Setting the Record Straight: Assessing the Reliability of Retrospective Accounts of Change

This is the final version of the article. Available from Wiley via the DOI in this record.Ecological degradation is accelerating, reducing our ability to detect and reverse declines. Resource user accounts have the potential to provide critical information on past change but their reliability can rarely be tested, hence they are often perceived as less valid than other forms of scientific data. We compared individual fishers' catch records, recorded 1-50 years ago, with their memories of past good, typical and poor catches for the corresponding time period. Good and poor catches were recalled with reasonable accuracy, matching variability in recorded catch with no significant change observed over time. Typical recalled catches were overestimated and became significantly more exaggerated over time, but were more comparable to mean than median recorded values. While accuracy of resource users' memory varied with the type of information recalled, our results suggest that carefully structured interview questions can produce reliable quantitative data to inform resource management, even after several decades have elapsed.All authors were supported by the Australian Research Council’s Centre for Excellence for Coral Reef Studies. Fieldwork components were supported by The University of Queensland’s New Staff Start-Up Fund (Project No. 2012000643) and the FRDC (Project No. 2013–018), on behalf of the Australian Government

Fast solid-phase extraction-gas chromatography-mass spectrometry procedure for oil fingerprinting. Application to the Prestige oil spill.

A rapid and simple fractionation procedure using solid-phase extraction (SPE) cartridges was developed for an accurate determination of aliphatic and polycyclic aromatic hydrocarbons in petroleum residues and further application in chemical fingerprinting of oil spills by gas chromatography-mass spectrometry (GC-MS). Among the adsorbents evaluated, SiO2/C3-CN exhibited the best selectivity, providing, by elution with n-hexane (4 ml) and n-hexane-CH2Cl2 (1:1) (5 ml), two well-resolved aliphatic and aromatic hydrocarbon fractions, with recoveries of 97 +/- 7.2 and 99.7 +/- 13.9%, respectively. The SPE fractionation procedure was compared with the conventional silica-alumina adsorption chromatography showing similar results but practical advantages in terms of reproducibility, analysis time, solvent reduction and cost. Moreover, is particularly suitable for routine analysis with a high sample throughput. The developed methodology was tested in the characterization of fuel-oil samples collected along the Spanish north-west coast, after the Prestige oil spill accident

Transfer and zero-shot learning for scalable weed detection and classification in UAV images

In an effort to reduce pesticide use, agronomists and computer scientists have joined forces to develop site-specific weed detection and classification systems. These systems aim to recognize and locate weed species within a crop field, using precision equipment to apply required herbicides timely and only where needed, with the objective of reducing the sprayable surface required to eliminate the given weed and protect the crop, with both economic and environmental benefits. Yet, with climate change on the rise, common weeds are expected to undergo some changes to adapt to their environment, possibly with new or invasive weeds spreading to areas where they did not exist before. These changes (often morphological) as well as new invasions need to be taken into account by future classifiers and detection algorithms to ensure system robustness and adaptation to new habitats/climate dynamics. This paper proposes a set of experiments evaluating the use of transfer learning and zero-shot learning for weed classification using our novel TomatoWeeds dataset. Residual networks of variable depth, pretrained on the Imagenet and/or DeepWeeds datasets were evaluated. A ResNet50 pretrained on both datasets and fine-tuned on the TomatoWeeds dataset performed best, returning a holdout set accuracy of 77.8%, showing the advantageous use of transfer learning in this domain. Zero-shot learning, using both embeddings of images and morphological and habitat text-based descriptions, is implemented to test the ability of machine learning pipelines of recognizing unseen classes at test time (which may arise e.g. due to changing climate dynamics), a learning task in which the field (and our experiments) are still far from satisfactory results. Further research could benefit from larger weed-specific datasets for transfer learning as well as deeper network architectures to improve model performance. The projection-based ZSL could also benefit from larger datasets and new zero-shot learning architectures in hope that unseen classes are accurately projected

The zebrafish as a promising tool for modeling human brain disorders: A review based upon an IBNS Symposium

