993 resultados para storage-discharge relationships


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This review summarizes the recent discovery of the cupin superfamily (from the Latin term "cupa," a small barrel) of functionally diverse proteins that initially were limited to several higher plant proteins such as seed storage proteins, germin (an oxalate oxidase), germin-like proteins, and auxin-binding protein. Knowledge of the three-dimensional structure of two vicilins, seed proteins with a characteristic beta-barrel core, led to the identification of a small number of conserved residues and thence to the discovery of several microbial proteins which share these key amino acids. In particular, there is a highly conserved pattern of two histidine-containing motifs with a varied intermotif spacing. This cupin signature is found as a central component of many microbial proteins including certain types of phosphomannose isomerase, polyketide synthase, epimerase, and dioxygenase. In addition, the signature has been identified within the N-terminal effector domain in a subgroup of bacterial AraC transcription factors. As well as these single-domain cupins, this survey has identified other classes of two-domain bicupins including bacterial gentisate 1, 2-dioxygenases and 1-hydroxy-2-naphthoate dioxygenases, fungal oxalate decarboxylases, and legume sucrose-binding proteins. Cupin evolution is discussed from the perspective of the structure-function relationships, using data from the genomes of several prokaryotes, especially Bacillus subtilis. Many of these functions involve aspects of sugar metabolism and cell wall synthesis and are concerned with responses to abiotic stress such as heat, desiccation, or starvation. Particular emphasis is also given to the oxalate-degrading enzymes from microbes, their biological significance, and their value in a range of medical and other applications.

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It is generally assumed that the variability of neuronal morphology has an important effect on both the connectivity and the activity of the nervous system, but this effect has not been thoroughly investigated. Neuroanatomical archives represent a crucial tool to explore structure–function relationships in the brain. We are developing computational tools to describe, generate, store and render large sets of three–dimensional neuronal structures in a format that is compact, quantitative, accurate and readily accessible to the neuroscientist. Single–cell neuroanatomy can be characterized quantitatively at several levels. In computer–aided neuronal tracing files, a dendritic tree is described as a series of cylinders, each represented by diameter, spatial coordinates and the connectivity to other cylinders in the tree. This ‘Cartesian’ description constitutes a completely accurate mapping of dendritic morphology but it bears little intuitive information for the neuroscientist. In contrast, a classical neuroanatomical analysis characterizes neuronal dendrites on the basis of the statistical distributions of morphological parameters, e.g. maximum branching order or bifurcation asymmetry. This description is intuitively more accessible, but it only yields information on the collective anatomy of a group of dendrites, i.e. it is not complete enough to provide a precise ‘blueprint’ of the original data. We are adopting a third, intermediate level of description, which consists of the algorithmic generation of neuronal structures within a certain morphological class based on a set of ‘fundamental’, measured parameters. This description is as intuitive as a classical neuroanatomical analysis (parameters have an intuitive interpretation), and as complete as a Cartesian file (the algorithms generate and display complete neurons). The advantages of the algorithmic description of neuronal structure are immense. If an algorithm can measure the values of a handful of parameters from an experimental database and generate virtual neurons whose anatomy is statistically indistinguishable from that of their real counterparts, a great deal of data compression and amplification can be achieved. Data compression results from the quantitative and complete description of thousands of neurons with a handful of statistical distributions of parameters. Data amplification is possible because, from a set of experimental neurons, many more virtual analogues can be generated. This approach could allow one, in principle, to create and store a neuroanatomical database containing data for an entire human brain in a personal computer. We are using two programs, L–NEURON and ARBORVITAE, to investigate systematically the potential of several different algorithms for the generation of virtual neurons. Using these programs, we have generated anatomically plausible virtual neurons for several morphological classes, including guinea pig cerebellar Purkinje cells and cat spinal cord motor neurons. These virtual neurons are stored in an online electronic archive of dendritic morphology. This process highlights the potential and the limitations of the ‘computational neuroanatomy’ strategy for neuroscience databases.

