1,224 research outputs found
Entropy data for the 3D core-collapse supernova simulation of a 40 solar mass progenitor done by Fornax.
No full textEntropy data (unit: kb per baryon) for the 3D core-collapse supernova simulation of a 40 solar mass progenitor done by Fornax. The entropies are saved as Numpy arrays with shape (1024, 128, 256) corresponding to the (r, theta, phi) directions.
The grid information can be read from grid.h5. The file read.py shows a demo on how to read the grid.h5 file. The demo prints R, theta, and phi of the grid as 1D arrays. Use numpy.meshgrid(R, theta, phi, indexing="ij") to create the 3D meshgrid.
The "*.xmf" files provided make it simple to be read by the open-source visualization engine Paraview (https://www.paraview.org/). Open the ".xmf" files from Paraview, and the variables will be automatically imported.
In real simulations, they are written every millisecond. However, the data in this repository are saved every 10 milliseconds because otherwise it takes too long to upload. Contact the corresponding author to acquire other data
Observation and modeling of atmospheric OH and HO₂* radicals at a subtropical rural site and implications for secondary pollutants
No full text202511 bcchVersion of RecordRGCOthersThis research was financially supported by the Hong Kong Research Grants Council (T24-504/17-N and 15223221 to Tao Wang), the National Science Foundation of China (42293322 to Tao Wang), and The Hong Kong Polytechnic University Postdoc Matching Fund Scheme (P0043403 to Tianshu Chen).PublishedC
Individual Differences and Category Learning Performance and Strategy - A scoping review protocol
No full textThis registration is the protocol of a scoping review under the working titled "Individual Differences and Category Learning Performance and Strategy - A scoping review". This report is not an update of any previous review. Author Contacts: Tianshu Zhu (corresponding author): [email protected] John Paul Minda, PhD: [email protected] Western Interdisciplinary Research Building, 1151 Richmond Street, London, ON N6A 3K7, Room 5158. Both authors contributed to the search strategy and analytic plan of this review. Any deviations from the protocol will be documented and discussed in the supplementary material of the review. Important deviations will be discussed in the review itself. This review is supported by the University of Western Ontario, which provides subscriptions to academic database and to Covidence. This institution has played no role in developing this protocol. This registration was dveloped using the PRISMA-ScR checklist
Penanganan Obesitas Dengan Kombinasi Terapi Pijat Swedish Pada Area Pinggang Dan Perut, Akupresur Pada Titik Tianshu, Taixi, Sanyinjiao, Dan Neiting, Serta Pemberian Sediaan Teh Hijau
No full textObesitas dalam TCM disebut “fei pang” (overweight) atau “tan yin” (fat man) (Qingshen, 2002). Berat badan yang berlebihan ini dikarenakan adanya disfungsi pada limpa dan ginjal serta adanya akumulasi dahak lembab pada tubuh (Yin & Liu, 2000). Dalam jurnal (Hua-wang, et al., 2019) pathogenesis obesitas yang utama yaitu obstruksi pembuluh darah akibat defisiensi Qi dan stagnasi lembab yang dapat disebabkan berbagai macam faktor internal dan eksternal seperti stagnasi Qi hati, defisiensi limpa, atau terlalu berlebihan dalam mengonsumsi makanan yang berlemak. Selain itu, obesitas juga dapat disebabkan oleh adanya panas pada lambung dan usus besar serta defisiensi Qi limpa dan lambung (Lacey, et al., 2013).Sebagai upaya mengatasi obesitas dapat dilakukan secara tradisional dengan pijat, akupresur dan herbal. Tujuan dilakukan studi kasus ini adalah untuk mengetahui apakah terapi pijat Swedish pinggang dan perut, akupresur pada titik Tianshu (ST-25), Sanyinjiao (SP6), Taixi (KI3), dan Neiting (ST44) serta seduhan daun teh hijau (Camellia sinensis L.) dapat murunkan IMT serta lingkar pinggang pada penderita obesitas. Terapi pijat dan akupresur dilakukan tiga kali dalam 1 minggu selama 2 minggu, dan terapi herbal dilakukan selama 14 hari. Hasil pada pemberian terapi pijat Swedish area pinggang dan perut, akupresur titik Tianshu (ST25), Sanyinjiao (SP6), Taixi (KI3), Neiting (ST44), serta kombinasi herbal seduhan daun teh hijau (Camellia sinensis L.) pada pasien obesitas selama 2 minggu mampu menurunkan berat badan, IMT, lingkar pinggang, dan LILA
THE GLOBAL SYNCHRONIZATION OF A NEW HYPERCHAOTIC LORENZ SYSTEM
No full text This paper studies the global synchronization of a new hyperchaotic Lorenz system proposed by Wang et al. Based on the Lyapunov stability theory, the coupled control matrix is discussed when either knowing or unknowing the system boundary, respectively. The analysis of theory and numerical simulations show that the synchronization of hyperchaos Lorenz system can be realized effectively with the methods. </jats:p
Three-dimensional nonreciprocal transport in photonic topological heterostructure of arbitrary shape
