1000 resultados para léxico temporal


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This work examines stable isotope ratios of carbon, oxygen and hydrogen in annual growth rings of trees. Isotopic composition in wood cellulose is used as a tool to study past climate. The method benefits from the accurate and precise dating provided by dendrochronology. In this study the origin, nature and the strength of climatic correlations are studied on different temporal scales and at different sites in Finland. The origin of carbon isotopic signal is in photosynthetic fractionation. The basic physical and chemical fractionations involved are reasonably well understood. This was confirmed by measuring instantaneous photosynthetic discrimination on Scots pine (Pinus sylvestris L.). The internal conductance of CO2 was recognized to have a significant impact on the observed fractionation, and further investigations are suggested to quantify its role in controlling the isotopic signal of photosynthates. Isotopic composition of the produced biomass can potentially be affected by variety of external factors that induce physiological changes in trees. Response of carbon isotopic signal in tree ring cellulose to changes in resource availability was assessed in a manipulation experiment. It showed that the signal was relatively stable despite of changes in water and nitrogen availability to the tree. Palaeoclimatic reconstructions are typically based on functions describing empirical relationship between isotopic and climatic parameters. These empirical relationships may change depending on the site conditions, species and timeframe studied. Annual variation in Scots pine tree ring carbon and oxygen isotopic composition was studied in northern and in central eastern Finland and annual variation in tree ring latewood carbon, oxygen and hydrogen isotopic ratio in Oak (Quercus robur L.) was studied in southern Finland. In all of the studied sites at least one of the studied isotope ratios was shown to record climate strongly enough to be used in climatic reconstructions. Using the observed relationships, four-century-long climate reconstructions from living Scots pine were created for northern and central eastern Finland. Also temporal stability of the relationships between three proxy indicators, tree ring growth and carbon and oxygen isotopic composition was studied during the four-hundred-year period. Isotope ratios measured from tree rings in Finland were shown to be sensitive indicators of climate. Increasing understanding of environmental controls and physiological mechanisms affecting tree ring isotopic composition will make possible more accurate interpretation of isotope data. This study also demonstrated that by measuring multiple isotopes and physical proxies from the same tree rings, additional information on tree physiology can be obtained. Thus isotopic ratios measured from tree ring cellulose provide means to improve the reliability of climate reconstructions.

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In a complex multitrophic plant-animal interaction system in which there are direct and indirect interactions between species, comprehending the dynamics of these multiple partners is very important for an understanding of how the system is structured. We investigated the plant Ficus racemosa L. (Moraceae) and its community of obligatory mutualistic and parasitic fig wasps (Hymenoptera: Chalcidoidea) that develop within the fig inflorescence or syconium, as well as their interaction with opportunistic ants. We focused on temporal resource partitioning among members of the fig wasp community over the development cycle of the fig syconia during which wasp oviposition and development occur and we studied the activity rhythm of the ants associated with this community. We found that the seven members of the wasp community partitioned their oviposition across fig syconium development phenology and showed interspecific variation in activity across the day-night cycle. The wasps presented a distinct sequence in their arrival at fig syconia for oviposition, with the parasitoid wasps following the galling wasps. Although fig wasps are known to be largely diurnal, we documented night oviposition in several fig wasp species for the first time. Ant activity on the fig syconia was correlated with wasp activity and was dependent on whether the ants were predatory or trophobiont-tending species; only numbers of predatory ants increased during peak arrivals of the wasps.

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A method was developed for relative radiometric calibration of single multitemporal Landsat TM image, several multitemporal images covering each others, and several multitemporal images covering different geographic locations. The radiometricly calibrated difference images were used for detecting rapid changes on forest stands. The nonparametric Kernel method was applied for change detection. The accuracy of the change detection was estimated by inspecting the image analysis results in field. The change classification was applied for controlling the quality of the continuously updated forest stand information. The aim was to ensure that all the manmade changes and any forest damages were correctly updated including the attribute and stand delineation information. The image analysis results were compared with the registered treatments and the stand information base. The stands with discrepancies between these two information sources were recommended to be field inspected.

