Hybrid Code Research Articles

Anisotropy of energetic particles and thermal transport on internal kink stability in HL-3

The kinetic effects of Neutral Beam Injection (NBI) induced energetic particles (EPs) on the stability of internal kink mode are numerically investigated in the presence of anisotropic thermal transport for the new medium-sized tokamak HL-3, utilizing the MHD-kinetic hybrid code MARS-K (Liu Y Q et al. 2008 Phys. Plasmas 15 112503). It is found that after including realistic level of thermal transport, the kinetic effect of EPs on the mode stability is stabilizing in the co-NBI case while destabilizing in the counter-NBI case, in contrast to the similar stabilizing effect with both NBI cases at vanishing thermal transport. Detailed investigation reveals that this opposite effect with the two NBI cases is due to the different non-adiabatic transit resonance contributions of passing EPs in the presence of thermal transport. Anisotropic thermal transport can indirectly affect the non-adiabatic contribution of passing EPs by modifying the mode eigenvalue, which also contributes to the resonance condition between the mode and passing EPs. The non-perturbative approach adopted in the study also enables comparison of different modifications to the mode eigen-structure between the two NBI cases.

Acceptability and Scalability of a Meditation App Among Adolescents With Type 1 Diabetes Mellitus.

Background Adolescents with type 1 diabetes mellitus (T1DM) experience stress from general life stressors and diabetes-specific stressors. This stress manifests in a range of ways, such as mood swings, heightened frustration, strained familial relationships, and difficulties in T1DM self-management, which then leads to worse health outcomes. There is small to moderate evidence that frequent use of mental health applications (MHapps) improves mental and physical health outcomes. Meditation apps may help reduce some of the stress associated with living with T1DM. This study explores the acceptability and scalability of a self-guided, smartphone-based meditation app, the Healthy Minds Program (HMP) app, among adolescents with T1DM using the Unified Theory of Acceptance and Use of Technology. Methods Eight adolescents ages 15-19 were recruited from a pediatric clinic in a Midwestern state and introduced to the HMP app. After using the HMP app for one week, they were invited to participate in three successive focus group meetings. During the meetings, they shared their perspectives on the content, navigation, and acceptability of the HMP app and strategies to introduce and scale app utilization among adolescents with T1DM. Researchers conducted conventional content analysis using a hybrid coding approach. Data was managed and analyzed using NVivo 10 (Lumivero, Denver, Colorado, USA). Findings Participants believed that the HMP app has the potential to enhance their stress management, mood, and coping abilities when dealing with the challenges of T1DM management. They found the app enjoyable and easy to use but expressed concerns about time constraints as a potential barrier. To address this, they shared recommendations for facilitating app uptake and usage. Conclusions This study's results provide an in-depth understanding of how positively this subset of adolescents with T1DM viewed the HMP app. The participants also offered valuable suggestions that can promote the adoption and sustained use of MHapps by adolescents living with T1DM.

A GPU-Based Lattice Boltzmann Method for Predicting Near- and Far-Field Jet Noise

Jet flow and noise are simulated using the lattice Boltzmann method (LBM). The D3Q19 lattice model calculates the flow field with a high-order distribution function to overcome LBM limitations in solving high Mach number flows. Multiple relaxation times (MRT) and large eddy simulation (LES) are used in this study. Compressible LBM was applied to the simulation jet flow to demonstrate the ability of the fifth-order equilibrium distribution function to simulate compressible flows efficiently. The results from the LBM simulation were then employed in Kirchhoff's surface integral approach to predict far-field jet noise. In this research, we used the compute unified device architecture (CUDA) to implement the LBM in a graphics processing unit (GPU), thus creating a hybrid code, LBM-MRT-LES. The obtained results agreed with the experimental and numerical results in the literature.

