847 resultados para Seamless transition
Resumo:
We performed mutual tapping experiments between two humans to investigate the conditions required for synchronized motion. A transition from an alternative mode to a synchronization mode was discovered under the same conditions when a subject changed from a reactive mode to an anticipation mode in single tapping experiments. Experimental results suggest that the cycle time for each tapping motion is tuned by a proportional control that is based on synchronization errors and cycle time errors. As the tapping frequency increases, the mathematical model based on the feedback control in the sensory-motor closed loop predicts a discrete mode transition as the gain factors of the proportional control decease. The conditions of the synchronization were shown as a consequence of the coupled dynamics based on the subsequent feedback loop in the sensory-motor system.
Resumo:
Careful examination of the probable natural conditions for travel in the North Sea and Irish Sea during the late Mesolithic are here combined with the latest radiocarbon dates to present a new picture of the transition to the Neolithic in the British Isles. The islands of the west were already connected by Mesolithic traffic and did not all go Neolithic at the same time. The introduction of the Neolithic package neither depended on seaborne incomers nor on proximity to the continent. More interesting forces were probably operating on an already busy seaway.
Resumo:
This paper investigates whether and to what extent a wide range of actors in the UK are adapting to climate change, and whether this is evidence of a social transition. We document evidence of over 300 examples of early adopters of adaptation practice to climate change in the UK. These examples span a range of activities from small adjustments (or coping), to building adaptive capacity, to implementing actions and to creating deeper systemic change in public and private organisations in a range of sectors. We find that adaptation in the UK has been dominated by government initiatives and has principally occurred in the form of research into climate change impacts. These government initiatives have stimulated a further set of actions at other scales in public agencies, regulatory agencies and regional government (and the devolved administrations), though with little real evidence of climate change adaptation initiatives trickling down to local government level. The sectors requiring significant investment in large scale infrastructure have invested more heavily than those that do not in identifying potential impacts and adaptations. Thus we find a higher level of adaptation activity by the water supply and flood defence sectors. Sectors that are not dependent on large scale infrastructure appear to be investing far less effort and resources in preparing for climate change. We conclude that the UK government-driven top-down targeted adaptation approach has generated anticipatory action at low cost in some areas. We also conclude that these actions may have created enough niche activities to allow for diffusion of new adaptation practices in response to real or perceived climate change. These results have significant implications for how climate policy can be developed to support autonomous adaptors in the UK and other countries.
Resumo:
In order to address the growing urgency of issues around environmental and resource limits, there is a clear need to develop policies that promote changes in behavior and the ways in which society both views and consumes goods and services. However, there is an argument to suggest that, in order to develop effective policies in this area, we need to move beyond a narrow understanding of ‘how individuals behave’ in order to cultivate a more nuanced approach that encompasses behavioral influences in different societies, contexts and settings. In this opinion article we therefore draw on a range of our own recent comparative research studies in order to provide fresh insights into the continued problem of how to engage people individually and collectively in establishing more sustainable, low-carbon societies.
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What are the microfoundations of dynamic capabilities that sustain competitive advantage in a highly volatile environment, such as a transition economy? We explore the detailed nature of these dynamic capabilities along with their antecedents by tracing the sequence of their development based on a longitudinal case study of an organization subject to an external context of radical transition — the Russian oil company, Yukos. Our rich qualitative data indicate two distinct types of dynamic capabilities that are pivotal for organizational transformation. Adaptation dynamic capabilities relate to routines of resource exploitation and deployment, which are supported by acquisition, internalization and dissemination of extant knowledge, as well as resource reconfiguration, divestment and integration. Innovation dynamic capabilities relate to the creation of completely new capabilities via exploration and path-creation processes, which are supported by search, experimentation and risk taking, as well as project selection, funding and implementation. Second, we find that sequencing the two types of dynamic capabilities, helped the organization both to secure short-term competitive advantage, and to create the basis for long-term competitive advantage. These dynamic capability constructs advance theoretical understanding of what dynamic capabilities are, whilst their sequencing explains how firms create, leverage and enhance them over time.
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A designed peptide amphiphile C16-KKFFVLK self-assembles into nanotubes and helical ribbons in aqueous solution at room temperature. A remarkable unwinding transition, leading to twisted tapes, is observed on heating. Nanotubes and ribbons re-form on cooling.
Resumo:
The CWRF is developed as a climate extension of the Weather Research and Forecasting model (WRF) by incorporating numerous improvements in the representation of physical processes and integration of external (top, surface, lateral) forcings that are crucial to climate scales, including interactions between land, atmosphere, and ocean; convection and microphysics; and cloud, aerosol, and radiation; and system consistency throughout all process modules. This extension inherits all WRF functionalities for numerical weather prediction while enhancing the capability for climate modeling. As such, CWRF can be applied seamlessly to weather forecast and climate prediction. The CWRF is built with a comprehensive ensemble of alternative parameterization schemes for each of the key physical processes, including surface (land, ocean), planetary boundary layer, cumulus (deep, shallow), microphysics, cloud, aerosol, and radiation, and their interactions. This facilitates the use of an optimized physics ensemble approach to improve weather or climate prediction along with a reliable uncertainty estimate. The CWRF also emphasizes the societal service capability to provide impactrelevant information by coupling with detailed models of terrestrial hydrology, coastal ocean, crop growth, air quality, and a recently expanded interactive water quality and ecosystem model. This study provides a general CWRF description and basic skill evaluation based on a continuous integration for the period 1979– 2009 as compared with that of WRF, using a 30-km grid spacing over a domain that includes the contiguous United States plus southern Canada and northern Mexico. In addition to advantages of greater application capability, CWRF improves performance in radiation and terrestrial hydrology over WRF and other regional models. Precipitation simulation, however, remains a challenge for all of the tested models.
