Article
Chemistry, Multidisciplinary
Yoona Choi, Subin Lee, Heejun Kim, Seung Bum Park
Summary: The rigidity and flexibility of small molecules complement each other in 3-dimensional ligand-protein interactions. Therefore, a chemical library with conformational diversity would be a valuable resource for studying the influence of skeletal flexibility on biological systems. In this study, we designed and synthesized ten conformationally diverse pyrimidine-embedded medium/macro- and bridged cyclic scaffolds with 7- to 14-member rings using an efficient skeletal transformation strategy. Their high conformational and shape diversity was confirmed through chemoinformatic analysis.
FRONTIERS IN CHEMISTRY
(2022)
Article
Chemistry, Physical
John F. Gallagher, Pavle Mocilac
Summary: Four solvates of the imide-based macrocycle (IO)(4) with different solvent molecules were reported, each showing unique molecular arrangements and crystal structures. The behavior of the solvent molecules varied among the solvates, with DMF molecules forming 1D channels in one structure, while DMSO molecules exhibited extensive disorder in another structure.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Article
Sport Sciences
Christopher Papic, Ross H. Sanders, Roozbeh Naemi, Marc Elipot, Jordan Andersen
Summary: This study compared the speed, accuracy, and reliability of 2D body landmark digitization using a neural network with manual digitization in the glide phase of swimming. The neural network digitized body landmarks 233 times faster than manual digitization, with a root-mean-square-error of around 4-5 mm, showing high accuracy and reliability. Results demonstrated strong agreement and correlation between body position and glide variable data obtained from the two methods.
JOURNAL OF SPORTS SCIENCES
(2021)
Article
Computer Science, Information Systems
Ruobing Xie, Qi Liu, Shukai Liu, Ziwei Zhang, Peng Cui, Bo Zhang, Leyu Lin
Summary: Real-world recommendation systems typically consist of a matching module and a ranking module, with recommendation diversity playing a crucial role in user experience. This article introduces a novel framework called GraphDR, based on heterogeneous graph neural networks, aimed at improving both recommendation accuracy and diversity in matching. GraphDR has been successfully deployed in a popular recommendation system, WeChat Top Stories, and has shown significant improvements in online and offline evaluations.
IEEE TRANSACTIONS ON BIG DATA
(2021)
Article
Agronomy
Xuezhang Li, Ming'an Shao, Xianli Xu, Kelin Wang
Summary: Knowledge of the spatiotemporal dynamics of soil water storage is crucial for hydrological modeling and vegetation restoration in semi-arid areas. This study investigated the influences of sampling frequency and soil depth on soil water storage and its temporal stability. The results showed that sampling frequency did not affect mean soil water storage, but significantly influenced temporal stability characteristics. Additionally, the study found that soil depth played a role in increasing the temporal stability of soil water storage.
EUROPEAN JOURNAL OF AGRONOMY
(2022)
Article
Engineering, Industrial
Gina Sierra, Elinirina Robinson, Kai Goebel
Summary: This paper investigates the use of prognostic information in decision-making processes, focusing on risk-informed thresholds for maintenance or operational setting changes. Sampling-based techniques are analyzed for their effectiveness in uncertainty propagation and analysis, with Latin Hypercube Sampling (LHS) showing no significant advantage over Monte Carlo Sampling (MCS) in terms of tail prediction with small sample sizes. A methodology combining MCS and Kernel Density Estimation (KDE) is explored for improving tail accuracy with reduced sample size in battery end-of-discharge data.
RELIABILITY ENGINEERING & SYSTEM SAFETY
(2021)
Article
Engineering, Electrical & Electronic
Qi Li, Dafang Wang, Jianhua Lin, Fangheng Jian, Zhifu Wang, Conggan Ma
Summary: This article proposes a new EME design method based on MIMO modeling and MCLCC structure, which can achieve dynamic accuracy objectives and robust performance at high operating speeds. Experimental results demonstrate the superiority of the proposed method.
IEEE TRANSACTIONS ON POWER ELECTRONICS
(2022)
Article
Physics, Multidisciplinary
Stephen Whitelam
Summary: A new image classification method is proposed, which increases the coverage of configuration space in the training set through coarse-graining and stochastic sampling, while maintaining classification accuracy. This approach outperforms traditional machine learning techniques in terms of classification accuracy on the MNIST and Fashion-MNIST datasets.
