900 resultados para Multidimensional. Development. Convergence. Divergence. Analysis of groupings
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This article investigates to what extent the worldwide increase in body mass index (BMI) has been affected by economic globalization and inequality. We used time-series and longitudinal cross-national analysis of 127 countries from 1980 to 2008. Data on mean adult BMI were obtained from the Global Burden of Metabolic Risk Factors of Chronic Diseases Collaborating Group. Globalization was measured using the Swiss Economic Institute (KOF) index of economic globalization. Economic inequality between countries was measured with the mean difference in gross domestic product per capita purchasing power parity in international dollars. Economic inequality within countries was measured using the Gini index from the Standardized World Income Inequality Database. Other covariates including poverty, population size, urban population, openness to trade and foreign direct investment were taken from the World Development Indicators (WDI) database. Time-series regression analyses showed that the global increase in BMI is positively associated with both the index of economic globalization and inequality between countries, after adjustment for covariates. Longitudinal panel data analyses showed that the association between economic globalization and BMI is robust after controlling for all covariates and using different estimators. The association between economic inequality within countries and BMI, however, was significant only among high-income nations. More research is needed to study the pathways between economic globalization and BMI. These findings, however, contribute to explaining how contemporary globalization can be reformed to promote better health and control the global obesity epidemic. © 2013 Copyright Taylor and Francis Group, LLC.
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Increases in food production and the ever-present threat of food contamination from microbiological and chemical sources have led the food industry and regulators to pursue rapid, inexpensive methods of analysis to safeguard the health and safety of the consumer. Although sophisticated techniques such as chromatography and spectrometry provide more accurate and conclusive results, screening tests allow a much higher throughput of samples at a lower cost and with less operator training, so larger numbers of samples can be analysed. Biosensors combine a biological recognition element (enzyme, antibody, receptor) with a transducer to produce a measurable signal proportional to the extent of interaction between the recognition element and the analyte. The different uses of the biosensing instrumentation available today are extremely varied, with food analysis as an emerging and growing application. The advantages offered by biosensors over other screening methods such as radioimmunoassay, enzyme-linked immunosorbent assay, fluorescence immunoassay and luminescence immunoassay, with respect to food analysis, include automation, improved reproducibility, speed of analysis and real-time analysis. This article will provide a brief footing in history before reviewing the latest developments in biosensor applications for analysis of food contaminants (January 2007 to December 2010), focusing on the detection of pathogens, toxins, pesticides and veterinary drug residues by biosensors, with emphasis on articles showing data in food matrices. The main areas of development common to these groups of contaminants include multiplexing, the ability to simultaneously analyse a sample for more than one contaminant and portability. Biosensors currently have an important role in food safety; further advances in the technology, reagents and sample handling will surely reinforce this position.
The size and shape of shells used by hermit crabs: A multivariate analysis of Clibanarius erythropus
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Shell attributes Such as weight and shape affect the reproduction, growth, predator avoidance and behaviour of several hermit crab species. Although the importance of these attributes has been extensively investigated, it is still difficult to assess the relative role of size and shape. Multivariate techniques allow concise and efficient quantitative analysis of these multidimensional properties, and this paper aims to understand their role in determining patterns of hermit crab shell use. To this end, a multivariate approach based on a combination of size-unconstrained (shape) PCA and RDA ordination was used to model the biometrics of southern Mediterranean Clibanarius erythropus Populations and their shells. Patterns of shell utilization and morphological gradients demonstrate that size is more important than shape, probably due to the limited availability of empty shells in the environment. The shape (e.g. the degree of shell elongation) and weight of inhabited shells vary considerably in both female and male crabs. However, these variations are clearly accounted for by crab biometrics in males only. Oil the basis of statistical evidence and findings from past studies. it is hypothesized that larger males of adequate size and strength have access to the larger, heavier and relatively more available shells of the globose Osilinus turbinatus, which cannot be used by average-sized males or by females investing energy in egg production. This greater availability allows larger males to select more Suitable Shapes. (C) 2009 Elsevier Masson SAS. All rights reserved.
