Evidence-based medicine: 5 steps to navigate uncertainty by Rafael Martín-Masot, Carlos Ochoa Sangrador, Jaime Javier Cuervo Valdés, Carolina Blanco Rodríguez, Paz González Rodríguez, Javier González de Dios, M. Salomé Albi Rodríguez, Pilar Aizpurua Galdeano, María Aparicio Rodrigo, Nieves Balado Insunza, Albert Balaguer Santamaría, Fernando Carvajal Encina, Eduardo Cuestas Montañes, M. Jesús Esparza Olcina, Sergio Flores Villar, Garazi Frailea Astorga, M. Victoria Martínez Rubio, Manuel Molina Arias, Eduardo Ortega Páez, Begoña Pérez-Moneo Agapito, M. José Rivero Martín, Álvaro Gimeno Díaz de Atauri, Laura Cabrera Morente, Elena Pérez González, Juan Ruiz-Canela Cáceres

“…Este proceso ayuda a evitar el error de aceptar conclusiones sin cuestionarlas. …”
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3D-GloBFP: the first global three-dimensional building footprint dataset by Y. Che, X. Li, X. Liu, X. Liu, Y. Wang, W. Liao, X. Zheng, X. Zhang, X. Xu, Q. Shi, J. Zhu, H. Zhang, H. Zhang, H. Yuan, H. Yuan, Y. Dai, Y. Dai

“…Such datasets are indispensable for a variety of applications, including climate modeling, energy consumption analysis, and socioeconomic activities. …”
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Validación de una encuesta de opinión sobre la eficacia de la simulación para participantes by Aida Camps-Gómez, Anna González-Fernández, Jennifer Morata-Serrano, Katherina M. Faundez-Inostroza, Carmen Gomar-Sancho, Marina Mateu-Capell

“…Conclusión: la combinación de métodos cualitativos con cuantitativos ha permitido depurar el instrumento y detectar errores de método para reajustar el instrumento sin que afectara a su representatividad. …”
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Evaluating snow depth retrievals from Sentinel-1 volume scattering over NASA SnowEx sites by Z. Hoppinen, Z. Hoppinen, R. T. Palomaki, G. Brencher, D. Dunmire, D. Dunmire, E. Gagliano, A. Marziliano, J. Tarricone, J. Tarricone, H.-P. Marshall

“…Across all sites, we find agreement between the Sentinel-1 snow depth retrievals and the lidar snow depth measurements to be considerably lower than requirements placed for remotely sensed observations of snow depth, with a mean root mean square error (RMSE) of 0.92 m and a mean Pearson correlation coefficient <span class="inline-formula"><i>r</i></span> of 0.46. …”
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Comprehensive Evaluation of Operation Safety of Earth-rock Dams Based on Weight Optimization-cloud Model by ZHANG Jianwei, WU Weitao, HOU Ge, HUANG Jinlin, WANG Bingpeng, LIU Hongze, HU Zixu

“…Taking 95% engineering accuracy as the measurement standard, it was found that among these 20 random experiments, three experiments failed to satisfy the condition when the cloud droplet number was 2 000, and all experiments met the requirement when the cloud droplet number was 5 000. Since the error did not change significantly when the number of cloud drops continued to increase, 5 000 was taken as the optimal number of cloud drops to balance computational efficiency and accuracy.Results and DiscussionsThe established evaluation model was applied to the earth and rock dam of the Helong Reservoir in Guangdong Province. …”
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Development and validation of scales measuring self-efficacy and behavioral capability in managing common medical emergencies in dental clinics by Yasmine N. Alawaji, Hussam M. Alqahtani, Abdulmohsen Alfadley, Aram Alshehri, Ali Aboalela, Sahr H. Altuwaijri, Farraj Albalawi, Sara A. Kalagi, Abdulrhman Alghamdi, Abdullah Alshibani, Meshal Alharbi, Meshary Binhotan, Nesrin A. Alharthy

