How to crack a SMILES: automatic crosschecked chemical structure resolution across multiple services using MoleculeResolver by Simon Müller

“…MoleculeResolver systematically crosschecks structures retrieved from multiple reputable chemical databases, implements rigorous identifier plausibility checks, standardizes molecular structures, and intelligently selects the most accurate representation based on a unique resolution algorithm. Scientific contribution Benchmarks across diverse datasets confirm that MoleculeResolver significantly enhances precision, recall, and overall reliability compared to traditional single-source methods, proving its utility as a valuable resource for chemists, data scientists, and researchers engaged in high-quality molecular data analysis and predictive model development. …”
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Three-Dimensional Impact Time and Angle Control Guidance Based on MPSP by Yang Li, Hao Zhou, Wanchun Chen

“…The guidance law is devised using the model predictive static programming (MPSP) method, and the control saturation constraint is incorporated in the MPSP algorithm. …”
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HMS-PAU-IN: A heterogeneous multi-scale spatiotemporal interaction network model for population analysis units by Xiaorui Yang, Rui Li, Jing Xia, Junhao Wang, Hongyan Li, Nixiao Zou

“…To validate the model, we developed a population prediction model that integrates the multi-scale features of PAUs and introduced Leiden-IES-PMS, a community detection method based on the Leiden algorithm, which integrates internal and external environmental semantics and adopts a proximity merging strategy. …”
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Real-time monitoring of soil moisture in cotton fields using electromagnetic induction technology by Yang Gao, Quanze Hu, Jiaojiao Hui, Lin Chang, Mei Zeng, Qingsong Jiang

“…Currently, electromagnetic induction technology provides a non-destructive alternative, using the inversion simulation of soil apparent electrical conductivity (ECa) to construct an empirical θg model, but the prediction accuracy of the constructed model is questioned when dealing with dynamic or highly uncertain data, resulting in large errors in the prediction results and cannot meet the needs of practical applications. …”
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Collaborative optimization of signals and ecological driving speed guidance for buses without dedicated bus lanes in the connected environment by Hui Li, Yunfei Ge, Yuzhou Duan, Xu Zhang

“…Initially, an Extended Kalman Filter is employed to predict the arrival time of buses at intersections and the signal status. …”
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Computer Vision-Based Robotic System Framework for the Real-Time Identification and Grasping of Oysters by Hao-Ran Qu, Jue Wang, Lang-Rui Lei, Wen-Hao Su

“…In order to capture oyster motion dynamically on a conveyor belt, a Kalman filter (KF) combined with a Low-Pass filter algorithm was employed to predict oyster trajectories, thereby improving noise reduction and motion stability. …”
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Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through PSMA1- NF-κB-HIF-1α signaling axis by Qian Dai, Qian Dai, Hua Wang, Hua Wang, Fang Li, Fang Li, Runchun Huang, Runchun Huang, Chenjun Jiang, Chenjun Jiang, Liuya Yuan, Liuya Yuan, Yayun Wang, Yayun Wang, Xun Li, Xun Li

“…Prostate cancer (PCa) is a common and deadly cancer in men, and despite its low specificity, PSA testing is the main method that is used to predict prognosis. Effective methods for predicting prognosis in clinical practice are lacking. …”
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Grey Wolf Resampling-Based Rao-Blackwellized Particle Filter for Mobile Robot Simultaneous Localization and Mapping by Yong Dai, Ming Zhao

“…In addition, we propose an adaptive local data association (Range-SLAM) scheme to improve the computational efficiency for the algorithm of the nearest neighbor (NN) data association in the iteration of the RBPF prediction. …”
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Efficient signcryption scheme based on Cocks’ identity cryptosystem by Changgen PENG, Xiaoyu ZHANG, Hongfa DING, Shanhui YANG

“…Most of the existing identity-based signcryption schemes are based on bilinear or multilinear pairing operations construction.To solve the problem of low efficiency caused by complex pair operation, a new efficient signcryption scheme based on the identity cryptosystem of Cocks was proposed.Firstly, the security model of the proposed scheme was formalized, and the definition of confidentiality and unforgeability was given.Secondly, the quadratic residue problem was used to realize the concrete construction of the proposed scheme, and the signature algorithm was designed in a logical step by combining Jacobi symbol operation.Finally, the security proofed that the scheme satisfied the confidentiality and unforgeability was given under the random prediction model.The efficiency analysis shows that compared with the existing identity-based signcryption scheme, the proposed scheme greatly improves the computing efficiency and has good characteristics of identity-based cryptosystem.…”
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Complexity control method of random forest based HEVC by Peng WEN, Zongju PENG, Fen CHEN, Gangyi JIANG, Mei YU