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Two vitellins, VtA and VtB, were purified from the eggs of Dysdercus koenigii by gel filtration and ion exchange chromatography. VtA and VtB have molecular weights of 290 and 260 kDa, respectively. Both Vts are glycolipoproteinaceous in nature. VtA is composed of three polypeptides of M-r 116, 92 and 62 kDa while VtB contained an additional subunit of M-r 40 kDa. All subunits except the 116-kDa subunit are glycolipopolypeptides. Polyclonal antibody raised against VtA (anti-VtA antibody) cross-reacted with VtB and also with vitellogenic haemolymph and ovaries and pre-vitellogenic fat bodies, but not with haemolymph from either adult male, fifth instar female, or pre-vitellogenic females demonstrating sex and stage specificity of the Vts. Immunoblots in the presence of anti-VtA revealed two proteins (of 290 and 260 kDa) in both vitellogenic haemolymph and pre-vitellogenic fat bodies that are recognised as D. koenigii Vgs. In newly emerged females, Vgs appeared on day 1 in fat bodies and on day 3 in haemolymph and ovaries. Vg concentration was maximum on day 2 in fat body, day 4 in haemolymph and day 7 in ovary. Although the biochemical and temporal characteristics of these proteins show similarity to some hemipterans, they are strikingly dissimilar with those of a very closely related species. (C) 1999 Elsevier Science Inc. All rights reserved.

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A framework based on the notion of "conflict-tolerance" was proposed in as a compositional methodology for developing and reasoning about systems that comprise multiple independent controllers. A central notion in this framework is that of a "conflict-tolerant" specification for a controller. In this work we propose a way of defining conflict-tolerant real-time specifications in Metric Interval Temporal Logic (MITL). We call our logic CT-MITL for Conflict-Tolerant MITL. We then give a clock optimal "delay-then-extend" construction for building a timed transition system for monitoring past-MITL formulas. We show how this monitoring transition system can be used to solve the associated verification and synthesis problems for CT-MITL.

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Background: Temporal analysis of gene expression data has been limited to identifying genes whose expression varies with time and/or correlation between genes that have similar temporal profiles. Often, the methods do not consider the underlying network constraints that connect the genes. It is becoming increasingly evident that interactions change substantially with time. Thus far, there is no systematic method to relate the temporal changes in gene expression to the dynamics of interactions between them. Information on interaction dynamics would open up possibilities for discovering new mechanisms of regulation by providing valuable insight into identifying time-sensitive interactions as well as permit studies on the effect of a genetic perturbation. Results: We present NETGEM, a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions between proteins based on the dynamics of the expression changes of the genes that encode them. The model treats the interaction strengths as random variables which are modulated by suitable priors. This approach is necessitated by the extremely small sample size of the datasets, relative to the number of interactions. The model is amenable to a linear time algorithm for efficient inference. Using temporal gene expression data, NETGEM was successful in identifying (i) temporal interactions and determining their strength, (ii) functional categories of the actively interacting partners and (iii) dynamics of interactions in perturbed networks. Conclusions: NETGEM represents an optimal trade-off between model complexity and data requirement. It was able to deduce actively interacting genes and functional categories from temporal gene expression data. It permits inference by incorporating the information available in perturbed networks. Given that the inputs to NETGEM are only the network and the temporal variation of the nodes, this algorithm promises to have widespread applications, beyond biological systems. The source code for NETGEM is available from https://github.com/vjethava/NETGEM

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Over past few years, the studies of cultured neuronal networks have opened up avenues for understanding the ion channels, receptor molecules, and synaptic plasticity that may form the basis of learning and memory. The hippocampal neurons from rats are dissociated and cultured on a surface containing a grid of 64 electrodes. The signals from these 64 electrodes are acquired using a fast data acquisition system MED64 (Alpha MED Sciences, Japan) at a sampling rate of 20 K samples with a precision of 16-bits per sample. A few minutes of acquired data runs in to a few hundreds of Mega Bytes. The data processing for the neural analysis is highly compute-intensive because the volume of data is huge. The major processing requirements are noise removal, pattern recovery, pattern matching, clustering and so on. In order to interface a neuronal colony to a physical world, these computations need to be performed in real-time. A single processor such as a desk top computer may not be adequate to meet this computational requirements. Parallel computing is a method used to satisfy the real-time computational requirements of a neuronal system that interacts with an external world while increasing the flexibility and scalability of the application. In this work, we developed a parallel neuronal system using a multi-node Digital Signal processing system. With 8 processors, the system is able to compute and map incoming signals segmented over a period of 200 ms in to an action in a trained cluster system in real time.

