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Mitochondria are vital for retinal cell function and survival, and there is growing evidence linking mitochondrial dysfunction to retinal degenerations. Although ARL3 mutations have been linked to multiple forms of retinal degeneration, the relationship between ARL3 and mitochondria remains unexplored. Herein, we investigated the effects of ARL3T31A, ARL3C118F, and ARL3T31A/C118F mutations on mitochondrial function in fibroblasts obtained from patients with ARL3‐related rod‐cone dystrophy. Our findings revealed that these mutations led to a decrease in mitochondrial respiration, an increase in the accumulation mitochondrial reactive oxygen species (ROS), and induction of apoptosis in fibroblasts. Additionally, we conducted a comparative analysis of the effects of ARL3T31A, ARL3C118F, and ARL3T31A/C118F proteins on mitochondria in ARPE‐19 cells. Results showed that ARL3T31A and ARL3T31A/C118F not only affected mitochondrial function but also induced apoptosis in ARPE‐19 cells. Conversely, ARL3C118F primarily influenced cell apoptosis with minimal effects on mitochondrial function in ARPE‐19 cells. Transcriptome analysis further suggested the involvement of respiratory electron transport, response to ROS, and apoptotic signaling pathways in ARL3T31A/C118F cells. Our study demonstrated that ARL3‐related mutations play a significant role in the diversity of mitochondrial function, providing novel insights into the functional analysis of ARL3‐related mutations. [ABSTRACT FROM AUTHOR]

Different types of weather events, including tropical cyclones (TCs), mesoscale convective systems (MCSs), and atmospheric rivers (ARs), significantly impact precipitation patterns in East Asia. This study pioneers the application of deep learning (DL) methods, including convolutional neural network, U‐Net, and Attention U‐Net models, to simulate precipitation associated with these weather events. The spatial permutation method is also used to identify key meteorological variables for accurately generating precipitation in DL models. The DL models trained on all timeslots consistently surpass the performance of state‐of‐the‐art numerical simulations, although their efficacy slightly diminishes during extreme weather events. This outperformance is attributed to the appropriate emphasis on key variables that capture precipitation processes, such as low‐level moisture and mid‐level pressure fields. However, new DL models trained separately for TCs, MCSs, and ARs using clipped precipitation as the output does not exceed the performance of the previous DL models. Among all input features, moisture variables contribute the most to precipitation at low intensity, while the importance of other variables increases for more intense precipitation, although some discrepancies vary across models and event types. The spatial results further reveal the detailed locations of variables that are essential for accurately simulating precipitation related to weather events, such as areas of high specific humidity and strong winds. DL models could also acquire useful information from region remote to the events to improve the simulation. Overall, DL models serve as promising tools for simulating and enhancing our understanding of precipitation patterns associated with various weather events in East Asia. Plain Language Summary: Different types of weather events, including tropical cyclones (TCs), mesoscale convective systems (MCSs), and atmospheric rivers (ARs), produce a lot of precipitation in East Asia. In this study, we first use deep learning (DL) models to simulate precipitation associated with these weather events. We find that these models are consistently better than numerical simulations. However, the performance of DL models slightly diminishes during extreme weather events. The success of the DL models can be attributed to their ability to focus on key variables, such as low‐level moisture and mid‐level pressure fields. We also develop new DL models tailored for TCs, MCSs, and ARs with their associated precipitation as the output. Unexpectedly, these models do not perform better than the previous DL models. Among all the features, moisture variables contribute the most to low‐intensity precipitation, whereas other variables become more important for more intense precipitation. We find the important locations of key variables for accurate simulation, such as areas with high specific humidity and strong winds. DL models can also utilize nonlocal information from weather events to enhance their performance. Therefore, DL models are promising in generating precipitation associated with different weather events in East Asia. Key Points: Deep learning (DL) models surpass numerical models in simulating precipitation associated with different weather events in East AsiaDL models trained for different weather event types exhibit inferior performance compared to DL models trained on all timeslotsDL models effectively utilize information from meteorological variables, particularly moisture, to achieve strong performance [ABSTRACT FROM AUTHOR]

