cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.10001128
title: High-resolution configuration of the hydrodynamical ocean model SYMPHONIE (version 2.4) over the South China Sea

description: This file includes the codes of the hydrodynamical ocean model SYMPHONIE version 2.4 and the South China Sea configuration, together with input files and codes to generate figures in the study of water, heat and salt budget over this Southeast Asian Sea. 
archive_symphonie_v249.tar.gz contains the model codes and configurations
DataValid.tar.gz contains the data used to validate the model 
Rivers.tar.gz includes river discharges in the configuration
FigurePlot.tar.gz gathers codes to generate figures
DOI: 10.5281/zenodo.7941494
title: High-resolution configuration of the hydrodynamical ocean model SYMPHONIE (version 2.4) over the South China Sea

description: This file includes the codes of the hydrodynamical ocean model SYMPHONIE version 2.4 and the South China Sea configuration, together with input files and codes to generate figures in the study of water, heat and salt budget over this Southeast Asian Sea. 
archive_symphonie_v249.tar.gz contains the model codes and configurations
DataValid.tar.gz contains the data used to validate the model 
Rivers.tar.gz includes river discharges in the configuration
FigurePlot.tar.gz gathers codes to generate figures
DOI: 10.5517/ccdc.csd.cc2bx8n6
title: CCDC 2172128: Experimental Crystal Structure Determination

description: Related Article: Akshay Suresh Kshirsagar, Sayaji Arjun More, Rai-Shung Liu|2023|Chem.Commun.|59|11967|doi:10.1039/D3CC03979J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2cn8dq
title: CCDC 2194223: Experimental Crystal Structure Determination

description: Related Article: Akshay Suresh Kshirsagar, Sayaji Arjun More, Rai-Shung Liu|2023|Chem.Commun.|59|11967|doi:10.1039/D3CC03979J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2d1b93
title: CCDC 2205814: Experimental Crystal Structure Determination

description: Related Article: Akshay Suresh Kshirsagar, Sayaji Arjun More, Rai-Shung Liu|2023|Chem.Commun.|59|11967|doi:10.1039/D3CC03979J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dkj2l
title: CCDC 2221369: Experimental Crystal Structure Determination

description: Related Article: Pramod Kumar, Biplab Maji|2023|J.Mater.Chem.A|11|20752|doi:10.1039/D3TA03280A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2dyf0t
title: CCDC 2232806: Experimental Crystal Structure Determination

description: Related Article: Pramod Kumar, Biplab Maji|2023|J.Mater.Chem.A|11|20752|doi:10.1039/D3TA03280A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f70pd
title: CCDC 2241073: Experimental Crystal Structure Determination

description: Related Article: Yukiya Sato, Yusuke Miyamoto, Takanori Matsui, Yuto Sumida, Hirohisa Ohmiya|2023|Chem Cat.|3|100736|doi:10.1016/j.checat.2023.100736
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f70vk
title: CCDC 2241078: Experimental Crystal Structure Determination

description: Related Article: Yukiya Sato, Yusuke Miyamoto, Takanori Matsui, Yuto Sumida, Hirohisa Ohmiya|2023|Chem Cat.|3|100736|doi:10.1016/j.checat.2023.100736
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fcywn
title: CCDC 2245822: Experimental Crystal Structure Determination

description: Related Article: Jieli Lin, Shihua Liu, Jie Zhang, Hansjörg Grützmacher, Cheng-Yong Su, Zhongshu Li|2023|Chemical Science|14|10944|doi:10.1039/D3SC04506D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fcyxp
title: CCDC 2245823: Experimental Crystal Structure Determination

description: Related Article: Jieli Lin, Shihua Liu, Jie Zhang, Hansjörg Grützmacher, Cheng-Yong Su, Zhongshu Li|2023|Chemical Science|14|10944|doi:10.1039/D3SC04506D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fcyyq
title: CCDC 2245824: Experimental Crystal Structure Determination