The zebrafish represents an excellent compromise between system complexity and practical simplicity, features that make it useful for modeling and mechanistic analysis of complex brain disorders. Also promising are screens for psychoactive drugs with effects on larval and adult zebrafish behavior. This review, based upon a recent symposium held at the 2016 IBNS Congress, provides different perspectives on how the zebrafish may be utilized to advance research into human central nervous system disorders. It starts with a discussion on an important bottleneck in zebrafish research, measuring the behavior of this species (specifically shoaling), and continues with examples on research on autism spectrum disorder in larval zebrafish, on screening natural products for compounds with psychoactive properties in adult zebrafish, and on the development of a zebrafish model of fetal alcohol spectrum disorders. By providing information on a broad spectrum of brain disorders, experimental methods, and scientific approaches using both larval and adult zebrafish, the review is intended to showcase this underutilized laboratory species for behavioral neuroscience and psychopharmacology research

On stability of discretizations of the Helmholtz equation (extended version)

We review the stability properties of several discretizations of the Helmholtz equation at large wavenumbers. For a model problem in a polygon, a complete $k$-explicit stability (including $k$-explicit stability of the continuous problem) and convergence theory for high order finite element methods is developed. In particular, quasi-optimality is shown for a fixed number of degrees of freedom per wavelength if the mesh size $h$ and the approximation order $p$ are selected such that $kh/p$ is sufficiently small and $p = O(\log k)$, and, additionally, appropriate mesh refinement is used near the vertices. We also review the stability properties of two classes of numerical schemes that use piecewise solutions of the homogeneous Helmholtz equation, namely, Least Squares methods and Discontinuous Galerkin (DG) methods. The latter includes the Ultra Weak Variational Formulation

A tribute to José María ("Chema") Cantú

José María ("Chema") Cantú (1938-2007), nacido en México, fue un líder pionero, amado y respetado en genética médica y humana y bioética en América Latina. Se graduó como médico en México y luego se formó en genética médica y humana en Francia y los Estados Unidos. Fue instrumental en el desarrollo de un programa de investigación, capacitación y genética de primera categoría en genética médica y humana en Guadalajara, en el noroeste de México. Actuó enérgicamente a nivel nacional, regional e internacional para promover el desarrollo científico a través de la colaboración y la educación en ciencias y humanidades, al mismo tiempo que se esforzaba por la justicia, la paz, el amor y los derechos humanos. Él alcanzó algunos de los honores más altos que un científico y un humanista podían aspirar así como el reconocimiento de las comunidades que él sirvió. Cientos de discípulos de América Latina y del mundo se han inspirado en su visión de un mundo mejor a través de la conjunción de la ciencia, el respeto a la humanidad, la ética y el amor.José María (“Chema”) Cantú (1938-2007), born in Mexico, was a pioneering, loved and respected leader in medical and human genetics and bioethics in Latin America. He graduated as a physician in Mexico and then trained in medical and human genetics in France and the United States. He was instrumental in developing a first-rate research, training and genetic services program in medical and human genetics in Guadalajara, in northwestern Mexico. He acted forcefully at national, regional and international levels to promote scientific development through collaboration and education in science and humanities, while he simultaneously strived for justice, peace, love and human rights. He attained some of the highest honors a scientist and humanist could aspire to as well as the recognition of the communities he served. Hundreds of disciples throughout Latin America and the world have been inspired by his vision of a better world through the conjunction of science, respect for humankind, ethics and love

The cultural capitalists: notes on the ongoing reconfiguration of trafficking culture in Asia

Most analysis of the international flows of the illicit art market has described a global situation in which a postcolonial legacy of acquisition and collection exploits cultural heritage by pulling it westwards towards major international trade nodes in the USA and Europe. As the locus of consumptive global economic power shifts, however, these traditional flows are pulled in other directions: notably for the present commentary, towards and within Asia

Mechanical Systems with Symmetry, Variational Principles, and Integration Algorithms

This paper studies variational principles for mechanical systems with symmetry and their applications to integration algorithms. We recall some general features of how to reduce variational principles in the presence of a symmetry group along with general features of integration algorithms for mechanical systems. Then we describe some integration algorithms based directly on variational principles using a discretization technique of Veselov. The general idea for these variational integrators is to directly discretize Hamilton’s principle rather than the equations of motion in a way that preserves the original systems invariants, notably the symplectic form and, via a discrete version of Noether’s theorem, the momentum map. The resulting mechanical integrators are second-order accurate, implicit, symplectic-momentum algorithms. We apply these integrators to the rigid body and the double spherical pendulum to show that the techniques are competitive with existing integrators