993 resultados para sub-seasonal prediction


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This paper demonstrates the usefulness of fluorescence techniques for long-term monitoring and assessment of the dynamics (sources, transport and fate) of chromophoric dissolved organic matter (CDOM) in highly compartmentalized estuarine regions with non-point water sources. Water samples were collected monthly from a total of 73 sampling stations in the Florida Coastal Everglades (FCE) estuaries during 2001 and 2002. Spatial and seasonal variability of CDOM characteristics were investigated for geomorphologically distinct sub-regions within Florida Bay (FB), the Ten Thousand Islands (TTI), and Whitewater Bay (WWB). These variations were observed in both quantity and quality of CDOM. TOC concentrations in the FCE estuaries were generally higher during the wet season (June–October), reflecting high freshwater loadings from the Everglades in TTI, and a high primary productivity of marine biomass in FB. Fluorescence parameters suggested that the CDOM in FB is mainly of marine/microbial origin, while for TTI and WWB a terrestrial origin from Everglades marsh plants and mangroves was evident. Variations in CDOM quality seemed mainly controlled by tidal exchange/mixing of Everglades freshwater with Florida Shelf waters, tidally controlled releases of CDOM from fringe mangroves, primary productivity of marine vegetation in FB and diagenetic processes such as photodegradation (particularly for WWB). The source and dynamics of CDOM in these subtropical estuaries is complex and found to be influenced by many factors including hydrology, geomorphology, vegetation cover, landuse and biogeochemical processes. Simple, easy to measure, high sample throughput fluorescence parameters for surface waters can add valuable information on CDOM dynamics to long-term water quality studies which can not be obtained from quantitative determinations alone.

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Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

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The recently proposed global monsoon hypothesis interprets monsoon systems as part of one global-scale atmospheric overturning circulation, implying a connection between the regional monsoon systems and an in-phase behaviour of all northern hemispheric monsoons on annual timescales (Trenberth et al., 2000). Whether this concept can be applied to past climates and variability on longer timescales is still under debate, because the monsoon systems exhibit different regional characteristics such as different seasonality (i.e. onset, peak, and withdrawal). To investigate the interconnection of different monsoon systems during the pre-industrial Holocene, five transient global climate model simulations have been analysed with respect to the rainfall trend and variability in different sub-domains of the Afro-Asian monsoon region. Our analysis suggests that on millennial timescales with varying orbital forcing, the monsoons do not behave as a tightly connected global system. According to the models, the Indian and North African monsoons are coupled, showing similar rainfall trend and moderate correlation in rainfall variability in all models. The East Asian monsoon changes independently during the Holocene. The dissimilarities in the seasonality of the monsoon sub-systems lead to a stronger response of the North African and Indian monsoon systems to the Holocene insolation forcing than of the East Asian monsoon and affect the seasonal distribution of Holocene rainfall variations. Within the Indian and North African monsoon domain, precipitation solely changes during the summer months, showing a decreasing Holocene precipitation trend. In the East Asian monsoon region, the precipitation signal is determined by an increasing precipitation trend during spring and a decreasing precipitation change during summer, partly balancing each other. A synthesis of reconstructions and the model results do not reveal an impact of the different seasonality on the timing of the Holocene rainfall optimum in the different sub-monsoon systems. They rather indicate locally inhomogeneous rainfall changes and show, that single palaeo-records should not be used to characterise the rainfall change and monsoon evolution for entire monsoon sub-systems.

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Inorganic nitrogen depletion restricts productivity in much of the low-latitude oceans, generating a selective advantage for diazotrophic organisms capable of fixing atmospheric dinitrogen (N2). However, the abundance and activity of diazotrophs can in turn be controlled by the availability of other potentially limiting nutrients, including phosphorus (P) and iron (Fe). Here we present high-resolution data (~0.3°) for dissolved iron, aluminum, and inorganic phosphorus that confirm the existence of a sharp north-south biogeochemical boundary in the surface nutrient concentrations of the (sub)tropical Atlantic Ocean. Combining satellite-based precipitation data with results from a previous study, we here demonstrate that wet deposition in the region of the intertropical convergence zone acts as the major dissolved iron source to surface waters. Moreover, corresponding observations of N2 fixation and the distribution of diazotrophic Trichodesmium spp. indicate that movement in the region of elevated dissolved iron as a result of the seasonal migration of the intertropical convergence zone drives a shift in the latitudinal distribution of diazotrophy and corresponding dissolved inorganic phosphorus depletion. These conclusions are consistent with the results of an idealized numerical model of the system. The boundary between the distinct biogeochemical systems of the (sub)tropical Atlantic thus appears to be defined by the diazotrophic response to spatial-temporal variability in external Fe inputs. Consequently, in addition to demonstrating a unique seasonal cycle forced by atmospheric nutrient inputs, we suggest that the underlying biogeochemical mechanisms would likely characterize the response of oligotrophic systems to altered environmental forcing over longer timescales.

