Wormholes and factorization in exact effective theory by Sergio Hernández-Cuenca

“…This framework unifies and provides new insights into much of the phenomena observed in quantum gravity, including the interplay between wormholes and unitarity, the breakdown of bulk effective theory, the factorization puzzle, state ensembles, theory ensembles, quantum error correction, and baby universes. Some interesting lessons are drawn accounting also for characteristic aspects of gravity concerning IR/UV mixing and Kaluza-Klein reductions.…”
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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

“…Concretely, the tactical behavior was expressed by spatiotemporal tracking data using convolutional neural networks, recurrent neural networks, variational recurrent neural networks, and variational autoencoders, Delaunay method, player rank, hierarchical clustering, logistic regression, XGBoost, random forest classifier, repeated incremental pruning produce error reduction, principal component analysis, and T-distributed stochastic neighbor embedding. …”
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Modeling the Effects of Vegetation on Air Purification Through Computational Fluid Dynamics in Different Neighborhoods of Beijing by Bin Cai, Haomiao Cheng, Fanding Xiang, Han Wang, Tianfang Kang

“…The simulation results were also well validated by the trial-and-error method compared with the computation of vegetation absorption coefficients. …”
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Application of artificial neural networks for predicting soil settlement in geotechnical applications with plastic waste reinforcement above buried pipes by Sinan A. Al-Haddad, Hala Adnan Abbas, Luttfi A. Al-Haddad, Mustafa I. Al-Karkhi

“…The R2 values reached 0.9990 for training and 0.9965 for testing, while the Root Mean Square Error (RMSE) was maintained at 0.021% for training and 0.034% for testing which indicates minimal deviation between predicted-observed settlements. …”
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Assessment the Effects of Climate Change on the Degree of Heating and Cooling Days of Iran by Hasan Zolfaqari, Hamid Rahimi, Rohollah Oji

“…It is expected to stabilize and reduce the need for cooling in the Alborz and Zagros ridgetop. In spite of the reduction in heating demand for the country, the horizons are foreseen. …”
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Securing Medication Use in Pediatric Oncology Units in French-Speaking Africa: MAEva Pilot Program Results in Ivory Coast by Line Couitchere, Innocent Krasse, Léa Zaho, Marina Yao, Guy Yao, Carole Coze, Nadine Robert, Olga Molly, Max N'Doumy, Charles Akoun, Bertrand Pourroy

“…The aim of this study was to adapt and implement a proactive risk assessment tool for medication use in pediatric oncology units in French-speaking Africa to reduce medication errors and enhance patient safety.METHODSThe médiEval French tool was adapted into the MAEva tool for the African context through a three-stage process: content review by a multidisciplinary group, content formatting, and item modification/validation. …”
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Enhanced deep learning model for apple detection, localization, and counting in complex orchards for robotic arm-based harvesting by Tantan Jin, Xiongzhe Han, Pingan Wang, Zhao Zhang, Jie Guo, Fan Ding

“…In outdoor field experiments conducted under cloudy, low-light, and artificial lighting conditions, the model achieved localization errors of 2.43 mm (X-axis), 3.70 mm (Y-axis), and 1.28 mm (Z-axis), representing reductions of 19.27 %, 12.67 %, and 23.05 %, respectively. …”
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Do delayed responses introduce bias in ecological momentary assessment? Evidence from comparisons between self-reported and objective physical activity by Stefan Schneider, Stefan Schneider, Stefan Schneider, Meynard J. Toledo, Doerte U. Junghaenel, Doerte U. Junghaenel, Doerte U. Junghaenel, Joshua M. Smyth, Pey-Jiuan Lee, Sarah Goldstein, Olivia Pomeroy, Arthur A. Stone, Arthur A. Stone

“…There was no significant evidence that response delays systematically biased the levels of EMA reported activities, although delayed responses were associated with significantly more random errors in EMA reports (with small effect sizes).DiscussionThe results suggest that respondents self-select the moments for answering EMA surveys based on their current activity levels, but brief response delays do not translate into marked reductions in the quality of EMA data.…”
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Defect Detection and 3D Reconstruction of Complex Urban Underground Pipeline Scenes for Sewer Robots by Ruihao Liu, Zhongxi Shao, Qiang Sun, Zhenzhong Yu

“…For a real section of the pipeline, the maximum measurement error of the 3D reconstruction model is 0.57 m. These results indicate that the proposed sewer inspection framework is effective, with the detection model exhibiting advanced performance in terms of accuracy, low computational demand, and real-time capability. …”
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Multi-Energy-Microgrid Energy Management Strategy Optimisation Using Deep Learning by Wenyuan Sun, Shuailing Ma, Yufei Zhang, Yingai Jin, Firoz Alam

“…The proposed prediction model’s Mean Absolute Error (MAE) is found to be 1.3512, and its R² is 0.9683, proving its efficacy and reliability. …”
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Applying the greenhouse gas inventory calculation approach to predict the forest carbon sink by Fredric Mosley, Jari Niemi, Sampo Soimakallio

