Genetic diversity and verification of plant material compliance of Cocoa (Theobroma cacao L.) in the Barombi-Kang Regional variety trial. by Nto Marie Claire Eyango, Olivier Sounigo, Olivier Fouet, Honoré Tekeu, François Pierre Djocgoué, Mousseni Ives Bruno Efombagn, Claire Lanaud

“…Significantly, an 18.55% labeling error rate was identified, underscoring prevalent issues in germplasm management that could impact the efficacy of breeding programs. …”
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An Approach to Rapid Determination of Tween-80 for the Quality Control of Traditional Chinese Medicine Injection by Partial Least Squares Regression in Near-Infrared Spectral Model... by Jin-Fang Ma, Tian-Ling Chen, Xiang-Dong Zhang, Xue Xiao, Fa-Huan Ge

“…The standard error of cross validation (SECV), standard deviation of calibration (SEC), and the determination coefficient (R) of the established model were 0.0561, 0.0526, and 0.9986, respectively. …”
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Whisper Automatic Speech Recognition and GPT Large Language Models as Best Practice for Assessing Communication Progress in Autism Spectrum Disorder by Naela Fauzul Muna, Mukhammad Andri Setiawan

“…Whisper achieved a low Word Error Rate (WER) for mild autism (average 5%) and a higher rate for moderate autism (average 23%). …”
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Reliability assessment of two production lines using joint progressively type-II censored XLindley samples by I. Elbatal, Ahmed Elshahhat, H. E. Semary, Mazen Nassar

“…Furthermore, the applicability of the proposed methodology is demonstrated through the analysis of two real-world data sets, underscoring its practical utility within the field of reliability. …”
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Machine Learning for Dynamic Pressure Coefficient Prediction in Vertical Water Jets by Amin Salemnia, Seyedehmaryam Hosseini Boldaji, Vida Atashi, Manoochehr Fathi-Moghadam

“…The XGBoost model outperformed others, achieving an R-squared of 0.953 and a Root Mean Squared Error (RMSE) of 0.191. Residual analysis validated its better performance, demonstrating that it delivered the most accurate predictions with minimal bias. …”
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Rancang Bangun Smart Steamer untuk Monitoring Alat Sterilisasi Baglog Jamur Berbasis Internet of Things (IoT) by Anri Kurniawan, M Muhibbudin, Dede Setiadi

“…The research methodology consists of stages including the mushroom baglog steamer design, temperature monitoring system design, error testing (%), temperature increase testing, data collection, and data analysis. …”
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Development and Validation of an Agricultural Safety and Health Literacy Tool by Lee GY, Park KS

“…As a result of confirmatory factor analysis, the goodness-of-fit index (GFI) was shown as GFI=0.851, adjusted GFI=0.816, comparative fit index=0.901, normed fit index=0.835, root mean square error of approximation=0.071, and χ2/df=2.2. …”
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Association between dietary inflammatory index and visual impairment among adults in the NHANES 2005–2008 by Yudie Hu, Jiang Zheng, Lun He, Jinhui Hu, Zheng Yang

“…This study aimed to investigate the relationship between the DII and non-refractive visual impairment among US populations. A cross-sectional analysis was conducted using data from the National Health and Nutrition Examination Survey (NHANES) 2005–2008, including dietary information and visual impairment assessment. …”
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Development of Fast Analytical Method for the Detection and Quantification of Honey Adulteration Using Vibrational Spectroscopy and Chemometrics Tools by Omar Elhamdaoui, Aimen El Orche, Amine Cheikh, Brahim Mojemmi, Rachid Nejjari, Mustapha Bouatia

“…Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used for qualitative analysis to discriminate between adulterated and nonadulterated honey. …”
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Estimating and Downscaling ESA-CCI Soil Moisture Using Multi-Source Remote Sensing Images and Stacking-Based Ensemble Learning Algorithms in the Shandian River Basin, China by Liguo Wang, Ya Gao