Article
Multidisciplinary Sciences
Charlotte Wray, Alysse J. Kowalski, Feziwe Mpondo, Laura Ochaeta, Delia Belleza, Ann Digirolamo, Rachel Waford, Linda Richter, Nanette Lee, Gaia Scerif, Alan Stein, Aryeh D. Stein, COHORTS
Summary: Executive functions can be measured by accuracy, reaction times, and computed scores. Different scoring methods can lead to interpretation issues. This study compared two scoring approaches and found that computed scores may be a reliable measure of executive functions. However, different populations should carefully consider the scoring and interpretation methods.
Article
Engineering, Electrical & Electronic
Zeinab Saeidiyan, Mohammad Hosein Fatehi, Mehdi Taghizadeh, Mohammad Mehdi Ghanbarian
Summary: This paper presents a new design of low-power and fast analog to digital converter for specific applications in image processing. By using a method that involves rereading a limited number of pixels, considerable power reduction can be achieved compared to the method that relies on pixel values.
JOURNAL OF SENSORS
(2022)
Article
Chemistry, Multidisciplinary
Bryan A. Raubenolt, Steven W. Rick
Summary: This paper presents a replica-exchange method for overcoming the amide bond sampling problem in polypeptoids. The method allows for easy access to both cis and trans conformations and enhances sampling for other coordinates. The results show that the conformation of the peptoids depends on the side chain and potential model.
JOURNAL OF COMPUTATIONAL CHEMISTRY
(2022)
Article
Endocrinology & Metabolism
Robert Richer, Luca Abel, Arne Kuederle, Bjoern M. Eskofier, Nicolas Rohleder
Summary: A smartphone application called CARWatch has been developed to address the issues of low adherence and lack of objective methods in studying the cortisol awakening response (CAR). In a proof-of-concept study, CARWatch was used to objectively assess saliva sampling times and improve adherence in CAR studies. The results showed that CARWatch led to more consistent sampling behavior, reduced sampling delay, and improved accuracy in CAR measurements.
PSYCHONEUROENDOCRINOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Solenn Stoeckel, Barbara Porro, Sophie Arnaud-Haond
Summary: The study demonstrates two complementary behaviors in the probability distributions of genotypic and genetic indices with increasing rates of clonality. Genotypic indices provide reliable estimates of clonality, while genetic descriptors perform poorly for clonality levels below 0.95.
MOLECULAR ECOLOGY RESOURCES
(2021)
Article
Energy & Fuels
Zuo Dong, Xianjia Wang, Runzhou Zhu, Xuan Dong, Xueshan Ai
Summary: Hourly wind speed analysis is crucial for improving the accuracy of wind speed characterization and guiding the hourly operation of wind farms, outperforming annual wind speed series analysis. Gamma distribution shows better performance than the other three distributions in characterizing the hourly wind speed series.
Article
Computer Science, Artificial Intelligence
Seyed Mahdi Shariatzadeh, Mahmood Fathy, Reza Berangi
Summary: This paper aims to use neural architecture search to find optimal convolutional neural networks for industrial image processing applications. Through searching from about 32 billion models, we obtained an optimized CNN model with minimum validation error and low computational cost for multiple-templates matching applications such as license plate detection. After about 500 neural architecture evaluations, our final model achieved about 20-times error reduction and 6-times computational complexity reduction compared to the classic template matching algorithms, while performing more robust multiple-template matching with different scales.
