Preliminary space mission design under uncertainty

This paper proposes a way to model uncertainties and to introduce them explicitly in the design process of a preliminary space mission. Traditionally, a system margin approach is used in order to take them into account. In this paper, Evidence Theory is proposed to crystallise the inherent uncertainties. The design process is then formulated as an Optimisation Under Uncertainties (OUU). Three techniques are proposed to solve the OUU problem: (a) an evolutionary multi-objective approach, (b) a step technique consisting of maximising the belief for different levels of performance, and (c) a clustering method that firstly identifes feasible regions. The three methods are applied to the BepiColombo mission and their effectiveness at solving the OUU problem are compared

A comparative assessment of different deviation strategies for dangerous NEO

In this paper a number of deviation strategies for dangerous Near Earth Objects (NEO) have been compared. For each strategy (i.e. Solar Collector, Nuclear Blast, Kinetic Impactor, Low-thrust Propulsion, Mass Driver) a multi criteria optimisation method has been used to reconstruct the set of Pareto optimal solutions minimising the mass of the spacecraft and the warning time, and maximising the deviation. Then, a dominance criterion has been defined and used to compare all the Pareto sets. The achievable deviation at the MOID, either for a low-thrust or for an impulsive variation of the orbit of the NEO, has been computed through a set of analytical formulas. The variation of the orbit of the NEO has been estimated through a deviation action model that takes into account the wet mass of the spacecraft at the Earth. Finally the technology readiness level of each strategy has been used to compute a more realistic value for the required warning time

Flower development and pollen vitality of moringa oleifera lam. Grown in a humid temperate climatic condition

Moringa oleifera is a tropical tree cultivated in many countries. This species has acquired a great importance in human nutrition and it was recently indicated as a “novel food” by the European Commission. Recently, moringa plants have been introduced in humid temperate climatic areas, among which Moreno (Buenos Aires Province-Argentina). In such area, the cultivation is possible for the production of leaves, but plants need protection during winter time in order to overcome damages due to low temperatures and hence to produce capsules and seeds. The main objective of this research was to study flower morphology and anatomy of M. oleifera, as well as microsporogenesis and viability of pollen grains of plants cultivated in Moreno in comparison with those produced in a humid sub-tropical climatic area of Argentina (San Miguel de Tucumán). Flowers grown in the temperate environment resulted similar for morphological parameters to those observed in the sub-tropical environment. Nevertheless, pollen grain fertility depended directly on air temperature and it was negatively affected by the lower temperatures registered in the temperate site. According to the observed results, pollen viability increases with mean monthly temperatures above 16°C.Fil: Radice, Silvia. Universidad de Moron. Facultad de Agronomia y Ciencias Agroalimentarias. Laboratorio de Investigaciones En Fisiología Vegetal; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Giordani, Edgardo. Università degli Studi di Firenze; Itali

Image-based Lagrangian Particle Tracking in bed-load experiments

Image analysis has been increasingly used for the measurement of river flows due to its capabilities to furnish detailed quantitative depictions at a relatively low cost. This manuscript describes an application of particle tracking velocimetry (PTV) to a bed-load experiment with lightweight sediment. The key characteristics of the investigated sediment transport conditions were the presence of a covered flow and of a fixed rough bed above which particles were released in limited number at the flume inlet. Under the applied flow conditions, the motion of the individual bed-load particles was intermittent, with alternating movement and stillness terms. The flow pattern was preliminarily characterized by acoustic measurements of vertical profiles of the stream-wise velocity. During process visualization, a large field of view was obtained using two actioncameras placed at different locations along the flume. The experimental protocol is described in terms of channel calibration, experiment realization, image pre-processing, automatic particle tracking, and post-processing of particle track data from the two cameras. The presented proof-of-concept results include probability distributions of the particle hop length and duration. The achievements of this work are compared to those of existing literature to demonstrate the validity of the protocol

Assessment of diagnostic value of dipyridamole testing in angina pectoris.

Summary: In order to assess the diagnostic value of dipyridamole (D) testing, we studied the responses of 34 patients with chest pain and 10 normal subjects. Blood pressure and 12-lead ECG were recorded during and after intravenous infusion of 0.6 mg/kg dipyridamole for 10 minutes. Coronary arteriography and maximal or symptom-limited exercise tests were performed in the 34 patients with chest pain. During infusion 13 patients presented ischemic ST changes and 5 with anginal pain only. The latter group had normal coronary arteries. Among the 13 patients with ischemic ST changes, 7 had at least two critical coronary stenoses and the remaining 6 had no coronary lesions. Dipyridamole tests showed poor sensitivity (44%) and specificity (39%) with respect to coronary arteriography. The relatively high number of positive responses in subjects with normal coronary arteries indicates that the coronary steal phenomenon is not the sole cause of "ischemic" response to the drug. Indirect indexes of myocardial oxygen consumption were higher in patients with a positive response to drug infusion than in those with a negative response; however the value of rate-pressure product at infusion end never reached that observed at ischemic threshold during exercise testing in the same patient. This suggests that neither can oxygen consumption increase be considered as entirely responsible for ischemic response to dipyridamole. In conclusion dipyridamole test cannot be proposed for predicting critical coronary stenoses

Evaluating treatment effectiveness under model misspecification : a comparison of targeted maximum likelihood estimation with bias-corrected matching

Statistical approaches for estimating treatment effectiveness commonly model the endpoint, or the propensity score, using parametric regressions such as generalised linear models. Misspecification of these models can lead to biased parameter estimates. We compare two approaches that combine the propensity score and the endpoint regression, and can make weaker modelling assumptions, by using machine learning approaches to estimate the regression function and the propensity score. Targeted maximum likelihood estimation is a double-robust method designed to reduce bias in the estimate of the parameter of interest. Bias-corrected matching reduces bias due to covariate imbalance between matched pairs by using regression predictions. We illustrate the methods in an evaluation of different types of hip prosthesis on the health-related quality of life of patients with osteoarthritis. We undertake a simulation study, grounded in the case study, to compare the relative bias, efficiency and confidence interval coverage of the methods. We consider data generating processes with non-linear functional form relationships, normal and non-normal endpoints. We find that across the circumstances considered, bias-corrected matching generally reported less bias, but higher variance than targeted maximum likelihood estimation. When either targeted maximum likelihood estimation or bias-corrected matching incorporated machine learning, bias was much reduced, compared to using misspecified parametric models

Modelling the extremes of seasonal viruses and hospital congestion: The example of flu in a Swiss hospital

Viruses causing flu or milder coronavirus colds are often referred to as ‘seasonal viruses’ as they tend to subside in warmer months. In other words, meteorological conditions tend to impact the activity of viruses, and this information can be exploited for the operational management of hospitals. In this study, we use 3 years of daily data from one of the biggest hospitals in Switzerland and focus on modelling the extremes of hospital visits from patients showing flu-like symptoms and the number of positive flu cases. We propose employing a discrete generalized Pareto distribution for the number of positive and negative cases. Our modelling framework allows for the parameters of these distributions to be linked to covariate effects, and for outlying observations to be dealt with via a robust estimation approach. Because meteorological conditions may vary over time, we use meteorological and not calendar variations to explain hospital charge extremes, and our empirical findings highlight their significance. We propose a measure of hospital congestion and a related tool to estimate the resulting CaRe (Charge-at-Risk-estimation) under different meteorological conditions. The relevant numerical computations can be easily carried out using the freely available GJRM R package. The empirical effectiveness of the proposed method is assessed through a simulation study