No full textElectromagnetic wave propagation in three-dimensional (3D) space typically suffers omnidirectional scattering when encountering obstacles. In this study, we used Chern vectors to construct a topological heterostructure, where large-volume nonreciprocal topological transport in 3D is achieved. The shape of the cross section in the heterostructure can be arbitrary designed, and we experimentally observed the distinctive cross-shaped field pattern transport, nonreciprocal energy harvesting, and the remarkable ability of electromagnetic wave to traverse obstacles and abrupt structure changes without encountering reflections in 3D space
Determining pressure from velocity via physics-informed neural network
No full textThis paper describes a physics-informed neural network (PINN) for determining pressure from velocity where the Navier-Stokes (NS) equations are incorporated as a physical constraint, but the boundary condition is not explicitly imposed. The exact solution of the NS equations for the oblique Hiemenz flow is utilized to evaluate the accuracy of the PINN and the effects of the relevant factors including the boundary condition, data noise, number of collocation points, Reynolds number and impingement angle. In addition, the PINN is evaluated in the twodimensional flow over a NACA0012 airfoil based on computational fluid dynamics (CFD) simulation. Further, the PINN is applied to the velocity data of a flying hawkmoth (Manduca) obtained in high-speed schlieren visualizations, revealing some interesting pressure features associated with the vortex structures generated by the flapping wings. Overall, the PINN offers an alternative solution for the problem of pressure from velocity with the reasonable accuracy and robustness
Progenitors, Tracers, and Nucleosynthesis Results
No full text<p>New in Version 2: The "mu-neutrino" (representing mu, anti-mu, tau, and anti-tau neutrinos) spectra information are included. The tracer files are now saved at every 25 ms to fit the repository size limit (it was 20 ms in version 1). In addition, the electron and anti-e neutrino spectra in version 1 were the same, which was caused by a copy-paste bug. Now the bug is fixed in version 2. For further questions, please contact [email protected].</p>
<p>This dataset contains progenitor information, tracer trajectories, and nucleosynthesis results in Nucleosynthetic Analysis of Three-Dimensional Core-Collapse Supernova Simulations (Wang et al. 2023, <a href="https://arxiv.org/abs/2311.03446">https://arxiv.org/abs/2311.03446</a>). The README file provides a detailed description on all files saved in this dataset. This is a state-of-the-art 3D tracer dataset derived from long-term core-collapse supernova simulations.</p>
<p>Some of these simulations have been used in the following works:<br>* The Gravitational-Wave Signature of Core-Collapse Supernovae, Vartanyan et al. 2023, <a href="https://arxiv.org/abs/2302.07092">https://arxiv.org/abs/2302.07092</a><br>* Neutrino-Driven Winds in Three-Dimensional Core-Collapse Supernova Simulations, Wang et al. 2023, <a href="https://arxiv.org/abs/2306.13712">https://arxiv.org/abs/2306.13712</a><br>* Black-Hole Formation Accompanied by the Supernova Explosion of a 40-Msun Progenitor Star, Burrows et al. 2023, <a href="https://arxiv.org/abs/2308.05798">https://arxiv.org/abs/2308.05798</a><br>* A Theory for Neutron Star and Black Hole Kicks and Induced Spins, Burrows et al. 2023, <a href="https://arxiv.org/abs/2311.12109">https://arxiv.org/abs/2311.12109</a></p>
<p>Note: the tracer trajectory files are large.</p>
Modeling and optimizing the performance of PVC/PVB ultrafiltration membranes using supervised learning approaches
No full textMathematical models play an important role in performance prediction and optimization of ultrafiltration (UF) membranes fabricated via dry/wet phase inversion in an efficient and economical manner. In this study, a systematic approach, namely, a supervised, learning-based experimental data analytics framework, is developed to model and optimize the flux and rejection rate of poly(vinyl chloride) (PVC) and polyvinyl butyral (PVB) blend UF membranes. Four supervised learning (SL) approaches, namely, the multiple additive regression tree (MART), the neural network (NN), linear regression (LR), and the support vector machine (SVM), are employed in a rigorous fashion. The dependent variables representing membrane performance response with regard to independent variables representing fabrication conditions are systematically analyzed. By comparing the predicting indicators of the four SL methods, the NN model is found to be superior to the other SL models with training and testing R-squared values as high as 0.8897 and 0.6344, respectively, for the rejection rate, and 0.9175 and 0.8093, respectively, for the flux. The optimal combination of processing parameters and the most favorable flux and rejection rate for PVC/PVB ultrafiltration membranes are further predicted by the NN model and verified by experiments. We hope the approach is able to shed light on how to systematically analyze multi-objective optimization issues for fabrication conditions to obtain the desired ultrafiltration membrane performance based on complex experimental data characteristics
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