Learning to Generate Structured Code Summaries From Hybrid Code Context

Learning to Generate Structured Code Summaries From Hybrid Code Context

A perturbative multi-mode model with finite parallel electric field for fast-ion-driven Alfvén eigenmodes

Abstract Alfvén eigenmodes are of great interest in any fusion device as they can be excited by fast ions in the plasma. If the modes grow to large amplitudes, they can cause transport and redistribution of the fast ions, thus limiting fusion performance. To save computational resources, the resonant kinetic interaction between the fast-particle species and the modes is often modelled by MHD-kinetic hybrid codes. Here, we present such a hybrid model which is applicable to three-dimensional magnetic fields, accounts for a finite parallel electric field and multiple MHD modes present at the same time. The model extends the one previously implemented in the CKA-EUTERPE code allowing for a better estimate of the damping due to the parallel electric field and nonlinear mode-mode interaction. The capabilities of our model are illustrated by applying the code to model nonlinear frequency chirping and fast-ion profile flattening.

Atmospheric ion escape and solar wind deposition as a function of planetary radius

ABSTRACT We explore the ability of an unmagnetized planet to retain an atmosphere as a function of its radius. We use a particle-in-cell hybrid code to simulate the global plasma interaction of unmagnetized terrestrial planets at 1 au under average solar wind conditions. We vary the radius of the planet $(R_\mathrm{ p})$ from Mars-sized ($3390 \ \mathrm{km}$) to super-Earth-sized ($9390 \ \mathrm{km}$). We inject hydrogen and oxygen ion outflows from the ionosphere and quantify how the ion escape, recirculation, solar wind deposition, and net atmospheric mass flux vary as a function of planetary radius. We find that as the radius and the corresponding ionospheric outflow rate are varied, the fraction of outflowing $\mathrm{ H^+}$ that escapes remains at $15.5\pm 1.0{{\ \rm per\, cent}}$, while the rest recirculates back towards the planet. The fraction of produced $\mathrm{ O^+}$ that escapes from a Mars-sized planet is $27\pm 1{{\ \rm per\, cent}}$, and decreases to $7\pm 1{{\ \rm per\, cent}}$ for super-Earth, suggesting that smaller planets are less able to retain heavy ions. We find, however, that larger planets have lower solar wind deposition fractions because their bow shocks are at greater distances from the surface of the planet. The ionospheric outflow rate at which mass deposition is equal to mass escape is found to be proportional to $R_\mathrm{ p}^2$. Lastly, we propose that the bulk gyration of the solar wind at the induced magnetosphere can lead to differential escape trajectories of light and heavy ions.

M3D-K simulations of beam-driven instabilities in an energetic particle dominant KSTAR discharge

We perform a systematic simulation study of energetic passing particle-driven instabilities in KSTAR using the kinetic-MHD hybrid code M3D-K. Linear simulation results show that the observed n = 1 mode in the early phase of the discharge is the low-frequency fishbone driven by energetic passing beam ions. The mode frequency computed is in a good agreement with the experimental measurement. Nonlinear simulations show that the frequency of the n = 1 mode jumps up to a higher value corresponding to the β-induced Alfvén eigenmode (BAE). In the later phase of the discharge, the simulated n = 5 mode is identified as a BAE in its linear phase. In the nonlinear phase, the n = 5 mode exhibits a similar frequency jump to a higher value of an energetic particle (EP) mode after mode saturation. Analysis of perturbed beam ion distributions in phase space shows that these new modes in nonlinear stages are driven by new resonances due to nonlinearly evolved beam ion distributions. Further simulations of a beam beta scan for the n = 5 mode show that the frequency jump disappears for a sufficiently small beam beta or beam ion drive. This result may explain the non-existence of frequency jump in the experiment. Finally, the impact of toroidal rotation on mode characteristics is investigated, showing that it has a marginal influence on EP driven modes.

