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Underwater images collected are often of low clarity and suffer from severe color distortion due to the marine environment and Illumination conditions. This directly impacts tasks such as marine ecological monitoring and underwater target detection, which rely on image processing. Therefore, enhancing Underwater images to improve their quality is necessary. A generative adversarial network with an encoder-decoder structure is proposed to improve the quality of Underwater images. The network consists of a generative network and an adversarial network. The generative network is responsible for enhancing the images, while the adversarial network determines whether the input is an enhanced image or a real high-quality image. In the generative network, we first design a residual convolution module to extract more texture and edge information from underwater images. Next, we design a multi-scale dilated convolution module to capture underwater features at different scales. Then, we design a feature fusion adaptive attention module to reduce the interference of redundant features and enhance the local perception capabilities. Finally, we construct the generative network using these modules along with conventional modules. In the adversarial network, we first design a multi-scale feature extraction module to improve the feature extraction ability. We then use the multi-scale feature extraction module along with conventional convolution modules to design the adversarial network. Additionally, we propose an improved loss function by introducing color loss into the conventional loss function. The improved loss function can better measure the color discrepancy between the enhanced image and the real image. It is useful to reduce color distortion in the enhanced images. In experimental simulations, the images enhanced by the proposed methods have the highest PSNR, SSIM, and UIQM values, indicating that the proposed method has superior Underwater image enhancement capabilities compared to other methods.

The energy loss induced open‐circuit voltage (VOC) deficit hampers the rapid development of state‐of‐the‐art organic solar cells (OSCs), therefore, it is extremely urgent to explore effective strategies to address this issue. Herein, a new volatile solid additive 1,4‐bis(iodomethyl)cyclohexane (DIMCH) featured with concentrated electrostatic potential distribution is utilized to act as a morphology‐directing guest to reduce energy loss in multiple state‐of‐art blend system, leading to one of highest efficiency (18.8%) at the forefront of reported binary OSCs. Volatile DIMCH decreases radiative/non‐radiative recombination induced energy loss (ΔE2/ΔE3) by rationally balancing the crystallinity of donors and acceptors and realizing homogeneous network structure of crystal domain with reduced D–A phase separation during the film formation process and weakens energy disorder and trap density in OSCs. It is believed that this study brings not only a profound understanding of emerging volatile solid additives but also a new hope to further reduce energy loss and improve the performance of OSCs. The greatly reduced energy loss assisted by volatile solid additive 1,4‐bis(iodomethyl)cyclohexane (DIMCH) is demonstrated, and the role of DIMCH in weakening the disparity of imbalanced crystallinity of donor and acceptor, and reducing the energy disorder and trap density is unveiled, and its function to achieve forefront power conversion efficiency of 18.8% for binary organic solar cells.

As a prevalent geological hazard in underground engineering, the accurate prediction of mine earthquakes is crucial for ensuring operational safety and enhancing mining efficiency. The deformation localization method effectively predicts the instability of disaster rocks, yet the timing of mine earthquakes remains understudied. This study established a correlation between rock deformation localization and seismic activity within mines through theoretical derivations. A predictive model algorithm for forecasting mine earthquake timing was developed based on Saito’s theory, integrating optics, acoustics, and mathematical modeling theories. The “quiet period” was identified as a significant precursor; thus, the model used the initiation of deformation localization to accurately predict rock failure. Using the model, a coal mine in Inner Mongolia was selected as a case study to predict a historical mining earthquake. The results indicated that the following: (1) Deformation localization and the “quiet period” of microseismic (MS) and acoustic emission (AE) activities were identified as two key pre-cursory indicators. The model utilized the initiation time of deformation localization and the inflection point of the “quiet period” in MS and AE activity as primary parameters. (2) For predicting rock failure times, the earliest prediction time deviates from the actual failure time by 143 s. The accuracy rate of predicted time points falling within a 90% confidence interval of the actual failure times is 100%. The model achieved 60% in forecasting the occurrence times of mine earthquakes. (3) The model’s prediction accuracy improved as the starting time parameter more closely approximated the actual initiation time of deformation localization, with the accuracy increasing from 0% to 100%.

