52 resultados para Performance evolution due time

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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One of the current challenges in evolutionary ecology is understanding the long-term persistence of contemporary-evolving predator–prey interactions across space and time. To address this, we developed an extension of a multi-locus, multi-trait eco-evolutionary individual-based model that incorporates several interacting species in explicit landscapes. We simulated eco-evolutionary dynamics of multiple species food webs with different degrees of connectance across soil-moisture islands. A broad set of parameter combinations led to the local extinction of species, but some species persisted, and this was associated with (1) high connectance and omnivory and (2) ongoing evolution, due to multi-trait genetic variability of the embedded species. Furthermore, persistence was highest at intermediate island distances, likely because of a balance between predation-induced extinction (strongest at short island distances) and the coupling of island diversity by top predators, which by travelling among islands exert global top-down control of biodiversity. In the simulations with high genetic variation, we also found widespread trait evolutionary changes indicative of eco-evolutionary dynamics. We discuss how the ever-increasing computing power and high-resolution data availability will soon allow researchers to start bridging the in vivo–in silico gap.

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Background Cardiopulmonary resuscitation (CPR) causes significant stress, which may cause deficiencies in attention and increase distractibility. This may lead to misjudgements of priorities and delays in CPR performance, which may further increase mental stress (vicious cycle). This study assessed the impact of a task-focusing strategy on perceived stress levels and performance during a simulated CPR scenario. Methods This prospective, randomized-controlled trial was conducted at the simulator-center of the University Hospital Basel, Switzerland. A total of 124 volunteer medical students were randomized to receive a 10 minute instruction to cope with stress by loudly posing two taskfocusing questions (“what is the patient’s condition?”, “what immediate action is needed?”) when feeling overwhelmed by stress (intervention group) or a control group. The primary outcome was the perceived levels of stress and feeling overwhelmed (stress/overload); secondary outcomes were hands-on time, time to start CPR and number of leadership statements. Results Participants in the intervention group reported significantly less stress/overload levels compared to the control group (mean difference: -0.6 (95%CI −1.3, -0.1), p=0.04). Higher stress/overload was associated with less hands-on time. Leadership statements did not differ between groups, but the number of leadership statements did relate to performance. Hands-on time was longer in the intervention- group, but the difference was not statistically different (difference 5.5 (95%CI −3.1, 14.2), p=0.2); there were no differences in time to start CPR (difference −1.4 (95%CI −8.4, 5.7), p=0.71). Conclusions A brief stress-coping strategy moderately decreased perceived stress without significantly affecting performance in a simulated CPR. Further studies should investigate more intense interventions for reducing stress.

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“Cultural diversity” has become one of the latest buzzwords on the international policymaking scene. It is employed in various contexts – sometimes as a term close to “biological diversity”, at other times as correlated to the “exception culturelle” and most often, as a generic concept that is mobilised to counter the perceived negative effects of economic globalisation. While no one has yet provided a precise definition of what cultural diversity is, what we can observe is the emergence of the notion of cultural diversity as incorporating a distinct set of policy objectives and choices at the global level. These decisions are not confined, as one might have expected, to cultural policymaking, but rather spill over to multiple governance domains because of the complex linkages inherent to the simultaneous pursuit of economic and other societal goals that cultural diversity encompasses and has effects on. Accounting for these intricate interdependencies, the present article clarifies the origins of the concept of cultural diversity as understood in global law and traces its evolution over time. Observing the dynamics of the concept and the surrounding political and legal developments, the article explores its justification and overall impact on the global legal regime, as well as its discrete effects on different domains of policymaking, such as media, intellectual property and culture. While the analysis is legal in essence, the article is meant to speak also to a broader transdisciplinary public. The article is part of the speacial issue on ethnic diversity and cultural pluralism, which is available under the creative commons licence: http://www.mdpi.com/journal/diversity/special_issues/ethnic-diversity/.

