752 resultados para distributed-feedback (DFB)


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Snow cover is an important control in mountain environments and a shift of the snow-free period triggered by climate warming can strongly impact ecosystem dynamics. Changing snow patterns can have severe effects on alpine plant distribution and diversity. It thus becomes urgent to provide spatially explicit assessments of snow cover changes that can be incorporated into correlative or empirical species distribution models (SDMs). Here, we provide for the first time a with a lower overestimation comparison of two physically based snow distribution models (PREVAH and SnowModel) to produce snow cover maps (SCMs) at a fine spatial resolution in a mountain landscape in Austria. SCMs have been evaluated with SPOT-HRVIR images and predictions of snow water equivalent from the two models with ground measurements. Finally, SCMs of the two models have been compared under a climate warming scenario for the end of the century. The predictive performances of PREVAH and SnowModel were similar when validated with the SPOT images. However, the tendency to overestimate snow cover was slightly lower with SnowModel during the accumulation period, whereas it was lower with PREVAH during the melting period. The rate of true positives during the melting period was two times higher on average with SnowModel with a lower overestimation of snow water equivalent. Our results allow for recommending the use of SnowModel in SDMs because it better captures persisting snow patches at the end of the snow season, which is important when modelling the response of species to long-lasting snow cover and evaluating whether they might survive under climate change.

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Today’s commercial web sites are under heavy user load and they are expected to be operational and available at all times. Distributed system architectures have been developed to provide a scalable and failure tolerant high availability platform for these web based services. The focus on this thesis was to specify and implement resilient and scalable locally distributed high availability system architecture for a web based service. Theory part concentrates on the fundamental characteristics of distributed systems and presents common scalable high availability server architectures that are used in web based services. In the practical part of the thesis the implemented new system architecture is explained. Practical part also includes two different test cases that were done to test the system's performance capacity.

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This paper analyzes an innovative experience of formative assessment aimed at improving the teaching of Statistics, which could be easily extrapolated to other studies. We detail the implementation of the double correction, consisting of correcting students' work twice. With the first correction, carried out by classmates according to a rubric developed by the academic, possible errors or deficiencies are discovered, and students are provided with a feedback that allows them to correct and improve their work before being graded by the teacher; whereas in the second correction of the work, once upgraded, the professor evaluates and grades the work. As a result, there is a significant improvement in the quality of students" works, and an active learning from their own mistakes. Both contents and competencies are reinforced by the experience.

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Calcium signals trigger the translocation of the Prz1 transcription factor from the cytoplasm to the nucleus. The process is regulated by the calciumactivated phosphatase calcineurin, which activates Prz1 thereby maintaining active transcription during calcium signalling. When calcium signalling ceases, Prz1 is inactivated by phosphorylation and exported to the cytoplasm. In budding yeast and mammalian cells, different kinases have been reported to counter calcineurin activity and regulate nuclear export. Here, we show that the Ca2+/calmodulin-dependent kinase Cmk1 is first phosphorylated and activated by the newly identified kinase CaMKK2 homologue, Ckk2, in response to Ca2+. Then, active Cmk1 binds, phosphorylates and inactivates Prz1 transcription activity whilst at the same time cmk1 expression is enhanced by Prz1 in response to Ca2+. Furthermore, Cdc25 phosphatase is also phosphorylated by Cmk1, inducing cell cycle arrest in response to an increase in Ca2+. Moreover, cmk1 deletion shows a high tolerance to chronic exposure to Ca2+, due to the lack of cell cycle inhibition and elevated Prz1 activity. This work reveals that Cmk1 kinase activated by the newly identified Ckk2 counteracts calcineurin function by negatively regulating Prz1 activity which in turn is involved in activating cmk1 gene transcription. These results are the first insights into Cmk1 and Ckk2 function in Schizosaccharomyces pombe.

