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With advancements in integrated space–air–ground global observation capabilities, the volume of remote sensing data is experiencing exponential growth. Traditional computing models can no longer meet the task processing demands brought about by the vast amounts of remote sensing data. As an important means of processing remote sensing data, distributed cluster computing's task scheduling directly impacts the completion time and the efficiency of computing resource utilization. To enhance task processing efficiency and optimize the allocation of computing resources, this study proposes a Multi-Strategy Improved Siberian Tiger Optimization (MSSTO) algorithm based on the original Siberian Tiger Optimization (STO) algorithm. The MSSTO algorithm integrates the Tent chaotic map, the Lévy flight strategy, Cauchy mutation, and a learning strategy, showing significant advantages in convergence speed and global optimal solution search compared to the STO algorithm. By combining stochastic key encoding schemes and uniform allocation encoding schemes, taking the task scheduling of aerosol optical depth retrieval as a case study, the research results show that the MSSTO algorithm significantly shortens the completion time (21% shorter compared to the original STO algorithm and an average of 15% shorter compared to nine advanced algorithms, such as a particle swarm algorithm and a gray wolf algorithm). It demonstrates superior solution accuracy and convergence speed over various competing algorithms, achieving the optimal execution sequence and machine allocation scheme for task scheduling. [ABSTRACT FROM AUTHOR]

The Muri region of Qinghai Province is not only the source of important water sources, but also one of the key areas targeted by the ecological environment restoration project. The study of the Net ecosystem productivity (NEP) of grassland in the Muri region is of great importance in order to gain insight into the health of grassland ecosystems and to assess the carbon sink capacity. In this study, the net primary productivity (NPP) and NEP of the grassland in the Muri region from 2000 to 2022 were calculated using remote sensing data, meteorological data and land cover data, coupled with Carnegie-Ames-Stanford Approach (CASA) model and soil heterotrophic respiration model. The spatial and temporal patterns of NEP of grassland ecosystems over different periods from 2000 to 2022 were assessed following accuracy tests. The drivers affecting the spatial and temporal changes in NEP of grasslands in the Muri region were then explored with the help of Geogdetector. The study indicated that: (1) From 2000 to 2022, the mean annual NEP of grassland in the Muri region was 138.23 gC/m², exhibiting a significant increasing trend (p < 0.01). (2) Spatially, the NEP of grassland showed a pattern of distribution from south-east to north-west, from the center to either side and from high to low values, with 91.58% of grassland showing an increasing trend in all growth periods. (3) Climatic factors, altitude and slope are important drivers of changes in the NEP of grassland, with altitude being the most important factor influencing the NEP of grassland in this region. This study can provide valuable references for assessing the carbon sequestration capacity of grassland ecosystems and monitoring the health of grassland ecosystems in the Muri region, as well as for formulating future ecological protection policies and directions in the Muri region. [ABSTRACT FROM AUTHOR]

CsPbI3 perovskite nanocrystals are a promising optoelectronic material when stabilized in their cubic phase. While ongoing efforts have addressed this structural challenge through a variety of meta-stabilization approaches, the postsynthesis purification of these nanocrystal dispersions has remained a challenge. In this article, we undertake a detailed investigation into the chemical, optical, and structural changes that arise during purification of CsPbI3 nanocrystals. It is found that nanocrystal degradation can only be avoided through the judicious control of additives within each purification cycle. Under optimized additive-to-nanocrystal ratios, multiple purification cycles can be readily achieved, while retaining the quality and phase stability of the CsPbI3. This facile purification protocol ensures the preparation of high purity and high quality CsPbI3 nanocrystal inks that are suitable for better characterization or integration in optoelectronic devices. The approach has been generalized for CsPbX3 (X = Cl−, Br−, and I−). [ABSTRACT FROM AUTHOR]

The effectiveness of landslide disaster prevention depends largely on the quality of early identification of potential hazards, and how to comprehensively, deeply, and accurately identify such hazards has become a major difficulty in landslide disaster management. Existing deep learning methods for potential landslide hazard identification often use fixed-size window modeling and ignore the different window sizes required by landslides of different scales. To address this problem, we propose an adaptive identification method for potential landslide hazards based on multisource data. Taking Yongping County, China, as the study area, we create a multisource factor dataset based on the landslide disaster background in terms of topography, geology, human activities, hydrology, and vegetation as the sample for the identification model after processing. Moreover, we combine differential interferometric synthetic aperture radar (D-InSAR) and multitemporal InSAR (MT-InSAR) to process the surface deformation of the study area, and we measure the deformation richness based on the average of the pixel deformation difference within the current window of a pixel point in the image. Therefore, convolutional neural networks (CNNs) with different window sizes are adaptively selected. The results show that the precision of adaptive identification of potential landslide hazards in the study area is 85.30%, the recall is 83.03%, and the F1 score is 84.15%. The recognition rate for potential hazards reaches 80%, which is better than the fixed-window modeling result and proves the effectiveness of the proposed method. This method can help to improve intelligent identification systems for potential landslide hazards, and also contribute to the identification of other potential geological hazards, such as mudslides and collapses. [ABSTRACT FROM AUTHOR]