“…Clinical trial number Not applicable.…”
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Progress in integrated and fiber optics for time-bin based quantum information processing by Nicola Montaut, Agnes George, Monika Monika, Monika Monika, Farzam Nosrati, Farzam Nosrati, Hao Yu, Hao Yu, Stefania Sciara, Benjamin Crockett, Ulf Peschel, Zhiming Wang, Rosario Lo Franco, Mario Chemnitz, Mario Chemnitz, Mario Chemnitz, William J. Munro, William J. Munro, David J. Moss, José Azaña, Roberto Morandotti

“…We also review scalable on-chip schemes for quantum key distribution, demonstrating low quantum bit error rates and compatibility with higher-dimensional quantum communication protocols. …”
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Estimating Stellar Atmospheric Parameters and [α/Fe] for LAMOST O-M-type Stars Using a Spectral Emulator by Jun-Chao Liang, A-Li Luo, Yin-Bi Li, Xiao-Xiao Ma, Shuo Li, Shu-Guo Ma, Hai-Ling Lu, Yun-Jin Zhang, Bing Du, Xiao Kong

“…We observed that the internal error dispersions for T _eff , log g , [Fe/H], and [ α /Fe] across different spectral types lie within the ranges of 15–594 K, 0.03–0.27 dex, 0.02–0.10 dex, and 0.01–0.04 dex, respectively, indicating a good consistency. …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…The convolutional neural network (CNN) model, using variants with genome-wide P values less than E-02 (5516 SNPs), demonstrated the best performance with mean squared error (MSE) equals 0.012 (Accuracy = 0.83; Sensitivity = 0.90; Specificity = 0.75) in the validation dataset, 0.081 in an independent test dataset (Acc = 0.61, Sensitivity = 0.81; Specificity = 0.26). …”
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Global digital elevation model (GDEM) product generation by correcting ASTER GDEM elevation with ICESat-2 altimeter data by B. Li, B. Li, B. Li, B. Li, H. Xie, H. Xie, S. Liu, Z. Ye, Z. Hong, Q. Weng, Q. Weng, Q. Weng, Y. Sun, Q. Xu, X. Tong

“…<p>Advancements in scientific inquiry and practical applications have created a higher demand for the accuracy of global digital elevation models (GDEMs), especially for GDEMs whose main data source is optical imagery. …”
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TanSat-2: a new satellite for mapping solar-induced chlorophyll fluorescence at both red and far-red bands with high spatiotemporal resolution by D. Zhao, D. Zhao, D. Zhao, S. Du, S. Du, C. Zou, C. Zou, C. Zou, L. Tian, M. Fan, M. Fan, Y. Du, Y. Du, Y. Du, L. Liu, L. Liu, L. Liu

“…We then assessed the theoretical accuracy of TanSat-2 based on this spectral simulation dataset, yielding root mean square error (RMSE) values of 0.24 and 0.19 mW m<span class="inline-formula">⁻²</span> sr<span class="inline-formula">⁻¹</span> nm<span class="inline-formula">⁻¹</span> for SIF retrievals at 740 and 685 nm, respectively. …”
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Neurotoxic and Neuroprotective Effects of Psychedelics in a Human Neuroblastoma Cell Model by Andreia Machado Brito da Costa, Ricardo Jorge Dinis-Oliveira, Áurea Madureira-Carvalho, Diana Dias-da-Silva

“…Results were also presented as mean ± standard error of the mean. Statistical comparisons between groups were done using the Kruskal-Wallis test, followed by Dunn’s multiple comparison test. …”
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<i>PI-D^Æ</i>: An Adaptive PID Controller Utilizing a New Adaptive Exponent (Æ) Algorithm to Solve Derivative Term Issues by Juan M. Barrera-Fernández, Juan Pablo Manzo Hernández, Kevin Miramontes Escobedo, Alberto Vázquez-Cervantes, Julio-César Solano-Vargas