Annual herbaceous plants are frequently layered under the artificial sand-fixing forest within the desert oasis transition zone of the Hexi Corridor. The effect of drought stress on annual herbaceous plants is of great significance to the restoration of artificial vegetation as well as the stability of the ecosystem in the desert oasis transition zone. Setaria viridis, Chloris virgata, Halogeton arachnoideus, and Bassia dasyphylla are the typical annual herbaceous plants that occur naturally in the Caragana korshinskii forest and were used as the research subject in this study. Concentration gradient tests were conducted under different mixed growth conditions: 0 (blank control group), 5, 10, and 15 C. korshinskii seeds, and different drought stress conditions: 0%, 2%, 5%, 10%, and 15%, in order to explore the interactive effects of drought stress on annual herbaceous plants. The results demonstrated that the germination percentage and germination rate of annual herbaceous plants was significantly affected by the number of C. korshinskii seeds (p < 0.05), whereby the germination effect was optimal when no C. korshinskii seeds were present. Furthermore, we found that the germination percentage and germination rate of the annual Gramineae was higher than that of the Chenopods. In the growth stage, the biomass and root-shoot ratio of the chenopods were significantly affected by the number of C. korshinskii seeds and drought stress (p < 0.05). We found that the biomass of annual herbaceous plants was the highest at 2% drought stress, and the root-shoot ratio displayed a positive correlation with an increase in drought stress. Notably, the survival rate of annual herbaceous plants was higher when grown in combination with five C. korshinskii seeds, thus indicating a positive interaction; in contrast, the survival rate decreased significantly when they were grown in combination with more than five C. korshinskii seeds, indicating a negative interaction. We observed a decreasing trend in root activity and chlorophyll content when annual herbaceous plants were grown in combination with an increasing number of C. korshinskii seeds and drought stress. The reduced root activity and decline in photosynthetic ability resulted in the inhibition of seedling growth. Furthermore, we found that the root activity and chlorophyll content of the Gramineae was ~1.3–2.0 times higher than that of the Chenopods, which may be the reason behind the lower survival rate of the chenopods.

The use of simulation and reinforcement learning can be viewed as a flexible approach to aid managerial decision-making, particularly in the face of growing complexity in manufacturing and logistic systems. Efficient supply chains heavily rely on steamlined warehouse operations, and therefore, having a well-informed storage location assignment policy is crucial for their improvement. The traditional methods found in the literature for tackling the storage location assignment problem have certain drawbacks, including the omission of stochastic process variability or the neglect of interaction between various warehouse workers. In this context, we explore the possibilities of combining simulation with reinforcement learning to develop effective mechanisms that allow for the quick acquisition of information about a complex environment, the processing of that information, and then the decision-making about the best storage location assignment. In order to test these concepts, we will make use of the FlexSim commercial simulator.

The water diversion scheme of Heihe River Basin was implemented in 2000. Herein, we investigated the dynamic changes in soil moisture content and analyzed the fundamental reasons supporting the water diversion plan in this typical inland river basin in northwest China. Accordingly, we selected three typical landscape gradients—a mountain water conservation forest belt, an artificial sand-fixing forest belt at the edge of a desert oasis, and a desert riparian forest belt in the upper, middle, and lower reaches of the Heihe River Basin, respectively. In these diverse landscapes, an environmental measuring system was used to continuously monitor the dynamic and differentiation regularity of soil moisture in the 0–160 cm layer for 5 years. The results revealed that 1) the soil moisture content in each landscape increased and varied significantly across seasons. In the upper and middle reaches, the soil moisture content was significantly higher during the growing season than in the non-growing season, whereas the lower reach displayed a converse pattern. 2) The distribution of soil moisture at various depths of soil profiles varied significantly for each landscape. As the soil depth increased, the soil moisture in the upper reach decreased. Although the deep layers (120–160 cm) could store water in the non-growing season, the stored water was consumed during the growing season. The soil moisture content in the mid-reach initially increased, later decreased, and ultimately attained its highest level at 40–60 cm; however, the soil moisture content in the lower reach increased, and reached its highest level at 120–160 cm. 3) In the upper and middle reaches, the coefficient of variation of soil moisture decreased with an increasing soil depth, whereas the lower reach exhibited a converse trend. Similarly, the coefficient of variation of soil water storage were higher during the non-growing season than during the growing season within the upper and middle reaches, whereas an opposite trend was observed in the lower reach. 4) Since the implementation of the Heihe river water diversion plan, the soil moisture content in both the upper and middle reaches have increased but that of the lower reach has fluctuated and declined, especially in the shallow depths during the growing season. The present findings imply that the lower reaches of the Heihe River may require additional water transfers during the growing season.