Electronic heat conductivity in a two-temperature state

Heat transport in solids is governed by two fundamental contributions, atomic and electronic. The electronic energy transport in transient excited states is a defining factor in the problem of ultrafast material irradiation. Here, we calculate the electronic heat conductivity at elevated electron temperatures up to 40,000 K. We apply the novel combined method of tight binding formalism to calculate the electron-phonon contribution to the electronic heat conductivity, and the linear response theory (in the single-pole Ritchie-Howie loss function approximation) for its electron-electron counterpart, implemented in the hybrid code XTANT-3. It allows us to evaluate the electronic heat conductivity in a wide range of materials – fcc metals: Al, Ca, Ni, Cu, Sr, Y, Zr, Rh, Pd, Ag, Ir, Pt, Au, and Pb; hcp metals: Mg, Sc, Ti, Co, Zn, Tc, Ru, Cd, Hf, Re, and Os; bcc metals: V, Cr, Fe, Nb, Mo, Ba, Ta, and W; other metals: Sn, Ga, In, Mn, Te, and Se; semimetal graphite; semiconductors – group IV: Si, Ge, and SiC; group III-V: AlAs, AlP, GaP, GaAs, and GaSb; oxides: ZnO, TiO2, and Cu2O; and others: PbI2, ZnS, and B4C.

MolDStruct: Modeling the dynamics and structure of matter exposed to ultrafast x-ray lasers with hybrid collisional-radiative/molecular dynamics.

We describe a method to compute photon-matter interaction and atomic dynamics with x-ray lasers using a hybrid code based on classical molecular dynamics and collisional-radiative calculations. The forces between the atoms are dynamically determined based on changes to their electronic occupations and the formation of a free electron cloud created from the irradiation of photons in the x-ray spectrum. The rapid transition from neutral solid matter to dense plasma phase allows the use of screened potentials, reducing the number of non-bonded interactions. In combination with parallelization through domain decomposition, the hybrid code handles large-scale molecular dynamics and ionization. This method is applicable for large enough samples (solids, liquids, proteins, viruses, atomic clusters, and crystals) that, when exposed to an x-ray laser pulse, turn into a plasma in the first few femtoseconds of the interaction. We present four examples demonstrating the applicability of the method. We investigate the non-thermal heating and scattering of bulk water and damage-induced dynamics of a protein crystal using an x-ray pump-probe scheme. In both cases, we compare to the experimental data. For single particle imaging, we simulate the ultrafast dynamics of a methane cluster exposed to a femtosecond x-ray laser. In the context of coherent diffractive imaging, we study the fragmentation as given by an x-ray pump-probe setup to understand the evolution of radiation damage in the time range of hundreds of femtoseconds.

A Hybrid Neural Coding Approach for Pattern Recognition With Spiking Neural Networks.

Recently, brain-inspired spiking neural networks (SNNs) have demonstrated promising capabilities in solving pattern recognition tasks. However, these SNNs are grounded on homogeneous neurons that utilize a uniform neural coding for information representation. Given that each neural coding scheme possesses its own merits and drawbacks, these SNNs encounter challenges in achieving optimal performance such as accuracy, response time, efficiency, and robustness, all of which are crucial for practical applications. In this study, we argue that SNN architectures should be holistically designed to incorporate heterogeneous coding schemes. As an initial exploration in this direction, we propose a hybrid neural coding and learning framework, which encompasses a neural coding zoo with diverse neural coding schemes discovered in neuroscience. Additionally, it incorporates a flexible neural coding assignment strategy to accommodate task-specific requirements, along with novel layer-wise learning methods to effectively implement hybrid coding SNNs. We demonstrate the superiority of the proposed framework on image classification and sound localization tasks. Specifically, the proposed hybrid coding SNNs achieve comparable accuracy to state-of-the-art SNNs, while exhibiting significantly reduced inference latency and energy consumption, as well as high noise robustness. This study yields valuable insights into hybrid neural coding designs, paving the way for developing high-performance neuromorphic systems.