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In this paper, we examine the temporal stability of the evidence for two commodity futures pricing theories. We investigate whether the forecast power of commodity futures can be attributed to the extent to which they exhibit seasonality and we also consider whether there are time varying parameters or structural breaks in these pricing relationships. Compared to previous studies, we find stronger evidence of seasonality in the basis, which supports the theory of storage. The power of the basis to forecast subsequent price changes is also strengthened, while results on the presence of a risk premium are inconclusive. In addition, we show that the forecasting power of commodity futures cannot be attributed to the extent to which they exhibit seasonality. We find that in most cases where structural breaks occur, only changes in the intercepts and not the slopes are detected, illustrating that the forecast power of the basis is stable over different economic environments.

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The charging of an undivided cerium–zinc redox battery by various current waveforms some of which mimic the output of renewable energy (solar, wind, tidal, biofuel burning) to electricity transducers is considered in this work, where the battery operates through diffusion-only conditions, and is discharged galvanostatically. Under reasonable assumption, the mathematical model developed enables the observation that the performance characteristic of the cells charged with a constant power input differentiates between the various current–charge waveforms, with cell geometry and electrode kinetics playing subtle, but significant, roles; in particular, high efficiency is observed for sunlight-charged batteries which are thin and suffer no corrosion of the sacrificial electrode, and which have already experienced a charge–discharge cycle. The performance characteristics of the systems are interpreted in the light of consequences for smart grid realisation, and indicate that, for a constant power input, the most matched renewable is biofuel burning with a current output that linearly increases with time.

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A reliable hydrograph separation method is necessary for surface runoff modeling and hydrological studies. This paper investigates and compares the separation characteristics of two single-parameter digital filters, which are herein referred to as the one-parameter algorithm and the conceptual method. The application of the one-parameter algorithm was found to be restricted to low and medium baseflow separations, with a maximum separation limit of 50% of the total runoff hydrograph. The one-parameter algorithm was also observed to produce unrealistic sharp peaks under the peaks of the measured hydrograph when recession constant is smaller than 0.96. On the other hand, the conceptual method is applicable even for catchments fed largely by groundwater discharge. However, a reliable estimation of recession constant is a prerequisite for applying the conceptual method for large baseflow separations. Based on the hydrograph separation results, useful empirical relationships were developed for a partially urbanized watershed to estimate total runoff and direct runoff from the measured rainfall depth. The relationships between rainfall depth and total runoff depth and rainfall depth and direct runoff depth were found to be well represented by linear equations. The empirical relationships were then applied to estimate the long-term contribution of baseflow and surface runoff to total runoff at the study site. Baseflow was found to contribute about 58–61% of the annual total runoff.

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h-In2O3/carbon nanocomposites were obtained via a facile ball milling process from a mixture of h-In2O3 nanoparticles and Super P carbon. Compared to pure h-In2O3 nanoparticles, the nanocomposites exhibited an initial discharge capacity of 1360 mAh g-1, a stable reversible capacity of 867 mAh g-1 after 100 cycles as well as a high coulombic efficiency of 99%. The superior lithium-ion battery performance can be attributed to the specific structure of h-In2O3 and the uniform and continuous nano-carbon coating layers. The nano-carbon coating could protect the inner active materials from fragmentation and increase the electronic conductivity. This study not only provides a promising electrode material for high-performance lithium-ion batteries, but also further demonstrates a straightforward, effective and environmental friendly process for synthesizing nanocomposites. © 2014 Elsevier Ltd.

