Over the past 50 years, global land surface air temperature has been rising at a much higher rate at night than during the day. Understanding plant responses to the asymmetric daytime and nighttime warming in the context of climate change has been a hot topic in global change biology and global ecology. It has been debatable whether the asymmetric warming has opposite effects on vegetation activity (e.g., phenology, productivity). Here we settle the debate by scrutinizing the underpinnings of different statistical methods and revealing how the misuse or improper use of these methods could mischaracterize the effects of asymmetric warming with in situ and satellite observations. The use of the ordinary least square (OLS) methods including both daytime (T) and nighttime (T) temperature in the multiple regression models could overlook the multicollinearity problem and yield the misinterpretations that T and T had opposite effects on spring phenology, autumn phenology, gross primary production (GPP), and normalized difference vegetation index (NDVI). However, when the OLS methods were applied with T and T included in separate models or alternatively the ridge regression (RR) method with properly selected ridge parameter was used, the effects of T and T on vegetation activity were generally in the same direction. The use of the RR method with improperly selected ridge parameter could also mischaracterize the effects of asymmetric warming. Our findings show that daytime and nighttime warming has no opposite effects on vegetation phenology and productivity in the northern hemisphere, and properly dealing with the multicollinearity problem is critical for understanding the effects of asymmetric warming on vegetation activity.
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http://dx.doi.org/10.1016/j.scitotenv.2022.153386 | DOI Listing |
Digit Health
January 2025
Department of Cardiology, Peking University First Hospital, Beijing, China.
Background: Wearables satisfactorily detect atrial fibrillation (AF) longer than 1 hour. Our study aims to evaluate smartwatch performances for long-term AF monitoring, including AF with short durations.
Methods: This prospective study enrolled AF patients from 2020 to 2023.
Sci Rep
January 2025
School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, India.
This study introduces a novel ensemble learning technique namely Multi-Armed Bandit Ensemble (MAB-Ensemble), designed for lane detection in road images intended for autonomous vehicles. The foundation of the proposed MAB-Ensemble technique is inspired in terms of Multi-Armed bandit optimization to facilitate efficient model selection for lane segmentation. The benchmarking dataset namely TuSimple is used for training, validating and testing the proposed and existing lane detection techniques.
View Article and Find Full Text PDFACS Nano
January 2025
State Key Laboratory of Polymer Materials Engineering, Polymer Research Institute of Sichuan University, Chengdu 610065, China.
Daytime radiative cooling (DRC) materials offer a sustainable, pollution-free passive cooling solution. Traditional DRC materials are usually white to maximize solar reflectance, but applications like textiles and buildings need more aesthetic options. Unfortunately, colorizing DRC materials often reduce cooling efficiency due to colorant sunlight absorption.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Laboratoire de Physique et Chimie de l'Environnement et de l'Espace (LPC2E), CNRS-Université Orléans-CNES, Orléans Cedex 2 45071, France.
The source of nitrous acid (HONO) and its importance in island or marine environments are poorly understood. Herein, based on comprehensive field measurements at a hilltop on Corsica Island, we find an inverse diel variation of HONO with higher concentrations during daytime. Night-time HONO budget analysis indicates significant HONO formation during air mass transport along the hillside.
View Article and Find Full Text PDFNurs Rep
December 2024
Division of Pulmonary, Critical Care and Sleep Medicine, UC San Diego Health, La Jolla, CA 92093, USA.
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