924 resultados para Surrounding Regions
Resumo:
New economic geography models show that there may be a strong relationship between economic integration and the geographical concentration of industries. Nevertheless, this relationship is neither unique nor stable, and may follow a ?-shaped pattern in the long term. The aim of the present paper is to analyze the evolution of the geographical concentration of manufacturing across Spanish regions during the period 1856-1995. We construct several geographical concentration indices for different points in time over these 140 years. The analysis is carried out at two levels of aggregation, in regions corresponding to the NUTS-II and NUTS-III classifications. We confirm that the process of economic integration stimulated the geographical concentration of industrial activity. Nevertheless, the localization coefficients only started to fall after the beginning of the integration of the Spanish Economy into the international markets in the mid-70s, and this new path was not interrupted by Spain¿s entry in the European Union some years later
Resumo:
We characterize the approach regions so that the non-tangential maximal function is of weak-type on potential spaces, for which we use a simple argument involving Carleson measure estimates.
Resumo:
La complexitat dels mecanismes que determinen l'entrada i la sortida de signatures augmenta quan diferències geogràfiques de l'estructura de producció, la capital humana i l'atur són considerades. Variacions interregionals en la tarifa de les noves de signatures dintre de cada activitat industrial persisteixen durant els períodes llargs de temps, una circumstància que indica que hi ha determinants no-conjunturals en la capacitat de regions per a crear nous projectes industrials. Aquest estudi està preocupat amb l'establiment d'influència variables geogràfiques sobre la fundació de nous establiments de la fabricació. Les indústries (NEIX la R 25) en les regions espanyoles (el BOIG 2) han estat preses com les unitats d'anàlisis per al període 1980-1992
Resumo:
Glioblastoma multiforme (GBM) is the most malignant variant of human glial tumors. A prominent feature of this tumor is the occurrence of necrosis and vascular proliferation. The regulation of glial neovascularization is still poorly understood and the characterization of factors involved in this process is of major clinical interest. Macrophage migration inhibitory factor (MIF) is a pleiotropic cytokine released by leukocytes and by a variety of cells outside of the immune system. Recent work has shown that MIF may function to regulate cellular differentiation and proliferation in normal and tumor-derived cell lines, and may also contribute to the neovascularization of tumors. Our immunohistological analysis of MIF distribution in GBM tissues revealed the strong MIF protein accumulation in close association with necrotic areas and in tumor cells surrounding blood vessels. In addition, MIF expression was frequently associated with the presence of the tumor-suppressor gene p53. To substantiate the concept that MIF might be involved in the regulation of angiogenesis in GBM, we analyzed the MIF gene and protein expression under hypoxic and hypoglycemic stress conditions in vitro. Northern blot analysis showed a clear increase of MIF mRNA after hypoxia and hypoglycemia. We could also demonstrate that the increase of MIF transcripts on hypoxic stress can be explained by a profound transcriptional activation of the MIF gene. In parallel to the increase of MIF transcripts, we observed a significant rise in extracellular MIF protein on angiogenic stimulation. The data of our preliminary study suggest that the up-regulation of MIF expression during hypoxic and hypoglycemic stress might play a critical role for the neovascularization of glial tumors.
Resumo:
New economic geography models show that there may be a strong relationship between economic integration and the geographical concentration of industries. Nevertheless, this relationship is neither unique nor stable, and may follow a ?-shaped pattern in the long term. The aim of the present paper is to analyze the evolution of the geographical concentration of manufacturing across Spanish regions during the period 1856-1995. We construct several geographical concentration indices for different points in time over these 140 years. The analysis is carried out at two levels of aggregation, in regions corresponding to the NUTS-II and NUTS-III classifications. We confirm that the process of economic integration stimulated the geographical concentration of industrial activity. Nevertheless, the localization coefficients only started to fall after the beginning of the integration of the Spanish Economy into the international markets in the mid-70s, and this new path was not interrupted by Spain¿s entry in the European Union some years later
Resumo:
In this paper we use a gravity model to study the trade performance of French and Spanishborder regions relatively to non-border regions, over the past two decades. We find that,controlling for their size, proximity and location characteristics, border regions trade onaverage between 62% and 193% more with their neighbouring country than other regions,and twice as much if they are endowed with good cross border transport infrastructures.Despite European integration, however, this trade outperformance has fallen for the mostperipheral regions within the EU. We show that this trend was linked in part to a shift in the propensity of foreign investors to move their affiliates from the regions near their home market to the regions bordering the EU core.
