scholarly journals A novel approach in magnetic cloud-driven Forbush decrease modeling

2021 ◽  
pp. 49-55
Author(s):  
Simone Benella ◽  
Rami Vainio ◽  
Catia Grimani ◽  
Giuseppe Consolini ◽  
Qiang Hu ◽  
...  
Keyword(s):  
Large Scale ◽  
Forbush Decrease ◽  
Cosmic Ray ◽  
Particle Simulation ◽  
Magnetic Clouds ◽  
Particle Diffusion ◽  
Analysis Tool ◽  
Interplanetary Coronal Mass Ejections ◽  
Time Step ◽  
Novel Approach

Interplanetary coronal mass ejections (ICMEs) are large-scale solar wind disturbances propagating from the Sun and causing a depression of the galactic-cosmic ray (GCR) intensity known as Forbush decrease (FD). IC- MEs generally contain coherent plasma structures called magnetic clouds (MCs). A unique and powerful data analysis tool allowing for the study of the quasi-3-D configuration of a MC is the Grad-Shafranov (GS) recons - truction. The aim of this work is to investigate the role played by the MC configuration in the formation of a FD. A suited full-orbit test-particle simulation has been developed in order to evaluate FD amplitude and time pro- file produced by the MC obtained with the GS reconstruction. Particle trajectories are computed starting from an isotropic flux outside the MC region. In addition, particle diffusion has been modeled by superimposing a small-angle scattering over the unperturbed charged particle motion at each time step. The model allows us to investigate the MC effect on GCR propagation and to study the energy dependence of the physical processes in - volved, as it provides an estimate of ground-based GCR counts observations at different latitudes. A comparison between model results and both space-based cosmic-ray measurements in L1 and ground-based observations suggests a major role of drifts in producing the FD and a reduced contribution of GCR particle diffusion.

Empirical Studies on the Functional Complexity of Software in Large-Scale Software Systems

2013 ◽  
pp. 174-192
Author(s):  
Yingxu Wang ◽  
Vincent Chiew
Keyword(s):  
Cognitive Complexity ◽  
Large Scale ◽  
Complexity Analysis ◽  
Software Systems ◽  
Analysis Tool ◽  
Software System ◽  
Time Space ◽  
Novel Approach ◽  
Functional Complexity ◽  
Scope Problem

Functional complexity is one of the most fundamental properties of software because almost all other software attributes and properties such as functional size, development effort, costs, quality, and project duration are highly dependent on it. The functional complexity of software is a macro-scope problem concerning the semantic properties of software and human cognitive complexity towards a given software system; while the computational complexity is a micro-scope problem concerning algorithmic analyses towards machine throughput and time/space efficiency. This paper presents an empirical study on the functional complexity of software known as cognitive complexity based on large-scale samples using a Software Cognitive Complexity Analysis Tool (SCCAT). Empirical data are obtained with SCCAT on 7,531 programs and five formally specified software systems. The theoretical foundation of software functional complexity is introduced and the metric of software cognitive complexity is formally modeled. The functional complexities of a large-scale software system and the air traffic control systems (ATCS) are rigorously analyzed. A novel approach to represent software functional complexities and their distributions in software systems is developed. The nature of functional complexity of software in software engineering is rigorously explained. The relationship between the symbolic and functional complexities of software is quantitatively analyzed.

scholarly journals Study of Galactic Cosmic-Ray Flux Modulation by Interplanetary Plasma Structures for the Evaluation of Space Instrument Performance and Space Weather Science Investigations

Atmosphere ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 749 ◽  
Author(s):  
Catia Grimani ◽  
Daniele Telloni ◽  
Simone Benella ◽  
Andrea Cesarini ◽  
Michele Fabi ◽  
...  
Keyword(s):  
Large Scale ◽  
European Space Agency ◽  
Cosmic Ray ◽  
High Energy ◽  
Interplanetary Coronal Mass Ejections ◽  
Particle Detectors ◽  
Space Agency ◽  
Interplanetary Plasma ◽  
Galactic Cosmic Ray ◽  
Science Investigations