Observation and Numerical Simulation of Cold Ions Energized by EMIC Waves

AbstractThis is the first report of significant energization (up to 7,000 eV) of low‐energy He+ ions, which occurred simultaneously with H‐band electromagnetic ion cyclotron (EMIC) wave activity, in a direction mostly perpendicular to the ambient magnetic field. The event was detected by the Arase satellite in the dayside plasmatrough region off the magnetic equator on 15 May 2019. The peak energy of the He+ flux enhancements is mostly above 1,000 eV. At some interval, the He+ ions are energized up to ∼7,000 eV. The H‐band waves are excited in a frequency band between the local crossover and helium gyrofrequencies and are close to a linear polarization state with weakly left‐handed or right‐handed polarization. The normal angle of the waves exhibits significant variation between 0° and 80°, indicating a non‐parallel propagation. We run a hybrid code with parameters estimated from the Arase observations to examine the He+ energization. The simulations show that cold He+ ions are energized up to more than 1,000 eV, similar to the spacecraft observations. From the analysis of the simulated wave fields and cold plasma motions, we found that the ratio of the wave frequency to He+ gyrofrequency is a primary factor for transverse energization of cold He+ ions. As a consequence of the numerical analysis, we suggest that the significant transverse energization of He+ ions observed by Arase is attributed to H‐band EMIC waves excited near the local helium gyrofrequency.

Advancing Equity: Supporting the Mental Health and Emotional Well-Being of Black Youth in the School Setting

This study examines the impact of societal challenges on the mental health of Black youth and explores strategies for school personnel to support their well-being. With heightened awareness due to COVID-19 and incidents of police brutality, this paper assesses effective practices for fostering a supportive educational environment. Utilizing hybrid coding and a two-round literature review via PubMed, gaps in the intersection of Adverse Childhood Experiences (ACEs) and Black youth's educational experiences were identified. Thematic analysis revealed crucial strategies for combating biases, discrimination, and enhancing school connection. Recommendations include training educators in cultural responsiveness, building strong relationships among school staff, students, along with their families, and improving engagement with Black youth to alleviate negative school perceptions. The paper underscores the urgency of addressing mental health disparities and suggests comprehensive approaches encompassing personal, interpersonal, and public policy interventions to support Black students' mental health.

An image compression encryption scheme based on chaos and SPECK-DCT hybrid coding

An image compression encryption scheme based on chaos and SPECK-DCT hybrid coding

Yield Performance and Stability of Some Indian Castor Hybrids in Nigerian Ecology

Castor (Ricinus communis L.) is an industrial oil crop that is widely recognized as an ideal crop for tropical and subtropical regions. Nigeria has been identified as a country with high potential to meet her national castor oil need and provide surplus for export. This potential can be harnessed, only if adequate production technologies, such as improved varieties, are available to the farmers. In this research, three FTB castor hybrids (Code 11, Code 22 & Code 33) and two local checks (NCRICAS1 & NCRICAS1) were assessed for their yield performance and stability in Nigeria. The castor genotypes were evaluated in a replicated plots across six locations in the Southern and Northern Guinea savanna ecologies of Nigeria. The results revealed significant differences for traits assessed among the genotypes. Average seed yield among the hybrids ranged between 596.58kg/ha and 1372.49kg/ha. Average seed yields of the checks ranged between 849.58kg/ha and 1239.63kg/ha. The hybrid Code 33 out yielded the two local checks at four locations (i.e Badeggi, Benue, Kebbi & Sokoto) out of the six locations. The check 1 (Acc.036) recorded significant higher yield (1705.28kg/ha & 1648.15kg/ha) than the hybrid Code 33 (1573.91kg/ha & 867.58kg/ha) at Bacita and Bauchi locations. Besides recording comparable seed yield to the best hybrid (Code 33), the local check 1 (Acc.036) matured earlier than the hybrids evaluated. The GGE biplot view revealed good stability and responsiveness for both hybrid Code 33 (G5) and Acc.036 (G2). Based on performance per se, the hybrid Code 33 showed better adaptation to the ecology. However, further assessment on oil quantity and quality, and cost benefit analysis of the hybrid(s) in comparison to the local varieties is highly recommended.

