940 resultados para Global production network (GPN)


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The unsupervised categorization of sensory stimuli is typically attributed to feedforward processing in a hierarchy of cortical areas. This purely sensory-driven view of cortical processing, however, ignores any internal modulation, e.g., by top-down attentional signals or neuromodulator release. To isolate the role of internal signaling on category formation, we consider an unbroken continuum of stimuli without intrinsic category boundaries. We show that a competitive network, shaped by recurrent inhibition and endowed with Hebbian and homeostatic synaptic plasticity, can enforce stimulus categorization. The degree of competition is internally controlled by the neuronal gain and the strength of inhibition. Strong competition leads to the formation of many attracting network states, each being evoked by a distinct subset of stimuli and representing a category. Weak competition allows more neurons to be co-active, resulting in fewer but larger categories. We conclude that the granularity of cortical category formation, i.e., the number and size of emerging categories, is not simply determined by the richness of the stimulus environment, but rather by some global internal signal modulating the network dynamics. The model also explains the salient non-additivity of visual object representation observed in the monkey inferotemporal (IT) cortex. Furthermore, it offers an explanation of a previously observed, demand-dependent modulation of IT activity on a stimulus categorization task and of categorization-related cognitive deficits in schizophrenic patients.

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Polylactide (PLA) is a biodegradable polymer that has been used in particle form for drug release, due to its biocompatibility, tailorable degradation kinetics, and desirable mechanical properties. Active pharmaceutical ingredients (APIs) may be either dissolved or encapsulated within these biomaterials to create micro- or nanoparticles. Delivery of an AIP within fine particles may overcome solubility or stability issues that can result in early elimination or degradation of the AIP in a hostile biological environment. Furthermore, it is a promising method for controlling the rate of drug delivery and dosage. The goal of this project is to develop a simple and cost-effective device that allows us to produce monodisperse micro- and nanocapsules with controllable size and adjustable sheath thickness on demand. To achieve this goal, we have studied the dual-capillary electrospray and pulsed electrospray. Dual-capillary electrospray has received considerable attention in recent years due to its ability to create core-shell structures in a single-step. However, it also increases the difficulty of controlling the inner and outer particle morphology, since two simultaneous flows are required. Conventional electrospraying has been mainly conducted using direct-current (DC) voltage with little control over anything but the electrical potential. In contrast, control over the input voltage waveform (i.e. pulsing) in electrospraying offers greater control over the process variables. Poly(L-lactic acid) (PLLA) microspheres and microcapsules were successfully fabricated via pulsed-DC electrospray and dual-capillary electrospray, respectively. Core shell combinations produced include: Water/PLLA, PLLA/polyethylene glycol (PEG), and oleic Acid/PLLA. In this study, we designed a novel high-voltage pulse forming network and a set of new designs for coaxial electrospray nozzles. We also investigated the effect of the pulsed voltage characteristics (e.g. pulse frequency, pulse amplitude and pulse width) on the particle’s size and uniformity. We found that pulse frequency, pulse amplitude, pulse width, and the combinations of these factors had a statistically significant effect on the particle’s size. In addition, factors such as polymer concentration, solvent type, feed flow rate, collection method, temperature, and humidity can significantly affect the size and shape of the particles formed.

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Denitrification is an important process of global nitrogen cycle as it removes reactive nitrogen from the biosphere, and acts as the primary source of nitrous oxide (N2O). This thesis seeks to gain better understanding of the biogeochemistry of denitrification by investigating the process from four different aspects: genetic basis, enzymatic kinetics, environmental interactions, and environmental consequences. Laboratory and field experiments were combined with modeling efforts to unravel the complexity of denitrification process under microbiological and environmental controls. Dynamics of denitrification products observed in laboratory experiments revealed an important role of constitutive denitrification enzymes, whose presence were further confirmed with quantitative analysis of functional genes encoding nitrite reductase and nitrous oxide reductase. A metabolic model of denitrification developed with explicit denitrification enzyme kinetics and representation of constitutive enzymes successfully reproduced the dynamics of N2O and N2 accumulation observed in the incubation experiments, revealing important regulatory effect of denitrification enzyme kinetics on the accumulation of denitrification products. Field studies demonstrated complex interaction of belowground N2O production, consumption and transport, resulting in two pulse pattern in the surface flux. Coupled soil gas diffusion/denitrification model showed great potential in simulating the dynamics of N2O below ground, with explicit representation of the activity of constitutive denitrification enzymes. A complete survey of environmental variables showed distinct regulation regimes on the denitrification activity from constitutive enzymes and new synthesized enzymes. Uncertainties in N2O estimation with current biogeochemical models may be reduced as accurate simulation of the dynamics of N2O in soil and surface fluxes is possible with a coupled diffusion/denitrification model that includes explicit representation of denitrification enzyme kinetics. In conclusion, denitrification is a complex ecological function regulated at cellular level. To assess the environmental consequences of denitrification and develop useful tools to mitigate N2O emissions require a comprehensive understanding of the regulatory network of denitrification with respect to microbial physiology and environmental interactions.

