The evolution of inverted magnetic fields through the inner heliosphere

Local inversions are often observed in the heliospheric magnetic field (HMF), but their origins and evolution are not yet fully understood.Parker Solar Probe has recently observed rapid, Alfvénic, HMF inversions in the inner heliosphere, known as ‘switchbacks’, which have been interpreted as the possible remnants of coronal jets. It has also been suggested that inverted HMF may be produced by near-Sun interchange reconnection; a key process in mechanisms proposed for slow solar wind release. These cases suggest that the source of inverted HMF is near the Sun, and it follows that these inversions would gradually decay and straighten as they propagate out through the heliosphere. Alternatively, HMF inversions could form during solar wind transit, through phenomena such velocity shears, draping over ejecta, or waves and turbulence. Such processes are expected to lead to a qualitatively radial evolution of inverted HMF structures. Using Helios measurements spanning 0.3–1 AU, we examine the occurrence rate of inverted HMF, as well as other magnetic field morphologies, as a function of radial distance r, and find that it continually increases. This trend may be explained by inverted HMF observed between 0.3–1 AU being primarily driven by one or more of the above in-transit processes, rather than created at the Sun. We make suggestions as to the relative importance of these different processes based on the evolution of the magnetic field properties associated with inverted HMF. We also explore alternative explanations outside of our suggested driving processes which may lead to the observed trend

Hormonal regulation of female reproduction

Reproduction is an event that requires the coordination of peripheral organs with the nervous system to ensure that the internal and external environments are optimal for successful procreation of the species. This is accomplished by the hypothalamic-pituitary-gonadal axis that coordinates reproductive behavior with ovulation. The primary signal from the central nervous system is gonadotropin-releasing hormone (GnRH), which modulates the activity of anterior pituitary gonadotropes regulating follicle stimulating hormone (FSH) and luteinizing hormone (LH) release. As ovarian follicles develop they release estradiol, which negatively regulates further release of GnRH and FSH. As estradiol concentrations peak they trigger the surge release of GnRH, which leads to LH release inducing ovulation. Release of GnRH within the central nervous system helps modulate reproductive behaviors providing a node at which control of reproduction is regulated. To address these issues, this review focuses on several critical questions. How is the HPG axis regulated in species with different reproductive strategies? What internal and external conditions modulate the synthesis and release of GnRH? How does GnRH modulate reproductive behavior within the hypothalamus? How does disease shift the activity of the HPG axis.Fil: Christensen, A.. University of California at Los Angeles; Estados UnidosFil: Bentley, G. E.. University of California at Berkeley; Estados UnidosFil: Cabrera Kreiker, Ricardo Jorge. Universidad de Mendoza; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto de Medicina y Biología Experimental de Cuyo; ArgentinaFil: Ortega, Hugo Hector. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional de Litoral; ArgentinaFil: Perfito, N.. University of California at Berkeley; Estados UnidosFil: Wu, T. J.. Uniformed Services University Of The Health Sciences; Estados UnidosFil: Micevych, P.. University of California at Los Angeles; Estados Unido

An integrated approach for analysing and assessing the performance of virtual learning groups

Collaborative distance learning involves a variety of elements and factors that have to be considered and measured in order to analyse and assess group and individual performance more effectively and objectively. This paper presents an approach that integrates qualitative, social network analysis (SNA) and quantitative techniques for evaluating online collaborative learning interactions. Integration of various different data sources, tools and techniques provides a more complete and robust framework for group modelling and guarantees a more efficient evaluation of group effectiveness and individual competence. Our research relies on the analysis of a real, long-term, complex collaborative experience, which is initially evaluated in terms of principled criteria and a basic qualitative process. At the end of the experience, the coded student interactions are further analysed through the SNA technique to assess participatory aspects, identify the most effective groups and the most prominent actors. Finally, the approach is contrasted and completed through a statistical technique which sheds more light on the results obtained that far. The proposal draws a well-founded line toward the development of a principled framework for the monitoring and analysis of group interaction and group scaffolding which can be considered a major issue towards the actual application of the CSCL proposals to real classrooms.Peer ReviewedPostprint (author's final draft

