Probabilistic seasonal dengue forecasting in Vietnam: A modelling study using superensembles. by Felipe J Colón-González, Leonardo Soares Bastos, Barbara Hofmann, Alison Hopkin, Quillon Harpham, Tom Crocker, Rosanna Amato, Iacopo Ferrario, Francesca Moschini, Samuel James, Sajni Malde, Eleanor Ainscoe, Vu Sinh Nam, Dang Quang Tan, Nguyen Duc Khoa, Mark Harrison, Gina Tsarouchi, Darren Lumbroso, Oliver J Brady, Rachel Lowe

“…Moreover, the transition from theoretical to operational systems integrated with disease control activities is rare.<h4>Methods and findings</h4>We introduce an operational seasonal dengue forecasting system for Vietnam where Earth observations, seasonal climate forecasts, and lagged dengue cases are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to 6 months ahead. …”
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Vibration Signal Forecasting on Rotating Machinery by means of Signal Decomposition and Neurofuzzy Modeling by Daniel Zurita-Millán, Miguel Delgado-Prieto, Juan José Saucedo-Dorantes, Jesus Adolfo Cariño-Corrales, Roque A. Osornio-Rios, Juan Antonio Ortega-Redondo, Rene de J. Romero-Troncoso

“…The results of the study indicate the suitability of the method for vibration forecasting in complex electromechanical systems and their associated kinematic chains.…”
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Empirical prediction intervals applied to short term mortality forecasts and excess deaths by Ricarda Duerst, Jonas Schöley

“…Methods Using weekly death data from the Short-term Mortality Database (STMF) for 23 countries, we propose empirical prediction intervals based on the distribution of past out-of-sample forecasting errors for the study of weekly expected and excess deaths. …”
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Forecasting the number of identified information security vulnerabilities based on the theory of “Gray Systems” by A. O. Efimov, S. A. Mishin, E. A. Rogozin

“…The results of the study indicate the possibility of applying the theory of “gray systems” for short-term forecasting of the number of detected vulnerabilities. …”
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Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis by Cosmina-Mihaela Rosca, Adrian Stancu

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Automatically Detected CSES Ionospheric Precursors Before Part of the Strong Aftershocks of the 23 January 2024 Wushi <i>M</i>_S 7.1 Earthquake in Northwest China by Mei Li, Hongzhu Yan, Tianyu Liu

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A Hybrid ARIMA-LSTM-XGBoost Model with Linear Regression Stacking for Transformer Oil Temperature Prediction by Xuemin Huang, Xiaoliang Zhuang, Fangyuan Tian, Zheng Niu, Yujie Chen, Qian Zhou, Chao Yuan

“…The predictions of these three models are combined through a linear-regression stacking approach, improving accuracy and simplifying the model structure. This hybrid method outperforms traditional models, offering superior performance in predicting transformer oil temperature, which enhances fault detection and transformer reliability. …”
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Multimodal Computational Approach for Forecasting Cardiovascular Aging Based on Immune and Clinical–Biochemical Parameters by Madina Suleimenova, Kuat Abzaliyev, Ainur Manapova, Madina Mansurova, Symbat Abzaliyeva, Saule Doskozhayeva, Akbota Bugibayeva, Almagul Kurmanova, Diana Sundetova, Merey Abdykassymova, Ulzhas Sagalbayeva

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ANNUAL FORECAST IN PATIENTS WITH ACUTE ISCHEMIC STROKE: ROLE OF PATHOLOGICAL ANKLE-BRACHIAL INDEX by A. N. Sumin, J. A. Kolmykova, I. N. Kukhareva, M. V. Ott, N. I. Vodopyanova, A. A. Morkvenas, O. A. Trubnikova, A. V. Kovalenko

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WHY WE CANNOT PREDICT STRONG EARTHQUAKES IN THE EARTH’S CRUST by Iosif L. Gufeld, Margarita I. Matveeva, Oleg N. Novoselov

