891 resultados para large-scale restoration
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Recent large-scale analyses of mainly full-length cDNA libraries generated from a variety of mouse tissues indicated that almost half of all representative cloned sequences did flat contain ail apparent protein-coding sequence, and were putatively derived from non-protein-coding RNA (ncRNA) genes. However, many of these clones were singletons and the majority were unspliced, raising the possibility that they may be derived from genomic DNA or unprocessed pre-rnRNA contamination during library construction, or alternatively represent nonspecific transcriptional noise. Here we Show, using reverse transcriptase-dependent PCR, microarray, and Northern blot analyses, that many of these clones were derived from genuine transcripts Of unknown function whose expression appears to be regulated. The ncRNA transcripts have larger exons and fewer introns than protein-coding transcripts. Analysis of the genomic landscape around these sequences indicates that some cDNA clones were produced not from terminal poly(A) tracts but internal priming sites within longer transcripts, only a minority of which is encompassed by known genes. A significant proportion of these transcripts exhibit tissue-specific expression patterns, as well as dynamic changes in their expression in macrophages following lipopolysaccharide Stimulation. Taken together, the data provide strong support for the conclusion that ncRNAs are an important, regulated component of the mammalian transcriptome.
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As process management projects have increased in size due to globalised and company-wide initiatives, a corresponding growth in the size of process modeling projects can be observed. Despite advances in languages, tools and methodologies, several aspects of these projects have been largely ignored by the academic community. This paper makes a first contribution to a potential research agenda in this field by defining the characteristics of large-scale process modeling projects and proposing a framework of related issues. These issues are derived from a semi -structured interview and six focus groups conducted in Australia, Germany and the USA with enterprise and modeling software vendors and customers. The focus groups confirm the existence of unresolved problems in business process modeling projects. The outcomes provide a research agenda which directs researchers into further studies in global process management, process model decomposition and the overall governance of process modeling projects. It is expected that this research agenda will provide guidance to researchers and practitioners by focusing on areas of high theoretical and practical relevance.
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Le pitture intumescenti sono utilizzate come protettivi passivi antincendio nel settore delle costruzioni. In particolare sono utilizzate per aumentare la resistenza al fuoco di elementi in acciaio. Le proprietà termiche di questi rivestimenti sono spesso sconosciute o difficili da stimare per via del fatto che variano notevolmente durante il processo di espansione che subisce l’intumescente quando esposto al calore di un incendio. Per questa ragione la validazione della resistenza al fuoco di un rivestimento presente in commercio si basa su metodi costosi economicamente e come tempi di esecuzione nel quale ciascuna trave e colonna rivestita di protettivo deve essere testata una alla volta attraverso il test di resistenza al fuoco della curva cellulosica. In questo lavoro di tesi adottando invece un approccio basato sulla modellazione termica del rivestimento intumescente si ottiene un aiuto nella semplificazione della procedura di test ed un supporto nella progettazione della resistenza al fuoco delle strutture. Il tratto di unione nei vari passaggi della presente tesi è stata la metodologia di stima del comportamento termico sconosciuto, tale metodologia di stima è la “Inverse Parameter Estimation”. Nella prima fase vi è stata la caratterizzazione chimico fisica della vernice per mezzo di differenti apparecchiature come la DSC, la TGA e l’FT-IR che ci hanno permesso di ottenere la composizione qualitativa e le temperature a cui avvengono i principali processi chimici e fisici che subisce la pittura come anche le entalpie legate a questi eventi. Nella seconda fase si è proceduto alla caratterizzazione termica delle pitture al fine di ottenerne il valore di conduttività termica equivalente. A tale scopo si sono prima utilizzate le temperature dell’acciaio di prove termiche alla fornace con riscaldamento secondo lo standard ISO-834 e successivamente per meglio definire le condizioni al contorno si è presa come fonte di calore un cono calorimetrico in cui la misura della temperatura avveniva direttamente nello spessore del’intumescente. I valori di conduttività ottenuti sono risultati congruenti con la letteratura scientifica e hanno mostrato la dipendenza della stessa dalla temperatura, mentre si è mostrata poco variante rispetto allo spessore di vernice deposto ed alla geometria di campione utilizzato.
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Rural electrification projects and programmes in many countries have suffered from design, planning, implementation and operational flaws as a result of ineffective project planning and lack of systematic project risk analysis. This paper presents a hierarchical risk-management framework for effectively managing large-scale development projects. The proposed framework first identifies, with the involvement of stakeholders, the risk factors for a rural electrification programme at three different levels (national, state and site). Subsequently it develops a qualitative risk prioritising scheme through probability and severity mapping and provides mitigating measures for most vulnerable risks. The study concludes that the hierarchical risk-management approach provides an effective framework for managing large-scale rural electrification programmes. © IAIA 2007.
