonald Gibson, Jacqueline

2015-01-01

At hazardous waste sites, volatile chemicals can migrate through groundwater and soil into buildings, a process known as vapor intrusion. Due to increasing recognition of vapor intrusion as a potential indoor air pollution source, in 2015 the U.S. Environmental Protection Agency (EPA) released a new vapor intrusion guidance document. The guidance specifies two conditions for demonstrating that remediation is needed: (1) proof of a vapor intrusion pathway; and (2) evidence that human health risks exceed established thresholds (for example, one excess cancer among 10,000 exposed people). However, the guidance lacks details on methods for demonstrating these conditions. We review current evidence suggesting that monitoring and modeling approaches commonly employed at vapor intrusion sites do not adequately characterize long-term exposure and in many cases may underestimate risks. On the basis of this evidence, we recommend specific approaches to monitoring and modeling to account for these uncertainties. We propose a value of information approach to integrate the lines of evidence at a site and determine if more information is needed before deciding whether the two conditions specified in the vapor intrusion guidance are satisfied. To facilitate data collection and decision-making, we recommend a multi-directional community engagement strategy and consideration of environment justice concerns. PMID:26633433

Constraint Based Modeling Going Multicellular.

PubMed

Martins Conde, Patricia do Rosario; Sauter, Thomas; Pfau, Thomas

2016-01-01

Constraint based modeling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modeling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multi-tissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem, or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches.

Evidence-based management of otitis media: a 5S model approach.

PubMed

Wasson, J D; Yung, M W

2015-02-01

The 5S model proposes five hierarchical levels (systems, summaries, synopses, syntheses and studies) of pre-appraised evidence to guide evidence-based practice. This review aimed to identify and summarise pre-appraised evidence at the highest available 5S level for the management of different subsets of otitis media: acute otitis media, otitis media with effusion, chronic suppurative otitis media and cholesteatoma in both adults and children. Data sources were pre-appraised evidence resources. Evidence freely available from sources at the highest available level of the 5S model were summarised for this review. System level evidence exists for acute otitis media and otitis media with effusion. Summary level evidence exists for recurrent acute otitis media and medical management of chronic suppurative otitis media. There is an absence of randomised controlled trials to prove the efficacy of surgical management of chronic suppurative otitis media and cholesteatoma. Until randomised controlled trial data are generated, consensus publications on the surgical management of chronic suppurative otitis media and cholesteatoma should be used to guide best practice.

Population-based dietary approaches for the prevention of noncommunicable diseases.

PubMed

Somasundaram, Noel P; Kalupahana, Nishan Sudheera

2016-04-01

As the incidence of noncommunicable diseases such as diabetes continues to rise at an alarming rate in South-East Asia, it is imperative that urgent and population-wide strategies are adopted. The most important contributors to the rise in noncommunicable disease are a rise in mean caloric intake and a decrease in physical activity. The evidence for population-based dietary approaches to counter these factors is reviewed. Several structural and cohesive interdepartmental coordination efforts are required for effective implementation of prevention strategies. Since low- and middle-income countries may lack the frameworks for effective and integrated multi-stakeholder intervention, implementation of population-based dietary and physical-activity approaches may be delayed and may be too late for effective prevention in current at-risk cohorts. Evidence-based strategies to decrease energy intake and increase physical activity are now well established and their urgent adoption by Member States of the World Health Organization South-East Asia Region is essential. In the context of Sri Lanka, for example, it is recommended that the most effective and easy-to-implement interventions would be media campaigns, restrictions on advertisement of unhealthy foods, taxation of unhealthy foods, subsidies for production of healthy foods, and laws on nutrition labelling that introduce colour coding of packaged foods.

Sensitivity Analysis Based Approaches for Mitigating the Effects of Reducible Interval Input Uncertainty on Single- and Multi-Disciplinary Systems Using Multi-Objective Optimization

DTIC Science & Technology

2010-01-01

Multi-Disciplinary, Multi-Output Sensitivity Analysis ( MIMOSA ) .........29 3.1 Introduction to Research Thrust 1...39 3.3 MIMOSA Approach ..........................................................................................41 3.3.1...Collaborative Consistency of MIMOSA .......................................................41 3.3.2 Formulation of MIMOSA

Modeling, Materials, and Metrics: The Three-m Approach to FCS Signature Solutions

DTIC Science & Technology

2002-05-07

calculations. These multiple levels will be incorporated into the MuSES software. The four levels are described as follows: "* Radiosity - Deterministic...view-factor-based, all-diffuse solution. Very fast. Independent of user position. "* Directional Reflectivity - Radiosity with directional incident...target and environment facets (view factor with BRDF). Last ray cast bounce = radiosity solution. "* Multi-bounce path trace - Rays traced from observer

Providing NHS staff with height-adjustable workstations and behaviour change strategies to reduce workplace sitting time: protocol for the Stand More AT (SMArT) Work cluster randomised controlled trial.

PubMed

O'Connell, S E; Jackson, B R; Edwardson, C L; Yates, T; Biddle, S J H; Davies, M J; Dunstan, D; Esliger, D; Gray, L; Miller, P; Munir, F

2015-12-09

High levels of sedentary behaviour (i.e., sitting) are a risk factor for poor health. With high levels of sitting widespread in desk-based office workers, office workplaces are an appropriate setting for interventions aimed at reducing sedentary behaviour. This paper describes the development processes and proposed intervention procedures of Stand More AT (SMArT) Work, a multi-component randomised control (RCT) trial which aims to reduce occupational sitting time in desk-based office workers within the National Health Service (NHS). SMArT Work consists of 2 phases: 1) intervention development: The development of the SMArT Work intervention takes a community-based participatory research approach using the Behaviour Change Wheel. Focus groups will collect detailed information to gain a better understanding of the most appropriate strategies, to sit alongside the provision of height-adjustable workstations, at the environmental, organisational and individual level that support less occupational sitting. 2) intervention delivery and evaluation: The 12 month cluster RCT aims to reduce workplace sitting in the University Hospitals of Leicester NHS Trust. Desk-based office workers (n = 238) will be randomised to control or intervention clusters, with the intervention group receiving height-adjustable workstations and supporting techniques based on the feedback received from the development phase. Data will be collected at four time points; baseline, 3, 6 and 12 months. The primary outcome is a reduction in sitting time, measured by the activPAL(TM) micro at 12 months. Secondary outcomes include objectively measured physical activity and a variety of work-related health and psycho-social measures. A process evaluation will also take place. This study will be the first long-term, evidence-based, multi-component cluster RCT aimed at reducing occupational sitting within the NHS. This study will help form a better understanding and knowledge base of facilitators and barriers to creating a healthier work environment and contribute to health and wellbeing policy. ISRCTN10967042 . Registered 2 February 2015.

Highly Resolved Intravital Striped-illumination Microscopy of Germinal Centers

PubMed Central

Andresen, Volker; Sporbert, Anje

2014-01-01

Monitoring cellular communication by intravital deep-tissue multi-photon microscopy is the key for understanding the fate of immune cells within thick tissue samples and organs in health and disease. By controlling the scanning pattern in multi-photon microscopy and applying appropriate numerical algorithms, we developed a striped-illumination approach, which enabled us to achieve 3-fold better axial resolution and improved signal-to-noise ratio, i.e. contrast, in more than 100 µm tissue depth within highly scattering tissue of lymphoid organs as compared to standard multi-photon microscopy. The acquisition speed as well as photobleaching and photodamage effects were similar to standard photo-multiplier-based technique, whereas the imaging depth was slightly lower due to the use of field detectors. By using the striped-illumination approach, we are able to observe the dynamics of immune complex deposits on secondary follicular dendritic cells – on the level of a few protein molecules in germinal centers. PMID:24748007

[Research Progress of Multi-Model Medical Image Fusion at Feature Level].

PubMed

Zhang, Junjie; Zhou, Tao; Lu, Huiling; Wang, Huiqun

2016-04-01

Medical image fusion realizes advantage integration of functional images and anatomical images.This article discusses the research progress of multi-model medical image fusion at feature level.We firstly describe the principle of medical image fusion at feature level.Then we analyze and summarize fuzzy sets,rough sets,D-S evidence theory,artificial neural network,principal component analysis and other fusion methods’ applications in medical image fusion and get summery.Lastly,we in this article indicate present problems and the research direction of multi-model medical images in the future.

Updating Parameters for Volcanic Hazard Assessment Using Multi-parameter Monitoring Data Streams And Bayesian Belief Networks

NASA Astrophysics Data System (ADS)

Odbert, Henry; Aspinall, Willy

2014-05-01

Evidence-based hazard assessment at volcanoes assimilates knowledge about the physical processes of hazardous phenomena and observations that indicate the current state of a volcano. Incorporating both these lines of evidence can inform our belief about the likelihood (probability) and consequences (impact) of possible hazardous scenarios, forming a basis for formal quantitative hazard assessment. However, such evidence is often uncertain, indirect or incomplete. Approaches to volcano monitoring have advanced substantially in recent decades, increasing the variety and resolution of multi-parameter timeseries data recorded at volcanoes. Interpreting these multiple strands of parallel, partial evidence thus becomes increasingly complex. In practice, interpreting many timeseries requires an individual to be familiar with the idiosyncrasies of the volcano, monitoring techniques, configuration of recording instruments, observations from other datasets, and so on. In making such interpretations, an individual must consider how different volcanic processes may manifest as measureable observations, and then infer from the available data what can or cannot be deduced about those processes. We examine how parts of this process may be synthesised algorithmically using Bayesian inference. Bayesian Belief Networks (BBNs) use probability theory to treat and evaluate uncertainties in a rational and auditable scientific manner, but only to the extent warranted by the strength of the available evidence. The concept is a suitable framework for marshalling multiple strands of evidence (e.g. observations, model results and interpretations) and their associated uncertainties in a methodical manner. BBNs are usually implemented in graphical form and could be developed as a tool for near real-time, ongoing use in a volcano observatory, for example. We explore the application of BBNs in analysing volcanic data from the long-lived eruption at Soufriere Hills Volcano, Montserrat. We discuss the uncertainty of inferences, and how our method provides a route to formal propagation of uncertainties in hazard models. Such approaches provide an attractive route to developing an interface between volcano monitoring analyses and probabilistic hazard scenario analysis. We discuss the use of BBNs in hazard analysis as a tractable and traceable tool for fast, rational assimilation of complex, multi-parameter data sets in the context of timely volcanic crisis decision support.

Fast hierarchical knowledge-based approach for human face detection in color images

NASA Astrophysics Data System (ADS)

Jiang, Jun; Gong, Jie; Zhang, Guilin; Hu, Ruolan

2001-09-01

This paper presents a fast hierarchical knowledge-based approach for automatically detecting multi-scale upright faces in still color images. The approach consists of three levels. At the highest level, skin-like regions are determinated by skin model, which is based on the color attributes hue and saturation in HSV color space, as well color attributes red and green in normalized color space. In level 2, a new eye model is devised to select human face candidates in segmented skin-like regions. An important feature of the eye model is that it is independent of the scale of human face. So it is possible for finding human faces in different scale with scanning image only once, and it leads to reduction the computation time of face detection greatly. In level 3, a human face mosaic image model, which is consistent with physical structure features of human face well, is applied to judge whether there are face detects in human face candidate regions. This model includes edge and gray rules. Experiment results show that the approach has high robustness and fast speed. It has wide application perspective at human-computer interactions and visual telephone etc.

Elaboration and formalization of current scientific knowledge of risks and preventive measures illustrated by colorectal cancer.

PubMed

Giorgi, R; Gouvernet, J; Dufour, J; Degoulet, P; Laugier, R; Quilichini, F; Fieschi, M

2001-01-01

Present the method used to elaborate and formalize current scientific knowledge to provide physicians with tools available on the Internet, that enable them to evaluate individual patient risk, give personalized preventive recommendations or early screening measures. The approach suggested in this article is in line with medical procedures based on levels of evidence (Evidence-based Medicine). A cyclical process for developing recommendations allows us to quickly incorporate current scientific information. At each phase, the analysis is reevaluated by experts in the field collaborating on the project. The information is formalized through the use of levels of evidence and grades of recommendations. GLIF model is used to implement recommendations for clinical practice guidelines. The most current scientific evidence incorporated in a cyclical process includes several steps: critical analysis according to the Evidence-based Medicine method; identification of predictive factors; setting-up risk levels; identification of prevention measures; elaboration of personalized recommendation. The information technology implementation of the clinical practice guideline enables physicians to quickly obtain personalized information for their patients. Cases of colorectal prevention illustrate our approach. Integration of current scientific knowledge is an important process. The delay between the moment new information arrives and the moment the practitioner applies it, is thus reduced.

A Multi-Method Multi-Analytic Approach to Establishing Internal Construct Validity Evidence: The Sport Multidimensional Perfectionism Scale 2

ERIC Educational Resources Information Center

Gotwals, John K.; Dunn, John G. H.

2009-01-01

This article presents a chronology of three empirical studies that outline the measurement process by which two new subscales ("Doubts about Actions" and "Organization") were developed and integrated into a revised version of Dunn, Causgrove Dunn, and Syrotuik's (2002) "Sport Multidimensional Perfectionism Scale"…

The Development of Solution Focused Multi-Agency Meetings in a Psychological Service

ERIC Educational Resources Information Center

Alexander, Shiona; Sked, Heather

2010-01-01

This article outlines the successful development of multi-agency meetings as part of a staged approach aimed at supporting families and children within the Scottish Highland Council Area. Drawing on the research evidence for the factors which help to make meetings effective, a distinctive meeting structure was developed. This structure is…

Contributions of Youth Engagement to the Development of Social Capital through Community Mapping

ERIC Educational Resources Information Center

Nathaniel, Keith C.; Kinsey, Sharon B.

2013-01-01

The Multi-State North Central Extension Research Activity (NCERA), Contributions of 4-H Participation to the Development of Social Capital, identified a strategy to pilot a research method that incorporates an inquiry-based approach to understanding community level impact of youth programs. This article focuses on how youth engagement educators…

A Multi-Level Model of Moral Thinking Based on Neuroscience and Moral Psychology

ERIC Educational Resources Information Center

Jeong, Changwoo; Han, Hye Min

2011-01-01

Developments in neurobiology are providing new insights into the biological and physical features of human thinking, and brain-activation imaging methods such as functional magnetic resonance imaging have become the most dominant research techniques to approach the biological part of thinking. With the aid of neurobiology, there also have been…

American Pancreatic Association Practice Guidelines in Chronic Pancreatitis: Evidence-Based Report on Diagnostic Guidelines

PubMed Central

Conwell, Darwin L.; Lee, Linda S.; Yadav, Dhiraj; Longnecker, Daniel S.; Miller, Frank H.; Mortele, Koenraad J.; Levy, Michael J.; Kwon, Richard; Lieb, John G.; Stevens, Tyler; Toskes, Philip P.; Gardner, Timothy B.; Gelrud, Andres; Wu, Bechien U.; Forsmark, Christopher E.; Vege, Santhi S.

2016-01-01

The diagnosis of chronic pancreatitis remains challenging in early stages of the disease. This report defines the diagnostic criteria useful in the assessment of patients with suspected and established chronic pancreatitis. All current diagnostic procedures are reviewed and evidence based statements are provided about their utility and limitations. Diagnostic criteria for chronic pancreatitis are classified as definitive, probable or insufficient evidence. A diagnostic (STEP-wise; S-survey, T-tomography, E-endoscopy and P-pancreas function testing) algorithm is proposed that proceeds from a non-invasive to a more invasive approach. This algorithm maximizes specificity (low false positive rate) in subjects with chronic abdominal pain and equivocal imaging changes. Futhermore, a nomenclature is suggested to further characterize patients with established chronic pancreatitis based on TIGAR-O (T-toxic, I-idiopathic, G-genetic, A- autoimmune, R-recurrent and O-obstructive) etiology, gland morphology (Cambridge criteria) and physiologic state (exocrine, endocrine function) for uniformity across future multi-center research collaborations. This guideline will serve as a baseline manuscript that will be modified as new evidence becomes available and our knowledge of chronic pancreatitis improves. PMID:25333398

Accelerated sampling by infinite swapping of path integral molecular dynamics with surface hopping

NASA Astrophysics Data System (ADS)

Lu, Jianfeng; Zhou, Zhennan

2018-02-01

To accelerate the thermal equilibrium sampling of multi-level quantum systems, the infinite swapping limit of a recently proposed multi-level ring polymer representation is investigated. In the infinite swapping limit, the ring polymer evolves according to an averaged Hamiltonian with respect to all possible surface index configurations of the ring polymer and thus connects the surface hopping approach to the mean-field path-integral molecular dynamics. A multiscale integrator for the infinite swapping limit is also proposed to enable efficient sampling based on the limiting dynamics. Numerical results demonstrate the huge improvement of sampling efficiency of the infinite swapping compared with the direct simulation of path-integral molecular dynamics with surface hopping.

Exercise prescription for overhead athletes with shoulder pathology: a systematic review with best evidence synthesis.

PubMed

Wright, Alexis A; Hegedus, Eric J; Tarara, Daniel T; Ray, Samantha C; Dischiavi, Steven L

2018-02-01

To produce a best evidence synthesis of exercise prescription used when treating shoulder pathology in the overhead athlete. A systematic review of exercises used in overhead athletes including case studies and clinical commentaries. MEDLINE, PubMed, SPORTDiscus and CINAHL from database inception through July 8, 2016. We examined data from randomised controlled trials and prospective cohort (level I-IV evidence) studies that addressed exercise intervention in the rehabilitation of the overhead athlete with shoulder pathology. Case studies and clinical commentaries (level V evidence) were examined to account for expert opinion-based research. Data were combined using best evidence synthesis and graded (A-F) recommendations (Centre for Evidence-Based Medicine). There were 33 unique exercises in six level I-IV studies that met our inclusion criteria. Most exercises were single-plane, upper extremity exercises performed below 90 o of elevation. There were 102 unique exercises in 33 level V studies that met our inclusion criteria. These exercises emphasised plyometrics, kinetic chain and sport-specific training. Overall, evidence for exercise interventions in overhead athletes with shoulder pathology is dominated by expert opinion (grade D). There is great variability between exercise approaches suggested by experts and those investigated in research studies and the overall level of evidence is low. The strongest available evidence (level B) supports the use of single-plane, open chain upper extremity exercises performed below 90° of elevation and closed chain upper extremity exercises. Clinical expert pieces support a more advanced, global treatment approach consistent with the complex, multidimensional nature of sport. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Identification of key characteristics of male reproductive toxicants as an approach for screening and sorting mechanistic evidence.

EPA Science Inventory

The application of systematic review practices in human health assessment includes integration of multi-disciplinary evidence from epidemiological, experimental, and mechanistic studies. Although mode of action analysis relies on the evaluation of mechanistic and toxicological ou...

A high-throughput method for GMO multi-detection using a microfluidic dynamic array.

PubMed

Brod, Fábio Cristiano Angonesi; van Dijk, Jeroen P; Voorhuijzen, Marleen M; Dinon, Andréia Zilio; Guimarães, Luis Henrique S; Scholtens, Ingrid M J; Arisi, Ana Carolina Maisonnave; Kok, Esther J

2014-02-01

The ever-increasing production of genetically modified crops generates a demand for high-throughput DNA-based methods for the enforcement of genetically modified organisms (GMO) labelling requirements. The application of standard real-time PCR will become increasingly costly with the growth of the number of GMOs that is potentially present in an individual sample. The present work presents the results of an innovative approach in genetically modified crops analysis by DNA based methods, which is the use of a microfluidic dynamic array as a high throughput multi-detection system. In order to evaluate the system, six test samples with an increasing degree of complexity were prepared, preamplified and subsequently analysed in the Fluidigm system. Twenty-eight assays targeting different DNA elements, GM events and species-specific reference genes were used in the experiment. The large majority of the assays tested presented expected results. The power of low level detection was assessed and elements present at concentrations as low as 0.06 % were successfully detected. The approach proposed in this work presents the Fluidigm system as a suitable and promising platform for GMO multi-detection.

The population approach to falls injury prevention in older people: findings of a two community trial

PubMed Central

2010-01-01

Background There is a sound rationale for the population-based approach to falls injury prevention but there is currently insufficient evidence to advise governments and communities on how they can use population-based strategies to achieve desired reductions in the burden of falls-related injury. The aim of the study was to quantify the effectiveness of a streamlined (and thus potentially sustainable and cost-effective), population-based, multi-factorial falls injury prevention program for people over 60 years of age. Methods Population-based falls-prevention interventions were conducted at two geographically-defined and separate Australian sites: Wide Bay, Queensland, and Northern Rivers, NSW. Changes in the prevalence of key risk factors and changes in rates of injury outcomes within each community were compared before and after program implementation and changes in rates of injury outcomes in each community were also compared with the rates in their respective States. Results The interventions in neither community substantially decreased the rate of falls-related injury among people aged 60 years or older, although there was some evidence of reductions in occurrence of multiple falls reported by women. In addition, there was some indication of improvements in fall-related risk factors, but the magnitudes were generally modest. Conclusions The evidence suggests that low intensity population-based falls prevention programs may not be as effective as those that are intensively implemented. PMID:20167124

Identifying the Presence of Prostate Cancer in Individuals with PSA Levels <20 ng ml-1 Using Computational Data Extraction Analysis of High Dimensional Peripheral Blood Flow Cytometric Phenotyping Data.

PubMed

Cosma, Georgina; McArdle, Stéphanie E; Reeder, Stephen; Foulds, Gemma A; Hood, Simon; Khan, Masood; Pockley, A Graham

2017-01-01

Determining whether an asymptomatic individual with Prostate-Specific Antigen (PSA) levels below 20 ng ml -1 has prostate cancer in the absence of definitive, biopsy-based evidence continues to present a significant challenge to clinicians who must decide whether such individuals with low PSA values have prostate cancer. Herein, we present an advanced computational data extraction approach which can identify the presence of prostate cancer in men with PSA levels <20 ng ml -1 on the basis of peripheral blood immune cell profiles that have been generated using multi-parameter flow cytometry. Statistical analysis of immune phenotyping datasets relating to the presence and prevalence of key leukocyte populations in the peripheral blood, as generated from individuals undergoing routine tests for prostate cancer (including tissue biopsy) using multi-parametric flow cytometric analysis, was unable to identify significant relationships between leukocyte population profiles and the presence of benign disease (no prostate cancer) or prostate cancer. By contrast, a Genetic Algorithm computational approach identified a subset of five flow cytometry features ( CD 8 + CD 45 RA - CD 27 - CD 28 - ( CD 8 + Effector Memory cells); CD 4 + CD 45 RA - CD 27 - CD 28 - ( CD 4 + Terminally Differentiated Effector Memory Cells re-expressing CD45RA); CD 3 - CD 19 + (B cells); CD 3 + CD 56 + CD 8 + CD 4 + (NKT cells)) from a set of twenty features, which could potentially discriminate between benign disease and prostate cancer. These features were used to construct a prostate cancer prediction model using the k-Nearest-Neighbor classification algorithm. The proposed model, which takes as input the set of flow cytometry features, outperformed the predictive model which takes PSA values as input. Specifically, the flow cytometry-based model achieved Accuracy = 83.33%, AUC = 83.40%, and optimal ROC points of FPR = 16.13%, TPR = 82.93%, whereas the PSA-based model achieved Accuracy = 77.78%, AUC = 76.95%, and optimal ROC points of FPR = 29.03%, TPR = 82.93%. Combining PSA and flow cytometry predictors achieved Accuracy = 79.17%, AUC = 78.17% and optimal ROC points of FPR = 29.03%, TPR = 85.37%. The results demonstrate the value of computational intelligence-based approaches for interrogating immunophenotyping datasets and that combining peripheral blood phenotypic profiling with PSA levels improves diagnostic accuracy compared to using PSA test alone. These studies also demonstrate that the presence of cancer is reflected in changes in the peripheral blood immune phenotype profile which can be identified using computational analysis and interpretation of complex flow cytometry datasets.

Forthcoming Challenges in Mycotoxins Toxicology Research for Safer Food-A Need for Multi-Omics Approach.

PubMed

Dellafiora, Luca; Dall'Asta, Chiara

2017-01-04

The presence of mycotoxins in food represents a severe threat for public health and welfare, and poses relevant research challenges in the food toxicology field. Nowadays, food toxicologists have to provide answers to food-related toxicological issues, but at the same time they should provide the appropriate knowledge in background to effectively support the evidence-based decision-making in food safety. Therefore, keeping in mind that regulatory actions should be based on sound scientific findings, the present opinion addresses the main challenges in providing reliable data for supporting the risk assessment of foodborne mycotoxins.

Forthcoming Challenges in Mycotoxins Toxicology Research for Safer Food—A Need for Multi-Omics Approach

PubMed Central

Dellafiora, Luca; Dall’Asta, Chiara

2017-01-01

The presence of mycotoxins in food represents a severe threat for public health and welfare, and poses relevant research challenges in the food toxicology field. Nowadays, food toxicologists have to provide answers to food-related toxicological issues, but at the same time they should provide the appropriate knowledge in background to effectively support the evidence-based decision-making in food safety. Therefore, keeping in mind that regulatory actions should be based on sound scientific findings, the present opinion addresses the main challenges in providing reliable data for supporting the risk assessment of foodborne mycotoxins. PMID:28054977

Assessing the Impact of a Human Rights-Based Approach across a Spectrum of Change for Women's, Children's, and Adolescents' Health.

PubMed

Thomas, Rebekah; Kuruvilla, Shyama; Hinton, Rachel; Jensen, Steven L B; Magar, Veronica; Bustreo, Flavia

2015-12-10

Global momentum around women's, children's, and adolescents' health, coupled with the ambitious and equalizing agenda of the Sustainable Development Goals (SDGs), has exposed a tension between the need for comprehensive, multi-actor, rights-based approaches that seek to "close the gaps" and a growing economic and political imperative to demonstrate efficiency, effectiveness, and returns on specific investments. To address this challenge, this paper proposes a framework to measure "results" in a way that offers a more nuanced understanding of the impact of human rights-based approaches and their complexity, as well as their contextual, multi-sectoral, and evolving nature. We argue that the impact of human rights-based approaches is best measured across a spectrum of change-at the individual, programmatic, structural, and societal levels. Such an analysis would allow for more accurate assessments of the cumulative effect of these changes. The paper also underscores the long-overdue need to better define the parameters of a human rights-based approach to health. This is an important part of the research agenda on human rights and health in the context of the SDGs and the Global Strategy for Women's, Children's and Adolescents' Health, and amid calls for better measurement and greater accountability for resources, results, and rights at all levels. While this paper focuses on women's, children's, and adolescents' health, the proposed framework can apply as readily to other areas of health and provides a new frame of reference for assessing the impact of human rights-based approaches. Copyright © 2015 Thomas, Kuruvilla, Hinton, Jensen, Magar, Bustreo. This is an open access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited.

Performance management of Clostridium difficile infection in hospitals - The carrot or stick approach?

PubMed

Fitzpatrick, Fidelma; Riordan, Mary O

2016-02-01

Public and political pressure for healthcare quality indicator monitoring, specifically healthcare-associated infection (HAI) has intensified the debate regarding the merits of public reporting and target setting as policy approaches. This paper reviews the evidence for these approaches with a focus on HAI, including Clostridium difficile infection (CDI). Healthcare key performance indicators (KPIs) and associated targets have been used widely with little evaluation. While targets are associated with some HAI reductions including CDI, as their control is multi-factorial, it is likely that reductions are due to numerous, concurrent control measures. Targets may help tackle organizational-wide issues that require high level management engagement and have contributed to the increased access and influence of infection control teams. HAI public reporting has also gained traction and is mandatory in many countries despite little scientific evaluation. CDI is one of the KPIs used but there is little consensus as to the best KPI for public reporting. Countries without public reporting have also seen improvements. Using indicator-based strategies rather than evidence-based ones risk improving the KPI but not necessarily quality of care. 'Bottom-up' approaches focussing on quality improvement and innovation generated by front line staff are seen as a lever for sustainable change. Positive deviance, where the resourcefulness and problem solving abilities of staff is harnessed, enables 'bottom-up' changes with process and outcome improvements. As implementation of best practice in healthcare is dependent on behavioural and cultural change, it is most likely that a combination of 'top-down' and 'bottom-up' approaches are required for sustainable improvement. This combined approach was used to improve staff influenza vaccination rates. Regulation may initially direct the spot-light onto infection control needs but true sustainable HAI reduction will only be fostered with concurrent cultural and behavioural shifts in practice and ownership of the HAI burden across clinical, policy and management domains. It will be interesting if this approach will be increasingly used by policy makers, however, irrespective it is clear that there is a need for rigorous evaluation of our HAI policy approaches from this point forward. Copyright © 2015 Elsevier Ltd. All rights reserved.

Characterization of Evidence for Human System Risk Assessment

NASA Technical Reports Server (NTRS)

Steinberg, S. L.; Van Baalen, M.; Rossi, M.; Riccio, G.; Romero, E.; Francisco, D.

2016-01-01

Understanding the kinds of evidence available and using the best evidence to answer a question is critical to evidenced-based decision-making, and it requires synthesis of evidence from a variety of sources. Categorization of human system risks in spaceflight, in particular, focuses on how well the integration and interpretation of all available evidence informs the risk statement that describes the relationship between spaceflight hazards and an outcome of interest. A mature understanding and categorization of these risks requires: 1) sufficient characterization of risk, 2) sufficient knowledge to determine an acceptable level of risk (i.e., a standard), 3) development of mitigations to meet the acceptable level of risk, and 4) identification of factors affecting generalizability of the evidence to different design reference missions. In the medical research community, evidence is often ranked by increasing confidence in findings gleaned from observational and experimental research (e.g., "levels of evidence"). However, an approach based solely on aspects of experimental design is problematic in assessing human system risks for spaceflight. For spaceflight, the unique challenges and opportunities include: (1) The independent variables in most evidence are the hazards of spaceflight, such as space radiation or low gravity, which cannot be entirely duplicated in terrestrial (Earth-based) analogs, (2) Evidence is drawn from multiple sources including medical and mission operations, Lifetime Surveillance of Astronaut Health (LSAH), spaceflight research (LSDA), and relevant environmental & terrestrial databases, (3) Risk metrics based primarily on LSAH data are typically derived from available prevalence or incidence data, which may limit rigorous interpretation, (4) The timeframe for obtaining adequate spaceflight sample size (n) is very long, given the small population, (5) Randomized controlled trials are unattainable in spaceflight, (6) Collection of personal and environmental data on the astronaut population may create opportunities for advanced analytics and human-environment modeling that goes beyond that achieved in isolated experimental designs; and (7) Translation of relevant research to operations is a complex, transdisciplinary enterprise in which the approach must apply across the physical, biological, behavioral, and social sciences. The approach to synthesizing evidence must address both source and fidelity of data, and reflect the most general attributes of quality of evidence in science and engineering: reliability and validity. The authors are developing a two-factor approach which includes the various kinds of evidence required to understand risks and for the integrated interpretation of all evidence that is essential to develop standards and countermeasures. A unified framework for aggregating and assessing different kinds of evidence provides a consistent, traceable, evidence-based decision-making process to translate research to operations in an environment where engineers, scientists, physicians, and managers all engage in analyzing the trade space of vehicle design, standards, requirements and solutions for spaceflight.