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Bangalore is experiencing unprecedented urbanisation in recent times due to concentrated developmental activities with impetus on IT (Information Technology) and BT (Biotechnology) sectors. The concentrated developmental activities has resulted in the increase in population and consequent pressure on infrastructure, natural resources, ultimately giving rise to a plethora of serious challenges such as urban flooding, climate change, etc. One of the perceived impact at local levels is the increase in sensible heat flux from the land surface to the atmosphere, which is also referred as heat island effect. In this communication, we report the changes in land surface temperature (LST) with respect to land cover changes during 1973 to 2007. A novel technique combining the information from sub-pixel class proportions with information from classified image (using signatures of the respective classes collected from the ground) has been used to achieve more reliable classification. The analysis showed positive correlation with the increase in paved surfaces and LST. 466% increase in paved surfaces (buildings, roads, etc.) has lead to the increase in LST by about 2 ºC during the last 2 decades, confirming urban heat island phenomenon. LSTs’ were relatively lower (~ 4 to 7 ºC) at land uses such as vegetation (parks/forests) and water bodies which act as heat sinks.

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Various logical formalisms with the freeze quantifier have been recently considered to model computer systems even though this is a powerful mechanism that often leads to undecidability. In this paper, we study a linear-time temporal logic with past-time operators such that the freeze operator is only used to express that some value from an infinite set is repeated in the future or in the past. Such a restriction has been inspired by a recent work on spatio-temporal logics. We show decidability of finitary and infinitary satisfiability by reduction into the verification of temporal properties in Petri nets. This is a surprising result since the logic is closed under negation, contains future-time and past-time temporal operators and can express the nonce property and its negation. These ingredients are known to lead to undecidability with a more liberal use of the freeze quantifier.

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We address the problem of estimating the fundamental frequency of voiced speech. We present a novel solution motivated by the importance of amplitude modulation in sound processing and speech perception. The new algorithm is based on a cumulative spectrum computed from the temporal envelope of various subbands. We provide theoretical analysis to derive the new pitch estimator based on the temporal envelope of the bandpass speech signal. We report extensive experimental performance for synthetic as well as natural vowels for both realworld noisy and noise-free data. Experimental results show that the new technique performs accurate pitch estimation and is robust to noise. We also show that the technique is superior to the autocorrelation technique for pitch estimation.

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Natural hazards such as landslides are triggered by numerous factors such as ground movements, rock falls, slope failure, debris flows, slope instability, etc. Changes in slope stability happen due to human intervention, anthropogenic activities, change in soil structure, loss or absence of vegetation (changes in land cover), etc. Loss of vegetation happens when the forest is fragmented due to anthropogenic activities. Hence land cover mapping with forest fragmentation can provide vital information for visualising the regions that require immediate attention from slope stability aspects. The main objective of this paper is to understand the rate of change in forest landscape from 1973 to 2004 through multi-sensor remote sensing data analysis. The forest fragmentation index presented here is based on temporal land use information and forest fragmentation model, in which the forest pixels are classified as patch, transitional, edge, perforated, and interior, that give a measure of forest continuity. The analysis carried out for five prominent watersheds of Uttara Kannada district– Aganashini, Bedthi, Kali, Sharavathi and Venkatpura revealed that interior forest is continuously decreasing while patch, transitional, edge and perforated forest show increasing trend. The effect of forest fragmentation on landslide occurrence was visualised by overlaying the landslide occurrence points on classified image and forest fragmentation map. The increasing patch and transitional forest on hill slopes are the areas prone to landslides, evident from the field verification, indicating that deforestation is a major triggering factor for landslides. This emphasises the need for immediate conservation measures for sustainable management of the landscape. Quantifying and describing land use - land cover change and fragmentation is crucial for assessing the effect of land management policies and environmental protection decisions.

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Data mining is concerned with analysing large volumes of (often unstructured) data to automatically discover interesting regularities or relationships which in turn lead to better understanding of the underlying processes. The field of temporal data mining is concerned with such analysis in the case of ordered data streams with temporal interdependencies. Over the last decade many interesting techniques of temporal data mining were proposed and shown to be useful in many applications. Since temporal data mining brings together techniques from different fields such as statistics, machine learning and databases, the literature is scattered among many different sources. In this article, we present an overview of techniques of temporal data mining.We mainly concentrate on algorithms for pattern discovery in sequential data streams.We also describe some recent results regarding statistical analysis of pattern discovery methods.

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A method, system, and computer program product for fault data correlation in a diagnostic system are provided. The method includes receiving the fault data including a plurality of faults collected over a period of time, and identifying a plurality of episodes within the fault data, where each episode includes a sequence of the faults. The method further includes calculating a frequency of the episodes within the fault data, calculating a correlation confidence of the faults relative to the episodes as a function of the frequency of the episodes, and outputting a report of the faults with the correlation confidence.