A novel approach of generating pseudo revisited soil sample data based on environmental similarity for space-time soil organic carbon modelling by Wenkai Cui, Lin Yang, Lei Zhang, Chenconghai Yang, Chenxu Zhu, Chenghu Zhou

“…This study proposes a novel approach to generate pseudo revisited samples using environmental similarity, addressing the lack of revisited samples. …”
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The research on enhancing LA estimation accuracy across domains for small sample data based on data augmentation and data transfer integration optimization system by Ai-Dong Wang, Rui-Jie Li, Xiang-Qian Feng, Zi-Qiu Li, Wei-Yuan Hong, Hua-Xing Wu, Dan-Ying Wang, Song Chen

“…Fourteen morphological feature parameters are constructed, and the leaf area values are measured through destructive sampling, together forming the dataset. A comprehensive comparison of six algorithms (linear regression, support vector regression, random forest, XGBoost, CatBoost, and K-nearest neighbors) is conducted, assessing their performance under a combined strategy of data augmentation (noise injection, generative adversarial networks, Gaussian mixture model, variational autoencoders) and transfer learning (random, clustering, and hierarchical parameter transfer). …”
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A Controlled Study on Machine Learning Applications to Predict Dry Fabric Color from Wet Samples: Influences of Dye Concentration and Squeeze Pressure by Warren J. Jasper, Samuel M. Jasper

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Validation of the Multidimensional Scale of Perceived Social Support (MSPSS) in a Representative Sample of Adolescents: Links with Well-being, Mental Health, and Suicidal Behavior by David Pina, Alicia Pérez-Albéniz, Adriana Díez-Gómez, Alfonso Pérez-Esteban, Eduardo Fonseca-Pedrero

“…The main purpose of the present study was to validate the scores of the MSPSS in a large sample of non-clinical adolescents. Method: The sample consisted of 2,235 compulsory secondary education students in Spain (Mage = 14.49, SDage = 1.76, age range 12-18 years, 52% female) obtained by stratified random sampling. …”
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A new approach for monitoring spatial and temporal changes in forest types in subtropical regions with sample migration and multi-source remote sensing data by Pengfei Zheng, Dongyang Han, Jiang Liu, Bin Xu, Panfei Fang, Shaodong Huang, Wendou Liu, Shaozhi Chen

“…We propose a novel workflow for processing ground survey data to generate stable reference samples, which are then used with a transfer learning approach to construct a multi-year sample library. …”
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Evaluating the Diagnostic Potential of Biomarker Panels in Breast Cancer and Prostate Adenocarcinoma by Kldiashvili Ekaterina, Iordanishvili Saba, Adamia Sophia, Abiatari Ivane, Zarnadze Maia

“…Materials and Methods We analyzed blood samples from 162 participants (73 cancer patients: 51 with breast cancer and 22 with prostate adenocarcinoma; 89 healthy controls). …”
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Investigation and application of data balancing and combined discriminant model in rock burst severity prediction by Shaohong Yan, Runze Liu, Yanbo Zhang, Xulong Yao, Yueqi Yang, Qi Wang, Bin Guo, Shuai Wang

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Intra-tumoral Heterogeneity of KRAS and BRAF Mutation Status in Patients with Advanced Colorectal Cancer (aCRC) and Cost-Effectiveness of Multiple Sample Testing by Susan D. Richman, Philip Chambers, Matthew T. Seymour, Catherine Daly, Sophie Grant, Gemma Hemmings, Philip Quirke

“…In patients displaying heterogeneity, the relevant KRAS or BRAF mutation was also identified in ‘DNA cocktail’ samples when including DNA from mutant and wild-type blocks. …”
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Population attributable fractions of adolescent health and well-being outcomes associated with adverse childhood experiences in a provincially representative sample in Ontario, Can... by Janique Fortier, Tamara L. Taillieu, Ashley Stewart-Tufescu, Samantha Salmon, Andrea Gonzalez, Melissa Kimber, Harriet L. MacMillan, Tracie O. Afifi

