A Novel Two-Stage Approach for Nonlinearity Correction of Frequency-Modulated Continuous-Wave Laser Ranging Combining Data-Driven and Principle-Based Strategies by Shichang Xu, Guohui Yuan, Hongwei Zhang, Chunyu Hou, Zhirong Li, Pansong Zhang, Wenhao Xu, Zhuoran Wang

“…In this mechanism, the neural network (NN) model establishes a mapping relationship between the input and output of the real laser-modulation system, which effectively simulates this physical system and avoids the risk of trial-and-error damage. Afterwards, the Soft Actor–Critic (SAC) model interacts with the NN model and trains a decision-making agent to determine the optimal modulation strategy for the nonlinearity pre-correction of the frequency-swept light. …”
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Development of a 3D-Printed Chest Phantom with Simulation of Lung Nodules for Studying Ultra-Low-Dose Computed Tomography Protocols by Jenna Silberstein, Steven Tran, Yin How Wong, Chai Hong Yeong, Zhonghua Sun

“…The measurement error between patient and phantom scans was −0.03 ± 0.14 cm. …”
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Intrathecal drug delivery systems: A case series advancing surgical, clinical, and technological safety with broader implications for invasive neuromodulation therapies by Bi Mo, Sandra Sacks, Jerry Markar

“…Invasive neuromodulation therapies, including intrathecal drug delivery systems, present multifaceted challenges that necessitate rigorous patient and therapeutic agent selection, meticulous risk factor mitigation, continuous neuromonitoring, and prompt detection of subtle neurological changes indicative of potential complications. This analysis delineates three critical domains: first, clinical vigilance and enhanced monitoring protocols are essential for the early identification of severe complications, such as granuloma formation; second, an educational paradigm shift, standardized, comprehensive surgical training in fellowship programs is required to ensure technical proficiency, optimal postoperative management, and an in-depth understanding of psychosocial factors; and third, technological leadership, the adoption of app-based management systems on consumer platforms introduces vulnerabilities including software malfunctions and cybersecurity threats, thereby necessitating that physicians advocate for stringent safety standards and robust regulatory oversight. …”
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Revolutionizing Clear-Sky Humidity Profile Retrieval with Multi-Angle-Aware Networks for Ground-Based Microwave Radiometers by Yinshan Yang, Zhanqing Li, Jianping Guo, Yuying Wang, Hao Wu, Yi Shang, Ye Wang, Langfeng Zhu, Xing Yan

“…Moreover, additional independent validation results demonstrate that AngleNet exhibits excellent stability and retrieval accuracy during periods without radiosonde measurements. Feature analysis and evaluations of the “multi-angle-aware” module indicate that optimal RH retrieval performance is achieved by combining zenith-angle BTs with oblique angles at 30° and 19.2°. …”
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A nomogram based on ultrasound scoring parameters and clinical indicators for differentiating primary Sjὅgren′s syndrome from IgG4-related sialadenitis by LIU Chuxuan, ZUO Jiaxin, XIONG Ping

“…The bootstrap method was used for internal validation with 1 000 resampling iterations, and the average absolute error was 0.018. Calibration curve demonstrated good agreement between predicted and observed values. …”
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Study on Prosthetic Hand Proprioception Feedback Based on Hybrid Vibro-Electrotactile Stimulation by Guangfei Wu, Wenqing Gu, Yi Luo, Xin Zhang, Lei Li, Jingming Hou, Haoyue Deng, Wensheng Hou, Lin Chen, Xing Wang

“…Outcome measures included categorical analysis of task completion outcomes, control precision error (CPE), completion time (CT), and feedback preference. …”
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Dynamic prediction of surface subsidence at any point based on Boltzmann time function model by Liangji XU, Zhihao SUN, Xiaopeng LIU, Kun ZHANG, Zongyou CAO

“…Results indicate that the dynamic prediction relative error during the mining process is less than 6.0%, the minimum is 2.7%.…”
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UAV-Based Multispectral Winter Wheat Growth Monitoring with Adaptive Weight Allocation by Lulu Zhang, Xiaowen Wang, Huanhuan Zhang, Bo Zhang, Jin Zhang, Xinkang Hu, Xintong Du, Jianrong Cai, Weidong Jia, Chundu Wu

“…Among the evaluated models, the RF model achieved the best performance, with a coefficient of determination (R²) of 0.895 and a root mean square error (RMSE) of 0.0058. A comparison with wheat orthophotos from the same period confirmed that the inversion results were highly consistent with actual growth conditions in the study area. …”
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Color-Sensitive Sensor Array Combined with Machine Learning for Non-Destructive Detection of AFB₁ in Corn Silage by Daqian Wan, Haiqing Tian, Lina Guo, Kai Zhao, Yang Yu, Xinglu Zheng, Haijun Li, Jianying Sun

