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A Prediction-Correction Based Iterative Convolution-Thresholding Method for Topology Optimization of Heat Transfer Problems

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SSRN 2024年

关键词： Convolution

Experimental Investigation and Thermodynamic Assessment of Phase Equilibria in the Al-Ta-V Ternary System

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SSRN 2023年

作者： Lu, Yong Wang, Cuiping Zheng, Debin Zheng, Zhangcan Wu, Lianzhang Le, Jianping Guo, Yihui Huang, Yixiong Zhang, Jinbin Liu, Xingjun College of Materials Fujian Key Laboratory of Surface and Interface Engineering for High Performance Materials Xiamen University Xiamen361005 China Xiamen Key Laboratory of High Performance Metals and Materials Xiamen University Xiamen361005 China School of Materials Science and Engineering Institute of Materials Genome & Big Data Harbin Institute of Technology Shenzhen518055 China

The phase equilibria in the Al-Ta-V ternary system at 1000 °C and 1200 °C have been studied by using electron probe microanalysis and X-ray diffraction. τ-Al2.9Ta2.7V1.4 phase was found in the Al-Ta-V ternary system in both two isothermal sections. The addition of V makes the Al69Ta39 phase be stable at 1000 °C. The linear compound Al3(V,Ta) phase (D022-type) forms a continuous solution from the Al-V side to the Al-Ta side at both temperatures. Based on our experimental results, reported liquidus projection of the ternary Al-Ta-V system and thermodynamic data of the binary systems of Al-V, Al-Ta and V-Ta, a thermodynamic evaluation of Al-Ta-V system was carried out by CALPHAD technique. A set of reliable thermodynamic parameters for the Al-Ta-V system was obtained. The current calculation results agree well with the available experimental data. The invariant reaction scheme of Al-Ta-V ternary system was presented. The present study could provide essential experimental and thermodynamic data for establishing a comprehensive Co-based alloy database. © 2023, The Authors. All rights reserved.

关键词： Ternary systems

Modulating Structural Stability and Properties in the Co-Based Alloy Via Anti-Site Defects

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SSRN 2023年

作者： Yang, Chen Yu, Xiang Chen, Youheng Han, Jiajia Wang, Cuiping Liu, Xingjun College of Materials Fujian Key Laboratory of Surface and Interface Engineering for High Performance Materials Xiamen University Xiamen361005 China Xiamen Key Laboratory of High Performance Metals and Materials Xiamen University Xiamen361005 China School of Materials Science and Engineering Institute of Materials Genome & Big Data Harbin Institute of Technology Shenzhen518055 China

The design of the composition for two-phase superalloys of γ/γ' has always been key to achieving a breakthrough in their mechanical performance. However, the underlying mechanism of the anti-site defects in γ' precipitates that severely affect stability and performance have rarely been explored. The present work therefore specifically investigated the structural stability and mechanical properties of strictly stoichiometric and off-stoichiometric γ'-Co3(Al, Nb) phases by using the first-principles calculations. The results show that the change in the Al/Nb ratios in the compounds could induce the instability of the L12 structure, while an increase of Nb atoms leads to compounds with predominantly covalent bonds exhibiting stronger mechanical properties. After evaluating the Gibbs free energy of these γ'-Co3(Al, Nb) phases at finite temperature, it is found that Co29Al2Nb1 and Co29Al1Nb2 compounds with anti-site defects can be thermodynamically stable at greater than 710 and 905 K, respectively. Accordingly, Co-10Al-2Nb and Co-2.5Al-3Nb alloys were successfully prepared experimentally, further confirming that the γ'-Co3(Al, Nb) phase with anti-site defects can precipitate preferentially and remain stable during the 168 h annealing treatment. © 2023, The Authors. All rights reserved.

关键词： Aluminum alloys

Narrow Bandwidth Gamma Comb from Nonlinear Compton Scattering Using the Polarization Gating Technique

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Physical Review Letters 2021年第19期126卷 194801-194801页

作者： M. A. Valialshchikov V. Yu. Kharin S. G. Rykovanov High Performance Computing and Big Data Laboratory Skolkovo Institute of Science and Technology Moscow 143026 Russia Genity LLC 444 W. Lake Street Chicago Illinois 60606 USA

Nonlinear Compton scattering is a promising source of bright gamma rays. Using readily available intense laser pulses to scatter off the energetic electrons, on the one hand, allows us to significantly increase the total photon yield, but on the other hand, leads to a dramatic spectral broadening of the fundamental emission line as well as its harmonics due to the laser pulse shape induced ponderomotive effects. In this Letter we propose to avoid ponderomotive broadening in harmonics by using the polarization gating technique—a well-known method to construct a laser pulse with temporally varying polarization. We show that by restricting harmonic emission only to the region near the peak of the pulse, where the polarization is linear, it is possible to generate a bright narrow bandwidth comb in the gamma region.