Synchro-waveform data compression using multi-stage hybrid coding algorithm

To augment situational awareness capabilities for high-frequency disturbances, the modern power system necessitates the implementation of high-sampling rates for real-time Synchro-Waveform (SW) measurements. Nevertheless, the nonlinear nature of data collected from SW measurement devices poses significant challenges to the communication and storage capacities of data centers. To effectively tackle this issue, this paper proposes a Multi-stage Hybrid Coding (MHC) method for the lossless compression of SW data. The MHC method utilizes a well-structured two-stage approach to achieve efficient compression. In the first stage, a variable frame-based method is designed to reduce redundant information and achieve initial compression using multiple periodic recursive compression. Subsequently, the dictionary-based method, specifically the Lempel–Ziv–Markov chain algorithm, is seamlessly integrated to further compress the SW data. Experimental and numerical analyses are conducted using both simulated and real-world source data, with real-time performance validation in SW measurement units. The obtained results convincingly demonstrate that the proposed method enables online compression of both event and non-event SW data, achieving an impressive reduction of over 73.4% in data space, while maintaining a data loss ratio lower than 0.4% for high-density SW data.

Cross‐Comparison of Observations With the Predictions of Global Hybrid Simulations for Multiple IMF Discontinuities Impacting the Bow Shock and Magnetosheath

AbstractWe use the three‐dimensional (3‐D) global hybrid code ANGIE3D to simulate the interaction of four solar wind tangential discontinuities (TDs) observed by ARTEMIS P1 from 0740 UT to 0800 UT on 28 December 2019 with the bow shock, magnetosheath, and magnetosphere. We demonstrate how the four discontinuities produce foreshock transients, a magnetosheath cavity‐like structure, and a brief magnetopause crossing observed by THEMIS and MMS spacecraft from 0800 UT to 0830 UT. THEMIS D observed entries into foreshock transients exhibiting low density, low magnetic field strength, and high temperature cores bounded by compressional regions with high densities and high magnetic field strengths. The MMS spacecraft observed cavities with strongly depressed magnetic field strengths and highly deflected velocity in the magnetosheath downstream from the foreshock. Dawnside THEMIS A magnetosheath observations indicate a brief magnetosphere entry exhibiting enhanced magnetic field strength, low density, and decreased and deflected velocity (sunward flow). The solar wind inputs into the 3‐D hybrid simulations resemble those seen by ARTEMIS. We simulate the interaction of four oblique TDs with properties similar to those in the observation. We place virtual spacecraft at the locations where observations were made. The hybrid simulations predict similar characteristics of the foreshock transients, a magnetosheath cavity, and a magnetopause crossing with characteristics similar to those observed by the multi‐spacecraft observations. The detailed and successful comparison of the interaction involving multiple TDs will be presented.

Deep Is Better? An Empirical Comparison of Information Retrieval and Deep Learning Approaches to Code Summarization

Code summarization aims to generate short functional descriptions for source code to facilitate code comprehension. While Information Retrieval (IR) approaches that leverage similar code snippets and corresponding summaries have led the early research, Deep Learning (DL) approaches that use neural models to capture statistical properties between code and summaries are now mainstream. Although some preliminary studies suggest that IR approaches are more effective in some cases, it is currently unclear how effective the existing approaches can be in general, where and why IR/DL approaches perform better, and whether the integration of IR and DL can achieve better performance. Consequently, there is an urgent need for a comprehensive study of the IR and DL code summarization approaches to provide guidance for future development in this area. This article presents the first large-scale empirical study of 18 IR, DL, and hybrid code summarization approaches on five benchmark datasets. We extensively compare different types of approaches using automatic metrics, we conduct quantitative and qualitative analyses of where and why IR and DL approaches perform better, respectively, and we also study hybrid approaches for assessing the effectiveness of integrating IR and DL. The study shows that the performance of IR approaches should not be underestimated, that while DL models perform better in predicting tokens from method signatures and capturing structural similarities in code, simple IR approaches tend to perform better in the presence of code with high similarity or long reference summaries, and that existing hybrid approaches do not perform as well as individual approaches in their respective areas of strength. Based on our findings, we discuss future research directions for better code summarization.

