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Schistosomiasis, or "snail fever", is a parasitic disease affecting over 200 million people worldwide. People become infected when exposed to water containing particular species of freshwater snails. Habitats for such snails can be mapped using lightweight, inexpensive and field-deployable consumer-grade Unmanned Aerial Vehicles (UAVs), also known as drones. Drones can obtain imagery in remote areas with poor satellite imagery. An unexpected outcome of using drones is public engagement. Whereas sampling snails exposes field technicians to infection risk and might disturb locals who are also using the water site, drones are novel and fun to watch, attracting crowds that can be educated about the infection risk.
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http://dx.doi.org/10.4081/gh.2020.818 | DOI Listing |
Ther Innov Regul Sci
September 2025
Fiocruz Brasilia, ColLaboratory of Science, Technology, Innovation and Society (CTIS), Brasilia, DF, Brazil.
Purpose: To identify and review scientific evidence from experimental studies utilizing unmanned aerial vehicles (UAVs) to transport samples for the diagnosis of COVID-19 and tuberculosis (TB). This exploratory study aims to support the future development of UAVs for transporting biological samples within the Brazilian Unified Health System (SUS).
Methods: This scoping review defined its eligibility criteria using the PECO acronym, focusing on: Population: biological samples for diagnosing COVID-19 or TB; Exposure: UAV transportation; Comparator: land transportation; Outcomes: Cost, effectiveness, methods for sample preservation, flight parameters (time, altitude, speed, distance), and quality of transported samples.
ISA Trans
August 2025
College of Automotive Engineering, Jilin University, No. 5988, Renmin Street, Nanguan District, Changchun City, Jilin Province 130000, China. Electronic address:
In this paper, an event-triggered fuzzy control algorithm is proposed for the unmanned surface vessel (USV) and unmanned aerial vehicle (UAV) cooperative plant to achieve the high-precision landing mission. In the guidance module, an L virtual ship-L virtual aerial vehicle (LVS-LVA) guidance principle is developed to generate the reasonable reference signals for the USV-UAV plant under the landing mission. The proposed guidance principle incorporates a rolling kinematic compensation mechanism based on the 4-degree-of-freedom model of USV, specifically designed to counteract wave-induced rolling disturbances during UAV landing operations on unstable marine platforms.
View Article and Find Full Text PDFTraffic Inj Prev
September 2025
Department of Civil Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, India.
Objective: This study aimed to identify dynamic spatiotemporal traffic factors influencing conflict risk levels on National Highways under heterogeneous traffic conditions in India. The research addresses gaps by capturing vehicle interactions using high-resolution UAV-based trajectory data and proposes a novel two-stage methodology for real-time conflict risk evaluation, moving beyond traditional binary risk classifications to a four-level framework (High, Moderate, Low, No-Risk).
Methods: Over 40,000 conflict risk sequences were classified into four severity levels using the Modified Time-to-Collision (MTTC) surrogate safety measure.
Sci Adv
September 2025
Department of Applied Physics, The Hong Kong Polytechnic University, Hong Kong 999077, China.
Optical superposition natural compound eyes (OSNCEs) allow circadian insects to thrive in varying light conditions thanks to their unique anatomical structures. This provides a blueprint for optical superposition artificial compound eyes (OSACEs) that can adapt to different illumination intensities. However, OSACEs have received limited research attention until recently, with most studies focusing on apposition compound eyes that operate only in bright light.
View Article and Find Full Text PDFFront Artif Intell
August 2025
Aviation Industry Development Research Center of China, Beijing, China.
Autonomous systems operating in high-dimensional environments increasingly rely on prioritization heuristics to allocate attention and assess risk, yet these mechanisms can introduce cognitive biases such as salience, spatial framing, and temporal familiarity that influence decision-making without altering the input or accessing internal states. This study presents Priority Inversion via Operational Reasoning (PRIOR), a black-box, non-perturbative diagnostic framework that employs structurally biased but semantically neutral scenario cues to probe inference-level vulnerabilities without modifying pixel-level, statistical, or surface semantic properties. Given the limited accessibility of embodied vision-based systems, we evaluate PRIOR using large language models (LLMs) as abstract reasoning proxies to simulate cognitive prioritization in constrained textual surveillance scenarios inspired by Unmanned Aerial Vehicle (UAV) operations.
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