“…High efficiency video coding (HEVC) has high computational complexity,and fast algorithm cannot perform video coding under restricted coding time.Therefore,a complexity control method of HEVC based on random forest was proposed.Firstly,three random forest classifiers with different prediction accuracy were trained to provide various coding configurations for coding tree unit (CTU).Then,an average depth-complexity model was built to allocate CTU complexity.Finally,the CTU coding configuration,determined by the smoothness,average depth,bit,and CTU-level accumulated coding error,was used to complete complexity control.The experimental results show that the proposed method has better complexity control precision,and outperforms the state-of-the-art method in terms of video quality.…”
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基于改进Kriging模型的主动学习可靠性分析方法 by 陈哲, 杨旭锋, 程鑫

“…,the differential evolution algorithm is introduced to explore the optimal parameter of Kriging model and improve the accuracy of Kriging prediction information.As a result,the training point in each iteration is guaranteed to be the global optimal one and the efficiency of ALK model is largely improved.…”
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Efficient signcryption scheme based on Cocks’ identity cryptosystem by Changgen PENG, Xiaoyu ZHANG, Hongfa DING, Shanhui YANG

“…Most of the existing identity-based signcryption schemes are based on bilinear or multilinear pairing operations construction.To solve the problem of low efficiency caused by complex pair operation, a new efficient signcryption scheme based on the identity cryptosystem of Cocks was proposed.Firstly, the security model of the proposed scheme was formalized, and the definition of confidentiality and unforgeability was given.Secondly, the quadratic residue problem was used to realize the concrete construction of the proposed scheme, and the signature algorithm was designed in a logical step by combining Jacobi symbol operation.Finally, the security proofed that the scheme satisfied the confidentiality and unforgeability was given under the random prediction model.The efficiency analysis shows that compared with the existing identity-based signcryption scheme, the proposed scheme greatly improves the computing efficiency and has good characteristics of identity-based cryptosystem.…”
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Echo state networks for modeling turbulent convection by Mohammad Sharifi Ghazijahani, Christian Cierpka

“…Even for this highly turbulent flow, it is challenging to distinguish predictions from the ground truth. The statistical convergence of the ESN goes beyond the velocity values and is represented in secondary aspects of the flow dynamics, such as spatial and temporal derivatives and vortices. …”
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Post-Pandemic Urban Future: Identification of the main trends of change in Latin America, through the application of the Delphi method by Yeimis Milton Palomino Pichihua

“…Additionally, it employs machine learning algorithms to transform them into predictions. The sample is made up of 26 panelists from different Latin American countries, who participated in successive questionnaires until stable results were reached. …”
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Advanced Solar Irradiance Forecasting Using Hybrid Ensemble Deep Learning and Multisite Data Analytics for Optimal Solar-Hydro Hybrid Power Plants by Sudharshan Konduru, Naveen C., Jagabar Sathik M.

“…A novel hybrid decomposed residual ensembling model for deep learning (SBLTSRARW) using models such as autoregressive integrated moving average (ARIMA) and seasonal-trend decomposition using loess (STL) along with prediction and optimization models such as Bidirectional LSTM (Bi-LSTM), and Whale Optimization Algorithm (WOA) methods are used to predict the irradiances. …”
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An Empirical Configuration Study of a Common Document Clustering Pipeline by Anton Eklund, Mona Forsman, Frank Drewes

“…The results suggest that BERT embeddings combined with UMAP dimension reduction to no less than 15 dimensions provides a good basis for clustering, regardless of the specific clustering algorithm used. …”
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Enhanced flux potential analysis links changes in enzyme expression to metabolic flux by Xuhang Li, Albertha J M Walhout, L Safak Yilmaz

“…Abstract Algorithms that constrain metabolic network models with enzyme levels to predict metabolic activity assume that changes in enzyme levels are indicative of flux variations. …”
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High-confidence assessment of functional impact of human mitochondrial non-synonymous genome variations by APOGEE. by Stefano Castellana, Caterina Fusilli, Gianluigi Mazzoccoli, Tommaso Biagini, Daniele Capocefalo, Massimo Carella, Angelo Luigi Vescovi, Tommaso Mazza

“…Since these tools proved to be rather incongruent, we have designed and implemented APOGEE, a machine-learning algorithm that outperforms all existing prediction methods in estimating the harmfulness of mitochondrial non-synonymous genome variations. …”
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Characteristics of gut and lung microbiota in patients with lung masses and their relationship with clinical features by Yanping Yang, Jiacheng Shen, Sulan Wei, Maosong Ye, Xing Zhao, Jian Zhou, Lin Tong, Jie Hu, Yuanlin Song, Shengdi Wu, Nuo Xu

“…For differentiating benign and malignant masses, the combination of Megasphaera and norank_p__Saccharibacteria in BALF demonstrated superior predictive performance, with an AUC reaching 0.8 (95% CI 0.59-1). …”
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Machine learning-based radiomics for differentiating lung cancer subtypes in brain metastases using CE-T1WI by Xueming Xia, Wei Du, Qiheng Gou

“…The models’ performance was evaluated using receiver operating characteristic (ROC) analysis and area under the curve (AUC) calculations, complemented by additional metrics such as accuracy, specificity, sensitivity, positive predictive value (PPV), and negative predictive value (NPV).ResultsA total of 833 radiomic features were extracted from the ROIs. …”
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