“…Lesson should be learned from our common fiasco in forecasting, taking into account research results obtained during the past 50–60 years. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The GEO-based feature selection method effectively identified the most relevant predictors, while the Deep-NARMAX model captured temporal dynamics for accurate forecasting. …”
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Tools for forecasting regional economic growth using big data and business intelligence technologies by Afanasev Kirill, Kalinin Aleksandr

“…The significance of the study is due to the increasing complexity of regional economic growth forecasting in the context of digital transformation and the limitations of traditional analysis methods. …”
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Forecasting CO2 emissions in BRICS countries using the grey breakpoint prediction models by Huiping Wang, Xinge Guo

“…Finally, the novel grey breakpoint prediction models are used to simulate and forecast the CO2 emissions in BRICS countries. We can see that by setting time breakpoints and fuzzy breakpoint intervals, the novel methods successfully detect abrupt changes in the system and achieve accurate predictions, thus improving the accuracy and applicability of the grey model. …”
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CO-MORBIDITY AND FORECASTING THE RISK OF POST-OPERATIVE INFECTIOUS COMPLICATIONS IN TUBERCULOUS SPONDYLITIS PATIENTS by S. V. Burlakov, A. A. Vishnevskiy

“…Early and late infectious complications were detected in 4 (9.7%) of patients with ASA at 3-4 scores, Charlson score exceeding 5 and high risk as per PITSS (more than 21 scores). …”
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Lessons learned from the co-development of operational climate forecast services for vineyards management by N. Pérez-Zanón, V. Agudetse, E. Baulenas, P.A. Bretonnière, C. Delgado-Torres, N. González-Reviriego, A. Manrique-Suñén, A. Nicodemou, M. Olid, Ll. Palma, M. Terrado, B. Basile, F. Carteni, A. Dente, C. Ezquerra, F. Oldani, M. Otero, F. Santos-Alves, M. Torres, J. Valente, A. Soret

“…In the co-design phase, more intense engagement methods were implemented to communicate the capabilities of climate forecasts and design the product’s visualisation. …”
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Linking Critical Heights in Solar Active Regions with 3D Coronal Mass Ejection Speeds: Insights from Automated and Manual Polarity Inversion Line Detection Methods by Harshita Gandhi, Alexander W James, Huw Morgan, Lucie Green

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Structural time series modelling for weekly forecasting of enterovirus outpatient, inpatient, and emergency department visits. by Cathy W S Chen, Leon L Hsieh, Betty X Y Chu

“…The study evaluates forecast accuracy using five key metrics and identifies significant surges in cases by detecting values that exceed the 95% prediction intervals, enhancing anomaly detection.…”
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Ultra-Short-Term Wind Power Forecasting in Complex Terrain: A Physics-Based Approach by Dimitrios Michos, Francky Catthoor, Dimitris Foussekis, Andreas Kazantzidis

“…This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. …”
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Impact of Assimilating Microwave Radiance Data on Forecast of "23·7" Extreme Rainstorm in North China by Zhong Peiwen, Chen Yaodeng, Xie Yanhui, Chen Min, Fan Shuiyong, Li Juan

“…CMA-MESO model is utilized to investigate the impact of assimilating multi-source polar-orbiting satellite microwave radiance data on forecast of "23.7" severe rainstorm event in North China. …”
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Scientific geovisualization of the dynamics of Sargassum dispersion and landfall in the Caribbean, based on satellite imagery and numerical forecasts. by Francisco Javier Osorno-Covarrubias, Jorge Prado Molina, Gabriela Gómez-Rodríguez, Uriel Mendoza, Stéphane Couturier

“…An automated prototype is developed incorporating the following components: 1) Detection of Sargassum Rafts: Individual sargassum rafts are identified using Sentinel-2 images with a revisiting period of five days. 2) Forecasting/Hindcasting Vector Fields: One-week forecasts (or hindcasts) are obtained at hourly intervals for the primary forces affecting raft movement—currents, tides, waves, and wind—using supercomputing services (Copernicus Marine Service) 3) Lagrangian Simulation: The movement of detected rafts in step 1 is simulated using the vector fields obtained in step 2. …”
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