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The population of space debris increased drastically during the last years. These objects have become a great threat for active satellites. Because the relative velocities between space debris and satellites are high, space debris objects may destroy active satellites through collisions. Furthermore, collisions involving massive objects produce large number of fragments leading to significant growth of the space debris population. The long term evolution of the debris population is essentially driven by so-called catastrophic collisions. An effective remediation measure in order to stabilize the population in Low Earth Orbit (LEO) is therefore the removal of large, massive space debris. To remove these objects, not only precise orbits, but also more detailed information about their attitude states will be required. One important property of an object targeted for removal is its spin period, spin axis orientation and their change over time. Rotating objects will produce periodic brightness variations with frequencies which are related to the spin periods. Such a brightness variation over time is called a light curve. Collecting, but also processing light curves is challenging due to several reasons. Light curves may be undersampled, low frequency components due to phase angle and atmospheric extinction changes may be present, and beat frequencies may occur when the rotation period is close to a multiple of the sampling period. Depending on the method which is used to extract the frequencies, also method-specific properties have to be taken into account. The astronomical Institute of the University of Bern (AIUB) light curve database will be introduced, which contains more than 1,300 light curves acquired over more than seven years. We will discuss properties and reliability of different time series analysis methods tested and currently used by AIUB for the light curve processing. Extracted frequencies and reconstructed phases for some interesting targets, e.g. GLONASS satellites, for which also SLR data were available for the period confirmation, will be presented. Finally we will present the reconstructed phase and its evolution over time of a High-Area-to-Mass-Ratio (HAMR) object, which AIUB observed for several years.

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The analysis of short segments of noise-contaminated, multivariate real world data constitutes a challenge. In this paper we compare several techniques of analysis, which are supposed to correctly extract the amount of genuine cross-correlations from a multivariate data set. In order to test for the quality of their performance we derive time series from a linear test model, which allows the analytical derivation of genuine correlations. We compare the numerical estimates of the four measures with the analytical results for different correlation pattern. In the bivariate case all but one measure performs similarly well. However, in the multivariate case measures based on the eigenvalues of the equal-time cross-correlation matrix do not extract exclusively information about the amount of genuine correlations, but they rather reflect the spatial organization of the correlation pattern. This may lead to failures when interpreting the numerical results as illustrated by an application to three electroencephalographic recordings of three patients suffering from pharmacoresistent epilepsy.

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The areca alkaloids comprise arecoline, arecaidine, guvacoline, and guvacine. Approximately 600 million users of areca nut products, for example, betel quid chewers, are exposed to these alkaloids, principally arecoline and arecaidine. Metabolism of arecoline (20 mg/kg p.o. and i.p.) and arecaidine (20 mg/kg p.o. and i.p.) was investigated in the mouse using a metabolomic approach employing ultra-performance liquid chromatography-time-of-flight mass spectrometric analysis of urines. Eleven metabolites of arecoline were identified, including arecaidine, arecoline N-oxide, arecaidine N-oxide, N-methylnipecotic acid, N-methylnipecotylglycine, arecaidinylglycine, arecaidinylglycerol, arecaidine mercapturic acid, arecoline mercapturic acid, and arecoline N-oxide mercapturic acid, together with nine unidentified metabolites. Arecaidine shared six of these metabolites with arecoline. Unchanged arecoline comprised 0.3-0.4%, arecaidine 7.1-13.1%, arecoline N-oxide 7.4-19.0%, and N-methylnipecotic acid 13.5-30.3% of the dose excreted in 0-12 h urine after arecoline administration. Unchanged arecaidine comprised 15.1-23.0%, and N-methylnipecotic acid 14.8%-37.7% of the dose excreted in 0-12 h urine after arecaidine administration. The major metabolite of both arecoline and arecaidine, N-methylnipecotic acid, is a novel metabolite arising from carbon-carbon double-bond reduction. Another unusual metabolite found was the monoacylglyceride of arecaidine. What role, if any, that is played by these uncommon metabolites in the toxicology of arecoline and arecaidine is not known. However, the enhanced understanding of the metabolic transformation of arecoline and arecaidine should contribute to further research into the clinical toxicology of the areca alkaloids.

