We present results from a data challenge posed to the radial velocity (RV) community: namely, to quantify the Bayesian "evidence" for n = {0, 1, 2, 3} planets in a set of synthetically generated RV ...data sets containing a range of planet signals. Participating teams were provided the same likelihood function and set of priors to use in their analysis. They applied a variety of methods to estimate , the marginal likelihood for each n-planet model, including cross-validation, the Laplace approximation, importance sampling, and nested sampling. We found the dispersion in across different methods grew with increasing n-planet models: ∼3 for zero planets, ∼10 for one planet, ∼102-103 for two planets, and >104 for three planets. Most internal estimates of uncertainty in for individual methods significantly underestimated the observed dispersion across all methods. Methods that adopted a Monte Carlo approach by comparing estimates from multiple runs yielded plausible uncertainties. Finally, two classes of numerical algorithms (those based on importance and nested samplers) arrived at similar conclusions regarding the ratio of for n- and (n + 1)-planet models. One analytic method (the Laplace approximation) demonstrated comparable performance. We express both optimism and caution: we demonstrate that it is practical to perform rigorous Bayesian model comparison for models of ≤3 planets, yet robust planet discoveries require researchers to better understand the uncertainty in and its connections to model selection.
In competitive electricity markets with deep concerns for the efficiency level, demand response programs gain considerable significance. As demand response levels have decreased after the ...introduction of competition in the power industry, new approaches are required to take full advantage of demand response opportunities.
This paper presents DemSi, a demand response simulator that allows studying demand response actions and schemes in distribution networks. It undertakes the technical validation of the solution using realistic network simulation based on PSCAD. The use of DemSi by a retailer in a situation of energy shortage, is presented. Load reduction is obtained using a consumer based price elasticity approach supported by real time pricing. Non-linear programming is used to maximize the retailer’s profit, determining the optimal solution for each envisaged load reduction. The solution determines the price variations considering two different approaches, price variations determined for each individual consumer or for each consumer type, allowing to prove that the approach used does not significantly influence the retailer’s profit.
The paper presents a case study in a 33 bus distribution network with 5 distinct consumer types. The obtained results and conclusions show the adequacy of the used methodology and its importance for supporting retailers’ decision making.
► Load demand reduction in response to electricity price. ► Load demand reduction depending on the price elasticity of demand value. ► Electricity price managed by the supplier aiming a load reduction need. ► Demand response simulator.
The decolourisation of dye solutions by oxidation with H2O2, using activated carbon as catalyst, is studied. For this purpose, three different samples, mainly differing in the respective surface ...chemistries, were prepared and characterized. Moreover, this work involved three pH levels, corresponding to acid, neutral and alkaline solutions, and six dyes belonging to several classes. The catalytic decolourisation tests were performed in a laboratorial batch reactor. Adsorption on activated carbon and non-catalytic peroxidation kinetic experiments were also carried out in the same reactor, in order to compare the efficiencies of the three processes. The non-catalytic reaction is usually inefficient and, typically, adsorption presents a low level of decolourisation. In these cases, the combination of activated carbon with hydrogen peroxide may significantly enhance the process, since the activated carbon catalyses the decomposition of H2O2 into hydroxyl radicals, which are very reactive. Based on the experiments with the different activated carbon samples, which have similar physical properties, it is proved that the surface chemistry of the catalyst plays a key role, being the basic sample the most active. This is discussed considering the involvement of the free electrons on the graphene basal planes of activated carbon as active centres for the catalytic reaction. Additionally, it is shown that the decolourisation is enhanced at high pH values, and a possible explanation for this observation, based on the proposed mechanism, is given.
Just as the power of the open-source design paradigm has driven down the cost of software to the point that it is accessible to most people, the rise of open-source hardware is poised to drive down ...the cost of doing experimental science to expand access to everyone. To assist in this aim, this paper introduces a library of open-source 3-D-printable optics components. This library operates as a flexible, low-cost public-domain tool set for developing both research and teaching optics hardware. First, the use of parametric open-source designs using an open-source computer aided design package is described to customize the optics hardware for any application. Second, details are provided on the use of open-source 3-D printers (additive layer manufacturing) to fabricate the primary mechanical components, which are then combined to construct complex optics-related devices. Third, the use of the open-source electronics prototyping platform are illustrated as control for optical experimental apparatuses. This study demonstrates an open-source optical library, which significantly reduces the costs associated with much optical equipment, while also enabling relatively easily adapted customizable designs. The cost reductions in general are over 97%, with some components representing only 1% of the current commercial investment for optical products of similar function. The results of this study make its clear that this method of scientific hardware development enables a much broader audience to participate in optical experimentation both as research and teaching platforms than previous proprietary methods.
Abstract
For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the ...biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.
Stellar activity can induce signals in the radial velocities of stars, complicating the detection of orbiting low-mass planets. We present a method to determine the number of planetary signals ...present in radial-velocity datasets of active stars, using only radial-velocity observations. Instead of considering separate fits with different number of planets, we use a birth-death Markov chain Monte Carlo algorithm to infer the posterior distribution for the number of planets in a single run. In a natural way, the marginal distributions for the orbital parameters of all planets are also inferred. This method is applied to HARPS data of CoRoT-7. We confidently recover the orbits of both CoRoT-7b and CoRoT-7c although the data show evidence for the presence of additional signals.
Context.
Proxima Centauri is the closest star to the Sun. This small, low-mass, mid M dwarf is known to host an Earth-mass exoplanet with an orbital period of 11.2 days within the habitable zone, as ...well as a long-period planet candidate with an orbital period of close to 5 yr.
Aims.
We report on the analysis of a large set of observations taken with the ESPRESSO spectrograph at the VLT aimed at a thorough evaluation of the presence of a third low-mass planetary companion, which started emerging during a previous campaign.
Methods.
Radial velocities (RVs) were calculated using both a cross-correlation function (CCF) and a template matching approach. The RV analysis includes a component to model Proxima’s activity using a Gaussian process (GP). We use the CCF’s full width at half maximum to help constrain the GP, and we study other simultaneous observables as activity indicators in order to assess the nature of any potential RV signals.
Results.
We detect a signal at 5.12 ± 0.04 days with a semi-amplitude of 39 ± 7 cm s
−1
. The analysis of subsets of the ESPRESSO data, the activity indicators, and chromatic RVs suggest that this signal is not caused by stellar variability but instead by a planetary companion with a minimum mass of 0.26 ± 0.05
M
⊕
(about twice the mass of Mars) orbiting at 0.029 au from the star. The orbital eccentricity is well constrained and compatible with a circular orbit.
In the era of next-generation sequencing and ubiquitous assembly and binning of metagenomes, new putative genome sequences are being produced from isolate and microbiome samples at ever-increasing ...rates. Genome-scale metabolic models have enormous utility for supporting the analysis and predictive characterization of these genomes based on sequence data. As a result, tools for rapid automated reconstruction of metabolic models are becoming critically important for supporting the analysis of new genome sequences. Many tools and algorithms have now emerged to support rapid model reconstruction and analysis. Here, we are comparing and contrasting the capabilities and output of a variety of these tools, including ModelSEED, Raven Toolbox, PathwayTools, SuBliMinal Toolbox and
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