915 resultados para Cost and standard of living--New York (State)--New York


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Vol. 2 has imprint: Ann Arbor, Institute for Social Research, University of Michigan.

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Mode of access: Internet.

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"Form CE-317, January 1986."

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A novel, untransformed koala cell line (KC-1) was established by culturing koala conjunctival tissue in growth medium, which has permitted the study of the cell biology of this unique system. After the establishment of the KC-1 cell line, the cells were characterized by light microscopy, doubling time, and Western blot analysis. Light microscopy revealed that the cells have an epithelial morphology. Doubling times were significantly different (P < 0.015) depending on fetal calf serum (FCS) concentration (16.5 h in 10% FCS and 26.5 h in 2% FCS). Cells constricted while in suspension but were shown to attach to the coverslip (or flask) and flatten rapidly, less than 1 h after seeding. To confirm the epithelial nature of the cells, protein was extracted and Western blot analysis was performed. Subsequent probing with primary and secondary antibodies (monoclonal anticytokeratin clone C-11 IgG1 and anti-mouse IgG) revealed two bands at 45 and 52 kDa (compared against a protein molecular weight marker) that correspond to primary type I keratin and major type II keratin, respectively, expressed in simple epithelial cells. The koala cell line was adapted to grow continuously in Dulbecco modified Eagle medium containing 10% FCS for at least 30 passages. This unique cell line is an ideal toot for further investigation on koala cell biology and cytogenetics and for exploration of the pathophysiological mechanism of eye infections caused by different pathogens in koalas.

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Construction of an international index of standards of living, incorporating social indicators and economic output, typically involves scaling and weighting procedures that lack welfare-economic foundations. Revealed preference axioms can be used to make quality-of-life comparisons if we can estimate the representative household's production technology for the social indicators. This method is applied to comparisons of gross domestic product (GDP) and life expectancy for 58 countries. Neither GDP rankings, nor the rankings of the Human Development Index (HDI), are consistent with the partial ordering of revealed preference. A method of constructing a utility-consistent index incorporating both consumption and life expectancy is suggested. (C) 2003 Elsevier Science B.V. All rights reserved.

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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

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We review and compare four broad categories of spatially-explicit modelling approaches currently used to understand and project changes in the distribution and productivity of living marine resources including: 1) statistical species distribution models, 2) physiology-based, biophysical models of single life stages or the whole life cycle of species, 3) food web models, and 4) end-to-end models. Single pressures are rare and, in the future, models must be able to examine multiple factors affecting living marine resources such as interactions between: i) climate-driven changes in temperature regimes and acidification, ii) reductions in water quality due to eutrophication, iii) the introduction of alien invasive species, and/or iv) (over-)exploitation by fisheries. Statistical (correlative) approaches can be used to detect historical patterns which may not be relevant in the future. Advancing predictive capacity of changes in distribution and productivity of living marine resources requires explicit modelling of biological and physical mechanisms. New formulations are needed which (depending on the question) will need to strive for more realism in ecophysiology and behaviour of individuals, life history strategies of species, as well as trophodynamic interactions occurring at different spatial scales. Coupling existing models (e.g. physical, biological, economic) is one avenue that has proven successful. However, fundamental advancements are needed to address key issues such as the adaptive capacity of species/groups and ecosystems. The continued development of end-to-end models (e.g., physics to fish to human sectors) will be critical if we hope to assess how multiple pressures may interact to cause changes in living marine resources including the ecological and economic costs and trade-offs of different spatial management strategies. Given the strengths and weaknesses of the various types of models reviewed here, confidence in projections of changes in the distribution and productivity of living marine resources will be increased by assessing model structural uncertainty through biological ensemble modelling.

