Hvad er gode forudsætninger for at undervise i mindfulness?

Mindfulness-based clinical interventions have become popular and broadly implemented within several university clinics and hospitals. The efficacy of mindfulness-based stress reduction (MBSR) and mindfulness-based cognitive therapy (MBCT) is supported by evidence from numerous clinical trials and meta-analyses. However, with the increase inpopularity and greater demand, the central risk is that the quality and integrity of MBSR and MBCT could be lost, in particular if these evidence-based interventions are not delivered as intended. In this article, an overall model of quality and integrity is presented with an emphasis on professional training, standards of good practice, teaching competencies,ethics, and insights of contemplative traditions. It is suggested that professional training requires a longer time frame in order to develop, integrate, implement, and evaluate the basic competencies needed to effectively teach MBSR and MBCT. It is also argued that teachers of MBSR and MBCT need to be engage in the personal work ofintegrating mindfulness into their own lives

What can Recycling in Thermal Reactors Accomplish?

Thermal recycle provides several potential benefits when used as stop-gap, mixed, or backup recycling to recycling in fast reactors. These three roles involve a mixture of thermal and fast recycling; fast reactors are required to some degree at some time. Stop-gap uses thermal reactors only until fast reactors are adequately deployed and until any thermal-recycle-only facilities have met their economic lifetime. Mixed uses thermal and fast reactors symbiotically for an extended period of time. Backup uses thermal reactors only if problems later develop in the fast reactor portion of a recycling system. Thermal recycle can also provide benefits when used as pure thermal recycling, with no intention to use fast reactors. However, long term, the pure thermal recycling approach is inadequate to meet several objectives

Exponential or power distance-decay for commuting? An alternative specification

In this paper we investigate the form of the distance-decay function for commuting, on the basis of an analysis of home-to-work relationships between municipalities in Denmark. The equation for the number of commuters is taken from Alonso’s Theory of Movements, in which the Spatial Interaction Models of Wilson’s Family are nested. Our estimation method separates the decay function F from the balancing factors, and includes a weighting procedure that takes specification error and heteroscedasticity into account. It appears that neither an exponential nor a power distance-decay function fits the data well. The specification of log F as a (downwards) logistic function of log cost results in a better fit. We find that the cost elasticity reaches a value of –4 for distances around 24 km, while it is close to for both very short and very long distances. Finally, we demonstrate that the choice of functional form for distance-decay can make an important difference for predictions concerning the effect of infrastructure improvements on commuting flows.

A systematic review of mechanisms of change in mindfulness-based cognitive therapy in the treatment of recurrent major depressive disorder

AbstractBackgroundThe investigation of treatment mechanisms in randomized controlled trials has considerable clinical and theoretical relevance. Despite the empirical support for the effect of mindfulness-based cognitive therapy (MBCT) in the treatment of recurrent major depressive disorder (MDD), the specific mechanisms by which MBCT leads to therapeutic change remain unclear.ObjectiveBy means of a systematic review we evaluate how the field is progressing in its empirical investigation of mechanisms of change in MBCT for recurrent MDD.MethodTo identify relevant studies, a systematic search was conducted. Studies were coded and ranked for quality.ResultsThe search produced 476 articles, of which 23 were included. In line with the theoretical premise, 12 studies found that alterations in mindfulness, rumination, worry, compassion, or meta-awareness were associated with, predicted or mediated MBCT's effect on treatment outcome. In addition, preliminary studies indicated that alterations in attention, memory specificity, self-discrepancy, emotional reactivity and momentary positive and negative affect might play a role in how MBCT exerts its clinical effects.ConclusionThe results suggest that MBCT could work through some of the MBCT model's theoretically predicted mechanisms. However, there is a need for more rigorous designs that can assess greater levels of causal specificity

Modeling and Simulation of Long-Term Performance of Near-Surface Barriers

Society has and will continue to generate hazardous wastes whose risks must be managed. For exceptionally toxic, long-lived, and feared waste, the solution is deep burial, e.g., deep geological disposal at Yucca Mtn. For some waste, recycle or destruction/treatment is possible. The alternative for other wastes is storage at or near the ground level (in someone’s back yard); most of these storage sites include a surface barrier (cap) to prevent migration of the waste due to infiltration of surface water. The design lifespan for such barriers ranges from 30 to 1000 years, depending on hazard and regulations. In light of historical performance, society needs a better basis for predicting barrier performance over long time periods and tools for optimizing maintenance of barriers while in service. We believe that, as in other industries, better understanding of the dynamics of barrier system degradation will enable improved barriers (cheaper, longer-lived, simpler, easier to maintain) and improved maintenance. We are focusing our research on earthen caps, especially those with evapo-transpiration and capillary breaks. Typical cap assessments treat the barrier’s structure as static prior to some defined lifetime. Environmental boundary conditions such as precipitation and temperature are treated as time dependent. However, other key elements of the barrier system are regarded as constant, including engineered inputs (e.g., fire management strategy, irrigation, vegetation control), surface ecology (critical to assessment of plant transpiration), capillary break interface, material properties, surface erosion rate, etc. Further, to be conservative, only harmful processes are typically considered. A more holistic examination of both harmful and beneficial processes will provide more realistic pre-service prediction and in-service assessment of performance as well as provide designers a tool to encourage beneficial processes while discouraging harmful processes. Thus, the INEEL started a new project on long-term barrier integrity in April 2002 that aims to catalyze a Barrier Improvement Cycle (iterative learning and application) and thus enable Remediation System Performance Management (doing the right maintenance neither too early nor too late, prior to system-level failure). This paper describes our computer simulation approach for better understanding the relationships and dynamics between the various components and management decisions in a cap. The simulation is designed to clarify the complex relationships between the various components within the cap system and the various management practices that affect the barrier performance. We have also conceptualized a time-dependent 3-D simulation with rigorous solution to unsaturated flow physics with complex surface boundary conditions

