Engraulicypris sardella is an endemic and economically important cyprinid species in Lake Nyasa/Malawi which has recently been infected by the tapeworm Ligula intestinalis. This parasite is known to induce severe pathological and behavioural effects on other cyprinids, including castration, followed by a collapse of infected populations. As a first step to understanding the dynamics between this parasite and E. sardella, we studied the spatial and temporal variation in prevalence over a period of 1 year. Overall prevalence was about 15%, but we observed a consistently higher prevalence in the littoral compared to the pelagic zone. Fish in the upper water levels showed the highest prevalence, with a marked decline with increasing water depth down to 150 m. The proportion of infected fish varied over time, with a significantly higher prevalence in the rainy season. In a huge lake like the Nyasa, with a surface area of 29,000 km2 and a maximum depth of 785 m, the transmission success of the parasite appears to show large variations in time and space. We suggest that these conditions could lead the parasite to become persistent within the lake, rather than the typical epidemic situation as observed in smaller bodies of water.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1017/S0022149X17000724 | DOI Listing |
Nano Converg
January 2025
Bendable Electronics and Sustainable Technologies (BEST) Group, Electrical and Computer Engineering Department, Northeastern University, Boston, MA, 02115, USA.
The intriguing way the receptors in biological skin encode the tactile data has inspired the development of electronic skins (e-skin) with brain-inspired or neuromorphic computing. Starting with local (near sensor) data processing, there is an inherent mechanism in play that helps to scale down the data. This is particularly attractive when one considers the huge data produced by large number of sensors expected in a large area e-skin such as the whole-body skin of a robot.
View Article and Find Full Text PDFSci Data
January 2025
University of Bern, Wyss Academy for Nature, Bern, 3011, Switzerland.
Throughout the last centuries, European climate changed substantially, which affected the potential to plant and grow crops. These changes happened not just over time but also had a spatial dimension. Yet, despite large climatic fluctuations, quantitative historical studies typically rely on static measures for agricultural suitability due to the non-availability of time-varying indices.
View Article and Find Full Text PDFSci Rep
January 2025
Xinjiang Vocational and Technical College of Communications, Urumqi, Xinjiang, 831401, China.
This paper aims to construct a green environmental protection system by advancing database energy-saving techniques and optimizing the energy-saving mechanism against the backdrop of blockchain integration. The protocol classification of wireless sensor networks is examined within the context of the rapid growth of information technology. The analysis draws upon the database storage and sharing model and recent research examples that connect blockchain and database technology.
View Article and Find Full Text PDFACS Nano
January 2025
Research Laboratory of Electronics, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02139, United States.
Understanding energy transport in semiconductors is critical for the design of electronic and optoelectronic devices. Semiconductor material properties, such as charge carrier mobility or diffusion length, are commonly measured in bulk crystals and determined using models that describe transport behavior in homogeneous media, where structural boundary effects are minimal. However, most emerging semiconductors exhibit nano- and microscale heterogeneity.
View Article and Find Full Text PDFJ Infect
January 2025
School of Veterinary Medicine, University of Surrey, Daphne Jackson Rd, Guildford GU2 7AL, United Kingdom; The Surrey Institute for People-Centred Artificial Intelligence, Stag Hill University Campus, Guildford GU2 7XH, United Kingdom; Institute for Sustainability, University of Surrey, Guildford, United Kingdom; University of Exeter, Exeter, United Kingdom.
Objectives: This study aimed to improve the understanding of seasonal incidence pattern observed in salmonellosis by identifying the most influential weather factors, characterizing the nature of this association, and assessing whether it is geographically restricted or generalizable to other locations.
Methods: A novel statistical model was employed to estimate the incidence of salmonellosis conditional to various combinations of three simultaneous weather factors from 14 available. The analysis utilised daily salmonellosis cases reported from 2000 to 2016 along with detailed spatial and temporal weather data from England and Wales, and the Netherlands.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!