Flexible solar cells based on foldable silicon wafers with blunted edges.

Flexible solar cells have a lot of market potential for application in photovoltaics integrated into buildings and wearable electronics because they are lightweight, shockproof and self-powered. Silicon solar cells have been successfully used in large power plants. However, despite the efforts made for more than 50 years, there has been no notable progress in the development of flexible silicon solar cells because of their rigidity1-4. Here we provide a strategy for fabricating large-scale, foldable silicon wafers and manufacturing flexible solar cells. A textured crystalline silicon wafer always starts to crack at the sharp channels between surface pyramids in the marginal region of the wafer. This fact enabled us to improve the flexibility of silicon wafers by blunting the pyramidal structure in the marginal regions. This edge-blunting technique enables commercial production of large-scale (>240 cm2), high-efficiency (>24%) silicon solar cells that can be rolled similarly to a sheet of paper. The cells retain 100% of their power conversion efficiency after 1,000 side-to-side bending cycles. After being assembled into large (>10,000 cm2) flexible modules, these cells retain 99.62% of their power after thermal cycling between -70 °C and 85 °C for 120 h. Furthermore, they retain 96.03% of their power after 20 min of exposure to air flow when attached to a soft gasbag, which models wind blowing during a violent storm.

Dynamic multi-site graph convolutional network for autism spectrum disorder identification.

Multi-site learning has attracted increasing interests in autism spectrum disorder (ASD) identification tasks by its efficacy on capturing data heterogeneity of neuroimaging taken from different medical sites. However, existing multi-site graph convolutional network (MSGCN) often ignores the correlations between different sites, and may obtain suboptimal identification results. Moreover, current feature extraction methods characterizing temporal variations of functional magnetic resonance imaging (fMRI) signals require the time series to be of the same length and cannot be directly applied to multi-site fMRI datasets. To address these problems, we propose a dual graph based dynamic multi-site graph convolutional network (DG-DMSGCN) for multi-site ASD identification. First, a sliding-window dual-graph convolutional network (SW-DGCN) is introduced for feature extraction, simultaneously capturing temporal and spatial features of fMRI data with different series lengths. Then we aggregate the features extracted from multiple medical sites through a novel dynamic multi-site graph convolutional network (DMSGCN), which effectively considers the correlations between different sites and is beneficial to improve identification performance. We evaluate the proposed DG-DMSGCN on public ABIDE I dataset containing data from 17 medical sites. The promising results obtained by our framework outperforms the state-of-the-art methods with increase in identification accuracy, indicating that it has a potential clinical prospect for practical ASD diagnosis. Our codes are available on https://github.com/Junling-Du/DG-DMSGCN.

Mental health effects caused by red imported fire ant attacks (Solenopsis invicta).

Susceptible individuals who have suffered painful stings caused by red imported fire ants, Solenopsis invicta, usually experience physical health effects such as fever, dizziness, generalized urticaria, or other systemic reactions such as anaphylactic shock. Whether S. invicta stings also have negative effects on mental health is not clear. In the present study, the psychological impact of S. invicta stings was evaluated using a questionnaire that included a previously published posttraumatic stress disorder (PTSD) checklist, the Patient Health Questionnaire 9-item (PHQ-9), the Generalized Anxiety Disorder 7-item (GAD-7) scale, the Beck Anxiety Inventory (BAI), and the Pittsburgh Sleep Quality Index, 5th scale (PSQI(5)). A total of 96 valid questionnaires were obtained; 37 participants were placed in the stung group, and 59 participants were placed in the unstung group. Our results showed that symptoms of anxiety, depression and sleep disturbances were not associated with S. invicta stings (for GAD-7 scale, Pearson Chi-Square test, χ2 = 0.152, df = 1, P = 0.697; for the BAI, χ2 = 2.252, df = 1, P = 0.133; for the PHQ-9, χ2 = 0.098, df = 1, P = 0.754; for the PSQI(5), χ2 = 0.536, df = 1, P = 0.453). In total, 2 of 83 individuals stung by S. invicta met the criteria (>50) for PTSD. However, there was no significant difference on PTSD between those stung by S. invicta in the 30-day group and the over 30-day group (χ2 = 0.318, df = 1, P = 0.573). Overall, our data do not show an effect of S. invicta stings on mental health as measured using a range of indicators.