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            Vehicular edge computing relies on the computational capabilities of interconnected edge devices to manage incoming requests from vehicles. This offloading process enhances the speed and efficiency of data handling, ultimately boosting the safety, performance, and reliability of connected vehicles. While previous studies have concentrated on processor characteristics, they often overlook the significance of the connecting components. Limited memory and storage resources on edge devices pose challenges, particularly in the context of deep learning, where these limitations can significantly affect performance. The impact of memory contention has not been thoroughly explored, especially regarding perception-based tasks. In our analysis, we identified three distinct behaviors of memory contention, each interacting differently with other resources. Additionally, our investigation of Deep Neural Network (DNN) layers revealed that certain convolutional layers experienced computation time increases exceeding 2849%, while activation layers showed a rise of 1173.34%. Through our characterization efforts, we can model workload behavior on edge devices according to their configuration and the demands of the tasks. This allows us to quantify the effects of memory contention. To our knowledge, this study is the first to characterize the influence of memory on vehicular edge computational workloads, with a strong emphasis on memory dynamics and DNN layers.more » « lessFree, publicly-accessible full text available January 1, 2026
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            The kinetochore scaffold 1 (KNL1) protein recruits spindle assembly checkpoint (SAC) proteins to ensure accurate chromosome segregation during mitosis. Despite such a conserved function among eukaryotic organisms, its molecular architectures have rapidly evolved so that the functional mode of plant KNL1 is largely unknown. To understand how SAC signaling is regulated at kinetochores, we characterized the function of theKNL1gene inArabidopsis thaliana. The KNL1 protein was detected at kinetochores throughout the mitotic cell cycle, and nullknl1mutants were viable and fertile but exhibited severe vegetative and reproductive defects. The mutant cells showed serious impairments of chromosome congression and segregation, that resulted in the formation of micronuclei. In the absence of KNL1, core SAC proteins were no longer detected at the kinetochores, and the SAC was not activated by unattached or misaligned chromosomes. Arabidopsis KNL1 interacted with SAC essential proteins BUB3.3 and BMF3 through specific regions that were not found in known KNL1 proteins of other species, and recruited them independently to kinetochores. Furthermore, we demonstrated that upon ectopic expression, the KNL1 homolog from the dicot tomato was able to functionally substitute KNL1 inA.thaliana, while others from the monocot rice or moss associated with kinetochores but were not functional, as reflected by sequence variations of the kinetochore proteins in different plant lineages. Our results brought insights into understanding the rapid evolution and lineage-specific connection between KNL1 and the SAC signaling molecules.more » « less
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            A new class of stable four-coordinated benzotriazole-borane compounds was developed via gold-catalyzed alkyne hydroboration. The application of polymeric (BH 2 CN) n reagent gave the formation of cyano-amine-boranes (CAB) complexes with less basic N-heterocyclic amines and anilines. Various new CABs were investigated in catalytic hydroboration to synthesize N–B cycles. The 1,2,3-benzotriazoles were identified as the only feasible N-source, giving the four coordinated borane N–B cycles (BTAB) in excellent yields (up to 90%) with good functional group tolerability. This new class of polycyclic N–B compounds showed excellent stability toward acid, base, high temperature, and photo-irradiation. The facile synthesis, excellent stability, strong and tunable fluorescence emission make BTAB interesting new fluorescent probes for future chemical and biological applications.more » « less
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