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http://dx.doi.org/10.1007/s00168-023-01224-3 | DOI Listing |
Environ Technol
January 2025
Shaanxi Huashan Road and Bridge Group Co., Ltd., Xi'an, People's Republic of China.
Due to the rapid development of urbanisation, cities frequently experience waterlogging during rainfall. Rain gardens are widely used in new urban construction because they effectively control surface runoff from rainwater, thereby reducing waterlogging. The runoff control effectiveness of rain gardens is influenced by multiple factors.
View Article and Find Full Text PDFChem Commun (Camb)
January 2025
State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering, Lanzhou University, 222 South Tianshui Road, Lanzhou 730000, P. R. China.
Conjugated porous polymers bearing flavone moieties (FL-CPPs) were synthesized a tandem approach. The carbonylative Sonogashira coupling in tandem with cyclization guided the assembling of building blocks with the accompanied production of flavone skeletons. The FL-CPPs were proved to be efficient metal-free photocatalysts for the [3+2] cycloaddition of phenols with olefins under the irradiation of visible-light.
View Article and Find Full Text PDFCancer Metab
January 2025
Molecular Oncology Laboratories, Department of Medical Oncology, Weatherall Institute of Molecular Medicine, John Radcliffe Hospital, University of Oxford, Oxford, OX3 9DS, UK.
Infant Ment Health J
January 2025
Department of Psychiatry and Human Behavior, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA.
Reflective supervision (RS) has been viewed as best practice and is therefore incorporated-and often mandated-as a key feature of many relationship-based infant and early childhood serving programs. To promote the implementation of high-quality RS for infant and early childhood professionals, it is critical that a focus is placed on how infant and early childhood professionals are trained to build RS capacities. To this end, we describe Rhode Island, United States's journey developing, implementing, and iteratively adapting an RS professional development series.
View Article and Find Full Text PDFJ Am Med Inform Assoc
January 2025
Department of Computer Science, Duke University, Durham, NC 27708, United States.
Objective: Prediction of mortality in intensive care unit (ICU) patients typically relies on black box models (that are unacceptable for use in hospitals) or hand-tuned interpretable models (that might lead to the loss in performance). We aim to bridge the gap between these 2 categories by building on modern interpretable machine learning (ML) techniques to design interpretable mortality risk scores that are as accurate as black boxes.
Material And Methods: We developed a new algorithm, GroupFasterRisk, which has several important benefits: it uses both hard and soft direct sparsity regularization, it incorporates group sparsity to allow more cohesive models, it allows for monotonicity constraint to include domain knowledge, and it produces many equally good models, which allows domain experts to choose among them.
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