The transition to remote learning in the context of COVID-19 led to dramatic setbacks in education. Is the return to in-person classes to eliminate these losses eventually? We study this question using data from the of secondary students in São Paulo State, Brazil. We estimate the causal medium-run impacts of the length of exposure to remote learning during the pandemic through a triple-differences strategy, which contrasts changes in educational outcomes across municipalities and grades that resumed in-person classes earlier (already by Q4/2020) or only in 2021. We find that relative learning losses from longer exposure to remote learning did fade out over time-attesting that school reopening was at the same time key but not enough to mitigate accumulated learning losses in face of persistence. Using observational and experimental variation in local responses across 645 municipalities, we further document that remedial educational policies in the aftermath of the pandemic boosted learning recovery.
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http://dx.doi.org/10.1073/pnas.2316300121 | DOI Listing |
Syst Biol Reprod Med
December 2025
Department of Mathematics and Computer Science, Laboratory of Analysis, Modeling and Simulation, Faculty of Sciences Ben M'sik, Hassan II University of Casablanca, Casablanca, Morocco.
Infertility has emerged as a significant public health concern, with assisted reproductive technology (ART) is a last-resort treatment option. However, ART's efficacy is limited by significant financial cost and physical discomfort. The aim of this study is to build Machine learning (ML) decision-support models to predict the optimal range of embryo numbers to transfer, using data from infertile couples identified through literature reviews.
View Article and Find Full Text PDFNPJ Digit Med
January 2025
Division of Psychology and Mental Health, School of Health Sciences, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, M13 9PL, UK.
There is increasing use of digital tools to monitor people with psychosis and schizophrenia remotely, but using this type of data is challenging. This systematic review aimed to summarise how studies processed and analysed data collected through digital devices. In total, 203 articles collecting passive data through smartphones or wearable devices, from participants with psychosis or schizophrenia were included in the review.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Control Science and Engineering, Harbin Institute of Technology, Harbin, 150001, China.
As a multivariate time series, the prediction of curling trajectories is crucial for athletes to devise game strategies. However, the wide prediction range and complex data correlations present significant challenges to this task. This paper puts forward an innovative deep learning approach, CasLSTM, by introducing integrated inter-layer memory, and establishes an encoder-predictor curling trajectory forecasting model accordingly.
View Article and Find Full Text PDFInt J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
Interv Pain Med
March 2025
Department of Anesthesiology, Perioperative, and Pain Medicine, Weill Cornell Medicine, New York, NY, USA.
•: The AI-assisted VR module enables learners to engage in a 360-degree immersive environment, manipulating holographic anatomy models and simulating fluoroscopic guidance to perform the Gasserian ganglion block.•: Key anatomical landmarks, like the foramen ovale, are highlighted, and proper C-arm positioning is demonstrated, helping practitioners localize the target area for needle advancement.•: The module includes AI-driven multi-language options and AI-generated multiple-choice questions to enhance learning and retention.
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