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When composing stock portfolios, managers frequently choose among hundreds of stocks. The stocks' risk properties are analyzed with statistical tools, and managers try to combine these to meet the investors' risk profiles. A recently developed tool for performing such optimization is called full-scale optimization (FSO). This methodology is very flexible for investor preferences, but because of computational limitations it has until now been infeasible to use when many stocks are considered. We apply the artificial intelligence technique of differential evolution to solve FSO-type stock selection problems of 97 assets. Differential evolution finds the optimal solutions by self-learning from randomly drawn candidate solutions. We show that this search technique makes large scale problem computationally feasible and that the solutions retrieved are stable. The study also gives further merit to the FSO technique, as it shows that the solutions suit investor risk profiles better than portfolios retrieved from traditional methods.
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An alternative explanation for the modes of failure of large scale failures of open pit walls to those of classical slope stability theory is proposed that makes use of the concept of a transition zone, which is described by a modified Prandtls prism.
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Advances in the area of industrial metrology have generated new technologies that are capable of measuring components with complex geometry and large dimensions. However, no standard or best-practice guides are available for the majority of such systems. Therefore, these new systems require appropriate testing and verification in order for the users to understand their full potential prior to their deployment in a real manufacturing environment. This is a crucial stage, especially when more than one system can be used for a specific measurement task. In this paper, two relatively new large-volume measurement systems, the mobile spatial co-ordinate measuring system (MScMS) and the indoor global positioning system (iGPS), are reviewed. These two systems utilize different technologies: the MScMS is based on ultrasound and radiofrequency signal transmission and the iGPS uses laser technology. Both systems have components with small dimensions that are distributed around the measuring area to form a network of sensors allowing rapid dimensional measurements to be performed in relation to large-size objects, with typical dimensions of several decametres. The portability, reconfigurability, and ease of installation make these systems attractive for many industries that manufacture large-scale products. In this paper, the major technical aspects of the two systems are briefly described and compared. Initial results of the tests performed to establish the repeatability and reproducibility of these systems are also presented. © IMechE 2009.
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Report published in the Proceedings of the National Conference on "Education in the Information Society", Plovdiv, May, 2013
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A multivariate statistical analysis was applied to a 10 year, multiparameter data set in an effort to describe the spatial dependence and inherent variation of water quality patterns in the mangrove estuaries of Ten Thousand Islands – Whitewater Bay area. Principal component analysis (PCA) of 16 water quality parameters collected monthly resulted in five groupings, which explained 72.5% of the variance of the original variables. The “Organic” component (PCI) was composed of alkaline phosphatase activity, total organic nitrogen, and total organic carbon; the “Dissolved Inorganic N” component (PCII) contained NO 3 − , NO 2 − , and NH 4 + ; the “Phytoplankton” component (PCIII) was made up of total phosphorus, chlorophyll a, and turbidity; dissolved oxygen and temperature were inversely related (PCIV); and salinity and soluble reactive phosphorus made up PCV. A cluster analysis of the mean and SD of PC scores resulted in the spatial aggregation of the 47 fixed stations into six classes having similar water quality, which we defined as: Mangrove Rivers, Whitewater Bay, Gulf Islands, Coot Bay, Blackwater River, and Inland Waterway. Marked differences in physical, chemical, and biological characteristics among classes were illustrated by this technique. Comparison of medians and variability of parameters among classes allowed large scale generalizations as to underlying differences in water quality in these regions. A strong south to north gradient in estuaries from high N - low P to low N - high P was ascribed to marked differences in landuse, freshwater input, geomorphology, and sedimentary geology along this tract. The ecological significance of this gradient discussed along with potential effects of future restoration plans.
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Synchronous interannual variability in water transparency observed in neighboring lakes has been linked to regional precipitation and resultant runoff of dissolved organic material, but many climate forcings oscillate over time scales longer than most limnological records can detect. A strong relationship (R2 5 0.86) between transparency and the previous two years’ rainfall and lake stage in a 25-yr record from a Florida lake enabled us to hindcast transparency from a longer 75-yr record of rainfall and lake stage. Predictions revealed a ,30-yr cycle in transparency linked to the Atlantic Multidecadal Oscillation (AMO). Transparency was greatest (4–8 m) in the cool phase of the AMO (,1962–1993) associated with below-average rainfall in south Florida and lowest (0.1– 3.0 m) during two warm phases (,1932–1961, 1994–present) associated with above-average, but more variable, annual rainfall. Models that predict effects of large-scale hydrologic restoration projects on solute export from South Florida’s expansive wetlands need to account for recent entry into a warm AMO phase, where teleconnections between the AMO phases and runoff are opposite of those shown for the U.S. interior.
