The design of a spacecraft trajectory can be formulated as a global optimization task. The complexity of the resulting problem depends greatly on the final target planet, the chosen spacecraft intermediate route, and the type of engine and power system available on-board. Few attempts have been made to directly use a global optimization framework to design trajectories that make use of low-thrust propulsion because of the large scale and extreme complexity of the resulting non-linear programming problem. The presence of non-convex constraints, in particular, requires the use of solvers able to deal with such an added complexity. Here, the Sims–Flanagan transcription method is proposed to model the low-thrust trajectory design as a constrained global optimization problem. Then, two different solvers are applied: basin hopping and simulated annealing with adaptive neighbourhood. Both algorithms are hybridized with a local search. Two different interplanetary trajectories are considered: an Earth–Earth–Jupiter transfer with a nuclear electric propulsion spacecraft inspired by the Jupiter Icy Moons Orbiter and a transfer to Mercury inspired by the BepiColombo mission. For both problems, the proposed approach proves to be able to explore automatically the vast solution space, producing a large number of trajectories in a large range of final mass and flight times, proving the possibility to apply global optimization techniques directly to the low-thrust problem.
In this paper we introduce the LeGO (Learning for Global Optimization) approach for global optimization in which machine learning is used to predict the outcome of a computationally expensive global optimization run, based upon a suitable training performed by standard runs of the same global optimization method. We propose to use a Support Vector Machine (although different machine learning tools might be employed) to learn the relationship between the starting point of an algorithm and the final outcome (which is usually related to the function value at the point returned by the procedure). Numerical experiments performed both on classical test functions and on difficult space trajectory planning problems show that the proposed approach can be very effective in identifying good starting points for global optimization.
The ␣ subunit of cone transducin (T␣C) is expressed exclusively in cone photoreceptors of the eye and pineal. T␣C is a key phototransduction protein, and inherited mutations in T␣C cause total color blindness in humans. We use transgenic zebrafish to identify and characterize cone photoreceptor regulatory element 1 (CPRE-1) a novel 20-bp enhancer element in the T␣C promoter (T␣CP). CPRE-1 is located ϳ2.5 kb upstream of the translation start site and is necessary for strong cone photoreceptor-specific expression in vivo. CPRE-1 comprises of a modular arrangement of two 10-bp elements that have separate, but co-dependent transcriptional activities. In vitro, CPRE-1 specifically binds nuclear factors that are enriched in ocular tissue. Bioinformatic alignments reveal that CPRE-1 sites are evolutionarily conserved in the promoter regions of fish, rodent, and mammalian T␣C orthologues and identify a 5-CTGGAGTG(A/T)TGGA(G/A)G-CAGGG(G/C)T-3 consensus sequence.The vertebrate retina contains distinct cone and rod photoreceptors that mediate scotopic and photopic vision, respectively (1). Although cones and rods originate from the same population of retinal progenitor cells, they have unique gene expression profiles that account for their differential cell fate, morphology, and signal transduction mechanisms. For example, many components of the G protein-coupled receptor phototransduction cascade are encoded by cone-or rod-specific genes (1). The molecular genetics underpinning cone photoreceptor-specific gene expression remain poorly defined.Several transcription factors, including Crx, Nr2e3, Nrl, and Tr2, regulate photoreceptor-specific gene expression. Cone rod homeobox is expressed in photoreceptors, and cone rod homeobox depletion leads to a developmental loss of both cone and rod photoreceptors in mice and zebrafish and to blindness in humans (2-4). Nr2e3 and Nrl are expressed in rods where they repress expression of cone-specific genes (5-10). Mutations in Nr2e3 or Nrl lead to rods inappropriately expressing cone-specific markers and to the human retinal disease enhanced S-cone syndrome (5-12). Thyroid hormone receptor 2 is a nuclear receptor required for M-cone development (13,14). Targeted deletion of thyroid hormone receptor 2 leads to a loss of M-cone function with an increase in functional S-cones (13,14). Although these transcription factors are known to regulate photoreceptor genes, the molecular regulators of conespecific gene expression are not well defined.One method of deciphering the molecular mechanisms regulating cone-specific expression is to characterize the cis-elements in a cone-specific promoter. Several studies have identified large promoter regions sufficient to direct transgene expression in cones (15-23). However, many of these promoter regions have weak activity, exhibit ectopic, non-cone expression, or require a heterologous enhancer element (16 -19, 21-23). With the exception of a cone rod homeobox-binding element, none of these studies have characterized individual cis-elements that d...
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