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Analysis of molecular interaction and conformational dynamics of biomolecules is of paramount importance in understanding of their vital functions in complex biological systems, disease detection, and new drug development. Plasmonic biosensors based upon surface plasmon resonance and localized surface plasmon resonance have become the predominant workhorse for detecting accumulated biomass caused by molecular binding events. However, unlike surface-enhanced Raman spectroscopy (SERS), the plasmonic biosensors indeed are not suitable tools to interrogate vibrational signatures of conformational transitions required for biomolecules to interact. Here, we show that plasmonic metamaterials can offer two transducing channels for parallel acquisition of optical transmission and sensitive SERS spectra at the biointerface, simultaneously probing the conformational states and binding affinity of biomolecules, e.g. G-quadruplexes, in different environments (Fig. 1). We further demonstrate the use of the metamaterials for fingerprinting and detection of arginine-glycine-glycine domain of nucleolin, a cancer biomarker which specifically binds to a G-quadruplex, with the picomolar sensitivity. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays.
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Analysis of binding recognition and conformation of biomolecules is of paramount important in understanding of their vital functions in complex biological systems. By enabling sub-wavelength light localization and strong local field enhancement, plasmonic biosensors have become dominant tools used for such analysis owing to their label-free and real-time attributes1,2. However, the plasmonic biosensors are not well-suited to provide information regarding conformation or chemical fingerprint of biomolecules. Here, we show that plasmonic metamaterials, consisting of periodic arrays of artificial split-ring resonators (SRRs)3, can enable capabilities of both sensing and fingerprinting of biomolecules. We demonstrate that by engineering geometry of individual SRRs, localized surface plasmon resonance (LSPR) frequency of the metamaterials could be tuned to visible-near infrared regimes (Vis-NIR) such that they possess high local field enhancement for surface-enhanced Raman scattering spectroscopy (SERS). This will provide the basis for the development of a dual mode label-free conformational-resolving and quantitative detection platform. We present here the ability of each sensing mode to independently detect binding adsorption and to identify different conformational states of Guanine (G)-rich DNA monolayers in different environment milieu. Also shown is the use of the nanosensor for fingerprinting and detection of Arginine-Glycine-Glycine (RGG) peptide binding to the G-quadruplex aptamer. The dual-mode nanosensor will significantly contribute to unraveling the complexes of the conformational dynamics of biomolecules as well as to improving specificity of biodetection assays that the conventional, population-averaged plasmonic biosensors cannot achieve.
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Microalbuminuria is a common diagnosis in the clinical care of patients with type 1 diabetes mellitus. Long-term outcomes after the development of microalbuminuria are variable.
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Mobile malware has been growing in scale and complexity spurred by the unabated uptake of smartphones worldwide. Android is fast becoming the most popular mobile platform resulting in sharp increase in malware targeting the platform. Additionally, Android malware is evolving rapidly to evade detection by traditional signature-based scanning. Despite current detection measures in place, timely discovery of new malware is still a critical issue. This calls for novel approaches to mitigate the growing threat of zero-day Android malware. Hence, the authors develop and analyse proactive machine-learning approaches based on Bayesian classification aimed at uncovering unknown Android malware via static analysis. The study, which is based on a large malware sample set of majority of the existing families, demonstrates detection capabilities with high accuracy. Empirical results and comparative analysis are presented offering useful insight towards development of effective static-analytic Bayesian classification-based solutions for detecting unknown Android malware.
