First performance evaluation of easyPET.3D, a high-resolution and cost-effective benchtop preclinical PET scanner by Fabiana M. Ribeiro, Pedro M. C. C. Encarnação, Ana L. M. Silva, Pedro M. M. Correia, Afonso X. Pinto, Regina G. Oliveira, José Sereno, Mariana Lapo Pais, Antero Abrunhosa, Ismael F. Castro, Ana C. Santos, João F. C. A. Veloso

“…Conclusion EasyPET.3D geometry favours the reduction of parallax error, despite its low sensitivity. …”
Get full text

Evaluating the accuracy of nine canopy resistance models in estimating winter wheat evapotranspiration using the Penman–Monteith equation by Yingnan Wu, Qiaozhen Li, Xiuli Zhong, Xiaoying Liu

“…The results showed that the FA, KP, and ST models performed better in estimating daily ET with original parameters, achieving a root mean square error (RMSE) of 1.07–1.16 mm d−1 and a mean bias error (MBE) of −0.59–0.02 mm d−1. …”
Get full text

Investigating the performance of high-resolution subseasonal precipitation forecasts in support of food insecurity early warning by William Turner, Shraddhanand Shukla, Greg Husak, Chris Funk, Charles Jones, Kathy Baylis

“…Our results show that SubC forecasts provide a 35%–55% reduction in EOS WRSI root mean squared error in 60% of the east African agropastoral areas during the short rains , with the highest accuracy being in areas that are most vulnerable to inconsistent PPT timing and quantities. …”
Get full text

A new-generation internal tide model based on 30 years of satellite sea surface height measurements: multiwave decomposition and isolated beams by Z. Zhao, Z. Zhao

“…ZHAO30yr is available at <a href="https://doi.org/10.6084/m9.figshare.28078523">https://doi.org/10.6084/m9.figshare.28078523</a> <span class="cit" id="xref_paren.1">(<a href="#bib1.bibx84">Zhao</a>, <a href="#bib1.bibx84">2024</a><a href="#bib1.bibx84">b</a>)</span>. Model errors are available at <a href="https://doi.org/10.6084/m9.figshare.28559978.v3">https://doi.org/10.6084/m9.figshare.28559978.v3</a> <span class="cit" id="xref_paren.2">(<a href="#bib1.bibx85">Zhao</a>, <a href="#bib1.bibx85">2025</a>)</span>.…”
Get full text

Adaptive Voxel-Division Method of GNSS Water Vapor Tomography and Its Application in Data Assimilation by Yongjie Ma, Qingzhi Zhao, Duoduo Jiang, Wanqiang Yao, Yibin Yao, Jinfang Yin, Hongwu Guo, Yuan Zhai, Ying Xu, Ruikun Wang, Qingfang Chen, Jingyu Zhang

“…The average improvement rate of the root-mean-square error (RMSE) in the water vapor profile ranges from 10.6% to 48.7%, while that in the integrated water vapor is 19.0&#x2013;42.9% . …”
Get full text

medAL-suite: A software solution for creating and deploying complex clinical decision support algorithms by Ludovico Gennaro Cobuccio, Vincent Faivre, Rainer Tan, Alan Vonlanthen, Fenella Beynon, Emmanuel Barchichat, Alain Fresco, Quentin Girard, Sinan Ucak, Sylvain Schaufelberger, Ibrahim Evans Mtebene, Peter Agrea, Emmanuel Kalisa, Gillian A. Levine, Martin Norris, Sabine Renggli, Alix Miauton, Lisa Cleveley, Kristina Keitel, Julien Thabard, Valérie D’Acremont, Alexandra V. Kulinkina

“…However, the process of translating paper-based guidelines into electronic algorithmic formats is often complex, inefficient, expensive, and error-prone due to reliance on advanced software development skills and clinical knowledge. …”
Get full text

Assessing the impact of multi-source environmental variables on soil organic carbon in different land use types of China using an interpretable high-precision machine learning meth... by Feng Wang, Ruilin Liang, Shuyue Li, Meiyan Xiang, Weihao Yang, Miao Lu, Yingqiang Song

“…To explore the impact of environmental factors on soil organic carbon (SOC) with machine learning (ML) model is of great significance for mitigating climate change and soil carbon sequestration and emission reduction. However, the traditional ML model is limited by the hyperparameter adjustment of artificially trial-and-error experimentation and the inexplicability of fitting process, and the precision and performance of ML model cannot be fully utilized. …”
Get full text

Lateral Bearing Characteristics of Bucket Foundation Breakwaters in Soft Soil of Port Areas by WANG Shuai, ZHANG Jia-lin, HU Shao-wei, YOU Jian-hua, YANG Yu-ming

“…When the displacement reached 150.3 mm, the maximum displacement of the soil on the rear side was 54.2 mm. (3) The ultimate bearing capacity obtained from the model test was 14.26 kN, while the finite element analysis calculated 15.07 kN, with a relative error of 5.68%. The deformation process of bucket foundation breakwaters could be divided into three stages: quasi-elastic stage, plastic stage, and failure stage. …”
Get full text

Myopia control efficacy of spectacle lenses with highly aspherical lenslets: results of a 5-year follow-up study by Xue Li, Yingying Huang, Chenyao Liu, Xindan Chang, Zaifeng Cui, Qiulin Yang, Björn Drobe, Mark A. Bullimore, Hao Chen, Jinhua Bao

“…Five-year myopia progression [mean ± standard error (SE)] in the HAL group was − 1.27 ± 0.14 D. …”
Get full text