“…The combined 1st D-PCA-KNN model showed optimal prediction performance, with determination coefficient (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi>R</mi><mi>p</mi><mn>2</mn></msubsup></mrow></semantics></math></inline-formula> = 0.87), root mean square error (<i>RMSEP</i> = 0.057), and relative prediction deviation (<i>RPD</i> = 2.773). …”
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Active power and frequency oscillation suppression strategy for parallel virtual synchronous generators system based on fractional-order virtual inertia by Lei Zhang, Rongliang Shi, Zheng Dong, Meishu Li, Junhui Li, Yu Zhang

“…Moreover, a small-signal state space model of the fractional-order PVSGS is developed, and the stability of the PVSGS is proved by using the root locus analysis method. Then, the optimal fractional-order virtual inertia order of the PVSGS are selected by using the ℋ2 and ℋ∞ norm. …”
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Calibration of Discrete Element Simulation Parameters and Model Construction for the Interaction Between Coastal Saline Alkali Soil and Soil-Engaging Components by Nan Xu, Zhenbo Xin, Jin Yuan, Zenghui Gao, Yu Tian, Chao Xia, Xuemei Liu, Dongwei Wang

“…Subsequently, by means of the discrete element method and the BBD experimental design method, a response surface model was established, and an optimization analysis was performed on the optimal parameters for the soil–soil collision recovery coefficient, static friction coefficient, and dynamic friction coefficient at each depth. …”
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Predicting the interfacial tension of CO2 and NaCl aqueous solution with machine learning by Kashif Liaqat, Daniel J. Preston, Laura Schaefer

“…Hyperparameter tuning algorithms are utilized to optimize each model, and the performance is evaluated using metrics such as mean absolute error (MAE) and mean absolute percentage error (MAPE). …”
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Research on future trends of electricity consumption based on conditional generative adversarial network considering dual‐carbon target by Jinghua Li, Zibei Qin, Yichen Luo, Jianfeng Chen, Shanyang Wei

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Pemanfaatan Internet Of Things (Iot) Dalam Proses Pengeringan Rimpang Dengan Menggunakan Platform Node-Red by Gaguk Suprianto

“…Moreover, with IoT the sensor data obtained is managed in a database for analysis purposes. Field test results for error testing obtained an average error percentage of 1.5% and accuracy testing obtained an average accuracy percentage of 98.49%. …”
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Study on the warm deformation behavior and microstructure evolution of the MDIFed Ti–6Al–4V titanium alloy by Yingxiang Yang, He Wang, Zhongxue Feng, Qingnan Shi, Bin Yang, Min Chen, Huarong Qi, Xiaoqi Wang

“…Through activation energy spectrum analysis, the average activation energy is approximately 308 kJ/mol. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…Ordinary Linear Regression (OLR), Geographically Weighted Regression (GWR), and Hierarchical Bayesian Approach (HBA) were employed to model GSV through comparative analysis of using various sample sizes. The results indicate that: (1) HBA(Site), which models different pine forest types (i.e. pure pine forest (PPF) and mixed pine forest (MXF)) separately, with typical site as a stratification factor, provided the best estimation results with coefficient of determination (R2) of 0.80 and 0.74, root mean square error (RMSE) of 25.15 m3/ha and 23.86 m3/ha for PPF and MXF, respectively. …”
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Black-box and white-box machine learning tools to estimate the frost formation condition during cryogenic CO2 capture from natural gas blends by Farag M.A. Altalbawy, Fadhel F. Sead, Dharmesh Sur, Anupam Yadav, José Gerardo León Chimbolema, Suhas Ballal, Abhayveer Singh, Anita Devi, Kamal Kant Joshi, Nizomiddin Juraev, Hossein Mahabadi Asl

“…To gain deeper insights into the most fundamental factors in controlling the FFT of CO2, a sensitivity analysis was conducted. The findings of the current study, in turn, contribute to the understanding of FFT of CO2 and the optimal design of the CCC processes in natural gas industries.…”
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Determination of Tungsten, Molybdenum and 5 Associated Elements in Tungsten-Molybdenum Ore by Inductively Coupled Plasma-Optical Emission Spectrometry with Direct Sintering by Zhou SONG, Yiping JI, Weihua WANG, Shaomin FANG, Jie YANG, Huoyan LUO, Yuqi ZHOU

“…At the same time, it can effectively reduce the emission of acid gas pollutants in the sample analysis and testing process and has a good application prospect. …”
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Assessment of predictors and mitigation strategy for therapeutic inertia in the management of hypertension: a quality improvement project by Ananyan Sampath, Shreya Deshpande, Rashmi Verma, Rajnish Joshi

“…Provider assessments included vignette-based evaluations to distinguish TI from clinical myopia. Statistical analysis using JASP 0.18.3 compared TI prevalence across subgroups, with significance testing and trend analysis. …”
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A Hybrid Machine Learning Approach: Analyzing Energy Potential and Designing Solar Fault Detection for an AIoT-Based Solar–Hydrogen System in a University Setting by Salaki Reynaldo Joshua, An Na Yeon, Sanguk Park, Kihyeon Kwon

“…The Transformer model was evaluated using metrics such as Mean Absolute Error (MAE), Mean Squared Error (MSE), and an additional variation of MAE (MAE2). …”
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