To explore pesticide uptake from soil into a growing potato, a moving-boundary dynamic model is proposed on the basis of the radical diffusion process of a chemical to a sphere. This model, which considers the logistic growth of the potato tuber, describes two hypothetical processes of chemical diffusion within a growing tuber. The model was tested in an illustrative case study for an application of chlorpyrifos. Results indicate that the distribution of chlorpyrifos concentrations along the potato radius is significantly affected by the tuber development. In comparison of our results to results from a classic model using a fixed boundary, the proposed dynamic model yields a quick and big jump for both the average concentration and bioconcentration factor (BCF) of chlorpyrifos in the potato as a result of the sigmoid expansion boundary. Overall, the dynamic model predicts that chlorpyrifos BCFs in the potato at harvest are higher than those using the classical model. In comparison of model results to measured uptake of chlorpyrifos into potato at harvest, the dynamic model shows better performance than the classical model. Our results provide a new perspective on pesticide uptake into potatoes and inform human health risk assessment for pesticides applied at different tuber growth stages.
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http://dx.doi.org/10.1021/acs.jafc.1c00151 | DOI Listing |
Commun Psychol
January 2025
Princeton Neuroscience Institute, Princeton University, Princeton, NJ, USA.
How do people model the world's dynamics to guide mental simulation and evaluate choices? One prominent approach, the Successor Representation (SR), takes advantage of temporal abstraction of future states: by aggregating trajectory predictions over multiple timesteps, the brain can avoid the costs of iterative, multi-step mental simulation. Human behavior broadly shows signatures of such temporal abstraction, but finer-grained characterization of individuals' strategies and their dynamic adjustment remains an open question. We developed a task to measure SR usage during dynamic, trial-by-trial learning.
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January 2025
North Carolina School of Science and Mathematics, Durham, NC, 27705, USA.
Mobile Ad Hoc Networks (MANETs) are increasingly replacing conventional communication systems due to their decentralized and dynamic nature. However, their wireless architecture makes them highly vulnerable to flooding attacks, which can disrupt communication, deplete energy resources, and degrade network performance. This study presents a novel hybrid deep learning approach integrating Convolutional Neural Networks (CNN) with Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) architectures to effectively detect and mitigate flooding attacks in MANETs.
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January 2025
Institute for System Dynamics, University of Stuttgart, Waldburgstr. 19, 70563, Stuttgart, Germany.
Including sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove.
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January 2025
School of Cyberspace Security, Hebei University of Engineering Science, Shijiazhuang, 050091, China.
Aerial images can cover a wide area and capture rich scene information. These images are often taken from a high altitude and contain many small objects. It is difficult to detect small objects accurately because their features are not obvious and are susceptible to background interference.
View Article and Find Full Text PDFMed Biol Eng Comput
January 2025
School of Medical Engineering, Department of Cardiology of The First Affiliated Hospital of Xinxiang Medical University, Xinxiang Medical University, Xinxiang, 453003, Henan, China.
The research aims to investigate the mechanical response of footfalls at different velocities to understand the mechanism of heel injury and provide a scientific basis for the prevention and treatment of heel fractures. A three-dimensional solid model of foot drop was constructed using anatomical structures segmented from medical CT scans, including bone, cartilage, ligaments, plantar fascia, and soft tissues, and the impact velocities of the foot were set to be 2 m/s, 4 m/s, 6 m/s, 8 m/s, and 10 m/s. Explicit kinetic analysis methods were used to investigate the mechanical response of the foot landing with different speeds to explore the damage mechanism of heel bone at different impact velocities.
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