“…Background: It is well known that Adverse Childhood Experiences (ACEs) are associated with poor health and well-being outcomes among adult samples. However, there are notable gaps in examining these relationships among youth. …”
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Scent dogs identify SARS-CoV-2-infections in respiratory samples from experimentally infected ferrets and hamsters—a pilot study by Claudia Schulz, Friederike Twele, Sebastian Meller, Nele A. ten Hagen, Veronika Pilchová, Veronika Pilchová, Katrin Wirz, Katrin Wirz, Sabrina Clever, Sabrina Clever, Christian Meyer zu Natrup, Christian Meyer zu Natrup, Asisa Volz, Asisa Volz, Maren von Köckritz-Blickwede, Maren von Köckritz-Blickwede, Holger A. Volk

“…DDTS allows a fast, blinded, randomized, and automated sample presentation without trainer interference. …”
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Method for Selecting Pulsed Signals by Their Duration in Fading Channels by M. V. Buhaiov, S. V. Zakirov

“…In sophisticated electronic environment, it is also may be random interference in signal processing channel, which leads to the occurrence of false pulses with random durations. …”
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Incidence‐data‐based species richness estimation via a Beta‐Binomial model by Chun‐Huo Chiu

“…For species individual with spatial aggregation, individual‐unit‐based random sampling scheme is difficult to implement, and quadrat‐unit‐based sampling scheme is more available to implement and more likely to fit the model assumption of random sampling. …”
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A general-purpose code for correlated sampling using batch statistics with MCNP6 for fixed-source problems [version 1; peer review: 2 approved] by Jeffrey A. Favorite

“…The cases are correlated if they are run with the same random number sequence. Equations implemented Equations used to apply correlated sampling to the difference of two tallies are summarized from previous work. …”
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Transformative advances in veterinary laboratory practices: Evaluating the impact of preliminary training in Khyber Pakhtunkhwa and Balochistan provinces of Pakistan by Javed Khan, Asghar Ali, Shaukat Khan, Murad Khan, Saima Mohsin, Cecelia Madsen

“…Hands-on training, essential laboratory equipment, and a comprehensive training kit, including personal protective equipment (PPE), were provided to 13 laboratories within the Livestock and Dairy Development Departments of Khyber Pakhtunkhwa and Balochistan. A random sample of 152 individuals from a cohort of 314 trained personnel was selected to assess procedural changes post-training, supplemented by Training Needs Assessments (TNAs) and follow-up visits. …”
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Time-series urban green space mapping and analysis through automatic sample generation and seasonal consistency modification on Sentinel-2 data: A case study of Shanghai, China by Zhuoqun Chai, Keyao Wen, Hao Fu, Mengxi Liu, Qian Shi

“…Specifically, temporal training samples were selected automatically through anomaly detection and probability filtering. …”
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Dual-platform integration of HPTLC and firefly algorithm-optimized chemometrics with hammersley sequence sampling for simultaneous quantification of bisoprolol, amlodipine, and mut... by Lateefa A. Al-Khateeb, Ahmed Emad F. Abbas, Mohamed R. Elghobashy, Nisreen F. Abo Talib, Ibrahim A. Naguib, Mohammed Alqarni, Michael K. Halim

“…The FA-PLS model incorporated a novel Hammersley Sequence Sampling (HSS) strategy for validation set construction, ensuring uniform concentration space coverage and eliminating sampling bias inherent in conventional random approaches. …”
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Convergence of Limiting Cases of Continuous-Time, Discrete-Space Jump Processes to Diffusion Processes for Bayesian Inference by Aaron Lanterman

“…Jump-diffusion algorithms are applied to sampling from Bayesian posterior distributions. We consider a class of random sampling algorithms based on continuous-time jump processes. …”
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AC contactor fault recognition based on ERF and BO-SVC by LIU Shuxin, QI Xinzhi, LYU Xianfeng

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Random Variables Aren’t Random by Paul W. Vos

“…This paper examines the foundational concept of random variables in probability theory and statistical inference, demonstrating that their mathematical definition requires no reference to randomization or hypothetical repeated sampling. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…The unbalanced distribution of “Severity” was improved through under-sampling and over-sampling techniques. Firstly, we adopted a multi-stage fusion strategy. …”
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