Associations of maternal quitting, reducing, and continuing smoking during pregnancy with longitudinal fetal growth: Findings from Mendelian randomization and parental negative con... by Judith S Brand, Romy Gaillard, Jane West, Rosemary R C McEachan, John Wright, Ellis Voerman, Janine F Felix, Kate Tilling, Deborah A Lawlor

“…Study limitations include measurement error due to maternal self-report of smoking and the modest sample size for MR analyses resulting in unconfounded estimates being less precise. …”
Get full text

Analysis of factors influencing clinical pregnancy rates in frozen-thawed embryo transfer cycles by Junqiang Wang, Zexing Yang, Ying Chen, Ying Chen, Fengchen Gao, Wenxiu Zhao, Shuxuan Cao, Yixi Li, Limei He, Limei He

“…The top-ranked predictors with the lowest average out-of-bag (OOB) error rates were incorporated into a multivariate logistic regression model to determine independent predictors of clinical pregnancy in FET cycles.ResultsThe overall clinical pregnancy rate (CPR) was 46.08%. …”
Get full text

Projection of sea ice conditions in the Canadian Arctic Archipelago based on CMIP6 assessments by Yu-Fei Liang, Yu Zhang, Hai-Long Guo, Chang-Sheng Chen, Wei-Zeng Shao, Yi Zhou, De-Shuai Wang

“…The assessment of SIC indicates that CESM2, GFDL-CM4, IPSL-CM6A-LR, and UKESM1-0-LL exhibit better performance, with a relatively low bias (less than 7%), a root mean square error (RMSE) below 22%, and a relatively high correlation coefficient (CC) exceeding 0.75. …”
Get full text

Shared decision-making for pediatric acute otitis media in the United States: a randomized emergency department trial by Jana L. Anderson, Lucas Oliveira J. E. Silva, Erik P. Hess, Derek E. Vanmeter, Aidan Mullan, Juan P. Brito, Ian G. Hargraves, Fernanda Bellolio

“…Although no significant reduction in antibiotic prescribing was observed, this may be due to the study’s limited sample size, which increases the risk of Type II error. …”
Get full text

A novel method for soil organic carbon prediction using integrated ‘ground-air-space’ multimodal remote sensing data by Yilin Bao, Xiangtian Meng, Huanjun Liu, Mengyuan Xu, Mingchang Wang

“…This model improves coefficient of determination (R2) and ratio of performance to interquartile distance (RPIQ) by 0.09 and 0.28, respectively, and reduces root mean square error (RMSE) by 0.52 g kg−1 compared to Model (ii). …”
Get full text

International Natural Uranium Price Prediction Based on TF-CNN-BiLSTM Model by YANG Jingzhe, XUE Xiaogang

“…The study meticulously constructed and trained the TF-CNN-BiLSTM model using TensorFlow with the Adam optimizer and mean squared error loss function. The training process was optimized with learning rate reduction and early stopping callbacks to prevent overfitting. …”

Sex-Specific Association of Ambient Temperature With Urine Biomarkers in Southwest Coastal Bangladesh by Hoimonty Mazumder, Momenul Haque Mondol, Mahbubur Rahman, Rizwana Khan, Solaiman Doza, Leanne Unicomb, Farjana Jahan, Ayesha Mukhopadhyay, Konstantinos C. Makris, Alberto Caban-Martinez, Romaina Iqbal, Faruk Ahmed, Lota Creencia, Mohammad Shamsudduha, Fawaz Mzayek, Chunrong Jia, Hongmei Zhang, Anwar Musah, Lora E. Fleming, Xichen Mou, Csaba P. Kovesdy, Matthew O. Gribble, Abu Mohd Naser

Get full text

A peer-support lifestyle intervention for preventing type 2 diabetes in India: A cluster-randomized controlled trial of the Kerala Diabetes Prevention Program. by Kavumpurathu R Thankappan, Thirunavukkarasu Sathish, Robyn J Tapp, Jonathan E Shaw, Mojtaba Lotfaliany, Rory Wolfe, Pilvikki Absetz, Elezebeth Mathews, Zahra Aziz, Emily D Williams, Edwin B Fisher, Paul Z Zimmet, Ajay Mahal, Sajitha Balachandran, Fabrizio D'Esposito, Priyanka Sajeev, Emma Thomas, Brian Oldenburg

“…We did not adjust for multiple comparisons, which may have increased the overall type I error rate.<h4>Conclusions</h4>A low-cost community-based peer-support lifestyle intervention resulted in a nonsignificant reduction in diabetes incidence in this high-risk population at 24 months. …”
Get full text

Establishing a monitoring system for black rhinos in the Solio Game Reserve, central Kenya by Felix Patton, Petra Campbell, Edward Parfet

“…At the end of the first year, using identification photographs and with nearly 6000 sightings, 87 rhinos were identified but with the likelihood that there were some duplication errors and some rhinos not yet found and photographed. …”
Get full text

Diffusion models enable zero-shot pose estimation for lower-limb prosthetic users. by Tianxun Zhou, Muhammad Nur Shahril Iskandar, Keng-Hwee Chiam

“…The zero-shot approach achieved substantial reductions in keypoint coordinate errors of 37% for transtibial and 76% for transfemoral prosthetic limbs compared to OpenPose on the original videos. …”
Get full text

Towards enhanced photovoltaic Modeling: New single diode Model variants with nonlinear ideality factor dependence by Martin Ćalasan, Snežana Vujošević, Gojko Krunić

“…Experimental validation was conducted on a standard solar cell (RTC France) and three commercial modules (MSX60, PWP201, KC200GT), demonstrating significant reductions in modeling errors (RMSE) compared to classical SDM, DDM, and TDM approaches. …”
Get full text