关键词： Radiation from moving charges Synchrotron radiation & free-electron lasers Synchrotron radiation facilities Compton scattering

Towards a Benchmark for Colorectal Cancer Segmentation in Endorectal Ultrasound Videos: dataset and Model Development

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arXiv

arXiv 2024年

作者： Jiang, Yuncheng Hu, Yiwen Zhang, Zixun Wei, Jun Feng, Chun-Mei Tang, Xuemei Wan, Xiang Liu, Yong Cui, Shuguang Li, Zhen SSE The Chinese University of Hong Kong Shenzhen China Shenzhen Future Network of Intelligence Insititute China Institute of High Performance Computing Agency for Science Technology and Research Singapore Shenzhen Research Institute of Big Data Shenzhen China Affiliated Hospital of North Sichuan Medical College Sichuan China

Endorectal ultrasound (ERUS) is an important imaging modality that provides high reliability for diagnosing the depth and boundary of invasion in colorectal cancer. However, the lack of a large-scale ERUS dataset with high-quality annotations hinders the development of automatic ultrasound diagnostics. In this paper, we collected and annotated the first benchmark dataset that covers diverse ERUS scenarios, i.e. colorectal cancer segmentation, detection, and infiltration depth staging. Our ERUS-10K dataset comprises 77 videos and 10,000 high-resolution annotated frames. Based on this dataset, we further introduce a benchmark model for colorectal cancer segmentation, named the Adaptive Sparse-context TRansformer (ASTR). ASTR is designed based on three considerations: scanning mode discrepancy, temporal information, and low computational complexity. For generalizing to different scanning modes, the adaptive scanning-mode augmentation is proposed to convert between raw sector images and linear scan ones. For mining temporal information, the sparse-context transformer is incorporated to integrate inter-frame local and global features. For reducing computational complexity, the sparse-context block is introduced to extract contextual features from auxiliary frames. Finally, on the benchmark dataset, the proposed ASTR model achieves a 77.6% Dice score in rectal cancer segmentation, largely outperforming previous state-of-the-art methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Diagnosis

Synthesis of high-Specific-Capacity Prussian Blue Analogues for Sodium-Ion Batteries Boosted by Grooved Structure

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SSRN 2023年

作者： Han, Jiajia Hu, Ya'nan Han, Qinghao Liu, Xingjun Wang, Cuiping Fujian Key Laboratory of Surface and Interface Engineering for High Performance Materials Xiamen University Xiamen361005 China Xiamen Key Laboratory of High Performance Metals and Materials Xiamen University Xiamen361005 China State Key Laboratory of Advanced Welding and Joining Harbin Institute of Technology Harbin150001 China Institute of Materials Genome and Big Data Harbin Institute of Technology Shenzhen518055 China

In view of the problems of low specific capacity and poor cycle performance of Prussian blue analogues as cathode materials of sodium-ion battery, this work made surface etching modification on the synthesized Fe0.8Co0.2HCF with regular cube structure and optimized electrochemical performance. With the help of the resulting grooved structure, the electrode material has been further significantly improved. The results show that the etched sample has a discharge capacity of 153.3 mAh/g at 0.5 C and maintains 83.3 % after 200 cycles at 2 C. When the rate returns from 16 C to 0.5 C, the discharge capacity can be maintained at about 90.7 %. Combined with experimental analysis and theoretical calculation, the improved electrochemical performance of etching sample is mainly attributed to the following three aspects: (1) fast diffusivity of Na+;(2) reduced water content;(3) large contact area between electrode and electrolyte. © 2023, The Authors. All rights reserved.

关键词： Sodium-ion batteries

A Parallelizable Counterfactual Generation Method Based on Gradient Optimization 29

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A Parallelizable Counterfactual Generation Method Based on G...