The role of high-energy particles in limiting the performance of on-board instruments was studied for the European Space Agency (ESA) Laser Interferometer Space Antenna (LISA) Pathfinder (LPF) and ESA/National Astronautics and Space Administration Solar Orbiter missions. Particle detectors (PD) placed on board the LPF spacecraft allowed for testing the reliability of pre-launch predictions of galactic cosmic-ray (GCR) energy spectra and for studying the modulation of proton and helium overall flux above 70 MeV n − 1 on a day-by-day basis. GCR flux variations up to approximately 15% in less than a month were observed with LPF orbiting around the Lagrange point L1 between 2016 and 2017. These variations appeared barely detected or undetected in neutron monitors. In this work the LPF data and contemporaneous observations carried out with the magnetic spectrometer AMS-02 experiment are considered to show the effects of GCR flux short-term variations with respect to monthly averaged measurements. Moreover, it is shown that subsequent large-scale interplanetary structures cause a continuous modulation of GCR fluxes. As a result, small Forbush decreases cannot be considered good proxies for the transit of interplanetary coronal mass ejections and for geomagnetic storm forecasting.

scholarly journals Galactic cosmic ray decreases associated with non-interacting magnetic clouds in the 23rd solar cycle

2013 ◽  
Vol 8 (S300) ◽  
pp. 483-484
Author(s):  
J. J. Masías-Meza ◽  
S. Dasso
Keyword(s):  
Solar Cycle ◽  
Cosmic Ray ◽  
Total Sample ◽  
Magnetic Clouds ◽  
Neutron Monitors ◽  
Interplanetary Coronal Mass Ejections ◽  
23Rd Solar Cycle ◽  
Preliminary Study ◽  
Galactic Cosmic Ray ◽  
Selection Of

AbstractSudden Galactic Cosmic Ray (GCR) intensity decreases are related to the passage of Interplanetary Coronal Mass Ejections (ICMEs). These phenomena are also known as Forbush Decreases (FDs). The deepest FDs are associated with the passage of Magnetic Clouds (MCs). In this preliminary study we select “non-interacting” MCs associated with FDs observed from ground Neutron Monitors in the period 1996-2009, with the aim of reducing the complexity and the number of parameters involved in the GCR-MC interactions. We introduce a method to determine properties of the “ejecta component” of the FD. We analyze properties of the ejecta component in combination with properties of MCs. From the resulting selection of events, we find that those FDs containing ejecta components show stronger correlations with MC parameters than our total sample of events.

scholarly journals Understanding the variability of magnetic storms caused by ICMEs

2017 ◽  
Vol 35 (1) ◽  
pp. 147-159 ◽  
Author(s):  
Remi Benacquista ◽  
Sandrine Rochel ◽  
Guy Rolland
Keyword(s):  
Solar Wind ◽  
Magnetic Structure ◽  
Large Scale ◽  
Temporal Dynamics ◽  
Magnetic Storms ◽  
Magnetic Clouds ◽  
Interplanetary Coronal Mass Ejections ◽  
Superposed Epoch Analysis ◽  
Original Insight ◽  
Ambient Solar Wind

Abstract. In this paper, we study the dynamics of magnetic storms due to interplanetary coronal mass ejections (ICMEs). We used multi-epoch superposed epoch analyses (SEAs) with a choice of epoch times based on the structure of the events. By sorting the events with respect to simple large-scale features (presence of a shock, magnetic structure, polarity of magnetic clouds), this method provides an original insight into understanding the variability of magnetic storm dynamics. Our results show the necessity of seeing ICMEs and their preceding sheaths as a whole since each substructure impacts the other and has an effect on its geoeffectiveness. It is shown that the presence of a shock drives the geoeffectiveness of the sheaths, while both the shock and the magnetic structure impact the geoeffectiveness of the ICMEs. In addition, we showed that the ambient solar wind characteristics are not the same for ejecta and magnetic clouds (MCs). The ambient solar wind upstream magnetic clouds are quieter than upstream ejecta and particularly slower. We also focused on the polarity of magnetic clouds since it drives not only their geoeffectiveness but also their temporal dynamics. South–north magnetic clouds (SN-MCs) and north–south magnetic clouds (NS-MCs) show no difference in geoeffectiveness for our sample of events. Lastly, since it is well-known that sequences of events can possibly induce strong magnetic storms, such sequences have been studied using superposed epoch analysis (SEA) for the first time. We found that these sequences of ICMEs are very usual and concern about 40 % of the ICMEs. Furthermore, they cause much more intense magnetic storms than isolated events do.

