This study aims at casting light on the ways in which spatial aspects of mobility and belonging serve as social-psychological discursive resources used by Intra-European Greek immigrants in order to account for integration. For the purposes of the study, 17 virtual interviews with Greek migrants in European cities were analysed. Interview discussion was facilitated by photographs of participants' meaningful places. In the analysis, accounts of belonging to the community 'in general' were juxtaposed to accounts of bonding with specific places. Participants, using spatial discursive resources and constituting complex relationships between political participation, citizenship and place, developed competing arguments and positioned themselves as integrated or excluded from local, national or supranational communities. Accounts of attachment to private and public places mobilized constructions of citizenship based on place appropriation and people-environment relations and constructed spatial or symbolic boundaries. The conclusions underscore the benefits of understanding migrant integration through multilevel (local, national and supranational) constructions of political participation and urban and localized perspectives of citizenship.
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http://dx.doi.org/10.1111/bjso.12649 | DOI Listing |
Sensors (Basel)
January 2025
College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210023, China.
Gesture recognition technology based on millimeter-wave radar can recognize and classify user gestures in non-contact scenarios. To address the complexity of data processing with multi-feature inputs in neural networks and the poor recognition performance with single-feature inputs, this paper proposes a gesture recognition algorithm based on esNet ong Short-Term Memory with an ttention Mechanism (RLA). In the aspect of signal processing in RLA, a range-Doppler map is obtained through the extraction of the range and velocity features in the original mmWave radar signal.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Mechnical and Vehicle Engineering, Hunan University, Changsha 411082, China.
Chip defect detection is a crucial aspect of the semiconductor production industry, given its significant impact on chip performance. This paper proposes a lightweight neural network with dual decoding paths for LED chip segmentation, named LDDP-Net. Within the LDDP-Net framework, the receptive field of the MobileNetv3 backbone is modified to mitigate information loss.
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January 2025
School of Automation, Beijing Institute of Technology, Beijing 100081, China.
Existing autonomous driving systems face challenges in accurately capturing drivers' cognitive states, often resulting in decisions misaligned with drivers' intentions. To address this limitation, this study introduces a pioneering human-centric spatial cognition detecting system based on drivers' electroencephalogram (EEG) signals. Unlike conventional EEG-based systems that focus on intention recognition or hazard perception, the proposed system can further extract drivers' spatial cognition across two dimensions: relative distance and relative orientation.
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January 2025
College of Computer and Information Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Compared with conventional targets, small objects often face challenges such as smaller size, lower resolution, weaker contrast, and more background interference, making their detection more difficult. To address this issue, this paper proposes an improved small object detection method based on the YOLO11 model-PC-YOLO11s. The core innovation of PC-YOLO11s lies in the optimization of the detection network structure, which includes the following aspects: Firstly, PC-YOLO11s has adjusted the hierarchical structure of the detection network and added a P2 layer specifically for small object detection.
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Cytology and Histology, Saint Petersburg State University, 7/9 Universitetskaya Embankment, 199034 Saint Petersburg, Russia.
Flavonoids are a large group of secondary metabolites, which are responsible for pigmentation, signaling, protection from unfavorable environmental conditions, and other important functions, as well as providing numerous benefits for human health. Various stages of flavonoid biosynthesis are subject to complex regulation by three groups of transcription regulators-MYC-like bHLH, R2R3-MYB and WDR which form the MBW regulatory complex. We attempt to cover the main aspects of this intriguing regulatory system in plants, as well as to summarize information on their distinctive features in cereals.
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