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Background: Interventions to increase cooking skills (CS) and food skills (FS) as a route to improving overall diet are popular within public health. This study tested a comprehensive model of diet quality by assessing the influence of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. The correspondence of two measures of diet quality further validated the Eating Choices Index (ECI) for use in quantitative research.
Methods: A cross-sectional survey was conducted in a quota-controlled nationally representative sample of 1049 adults aged 20–60 years drawn from the Island of Ireland. Surveys were administered in participants’ homes via computer-assisted personal interviewing (CAPI) assessing a range of socio-demographic, knowledge- and psychological-related variables alongside perceived CS and FS abilities. Regression models were used to model factors influencing diet quality. Correspondence between 2 measures of diet quality was assessed using chi-square and Pearson correlations.
Results: ECI score was significantly negatively correlated with DINE Fat intake (r = -0.24, p < 0.001), and ECI score was significantly positively correlated with DINE Fibre intake (r = 0.38, p < 0.001), demonstrating a high agreement. Findings indicated that males, younger respondents and those with no/few educational qualifications scored significantly lower on both CS and FS abilities. The relative influence of socio-demographic, knowledge, psychological variables and CS and FS abilities on dietary outcomes varied, with regression models explaining 10–20 % of diet quality variance. CS ability exerted the strongest relationship with saturated fat intake (β = -0.296, p < 0.001) and was a significant predictor of fibre intake (β = -0.113, p < 0.05), although not for healthy food choices (ECI) (β = 0.04, p > 0.05).
Conclusion: Greater CS and FS abilities may not lead directly to healthier dietary choices given the myriad of other factors implicated; however, CS appear to have differential influences on aspects of the diet, most notably in relation to lowering saturated fat intake. Findings suggest that CS and FS should not be singular targets of interventions designed to improve diet; but targeting specific sub-groups of the population e.g. males, younger adults, those with limited education might be more fruitful. A greater understanding of the interaction of factors influencing cooking and food practices within the home is needed.

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The Behavioral Finance develop as it is perceived anomalies in these markets efficient. This fields of study can be grouped into three major groups: heuristic bias, tying the shape and inefficient markets. The present study focuses on issues concerning the heuristics of representativeness and anchoring. This study aimed to identify the then under-reaction and over-reaction, as well as the existence of symmetry in the active first and second line of the Brazilian stock market. For this, it will be use the Fuzzy Logic and the indicators that classify groups studied from the Discriminant Analysis. The highest present, indicator in the period studied, was the Liabilities / Equity, demonstrating the importance of the moment to discriminate the assets to be considered "winners" and "losers." Note that in the MLCX biases over-reaction is concentrated in the period of financial crisis, and in the remaining periods of statistically significant biases, are obtained by sub-reactions. The latter would be in times of moderate levels of uncertainty. In the Small Caps the behavioral responses in 2005 and 2007 occur in reverse to those observed in the Mid-Large Cap. Now in times of crisis would have a marked conservatism while near the end of trading on the Bovespa speaker, accompanied by an increase of negotiations, there is an overreaction by investors. The other heuristics in SMLL occurred at the end of the period studied, this being a under-reaction and the other a over-reaction and the second occurring in a period of financial-economic more positive than the first. As regards the under / over-reactivity in both types, there is detected a predominance of either, which probably be different in the context in MLCX without crisis. For the period in which such phenomena occur in a statistically significant to note that, in most cases, such phenomena occur during the periods for MLCX while in SMLL not only biases are less present as there is no concentration of these at any time . Given the above, it is believed that while detecting the presence of bias behavior at certain times, these do not tend to appear to a specific type or heuristics and while there were some indications of a seasonal pattern in Mid- Large Caps, the same behavior does not seem to be repeated in Small Caps. The tests would then suggest that momentary failures in the Efficient Market Hypothesis when tested in semistrong form as stated by Behavioral Finance. This result confirms the theory by stating that not only rationality, but also human irrationality, is limited because it would act rationally in many circumstances