Eleven-year modulation of galactic cosmic rays in interplanetary space

1968 ◽  
Vol 46 (10) ◽  
pp. S879-S882 ◽  
Author(s):  
A. N. Chaeakhchyan ◽  
T. N. Charakhchyan
Keyword(s):  
Solar Activity ◽  
Cosmic Rays ◽  
Large Scale ◽  
Interplanetary Space ◽  
Cosmic Ray ◽  
Galactic Cosmic Rays ◽  
Magnetic Clouds ◽  
The Sun ◽  
Cosmic Ray Intensity ◽  
Stationary Level

Almost the whole increase in the cosmic-ray intensity in the stratosphere during the period of decreasing solar activity (1960–64) was composed of a number of individual events occurring at intervals of 6–12 months. This phenomenon is almost entirely due to the corresponding decrease of solar activity (according to the sunspot number).Several interesting cases were found when solar-activity decreases to a new stationary level took place rapidly (within several days). After such events the cosmic-ray intensity gradually increased to reach a stationary level over a period of about two months. The time, tst, during which the cosmic-ray intensity in interplanetary space (after the above-mentioned events on the sun) approaches a stationary value is about 40, 60, and 80 days according to observations in 1961, 1963, and 1964 respectively.Some results have been obtained on the large-scale magnetic "clouds" which modulate the galactic cosmic rays in interplanetary space: (a) The velocity of propagation of these magnetic clouds is [Formula: see text]. According to the data on u and tst the radius of the sphere around the sun, r, within which the cosmic rays are modulated depends little on solar activity and is equal to 10–15 AU. (b) The density of magnetic clouds in space is either independent of the distance to the sun or decreases less rapidly than the inverse square law suggested by conservation of clouds.[Formula: see text]

Teaching AI Agents Ethical Values Using Reinforcement Learning and Policy Orchestration

2019 ◽  
Author(s):  
Ritesh Noothigattu ◽  
Djallel Bouneffouf ◽  
Nicholas Mattei ◽  
Rachita Chandra ◽  
Piyush Madan ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Ethical Values ◽  
Large Role ◽  
Learning To Learn ◽  
Inverse Reinforcement Learning ◽  
Time Step ◽  
Novel Approach

Autonomous cyber-physical agents play an increasingly large role in our lives. To ensure that they behave in ways aligned with the values of society, we must develop techniques that allow these agents to not only maximize their reward in an environment, but also to learn and follow the implicit constraints of society. We detail a novel approach that uses inverse reinforcement learning to learn a set of unspecified constraints from demonstrations and reinforcement learning to learn to maximize environmental rewards. A contextual bandit-based orchestrator then picks between the two policies: constraint-based and environment reward-based. The contextual bandit orchestrator allows the agent to mix policies in novel ways, taking the best actions from either a reward-maximizing or constrained policy. In addition, the orchestrator is transparent on which policy is being employed at each time step. We test our algorithms using Pac-Man and show that the agent is able to learn to act optimally, act within the demonstrated constraints, and mix these two functions in complex ways.

