996 resultados para Feedback Interactions
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Predominant frameworks for understanding plant ecology have an aboveground bias that neglects soil micro-organisms. This is inconsistent with recent work illustrating the importance of soil microbes in terrestrial ecology. Microbial effects have been incorporated into plant community dynamics using ideas of niche modification and plant–soil community feedbacks. Here, we expand and integrate qualitative conceptual models of plant niche and feedback to explore implications of microbial interactions for understanding plant community ecology. At the same time we review the empirical evidence for these processes. We also consider common mycorrhizal networks, and propose that these are best interpreted within the feedback framework. Finally, we apply our integrated model of niche and feedback to understanding plant coexistence, monodominance and invasion ecology.
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Introducing a parameterization of the interactions between wind-driven snow depth changes and melt pond evolution allows us to improve large scale models. In this paper we have implemented an explicit melt pond scheme and, for the first time, a wind dependant snow redistribution model and new snow thermophysics into a coupled ocean–sea ice model. The comparison of long-term mean statistics of melt pond fractions against observations demonstrates realistic melt pond cover on average over Arctic sea ice, but a clear underestimation of the pond coverage on the multi-year ice (MYI) of the western Arctic Ocean. The latter shortcoming originates from the concealing effect of persistent snow on forming ponds, impeding their growth. Analyzing a second simulation with intensified snow drift enables the identification of two distinct modes of sensitivity in the melt pond formation process. First, the larger proportion of wind-transported snow that is lost in leads directly curtails the late spring snow volume on sea ice and facilitates the early development of melt ponds on MYI. In contrast, a combination of higher air temperatures and thinner snow prior to the onset of melting sometimes make the snow cover switch to a regime where it melts entirely and rapidly. In the latter situation, seemingly more frequent on first-year ice (FYI), a smaller snow volume directly relates to a reduced melt pond cover. Notwithstanding, changes in snow and water accumulation on seasonal sea ice is naturally limited, which lessens the impacts of wind-blown snow redistribution on FYI, as compared to those on MYI. At the basin scale, the overall increased melt pond cover results in decreased ice volume via the ice-albedo feedback in summer, which is experienced almost exclusively by MYI.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Relevance feedback approaches have been established as an important tool for interactive search, enabling users to express their needs. However, in view of the growth of multimedia collections available, the user efforts required by these methods tend to increase as well, demanding approaches for reducing the need of user interactions. In this context, this paper proposes a semi-supervised learning algorithm for relevance feedback to be used in image retrieval tasks. The proposed semi-supervised algorithm aims at using both supervised and unsupervised approaches simultaneously. While a supervised step is performed using the information collected from the user feedback, an unsupervised step exploits the intrinsic dataset structure, which is represented in terms of ranked lists of images. Several experiments were conducted for different image retrieval tasks involving shape, color, and texture descriptors and different datasets. The proposed approach was also evaluated on multimodal retrieval tasks, considering visual and textual descriptors. Experimental results demonstrate the effectiveness of the proposed approach.
