Article
Plant Sciences
Yulei Zhu, Gang Sun, Guohui Ding, Jie Zhou, Mingxing Wen, Shichao Jin, Qiang Zhao, Joshua Colmer, Yanfeng Ding, Eric S. Ober, Ji Zhou
Summary: This study introduces a large-scale phenotyping solution combining LiDAR device and CropQuant-3D software for wheat phenotype analysis, demonstrating the system's ability to perform 3D trait analysis at a larger scale and more quickly. The results show that the system can effectively differentiate significant genotype and treatment effects, address challenges in mobility, throughput, and scalability, and have potential for further development in accuracy and affordability.
Article
Biochemical Research Methods
Brian J. Bender, Stefan Gahbauer, Andreas Luttens, Jiankun Lyu, Chase M. Webb, Reed M. Stein, Elissa A. Fink, Trent E. Balius, Jens Carlsson, John J. Irwin, Brian K. Shoichet
Summary: Structure-based docking screens of compound libraries are common in early drug and probe discovery. Best practices and control calculations are outlined to evaluate docking parameters prior to undertaking a large-scale prospective screen.
Article
Astronomy & Astrophysics
Samuel Goldstein, Angelo Esposito, Oliver H. E. Philcox, Lam Hui, J. Colin Hill, Roman Scoccimarro, Maximilian H. Abitbol
Summary: This paper shows how consistency relations can be used to effectively extract the amplitude of local primordial non-Gaussianity (fNL) from the squeezed limit of the matter bispectrum, even in the nonlinear regime. The authors derive a nonperturbative relation between primordial non-Gaussianity and the leading term in the squeezed bispectrum, and successfully measure fNL from N-body simulations. They discuss the dependence of the results on different scale cuts and redshifts, and show that the analysis is strongly influenced by the choice of the smallest soft momentum, qmin, but largely independent of the largest hard momentum, kmax, due to the non-Gaussian nature of the covariance. They also find that the constraints on fNL improve at higher redshift due to a reduced off-diagonal covariance. Finally, they compare their results with a Fisher forecast and find that the current analysis is close to the Fisher error, which is promising for the future application of consistency relations to constrain primordial non-Gaussianity using observations.
Article
Engineering, Civil
Dapeng Qiu, Jianyun Chen, Xiangyu Cao
Summary: This paper investigates the seismic control measures for underground large-scale frame structures. The study finds that isolation bearings can control the stresses of column joints to some extent, but increase the seismic responses of floor slabs and outside walls. Therefore, a new separation seismic control measure is proposed to address the failure mechanisms of the structure. The analysis results show that the new measure effectively reduces the adverse effects of soil-structure interaction and decreases the seismic responses of the entire structure.
Article
Energy & Fuels
Mo Zheng, Xiaoxia Li, Jin Bai, Li Guo
Summary: Understanding the relationship between the coal chemical structure and its thermal reactivity is crucial for studying coal pyrolysis behaviors. This study used ReaxFF MD simulations and cheminformatics based reaction analysis to explore the effects of chemical structure on pyrolysis processes. The results provide insights into the temperature mapping and prediction of pyrolysis stages, weight loss profiles, and major pyrolyzate distributions based on coal structures. The simulation approach can complement experimental observations and be used as a preliminary screening tool for selecting coal types or ranks for industrial utilization.
Article
Computer Science, Artificial Intelligence
Jerret Ross, Brian Belgodere, Vijil Chenthamarakshan, Inkit Padhi, Youssef Mroueh, Payel Das
Summary: Researchers have used large language models to model molecules and obtained good results in property prediction. By training an efficient transformer model on unlabeled molecular data, better molecular embeddings were obtained compared to existing benchmarks. This suggests that large-scale molecular language models can capture sufficient chemical and structural information to predict various distinct molecular properties.
NATURE MACHINE INTELLIGENCE
(2022)
Article
Computer Science, Software Engineering
Devin Lange, Eddie Polanco, Robert Judson-Torres, Thomas Zangle, Alexander Lex
Summary: A new microscopy-based approach for measuring the mass of individual cancer cells treated with different drugs promises to determine the most promising drug for a cancer patient. However, the data analysis process still requires human intervention for quality control and data accuracy. The visualization tool called Loon is developed to analyze drug screening data and provides selection and filtering capabilities for representative cell samples, aiding in the decision-making process for suitable drugs for specific patients.