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A new process for the surface modification of hydrogen storage intermetallic particles used as anode material in secondary batteries is proposed in this article. The copper oxide particles coverage obtained by the sol-gel method is proposed to produce, under operational conditions of a Ni-MH battery, a metallic framework that tolerates the volume changes in charge/discharge cycles and does not inhibit the hydrogen absorption. Furthermore it was noticed an enhancement on the discharge capacity of the electrode material that can be related to a new hydrogen storage phase or to an inhibition of the surface oxidation promoted by the film coverage.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Die vorliegende Arbeit befasst sich mit der Synthese und Charakterisierung von Polymeren mit redox-funktionalen Phenothiazin-Seitenketten. Phenothiazin und seine Derivate sind kleine Redoxeinheiten, deren reversibles Redoxverhalten mit electrochromen Eigenschaften verbunden ist. Das besondere an Phenothiazine ist die Bildung von stabilen Radikalkationen im oxidierten Zustand. Daher können Phenothiazine als bistabile Moleküle agieren und zwischen zwei stabilen Redoxzuständen wechseln. Dieser Schaltprozess geht gleichzeitig mit einer Farbveränderung an her.rnrnIm Rahmen dieser Arbeit wird die Synthese neuartiger Phenothiazin-Polymere mittels radikalischer Polymerisation beschrieben. Phenothiazin-Derivate wurden kovalent an aliphatischen und aromatischen Polymerketten gebunden. Dies erfolgte über zwei unterschiedlichen synthetischen Routen. Die erste Route beinhaltet den Einsatz von Vinyl-Monomeren mit Phenothiazin Funktionalität zur direkten Polymerisation. Die zweite Route verwendet Amin modifizierte Phenothiazin-Derivate zur Funktionalisierung von Polymeren mit Aktivester-Seitenketten in einer polymeranalogen Reaktion. rnrnPolymere mit redox-funktionalen Phenothiazin-Seitenketten sind aufgrund ihrer Elektron-Donor-Eigenschaften geeignete Kandidaten für die Verwendung als Kathodenmaterialien. Zur Überprüfung ihrer Eignung wurden Phenothiazin-Polymere als Elektrodenmaterialien in Lithium-Batteriezellen eingesetzt. Die verwendeten Polymere wiesen gute Kapazitätswerte von circa 50-90 Ah/kg sowie schnelle Aufladezeiten in der Batteriezelle auf. Besonders die Aufladezeiten sind 5-10 mal höher als konventionelle Lithium-Batterien. Im Hinblick auf Anzahl der Lade- und Entladezyklen, erzielten die Polymere gute Werte in den Langzeit-Stabilitätstests. Insgesamt überstehen die Polymere 500 Ladezyklen mit geringen Veränderungen der Anfangswerte bezüglich Ladezeiten und -kapazitäten. Die Langzeit-Stabilität hängt unmittelbar mit der Radikalstabilität zusammen. Eine Stabilisierung der Radikalkationen gelang durch die Verlängerung der Seitenkette am Stickstoffatom des Phenothiazins und der Polymerhauptkette. Eine derartige Alkyl-Substitution erhöht die Radikalstabilität durch verstärkte Wechselwirkung mit dem aromatischen Ring und verbessert somit die Batterieleistung hinsichtlich der Stabilität gegenüber Lade- und Entladezyklen. rnrnDes Weiteren wurde die praktische Anwendung von bistabilen Phenothiazin-Polymeren als Speichermedium für hohe Datendichten untersucht. Dazu wurden dünne Filme des Polymers auf leitfähigen Substraten elektrochemisch oxidiert. Die elektrochemische Oxidation erfolgte mittels Rasterkraftmikroskopie in Kombination mit leitfähigen Mikroskopspitzen. Mittels dieser Technik gelang es, die Oberfläche des Polymers im nanoskaligen Bereich zu oxidieren und somit die lokale Leitfähigkeit zu verändern. Damit konnten unterschiedlich große Muster lithographisch beschrieben und aufgrund der Veränderung ihrer Leitfähigkeit detektiert werden. Der Schreibprozess führte nur zu einer Veränderung der lokalen Leitfähigkeit ohne die topographische Beschaffenheit des Polymerfilms zu beeinflussen. Außerdem erwiesen sich die Muster als besonders stabil sowohl mechanisch als auch über die Zeit.rnrnZum Schluss wurden neue Synthesestrategien entwickelt um mechanisch stabile als auch redox-funktionale Oberflächen zu produzieren. Mit Hilfe der oberflächen-initiierten Atomtransfer-Radikalpolymerisation wurden gepfropfte Polymerbürsten mit redox-funktionalen Phenothiazin-Seitenketten hergestellt und mittels Röntgenmethoden und Rasterkraftmikroskopie analysiert. Eine der Synthesestrategien geht von gepfropften Aktivesterbürsten aus, die anschließend in einem nachfolgenden Schritt mit redox-funktionalen Gruppen modifiziert werden können. Diese Vorgehensweise ist besonders vielversprechend und erlaubt es unterschiedliche funktionelle Gruppen an den Aktivesterbürsten zu verankern. Damit können durch Verwendung von vernetzenden Gruppen neben den Redoxeigenschaften, die mechanische Stabilität solcher Polymerfilme optimiert werden. rn rn

