998 resultados para Flooding events


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Long-wave dynamics of the interannual variations of the equatorial Indian Ocean circulation are studied using an ocean general circulation model forced by the assimilated surface winds and heat flux of the European Centre for Medium-Range Weather Forecasts. The simulation has reproduced the sea level anomalies of the Ocean Topography Experiment (TOPEX)/Poseidon altimeter observations well. The equatorial Kelvin and Rossby waves decomposed from the model simulation show that western boundary reflections provide important negative feedbacks to the evolution of the upwelling currents off the Java coast during Indian Ocean dipole (IOD) events. Two downwelling Kelvin wave pulses are generated at the western boundary during IOD events: the first is reflected from the equatorial Rossby waves and the second from the off-equatorial Rossby waves in the southern Indian Ocean. The upwelling in the eastern basin during the 1997-98 IOD event is weakened by the first Kelvin wave pulse and terminated by the second. In comparison, the upwelling during the 1994 IOD event is terminated by the first Kelvin wave pulse because the southeasterly winds off the Java coast are weak at the end of 1994. The atmospheric intraseasonal forcing, which plays an important role in inducing Java upwelling during the early stage of an IOD event, is found to play a minor role in terminating the upwelling off the Java coast because the intraseasonal winds are either weak or absent during the IOD mature phase. The equatorial wave analyses suggest that the upwelling off the Java coast during IOD events is terminated primarily by western boundary reflections.

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With the intermediate-complexity Zebiak-Cane model, we investigate the 'spring predictability barrier' (SPB) problem for El Nino events by tracing the evolution of conditional nonlinear optimal perturbation (CNOP), where CNOP is superimposed on the El Nino events and acts as the initial error with the biggest negative effect on the El Nino prediction. We show that the evolution of CNOP-type errors has obvious seasonal dependence and yields a significant SPB, with the most severe occurring in predictions made before the boreal spring in the growth phase of El Nino. The CNOP-type errors can be classified into two types: one possessing a sea-surface-temperature anomaly pattern with negative anomalies in the equatorial central-western Pacific, positive anomalies in the equatorial eastern Pacific, and a thermocline depth anomaly pattern with positive anomalies along the Equator, and another with patterns almost opposite to those of the former type. In predictions through the spring in the growth phase of El Nino, the initial error with the worst effect on the prediction tends to be the latter type of CNOP error, whereas in predictions through the spring in the decaying phase, the initial error with the biggest negative effect on the prediction is inclined to be the former type of CNOP error. Although the linear singular vector (LSV)-type errors also have patterns similar to the CNOP-type errors, they cover a more localized area than the CNOP-type errors and cause a much smaller prediction error, yielding a less significant SPB. Random errors in the initial conditions are also superimposed on El Nino events to investigate the SPB. We find that, whenever the predictions start, the random errors neither exhibit an obvious season-dependent evolution nor yield a large prediction error, and thus may not be responsible for the SPB phenomenon for El Nino events. These results suggest that the occurrence of the SPB is closely related to particular initial error patterns. The two kinds of CNOP-type error are most likely to cause a significant SPB. They have opposite signs and, consequently, opposite growth behaviours, a result which may demonstrate two dynamical mechanisms of error growth related to SPB: in one case, the errors grow in a manner similar to El Nino; in the other, the errors develop with a tendency opposite to El Nino. The two types of CNOP error may be most likely to provide the information regarding the 'sensitive area' of El Nino-Southern Oscillation (ENSO) predictions. If these types of initial error exist in realistic ENSO predictions and if a target method or a data assimilation approach can filter them, the ENSO forecast skill may be improved. Copyright (C) 2009 Royal Meteorological Society

