Localization in GPS-denied environments has become a bottleneck problem for small unmanned aerial vehicles (UAVs). Smartphones equipped with multi-sensors and multi-core processors provide a choice advantage for small UAVs for their high integration and light weight. However, the built-in phone sensor has low accuracy and the phone storage and computing resources are limited, which make the traditional localization methods unable to be readily converted to smartphone-based ones. The paper aims at exploring the feasibility of the phone sensors, and presenting a real-time, less memory autonomous localization method based on the phone sensors, so that the combination of “small UAV+smartphone” can operate in GPS-denied areas regardless of the overload problem. Indoor and outdoor flight experiments are carried out, respectively, based on an off-the-shelf smartphone and a XAircraft 650 quad-rotor platform. The results show that the precision performance of the phone sensors and real-time accurate localization in indoor environment is possible.

Aims: To investigate the effects of an 8‐week standardized computerized working memory training (WMT) program on cortical microstructure, morphometric similarity network (MSN) changes, and associated genetic factors in healthy adults.Methods: A total of 76 participants were divided into WMT and control groups. Cortical morphological measurements, including cortical thickness (CT) and fractional dimensions (FD), were measured. MSN changes based on CT and FD measures were analyzed. Additionally, partial least squares (PLS) analysis was conducted to investigate the relationship between critical microstructural alterations and gene transcript expression levels.Results: The WMT group exhibited reduced response times for updating, switching functions, and phonological loop tasks. The cortical morphological measurements revealed increases in CT in several right frontal regions, as well as FD in the frontopolar and middle frontal areas after WMT compared to baseline. Furthermore, significant decreases in MSN based on CT measures were found in specific occipital and intraparietal sulci. Similarly, the MSN of FD showed notable decreases in eigenvector and degree centrality in the left frontomarginal cortex and right middle temporal gyrus. PLS analysis revealed strong links between microstructural changes and gene expression, with PLS+ genes enriched in synaptic transmission, neural regulation, and energy metabolism, while PLS− genes were associated with intracellular transport, protein modification, and stress responses.Conclusion: The findings highlight the subtle influences of WMT on brain structure and underlying biological processes, providing insights into its role in neural plasticity and suggesting potential genetic contributions to these structural changes.

Sleep deprivation (SD) impairs mood and cognition, yet its dynamic neural mechanisms remain unclear. Forty healthy adults (30-h SD) completed mood assessments, resting-state fMRI (rs-fMRI), and psychomotor vigilance task (PVT) tests at baseline and post-SD. Using dynamic functional connectivity (dFC) with sliding windows and k-means clustering, we identified two recurrent whole-brain states: (i) an economical state with sparse, weaker global coupling and (ii) a maladaptive compensatory state with globally strengthened synchronization. SD increased both the fraction of windows and mean dwell time (MDT) of the maladaptive state. Across participants, PVT lapses correlated positively with the maladaptive state's MDT and fraction of windows and negatively with those of the economical state. Finally, we built an interpretable predictive model of PVT lapses using competitive adaptive reweighted sampling partial least-squares regression (CARS-PLSR), which highlighted connections within the dorsal attention network (DAN) as key predictors. These findings link behavioral impairment to altered brain-state dynamics and provide a sparse, testable feature set that can support early risk stratification and intervention for SD-related cognitive decline.