Molecular mechanisms of flowering time differentiation revealed by transcriptomic sequencing and de novo analysis in Chinese invasive populations of Ambrosia artemisiifolia by Xiao-Feng Yang, Xiao-Meng Li, Pär K. Ingvarsson, Chao Xi, Wan-Jin Liao

“…Notably, NCL(1), FBH3, MAF2, and FLK may function differently in A. artemisiifolia compared to Arabidopsis thaliana. …”
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Design of Constant Speed Controller for Hydraulic Retarder Based on Robust Control by Pengxiang Song, Ao Meng, Yang Ding

“…Then, based on the concept of sliding mode control, the sliding mode controller with saturation function and the high-frequency robust controller are developed to modulate the filling rate of the hydraulic retarder in response to variations in vehicle speed. …”
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Machine learning based method for forecasting short-term passenger flow in urban rail stations by HU Mingwei, SHI Xiaolong, WU Wenlin, HE Guoqing

“…Compared with a single model, LightGBM-LSTM model equipped with merits of multiple models, fulfills a better function in forecasting and a better adaptability to different types of urban rail transit stations.…”
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An Interpretable Siamese Attention Res-CNN for Fingerprint Spoofing Detection by Chengsheng Yuan, Zhenyu Xu, Xinting Li, Zhili Zhou, Junhao Huang, Ping Guo

“…The model mitigates the performance deterioration caused by gradient disappearance. Furthermore, to highlight the difference in RCF, a Siamese attention residual network is devised, and the ridge continuity amplification loss function is designed to optimize the training process. …”
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CSNet: A Remote Sensing Image Semantic Segmentation Network Based on Coordinate Attention and Skip Connections by Jiahao Li, Hongguo Zhang, Liang Chen, Binbin He, Huaixin Chen

“…Additionally, a hybrid loss function combining weighted cross-entropy and Dice loss is employed. …”
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Alternative ‘block and delivery’ approach for alcohol septal ablation in hypertrophic cardiomyopathy with ischemia: a case report by S. M. Mamun Iqbal, Neuton Mondal, Mafuza Tabassum Khan, Ashir Faishal Hamim, Nurullah Mujahid Majumder, Anindita Das Barshan, Mohammad Jahid Hasan

“…Abstract Background Hypertrophic cardiomyopathy (HCM) is a prevalent hereditary cardiac disorder characterized by marked myocardial hypertrophy, which may lead to impaired diastolic function and relative myocardial ischemia. On rare occasions, HCM coexists with coronary artery disease (CAD), complicating therapeutic decisions due to heightened risks of heart failure and ischemic events. …”
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Identification of CT based radiomic biomarkers for progression free survival in head and neck squamous cell carcinoma by Xiao Ling, Soha Bazyar, Matthew Ferris, Jason Molitoris, Erin Allor, Hannah Thomas, Danielle Arons, Lisa Schumaker, Rebecca Krc, William Silva Mendes, Phuoc T. Tran, Amit Sawant, Ranee Mehra, Daria A. Gaykalova, Lei Ren

“…An ensemble feature selection involving correlation analysis, univariate survival analysis, best-subset selection, and the LASSO-Cox algorithm was used to select functional features, which were then used to build final Cox Proportional Hazards models (CPH). …”
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Deep neural networks have an inbuilt Occam’s razor by Chris Mingard, Henry Rees, Guillermo Valle-Pérez, Ard A. Louis

“…Combining this with the prior yields an accurate prediction for the posterior, measured for DNNs trained with stochastic gradient descent. This analysis shows that structured data, together with a specific Occam’s razor-like inductive bias towards (Kolmogorov) simple functions that exactly counteracts the exponential growth of the number of functions with complexity, is a key to the success of DNNs.…”
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Diastolic Mitral Regurgitation Caused by Acute Myocardial Infarction Complicated With Severe Heart Failure by Wataru Suzuki, Kentaro Mukai, Hirofumi Ohashi, Yoshiyuki Ogawa, Manami Ono, Masanobu Fujimoto, Hirohiko Ando, Tetsuya Amano

“…Diastolic mitral regurgitation (MR) is a rare and often-overlooked form of functional MR. Key factors in the development of diastolic MR include incomplete closure of the mitral valve, reversal of left atrioventricular pressure gradient during diastole, and elevated left ventricular diastolic pressure. …”
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Adam Algorithm with Step Adaptation by Vladimir Krutikov, Elena Tovbis, Lev Kazakovtsev