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Using a cost-efficient climate model, the effect of changes in overturning circulation on neodymium isotopic composition,ϵNd, is systematically examined for the first time. Idealized sequences of abrupt climate changes are induced by the application of periodic freshwater fluxes to the North Atlantic (NA) and the Southern Ocean (SO), thus mainly affecting either the formation of North Atlantic Deep Water (NADW) or Antarctic Bottom Water (AABW). Variations in ϵNd reflect weakening and strengthening of the formation of NADW and AABW, changes in ϵNdof end-members are relatively small. Relationships betweenϵNd and the strength of NADW or AABW are more pronounced for AABW than for NADW. Atlantic patterns of variations in ϵNd systematically differ between NA and SO experiments. Additionally, the signature of changes in ϵNd in the Atlantic and the Pacific is alike in NA but opposite in SO experiments. Discrimination between NA and SO experiments is therefore possible based on the Atlantic pattern of variations in ϵNd and the contrariwise behavior of ϵNd in the Atlantic and the Pacific. In further experiments we examined the effect of variations in magnitudes of particle export fluxes. Within the examined range, and although settling particles represent the only sink of Nd, their effects on ϵNd are relatively small. Our results confirm the large potential of ϵNd as a paleocirculation tracer but also indicate its limitations of quantitative reconstructions of changes in the Atlantic Meridional Ocean Circulation.

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The role of irregular cortical firing in neuronal computation is still debated, and it is unclear how signals carried by fluctuating synaptic potentials are decoded by downstream neurons. We examined in vitro frequency versus current (f-I) relationships of layer 5 (L5) pyramidal cells of the rat medial prefrontal cortex (mPFC) using fluctuating stimuli. Studies in the somatosensory cortex show that L5 neurons become insensitive to input fluctuations as input mean increases and that their f-I response becomes linear. In contrast, our results show that mPFC L5 pyramidal neurons retain an increased sensitivity to input fluctuations, whereas their sensitivity to the input mean diminishes to near zero. This implies that the discharge properties of L5 mPFC neurons are well suited to encode input fluctuations rather than input mean in their firing rates, with important consequences for information processing and stability of persistent activity at the network level.