Modeling the Nuclear Fuel Cycle

The Advanced Fuel Cycle Initiative is developing a system dynamics model as part of their broad systems analysis of future nuclear energy in the United States. The model will be used to analyze and compare various proposed technology deployment scenarios. The model will also give a better understanding of the linkages between the various components of the nuclear fuel cycle that includes uranium resources, reactor number and mix, nuclear fuel type and waste management. Each of these components is tightly connected to the nuclear fuel cycle but usually analyzed in isolation of the other parts. This model will attempt to bridge these components into a single model for analysis. This work is part of a multi-national laboratory effort between Argonne National Laboratory, Idaho National Laboratory and United States Department of Energy. This paper summarizes the basics of the system dynamics model and looks at some results from the model

Real-Time Feedback for Colonoscopy in a Multicenter Clinical Trial

We report the technical challenges, solutions, and lessons learned from deploying real-time feedback systems in three hospitals as part of a multi-center controlled clinical trial to improve quality of colonoscopy. Previous clinical trials were conducted in one center. The technical challenges for our multicenter clinical trial include 1) reducing additional work by the endoscopists to utilize real-time feedback, 2) handling different colonoscopy practices at different hospitals, and 3) training an effective CNN-based classification model with a large variety of patterns of data in day-to-day colonoscopy practice. We report performance of our real-time systems over a period of 20 weeks at each hospital. We conclude that CNN-based classification can achieve very good performance in real-world deployment when trained with high quality data

Lessons Learned From Dynamic Simulations of Advanced Fuel Cycles

Years of performing dynamic simulations of advanced nuclear fuel cycle options provide insights into how they could work and how one might transition from the current once-through fuel cycle. This paper summarizes those insights from the context of the 2005 objectives and goals of the Advanced Fuel Cycle Initiative (AFCI). Our intent is not to compare options, assess options versus those objectives and goals, nor recommend changes to those objectives and goals. Rather, we organize what we have learned from dynamic simulations in the context of the AFCI objectives for waste management, proliferation resistance, uranium utilization, and economics. Thus, we do not merely describe “lessons learned” from dynamic simulations but attempt to answer the “so what” question by using this context. The analyses have been performed using the Verifiable Fuel Cycle Simulation of Nuclear Fuel Cycle Dynamics (VISION). We observe that the 2005 objectives and goals do not address many of the inherently dynamic discriminators among advanced fuel cycle options and transitions thereof

User Guide for VISION 3.4.7 (Verifiable Fuel Cycle Simulation) Model

The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters and options; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an R&D work in progress and may contain errors and omissions. It is based upon numerous assumptions. This model is intended to assist in evaluating 'what if' scenarios and in comparing fuel, reactor, and fuel processing alternatives at a systems level. The model is not intended as a tool for process flow and design modeling of specific facilities nor for tracking individual units of fuel or other material through the system. The model is intended to examine the interactions among the components of a fuel system as a function of time varying system parameters; this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., 'reactor types' not individual reactors and 'separation types' not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, and depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation or disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. You must use Powersim Studio 8 or better. We have tested VISION with the Studio 8 Expert, Executive, and Education versions. The Expert and Education versions work with the number of reactor types of 3 or less. For more reactor types, the Executive version is currently required. The input files are Excel2003 format (xls). The output files are macro-enabled Excel2007 format (xlsm). VISION 3.4 was designed with more flexibility than previous versions, which were structured for only three reactor types - LWRs that can use only uranium oxide (UOX) fuel, LWRs that can use multiple fuel types (LWR MF), and fast reactors. One could not have, for example, two types of fast reactors concurrently. The new version allows 10 reactor types and any user-defined uranium-plutonium fuel is allowed. (Thorium-based fuels can be input but several features of the model would not work.) The user identifies (by year) the primary fuel to be used for each reactor type. The user can identify for each primary fuel a contingent fuel to use if the primary fuel is not available, e.g., a reactor designated as using mixed oxide fuel (MOX) would have UOX as the contingent fuel. Another example is that a fast reactor using recycled transuranic (TRU) material can be designated as either having or not having appropriately enriched uranium oxide as a contingent fuel. Because of the need to study evolution in recycling and separation strategies, the user can now select the recycling strategy and separation technology, by year