Angular momentum evolution of young low-mass stars and brown dwarfs: observations and theory

This chapter aims at providing the most complete review of both the emerging concepts and the latest observational results regarding the angular momentum evolution of young low-mass stars and brown dwarfs. In the time since Protostars & Planets V, there have been major developments in the availability of rotation period measurements at multiple ages and in different star-forming environments that are essential for testing theory. In parallel, substantial theoretical developments have been carried out in the last few years, including the physics of the star-disk interaction, numerical simulations of stellar winds, and the investigation of angular momentum transport processes in stellar interiors. This chapter reviews both the recent observational and theoretical advances that prompted the development of renewed angular momentum evolution models for cool stars and brown dwarfs. While the main observational trends of the rotational history of low mass objects seem to be accounted for by these new models, a number of critical open issues remain that are outlined in this review.Comment: 22 pages, 8 figures, accepted for publication in Protostars & Planets VI, 2014, University of Arizona Press, eds. H. Beuther, R. Klessen, K. Dullemond, Th. Hennin

Impact of a complex food microbiota on energy metabolism in the model organism Caenorhabditis elegans

The nematode Caenorhabditis elegans is widely used as a model system for research on aging, development, and host-pathogen interactions. Little is currently known about the mechanisms underlying the effects exerted by foodborne microbes. We took advantage of C. elegans to evaluate the impact of foodborne microbiota on well characterized physiological features of the worms. Foodborne lactic acid bacteria (LAB) consortium was used to feed nematodes and its composition was evaluated by 16S rDNA analysis and strain typing before and after colonization of the nematode gut. Lactobacillus delbrueckii, L. fermentum, and Leuconostoc lactis were identified as the main species and shown to display different worm gut colonization capacities. LAB supplementation appeared to decrease nematode lifespan compared to the animals fed with the conventional Escherichia coli nutrient source or a probiotic bacterial strain. Reduced brood size was also observed in microbiota-fed nematodes. Moreover, massive accumulation of lipid droplets was revealed by BODIPY staining. Altered expression of nhr-49, pept-1, and tub-1 genes, associated with obesity phenotypes, was demonstrated by RT-qPCR. Since several pathways are evolutionarily conserved in C. elegans, our results highlight the nematode as a valuable model system to investigate the effects of a complex microbial consortium on host energy metabolism

Artificial Neural Networks: The Missing Link Between Curiosity and Accuracy

Artificial Neural Networks, as the name itself suggests, are biologically inspired algorithms designed to simulate the way in which the human brain processes information. Like neurons, which consist of a cell nucleus that receives input from other neurons through a web of input terminals, an Artificial Neural Network includes hundreds of single units, artificial neurons or processing elements, connected with coefficients (weights), and are organized in layers. The power of neural computations comes from connecting neurons in a network: in fact, in an Artificial Neural Network it is possible to manage a different number of information at the same time. What is not fully understood is which is the most efficient way to train an Artificial Neural Network, and in particular what is the best mini-batch size for maximize accuracy while minimizing training time. The idea that will be developed in this study has its roots in the biological world, that inspired the creation of Artificial Neural Network in the first place. Humans have altered the face of the world through extraordinary adaptive and technological advances: those changes were made possible by our cognitive structure, particularly the ability to reasoning and build causal models of external events. This dynamism is made possible by a high degree of curiosity. In the biological world, and especially in human beings, curiosity arises from the constant search of knowledge and information: behaviours that support the information sampling mechanism range from the very small (initial mini-batch size) to the very elaborate sustained (increasing mini-batch size). The goal of this project is to train an Artificial Neural Network by increasing dynamically, in an adaptive manner (with validation set), the mini-batch size; our hypothesis is that this training method will be more efficient (in terms of time and costs) compared to the ones implemented so far

Ritz-like values in steplength selections for stochastic gradient methods

The steplength selection is a crucial issue for the effectiveness of the stochastic gradient methods for large-scale optimization problems arising in machine learning. In a recent paper, Bollapragada et al. (SIAM J Optim 28(4):3312–3343, 2018) propose to include an adaptive subsampling strategy into a stochastic gradient scheme, with the aim to assure the descent feature in expectation of the stochastic gradient directions. In this approach, theoretical convergence properties are preserved under the assumption that the positive steplength satisfies at any iteration a suitable bound depending on the inverse of the Lipschitz constant of the objective function gradient. In this paper, we propose to tailor for the stochastic gradient scheme the steplength selection adopted in the full-gradient method knows as limited memory steepest descent method. This strategy, based on the Ritz-like values of a suitable matrix, enables to give a local estimate of the inverse of the local Lipschitz parameter, without introducing line search techniques, while the possible increase in the size of the subsample used to compute the stochastic gradient enables to control the variance of this direction. An extensive numerical experimentation highlights that the new rule makes the tuning of the parameters less expensive than the trial procedure for the efficient selection of a constant step in standard and mini-batch stochastic gradient methods