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Caspian Sea with its unique characteristics is a significant source to supply required heat and moisture for passing weather systems over the north of Iran. Investigation of heat and moisture fluxes in the region and their effects on these systems that could lead to floods and major financial and human losses is essential in weather forecasting. Nowadays by improvement of numerical weather and climate prediction models and the increasing need to more accurate forecasting of heavy rainfall, the evaluation and verification of these models has been become much more important. In this study we have used the WRF model as a research-practical one with many valuable characteristics and flexibilities. In this research, the effects of heat and moisture fluxes of Caspian Sea on the synoptic and dynamical structure of 20 selective systems associated with heavy rainfall in the southern shores of Caspian Sea are investigated. These systems are selected based on the rainfall data gathered by three local stations named: Rasht, Babolsar and Gorgan in different seasons during a five-year period (2005-2010) with maximum amount of rainfall through the 24 hours of a day. In addition to synoptic analyses of these systems, the WRF model with and without surface flues was run using the two nested grids with the horizontal resolutions of 12 and 36 km. The results show that there are good consistencies between the predicted distribution of rainfall field, time of beginning and end of rainfall by the model and the observations. But the model underestimates the amounts of rainfall and the maximum difference with the observation is about 69%. Also, no significant changes in the results are seen when the domain and the resolution of computations are changed. The other noticeable point is that the systems are severely weakened by removing heat and moisture fluxes and thereby the amounts of large scale rainfall are decreased up to 77% and the convective rainfalls tend to zero.

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The Behavioral Finance develop as it is perceived anomalies in these markets efficient. This fields of study can be grouped into three major groups: heuristic bias, tying the shape and inefficient markets. The present study focuses on issues concerning the heuristics of representativeness and anchoring. This study aimed to identify the then under-reaction and over-reaction, as well as the existence of symmetry in the active first and second line of the Brazilian stock market. For this, it will be use the Fuzzy Logic and the indicators that classify groups studied from the Discriminant Analysis. The highest present, indicator in the period studied, was the Liabilities / Equity, demonstrating the importance of the moment to discriminate the assets to be considered "winners" and "losers." Note that in the MLCX biases over-reaction is concentrated in the period of financial crisis, and in the remaining periods of statistically significant biases, are obtained by sub-reactions. The latter would be in times of moderate levels of uncertainty. In the Small Caps the behavioral responses in 2005 and 2007 occur in reverse to those observed in the Mid-Large Cap. Now in times of crisis would have a marked conservatism while near the end of trading on the Bovespa speaker, accompanied by an increase of negotiations, there is an overreaction by investors. The other heuristics in SMLL occurred at the end of the period studied, this being a under-reaction and the other a over-reaction and the second occurring in a period of financial-economic more positive than the first. As regards the under / over-reactivity in both types, there is detected a predominance of either, which probably be different in the context in MLCX without crisis. For the period in which such phenomena occur in a statistically significant to note that, in most cases, such phenomena occur during the periods for MLCX while in SMLL not only biases are less present as there is no concentration of these at any time . Given the above, it is believed that while detecting the presence of bias behavior at certain times, these do not tend to appear to a specific type or heuristics and while there were some indications of a seasonal pattern in Mid- Large Caps, the same behavior does not seem to be repeated in Small Caps. The tests would then suggest that momentary failures in the Efficient Market Hypothesis when tested in semistrong form as stated by Behavioral Finance. This result confirms the theory by stating that not only rationality, but also human irrationality, is limited because it would act rationally in many circumstances