Evidence-based interventions for preventing substance use disorders in adolescents.

PubMed

Griffin, Kenneth W; Botvin, Gilbert J

2010-07-01

Substantial progress has been made in developing prevention programs for adolescent drug abuse. The most effective interventions target salient risk and protective factors at the individual, family, and community levels and are guided by relevant psychosocial theories regarding the etiology of substance use and abuse. This article reviews the epidemiology, etiologic risk and protective factors, and evidence-based approaches that have been found to be most effective in preventing adolescent substance use and abuse. Exemplary school- and family-based prevention programs for universal (everyone in population), selected (members of at-risk groups), and indicated (at-risk individuals) target populations are reviewed, along with model community-based prevention approaches. Challenges remain in widely disseminating evidence-based prevention programs into schools, families, and communities. Copyright (c) 2010 Elsevier Inc. All rights reserved.

Evidence-Based Interventions for Preventing Substance Use Disorders in Adolescents

PubMed Central

Griffin, Kenneth W.; Botvin, Gilbert J.

2010-01-01

Synopsis Substantial progress has been made in developing prevention programs for adolescent drug abuse. The most effective interventions target salient risk and protective factors at the individual, family, and/or community levels and are guided by relevant psychosocial theories regarding the etiology of substance use and abuse. This article reviews the epidemiology, etiologic risk and protective factors, and evidence-based approaches that have been found to be most effective in preventing adolescent substance use and abuse. Exemplary school and family-based prevention programs for universal (everyone in population), selected (members of at-risk groups), and indicated (at-risk individuals) target populations are reviewed, along with model community-based prevention approaches. Challenges remain in widely disseminating evidence-based prevention programs into schools, families, and communities. PMID:20682218

Introducing a Chair-Side Novel Approach to Reach Evidence-based Periodontal Information in the Daily Periodontal Practice

PubMed Central

Dannan, Aous

2009-01-01

Background Evidence-based healthcare is not an easier approach to patient management, but should provide both clinicians and patients with greater confidence and trust in their mutual relationship. The intellectual embrace of evidence-based methods, coupled with clinical expertise and consideration of the patients individual uniqueness and requirements, is needed for all periodontal therapists if optimum care is the goal. One important element of evidence-based decision making in periodontology is the systematic review. Systematic reviews usually provide the periodontist with the highest level of evidence which should be taken into consideration when constructing any treatment plan in the dental clinic. However, reaching systematic reviews might be a time-consuming procedure that needs further personal skills. Methods In this paper, a chair-side novel approach to facilitate the incorporation of systematic reviews into daily periodontal practice is presented. It is based on three simple tools, namely, a list of suitable periodontics-related key words, a data bank of all up-to-date published systematic reviews in periodontology, and hand-made paper sheets to match the key words with their related systematic review statements. Results and Conclusions A primary validation of this method indicated the simplicity in learning and application. Keywords Chair-side; Evidence-based medicine; Periodontology; Systematic review PMID:22461868

Local variance for multi-scale analysis in geomorphometry.

PubMed

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-07-15

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements.

Local variance for multi-scale analysis in geomorphometry

PubMed Central

Drăguţ, Lucian; Eisank, Clemens; Strasser, Thomas

2011-01-01

Increasing availability of high resolution Digital Elevation Models (DEMs) is leading to a paradigm shift regarding scale issues in geomorphometry, prompting new solutions to cope with multi-scale analysis and detection of characteristic scales. We tested the suitability of the local variance (LV) method, originally developed for image analysis, for multi-scale analysis in geomorphometry. The method consists of: 1) up-scaling land-surface parameters derived from a DEM; 2) calculating LV as the average standard deviation (SD) within a 3 × 3 moving window for each scale level; 3) calculating the rate of change of LV (ROC-LV) from one level to another, and 4) plotting values so obtained against scale levels. We interpreted peaks in the ROC-LV graphs as markers of scale levels where cells or segments match types of pattern elements characterized by (relatively) equal degrees of homogeneity. The proposed method has been applied to LiDAR DEMs in two test areas different in terms of roughness: low relief and mountainous, respectively. For each test area, scale levels for slope gradient, plan, and profile curvatures were produced at constant increments with either resampling (cell-based) or image segmentation (object-based). Visual assessment revealed homogeneous areas that convincingly associate into patterns of land-surface parameters well differentiated across scales. We found that the LV method performed better on scale levels generated through segmentation as compared to up-scaling through resampling. The results indicate that coupling multi-scale pattern analysis with delineation of morphometric primitives is possible. This approach could be further used for developing hierarchical classifications of landform elements. PMID:21779138

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments.

PubMed

Roy, Nirmalya; Misra, Archan; Cook, Diane

2016-02-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional 'hidden' context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions.

Ambient and smartphone sensor assisted ADL recognition in multi-inhabitant smart environments

PubMed Central

Misra, Archan; Cook, Diane

2016-01-01

Activity recognition in smart environments is an evolving research problem due to the advancement and proliferation of sensing, monitoring and actuation technologies to make it possible for large scale and real deployment. While activities in smart home are interleaved, complex and volatile; the number of inhabitants in the environment is also dynamic. A key challenge in designing robust smart home activity recognition approaches is to exploit the users' spatiotemporal behavior and location, focus on the availability of multitude of devices capable of providing different dimensions of information and fulfill the underpinning needs for scaling the system beyond a single user or a home environment. In this paper, we propose a hybrid approach for recognizing complex activities of daily living (ADL), that lie in between the two extremes of intensive use of body-worn sensors and the use of ambient sensors. Our approach harnesses the power of simple ambient sensors (e.g., motion sensors) to provide additional ‘hidden’ context (e.g., room-level location) of an individual, and then combines this context with smartphone-based sensing of micro-level postural/locomotive states. The major novelty is our focus on multi-inhabitant environments, where we show how the use of spatiotemporal constraints along with multitude of data sources can be used to significantly improve the accuracy and computational overhead of traditional activity recognition based approaches such as coupled-hidden Markov models. Experimental results on two separate smart home datasets demonstrate that this approach improves the accuracy of complex ADL classification by over 30 %, compared to pure smartphone-based solutions. PMID:27042240

A Multi-Level Examination of Stakeholder Perspectives of Implementation of Evidence-Based Practices in a Large Urban Publicly-Funded Mental Health System

PubMed Central

Beidas, Rinad S.; Stewart, Rebecca E.; Adams, Danielle R.; Fernandez, Tara; Lustbader, Susanna; Powell, Byron J.; Aarons, Gregory; Hoagwood, Kimberly E.; Evans, Arthur C.; Hurford, Matthew O.; Rubin, Ronnie; Hadley, Trevor; Mandell, David; Barg, Frances

2015-01-01

Our goal was to identify barriers and facilitators to the implementation of evidence-based practices from the perspectives of multiple stakeholders in a large publicly funded mental health system. We completed 56 interviews with three stakeholder groups: treatment developers (n = 7), agency administrators (n = 33), and system leadership (n = 16). The three stakeholder groups converged on the importance of inner (e.g., agency competing resources and demands, therapist educational background) and outer context (e.g., funding) factors as barriers to implementation. Potential threats to implementation and sustainability included the fiscal landscape of community mental health clinics and an evolving workforce. Intervention characteristics were rarely endorsed as barriers. Inner context, outer context, and intervention characteristics were all seen as important facilitators. All stakeholders endorsed the importance of coordinated collaboration across stakeholder groups within the system to successfully implement evidence-based practices. PMID:26658692

Policies and Practices in the Delivery of HIV Services in Correctional Agencies and Facilities: Results from a Multi-Site Survey

PubMed Central

Belenko, Steven; Hiller, Matthew; Visher, Christy; Copenhaver, Michael; O’Connell, Daniel; Burdon, William; Pankow, Jennifer; Clarke, Jennifer; Oser, Carrie

2013-01-01

HIV risk is disproportionately high among incarcerated individuals. Corrections agencies have been slow to implement evidence-based guidelines and interventions for HIV prevention, testing, and treatment. The emerging field of implementation science focuses on organizational interventions to facilitate adoption and implementation of evidence-based practices. A survey of among CJ-DATS correctional agency partners revealed that HIV policies and practices in prevention, detection and medical care varied widely, with some corrections agencies and facilities closely matching national guidelines and/or implementing evidence-based interventions. Others, principally attributed to limited resources, had numerous gaps in delivery of best HIV service practices. A brief overview is provided of a new CJ-DATS cooperative research protocol, informed by the survey findings, to test an organization-level intervention to reduce HIV service delivery gaps in corrections. PMID:24078624

Importance of multi-modal approaches to effectively identify cataract cases from electronic health records

PubMed Central

Rasmussen, Luke V; Berg, Richard L; Linneman, James G; McCarty, Catherine A; Waudby, Carol; Chen, Lin; Denny, Joshua C; Wilke, Russell A; Pathak, Jyotishman; Carrell, David; Kho, Abel N; Starren, Justin B

2012-01-01

Objective There is increasing interest in using electronic health records (EHRs) to identify subjects for genomic association studies, due in part to the availability of large amounts of clinical data and the expected cost efficiencies of subject identification. We describe the construction and validation of an EHR-based algorithm to identify subjects with age-related cataracts. Materials and methods We used a multi-modal strategy consisting of structured database querying, natural language processing on free-text documents, and optical character recognition on scanned clinical images to identify cataract subjects and related cataract attributes. Extensive validation on 3657 subjects compared the multi-modal results to manual chart review. The algorithm was also implemented at participating electronic MEdical Records and GEnomics (eMERGE) institutions. Results An EHR-based cataract phenotyping algorithm was successfully developed and validated, resulting in positive predictive values (PPVs) >95%. The multi-modal approach increased the identification of cataract subject attributes by a factor of three compared to single-mode approaches while maintaining high PPV. Components of the cataract algorithm were successfully deployed at three other institutions with similar accuracy. Discussion A multi-modal strategy incorporating optical character recognition and natural language processing may increase the number of cases identified while maintaining similar PPVs. Such algorithms, however, require that the needed information be embedded within clinical documents. Conclusion We have demonstrated that algorithms to identify and characterize cataracts can be developed utilizing data collected via the EHR. These algorithms provide a high level of accuracy even when implemented across multiple EHRs and institutional boundaries. PMID:22319176

Radiative characterization of random fibrous media with long cylindrical fibers: Comparison of single- and multi-RTE approaches

NASA Astrophysics Data System (ADS)

Randrianalisoa, Jaona; Haussener, Sophia; Baillis, Dominique; Lipiński, Wojciech

2017-11-01

Radiative heat transfer is analyzed in participating media consisting of long cylindrical fibers with a diameter in the limit of geometrical optics. The absorption and scattering coefficients and the scattering phase function of the medium are determined based on the discrete-level medium geometry and optical properties of individual fibers. The fibers are assumed to be randomly oriented and positioned inside the medium. Two approaches are employed: a volume-averaged two-intensity approach referred to as multi-RTE approach and a homogenized single-intensity approach referred to as the single-RTE approach. Both approaches require effective properties, determined using direct Monte Carlo ray tracing techniques. The macroscopic radiative transfer equations (for single intensity or two volume-averaged intensities) with the corresponding effective properties are solved using Monte Carlo techniques and allow for the determination of the radiative flux distribution as well as overall transmittance and reflectance of the medium. The results are compared against predictions by the direct Monte Carlo simulation on the exact morphology. The effects of fiber volume fraction and optical properties on the effective radiative properties and the overall slab radiative characteristics are investigated. The single-RTE approach gives accurate predictions for high porosity fibrous media (porosity about 95%). The multi-RTE approach is recommended for isotropic fibrous media with porosity in the range of 79-95%.

Single Cell Multi-Omics Technology: Methodology and Application.

PubMed

Hu, Youjin; An, Qin; Sheu, Katherine; Trejo, Brandon; Fan, Shuxin; Guo, Ying

2018-01-01

In the era of precision medicine, multi-omics approaches enable the integration of data from diverse omics platforms, providing multi-faceted insight into the interrelation of these omics layers on disease processes. Single cell sequencing technology can dissect the genotypic and phenotypic heterogeneity of bulk tissue and promises to deepen our understanding of the underlying mechanisms governing both health and disease. Through modification and combination of single cell assays available for transcriptome, genome, epigenome, and proteome profiling, single cell multi-omics approaches have been developed to simultaneously and comprehensively study not only the unique genotypic and phenotypic characteristics of single cells, but also the combined regulatory mechanisms evident only at single cell resolution. In this review, we summarize the state-of-the-art single cell multi-omics methods and discuss their applications, challenges, and future directions.

Single Cell Multi-Omics Technology: Methodology and Application

PubMed Central

Hu, Youjin; An, Qin; Sheu, Katherine; Trejo, Brandon; Fan, Shuxin; Guo, Ying

2018-01-01

In the era of precision medicine, multi-omics approaches enable the integration of data from diverse omics platforms, providing multi-faceted insight into the interrelation of these omics layers on disease processes. Single cell sequencing technology can dissect the genotypic and phenotypic heterogeneity of bulk tissue and promises to deepen our understanding of the underlying mechanisms governing both health and disease. Through modification and combination of single cell assays available for transcriptome, genome, epigenome, and proteome profiling, single cell multi-omics approaches have been developed to simultaneously and comprehensively study not only the unique genotypic and phenotypic characteristics of single cells, but also the combined regulatory mechanisms evident only at single cell resolution. In this review, we summarize the state-of-the-art single cell multi-omics methods and discuss their applications, challenges, and future directions. PMID:29732369

Evidence-based management - healthcare manager viewpoints.

PubMed

Janati, Ali; Hasanpoor, Edris; Hajebrahimi, Sakineh; Sadeghi-Bazargani, Homayoun

2018-06-11

Purpose Hospital manager decisions can have a significant impact on service effectiveness and hospital success, so using an evidence-based approach can improve hospital management. The purpose of this paper is to identify evidence-based management (EBMgt) components and challenges. Consequently, the authors provide an improving evidence-based decision-making framework. Design/methodology/approach A total of 45 semi-structured interviews were conducted in 2016. The authors also established three focus group discussions with health service managers. Data analysis followed deductive qualitative analysis guidelines. Findings Four basic themes emerged from the interviews, including EBMgt evidence sources (including sub-themes: scientific and research evidence, facts and information, political-social development plans, managers' professional expertise and ethical-moral evidence); predictors (sub-themes: stakeholder values and expectations, functional behavior, knowledge, key competencies and skill, evidence sources, evidence levels, uses and benefits and government programs); EBMgt barriers (sub-themes: managers' personal characteristics, decision-making environment, training and research system and organizational issues); and evidence-based hospital management processes (sub-themes: asking, acquiring, appraising, aggregating, applying and assessing). Originality/value Findings suggest that most participants have positive EBMgt attitudes. A full evidence-based hospital manager is a person who uses all evidence sources in a six-step decision-making process. EBMgt frameworks are a good tool to manage healthcare organizations. The authors found factors affecting hospital EBMgt and identified six evidence sources that healthcare managers can use in evidence-based decision-making processes.

A map of community-based obesity prevention initiatives in Australia following obesity funding 2009–2013

PubMed Central

Whelan, Jillian; Love, Penny; Romanus, Anne; Pettman, Tahna; Bolton, Kristy; Smith, Erin; Gill, Tim; Coveney, John; Waters, Elizabeth; Allender, Steve

2015-01-01

Abstract Objective: Obesity is the single biggest public health threat to developed and developing economies. In concert with healthy public policy, multi-strategy, multi-level community-based initiatives appear promising in preventing obesity, with several countries trialling this approach. In Australia, multiple levels of government have funded and facilitated a range of community-based obesity prevention initiatives (CBI), heterogeneous in their funding, timing, target audience and structure. This paper aims to present a central repository of CBI operating in Australia during 2013, to facilitate knowledge exchange and shared opportunities for learning, and to guide professional development towards best practice for CBI practitioners. Methods: A comprehensive search of government, non-government and community websites was undertaken to identify CBI in Australia in 2013. This was supplemented with data drawn from available reports, personal communication and key informant interviews. The data was translated into an interactive map for use by preventive health practitioners and other parties. Results: We identified 259 CBI; with the majority (84%) having a dual focus on physical activity and healthy eating. Few initiatives, (n=37) adopted a four-pronged multi-strategy approach implementing policy, built environment, social marketing and/or partnership building. Conclusion: This comprehensive overview of Australian CBI has the potential to facilitate engagement and collaboration through knowledge exchange and information sharing amongst CBI practitioners, funders, communities and researchers. Implications: An enhanced understanding of current practice highlights areas of strengths and opportunities for improvement to maximise the impact of obesity prevention initiatives. PMID:25561083

A map of community-based obesity prevention initiatives in Australia following obesity funding 2009-2013.

PubMed

Whelan, Jillian; Love, Penny; Romanus, Anne; Pettman, Tahna; Bolton, Kristy; Smith, Erin; Gill, Tim; Coveney, John; Waters, Elizabeth; Allender, Steve

2015-04-01

Obesity is the single biggest public health threat to developed and developing economies. In concert with healthy public policy, multi-strategy, multi-level community-based initiatives appear promising in preventing obesity, with several countries trialling this approach. In Australia, multiple levels of government have funded and facilitated a range of community-based obesity prevention initiatives (CBI), heterogeneous in their funding, timing, target audience and structure. This paper aims to present a central repository of CBI operating in Australia during 2013, to facilitate knowledge exchange and shared opportunities for learning, and to guide professional development towards best practice for CBI practitioners. A comprehensive search of government, non-government and community websites was undertaken to identify CBI in Australia in 2013. This was supplemented with data drawn from available reports, personal communication and key informant interviews. The data was translated into an interactive map for use by preventive health practitioners and other parties. We identified 259 CBI; with the majority (84%) having a dual focus on physical activity and healthy eating. Few initiatives, (n=37) adopted a four-pronged multi-strategy approach implementing policy, built environment, social marketing and/or partnership building. This comprehensive overview of Australian CBI has the potential to facilitate engagement and collaboration through knowledge exchange and information sharing amongst CBI practitioners, funders, communities and researchers. An enhanced understanding of current practice highlights areas of strengths and opportunities for improvement to maximise the impact of obesity prevention initiatives. © 2015 Public Health Association of Australia.

Understanding the Common Elements of Evidence-Based Practice: Misconceptions and Clinical Examples

ERIC Educational Resources Information Center

Chorpita, Bruce F.; Becker, Kimberly D.; Daleiden, Eric L.

2007-01-01

In this article, the authors proposed a distillation and matching model (DMM) that describes how evidence-based treatment operations can be conceptualized at a lower order level of analysis than simply by their manuals. Also referred to as the "common elements" approach, this model demonstrates the feasibility of coding and identifying the…

Cell Motility Dynamics: A Novel Segmentation Algorithm to Quantify Multi-Cellular Bright Field Microscopy Images

PubMed Central

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications. PMID:22096600

Cell motility dynamics: a novel segmentation algorithm to quantify multi-cellular bright field microscopy images.

PubMed

Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan

2011-01-01

Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.

Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

USGS Publications Warehouse

Velpuri, Naga Manohar; Senay, Gabriel B.

2012-01-01

Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80% of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in-situ datasets. In this study, we used 12 years (1998–2009) of existing multi-source satellite and model-assimilated global weather data. We use calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of Gibe III dam using three different approaches such as (a historical approach, a knowledge-based approach, and a nonparametric bootstrap resampling approach) to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8–10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 2 m (95% confidence) compared to the lake level modelled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modelling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas along the Lake Turkana shoreline that are vulnerable to fluctuations in lake levels were also identified. This study demonstrates the effectiveness of using existing multi-source satellite data in a basic modeling framework to assess the potential hydrological impact of an upstream dam on a terminal downstream lake. The results obtained from this study could also be used to evaluate alternate dam-filling scenarios and assess the potential impact of the dam on Lake Turkana under different operational strategies.

Multi-parameter phenotypic profiling: using cellular effects to characterize small-molecule compounds.

PubMed

Feng, Yan; Mitchison, Timothy J; Bender, Andreas; Young, Daniel W; Tallarico, John A

2009-07-01

Multi-parameter phenotypic profiling of small molecules provides important insights into their mechanisms of action, as well as a systems level understanding of biological pathways and their responses to small molecule treatments. It therefore deserves more attention at an early step in the drug discovery pipeline. Here, we summarize the technologies that are currently in use for phenotypic profiling--including mRNA-, protein- and imaging-based multi-parameter profiling--in the drug discovery context. We think that an earlier integration of phenotypic profiling technologies, combined with effective experimental and in silico target identification approaches, can improve success rates of lead selection and optimization in the drug discovery process.

Combining evidence, biomedical literature and statistical dependence: new insights for functional annotation of gene sets

PubMed Central

Aubry, Marc; Monnier, Annabelle; Chicault, Celine; de Tayrac, Marie; Galibert, Marie-Dominique; Burgun, Anita; Mosser, Jean

2006-01-01

Background Large-scale genomic studies based on transcriptome technologies provide clusters of genes that need to be functionally annotated. The Gene Ontology (GO) implements a controlled vocabulary organised into three hierarchies: cellular components, molecular functions and biological processes. This terminology allows a coherent and consistent description of the knowledge about gene functions. The GO terms related to genes come primarily from semi-automatic annotations made by trained biologists (annotation based on evidence) or text-mining of the published scientific literature (literature profiling). Results We report an original functional annotation method based on a combination of evidence and literature that overcomes the weaknesses and the limitations of each approach. It relies on the Gene Ontology Annotation database (GOA Human) and the PubGene biomedical literature index. We support these annotations with statistically associated GO terms and retrieve associative relations across the three GO hierarchies to emphasise the major pathways involved by a gene cluster. Both annotation methods and associative relations were quantitatively evaluated with a reference set of 7397 genes and a multi-cluster study of 14 clusters. We also validated the biological appropriateness of our hybrid method with the annotation of a single gene (cdc2) and that of a down-regulated cluster of 37 genes identified by a transcriptome study of an in vitro enterocyte differentiation model (CaCo-2 cells). Conclusion The combination of both approaches is more informative than either separate approach: literature mining can enrich an annotation based only on evidence. Text-mining of the literature can also find valuable associated MEDLINE references that confirm the relevance of the annotation. Eventually, GO terms networks can be built with associative relations in order to highlight cooperative and competitive pathways and their connected molecular functions. PMID:16674810

From the EBM pyramid to the Greek temple: a new conceptual approach to Guidelines as implementation tools in mental health.

PubMed

Salvador-Carulla, L; Lukersmith, S; Sullivan, W

2017-04-01

Guideline methods to develop recommendations dedicate most effort around organising discovery and corroboration knowledge following the evidence-based medicine (EBM) framework. Guidelines typically use a single dimension of information, and generally discard contextual evidence and formal expert knowledge and consumer's experiences in the process. In recognition of the limitations of guidelines in complex cases, complex interventions and systems research, there has been significant effort to develop new tools, guides, resources and structures to use alongside EBM methods of guideline development. In addition to these advances, a new framework based on the philosophy of science is required. Guidelines should be defined as implementation decision support tools for improving the decision-making process in real-world practice and not only as a procedure to optimise the knowledge base of scientific discovery and corroboration. A shift from the model of the EBM pyramid of corroboration of evidence to the use of broader multi-domain perspective graphically depicted as 'Greek temple' could be considered. This model takes into account the different stages of scientific knowledge (discovery, corroboration and implementation), the sources of knowledge relevant to guideline development (experimental, observational, contextual, expert-based and experiential); their underlying inference mechanisms (deduction, induction, abduction, means-end inferences) and a more precise definition of evidence and related terms. The applicability of this broader approach is presented for the development of the Canadian Consensus Guidelines for the Primary Care of People with Developmental Disabilities.

Adopting an Evidence-Based Lifestyle Physical Activity Program: Dissemination Study Design and Methods.

PubMed

Dunn, Andrea L; Buller, David B; Dearing, James W; Cutter, Gary; Guerra, Michele; Wilcox, Sara; Bettinghaus, Erwin P

2012-06-01

BACKGROUND: There is a scarcity of research studies that have examined academic-commercial partnerships to disseminate evidence-based physical activity programs. Understanding this approach to dissemination is essential because academic-commercial partnerships are increasingly common. Private companies have used dissemination channels and strategies to a degree that academicians have not, and declining resources require academicians to explore these partnerships. PURPOSE: This paper describes a retrospective case-control study design including the methods, demographics, organizational decision-making, implementation rates, and marketing strategy for Active Living Every Day (ALED), an evidence-based lifestyle physical activity program that has been commercially available since 2001. Evidence-based public health promotion programs rely on organizations and targeted sectors to disseminate these programs although relatively little is known about organizational-level and sector-level influences that lead to their adoption and implementation. METHODS: Cases (n=154) were eligible if they had signed an ALED license agreement with Human Kinetics (HK), publisher of the program's textbooks and facilitator manuals, between 2001 and 2008. Two types of controls were matched (2:2:1) and stratified by sector and region. Active controls (Control 1; n=319) were organizations that contacted HK to consider adopting ALED. Passive controls (Control 2; n=328) were organizations that received unsolicited marketing materials and did not initiate contact with HK. We used Diffusion of Innovations Theory (DIT) constructs as the basis for developing the survey of cases and controls. RESULTS: Using the multi-method strategy recommended by Dillman, a total of n=801 cases and controls were surveyed. Most organizations were from the fitness sector followed by medical, nongovernmental, governmental, educational, worksite and other sectors with significantly higher response rates from government, educational and medical sectors compared with fitness and other sectors, (p=0.02). More cases reported being involved in the decision to adopt ALED (p<0.0001). Data indicate that a low percentage of controls had ever heard of ALED despite repeated marketing and offering other types of physical activity programs and services. Finally, slightly over half of the adopters reported they had actually implemented the ALED program. CONCLUSION: Dissemination research requires new perspectives and designs to produce valid insights about the results of dissemination efforts. This study design, survey methods and theoretically-based questions can serve as a useful model for other evidence-based public health interventions that are marketed by commercial publishers to better understand key issues related to adoption and implementation of evidence-based programs.

Do Prophylactic Foam Dressings Reduce Heel Pressure Injuries?

PubMed

Ramundo, Janet; Pike, Catlin; Pittman, Joyce

The purpose of this evidence-based report card is to examine the evidence and provide recommendations related to the effectiveness of prophylactic foam dressings in reducing heel pressure injuries. Do prophylactic foam dressings applied to the heel reduce heel pressure injuries for patients in the acute care setting? A search of the literature was performed by a trained university librarian that resulted in 56 articles that examined pressure injury, prevention, and prophylactic dressings. A systematic approach was used to review titles, abstracts, and text, yielding 13 studies that met inclusion criteria. Strength of the evidence was rated based on the methodology from Essential Evidence Plus: Levels of Evidence and Oxford Center for Evidence-Based Medicine. Thirteen studies were identified that met inclusion criteria; 1 was a randomized controlled trial, 2 were systematic reviews, 3 quasi-experimental cohort studies, 1 quality improvement study, 1 case series, 1 scoping review, 1 consensus panel, and 3 bench studies. All of the studies identified suggest that the use of prophylactic foam dressings reduces the development of pressure injuries on the heel when used in conjunction with a pressure injury prevention program. The strength of the evidence for the identified studies was level 1 (4 level A, 4 level B, and 5 level C). The use of prophylactic multilayer foam dressings applied to the heels, in conjunction with an evidence-based pressure injury prevention program, is recommended for prevention of pressure injuries on the heel (SORT level 1).

From Synergy to Complexity: The Trend Toward Integrated Value Chain and Landscape Governance.

PubMed

Ros-Tonen, Mirjam A F; Reed, James; Sunderland, Terry

2018-07-01

This Editorial introduces a special issue that illustrates a trend toward integrated landscape approaches. Whereas two papers echo older "win-win" strategies based on the trade of non-timber forest products, ten papers reflect a shift from a product to landscape perspective. However, they differ from integrated landscape approaches in that they emanate from sectorial approaches driven primarily by aims such as forest restoration, sustainable commodity sourcing, natural resource management, or carbon emission reduction. The potential of such initiatives for integrated landscape governance and achieving landscape-level outcomes has hitherto been largely unaddressed in the literature on integrated landscape approaches. This special issue addresses this gap, with a focus on actor constellations and institutional arrangements emerging in the transition from sectorial to integrated approaches. This editorial discusses the trends arising from the papers, including the need for a commonly shared concern and sense of urgency; inclusive stakeholder engagement; accommodating and coordinating polycentric governance in landscapes beset with institutional fragmentation and jurisdictional mismatches; alignment with locally embedded initiatives and governance structures; and a framework to assess and monitor the performance of integrated multi-stakeholder approaches. We conclude that, despite a growing tendency toward integrated approaches at the landscape level, inherent landscape complexity renders persistent and significant challenges such as balancing multiple objectives, equitable inclusion of all relevant stakeholders, dealing with power and gender asymmetries, adaptive management based on participatory outcome monitoring, and moving beyond existing administrative, jurisdictional, and sectorial silos. Multi-stakeholder platforms and bridging organizations and individuals are seen as key in overcoming such challenges.

Methodological flaws introduce strong bias into molecular analysis of microbial populations.

PubMed

Krakat, N; Anjum, R; Demirel, B; Schröder, P

2017-02-01

In this study, we report how different cell disruption methods, PCR primers and in silico analyses can seriously bias results from microbial population studies, with consequences for the credibility and reproducibility of the findings. Our results emphasize the pitfalls of commonly used experimental methods that can seriously weaken the interpretation of results. Four different cell lysis methods, three commonly used primer pairs and various computer-based analyses were applied to investigate the microbial diversity of a fermentation sample composed of chicken dung. The fault-prone, but still frequently used, amplified rRNA gene restriction analysis was chosen to identify common weaknesses. In contrast to other studies, we focused on the complete analytical process, from cell disruption to in silico analysis, and identified potential error rates. This identified a wide disagreement of results between applied experimental approaches leading to very different community structures depending on the chosen approach. The interpretation of microbial diversity data remains a challenge. In order to accurately investigate the taxonomic diversity and structure of prokaryotic communities, we suggest a multi-level approach combining DNA-based and DNA-independent techniques. The identified weaknesses of commonly used methods to study microbial diversity can be overcome by a multi-level approach, which produces more reliable data about the fate and behaviour of microbial communities of engineered habitats such as biogas plants, so that the best performance can be ensured. © 2016 The Society for Applied Microbiology.