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This study aims at a comprehensive understanding of the effects of aerosol-cloud interactions and their effects on cloud properties and climate using the chemistry-climate model EMAC. In this study, CCN activation is regarded as the dominant driver in aerosol-cloud feedback loops in warm clouds. The CCN activation is calculated prognostically using two different cloud droplet nucleation parameterizations, the STN and HYB CDN schemes. Both CDN schemes account for size and chemistry effects on the droplet formation based on the same aerosol properties. The calculation of the solute effect (hygroscopicity) is the main difference between the CDN schemes. The kappa-method is for the first time incorporated into Abdul-Razzak and Ghan activation scheme (ARG) to calculate hygroscopicity and critical supersaturation of aerosols (HYB), and the performance of the modied scheme is compared with the osmotic coefficient model (STN), which is the standard in the ARG scheme. Reference simulations (REF) with the prescribed cloud droplet number concentration have also been carried out in order to understand the effects of aerosol-cloud feedbacks. In addition, since the calculated cloud coverage is an important determinant of cloud radiative effects and is influencing the nucleation process two cloud cover parameterizations (i.e., a relative humidity threshold; RH-CLC and a statistical cloud cover scheme; ST-CLC) have been examined together with the CDN schemes, and their effects on the simulated cloud properties and relevant climate parameters have been investigated. The distinct cloud droplet spectra show strong sensitivity to aerosol composition effects on cloud droplet formation in all particle sizes, especially for the Aitken mode. As Aitken particles are the major component of the total aerosol number concentration and CCN, and are most sensitive to aerosol chemical composition effect (solute effect) on droplet formation, the activation of Aitken particles strongly contribute to total cloud droplet formation and thereby providing different cloud droplet spectra. These different spectra influence cloud structure, cloud properties, and climate, and show regionally varying sensitivity to meteorological and geographical condition as well as the spatiotemporal aerosol properties (i.e., particle size, number, and composition). The changes responding to different CDN schemes are more pronounced at lower altitudes than higher altitudes. Among regions, the subarctic regions show the strongest changes, as the lower surface temperature amplifies the effects of the activated aerosols; in contrast, the Sahara desert, where is an extremely dry area, is less influenced by changes in CCN number concentration. The aerosol-cloud coupling effects have been examined by comparing the prognostic CDN simulations (STN, HYB) with the reference simulation (REF). Most pronounced effects are found in the cloud droplet number concentration, cloud water distribution, and cloud radiative effect. The aerosol-cloud coupling generally increases cloud droplet number concentration; this decreases the efficiency of the formation of weak stratiform precipitation, and increases the cloud water loading. These large-scale changes lead to larger cloud cover and longer cloud lifetime, and contribute to high optical thickness and strong cloud cooling effects. This cools the Earth's surface, increases atmospheric stability, and reduces convective activity. These changes corresponding to aerosol-cloud feedbacks are also differently simulated depending on the cloud cover scheme. The ST-CLC scheme is more sensitive to aerosol-cloud coupling, since this scheme uses a tighter linkage of local dynamics and cloud water distributions in cloud formation process than the RH-CLC scheme. For the calculated total cloud cover, the RH-CLC scheme simulates relatively similar pattern to observations than the ST-CLC scheme does, but the overall properties (e.g., total cloud cover, cloud water content) in the RH simulations are overestimated, particularly over ocean. This is mainly originated from the difference in simulated skewness in each scheme: the RH simulations calculate negatively skewed distributions of cloud cover and relevant cloud water, which is similar to that of the observations, while the ST simulations yield positively skewed distributions resulting in lower mean values than the RH-CLC scheme does. The underestimation of total cloud cover over ocean, particularly over the intertropical convergence zone (ITCZ) relates to systematic defficiency of the prognostic calculation of skewness in the current set-ups of the ST-CLC scheme.rnOverall, the current EMAC model set-ups perform better over continents for all combinations of the cloud droplet nucleation and cloud cover schemes. To consider aerosol-cloud feedbacks, the HYB scheme is a better method for predicting cloud and climate parameters for both cloud cover schemes than the STN scheme. The RH-CLC scheme offers a better simulation of total cloud cover and the relevant parameters with the HYB scheme and single-moment microphysics (REF) than the ST-CLC does, but is not very sensitive to aerosol-cloud interactions.