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Phase locking or synchronization of brain areas is a key concept of information processing in the brain. Synchronous oscillations have been observed and investigated extensively in EEG during the past decades. EEG oscillations occur over a wide frequency range. In EEG, a prominent type of oscillations is alpha-band activity, present typically when a subject is awake, but at rest with closed eyes. The spectral power of alpha rhythms has recently been investigated in simultaneous EEG/fMRI recordings, establishing a wide-range cortico-thalamic network. However, spectral power and synchronization are different measures and little is known about the correlations between BOLD effects and EEG synchronization. Interestingly, the fMRI BOLD signal also displays synchronous oscillations across different brain regions. These oscillations delineate so-called resting state networks (RSNs) that resemble the correlation patterns of simultaneous EEG/fMRI recordings. However, the nature of these BOLD oscillations and their relations to EEG activity is still poorly understood. One hypothesis is that the subunits constituting a specific RSN may be coordinated by different EEG rhythms. In this study we report on evidence for this hypothesis. The BOLD correlates of global EEG synchronization (GFS) in the alpha frequency band are located in brain areas involved in specific RSNs, e.g. the 'default mode network'. Furthermore, our results confirm the hypothesis that specific RSNs are organized by long-range synchronization at least in the alpha frequency band. Finally, we could localize specific areas where the GFS BOLD correlates and the associated RSN overlap. Thus, we claim that not only the spectral dynamics of EEG are important, but also their spatio-temporal organization.

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Rationale: Focal onset epileptic seizures are due to abnormal interactions between distributed brain areas. By estimating the cross-correlation matrix of multi-site intra-cerebral EEG recordings (iEEG), one can quantify these interactions. To assess the topology of the underlying functional network, the binary connectivity matrix has to be derived from the cross-correlation matrix by use of a threshold. Classically, a unique threshold is used that constrains the topology [1]. Our method aims to set the threshold in a data-driven way by separating genuine from random cross-correlation. We compare our approach to the fixed threshold method and study the dynamics of the functional topology. Methods: We investigate the iEEG of patients suffering from focal onset seizures who underwent evaluation for the possibility of surgery. The equal-time cross-correlation matrices are evaluated using a sliding time window. We then compare 3 approaches assessing the corresponding binary networks. For each time window: * Our parameter-free method derives from the cross-correlation strength matrix (CCS)[2]. It aims at disentangling genuine from random correlations (due to finite length and varying frequency content of the signals). In practice, a threshold is evaluated for each pair of channels independently, in a data-driven way. * The fixed mean degree (FMD) uses a unique threshold on the whole connectivity matrix so as to ensure a user defined mean degree. * The varying mean degree (VMD) uses the mean degree of the CCS network to set a unique threshold for the entire connectivity matrix. * Finally, the connectivity (c), connectedness (given by k, the number of disconnected sub-networks), mean global and local efficiencies (Eg, El, resp.) are computed from FMD, CCS, VMD, and their corresponding random and lattice networks. Results: Compared to FMD and VMD, CCS networks present: *topologies that are different in terms of c, k, Eg and El. *from the pre-ictal to the ictal and then post-ictal period, topological features time courses that are more stable within a period, and more contrasted from one period to the next. For CCS, pre-ictal connectivity is low, increases to a high level during the seizure, then decreases at offset. k shows a ‘‘U-curve’’ underlining the synchronization of all electrodes during the seizure. Eg and El time courses fluctuate between the corresponding random and lattice networks values in a reproducible manner. Conclusions: The definition of a data-driven threshold provides new insights into the topology of the epileptic functional networks.