Taxonomy of multi-focal nematode image stacks by a CNN based image fusion approach.

PubMed

Liu, Min; Wang, Xueping; Zhang, Hongzhong

2018-03-01

In the biomedical field, digital multi-focal images are very important for documentation and communication of specimen data, because the morphological information for a transparent specimen can be captured in form of a stack of high-quality images. Given biomedical image stacks containing multi-focal images, how to efficiently extract effective features from all layers to classify the image stacks is still an open question. We present to use a deep convolutional neural network (CNN) image fusion based multilinear approach for the taxonomy of multi-focal image stacks. A deep CNN based image fusion technique is used to combine relevant information of multi-focal images within a given image stack into a single image, which is more informative and complete than any single image in the given stack. Besides, multi-focal images within a stack are fused along 3 orthogonal directions, and multiple features extracted from the fused images along different directions are combined by canonical correlation analysis (CCA). Because multi-focal image stacks represent the effect of different factors - texture, shape, different instances within the same class and different classes of objects, we embed the deep CNN based image fusion method within a multilinear framework to propose an image fusion based multilinear classifier. The experimental results on nematode multi-focal image stacks demonstrated that the deep CNN image fusion based multilinear classifier can reach a higher classification rate (95.7%) than that by the previous multilinear based approach (88.7%), even we only use the texture feature instead of the combination of texture and shape features as in the previous work. The proposed deep CNN image fusion based multilinear approach shows great potential in building an automated nematode taxonomy system for nematologists. It is effective to classify multi-focal image stacks. Copyright © 2018 Elsevier B.V. All rights reserved.

Lessons learned from recruiting nursing homes to a quantitative cross-sectional pilot study.

PubMed

Tzouvara, Vasiliki; Papadopoulos, Chris; Randhawa, Gurch

2016-03-01

A growing older adult population is leading to increased admission rates to long-term care facilities such as nursing homes and residential care homes. Assisted healthcare services should be flexible, integrated, and responsive to older adults' needs. However, there is a limited body of empirical evidence because of the recruitment challenges in these settings. To describe the barriers and challenges faced in recruiting to a recent pilot study, consider previously implemented and proposed recruitment strategies, and propose a new multi-method approach to maximising recruitment of care homes. The proposed multi-method approach harnesses key recruitment strategies previously highlighted as effective in navigating the many challenges and barriers that are likely to be encountered, such as mistrust, scepticism and concerns about disruption to routines. This includes making strategic use of existing personal and professional connections within the research team, engaging with care homes that have previously engaged with the research process, forming relationships of trust, and employing a range of incentives. Implementing carefully planned recruitment strategies is likely to improve relationships between nursing homes and researchers. As a consequence, recruitment can be augmented which can enable the production of rigorous evidence required for achieving effective nursing practice and patient wellbeing. Boosting recruitment rates is crucial in helping to build new and less biased research evidence and for informing and underpinning all forms of evidence-based practice. The lessons learned from our pilot and the review of the literature highlight these issues and better enable investigators to access research settings that commonly possess many complex recruitment barriers and challenges.

Statin Selection in Qatar Based on Multi-indication Pharmacotherapeutic Multi-criteria Scoring Model, and Clinician Preference.

PubMed

Al-Badriyeh, Daoud; Fahey, Michael; Alabbadi, Ibrahim; Al-Khal, Abdullatif; Zaidan, Manal

2015-12-01

Statin selection for the largest hospital formulary in Qatar is not systematic, not comparative, and does not consider the multi-indication nature of statins. There are no reports in the literature of multi-indication-based comparative scoring models of statins or of statin selection criteria weights that are based primarily on local clinicians' preferences and experiences. This study sought to comparatively evaluate statins for first-line therapy in Qatar, and to quantify the economic impact of this. An evidence-based, multi-indication, multi-criteria pharmacotherapeutic model was developed for the scoring of statins from the perspective of the main health care provider in Qatar. The literature and an expert panel informed the selection criteria of statins. Relative weighting of selection criteria was based on the input of the relevant local clinician population. Statins were comparatively scored based on literature evidence, with those exceeding a defined scoring threshold being recommended for use. With 95% CI and 5% margin of error, the scoring model was successfully developed. Selection criteria comprised 28 subcriteria under the following main criteria: clinical efficacy, best publish evidence and experience, adverse effects, drug interaction, dosing time, and fixed dose combination availability. Outcome measures for multiple indications were related to effects on LDL cholesterol, HDL cholesterol, triglyceride, total cholesterol, and C-reactive protein. Atorvastatin, pravastatin, and rosuvastatin exceeded defined pharmacotherapeutic thresholds. Atorvastatin and pravastatin were recommended as first-line use and rosuvastatin as a nonformulary alternative. It was estimated that this would produce a 17.6% cost savings in statins expenditure. Sensitivity analyses confirmed the robustness of the evaluation's outcomes against input uncertainties. Incorporating a comparative evaluation of statins in Qatari practices based on a locally developed, transparent, multi-indication, multi-criteria scoring model has the potential to considerably reduce expenditures on statins. Atorvastatin and pravastatin should be the first-line statin therapies in the main Qatari health care provider, with rosuvastatin as an alternative. Copyright © 2015 Elsevier HS Journals, Inc. All rights reserved.

A novel multi-scale adaptive sampling-based approach for energy saving in leak detection for WSN-based water pipelines

NASA Astrophysics Data System (ADS)

Saqib, Najam us; Faizan Mysorewala, Muhammad; Cheded, Lahouari

2017-12-01

In this paper, we propose a novel monitoring strategy for a wireless sensor networks (WSNs)-based water pipeline network. Our strategy uses a multi-pronged approach to reduce energy consumption based on the use of two types of vibration sensors and pressure sensors, all having different energy levels, and a hierarchical adaptive sampling mechanism to determine the sampling frequency. The sampling rate of the sensors is adjusted according to the bandwidth of the vibration signal being monitored by using a wavelet-based adaptive thresholding scheme that calculates the new sampling frequency for the following cycle. In this multimodal sensing scheme, the duty-cycling approach is used for all sensors to reduce the sampling instances, such that the high-energy, high-precision (HE-HP) vibration sensors have low duty cycles, and the low-energy, low-precision (LE-LP) vibration sensors have high duty cycles. The low duty-cycling (HE-HP) vibration sensor adjusts the sampling frequency of the high duty-cycling (LE-LP) vibration sensor. The simulated test bed considered here consists of a water pipeline network which uses pressure and vibration sensors, with the latter having different energy consumptions and precision levels, at various locations in the network. This is all the more useful for energy conservation for extended monitoring. It is shown that by using the novel features of our proposed scheme, a significant reduction in energy consumption is achieved and the leak is effectively detected by the sensor node that is closest to it. Finally, both the total energy consumed by monitoring as well as the time to detect the leak by a WSN node are computed, and show the superiority of our proposed hierarchical adaptive sampling algorithm over a non-adaptive sampling approach.

Population-based health promotion perspective for older driver safety: Conceptual framework to intervention plan

PubMed Central

Classen, Sherrilene; Lopez, Ellen DS; Winter, Sandra; Awadzi, Kezia D; Ferree, Nita; Garvan, Cynthia W

2007-01-01

The topic of motor vehicle crashes among the elderly is dynamic and multi-faceted requiring a comprehensive and synergistic approach to intervention planning. This approach must be based on the values of a given population as well as health statistics and asserted through community, organizational and policy strategies. An integrated summary of the predictors (quantitative research), and views (qualitative research) of the older drivers and their stakeholders, does not currently exist. This study provided an explicit socio-ecological view explaining the interrelation of possible causative factors, an integrated summary of these causative factors, and empirical guidelines for developing public health interventions to promote older driver safety. Using a mixed methods approach, we were able to compare and integrate main findings from a national crash dataset with perspectives of stakeholders. We identified: 11 multi-causal factors for safe elderly driving; the importance of the environmental factors - previously underrated in the literature- interacting with behavioral and health factors; and the interrelatedness among many socio-ecological factors. For the first time, to our knowledge, we conceptualized the fundamental elements of a multi-causal health promotion plan, with measurable intermediate and long-term outcomes. After completing the detailed plan we will test the effectiveness of this intervention on multiple levels. PMID:18225470

The potential of neuroscience for health sciences education: towards convergence of evidence and resisting seductive allure.

PubMed

de Bruin, Anique B H

2016-12-01

Since emergence of the field 'Educational Neuroscience' (EN) in the late nineties of the previous century, a debate has emerged about the potential this field holds to influence teaching and learning in the classroom. By now, most agree that the original claims promising direct translations to teaching and learning were too strong. I argue here that research questions in (health professions) education require multi-methodological approaches, including neuroscience, while carefully weighing what (combination of) approaches are most suitable given a research question. Only through a multi-methodological approach will convergence of evidence emerge, which is so desperately needed for improving teaching and learning in the classroom. However, both researchers and teachers should become aware of the so-called 'seductive allure' of EN; that is, the demonstrable physical location and apparent objectivity of the measurements can be interpreted as yielding more powerful evidence and warranting stronger conclusions than, e.g., behavioral experiments, where in fact oftentimes the reverse is the case. I conclude that our tendency as researchers to commit ourselves to one methodological approach and to addressing educational research questions from a single methodological perspective is limiting progress in educational science and in translation to education.

An efficient method for the fusion of light field refocused images

NASA Astrophysics Data System (ADS)

Wang, Yingqian; Yang, Jungang; Xiao, Chao; An, Wei

2018-04-01

Light field cameras have drawn much attention due to the advantage of post-capture adjustments such as refocusing after exposure. The depth of field in refocused images is always shallow because of the large equivalent aperture. As a result, a large number of multi-focus images are obtained and an all-in-focus image is demanded. Consider that most multi-focus image fusion algorithms do not particularly aim at large numbers of source images and traditional DWT-based fusion approach has serious problems in dealing with lots of multi-focus images, causing color distortion and ringing effect. To solve this problem, this paper proposes an efficient multi-focus image fusion method based on stationary wavelet transform (SWT), which can deal with a large quantity of multi-focus images with shallow depth of fields. We compare SWT-based approach with DWT-based approach on various occasions. And the results demonstrate that the proposed method performs much better both visually and quantitatively.

Evidence-based practice of transfusion medicine: is it possible and what do the words mean?

PubMed

Vamvakas, Eleftherios C

2004-10-01

Evidence-based medicine (EBM) optimizes clinical decision making by dictating that clinical decisions be based on the best available research evidence and by integrating best research evidence with clinical expertise and patient values. Several rankings of the strength of the evidence generated from different types of clinical research designs have been presented, and, in addressing a particular problem, clinicians can base their decision making on the types of clinical reports that have been published, along with an assessment of the strengths and weaknesses of each study. At a policy level, the concept of EBM would dictate that policy decisions also be made based on the best available research evidence. In transfusion medicine, however, decisions are based on a broader range of inputs, and the criteria for evaluating the efficacy and/or cost-effectiveness of proposed interventions differ from those used in other areas. Reasons why policy decisions are often based on considerations other than the best research evidence include public expectations about transfusion safety and proposals for applying the precautionary principle to transfusion medicine. Using the debate over the appropriateness of introducing universal white-cell reduction as an example, this review describes 2 perspectives for assessing evidence and/or making clinical or policy decisions: the evidence-based approach and the precautionary-principle approach; and also considers whether decisions in transfusion medicine can be truly evidence based.

Pattern Search in Multi-structure Data: A Framework for the Next-Generation Evidence-based Medicine

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sukumar, Sreenivas R; Ainsworth, Keela C

With the advent of personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledge-bases) to predict diagnostic risks is fast emerging. Addressing this need, we pose and address the following questions (i) How can we jointly analyze both qualitative and quantitative data ? (ii) Is the fusion of multi-structure data expected to provide better insights than either of them individually ? We present experiments on two bio-medical data sets - mammography and traumatic brain studies to demonstrate architectures and tools for evidence-pattern search.

Multi-species data integration and gene ranking enrich significant results in an alcoholism genome-wide association study.

PubMed

Zhao, Zhongming; Guo, An-Yuan; van den Oord, Edwin J C G; Aliev, Fazil; Jia, Peilin; Edenberg, Howard J; Riley, Brien P; Dick, Danielle M; Bettinger, Jill C; Davies, Andrew G; Grotewiel, Michael S; Schuckit, Marc A; Agrawal, Arpana; Kramer, John; Nurnberger, John I; Kendler, Kenneth S; Webb, Bradley T; Miles, Michael F

2012-01-01

A variety of species and experimental designs have been used to study genetic influences on alcohol dependence, ethanol response, and related traits. Integration of these heterogeneous data can be used to produce a ranked target gene list for additional investigation. In this study, we performed a unique multi-species evidence-based data integration using three microarray experiments in mice or humans that generated an initial alcohol dependence (AD) related genes list, human linkage and association results, and gene sets implicated in C. elegans and Drosophila. We then used permutation and false discovery rate (FDR) analyses on the genome-wide association studies (GWAS) dataset from the Collaborative Study on the Genetics of Alcoholism (COGA) to evaluate the ranking results and weighting matrices. We found one weighting score matrix could increase FDR based q-values for a list of 47 genes with a score greater than 2. Our follow up functional enrichment tests revealed these genes were primarily involved in brain responses to ethanol and neural adaptations occurring with alcoholism. These results, along with our experimental validation of specific genes in mice, C. elegans and Drosophila, suggest that a cross-species evidence-based approach is useful to identify candidate genes contributing to alcoholism.

Cesarean section rate in Iran, multidimensional approaches for behavioral change of providers: a qualitative study

PubMed Central

2011-01-01

Background The cesarean section rate has been steadily rising from 35% in 2000 to 40% in 2005 in Iran. The objective of this study was to identify barriers of reduce the cesarean section rate in Iran, as perceived by obstetricians and midwives as the main behavioral change target groups. Methods A qualitative study with purposive sampling was designed in which data were collected through in-depth interviews and document analyses. Hospitals were selected on the bases of being public and or private and their response to the ministry's C-section reduction interventions. The hospital director, obstetricians and midwives from each hospital were included in the study. The classification of barriers suggested by Grol and Wensing was used for the thematic analysis. Results After 26 in-depth interviews and document analyses, the barriers were identified as: financial, insurance and judicial problems at the economic and political context level; the type and ownership of hospitals, absence of an on call physician, absence of clear job-descriptions for obstetricians and midwives, too many interventions in the delivery process and shortage of human resources and facilities at the organizational context level; distrust and insufficient collaborations between obstetricians and midwives from macro to micro level at the social context level; attitudes toward complications of C-section, reduced capabilities of obstetricians, midwives and residents at the individual professional level; and finally, at the innovation level, vaginal delivery is time consuming, imposes high stress levels and is unpredictable. Conclusion Changing service providers' behavior is not possible through presentation of scientific evidence alone. A multi-level and multidisciplinary approach using behavior change theories is unavoidable. In future studies, the effect of the barriers should be determined to help policy makers recognize the most effective interventional package. PMID:21729279

Maintenance Cognitive Stimulation Therapy (CST) for dementia: A single-blind, multi-centre, randomized controlled trial of Maintenance CST vs. CST for dementia

PubMed Central

2010-01-01

Background Psychological treatments for dementia are widely used in the UK and internationally, but only rarely have they been standardised, adequately evaluated or systematically implemented. There is increasing recognition that psychosocial interventions may have similar levels of effectiveness to medication, and both can be used in combination. Cognitive Stimulation Therapy (CST) is a 7-week cognitive-based approach for dementia that has been shown to be beneficial for cognition and quality of life and is cost-effective, but there is less conclusive evidence for the effects of CST over an extended period. Methods/Design This multi-centre, pragmatic randomised controlled trial (RCT) to assess the effectiveness and cost-effectiveness of Maintenance CST groups for dementia compares a intervention group who receive CST for 7 weeks followed by the Maintenance CST programme once a week for 24 weeks with the control group who receive CST for 7 weeks, followed by treatment as usual for 24 weeks. The primary outcome measures are quality of life of people with dementia assessed by the QoL-AD and cognition assessed by the ADAS-Cog. Secondary outcomes include the person with dementia's mood, behaviour, activities of daily living, ability to communicate and costs; as well as caregiver health-related quality of life. Using a 5% significance level, comparison of 230 participants will yield 80% power to detect a standardised difference of 0.39 on the ADAS-Cog between the groups. The trial includes a cost-effectiveness analysis from a public sector perspective. Discussion A pilot study of longer-term Maintenance CST, offering 16 weekly sessions of maintenance following the initial CST programme, previously found a significant improvement in cognitive function (MMSE) for those on the intervention group. The study identified the need for a large-scale, multi-centre RCT to define the potential longer-term benefits of continuing the therapy. This study aims to provide definitive evidence of the potential efficacy of maintenance CST and establish how far the long-term benefits can be compared with antidementia drugs such as cholinesterase inhibitors. Trial Registration ISRCTN26286067 PMID:20426866

Maintenance Cognitive Stimulation Therapy (CST) for dementia: a single-blind, multi-centre, randomized controlled trial of Maintenance CST vs. CST for dementia.

PubMed

Aguirre, Elisa; Spector, Aimee; Hoe, Juanita; Russell, Ian T; Knapp, Martin; Woods, Robert T; Orrell, Martin

2010-04-28

Psychological treatments for dementia are widely used in the UK and internationally, but only rarely have they been standardised, adequately evaluated or systematically implemented. There is increasing recognition that psychosocial interventions may have similar levels of effectiveness to medication, and both can be used in combination. Cognitive Stimulation Therapy (CST) is a 7-week cognitive-based approach for dementia that has been shown to be beneficial for cognition and quality of life and is cost-effective, but there is less conclusive evidence for the effects of CST over an extended period. This multi-centre, pragmatic randomised controlled trial (RCT) to assess the effectiveness and cost-effectiveness of Maintenance CST groups for dementia compares a intervention group who receive CST for 7 weeks followed by the Maintenance CST programme once a week for 24 weeks with the control group who receive CST for 7 weeks, followed by treatment as usual for 24 weeks.The primary outcome measures are quality of life of people with dementia assessed by the QoL-AD and cognition assessed by the ADAS-Cog. Secondary outcomes include the person with dementia's mood, behaviour, activities of daily living, ability to communicate and costs; as well as caregiver health-related quality of life. Using a 5% significance level, comparison of 230 participants will yield 80% power to detect a standardised difference of 0.39 on the ADAS-Cog between the groups. The trial includes a cost-effectiveness analysis from a public sector perspective. A pilot study of longer-term Maintenance CST, offering 16 weekly sessions of maintenance following the initial CST programme, previously found a significant improvement in cognitive function (MMSE) for those on the intervention group. The study identified the need for a large-scale, multi-centre RCT to define the potential longer-term benefits of continuing the therapy. This study aims to provide definitive evidence of the potential efficacy of maintenance CST and establish how far the long-term benefits can be compared with antidementia drugs such as cholinesterase inhibitors.

Evidence-informed decision-making by professionals working in addiction agencies serving women: a descriptive qualitative study.

PubMed

Jack, Susan M; Dobbins, Maureen; Sword, Wendy; Novotna, Gabriela; Brooks, Sandy; Lipman, Ellen L; Niccols, Alison

2011-11-07

Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions.

Evidence-informed decision-making by professionals working in addiction agencies serving women: a descriptive qualitative study

PubMed Central

2011-01-01

Background Effective approaches to the prevention and treatment of substance abuse among mothers have been developed but not widely implemented. Implementation studies suggest that the adoption of evidence-based practices in the field of addictions remains low. There is a need, therefore, to better understand decision making processes in addiction agencies in order to develop more effective approaches to promote the translation of knowledge gained from addictions research into clinical practice. Methods A descriptive qualitative study was conducted to explore: 1) the types and sources of evidence used to inform practice-related decisions within Canadian addiction agencies serving women; 2) how decision makers at different levels report using research evidence; and 3) factors that influence evidence-informed decision making. A purposeful sample of 26 decision-makers providing addiction treatment services to women completed in-depth qualitative interviews. Interview data were coded and analyzed using directed and summative content analysis strategies as well as constant comparison techniques. Results Across all groups, individuals reported locating and using multiple types of evidence to inform decisions. Some decision-makers rely on their experiential knowledge of addiction and recovery in decision-making. Research evidence is often used directly in decision-making at program management and senior administrative levels. Information for decision-making is accessed from a range of sources, including web-based resources and experts in the field. Individual and organizational facilitators and barriers to using research evidence in decision making were identified. Conclusions There is support at administrative levels for integrating EIDM in addiction agencies. Knowledge transfer and exchange strategies should be focussed towards program managers and administrators and include capacity building for locating, appraising and using research evidence, knowledge brokering, and for partnering with universities. Resources are required to maintain web-based databases of searchable evidence to facilitate access to research evidence. A need exists to address the perception that there is a paucity of research evidence available to inform program decisions. Finally, there is a need to consider how experiential knowledge influences decision-making and what guidance research evidence has to offer regarding the implementation of different treatment approaches within the field of addictions. PMID:22059528

A multi-valued neutrosophic qualitative flexible approach based on likelihood for multi-criteria decision-making problems

NASA Astrophysics Data System (ADS)

Peng, Juan-juan; Wang, Jian-qiang; Yang, Wu-E.

2017-01-01

In this paper, multi-criteria decision-making (MCDM) problems based on the qualitative flexible multiple criteria method (QUALIFLEX), in which the criteria values are expressed by multi-valued neutrosophic information, are investigated. First, multi-valued neutrosophic sets (MVNSs), which allow the truth-membership function, indeterminacy-membership function and falsity-membership function to have a set of crisp values between zero and one, are introduced. Then the likelihood of multi-valued neutrosophic number (MVNN) preference relations is defined and the corresponding properties are also discussed. Finally, an extended QUALIFLEX approach based on likelihood is explored to solve MCDM problems where the assessments of alternatives are in the form of MVNNs; furthermore an example is provided to illustrate the application of the proposed method, together with a comparison analysis.

Development of Evidence-Based Health Policy Documents in Developing Countries: A Case of Iran

PubMed Central

Imani-Nasab, Mohammad Hasan; Seyedin, Hesam; Majdzadeh, Reza; Yazdizadeh, Bahareh; Salehi, Masoud

2014-01-01

Background: Evidence-based policy documents that are well developed by senior civil servants and are timely available can reduce the barriers to evidence utilization by health policy makers. This study examined the barriers and facilitators in developing evidence-based health policy documents from the perspective of their producers in a developing country. Methods: In a qualitative study with a framework analysis approach, we conducted semi-structured interviews using purposive and snowball sampling. A qualitative analysis software (MAXQDA-10) was used to apply the codes and manage the data. This study was theory-based and the results were compared to exploratory studies about the factors influencing evidence-based health policymaking. Results: 18 codes and three main themes of behavioral, normative, and control beliefs were identified. Factors that influence the development of evidence-based policy documents were identified by the participants: behavioral beliefs included quality of policy documents, use of resources, knowledge and innovation, being time-consuming and contextualization; normative beliefs included policy authorities, policymakers, policy administrators, and co-workers; and control beliefs included recruitment policy, performance management, empowerment, management stability, physical environment, access to evidence, policy making process, and effect of other factors. Conclusion: Most of the cited barriers to the development of evidence-based policy were related to control beliefs, i.e. barriers at the organizational and health system levels. This study identified the factors that influence the development of evidence-based policy documents based on the components of the theory of planned behavior. But in exploratory studies on evidence utilization by health policymakers, the identified factors were only related to control behaviors. This suggests that the theoretical approach may be preferable to the exploratory approach in identifying the barriers and facilitators of a behavior. PMID:24762343

Development of evidence-based health policy documents in developing countries: a case of Iran.

PubMed

Imani-Nasab, Mohammad Hasan; Seyedin, Hesam; Majdzadeh, Reza; Yazdizadeh, Bahareh; Salehi, Masoud

2014-02-07

Evidence-based policy documents that are well developed by senior civil servants and are timely available can reduce the barriers to evidence utilization by health policy makers. This study examined the barriers and facilitators in developing evidence-based health policy documents from the perspective of their producers in a developing country. In a qualitative study with a framework analysis approach, we conducted semi-structured interviews using purposive and snowball sampling. A qualitative analysis software (MAXQDA-10) was used to apply the codes and manage the data. This study was theory-based and the results were compared to exploratory studies about the factors influencing evidence-based health policy-making. 18 codes and three main themes of behavioral, normative, and control beliefs were identified. Factors that influence the development of evidence-based policy documents were identified by the participants: behavioral beliefs included quality of policy documents, use of resources, knowledge and innovation, being time-consuming and contextualization; normative beliefs included policy authorities, policymakers, policy administrators, and co-workers; and control beliefs included recruitment policy, performance management, empowerment, management stability, physical environment, access to evidence, policy making process, and effect of other factors. Most of the cited barriers to the development of evidence-based policy were related to control beliefs, i.e. barriers at the organizational and health system levels. This study identified the factors that influence the development of evidence-based policy documents based on the components of the theory of planned behavior. But in exploratory studies on evidence utilization by health policymakers, the identified factors were only related to control behaviors. This suggests that the theoretical approach may be preferable to the exploratory approach in identifying the barriers and facilitators of a behavior.

Multi-locus and long amplicon sequencing approach to study microbial diversity at species level using the MinION™ portable nanopore sequencer

PubMed Central

Sanz, Yolanda

2017-01-01

Abstract The miniaturized and portable DNA sequencer MinION™ has demonstrated great potential in different analyses such as genome-wide sequencing, pathogen outbreak detection and surveillance, human genome variability, and microbial diversity. In this study, we tested the ability of the MinION™ platform to perform long amplicon sequencing in order to design new approaches to study microbial diversity using a multi-locus approach. After compiling a robust database by parsing and extracting the rrn bacterial region from more than 67000 complete or draft bacterial genomes, we demonstrated that the data obtained during sequencing of the long amplicon in the MinION™ device using R9 and R9.4 chemistries were sufficient to study 2 mock microbial communities in a multiplex manner and to almost completely reconstruct the microbial diversity contained in the HM782D and D6305 mock communities. Although nanopore-based sequencing produces reads with lower per-base accuracy compared with other platforms, we presented a novel approach consisting of multi-locus and long amplicon sequencing using the MinION™ MkIb DNA sequencer and R9 and R9.4 chemistries that help to overcome the main disadvantage of this portable sequencing platform. Furthermore, the nanopore sequencing library, constructed with the last releases of pore chemistry (R9.4) and sequencing kit (SQK-LSK108), permitted the retrieval of the higher level of 1D read accuracy sufficient to characterize the microbial species present in each mock community analysed. Improvements in nanopore chemistry, such as minimizing base-calling errors and new library protocols able to produce rapid 1D libraries, will provide more reliable information in the near future. Such data will be useful for more comprehensive and faster specific detection of microbial species and strains in complex ecosystems. PMID:28605506

Evidence-based approach to HIV/AIDS policy and research prioritization in the Islamic Republic of Iran.

PubMed

Feizzadeh, A; Nedjat, S; Asghari, S; Keshtkar, A; Heshmat, R; Setayesh, H; Majdzadeh, R

2010-03-01

In formulating the second national strategic plan for prevention of HIV/AIDS in the Islamic Republic of Iran a more evidence-based approach was needed. This paper reports on a systematic review of the local evidence about the determinants of HIV/AIDS transmission in 3 categories: poor knowledge and negative attitudes about HIV transmission; injection drug use; and sexual promiscuity. Of 93 reports reviewed, 53 met the inclusion criteria. Information about the prevalence and magnitude of effect for the 3 risk determinants at the national and regional level was scarce. Heterogeneity between studies, even in the same sub-population, was significant. An improved research base and better sharing of information are needed within countries of the Eastern Mediterranean Region.

The Robust Learning Model (RLM): A Comprehensive Approach to a New Online University

ERIC Educational Resources Information Center

Neumann, Yoram; Neumann, Edith F.

2010-01-01

This paper outlines the components of the Robust Learning Model (RLM) as a conceptual framework for creating a new online university offering numerous degree programs at all degree levels. The RLM is a multi-factorial model based on the basic belief that successful learning outcomes depend on multiple factors employed together in a holistic…

Multi-Level Steering and Institution Building: The European Union's Approach to Research Policy

ERIC Educational Resources Information Center

Young, Mitchell

2012-01-01

Adopting the conception of the university as a primary driver of innovation and economic growth has brought increased pressure for the European Union (EU) to actively steer university-based research policy, despite its being outside of the EU's direct jurisdiction. While the open method of coordination (OMC) was developed for such situations, the…

Implementation of evidence-based weekend service recommendations for allied health managers: a cluster randomised controlled trial protocol.

PubMed

Sarkies, Mitchell N; White, Jennifer; Morris, Meg E; Taylor, Nicholas F; Williams, Cylie; O'Brien, Lisa; Martin, Jenny; Bardoel, Anne; Holland, Anne E; Carey, Leeanne; Skinner, Elizabeth H; Bowles, Kelly-Ann; Grant, Kellie; Philip, Kathleen; Haines, Terry P

2018-04-24

It is widely acknowledged that health policy and practice do not always reflect current research evidence. Whether knowledge transfer from research to practice is more successful when specific implementation approaches are used remains unclear. A model to assist engagement of allied health managers and clinicians with research implementation could involve disseminating evidence-based policy recommendations, along with the use of knowledge brokers. We developed such a model to aid decision-making for the provision of weekend allied health services. This protocol outlines the design and methods for a multi-centre cluster randomised controlled trial to evaluate the success of research implementation strategies to promote evidence-informed weekend allied health resource allocation decisions, especially in hospital managers. This multi-centre study will be a three-group parallel cluster randomised controlled trial. Allied health managers from Australian and New Zealand hospitals will be randomised to receive either (1) an evidence-based policy recommendation document to guide weekend allied health resource allocation decisions, (2) the same policy recommendation document with support from a knowledge broker to help implement weekend allied health policy recommendations, or (3) a usual practice control group. The primary outcome will be alignment of weekend allied health service provision with policy recommendations. This will be measured by the number of allied health service events (occasions of service) occurring on weekends as a proportion of total allied health service events for the relevant hospital wards at baseline and 12-month follow-up. Evidence-based policy recommendation documents communicate key research findings in an accessible format. This comparatively low-cost research implementation strategy could be combined with using a knowledge broker to work collaboratively with decision-makers to promote knowledge transfer. The results will assist managers to make decisions on resource allocation, based on evidence. More generally, the findings will inform the development of an allied health model for translating research into practice. This trial is registered with the Australian New Zealand Clinical Trials Registry (ANZCTR) ( ACTRN12618000029291 ). Universal Trial Number (UTN): U1111-1205-2621.

