Our ability to learn unfamiliar routes declines in typical and atypical ageing. The reasons for this decline, however, are not well understood. Here we used eye-tracking to investigate how ageing affects people's ability to attend to navigationally relevant information and to select unique objects as landmarks. We created short routes through a virtual environment, each comprised of four intersections with two objects each, and we systematically manipulated the saliency and uniqueness of these objects. While salient objects might be easier to memorise than non-salient objects, they cannot be used as reliable landmarks if they appear more than once along the route. As cognitive ageing affects executive functions and control of attention, we hypothesised that the process of selecting navigationally relevant objects as landmarks might be affected as well. The behavioural data showed that younger participants outperformed the older participants and the eye-movement data revealed some systematic differences between age groups. Specifically, older adults spent less time looking at the unique, and therefore navigationally relevant, landmark objects. Both young and older participants, however, effectively directed gaze towards the unique and away from the non-unique objects, even if these were more salient. These findings highlight specific age-related differences in the control of attention that could contribute to declining route learning abilities in older age. Interestingly, route-learning performance in the older age group was more variable than in the young age group with some older adults showing performance similar to the young group. These individual differences in route learning performance were strongly associated with verbal and episodic memory abilities.
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http://dx.doi.org/10.1016/j.cognition.2019.02.012 | DOI Listing |
BMC Med Educ
January 2025
HAN University of Applied Sciences, Academy Allied Health Sciences, Nijmegen, The Netherlands.
Background: Educational innovation in health professional education is needed to keep up with rapidly changing healthcare systems and societal needs. This study evaluates the implementation of PACE, an innovative curriculum designed by the physiotherapy department of the HAN University of Applied Sciences in The Netherlands. The PACE concept features an integrated approach to learning and assessment based on pre-set learning outcomes, personalized learning goals, flexible learning routes, and programmatic assessment.
View Article and Find Full Text PDFAnal Chem
January 2025
Department of Chemistry, University of Waterloo, 200 University Avenue W., Waterloo, Ontario N2L 3G1, Canada.
Research has shown microplastic particles to be pervasive pollutants in the natural environment, but labor-intensive sample preparation, data acquisition, and analysis protocols continue to be necessary to navigate their diverse chemistry. Machine learning (ML) classification models have shown promise for identifying microplastics from their Raman spectra, but all attempts to date have focused on the lower energy "fingerprint" region of the spectrum. We explore strategies to improve ML classification models based on the -nearest-neighbor algorithm by including other regions of the Raman spectra.
View Article and Find Full Text PDFNat Biotechnol
January 2025
Institute for Intelligent Biotechnologies (iBIO), Helmholtz Center Munich, Neuherberg, Germany.
Efficient and accurate nanocarrier development for targeted drug delivery is hindered by a lack of methods to analyze its cell-level biodistribution across whole organisms. Here we present Single Cell Precision Nanocarrier Identification (SCP-Nano), an integrated experimental and deep learning pipeline to comprehensively quantify the targeting of nanocarriers throughout the whole mouse body at single-cell resolution. SCP-Nano reveals the tissue distribution patterns of lipid nanoparticles (LNPs) after different injection routes at doses as low as 0.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Civil and Environmental Engineering, University of South Carolina, Columbia, SC, 29209, USA.
Accurately predicting the energy consumption plays a vital role in battery electric buses (BEBs) route planning and deployment. Based on the algebraic derivative estimation, we present a novel method to forecast the energy consumption in real time. In contrast to the mainstream machine-learning-based methods, the proposed method does not require access to the historical energy consumption data.
View Article and Find Full Text PDFSci Rep
January 2025
Biosciences Division, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
For decades, Agrobacterium tumefaciens-mediated plant transformation has played an integral role in advancing fundamental and applied plant biology. The recent omnipresent emergence of synthetic biology, which relies on plant transformation to manipulate plant DNA and gene expression for novel product biosynthesis, has further propelled basic as well as applied interests in plant transformation technologies. The strong demand for a faster design-build-test-learn cycle, the essence of synthetic biology, is, however, still ill-matched with the long-standing issues of high tissue culture recalcitrance and low transformation efficiency of a wide range of plant species especially food, fiber and energy crops.
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