“…Adam (Adaptive Moment Estimation) is a well-known algorithm for the first-order gradient-based optimization of stochastic objective functions, based on adaptive estimates of lower-order moments. …”
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The Space Decomposition Theory for a Class of Semi-Infinite Maximum Eigenvalue Optimizations by Ming Huang, Li-Ping Pang, Xi-Jun Liang, Zun-Quan Xia

“…For the class of max-functions, which possesses the so-called primal-dual gradient structure, we compute smooth trajectories along which certain second-order expansions can be obtained. …”
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Study on the mechanisms associating community outdoor public spaces with elderly behavior by Lei Wang, Wenqi He, Shan Wu, Bo Zhang, Xiaorui Zhang, Hu Yin

“…Subsequently, a set of quantifiable indicators for community outdoor public spaces is established, and nonlinear machine learning models (Random Forest, Gradient Boosting Decision Tree, and eXtreme Gradient Boosting) are employed to reveal the association mechanisms between these six behaviors and the four categories of spatial metrics. …”
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Machine learning prediction of pKa of organic acids by Juda Baikété, Alhadji Malloum, Jeanet Conradie

“…Further molecular descriptors have been generated using density functional theory (DFT) calculations, and RDKit library. …”
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Offshore wind farm layout optimization accounting for participation in secondary reserve markets by T.-H. Nguyen, J. Quick, P.-E. Réthoré, J.-F. Toubeau, E. De Jaeger, F. Vallée

“…This study presents a new formulation for wind farm layout optimization where the objective function aims at maximizing revenues from both day-ahead and reserve markets. …”
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AIF: Infrared and Visible Image Fusion Based on Ascending–Descending Mechanism and Illumination Perception Subnetwork by Ying Liu, Xinyue Mi, Zhaofu Liu, Yu Yao

“…The customized loss function consists of illumination loss, gradient loss, and intensity loss. …”
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Multi-scenario simulation of land use optimization based on ecosystem services and ecological security patterns in the Liaohe River Basin by Qing Luo, Jing Zhang, Yajing Bao, Yilin Zhang, Jie Yu, Jiaxin Li, Xunwen Wu, Shuai Zhang, Nan Cao, Dongli Wang

“…These ESPs were further embedded as redline constraints in scenario-based land use simulations under four development pathways, forming a spatial structure that links ecological function with landscape connectivity and couples service assessments with spatial policy optimization.ResultsThe results showed that: (1) the Total Ecosystem Service (TES) exhibited a spatial gradient of high values in the east and west and low values in the central basin, with the strongest synergy with habitat quality, and the weakest with water yield; (2) ecosystem service bundle zoning revealed that the Comprehensive Service Function Zone and the Ecological Buffer Zone had the highest levels of diversity and connectivity, while the Agricultural Development Priority Zone exhibited a strong coupling between spatial structure and dominant function; (3) among different scenarios, the ecological-priority scenario (PEP) reduced net forest loss by 63.2% compared to the economic-priority scenario (PUD), significantly enhancing ecological spatial integrity.DiscussionThis study proposed a scenario-based simulation framework to support ecological redline delineation and watershed-scale ecosystem governance for territorial ecological restoration.…”
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An Optimized Path Planning Method for Coastal Ships Based on Improved DDPG and DP by Yiquan Du, Xiuguo Zhang, Zhiying Cao, Shaobo Wang, Jiacheng Liang, Fengge Zhang, Jiawei Tang

“…Hence, this paper improves the reward principle of traditional DDPG through the mainline reward function and auxiliary reward function, which not only helps to plan a better path for ship but also improves the convergence speed of the model. …”
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GAN-based pseudo random number generation optimized through genetic algorithms by Xuguang Wu, Yiliang Han, Minqing Zhang, Yu Li, Su Cui

“…In situations where non-differentiable activation functions, such as the modulo operation, are employed and traditional gradient-based backpropagation methods are inapplicable, genetic algorithms are utilized to optimize the parameters of the generator network. …”
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Electrochemically grown porous platinum for electrocatalysis and optical applications by Sarmiza-Elena Stanca, Marco Diegel, Jan Dellith, Gabriel Zieger, Uwe Hübner, Andreas Ihring, Heidemarie Krüger

“…These layers exhibit a thickness gradient and surface corner overloading due to electric charge accumulation at the sharp corners. …”
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Using GNN property predictors as molecule generators by Félix Therrien, Edward H. Sargent, Oleksandr Voznyy

“…We demonstrate the application of this method by generating molecules with specific energy gaps verified with density functional theory (DFT) and with specific octanol-water partition coefficients (logP). …”
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