“…We compared the predicted SM and ESA-CCI SM; it is evident that the predicted results exhibit a strong correlation with ESA-CCI SM, with a maximum Pearson correlation coefficient (PCC) value of 0.979 and a minimum value of 0.629. The Mean Absolute Error (MAE) values range from 0.002 to 0.005 m³/m³, and the Root Mean Square Error (RMSE) ranges from 0.003 to 0.006 m³/m³. …”
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Decision-making method for residual support force of hydraulic supports during pressurized moving under fragmented roof conditions in ultra-thin coal seams by ZHANG Chuanwei, ZHANG Gangqiang, LU Zhengxiong, LI Linyue, HE Zhengwei, GONG Lingxiao, HUANG Junfeng

“…The IDBO algorithm was further employed to optimize the hyperparameters of the DHKELM model, forming the IDBO-DHKELM model. Using field-measured data from hydraulic supports during pressurized moving in a fully mechanized ultra-thin coal seam mining face, key influencing factors of residual support force—including support number, support force before pressurized moving, pushing cylinder inlet pressure, and pushing cylinder stroke variation speed—were identified through visualization and correlation analysis. …”
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Straightness control method of hydraulic support group pushing system based on neural network compensation by Yunfei WANG, Jiyun ZHAO, He ZHANG, Hao WANG, Yang ZHANG

“…The research results provide an idea for the dynamic analysis and straightness control of hydraulic support pushing system.…”
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Bias in Discontinuous Elevational Transects for Tracking Species Range Shifts by Shixuan Li, Jiannan Yao, Yang Lin, Siyu Wu, Zhongjie Yang, Chao Jin, Yuhan Zhang, Zhen Wang, Jinliang Liu, Guochun Shen, Mingjian Yu

“…The results were striking: the widely used settings for discontinuous transects failed to detect 7.2% of species, inaccurately estimated shift distances for 78% of species, and produced an overall error rate of 86%. Wider quadrat spacing increased these error rates, while longer survey intervals generally reduced them. …”
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Empirical modeling of tropospheric delays with uncertainty by J. Wang, J. Wang, J. Wang, J. Chen, J. Chen, J. Chen, Y. Zhang

“…<p>Accurate modeling of tropospheric delay is important for high-precision data analysis of space geodetic techniques, such as the Global Navigation Satellite System (GNSS). …”
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Study on Discrete Null-Field Equation Methods for Bounded Simply Connected Domains: Better Locations of Source Nodes by Li-Ping Zhang, Zi-Cai Li, Hung-Tsai Huang, Ming-Gong Lee, Alexander L. Kazakov

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Understanding the determinants of domestic food availability: Evidence from a Caribbean Small Island Developing State by David Forgenie, Meera Mahase-Forgenie, Sunshine De Caires, Wendy Ann P. Isaac, Karambir Singh Dhayal

“…Using an Autoregressive Distributed Lag (ARDL) model with an Error-correction Mechanism (ECM) and annual data spanning 1983 to2022, this study investigates both short- and long-run dynamics. …”
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Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

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Comparative performance of PROMIS Sleep Disturbance computerized adaptive testing algorithms and static short form in postmenopausal women by Andrew Trigg, Claudia Haberland, Huda Shalhoub, Christoph Gerlinger, Christian Seitz

“…Methods This is a secondary analysis of data collected for the original psychometric testing of the PROMIS Sleep Disturbance item bank, in a sub-sample of women aged ≥55. …”
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Forecasting invasive mosquito abundance in the Basque Country, Spain using machine learning techniques by Vanessa Steindorf, Hamna Mariyam K. B., Nico Stollenwerk, Aitor Cevidanes, Jesús F. Barandika, Patricia Vazquez, Ana L. García-Pérez, Maíra Aguiar

“…Forecasting models, including random forest (RF) and seasonal autoregressive integrated moving average (SARIMAX), were evaluated using root mean squared error (RMSE) and mean absolute error (MAE) metrics. …”
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Time in range prediction using the experimental mobile application in type 1 diabetes by A. N. Rusanov, T. I. Rodionova

“…The current problem is the assessment and prediction of TIR for patients who use self-monitoring of blood glucose (SМBG) corresponding low CGM availability for the majority of diabetic patients.AIM: To develop a predictive model of TIR for patients with T1DM based on data of the experimental mobile application.MATERIALS AND METHODS: An analysis of 1253 professional CGM profiles of patients with T1DM was performed. …”
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