The optimization path of agricultural industry structure and intelligent transformation by deep learning by Xingchen Pan, Jinyu Chen

“…In crop yield prediction, the proposed method achieves superior performance, as evidenced by reductions in both absolute error and mean squared error, along with attaining the highest R2 value (0.93). …”
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Physical activity attenuates the genetic predisposition to obesity in 20,000 men and women from EPIC-Norfolk prospective population study. by Shengxu Li, Jing Hua Zhao, Jian'an Luan, Ulf Ekelund, Robert N Luben, Kay-Tee Khaw, Nicholas J Wareham, Ruth J F Loos

“…Each additional BMI-increasing allele was associated with 0.154 (standard error [SE] 0.012) kg/m(2) (p = 6.73 x 10(-37)) increase in BMI (equivalent to 445 g in body weight for a person 1.70 m tall). …”
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Antihypertensive Drug Recommendations for Reducing Arterial Stiffness in Patients With Hypertension: Machine Learning–Based Multicohort (RIGIPREV) Study by Iván Cavero-Redondo, Arturo Martinez-Rodrigo, Alicia Saz-Lara, Nerea Moreno-Herraiz, Veronica Casado-Vicente, Leticia Gomez-Sanchez, Luis Garcia-Ortiz, Manuel A Gomez-Marcos

“…A multioutput regressor using 6 random forest models was used to predict the impact of each antihypertensive class on PWV reduction. Model performance was evaluated using the coefficient of determination (R2) and mean squared error. …”
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Editorial – An overview on the “crisis” of testimonial evidence as a judicial decision making tool, between ECHR and Italian Criminal Proceeding: by Pier Paolo Paulesu

“…Science can in fact constitute a false ally for the judge, dangerously channeling the process towards judicial error. The matter is well known. Criminal justice now draws heavily on the results of science, but has to deal with its overt fallibility. …”
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Ocean Surface Wind Field Retrieval Simultaneously Using SAR Backscatter and Doppler Shift Measurements by Yulei Xu, Kangyu Zhang, Liwei Jing, Biao Zhang, Shengren Fan, He Fang

“…The most notable bias reduction was observed at wind speeds exceeding 10 m/s. …”
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Accelerating compound flood risk assessments through active learning: A case study of Charleston County (USA) by L. Terlinden-Ruhl, L. Terlinden-Ruhl, A. Couasnon, A. Couasnon, D. Eilander, D. Eilander, G. G. Hendrickx, P. Mares-Nasarre, J. A. Á. Antolínez

“…The proposed framework decreased the overall computational time by a factor of 4 and decreased the root mean square error in damages by a factor of 8. With a reduction in overall computational time and errors, additional stochastic variables such as the drivers' duration and time lag were included in the compound flood risk assessment. …”
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Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification by Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu

“…We found that 1) human-annotated label noise exhibits significant class and instance dependence; 2) an additional 1% of human-annotated label noise in training data leads to a 0.5% reduction in the overall accuracy of ConvNets classification; and 3) the error pattern of ConvNet predictions was strongly correlated with that of participant's labels. …”
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Study of Influence of Various Methods of Intraoperative Keratoprotection in Phacoemulsification of Senile Cataract on Morphological and Functional State of Ocular Surface Structure... by S. V. Tonkonogiy, О. V. Kolenko, A. V. Vasiliev

“…The developed method for predicting iatrogenic DES in patients after PE in SC is highly informative, because the number of patients in the 1st group with DES was within the expected range of error.…”
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Volumetric evolution of supraglacial lakes in southwestern Greenland using ICESat-2 and Sentinel-2 by T. Feng, T. Feng, X. Ma, X. Ma, X. Liu, X. Liu, X. Liu

“…The accuracy of depth inversion based on the MLP model surpasses traditional empirical formula methods, achieving a mean absolute error of 0.42 m. The trained MLP model is then used to estimate the depth over the entire lake areas. …”
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Research on Active Disturbance Rejection Control of Rigid–Flexible Coupled Constant Force Actuator by Chuanxing Jiang, Zhijun Yang, Jun Zheng, Bangshang Fu, Youdun Bai

“…Experimental results indicate enhanced performance compared to PID control: under dynamic disturbances, force deviations are limited to <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>±</mo><mn>0.2</mn><mo> </mo><mi mathvariant="normal">N</mi></mrow></semantics></math></inline-formula> with a 98.5% reduction in mean absolute error, a 96.3% increase in settling speed, and 99% suppression of oscillations. …”
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Addressing ORPD problem in a standard IEEE power network accompanied with RESs and FACTs appliances by COMMKE under volatile load scenarios by Susanta Dutta, Tushnik Sarkar, Chandan Paul, Sabbir Reza Tarafdar, Provas Kumar Roy, Ghanshyam G. Tejani, Seyed Jalaleddin Mousavirad

