38 resultados para happiness, utility functions, correlation analysis, personal income, economic models
Resumo:
We present a new Bayesian econometric specification for a hypothetical Discrete Choice Experiment (DCE) incorporating respondent ranking information about attribute importance. Our results indicate that a DCE debriefing question that asks respondents to rank the importance of attributes helps to explain the resulting choices. We also examine how mode of survey delivery (online and mail) impacts model performance, finding that results are not substantively a§ected by the mode of survey delivery. We conclude that the ranking data is a complementary source of information about respondent utility functions within hypothetical DCEs
Resumo:
The time scale of the response of the high-latitude dayside ionospheric flow to changes in the North-South component of the interplanetary magnetic field (IMF) has been investigated by examining the time delays between corresponding sudden changes. Approximately 40 h of simultaneous IMF and ionospheric flow data have been examined, obtained by the AMPTE-UKS and -IRM spacecraft and the EISCAT “Polar” experiment, respectively, in which 20 corresponding sudden changes have been identified. Ten of these changes were associated with southward turnings of the IMF, and 10 with northward turnings. It has been found that the corresponding flow changes occurred simultaneously over the whole of the “Polar” field-of-view, extending more than 2° in invariant latitude, and that the ionospheric response delay following northward turnings is the same as that following southward turnings, though the form of the response is different in the two cases. The shortest response time, 5.5 ± 3.2 min, is found in the early- to mid-afternoon sector, increasing to 9.5 ± 3.0 min in the mid-morning sector, and to 9.5 ± 3.1 min near to dusk. These times represent the delays in the appearance of perturbed flows in the “Polar” field-of-view following the arrival of IMF changes at the subsolar magnetopause. Overall, the results agree very well with those derived by Etemadi et al. (1988, Planet. Space Sci.36, 471) from a general cross-correlation analysis of the IMF Bz and “Polar” beam-swinging vector flow data.
Resumo:
Producing according to enhanced farm animal welfare (FAW) standards increases costs along the livestock value chain, especially for monitoring certified animal friendly products. In the choice between public or private bodies for carrying out and monitoring certification, consumer preferences and trust play a role. We explore this issue by applying logit analysis involving socio-economic and psychometric variables to survey data from Italy. Results identify marked consumer preferences for public bodies and trust in stakeholders a key determinant.
Resumo:
Background: The electroencephalogram (EEG) may be described by a large number of different feature types and automated feature selection methods are needed in order to reliably identify features which correlate with continuous independent variables. New method: A method is presented for the automated identification of features that differentiate two or more groups inneurologicaldatasets basedupona spectraldecompositionofthe feature set. Furthermore, the method is able to identify features that relate to continuous independent variables. Results: The proposed method is first evaluated on synthetic EEG datasets and observed to reliably identify the correct features. The method is then applied to EEG recorded during a music listening task and is observed to automatically identify neural correlates of music tempo changes similar to neural correlates identified in a previous study. Finally,the method is applied to identify neural correlates of music-induced affective states. The identified neural correlates reside primarily over the frontal cortex and are consistent with widely reported neural correlates of emotions. Comparison with existing methods: The proposed method is compared to the state-of-the-art methods of canonical correlation analysis and common spatial patterns, in order to identify features differentiating synthetic event-related potentials of different amplitudes and is observed to exhibit greater performance as the number of unique groups in the dataset increases. Conclusions: The proposed method is able to identify neural correlates of continuous variables in EEG datasets and is shown to outperform canonical correlation analysis and common spatial patterns.
Resumo:
5-Hydroxymethylcytosine (5hmC), a modified form of cytosine that is considered the sixth nucleobase in DNA, has been detected in mammals and is believed to play an important role in gene regulation. In this study, 5hmC modification was detected in rice by employing a dot-blot assay, and its levels was further quantified in DNA from different rice tissues using liquid chromatography-multistage mass spectrometry (LC-MS/MS/MS). The results showed large intertissue variation in 5hmC levels. The genome-wide profiles of 5hmC modification in three different rice cultivars were also obtained using a sensitive chemical labelling followed by a next-generation sequencing method. Thousands of 5hmC peaks were identified, and a comparison of the distributions of 5hmC among different rice cultivars revealed the specificity and conservation of 5hmC modification. The identified 5hmC peaks were significantly enriched in heterochromatin regions,and mainly located in transposable element (TE) genes, especially around retrotransposons. The correlation analysis of 5hmC and gene expression data revealed a close association between 5hmC and silent TEs. These findings provide a resource for plant DNA 5hmC epigenetic studies and expand our knowledge of 5hmC modification.