Multi-Element Behaviour Support as a Model for the Delivery of a Human Rights Based Approach for Working with People with Intellectual Disabilities and Behaviours that Challenge

ERIC Educational Resources Information Center

Doody, Christina

2009-01-01

This paper demonstrates the effectiveness of the multi-element behaviour support (MEBS) model in meeting the rights of persons with intellectual disabilities and behaviours that challenge. It does this through explicitly linking the multi-element model to the guiding principles of a human rights based approach (HRBA) using a vignette to…

The Childhood Obesity Declines Project: Implications for Research and Evaluation Approaches.

PubMed

Young-Hyman, Deborah; Morris, Kathryn; Kettel Khan, Laura; Dawkins-Lyn, Nicola; Dooyema, Carrie; Harris, Carole; Jernigan, Jan; Ottley, Phyllis; Kauh, Tina

2018-03-01

Childhood obesity remains prevalent and is increasing in some disadvantaged populations. Numerous research, policy and community initiatives are undertaken to impact this pandemic. Understudied are natural experiments. The need to learn from these efforts is paramount. Resulting evidence may not be readily available to inform future research, community initiatives, and policy development/implementation. We discuss the implications of using an adaptation of the Systematic Screening and Assessment (SSA) method to evaluate the Childhood Obesity Declines (COBD) project. The project examined successful initiatives, programs and policies in four diverse communities which were concurrent with significant declines in child obesity. In the context of other research designs and evaluation schemas, rationale for use of SSA is presented. Evidence generated by this method is highlighted and guidance suggested for evaluation of future studies of community-based childhood obesity prevention initiatives. Support for the role of stakeholder collaboratives, in particular the National Collaborative on Childhood Obesity Research, as a synergistic vehicle to accelerate research on childhood obesity is discussed. SSA mapped active processes and provided contextual understanding of multi-level/component simultaneous efforts to reduce rates of childhood obesity in community settings. Initiatives, programs and policies were not necessarily coordinated. And although direct attribution of intervention/initiative/policy components could not be made, the what, by who, how, to whom was temporally associated with statistically significant reductions in childhood obesity. SSA provides evidence for context and processes which are not often evaluated in other data analytic methods. SSA provides an additional tool to layer with other evaluation approaches.

Using a multi-scale approach to identify and quantify oil and gas emissions: a case study for GHG emissions verification

NASA Astrophysics Data System (ADS)

Sweeney, C.; Kort, E. A.; Rella, C.; Conley, S. A.; Karion, A.; Lauvaux, T.; Frankenberg, C.

2015-12-01

Along with a boom in oil and natural gas production in the US, there has been a substantial effort to understand the true environmental impact of these operations on air and water quality, as well asnet radiation balance. This multi-institution effort funded by both governmental and non-governmental agencies has provided a case study for identification and verification of emissions using a multi-scale, top-down approach. This approach leverages a combination of remote sensing to identify areas that need specific focus and airborne in-situ measurements to quantify both regional and large- to mid-size single-point emitters. Ground-based networks of mobile and stationary measurements provide the bottom tier of measurements from which process-level information can be gathered to better understand the specific sources and temporal distribution of the emitters. The motivation for this type of approach is largely driven by recent work in the Barnett Shale region in Texas as well as the San Juan Basin in New Mexico and Colorado; these studies suggest that relatively few single-point emitters dominate the regional emissions of CH4.

Multi-energy CT based on a prior rank, intensity and sparsity model (PRISM).

PubMed

Gao, Hao; Yu, Hengyong; Osher, Stanley; Wang, Ge

2011-11-01

We propose a compressive sensing approach for multi-energy computed tomography (CT), namely the prior rank, intensity and sparsity model (PRISM). To further compress the multi-energy image for allowing the reconstruction with fewer CT data and less radiation dose, the PRISM models a multi-energy image as the superposition of a low-rank matrix and a sparse matrix (with row dimension in space and column dimension in energy), where the low-rank matrix corresponds to the stationary background over energy that has a low matrix rank, and the sparse matrix represents the rest of distinct spectral features that are often sparse. Distinct from previous methods, the PRISM utilizes the generalized rank, e.g., the matrix rank of tight-frame transform of a multi-energy image, which offers a way to characterize the multi-level and multi-filtered image coherence across the energy spectrum. Besides, the energy-dependent intensity information can be incorporated into the PRISM in terms of the spectral curves for base materials, with which the restoration of the multi-energy image becomes the reconstruction of the energy-independent material composition matrix. In other words, the PRISM utilizes prior knowledge on the generalized rank and sparsity of a multi-energy image, and intensity/spectral characteristics of base materials. Furthermore, we develop an accurate and fast split Bregman method for the PRISM and demonstrate the superior performance of the PRISM relative to several competing methods in simulations.

Strategies for efficient numerical implementation of hybrid multi-scale agent-based models to describe biological systems

PubMed Central

Cilfone, Nicholas A.; Kirschner, Denise E.; Linderman, Jennifer J.

2015-01-01

Biologically related processes operate across multiple spatiotemporal scales. For computational modeling methodologies to mimic this biological complexity, individual scale models must be linked in ways that allow for dynamic exchange of information across scales. A powerful methodology is to combine a discrete modeling approach, agent-based models (ABMs), with continuum models to form hybrid models. Hybrid multi-scale ABMs have been used to simulate emergent responses of biological systems. Here, we review two aspects of hybrid multi-scale ABMs: linking individual scale models and efficiently solving the resulting model. We discuss the computational choices associated with aspects of linking individual scale models while simultaneously maintaining model tractability. We demonstrate implementations of existing numerical methods in the context of hybrid multi-scale ABMs. Using an example model describing Mycobacterium tuberculosis infection, we show relative computational speeds of various combinations of numerical methods. Efficient linking and solution of hybrid multi-scale ABMs is key to model portability, modularity, and their use in understanding biological phenomena at a systems level. PMID:26366228

A Multi-Level Approach to Outreach for Geologic Sequestration Projects

USGS Publications Warehouse

Greenberg, S.E.; Leetaru, H.E.; Krapac, I.G.; Hnottavange-Telleen, K.; Finley, R.J.

2009-01-01

Public perception of carbon capture and sequestration (CCS) projects represents a potential barrier to commercialization. Outreach to stakeholders at the local, regional, and national level is needed to create familiarity with and potential acceptance of CCS projects. This paper highlights the Midwest Geological Sequestration Consortium (MGSC) multi-level outreach approach which interacts with multiple stakeholders. The MGSC approach focuses on external and internal communication. External communication has resulted in building regional public understanding of CCS. Internal communication, through a project Risk Assessment process, has resulted in enhanced team communication and preparation of team members for outreach roles. ?? 2009 Elsevier Ltd. All rights reserved.

Shape coexistence and the role of axial asymmetry in 72Ge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ayangeakaa, A. D.; Janssens, R. F.; Wu, C. Y.

2016-01-22

The quadrupole collectivity of low-lying states and the anomalous behavior of the0 + 2 and 2 + 3 levels in 72Ge are investigated via projectile multi-step Coulomb excitation with GRETINA and CHICO-2. A total of forty six E2 and M1 matrix elements connecting fourteen low-lying levels were determined using the least-squares search code, GOSIA. Evidence for triaxiality and shape coexistence, based on the model-independent shape invariants deduced from the Kumar–Cline sum rule, is presented. Moreover, these are interpreted using a simple two-state mixing model as well as multi-state mixing calculations carried out within the framework of the triaxial rotor model.more » Our results represent a significant milestone towards the understanding of the unusual structure of this nucleus.« less

Multi-frequency Defect Selective Imaging via Nonlinear Ultrasound

NASA Astrophysics Data System (ADS)

Solodov, Igor; Busse, Gerd

The concept of defect-selective ultrasonic nonlinear imaging is based on visualization of strongly nonlinear inclusions in the form of localized cracked defects. For intense excitation, the ultrasonic response of defects is affected by mechanical constraint between their fragments that makes their vibrations extremely nonlinear. The cracked flaws, therefore, efficiently generate multiple new frequencies, which can be used as a nonlinear "tag" to detect and image them. In this paper, the methodologies of nonlinear scanning laser vibrometry (NSLV) and nonlinear air-coupled emission (NACE) are applied for nonlinear imaging of various defects in hi-tech and constructional materials. A broad database obtained demonstrates evident advantages of the nonlinear approach over its linear counterpart. The higher-order nonlinear frequencies provide increase in signal-to-noise ratio and enhance the contrast of imaging. Unlike conventional ultrasonic instruments, the nonlinear approach yields abundant multi-frequency information on defect location. The application of image recognition and processing algorithms is described and shown to improve reliability and quality of ultrasonic imaging.

Bayesian Multi-Trait Analysis Reveals a Useful Tool to Increase Oil Concentration and to Decrease Toxicity in Jatropha curcas L.

PubMed Central

Silva Junqueira, Vinícius; de Azevedo Peixoto, Leonardo; Galvêas Laviola, Bruno; Lopes Bhering, Leonardo; Mendonça, Simone; Agostini Costa, Tania da Silveira; Antoniassi, Rosemar

2016-01-01

The biggest challenge for jatropha breeding is to identify superior genotypes that present high seed yield and seed oil content with reduced toxicity levels. Therefore, the objective of this study was to estimate genetic parameters for three important traits (weight of 100 seed, oil seed content, and phorbol ester concentration), and to select superior genotypes to be used as progenitors in jatropha breeding. Additionally, the genotypic values and the genetic parameters estimated under the Bayesian multi-trait approach were used to evaluate different selection indices scenarios of 179 half-sib families. Three different scenarios and economic weights were considered. It was possible to simultaneously reduce toxicity and increase seed oil content and weight of 100 seed by using index selection based on genotypic value estimated by the Bayesian multi-trait approach. Indeed, we identified two families that present these characteristics by evaluating genetic diversity using the Ward clustering method, which suggested nine homogenous clusters. Future researches must integrate the Bayesian multi-trait methods with realized relationship matrix, aiming to build accurate selection indices models. PMID:27281340

Towards a Multi-Resolution Model of Seismic Risk in Central Asia. Challenge and perspectives

NASA Astrophysics Data System (ADS)

Pittore, M.; Wieland, M.; Bindi, D.; Parolai, S.

2011-12-01

Assessing seismic risk, defined as the probability of occurrence of economical and social losses as consequence of an earthquake, both at regional and at local scale is a challenging, multi-disciplinary task. In order to provide a reliable estimate, diverse information must be gathered by seismologists, geologists, engineers and civil authorities, and carefully integrated keeping into account the different levels of uncertainty. The research towards an integrated methodology, able to seamlessly describe seismic risk at different spatial scales is challenging, but discloses new application perspectives, particularly in those countries which suffer from a relevant seismic hazard but do not have resources for a standard assessment. Central Asian countries in particular, which exhibit one of the highest seismic hazard in the world, are experiencing a steady demographic growth, often accompanied by informal settlement and urban sprawling. A reliable evaluation of how these factors affect the seismic risk, together with a realistic assessment of the assets exposed to seismic hazard and their structural vulnerability is of particular importance, in order to undertake proper mitigation actions and to promptly and efficiently react to a catastrophic event. New strategies are needed to efficiently cope with systematic lack of information and uncertainties. An original approach is presented to assess seismic risk based on integration of information coming from remote-sensing and ground-based panoramic imaging, in situ measurements, expert knowledge and already available data. Efficient sampling strategies based on freely available medium-resolution multi-spectral satellite images are adopted to optimize data collection and validation, in a multi-scale approach. Panoramic imaging is also considered as a valuable ground-based visual data collection technique, suitable both for manual and automatic analysis. A full-probabilistic framework based on Bayes Network is proposed to integrate available information taking into account both aleatory and epistemic uncertainties. An improved risk model for the capital of Kyrgyz Republic, Biskek, has been developed following this approach and tested based on different earthquake scenarios. Preliminary results will be presented and discussed.

Multi-Level Adaptation in End-User Development of 3D Virtual Chemistry Experiments

ERIC Educational Resources Information Center

Liu, Chang; Zhong, Ying

2014-01-01

Multi-level adaptation in end-user development (EUD) is an effective way to enable non-technical end users such as educators to gradually introduce more functionality with increasing complexity to 3D virtual learning environments developed by themselves using EUD approaches. Parameterization, integration, and extension are three levels of…

Trans-Ethnic Meta-Analysis Identifies Common and Rare Variants Associated with Hepatocyte Growth Factor Levels in the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Larson, Nicholas B.; Berardi, Cecilia; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; Taylor, Kent D.; Bielinski, Suzette J.

2015-01-01

Summary Hepatocyte growth factor (HGF) is a mesenchyme-derived pleiotropic factor that regulates cell growth, motility, mitogenesis, and morphogenesis in a variety of cells, and increased serum levels of HGF have been linked to a number of clinical and subclinical cardiovascular disease phenotypes. However, little is currently known regarding what genetic factors influence HGF levels, despite evidence of substantial genetic contributions to HGF variation. Based upon ethnicity-stratified single-variant association analysis and trans-ethnic meta-analysis of 6201 participants of the Multi-Ethnic Study of Atherosclerosis (MESA), we discovered five statistically significant common and low-frequency variants: HGF missense polymorphism rs5745687 (p.E299K) as well as four variants (rs16844364, rs4690098, rs114303452, rs3748034) within or in proximity to HGFAC. We also identified two significant ethnicity-specific gene-level associations (A1BG in African Americans; FASN in Chinese Americans) based upon low-frequency/rare variants, while meta-analysis of gene-level results identified a significant association for HGFAC. However, identified single-variant associations explained modest proportions of the total trait variation and were not significantly associated with coronary artery calcium or coronary heart disease. Our findings indicate genetic factors influencing circulating HGF levels may be complex and ethnically diverse. PMID:25998175

Synchrony in Dyadic Psychotherapy Sessions

NASA Astrophysics Data System (ADS)

Ramseyer, Fabian; Tschacher, Wolfgang

Synchrony is a multi-faceted concept used in diverse domains such as physics, biology, and the social sciences. This chapter reviews some of the evidence of nonverbal synchrony in human communication, with a main focus on the role of synchrony in the psychotherapeutic setting. Nonverbal synchrony describes coordinated behavior of patient and therapist. Its association with empathy, rapport and the therapeutic relationship has been pointed out repeatedly, yet close evaluation of empirical studies suggests that the evidence remains inconclusive. Particularly in naturalistic studies, research with quantitative measures of synchrony is still lacking. We introduce a new empirical approach for the study of synchrony in psychotherapies under field conditions: Motion Energy Analysis (MEA). This is a video-based algorithm that quantifies the amount of movement in freely definable regions of interest. Our statistical analysis detects synchrony on a global level, irrespective of the specific body parts moving. Synchrony thus defined can be considered as a general measure of movement coordination between interacting individuals. Data from a sequence of N = 21 therapy sessions taken from one psychotherapy dyad shows a high positive relationship between synchrony and the therapeutic bond. Nonverbal synchrony can thus be considered a promising concept for research on the therapeutic alliance. Further areas of application are discussed.

The Adolescent Mentalization-based Integrative Treatment (AMBIT) approach to outcome evaluation and manualization: adopting a learning organization approach.

PubMed

Fuggle, Peter; Bevington, Dickon; Cracknell, Liz; Hanley, James; Hare, Suzanne; Lincoln, John; Richardson, Garry; Stevens, Nina; Tovey, Heather; Zlotowitz, Sally

2015-07-01

AMBIT (Adolescent Mentalization-Based Integrative Treatment) is a developing team approach to working with hard-to-reach adolescents. The approach applies the principle of mentalization to relationships with clients, team relationships and working across agencies. It places a high priority on the need for locally developed evidence-based practice, and proposes that outcome evaluation needs to be explicitly linked with processes of team learning using a learning organization framework. A number of innovative methods of team learning are incorporated into the AMBIT approach, particularly a system of web-based wiki-formatted AMBIT manuals individualized for each participating team. The paper describes early development work of the model and illustrates ways of establishing explicit links between outcome evaluation, team learning and manualization by describing these methods as applied to two AMBIT-trained teams; one team working with young people on the edge of care (AMASS - the Adolescent Multi-Agency Support Service) and another working with substance use (CASUS - Child and Adolescent Substance Use Service in Cambridgeshire). Measurement of the primary outcomes for each team (which were generally very positive) facilitated team learning and adaptations of methods of practice that were consolidated through manualization. © The Author(s) 2014.

Improving our understanding of multi-tasking in healthcare: Drawing together the cognitive psychology and healthcare literature.

PubMed

Douglas, Heather E; Raban, Magdalena Z; Walter, Scott R; Westbrook, Johanna I

2017-03-01

Multi-tasking is an important skill for clinical work which has received limited research attention. Its impacts on clinical work are poorly understood. In contrast, there is substantial multi-tasking research in cognitive psychology, driver distraction, and human-computer interaction. This review synthesises evidence of the extent and impacts of multi-tasking on efficiency and task performance from health and non-healthcare literature, to compare and contrast approaches, identify implications for clinical work, and to develop an evidence-informed framework for guiding the measurement of multi-tasking in future healthcare studies. The results showed healthcare studies using direct observation have focused on descriptive studies to quantify concurrent multi-tasking and its frequency in different contexts, with limited study of impact. In comparison, non-healthcare studies have applied predominantly experimental and simulation designs, focusing on interleaved and concurrent multi-tasking, and testing theories of the mechanisms by which multi-tasking impacts task efficiency and performance. We propose a framework to guide the measurement of multi-tasking in clinical settings that draws together lessons from these siloed research efforts. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Accelerating and focusing protein-protein docking correlations using multi-dimensional rotational FFT generating functions.

PubMed

Ritchie, David W; Kozakov, Dima; Vajda, Sandor

2008-09-01

Predicting how proteins interact at the molecular level is a computationally intensive task. Many protein docking algorithms begin by using fast Fourier transform (FFT) correlation techniques to find putative rigid body docking orientations. Most such approaches use 3D Cartesian grids and are therefore limited to computing three dimensional (3D) translational correlations. However, translational FFTs can speed up the calculation in only three of the six rigid body degrees of freedom, and they cannot easily incorporate prior knowledge about a complex to focus and hence further accelerate the calculation. Furthemore, several groups have developed multi-term interaction potentials and others use multi-copy approaches to simulate protein flexibility, which both add to the computational cost of FFT-based docking algorithms. Hence there is a need to develop more powerful and more versatile FFT docking techniques. This article presents a closed-form 6D spherical polar Fourier correlation expression from which arbitrary multi-dimensional multi-property multi-resolution FFT correlations may be generated. The approach is demonstrated by calculating 1D, 3D and 5D rotational correlations of 3D shape and electrostatic expansions up to polynomial order L=30 on a 2 GB personal computer. As expected, 3D correlations are found to be considerably faster than 1D correlations but, surprisingly, 5D correlations are often slower than 3D correlations. Nonetheless, we show that 5D correlations will be advantageous when calculating multi-term knowledge-based interaction potentials. When docking the 84 complexes of the Protein Docking Benchmark, blind 3D shape plus electrostatic correlations take around 30 minutes on a contemporary personal computer and find acceptable solutions within the top 20 in 16 cases. Applying a simple angular constraint to focus the calculation around the receptor binding site produces acceptable solutions within the top 20 in 28 cases. Further constraining the search to the ligand binding site gives up to 48 solutions within the top 20, with calculation times of just a few minutes per complex. Hence the approach described provides a practical and fast tool for rigid body protein-protein docking, especially when prior knowledge about one or both binding sites is available.

Using structural knowledge in the protein data bank to inform the search for potential host-microbe protein interactions in sequence space: application to Mycobacterium tuberculosis.

PubMed

Mahajan, Gaurang; Mande, Shekhar C

2017-04-04

A comprehensive map of the human-M. tuberculosis (MTB) protein interactome would help fill the gaps in our understanding of the disease, and computational prediction can aid and complement experimental studies towards this end. Several sequence-based in silico approaches tap the existing data on experimentally validated protein-protein interactions (PPIs); these PPIs serve as templates from which novel interactions between pathogen and host are inferred. Such comparative approaches typically make use of local sequence alignment, which, in the absence of structural details about the interfaces mediating the template interactions, could lead to incorrect inferences, particularly when multi-domain proteins are involved. We propose leveraging the domain-domain interaction (DDI) information in PDB complexes to score and prioritize candidate PPIs between host and pathogen proteomes based on targeted sequence-level comparisons. Our method picks out a small set of human-MTB protein pairs as candidates for physical interactions, and the use of functional meta-data suggests that some of them could contribute to the in vivo molecular cross-talk between pathogen and host that regulates the course of the infection. Further, we present numerical data for Pfam domain families that highlights interaction specificity on the domain level. Not every instance of a pair of domains, for which interaction evidence has been found in a few instances (i.e. structures), is likely to functionally interact. Our sorting approach scores candidates according to how "distant" they are in sequence space from known examples of DDIs (templates). Thus, it provides a natural way to deal with the heterogeneity in domain-level interactions. Our method represents a more informed application of local alignment to the sequence-based search for potential human-microbial interactions that uses available PPI data as a prior. Our approach is somewhat limited in its sensitivity by the restricted size and diversity of the template dataset, but, given the rapid accumulation of solved protein complex structures, its scope and utility are expected to keep steadily improving.

The Development of Health for Hearts United: A Longitudinal Church-based Intervention to Reduce Cardiovascular Risk in Mid-life and Older African Americans

PubMed Central

Ralston, Penny A.; Young-Clark, Iris; Coccia, Catherine

2017-01-01

This article describes Health for Hearts United, a longitudinal church-based intervention to reduce cardiovascular disease (CVD) risk in mid-life and older African Americans. Using community-based participatory research (CBPR) approaches and undergirded by both the Socio-ecological Theory and the Transtheoretical Model of Behavior Change, the 18-month intervention was developed in six north Florida churches, randomly assigned as treatment or comparison. The intervention was framed around three conceptual components: awareness building (individual knowledge development); clinical learning (individual and small group educational sessions); and efficacy development (recognition and sustainability). We identified three lessons learned: providing consistency in programming even during participant absences; providing structured activities to assist health ministries in sustainability; and addressing changes at the church level. Recommendations include church-based approaches that reflect multi-level CBPR and the collaborative faith model. PMID:28115818

Realizing the Potential of Adolescence to Prevent Transgenerational Conditioning of Noncommunicable Disease Risk: Multi-Sectoral Design Frameworks

PubMed Central

Bay, Jacquie L.; Morton, Susan M.; Vickers, Mark H.

2016-01-01

Evidence from the field of Developmental Origins of Health and Disease (DOHaD) demonstrates that early life environmental exposures impact later-life risk of non-communicable diseases (NCDs). This has revealed the transgenerational nature of NCD risk, thus demonstrating that interventions to improve environmental exposures during early life offer important potential for primary prevention of DOHaD-related NCDs. Based on this evidence, the prospect of multi-sectoral approaches to enable primary NCD risk reduction has been highlighted in major international reports. It is agreed that pregnancy, lactation and early childhood offer significant intervention opportunities. However, the importance of interventions that establish positive behaviors impacting nutritional and non-nutritional environmental exposures in the pre-conceptual period in both males and females, thus capturing the full potential of DOHaD, must not be overlooked. Adolescence, a period where life-long health-related behaviors are established, is therefore an important life-stage for DOHaD-informed intervention. DOHaD evidence underpinning this potential is well documented. However, there is a gap in the literature with respect to combined application of theoretical evidence from science, education and public health to inform intervention design. This paper addresses this gap, presenting a review of evidence informing theoretical frameworks for adolescent DOHaD interventions that is accessible collectively to all relevant sectors. PMID:27417627

Contract Monitoring in Agent-Based Systems: Case Study

NASA Astrophysics Data System (ADS)

Hodík, Jiří; Vokřínek, Jiří; Jakob, Michal

Monitoring of fulfilment of obligations defined by electronic contracts in distributed domains is presented in this paper. A two-level model of contract-based systems and the types of observations needed for contract monitoring are introduced. The observations (inter-agent communication and agents’ actions) are collected and processed by the contract observation and analysis pipeline. The presented approach has been utilized in a multi-agent system for electronic contracting in a modular certification testing domain.

Scale separation for multi-scale modeling of free-surface and two-phase flows with the conservative sharp interface method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Han, L.H., E-mail: Luhui.Han@tum.de; Hu, X.Y., E-mail: Xiangyu.Hu@tum.de; Adams, N.A., E-mail: Nikolaus.Adams@tum.de

In this paper we present a scale separation approach for multi-scale modeling of free-surface and two-phase flows with complex interface evolution. By performing a stimulus-response operation on the level-set function representing the interface, separation of resolvable and non-resolvable interface scales is achieved efficiently. Uniform positive and negative shifts of the level-set function are used to determine non-resolvable interface structures. Non-resolved interface structures are separated from the resolved ones and can be treated by a mixing model or a Lagrangian-particle model in order to preserve mass. Resolved interface structures are treated by the conservative sharp-interface model. Since the proposed scale separationmore » approach does not rely on topological information, unlike in previous work, it can be implemented in a straightforward fashion into a given level set based interface model. A number of two- and three-dimensional numerical tests demonstrate that the proposed method is able to cope with complex interface variations accurately and significantly increases robustness against underresolved interface structures.« less

Involving older people in a multi-centre randomised trial of a complex intervention in pre-hospital emergency care: implementation of a collaborative model.

PubMed

Koniotou, Marina; Evans, Bridie Angela; Chatters, Robin; Fothergill, Rachael; Garnsworthy, Christopher; Gaze, Sarah; Halter, Mary; Mason, Suzanne; Peconi, Julie; Porter, Alison; Siriwardena, A Niroshan; Toghill, Alun; Snooks, Helen

2015-07-10

Health services research is expected to involve service users as active partners in the research process, but few examples report how this has been achieved in practice in trials. We implemented a model to involve service users in a multi-centre randomised controlled trial in pre-hospital emergency care. We used the generic Standard Operating Procedure (SOP) from our Clinical Trials Unit (CTU) as the basis for creating a model to fit the context and population of the SAFER 2 trial. In our model, we planned to involve service users at all stages in the trial through decision-making forums at 3 levels: 1) strategic; 2) site (e.g. Wales; London; East Midlands); 3) local. We linked with charities and community groups to recruit people with experience of our study population. We collected notes of meetings alongside other documentary evidence such as attendance records and study documentation to track how we implemented our model. We involved service users at strategic, site and local level. We also added additional strategic level forums (Task and Finish Groups and Writing Days) where we included service users. Service user involvement varied in frequency and type across meetings, research stages and locations but stabilised and increased as the trial progressed. Involving service users in the SAFER 2 trial showed how it is feasible and achievable for patients, carers and potential patients sharing the demographic characteristics of our study population to collaborate in a multi-centre trial at the level which suited their health, location, skills and expertise. A standard model of involvement can be tailored by adopting a flexible approach to take account of the context and complexities of a multi-site trial. Current Controlled Trials ISRCTN60481756. Registered: 13 March 2009.

Evidence-Based Practice: Separating Science From Pseudoscience

PubMed Central

Lee, Catherine M; Hunsley, John

2015-01-01

Evidence-based practice (EBP) requires that clinicians be guided by the best available evidence. In this article, we address the impact of science and pseudoscience on psychotherapy in psychiatric practice. We describe the key principles of evidence-based intervention. We describe pseudoscience and provide illustrative examples of popular intervention practices that have not been abandoned, despite evidence that they are not efficacious and may be harmful. We distinguish efficacy from effectiveness, and describe modular approaches to treatment. Reasons for the persistence of practices that are not evidence based are examined at both the individual and the professional system level. Finally, we offer suggestions for the promotion of EBP through clinical practice guidelines, modelling of scientific decision making, and training in core skills. PMID:26720821

Evidence-Based Practice: Separating Science From Pseudoscience.

PubMed

Lee, Catherine M; Hunsley, John

2015-12-01

Evidence-based practice (EBP) requires that clinicians be guided by the best available evidence. In this article, we address the impact of science and pseudoscience on psychotherapy in psychiatric practice. We describe the key principles of evidence-based intervention. We describe pseudoscience and provide illustrative examples of popular intervention practices that have not been abandoned, despite evidence that they are not efficacious and may be harmful. We distinguish efficacy from effectiveness, and describe modular approaches to treatment. Reasons for the persistence of practices that are not evidence based are examined at both the individual and the professional system level. Finally, we offer suggestions for the promotion of EBP through clinical practice guidelines, modelling of scientific decision making, and training in core skills.

Advances in studies of disease-navigating webs: Sarcoptes scabiei as a case study

PubMed Central

2014-01-01

The discipline of epidemiology is the study of the patterns, causes and effects of health and disease conditions in defined anima populations. It is the key to evidence-based medicine, which is one of the cornerstones of public health. One of the important facets of epidemiology is disease-navigating webs (disease-NW) through which zoonotic and multi-host parasites in general move from one host to another. Epidemiology in this context includes (i) classical epidemiological approaches based on the statistical analysis of disease prevalence and distribution and, more recently, (ii) genetic approaches with approximations of disease-agent population genetics. Both approaches, classical epidemiology and population genetics, are useful for studying disease-NW. However, both have strengths and weaknesses when applied separately, which, unfortunately, is too often current practice. In this paper, we use Sarcoptes scabiei mite epidemiology as a case study to show how important an integrated approach can be in understanding disease-NW and subsequent disease control. PMID:24406101

Evidence based mental healthcare and service innovation: review of concepts and challenges.

PubMed

Kouimtsidis, Ch; John-Smith, St; Kemp, P; Ikkos, G

2013-01-01

Health provision systems in the developed western nations are currently facing major financial challenges. In order to meet these challenges, a number of new approaches used to assist the provision of health have been introduced, including the practice of health professionals. These approaches utilize specific methods of data capture and summarization such as: evidence based medicine (EBM) and practice guidelines. Evidence is generated from systematic clinical research as well as reported clinical experience and individually case based empirical evidence. All types of research though (quantitative or qualitative) have limitations. Similarly all types of evidence have advantages and disadvantages and can be complimentary to each other. Evidencebased individual decision (EBID) making is the commonest evidence-based medicine as practiced by the individual clinician in making decisions about the care of the individual patient. It involves integrating individual clinical expertise with the best available external clinical evidence from systematic research. However this sort of evidence-based medicine, focuses excessively on the individual (potentially at the expense of others) in a system with limited budgets. Evidence-based guidelines (EBG) also support the practice of evidence-based medicine but at the organizational or institutional level. The main aim is to identify which interventions, over a range of patients, work best and which is cost-effective in order to guide service development and provision at a strategic level. Doing this effectively is a scientific and statistical skill in itself and the quality of guidelines is based primarily on the quality research evidence. It is important to note that lack of systematic evidence to support an intervention does not automatically mean that an intervention must instantly be abandoned. It is also important that guidelines are understood for what they are, i.e. not rules, or complete statements of knowledge. EBM will never have enough suitable evidence for all and every aspects of health provision in every locality. Innovation signifies a substantial positive change compared to gradual or incremental changes. Innovation using inductive reasoning has to play a major role within health care system and it is applicable to all three level of service provision: clinical practice, policy and organisation structure. The aim of this paper is to examine critically the above concepts and their complimentary role in supporting provision of health care systems which are suitable for the requirements of the population, affordable, deliverable, flexible and adaptable to social changes.