description: Related Article: Jieli Lin, Shihua Liu, Jie Zhang, Hansjörg Grützmacher, Cheng-Yong Su, Zhongshu Li|2023|Chemical Science|14|10944|doi:10.1039/D3SC04506D
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fnkj6
title: CCDC 2254088: Experimental Crystal Structure Determination

description: Related Article: Yukiya Sato, Yusuke Miyamoto, Takanori Matsui, Yuto Sumida, Hirohisa Ohmiya|2023|Chem Cat.|3|100736|doi:10.1016/j.checat.2023.100736
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2fnkk7
title: CCDC 2254089: Experimental Crystal Structure Determination

description: Related Article: Yukiya Sato, Yusuke Miyamoto, Takanori Matsui, Yuto Sumida, Hirohisa Ohmiya|2023|Chem Cat.|3|100736|doi:10.1016/j.checat.2023.100736
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2g8081
title: CCDC 2271812: Experimental Crystal Structure Determination

description: Related Article: Mengjia Jiang, Yi Su, Shuyu Li, Siyao Fu, Lingsong Wang, Darya Khan, Yajing Sun, Lingjie Sun, Xiaotao Zhang, Wenping Hu|2023|J.Mater.Chem.C|11|13274|doi:10.1039/D3TC02277C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2f63zr
title: CCDC 2240214: Experimental Crystal Structure Determination

description: Related Article: Biman Ari, Manik Das, Paola Brandao, Somali Mukherjee, Atish Dipankar Jana, Biplab Koley, Soumik Laha, Md. Maidul Islam, Indranil Choudhuri, Nandan Bhattacharya, Bidhan Chandra Samanta, Nitin Chattopadhyay, Tithi Maity|2023|New J.Chem.|47|17881|doi:10.1039/D3NJ02960C
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ggprd
title: CCDC 2278244: Experimental Crystal Structure Determination

description: Related Article: Alexandros S. Armenis, Dimitris I. Alexandropoulos, Anne Worrell, Luís Cunha-Silva, Kim R. Dunbar, Theocharis C. Stamatatos|2023|Dalton Trans.|52|13565|doi:10.1039/D3DT02596A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ggpsf
title: CCDC 2278245: Experimental Crystal Structure Determination

description: Related Article: Alexandros S. Armenis, Dimitris I. Alexandropoulos, Anne Worrell, Luís Cunha-Silva, Kim R. Dunbar, Theocharis C. Stamatatos|2023|Dalton Trans.|52|13565|doi:10.1039/D3DT02596A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ggptg
title: CCDC 2278246: Experimental Crystal Structure Determination

description: Related Article: Alexandros S. Armenis, Dimitris I. Alexandropoulos, Anne Worrell, Luís Cunha-Silva, Kim R. Dunbar, Theocharis C. Stamatatos|2023|Dalton Trans.|52|13565|doi:10.1039/D3DT02596A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2ggpvh
title: CCDC 2278247: Experimental Crystal Structure Determination

description: Related Article: Alexandros S. Armenis, Dimitris I. Alexandropoulos, Anne Worrell, Luís Cunha-Silva, Kim R. Dunbar, Theocharis C. Stamatatos|2023|Dalton Trans.|52|13565|doi:10.1039/D3DT02596A
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.5517/ccdc.csd.cc2gm5r1
title: CCDC 2282553: Experimental Crystal Structure Determination

description: Related Article: Akshay Suresh Kshirsagar, Sayaji Arjun More, Rai-Shung Liu|2023|Chem.Commun.|59|11967|doi:10.1039/D3CC03979J
description: An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.
DOI: 10.17632/dgypyc34gb.1
title: A finite element toolbox for the Bogoliubov-de Gennes stability analysis of Bose-Einstein condensates