The excellent optoelectronic properties and structural stability of inorganic cesium lead halide perovskites make them promising candidates for multiple types of optoelectronic devices. However, it remains a challenge to fabricate monocrystalline phase‐pure perovskite microstructures by facile low‐temperature solution‐based methods. Herein, a solution‐based method is demonstrated for controlling the crystallization of cesium halide perovskite microstructures. The structure of perovskite crystals is successfully tuned from non‐corner sharing Cs4PbBr6 (0D) to corner‐sharing CsPbBr3 (3D) to layered CsPb2Br5 (2D) by controlling water (H2O) to dimethylsulfoxide (DMSO) ratios. Molecular dynamics simulations and thermodynamic analysis indicate that the relative stability of Pb2+ and Br− ions in solution is the key factor in determining which crystals form at different H2O/DMSO ratios, with Cs+ simply incorporated as needed. The phase‐pure 0D crystals exhibit a high photoluminescence quantum yield of 41%, whilst the 2D crystals have an onset of absorption at 350 nm. Furthermore, the as‐synthesized, highly uniform 3D perovskite single crystals are coupled with nanofabricated interdigitated electrodes to show excellent X‐ray detection, with a high sensitivity of 8000 μC Gyair−1cm−2 obtained under a 0.5V external bias. This is comparable to many commercial X‐ray detectors (Si, α‐Se) and several times higher than other reported inorganic perovskite materials (CsPbBr3 quantum dots, Cs2AgBiBr6). [ABSTRACT FROM AUTHOR]

The rapid nucleation and growth dynamics of metal halide perovskite nanocrystals (PNCs) present major challenges in controlling their ensemble evolution and scaling using typical batch syntheses. Continuous flow approaches are an alternative scalable and high-throughput process that can address these limitations by enabling rapid mixing and more precise control of reaction profiles. In this work, we use an acoustically actuated mixer within a continuous microfluidic (MF) platform to study the effect of precursor mixing rate on the synthesis of CsPbBr3 PNCs using the ligand assisted reprecipitation (LARP) approach. It is found that near complete mixing can be achieved at <23 ms timescales under highly efficient acoustic mixing. This enables superior control of the nanocrystal formation stages compared to both non-actuated MF and the standard batch LARP syntheses, which can take more than 2 s to achieve complete mixing with magnetic stirring. Through the study of the temporal evolution of the optical properties in the MF system, it is further found that nanoplatelet formation dominates during early reaction times <200 ms, which subsequently transform into nanocuboids. This complex colloidal evolution of PNCs further validates the need to achieve mixing at the millisecond timescale to afford structurally controlled PNCs with minimal polydispersity. [ABSTRACT FROM AUTHOR]

Color-conversion films (CCFs) were fabricated with CuInS2/ZnS quantum dot (QD)-embedded polymer nanofibers and applied for white color emission with blue light-emitting diodes (LEDs). Red-orange color emitting CuInS2/ZnS QDs were synthesized and a photoluminescence quantum yield (PL QY) of 75% was achieved by controlling the Cu : In ratio in the QDs as well as the ZnS shell thickness. QD-embedded polystyrene nanofibers were electrospun on conducting aluminium substrates. The QD-embedded nanofiber (QDEN) structure is believed to reduce the aggregation of the QDs compared to that in a thin-film polymer. Time-resolved photoluminescence (TRPL) analysis showed a longer PL lifetime (138 ns) with the QDEN film than with a mould-cast thin film (45 ns). The longer PL lifetime with the QDEN structure is attributed to decreased quenching due to reduced aggregation. For the white lighting device, the QDEN films were applied as CCFs on a light guide plate (4.3 inch) with a GaN blue LED source. The resulting device demonstrated increased efficiency (from 11.5 to 32.3 lm W−1) and color rendering index values (from 71 to 91) compared to commercial white LEDs. These Cd-free QD-embedded nanofiber films are expected to provide efficient and safe solutions for large-area processing of lighting devices. [ABSTRACT FROM AUTHOR]