Multi-Level Sequential Pattern Mining Based on Prime Encoding

NASA Astrophysics Data System (ADS)

Lianglei, Sun; Yun, Li; Jiang, Yin

Encoding is not only to express the hierarchical relationship, but also to facilitate the identification of the relationship between different levels, which will directly affect the efficiency of the algorithm in the area of mining the multi-level sequential pattern. In this paper, we prove that one step of division operation can decide the parent-child relationship between different levels by using prime encoding and present PMSM algorithm and CROSS-PMSM algorithm which are based on prime encoding for mining multi-level sequential pattern and cross-level sequential pattern respectively. Experimental results show that the algorithm can effectively extract multi-level and cross-level sequential pattern from the sequence database.

Supporting Creativity, Inclusion and Collaborative Multi-Professional Learning

ERIC Educational Resources Information Center

Davis, John M.

2013-01-01

This article connects arguments in the field of integrated and multi-professional working concerning the need to promote a strengths-based approach to children, childhood and children's services with writing about creativity in schooling. It utilizes strength-based and social justice approaches to encourage professionals who work with children and…

Working towards More Effective Implementation, Dissemination and Scale-Up of Lower-Limb Injury-Prevention Programs: Insights from Community Australian Football Coaches

PubMed Central

2018-01-01

Disseminating lower-limb injury-prevention exercise programs (LL-IPEPs) with strategies that effectively reach coaches across sporting environments is a way of preventing lower-limb injuries (LLIs) and ensuring safe and sustainable sport participation. The aim of this study was to explore community-Australian Football (community-AF) coaches’ perspectives on the strategies they believed would enhance the dissemination and scale-up of LL-IPEPs. Using a qualitative multiple case study design, semi-structured interviews with community-AF coaches in Victoria, Australia, were conducted. Overall, coaches believed a range of strategies were important including: coach education, policy drivers, overcoming potential problem areas, a ‘try before you buy approach’, presenting empirical evidence and guidelines for injury-prevention exercise programs (IPEPs), forming strategic collaboration and working in partnership, communication and social marketing, public meetings, development of a coach hotline, and targeted multi-focused approaches. A shift to a culture whereby evidence-based IPEP practices in community-AF will take time, and persistent commitment by all involved in the sport is important. This will support the creation of strategies that will enhance the dissemination and scale-up of LL-IPEPs across community sport environments. The focus of research needs to continue to identify effective, holistic and multi-level interventions to support coaches in preventing LLIs. This could lead to the determination of successful strategies such as behavioural regulation strategies and emotional coping resources to implement LL-IPEPs into didactic curricula and practice. Producing changes in practice will require attention to which strategies are a priority and the most effective. PMID:29462913

Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient.

PubMed

Shi, Fengjian; Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

2017-10-16

In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster-Shafer evidence theory (D-S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D-S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method.

Research on the Fusion of Dependent Evidence Based on Rank Correlation Coefficient

PubMed Central

Su, Xiaoyan; Qian, Hong; Yang, Ning; Han, Wenhua

2017-01-01

In order to meet the higher accuracy and system reliability requirements, the information fusion for multi-sensor systems is an increasing concern. Dempster–Shafer evidence theory (D–S theory) has been investigated for many applications in multi-sensor information fusion due to its flexibility in uncertainty modeling. However, classical evidence theory assumes that the evidence is independent of each other, which is often unrealistic. Ignoring the relationship between the evidence may lead to unreasonable fusion results, and even lead to wrong decisions. This assumption severely prevents D–S evidence theory from practical application and further development. In this paper, an innovative evidence fusion model to deal with dependent evidence based on rank correlation coefficient is proposed. The model first uses rank correlation coefficient to measure the dependence degree between different evidence. Then, total discount coefficient is obtained based on the dependence degree, which also considers the impact of the reliability of evidence. Finally, the discount evidence fusion model is presented. An example is illustrated to show the use and effectiveness of the proposed method. PMID:29035341

Development of Prototype HTS Components for Magnetic Suspension Applications

NASA Technical Reports Server (NTRS)

Haldar, P.; Hoehn, J., Jr.; Selvamanickam, V.; Farrell, R. A.; Balachandran, U.; Iyer, A. N.; Peterson, E.; Salazar, K.

1996-01-01

We have concentrated on developing prototype lengths of bismuth and thallium based silver sheathed superconductors by the powder-in-tube approach to fabricate high temperature superconducting (HTS) components for magnetic suspension applications. Long lengths of mono and multi filament tapes are presently being fabricated with critical current densities useful for maglev and many other applications. We have recently demonstrated the prototype manufacture of lengths exceeding 1 km of Bi-2223 multi filament conductor. Long lengths of thallium based multi-filament conductor have also been fabricated with practical levels of critical current density and improved field dependence behavior. Test coils and magnets have been built from these lengths and characterized over a range of temperatures and background fields to determine their performance. Work is in progress to develop, fabricate and test HTS windings that will be suitable for magnetic suspension, levitation and other electric power related applications.

Shared decision making in chronic care in the context of evidence based practice in nursing.

PubMed

Friesen-Storms, Jolanda H H M; Bours, Gerrie J J W; van der Weijden, Trudy; Beurskens, Anna J H M

2015-01-01

In the decision-making environment of evidence-based practice, the following three sources of information must be integrated: research evidence of the intervention, clinical expertise, and the patient's values. In reality, evidence-based practice usually focuses on research evidence (which may be translated into clinical practice guidelines) and clinical expertise without considering the individual patient's values. The shared decision-making model seems to be helpful in the integration of the individual patient's values in evidence-based practice. We aim to discuss the relevance of shared decision making in chronic care and to suggest how it can be integrated with evidence-based practice in nursing. We start by describing the following three possible approaches to guide the decision-making process: the paternalistic approach, the informed approach, and the shared decision-making approach. Implementation of shared decision making has gained considerable interest in cases lacking a strong best-treatment recommendation, and when the available treatment options are equivalent to some extent. We discuss that in chronic care it is important to always invite the patient to participate in the decision-making process. We delineate the following six attributes of health care interventions in chronic care that influence the degree of shared decision making: the level of research evidence, the number of available intervention options, the burden of side effects, the impact on lifestyle, the patient group values, and the impact on resources. Furthermore, the patient's willingness to participate in shared decision making, the clinical expertise of the nurse, and the context in which the decision making takes place affect the shared decision-making process. A knowledgeable and skilled nurse with a positive attitude towards shared decision making—integrated with evidence-based practice—can facilitate the shared decision-making process. We conclude that nurses as well as other health care professionals in chronic care should integrate shared decision making with evidence-based practice to deliver patient-centred care. Copyright © 2014 Elsevier Ltd. All rights reserved.

The University of Illinois at Chicago School of Public Health Doctor of Public Health program: an innovative approach to doctoral-level practice leadership development.

PubMed

Lenihan, Patrick; Welter, Christina; Brandt-Rauf, Paul; Neuberger, Babette; Pinsker, Eve; Petros, Michael; Risley, Kristine

2015-03-01

The University of Illinois at Chicago, School of Public Health, Doctor of Public Health degree is designed to build leadership skills and an ability to contribute to the evidence base of practice. The competency-based, distance-format, doctoral-level program for midcareer professionals features an action learning approach in which students apply leadership principles from the virtual classroom to real-world problems at their work sites. Students demonstrate mastery of the competencies and readiness to advance to the dissertation stage through completing a portfolio by using a process of systematic reflection. The practice-oriented dissertation demonstrates the ability to contribute to the evidence base of public health practice in an area of emphasis. Preliminary evaluation data indicate that the program is meeting its intended purposes.

The University of Illinois at Chicago School of Public Health Doctor of Public Health Program: An Innovative Approach to Doctoral-Level Practice Leadership Development

PubMed Central

Welter, Christina; Brandt-Rauf, Paul; Neuberger, Babette; Pinsker, Eve; Petros, Michael; Risley, Kristine

2015-01-01

The University of Illinois at Chicago, School of Public Health, Doctor of Public Health degree is designed to build leadership skills and an ability to contribute to the evidence base of practice. The competency-based, distance-format, doctoral-level program for midcareer professionals features an action learning approach in which students apply leadership principles from the virtual classroom to real-world problems at their work sites. Students demonstrate mastery of the competencies and readiness to advance to the dissertation stage through completing a portfolio by using a process of systematic reflection. The practice-oriented dissertation demonstrates the ability to contribute to the evidence base of public health practice in an area of emphasis. Preliminary evaluation data indicate that the program is meeting its intended purposes. PMID:25706020

The Validity and Responsiveness of Isometric Lower Body Multi-Joint Tests of Muscular Strength: a Systematic Review.

PubMed

Drake, David; Kennedy, Rodney; Wallace, Eric

2017-12-01

Researchers and practitioners working in sports medicine and science require valid tests to determine the effectiveness of interventions and enhance understanding of mechanisms underpinning adaptation. Such decision making is influenced by the supportive evidence describing the validity of tests within current research. The objective of this study is to review the validity of lower body isometric multi-joint tests ability to assess muscular strength and determine the current level of supporting evidence. Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed in a systematic fashion to search, assess and synthesize existing literature on this topic. Electronic databases such as Web of Science, CINAHL and PubMed were searched up to 18 March 2015. Potential inclusions were screened against eligibility criteria relating to types of test, measurement instrument, properties of validity assessed and population group and were required to be published in English. The Consensus-based Standards for the Selection of health Measurement Instruments (COSMIN) checklist was used to assess methodological quality and measurement property rating of included studies. Studies rated as fair or better in methodological quality were included in the best evidence synthesis. Fifty-nine studies met the eligibility criteria for quality appraisal. The ten studies that rated fair or better in methodological quality were included in the best evidence synthesis. The most frequently investigated lower body isometric multi-joint tests for validity were the isometric mid-thigh pull and isometric squat. The validity of each of these tests was strong in terms of reliability and construct validity. The evidence for responsiveness of tests was found to be moderate for the isometric squat test and unknown for the isometric mid-thigh pull. No tests using the isometric leg press met the criteria for inclusion in the best evidence synthesis. Researchers and practitioners can use the isometric squat and isometric mid-thigh pull with confidence in terms of reliability and construct validity. Further work to investigate other validity components such as criterion validity, smallest detectable change and responsiveness to resistance exercise interventions may be beneficial to the current level of evidence.

A comparison of synthesis and integrative approaches for meaning making and information fusion

NASA Astrophysics Data System (ADS)

Eggleston, Robert G.; Fenstermacher, Laurie

2017-05-01

Traditionally, information fusion approaches to meaning making have been integrative or aggregative in nature, creating meaning "containers" in which to put content (e.g., attributes) about object classes. In a large part, this was due to the limits in technology/tools for supporting information fusion (e.g., computers). A different synthesis based approach for meaning making is described which takes advantage of computing advances. The approach is not focused on the events/behaviors being observed/sensed; instead, it is human work centric. The former director of the Defense Intelligence Agency once wrote, "Context is king. Achieving an understanding of what is happening - or will happen - comes from a truly integrated picture of an area, the situation and the various personalities in it…a layered approach over time that builds depth of understanding."1 The synthesis based meaning making framework enables this understanding. It is holistic (both the sum and the parts, the proverbial forest and the trees), multi-perspective and emulative (as opposed to representational). The two approaches are complementary, with the synthesis based meaning making framework as a wrapper. The integrative approach would be dominant at level 0,1 fusion: data fusion, track formation and the synthesis based meaning making becomes dominant at higher fusion levels (levels 2 and 3), although both may be in play. A synthesis based approach to information fusion is thus well suited for "gray zone" challenges in which there is aggression and ambiguity and which are inherently perspective dependent (e.g., recent events in Ukraine).

Optimizing decentralized production-distribution planning problem in a multi-period supply chain network under uncertainty

NASA Astrophysics Data System (ADS)

Nourifar, Raheleh; Mahdavi, Iraj; Mahdavi-Amiri, Nezam; Paydar, Mohammad Mahdi

2017-09-01

Decentralized supply chain management is found to be significantly relevant in today's competitive markets. Production and distribution planning is posed as an important optimization problem in supply chain networks. Here, we propose a multi-period decentralized supply chain network model with uncertainty. The imprecision related to uncertain parameters like demand and price of the final product is appropriated with stochastic and fuzzy numbers. We provide mathematical formulation of the problem as a bi-level mixed integer linear programming model. Due to problem's convolution, a structure to solve is developed that incorporates a novel heuristic algorithm based on Kth-best algorithm, fuzzy approach and chance constraint approach. Ultimately, a numerical example is constructed and worked through to demonstrate applicability of the optimization model. A sensitivity analysis is also made.

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

NASA Astrophysics Data System (ADS)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

Daytime Water Detection by Fusing Multiple Cues for Autonomous Off-Road Navigation

NASA Technical Reports Server (NTRS)

Rankin, A. L.; Matthies, L. H.; Huertas, A.

2004-01-01

Detecting water hazards is a significant challenge to unmanned ground vehicle autonomous off-road navigation. This paper focuses on detecting the presence of water during the daytime using color cameras. A multi-cue approach is taken. Evidence of the presence of water is generated from color, texture, and the detection of reflections in stereo range data. A rule base for fusing water cues was developed by evaluating detection results from an extensive archive of data collection imagery containing water. This software has been implemented into a run-time passive perception subsystem and tested thus far under Linux on a Pentium based processor.

Post-deployment Multi-symptom Disorder rehabilitation: An integrated approach to rehabilitation.

PubMed

Bosco, Michelle A; Murphy, Jennifer; Peters, Walter E; Clark, Michael E

2015-01-01

Veterans and active duty service members returning from Operation New Dawn and those having returned from Operations Iraqi and Enduring Freedom frequently report the presence of overlapping, co-morbid symptom clusters consisting of chronic pain, mild cognitive complaints, and posttraumatic stress symptoms/disorder or mood disturbance. This presentation has been called Post-deployment Multi-symptom Disorder (PMD) and its implications not only impact various functional domains, but have also influenced a system/continuum of care to rise to meet the challenges of treating PMD. This continuum is based on innovation informed by evidence-based therapies, systemic limitations, and a focus on functional improvement rather than diagnostic classification. The purpose of this paper is to describe the symptomatic, functional and systemic challenges inherent to PMD conceptualization and treatment. The constituent clusters of PMD are defined and exemplified, its functional impact is illustrated, and a continuum of care at a large southeastern Veterans Affairs (VA) hospital offering an interdisciplinary approach to integrated rehabilitation is described. Three case examples are provided that that underscore the importance of vocation for improved behavioral health and quality of life. The case examples demonstrate how vocational rehabilitation services are an integral component of PMD treatment.}

Failure analysis of fuel cell electrodes using three-dimensional multi-length scale X-ray computed tomography

NASA Astrophysics Data System (ADS)

Pokhrel, A.; El Hannach, M.; Orfino, F. P.; Dutta, M.; Kjeang, E.

2016-10-01

X-ray computed tomography (XCT), a non-destructive technique, is proposed for three-dimensional, multi-length scale characterization of complex failure modes in fuel cell electrodes. Comparative tomography data sets are acquired for a conditioned beginning of life (BOL) and a degraded end of life (EOL) membrane electrode assembly subjected to cathode degradation by voltage cycling. Micro length scale analysis shows a five-fold increase in crack size and 57% thickness reduction in the EOL cathode catalyst layer, indicating widespread action of carbon corrosion. Complementary nano length scale analysis shows a significant reduction in porosity, increased pore size, and dramatically reduced effective diffusivity within the remaining porous structure of the catalyst layer at EOL. Collapsing of the structure is evident from the combination of thinning and reduced porosity, as uniquely determined by the multi-length scale approach. Additionally, a novel image processing based technique developed for nano scale segregation of pore, ionomer, and Pt/C dominated voxels shows an increase in ionomer volume fraction, Pt/C agglomerates, and severe carbon corrosion at the catalyst layer/membrane interface at EOL. In summary, XCT based multi-length scale analysis enables detailed information needed for comprehensive understanding of the complex failure modes observed in fuel cell electrodes.

A generic architecture for an adaptive, interoperable and intelligent type 2 diabetes mellitus care system.

PubMed

Uribe, Gustavo A; Blobel, Bernd; López, Diego M; Schulz, Stefan

2015-01-01

Chronic diseases such as Type 2 Diabetes Mellitus (T2DM) constitute a big burden to the global health economy. T2DM Care Management requires a multi-disciplinary and multi-organizational approach. Because of different languages and terminologies, education, experiences, skills, etc., such an approach establishes a special interoperability challenge. The solution is a flexible, scalable, business-controlled, adaptive, knowledge-based, intelligent system following a systems-oriented, architecture-centric, ontology-based and policy-driven approach. The architecture of real systems is described, using the basics and principles of the Generic Component Model (GCM). For representing the functional aspects of a system the Business Process Modeling Notation (BPMN) is used. The system architecture obtained is presented using a GCM graphical notation, class diagrams and BPMN diagrams. The architecture-centric approach considers the compositional nature of the real world system and its functionalities, guarantees coherence, and provides right inferences. The level of generality provided in this paper facilitates use case specific adaptations of the system. By that way, intelligent, adaptive and interoperable T2DM care systems can be derived from the presented model as presented in another publication.

Management of pain in patients with temporomandibular disorder (TMD): challenges and solutions

PubMed Central

Gil-Martínez, Alfonso; Paris-Alemany, Alba; López-de-Uralde-Villanueva, Ibai; La Touche, Roy

2018-01-01

Thanks to advances in neuroscience, biopsychosocial models for diagnostics and treatment (including physical, psychological, and pharmacological therapies) currently have more clinical support and scientific growth. At present, a conservative treatment approach prevails over surgery, given it is less aggressive and usually results in satisfactory clinical outcomes in mild–moderate temporomandibular disorder (TMD). The aim of this review is to evaluate the recent evidence, identify challenges, and propose solutions from a clinical point of view for patients with craniofacial pain and TMD. The treatment we propose is structured in a multi-modal approach based on a biobehavioral approach that includes medical, physiotherapeutic, psychological, and dental treatments. We also propose a new biobehavioral model regarding pain perception and motor behavior for the diagnosis and treatment of patients with painful TMD. PMID:29588615

The SDGs Will Require Integrated Agriculture, Nutrition, and Health at the Community Level.

PubMed

Canavan, Chelsey R; Graybill, Lauren; Fawzi, Wafaie; Kinabo, Joyce

2016-03-01

Child malnutrition is an urgent and complex issue and requires integrated approaches across agriculture, nutrition, and health. This issue has gained prominence at the global level. While national-level efforts are underway in many countries, there is little information on how to integrate at the community level. Here, we offer a community-based approach using cadres of agricultural and community health workers, drawing on qualitative work we have conducted in Tanzania. Agriculture is an important driver of nutritional and health outcomes, and improving child health will require practical solutions for integration that can add to the evidence base. © The Author(s) 2016.

Integrating multi-criteria evaluation techniques with geographic information systems for landfill site selection: a case study using ordered weighted average.

PubMed

Gorsevski, Pece V; Donevska, Katerina R; Mitrovski, Cvetko D; Frizado, Joseph P

2012-02-01

This paper presents a GIS-based multi-criteria decision analysis approach for evaluating the suitability for landfill site selection in the Polog Region, Macedonia. The multi-criteria decision framework considers environmental and economic factors which are standardized by fuzzy membership functions and combined by integration of analytical hierarchy process (AHP) and ordered weighted average (OWA) techniques. The AHP is used for the elicitation of attribute weights while the OWA operator function is used to generate a wide range of decision alternatives for addressing uncertainty associated with interaction between multiple criteria. The usefulness of the approach is illustrated by different OWA scenarios that report landfill suitability on a scale between 0 and 1. The OWA scenarios are intended to quantify the level of risk taking (i.e., optimistic, pessimistic, and neutral) and to facilitate a better understanding of patterns that emerge from decision alternatives involved in the decision making process. Copyright © 2011 Elsevier Ltd. All rights reserved.

Analysis Commons, A Team Approach to Discovery in a Big-Data Environment for Genetic Epidemiology

PubMed Central

Brody, Jennifer A.; Morrison, Alanna C.; Bis, Joshua C.; O'Connell, Jeffrey R.; Brown, Michael R.; Huffman, Jennifer E.; Ames, Darren C.; Carroll, Andrew; Conomos, Matthew P.; Gabriel, Stacey; Gibbs, Richard A.; Gogarten, Stephanie M.; Gupta, Namrata; Jaquish, Cashell E.; Johnson, Andrew D.; Lewis, Joshua P.; Liu, Xiaoming; Manning, Alisa K.; Papanicolaou, George J.; Pitsillides, Achilleas N.; Rice, Kenneth M.; Salerno, William; Sitlani, Colleen M.; Smith, Nicholas L.; Heckbert, Susan R.; Laurie, Cathy C.; Mitchell, Braxton D.; Vasan, Ramachandran S.; Rich, Stephen S.; Rotter, Jerome I.; Wilson, James G.; Boerwinkle, Eric; Psaty, Bruce M.; Cupples, L. Adrienne

2017-01-01

Summary paragraph The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations. PMID:29074945

Design and Simulation of Material-Integrated Distributed Sensor Processing with a Code-Based Agent Platform and Mobile Multi-Agent Systems

PubMed Central

Bosse, Stefan

2015-01-01

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques. PMID:25690550

Design and simulation of material-integrated distributed sensor processing with a code-based agent platform and mobile multi-agent systems.

PubMed

Bosse, Stefan

2015-02-16

Multi-agent systems (MAS) can be used for decentralized and self-organizing data processing in a distributed system, like a resource-constrained sensor network, enabling distributed information extraction, for example, based on pattern recognition and self-organization, by decomposing complex tasks in simpler cooperative agents. Reliable MAS-based data processing approaches can aid the material-integration of structural-monitoring applications, with agent processing platforms scaled to the microchip level. The agent behavior, based on a dynamic activity-transition graph (ATG) model, is implemented with program code storing the control and the data state of an agent, which is novel. The program code can be modified by the agent itself using code morphing techniques and is capable of migrating in the network between nodes. The program code is a self-contained unit (a container) and embeds the agent data, the initialization instructions and the ATG behavior implementation. The microchip agent processing platform used for the execution of the agent code is a standalone multi-core stack machine with a zero-operand instruction format, leading to a small-sized agent program code, low system complexity and high system performance. The agent processing is token-queue-based, similar to Petri-nets. The agent platform can be implemented in software, too, offering compatibility at the operational and code level, supporting agent processing in strong heterogeneous networks. In this work, the agent platform embedded in a large-scale distributed sensor network is simulated at the architectural level by using agent-based simulation techniques.

Acknowledging and Interrogating Multiplicities: Towards a Generous Approach in Evaluations of Early Literacy Innovation and Intervention

ERIC Educational Resources Information Center

Burnett, Cathy

2017-01-01

At a time of increasing calls from policy makers for the use of "hard evidence" in driving decision-making at national and local levels in educational contexts, this article contributes to debates about evidence-based practice in early literacy research. It proposes that a reliance on studies designed to generate 'hard' evidence limits…

Modelling strategies to predict the multi-scale effects of rural land management change

NASA Astrophysics Data System (ADS)

Bulygina, N.; Ballard, C. E.; Jackson, B. M.; McIntyre, N.; Marshall, M.; Reynolds, B.; Wheater, H. S.

2011-12-01

Changes to the rural landscape due to agricultural land management are ubiquitous, yet predicting the multi-scale effects of land management change on hydrological response remains an important scientific challenge. Much empirical research has been of little generic value due to inadequate design and funding of monitoring programmes, while the modelling issues challenge the capability of data-based, conceptual and physics-based modelling approaches. In this paper we report on a major UK research programme, motivated by a national need to quantify effects of agricultural intensification on flood risk. Working with a consortium of farmers in upland Wales, a multi-scale experimental programme (from experimental plots to 2nd order catchments) was developed to address issues of upland agricultural intensification. This provided data support for a multi-scale modelling programme, in which highly detailed physics-based models were conditioned on the experimental data and used to explore effects of potential field-scale interventions. A meta-modelling strategy was developed to represent detailed modelling in a computationally-efficient manner for catchment-scale simulation; this allowed catchment-scale quantification of potential management options. For more general application to data-sparse areas, alternative approaches were needed. Physics-based models were developed for a range of upland management problems, including the restoration of drained peatlands, afforestation, and changing grazing practices. Their performance was explored using literature and surrogate data; although subject to high levels of uncertainty, important insights were obtained, of practical relevance to management decisions. In parallel, regionalised conceptual modelling was used to explore the potential of indices of catchment response, conditioned on readily-available catchment characteristics, to represent ungauged catchments subject to land management change. Although based in part on speculative relationships, significant predictive power was derived from this approach. Finally, using a formal Bayesian procedure, these different sources of information were combined with local flow data in a catchment-scale conceptual model application , i.e. using small-scale physical properties, regionalised signatures of flow and available flow measurements.

A game theory-reinforcement learning (GT-RL) method to develop optimal operation policies for multi-operator reservoir systems

NASA Astrophysics Data System (ADS)

Madani, Kaveh; Hooshyar, Milad

2014-11-01

Reservoir systems with multiple operators can benefit from coordination of operation policies. To maximize the total benefit of these systems the literature has normally used the social planner's approach. Based on this approach operation decisions are optimized using a multi-objective optimization model with a compound system's objective. While the utility of the system can be increased this way, fair allocation of benefits among the operators remains challenging for the social planner who has to assign controversial weights to the system's beneficiaries and their objectives. Cooperative game theory provides an alternative framework for fair and efficient allocation of the incremental benefits of cooperation. To determine the fair and efficient utility shares of the beneficiaries, cooperative game theory solution methods consider the gains of each party in the status quo (non-cooperation) as well as what can be gained through the grand coalition (social planner's solution or full cooperation) and partial coalitions. Nevertheless, estimation of the benefits of different coalitions can be challenging in complex multi-beneficiary systems. Reinforcement learning can be used to address this challenge and determine the gains of the beneficiaries for different levels of cooperation, i.e., non-cooperation, partial cooperation, and full cooperation, providing the essential input for allocation based on cooperative game theory. This paper develops a game theory-reinforcement learning (GT-RL) method for determining the optimal operation policies in multi-operator multi-reservoir systems with respect to fairness and efficiency criteria. As the first step to underline the utility of the GT-RL method in solving complex multi-agent multi-reservoir problems without a need for developing compound objectives and weight assignment, the proposed method is applied to a hypothetical three-agent three-reservoir system.

A Multi-Faceted Approach for the Development of the Army's Functional Basic Skills Education Program (BSEP).

ERIC Educational Resources Information Center

Begland, Robert R.

In reviewing the Army Continuing Education System in 1979, the Assistant Secretary of the Army found a basic skills program based on traditional academic level goals was inadequate to meet the Army's requirement to provide functional, job-related basic skill education. Combining the shrinking manpower pool and projected basic skill deficiencies of…

Imaging empathy and prosocial emotions.

PubMed

Lamm, Claus; Rütgen, Markus; Wagner, Isabella C

2017-06-29

Empathy is a multi-faceted construct with important implications for social behavior. Based on a selective review of the neuroscientific evidence collected in humans, the present paper discusses the neural representations underlying affect sharing, its relation to mentalizing, the importance of self-other distinction, the distinction between empathy, sympathy and compassion, and how these phenomena are linked to prosocial behavior. Apart from reviewing the literature, we also highlight open questions and how they might be addressed by a research approach that tries to integrate across these diverse constructs. Copyright © 2017 Elsevier B.V. All rights reserved.

Strategies which aim to positively impact on weight, physical activity, diet and sedentary behaviours in children from zero to five years. A systematic review of the literature.

PubMed

Campbell, K J; Hesketh, K D

2007-07-01

Preventing the development of obesity in children is an international health priority. To assess the effectiveness of interventions designed to prevent obesity, promote healthy eating and/or physical activity and/or to reduce sedentary behaviours in 0-5-year-old children, a systematic review of the literature was performed. Literature searches were limited to articles published between January 1995 and June 2006, printed in English and sampling children aged 0-5-years. Searches excluded literature concerned with breastfeeding, eating disorders, and interventions which were school-based or concerned with obesity treatment. Two reviewers independently extracted data and assessed study strengths and weaknesses. Nine included studies were grouped based on the settings in which they were delivered. Most studies involved multi-approach interventions, were conducted in the USA and varied in study designs and quality. All showed some level of effectiveness on at least one obesity-behaviour in young children. These studies support, at a range of levels, the premise that parents are receptive to and capable of some behavioural changes that may promote healthy weight in their young children. The small quantity of research heralds the need, particularly given the potential for early intervention to have long-lasting impacts on individual and population health, to build in a substantial way upon this evidence base.

Integrative Data Analysis of Multi-Platform Cancer Data with a Multimodal Deep Learning Approach.

PubMed

Liang, Muxuan; Li, Zhizhong; Chen, Ting; Zeng, Jianyang

2015-01-01

Identification of cancer subtypes plays an important role in revealing useful insights into disease pathogenesis and advancing personalized therapy. The recent development of high-throughput sequencing technologies has enabled the rapid collection of multi-platform genomic data (e.g., gene expression, miRNA expression, and DNA methylation) for the same set of tumor samples. Although numerous integrative clustering approaches have been developed to analyze cancer data, few of them are particularly designed to exploit both deep intrinsic statistical properties of each input modality and complex cross-modality correlations among multi-platform input data. In this paper, we propose a new machine learning model, called multimodal deep belief network (DBN), to cluster cancer patients from multi-platform observation data. In our integrative clustering framework, relationships among inherent features of each single modality are first encoded into multiple layers of hidden variables, and then a joint latent model is employed to fuse common features derived from multiple input modalities. A practical learning algorithm, called contrastive divergence (CD), is applied to infer the parameters of our multimodal DBN model in an unsupervised manner. Tests on two available cancer datasets show that our integrative data analysis approach can effectively extract a unified representation of latent features to capture both intra- and cross-modality correlations, and identify meaningful disease subtypes from multi-platform cancer data. In addition, our approach can identify key genes and miRNAs that may play distinct roles in the pathogenesis of different cancer subtypes. Among those key miRNAs, we found that the expression level of miR-29a is highly correlated with survival time in ovarian cancer patients. These results indicate that our multimodal DBN based data analysis approach may have practical applications in cancer pathogenesis studies and provide useful guidelines for personalized cancer therapy.