Resumo:
To study the major histocompatibility complex class II I-E dependence of mouse mammary tumor virus (MMTV) superantigens, we constructed hybrids between the I-E-dependent MMTV(GR) and the I-E-independent mtv-7 superantigens and tested them in vivo. Our results suggest that, although the C-terminal third mediates I-A interaction, additional binding sites are located elsewhere in the superantigen.
Resumo:
Anthropogenic emissions of metals from sources such as smelters are an international problem, but there is limited published information on emissions from Australian smelters. The objective of this study was to investigate the regional distribution of heavy metals in soils in the vicinity of the industrial complex of Port Kembla, NSW, Australia, which comprises a copper smelter, steelworks and associated industries. Soil samples (n=25) were collected at the depths of 0-5 and 5-20 cm, air dried and sieved to < 2 mm. Aqua regia extractable amounts of As, Cr, Cu, Ph and Zn were analysed by inductively coupled plasma mass spectrometry (lCP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). Outliers were identified from background levels by statistical methods. Mean background levels at a depth of 0-5 cm were estimated at 3.2 mg/kg As, 12 mg/kg Cr, 49 mg/kg Cu, 20 mg/kg Ph and 42 mg/kg Zn. Outliers for elevated As and Cu values were mainly present within 4 km from the Port Kembla industrial complex, but high Ph at two sites and high Zn concentrations were found at six sites up to 23 km from Port Kembla. Chromium concentrations were not anomalous close to the industrial complex. There was no significant difference of metal concentrations at depths of 0-5 and 5-20 cm, except for Ph and Zn. Copper and As concentrations in the soils are probably related to the concentrations in the parent rock. From this investigation, the extent of the contamination emanating from the Port Kembla industrial complex is limited to 1-13 km, but most likely <4 km, depending on the element; the contamination at the greater distance may not originate from the industrial complex. (C) 2003 Elsevier B.V. All rights reserved.
Resumo:
The methylation status of the O(6)-methylguanine-DNA methyltransferase (MGMT) gene is an important predictive biomarker for benefit from alkylating agent therapy in glioblastoma. Recent studies in anaplastic glioma suggest a prognostic value for MGMT methylation. Investigation of pathogenetic and epigenetic features of this intriguingly distinct behavior requires accurate MGMT classification to assess high throughput molecular databases. Promoter methylation-mediated gene silencing is strongly dependent on the location of the methylated CpGs, complicating classification. Using the HumanMethylation450 (HM-450K) BeadChip interrogating 176 CpGs annotated for the MGMT gene, with 14 located in the promoter, two distinct regions in the CpG island of the promoter were identified with high importance for gene silencing and outcome prediction. A logistic regression model (MGMT-STP27) comprising probes cg1243587 and cg12981137 provided good classification properties and prognostic value (kappa = 0.85; log-rank p < 0.001) using a training-set of 63 glioblastomas from homogenously treated patients, for whom MGMT methylation was previously shown to be predictive for outcome based on classification by methylation-specific PCR. MGMT-STP27 was successfully validated in an independent cohort of chemo-radiotherapy-treated glioblastoma patients (n = 50; kappa = 0.88; outcome, log-rank p < 0.001). Lower prevalence of MGMT methylation among CpG island methylator phenotype (CIMP) positive tumors was found in glioblastomas from The Cancer Genome Atlas than in low grade and anaplastic glioma cohorts, while in CIMP-negative gliomas MGMT was classified as methylated in approximately 50 % regardless of tumor grade. The proposed MGMT-STP27 prediction model allows mining of datasets derived on the HM-450K or HM-27K BeadChip to explore effects of distinct epigenetic context of MGMT methylation suspected to modulate treatment resistance in different tumor types.