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
(2022)
Article
Environmental Studies
Joan Marull, Merce Farre, Marta Andreu Espuna, Adria Prior, Vittorio Galletto, Joan Trullen
Summary: This article uses new methods and evidence from satellite data to analyze the urban network structure of 100 European metropolitan regions. It develops indicators to test the hypothesis that complex urban networks are more economically efficient and less dependent on energy consumption. The results show that polycentric urban networks create more innovation, leading to greater economic efficiency and lower energy consumption. Further research is needed to explore the relationships between urban network structures and their social, economic, and ecological performances.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2023)
Article
Computer Science, Interdisciplinary Applications
Amir H. Gandomi, Kalyanmoy Deb, Ronald C. Averill, Shahryar Rahnamayan, Mohammad Nabi Omidvar
Summary: To solve complex real-world problems, a concept-based approach called variable functioning (Fx) is introduced to reduce optimization variables and narrow down the search space. By using problem structure analysis and engineering expert knowledge, the Fx method enhances the steel frame design optimization process. Coupled with particle swarm optimization and differential evolution algorithms, the proposed approach improves the convergence rate and final design of frame structures.
STRUCTURAL AND MULTIDISCIPLINARY OPTIMIZATION
(2023)
Article
Multidisciplinary Sciences
Joshua C. Peterson, David D. Bourgin, Mayank Agrawal, Daniel Reichman, Thomas L. Griffiths
Summary: By using large datasets and machine learning algorithms to analyze risky decision-making, this study was able to replicate historical findings, improve existing theories, and discover a more accurate model of human decision-making.
Article
Environmental Sciences
Wen-Cheng Liu, Chien-Hsing Lu, Wei-Che Huang
Summary: The large-scale particle image velocimetry (LSPIV) captured by a UAV and a terrestrial fixed station provides an effective method for measuring river surface velocity. Under low flow conditions, the accuracy of surface velocity measurements using LSPIV from a UAV is higher than that from a terrestrial fixed station. Optimal flight heights and parameter settings can enhance the accuracy of velocity measurements.
Article
Public Administration
E. Ezzahid, Z. Firano, J. Ennouhi, A. Laaroussi, A. Serghini Anbari
Summary: This paper proposes a new approach to rank countries based on their preparedness to handle large-scale crises and validates it using the COVID-19 health crisis. The findings suggest that countries with higher preparedness were able to respond better to the crisis.
Article
Astronomy & Astrophysics
Koki Yamashita, Yue Nan, Yuuki Sugiyama, Kazuhiro Yamamoto
Summary: This paper investigates a cosmological model with random inhomogeneities and anisotropies on large scales and explores their impact on the formation of the large-scale structure of the Universe. By solving the cosmological perturbation equations, the researchers find that the model is consistent with observations.
Article
Astronomy & Astrophysics
C. Gehan, B. Mosser, E. Michel, M. S. Cunha
Summary: Measuring stellar inclinations is crucial for understanding planetary formation, dynamics, and physical conditions during star formation. This study aims to develop an automated approach for measuring stellar inclinations applicable to solar-type pulsators and validate it using observed red giant branch stars. By analyzing dipole mixed modes with different azimuthal orders, the study successfully derived the statistical distribution of inclinations in an unbiased manner.
ASTRONOMY & ASTROPHYSICS
(2021)
Article
Geography, Physical
Bufan Zhao, Xijiang Chen, Xianghong Hua, Wei Xuan, Derek D. Lichti
Summary: This paper proposes a point cloud completion method with structural constraint to address the problem of incomplete building point clouds. By simulating the sinking and rebounding stages of cloth nodes, the position of point cloud in the area of interest is recovered, and the missing surfaces are completed through attitude adjustment. Experimental results demonstrate the feasibility and accuracy of the proposed method, which improves the integrity of a building point cloud and enhances the detail of LoD2 reconstruction.
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2023)