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A three-dimensional, regional coupled atmosphere-ocean model with full physics is developed to study air-sea interactions during winter storms off the U. S. east coast. Because of the scarcity of open ocean observations, models such as this offer valuable opportunities to investigate how oceanic forcing drives atmospheric circulation and vice versa. The study presented here considers conditions of strong atmospheric forcing (high wind speeds) and strong oceanic forcing (significant sea surface temperature (SST) gradients). A simulated atmospheric cyclone evolves in a manner consistent with Eta reanalysis, and the simulated air-sea heat and momentum exchanges strongly affect the circulations in both the atmosphere and the ocean. For the simulated cyclone of 19-20 January 1998, maximum ocean-to-atmosphere heat fluxes first appear over the Gulf Stream in the South Atlantic Bight, and this results in rapid deepening of the cyclone off the Carolina coast. As the cyclone moves eastward, the heat flux maximum shifts into the region near Cape Hatteras and later northeast of Hatteras, where it enhances the wind locally. The oceanic response to the atmospheric forcing is closely related to the wind direction. Southerly and southwesterly winds tend to strengthen surface currents in the Gulf Stream, whereas northeasterly winds weaken the surface currents in the Gulf Stream and generate southwestward flows on the shelf. The oceanic feedback to the atmosphere moderates the cyclone strength. Compared with a simulation in which the oceanic model always passes the initial SST to the atmospheric model, the coupled simulation in which the oceanic model passes the evolving SST to the atmospheric model produces higher ocean-to-atmosphere heat flux near Gulf Stream meander troughs. This is due to wind-driven lateral shifts of the stream, which in turn enhance the local northeasterly winds. Away from the Gulf Stream the coupled simulation produces surface winds that are 5 similar to 10% weaker. Differences in the surface ocean currents between these two experiments are significant on the shelf and in the open ocean.
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Introduction Assist in unison to the patient’s inspiratory neural effort and feedback-controlled limitation of lung distension with neurally adjusted ventilatory assist (NAVA) may reduce the negative effects of mechanical ventilation on right ventricular function. Methods Heart–lung interaction was evaluated in 10 intubated patients with impaired cardiac function using esophageal balloons, pulmonary artery catheters and echocardiography. Adequate NAVA level identified by a titration procedure to breathing pattern (NAVAal), 50% NAVAal, and 200% NAVAal and adequate pressure support (PSVal, defined clinically), 50% PSVal, and 150% PSVal were implemented at constant positive end-expiratory pressure for 20 minutes each. Results NAVAal was 3.1 ± 1.1cmH2O/μV and PSVal was 17 ± 2 cmH20. For all NAVA levels negative esophageal pressure deflections were observed during inspiration whereas this pattern was reversed during PSVal and PSVhigh. As compared to expiration, inspiratory right ventricular outflow tract velocity time integral (surrogating stroke volume) was 103 ± 4%, 109 ± 5%, and 100 ± 4% for NAVAlow, NAVAal, and NAVAhigh and 101 ± 3%, 89 ± 6%, and 83 ± 9% for PSVlow, PSVal, and PSVhigh, respectively (p < 0.001 level-mode interaction, ANOVA). Right ventricular systolic isovolumetric pressure increased from 11.0 ± 4.6 mmHg at PSVlow to 14.0 ± 4.6 mmHg at PSVhigh but remained unchanged (11.5 ± 4.7 mmHg (NAVAlow) and 10.8 ± 4.2 mmHg (NAVAhigh), level-mode interaction p = 0.005). Both indicate progressive right ventricular outflow impedance with increasing pressure support ventilation (PSV), but no change with increasing NAVA level. Conclusions Right ventricular performance is less impaired during NAVA compared to PSV as used in this study. Proposed mechanisms are preservation of cyclic intrathoracic pressure changes characteristic of spontaneous breathing and limitation of right-ventricular outflow impedance during inspiration, regardless of the NAVA level.
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Effective adaptive behavior rests on an appropriate understanding of how much responsibility we have over outcomes in the environment. This attribution of agency to ourselves or to an external event influences our behavioral and affective response to the outcomes. Despite its special importance to understanding human motivation and affect, the neural mechanisms involved in self-attributed rewards and punishments remain unclear. Previous evidence implicates the anterior insula (AI) in evaluating the consequences of our own actions. However, it is unclear if the AI has a general role in feedback evaluation (positive and negative) or plays a specific role during error processing. Using functional magnetic resonance imaging and a motion prediction task, we investigate neural responses to self- and externally attributed monetary gains and losses. We found that attribution effects vary according to the valence of feedback: significant valence × attribution interactions in the right AI, the anterior cingulate cortex (ACC), the midbrain, and the right ventral putamen. Self-attributed losses were associated with increased activity in the midbrain, the ACC and the right AI, and negative BOLD response in the ventral putamen. However, higher BOLD activity to self-attributed feedback (losses and gains) was observed in the left AI, the thalamus, and the cerebellar vermis. These results suggest a functional lateralization of the AI. The right AI, together with the midbrain and the ACC, is mainly involved in processing the salience of the outcome, whereas the left is part of a cerebello-thalamic-cortical pathway involved in cognitive control processes important for subsequent behavioral adaptations.