Resumo:
Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.
Resumo:
Abstract. The ability of 2 Rapid Bioassessment Protocols (RBPs) to assess stream water quality was compared in 2 Mediterranean-climate regions. The most commonly used RBPs in South Africa (SAprotocol) and the Iberian Peninsula (IB-protocol) are both multihabitat, field-based methods that use macroinvertebrates. Both methods use preassigned sensitivity weightings to calculate metrics and biotic indices. The SA- and IB-protocols differ with respect to sampling equipment (mesh size: 1000 lm vs 250 300 lm, respectively), segregation of habitats (substrate vs flow-type), and sampling and sorting procedures (variable time and intensity). Sampling was undertaken at 6 sites in South Africa and 5 sites in the Iberian Peninsula. Forty-four and 51 macroinvertebrate families were recorded in South Africa and the Iberian Peninsula, respectively; 77.3% of South African families and 74.5% of Iberian Peninsula families were found using both protocols. Estimates of community similarity compared between the 2 protocols were .60% similar among sites in South Africa and .54% similar among sites in the Iberian Peninsula (BrayCurtis similarity), and no significant differences were found between protocols (Multiresponse Permutation Procedure). Ordination based on Non-metric Multidimensional Scaling grouped macroinvertebrate samples on the basis of site rather than protocol. Biotic indices generated with the 2 protocols at each site did not differ. Thus, both RBPs produced equivalent results, and both were able to distinguish between biotic communities (mountain streams vs foothills) and detect water-quality impairment, regardless of differences in sampling equipment, segregation of habitats, and sampling and sorting procedures. Our results indicate that sampling a single habitat may be sufficient for assessing water quality, but a multihabitat approach to sampling is recommended where intrinsic variability of macroinvertebrate assemblages is high (e.g., in undisturbed sites in regions with Mediterranean climates). The RBP of choice should depend on whether the objective is routine biomonitoring of water quality or autecological or faunistic studies.
Resumo:
STUDY DESIGN: A cross-sectional survey was performed. OBJECTIVE: To estimate the extent of low back pain as a public health problem. SUMMARY OF BACKGROUND DATA: Health surveys converge on very high estimates of low back pain in general populations, but few studies have included severity criteria in their definition and conclusions. Because it is unlikely that interventions will influence the prevalence of minimal and infrequent symptoms, greater attention should be paid to characteristics of low back pain that indicate some impact on the life of survey respondents. METHODS: Two regions participated in the MONICA (MONitoring of trends and determinants in CArdiovascular disease) project in Switzerland. Participants randomly selected from the general population completed a standard self-administered questionnaire on cardiovascular risk factors. A special section on low back pain was added in the third (1992-1993) MONICA survey and completed by 3227 participants. RESULTS: A regional difference found in the 12-month prevalence rate disappeared with the inclusion of severity criteria. Low back pain over more than seven cumulated days was reported among men by 20.2% (age range, 25-34 years) to 28.5% (age range, 65-74 years), respectively, among women by 31.1% to 38.5%. Similar rates of reduction in activity (professional, housekeeping, and leisure time) and medical consultation (conventional and nonconventional) motivated by low back pain characterized the two participating regions. The cumulative duration of pain was related to all the indicators showing the impact of low back pain on everyday life. CONCLUSIONS: Determining the cumulative duration of low back pain over the preceding year is a straightforward task, and a cutoff at 1 week seems appropriate for distinguishing between low- and high-impact low back pain.