“…The tool can replicate forest GHG balances for forest land with an average annual error of 1.0 Mt CO2, representing 4% of the average annual forest carbon sink. …”
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Enhancing Joint Probability of Maxima Method Through ENSO Integration: A Case Study of Annapolis, Maryland by Paul F. Magoulick, Li P. Sung

“…The ENSO-JPMM demonstrates improved predictive accuracy across all phases, with root mean square error reductions of up to 5.96% during Neutral conditions and 3.56% during El Niño phases. …”
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Image Similarity Quantum Algorithm and Its Application in Image Retrieval Systems by Qingchuan Yang, Xianing Feng, Lianfu Wei

“…Overall, within the acceptable error thresholds, the AE-QIP algorithm exhibits enhanced efficiency relative to the ST-QIP algorithm. …”
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A framework for continual learning in real-time traffic forecasting utilizing spatial–temporal graph convolutional recurrent networks by Mariam Labib Francies, Abeer Twakol Khalil, Hanan M. Amer, Mohamed Maher Ata

“…Extensive experiments conducted on the PeMSD3, PeMSD4, PeMSD7, and PeMSD8 datasets reveal the superiority of the proposed models, STGCN-EWC, STGCN-MAS, and STGCN-SI models achieve significant reductions in error rates compared to baseline methodologies. …”
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Hyperspectral Remote Sensing Estimation of Rice Canopy LAI and LCC by UAV Coupled RTM and Machine Learning by Zhongyu Jin, Hongze Liu, Huini Cao, Shilong Li, Fenghua Yu, Tongyu Xu

“…The results indicate that the RPIOSL-UBM model’s hyperspectra closely match measured data in the 500–650 nm and 750–1000 nm ranges, reducing the root mean square error (RMSE) by 0.0359 compared to the PROSAIL model. …”
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Enhancing LiDAR Mapping with YOLO-Based Potential Dynamic Object Removal in Autonomous Driving by Seonghark Jeong, Heeseok Shin, Myeong-Jun Kim, Dongwan Kang, Seangwock Lee, Sangki Oh

“…The system achieved RMSE (Root Mean Square Error) reductions compared to conventional methods, with RMSE values decreasing from 0.9870 to 0.9724 in open areas and from 1.3874 to 1.1217 in urban areas. …”
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Supplemental parenteral nutrition within an enhanced recovery program for open pancreatoduodenectomy for cancer: a pragmatic, multicenter, randomized controlled trialResearch in co... by Luca Gianotti, Salvatore Paiella, Giovanni Capretti, Nicolò Pecorelli, Isabella Frigerio, Marta Sandini, Alessandro Fogliati, Eleonora Vico, Marco Braga, Christian Cotsoglou, Alfonso Pedalino, Giuseppe Malleo, Simone Ricchitelli, Sabrina Caspani, Giovanni Guarneri, Alessia Vallorani, Alessandro Giardino, Elettra Pasqualoni, Roberto Salvia, Alessandro Zerbi, Massimo Falconi, Giovanni Butturini, Davide Paolo Bernasconi

“…The expected complication rate was 60%, and the type I error rate was set at 5%. Registration at ClinicalTrials.gov (#NCT04438447). …”
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Estimating small area population from health intervention campaign surveys and partially observed settlement data by Chibuzor Christopher Nnanatu, Amy Bonnie, Josiah Joseph, Ortis Yankey, Duygu Cihan, Assane Gadiaga, Hal Voepel, Thomas Abbott, Heather R. Chamberlain, Mercedita Tia, Marielle Sander, Justin Davis, Attila N. Lazar, Andrew J. Tatem

“…Here, we present a two-step Bayesian hierarchical modelling approach that can integrate routinely collected health intervention campaign data and partially observed settlement data to produce reliable small area population estimates. Reductions in relative error rates were 32–73% in a simulation study, and ~32% when applied to malaria survey data in Papua New Guinea. …”
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Study of Thermodynamic Horizontal Structure of the Middle and Upper Atmosphere Based on Atmospheric Detection Lidar Networks by Liting Ren, Yong Yang, Linmei Liu, Xin Lin, Jinzhou Zheng, Wei Wang, Jiaming Liang, Yuan Xia, Jiqin Wang, Kaijie Ji, Zhenwei Chen, Yuqi Zhang, Xuewu Cheng, Faquan Li

“…The assimilated temperature profiles closely match lidar observations, with the RMSE (root mean square error) of residual reductions of 67.35% at Urumqi, 60.69% at Yuzhong, and 34.80% at Yangbajing. …”
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Deep-Transfer-Learning Strategies for Crop Yield Prediction Using Climate Records and Satellite Image Time-Series Data by Abhasha Joshi, Biswajeet Pradhan, Subrata Chakraborty, Renuganth Varatharajoo, Shilpa Gite, Abdullah Alamri

“…The proposed transfer-learning approaches outperformed the baseline deep-learning model, with mean absolute error reductions ranging from 9% to 28%, demonstrating the effectiveness of these methods. …”
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