Comparison of Imaging Modalities for Left Ventricular Noncompaction Morphology by Márton Horváth, Dorottya Kiss, István Márkusz, Márton Tokodi, Anna Réka Kiss, Zsófia Gregor, Kinga Grebur, Kristóf Farkas-Sütő, Balázs Mester, Flóra Gyulánczi, Attila Kovács, Béla Merkely, Hajnalka Vágó, Andrea Szűcs

“…While cardiac magnetic resonance imaging (CMR) is considered the gold standard for evaluating LV morphology, the optimal modality for follow-up remains uncertain. …”
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Physics-Informed Neural Networks: A Review of Methodological Evolution, Theoretical Foundations, and Interdisciplinary Frontiers Toward Next-Generation Scientific Computing by Zhiyuan Ren, Shijie Zhou, Dong Liu, Qihe Liu

“…The contributions include threefold: First, identifying the co-evolutionary path of algorithmic architectures from adaptive optimization (neural tangent kernel-guided weighting achieving 230% convergence acceleration in Navier-Stokes solutions) to hybrid numerical-deep learning integration (5× speedup via domain decomposition) and second, constructing bidirectional theory-application mappings where convergence analysis (operator approximation theory) and generalization guarantees (Bayesian-physical hybrid frameworks) directly inform engineering implementations, as validated by <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>72</mn><mo>%</mo></mrow></semantics></math></inline-formula> cost reduction compared to FEM in high-dimensional spaces (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>p</mi><mo><</mo><mn>0.01</mn><mo>,</mo><mi>n</mi><mo>=</mo><mn>15</mn></mrow></semantics></math></inline-formula> benchmarks). …”
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A Modified MobileNetv3 Coupled With Inverted Residual and Channel Attention Mechanisms for Detection of Tomato Leaf Diseases by Rubina Rashid, Waqar Aslam, Romana Aziz, Ghadah Aldehim

“…While deep learning models have been instrumental in detecting plant leaf diseases, they often involve complex models and significant computational demands to achieve optimal performance. This study introduces a feasible lightweight model optimized for an Android application to detect diseased areas within images. …”
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Evidence for YORP-induced Spin Deceleration in Asteroid (433) Eros by Shuai Feng, Shaoming Hu, Xu Chen, Liyong Zhou, Yangbo Xu, Zehua Qi

“…To account for possible systematic errors, we applied bootstrap resampling at the light-curve level. …”
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Estimation of Leaf, Spike, Stem and Total Biomass of Winter Wheat Under Water-Deficit Conditions Using UAV Multimodal Data and Machine Learning by Jinhang Liu, Wenying Zhang, Yongfeng Wu, Juncheng Ma, Yulin Zhang, Binhui Liu

“…Traditional field sampling methods, such as random plant selection or full-quadrat harvesting, are labor intensive and may introduce substantial errors compared to the canopy-level estimates obtained from UAV imagery. …”
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Classification of maize seed hyperspectral images based on variable-depth convolutional kernels by Yating Hu, Hongchen Zhang, Hongchen Zhang, Changming Li, Qianfu Su, Wei Wang

“…The method offers a promising framework for hyperspectral image analysis in seed classification and other agricultural applications.…”
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Presenting the conceptual model of organizational democracy with an emphasis on the development of employees' psychological capital by Sattar jahantabi neghad, Foad Makvandi, ezat allah Kiani, ghanbar Amirnegad, Vahid Chenari

“…Because significance is checked at the error level of 0.05, so if the amount of factor loadings observed with the t-value test is calculated to be smaller than 1.96, the relationship is not significant and the question should be removed from the research. …”
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A chemical autonomous robotic platform for end-to-end synthesis of nanoparticles by Fan Gao, Hongqiang Li, Zhilong Chen, Yunai Yi, Shihao Nie, Zihao Cheng, Zeming Liu, Yuanfang Guo, Shumin Liu, Qizhen Qin, Zhengjian Li, Lisong Zhang, Han Hu, Cunjin Li, Liang Yang, Yunhong Wang, Guangxu Chen

“…Abstract Traditional nanomaterial development faces inefficiency and unstable results due to labor-intensive trial-and-error methods. To overcome these challenges, we developed a data-driven automated platform integrating artificial intelligence (AI) decision modules with automated experiments. …”
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High-Precision Small-Signal Model for Double-Channel–High-Electron-Mobility Transistors Based on the Double-Channel Coupling Effect by Ziyue Zhao, Qian Yu, Yang Lu, Chupeng Yi, Xin Liu, Ting Feng, Wei Zhao, Yilin Chen, Ling Yang, Xiaohua Ma, Yue Hao

“…This paper presents a new small-signal model for double-channel (DC)–high-electron-mobility transistors, developed through an analysis of the unique coupling effects between channels in devices. …”
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High resolution soil moisture mapping in 3D space and time using machine learning and depth functions by Mo Zhang, Yong Ge, Gerard B.M. Heuvelink, Yuxin Ma

“…The fitting of depth functions introduced only small errors, but caution is still needed when predicting at unobserved depths. …”
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SMART DShot: Secure Machine-Learning-Based Adaptive Real-Time Timing Correction by Hyunmin Kim, Zahid Basha Shaik Kadu, Kyusuk Han