“…This adaptive exponent strategy offers a practical and scalable enhancement to classical PID, improving performance and robustness without added complexity, and thus provides a promising control solution for real-world applications in which simplicity, adaptability, and reliability are essential.…”
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La tecnología como complemento al proceso de enseñanza-aprendizaje de la flauta dulce en la etapa de Educación Primaria / Technology as a complement to the teaching-learning proces... by Paloma Bravo-Fuentes

“…Este trabajo propone la inclusión de una herramienta digital como complemento a las carencias que presenta el proceso de enseñanza-aprendizaje del instrumento, así como una propuesta de protocolo de estudio a seguir por parte del alumnado en su avance autónomo.La aplicación informática tiene como objetivos ofrecer la posibilidad de escuchar la pieza musical, mostrar la partitura, grabar las interpretaciones y, finalmente, brindar referencias y datos sobre los errores cometidos, tanto al alumnado como a la figura docente. …”
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The Effect of Gamified Physical Activities on the Quality of Students' Leisure Time (Case Study: Female Secondary School Students in Ardabil City) by aylar sefidgar, Hamed Kheirollahi Meidani, Mehrdad Moharramzadeh

“…All these activities were conducted under strict supervision to prevent external influences and potential errors. The classes were held over two months, with two one-hour sessions each week. 4. …”
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Correction of TRMM 3B43 Monthly Precipitation Data Using Quantile Regression Model in the Urmia Lake Basin by Sima Kazempour Choursi, Mahdi Erfanian, Hirad Abghari, Mirhassan Miryaghoobzadeh, khadijeh Javan

“…Furthermore, the Mean Absolute Error (MAE) significantly decreased after quantile regression correction, demonstrating a closer alignment between TRMM data and observed rainfall. …”
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Identification and analysis of factors affecting the technology transfer process in the power train of automotive (Case study : Iran Khodro Industrial Group) by ٍEbrahim Doostzadeh, Abbas Toloie Ashlaghi, Manochehr Manteghi, Reza Radfard

“…Among the most important applications of this method is data reduction or structure identification. …”
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Development and comparison of empirical models for all-sky downward longwave radiation estimation at the ocean surface using long-term observations by J. Peng, J. Peng, J. Peng, J. Peng, B. Jiang, B. Jiang, H. Liang, H. Liang, S. Li, S. Li, J. Han, J. Han, T. C. Ingalls, T. C. Ingalls, J. Cheng, J. Cheng, Y. Yao, Y. Yao, K. Jia, K. Jia, X. Zhang, X. Zhang

“…The validation results showed that the accuracy of the newly constructed model is superior to that of other models, yielding overall root mean square error (RMSE) values of 13.44 and 8.34 W m<span class="inline-formula">⁻²</span> under clear-sky conditions and 15.64 and 10.27 W m<span class="inline-formula">⁻²</span> under all-sky conditions at hourly and daily scales, respectively. …”
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Surface water quality prediction based on BOA-BiLSTM model(基于BOA-BiLSTM模型的地表水水质预测) by 章佩丽(ZHANG Peili), 赵文雅(ZHAO Wenya), 许旭敏(XU Xumin), 包鑫磊(BAO Xinlei)

“…通过BOA和双向信息传递机制优化LSTM超参数和模型结构，结果显示，用BOA-BiLSTM模型预测，未来4 h NH3—N浓度的均方根误差（root mean squared error，RMSE）分别为0.213 2，0.368 9，0.332 7和0.374 0；未来4 h TP浓度的RMSE分别为0.024 6，0.032 1，0.042 2和0.033 4。…”
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The Property of the <i>Gaia</i> Celestial Reference Frame 3 (<i>Gaia</i>-CRF3) by Guangyi Liu, Sufen Guo

“…These findings confirm that <i>Gaia</i>-CRF3 is a reliable and accurate reference frame, comparable in precision to ICRF3, making it a robust implementation of the optical ICRS for astrometric applications.…”
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