Green synthesis, characterization of silver sulfide nanoparticles and antibacterial activity evaluation

2019 ◽  
Author(s):  
Chem Int
Keyword(s):  
Antibacterial Activity ◽  
Large Scale ◽  
Research Work ◽  
Silver Sulfide ◽  
Morphological Properties ◽  
Effective Diameter ◽  
Novel Approach ◽  
Transmission Electron ◽  
Green Route ◽  
Silver Sulfide Nanoparticles

This research work presents a facile and green route for synthesis silver sulfide (Ag2SNPs) nanoparticles from silver nitrate (AgNO3) and sodium sulfide nonahydrate (Na2S.9H2O) in the presence of rosemary leaves aqueous extract at ambient temperature (27 oC). Structural and morphological properties of Ag2SNPs nanoparticles were analyzed by X-ray diffraction (XRD) and transmission electron microscopy (TEM). The surface Plasmon resonance for Ag2SNPs was obtained around 355 nm. Ag2SNPs was spherical in shape with an effective diameter size of 14 nm. Our novel approach represents a promising and effective method to large scale synthesis of eco-friendly antibacterial activity silver sulfide nanoparticles.

scholarly journals Fractional ridge regression: a fast, interpretable reparameterization of ridge regression

GigaScience ◽  
2020 ◽  
Vol 9 (12) ◽  
Author(s):  
Ariel Rokem ◽  
Kendrick Kay
Keyword(s):  
Ridge Regression ◽  
Large Scale ◽  
Imaging Data ◽  
Regularization Technique ◽  
Large Scale Data ◽  
Novel Approach ◽  
Manual Exploration ◽  
L2 Norm ◽  
Software Implementations ◽  
Brain Imaging Data

Abstract Background Ridge regression is a regularization technique that penalizes the L2-norm of the coefficients in linear regression. One of the challenges of using ridge regression is the need to set a hyperparameter (α) that controls the amount of regularization. Cross-validation is typically used to select the best α from a set of candidates. However, efficient and appropriate selection of α can be challenging. This becomes prohibitive when large amounts of data are analyzed. Because the selected α depends on the scale of the data and correlations across predictors, it is also not straightforwardly interpretable. Results The present work addresses these challenges through a novel approach to ridge regression. We propose to reparameterize ridge regression in terms of the ratio γ between the L2-norms of the regularized and unregularized coefficients. We provide an algorithm that efficiently implements this approach, called fractional ridge regression, as well as open-source software implementations in Python and matlab (https://github.com/nrdg/fracridge). We show that the proposed method is fast and scalable for large-scale data problems. In brain imaging data, we demonstrate that this approach delivers results that are straightforward to interpret and compare across models and datasets. Conclusion Fractional ridge regression has several benefits: the solutions obtained for different γ are guaranteed to vary, guarding against wasted calculations; and automatically span the relevant range of regularization, avoiding the need for arduous manual exploration. These properties make fractional ridge regression particularly suitable for analysis of large complex datasets.

scholarly journals PRISMS-Fatigue computational framework for fatigue analysis in polycrystalline metals and alloys

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Mohammadreza Yaghoobi ◽  
Krzysztof S. Stopka ◽  
Aaditya Lakshmanan ◽  
Veera Sundararaghavan ◽  
John E. Allison ◽  
...  
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Large Scale ◽  
Metals And Alloys ◽  
Analysis Tool ◽  
Computational Framework ◽  
Crystal Plasticity Finite Element ◽  
Polycrystalline Metals ◽  
Simulation Based ◽  
Open Source Framework

AbstractThe PRISMS-Fatigue open-source framework for simulation-based analysis of microstructural influences on fatigue resistance for polycrystalline metals and alloys is presented here. The framework uses the crystal plasticity finite element method as its microstructure analysis tool and provides a highly efficient, scalable, flexible, and easy-to-use ICME community platform. The PRISMS-Fatigue framework is linked to different open-source software to instantiate microstructures, compute the material response, and assess fatigue indicator parameters. The performance of PRISMS-Fatigue is benchmarked against a similar framework implemented using ABAQUS. Results indicate that the multilevel parallelism scheme of PRISMS-Fatigue is more efficient and scalable than ABAQUS for large-scale fatigue simulations. The performance and flexibility of this framework is demonstrated with various examples that assess the driving force for fatigue crack formation of microstructures with different crystallographic textures, grain morphologies, and grain numbers, and under different multiaxial strain states, strain magnitudes, and boundary conditions.

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