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This project addresses the potential impacts of changing climate on dry-season water storage and discharge from a small, mountain catchment in Tanzania. Villagers and water managers around the catchment have experienced worsening water scarcity and attribute it to increasing population and demand, but very little has been done to understand the physical characteristics and hydrological behavior of the spring catchment. The physical nature of the aquifer was characterized and water balance models were calibrated to discharge observations so as to be able to explore relative changes in aquifer storage resulting from climate changes. To characterize the shallow aquifer supplying water to the Jandu spring, water quality and geochemistry data were analyzed, discharge recession analysis was performed, and two water balance models were developed and tested. Jandu geochemistry suggests a shallow, meteorically-recharged aquifer system with short circulation times. Baseflow recession analysis showed that the catchment behavior could be represented by a linear storage model with an average recession constant of 0.151/month from 2004-2010. Two modified Thornthwaite-Mather Water Balance (TMWB) models were calibrated using historic rainfall and discharge data and shown to reproduce dry-season flows with Nash-Sutcliffe efficiencies between 0.86 and 0.91. The modified TMWB models were then used to examine the impacts of nineteen, perturbed climate scenarios to test the potential impacts of regional climate change on catchment storage during the dry season. Forcing the models with realistic scenarios for average monthly temperature, annual precipitation, and seasonal rainfall distribution demonstrated that even small climate changes might adversely impact aquifer storage conditions at the onset of the dry season. The scale of the change was dependent on the direction (increasing vs. decreasing) and magnitude of climate change (temperature and precipitation). This study demonstrates that small, mountain aquifer characterization is possible using simple water quality parameters, recession analysis can be integrated into modeling aquifer storage parameters, and water balance models can accurately reproduce dry-season discharges and might be useful tools to assess climate change impacts. However, uncertainty in current climate projections and lack of data for testing the predictive capabilities of the model beyond the present data set, make the forecasts of changes in discharge also uncertain. The hydrologic tools used herein offer promise for future research in understanding small, shallow, mountainous aquifers and could potentially be developed and used by water resource professionals to assess climatic influences on local hydrologic systems.

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Agricultural pesticide use has increased worldwide during the last several decades, but the long-term fate, storage, and transfer dynamics of pesticides in a changing environment are poorly understood. Many pesticides have been progressively banned, but in numerous cases, these molecules are stable and may persist in soils, sediments, and ice. Many studies have addressed the question of their possible remobilization as a result of global change. In this article, we present a retro-observation approach based on lake sediment records to monitor micropollutants and to evaluate the long-term succession and diffuse transfer of herbicides, fungicides, and insecticide treatments in a vineyard catchment in France. The sediment allows for a reliable reconstruction of past pesticide use through time, validated by the historical introduction, use, and banning of these organic and inorganic pesticides in local vineyards. Our results also revealed how changes in these practices affect storage conditions and, consequently, the pesticides’ transfer dynamics. For example, the use of postemergence herbicides (glyphosate), which induce an increase in soil erosion, led to a release of a banned remnant pesticide (dichlorodiphenyltrichloro- ethane, DDT), which had been previously stored in vineyard soil, back into the environment. Management strategies of ecotoxico- logical risk would be well served by recognition of the diversity of compounds stored in various environmental sinks, such as agriculture soil, and their capability to become sources when environmental conditions change.

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Dissolved organic matter (DOM) dynamics during storm events has received considerable attention in forested watersheds, but the extent to which storms impart rapid changes in DOM concentration and composition in highly disturbed agricultural watersheds remains poorly understood. In this study, we used identical in situ optical sensors for DOM fluorescence (FDOM) with and without filtration to continuously evaluate surface water DOM dynamics in a 415 km(2) agricultural watershed over a 4 week period containing a short-duration rainfall event. Peak turbidity preceded peak discharge by 4 h and increased by over 2 orders of magnitude, while the peak filtered FDOM lagged behind peak turbidity by 15 h. FDOM values reported using the filtered in situ fluorometer increased nearly fourfold and were highly correlated with dissolved organic carbon (DOC) concentrations (r(2) = 0.97), providing a highly resolved proxy for DOC throughout the study period. Discrete optical properties including specific UV absorbance (SUVA(254)), spectral slope (S(290-350)), and fluorescence index (FI) were also strongly correlated with in situ FDOM and indicate a shift toward aromatic, high molecular weight DOM from terrestrially derived sources during the storm. The lag of the peak in FDOM behind peak discharge presumably reflects the draining of watershed soils from natural and agricultural landscapes. Field and experimental evidence showed that unfiltered FDOM measurements underestimated filtered FDOM concentrations by up to similar to 60% at particle concentrations typical of many riverine systems during hydrologic events. Together, laboratory and in situ data provide insights into the timing and magnitude of changes in DOM quantity and quality during storm events in an agricultural watershed, and indicate the need for sample filtration in systems with moderate to high suspended sediment loads.