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The activated sludge process - the main biological technology usually applied towastewater treatment plants (WWTP) - directly depends on live beings (microorganisms), and therefore on unforeseen changes produced by them. It could be possible to get a good plant operation if the supervisory control system is able to react to the changes and deviations in the system and can take thenecessary actions to restore the system’s performance. These decisions are oftenbased both on physical, chemical, microbiological principles (suitable to bemodelled by conventional control algorithms) and on some knowledge (suitable to be modelled by knowledge-based systems). But one of the key problems in knowledge-based control systems design is the development of an architecture able to manage efficiently the different elements of the process (integrated architecture), to learn from previous cases (spec@c experimental knowledge) and to acquire the domain knowledge (general expert knowledge). These problems increase when the process belongs to an ill-structured domain and is composed of several complex operational units. Therefore, an integrated and distributed AIarchitecture seems to be a good choice. This paper proposes an integrated and distributed supervisory multi-level architecture for the supervision of WWTP, that overcomes some of the main troubles of classical control techniques and those of knowledge-based systems applied to real world systems

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Previous genetic studies have demonstrated that natal homing shapes the stock structure of marine turtle nesting populations. However, widespread sharing of common haplotypes based on short segments of the mitochondrial control region often limits resolution of the demographic connectivity of populations. Recent studies employing longer control region sequences to resolve haplotype sharing have focused on regional assessments of genetic structure and phylogeography. Here we synthesize available control region sequences for loggerhead turtles from the Mediterranean Sea, Atlantic, and western Indian Ocean basins. These data represent six of the nine globally significant regional management units (RMUs) for the species and include novel sequence data from Brazil, Cape Verde, South Africa and Oman. Genetic tests of differentiation among 42 rookeries represented by short sequences (380 bp haplotypes from 3,486 samples) and 40 rookeries represented by long sequences (~800 bp haplotypes from 3,434 samples) supported the distinction of the six RMUs analyzed as well as recognition of at least 18 demographically independent management units (MUs) with respect to female natal homing. A total of 59 haplotypes were resolved. These haplotypes belonged to two highly divergent global lineages, with haplogroup I represented primarily by CC-A1, CC-A4, and CC-A11 variants and haplogroup II represented by CC-A2 and derived variants. Geographic distribution patterns of haplogroup II haplotypes and the nested position of CC-A11.6 from Oman among the Atlantic haplotypes invoke recent colonization of the Indian Ocean from the Atlantic for both global lineages. The haplotypes we confirmed for western Indian Ocean RMUs allow reinterpretation of previous mixed stock analysis and further suggest that contemporary migratory connectivity between the Indian and Atlantic Oceans occurs on a broader scale than previously hypothesized. This study represents a valuable model for conducting comprehensive international cooperative data management and research in marine ecology.

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Simulation has traditionally been used for analyzing the behavior of complex real world problems. Even though only some features of the problems are considered, simulation time tends to become quite high even for common simulation problems. Parallel and distributed simulation is a viable technique for accelerating the simulations. The success of parallel simulation depends heavily on the combination of the simulation application, algorithm and message population in the simulation is sufficient, no additional delay is caused by this environment. In this thesis a conservative, parallel simulation algorithm is applied to the simulation of a cellular network application in a distributed workstation environment. This thesis presents a distributed simulation environment, Diworse, which is based on the use of networked workstations. The distributed environment is considered especially hard for conservative simulation algorithms due to the high cost of communication. In this thesis, however, the distributed environment is shown to be a viable alternative if the amount of communication is kept reasonable. Novel ideas of multiple message simulation and channel reduction enable efficient use of this environment for the simulation of a cellular network application. The distribution of the simulation is based on a modification of the well known Chandy-Misra deadlock avoidance algorithm with null messages. The basic Chandy Misra algorithm is modified by using the null message cancellation and multiple message simulation techniques. The modifications reduce the amount of null messages and the time required for their execution, thus reducing the simulation time required. The null message cancellation technique reduces the processing time of null messages as the arriving null message cancels other non processed null messages. The multiple message simulation forms groups of messages as it simulates several messages before it releases the new created messages. If the message population in the simulation is suffiecient, no additional delay is caused by this operation A new technique for considering the simulation application is also presented. The performance is improved by establishing a neighborhood for the simulation elements. The neighborhood concept is based on a channel reduction technique, where the properties of the application exclusively determine which connections are necessary when a certain accuracy for simulation results is required. Distributed simulation is also analyzed in order to find out the effect of the different elements in the implemented simulation environment. This analysis is performed by using critical path analysis. Critical path analysis allows determination of a lower bound for the simulation time. In this thesis critical times are computed for sequential and parallel traces. The analysis based on sequential traces reveals the parallel properties of the application whereas the analysis based on parallel traces reveals the properties of the environment and the distribution.

