A Data-driven Model of Nucleosynthesis with Chemical Tagging in a Lower-dimensional Latent Space

Chemical tagging seeks to identify unique star formation sites from present-day stellar abundances. Previous techniques have treated each abundance dimension as being statistically independent, despite theoretical expectations that many elements can be produced by more than one nucleosynthetic process. In this work, we introduce a data-driven model of nucleosynthesis, where a set of latent factors (e.g., nucleosynthetic yields) contribute to all stars with different scores and clustering (e.g., chemical tagging) is modeled by a mixture of multivariate Gaussians in a lower-dimensional latent space. We use an exact method to simultaneously estimate the factor scores for each star, the partial assignment of each star to each cluster, and the latent factors common to all stars, even in the presence of missing data entries. We use an information-theoretic Bayesian principle to estimate the number of latent factors and clusters. Using the second Galah data release, we find that six latent factors are preferred to explain N = 2566 stars with 17 chemical abundances. We identify the rapid- and slow neutron-capture processes, as well as latent factors consistent with Fe-peak and α-element production, and another where K and Zn dominate. When we consider N ~ 160,000 stars with missing abundances, we find another seven factors, as well as 16 components in latent space. Despite these components showing separation in chemistry, which is explained through different yield contributions, none show significant structure in their positions or motions. We argue that more data and joint priors on cluster membership that are constrained by dynamical models are necessary to realize chemical tagging at a galactic-scale. We release accompanying software that scales well with the available data, allowing for the model's parameters to be optimized in seconds given a fixed number of latent factors, components, and ~107 abundance measurements.We acknowledge support from the Australian Research Council through Discovery Project DP160100637. J.B.H. is supported by a Laureate Fellowship from the Australian Research Council. Parts of this research were supported by the Australian Research Council (ARC) Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D), through project number CE170100013. S.~B. acknowledges funds from the Alexander von Humboldt Foundation in the framework of the Sofja Kovalevskaja Award endowed by the Federal Ministry of Education and Research. S.B. is supported by the Australian Research Council (grants DP150100250 and DP160103747). S.L.M. acknowledges the support of the UNSW Scientia Fellowship program. J.D.S., S.L.M., and D.B.Z. acknowledge the support of the Australian Research Council through Discovery Project grant DP180101791. The Galah survey is based on observations made at the Australian Astronomical Observatory, under programmes A/2013B/13, A/2014A/25, A/2015A/19, and A/2017A/18. We acknowledge the traditional owners of the land on which the AAT stands, the Gamilaraay people, and pay our respects to elders past and present. This research has made use of NASA’s Astrophysics Data System

Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement

The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10462-016-9505-7.The evaluation of artificial intelligence systems and components is crucial for the progress of the discipline. In this paper we describe and critically assess the different ways AI systems are evaluated, and the role of components and techniques in these systems. We first focus on the traditional task-oriented evaluation approach. We identify three kinds of evaluation: human discrimination, problem benchmarks and peer confrontation. We describe some of the limitations of the many evaluation schemes and competitions in these three categories, and follow the progression of some of these tests. We then focus on a less customary (and challenging) ability-oriented evaluation approach, where a system is characterised by its (cognitive) abilities, rather than by the tasks it is designed to solve. We discuss several possibilities: the adaptation of cognitive tests used for humans and animals, the development of tests derived from algorithmic information theory or more integrated approaches under the perspective of universal psychometrics. We analyse some evaluation tests from AI that are better positioned for an ability-oriented evaluation and discuss how their problems and limitations can possibly be addressed with some of the tools and ideas that appear within the paper. Finally, we enumerate a series of lessons learnt and generic guidelines to be used when an AI evaluation scheme is under consideration.I thank the organisers of the AEPIA Summer School On Artificial Intelligence, held in September 2014, for giving me the opportunity to give a lecture on 'AI Evaluation'. This paper was born out of and evolved through that lecture. The information about many benchmarks and competitions discussed in this paper have been contrasted with information from and discussions with many people: M. Bedia, A. Cangelosi, C. Dimitrakakis, I. GarcIa-Varea, Katja Hofmann, W. Langdon, E. Messina, S. Mueller, M. Siebers and C. Soares. Figure 4 is courtesy of F. Martinez-Plumed. Finally, I thank the anonymous reviewers, whose comments have helped to significantly improve the balance and coverage of the paper. This work has been partially supported by the EU (FEDER) and the Spanish MINECO under Grants TIN 2013-45732-C4-1-P, TIN 2015-69175-C4-1-R and by Generalitat Valenciana PROMETEOII2015/013.José Hernández-Orallo (2016). Evaluation in artificial intelligence: From task-oriented to ability-oriented measurement. 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Valorization, comparison and characterization of coconuts waste and cactus in a biorefinery context using NaClO2-C2H4O2 and sequential NaClO2-C2H4O2/autohydrolysis pretreatment