Article
Biochemistry & Molecular Biology
Ajay S. Tanwar, Daniel J. Sindhikara, Fumio Hirata, Ruchi Anand
ACS CHEMICAL BIOLOGY
(2015)
Article
Biophysics
Akihiro Maeno, Daniel Sindhikara, Fumio Hirata, Renee Otten, Frederick W. Dahlquist, Shigeyuki Yokoyama, Kazuyuki Akasaka, Frans A. A. Mulder, Ryo Kitahara
BIOPHYSICAL JOURNAL
(2015)
Article
Biochemistry & Molecular Biology
Jiraphorn Phanich, Thanyada Rungrotmongkol, Daniel Sindhikara, Saree Phongphanphanee, Norio Yoshida, Fumio Hirata, Nawee Kungwan, Supot Hannongbua
Article
Chemistry, Medicinal
Siegfried S. F. Leung, Daniel Sindhikara, Matthew P. Jacobson
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2016)
Article
Chemistry, Physical
Haoyu S. Yu, Yuqing Deng, Yujie Wu, Dan Sindhikara, Amy R. Rask, Takayuki Kimura, Robert Abel, Lingle Wang
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
(2017)
Article
Multidisciplinary Sciences
Dan Sindhikara, Ken Borrelli
SCIENTIFIC REPORTS
(2018)
Article
Chemistry, Physical
Derek P. Metcalf, Alexios Koutsoukas, Steven A. Spronk, Brian L. Claus, Deborah A. Loughney, Stephen R. Johnson, Daniel L. Cheney, C. David Sherrill
JOURNAL OF CHEMICAL PHYSICS
(2020)
Article
Chemistry, Physical
Zachary L. Glick, Derek P. Metcalf, Alexios Koutsoukas, Steven A. Spronk, Daniel L. Cheney, C. David Sherrill
JOURNAL OF CHEMICAL PHYSICS
(2020)
Article
Food Science & Technology
Binita Shah, Dan Sindhikara, Ken Borrelli, Abba E. Leffler
Article
Chemistry, Medicinal
Derek P. Metcalf, Andy Jiang, Steven A. Spronk, Daniel L. Cheney, C. David Sherrill
Summary: EPNN is a fast and accurate neural network atomic charge partitioning model that conserves total molecular charge at a fraction of the cost of traditional quantum mechanical computations. It can be easily applied to large biomolecules, making it highly practical for various applications.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2021)
Article
Chemistry, Physical
Jeffrey B. Schriber, Daniel R. Nascimento, Alexios Koutsoukas, Steven A. Spronk, Daniel L. Cheney, C. David Sherrill
Summary: CLIFF is a machine-learned intermolecular force field that combines accurate physics equations with automatic parameterization, achieving high precision in drug discovery and protein models. It demonstrates excellent performance in both test sets and applications by accurately ranking ligand binding strengths and producing low errors compared to reference values.
JOURNAL OF CHEMICAL PHYSICS
(2021)
Article
Chemistry, Medicinal
Yan Shi, Ying Wang, Wei Meng, Robert P. Brigance, Denis E. Ryono, Scott Bolton, Hao Zhang, Sean Chen, Rebecca Smirk, Shiwei Tao, Joseph A. Tino, Kristin N. Williams, Richard Sulsky, Laura Nielsen, Bruce Ellsworth, Michael K. Y. Wong, Jung-Hui Sun, Leslie W. Leith, Dawn Sun, Dauh-Rurng Wu, Anuradha Gupta, Richard Rampulla, Arvind Mathur, Bang-Chi Chen, Aiying Wang, Helen G. Fuentes-Catanio, Lori Kunselman, Michael Cap, Jacob Zalaznick, Xiaohui Ma, Heng Liu, Joseph R. Taylor, Rachel Zebo, Beverly Jones, Stephen Kalinowski, Joann Swartz, Ada Staal, Kevin O'Malley, Lisa Kopcho, Jodi K. Muckelbauer, Stanley R. Krystek, Steven A. Spronk, Jovita Marcinkeviciene, Gerry Everlof, Xue-Qing Chen, Carrie Xu, Yi-Xin Li, Robert A. Langish, Yanou Yang, Qi Wang, Kamelia Behnia, Aberra Fura, Evan B. Janovitz, Nicola Pannacciulli, Steven Griffen, Bradley A. Zinker, John Krupinski, Mark Kirby, Jean Whaley, Robert Zahler, Joel C. Barrish, Jeffrey A. Robl, Peter T. W. Cheng
Summary: This article focuses on the investigation of a potential treatment for type 2 diabetes through the activation of glucokinase. By studying a series of compounds, a partial glucokinase activator was discovered and its pharmacokinetics and pharmacology were explored. The results show promising efficacy and safety, leading to the advancement of this activator into human clinical trials.
JOURNAL OF MEDICINAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Scott A. Shaw, Benjamin P. Vokits, Andrew K. Dilger, Andrew Viet, Charles G. Clark, Lynn M. Abell, Gregory A. Locke, Gerald Duke, Lisa M. Kopcho, Ashok Dongre, Ji Gao, Arathi Krishnakumar, Sutjano Jusuf, Javed Khan, Steven A. Spronk, Michael D. Basso, Lei Zhao, Glenn H. Cantor, Joelle M. Onorato, Ruth R. Wexler, Franck Duclos, Ellen K. Kick
BIOORGANIC & MEDICINAL CHEMISTRY
(2020)