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Species structure and composition in Mediterranean riparian forests are determined by hydrological features, longitudinal zonation, and riverbank topography. This study assesses the distribution of four native riparian plants along the riverbank topographic gradient in three river stretches in southern Spain, with special emphasis on the occupation of adult and young feet of each species. The studied stretches suffered minimal human disturbances, displayed semi-arid conditions, and had wide riparian areas to allow the development of the target species: black alder (Alnus glutinosa), salvia leaf willow (Salix salviifolia), narrow-leafed ash (Fraxinus angustifolia), and oleander (Nerium oleander). Thalweg height was used to define the riverbank topographic gradient. The results showed a preferential zone for black alder and salvia leaf willow in the range of 0-150 cm from the channel thalweg, with adult alders and willows being more common between 51 and 150 cm and young alders being more common under 50 cm. Conversely, narrow-leafed ash and oleander were much more frequent, and showed greater development, in the ranges of 151-200 cm and 201-250 cm, respectively, whereas the young feet of both species covered the entire topographic range. Adult feet of the four species were spatially segregated along the riverbank topographic gradient, indicating their differential ability to cope with water stress from the non-tolerant alders and willows to more tolerant narrow-leafed ash trees and oleanders. Young feet, however, showed a strategy more closely linked to the initial availability of colonisation sites within riparian areas to the dispersion strategy of each species and to the distribution of adult feet. In Mediterranean areas, where riparian management has traditionally faced great challenges, the incorporation of species preferences along riverbank gradients could improve the performance of restoration projects.

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This study examines Smart Grids and distributed generation, which is connected to a single-family house. The distributed generation comprises small wind power plant and solar panels. The study is done from the consumer point of view and it is divided into two parts. The first part presents the theoretical part and the second part presents the research part. The theoretical part consists of the definition of distributed generation, wind power, solar energy and Smart Grids. The study examines what the Smart Grids will enable. New technology concerning Smart Grids is also examined. The research part introduces wind and sun conditions from two countries. The countries are Finland and Germany. According to the wind and sun conditions of these two countries, the annual electricity production from wind power plant and solar panels will be calculated. The costs of generating electricity from wind and solar energy are calculated from the results of annual electricity productions. The study will also deal with feed-in tariffs, which are supporting systems for renewable energy resources. It is examined in the study, if it is cost-effective for the consumers to use the produced electricity by themselves or sell it to the grid. Finally, figures for both countries are formed. The figures include the calculated cost of generating electricity from wind power plant and solar panels, retail and wholesale prices and feed-in tariffs. In Finland, it is not cost-effective to sell the produced electricity to the grid, before there are support systems. In Germany, it is cost-effective to sell the produced electricity from solar panels to the grid because of feed-in tariffs. On the other hand, in Germany it is cost-effective to produce electricity from wind to own use because the retail price is higher than the produced electricity from wind.

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In this paper we address the problem of extracting representative point samples from polygonal models. The goal of such a sampling algorithm is to find points that are evenly distributed. We propose star-discrepancy as a measure for sampling quality and propose new sampling methods based on global line distributions. We investigate several line generation algorithms including an efficient hardware-based sampling method. Our method contributes to the area of point-based graphics by extracting points that are more evenly distributed than by sampling with current algorithms

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Feedback-related negativity (FRN) is an ERP component that distinguishes positive from negative feedback. FRN has been hypothesized to be the product of an error signal that may be used to adjust future behavior. In addition, associative learning models assume that the trial-to-trial learning of cueoutcome mappings involves the minimization of an error term. This study evaluated whether FRN is a possible electrophysiological correlate of this error term in a predictive learning task where human subjects were asked to learn different cueoutcome relationships. Specifically, we evaluated the sensitivity of the FRN to the course of learning when different stimuli interact or compete to become a predictor of certain outcomes. Importantly, some of these cues were blocked by more informative or predictive cues (i.e., the blocking effect). Interestingly, the present results show that both learning and blocking affect the amplitude of the FRN component. Furthermore, independent analyses of positive and negative feedback event-related signals showed that the learning effect was restricted to the ERP component elicited by positive feedback. The blocking test showed differences in the FRN magnitude between a predictive and a blocked cue. Overall, the present results show that ERPs that are related to feedback processing correspond to the main predictions of associative learning models. ■