A robust Bayesian land use model for crop rotations

Often, in dynamical systems, such as farmers’ crop choices, the dynamics are driven by external non-stationary factors, such as rainfall and agricultural input and output prices. Such dynamics can be modelled by a non-stationary stochastic process, where the transition probabilities are functions of such external factors. We propose using a multinomial logit model for these transition probabilities, and investigate the problem of estimating the parameters of this model from data. We adapt the work of Chen and Ibrahim to propose a conjugate prior distribution for the parameters of the multinomial logit model. Inspired by the imprecise Dirichlet model, we will perform a robust Bayesian analysis by proposing a fairly broad class of prior distributions, in order to accommodate scarcity of data and lack of strong prior expert opinion. We discuss the computation of bounds for the posterior transition probabilities, using a variety of calculation methods. These sets of posterior transition probabilities mean that our land use model consists of a non-stationary imprecise stochastic process. We discuss computation of future events in this process. Finally, we use our novel land use model to investigate real-world data. We investigate the impact of external variables on the posterior transition probabilities, and investigate a scenario for future crop growth. We also use our model to solve a hypothetical yet realistic policy problem

Logistic regression on Markov chains for crop rotation modelling.

Often, in dynamical systems, such as farmer's crop choices, the dynamics is driven by external non-stationary factors, such as rainfall, temperature, and economy. Such dynamics can be modelled by a non-stationary Markov chain, where the transition probabilities are logistic functions of such external factors. We investigate the problem of estimating the parameters of the logistic model from data, using conjugate analysis with a fairly broad class of priors, to accommodate scarcity of data and lack of strong prior expert opinions. We show how maximum likelihood methods can be used to get bounds on the posterior mode of the parameters

A robust Bayesian analysis of the impact of policy decisions on crop rotations.

We analyse the impact of a policy decision on crop rotations, using the imprecise land use model that was developed by the authors in earlier work. A specific challenge in crop rotation models is that farmer’s crop choices are driven by both policy changes and external non-stationary factors, such as rainfall, temperature and agricultural input and output prices. Such dynamics can be modelled by a non-stationary stochastic process, where crop transition probabilities are multinomial logistic functions of such external factors. We use a robust Bayesian approach to estimate the parameters of our model, and validate it by comparing the model response with a non-parametric estimate, as well as by cross validation. Finally, we use the resulting predictions to solve a hypothetical yet realistic policy problem

Hypertension:A problem of organ blood flow supply-demand mismatch

This review introduces a new hypothesis that sympathetically mediated hypertensive diseases are caused, in the most part, by the activation of visceral afferent systems that are connected to neural circuits generating sympathetic activity. We consider how organ hypoperfusion and blood flow supply–demand mismatch might lead to both sensory hyper-reflexia and aberrant afferent tonicity. We discuss how this may drive sympatho-excitatory-positive feedback and extend across multiple organs initiating, or at least amplifying, sympathetic hyperactivity. The latter, in turn, compounds the challenge to sufficient organ blood flow through heightened vasoconstriction that both maintains and exacerbates hypertension

Relationship between markers of malnutrition and clinical outcomes in older adults with cancer: systematic review, narrative synthesis and meta-analysis

© 2020, The Author(s). Malnutrition predicts poorer clinical outcomes for people with cancer. Older adults with cancer are a complex, growing population at high risk of weight-losing conditions. A number of malnutrition screening tools exist, however the best screening tool for this group is unknown. The aim was to systematically review the published evidence regarding markers and measures of nutritional status in older adults with cancer (age ≥ 70). A systematic search was performed in Ovid Medline, EMBASE, Web of Science, CINAHL, British Nursing Database and Cochrane CENTRAL; search terms related to malnutrition, cancer, older adults. Titles, abstracts and papers were screened and quality-appraised. Data evaluating ability of markers of nutritional status to predict patient outcomes were subjected to meta-analysis or narrative synthesis. Forty-two studies, describing 15 markers were included. Meta-analysis found decreased food intake was associated with mortality (OR 2.15 [2.03–4.20] p = < 0.00001) in univariate analysis. Prognostic Nutritional Index (PNI) was associated with overall survival (HR 1.89 [1.03–3.48] p = 0.04). PNI markers (albumin, total lymphocyte count) could be seen as markers of inflammation rather than nutrition. There a suggested relationship between very low body mass index (BMI)

Logistic Regression on Markov Chains for Crop Rotation Modelling

Often, in dynamical systems, such as farmer's crop choices, the dynamics is driven by external non-stationary factors, such as rainfall, temperature, and economy. Such dynamics can be modelled by a non-stationary Markov chain, where the transition probabilities are logistic functions of such external factors. We investigate the problem of estimating the parameters of the logistic model from data, using conjugate analysis with a fairly broad class of priors, to accommodate scarcity of data and lack of strong prior expert opinions. We show how maximum likelihood methods can be used to get bounds on the posterior mode of the parameters