Evaluation of dimensionality reduction methods applied to numerical weather models for solar radiation forecasting

The interest in solar radiation prediction has increased greatly in recent times among the scientific community. In this context, Machine Learning techniques have shown their ability to learn accurate prediction models. The aim of this paper is to go one step further and automatically achieve interpretability during the learning process by performing dimensionality reduction on the input variables. To this end, three non standard multivariate feature selection approaches are applied, based on the adaptation of strong learning algorithms to the feature selection task, as well as a battery of classic dimensionality reduction models. The goal is to obtain robust sets of features that not only improve prediction accuracy but also provide more interpretable and consistent results. Real data from the Weather Research and Forecasting model, which produces a very large number of variables, is used as the input. As is to be expected, the results prove that dimensionality reduction in general is a useful tool for improving performance, as well as easing the interpretability of the results. In fact, the proposed non standard methods offer important accuracy improvements and one of them provides with an intuitive and reduced selection of features and mesoscale nodes (around 10% of the initial variables centered on three specific nodes).This work has been partially supported by the projects TIN2014-54583-C2-2-R, TEC2014-52289-R and TEC2016-81900-REDT of the Spanish Interministerial Commission of Science and Technology (MICYT), and by Comunidad Autónoma de Madrid, under project PRICAM P2013ICE-2933

A morphogenetic EphB/EphrinB code controls hepatopancreatic duct formation

© 2019 The Authors. Published by Springer. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.1038/s41467-019-13149-7The hepatopancreatic ductal (HPD) system connects the intrahepatic and intrapancreatic ducts to the intestine and ensures the afferent transport of the bile and pancreatic enzymes. Yet the molecular and cellular mechanisms controlling their differentiation and morphogenesis into a functional ductal system are poorly understood. Here, we characterize HPD system morphogenesis by high-resolution microscopy in zebrafish. The HPD system differentiates from a rod of unpolarized cells into mature ducts by de novo lumen formation in a dynamic multi-step process. The remodeling step from multiple nascent lumina into a single lumen requires active cell intercalation and myosin contractility. We identify key functions for EphB/EphrinB signaling in this dynamic remodeling step. Two EphrinB ligands, EphrinB1 and EphrinB2a, and two EphB receptors, EphB3b and EphB4a, control HPD morphogenesis by remodeling individual ductal compartments, and thereby coordinate the morphogenesis of this multi-compartment ductal system.This work was funded by the Novo Nordisk Foundation (NNF17CC0027852) and Danish National Research Foundation (DNRF116). J.C. and D.G.W. were supported by the Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001217), the UK Medical Research Council (FC001217), and the Wellcome Trust (FC001217). S.C. was supported by an SNSF Early Postdoc Mobility fellowship (P2ZHP3_164840) and a Long Term EMBO Postdoc fellowship (ALTF 511-2016), and L.S. and J.B.A. by the Independent Research Fund Denmark (DFF; Sapere Aude2 4183-00118B).Published versio

Attempted Cultivation of Jatropha curcas L. in the Lower Senegal River Valley: Story of a Failure

With the objective of determining whether it would be possible to sustainably produce Jatropha curcas L. seeds on the marginal land situated close to the Senegal River, a 6-hectare pilot plantation was cultivated under drip irrigation between September 2007-November 2011, close to the village of Bokhol (Lat. 16°31'N, Long. 15°23'W). A series of tests were conducted on this plot, in order to identify the best cultivation methods for the area (date, density and method of planting, appropriate type of pruning, fertilisers to be applied, irrigation method, etc.). The average yields obtained at this site, after four years of cultivation (less than 500 kg.ha-1 of dry seed), using the best known production techniques, are significantly lower than anticipated, compared to the available figures for the irrigated cultivation of Jatropha in other parts of the world. The main causes of this failure are the plant's limited useful vegetation period of six months per year, instead of twelve, and the scale of attacks by a soilborne vascular disease, which destroyed over 60% of the plantation within four years

Principal Disease and Insect Pests of Jatropha curcas L. in the Lower Valley of the Senegal River

Jatropha curcas L. seed oil is proven to be toxic to many microorganisms, insects and animals. Despite its toxicity, Jatropha is not pest and disease resistant. The following major pests and diseases affecting Jatropha in the lower valley of the Senegal river have been identified: the leaf miner Stomphastis thraustica (Meyrick, 1908) (Lepidoptera, Gracillariidae), the leaf and stem miner Pempelia morosalis (Saalmuller, 1880) (Lepidoptera, Pyralidae) and the shield-backed bug Calidea panaethiopica (Kirkaldy, 1909) (Heteroptera, Scutelleridae), which can cause flower and fruit abortion. Damage from these pests was particularly great during the second year after the plantations were set up (2009) and before later receding. Nevertheless, the worst attacks were caused by a vascular disease transmitted through the soil, which killed 65% of the plants in four years. It is mainly characterised by collar and root rot, which causes foliage to yellow and wilt, before the plant eventually dies. These threats should increase if larger areas are planted with Jatropha. Considering the scale of the damage caused by these attacks in Bokhol, the development of an integrated pest management programme adapted to the local context should be considered

Oral monosaccharide therapies to reverse renal and muscle hyposialylation in a mouse model of GNE myopathy

Abstract. To improve solution robustness, we introduce the concept of super solutions to constraint programming. An (a, b)-super solution is one in which if a variables lose their values, the solution can be repaired by assigning these variables with a new values and at most b other variables. Super solutions are a generalization of supermodels in propositional satisfiability. We focus in this paper on (1,0)-super solutions, where if one variable loses its value, we can find another solution by re-assigning this variable with a new value. To find super solutions, we explore methods based both on reformulation and on search. Our reformulation methods transform the constraint satisfaction problem so that the only solutions are super solutions. Our search methods are based on a notion of super consistency. Experiments show that super MAC, a novel search-based method shows considerable promise. When super solutions do not exist, we show how to find the most robust solution. Finally, we extend our approach from robust solutions of constraint satisfaction problems to constraint optimization problems.

A method for campus-wide SARS-CoV-2 surveillance at a large public university

The systematic screening of asymptomatic and pre-symptomatic individuals is a powerful tool for controlling community transmission of infectious disease on college campuses. Faced with a paucity of testing in the beginning of the COVID-19 pandemic, many universities developed molecular diagnostic laboratories focused on SARS-CoV-2 diagnostic testing on campus and in their broader communities. We established the UC Santa Cruz Molecular Diagnostic Lab in early April 2020 and began testing clinical samples just five weeks later. Using a clinically-validated laboratory developed test (LDT) that avoided supply chain constraints, an automated sample pooling and processing workflow, and a custom laboratory information management system (LIMS), we expanded testing from a handful of clinical samples per day to thousands per day with the testing capacity to screen our entire campus population twice per week. In this report we describe the technical, logistical, and regulatory processes that enabled our pop-up lab to scale testing and reporting capacity to thousands of tests per day