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The number of large research networks and programmes engaging in knowledge production for development has grown over the past years. One of these programmes devoted to generating knowledge about and for development is National Centre of Competence in Research (NCCR) North–South, a cross-disciplinary, international development research network funded by the Swiss Agency for Development and Cooperation and the Swiss National Science Foundation. Producing relevant knowledge for development is a core goal of the programme and an important motivation for many of the participating researchers. Over the years, the researchers have made use of various spaces for exchange and instruments for co-production of knowledge by academic and non-academic development actors. In this article we explore the characteristics of co-producing and sharing knowledge in interfaces between development research, policy and NCCR North–South practice. We draw on empirical material of the NCCR North–South programme and its specific programme element of the Partnership Actions. Our goal is to make use of the concept of the interface to reflect critically about the pursued strategies and instruments applied in producing and sharing knowledge for development across boundaries.

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Open collaborative projects are moving to the foreground of knowledge production. Some online user communities develop into longterm projects that generate a highly valuable and at the same time freely accessible output. Traditional copyright law that is organized around the idea of a single creative entity is not well equipped to accommodate the needs of these forms of collaboration. In order to enable a peculiar network-type of interaction participants instead draw on public licensing models that determine the freedoms to use individual contributions. With the help of these access rules the operational logic of the project can be implemented successfully. However, as the case of the Wikipedia GFDL-CC license transition demonstrates, the adaptation of access rules in networks to new circumstances raises collective action problems and suffers from pitfalls caused by the fact that public licensing is grounded in individual copyright. Legal governance of open collaboration projects is a largely unexplored field. The article argues that the license steward of a public license assumes the position of a fiduciary of the knowledge commons generated under the license regime. Ultimately, the governance of decentralized networks translates into a composite of organizational and contractual elements. It is concluded that the production of global knowledge commons relies on rules of transnational private law.

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Emphasizing the global and regional importance of mountain ecosystem services and referring to the anticipated future environmental changes affecting the provision of these services, this chapter takes a closer look at the Carpathian Mountains. In addition to climate change and general effects of globalization, rapid socioeconomic transformations after the fall of the Iron Curtain pose an extra challenge to the sustainable development of the region. Describing the early efforts of organizing mountain science through programs such as UNESCO MAB and UNEP at the global scale, this chapter focuses on the recent history of research coordination for the European mountains, in particular on the activities of the Carpathian Convention and the European Program of the Mountain Research Initiative, which were among main driving factors for the initiation of the Science for the Carpathians (S4C) network. This regional mountain research network was established in 2008 to foster scientific collaboration and communication and to promote applied research and capacity building, which in turn would support sustainable development in the Carpathian Mountains. Forum Carpaticum, a biennial open science conference, has become a central activity of the S4C network counting more than 400 members today.

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During the second half of the 20th century untreated sewage released from housing and industry into natural waters led to a degradation of many freshwater lakes and reservoirs worldwide. In order to mitigate eutrophication, wastewater treatment plants, including Fe-induced phosphorus precipitation, were implemented throughout the industrialized world, leading to reoligotrophication in many freshwater lakes. To understand and assess the effects of reoligotrophication on primary productivity, we analyzed 28 years of 14C assimilation rates, as well as other biotic and abiotic parameters, such as global radiation, nutrient concentrations and plankton densities in peri-alpine Lake Lucerne, Switzerland. Using a simple productivity-light relationship, we estimated continuous primary production and discussed the relation between productivity and observed limnological parameters. Furthermore, we assessed the uncertainty of our modeling approach based on monthly 14C assimilation measurements using Monte Carlo simulations. Results confirm that monthly sampling of productivity is sufficient for identifying long-term trends in productivity and that conservation management has successfully improved water quality during the past three decades via reducing nutrients and primary production in the lake. However, even though nutrient concentrations have remained constant in recent years, annual primary production varies significantly from year to year. Despite the fact that nutrient concentrations have decreased by more than an order of magnitude, primary production has decreased only slightly. These results suggest that primary production correlates well to nutrients availability but meteorological conditions lead to interannual variability regardless of the trophic status of the lake. Accordingly, in oligotrophic freshwaters meteorological forcing may reduce productivity impacting on the entire food chain of the ecosystem.