29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Ding, Haorun Jiang, Xuesong Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Qilu University of Technology Shandong Academy of Sciences Jinan China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Jinan China Quan Cheng Laboratory Jinan China State Key Laboratory of High-end Server and Storage Technology Jinan China

ISBN: (纸本)9798350330717

Post-hoc explanations are important for people to understand the predictions of explanation models. One class of methods in post-hoc explanation is the generation of counterfactuals, where a hypothetical example is obtained by perturbing the inputs to show how one could obtain a different prediction from the decision model. Counter-factual explanations should satisfy several properties: One is that counterfactuals generated under specific scenarios and constraints should be feasible for users, i.e., they should accommodate different causal constraints. The other is that it is more desirable for users to have a wider variety of viable examples, i.e., counterfactual diversity. To this end, we propose a parallelizable method based on gradient optimization. We partition the input feasible domains, perform counterfactual generation independently for each feasible domain, and then parallelize the counterfactual generation process for each feasible domain. Experimental results show that our approach effectively improves the diversity, sparsity, and proximity of the generated counterfactual instances on the public datasets Adult-Income, Lending-Club, German-Credit, and COMPAS compared to other models. © 2023 IEEE.

关键词： counterfactual explanation machine learning parallel computing

Boosting Meaningful Dependency Mining with Clustering and Covariance Analysis

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Boosting Meaningful Dependency Mining with Clustering and Co...

International Conference on data Engineering

作者： Xi Wang Ruochun Jin Wanrong Huang Yuhua Tang Institute for Quantum Information & State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha China Department of Intelligent Data Science College of Computer Science and Technology National University of Defense Technology Changsha China

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

Functional dependencies (FDs) form a valuable ingredient for various data management tasks. However, existing methods can hardly discover practical and interpretable FDs, especially in large noisy real-life datasets. This paper studies the problem of discovering meaningful functional dependencies (FDms) that utilize support and error parameters to capture interesting dependencies in such datasets and proposes an efficient discovery algorithm called FDMε. In order to scale with large datasets, FDM ε employs an efficient sampling method with accuracy guarantees to capture the differences between tuple pairs and to quantify the connection between support/error of dependencies on samples and those on the entire dataset. Moreover, it adopts a clustering-based correlated attributes extraction to divide the exponentially large search space into multiple small sub-spaces and proposes an easy-first traversal strategy with covariance-based guidance that quickly detects candidate dependencies and validates them. Additionally, we prove a covariance lower bound as an additional pruning criterion to reduce the search space. Extensive experiments on real-life and synthetic datasets demonstrate that FDM ε is 14 times faster than existing discovery algorithms on average, up to 31 times, and scales to larger datasets with the least memory cost.

关键词： Accuracy Costs Clustering algorithms Search problems data engineering Noise measurement Frequency division multiplexing

STAR NRE: Solving supernova selection effects with set-based truncated auto-regressive neural ratio estimation

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arXiv

arXiv 2024年

作者： Karchev, Konstantin Trotta, Roberto via Bonomea 265 Trieste34136 Italy Astrophysics Group Physics Department Blackett Lab Imperial College London Prince Consort Road LondonSW7 2AZ United Kingdom INFN-National Institute for Nuclear Physics Via Valerio 2 Trieste34127 Italy Italian Research Center on High-Performance Computing Big Data and Quantum Computing Italy

Accounting for selection effects in supernova type Ia (SN Ia) cosmology is crucial for unbiased cosmological parameter inference-even more so for the next generation of large, mostly photometric-only surveys. The conventional "bias correction" procedure has a built-in systematic bias towards the fiducial model used to derive it and fails to account for the additional Eddington bias that arises in the presence of significant redshift uncertainty. On the other hand, Bayesian hierarchical models scale poorly with the data set size and require explicit assumptions for the selection function that may be inaccurate or contrived. To address these limitations, we introduce STAR NRE, a simulation-based approach that makes use of a conditioned deep set neural network and combines efficient high-dimensional global inference with subsampling-based truncation in order to scale to very large survey sizes while training on sets with varying cardinality. Applying it to a simplified SN Ia model consisting of standardised brightnesses and redshifts with Gaussian uncertainties and a selection procedure based on the expected LSST sensitivity, we demonstrate precise and unbiased inference of cosmological parameters and the redshift evolution of the volumetric SN Ia rate from ≈100 000 mock SNa Ia. Our inference procedure can incorporate arbitrarily complex selection criteria, including transient classification, in the forward simulator and be applied to complex data like light curves. We outline these and other steps aimed at integrating STAR NRE into an end-to-end simulation-based pipeline for the analysis of future photometric-only SN Ia data. Copyright © 2024, The Authors. All rights reserved.

关键词： Cosmology