Henan Province, a significant cultural heritage province in China, has abundant tangible cultural heritage resources distributed across the region. Watersheds are the fundamental geographical units that have consistently supported human production and subsistence activities from ancient times to the present. Analyzing the spatial distribution characteristics and influencing factors of tangible cultural heritage resources of the watersheds in Henan Province is of great importance for its macro-level preservation, value promotion, and sustainable development. This research focuses on the 421 major historical and cultural sites protected at the national level in Henan Province, utilizing GIS spatial analysis techniques such as kernel density estimation, nearest neighbor index, Thiessen polygons, spatial auto-correlation analysis, and geographically weighted regression to investigate the spatial distribution characteristics and influencing factors of tangible cultural heritage across different watersheds in the province. The results indicate the following: (1) The cultural heritage sites in Henan Province exhibit an overall clustered distribution. Within specific watersheds, such as the Jindihe River, Huaihe River, and Baihe River, the cultural heritage distribution is relatively sparse, displaying a random distribution pattern. (2) The cultural heritage distribution forms two high-density centers and one high-density distribution belt, exhibiting a tendency to align along lower-grade rivers. (3) The distribution of cultural heritage shows significant spatial auto-correlation, with high-value areas (hotspots) concentrated at the watershed intersections of the Yiluohe River, Weihe River, and Yinghe River. (4) Elevation, precipitation, GDP from the tertiary sector, museum density, and proximity to the nearest historical and cultural cities are the primary factors influencing the spatial differentiation of cultural heritage within each watershed. Moreover, there is significant spatial heterogeneity between different watersheds. Lastly, specific strategies for the sustainable preservation and utilization of cultural heritage in Henan Province are proposed, including differentiated preservation approaches, strengthening the preservation of water-related cultural heritage, promoting sustainable cultural tourism development, and establishing mechanisms for cross-regional cooperation. [ABSTRACT FROM AUTHOR]

This study examines the remote influence of the Tibetan Plateau (TP) diabatic heating on atmospheric river (AR) activity in the North Pacific. First, we identify a sensitive heating region on the southern TP establishing a positive correlation between its heating and AR frequency. This correlation is attributed to latent heat release supported by a substantial moisture supply. Further analysis reveals that the dynamic effect of the eastward-propagating Rossby waves, originating from the Atlantic Ocean and modulated by the TP, facilitates upward moisture lifting. Using the Water Accounting Model-2Layers, we demonstrate that this anomalous heating is primarily due to increased moisture from the Indian Ocean, the Arabian Sea, and the Bay of Bengal, amplified by the westward extension of the western North Pacific subtropical high (WNPSH). Additional moisture contributions are observed from Eurasia. Moreover, Rossby wave activity over the TP propagates to the east of Japan, enhancing westerlies with upper-level divergence field which develops a cyclonic and anticyclonic vortex structure. This structure attracts abundant moisture to the North Pacific, thereby increasing AR activity. This study also highlights a positive feedback mechanism involving the southern TP heating and the eastward-propagating upper-level anticyclone, which enhance the western extension of the WNPSH. These findings underscore the global climatic impacts of the TP, emphasizing its role as a critical factor in AR dynamics across the North Pacific. Significance Statement: This study explores the remote impact of the Tibetan Plateau (TP) heating on the atmospheric river (AR) in the North Pacific. Our findings indicate that southern TP heating resulting from remote moisture contribution, quantitatively assessed using Water Accounting Model-2Layers, coupled with the western extension of the western North Pacific subtropical high (WNPSH) and sea surface temperature warming anomaly as well as the eastward-propagating Rossby waves derived from the Atlantic Ocean, plays a crucial role in AR activity in the North Pacific. TP heating affects Rossby waves propagating east of Japan enhancing the westerlies and the easterlies. Moreover, the coupled divergence and cyclonic vortex structures attract more moisture toward the North Pacific fostering AR activity. Additionally, the interplay between southern TP heating and WNPSH builds a positive feedback mechanism. [ABSTRACT FROM AUTHOR]