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Uncontrollable intracranial pressure elevation in hyperacute liver failure often proves fatal if no suitable liver for transplantation is found in due time. Both ABO-compatible and auxiliary partial orthotopic liver transplantation have been described to control such scenario. However, each method is associated with downsides in terms of immunobiology, organ availability and effects on the overall waiting list.

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Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.

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In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

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In this work we devise two novel algorithms for blind deconvolution based on a family of logarithmic image priors. In contrast to recent approaches, we consider a minimalistic formulation of the blind deconvolution problem where there are only two energy terms: a least-squares term for the data fidelity and an image prior based on a lower-bounded logarithm of the norm of the image gradients. We show that this energy formulation is sufficient to achieve the state of the art in blind deconvolution with a good margin over previous methods. Much of the performance is due to the chosen prior. On the one hand, this prior is very effective in favoring sparsity of the image gradients. On the other hand, this prior is non convex. Therefore, solutions that can deal effectively with local minima of the energy become necessary. We devise two iterative minimization algorithms that at each iteration solve convex problems: one obtained via the primal-dual approach and one via majorization-minimization. While the former is computationally efficient, the latter achieves state-of-the-art performance on a public dataset.

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In a prospective memory task responding to a prospective memory target involves switching between ongoing and prospective memory task which can result in a slowing of subsequent ongoing task performance (i.e., an after-effect). Moreover, a slowing can also occur when prospective memory targets occur after the prospective memory task is deactivated (i.e., another after-effect). In this study, we investigated both after-effects within the same study. Moreover, we also tested whether the latter after-effects even occur on subsequent ongoing task trials. The results show, in fact, after-effects of all kinds. Thus, (1) correctly responding to prospective memory targets results in after-effects, a so far neglected cost on ongoing task performance, (2) responding to deactivated prospective memory targets also slows down performance, probably due to the involuntary retrieval of the intention, and (3) this slowing is present even on subsequent ongoing task trials, suggesting that even deactivated intentions are sufficient to induce a conflict that requires subsequent adaptation. Overall, these results indicate that performance slowing in a prospective memory experiment includes various kinds of sources, not only monitoring cost, and these sources may be understood best in terms of conflict adaptation.

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Context. OSIRIS, the scientific imaging system onboard the ESA Rosetta spacecraft, has been imaging the nucleus of comet 67P/Churyumov-Gerasimenko and its dust and gas environment since March 2014. The images serve different scientific goals, from morphology and composition studies of the nucleus surface, to the motion and trajectories of dust grains, the general structure of the dust coma, the morphology and intensity of jets, gas distribution, mass loss, and dust and gas production rates. Aims. We present the calibration of the raw images taken by OSIRIS and address the accuracy that we can expect in our scientific results based on the accuracy of the calibration steps that we have performed. Methods. We describe the pipeline that has been developed to automatically calibrate the OSIRIS images. Through a series of steps, radiometrically calibrated and distortion corrected images are produced and can be used for scientific studies. Calibration campaigns were run on the ground before launch and throughout the years in flight to determine the parameters that are used to calibrate the images and to verify their evolution with time. We describe how these parameters were determined and we address their accuracy. Results. We provide a guideline to the level of trust that can be put into the various studies performed with OSIRIS images, based on the accuracy of the image calibration.