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The economic loss caused by the storm surge disasters is much higher than that caused by any other marine disaster in China, the loss from the severe storm surge disaster being the highest. Statistics show that there were 62 typhoon landings over the east-southeast coast of China since 1990, three of which, occurring in 1992, 1994 and 1997, respectively, caused the most severe damage. The direct economic losses due to these events are 9.3, 17.0 and 30 billion yuan (RMB, or about 1.7, 2.6 and 3.8 billion USD, respectively), which is much greater than the loss of 5.5 billion yuan (RMB) on an average every year during the 1989-1991 period. This paper makes a comparative analysis of the damage caused by the three events and presents an overview of progress of precautions against storm surge disaster in China. The suggested counter measures to mitigate the loss from the severe storm surge disasters in China is as follows: (1) Raise the whole society awareness of precaution against severe storm surge disaster; (2) Work out a new plan for building sea walls; (3) Improve and perfect the available warning and disaster relief command system; (4) Develop the insurance service in order to promptly mitigate the loss caused by severe storm surge disaster event.

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Bewsher, D., Innes, D.E., Parnell, C.E. and Brown, D.S., 2005, Comparison of blinkers and explosive events, Astronomy and Astrophysics, 432, 307. Sponsorship: PPARC

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$u http://books.google.com/books?vid=OCLC02623863&id=mQz8gPn0et8C&a_sbrr=1 View book via Google

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http://www.archive.org/details/bibleworkinbible00birduoft

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Working memory neural networks are characterized which encode the invariant temporal order of sequential events that may be presented at widely differing speeds, durations, and interstimulus intervals. This temporal order code is designed to enable all possible groupings of sequential events to be stably learned and remembered in real time, even as new events perturb the system. Such a competence is needed in neural architectures which self-organize learned codes for variable-rate speech perception, sensory-motor planning, or 3-D visual object recognition. Using such a working memory, a self-organizing architecture for invariant 3-D visual object recognition is described that is based on the model of Seibert and Waxman [1].

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For at least two millennia and probably much longer, the traditional vehicle for communicating geographical information to end-users has been the map. With the advent of computers, the means of both producing and consuming maps have radically been transformed, while the inherent nature of the information product has also expanded and diversified rapidly. This has given rise in recent years to the new concept of geovisualisation (GVIS), which draws on the skills of the traditional cartographer, but extends them into three spatial dimensions and may also add temporality, photorealistic representations and/or interactivity. Demand for GVIS technologies and their applications has increased significantly in recent years, driven by the need to study complex geographical events and in particular their associated consequences and to communicate the results of these studies to a diversity of audiences and stakeholder groups. GVIS has data integration, multi-dimensional spatial display advanced modelling techniques, dynamic design and development environments and field-specific application needs. To meet with these needs, GVIS tools should be both powerful and inherently usable, in order to facilitate their role in helping interpret and communicate geographic problems. However no framework currently exists for ensuring this usability. The research presented here seeks to fill this gap, by addressing the challenges of incorporating user requirements in GVIS tool design. It starts from the premise that usability in GVIS should be incorporated and implemented throughout the whole design and development process. To facilitate this, Subject Technology Matching (STM) is proposed as a new approach to assessing and interpreting user requirements. Based on STM, a new design framework called Usability Enhanced Coordination Design (UECD) is ten presented with the purpose of leveraging overall usability of the design outputs. UECD places GVIS experts in a new key role in the design process, to form a more coordinated and integrated workflow and a more focused and interactive usability testing. To prove the concept, these theoretical elements of the framework have been implemented in two test projects: one is the creation of a coastal inundation simulation for Whitegate, Cork, Ireland; the other is a flooding mapping tool for Zhushan Town, Jiangsu, China. The two case studies successfully demonstrated the potential merits of the UECD approach when GVIS techniques are applied to geographic problem solving and decision making. The thesis delivers a comprehensive understanding of the development and challenges of GVIS technology, its usability concerns, usability and associated UCD; it explores the possibility of putting UCD framework in GVIS design; it constructs a new theoretical design framework called UECD which aims to make the whole design process usability driven; it develops the key concept of STM into a template set to improve the performance of a GVIS design. These key conceptual and procedural foundations can be built on future research, aimed at further refining and developing UECD as a useful design methodology for GVIS scholars and practitioners.