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PURPOSE In leukemic cutaneous T-cell lymphoma (L-CTCL), malignant T cells accumulate in the blood and give rise to widespread skin inflammation. Patients have intense pruritus, increased immunoglobulin E (IgE), and decreased T-helper (TH)-1 responses, and most die from infection. Depleting malignant T cells while preserving normal immunity is a clinical challenge. L-CTCL has been variably described as a malignancy of regulatory, TH2 and TH17 cells. EXPERIMENTAL DESIGN We analyzed phenotype and cytokine production in malignant and benign L-CTCL T cells, characterized the effects of malignant T cells on healthy T cells, and studied the immunomodulatory effects of treatment modalities in patients with L-CTCL. RESULTS Twelve out of 12 patients with L-CTCL overproduced TH2 cytokines. Remaining benign T cells were also strongly TH2 biased, suggesting a global TH2 skewing of the T-cell repertoire. Culture of benign T cells away from the malignant clone reduced TH2 and enhanced TH1 responses, but separate culture had no effect on malignant T cells. Coculture of healthy T cells with L-CTCL T cells reduced IFNγ production and neutralizing antibodies to interleukin (IL)-4 and IL-13 restored TH1 responses. In patients, enhanced TH1 responses were observed following a variety of treatment modalities that reduced malignant T-cell burden. CONCLUSIONS A global TH2 bias exists in both benign and malignant T cells in L-CTCL and may underlie the infectious susceptibility of patients. TH2 cytokines from malignant cells strongly inhibited TH1 responses. Our results suggest that therapies that inhibit TH2 cytokine activity, by virtue of their ability to improve TH1 responses, may have the potential to enhance both anticancer and antipathogen responses.

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The WOCAT network has collected, documented, and assessed more than 350 case studies on promising and good practices of SLM. Information on on- and off-site benefits of different SLM types, as well as on investment and maintenance costs is available, sometimes in quantitative and often in qualitative form. The objective of the present paper is to analyse what kind of economic benefits accrue to local stakeholders, and to better understand how these benefits compare to investment and maintenance costs. The large majority of the technologies contained in the database are perceived by land users as having positive benefits that outweigh costs in the long term. About three quarters of them also have positive or at least neutral benefits in the short term. The analysis shows that many SLM measures exist which can generate important benefits to land users, but also to other stakeholders. However, methodological issues need to be tackled and further quantitative and qualitative data are needed to better understand and support the adoption of SLM measures. Keywords: Sustainable Land Management, Costs, Benefits, Technologies

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Computational network analysis provides new methods to analyze the human connectome. Brain structural networks can be characterized by global and local metrics that recently gave promising insights for diagnosis and further understanding of neurological, psychiatric and neurodegenerative disorders. In order to ensure the validity of results in clinical settings the precision and repeatability of the networks and the associated metrics must be evaluated. In the present study, nineteen healthy subjects underwent two consecutive measurements enabling us to test reproducibility of the brain network and its global and local metrics. As it is known that the network topology depends on the network density, the effects of setting a common density threshold for all networks were also assessed. Results showed good to excellent repeatability for global metrics, while for local metrics it was more variable and some metrics were found to have locally poor repeatability. Moreover, between subjects differences were slightly inflated when the density was not fixed. At the global level, these findings confirm previous results on the validity of global network metrics as clinical biomarkers. However, the new results in our work indicate that the remaining variability at the local level as well as the effect of methodological characteristics on the network topology should be considered in the analysis of brain structural networks and especially in networks comparisons.

