A Gain Scheduling Model Predictive Controller for Blood Glucose Control in Type 1 Diabetes

This paper presents a control strategy for blood glucose(BG) level regulation in type 1 diabetic patients. To design the controller, model-based predictive control scheme has been applied to a newly developed diabetic patient model. The controller is provided with a feedforward loop to improve meal compensation, a gain-scheduling scheme to account for different BG levels, and an asymmetric cost function to reduce hypoglycemic risk. A simulation environment that has been approved for testing of artificial pancreas control algorithms has been used to test the controller. The simulation results show a good controller performance in fasting conditions and meal disturbance rejection, and robustness against model–patient mismatch and errors in meal estimation

Predictive motion control of a mirosot mobile robot

This paper discusses predictive motion control of a MiRoSoT robot. The dynamic model of the robot is deduced by taking into account the whole process - robot, vision, control and transmission systems. Based on the obtained dynamic model, an integrated predictive control algorithm is proposed to position precisely with either stationary or moving obstacle avoidance. This objective is achieved automatically by introducing distant constraints into the open-loop optimization of control inputs. Simulation results demonstrate the feasibility of such control strategy for the deduced dynamic model

Using the PfEMP1 Head Structure Binding Motif to Deal a Blow at Severe Malaria

Plasmodium falciparum (Pf) malaria causes 200 million cases worldwide, 8 million being severe and complicated leading to similar to 1 million deaths and similar to 100,000 abortions annually. Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1) has been implicated in cytoadherence and infected erythrocyte rosette formation, associated with cerebral malaria; chondroitin sulphate-A attachment and infected erythrocyte sequestration related to pregnancy-associated malaria and other severe forms of disease. An endothelial cell high activity binding peptide is described in several of this similar to 300 kDa hypervariable protein's domains displaying a conserved motif (GACxPxRRxxLC); it established H-bonds with other binding peptides to mediate red blood cell group A and chondroitin sulphate attachment. This motif (when properly modified) induced PfEMP1-specific strain-transcending, fully-protective immunity for the first time in experimental challenge in Aotus monkeys, opening the way forward for a long sought-after vaccine against severe malaria.

Objective quality of life, optimism, and social-juridical variables, as predictive ones of the subjective quality of life in disarmed Colombian persons

The goal of this research was to identify predic- tive psychosocial factors of the subjective quality of life in a group of 60 people, with ages between 19 and 57, from both sexes, included in the program of demobilization and social inclusion of the Pro- grama de la Alta Consejería para la Reintegración Social y Económica de Personas y Grupos Alzados en Armas en Colombia. this research was a predic- tive correlational descriptive study. the Question- naire of optimism/Pessimism was used to assess the optimist or pessimist trend, and, for assess the quality of life, these strategies were combined: a home visit to value the objective quality of life, the Analogous scale of subjective Quality of Life to value satisfaction and well-being, and a general format to collect socio-demographic and juridical information. Results show that some variables as perceived health, optimism, educational level, re- ligious believes, objective quality of life, type of demobilization and years spent in the armed group operating outside the law, are associated to better levels of perceived quality of life. The findings and limitations of the study are discussed.  

A predictive study of reading comprehension in third-grade Spanish students

Resumen tomado de la publicación

Is semantic impairment a predictive sign for Alzheimer disease?

Resumen basado en el de la publicaci??n

Local model predictive control for navigation of a wheeled mobile robot using monocular information

Aquesta tesi està inspirada en els agents naturals per tal de planificar de manera dinàmica la navegació d'un robot diferencial de dues rodes. Les dades dels sistemes de percepció són integrades dins una graella d'ocupació de l'entorn local del robot. La planificació de les trajectòries es fa considerant la configuració desitjada del robot, així com els vértexs més significatius dels obstacles més propers. En el seguiment de les trajectòries s'utilitzen tècniques locals de control predictiu basades en el model, amb horitzons de predicció inferiors a un segon. La metodologia emprada és validada mitjançant nombrosos experiments.

Parameter sensitivity and predictive uncertainty in a new water quality model, Q(2)

A new dynamic model of water quality, Q(2), has recently been developed, capable of simulating large branched river systems. This paper describes the application of a generalized sensitivity analysis (GSA) to Q(2) for single reaches of the River Thames in southern England. Focusing on the simulation of dissolved oxygen (DO) (since this may be regarded as a proxy for the overall health of a river); the GSA is used to identify key parameters controlling model behavior and provide a probabilistic procedure for model calibration. It is shown that, in the River Thames at least, it is more important to obtain high quality forcing functions than to obtain improved parameter estimates once approximate values have been estimated. Furthermore, there is a need to ensure reasonable simulation of a range of water quality determinands, since a focus only on DO increases predictive uncertainty in the DO simulations. The Q(2) model has been applied here to the River Thames, but it has a broad utility for evaluating other systems in Europe and around the world.

Predictive vegetation mapping in the Mediterranean context: Considerations and methodological issues

The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.

Predictive empirical modelling of Orobanche life cycle and seed ecology

Abstract 1.7.4

Evaluation of a predictive model for Mycosphaerella graminicola for economic and environmental benefits

A method was developed to evaluate crop disease predictive models for their economic and environmental benefits. Benefits were quantified as the value of a prediction measured by costs saved and fungicide dose saved. The value of prediction was defined as the net gain made by using predictions, measured as the difference between a scenario where predictions are available and used and a scenario without prediction. Comparable 'with' and 'without' scenarios were created with the use of risk levels. These risk levels were derived from a probability distribution fitted to observed disease severities. These distributions were used to calculate the probability that a certain disease induced economic loss was incurred. The method was exemplified by using it to evaluate a model developed for Mycosphaerella graminicola risk prediction. Based on the value of prediction, the tested model may have economic and environmental benefits to growers if used to guide treatment decisions on resistant cultivars. It is shown that the value of prediction measured by fungicide dose saved and costs saved is constant with the risk level. The model could also be used to evaluate similar crop disease predictive models.

A predictive model for early-warning of Septoria leaf blotch on winter wheat

Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.