1,776 research outputs found
Predicting Attitudes Towards Transactional Sex: The Interactive Relationship Between Gender and Attitudes on Sexual Behaviour
Introduction: This article explores explanations for attitudes towards the acceptability of transactional sex. The sparse research investigating attitudes towards transactional sex uncovers a link between gender equality, or feminism, and a lack of support for the trade in sex. However, there are no research agendas that attempt to explain variance in attitudes towards transactional sex where support for gender equality is widespread throughout a population. Methods: We estimate regression models utilizing the 2017 Danish Values Survey (Den Danske Værdiundersøgelse) in order to predict views on the acceptability of transactional sex. Results: While the trade in sex is legal in Denmark, we find that a majority of respondents hold negative attitudes towards transactional sex, which conveys a lack of congruence between public opinion and policy. Further, gender is a powerful predictor of attitudes towards transactional sex, with women finding it less acceptable. In addition, the analysis uncovers that general attitudes towards sexual behaviour are the largest predictor of views on the acceptability of transactional sex. That being said, we find that men’s views on the acceptability of transactional sex are more of a function of their general attitudes towards sexual behaviour than they are for women. Conclusions: The findings indicate that, unlike men, women appear to differentiate between their attitudes towards general sexual behaviour and their views on sexual behaviour that they may associate with negative societal implications
High-resolution spatiotemporal weather models for climate studies
<p>Abstract</p> <p>Background</p> <p>Climate may exert a strong influence on health, in particular on vector-borne infectious diseases whose vectors are intrinsically dependent on their environment. Although critical, linking climate variability to health outcomes is a difficult task. For some diseases in some areas, spatially and temporally explicit surveillance data are available, but comparable climate data usually are not. We utilize spatial models and limited weather observations in Puerto Rico to predict weather throughout the island on a scale compatible with the local dengue surveillance system.</p> <p>Results</p> <p>We predicted monthly mean maximum temperature, mean minimum temperature, and cumulative precipitation at a resolution of 1,000 meters. Average root mean squared error in cross-validation was 1.24°C for maximum temperature, 1.69°C for minimum temperature, and 62.2 millimeters for precipitation.</p> <p>Conclusion</p> <p>We present a methodology for efficient extrapolation of minimal weather observation data to a more meaningful geographical scale. This analysis will feed downstream studies of climatic effects on dengue transmission in Puerto Rico. Additionally, we utilize conditional simulation so that model error may be robustly passed to future analyses.</p
Gravity vs radiation model: on the importance of scale and heterogeneity in commuting flows
We test the recently introduced radiation model against the gravity model for
the system composed of England and Wales, both for commuting patterns and for
public transportation flows. The analysis is performed both at macroscopic
scales, i.e. at the national scale, and at microscopic scales, i.e. at the city
level. It is shown that the thermodynamic limit assumption for the original
radiation model significantly underestimates the commuting flows for large
cities. We then generalize the radiation model, introducing the correct
normalisation factor for finite systems. We show that even if the gravity model
has a better overall performance the parameter-free radiation model gives
competitive results, especially for large scales.Comment: in press Phys. Rev. E, 201
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Evaluation of Internet-Based Dengue Query Data: Google Dengue Trends
Dengue is a common and growing problem worldwide, with an estimated 70–140 million cases per year. Traditional, healthcare-based, government-implemented dengue surveillance is resource intensive and slow. As global Internet use has increased, novel, Internet-based disease monitoring tools have emerged. Google Dengue Trends (GDT) uses near real-time search query data to create an index of dengue incidence that is a linear proxy for traditional surveillance. Studies have shown that GDT correlates highly with dengue incidence in multiple countries on a large spatial scale. This study addresses the heterogeneity of GDT at smaller spatial scales, assessing its accuracy at the state-level in Mexico and identifying factors that are associated with its accuracy. We used Pearson correlation to estimate the association between GDT and traditional dengue surveillance data for Mexico at the national level and for 17 Mexican states. Nationally, GDT captured approximately 83% of the variability in reported cases over the 9 study years. The correlation between GDT and reported cases varied from state to state, capturing anywhere from 1% of the variability in Baja California to 88% in Chiapas, with higher accuracy in states with higher dengue average annual incidence. A model including annual average maximum temperature, precipitation, and their interaction accounted for 81% of the variability in GDT accuracy between states. This climate model was the best indicator of GDT accuracy, suggesting that GDT works best in areas with intense transmission, particularly where local climate is well suited for transmission. Internet accessibility (average ∼36%) did not appear to affect GDT accuracy. While GDT seems to be a less robust indicator of local transmission in areas of low incidence and unfavorable climate, it may indicate cases among travelers in those areas. Identifying the strengths and limitations of novel surveillance is critical for these types of data to be used to make public health decisions and forecasting models
Public health for the people: participatory infectious disease surveillance in the digital age