Resumo:
Parents have large genetic and environmental influences on offspring’s cognition, behavior, and brain. These intergenerational effects are observed in mood disorders, with particularly robust association in depression between mothers and daughters. No studies have thus far examined the neural bases of these intergenerational effects in humans. Corticolimbic circuitry is known to be highly relevant in a wide range of processes including mood regulation and depression. These findings suggest that corticolimbic circuitry may also show matrilineal transmission patterns. We therefore examined human parent-offspring association in this neurocircuitry, and investigated the degree of association in gray matter volume between parent and offspring. We used voxel-wise correlation analysis in a total of 35 healthy families, consisting of parents and their biological offspring. We found positive associations of regional grey matter volume in the corticolimbic circuit including the amygdala, hippocampus, anterior cingulate cortex, and ventromedial prefrontal cortex between biological mothers and daughters. This association was significantly greater than mother-son, father-daughter, and father-son associations. The current study suggests that the corticolimbic circuitry, which has been implicated in mood regulation, shows a matrilineal specific transmission patterns. Our preliminary findings are consistent with what has been found behaviorally in depression, and may have clinical implications for disorders known to have dysfunction in mood regulation such as depression. Studies such as ours will likely bridge animal work examining gene expression in the brains and clinical symptom-based observations, and provide promising ways to investigate intergenerational transmission patterns in the human brain.
Resumo:
Lagged correlation analysis is often used to infer intraseasonal dynamical effects but is known to be affected by non-stationarity. We highlight a pronounced quasi-two-year peak in the anomalous zonal wind and eddy momentum flux convergence power spectra in the Southern Hemisphere, which is prima facie evidence for non-stationarity. We then investigate the consequences of this non-stationarity for the Southern Annular Mode and for eddy momentum flux convergence. We argue that positive lagged correlations previously attributed to the existence of an eddy feedback are more plausibly attributed to non-stationary interannual variability external to any potential feedback process in the mid-latitude troposphere. The findings have implications for the diagnosis of feedbacks in both models and re-analysis data as well as for understanding the mechanisms underlying variations in the zonal wind.
Resumo:
Epidemiological studies have shown protective effects of fruits and vegetables (F&V) in lowering the risk of developing cardiovascular diseases (CVD) and cancers. Plant-derived dietary fibre (non-digestible polysaccharides) and/or flavonoids may mediate the observed protective effects particularly through their interaction with the gut microbiota. The aim of this study was to assess the impact of fruit and vegetable (F&V) intake on gut microbiota, with an emphasis on the role of flavonoids, and further to explore relationships between microbiota and factors associated with CVD risk. In the study, a parallel design with 3 study groups, participants in the two intervention groups representing high-flavonoid (HF) and low flavonoid (LF) intakes were asked to increase their daily F&V intake by 2, 4 and 6 portions for a duration of 6 weeks each, while a third (control) group continued with their habitual diet. Faecal samples were collected at baseline and after each dose from 122 subjects. Faecal bacteria enumeration was performed by fluorescence in situ hybridisation (FISH). Correlations of dietary components, flavonoid intake and markers of CVD with bacterial numbers were also performed. A significant dose X treatment interaction was only found for Clostidium leptum-Ruminococcus bromii/flavefaciens with a significant increase after intake of 6 additional portions in the LF group. Correlation analysis of the data from all 122 subjects independent from dietary intervention indicated an inhibitory role of F&V intake, flavonoid content and sugars against the growth of potentially pathogenic clostridia. Additionally, we observed associations between certain bacterial populations and CVD risk factors including plasma TNF-α, plasma lipids and BMI/waist circumference.