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The barrier surfaces of the skin, lung, and intestine are constantly exposed to environmental stimuli that can result in inflammation and tissue damage. Interleukin (IL)-33-dependent group 2 innate lymphoid cells (ILC2s) are enriched at barrier surfaces and have been implicated in promoting inflammation; however, the mechanisms underlying the tissue-protective roles of IL-33 or ILC2s at surfaces such as the intestine remain poorly defined. Here we demonstrate that, following activation with IL-33, expression of the growth factor amphiregulin (AREG) is a dominant functional signature of gut-associated ILC2s. In the context of a murine model of intestinal damage and inflammation, the frequency and number of AREG-expressing ILC2s increases following intestinal injury and genetic disruption of the endogenous AREG-epidermal growth factor receptor (EGFR) pathway exacerbated disease. Administration of exogenous AREG limited intestinal inflammation and decreased disease severity in both lymphocyte-sufficient and lymphocyte-deficient mice, revealing a previously unrecognized innate immune mechanism of intestinal tissue protection. Furthermore, treatment with IL-33 or transfer of ILC2s ameliorated intestinal disease severity in an AREG-dependent manner. Collectively, these data reveal a critical feedback loop in which cytokine cues from damaged epithelia activate innate immune cells to express growth factors essential for ILC-dependent restoration of epithelial barrier function and maintenance of tissue homeostasis.
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Differences in how organisms modify their environment can evolve rapidly and might influence adaptive population divergence [1, 2]. In a common garden experiment in aquatic mesocosms, we found that adult stickleback from a recently diverged pair of lake and stream populations had contrasting effects on ecosystem metrics. These modifications were caused by both genetic and plastic differences between populations and were sometimes comparable in magnitude to those caused by the presence/ absence of stickleback. Lake and streamfish differentially affected the biomass of zooplankton and phytoplankton, the concentration of phosphorus, and the abundance of several prey (e.g., copepods) and non-prey (e.g., cyanobacteria) species. The adult mediated effects on mesocosm ecosystems influenced the survival and growth of a subsequent generation of juvenile stickleback reared in the same mesocosms. The prior presence of adults decreased the overall growth rate of juveniles, and the prior presence of stream adults lowered overall juvenile survival. Among the survivors, lake juveniles grew faster than co-occurring stream juveniles, except in mesocosm ecosystems previously modified by adult lake fish that were reared on plankton. Overall, our results provide evidence for reciprocal interactions between ecosystem dynamics and evolutionary change (i.e., eco-evolutionary feedbacks) in the early stages of adaptive population divergence.
