Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution

The deployment of Machine Learning (ML) models is a difficult and time-consuming job that comprises a series of sequential and correlated tasks that go from the data pre-processing, and the design and extraction of features, to the choice of the ML algorithm and its parameterisation. The task is even more challenging considering that the design of features is in many cases problem specific, and thus requires domain-expertise. To overcome these limitations Automated Machine Learning (AutoML) methods seek to automate, with few or no human-intervention, the design of pipelines, i.e., automate the selection of the sequence of methods that have to be applied to the raw data. These methods have the potential to enable non-expert users to use ML, and provide expert users with solutions that they would unlikely consider. In particular, this paper describes AutoML-DSGE - a novel grammar-based framework that adapts Dynamic Structured Grammatical Evolution (DSGE) to the evolution of Scikit-Learn classification pipelines. The experimental results include comparing AutoML-DSGE to another grammar-based AutoML framework, Resilient ClassificationPipeline Evolution (RECIPE), and show that the average performance of the classification pipelines generated by AutoML-DSGE is always superior to the average performance of RECIPE; the differences are statistically significant in 3 out of the 10 used datasets.Comment: EvoApps 202

High prevalence of peripheral neuropathy in multiple myeloma patients and the impact of vitamin D levels, a cross-sectional study

Purpose: Peripheral neuropathy (PN) is common in patients with multiple myeloma (MM). We hypothesized that the relationship between hypovitaminosis D and PN described in diabetes mellitus patients may also be present in MM patients. Methods: To study this potential association, we assessed the incidence of hypovitaminosis D (vitamin D < 75 nmol/L [= 30 ng/mL]) in smouldering and active MM patients in two Dutch hospitals. Furthermore, a validated questionnaire was used to distinguish different PN grades. Results: Of the 120 patients included between January 2017 and August 2018, 84% had an inadequate vitamin D level (median vitamin D level 49.5 nmol/L [IQR 34–65 nmol/L]; mean age: 68 years [SD ± 7.7]; males: 58%). PN was reported by 69% of patients (n = 83); however, of these 83 patients, PN was not documented in the medical records of 52%. An association was found between lower vitamin D levels and higher incidence of PN in the total population (P = 0.035), and in the active MM patients (P = 0.016). Conclusion: This multi-centre cohort study showed that PN and hypovitaminosis D are common in MM patients, and addressing low vitamin D levels in the treatment of MM patients might be beneficial in reducing the risk of PN. More attention for PN is warranted, as PN is underreported by clinicians. Further research is needed to fully understand the implications of vitamin D in the development of PN in patients with MM. Clinical trial registration: Netherland Trial Register NL5835, date of registration July 28, 2016

HPLC-DAD and HPLC-ESI-Q-ToF characterisation of early 20th century lake and organic pigments from Lefranc archives

The characterisation of atelier materials and of the historical commercial formulation of paint materials has recently gained new interest in the field of conservation science applied to modern and contemporary art, since modern paint materials are subjected to peculiar and often unpredictable degradation and fading processes. Assessing the composition of the original materials purchased by artists can guide not only their identification in works of art, but also their restoration and conservation. Advances in characterisation methods and models for data interpretation are particularly important in studying organic coloring materials in the transition period corresponding to the late 19th-early 20th century, when many such variants or combinations were hypothetically possible in their formulations. There is thus a need for reliable databases of materials introduced in that period and for gaining chemical knowledge at a molecular level related to modern organic pigments, by state-of-the-art protocols. This paper reports on the results of a study on 44 samples of historical colorants in powder and paint tubes, containing both lake pigments and synthetic organic pigments dating from 1890 to 1926. The samples were collected at the Lefranc Archive in Le Mans (France) as a part of Project Futurahma "From Futurism to Classicism (1910-1922). Research, Art History and Material Analysis", (FIRB2012, Italian Ministry of University and Research), and were investigated using an analytical approach based on chromatographic and mass spectrometric techniques. The focus of the chemical analyses was to reveal the composition of the historical organic lake pigments including minor components, to discriminate between different recipes for the extraction of chromophore-containing molecules from the raw materials, and ultimately to distinguish between different formulations and recipes. High performance liquid chromatography (HPLC) with diode array detector (DAD) or electrospray-Quadrupole-Time of Flight tandem mass spectrometry detector (ESI-Q-ToF) were chosen given their considerable capacity to identify such complex and widespread organic materials. Although the inorganic components of the pigments were not taken into account in this survey, the specific molecular profiles provided invaluable information on the extraction procedures or synthetic strategy followed by the different producers, at different times. For instance, the use of Kopp's purpurin and garancine was highlighted, and synthetic by-products were identified. The results provided evidence that the addition of synthetic organic pigments to paint mixtures started from 1910 onwards, but they also suggest that in the formulation of high quality (surfin) colorants, natural products were still preferred. Moreover, in one of the samples the use of murexide as the colouring material was confirmed. This paper presents the first systematic and comprehensive survey on organic lakes and pigments belonging to an historical archive, by both HPLC-DAD and HPLC-ESI-Q-ToF. Specific by-products of synthetic production of pigments, which can act as specific molecular markers for dating or locating a work of art, were also identified for the first time