Transition index maps for urban growth simulation: application of artificial neural networks, weight of evidence and fuzzy multi-criteria evaluation.

PubMed

Shafizadeh-Moghadam, Hossein; Tayyebi, Amin; Helbich, Marco

2017-06-01

Transition index maps (TIMs) are key products in urban growth simulation models. However, their operationalization is still conflicting. Our aim was to compare the prediction accuracy of three TIM-based spatially explicit land cover change (LCC) models in the mega city of Mumbai, India. These LCC models include two data-driven approaches, namely artificial neural networks (ANNs) and weight of evidence (WOE), and one knowledge-based approach which integrates an analytical hierarchical process with fuzzy membership functions (FAHP). Using the relative operating characteristics (ROC), the performance of these three LCC models were evaluated. The results showed 85%, 75%, and 73% accuracy for the ANN, FAHP, and WOE. The ANN was clearly superior compared to the other LCC models when simulating urban growth for the year 2010; hence, ANN was used to predict urban growth for 2020 and 2030. Projected urban growth maps were assessed using statistical measures, including figure of merit, average spatial distance deviation, producer accuracy, and overall accuracy. Based on our findings, we recomend ANNs as an and accurate method for simulating future patterns of urban growth.

Joint multi-object registration and segmentation of left and right cardiac ventricles in 4D cine MRI

NASA Astrophysics Data System (ADS)

Ehrhardt, Jan; Kepp, Timo; Schmidt-Richberg, Alexander; Handels, Heinz

2014-03-01

The diagnosis of cardiac function based on cine MRI requires the segmentation of cardiac structures in the images, but the problem of automatic cardiac segmentation is still open, due to the imaging characteristics of cardiac MR images and the anatomical variability of the heart. In this paper, we present a variational framework for joint segmentation and registration of multiple structures of the heart. To enable the simultaneous segmentation and registration of multiple objects, a shape prior term is introduced into a region competition approach for multi-object level set segmentation. The proposed algorithm is applied for simultaneous segmentation of the myocardium as well as the left and right ventricular blood pool in short axis cine MRI images. Two experiments are performed: first, intra-patient 4D segmentation with a given initial segmentation for one time-point in a 4D sequence, and second, a multi-atlas segmentation strategy is applied to unseen patient data. Evaluation of segmentation accuracy is done by overlap coefficients and surface distances. An evaluation based on clinical 4D cine MRI images of 25 patients shows the benefit of the combined approach compared to sole registration and sole segmentation.

An Approach for Web Service Selection Based on Confidence Level of Decision Maker

PubMed Central

Khezrian, Mojtaba; Jahan, Ali; Wan Kadir, Wan Mohd Nasir; Ibrahim, Suhaimi

2014-01-01

Web services today are among the most widely used groups for Service Oriented Architecture (SOA). Service selection is one of the most significant current discussions in SOA, which evaluates discovered services and chooses the best candidate from them. Although a majority of service selection techniques apply Quality of Service (QoS), the behaviour of QoS-based service selection leads to service selection problems in Multi-Criteria Decision Making (MCDM). In the existing works, the confidence level of decision makers is neglected and does not consider their expertise in assessing Web services. In this paper, we employ the VIKOR (VIšekriterijumskoKOmpromisnoRangiranje) method, which is absent in the literature for service selection, but is well-known in other research. We propose a QoS-based approach that deals with service selection by applying VIKOR with improvement of features. This research determines the weights of criteria based on user preference and accounts for the confidence level of decision makers. The proposed approach is illustrated by an example in order to demonstrate and validate the model. The results of this research may facilitate service consumers to attain a more efficient decision when selecting the appropriate service. PMID:24897426

Characterizing multi-pollutant air pollution in China: Comparison of three air quality indices.

PubMed

Hu, Jianlin; Ying, Qi; Wang, Yungang; Zhang, Hongliang

2015-11-01

Multi-pollutant air pollution (i.e., several pollutants reaching very high concentrations simultaneously) frequently occurs in many regions across China. Air quality index (AQI) is used worldwide to inform the public about levels of air pollution and associated health risks. The current AQI approach used in China is based on the maximum value of individual pollutants, and does not consider the combined health effects of exposure to multiple pollutants. In this study, two novel alternative indices--aggregate air quality index (AAQI) and health-risk based air quality index (HAQI)--were calculated based on data collected in six megacities of China (Beijing, Shanghai, Guangzhou, Shjiazhuang, Xi'an, and Wuhan) during 2013 to 2014. Both AAQI and HAQI take into account the combined health effects of various pollutants, and the HAQI considers the exposure (or concentration)-response relationships of pollutants. AAQI and HAQI were compared to AQI to examine the effectiveness of the current AQI in characterizing multi-pollutant air pollution in China. The AAQI and HAQI values are higher than the AQI on days when two or more pollutants simultaneously exceed the Chinese Ambient Air Quality Standards (CAAQS) 24-hour Grade II standards. The results of the comparison of the classification of risk categories based on the three indices indicate that the current AQI approach underestimates the severity of health risk associated with exposure to multi-pollutant air pollution. For the AQI-based risk category of 'unhealthy', 96% and 80% of the days would be 'very unhealthy' or 'hazardous' if based on AAQI and HAQI, respectively; and for the AQI-based risk category of 'very unhealthy', 67% and 75% of the days would be 'hazardous' if based on AAQI and HAQI, respectively. The results suggest that the general public, especially sensitive population groups such as children and the elderly, should take more stringent actions than those currently suggested based on the AQI approach during high air pollution events. Sensitivity studies were conducted to examine the assumptions used in the AAQI and HAQI approaches. Results show that AAQI is sensitive to the choice of pollutant irrelevant constant. HAQI is sensitive to the choice of both threshold values and pollutants included in total risk calculation. Copyright © 2015 Elsevier Ltd. All rights reserved.

The care unit in nursing home research: evidence in support of a definition.

PubMed

Estabrooks, Carole A; Morgan, Debra G; Squires, Janet E; Boström, Anne-Marie; Slaughter, Susan E; Cummings, Greta G; Norton, Peter G

2011-04-14

Defining what constitutes a resident care unit in nursing home research is both a conceptual and practical challenge. The aim of this paper is to provide evidence in support of a definition of care unit in nursing homes by demonstrating: (1) its feasibility for use in data collection, (2) the acceptability of aggregating individual responses to the unit level, and (3) the benefit of including unit level data in explanatory models. An observational study design was used. Research (project) managers, healthcare aides, care managers, nursing home administrators and directors of care from thirty-six nursing homes in the Canadian prairie provinces of Alberta, Saskatchewan and Manitoba provided data for the study. A definition of care unit was developed and applied in data collection and analyses. A debriefing session was held with research managers to investigate their experiences with using the care unit definition. In addition, survey responses from 1258 healthcare aides in 25 of the 36 nursing homes in the study, that had more than one care unit, were analyzed using a multi-level modeling approach. Trained field workers administered the Alberta Context Tool (ACT), a 58-item self-report survey reflecting 10 organizational context concepts, to healthcare aides using computer assisted personal interviews. To assess the appropriateness of obtaining unit level scores, we assessed aggregation statistics (ICC(1), ICC(2), η², and ω²), and to assess the value of using the definition of unit in explanatory models, we performed multi-level modeling. In 10 of the 36 nursing homes, the care unit definition developed was used to align the survey data (for analytic purposes) to specific care units as designated by our definition, from that reported by the facility administrator. The aggregation statistics supported aggregating the healthcare aide responses on the ACT to the realigned unit level. Findings from the multi-level modeling further supported unit level aggregation. A significantly higher percentage of variance was explained in the ACT concepts at the unit level compared to the individual and/or nursing home levels. The statistical results support the use of our definition of care unit in nursing home research in the Canadian prairie provinces. Beyond research convenience however, the results also support the resident unit as an important Clinical Microsystem to which future interventions designed to improve resident quality of care and staff (healthcare aide) worklife should be targeted.

An ecological approach to hearing-health promotion in workplaces.

PubMed

Reddy, Ravi; Welch, David; Ameratunga, Shanthi; Thorne, Peter

2017-05-01

To develop and assess use, acceptability and feasibility of an ecological hearing conservation programme for workplaces. A school-based public health hearing preservation education programme (Dangerous Decibels®) was adapted for workplaces using the Multi-level Approach to Community Health (MATCH) Model. The programme was delivered in small manufacturing companies and evaluated using a questionnaire before the training and at one week and two-months after training. Workers (n = 56) from five small manufacturing companies were recruited. There was a significant improvement in knowledge, attitudes and behaviour of workers at the intrapersonal level; in behaviour motivation and safety culture at the interpersonal and organisational levels; and an overall improvement in hearing-health behaviour after two months post-intervention. The developed programme offers a simple, interactive and theory-based intervention that is well accepted and effective in promoting positive hearing-health behaviour in workplaces.

Factors influencing early rehabilitation after THA: a systematic review.

PubMed

Sharma, Vivek; Morgan, Patrick M; Cheng, Edward Y

2009-06-01

A wide variation exists in rehabilitation after total hip arthroplasty (THA) in part due to a paucity of evidence-based literature. We asked whether a minimally invasive surgical approach, a multimodal approach to pain control with revised anesthesia protocols, hip restrictions, or preoperative physiotherapy achieved a faster rehabilitation and improved immediate short-term outcome. We conducted a systematic review of 16 level I and II studies after a strategy-based search of English literature on OVID Medline, PubMed, CINAHL, Cochrane, and EMBASE databases. We defined the endpoint of assessment as independent ambulation and ability to perform activities of daily living. Literature supports the use of a multimodal pain control to improve patient compliance in accelerated rehabilitation. Multimodal pain control with revised anesthesia protocols and accelerated rehabilitation speeds recovery after minimally invasive THA compared to the standard approach THA, but a smaller incision length or minimally invasive approach does not demonstrably improve the short-term outcome. Available studies justify no hip restrictions following an anterolateral approach but none have examined the question for a posterior approach. Preoperative physiotherapy may facilitate faster postoperative functional recovery but multicenter and well-designed prospective randomized studies with outcome measures are necessary to confirm its efficacy. Level II, therapeutic study. See Guidelines for Authors for a complete description of levels of evidence.

On the Integration of Remote Experimentation into Undergraduate Laboratories--Pedagogical Approach

ERIC Educational Resources Information Center

Esche, Sven K.

2005-01-01

This paper presents an Internet-based open approach to laboratory instruction. In this article, the author talks about an open laboratory approach using a multi-user multi-device remote facility. This approach involves both the direct contact with the computer-controlled laboratory setup of interest with the students present in the laboratory…

Towards Simpler Custom and OpenSearch Services for Voluminous NEWS Merged A-Train Data (Invited)

NASA Astrophysics Data System (ADS)

Hua, H.; Fetzer, E.; Braverman, A. J.; Lewis, S.; Henderson, M. L.; Guillaume, A.; Lee, S.; de La Torre Juarez, M.; Dang, H. T.

2010-12-01

To simplify access to large and complex satellite data sets for climate analysis and model verification, we developed web services that is used to study long-term and global-scale trends in climate, water and energy cycle, and weather variability. A related NASA Energy and Water Cycle Study (NEWS) task has created a merged NEWS Level 2 data from multiple instruments in NASA’s A-Train constellation of satellites. We used this data to enable creation of climatologies that include correlation between observed temperature, water vapor and cloud properties from the A-Train sensors. Instead of imposing on the user an often rigid and limiting web-based analysis environment, we recognize the need for simple and well-designed services so that users can perform analysis in their own familiar computing environments. Custom on-demand services were developed to improve data accessibility of voluminous multi-sensor data. Services enabling geospatial, geographical, and multi-sensor parameter subsets of the data, as well a custom time-averaged Level 3 service will be presented. We will also show how a Level 3Q data reduction approach can be used to help “browse” the voluminous multi-sensor Level 2 data. An OpenSearch capability with full text + space + time search of data products will also be presented as an approach to facilitated interoperability with other data systems. We will present our experiences for improving user usability as well as strategies for facilitating interoperability with other data systems.

A new system for parallel drug screening against multiple-resistant HIV mutants based on lentiviral self-inactivating (SIN) vectors and multi-colour analyses

PubMed Central

2013-01-01

Background Despite progress in the development of combined antiretroviral therapies (cART), HIV infection remains a significant challenge for human health. Current problems of cART include multi-drug-resistant virus variants, long-term toxicity and enormous treatment costs. Therefore, the identification of novel effective drugs is urgently needed. Methods We developed a straightforward screening approach for simultaneously evaluating the sensitivity of multiple HIV gag-pol mutants to antiviral drugs in one assay. Our technique is based on multi-colour lentiviral self-inactivating (SIN) LeGO vector technology. Results We demonstrated the successful use of this approach for screening compounds against up to four HIV gag-pol variants (wild-type and three mutants) simultaneously. Importantly, the technique was adapted to Biosafety Level 1 conditions by utilising ecotropic pseudotypes. This allowed upscaling to a large-scale screening protocol exploited by pharmaceutical companies in a successful proof-of-concept experiment. Conclusions The technology developed here facilitates fast screening for anti-HIV activity of individual agents from large compound libraries. Although drugs targeting gag-pol variants were used here, our approach permits screening compounds that target several different, key cellular and viral functions of the HIV life-cycle. The modular principle of the method also allows the easy exchange of various mutations in HIV sequences. In conclusion, the methodology presented here provides a valuable new approach for the identification of novel anti-HIV drugs. PMID:23286882

Targeted exploration and analysis of large cross-platform human transcriptomic compendia

PubMed Central

Zhu, Qian; Wong, Aaron K; Krishnan, Arjun; Aure, Miriam R; Tadych, Alicja; Zhang, Ran; Corney, David C; Greene, Casey S; Bongo, Lars A; Kristensen, Vessela N; Charikar, Moses; Li, Kai; Troyanskaya, Olga G.

2016-01-01

We present SEEK (http://seek.princeton.edu), a query-based search engine across very large transcriptomic data collections, including thousands of human data sets from almost 50 microarray and next-generation sequencing platforms. SEEK uses a novel query-level cross-validation-based algorithm to automatically prioritize data sets relevant to the query and a robust search approach to identify query-coregulated genes, pathways, and processes. SEEK provides cross-platform handling, multi-gene query search, iterative metadata-based search refinement, and extensive visualization-based analysis options. PMID:25581801

Reclaiming Gender and Power in Sexual Violence Prevention in Adolescence.

PubMed

Miller, Elizabeth

2018-03-01

The Mentors in Violence Prevention (MVP) model seeks to address the root causes of gender violence using a bystander approach and leadership training to challenge structures of patriarchy. Emerging research on adolescent relationship abuse and sexual violence points to key modifiable targets-transforming gender norms, addressing homophobia, integrating with comprehensive sexuality education, and acknowledging the needs of youth already exposed to violence. A social justice-based bystander approach such as the MVP model should be part of a multi-level approach to sexual violence prevention that addresses gender and power, encourages healthy sexuality conversations, and provides safety and support for survivors.

Integrating Model-Based Transmission Reduction into a multi-tier architecture

NASA Astrophysics Data System (ADS)

Straub, J.

A multi-tier architecture consists of numerous craft as part of the system, orbital, aerial, and surface tiers. Each tier is able to collect progressively greater levels of information. Generally, craft from lower-level tiers are deployed to a target of interest based on its identification by a higher-level craft. While the architecture promotes significant amounts of science being performed in parallel, this may overwhelm the computational and transmission capabilities of higher-tier craft and links (particularly the deep space link back to Earth). Because of this, a new paradigm in in-situ data processing is required. Model-based transmission reduction (MBTR) is such a paradigm. Under MBTR, each node (whether a single spacecraft in orbit of the Earth or another planet or a member of a multi-tier network) is given an a priori model of the phenomenon that it is assigned to study. It performs activities to validate this model. If the model is found to be erroneous, corrective changes are identified, assessed to ensure their significance for being passed on, and prioritized for transmission. A limited amount of verification data is sent with each MBTR assertion message to allow those that might rely on the data to validate the correct operation of the spacecraft and MBTR engine onboard. Integrating MBTR with a multi-tier framework creates an MBTR hierarchy. Higher levels of the MBTR hierarchy task lower levels with data collection and assessment tasks that are required to validate or correct elements of its model. A model of the expected conditions is sent to the lower level craft; which then engages its own MBTR engine to validate or correct the model. This may include tasking a yet lower level of craft to perform activities. When the MBTR engine at a given level receives all of its component data (whether directly collected or from delegation), it randomly chooses some to validate (by reprocessing the validation data), performs analysis and sends its own results (v- lidation and/or changes of model elements and supporting validation data) to its upstream node. This constrains data transmission to only significant (either because it includes a change or is validation data critical for assessing overall performance) information and reduces the processing requirements (by not having to process insignificant data) at higher-level nodes. This paper presents a framework for multi-tier MBTR and two demonstration mission concepts: an Earth sensornet and a mission to Mars. These multi-tier MBTR concepts are compared to a traditional mission approach.

Comparison of alternative approaches for analysing multi-level RNA-seq data

PubMed Central

Mohorianu, Irina; Bretman, Amanda; Smith, Damian T.; Fowler, Emily K.; Dalmay, Tamas

2017-01-01

RNA sequencing (RNA-seq) is widely used for RNA quantification in the environmental, biological and medical sciences. It enables the description of genome-wide patterns of expression and the identification of regulatory interactions and networks. The aim of RNA-seq data analyses is to achieve rigorous quantification of genes/transcripts to allow a reliable prediction of differential expression (DE), despite variation in levels of noise and inherent biases in sequencing data. This can be especially challenging for datasets in which gene expression differences are subtle, as in the behavioural transcriptomics test dataset from D. melanogaster that we used here. We investigated the power of existing approaches for quality checking mRNA-seq data and explored additional, quantitative quality checks. To accommodate nested, multi-level experimental designs, we incorporated sample layout into our analyses. We employed a subsampling without replacement-based normalization and an identification of DE that accounted for the hierarchy and amplitude of effect sizes within samples, then evaluated the resulting differential expression call in comparison to existing approaches. In a final step to test for broader applicability, we applied our approaches to a published set of H. sapiens mRNA-seq samples, The dataset-tailored methods improved sample comparability and delivered a robust prediction of subtle gene expression changes. The proposed approaches have the potential to improve key steps in the analysis of RNA-seq data by incorporating the structure and characteristics of biological experiments. PMID:28792517

Perioperative analgesia for patients undergoing endoscopic sinus surgery: an evidence-based review.

PubMed

Svider, Peter F; Nguyen, Brandon; Yuhan, Brian; Zuliani, Giancarlo; Eloy, Jean Anderson; Folbe, Adam J

2018-04-12

Misuse and diversion of prescription opioids have been critical in facilitating the opioid epidemic. Our objective was to perform a systematic evidence-based review delineating perioperative regimens (including opioid alternatives) evaluated for endoscopic sinus surgery. PubMed/MEDLINE, Cochrane Library, and EmBase databases were evaluated for studies detailing analgesics employed after endoscopic sinus surgery. Studies were assessed for level of evidence. Bias risk was evaluated using the Cochrane Bias tool and GRADE criteria. Medication, administration, adverse effects, pain scores, and rescue analgesic consumption were evaluated. A summary of evidence detailing benefits, harm, and cost was prepared. Thirty-two studies encompassing 1812 patients were included. The GRADE criteria determined the overall evidence to be of moderate quality. Perioperative acetaminophen had few adverse events and reduced immediate need for opioid rescue after sinus surgery; studies evaluating acetaminophen demonstrate a preponderance of benefit over harm. Nonsteroidal anti-inflammatory drugs (NSAIDs) also reduce postoperative opioid consumption, although a small portion of patients undergoing sinus surgery harbor the potential for NSAID intolerance. The aggregate level of evidence for studies evaluating NSAIDs was grade A, whereas the aggregate grade of evidence for several other agents was grade B. There is evidence supporting the use of NSAIDs and gabapentin for the control of pain after endoscopic sinus surgery. Acetaminophen, α-agonists, and local anesthetics are also viable options for postoperative analgesia. Familiarity with these data is essential to facilitate the use of opioid alternatives. Further large-scale, multi-institutional, randomized trials are needed to provide conclusive recommendations for these perioperative analgesics. © 2018 ARS-AAOA, LLC.

Peripheral arterial disease and revascularization of the diabetic foot.

PubMed

Forsythe, R O; Brownrigg, J; Hinchliffe, R J

2015-05-01

Diabetes is a complex disease with many serious potential sequelae, including large vessel arterial disease and microvascular dysfunction. Peripheral arterial disease is a common large vessel complication of diabetes, implicated in the development of tissue loss in up to half of patients with diabetic foot ulceration. In addition to peripheral arterial disease, functional changes in the microcirculation also contribute to the development of a diabetic foot ulcer, along with other factors such as infection, oedema and abnormal biomechanical loading. Peripheral arterial disease typically affects the distal vessels, resulting in multi-level occlusions and diffuse disease, which often necessitates challenging distal revascularisation surgery or angioplasty in order to improve blood flow. However, technically successful revascularisation does not always result in wound healing. The confounding effects of microvascular dysfunction must be recognised--treatment of a patient with a diabetic foot ulcer and peripheral arterial disease should address this complex interplay of pathophysiological changes. In the case of non-revascularisable peripheral arterial disease or poor response to conventional treatment, alternative approaches such as cell-based treatment, hyperbaric oxygen therapy and the use of vasodilators may appear attractive, however more robust evidence is required to justify these novel approaches. © 2014 John Wiley & Sons Ltd.

Semantics-Based Composition of Integrated Cardiomyocyte Models Motivated by Real-World Use Cases.

PubMed

Neal, Maxwell L; Carlson, Brian E; Thompson, Christopher T; James, Ryan C; Kim, Karam G; Tran, Kenneth; Crampin, Edmund J; Cook, Daniel L; Gennari, John H

2015-01-01

Semantics-based model composition is an approach for generating complex biosimulation models from existing components that relies on capturing the biological meaning of model elements in a machine-readable fashion. This approach allows the user to work at the biological rather than computational level of abstraction and helps minimize the amount of manual effort required for model composition. To support this compositional approach, we have developed the SemGen software, and here report on SemGen's semantics-based merging capabilities using real-world modeling use cases. We successfully reproduced a large, manually-encoded, multi-model merge: the "Pandit-Hinch-Niederer" (PHN) cardiomyocyte excitation-contraction model, previously developed using CellML. We describe our approach for annotating the three component models used in the PHN composition and for merging them at the biological level of abstraction within SemGen. We demonstrate that we were able to reproduce the original PHN model results in a semi-automated, semantics-based fashion and also rapidly generate a second, novel cardiomyocyte model composed using an alternative, independently-developed tension generation component. We discuss the time-saving features of our compositional approach in the context of these merging exercises, the limitations we encountered, and potential solutions for enhancing the approach.

Semantics-Based Composition of Integrated Cardiomyocyte Models Motivated by Real-World Use Cases

PubMed Central

Neal, Maxwell L.; Carlson, Brian E.; Thompson, Christopher T.; James, Ryan C.; Kim, Karam G.; Tran, Kenneth; Crampin, Edmund J.; Cook, Daniel L.; Gennari, John H.

2015-01-01

Semantics-based model composition is an approach for generating complex biosimulation models from existing components that relies on capturing the biological meaning of model elements in a machine-readable fashion. This approach allows the user to work at the biological rather than computational level of abstraction and helps minimize the amount of manual effort required for model composition. To support this compositional approach, we have developed the SemGen software, and here report on SemGen’s semantics-based merging capabilities using real-world modeling use cases. We successfully reproduced a large, manually-encoded, multi-model merge: the “Pandit-Hinch-Niederer” (PHN) cardiomyocyte excitation-contraction model, previously developed using CellML. We describe our approach for annotating the three component models used in the PHN composition and for merging them at the biological level of abstraction within SemGen. We demonstrate that we were able to reproduce the original PHN model results in a semi-automated, semantics-based fashion and also rapidly generate a second, novel cardiomyocyte model composed using an alternative, independently-developed tension generation component. We discuss the time-saving features of our compositional approach in the context of these merging exercises, the limitations we encountered, and potential solutions for enhancing the approach. PMID:26716837

Using multi-source satellite data for lake level modelling in ungauged basins: A case study for Lake Turkana, East Africa

USGS Publications Warehouse

Velpuri, N.M.; Senay, G.B.; Asante, K.O.

2011-01-01

Managing limited surface water resources is a great challenge in areas where ground-based data are either limited or unavailable. Direct or indirect measurements of surface water resources through remote sensing offer several advantages of monitoring in ungauged basins. A physical based hydrologic technique to monitor lake water levels in ungauged basins using multi-source satellite data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, a digital elevation model, and other data is presented. This approach is applied to model Lake Turkana water levels from 1998 to 2009. Modelling results showed that the model can reasonably capture all the patterns and seasonal variations of the lake water level fluctuations. A composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data is used for model calibration (1998-2000) and model validation (2001-2009). Validation results showed that model-based lake levels are in good agreement with observed satellite altimetry data. Compared to satellite altimetry data, the Pearson's correlation coefficient was found to be 0.81 during the validation period. The model efficiency estimated using NSCE is found to be 0.93, 0.55 and 0.66 for calibration, validation and combined periods, respectively. Further, the model-based estimates showed a root mean square error of 0.62 m and mean absolute error of 0.46 m with a positive mean bias error of 0.36 m for the validation period (2001-2009). These error estimates were found to be less than 15 % of the natural variability of the lake, thus giving high confidence on the modelled lake level estimates. The approach presented in this paper can be used to (a) simulate patterns of lake water level variations in data scarce regions, (b) operationally monitor lake water levels in ungauged basins, (c) derive historical lake level information using satellite rainfall and evapotranspiration data, and (d) augment the information provided by the satellite altimetry systems on changes in lake water levels. ?? Author(s) 2011.

A GIS-based multi-source and multi-box modeling approach (GMSMB) for air pollution assessment--a North American case study.

PubMed

Wang, Bao-Zhen; Chen, Zhi

2013-01-01

This article presents a GIS-based multi-source and multi-box modeling approach (GMSMB) to predict the spatial concentration distributions of airborne pollutant on local and regional scales. In this method, an extended multi-box model combined with a multi-source and multi-grid Gaussian model are developed within the GIS framework to examine the contributions from both point- and area-source emissions. By using GIS, a large amount of data including emission sources, air quality monitoring, meteorological data, and spatial location information required for air quality modeling are brought into an integrated modeling environment. It helps more details of spatial variation in source distribution and meteorological condition to be quantitatively analyzed. The developed modeling approach has been examined to predict the spatial concentration distribution of four air pollutants (CO, NO(2), SO(2) and PM(2.5)) for the State of California. The modeling results are compared with the monitoring data. Good agreement is acquired which demonstrated that the developed modeling approach could deliver an effective air pollution assessment on both regional and local scales to support air pollution control and management planning.

Hierarchical vs non-hierarchical audio indexation and classification for video genres

NASA Astrophysics Data System (ADS)

Dammak, Nouha; BenAyed, Yassine

2018-04-01

In this paper, Support Vector Machines (SVMs) are used for segmenting and indexing video genres based on only audio features extracted at block level, which has a prominent asset by capturing local temporal information. The main contribution of our study is to show the wide effect on the classification accuracies while using an hierarchical categorization structure based on Mel Frequency Cepstral Coefficients (MFCC) audio descriptor. In fact, the classification consists in three common video genres: sports videos, music clips and news scenes. The sub-classification may divide each genre into several multi-speaker and multi-dialect sub-genres. The validation of this approach was carried out on over 360 minutes of video span yielding a classification accuracy of over 99%.

Project Based Learning in Multi-Grade Class

ERIC Educational Resources Information Center

Ciftci, Sabahattin; Baykan, Ayse Aysun

2013-01-01

The purpose of this study is to evaluate project based learning in multi-grade classes. This study, based on a student-centered learning approach, aims to analyze students' and parents' interpretations. The study was done in a primary village school belonging to the Centre of Batman, already adapting multi-grade classes in their education system,…

Evidence-based neurosurgery

PubMed Central

Esene, Ignatius N.; Baeesa, Saleh S.; Ammar, Ahmed

2016-01-01

Medical evidence is obtainable from approaches, which might be descriptive, analytic and integrative and ranked into levels of evidence, graded according to quality and summarized into strengths of recommendation. Sources of evidence range from expert opinions through well-randomized control trials to meta-analyses. The conscientious, explicit, and judicious use of current best evidence in making decisions related to the care of individual patients defines the concept of evidence-based neurosurgery (EBN). We reviewed reference books of clinical epidemiology, evidence-based practice and other previously related articles addressing principles of evidence-based practice in neurosurgery. Based on existing theories and models and our cumulative years of experience and expertise conducting research and promoting EBN, we have synthesized and presented a holistic overview of the concept of EBN. We have also underscored the importance of clinical research and its relationship to EBN. Useful electronic resources are provided. The concept of critical appraisal is introduced. PMID:27356649

Management of bone disease in women after breast cancer.

PubMed

Milat, F; Vincent, A J

2015-01-01

Breast cancer and osteoporosis are common conditions affecting women, particularly following menopause. With increasing breast cancer incidence, effects of therapies and decreasing mortality, issues relating to the preservation of bone health with breast cancer therapy have become a priority. Contributing factors to bone loss and fractures in women with breast cancer include tumor effects, estrogen deprivation secondary to breast cancer therapies (chemotherapy, ovarian ablation or aromatase inhibitors), natural menopause and secondary causes of bone loss, typically from concurrently prescribed medications. Management of osteoporosis and other survivorship care is complex, and a multi-disciplinary approach is recommended with assessment of risk factors for bone loss, optimization of bone health through lifestyle approaches and pharmacological interventions based on evidence-based algorithms. This review examines the pathophysiology of bone loss and gives guidelines for the management of bone disease in women with breast cancer.