Solving kk-means on High-dimensional Big Data

In recent years, there have been major efforts to develop data stream algorithms that process inputs in one pass over the data with little memory requirement. For the $k$-means problem, this has led to the development of several $(1+\varepsilon)$-approximations (under the assumption that $k$ is a constant), but also to the design of algorithms that are extremely fast in practice and compute solutions of high accuracy. However, when not only the length of the stream is high but also the dimensionality of the input points, then current methods reach their limits. We propose two algorithms, piecy and piecy-mr that are based on the recently developed data stream algorithm BICO that can process high dimensional data in one pass and output a solution of high quality. While piecy is suited for high dimensional data with a medium number of points, piecy-mr is meant for high dimensional data that comes in a very long stream. We provide an extensive experimental study to evaluate piecy and piecy-mr that shows the strength of the new algorithms.Comment: 23 pages, 9 figures, published at the 14th International Symposium on Experimental Algorithms - SEA 201

Band-filling-controlled magnetism from transition metal intercalation in N1/3NbS2 revealed with first-principles calculations

We present a first-principles study of the effect of 3d transition metal intercalation on the magnetic properties of the 2H-NbS2 system, using spin-resolved density functional theory calculations to investigate the electronic structure of N1/3NbS2 (N=Ti, V, Cr, Mn, Fe, Co, Ni). We are able to accurately determine the magnetic moments and crystal-field splitting, and find that the magnetic properties of the materials are determined by a mechanism based on filling rigid bands with electrons from the intercalant. We predict the dominant magnetic interaction of these materials by considering Fermi-surface topology, finding agreement with experiment where data are available

Bigger Buffer k-d Trees on Multi-Many-Core Systems

A buffer k-d tree is a k-d tree variant for massively-parallel nearest neighbor search. While providing valuable speed-ups on modern many-core devices in case both a large number of reference and query points are given, buffer k-d trees are limited by the amount of points that can fit on a single device. In this work, we show how to modify the original data structure and the associated workflow to make the overall approach capable of dealing with massive data sets. We further provide a simple yet efficient way of using multiple devices given in a single workstation. The applicability of the modified framework is demonstrated in the context of astronomy, a field that is faced with huge amounts of data

Capturing uncertainty in magnetospheric ultra-low frequency wave models

We develop and test an empirical model predicting ground-based observations of ultra-low frequency (ULF, 1-20 mHz) wave power across a range of frequencies, latitudes and magnetic local time sectors. This is parameterized by instantaneous solar wind speed $v_{sw}$, variance in proton number density $var(Np)$ and interplanetary southward magnetic field $B_z$. A probabilistic model of ULF wave power will allow us to address uncertainty in radial diffusion coefficients and therefore improve diffusion modeling of radial transport in Earth's outer radiation belt. Our model can be used in two ways to reproduce wave power; by sampling from conditional probability distribution functions or by using the mean (expectation) values. We derive a method for testing the quality of the parameterization and test the ability of the model to reproduce ULF wave power time series. Sampling is a better method for reproducing power over an extended time period as it retains the same overall distribution while mean values are better for predicting the power in a time series. The model predicts each hour in a time series better than the assumption that power persists from the preceding hour. Finally, we review other sources of diffusion coefficient uncertainty. Although this wave model is designed principally for the goal of improved radial diffusion coefficients to include in outer radiation belt diffusion based modeling, we anticipate that our model can also be used to investigate the occurrence of ULF waves throughout the magnetosphere and hence the physics of ULF wave generation and propagation

Dynamic optimal taxation with human capital.

This paper revisits the dynamic optimal taxation results of Jones, Manuelli, and Rossi (1993, 1997). They use a growth model with human capital and find that optimal taxes on both capital income and labor income converge to zero in steady state. For one of the models under consideration, I show that the representative household's problem does not have an interior solution. This raises concerns since these corners are inconsistent with aggregate data. Interiority is restored if preferences are modified so that human capital augments the value of leisure time. With this change, the optimal tax problem is analyzed and, reassuringly, the Jones, Manuelli, and Rossi results are confirmed: neither capital income nor labor income should be taxed in steady state

Transition rates and nuclear structure changes in mirror nuclei 47Cr and 47V

Lifetime measurements in the mirror nuclei 47Cr and 47V were performed by means of the Doppler-shift attenuation method using the multidetector array EUROBALL, in conjunction with the ancillary detectors ISIS and the Neutron Wall. The determined transition strengths in the yrast cascades are well described by full pf shell model calculations.Comment: Latex2e, 11 pages, 3 figure