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In this paper we make use of the 9-year old wave of the Growing Up in Ireland study to analyse multidimensional deprivation in Ireland. The Alkire and Foster adjusted head count ratio approach (AHCR; 2007, 2011a, 2011b) applied here constitutes a significant improvement on union and intersection approaches and allows for the decomposition of multidimensional poverty in terms of dimensions and sub-groups. The approach involves a censoring of data such that deprivations count only for those above the specified multidimensional threshold leading to a stronger set of interrelationships between deprivation dimensions. Our analysis shows that the composition of the adjusted head ratio is influenced by a range of socio-economic factors. For less-favoured socio-economic groups dimensions relating to material deprivation are disproportionately represented while for the more advantaged groups, those relating to behavioral and emotional issues and social interaction play a greater role. Notwithstanding such variation in composition, our analysis showed that the AHCR varied systematically across categories of household type, and the social class, education and age group of the primary care giver. Furthermore, these variables combined in a cumulative manner. The most systematic variation was in relation to the head count of those above the multidimensional threshold rather than intensity, conditional on being above that cut-off point. Without seeking to arbitrate on the relative value of composite indices versus disaggregated profiles, our analysis demonstrates that there is much to be gained from adopting an approach with clearly understood axiomatic properties. Doing so allows one to evaluate the consequences of the measurement strategy employed for the understanding of levels of multidimensional deprivation, the nature of such deprivation profiles and socio-economic risk patterns. Ultimately it permits an informed assessment of the strengths and weaknesses of the particular choices made.
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Background: Obesity is increasingly prevalent in many countries. Obesity is a major risk factor for the development of type 2 diabetes but its relationship with diabetic kidney disease (DKD) remains unclear. Some studies have suggested that the metabolic syndrome (including obesity) may be associated with DKD in type 1 diabetes. Aim: To investigate the association between obesity and DKD. Design: Retrospective cross-sectional study. Methods: National Diabetes Audit data were available for the 2007–08 cycle. Type 1 and 2 diabetes patients with both a valid serum creatinine and urinary albumin:creatinine ratio were included. DKD was defined as an estimated glomerular filtration rate (eGFR) <60 ml/min/1.73 m2, albuminuria or both. Logistic regression was used to analyse associations of obesity (body mass index ≥30 kg/m2) and other variables including year of birth, year of diagnosis, ethnicity and stage of kidney disease. Results: A total of 58 791 type 1 and 733 769 type 2 diabetes patients were included in the analysis. After adjustment, when compared with type 1 diabetes patients with normal renal function those with DKD were up to twice as likely to be obese. Type 2 DKD patients were also more likely to be obese. For example, type 2 diabetes patients with an eGFR <15 ml/min/1.73 m2 and normoalbuminuria, microalbuminuria or macroalbuminuria were all more likely to be obese; odds ratios (95% CI) 1.65 (1.3–2.1), 1.56 (1.28–1.92) and 1.27 (1.05–1.54), respectively. Conclusions: This study has highlighted a strong association between obesity and kidney disease in type 1 diabetes and confirmed their association in type 2 diabetes.
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The ability to predict the mechanical behavior of polymer composites is crucial for their design and manufacture. Extensive studies based on both macro- and micromechanical analyses are used to develop new insights into the behavior of composites. In this respect, finite element modeling has proved to be a particularly powerful tool. In this article, we present a Galerkin scheme in conjunction with the penalty method for elasticity analyses of different types of polymer composites. In this scheme, the application of Green's theorem to the model equation results in the appearance of interfacial flux terms along the boundary between the filler and polymer matrix. It is shown that for some types of composites these terms significantly affect the stress transfer between polymer and fillers. Thus, inclusion of these terms in the working equations of the scheme preserves the accuracy of the model predictions. The model is used to predict the most important bulk property of different types of composites. Composites filled with rigid or soft particles, and composites reinforced with short or continuous fibers are investigated. For each case, the results are compared with the available experimental results and data obtained from other models reported in the literature. Effects of assumptions made in the development of the model and the selection of the prescribed boundary conditions are discussed.