“…These are, both alone and together, a drop in aggregated voltage deviation (AVD) over buses and a reduction in active power loss (APL). Twenty one cases in all have been looked at using three test frameworks. …”
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ELECTROMYOGRAPHY INDICATORS STUDIES OF MASTICATORY MUSCLES IN PREGNANT WOMEN WITH PARTIAL DEFECTS OF DENTITION BY ROC TA AND ROC MM INDEXES by V. Pekhnyo, K. Hulavska

“…The results of the research were divided on the time interval(1-trimester, 2nd trimester, 3rd trimester and postpartum), the results obtained were classified with an error of research. In group A we observed a reduction in ROC TA less than 95% from 36.7% (1st Trimester) to 35.2%(postpartum period), fluctuations in the indicator ROC TA from 95% to 105% was within 1%(7,5%-6,5%), the index of ROC TA більше105% grew from 55.8 per cent to 58.3%. …”
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Nurses’ perception of patient safety culture using the Hospital Survey on Patient Safety Culture tool and its association with nursing-patient outcomes: a systematic review in Iran... by Alireza Hajizadeh, Behrouz Amini Kordkandi, Sevda Sadeghpour, Milad Khodavandi, Jalal Saeidpour, Edris Kakemam

“…Finally, PSC among nurses was significantly associated with a reduction in second-victim experience (β = − 0.39) and burnout (β = − 0.24). …”
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Comparison of Molnupiravir Exposure‐Response Relationships for Virology Response and Mechanism of Action Biomarkers With Clinical Outcomes in Treatment of COVID‐19 by Akshita Chawla, Ruthie Birger, Brian M. Maas, Youfang Cao, Hong Wan, Julie Strizki, Arthur Fridman, Amanda Paschke, Carisa deAnda, Wei Gao, Matthew L. Rizk, Wendy Painter, Wayne Holman, Susanne Sardella, George Painter, Julie A. Stone

“…NHC incorporation in the SARS‐CoV‐2 RNA strand causes an accumulation of deleterious errors in the genome, resulting in reduced viral infectivity and replication. …”
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Real‐Time Self‐Optimization of Quantum Dot Laser Emissions During Machine Learning‐Assisted Epitaxy by Chao Shen, Wenkang Zhan, Shujie Pan, Hongyue Hao, Ning Zhuo, Kaiyao Xin, Hui Cong, Chi Xu, Bo Xu, Tien Khee Ng, Siming Chen, Chunlai Xue, Zhanguo Wang, Chao Zhao

“…Abstract Traditional methods for optimizing light source emissions rely on a time‐consuming trial‐and‐error approach. While in situ optimization of light source gain media emission during growth is ideal, it has yet to be realized. …”
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Improving the Incident Management Process Based on a Use Case Approach by A. A. Mikryukov, A. V. Kuular

“…This method does not require large computational costs and provides the required degree of reliability (error) of the decision. The application of the nearest neighbor method is based on calculating the degree of proximity of the current situation to the use cases stored in the base of use cases.Results. …”
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Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…When SOH is used to characterize battery life, significant errors will be introduced. In contrast, RUL will irreversibly decrease as the service time increases, which can provide a more reliable criterion for evaluation. …”
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Advancing Evapotranspiration Modeling With Optimized Soil and Canopy Resistance Combinations by Jinfeng Zhao, Shikun Sun, Yali Yin, Yihe Tang, Chong Li, Yongshan Liang, Yubao Wang, Alexander Winkler, Shijie Jiang

“…The performance of best‐performing but unexplored combinations (S2‐C1, S2‐C2, S2‐C5) is consistent with PML‐V2, GLEAM4, and underlying water use efficiency model, explaining 56% of the variation in daily ET and achieving an root mean square error as low as 1.02 mm day−1. However, these models show reduced accuracy in arid zones, where prolonged water stress led to a 38% reduction in R2. …”
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Framingham Risk Score Prediction at 12 Months in the STANDFIRM Randomized Control Trial by Thanh G. Phan, Velandai K. Srikanth, Dominique A. Cadilhac, Mark Nelson, Joosup Kim, Muideen T. Olaiya, Sharyn M. Fitzgerald, Christopher Bladin, Richard Gerraty, Henry Ma, Amanda G. Thrift

“…We determine baseline characteristics that predict reduction in FRS at 12 months and whether future FRS is predetermined at baseline. …”
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Generating synthetic brain PET images of synaptic density based on MR T1 images using deep learning by Xinyuan Zheng, Patrick Worhunsky, Qiong Liu, Xueqi Guo, Xiongchao Chen, Heng Sun, Jiazhen Zhang, Takuya Toyonaga, Adam P. Mecca, Ryan S. O’Dell, Christopher H. van Dyck, Gustavo A. Angarita, Kelly Cosgrove, Deepak D’Souza, David Matuskey, Irina Esterlis, Richard E. Carson, Rajiv Radhakrishnan, Chi Liu

“…The model also demonstrates a capacity for noise reduction, producing images of higher quality compared to the low-dose scans. …”
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