Multiple solutions for asteroid orbits: Computational procedure and applications

We describe the Multiple Solutions Method, a one-dimensional sampling of the six-dimensional orbital confidence region that is widely applicable in the field of asteroid orbit determination. In many situations there is one predominant direction of uncertainty in an orbit determination or orbital prediction, i.e., a ``weak'' direction. The idea is to record Multiple Solutions by following this, typically curved, weak direction, or Line Of Variations (LOV). In this paper we describe the method and give new insights into the mathematics behind this tool. We pay particular attention to the problem of how to ensure that the coordinate systems are properly scaled so that the weak direction really reflects the intrinsic direction of greatest uncertainty. We also describe how the multiple solutions can be used even in the absence of a nominal orbit solution, which substantially broadens the realm of applications. There are numerous applications for multiple solutions; we discuss a few problems in asteroid orbit determination and prediction where we have had good success with the method. In particular, we show that multiple solutions can be used effectively for potential impact monitoring, preliminary orbit determination, asteroid identification, and for the recovery of lost asteroids

Synthesis And Characterization Of Polyynes End-Capped By Biphenyl Groups ({\Alpha},{\Omega}-Biphenylpolyynes)

Stable polyyne chains terminated with biphenyl end groups (a,u-biphenylpolyynes) were synthesized in a single step through a simple procedure by using the Cadiot-Chodkiewicz reaction conditions. The a,ubiphenylpolyynes were separated through HPLC analysis and identified by means of their electronic absorption spectra. The a,u-biphenylpolyynes were studied by FT-IR and Raman spectroscopy and the spectral interpretation was supported with DFT calculations. A peculiarly low reactivity of a,u-biphenylpolyynes with ozone was observed.Comment: The research leading to these results has received funding from the European Research Council Consolidator Grant EspLORE (ERC-2016-CoG Grant No.724610

Survey of irrigation efficiencies on horticultural properties in the Peel-Harvey catchment

A detailed efficiency survey of about 30 per cent of the irrigated horticultural area in the Peel-Harvey catchment revealed that only two out of 20 growers operated at the recommended efficiency levels. In addition it was found that the expenses associated with inefficiency were such that 12 out of 18 farmers would be able to recover improvement costs within one year of operation

Low-frequency modes in the Raman spectrum of sp-sp2 nanostructured carbon

A novel form of amorphous carbon with sp-sp2 hybridization has been recently produced by supersonic cluster beam deposition showing the presence in the film of both polyynic and cumulenic species [L. Ravagnan et al. Phys. Rev. Lett. 98, 216103 (2007)]. Here we present a in situ Raman characterization of the low frequency vibrational region (400-800 cm-1) of sp-sp2 films at different temperatures. We report the presence of two peaks at 450 cm-1 and 720 cm-1. The lower frequency peak shows an evolution with the variation of the sp content and it can be attributed, with the support of density functional theory (DFT) simulations, to bending modes of sp linear structures. The peak at 720 cm-1 does not vary with the sp content and it can be attributed to a feature in the vibrational density of states activated by the disorder of the sp2 phase.Comment: 15 pages, 5 figures, 1 tabl

A Sequential Meta-Transfer (SMT) Learning to Combat Complexities of Physics-Informed Neural Networks: Application to Composites Autoclave Processing

Physics-Informed Neural Networks (PINNs) have gained popularity in solving nonlinear partial differential equations (PDEs) via integrating physical laws into the training of neural networks, making them superior in many scientific and engineering applications. However, conventional PINNs still fall short in accurately approximating the solution of complex systems with strong nonlinearity, especially in long temporal domains. Besides, since PINNs are designed to approximate a specific realization of a given PDE system, they lack the necessary generalizability to efficiently adapt to new system configurations. This entails computationally expensive re-training from scratch for any new change in the system. To address these shortfalls, in this work a novel sequential meta-transfer (SMT) learning framework is proposed, offering a unified solution for both fast training and efficient adaptation of PINNs in highly nonlinear systems with long temporal domains. Specifically, the framework decomposes PDE's time domain into smaller time segments to create "easier" PDE problems for PINNs training. Then for each time interval, a meta-learner is assigned and trained to achieve an optimal initial state for rapid adaptation to a range of related tasks. Transfer learning principles are then leveraged across time intervals to further reduce the computational cost.Through a composites autoclave processing case study, it is shown that SMT is clearly able to enhance the adaptability of PINNs while significantly reducing computational cost, by a factor of 100

Assessing radiative transfer models trained by numerical weather forecasts using sun-tracking radiometric measurements for satellite link characterization up to W band

Radio communications, and in particular Earth-to-satellite links, are worldwide used for delivering digital services. The bandwidth demand of such services is increasing accordingly to the advent of more advanced applications (e.g., multimedia services, deep-space explorations, etc.) thus pushing the scientific community toward the investigation of channel carriers at higher frequencies. When using carrier frequencies above X band, the main drawback is how to tackle the impact of tropospheric processes (i.e., rain, cloud, water vapor). This work assesses the joint use of weather forecast models, radiative transfer models and Sun-tracking radiometric measurements to explore their potential benefits in predicting path attenuation and sky noise temperature for slant paths at frequencies between K and W band, thus paving the way to the optimization of satellite link-budgets