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Hurricane is one of the most destructive and costly natural hazard to the built environment and its impact on low-rise buildings, particularity, is beyond acceptable. The major objective of this research was to perform a parametric evaluation of internal pressure (IP) for wind-resistant design of low-rise buildings and wind-driven natural ventilation applications. For this purpose, a multi-scale experimental, i.e. full-scale at Wall of Wind (WoW) and small-scale at Boundary Layer Wind Tunnel (BLWT), and a Computational Fluid Dynamics (CFD) approach was adopted. This provided new capability to assess wind pressures realistically on internal volumes ranging from small spaces formed between roof tiles and its deck to attic to room partitions. Effects of sudden breaching, existing dominant openings on building envelopes as well as compartmentalization of building interior on the IP were systematically investigated. Results of this research indicated: (i) for sudden breaching of dominant openings, the transient overshooting response was lower than the subsequent steady state peak IP and internal volume correction for low-wind-speed testing facilities was necessary. For example a building without volume correction experienced a response four times faster and exhibited 30–40% lower mean and peak IP; (ii) for existing openings, vent openings uniformly distributed along the roof alleviated, whereas one sided openings aggravated the IP; (iii) larger dominant openings exhibited a higher IP on the building envelope, and an off-center opening on the wall exhibited (30–40%) higher IP than center located openings; (iv) compartmentalization amplified the intensity of IP and; (v) significant underneath pressure was measured for field tiles, warranting its consideration during net pressure evaluations. The study aimed at wind driven natural ventilation indicated: (i) the IP due to cross ventilation was 1.5 to 2.5 times higher for Ainlet/Aoutlet>1 compared to cases where Ainlet/Aoutlet<1, this in effect reduced the mixing of air inside the building and hence the ventilation effectiveness; (ii) the presence of multi-room partitioning increased the pressure differential and consequently the air exchange rate. Overall good agreement was found between the observed large-scale, small-scale and CFD based IP responses. Comparisons with ASCE 7-10 consistently demonstrated that the code underestimated peak positive and suction IP.
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Physiological processes and local-scale structural dynamics of mangroves are relatively well studied. Regional-scale processes, however, are not as well understood. Here we provide long-term data on trends in structure and forest turnover at a large scale, following hurricane damage in mangrove ecosystems of South Florida, U.S.A. Twelve mangrove vegetation plots were monitored at periodic intervals, between October 1992 and March 2005. Mangrove forests of this region are defined by a −1.5 scaling relationship between mean stem diameter and stem density, mirroring self-thinning theory for mono-specific stands. This relationship is reflected in tree size frequency scaling exponents which, through time, have exhibited trends toward a community average that is indicative of full spatial resource utilization. These trends, together with an asymptotic standing biomass accumulation, indicate that coastal mangrove ecosystems do adhere to size-structured organizing principles as described for upland tree communities. Regenerative dynamics are different between areas inside and outside of the primary wind-path of Hurricane Andrew which occurred in 1992. Forest dynamic turnover rates, however, are steady through time. This suggests that ecological, more-so than structural factors, control forest productivity. In agreement, the relative mean rate of biomass growth exhibits an inverse relationship with the seasonal range of porewater salinities. The ecosystem average in forest scaling relationships may provide a useful investigative tool of mangrove community biomass relationships, as well as offer a robust indicator of general ecosystem health for use in mangrove forest ecosystem management and restoration.