description: We present a finite element toolbox for the computation of Bogoliubov-de Gennes modes used to assess the linear stability of stationary solutions of the Gross-Pitaevskii (GP) equation. Applications concern one (single GP equation) or two-component (a system of coupled GP equations) Bose-Einstein condensates in one, two and three dimensions of space. An implementation using the free software Image 1is distributed with this paper. For the computation of the GP stationary (complex or real) solutions we use a Newton algorithm coupled with a continuation method exploring the parameter space (the chemical potential or the interaction constant). Bogoliubov-de Gennes equations are then solved using dedicated libraries for the associated eigenvalue problem. Mesh adaptivity is proved to considerably reduce the computational time for cases implying complex vortex states. Programs are validated through comparisons with known theoretical results for simple cases and numerical results reported in the literature.
DOI: 10.17632/zvttrz5bb2.1
title: The Relative Dispersion Variation and Asymmetric Information

description: In this study, we introduce a new gauge of information asymmetry called the Relative Dispersion Variation (RDV). By calculating the ratio of the deviation of return to the deviation of trading volume, RDV provides a simple yet effective way to assess the level of information asymmetry in security markets. Building upon the inefficient market model proposed by Grossman and Stiglitz (1980) that addresses information cost, we demonstrate that RDV is positively correlated with the proportion of informed trade. Empirically, we calculate RDV using daily data on returns and trading volume, and our findings strongly support the hypothesis that RDV is indicative of information asymmetry. We examine various factors such as return reversals, institutional ownership, and firm-specific measures of asymmetric information in Chinese stocks. Furthermore, we establish the importance of RDV in factor asset pricing. By constructing the UMI factor using RDV, we confirm that UMI significantly improves the asset pricing performance of popular models such as CAPM, Fama & French (1993) (FF3), and Fama & French (2015) (FF5).
DOI: 10.17632/r99gdp9v76.1
title: PFD-PARALLEL, a Singular/GPI-Space package for massively parallel multivariate partial fractioning

description: Multivariate partial fractioning is a powerful tool for simplifying rational function coefficients in scattering amplitude computations. Since current research problems lead to large sets of complicated rational functions, performance of the partial fractioning as well as size of the obtained expressions are a prime concern. We develop a large scale parallel framework for multivariate partial fractioning, which implements and combines an improved version of Leinartas' algorithm and the MultivariateApart algorithm. Our approach relies only on open source software. It combines parallelism over the different rational function coefficients with parallelism for individual expressions. The implementation is based on the Singular/GPI-Space framework for massively parallel computer algebra, which formulates parallel algorithms in terms of Petri nets. The modular nature of this approach allows for easy incorporation of future algorithmic developments into our package. We demonstrate the performance of our framework by simplifying expressions arising from current multiloop scattering amplitude problems. We also provide a Mathematica interface to our package, which is available on https://github.com/Wu-Zihao/PfdParallelM.
DOI: 10.6084/m9.figshare.24305632
title: LBT and analysis codes for single jet

description: This interface in main.cpp is well written so that parton showers generated from PYTHIA 8 can directly propagate in the LBT model. One can analyze the output for jet or parton observables in heavy-ion collisions. The interface and analysis examples for dijet and gamma/Z-triggered jet will also be uploaded in a few weeks.We add smooth hydro profiles for Pb+Pb 5.02 TeV 0-10% collisions in this project. Hydro profiles for other center-of-mass energy and centrality bins will be uploaded in a few weeks.It's simple to run the LBT codes. Here are the steps:make clean && makemodify parameters in m01.cmnd for pp collisions and LBT.in for AA collisions, and make sure the number of events is the same for both pp and AAmodify the path for scattering rate tables and hydro profiles./lbtThe output files are pp.txt for pp collisions, positive.txt and negative.txt for AA collisions.To analyze the final particles, calculate the pT spectrum for jets as an example in dNdpT.ccmodify the path of the final particles, the number of events in dNdpT.ccmake clean && make./dNdpTOne should note that the back reaction in negative.txt should be subtracted during jet reconstruction.For the use of the LBT model, please kindly cite our papers:LBT elastic and recoil: https://arxiv.org/abs/1503.03313LBT radiation and applications: https://arxiv.org/abs/2306.13742For more detailed calculations of single jet suppression and jet anisotropic flow in the LBT, one can refersingle jet suppression: https://arxiv.org/abs/1809.02525jet anisotropic flow: https://arxiv.org/abs/2201.08408The hydro profiles are generated within CLVisc hydrodynamic model, one can referhttps://arxiv.org/abs/1411.7767https://arxiv.org/abs/1205.5019https://arxiv.org/abs/1802.04449
DOI: 10.6084/m9.figshare.24305632.v1
title: LBT codes, analysis codes for dNdpT, scattering rate tables and hydro profiles

