Seasonal patterns, as they occur in time series of infectious disease surveillance counts, are frequently modelled using a superposition of sine and cosine functions. However, in some cases this might be too simple. We propose the use of circular second order random walks instead and extend this approach to multivariate time series of counts. A correlated Gaussian Markov random field approach c...

background: migrant farmworkers are prone to several psychosocial stressors. objective: to investigate the effect of perceived psychosocial factors on pesticide exposure among seasonal migrant hispanic farmworkers in north carolina, usa. methods: a cross-sectional interview survey of 187 seasonal migrant farmworkers of mexican descent, identified from labor camps located in rural counties in no...

temperature and precipitation are among important atmospheric parameters for watershed planning. assessment of temperature and precipitation trends is very important for future watershed planning. in this paper, trends of atmospheric parameters such as seasonal and annual temperature and precipitation were examined for the synoptic stations of bandar anzali, rasht, ramsar, babolsar and gorgan. ...

Agricultural drought is the leading cause for crop failure throughout the world. In the USA, significant impacts of recent droughts on agricultural production indicate the continuing vulnerability of the country to drought. This paper presents a methodology for spatial representation of the agroclimatic component of agricultural drought vulnerability. This methodology was developed as a part of...

Estimation of crop production can be a very useful tool while planning a nation’s agriculture. The use of statistical techniques in developing such tools is a popular and well studied problem. In this paper, we present a statistical model that predicts the total crop production for a geographical region, given the season of harvest and the total land used. We apply this model on four major crop...

We shed light on a class of models that increase the flexibility of the seasonal pattern within a framework of the structural time series model. The basic idea is to drive the seasonal summation model by a moving average process rather than by a white noise or an AR process. Generally, such an approach can be exhaustive in parameters, but the proposed model is parsimonious in the sense that we ...

[1] This study uses a Bayesian approach to merge ensemble seasonal climate forecasts generated by multiple climate models for better probabilistic and deterministic forecasting. Within the Bayesian framework, the climatological distribution of the variable of interest serves as the prior, and the likelihood function is developed with a weighted linear regression between the climate model hindca...

The background field approach to multi-loop calculations in gauge field theories is presented. A relation between the gauge-invariant effective action computed using this method and the effective action of the conventional functional approach is derived. Feynman rules are given and renormalization is discussed. It is shown that the renormalization programme can be carried out without any refere...

This talk presents details of the calculation of two-loop corrections to heavy baryon currents containing one heavy quark in leading order of the 1/mQ-expansion, i.e. in the limit of Heavy Quark Symmetry (HQS). The calculations lead to the determination of the anomalous dimension of these currents. I also discuss problems with different γ5-schemes and their solution by the finite renormalizatio...

Success in higher education depends on students’ ability to meet the writing requirements of their chosen courses, and in many cases this involves adapting to the literacy practices of particular disciplines. While research into professional academic discourse suggests that it may reflect differences in disciplinary culture and epistemology, there has been relatively little investigation of dis...