The popularity of blockchain technology stems largely from its association with cryptocurrencies, but its potential applications extend beyond this. Fungible tokens, which are interchangeable, can facilitate value transactions, while smart contracts using non-fungible tokens enable the exchange of digital assets. Utilizing blockchain technology, tokenized platforms can create virtual markets that operate without the need for a central authority. In principle, blockchain technology provides these markets with a high degree of security, trustworthiness, and dependability. This article surveys recent developments in these areas, including examples of architectures, designs, challenges, and best practices (case studies) for the design and implementation of tokenized platforms for exchanging digital assets.

The future applications of organic solar cells (OSCs) necessitate a thorough consideration of their ambient stability and processability, particularly for large area air‐processed engineering, but water‐induced degradation of active layer critically restricts its development. To surmount this hurdle, a water‐obstructing guest (WOG) strategy is proposed to attenuate the interaction of the active layer with water molecules, reduce defects in blend films, and enhance the devices stability under high relative humidity (RH) conditions by introducing a siloxane‐containing polymer D18‐SiO. In addition to suppressing trap density, the WOG with hydrophobic and low surface free energy characteristics, forms a capping layer that blocks moisture penetration while preserving ideal nano‐micromorphology with high crystallinity and tight packing properties. Power conversion efficiencies (PCE) of >19% is reported for spin coating OSCs fabricated across an RH range of 20 to 90%, and PCE of >17% blade coating OSCs at 90% RH. The D18‐SiO, serves as a protective barrier to enhance the device stability, and the corresponding unencapsulated OSCs retained 80.7% of its initial performance in air (≈ 40% RH) after 600‐h maximum power point tracking under continuous light illumination, showcasing great potential in designing WOG strategy for large‐scale production of air‐processed OSCs. The Water‐obstructing Guest (WOG) strategy, employing a siloxane decorated polymer D18‐SiO as a capping layer, is proposed to minimize moisture penetration while preserving original morphology and suppresing trap density in high humidity condition. WOG‐based Organic solar cells, fabricated at 90% relative humidity (RH), achieved a power conversion efficiency (PCE) of 19.1% with excellent stability.

In the context of increasing complexity in manufacturing and logistic systems, the combination of optimization and simulation can be considered a versatile tool for supporting managerial decision-making. An informed storage location assignment policy is key for improving warehouse operations, which play a vital role in the efficiency of supply chains. Traditional approaches in the literature to solve the storage location assignment problem present some limitations, such as excluding the stochastic variability of processes or the interaction among different warehouse activities. This work addresses those limitations by proposing a discrete-event simheuristic framework that ensures robust solutions in the face of real-life warehouse conditions. The approach followed embraces the complexity of the problem by integrating the order sequence and picking route in the solution construction and uses commercial simulation software to reduce the impact of stochastic events on the quality of the solution. The implementation of this type of novel methodology within a warehouse management system can enhance warehouse efficiency without requiring an increase in automation level. The method developed is tested under a number of computational experiments that show its convenience and point toward future lines of research.

Exciton binding energy (Eb) has been regarded as a critical parameter in charge separation during photovoltaic conversion. Minimizing the Eb of the photovoltaic materials can facilitate the exciton dissociation in low‐driving force organic solar cells (OSCs) and thus improve the power conversion efficiency (PCE); nevertheless, diminishing the Eb with deliberate design principles remains a significant challenge. Herein, bulky side chain as steric hindrance structure was inserted into Y‐series acceptors to minimize the Eb by modulating the intra‐ and intermolecular interaction. Theoretical and experimental results indicate that steric hindrance‐induced optimal intra‐ and intermolecular interaction can enhance molecular polarizability, promote electronic orbital overlap between molecules, and facilitate delocalized charge transfer pathways, thereby resulting in a low Eb. The conspicuously reduced Eb obtained in Y‐ChC5 with pinpoint steric hindrance modulation can minimize the detrimental effects on exciton dissociation in low‐driving‐force OSCs, achieving a remarkable PCE of 19.1% with over 95% internal quantum efficiency. Our study provides a new molecular design rationale to reduce the Eb. An effective method for reducing the exciton binding energy (Eb) of Y‐series molecules by manipulating both intra‐ and intermolecular interaction was demonstrated through a joint experimental and theoretical investigation. The significantly decreased Eb obtained in Y‐ChC5 via meticulous adjustment of steric hindrance can still facilitate effective exciton dissociation and charge generation under small interfacial energy offsets in organic solar cells.