“…Our approach addresses critical vulnerabilities in Electronic Speed Controller (ESC) interfaces by deploying four synergistic algorithms—Kalman Filter Timing Correction (KFTC), Recursive Least Squares Timing Correction (RLSTC), Fuzzy Logic Timing Correction (FLTC), and Hybrid Adaptive Timing Correction (HATC)—each optimized for specific error characteristics and attack scenarios. …”
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Perinatal artificial intelligence in ultrasound (PAIR) study: predicting delivery timing by Neil Patel, John O’Brien, Robert Bunn, Brandon Schanbacher, John Bauer, Garrett K. Lam

“…Unique predictions were made for each patient after each ultrasound exam, and the AI’s performance was evaluated against the actual delivery date using metrics such as R2 values and mean absolute error (MAE) compared to actual days until delivery. …”
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Short-term Precipitation Forecast Correction in Beijing-Tianjin-Hebei Region Based on Deep Learning by Wang Yuhong, Kong Dexuan, Zhu Shoupeng, Zhang Nan, Ji Yan, Zhang Shan, Xu Huan

“…The model employs a weighted combination of threat score (TS) and mean square error (MSE) as its loss function. The weight assigned to TS directly influences the model's performance. …”
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Mental fatigue of operating room nurses and its relationship with missed perioperative nursing care: a descriptive-analytical study by Vahid Rahmani, Valerie L. Marsh, Ebrahim Aliafsari Mamaghani, Ali Soleimani, Maedeh Alizadeh, Omid Zadi, Nasrin Aghazadeh

“…Abstract Introduction Mental fatigue is a psychological condition characterised by diminished alertness, impaired cognitive functioning, heightened error rates, and overall decreased performance. missed perioperative nursing care diminishes patient safety and increases the likelihood of adverse incidents. …”
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Consistency of the orbital chronologies derived for Vostok and EPICA DC ice cores based on the dependence of ice air content on local insolation by V. A. Khomyakova, N. A. Tebenkova, V. Ya. Lipenkov, D. Raynaud

“…Comparison of the TAC timescales with the optimized chronologies AICC2012 and AICC2023 for the Vostok and EDC cores showed that their discrepancy, as a rule, does not exceed 2 ka, which is consistent with both the standard error of the TAC­based dating method (±2.1 ka) and the standard errors of the AICC2012 (±1.9…4.8 ka) and AICC2023 (±0.8…2.6 ka) reference chronologies themselves. …”
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Three-dimensional visualization of maize roots based on magnetic resonance imaging by Fang Xiaorong, Wang Nanfei, Zhang Jianfeng, Gong Xiangyang, Liu Fei, He Yong

“…Plant root system is plastic and dynamic, allowing plants to respond to their different environments in order to optimize acquisition of important soil resources. A number of root architecture parameters are known to be correlated with improved crop performance. …”
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Determination of Rare Earth Elements in Soil and Stream Sediment by Inductively Coupled Plasma-Mass Spectrometry with Automatic Graphite Digestion by Meiyun ZENG, Qisheng HE, Xin SHAO, Xiaoli YANG

“…The digestion procedure, the effects of digestion mixed acid, precision, accuracy, and detection limit of the method were studied by soil and stream sediment reference materials including GBW07402, GBW07446, GBW07448, GBW07454, GBW07456, GBW07457, GBW07304a, GBW07307a, GBW07308, GBW07312, GBW07359 and GBW07361.RESULTSThe results showed that the amount of mixed acids was 4mL consumed by soil and stream sediment digestion according to optimized digestion procedure. The absolute values of relative error and ΔlgC of rare earth elements were 0-6.67% and 0-0.028, respectively. …”
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The Development of an Air Suction Precision Seed-Metering Device for Rice Plot Breeding by Wei Qin, Yuwu Li, Cheng Qian, Zhuorong Fan, Daoqing Yan, Guo Zou, Siqian Liu, Zaiman Wang, Ying Zang, Minghua Zhang

“…Firstly, based on morphological analysis and MATLAB image processing, an active contour method was used to construct a suction hole model. …”
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Biologically inert ceramics thermodynamic mechanisms and models in cutting and grinding: a comparative assessment by Xianggang Kong, Xiaotong Chen, Min Yang, Fuhe Hao, Xin Cui, Mingzheng Liu, Benkai Li, Yanbin Zhang, Xiao Ma, Changhe Li

“…At the same time, an optimization analysis of the machining parameters in cutting and grinding processes was conducted, and the optimal range of machining parameters under different processing methods was determined. …”
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Impact of SLR long-term mean range biases on SLRF2020-based orbits of altimetry satellites by Sergei Rudenko, Mathis Bloßfeld, Alexander Kehm, Denise Dettmering, Julian Zeitlhöfler

“…However, one should be careful with applying the latter approach, since frequently (i.e. with a high temporal resolution) estimated biases in the radial direction absorb, beside SLR measurement errors and system delays, also non-modeled or not-perfectly modeled geophysical signals (e.g., non-tidal station loading) which might be of particular importance for some analysis. …”
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