Power Test of the First Two HL-LHC Insertion Quadrupole Magnets Built at CERN

The High-Luminosity project (HL-LHC) of the CERN Large Hadron Collider (LHC), requires low β* quadrupole magnets in Nb$_3$Sn technology that will be installed on each side of the ATLAS and CMS experiments. After a successful shortmodel magnet manufacture and test campaign, the project has advanced with the production, assembly, and test of full-size 7.15- m-long magnets. In the last two years, two CERN-built prototypes (MQXFBP1 and MQXFBP2) have been tested and magnetically measured at the CERN SM18 test facility. These are the longest accelerator magnets based on Nb$_3$Sn technology built and tested to date. In this paper, we present the test and analysis results of these two magnets, with emphasis on quenches and training, voltage-current measurements and the quench localization with voltage taps and a new quench antenna

A spatially restricted increase in receptor mobility is involved in directional sensing during Dictyostelium discoideum chemotaxis

Biological and Soft Matter PhysicsAnimal science

Ecological mechanisms in cognitive science

© The Author(s) 2019. In 2010, Bechtel and Abrahamsen defined and described what it means to be a dynamic causal mechanistic explanatory model. They discussed the development of a mechanistic explanation of circadian rhythms as an exemplar of the process and challenged cognitive science to follow this example. This article takes on that challenge. A mechanistic model is one that accurately represents the real parts and operations of the mechanism being studied. These real components must be identified by an empirical programme that decomposes the system at the correct scale and localises the components in space and time. Psychological behaviour emerges from the nature of our real-time interaction with our environments—here we show that the correct scale to guide decomposition is picked out by the ecological perceptual information that enables that interaction. As proof of concept, we show that a simple model of coordinated rhythmic movement, grounded in information, is a genuine dynamical mechanistic explanation of many key coordination phenomena

Design of MRI Structured Spiking Neural Networks and Learning Algorithms for Personalized Modelling, Analysis, and Prediction of EEG Signals

Abstract This paper proposes a novel method and algorithms for the design of MRI structured personalized 3D spiking neural network models (MRI-SNN) for a better analysis, modeling, and prediction of EEG signals. It proposes a novel gradient-descent learning algorithm integrated with a spike-time-dependent-plasticity algorithm. The models capture informative personal patterns of interaction between EEG channels, contrary to single EEG signal modeling methods or to spike-based approaches which do not use personal MRI data to pre-structure a model. The proposed models can not only learn and model accurately measured EEG data, but they can also predict signals at 3D model locations that correspond to non-monitored brain areas, e.g. other EEG channels, from where data has not been collected. This is the first study in this respect. As an illustration of the method, personalized MRI-SNN models are created and tested on EEG data from two subjects. The models result in better prediction accuracy and a better understanding of the personalized EEG signals than traditional methods due to the MRI and EEG information integration. The models are interpretable and facilitate a better understanding of related brain processes. This approach can be applied for personalized modeling, analysis, and prediction of EEG signals across brain studies such as the study and prediction of epilepsy, peri-perceptual brain activities, brain-computer interfaces, and others

Standardized postnatal management of infants with congenital diaphragmatic hernia in Europe: The CDH EURO Consortium Consensus - 2015 Update

In 2010, the congenital diaphragmatic hernia (CDH) EURO Consortium published a standardized neonatal treatment protocol. Five years later, the number of participating centers has been raised from 13 to 22. In this article the relevant literature is updated, and consensus has been reached between the members of the CDH EURO Consortium. Key updated recommendations are: (1) planned delivery after a gestational age of 39 weeks in a high-volume tertiary center; (2) neuromuscular blocking agents to be avoided during initial treatment in the delivery room; (3) adapt treatment to reach a preductal saturation of between 80 and 95% and postductal saturation >70%; (4) target PaCO2 to be between 50 and 70 mm Hg; (5) conventional mechanical ventilation to be the optimal initial ventilation strategy, and (6) intravenous sildenafil to be considered in CDH patients with severe pulmonary hypertension. This article represents the current opinion of all consortium members in Europe for the optimal neonatal treatment of CDH