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In this study, we successfully accomplished a one‐to‐one micro‐lens array with pixel via printing technology on a hydrophobic film layer without pattern. By meticulous adjustments to the lens printing process and device structure, we achieved a notable increase in current efficiency exceeding 30% for RGB OELD. [ABSTRACT FROM AUTHOR]

Our study utilizes a global reanalysis of near-surface daily air temperature data spanning the years from 1949 to 2019 to construct climate networks. By employing community detection for each year, we reveal the evolving community structure of the climate network within the context of global warming. Our findings indicate significant changes in measures such as network modularity and the number of communities over the past 30 years. Notably, the community structure of the climate network has undergone a discernible transition since the early 1980s. We attribute this transition to the substantial increase in isolated nodes since the 1980s, primarily concentrated in equatorial ocean regions. Additionally, we demonstrate that nodes experiencing amplified isolation tend to diminish connectivity with other nodes globally, particularly those within the same oceanic basin, while showing a significant strengthening of connections with the Eurasian and North African continents. We deduce that the mechanism driving amplified isolation in the climate network may be comprehended through the weakening of tropical circulations, such as the Hadley cell and Walker circulation, in response to increasing greenhouse gases. [ABSTRACT FROM AUTHOR]

By constructing a correlation network between global sea surface temperature anomalies (SSTAs) and summer precipitation anomalies in the Yunnan–Guizhou Plateau, key SST regions influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau were selected. It was found that spring SSTAs in the Bay of Bengal, southwestern Atlantic, and eastern Pacific are crucial for influencing summer precipitation anomalies in the Yunnan–Guizhou Plateau. Setting SSTAs from these three regions as predictor variables 3 months in advance, we constructed multiple linear regression (MLR), ridge regression (RR), and lasso regression (LR) models to predict summer precipitation anomalies over the Yunnan–Guizhou region. The training phase involved data spanning from 1961 to 2005, which aimed to predict precipitation anomalies in the Yunnan–Guizhou Plateau for the period extending from 2006 to 2022. Based on MLR, RR, and LR models, the correlations between predicted values and observed summer precipitation anomalies in Yunnan–Guizhou were 0.48, 0.46, and 0.46, respectively. These values were all higher than the correlation coefficients of the NCC_CSM model's predicted and observed values. Additionally, its performance in predicting summer precipitation anomalies over the Yunnan–Guizhou region, based on key SST regions, was assessed using performance metrics such as anomaly correlation coefficient (ACC), anomaly sign consistency rate (PC), and trend anomaly comprehensive score (PS score). The average ACC of MLR, RR, and LR models was higher than that of the NCC_CSM model's predictions. For MLR, RR, LR, and NCC_CSM models, the PCs exceeding 50% of the year were 14, 14, 11, and 10, respectively. Furthermore, the average PS score for predicting summer precipitation anomalies over the Yunnan–Guizhou region using MLR, RR, and LR was approximately 73 points; 8 higher than the average PS score of the NCC_CSM model. Therefore, predicting summer precipitation anomalies over the Yunnan–Guizhou region based on key SST regions is of great significance for improving the prediction skills of precipitation anomalies in this region. [ABSTRACT FROM AUTHOR]

In this article, we develop a new adaptive event‐triggered asymptotic control scheme for strict‐feedback systems with fast time‐varying parameters. To deal with time‐varying parameters with unknown variation boundaries in the feedback path and the input path, we construct three adaptive laws for parameter estimation, two for the uncertain parameters in the feedback path and one for the uncertain parameters in the input path. In particular, two sets of tuning functions are introduced to avoid over‐parametrization. Additionally, an event‐triggering mechanism is embedded in this adaptive control framework to reduce the data transmission from the controller to the actuator. We also introduce a soft sign function to handle the perturbations caused by sampling errors to achieve asymptotic stability and avoid the so‐called parameter drift. The stability analysis shows that the closed‐loop system is globally uniformly asymptotically stable and the Zeno behavior can be excluded. Simulation results verify the effectiveness and performance of the proposed adaptive scheme. [ABSTRACT FROM AUTHOR]

Seizure prediction are necessary for epileptic patients. The global spatial interactions among channels, and long-range temporal dependencies play a crucial role in seizure onset prediction. In addition, it is necessary to search for seizure prediction features in a vast space to learn new generalized feature representations. Many previous deep learning algorithms have achieved some results in automatic seizure prediction. However, most of them do not consider global spatial interactions among channels and long-range temporal dependencies together, and only learn the feature representation in the deep space. To tackle these issues, in this study, an novel bi-level programming seizure prediction model, B2-ViT Net, is proposed for learning the new generalized spatio-temporal long-range correlation features, which can characterize the global interactions among channels in spatial, and long-range dependencies in temporal required for seizure prediction. In addition, the proposed model can comprehensively learn generalized seizure prediction features in a vast space due to its strong deep and broad feature search capabilities. Sufficient experiments are conducted on two public datasets, CHB-MIT and Kaggle datasets. Compared with other existing methods, our proposed model has shown promising results in automatic seizure prediction tasks, and provides a certain degree of interpretability. [ABSTRACT FROM AUTHOR]

To investigate the impact of the effective radiation dose to immune cells (EDIC) and gross tumor volume (GTV) on lymphopenia and survival in patients with locally advanced esophageal squamous cell carcinoma (LAESCC). Between January 2013 and December 2020, 272 LAESCC patients were treated with definitive radiotherapy in two institutions. Based on radiation doses to the lungs, heart, and body region scanned, EDIC was calculated as an equal uniform dose to the total blood considering blood flow and fraction effect. The radiotherapy plan was used to calculate the GTVs. Lymphopenia was graded based on the lowest lymphocyte count during RT. The overall survival (OS), progress-free survival (PFS), and local recurrence-free survival (LRFS) were analyzed statistically. The lowest lymphocyte count was significantly correlated with EDIC (r= −0.389, p <.001) and GTV (r= −0.211, p <.001). Lymphopenia, EDIC, and GTV are risk factors for patients with ESCC. In a Kaplan-Meier analysis with EDIC and GTV as stratification factors, lymphopenia was not associated with OS in the EDIC>12.9 Gy group (p =.294)and EDIC ≤ 12.9 Gy group, and it was also not associated with OS in GTV>68.8 cm3 group (p =.242) and GTV ≤ 68.8 cm3 group(p =.165). GTV and EDIC had an impact on the relationship between lymphopenia and OS in patients with LAESCC undergoing definitive RT. Poorer OS, PFS, and LRFS are correlated with lymphopenia, higher EDIC, and larger GTV. [ABSTRACT FROM AUTHOR]

Interleukin‐17 s (IL‐17s) are well‐known proinflammatory cytokines, and their antagonists perform excellently in the treatment of inflammatory skin diseases such as psoriasis. However, their physiological functions have not been given sufficient attention by clinicians. IL‐17s can protect the host from extracellular pathogens, maintain epithelial integrity, regulate cognitive processes and modulate adipocyte activity through distinct mechanisms. Here, we present a systematic review concerning the physiological functions of IL‐17s. Our goal is not to negate the therapeutic effect of IL‐17 antagonists, but to ensure their safe use and reasonably explain the possible adverse events that may occur in their application. [ABSTRACT FROM AUTHOR]