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Decadal-to-century scale trends for a range of marine environmental variables in the upper mesopelagic layer (UML, 100–600 m) are investigated using results from seven Earth System Models forced by a high greenhouse gas emission scenario. The models as a class represent the observation-based distribution of oxygen (O2) and carbon dioxide (CO2), albeit major mismatches between observation-based and simulated values remain for individual models. By year 2100 all models project an increase in SST between 2 °C and 3 °C, and a decrease in the pH and in the saturation state of water with respect to calcium carbonate minerals in the UML. A decrease in the total ocean inventory of dissolved oxygen by 2% to 4% is projected by the range of models. Projected O2 changes in the UML show a complex pattern with both increasing and decreasing trends reflecting the subtle balance of different competing factors such as circulation, production, remineralization, and temperature changes. Projected changes in the total volume of hypoxic and suboxic waters remain relatively small in all models. A widespread increase of CO2 in the UML is projected. The median of the CO2 distribution between 100 and 600m shifts from 0.1–0.2 mol m−3 in year 1990 to 0.2–0.4 mol m−3 in year 2100, primarily as a result of the invasion of anthropogenic carbon from the atmosphere. The co-occurrence of changes in a range of environmental variables indicates the need to further investigate their synergistic impacts on marine ecosystems and Earth System feedbacks.

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Radiocarbon production, solar activity, total solar irradiance (TSI) and solar-induced climate change are reconstructed for the Holocene (10 to 0 kyr BP), and TSI is predicted for the next centuries. The IntCal09/SHCal04 radiocarbon and ice core CO2 records, reconstructions of the geomagnetic dipole, and instrumental data of solar activity are applied in the Bern3D-LPJ, a fully featured Earth system model of intermediate complexity including a 3-D dynamic ocean, ocean sediments, and a dynamic vegetation model, and in formulations linking radiocarbon production, the solar modulation potential, and TSI. Uncertainties are assessed using Monte Carlo simulations and bounding scenarios. Transient climate simulations span the past 21 thousand years, thereby considering the time lags and uncertainties associated with the last glacial termination. Our carbon-cycle-based modern estimate of radiocarbon production of 1.7 atoms cm−2 s−1 is lower than previously reported for the cosmogenic nuclide production model by Masarik and Beer (2009) and is more in-line with Kovaltsov et al. (2012). In contrast to earlier studies, periods of high solar activity were quite common not only in recent millennia, but throughout the Holocene. Notable deviations compared to earlier reconstructions are also found on decadal to centennial timescales. We show that earlier Holocene reconstructions, not accounting for the interhemispheric gradients in radiocarbon, are biased low. Solar activity is during 28% of the time higher than the modern average (650 MeV), but the absolute values remain weakly constrained due to uncertainties in the normalisation of the solar modulation to instrumental data. A recently published solar activity–TSI relationship yields small changes in Holocene TSI of the order of 1 W m−2 with a Maunder Minimum irradiance reduction of 0.85 ± 0.16 W m−2. Related solar-induced variations in global mean surface air temperature are simulated to be within 0.1 K. Autoregressive modelling suggests a declining trend of solar activity in the 21st century towards average Holocene conditions.

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Both deepening sleep and evolving epileptic seizures are associated with increasing slow-wave activity. Larger-scale functional networks derived from electroencephalogram indicate that in both transitions dramatic changes of communication between brain areas occur. During seizures these changes seem to be 'condensed', because they evolve more rapidly than during deepening sleep. Here we set out to assess quantitatively functional network dynamics derived from electroencephalogram signals during seizures and normal sleep. Functional networks were derived from electroencephalogram signals from wakefulness, light and deep sleep of 12 volunteers, and from pre-seizure, seizure and post-seizure time periods of 10 patients suffering from focal onset pharmaco-resistant epilepsy. Nodes of the functional network represented electrical signals recorded by single electrodes and were linked if there was non-random cross-correlation between the two corresponding electroencephalogram signals. Network dynamics were then characterized by the evolution of global efficiency, which measures ease of information transmission. Global efficiency was compared with relative delta power. Global efficiency significantly decreased both between light and deep sleep, and between pre-seizure, seizure and post-seizure time periods. The decrease of global efficiency was due to a loss of functional links. While global efficiency decreased significantly, relative delta power increased except between the time periods wakefulness and light sleep, and pre-seizure and seizure. Our results demonstrate that both epileptic seizures and deepening sleep are characterized by dramatic fragmentation of larger-scale functional networks, and further support the similarities between sleep and seizures.