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Biogeochemical-Argo is the extension of the Argo array of profiling floats to include floats that are equipped with biogeochemical sensors for pH, oxygen, nitrate, chlorophyll, suspended particles, and downwelling irradiance. Argo is a highly regarded, international program that measures the changing ocean temperature (heat content) and salinity with profiling floats distributed throughout the ocean. Newly developed sensors now allow profiling floats to also observe biogeochemical properties with sufficient accuracy for climate studies. This extension of Argo will enable an observing system that can determine the seasonal to decadal-scale variability in biological productivity, the supply of essential plant nutrients from deep-waters to the sunlit surface layer, ocean acidification, hypoxia, and ocean uptake of CO2. Biogeochemical-Argo will drive a transformative shift in our ability to observe and predict the effects of climate change on ocean metabolism, carbon uptake, and living marine resource management. Presently, vast areas of the open ocean are sampled only once per decade or less, with sampling occurring mainly in summer. Our ability to detect changes in biogeochemical processes that may occur due to the warming and acidification driven by increasing atmospheric CO2, as well as by natural climate variability, is greatly hindered by this undersampling. In close synergy with satellite systems (which are effective at detecting global patterns for a few biogeochemical parameters, but only very close to the sea surface and in the absence of clouds), a global array of biogeochemical sensors would revolutionize our understanding of ocean carbon uptake, productivity, and deoxygenation. The array would reveal the biological, chemical, and physical events that control these processes. Such a system would enable a new generation of global ocean prediction systems in support of carbon cycling, acidification, hypoxia and harmful algal blooms studies, as well as the management of living marine resources. In order to prepare for a global Biogeochemical-Argo array, several prototype profiling float arrays have been developed at the regional scale by various countries and are now operating. Examples include regional arrays in the Southern Ocean (SOCCOM ), the North Atlantic Sub-polar Gyre (remOcean ), the Mediterranean Sea (NAOS ), the Kuroshio region of the North Pacific (INBOX ), and the Indian Ocean (IOBioArgo ). For example, the SOCCOM program is deploying 200 profiling floats with biogeochemical sensors throughout the Southern Ocean, including areas covered seasonally with ice. The resulting data, which are publically available in real time, are being linked with computer models to better understand the role of the Southern Ocean in influencing CO2 uptake, biological productivity, and nutrient supply to distant regions of the world ocean. The success of these regional projects has motivated a planning meeting to discuss the requirements for and applications of a global-scale Biogeochemical-Argo program. The meeting was held 11-13 January 2016 in Villefranche-sur-Mer, France with attendees from eight nations now deploying Argo floats with biogeochemical sensors present to discuss this topic. In preparation, computer simulations and a variety of analyses were conducted to assess the resources required for the transition to a global-scale array. Based on these analyses and simulations, it was concluded that an array of about 1000 biogeochemical profiling floats would provide the needed resolution to greatly improve our understanding of biogeochemical processes and to enable significant improvement in ecosystem models. With an endurance of four years for a Biogeochemical-Argo float, this system would require the procurement and deployment of 250 new floats per year to maintain a 1000 float array. The lifetime cost for a Biogeochemical-Argo float, including capital expense, calibration, data management, and data transmission, is about $100,000. A global Biogeochemical-Argo system would thus cost about $25,000,000 annually. In the present Argo paradigm, the US provides half of the profiling floats in the array, while the EU, Austral/Asia, and Canada share most the remaining half. If this approach is adopted, the US cost for the Biogeochemical-Argo system would be ~$12,500,000 annually and ~$6,250,000 each for the EU, and Austral/Asia and Canada. This includes no direct costs for ship time and presumes that float deployments can be carried out from future research cruises of opportunity, including, for example, the international GO-SHIP program (http://www.go-ship.org). The full-scale implementation of a global Biogeochemical-Argo system with 1000 floats is feasible within a decade. The successful, ongoing pilot projects have provided the foundation and start for such a system.

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We used 2012 sap flow measurements to assess the seasonal dynamics of daily plant transpiration (ETc) in a high-density olive orchard (Olea europaea L. cv. ‘Arbequina’) with a well-watered (HI) control treatment A to supply 100 % of the crop water needs, and a moderately (MI) watered treatment B that replaced 70% of crop needs. To assure that treatment A was well-watered, we compared field daily ETc values against ETc obtained with the Penman-Monteith (PM) combination equation incorporating the Orgaz et al. (2007) bulk daily canopy conductance (gc) model, validated for our non-limiting conditions. We then tested the hypothesis of indirectly monitoring olive ETc from readily available vegetation index (VI) and ground-based plant water stress indicator. In the process we used the FAO56 dual crop coefficient (Kc) approach. For the HI olive trees we defined Kcb as the basal transpiration coefficient, and we related Kcb to remotely sensed Soil Adjusted Vegetation Index (SAVI) through a Kcb-SAVI functional relationship. For the MI treatment, we defined the actual transpiration ETc as the product of Kcb and the stress reduction coefficient Ks obtained as the ratio of actual to crop ETc, and we correlated Ks with MI midday stem water potential (ψst) values through a Ks-ψ functional relationship. Operational monitoring of ETc was then implemented with the ETc = Kcb(SAVI)Ks(ψ)ETo relationship stemmed from the FAO56 approach and validated taking as inputs collected SAVI and ψst data reporting to year 2011. Low validation error (6%) and high goodness-of-fit of prediction were observed (R2 = 0.94, RSME = 0.2 mm day-1, P = 0.0015), allowing to consider that under field conditions it is possible to predict ETc values for our hedgerow olive orchards if SAVI and water potential (ψst) values are known.