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Background: The nitration of tyrosine residues in proteins is associated with nitrosative stress, resulting in the formation of 3-nitrotyrosine (3-NT). 3-NT levels in biological samples have been associated with numerous physiological and pathological conditions. For this reason, several attempts have been made in order to develop methods that accurately quantify 3-NT in biological samples. Regarding chromatographic methods, they seem to be very accurate, showing very good sensibility and specificity. However, accurate quantification of this molecule, which is present at very low concentrations both at physiological and pathological states, is always a complex task and a target of intense research. Objectives: We aimed to develop a simple, rapid, low-cost and sensitive 3-NT quantification method for use in medical laboratories as an additional tool for diagnosis and/or treatment monitoring of a wide range of pathologies. We also aimed to evaluate the performance of the HPLC-based method developed here in a wide range of biological matrices. Material and methods: All experiments were performed on a Hitachi LaChrom Elite® HPLC system and separation was carried out using a Lichrocart® 250-4 Lichrospher 100 RP-18 (5μm) column. The method was further validated according to ICH guidelines. The biological matrices tested were serum, whole blood, urine, B16 F-10 melanoma cell line, growth medium conditioned with the same cell line, bacterial and yeast suspensions. Results: From all the protocols tested, the best results were obtained using 0.5% CH3COOH:MeOH:H2O (15:15:70) as the mobile phase, with detection at wavelengths 215, 276 and 356 nm, at 25ºC, and using a flow rate of 1 mL/min. By using this protocol, it was possible to obtain a linear calibration curve (correlation coefficient = 1), limits of detection and quantification in the order of ng/mL, and a short analysis time (<15 minutes per sample). Additionally, the developed protocol allowed the successful detection and quantification of 3-NT in all biological matrices tested, with detection at 356 nm. Conclusion: The method described in this study, which was successfully developed and validated for 3-NT quantification, is simple, cheap and fast, rendering it suitable for analysis in a wide range of biological matrices.

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In this paper, we consider the variable-order nonlinear fractional diffusion equation View the MathML source where xRα(x,t) is a generalized Riesz fractional derivative of variable order View the MathML source and the nonlinear reaction term f(u,x,t) satisfies the Lipschitz condition |f(u1,x,t)-f(u2,x,t)|less-than-or-equals, slantL|u1-u2|. A new explicit finite-difference approximation is introduced. The convergence and stability of this approximation are proved. Finally, some numerical examples are provided to show that this method is computationally efficient. The proposed method and techniques are applicable to other variable-order nonlinear fractional differential equations.

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A method is presented for the development of a regional Landsat-5 Thematic Mapper (TM) and Landsat-7 Enhanced Thematic Mapper plus (ETM+) spectral greenness index, coherent with a six-dimensional index set, based on a single ETM+ spectral image of a reference landscape. The first three indices of the set are determined by a polar transformation of the first three principal components of the reference image and relate to scene brightness, percent foliage projective cover (FPC) and water related features. The remaining three principal components, of diminishing significance with respect to the reference image, complete the set. The reference landscape, a 2200 km2 area containing a mix of cattle pasture, native woodland and forest, is located near Injune in South East Queensland, Australia. The indices developed from the reference image were tested using TM spectral images from 19 regionally dispersed areas in Queensland, representative of dissimilar landscapes containing woody vegetation ranging from tall closed forest to low open woodland. Examples of image transformations and two-dimensional feature space plots are used to demonstrate image interpretations related to the first three indices. Coherent, sensible, interpretations of landscape features in images composed of the first three indices can be made in terms of brightness (red), foliage cover (green) and water (blue). A limited comparison is made with similar existing indices. The proposed greenness index was found to be very strongly related to FPC and insensitive to smoke. A novel Bayesian, bounded space, modelling method, was used to validate the greenness index as a good predictor of FPC. Airborne LiDAR (Light Detection and Ranging) estimates of FPC along transects of the 19 sites provided the training and validation data. Other spectral indices from the set were found to be useful as model covariates that could improve FPC predictions. They act to adjust the greenness/FPC relationship to suit different spectral backgrounds. The inclusion of an external meteorological covariate showed that further improvements to regional-scale predictions of FPC could be gained over those based on spectral indices alone.