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Using molecular dynamics simulations, we find a reversible transition between the dispersion and aggregation states of solute molecules in aqueous solutions confined in nanoscale geometry, which is not observed in macroscopic systems. The nanoscale confinement also leads to a significant increase of the critical aggregation concentration (CAC). A theoretical model based on Gibbs free energy calculation is developed to describe the simulation results. It indicates that the reversible state transition is attributed to the low free energy barrier (of order kBT) in between two energy minima corresponding to the dispersion and aggregation states, and the enhancement of the CAC results from the fact that at lower concentrations the number of solute molecules is not large enough to allow the formation of a stable cluster in the confined systems.
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Grassroots innovations emerge as networks generating innovative solutions for climate change adaptation and mitigation. However, it is unclear if grassroots innovations can be successful in responding to climate change. Little evidence exists on replication, international comparisons are rare, and research tends to overlook discontinued responses in favour of successful ones. We take the Transition Movement as a case study of a rapidly spreading transnational grassroots network, and include both active and non-active local transition initiatives. We investigate the replication of grassroots innovations in different contexts with the aim to uncover general patterns of success and failure, and identify questions for future research. An online survey was carried out in 23 countries (N=276). The data analysis entailed testing the effect of internal and contextual factors of success as drawn from the existing literature, and the identification of clusters of transition initiatives with similar internal and contextual factor configurations. Most transition initiatives consider themselves successful. Success is defined along the lines of social connectivity and empowerment, and external environmental impact. We find that less successful transition initiatives might underestimate the importance of contextual factors and material resources in influencing success. We also find that their diffusion is linked to the combination of local-global learning processes, and that there is an incubation period during which a transition initiative is consolidated. Transition initiatives seem capable of generalising organisational principles derived from unique local experiences that seem to be effective in other local contexts. However, the geographical locations matter with regard to where transition initiatives take root and the extent of their success, and ‘place attachment’ may have a role in the diffusion of successful initatives. We suggest that longitudinal comparative studies can advance our understanding in this regard, as well as inform the changing nature of the definition of success at different stages of grassroots innovation development, and the dynamic nature of local and global linkages.
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This paper provides a high-level overview of E-UTRAN interworking and interoperability with existing Third Generation Partnership Project (3GPP) and non-3GPP wireless networks. E-UTRAN access networks (LTE and LTE-A) are currently the latest technologies for 3GPP evolution specified in Release 8, 9 and beyond. These technologies promise higher throughputs and lower latency while also reducing the cost of delivering the services to fit with subscriber demands. 3GPP offers a direct transition path from the current 3GPP UTRAN/GERAN networks to LTE including seamless handover. E-UTRAN and other wireless networks interworking is an option that allows operators to maximize the life of their existing network components before a complete transition to truly 4G networks. Network convergence, backward compatibility and interpretability are regarded as the next major challenge in the evolution and the integration of mobile wireless communications. In this paper, interworking and interoperability between the E-UTRAN Evolved Packet Core (EPC) architecture and 3GPP, 3GPP2 and IEEE based networks are clearly explained. How the EPC is designed to deliver multimedia and facilitate interworking is also explained. Moreover, the seamless handover needed to perform this interworking efficiently is described briefly. This study showed that interoperability and interworking between existing networks and E-UTRAN are highly recommended as an interim solution before the transition to full 4G. Furthermore, wireless operators have to consider a clear interoperability and interworking plan for their existing networks before making a decision to migrate completely to LTE. Interworking provides not only communication between different wireless networks; in many scenarios it contributes to add technical enhancements to one or both environments.
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Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage. If the primary endpoint is observable only after some period of follow-up, at the interim analysis data may be available on some early outcome on a larger number of patients than those for whom the primary endpoint is available. These early endpoint data can thus be used for treatment selection. For two previously proposed approaches, the power has been shown to be greater for one or other method depending on the true treatment effects and correlations. We propose a new approach that builds on the previously proposed approaches and uses data available at the interim analysis to estimate these parameters and then, on the basis of these estimates, chooses the treatment selection method with the highest probability of correctly selecting the most effective treatment. This method is shown to perform well compared with the two previously described methods for a wide range of true parameter values. In most cases, the performance of the new method is either similar to or, in some cases, better than either of the two previously proposed methods.
Resumo:
Monte Carlo algorithms often aim to draw from a distribution π by simulating a Markov chain with transition kernel P such that π is invariant under P. However, there are many situations for which it is impractical or impossible to draw from the transition kernel P. For instance, this is the case with massive datasets, where is it prohibitively expensive to calculate the likelihood and is also the case for intractable likelihood models arising from, for example, Gibbs random fields, such as those found in spatial statistics and network analysis. A natural approach in these cases is to replace P by an approximation Pˆ. Using theory from the stability of Markov chains we explore a variety of situations where it is possible to quantify how ’close’ the chain given by the transition kernel Pˆ is to the chain given by P . We apply these results to several examples from spatial statistics and network analysis.