Automated multigravity assist trajectory planning with a modified ant colony algorithm

The paper presents an approach to transcribe a multigravity assist trajectory design problem into an integrated planning and scheduling problem. A modified Ant Colony Optimization (ACO) algorithm is then used to generate optimal plans corresponding to optimal sequences of gravity assists and deep space manoeuvers to reach a given destination. The modified Ant Colony Algorithm is based on a hybridization between standard ACO paradigms and a tabu-based heuristic. The scheduling algorithm is integrated into the trajectory model to provide a fast time-allocation of the events along the trajectory. The approach demonstrated to be very effective on a number of real trajectory design problems

Autonomous distributed LQR/APF control algorithms for CubeSat swarms manoeuvring in eccentric orbits

Spacecraft formation flying has shown to be promising approach to enhance mission capabilities. Nevertheless, formation flying presents several control challenges which escalate as the numbers of elements in the formation is increased. The objective of this paper is to develop decentralised control algorithms to regulate the station-keeping, reconfiguration and collision avoidance of spacecraft in formation around eccentric reference orbits using the combination of a Linear Quadratic Regulator (LQR) and an Artificial Potential Function (APF). Within this control scheme, the LQR will provide station-keeping and reconfiguration capabilities toward desired positions, while optimizing fuel consumption and the APF will ensure collision free manoeuvres between the elements of the formation during manoeuvres. The controller is designed under the assumption of continuous thrust as a standard LQR problem using the Pontryagin minimum principle, an APF based in normalized Gaussian functions and the Tschauner and Hempel (TH) equations as the relative dynamics model

An approach to model interest for planetary rover through Dezert–Smarandache theory

In this paper, we propose an approach for assigning an interest level to the goals of a planetary rover. Assigning an interest level to goals allows the rover autonomously to transform and reallocate the goals. The interest level is defined by data-fusing payload and navigation information. The fusion yields an "interest map" that quantifies the level of interest of each area around the rover. In this way the planner can choose the most interesting scientific objectives to be analyzed, with limited human intervention, and reallocates its goals autonomously. The Dezert-Smarandache Theory of Plausible and Paradoxical Reasoning was used for information fusion: this theory allows dealing with vague and conflicting data. In particular, it allows us directly to model the behavior of the scientists that have to evaluate the relevance of a particular set of goals. The paper shows an application of the proposed approach to the generation of a reliable interest map

Perspective: How good is DFT for water?

Kohn-Sham density functional theory (DFT) has become established as an indispensable tool for investigating aqueous systems of all kinds, including those important in chemistry, surface science, biology and the earth sciences. Nevertheless, many widely used approximations for the exchange-correlation (XC) functional describe the properties of pure water systems with an accuracy that is not fully satisfactory. The explicit inclusion of dispersion interactions generally improves the description, but there remain large disagreements between the predictions of different dispersion-inclusive methods. We present here a review of DFT work on water clusters, ice structures and liquid water, with the aim of elucidating how the strengths and weaknesses of different XC approximations manifest themselves across this variety of water systems. Our review highlights the crucial role of dispersion in describing the delicate balance between compact and extended structures of many different water systems, including the liquid. By referring to a wide range of published work, we argue that the correct description of exchange-overlap interactions is also extremely important, so that the choice of semi-local or hybrid functional employed in dispersion-inclusive methods is crucial. The origins and consequences of beyond-2-body errors of approximate XC functionals are noted, and we also discuss the substantial differences between different representations of dispersion. We propose a simple numerical scoring system that rates the performance of different XC functionals in describing water systems, and we suggest possible future developments

Analysis of 22 mutations within milk protein genes in Italian Friesian cattle

The bovine milk protein caseins, αS1-CN, β-CN, αS2-CN, and κ-CN are codified by four well characterized genes, named CSN1S1, CSN2, CSN1S2, and CSN3 respectively and clustered in a region of 250-kb of chromosome 6. A recent revision of milk protein nomenclature considering only protein polymorphisms indicates 8 αS1-CN, 4 αS2-CN, 12 β-CN, and 11 κ-CN variants within the genus Bos. Other mutations were found in the non-coding regions of the cluster, such as the promoter regions or the 3'UTR. Many of these polymorphisms, together with others in various genes, such as the one coding for β-lactoglobulin (LGB), show important associations with different milk quality traits. Analyzing all these polymorphisms could help clarify the role of both the casein haplotype and the other polymorphisms in milk composition and cheese-making properties, and could explain which polymorphisms are really or mostly involved. The mPCR-LDR-UA approach recently developed to test simultaneously 22 SNPs in DNA regions responsible for milk protein expression was used to type 250 Italian Friesian cattle. In perfect agreement with literature, the most frequent alleles were CSN1S1*B, CSN2*A2, CSN3*A, variant 2 of CSN1S1 promoter, and variant A of Bov-A2 element. A quite balanced frequency was observed for the LGB*A and LGB*B. No CSN2*C, CSN3*C, and CSN3*H alleles were found. The CSN1S1*C, CSN2*A3, CSN2*I alleles were detected only at the heterozygous condition and at a frequency lower than 2%. The method allowed also finding some unusual intragenic haplotype, such as the Bov-A2 element-CSN3 haplotypes A-B and B-E. As to LGB one of the four SNPs tested was always homozygous for the same mutation, as already noticed. This finding confirms that this synonymous SNP is probably a sequencing mistake or a rare mutation not decisive for the LGB typing in the Italian Friesian. Reducing cost and time for typing simultaneously many SNPs, the method will be applied to a greater number of individuals and to other breeds, aiming to find out a number of animals for each haplotype sufficient for accurate statistical analysis to give a better understanding of the significance of milk protein polymorphism

Genetic variability of the ovine αs1-casein

The casein genetic polymorphisms are important for their effects on quantitative traits and technological properties of milk. At the αs1-casein (CSN1S1) level three genetic variants were characterised (A, C, D) in ovine milk (Ferranti et al., 1995)

Kinetic Enzymatic Determination of Creatinine by a Rapid Semiautomated Procedure

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