Aerogels with tailored geometric features and improved mechanical properties are urgently needed for thermal insulation applications in specific scenarios. However, traditional manufacturing strategies show limitations in the on-demand shaping of aerogels due to their costly and time-consuming fabrication cycles and poor serious impediment fragility. Herein, the ultraviolet (UV)-assisted extrusion printing strategy has been adopted to fabricate photosensitive resin-crosslinked silica (PRCS) aerogel composites. During extrusion printing, there is a synergic process of consecutive ink extrusion deposition and instantaneous photopolymerization of photosensitive resins, displaying a considerable characteristic of solidification-while-printing. The successful implementation for the UV-assisted extrusion printing of PRCS aerogel composites depends on the viscoelasticity and photosensitivity of inks, where the viscoelasticity enables inks to smoothly flow from nozzles and the photosensitivity allows inks to solidify rapidly based on the radical polymerization of photosensitive resin monomers. The UV-assisted extrusion printing strategy has a huge capacity for the rapid manufacturing of aerogel geometries without an additional auxiliary support. After supercritical drying, the 3D-printed PRCS aerogel composites exhibit high shape fidelity and comparable aerogel performances, such as low density (0.256 g·cm–3), high specific surface area (269.3 m2·g–1), high pore volume (1.82 cm3·g–1), improved mechanical properties (compressive strength up to 0.28 MPa), and low thermal conductivity (38.41 mW·m–1·K–1). This work would provide more potential for silica aerogels to satisfy the requirements of shape-dominated insulation applications in specific scenarios. [ABSTRACT FROM AUTHOR]

Purpose: To explore the effect of solid waste material and high-sulfur tailings with potential cementing activity around the mine on the strength of cemented backfill and filling slurry,and reveal the excitation mechanism of high-sulfur tailings composite backfill material. Method:Through uniaxial compressive test and SKM/EDS test,the compressive strength, failure mode, and microstructure of backfill samples with different proportions were analyzed. Result;The results show that compared with 100%cement,the 7 d strength of the 3 : 7 or 4 : 6 cemented backfill samples with tailing sand and Gobi aggregate is improved when quicklime is used as the activator. When the proportion of tailing sand and Gobi aggregate is the same, the mechanical strength of cemented backfill gradually decreases with the increase of lime content,and the optimal lime content is 10%. Appropriate increase of slag powder content is conducive to the improvement of mechanical strength. Through microstructure analysis,a large number of fibrous C-S-H and acicular ettringite( Aft) were generated inside the hydration reaction specimen. The main elements in the backfill sample were O, C, Si, Ca, Al, and Mg. Conclusion; It is feasible to replace cement with solid waste. Significance;The research results can provide the theoretical and technical basis for the application of solid waste materials under different requirements of filling technology. [ABSTRACT FROM AUTHOR]

The formal beauty of "objects" is the main focus of modern rural landscapes, ignoring human interaction with the environment and the emotional reflection in this behavioral process. It is unable to satisfy the emotional needs of younger people who aspire to a high-quality life in the rural environment. The research idea of this paper is 'first assessment—then design—then validation'. First, A 5-point Likert scale was used to investigate differences in contemporary young people's emotional perceptions of the four rural natural landscapes in terms of instinct, behavior, and reflection. Then, using architectural design methods, a visual attraction element (viewing platform) was added by selecting samples that varied in all three dimensions (visual richness, behavioral attraction, and depth of thought). After that, a desktop eye tracker was used to record the eyeball characteristics of participants viewing the current images of natural landscapes and images of modified natural landscapes (pupil diameter, fixation duration, gaze point, etc.), and these data were combined with the subjective psychological perception scale score to determine whether or not the subjects' positive emotions are evoked by the modified natural environment. The findings indicate that placing visually attractive elements between people and the natural world can cause subjects to feel good, think deeply, and feel more a part of the surroundings. Furthermore, we confirmed that subjects' emotions can be evoked by 2D natural environment pictures and that the length of time subjects gaze at a picture is unaffected by the size of any individual element. [ABSTRACT FROM AUTHOR]