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The importance of γ-secretase protease activities in development, neurogenesis and the immune system are highlighted by the diversity of its substrates and phenotypic characterization of Presenilin (PS)-deficient transgenic animals. Since the discovery of Amyloid precursor protein (APP) and it’s cleavage by γ-secretase complexes, over 90 other type I membrane proteins have been identified as γ-secretase substrates. We have identified interleukin-1 (IL-1) receptor type I (IL-1R1), toll-like receptor 4 (TLR4) and tumour necrosis factor-α (TNFα) receptor-1 (TNFR1) as novel substrates for - secretase cleavage, which play an important role in innate immunity. In this study, using PS-deficient cells and PS-knockout animal models we examined the role of PS proteins, PS1 and PS2, in IL-1R1-, TLR4- and TNFR1- mediated inflammatory responses. Data presented show that in response to IL- 1β, lipopolysaccharide (LPS) or TNFα, immortalised fibroblasts from PS2- deficient animals have diminished production of specific cytokines and chemokine, with differential reduction in nuclear factor-κB (NF-κB) and (mitogen activated protein kinase) MAPK activities. In contrast, no defect in the response to IL-1β, LPS or TNFα was observed in PS1-deficient immortalised fibroblasts. These observations were confirmed using bone marrow-derived macrophages from PS2-null mice, which also display impaired responsiveness to IL-1β- and LPS, with decreased production of inflammatory cytokines. Furthermore, in whole animal in vivo responses, we show that PS2-deficient animals display ligand (IL-1β, LPS and TNFα)-dependent alterations in the production of specific pro-inflammatory cytokines or chemokines. Importantly, this reduced responsiveness to IL-1β, LPS or TNFα is independent of γ- secretase protease activity and γ-secretase cleavage of TNFR1, IL-1R1 or TLR4. These observations suggest a novel γ-secretase-independent role of PS2 in the regulation of innate immune responsiveness and challenge current concepts regarding the regulation of IL-1β-, LPS- and TNFα-mediated immune signalling.

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The universality versus culture specificity of quantitative evaluations (negative-positive) of 40 events in world history was addressed using World History Survey data collected from 5,800 university students in 30 countries/societies. Multidimensional scaling using generalized procrustean analysis indicated poor fit of data from the 30 countries to an overall mean configuration, indicating lack of universal agreement as to the associational meaning of events in world history. Hierarchical cluster analysis identified one Western and two non-Western country clusters for which adequate multidimensional fit was obtained after item deletions. A two-dimensional solution for the three country clusters was identified, where the primary dimension was historical calamities versus progress and a weak second dimension was modernity versus resistance to modernity. Factor analysis further reduced the item inventory to identify a single concept with structural equivalence across cultures, Historical Calamities, which included man-made and natural, intentional and unintentional, predominantly violent but also nonviolent calamities. Less robust factors were tentatively named as Historical Progress and Historical Resistance to Oppression. Historical Calamities and Historical Progress were at the individual level both significant and independent predictors of willingness to fight for one’s country in a hierarchical linear model that also identified significant country-level variation in these relationships. Consensus around calamity but disagreement as to what constitutes historical progress is discussed in relation to the political culture of nations and lay perceptions of history as catastrophe.

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This study investigates the effect of serious health events including new diagnoses of heart attacks, strokes, cancers, chronic lung disease, chronic heart failure, diabetes, and heart disease on future smoking status up to 6 years postevent. Data come from the Health and Retirement Study, a nationally representative longitudinal survey of Americans aged 51-61 in 1991, followed every 2 years from 1992 to 1998. Smoking status is evaluated at each of three follow-ups, (1994, 1996, and 1998) as a function of health events between each of the four waves. Acute and chronic health events are associated with much lower likelihood of smoking both in the wave immediately following the event and up to 6 years later. However, future events do not retrospectively predict past cessation. In sum, serious health events have substantial impacts on cessation rates of older smokers. Notably, these effects persist for as much as 6 years after a health event.

