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Landscape influences bat suppression of pine processionary moth: Implications for pest management.
J Environ Manage
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CE3c - Centre for Ecology, Evolution and Environmental Changes & CHANGE - Global Change and Sustainability Institute, Departamento de Biologia Animal, Faculdade de Ciências, Universidade de Lisboa, 1749-016, Lisboa, Portugal.
Bats provide important ecosystem services, particularly in agriculture, yet integrating bat management into conservation plans remains challenging. Some landscape features considerably influence bat presence, diversity, and ecosystem service provision. Understanding the relationship between landscape structure, composition, pest suppression, and ecosystem services is crucial.
View Article and Find Full Text PDFIdentifying priority conservation areas for threatened amphibian habitats in the Yangtze river Delta region to maintain regional biodiversity.
J Environ Manage
December 2024
School of Geography and Ocean Science, Nanjing University, Xianlin Ave.163, 210023, Nanjing, China.
The complex life cycle traits of amphibians make them especially sensitive to environmental change, and their ongoing conservation requires the maintenance of suitable habitat that accounts for such life cycle characteristics which may impacted by local environmental dynamics arising from climate change and human disturbance. Many existing studies on amphibian habitats disregard this important issue, leading to uncertainty in managing critical habitats. The application of appropriate conservation practices is therefore constrained by the fact that the major factors influencing amphibian habitats, and their spatio-temporal dynamics at different life stages, are poorly understood.
View Article and Find Full Text PDFRemoval, conversion and utilization technologies of alkali components in bayer red mud.
J Environ Manage
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China MCC22 Group Corporation Ltd., No.16 Xingfu Road, Fengrun District, Tangshan, Hebei, China.
Bayer red mud is a highly alkaline industrial solid waste generated during alumina production, and its massive discharge and stockpiling poses significant environmental risks. The strong alkalinity of red mud is a primary challenge limiting its effective utilization. This study systematically analyzes the composition and characteristics of alkaline components in red mud, emphasizing the roles of soluble free alkali and chemically bound alkali in regulating its alkalinity.
View Article and Find Full Text PDFA bimodal closed-loop neuromodulation implant integrated with ultraflexible probes to treat epilepsy.
Biosens Bioelectron
December 2024
2020 X-Lab, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China; Center of Materials Science and Optoelectronics Engineering, University of Chinese Academy of Sciences, Beijing, 100049, China; State Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, 200050, China; School of Graduate Study, University of Chinese Academy of Sciences, Beijing, 100049, China. Electronic address:
Anti-seizure medications and deep brain stimulation are widely used therapies to treat seizures; however, both face limitations such as resistance and the unpredictable nature of seizures. Recent advancements, including responsive neural stimulation and on-demand drug release, have been developed to address these challenges. However, a gap remains, as electrical stimulation provides only transient effects while medication has a delayed onset.
View Article and Find Full Text PDFA sparse and wide neural network model for DNA sequences.
Neural Netw
December 2024
Norwegian University of Science and Technology, Trondheim, Norway; Jinhua Institute of Zhejiang University, Hangzhou, China.
Accurate modeling of DNA sequences requires capturing distant semantic relationships between the nucleotide acid bases. Most existing deep neural network models face two challenges: (1) they are limited to short DNA fragments and cannot capture long-range interactions, and (2) they require many supervised labels, which is often expensive in practice. We propose a new neural network model called SwanDNA to address the above challenges.
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