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Information-centric networking (ICN) is a new communication paradigm that has been proposed to cope with drawbacks of host-based communication protocols, namely scalability and security. In this thesis, we base our work on Named Data Networking (NDN), which is a popular ICN architecture, and investigate NDN in the context of wireless and mobile ad hoc networks. In a first part, we focus on NDN efficiency (and potential improvements) in wireless environments by investigating NDN in wireless one-hop communication, i.e., without any routing protocols. A basic requirement to initiate informationcentric communication is the knowledge of existing and available content names. Therefore, we develop three opportunistic content discovery algorithms and evaluate them in diverse scenarios for different node densities and content distributions. After content names are known, requesters can retrieve content opportunistically from any neighbor node that provides the content. However, in case of short contact times to content sources, content retrieval may be disrupted. Therefore, we develop a requester application that keeps meta information of disrupted content retrievals and enables resume operations when a new content source has been found. Besides message efficiency, we also evaluate power consumption of information-centric broadcast and unicast communication. Based on our findings, we develop two mechanisms to increase efficiency of information-centric wireless one-hop communication. The first approach called Dynamic Unicast (DU) avoids broadcast communication whenever possible since broadcast transmissions result in more duplicate Data transmissions, lower data rates and higher energy consumption on mobile nodes, which are not interested in overheard Data, compared to unicast communication. Hence, DU uses broadcast communication only until a content source has been found and then retrieves content directly via unicast from the same source. The second approach called RC-NDN targets efficiency of wireless broadcast communication by reducing the number of duplicate Data transmissions. In particular, RC-NDN is a Data encoding scheme for content sources that increases diversity in wireless broadcast transmissions such that multiple concurrent requesters can profit from each others’ (overheard) message transmissions. If requesters and content sources are not in one-hop distance to each other, requests need to be forwarded via multi-hop routing. Therefore, in a second part of this thesis, we investigate information-centric wireless multi-hop communication. First, we consider multi-hop broadcast communication in the context of rather static community networks. We introduce the concept of preferred forwarders, which relay Interest messages slightly faster than non-preferred forwarders to reduce redundant duplicate message transmissions. While this approach works well in static networks, the performance may degrade in mobile networks if preferred forwarders may regularly move away. Thus, to enable routing in mobile ad hoc networks, we extend DU for multi-hop communication. Compared to one-hop communication, multi-hop DU requires efficient path update mechanisms (since multi-hop paths may expire quickly) and new forwarding strategies to maintain NDN benefits (request aggregation and caching) such that only a few messages need to be transmitted over the entire end-to-end path even in case of multiple concurrent requesters. To perform quick retransmission in case of collisions or other transmission errors, we implement and evaluate retransmission timers from related work and compare them to CCNTimer, which is a new algorithm that enables shorter content retrieval times in information-centric wireless multi-hop communication. Yet, in case of intermittent connectivity between requesters and content sources, multi-hop routing protocols may not work because they require continuous end-to-end paths. Therefore, we present agent-based content retrieval (ACR) for delay-tolerant networks. In ACR, requester nodes can delegate content retrieval to mobile agent nodes, which move closer to content sources, can retrieve content and return it to requesters. Thus, ACR exploits the mobility of agent nodes to retrieve content from remote locations. To enable delay-tolerant communication via agents, retrieved content needs to be stored persistently such that requesters can verify its authenticity via original publisher signatures. To achieve this, we develop a persistent caching concept that maintains received popular content in repositories and deletes unpopular content if free space is required. Since our persistent caching concept can complement regular short-term caching in the content store, it can also be used for network caching to store popular delay-tolerant content at edge routers (to reduce network traffic and improve network performance) while real-time traffic can still be maintained and served from the content store.

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Global scale impacts modify the physical or thermal state of a substantial fraction of a target asteroid. Specific effects include accretion, family formation, reshaping, mixing and layering, shock and frictional heating, fragmentation, material compaction, dilatation, stripping of mantle and crust, and seismic degradation. Deciphering the complicated record of global scale impacts, in asteroids and meteorites, will lead us to understand the original planet-forming process and its resultant populations, and their evolution in time as collisions became faster and fewer. We provide a brief overview of these ideas, and an introduction to models.

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Software must be constantly adapted due to evolving domain knowledge and unanticipated requirements changes. To adapt a system at run-time we need to reflect on its structure and its behavior. Object-oriented languages introduced reflection to deal with this issue, however, no reflective approach up to now has tried to provide a unified solution to both structural and behavioral reflection. This paper describes Albedo, a unified approach to structural and behavioral reflection. Albedo is a model of fined-grained unanticipated dynamic structural and behavioral adaptation. Instead of providing reflective capabilities as an external mechanism we integrate them deeply in the environment. We show how explicit meta-objects allow us to provide a range of reflective features and thereby evolve both application models and environments at run-time.