description: We have developed a linear Boltzmann transport model to simulate the interaction between high-energy parton showers and the thermal partons in the hot and dense quark-gluon plasma in heavy-ion collisions. The model places emphasis on jet transport and jet-induced medium response which could form a Mach-cone-like structure with wavefront and diffusion wake.
DOI: 10.17632/h4787mfvfz.1
title: SmeftFR v3 – Feynman rules generator for the Standard Model Effective Field Theory

description: We present version 3 of SmeftFR, a Mathematica package designed to generate the Feynman rules for the Standard Model Effective Field Theory (SMEFT) including the complete set of gauge invariant operators up to dimension-6 and the complete set of bosonic operators of dimension-8. Feynman rules are generated with the use of FeynRules package, directly in the physical (mass eigenstates) basis for all fields. The complete set of interaction vertices can be derived, including all or any chosen subset of SMEFT operators. As an option, the user can also choose preferred gauge fixing, generating Feynman rules in unitary or R_ξ-gauges. The novel feature in version-3 of SmeftFR is its ability to calculate SMEFT interactions consistently up to dimension-8 in EFT expansion (including quadratic dimension-6 terms) and express the vertices directly in terms of user-defined set of input-parameters. The derived Lagrangian in the mass basis can be exported in various formats supported by FeynRules, such as UFO, FeynArts, etc. Initialisation of numerical values of Wilson coefficients of higher dimension operators is interfaced to WCxf format. The package also includes a dedicated Latex generator allowing to print the result in clear human-readable form. The SmeftFR v3 is publicly available at http://www.fuw.edu.pl/smeft.
DOI: 10.17632/yxp37csy5x.1
title: MLQD: A package for machine learning-based quantum dissipative dynamics

description: Machine learning has emerged as a promising paradigm to study the quantum dissipative dynamics of open quantum systems. To facilitate the use of our recently published ML-based approaches for quantum dissipative dynamics, here we present an open-source Python package MLQD (https://github.com/Arif-PhyChem/MLQD), which currently supports the three ML-based quantum dynamics approaches: (1) the recursive dynamics with kernel ridge regression (KRR) method, (2) the non-recursive artificial-intelligence-based quantum dynamics (AIQD) approach and (3) the blazingly fast one-shot trajectory learning (OSTL) approach, where both AIQD and OSTL use the convolutional neural networks (CNN). This paper describes the features of the MLQD package, the technical details, optimization of hyperparameters, visualization of results, and the demonstration of the MLQD's applicability for two widely studied systems, namely the spin-boson model and the Fenna–Matthews–Olson (FMO) complex. To make MLQD more user-friendly and accessible, we have made it available on the Python Package Index (PyPi) platform and it can be installed via pip install mlqd. In addition, it is also available on the XACS cloud computing platform (https://XACScloud.com) via the interface to the MLatom package (http://MLatom.com).
DOI: 10.17632/wn4n636bm9.1
title: Online Appendix A and B

description: Dataset of the manuscript entitled "Three-way group decision based on regret theory under dual hesitant fuzzy environment".
DOI: 10.17632/h4ndhvbdjt.1
title: Liquidity Risk in FinTech Lending

description: Liquidity Risk in FinTech Lending
DOI: 10.17632/h4ndhvbdjt.2
title: Liquidity Risk in FinTech Lending

description: Liquidity Risk in FinTech Lending