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Florida Bay is a highly dynamic estuary that exhibits wide natural fluctuations in salinity due to changes in the balance of precipitation, evaporation and freshwater runoff from the mainland. Rapid and large-scale modification of freshwater flow and construction of transportation conduits throughout the Florida Keys during the late nineteenth and twentieth centuries reshaped water circulation and salinity patterns across the ecosystem. In order to determine long-term patterns in salinity variation across the Florida Bay estuary, we used a diatom-based salinity transfer function to infer salinity within 3.27 ppt root mean square error of prediction from diatom assemblages from four ~130 year old sediment records. Sites were distributed along a gradient of exposure to anthropogenic shifts in the watershed and salinity. Precipitation was found to be the primary driver influencing salinity fluctuations over the entire record, but watershed modifications on the mainland and in the Florida Keys during the late-1800s and 1900s were the most likely cause of significant shifts in baseline salinity. The timing of these shifts in the salinity baseline varies across the Bay: that of the northeastern coring location coincides with the construction of the Florida Overseas Railway (AD 1906–1916), while that of the east-central coring location coincides with the drainage of Lake Okeechobee (AD 1881–1894). Subsequent decreases occurring after the 1960s (east-central region) and early 1980s (southwestern region) correspond to increases in freshwater delivered through water control structures in the 1950s–1970s and again in the 1980s. Concomitant increases in salinity in the northeastern and south-central regions of the Bay in the mid-1960s correspond to an extensive drought period and the occurrence of three major hurricanes, while the drop in the early 1970s could not be related to any natural event. This paper provides information about major factors influencing salinity conditions in Florida Bay in the past and quantitative estimates of the pre- and post-South Florida watershed modification salinity levels in different regions of the Bay. This information should be useful for environmental managers in setting restoration goals for the marine ecosystems in South Florida, especially for Florida Bay.
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Dissolved organic matter (DOM) is an essential component of the carbon cycle and a critical driver in controlling variety of biogeochemical and ecological processes in wetlands. The quality of this DOM as it relates to composition and reactivity is directly related to its sources and may vary on temporal and spatial scales. However, large scale, long-term studies of DOM dynamics in wetlands are still scarce in the literature. Here we present a multi-year DOM characterization study for monthly surface water samples collected at 14 sampling stations along two transects within the greater Everglades, a subtropical, oligotrophic, coastal freshwater wetland-mangrove-estuarine ecosystem. In an attempt to assess quantitative and qualitative variations of DOM on both spatial and temporal scales, we determined dissolved organic carbon (DOC) values and DOM optical properties, respectively. DOM quality was assessed using, excitation emission matrix (EEM) fluorescence coupled with parallel factor analysis (PARAFAC). Variations of the PARAFAC components abundance and composition were clearly observed on spatial and seasonal scales. Dry versus wet season DOC concentrations were affected by dry-down and re-wetting processes in the freshwater marshes, while DOM compositional features were controlled by soil and higher plant versus periphyton sources respectively. Peat-soil based freshwater marsh sites could be clearly differentiated from marl-soil based sites based on EEM–PARAFAC data. Freshwater marsh DOM was enriched in higher plant and soil-derived humic-like compounds, compared to estuarine sites which were more controlled by algae- and microbial-derived inputs. DOM from fringe mangrove sites could be differentiated between tidally influenced sites and sites exposed to long inundation periods. As such coastal estuarine sites were significantly controlled by hydrology, while DOM dynamics in Florida Bay were seasonally driven by both primary productivity and hydrology. This study exemplifies the application of long term optical properties monitoring as an effective technique to investigate DOM dynamics in aquatic ecosystems. The work presented here also serves as a pre-restoration condition dataset for DOM in the context of the Comprehensive Everglades Restoration Plan (CERP).
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Globally, small-scale fisheries (SSFs) are driven by climate, governance, and market factors of social-ecological change, presenting both challenges and opportunities. The ability of small-scale fishermen and buyers to adapt to changing conditions allows participants to survive economic or environmental disturbances and to benefit from optimal conditions. This study presented here identifies key large-scale factors that drive SSFs in California to shift focus among targets and that dictate long-term trends in landings. We use Elinor Ostrom’s Social-Ecological System (SES) framework to apply an interdisciplinary approach when identifying potential factors and when understanding the complex dynamics of these fisheries. We analyzed the interactions among Monterey Bay SSFs over the past four decades since the passage of the Magnuson Stevens Fisheries Conservation and Management Act of 1976. In this region, the Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), and market squid (Loligo opalescens) fisheries comprise a tightly linked system where shifting focus among fisheries is a key element to adaptive capacity and reduced social and ecological vulnerability. Using a cluster analysis of landings, we identified four modes from 1974 to 2012 that were dominated by squid, sardine, anchovy, or lacked any dominance, enabling us to identify external drivers attributed to a change in fishery dominance during seven distinct transition points. Overall, we show that market and climate factors drive the transitions among dominance modes. Governance phases most dictated long-term trends in landings and are best viewed as a response to changes in perceived biomass and thus a proxy for biomass. Our findings suggest that globally, small-scale fishery managers should consider enabling shifts in effort among fisheries and retaining existing flexibility, as adaptive capacity is a critical determinant for social and ecological resilience.