Results 131 to 140 of about 148,894 (295)
A multinode wearable system tailored for firefighters is presented, featuring LoRa‐BLE heterogeneous communication and edge‐side deep learning. It integrates a lightweight 1D‐CNN for real‐time posture recognition and an adaptive Physiological Strain Index (aPSI) model, ensuring reliable status monitoring and safety warning in complex fireground ...
Chongyuan Ni +8 more
wiley +1 more source
The shift to ‘close to nature forestry' as the dominating forestry regime in western‐European forests has resulted in increasing timber volume and denser forests with negative effects on photophilic species. Hence, there is an increasing focus on active habitat management measures to support these species.
Maria Kochs +6 more
wiley +1 more source
Exploration of new wildlife surveying methodologies that leverage advances in sensor technology and machine learning has led to tentative research into the application of seismology techniques. This, most commonly, involves the deployment of a footfall trap – a seismic sensor and data logger customised for wildlife footfall.
Benjamin J. Blackledge +4 more
wiley +1 more source
Hemipteran vectors of stylet‐borne plant viruses: Aphids lead the charge
Among all sap‐feeding hemipterans, aphids stand out by far as the most important vectors of noncirculative plant viruses. Compared to whiteflies and mealybugs, aphids’ highly specialized stylet anatomy and distinct feeding behaviors contribute, together with other features of their biology, to their remarkable efficiency in transmitting stylet‐borne ...
Yu Fu, Stefano Colella, Marilyne Uzest
wiley +1 more source
Adaptation of the invasive pest Drosophila suzukii to a specialized nutritional niche
Unlike most Drosophila larvae that feed on spoiled food, Drosophila suzukii larvae thrive on ripening fruits and consequently face a low‐protein, high‐carbohydrate nutritional challenge. Comparisons of growth among D. suzukii, D. biarmipes, and D. melanogaster larvae across diets with varying protein‐to‐carbohydrate ratios demonstrate that D.
Yan Hou, Ying Zhen
wiley +1 more source
AutoPollS: A tool for automated monitoring of pollinators using deep learning
Abstract Deep learning and computer vision hold enormous potential for automated monitoring of biodiversity, including pollinators and other insects. Efficient, scalable monitoring of insect pollinators is crucial given pollinators' role in supporting biodiversity and agricultural productivity amidst declining pollinator populations.
Matthew A.‐Y. Smith +13 more
wiley +1 more source
Mothbox and Mothbot: Automated light trap and data processing system for scalable insect monitoring
Abstract Insects represent the most diverse group of organisms on Earth and comprise the majority of known species; yet they are seldom accounted for in large‐scale biodiversity monitoring systems and conservation planning. We have developed the Mothbox—an open source automated light trap that makes insect monitoring accessible to non‐specialists and ...
Hubert A. Szczygieł +5 more
wiley +1 more source
Refuge by day, forage by night: Diel activity of vine weevil as characterised by smart monitoring
Vine weevil activity was monitored using a Smart trap, which recorded diel refuge‐seeking behaviour. Increasing light intensity triggered refuge seeking behaviour, while lower light intensity induced forage seeking activity. Understanding vine weevil diel activity can enhance early detection, which can improve the effectiveness of integrated pest ...
Ronald Manjoro +5 more
wiley +1 more source
The Outsiders: Principled Withdrawal, Whiteness, and Power in the Los Angeles Food Justice Movement
ABSTRACT This article draws on understandings of whiteness and the misconstrual of South Central Los Angeles to analyze the power dynamics between “outsider” activists and residents of South Central as they worked toward a more equitable food system.
Hanna Garth
wiley +1 more source
Detection of Certain Berries in Difficult Samples by Singleplex and Multiplex Real-Time PCR-HRM: A Case Study of Pitfalls. [PDF]
Fialova L, Marova I.
europepmc +1 more source