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This paper analyzes the behavior of a Voltage Source Converter Based HVDC system under DC cable fault conditions. The behavior of the HVDC system during a permanent line-to-earth fault is analyzed, outlining the systems configuration and behavior at each stage of the fault timeline. Operation of the proposed system under a single earthing configurations i.e. Converter (solid) earthed/AC transformer unearthed, was analyzed and simulated, with particular attention paid to the converters operation. It was observed that the development of potential earth loops within the system as a result of DC line- toearth faults leads to substantial overcurrent and results in system configuration oscillation.
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Genuine Savings has emerged as a widely-used indicator of sustainable development. In this paper, we use long-term data stretching back to 1870 to undertake empirical tests of the relationship between Genuine Savings (GS) and future well-being for three countries: Britain, the USA and Germany. Our tests are based on an underlying theoretical relationship between GS and changes in the present value of future consumption. Based on both single country and panel results, we find evidence supporting the existence of a cointegrating (long run equilibrium) relationship between GS and future well-being, and fail to reject the basic theoretical result on the relationship between these two macroeconomic variables. This provides some support for the GS measure of weak sustainability. We also show the effects of modelling shocks, such as World War Two and the Great Depression.
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There is limited binding international law specifically covering the provision of humanitarian assistance in response to natural and human-made disasters. Yet a variety of authoritative soft law texts have been developed in the past 20 years, including the UN Guiding Principles on Internal Displacement, the Red Cross Red Crescent Code of Conduct and the Sphere Project’s Humanitarian Charter and Minimum Standards in Disaster Response. While such ‘non-binding normative standards’ do not carry the weight of international law, they play an essential role in the provision of humanitarian assistance albeit subject to their limited enforceability vis-à-vis intended beneficiaries and to their voluntary application by humanitarian actors. Notwithstanding a lack of legal compulsion, certain non-binding normative standards may directly influence the actions of States and non-State actors, and so obtain a strongly persuasive character. Analysis of texts that influence the practice of humanitarian assistance advances our understanding of humanitarian principles and performance standards for disaster response. As the International Law Commission debates draft articles on the Protection of Persons in the Event of Disasters, such non-binding normative standards are crucial to the development of an internationally accepted legal framework to protect victims of disasters.
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TAP pulse responses are normally analysed using moments, which are integrals of the full TAP pulse response. However, in some cases the entire pulse response may not be recorded due to technical reasons, thereby compromising any data analysis due to moments generated from incomplete pulse responses. The current work discloses the development of a function which mathematically expands the tail of a TAP pulse response, so that the TAP data analysis can be accurately conducted. This newly developed analysis method has been applied to the oxidative dehydrogenation of ethane over Co–Cr–Sn–WOx/α-Al2O3 and Co–Cr–Sn–WOx/α-Al2O3 catalysts as a case study.
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Fault and fracture systems are the most important store and pathway for groundwater in Ireland’s bedrock aquifers, either directly as conductive flow structures, or indirectly as the locus for the development of dolomitised limestone and karst. This article presents the preliminary results of a study involving the quantitative analysis of fault and fracture systems in the broad range of Irish bedrock types and a consideration of their impact on groundwater flow. The principal aims of the project are to develop generic conceptual models for different fault/fracture systems in different lithologies and at different depths, and to link them to observed groundwater behaviour. Here we briefly describe the geometrical characteristics of the main post-Devonian fault/fracture systems controlling groundwater flow from field observations at outcrops, quarries and mines. The structures range from Lower Carboniferous normal faults through to Variscan-related faults and veins, with the most recent structures including Tertiary strike-slip faults and ubiquitous uplift-related joint systems. The geometrical characteristics of different fault/fracture systems combined with observations of groundwater behaviour in both quarry and mine localities, can be linked to general flow and transport conceptualisations of Irish fractured bedrock. Most importantly they also provide a basis for relating groundwater flow to particular fault/fracture systems and their expression with depth and within different lithological sequences, as well as their regional variability.