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Recurrence of Head and Neck Squamous Cell Carcinoma (HNSCC) is common; thus, it is essential to improve the effectiveness and reduce toxicity of current treatments. Proteins in the Src/Jak/STAT pathway represent potential therapeutic targets, as this pathway is hyperactive in HNSCC and it has roles in cell migration, metastasis, proliferation, survival, and angiogenesis. During short-term Src inhibition, Janus kinase (Jak) 2, and signal transducer and activator of transcription (STAT) 3 and STAT5 are dephosphorylated and inactivated. Following sustained Src inhibition, STAT5 remains inactive, but Jak2 and STAT3 are reactivated following their early inhibition. To further characterize the mechanism of this novel feedback pathway we performed several experiments to look at the interactions between Src, Jak2, STAT5 and STAT3. We attempted to develop a non-radioactive kinase assay using purified recombinant Jak2 and Src proteins, but found that phospho-tyrosine antibodies were non-specifically binding to purified recombinant proteins. We then performed in vitro kinase assays (IVKAs) using purified recombinant Jak2, Src, STAT3, and STAT5 proteins with and without Src and Jak2 pharmacologic inhibitors. We also examined the interactions of these proteins in intact HNSCC cells. We found that recombinant Jak2, STAT3, and STAT5 are direct substrates of Src and that recombinant Src, STAT3, and STAT5 are direct substrates of Jak2 in the IVKA. To our knowledge, the finding that Src is a Jak substrate is novel and has not been shown before. In intact HNSCC cells we find that STAT3 can be reactivated despite continuous Src inhibition and that STAT5 continues to be inhibited despite Jak2 reactivation. Also, Jak2 inhibition did not affect Src or STAT5 activity but it did cause STAT3 inhibition. We hypothesized that the differences between the intact cells and the IVKA assays were due to a potential need for binding partners in intact HNSCC cells. One potential binding partner that we examined is the epidermal growth factor receptor (EGFR). We found that EGFR activation caused increased activation of Src and STAT5 but not Jak2. Our results demonstrate that although STAT3 and STAT5 are capable of being Src and Jak2 substrates, in intact HNSCC cells Src predominantly regulates STAT5 and Jak2 regulates STAT3. Regulation of STAT5 by Src may involve interactions between Src and EGFR. This knowledge along with future studies will better define the mechanisms of STAT regulation in HNSCC cells and ultimately result in an ideal combination of therapeutic agents for HNSCC.
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The combined effects of drought stress and grazing pressure on shaping plant–plant interactions are still poorly understood, while this combination is common in arid ecosystems. In this study we assessed the relative effect of grazing pressure and slope aspect (drought stress) on vegetation cover and soil functioning in semi-arid Mediterranean grassland–shrublands in southeastern Spain. Moreover, we linked these two stress factors to plant co-occurrence patterns at species-pair and community levels, by performing C-score analyses. Vegetation cover and soil functioning decreased with higher grazing pressure and more south-facing (drier) slopes. At the community level, plants at south-facing slopes were negatively associated at no grazing but positively associated at low grazing pressure and randomly associated at high grazing pressure. At north-facing slopes, grazing did not result in a shift in the direction of the association. In contrast, analysis of pairwise species co-occurrence patterns showed that the dominant species Stipa tenacissima and Anthyllis cytisoides shifted from excluding each other to co-occurring with increasing grazing pressure at north-facing slopes. Our findings highlight that for improved understanding of plant interactions along stress gradients, interactions between species pairs and interactions at the community level should be assessed, as these may reveal contrasting results.
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L’évolution continue des besoins d’apprentissage vers plus d’efficacité et plus de personnalisation a favorisé l’émergence de nouveaux outils et dimensions dont l’objectif est de rendre l’apprentissage accessible à tout le monde et adapté aux contextes technologiques et sociaux. Cette évolution a donné naissance à ce que l’on appelle l'apprentissage social en ligne mettant l'accent sur l’interaction entre les apprenants. La considération de l’interaction a apporté de nombreux avantages pour l’apprenant, à savoir établir des connexions, échanger des expériences personnelles et bénéficier d’une assistance lui permettant d’améliorer son apprentissage. Cependant, la quantité d'informations personnelles que les apprenants divulguent parfois lors de ces interactions, mène, à des conséquences souvent désastreuses en matière de vie privée comme la cyberintimidation, le vol d’identité, etc. Malgré les préoccupations soulevées, la vie privée en tant que droit individuel représente une situation idéale, difficilement reconnaissable dans le contexte social d’aujourd’hui. En effet, on est passé d'une conceptualisation de la vie privée comme étant un noyau des données sensibles à protéger des pénétrations extérieures à une nouvelle vision centrée sur la négociation de la divulgation de ces données. L’enjeu pour les environnements sociaux d’apprentissage consiste donc à garantir un niveau maximal d’interaction pour les apprenants tout en préservant leurs vies privées. Au meilleur de nos connaissances, la plupart des innovations dans ces environnements ont porté sur l'élaboration des techniques d’interaction, sans aucune considération pour la vie privée, un élément portant nécessaire afin de créer un environnement favorable à l’apprentissage. Dans ce travail, nous proposons un cadre de vie privée que nous avons appelé « gestionnaire de vie privée». Plus précisément, ce gestionnaire se charge de gérer la protection des données personnelles et de la vie privée de l’apprenant durant ses interactions avec ses co-apprenants. En s’appuyant sur l’idée que l’interaction permet d’accéder à l’aide en ligne, nous analysons l’interaction comme une activité cognitive impliquant des facteurs contextuels, d’autres apprenants, et des aspects socio-émotionnels. L'objectif principal de cette thèse est donc de revoir les processus d’entraide entre les apprenants en mettant en oeuvre des outils nécessaires pour trouver un compromis entre l’interaction et la protection de la vie privée. ii Ceci a été effectué selon trois niveaux : le premier étant de considérer des aspects contextuels et sociaux de l’interaction telle que la confiance entre les apprenants et les émotions qui ont initié le besoin d’interagir. Le deuxième niveau de protection consiste à estimer les risques de cette divulgation et faciliter la décision de protection de la vie privée. Le troisième niveau de protection consiste à détecter toute divulgation de données personnelles en utilisant des techniques d’apprentissage machine et d’analyse sémantique.