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STUDY DESIGN: The inflammatory responses of primary human intervertebral disc (IVD) cells to tumor necrosis factor α (TNF-α) and an antagonist were evaluated in vitro. OBJECTIVE: To investigate an ability for soluble TNF receptor type II (sTNFRII) to antagonize TNF-α-induced inflammatory events in primary human IVD cells in vitro. SUMMARY OF BACKGROUND DATA: TNF-α is a known mediator of inflammation and pain associated with radiculopathy and IVD degeneration. sTNFRs and their analogues are of interest for the clinical treatment of these IVD pathologies, although information on the effects of sTNFR on human IVD cells remains unknown. METHODS: IVD cells were isolated from surgical tissues procured from 15 patients and cultured with or without 1.4 nmol/L TNF-α (25 ng/mL). Treatment groups were coincubated with varying doses of sTNFRII (12.5-100 nmol/L). Nitric oxide (NO), prostaglandin E₂ (PGE₂), and interleukin-6 (IL6) levels in media were quantified to characterize the inflammatory phenotype of the IVD cells. RESULTS: Across all patients, TNF-α induced large, statistically significant increases in NO, PGE₂, and IL6 secretion from IVD cells compared with controls (60-, 112-, and 4-fold increases, respectively; P < 0.0001). Coincubation of TNF-α with nanomolar doses of sTNFRII significantly attenuated the secretion of NO and PGE₂ in a dose-dependent manner, whereas IL6 levels were unchanged. Mean IC₅₀ values for NO and PGE₂ were found to be 35.1 and 20.5 nmol/L, respectively. CONCLUSION: Nanomolar concentrations of sTNFRII were able to significantly attenuate the effects of TNF-α on primary human IVD cells in vitro. These results suggest this sTNFR to be a potent TNF antagonist with potential to attenuate inflammation in IVD pathology.

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BACKGROUND: Molecular tools may provide insight into cardiovascular risk. We assessed whether metabolites discriminate coronary artery disease (CAD) and predict risk of cardiovascular events. METHODS AND RESULTS: We performed mass-spectrometry-based profiling of 69 metabolites in subjects from the CATHGEN biorepository. To evaluate discriminative capabilities of metabolites for CAD, 2 groups were profiled: 174 CAD cases and 174 sex/race-matched controls ("initial"), and 140 CAD cases and 140 controls ("replication"). To evaluate the capability of metabolites to predict cardiovascular events, cases were combined ("event" group); of these, 74 experienced death/myocardial infarction during follow-up. A third independent group was profiled ("event-replication" group; n=63 cases with cardiovascular events, 66 controls). Analysis included principal-components analysis, linear regression, and Cox proportional hazards. Two principal components analysis-derived factors were associated with CAD: 1 comprising branched-chain amino acid metabolites (factor 4, initial P=0.002, replication P=0.01), and 1 comprising urea cycle metabolites (factor 9, initial P=0.0004, replication P=0.01). In multivariable regression, these factors were independently associated with CAD in initial (factor 4, odds ratio [OR], 1.36; 95% CI, 1.06 to 1.74; P=0.02; factor 9, OR, 0.67; 95% CI, 0.52 to 0.87; P=0.003) and replication (factor 4, OR, 1.43; 95% CI, 1.07 to 1.91; P=0.02; factor 9, OR, 0.66; 95% CI, 0.48 to 0.91; P=0.01) groups. A factor composed of dicarboxylacylcarnitines predicted death/myocardial infarction (event group hazard ratio 2.17; 95% CI, 1.23 to 3.84; P=0.007) and was associated with cardiovascular events in the event-replication group (OR, 1.52; 95% CI, 1.08 to 2.14; P=0.01). CONCLUSIONS: Metabolite profiles are associated with CAD and subsequent cardiovascular events.