The 21st century has seen the rise of Internet-based participatory surveillance systems for infectious diseases. These systems capture voluntarily submitted symptom data from the general public and can aggregate and communicate that data in near real-time. We reviewed participatory surveillance systems currently running in 13 different countries. These systems have a growing evidence base showing a high degree of accuracy and increased sensitivity and timeliness relative to traditional healthcare-based systems. They have also proven useful for assessing risk factors, vaccine effectiveness, and patterns of healthcare utilization while being less expensive, more flexible, and more scalable than traditional systems. Nonetheless, they present important challenges including biases associated with the population that chooses to participate, difficulty in adjusting for confounders, and limited specificity because of reliance only on syndromic definitions of disease limits. Overall, participatory disease surveillance data provides unique disease information that is not available through traditional surveillance sources
Asking About “Prostitution”, “Sex Work” and “Transactional Sex”: Question Wording and Attitudes Toward Trading Sexual Services
This study explored the impact of question wording on attitudes toward trading sexual services. There are no previous research agendas investigating how views on the trade in sex are susceptible to question word choice. We utilized an original survey to assess how three different concepts used to represent the exchange of sexual services impact on the reported level of acceptability among respondents. The concepts we selected were “prostitution,” “sex work”, and “transactional sex.” We also explored the contrasting effects of predictor variables based on question wording, such as general sexual attitudes and positive and negative associations with trading sex. We found that attitudes toward the trading of sex is partially a function of question wording. Respondents were more likely to translate negative associations with the exchange of sexual services into unacceptability when assigned a question using the term prostitution. The results indicated that prostitution is a stigmatized word, resonating more negatively with respondents as compared to sex work or transactional sex. When asked about transactional sex, respondents were less likely to translate an attitude into an assessment on acceptability, indicating that the term is vague. Sex work elicited more neutral responses on acceptability. The results suggest that sex work would be the most useful term to use in dialogue and debate regarding the trade in sexual services. Sex work does not appear to be imbued with the same sense of negativity as prostitution and the meaning of sex work seems clearer than transactional sex.</p
A quantitative central limit theorem for linear statistics of random matrix eigenvalues
It is known that the fluctuations of suitable linear statistics of Haar
distributed elements of the compact classical groups satisfy a central limit
theorem. We show that if the corresponding test functions are sufficiently
smooth, a rate of convergence of order almost can be obtained using a
quantitative multivariate CLT for traces of powers that was recently proven
using Stein's method of exchangeable pairs.Comment: Title modified; main result stated under slightly weaker conditions;
accepted for publication in the Journal of Theoretical Probabilit
Evaluating the Performance of Infectious Disease Forecasts: A Comparison of Climate-Driven and Seasonal Dengue Forecasts for Mexico
Dengue viruses, which infect millions of people per year worldwide, cause large epidemics that strain healthcare systems. Despite diverse efforts to develop forecasting tools including autoregressive time series, climate-driven statistical, and mechanistic biological models, little work has been done to understand the contribution of different components to improved prediction. We developed a framework to assess and compare dengue forecasts produced from different types of models and evaluated the performance of seasonal autoregressive models with and without climate variables for forecasting dengue incidence in Mexico. Climate data did not significantly improve the predictive power of seasonal autoregressive models. Short-term and seasonal autocorrelation were key to improving short-term and long-term forecasts, respectively. Seasonal autoregressive models captured a substantial amount of dengue variability, but better models are needed to improve dengue forecasting. This framework contributes to the sparse literature of infectious disease prediction model evaluation, using state-of-the-art validation techniques such as out-of-sample testing and comparison to an appropriate reference model
Fluctuation properties of the TASEP with periodic initial configuration
We consider the joint distributions of particle positions for the continuous
time totally asymmetric simple exclusion process (TASEP). They are expressed as
Fredholm determinants with a kernel defining a signed determinantal point
process. We then consider certain periodic initial conditions and determine the
kernel in the scaling limit. This result has been announced first in a letter
by one of us and here we provide a self-contained derivation. Connections to
last passage directed percolation and random matrices are also briefly
discussed.Comment: 33 pages, 4 figure, LaTeX; We added several references to the general
framework and techniques use
Effect of Molecular Organization on the Properties of Fractionated Lignin-Based Thiol–Ene Thermoset Materials
In this study, the combination of sequential solvent fractionation of technical Kraft lignin was followed by allylation of most OH functionalities to give highly functional thermoset resins. All lignin fractions were highly functionalized on the phenolic (≥95%) and carboxylic acid OH (≥85%) and to a significant extent on the aliphatic OH moieties (between 43 and 75%). The resins were subsequently cross-linked using thiol–ene chemistry. The high amount of allyl functionalities resulted in a high cross-link density. Dynamic mechanical analysis measurements showed that the thioether content, directly related to the allyl content, strongly affects the performance of these thermosets with a glass transition temperature () between 81 and 95 °C and with a storage modulus between 1.9 and 3.8 GPa for all thermosets. The lignin fractions and lignin-based thermosets’ morphology, at the nanoscale, was studied by wide-angle X-ray scattering measurements. Two π–π stacking interactions were observed: sandwich (≈4.1–4.7 Å) and T-shaped (≈5.5–7.2 Å). The introduction of allyl functionalities weakens the T-shaped π–π stacking interactions. A new signal corresponding to a distance of ≈3.5 Å was observed in lignin-based thermosets, which was attributed to a thioether organized structure. At the same time, a lignin superstructure was observed with a distance/size corresponding to 7.9–17.5 Å in all samples
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