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L’évolution continue des besoins d’apprentissage vers plus d’efficacité et plus de personnalisation a favorisé l’émergence de nouveaux outils et dimensions dont l’objectif est de rendre l’apprentissage accessible à tout le monde et adapté aux contextes technologiques et sociaux. Cette évolution a donné naissance à ce que l’on appelle l'apprentissage social en ligne mettant l'accent sur l’interaction entre les apprenants. La considération de l’interaction a apporté de nombreux avantages pour l’apprenant, à savoir établir des connexions, échanger des expériences personnelles et bénéficier d’une assistance lui permettant d’améliorer son apprentissage. Cependant, la quantité d'informations personnelles que les apprenants divulguent parfois lors de ces interactions, mène, à des conséquences souvent désastreuses en matière de vie privée comme la cyberintimidation, le vol d’identité, etc. Malgré les préoccupations soulevées, la vie privée en tant que droit individuel représente une situation idéale, difficilement reconnaissable dans le contexte social d’aujourd’hui. En effet, on est passé d'une conceptualisation de la vie privée comme étant un noyau des données sensibles à protéger des pénétrations extérieures à une nouvelle vision centrée sur la négociation de la divulgation de ces données. L’enjeu pour les environnements sociaux d’apprentissage consiste donc à garantir un niveau maximal d’interaction pour les apprenants tout en préservant leurs vies privées. Au meilleur de nos connaissances, la plupart des innovations dans ces environnements ont porté sur l'élaboration des techniques d’interaction, sans aucune considération pour la vie privée, un élément portant nécessaire afin de créer un environnement favorable à l’apprentissage. Dans ce travail, nous proposons un cadre de vie privée que nous avons appelé « gestionnaire de vie privée». Plus précisément, ce gestionnaire se charge de gérer la protection des données personnelles et de la vie privée de l’apprenant durant ses interactions avec ses co-apprenants. En s’appuyant sur l’idée que l’interaction permet d’accéder à l’aide en ligne, nous analysons l’interaction comme une activité cognitive impliquant des facteurs contextuels, d’autres apprenants, et des aspects socio-émotionnels. L'objectif principal de cette thèse est donc de revoir les processus d’entraide entre les apprenants en mettant en oeuvre des outils nécessaires pour trouver un compromis entre l’interaction et la protection de la vie privée. ii Ceci a été effectué selon trois niveaux : le premier étant de considérer des aspects contextuels et sociaux de l’interaction telle que la confiance entre les apprenants et les émotions qui ont initié le besoin d’interagir. Le deuxième niveau de protection consiste à estimer les risques de cette divulgation et faciliter la décision de protection de la vie privée. Le troisième niveau de protection consiste à détecter toute divulgation de données personnelles en utilisant des techniques d’apprentissage machine et d’analyse sémantique.
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Thesis (Master's)--University of Washington, 2016-06