The search for new sources of lignocellulosic raw materials for the generation of energy and new compounds encourages the search for locations not well known and with a high potential for biomass availability as is the case of the Northeast Region of Brazil. Thus, the cactus (CAC), green coconut shell (GCS), mature coconut fibre and mature coconut shell were pretreated by NaClO2C2H4O2 and sequential NaClO2C2H4O2/autohydrolysis aiming at the obtention of high added-value compounds in the liquid fraction and solid phase. The yield of the solid phase was between 61.42 and 90.97% and the reduction up to 91.63% of lignin in the materials pretreated by NaClO2C2H4O2. After NaClO2C2H4O2/autohydrolysis pretreatment the obtained solids yield was between 43.57 and 52.08%, with a solubilization of the hemicellulose content up to 81.42%. For both pretreatments the cellulosic content remained almost unchanged. The pretreated solids were characterized by SEM, X-ray and crystallinity indexes showing significant modifications when submitted to pretreatments. These results were further confirmed by the enzymatic conversion yields of 81.6890.03 and 86.9790.36% of the LCMs pretreated by NaClO2C2H4O2 and pretreated by NaClO2C2H4O2/autohydrolysis, respectively. The resulting liquors had a total phenolic compounds content between 0.20 and 3.05 g/L, lignin recovered up to 7.40 g/L (absence of sulphur) and xylooligosaccharides between 16.13 and 20.37 g/L. Thus, these pretreatments showed an efficient fractionation of LCMs, especially in the GCS, being an important requirement for the generation of products and byproducts in the context of the biorefinery.The authors gratefully acknowledge the Brazilian research funding agencies CNPq and CAPES for financial support. Financial support from the Energy Sustainability Fund 2014-05 (CONACYT-SENER), Mexican Centre for Innovation in Bioenergy (CemieBio), Cluster of Bioalcohols (Ref. 249564) is gratefully acknowledged. We also gratefully acknowledge support for this research by the Mexican Science and Technology Council (CONACYT, Mexico) for the infrastructure project - INFR201601 (Ref. 269461) and CB-2015-01 (Ref. 254808).info:eu-repo/semantics/publishedVersio

In defence of activities

In this paper, we examine what is to be said in defence of Machamer, Darden and Craver’s (MDC) controversial dualism about activities and entities (Machamer, Darden and Craver’s in Philos Sci 67:1–25, 2000). We explain why we believe the notion of an activity to be a novel, valuable one, and set about clearing away some initial objections that can lead to its being brushed aside unexamined. We argue that substantive debate about ontology can only be effective when desiderata for an ontology are explicitly articulated. We distinguish three such desiderata. The first is a more permissive descriptive ontology of science, the second a more reductive ontology prioritising understanding, and the third a more reductive ontology prioritising minimalism. We compare MDC’s entities-activities ontology to its closest rival, the entities-capacities ontology, and argue that the entities-activities ontology does better on all three desiderata

Selection in a Complex World: Deriving Causality from Stable Equilibrium

It is an ongoing controversy whether natural selection is a cause of population change, or a mere statistical description of how individual births and deaths accumulate. In this paper I restate the problem in terms of the reference class problem, and propose how the structure of stable equilibrium can provide a solution in continuity with biological practice. Insofar natural selection can be understood as a tendency towards equilibrium, key statisticalist criticisms are avoided. Further, in a modification of the Newtonian-force analogy, it can be suggested that a better metaphor for natural selection is that of an emergent force, similar in nature to entropic forces: with magnitude and direction, but lacking a spatiotemporal origin or point of application.status: publishe

Pre-emption cases may support, not undermine, the counterfactual theory of causation

Pre-emption cases have been taken by almost everyone to imply the unviability of the simple counterfactual theory of causation. Yet there is ample motivation from scientific practice to endorse a simple version of the theory if we can. There is a way in which a simple counterfactual theory, at least if understood contrastively, can be supported even while acknowledging that intuition goes firmly against it in pre-emption cases – or rather, only in some of those cases. For I present several new pre-emption cases in which causal intuition does not go against the counterfactual theory, a fact that has been verified experimentally. I suggest an account of framing effects that can square the circle. Crucially, this account offers hope of theoretical salvation – but only to the counterfactual theory of causation, not to others. Again, there is (admittedly only preliminary) experimental support for this account