Neutron shielding calculation for DEMO-Prad/SXR measurement system

In plasma fusion devices, the selection of shielding materials is one of the challenges for plasma diagnostic and control systems under high radiation levels during long operation times. This study presents the effect of shielding materials on neutron flux for a radiated power and soft x-ray core intensity measurement system for a DEMOnstration power plant. A calculation model of neutron shielding was used to investigate the neutron shielding performance of borides and carbides for a large distance from plasma to the diagnostic system. The neutron fluxes were characterized for three points close to the measurement system location. The related neutronic calculations were performed with an ADVANTG hybrid code to obtain neutron flux distribution and attenuation rate depending on the thickness of shielding materials. The results indicate that B4C, W2B5, and WB4 are the most effective options to serve as shielding material due to the effect of boron on neutron shielding effectiveness.

Dynamic Mesh Simulations in OpenFOAM: A Hybrid Eulerian–Lagrangian Approach

The past few decades have witnessed a growing popularity in Eulerian–Lagrangian solvers due to their significant potential for simulating aerodynamic flows, particularly in cases involving strong body–vortex interactions. In this hybrid approach, the two component solvers are mutually coupled in a two-way fashion. Initially, the Lagrangian solver can supply boundary conditions to the Eulerian solver, while the Eulerian solver functions as a corrector for the Lagrangian solution in regions where the latter cannot achieve high accuracy. To utilize such tools effectively, it is vital for them to be capable of handling dynamic mesh movements. This study builds upon the previous research conducted by our team and extends the capabilities of the hybrid solver to handle dynamic meshes. While OpenFOAM, the Eulerian component of this hybrid code, incorporates built-in dynamic mesh properties, certain modifications are necessary to ensure its compatibility with the Lagrangian solver. More specifically, the evolution algorithm of the pimpleFOAM solver needs to be divided into two discrete steps: first, updating the mesh, and later, evolving the solution. This division enables a proper coupling between pimpleFOAM and the Lagrangian solver as an intermediate step. Therefore, the primary objective of this specific paper is to adapt the OpenFOAM solver to meet the demands of the hybrid solver and subsequently validate that the hybrid solver can effectively address dynamic mesh challenges using this approach. This approach introduces a pioneering method for conducting dynamic mesh simulations within the OpenFOAM framework, showcasing its potential for broader applications. To validate the approach, various test cases involving dynamic mesh movements are employed. Specifically, all these cases employ the Lamb–Oseen diffusing vortex, but each case incorporates different types of mesh movements, including translational, rotational, oscillational, and combinations thereof. The results from these cases demonstrate the effectiveness of the proposed OpenFOAM algorithm, with the maximum relative errors —when compared to the analytical solution across all presented cases—capped at 2.0% for the worst-case scenario. This affirms the algorithm’s capability to successfully handle dynamic mesh simulations with the proposed solver.

Control of the robotic arm system with an SSVEP-based BCI

Recent studies on brain–computer interfaces (BCIs) implemented in robotic systems have shown that the system’s effectiveness in assisting individuals with movement disorders to enhance their human–computer interaction skills. However, achieving precise and rapid online completion of tasks remains a challenge for manipulators with multiple degrees of freedom (DOFs). In this paper, we explore a time-sharing control strategy for studying motion control of a robotic arm based on steady-state visual evoked potentials. The signals are generated by the joint frequency-phase modulation method, analyzed with the filter-bank canonical correlation analysis algorithm, and identified to control the six-DOF robotic arm for task execution. The shared control strategy not only reduces user’s cognitive fatigue but also enhances system in practical environments. The use of high-frequency stimuli significantly improves user comfort, and hybrid coding increases the universality of the BCI system. Additionally, by setting multiple locations and actions randomly, the robotic arm can adaptively program the optimal path. The online results showed that BCI instructions of the proposed system could be accurately chosen from six options within 6.45 s. Subjects used an average of 12 commands for the robotic arm to achieve the proposed task with an average accuracy of 98.21%. These findings validate the feasibility and effectiveness of applying the system to robotic control. The control strategy proposed in this study exhibits versatility in controlling robots to perform various complex tasks across different domains.