Large quadratic programs in training gaussian support vector machines

We consider the numerical solution of the large convex quadratic program arising in training the learning machines named support vector machines. Since the matrix of the quadratic form is dense and generally large, solution approaches based on explicitstorage of this matrix are not practicable. Well known strategies for this quadratic program are based on decomposition techniques that split the problem into a sequence of smaller quadratic programming subproblems. For the solution of these subproblems we present an iterative projection-type method suited for the structure of the constraints and very eective in case of Gaussian support vector machines. We develop an appropriate decomposition technique designed to exploit the high performance of the proposed inner solver on medium or large subproblems. Numerical experiments on large-scale benchmark problems allow to compare this approach with another widelyused decomposition technique. Finally, a parallel extension of the proposed strategy is described

Large scale magnetic fields in viscous resistive accretion disks. I. Ejection from weakly magnetized disks

Cold steady-state disk wind theory from near Keplerian accretion disks requires a large scale magnetic field at near equipartition strength. However the minimum magnetization has never been tested. We investigate the time evolution of an accretion disk threaded by a weak vertical magnetic field. The strength of the field is such that the disk magnetization falls off rapidly with radius. Four 2.5D numerical simulations of viscous resistive accretion disk are performed using the magnetohydrodynamic code PLUTO. In these simulations, a mean field approach is used and turbulence is assumed to give rise to anomalous transport coefficients (alpha prescription). The large scale magnetic field introduces only a small perturbation to the disk structure, with accretion driven by the dominant viscous torque. A super fast magnetosonic jet is observed to be launched from the innermost regions and remains stationary over more than 953 Keplerian orbits. The self-confined jet is launched from a finite radial zone in the disk which remains constant over time. Ejection is made possible because the magnetization reaches unity at the disk surface, due to the steep density decrease. However, no ejection is reported when the midplane magnetization becomes too small. The asymptotic jet velocity remains nevertheless too low to explain observed jets due to the negligible power carried away by the jet. Astrophysical disks with superheated surface layers could drive analogous outflows even if their midplane magnetization is low. Sufficient angular momentum would be extracted by the turbulent viscosity to allow the accretion process to continue. The magnetized outflows would be no more than byproducts, rather than a fundamental driver of accretion. However, if the midplane magnetization increases towards the center, a natural transition to an inner jet dominated disk could be achieved.Comment: Accepted by Astronomy and Astrophysic

Exploring the attitude towards the adoption of a sustainable diet: a cross-country comparison

Purpose: Understanding the determinants that influence consumers' attitude to adopt sustainable diets represents an important area of research to promote sustainable food consumption. The aim of this study is to investigate how (1) the individual openness to new foods (ONFs), (2) the involvement in food trends (IFTs) and (3) the social media use (SMU) can potentially impact the attitude towards the adoption of a sustainable diet (ATSD). Design/methodology/approach: The authors conducted a structured survey in eight countries: Italy, Germany, Poland, USA, Brazil, Japan, Korea and China. The final sample of 5,501 individuals was analysed applying a structural equation model. Findings: The main results show that attitude towards the ATSD is influenced differently by the antecedents investigated in each country. In particular, the ONF positively influences the ATSD only in Italy, USA and Germany. IFT positively influences the ATSD only in Italy, Poland and USA, while negatively in Germany. SMU has a positive influence on the ATSD only in Japan, USA and Germany, while a negative one in Brazil and Korea. Originality/value: This study presents a cross-country comparison about the antecedents of attitude towards the ATSD, thus providing evidence for the need of ad hoc marketing strategies by companies and policies by institutions at single country level

A novel mutation in isoform 3 of the plasma membrane Ca2+ pump impairs cellular Ca2+ homeostasis in a patient with cerebellar ataxia and laminin subunit 1\u3b1 mutations.

The particular importance of Ca2+ signaling to neurons demands its precise regulation within their cytoplasm. Isoform 3 of the plasma membrane Ca2+ ATPase (the PMCA3 pump), which is highly expressed in brain and cerebellum, plays an important role in the regulation of neuronal Ca2+. A genetic defect of the function of the PMCA3 pump has been described in one family with X-linked congenital cerebellar ataxia. Here we describe a novel mutation of the PMCA3 pump (ATP2B3) in a patient with global developmental delay, generalized hypotonia and cerebellar ataxia. The mutation (a R482H replacement) impairs the Ca2+ ejection function of the pump. It reduces the ability of the pump expressed in model cells to control Ca2+ transients generated by cell stimulation and impairs its Ca2+ extrusion function under conditions of low resting cytosolic Ca2+ as well. In silico analysis of the structural effect of the mutation suggests a reduced stabilization of the portion of the pump surrounding the mutated residue in the Ca2+-bound state. The patient also carries two missense mutations in LAMA1, encoding for laminin subunit 1\u3b1. On the basis of the family pedigree of the patient, the presence of both PMCA3 and LAMA1 mutations appears to be necessary for the development of the disease. Considering the observed defect in cellular Ca2+ homeostasis and the previous finding that PMCAs act as digenic modulators in Ca2+-linked pathologies, the PMCA3 dysfunction along with LAMA1 mutations could act synergistically to cause the neurological phenotype