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Patients undergoing radiation therapy for cancer face a series of challenges that require support from a multidisciplinary team which includes radiation oncology nurses. However, the specific contribution of nursing, and the models of care that best support the delivery of nursing interventions in the radiotherapy setting, is not well described. In this case study, the Interaction Model of Client Health Behaviour and the associated principles of person-centred care were incorporated into a new model of care that was implemented in one radiation oncology setting in Brisbane, Australia. The new model of care was operationalised through a Primary Nursing/Collaborative Practice framework. To evaluate the impact of the new model for patients and health professionals, multiple sources of data were collected from patients and clinical staff prior to, during, and 18 months following introduction of the practice redesign. One cohort of patients and clinical staff completed surveys incorporating measures of key outcomes immediately prior to implementation of the model, while a second cohort of patients and clinical staff completed these same surveys 18 months following introduction of the model. In-depth interviews were also conducted with nursing, medical and allied health staff throughout the implementation phase to obtain a more comprehensive account of the processes and outcomes associated with implementing such a model. From the patients’ perspectives, this study demonstrated that, although adverse effects of radiotherapy continue to affect patient well-being, patients continue to be satisfied with nursing care in this specialty, and that they generally reported high levels of functioning despite undergoing a curative course of radiotherapy. From the health professionals’ perspective, there was evidence of attitudinal change by nursing staff within the radiotherapy department which reflected a greater understanding and appreciation of a more person-centred approach to care. Importantly, this case study has also confirmed that a range of factors need to be considered when redesigning nursing practice in the radiotherapy setting, as the challenges associated with changing traditional practices, ensuring multidisciplinary approaches to care, and resourcing a new model were experienced. The findings from this study suggest that the move from a relatively functional approach to a person-centred approach in the radiotherapy setting has contributed to some improvements in the provision of individualised and coordinated patient care. However, this study has also highlighted that primary nursing may be limited in its approach as a framework for patient care unless it is supported by a whole team approach, an appropriate supportive governance model, and sufficient resourcing. Introducing such a model thus requires effective education, preparation and ongoing support for the whole team. The challenges of providing care in the context of complex interdisciplinary relationships have been highlighted by this study. Aspects of this study may assist in planning further nursing interventions for patients undergoing radiotherapy for cancer, and continue to enhance the contribution of the radiation oncology nurse to improved patient outcomes.

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Background Low levels of physical activity and high levels of sedentary behavior (SB) are major public health concerns. This study was designed to develop and validate the 7-day Sedentary (S) and Light Intensity Physical Activity (LIPA) Log (7-day SLIPA Log), a self-report measure of specific daily behaviors. Method To develop the log, 62 specific SB and LIPA behaviors were chosen from the Compendium of Physical Activities. Face-to-face interviews were conducted with 32 sedentary volunteers to identify domains and behaviors of SB and LIPA. To validate the log, a further 22 sedentary adults were recruited to wear the GT3X for 7 consecutive days and nights. Results Pearson correlations (r) between the 7-day SLIPA Log and GT3X were significant for sedentary (r =.86, p < 0.001), for LIPA (r =.80, p < 0.001). Lying and sitting postures were positively correlated with GT3X output (r =.60 and r =.64, p < 0.001, respectively). No significant correlation was found for standing posture (r =.14, p = 0.53).The kappa values between the 7-day SLIPA Log and GT3X variables ranged from 0.09–0.61, indicating poor to good agreement. Conclusion The 7-day SLIPA Log is a valid self-report measure of SB and LIPA in specific behavioral domains.

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Technical dinitrotoluene (DNT) is a mixture of 2,4- and 2,6-DNT. In humans, industrial or environmental exposure can occur orally, by inhalation, or by skin contact. The classification of DNT as an 'animal carcinogen' is based on the formation of malignant tumors in kidneys, liver, and mammary glands of rats and mice. Clear signs of toxic nephropathy were found in rats dosed with DNT, and the concept was derived of an interrelation between renal toxicity and carcinogenicity. Recent data point to the carcinogenicity of DNT on the urinary tract of exposed humans. Between 1984 and 1997, 6 cases of urothelial cancer and 14 cases of renal cell cancer were diagnosed in a group of 500 underground mining workers in the copper mining industry of the former GDR and having high exposures to explosives containing technical DNT. The incidences of both urothelial and renal cell tumors in this group were 4.5 and 14.3 times higher, respectively, than anticipated on the basis of the cancer registers of the GDR. The genotyping of all identified tumor patients for the polymorphic enzymes NAT2, GSTM1, and GSTT1 identified the urothelial tumor cases as exclusively 'slow acetylates'. A group of 161 miners highly exposed to DNT was investigated for signs of subclinical renal damage. The exposures were categorized semi-quantitatively into 'low', 'medium', 'high', and 'very high'. A straight dose-dependence of the excretion of urinary biomarker proteins with the ranking of exposure was seen. Biomarker excretion (alpha1-microglobulin, glutathione S-transferases alpha and pi) indicated that DNT-induced damage was directed toward the tubular system. New data on DNT-exposed humans appear consistent with the concept of cancer initiation by DNT isomers and the subsequent promotion of renal carcinogenesis by selective damage to the proximal tubule. The differential pathways of metabolic activation of DNT appear to apply to the proximal tubule of the kidney and to the urothelium of the renal pelvis and lower urinary tract as target tissues of carcinogenicity.