Adaptive mesh refinement and load balancing based on multi-level block-structured Cartesian mesh

NASA Astrophysics Data System (ADS)

Misaka, Takashi; Sasaki, Daisuke; Obayashi, Shigeru

2017-11-01

We developed a framework for a distributed-memory parallel computer that enables dynamic data management for adaptive mesh refinement and load balancing. We employed simple data structure of the building cube method (BCM) where a computational domain is divided into multi-level cubic domains and each cube has the same number of grid points inside, realising a multi-level block-structured Cartesian mesh. Solution adaptive mesh refinement, which works efficiently with the help of the dynamic load balancing, was implemented by dividing cubes based on mesh refinement criteria. The framework was investigated with the Laplace equation in terms of adaptive mesh refinement, load balancing and the parallel efficiency. It was then applied to the incompressible Navier-Stokes equations to simulate a turbulent flow around a sphere. We considered wall-adaptive cube refinement where a non-dimensional wall distance y+ near the sphere is used for a criterion of mesh refinement. The result showed the load imbalance due to y+ adaptive mesh refinement was corrected by the present approach. To utilise the BCM framework more effectively, we also tested a cube-wise algorithm switching where an explicit and implicit time integration schemes are switched depending on the local Courant-Friedrichs-Lewy (CFL) condition in each cube.

Evidence for a Cyanine Link between Propargylamine Drugs and Monoamine Oxidase Clarifies the Inactivation Mechanism

NASA Astrophysics Data System (ADS)

Albreht, Alen; Vovk, Irena; Mavri, Janez; Marco-Contelles, Jose; Ramsay, Rona R.

2018-05-01

Successful propargylamine drugs such as deprenyl inactivate monoamine oxidase (MAO), a target in multi-faceted approaches to prevent neurodegeneration in the aging population, but the chemical structure and mechanism of the irreversible inhibition are still debated. We characterized the covalent cyanine structure linking the multi-target propargylamine inhibitor ASS234 and the flavin adenine dinucleotide in MAO-A using a combination of ultra-high performance liquid chromatography, spectroscopy, mass spectrometry, and computational methods. The partial double bond character of the cyanine chain gives rise to 4 interconverting geometric isomers of the adduct which were chromatographically separated at low temperatures. The configuration of the cyanine linker governs adduct stability with segments of much higher flexibility and rigidity than previously hypothesized. The findings indicate the importance of intramolecular electrostatic interactions in the MAO binding site and provide key information relevant to incorporation of the propargyl moiety into novel multi-target drugs. Based on the structure, we propose a mechanism of MAO inactivation applicable to all propargylamine inhibitors.

Bayesian Model Selection under Time Constraints

NASA Astrophysics Data System (ADS)

Hoege, M.; Nowak, W.; Illman, W. A.

2017-12-01

Bayesian model selection (BMS) provides a consistent framework for rating and comparing models in multi-model inference. In cases where models of vastly different complexity compete with each other, we also face vastly different computational runtimes of such models. For instance, time series of a quantity of interest can be simulated by an autoregressive process model that takes even less than a second for one run, or by a partial differential equations-based model with runtimes up to several hours or even days. The classical BMS is based on a quantity called Bayesian model evidence (BME). It determines the model weights in the selection process and resembles a trade-off between bias of a model and its complexity. However, in practice, the runtime of models is another weight relevant factor for model selection. Hence, we believe that it should be included, leading to an overall trade-off problem between bias, variance and computing effort. We approach this triple trade-off from the viewpoint of our ability to generate realizations of the models under a given computational budget. One way to obtain BME values is through sampling-based integration techniques. We argue with the fact that more expensive models can be sampled much less under time constraints than faster models (in straight proportion to their runtime). The computed evidence in favor of a more expensive model is statistically less significant than the evidence computed in favor of a faster model, since sampling-based strategies are always subject to statistical sampling error. We present a straightforward way to include this misbalance into the model weights that are the basis for model selection. Our approach follows directly from the idea of insufficient significance. It is based on a computationally cheap bootstrapping error estimate of model evidence and is easy to implement. The approach is illustrated in a small synthetic modeling study.

An educational video to promote multi-factorial approaches for fall and injury prevention in long-term care facilities

PubMed Central

2014-01-01

Background Older adults living in long term care (LTC) settings are vulnerable to fall-related injuries. There is a need to develop and implement evidence-based approaches to address fall injury prevention in LTC. Knowledge translation (KT) interventions to support the uptake of evidence-based approaches to fall injury prevention in LTC need to be responsive to the learning needs of LTC staff and use mediums, such as videos, that are accessible and easy-to-use. This article describes the development of two unique educational videos to promote fall injury prevention in long-term care (LTC) settings. These videos are unique from other fall prevention videos in that they include video footage of real life falls captured in the LTC setting. Methods Two educational videos were developed (2012–2013) to support the uptake of findings from a study exploring the causes of falls based on video footage captured in LTC facilities. The videos were developed by: (1) conducting learning needs assessment in LTC settings via six focus groups (2) liaising with LTC settings to identify learning priorities through unstructured conversations; and (3) aligning the content with principles of adult learning theory. Results The videos included footage of falls, interviews with older adults and fall injury prevention experts. The videos present evidence-based fall injury prevention recommendations aligned to the needs of LTC staff and: (1) highlight recommendations deemed by LTC staff as most urgent (learner-centered learning); (2) highlight negative impacts of falls on older adults (encourage meaning-making); and, (3) prompt LTC staff to reflect on fall injury prevention practices (encourage critical reflection). Conclusions Educational videos are an important tool available to researchers seeking to translate evidence-based recommendations into LTC settings. Additional research is needed to determine their impact on practice. PMID:24884899

How community organizations moderate the effect of armed conflict on migration in Nepal

PubMed Central

Williams, Nathalie E.

2013-01-01

This article describes an analytical study of systematic micro-level variability in migration during conflict. The study is based on a multi-dimensional model of individual out-migration that examines the economic, social, and political consequences of conflict and how community organizations condition the experience of these consequences and systematically alter migration patterns. A unique combination of detailed data on violent events and individual behaviours during the Maoist insurrection in Nepal and multi-level event-history models were used to empirically test the model. Results indicate that community organizations dampened the effect of conflict on out-migration by providing resources that helped people to cope with the danger as well as economic, social and political consequences of conflict. This evidence suggests a systematic redistribution of population, partially contingent upon specific resources available in each community, which will likely affect the socio-demographic context of post-conflict Nepal into the future. PMID:23356735

A multi-scale, multi-disciplinary approach for assessing the technological, economic and environmental performance of bio-based chemicals.

PubMed

Herrgård, Markus; Sukumara, Sumesh; Campodonico, Miguel; Zhuang, Kai

2015-12-01

In recent years, bio-based chemicals have gained interest as a renewable alternative to petrochemicals. However, there is a significant need to assess the technological, biological, economic and environmental feasibility of bio-based chemicals, particularly during the early research phase. Recently, the Multi-scale framework for Sustainable Industrial Chemicals (MuSIC) was introduced to address this issue by integrating modelling approaches at different scales ranging from cellular to ecological scales. This framework can be further extended by incorporating modelling of the petrochemical value chain and the de novo prediction of metabolic pathways connecting existing host metabolism to desirable chemical products. This multi-scale, multi-disciplinary framework for quantitative assessment of bio-based chemicals will play a vital role in supporting engineering, strategy and policy decisions as we progress towards a sustainable chemical industry. © 2015 Authors; published by Portland Press Limited.

Acceptability and feasibility of a low-cost, theory-based and co-produced intervention to reduce workplace sitting time in desk-based university employees.

PubMed

Mackenzie, Kelly; Goyder, Elizabeth; Eves, Francis

2015-12-24

Prolonged sedentary time is linked with poor health, independent of physical activity levels. Workplace sitting significantly contributes to sedentary time, but there is limited research evaluating low-cost interventions targeting reductions in workplace sitting. Current evidence supports the use of multi-modal interventions developed using participative approaches. This study aimed to explore the acceptability and feasibility of a low-cost, co-produced, multi-modal intervention to reduce workplace sitting. The intervention was developed with eleven volunteers from a large university department in the UK using participative approaches and "brainstorming" techniques. Main components of the intervention included: emails suggesting ways to "sit less" e.g. walking and standing meetings; free reminder software to install onto computers; social media to increase awareness; workplace champions; management support; and point-of-decision prompts e.g. by lifts encouraging stair use. All staff (n = 317) were invited to take part. Seventeen participated in all aspects of the evaluation, completing pre- and post-intervention sitting logs and questionnaires. The intervention was delivered over four weeks from 7th July to 3rd August 2014. Pre- and post-intervention difference in daily workplace sitting time was presented as a mean ± standard deviation. Questionnaires were used to establish awareness of the intervention and its various elements, and to collect qualitative data regarding intervention acceptability and feasibility. Mean baseline sitting time of 440 min/workday was reported with a mean reduction of 26 ± 54 min/workday post-intervention (n = 17, 95 % CI = -2 to 53). All participants were aware of the intervention as a whole, although there was a range of awareness for individual elements of the intervention. The intervention was generally felt to be both acceptable and feasible. Management support was perceived to be a strength, whilst specific strategies that were encouraged, including walking and standing meetings, received mixed feedback. This small-scale pilot provides encouragement for the acceptability and feasibility of low-cost, multi-modal interventions to reduce workplace sitting in UK settings. Evaluation of this intervention provides useful information to support participatory approaches during intervention development and the potential for more sustainable low-cost interventions. Findings may be limited in terms of generalisability as this pilot was carried out within a health-related academic setting.

Model-Driven Useware Engineering

NASA Astrophysics Data System (ADS)

Meixner, Gerrit; Seissler, Marc; Breiner, Kai

User-oriented hardware and software development relies on a systematic development process based on a comprehensive analysis focusing on the users' requirements and preferences. Such a development process calls for the integration of numerous disciplines, from psychology and ergonomics to computer sciences and mechanical engineering. Hence, a correspondingly interdisciplinary team must be equipped with suitable software tools to allow it to handle the complexity of a multimodal and multi-device user interface development approach. An abstract, model-based development approach seems to be adequate for handling this complexity. This approach comprises different levels of abstraction requiring adequate tool support. Thus, in this chapter, we present the current state of our model-based software tool chain. We introduce the use model as the core model of our model-based process, transformation processes, and a model-based architecture, and we present different software tools that provide support for creating and maintaining the models or performing the necessary model transformations.

Structural analysis of health-relevant policy-making information exchange networks in Canada.

PubMed

Contandriopoulos, Damien; Benoît, François; Bryant-Lukosius, Denise; Carrier, Annie; Carter, Nancy; Deber, Raisa; Duhoux, Arnaud; Greenhalgh, Trisha; Larouche, Catherine; Leclerc, Bernard-Simon; Levy, Adrian; Martin-Misener, Ruth; Maximova, Katerina; McGrail, Kimberlyn; Nykiforuk, Candace; Roos, Noralou; Schwartz, Robert; Valente, Thomas W; Wong, Sabrina; Lindquist, Evert; Pullen, Carolyn; Lardeux, Anne; Perroux, Melanie

2017-09-20

Health systems worldwide struggle to identify, adopt, and implement in a timely and system-wide manner the best-evidence-informed-policy-level practices. Yet, there is still only limited evidence about individual and institutional best practices for fostering the use of scientific evidence in policy-making processes The present project is the first national-level attempt to (1) map and structurally analyze-quantitatively-health-relevant policy-making networks that connect evidence production, synthesis, interpretation, and use; (2) qualitatively investigate the interaction patterns of a subsample of actors with high centrality metrics within these networks to develop an in-depth understanding of evidence circulation processes; and (3) combine these findings in order to assess a policy network's "absorptive capacity" regarding scientific evidence and integrate them into a conceptually sound and empirically grounded framework. The project is divided into two research components. The first component is based on quantitative analysis of ties (relationships) that link nodes (participants) in a network. Network data will be collected through a multi-step snowball sampling strategy. Data will be analyzed structurally using social network mapping and analysis methods. The second component is based on qualitative interviews with a subsample of the Web survey participants having central, bridging, or atypical positions in the network. Interviews will focus on the process through which evidence circulates and enters practice. Results from both components will then be integrated through an assessment of the network's and subnetwork's effectiveness in identifying, capturing, interpreting, sharing, reframing, and recodifying scientific evidence in policy-making processes. Knowledge developed from this project has the potential both to strengthen the scientific understanding of how policy-level knowledge transfer and exchange functions and to provide significantly improved advice on how to ensure evidence plays a more prominent role in public policies.

Distributed Generation Planning using Peer Enhanced Multi-objective Teaching-Learning based Optimization in Distribution Networks

NASA Astrophysics Data System (ADS)

Selvam, Kayalvizhi; Vinod Kumar, D. M.; Siripuram, Ramakanth

2017-04-01

In this paper, an optimization technique called peer enhanced teaching learning based optimization (PeTLBO) algorithm is used in multi-objective problem domain. The PeTLBO algorithm is parameter less so it reduced the computational burden. The proposed peer enhanced multi-objective based TLBO (PeMOTLBO) algorithm has been utilized to find a set of non-dominated optimal solutions [distributed generation (DG) location and sizing in distribution network]. The objectives considered are: real power loss and the voltage deviation subjected to voltage limits and maximum penetration level of DG in distribution network. Since the DG considered is capable of injecting real and reactive power to the distribution network the power factor is considered as 0.85 lead. The proposed peer enhanced multi-objective optimization technique provides different trade-off solutions in order to find the best compromise solution a fuzzy set theory approach has been used. The effectiveness of this proposed PeMOTLBO is tested on IEEE 33-bus and Indian 85-bus distribution system. The performance is validated with Pareto fronts and two performance metrics (C-metric and S-metric) by comparing with robust multi-objective technique called non-dominated sorting genetic algorithm-II and also with the basic TLBO.

A multi-characteristic based algorithm for classifying vegetation in a plateau area: Qinghai Lake watershed, northwestern China

NASA Astrophysics Data System (ADS)

Ma, Weiwei; Gong, Cailan; Hu, Yong; Li, Long; Meng, Peng

2015-10-01

Remote sensing technology has been broadly recognized for its convenience and efficiency in mapping vegetation, particularly in high-altitude and inaccessible areas where there are lack of in-situ observations. In this study, Landsat Thematic Mapper (TM) images and Chinese environmental mitigation satellite CCD sensor (HJ-1 CCD) images, both of which are at 30m spatial resolution were employed for identifying and monitoring of vegetation types in a area of Western China——Qinghai Lake Watershed(QHLW). A decision classification tree (DCT) algorithm using multi-characteristic including seasonal TM/HJ-1 CCD time series data combined with digital elevation models (DEMs) dataset, and a supervised maximum likelihood classification (MLC) algorithm with single-data TM image were applied vegetation classification. Accuracy of the two algorithms was assessed using field observation data. Based on produced vegetation classification maps, it was found that the DCT using multi-season data and geomorphologic parameters was superior to the MLC algorithm using single-data image, improving the overall accuracy by 11.86% at second class level and significantly reducing the "salt and pepper" noise. The DCT algorithm applied to TM /HJ-1 CCD time series data geomorphologic parameters appeared as a valuable and reliable tool for monitoring vegetation at first class level (5 vegetation classes) and second class level(8 vegetation subclasses). The DCT algorithm using multi-characteristic might provide a theoretical basis and general approach to automatic extraction of vegetation types from remote sensing imagery over plateau areas.

Delamination detection by Multi-Level Wavelet Processing of Continuous Scanning Laser Doppler Vibrometry data

NASA Astrophysics Data System (ADS)

Chiariotti, P.; Martarelli, M.; Revel, G. M.

2017-12-01

A novel non-destructive testing procedure for delamination detection based on the exploitation of the simultaneous time and spatial sampling provided by Continuous Scanning Laser Doppler Vibrometry (CSLDV) and the feature extraction capability of Multi-Level wavelet-based processing is presented in this paper. The processing procedure consists in a multi-step approach. Once the optimal mother-wavelet is selected as the one maximizing the Energy to Shannon Entropy Ratio criterion among the mother-wavelet space, a pruning operation aiming at identifying the best combination of nodes inside the full-binary tree given by Wavelet Packet Decomposition (WPD) is performed. The pruning algorithm exploits, in double step way, a measure of the randomness of the point pattern distribution on the damage map space with an analysis of the energy concentration of the wavelet coefficients on those nodes provided by the first pruning operation. A combination of the point pattern distributions provided by each node of the ensemble node set from the pruning algorithm allows for setting a Damage Reliability Index associated to the final damage map. The effectiveness of the whole approach is proven on both simulated and real test cases. A sensitivity analysis related to the influence of noise on the CSLDV signal provided to the algorithm is also discussed, showing that the processing developed is robust enough to measurement noise. The method is promising: damages are well identified on different materials and for different damage-structure varieties.

Population-level interventions to reduce alcohol-related harm: an overview of systematic reviews.

PubMed

Martineau, Fred; Tyner, Elizabeth; Lorenc, Theo; Petticrew, Mark; Lock, Karen

2013-10-01

To analyse available review-level evidence on the effectiveness of population-level interventions in non-clinical settings to reduce alcohol consumption or related health or social harm. Health, social policy and specialist review databases between 2002 and 2012 were searched for systematic reviews of the effectiveness of population-level alcohol interventions on consumption or alcohol-related health or social outcomes. Data were extracted on review research aim, inclusion criteria, outcome indicators, results, conclusions and limitations. Reviews were quality-assessed using AMSTAR criteria. A narrative synthesis was conducted overall and by policy area. Fifty-two reviews were included from ten policy areas. There is good evidence for policies and interventions to limit alcohol sale availability, to reduce drink-driving, to increase alcohol price or taxation. There is mixed evidence for family- and community-level interventions, school-based interventions, and interventions in the alcohol server setting and the mass media. There is weak evidence for workplace interventions and for interventions targeting illicit alcohol sales. There is evidence of the ineffectiveness of interventions in higher education settings. There is a pattern of support from the evidence base for regulatory or statutory enforcement interventions over local non-regulatory approaches targeting specific population groups. © 2013.

A Multi-Level Examination of Stakeholder Perspectives of Implementation of Evidence-Based Practices in a Large Urban Publicly-Funded Mental Health System.

PubMed

Beidas, Rinad S; Stewart, Rebecca E; Adams, Danielle R; Fernandez, Tara; Lustbader, Susanna; Powell, Byron J; Aarons, Gregory A; Hoagwood, Kimberly E; Evans, Arthur C; Hurford, Matthew O; Rubin, Ronnie; Hadley, Trevor; Mandell, David S; Barg, Frances K

2016-11-01

Our goal was to identify barriers and facilitators to the implementation of evidence-based practices from the perspectives of multiple stakeholders in a large publicly funded mental health system. We completed 56 interviews with three stakeholder groups: treatment developers (n = 7), agency administrators (n = 33), and system leadership (n = 16). The three stakeholder groups converged on the importance of inner (e.g., agency competing resources and demands, therapist educational background) and outer context (e.g., funding) factors as barriers to implementation. Potential threats to implementation and sustainability included the fiscal landscape of community mental health clinics and an evolving workforce. Intervention characteristics were rarely endorsed as barriers. Inner context, outer context, and intervention characteristics were all seen as important facilitators. All stakeholders endorsed the importance of coordinated collaboration across stakeholder groups within the system to successfully implement evidence-based practices.

Increasing knowledge of best practices for occupational therapists treating post-stroke unilateral spatial neglect: results of a knowledge-translation intervention study.

PubMed

Petzold, Anita; Korner-Bitensky, Nicol; Salbach, Nancy M; Ahmed, Sara; Menon, Anita; Ogourtsova, Tatiana

2012-02-01

The aim of this study was to investigate: (i) the feasibility of delivering a multi-modal knowledge translation intervention specific to the management of acute post-stroke unilateral spatial neglect; and (ii) the impact of the knowledge translation intervention on occupational therapists' knowledge of evidence-based unilateral spatial neglect problem identification, assessment and treatment, and self-efficacy related to evidence-based practice implementation. A 3-period (pre-post) repeated measures design. Acute care occupational therapists treating patients with post-stroke unilateral spatial neglect were recruited from two major Canadian cities. Participants completed two pre-intervention assessments, took part in a day-long interactive multi-modal knowledge translation intervention and a subsequent 8-week follow-up, and completed a post-intervention assessment. Knowledge of evidence-based problem identification, assessment and treatment of unilateral spatial neglect, and self-efficacy to perform evidence-based practice activities were measured using standard scales. The intervention was tested on 20 occupational therapists. Results indicate a significant improvement in knowledge of best practice unilateral spatial neglect management (p < 0.000) and evidence-based practice self-efficacy in carrying out evidence-based practice activities (p < 0.045) post-intervention. Use of a multi-modal knowledge translation intervention is feasible and can significantly improve occupational therapists' knowledge of unilateral spatial neglect best practices and self-efficacy. The findings should help advance best practices specific to the management of post-stroke unilateral spatial neglect as well as informing knowledge translation studies in other areas of practice.

Civil Engineering Applications of Ground Penetrating Radar Recent Advances @ the ELEDIA Research Center

NASA Astrophysics Data System (ADS)

Salucci, Marco; Tenuti, Lorenza; Nardin, Cristina; Oliveri, Giacomo; Viani, Federico; Rocca, Paolo; Massa, Andrea

2014-05-01

The application of non-destructive testing and evaluation (NDT/NDE) methodologies in civil engineering has raised a growing interest during the last years because of its potential impact in several different scenarios. As a consequence, Ground Penetrating Radar (GPR) technologies have been widely adopted as an instrument for the inspection of the structural stability of buildings and for the detection of cracks and voids. In this framework, the development and validation of GPR algorithms and methodologies represents one of the most active research areas within the ELEDIA Research Center of the University of Trento. More in detail, great efforts have been devoted towards the development of inversion techniques based on the integration of deterministic and stochastic search algorithms with multi-focusing strategies. These approaches proved to be effective in mitigating the effects of both nonlinearity and ill-posedness of microwave imaging problems, which represent the well-known issues arising in GPR inverse scattering formulations. More in detail, a regularized multi-resolution approach based on the Inexact Newton Method (INM) has been recently applied to subsurface prospecting, showing a remarkable advantage over a single-resolution implementation [1]. Moreover, the use of multi-frequency or frequency-hopping strategies to exploit the information coming from GPR data collected in time domain and transformed into its frequency components has been proposed as well. In this framework, the effectiveness of the multi-resolution multi-frequency techniques has been proven on synthetic data generated with numerical models such as GprMax [2]. The application of inversion algorithms based on Bayesian Compressive Sampling (BCS) [3][4] to GPR is currently under investigation, as well, in order to exploit their capability to provide satisfactory reconstructions in presence of single and multiple sparse scatterers [3][4]. Furthermore, multi-scaling approaches exploiting level-set-based optimization have been developed for the qualitative reconstruction of multiple and disconnected homogeneous scatterers [5]. Finally, the real-time detection and classification of subsurface scatterers has been investigated by means of learning-by-examples (LBE) techniques, such as Support Vector Machines (SVM) [6]. Acknowledgment - This work was partially supported by COST Action TU1208 'Civil Engineering Applications of Ground Penetrating Radar' References [1] M. Salucci, D. Sartori, N. Anselmi, A. Randazzo, G. Oliveri, and A. Massa, 'Imaging Buried Objects within the Second-Order Born Approximation through a Multiresolution Regularized Inexact-Newton Method', 2013 International Symposium on Electromagnetic Theory (EMTS), (Hiroshima, Japan), May 20-24 2013 (invited). [2] A. Giannopoulos, 'Modelling ground penetrating radar by GprMax', Construct. Build. Mater., vol. 19, no. 10, pp.755 -762 2005 [3] L. Poli, G. Oliveri, P. Rocca, and A. Massa, "Bayesian compressive sensing approaches for the reconstruction of two-dimensional sparse scatterers under TE illumination," IEEE Trans. Geosci. Remote Sensing, vol. 51, no. 5, pp. 2920-2936, May. 2013. [4] L. Poli, G. Oliveri, and A. Massa, "Imaging sparse metallic cylinders through a Local Shape Function Bayesian Compressive Sensing approach," Journal of Optical Society of America A, vol. 30, no. 6, pp. 1261-1272, 2013. [5] M. Benedetti, D. Lesselier, M. Lambert, and A. Massa, "Multiple shapes reconstruction by means of multi-region level sets," IEEE Trans. Geosci. Remote Sensing, vol. 48, no. 5, pp. 2330-2342, May 2010. [6] L. Lizzi, F. Viani, P. Rocca, G. Oliveri, M. Benedetti and A. Massa, "Three-dimensional real-time localization of subsurface objects - From theory to experimental validation," 2009 IEEE International Geoscience and Remote Sensing Symposium, vol. 2, pp. II-121-II-124, 12-17 July 2009.

Cardiac Multi-detector CT Segmentation Based on Multiscale Directional Edge Detector and 3D Level Set.

PubMed

Antunes, Sofia; Esposito, Antonio; Palmisano, Anna; Colantoni, Caterina; Cerutti, Sergio; Rizzo, Giovanna

2016-05-01

Extraction of the cardiac surfaces of interest from multi-detector computed tomographic (MDCT) data is a pre-requisite step for cardiac analysis, as well as for image guidance procedures. Most of the existing methods need manual corrections, which is time-consuming. We present a fully automatic segmentation technique for the extraction of the right ventricle, left ventricular endocardium and epicardium from MDCT images. The method consists in a 3D level set surface evolution approach coupled to a new stopping function based on a multiscale directional second derivative Gaussian filter, which is able to stop propagation precisely on the real boundary of the structures of interest. We validated the segmentation method on 18 MDCT volumes from healthy and pathologic subjects using manual segmentation performed by a team of expert radiologists as gold standard. Segmentation errors were assessed for each structure resulting in a surface-to-surface mean error below 0.5 mm and a percentage of surface distance with errors less than 1 mm above 80%. Moreover, in comparison to other segmentation approaches, already proposed in previous work, our method presented an improved accuracy (with surface distance errors less than 1 mm increased of 8-20% for all structures). The obtained results suggest that our approach is accurate and effective for the segmentation of ventricular cavities and myocardium from MDCT images.

Intervention Mapping as a Participatory Approach to Developing an HIV prevention Intervention in Rural African American Communities

PubMed Central

Corbie-Smith, Giselle; Akers, Aletha; Blumenthal, Connie; Council, Barbara; Wynn, Mysha; Muhammad, Melvin; Stith, Doris

2011-01-01

Southeastern states are among the hardest hit by the HIV epidemic in this country, and racial disparities in HIV rates are high in this region. This is particularly true in our communities of interest in rural eastern North Carolina. Although most recent efforts to prevent HIV attempt to address multiple contributing factors, we have found few multilevel HIV interventions that have been developed, tailored or tested in rural communities for African Americans. We describe how Project GRACE integrated Intervention Mapping (IM) methodology with community based participatory research (CBPR) principles to develop a multi-level, multi-generational HIV prevention intervention. IM was carried out in a series of steps from review of relevant data through producing program components. Through the IM process, all collaborators agreed that we needed a family-based intervention involving youth and their caregivers. We found that the structured approach of IM can be adapted to incorporate the principles of CBPR. PMID:20528128

A multi-band, multi-level, multi-electron model for efficient FDTD simulations of electromagnetic interactions with semiconductor quantum wells

NASA Astrophysics Data System (ADS)

Ravi, Koustuban; Wang, Qian; Ho, Seng-Tiong

2015-08-01

We report a new computational model for simulations of electromagnetic interactions with semiconductor quantum well(s) (SQW) in complex electromagnetic geometries using the finite-difference time-domain method. The presented model is based on an approach of spanning a large number of electron transverse momentum states in each SQW sub-band (multi-band) with a small number of discrete multi-electron states (multi-level, multi-electron). This enables accurate and efficient two-dimensional (2-D) and three-dimensional (3-D) simulations of nanophotonic devices with SQW active media. The model includes the following features: (1) Optically induced interband transitions between various SQW conduction and heavy-hole or light-hole sub-bands are considered. (2) Novel intra sub-band and inter sub-band transition terms are derived to thermalize the electron and hole occupational distributions to the correct Fermi-Dirac distributions. (3) The terms in (2) result in an explicit update scheme which circumvents numerically cumbersome iterative procedures. This significantly augments computational efficiency. (4) Explicit update terms to account for carrier leakage to unconfined states are derived, which thermalize the bulk and SQW populations to a common quasi-equilibrium Fermi-Dirac distribution. (5) Auger recombination and intervalence band absorption are included. The model is validated by comparisons to analytic band-filling calculations, simulations of SQW optical gain spectra, and photonic crystal lasers.

A Market-Based Approach to Multi-factory Scheduling

NASA Astrophysics Data System (ADS)

Vytelingum, Perukrishnen; Rogers, Alex; MacBeth, Douglas K.; Dutta, Partha; Stranjak, Armin; Jennings, Nicholas R.

In this paper, we report on the design of a novel market-based approach for decentralised scheduling across multiple factories. Specifically, because of the limitations of scheduling in a centralised manner - which requires a center to have complete and perfect information for optimality and the truthful revelation of potentially commercially private preferences to that center - we advocate an informationally decentralised approach that is both agile and dynamic. In particular, this work adopts a market-based approach for decentralised scheduling by considering the different stakeholders representing different factories as self-interested, profit-motivated economic agents that trade resources for the scheduling of jobs. The overall schedule of these jobs is then an emergent behaviour of the strategic interaction of these trading agents bidding for resources in a market based on limited information and their own preferences. Using a simple (zero-intelligence) bidding strategy, we empirically demonstrate that our market-based approach achieves a lower bound efficiency of 84%. This represents a trade-off between a reasonable level of efficiency (compared to a centralised approach) and the desirable benefits of a decentralised solution.

An approach for setting evidence-based and stakeholder-informed research priorities in low- and middle-income countries.

PubMed

Rehfuess, Eva A; Durão, Solange; Kyamanywa, Patrick; Meerpohl, Joerg J; Young, Taryn; Rohwer, Anke

2016-04-01

To derive evidence-based and stakeholder-informed research priorities for implementation in African settings, the international research consortium Collaboration for Evidence-Based Healthcare and Public Health in Africa (CEBHA+) developed and applied a pragmatic approach. First, an online survey and face-to-face consultation between CEBHA+ partners and policy-makers generated priority research areas. Second, evidence maps for these priority research areas identified gaps and related priority research questions. Finally, study protocols were developed for inclusion within a grant proposal. Policy and practice representatives were involved throughout the process. Tuberculosis, diabetes, hypertension and road traffic injuries were selected as priority research areas. Evidence maps covered screening and models of care for diabetes and hypertension, population-level prevention of diabetes and hypertension and their risk factors, and prevention and management of road traffic injuries. Analysis of these maps yielded three priority research questions on hypertension and diabetes and one on road traffic injuries. The four resulting study protocols employ a broad range of primary and secondary research methods; a fifth promotes an integrated methodological approach across all research activities. The CEBHA+ approach, in particular evidence mapping, helped to formulate research questions and study protocols that would be owned by African partners, fill gaps in the evidence base, address policy and practice needs and be feasible given the existing research infrastructure and expertise. The consortium believes that the continuous involvement of decision-makers throughout the research process is an important means of ensuring that studies are relevant to the African context and that findings are rapidly implemented.