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In this Thesis a series of numerical models for the evaluation of the seasonal performance of reversible air-to-water heat pump systems coupled to residential and non-residential buildings are presented. The exploitation of the energy saving potential linked to the adoption of heat pumps is a hard task for designers due to the influence on their energy performance of several factors, like the external climate variability, the heat pump modulation capacity, the system control strategy and the hydronic loop configuration. The aim of this work is to study in detail all these aspects. In the first part of this Thesis a series of models which use a temperature class approach for the prediction of the seasonal performance of reversible air source heat pumps are shown. An innovative methodology for the calculation of the seasonal performance of an air-to-water heat pump has been proposed as an extension of the procedure reported by the European standard EN 14825. This methodology can be applied not only to air-to-water single-stage heat pumps (On-off HPs) but also to multi-stage (MSHPs) and inverter-driven units (IDHPs). In the second part, dynamic simulation has been used with the aim to optimize the control systems of the heat pump and of the HVAC plant. A series of dynamic models, developed by means of TRNSYS, are presented to study the behavior of On-off HPs, MSHPs and IDHPs. The main goal of these dynamic simulations is to show the influence of the heat pump control strategies and of the lay-out of the hydronic loop used to couple the heat pump to the emitters on the seasonal performance of the system. A particular focus is given to the modeling of the energy losses linked to on-off cycling.

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The aim of this work is focused on the extraction and characterization of the Brazilian seaweed Sargassum filipendula alginate. Alginates obtained at different seasons were characterized by liquid state nuclear magnetic resonance spectroscopy and scanning electron microscopy. The alginate extraction efficiency was about 20%. Different seasons of the year and different stages in the life cycle of Sargassum sp. in southeastern Brazil influenced the M/G and, consequently, the technological properties of extracted alginates.

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New DNA-based predictive tests for physical characteristics and inference of ancestry are highly informative tools that are being increasingly used in forensic genetic analysis. Two eye colour prediction models: a Bayesian classifier - Snipper and a multinomial logistic regression (MLR) system for the Irisplex assay, have been described for the analysis of unadmixed European populations. Since multiple SNPs in combination contribute in varying degrees to eye colour predictability in Europeans, it is likely that these predictive tests will perform in different ways amongst admixed populations that have European co-ancestry, compared to unadmixed Europeans. In this study we examined 99 individuals from two admixed South American populations comparing eye colour versus ancestry in order to reveal a direct correlation of light eye colour phenotypes with European co-ancestry in admixed individuals. Additionally, eye colour prediction following six prediction models, using varying numbers of SNPs and based on Snipper and MLR, were applied to the study populations. Furthermore, patterns of eye colour prediction have been inferred for a set of publicly available admixed and globally distributed populations from the HGDP-CEPH panel and 1000 Genomes databases with a special emphasis on admixed American populations similar to those of the study samples.

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Negative-ion mode electrospray ionization, ESI(-), with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) was coupled to a Partial Least Squares (PLS) regression and variable selection methods to estimate the total acid number (TAN) of Brazilian crude oil samples. Generally, ESI(-)-FT-ICR mass spectra present a power of resolution of ca. 500,000 and a mass accuracy less than 1 ppm, producing a data matrix containing over 5700 variables per sample. These variables correspond to heteroatom-containing species detected as deprotonated molecules, [M - H](-) ions, which are identified primarily as naphthenic acids, phenols and carbazole analog species. The TAN values for all samples ranged from 0.06 to 3.61 mg of KOH g(-1). To facilitate the spectral interpretation, three methods of variable selection were studied: variable importance in the projection (VIP), interval partial least squares (iPLS) and elimination of uninformative variables (UVE). The UVE method seems to be more appropriate for selecting important variables, reducing the dimension of the variables to 183 and producing a root mean square error of prediction of 0.32 mg of KOH g(-1). By reducing the size of the data, it was possible to relate the selected variables with their corresponding molecular formulas, thus identifying the main chemical species responsible for the TAN values.