A systematic review of the effectiveness of individual, community and societal-level interventions at reducing socio-economic inequalities in obesity among adults

PubMed Central

Hillier-Brown, F C; Bambra, C L; Cairns, J-M; Kasim, A; Moore, H J; Summerbell, C D

2014-01-01

Background: Socioeconomic inequalities in obesity are well established in high-income countries. There is a lack of evidence of the types of intervention that are effective in reducing these inequalities among adults. Objectives: To systematically review studies of the effectiveness of individual, community and societal interventions in reducing socio-economic inequalities in obesity among adults. Methods: Nine electronic databases were searched from start date to October 2012 along with website and grey literature searches. The review examined the best available international evidence (both experimental and observational) of interventions at an individual, community and societal level that might reduce inequalities in obesity among adults (aged 18 years or over) in any setting and country. Studies were included if they reported a body fatness-related outcome and if they included a measure of socio-economic status. Data extraction and quality appraisal were conducted using established mechanisms and narrative synthesis was conducted. Results: The ‘best available' international evidence was provided by 20 studies. At the individual level, there was evidence of the effectiveness of primary care delivered tailored weight loss programmes among deprived groups. Community based behavioural weight loss interventions and community diet clubs (including workplace ones) also had some evidence of effectiveness—at least in the short term. Societal level evaluations were few, low quality and inconclusive. Further, there was little evidence of long term effectiveness, and few studies of men or outside the USA. However, there was no evidence to suggest that interventions increase inequalities. Conclusions: The best available international evidence suggests that some individual and community-based interventions may be effective in reducing socio-economic inequalities in obesity among adults in the short term. Further research is required particularly of more complex, multi-faceted and societal-level interventions. PMID:24813369

Multi-level significance of vulnerability indicators. Case study: Eastern Romania

NASA Astrophysics Data System (ADS)

Stanga, I. C.; Grozavu, A.

2012-04-01

Vulnerability assessment aims, most frequently, to emphasize internal fragility of a system comparing to a reference standard, to similar systems or in relation to a given hazard. Internal fragility, either biophysical or structural, may affect the capacity to predict, to prepare for, to cope with or to recover from a disaster. Thus, vulnerability is linked to resilience and adaptive capacity. From local level to global one, vulnerability factors and corresponding indicators are different and their significance must be tested and validated in a well-structured conceptual and methodological framework. In this paper, the authors aim to show the real vulnerability of rural settlements in Eastern Romania in a multi-level approach. The research area, Tutova Hills, counts about 3421 sq.km and more than 200.000 inhabitants in 421 villages characterized by deficient accessibility, lack of endowments, subsistential agriculture, high pressure on natural environment (especially on forest and soil resources), poverty and aging process of population. Factors that could influence the vulnerability of these rural settlements have been inventoried and assigned into groups through a cluster analysis: habitat and technical urban facilities, infrastructure, economical, social and demographical indicators, environment quality, management of emergency situations etc. Firstly, the main difficulty was to convert qualitative variable in quantitative indicators and to standardize all values to make possible mathematical and statistical processing of data. Secondly, the great variability of vulnerability factors, their different measuring units and their high amplitude of variation require different method of standardization in order to obtain values between zero (minimum vulnerability) and one (maximum vulnerability). Final vulnerability indicators were selected and integrated in a general scheme, according to their significance resulted from an appropriate factor analysis: linear and logistic regression, varimax rotation, multiple-criteria decision analysis, weight of evidence, multi-criteria evaluation method etc. The approach started from the local level which allows a functional and structural analysis and was progressively translated to an upper level and to a spatial analysis. The model shows that changing the level of analysis diminishes the functional significance of some indicators and increases the capacity of discretization in the case of others, highlighting the spatial and functional complexity of vulnerability.

Risk Factors of HIV and Other Sexually Transmitted Infections in China: A Systematic Review of Reviews

PubMed Central

Wong, William Chi Wai

2015-01-01

Background Sexually Transmitted Infections (STIs) are a global challenge. China, once said to have eradicated STIs, is now facing a rapid rise in the prevalence of HIV/STIs. This review of reviews aims to map HIV/STI risk factors among the Chinese population, with the objective of identifying risk factors to inform the formulation of effective prevention strategies. Methods A systematic search using key terms related to HIV/STIs, risk factors and the Chinese population in both English and Chinese databases (PubMed, PsycINFO, the Cochrane Library; Wanfang data, CNKI, VIP and SINOMED) was conducted, and peer-reviewed systematic reviews on the topic from 1991 to 2014 were selected. Identified risk factors were grouped into different level determinants based on the HIV Social Epidemiology Model, and then evaluated and reported based on the PRISMA checklist. Findings Of the twenty-eight reviews included, the majority were focused on well-established, individual level risk factors within key populations, with some highlighting the complexity of interacting factors (e.g., alcohol use and higher income in male migrants). While twenty-two reviews covered individual factors, only ten mentioned social factors and five had contents on structural factors. There are gaps in the evidence on social and structural level impacts of HIV/STIs, such as on stigma, discrimination, health policy, access to care, and illicit drug control policies. Migration and social expectation appear to pose a significant threat in aggravating the HIV/STI situation in China; for example, incarceration patterns indicated a significant risk of HIV/STIs for female sex workers. Conclusions Since international guidelines recommend an integrated and multi-level approach to HIV/STI prevention, a comprehensive approach targeting interventions at all levels along the continuum of care is needed to effectively curtail HIV/STI transmission in China. More research is needed to better understand the impact of socio-political interventions within a Chinese context. PMID:26468650

Policy, Systems, and Environmental Change in the Mississippi Delta: Considerations for Evaluation Design

ERIC Educational Resources Information Center

Kegler, Michelle C.; Honeycutt, Sally; Davis, Melvin; Dauria, Emily; Berg, Carla; Dove, Cassandra; Gamble, Abigail; Hawkins, Jackie

2015-01-01

Community-level policy, systems, and environmental (PSE) change strategies may offer an economical and sustainable approach to chronic disease prevention. The rapidly growing number of untested but promising PSE strategies currently underway offers an exciting opportunity to establish practice-based evidence for this approach. This article…

Collaborative action for person-centred coordinated care (P3C): an approach to support the development of a comprehensive system-wide solution to fragmented care.

PubMed

Lloyd, Helen M; Pearson, Mark; Sheaff, Rod; Asthana, Sheena; Wheat, Hannah; Sugavanam, Thava Priya; Britten, Nicky; Valderas, Jose; Bainbridge, Michael; Witts, Louise; Westlake, Debra; Horrell, Jane; Byng, Richard

2017-11-22

Fragmented care results in poor outcomes for individuals with complexity of need. Person-centred coordinated care (P3C) is perceived to be a potential solution, but an absence of accessible evidence and the lack of a scalable 'blue print' mean that services are 'experimenting' with new models of care with little guidance and support. This paper presents an approach to the implementation of P3C using collaborative action, providing examples of early developments across this programme of work, the core aim of which is to accelerate the spread and adoption of P3C in United Kingdom primary care settings. Two centrally funded United Kingdom organisations (South West Collaboration for Leadership in Applied Health Research and Care and South West Academic Health Science Network) are leading this initiative to narrow the gap between research and practice in this urgent area of improvement through a programme of service change, evaluation and research. Multi-stakeholder engagement and co-design are core to the approach. A whole system measurement framework combines outcomes of importance to patients, practitioners and health organisations. Iterative and multi-level feedback helps to shape service change while collecting practice-based data to generate implementation knowledge for the delivery of P3C. The role of the research team is proving vital to support informed change and challenge organisational practice. The bidirectional flow of knowledge and evidence relies on the transitional positioning of researchers and research organisations. Extensive engagement and embedded researchers have led to strong collaborations across the region. Practice is beginning to show signs of change and data flow and exchange is taking place. However, working in this way is not without its challenges; progress has been slow in the development of a linked data set to allow us to assess impact innovations from a cost perspective. Trust is vital, takes time to establish and is dependent on the exchange of services and interactions. If collaborative action can foster P3C it will require sustained commitment from both research and practice. This approach is a radical departure from how policy, research and practice traditionally work, but one that we argue is now necessary to deal with the most complex health and social problems.

Ontological approach for safe and effective polypharmacy prescription

PubMed Central

Grando, Adela; Farrish, Susan; Boyd, Cynthia; Boxwala, Aziz

2012-01-01

The intake of multiple medications in patients with various medical conditions challenges the delivery of medical care. Initial empirical studies and pilot implementations seem to indicate that generic safe and effective multi-drug prescription principles could be defined and reused to reduce adverse drug events and to support compliance with medical guidelines and drug formularies. Given that ontologies are known to provide well-principled, sharable, setting-independent and machine-interpretable declarative specification frameworks for modeling and reasoning on biomedical problems, we explore here their use in the context of multi-drug prescription. We propose an ontology for modeling drug-related knowledge and a repository of safe and effective generic prescription principles. To test the usability and the level of granularity of the developed ontology-based specification models and heuristic we implemented a tool that computes the complexity of multi-drug treatments, and a decision aid to check the safeness and effectiveness of prescribed multi-drug treatments. PMID:23304299

Pattern search in multi-structure data: a framework for the next-generation evidence-based medicine

NASA Astrophysics Data System (ADS)

Sukumar, Sreenivas R.; Ainsworth, Keela C.

2014-03-01

With the impetus towards personalized and evidence-based medicine, the need for a framework to analyze/interpret quantitative measurements (blood work, toxicology, etc.) with qualitative descriptions (specialist reports after reading images, bio-medical knowledgebase, etc.) to predict diagnostic risks is fast emerging. Addressing this need, we pose and answer the following questions: (i) How can we jointly analyze and explore measurement data in context with qualitative domain knowledge? (ii) How can we search and hypothesize patterns (not known apriori) from such multi-structure data? (iii) How can we build predictive models by integrating weakly-associated multi-relational multi-structure data? We propose a framework towards answering these questions. We describe a software solution that leverages hardware for scalable in-memory analytics and applies next-generation semantic query tools on medical data.

Diabetic foot infections: Current treatment and delaying the 'post-antibiotic era'.

PubMed

Lipsky, Benjamin A

2016-01-01

Treatment for diabetic foot infections requires properly diagnosing infection, obtaining an appropriate specimen for culture, assessing for any needed surgical procedures and selecting an empiric antibiotic regimen. Therapy will often need to be modified based on results of culture and sensitivity testing. Because of excessive and inappropriate use of antibiotics for treating diabetic foot infections, resistance to the usually employed bacteria has been increasing to alarming levels. This article reviews recommendations from evidence-based guidelines, informed by results of systematic reviews, on treating diabetic foot infections. Data from the pre-antibiotic era reported rates of mortality of about 9% and of high-level leg amputations of about 70%. Outcomes have greatly improved with appropriate antibiotic therapy. While there are now many oral and parenteral antibiotic agents that have demonstrated efficacy in treating diabetic foot infections, the rate of infection with multidrug-resistant pathogens is growing. This problem requires a multi-focal approach, including providing education to both clinicians and patients, developing robust antimicrobial stewardship programmes and using new diagnostic and therapeutic technologies. Recently, new methods have been developed to find novel antibiotic agents and to resurrect old treatments, like bacteriophages, for treating these difficult infections. Medical and political leaders have recognized the serious global threat posed by the growing problem of antibiotic resistance. By a multipronged approach that includes exerting administrative pressure on clinicians to do the right thing, investing in new technologies and encouraging the profitable development of new antimicrobials, we may be able to stave off the coming 'post-antibiotic era'. Copyright © 2016 John Wiley & Sons, Ltd.

Effectiveness of an education intervention to strengthen nurses' readiness for evidence-based practice: A single-blind randomized controlled study.

PubMed

Saunders, Hannele; Vehviläinen-Julkunen, Katri; Stevens, Kathleen R

2016-08-01

Nurses' lack of readiness for evidence-based practice slows down the uptake, adoption, and implementation of evidence-based practice which is of international concern as it impedes attainment of the highest quality of care and best patient outcomes. There is limited evidence about the most effective approaches to strengthen nurses' readiness for evidence-based practice. To evaluate the effectiveness of an Advanced Practice Nurse-delivered education program to strengthen nurses' readiness for evidence-based practice at a university hospital. A single-blind randomized controlled trial with repeated measures design, with measures completed during spring and fall 2015, before the education program (T0), within 1week after (T1), 8weeks after (T2), and 4months after completion of education interventions (T3). One large university hospital system in Finland, consisting of 15 acute care hospitals. The required sample size, calculated by a priori power analysis and including a 20% estimated attrition rate, called for 85 nurse participants to be recruited. Nurses working in different professional nursing roles and care settings were randomly allocated into two groups: intervention (evidence-based practice education, N=43) and control (research utilization education, N=34). The nurse participants received live 4-h education sessions on the basic principles of evidence-based practice (intervention group) and on the principles of research utilization (control group). The intervention group also received a web-based interactive evidence-based practice education module with a booster mentoring intervention. Readiness for evidence-based practice data, previous experience with evidence-based practice, and participant demographics were collected using the Stevens' EBP Readiness Inventory. Nurses' confidence in employing evidence-based practice and actual evidence-based practice knowledge were lower at T0, compared with the post-education scores, specifically at T1. The improvement in the confidence or actual evidence-based practice knowledge levels did not differ between the intervention and control groups. Confidence in employing evidence-based practice was directly correlated with level of education and inversely correlated with age. Actual evidence-based practice knowledge was lowest among nurses who had no previous knowledge or experience of evidence-based practice. Both the evidence-based practice and research utilization education interventions improved nurses' confidence in employing evidence-based practice and actual evidence-based practice knowledge, strengthening their evidence-based practice readiness at least in the short-term. Most of the variation in the confidence in employing evidence-based practice and actual evidence-based practice knowledge levels was due to background factors, such as primary role and education level, which emphasize differences in educational needs between nurses with diverse backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Fuel for Fun: a cluster-randomized controlled study of cooking skills, eating behaviors, and physical activity of 4th graders and their families.

PubMed

Cunningham-Sabo, Leslie; Lohse, Barbara; Smith, Stephanie; Browning, Ray; Strutz, Erin; Nigg, Claudio; Balgopal, Meena; Kelly, Kathleen; Ruder, Elizabeth

2016-05-26

Childhood obesity remains a serious concern in the United States and in many other countries. Direct experience preparing and tasting healthful foods and increasing activity during the school day are promising prevention approaches. Engaging parents and families remains an important challenge. Fuel for Fun: Cooking with Kids Plus Parents and Play is a multi-component school- and family-based intervention for 4th graders and their families intended to promote positive food and activity environments, policies and behaviors at the individual, family and school levels. This paper describes the design and evaluation plan. Four cohorts of 4th-graders and their parents from 8 schools in 2 districts in the same Northern Colorado region are participating in a 4-arm cluster randomized controlled trial. Theory-based Fuel for Fun consists of 5 components delivered over 1 school year: 1) Cooking with Kids - Colorado; an experiential classroom-based cooking and tasting curriculum, 2) Cafeteria Connections; cafeteria-based reinforcements of classroom food experiences using behavioral economic strategies, 3) SPARK active recess; a playground intervention to engage children in moderate to vigorous activity, 4) Fuel for Fun Family; multi-element supports targeting parents to reinforce the 3 school-based components at home, and 5) About Eating; an online interactive program for parents addressing constructs of eating competence and food resource management. Outcomes include child and parent measures of fruit and vegetable preferences and intake, cooking, physical activity, sedentary behaviors and attitudes. School level data assess lunch plate waste and physical activity at recess. In-depth diet and accelerometry assessments are collected with a subsample of parent-child dyads. Data are collected at baseline, immediately post-intervention at 7 months, and at 12 month follow-up. We anticipate recruiting 1320-1584 children and their parents over the length of the project. The Fuel for Fun study design allows for impact assessment of school-, family- and online parent-based intervention components separately and in combination. Study strengths include use of theory- and evidence-based programs, valid child and parent self-report instruments, and objective measures of food, cooking, and physical activity behaviors at the individual, family and school levels. Parent involvement and engagement is examined through multiple strategies. Clinicaltrials.gov registration number NCT02491294 . Registered 7 July, 2015.

Combined inverse-forward artificial neural networks for fast and accurate estimation of the diffusion coefficients of cartilage based on multi-physics models.

PubMed

Arbabi, Vahid; Pouran, Behdad; Weinans, Harrie; Zadpoor, Amir A

2016-09-06

Analytical and numerical methods have been used to extract essential engineering parameters such as elastic modulus, Poisson׳s ratio, permeability and diffusion coefficient from experimental data in various types of biological tissues. The major limitation associated with analytical techniques is that they are often only applicable to problems with simplified assumptions. Numerical multi-physics methods, on the other hand, enable minimizing the simplified assumptions but require substantial computational expertise, which is not always available. In this paper, we propose a novel approach that combines inverse and forward artificial neural networks (ANNs) which enables fast and accurate estimation of the diffusion coefficient of cartilage without any need for computational modeling. In this approach, an inverse ANN is trained using our multi-zone biphasic-solute finite-bath computational model of diffusion in cartilage to estimate the diffusion coefficient of the various zones of cartilage given the concentration-time curves. Robust estimation of the diffusion coefficients, however, requires introducing certain levels of stochastic variations during the training process. Determining the required level of stochastic variation is performed by coupling the inverse ANN with a forward ANN that receives the diffusion coefficient as input and returns the concentration-time curve as output. Combined together, forward-inverse ANNs enable computationally inexperienced users to obtain accurate and fast estimation of the diffusion coefficients of cartilage zones. The diffusion coefficients estimated using the proposed approach are compared with those determined using direct scanning of the parameter space as the optimization approach. It has been shown that both approaches yield comparable results. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improving police response to persons with mental illness: A Multi-level conceptualization of CIT

PubMed Central

Watson, Amy C; Morabito, Melissa Schaefer; Draine, Jeffrey; Ottati, Victor

2009-01-01

The large numbers of people with mental illness in jails and prisons has fueled policy concern in all domains of the justice system. This includes police practice, where initial decisions to involve persons in the justice system or divert them to mental health services are made. One approach to focus police response in these situations is the implementation of Crisis Intervention Teams (CIT). The CIT model is being implemented widely, with over 400 programs currently operating. While the limited evidence on CIT effectiveness is promising, research on CIT is limited in scope and conceptualization-much of it focusing on officer characteristics and training. In this paper we review the literature on CIT and present a conceptual model of police response to persons with mental illness that accounts for officer, organizational, mental health system and community level factors likely to influence implementation and effectiveness of CIT and other approaches. By moving our conceptualizations and research in this area to new levels of specificity, we may contribute more to effectiveness research on these interventions. PMID:18632154

Advancing antimicrobial stewardship: Summary of the 2015 CIDSC Report.

PubMed

Khan, F; Arthur, J; Maidment, L; Blue, D

2016-11-03

Antimicrobial resistance (AMR) is recognized as an important global public health concern that has a cross-cutting impact on human health, animal health, food and agriculture and the environment. The Communicable and Infectious Disease Steering Committee (CIDSC) of the Pan-Canadian Public Health Network (PHN) created a Task Group on Antimicrobial Stewardship to look at this issue from a Canadian perspective. To summarize the key findings of the Task Group Report that identified core components of antimicrobial stewardship programs, best practices, key challenges, gaps and recommendations to advance stewardship across jurisdictions. Search strategies were developed to identify scientific literature, grey literature and relevant websites on antimicrobial stewardship. The information was reviewed and based on this evidence, expert opinion and consensus-building, the Task Group identified core components, best practices, key challenges and gaps and developed recommendations to advance stewardship in Canada. The four components of a promising antimicrobial stewardship initiative were: leadership, interventions, monitoring/evaluation and future research. Best practices include a multi-sectoral/multipronged approach involving a wide range of stakeholders at the national, provincial/territorial, local and health care organizational levels. Key challenges and gaps identified were: the success and sustainability of stewardship undertakings require appropriate and sustained resourcing and expertise; there is limited evidence about how to effectively implement treatment guidance; and there is a challenge in ensuring accessibility, standardization and consistency of use among professionals. ​: Recommendations to the CIDSC about how to advance stewardship across jurisdictions included the following: institute a national infrastructure; develop best practices to implement stewardship programs; develop education and promote awareness; establish consistent evidence-based guidance, resources, tools and training; mandate the incorporation of stewardship education; develop audit and feedback tools; establish benchmarks and performance targets for stewardship; and conduct timely evaluation of stewardship programs. Findings of this report will inform a more systematic approach to addressing antimicrobial stewardship Canada-wide.

Serological patterns of brucellosis, leptospirosis and Q fever in Bos indicus cattle in Cameroon.

PubMed

Scolamacchia, Francesca; Handel, Ian G; Fèvre, Eric M; Morgan, Kenton L; Tanya, Vincent N; Bronsvoort, Barend M de C

2010-01-21

Brucellosis, leptospirosis and Q fever are important infections of livestock causing a range of clinical conditions including abortions and reduced fertility. In addition, they are all important zoonotic infections infecting those who work with livestock and those who consume livestock related products such as milk, producing non-specific symptoms including fever, that are often misdiagnosed and that can lead to severe chronic disease. This study used banked sera from the Adamawa Region of Cameroon to investigate the seroprevalences and distributions of seropositive animals and herds. A classical statistical and a multi-level prevalence modelling approach were compared. The unbiased estimates were 20% of herds were seropositive for Brucella spp. compared to 95% for Leptospira spp. and 68% for Q fever. The within-herd seroprevalences were 16%, 35% and 39% respectively. There was statistical evidence of clustering of seropositive brucellosis and Q fever herds. The modelling approach has the major advantage that estimates of seroprevalence can be adjusted for the sensitivity and specificity of the diagnostic test used and the multi-level structure of the sampling. The study found a low seroprevalence of brucellosis in the Adamawa Region compared to a high proportion of leptospirosis and Q fever seropositive herds. This represents a high risk to the human population as well as potentially having a major impact on animal health and productivity in the region.

System-level multi-target drug discovery from natural products with applications to cardiovascular diseases.

PubMed

Zheng, Chunli; Wang, Jinan; Liu, Jianling; Pei, Mengjie; Huang, Chao; Wang, Yonghua

2014-08-01

The term systems pharmacology describes a field of study that uses computational and experimental approaches to broaden the view of drug actions rooted in molecular interactions and advance the process of drug discovery. The aim of this work is to stick out the role that the systems pharmacology plays across the multi-target drug discovery from natural products for cardiovascular diseases (CVDs). Firstly, based on network pharmacology methods, we reconstructed the drug-target and target-target networks to determine the putative protein target set of multi-target drugs for CVDs treatment. Secondly, we reintegrated a compound dataset of natural products and then obtained a multi-target compounds subset by virtual-screening process. Thirdly, a drug-likeness evaluation was applied to find the ADME-favorable compounds in this subset. Finally, we conducted in vitro experiments to evaluate the reliability of the selected chemicals and targets. We found that four of the five randomly selected natural molecules can effectively act on the target set for CVDs, indicating the reasonability of our systems-based method. This strategy may serve as a new model for multi-target drug discovery of complex diseases.

Symposium on "The challenge of translating nutrition research into public health nutrition". Session 5: Nutrition communication. Obesity and social marketing: works in progress.

PubMed

Cairns, Georgina; Stead, Martine

2009-02-01

Internationally, socio-economic trends reinforce the complex physiological mechanisms that favour positive energy balance, leading to an accumulation of excess body weight and associated metabolic disorders. This so-called 'obesogenic environment' is characterised by increasing accessibility and affordability of energy-dense foods and declining levels of physical activity. In the face of such rapidly-rising obesity rates there is general consensus that strategies to address trends in weight gain must go forwards in the absence of complete evidence of cause or effective prevention strategy. Thus, strategy implementation and evaluation must contribute to, as well as be informed by, the evidence base. Social marketing research and practice has a track record that strongly indicates that it can contribute to both the evolving knowledge base on obesity and overweight control policy and the development of effective intervention strategies. Social marketing draws pragmatically on many disciplines to bring about voluntary behaviour change as well as requisite supporting policy and environmental change. Key objectives include: generating insights into the drivers of current behaviour patterns; important barriers to change; client-oriented approaches to new desirable diet and lifestyle choices. Social marketing recognises that target clients have the power to ensure success or failure of obesity control policies. Social marketing seeks to identify genuine exchange of benefits for target adopters of behaviour change and the advocates of change, and how they may be developed and offered within an appropriate relevant context. Social marketing adopts a cyclical approach of learning, strategic development and evaluation, and therefore is well placed to integrate with the multi-disciplinary demands of obesity prevention strategies.

Behavior-aware cache hierarchy optimization for low-power multi-core embedded systems

NASA Astrophysics Data System (ADS)

Zhao, Huatao; Luo, Xiao; Zhu, Chen; Watanabe, Takahiro; Zhu, Tianbo

2017-07-01

In modern embedded systems, the increasing number of cores requires efficient cache hierarchies to ensure data throughput, but such cache hierarchies are restricted by their tumid size and interference accesses which leads to both performance degradation and wasted energy. In this paper, we firstly propose a behavior-aware cache hierarchy (BACH) which can optimally allocate the multi-level cache resources to many cores and highly improved the efficiency of cache hierarchy, resulting in low energy consumption. The BACH takes full advantage of the explored application behaviors and runtime cache resource demands as the cache allocation bases, so that we can optimally configure the cache hierarchy to meet the runtime demand. The BACH was implemented on the GEM5 simulator. The experimental results show that energy consumption of a three-level cache hierarchy can be saved from 5.29% up to 27.94% compared with other key approaches while the performance of the multi-core system even has a slight improvement counting in hardware overhead.

Implementing Research-Based Substance Abuse Prevention in Communities: Effects of a Coalition-Based Prevention Initiative in Vermont

ERIC Educational Resources Information Center

Flewelling, Robert L.; Austin, David; Hale, Kelly; LaPlante, Marcia; Liebig, Melissa; Piasecki, Linda; Uerz, Lori

2005-01-01

Despite the popularity and perceived potential effectiveness of community-based coalitions in helping to prevent and reduce adolescent substance use, empirical evidence supporting this approach is sparse. Many reasons have been suggested for why coalition-based prevention initiatives, and community-level interventions in general, have not…

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information

PubMed Central

Wang, Xiaohong; Wang, Lizhi

2017-01-01

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system. PMID:28926930

Modeling of BN Lifetime Prediction of a System Based on Integrated Multi-Level Information.

PubMed

Wang, Jingbin; Wang, Xiaohong; Wang, Lizhi

2017-09-15

Predicting system lifetime is important to ensure safe and reliable operation of products, which requires integrated modeling based on multi-level, multi-sensor information. However, lifetime characteristics of equipment in a system are different and failure mechanisms are inter-coupled, which leads to complex logical correlations and the lack of a uniform lifetime measure. Based on a Bayesian network (BN), a lifetime prediction method for systems that combine multi-level sensor information is proposed. The method considers the correlation between accidental failures and degradation failure mechanisms, and achieves system modeling and lifetime prediction under complex logic correlations. This method is applied in the lifetime prediction of a multi-level solar-powered unmanned system, and the predicted results can provide guidance for the improvement of system reliability and for the maintenance and protection of the system.

Multi-Tier Mental Health Program for Refugee Youth

ERIC Educational Resources Information Center

Ellis, B. Heidi; Miller, Alisa B.; Abdi, Saida; Barrett, Colleen; Blood, Emily A.; Betancourt, Theresa S.

2013-01-01

Objective: We sought to establish that refugee youths who receive a multi-tiered approach to services, Project SHIFA, would show high levels of engagement in treatment appropriate to their level of mental health distress, improvements in mental health symptoms, and a decrease in resource hardships. Method: Study participants were 30 Somali and…

Multi-template tensor-based morphometry: Application to analysis of Alzheimer's disease

PubMed Central

Koikkalainen, Juha; Lötjönen, Jyrki; Thurfjell, Lennart; Rueckert, Daniel; Waldemar, Gunhild; Soininen, Hilkka

2012-01-01

In this paper methods for using multiple templates in tensor-based morphometry (TBM) are presented and comparedtothe conventional single-template approach. TBM analysis requires non-rigid registrations which are often subject to registration errors. When using multiple templates and, therefore, multiple registrations, it can be assumed that the registration errors are averaged and eventually compensated. Four different methods are proposed for multi-template TBM. The methods were evaluated using magnetic resonance (MR) images of healthy controls, patients with stable or progressive mild cognitive impairment (MCI), and patients with Alzheimer's disease (AD) from the ADNI database (N=772). The performance of TBM features in classifying images was evaluated both quantitatively and qualitatively. Classification results show that the multi-template methods are statistically significantly better than the single-template method. The overall classification accuracy was 86.0% for the classification of control and AD subjects, and 72.1%for the classification of stable and progressive MCI subjects. The statistical group-level difference maps produced using multi-template TBM were smoother, formed larger continuous regions, and had larger t-values than the maps obtained with single-template TBM. PMID:21419228

A ℓ2, 1 norm regularized multi-kernel learning for false positive reduction in Lung nodule CAD.

PubMed

Cao, Peng; Liu, Xiaoli; Zhang, Jian; Li, Wei; Zhao, Dazhe; Huang, Min; Zaiane, Osmar

2017-03-01

The aim of this paper is to describe a novel algorithm for False Positive Reduction in lung nodule Computer Aided Detection(CAD). In this paper, we describes a new CT lung CAD method which aims to detect solid nodules. Specially, we proposed a multi-kernel classifier with a ℓ 2, 1 norm regularizer for heterogeneous feature fusion and selection from the feature subset level, and designed two efficient strategies to optimize the parameters of kernel weights in non-smooth ℓ 2, 1 regularized multiple kernel learning algorithm. The first optimization algorithm adapts a proximal gradient method for solving the ℓ 2, 1 norm of kernel weights, and use an accelerated method based on FISTA; the second one employs an iterative scheme based on an approximate gradient descent method. The results demonstrates that the FISTA-style accelerated proximal descent method is efficient for the ℓ 2, 1 norm formulation of multiple kernel learning with the theoretical guarantee of the convergence rate. Moreover, the experimental results demonstrate the effectiveness of the proposed methods in terms of Geometric mean (G-mean) and Area under the ROC curve (AUC), and significantly outperforms the competing methods. The proposed approach exhibits some remarkable advantages both in heterogeneous feature subsets fusion and classification phases. Compared with the fusion strategies of feature-level and decision level, the proposed ℓ 2, 1 norm multi-kernel learning algorithm is able to accurately fuse the complementary and heterogeneous feature sets, and automatically prune the irrelevant and redundant feature subsets to form a more discriminative feature set, leading a promising classification performance. Moreover, the proposed algorithm consistently outperforms the comparable classification approaches in the literature. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.