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Under the trend in climate change, global warming, and the increasingly serious urban heat island effect, promoting urban wind corridor planning to reduce urban temperature and mitigate the effect of urban heat islands has received widespread attention in many cities. With emerging awareness of the need to explicitly incorporate climate considerations into urban planning and design, integrating current spatial analysis and simulation tools to enhance urban wind corridor planning to obtain the best urban ventilation effect has become an increasingly important research topic in green city development. However, how to systematically carry out urban wind corridor planning by employing related technology and simulation tools is a topic that needs to be explored urgently in both theory and practice. Taking Zhumadian City in China as an example, this study proposes a method and planning approach that uses remote sensing (RS), geographic information system (GIS), and computational fluid dynamics (CFD) in an integrated way to understand urban landscape and to conduct urban wind corridor planning. The research results reveal that the urban form of Zhumadian City favors the development of urban wind corridors, and that the railway lines and some major roads in the city have the potential to be developed as the city's main wind corridors. However, there are still ventilation barriers resulting from the existing land use model and building layout patterns that need to be adjusted. In terms of local-level analysis, the CFD simulation analysis also reveals that some common building layout patterns may result in environments with poor ventilation. Finally, based on the results of our empirical analysis and local planning environment, specific suggestions are provided on how to develop appropriate strategies for urban wind corridor planning and adjustments related to land use planning and building layout patterns in order to mitigate the impact of the urban heat island effect. [ABSTRACT FROM AUTHOR]

Salmonella is responsible for the majority of food poisoning outbreaks around the world. Pathogenic Salmonella mostly carries a virulence plasmid that contains the Salmonella plasmid virulence gene (spv), a highly conserved sequence encoding effector proteins that can manipulate host cells. Intestinal epithelial cells are crucial components of the innate immune system, acting as the first barrier of defense against infection. When the barrier is breached, Salmonella encounters the underlying macrophages in lamina propria, triggering inflammation and engaging in combat with immune cells recruited by inflammatory factors. Host regulated cell death (RCD) provides a variety of means to fight against or favour Salmonella infection. However, Salmonella releases effector proteins to regulate RCD, evading host immune killing and neutralizing host antimicrobial effects. This review provides an overview of pathogen-host interactions in terms of (1) pathogenicity of Salmonella spv on intestinal epithelial cells and macrophages, (2) mechanisms of host RCD to limit or promote pathogenic Salmonella expansion, and (3) effects and mechanisms of Salmonella spv gene on host RCD. [ABSTRACT FROM AUTHOR]

Auricularia auricula polysaccharides used in Pinus koraiensis polyphenol encapsulation and delivery under weightlessness are rarely reported. In this study, an anionic polysaccharide fragment named AAP Iα with a molecular weight of 133.304 kDa was isolated and purified to construct a polyphenol encapsulation system. Nanoparticles named NPs-PP loaded with a rough surface for Pinus koraiensis polyphenol (PP) delivery were fabricated by AAP Iα and ε-poly-L-lysine (ε-PL). SEM and the DLS tracking method were used to observe continuous changes in AAP Iα, ε-PL and PP on the nanoparticles' rough surface assembly, as well as the dispersion and stability. Hydrophilic, monodisperse and highly negative charged nanoparticles can be formed at AAP Iα 0.8 mg/mL, ε-PL 20 μg/mL and PP 80 μg/mL. FT-IR was used to determine their electrostatic interactions. Release kinetic studies showed that nanoparticles had an ideal gastrointestinal delivery effect. NPs-PP loaded were assembled through electrostatic interactions between polyelectrolytes after hydrogen bonding formation in PP-AAP Iα and PP-ε-PL, respectively. Colon adhesion properties and PP delivery in vivo of nanoparticles showed that NPs-PP loaded had high adhesion efficiency to the colonic mucosa under simulated microgravity and could enhance PP bioavailability. These results suggest that AAP Iα can be used in PP encapsulation and delivery under microgravity in astronaut food additives. [ABSTRACT FROM AUTHOR]

High-resolution (HR) MR images provide rich structural detail to assist physicians in clinical diagnosis and treatment plan. However, it is arduous to acquire HR MRI due to equipment limitations, scanning time or patient comfort. Instead, HR MRI could be obtained through a number of computer assisted post-processing methods that have proven to be effective and reliable. This paper aims to develop a convolutional neural network (CNN) based super-resolution reconstruction framework for low-resolution (LR) T2w images. In this paper, we propose a novel multi-modal HR MRI generation framework based on deep learning techniques. Specifically, we construct a CNN based on multi-resolution analysis to learn an end-to-end mapping between LR T2w and HR T2w, where HR T1w is fed into the network to offer detailed a priori information to help generate HR T2w. Furthermore, a low-frequency filtering module is introduced to filter out the interference from HR-T1w during high-frequency information extraction. Based on the idea of multi-resolution analysis, detailed features extracted from HR T1w and LR T2w are fused at two scales in the network and then HR T2w is reconstructed by upsampling and dense connectivity module. Extensive quantitative and qualitative evaluations demonstrate that the proposed method enhances the recovered HR T2w details and outperforms other state-of-the-art methods. In addition, the experimental results also suggest that our network has a lightweight structure and favorable generalization performance. The results show that the proposed method is capable of reconstructing HR T2w with higher accuracy. Meanwhile, the super-resolution reconstruction results on other dataset illustrate the excellent generalization ability of the method. [ABSTRACT FROM AUTHOR]

Functional motivations are closely linked to important volunteer outcomes, yet more socio-political forms of civic participation (CP) besides volunteering are growing. There is little attention on the applicability of functional motivations to such CP, including in disasters. Using a critical realist grounded theory methodology, 39 in-depth interviews were conducted with Singapore residents who had engaged in a diverse range of CP before and during COVID-19. A key mechanism, fulfilling personal functions, was found to relate to functional motivations. Overlapping functions were found, but there are differences in how these functions were fulfilled depending on the form of CP. Perceived accessibility, the subjective mental state about one’s potential to engage, mediated the effectuation of motivations in actual engagement. COVID-19 contributed to emergent CP by increasing perceived accessibility. Participating citizens pre-COVID-19 made adaptations to maintain perceived accessibility to continue CP during the pandemic. These theoretical developments inform policy and research agenda in understanding and leveraging CP. [ABSTRACT FROM AUTHOR]

Vehicle detection is an important component of intelligent transportation systems and autonomous driving. However, in real-world vehicle detection scenarios, the presence of many complex and high uncertainty factors, such as illumination differences, motion blur, occlusion, weather, etc., makes accurate and real-time vehicle detection still challenging. In order to reduce the influence of these uncertainties in real scenarios and improve the accuracy and real-time performance of vehicle detection, this paper proposes a type-1 fuzzy attention (T1FA), in which fuzzy entropy is introduced to re-weight the feature map in order to reduce the uncertainty of the feature map and facilitates the detector's focus on the target center as a way to effectively improve the accuracy of vehicle detection. Furthermore, to detect vehicles with different sizes more effectively, mixed depth convolution in MetaFormer (MDFormer) is employed as a token mixer to capture multi-scale perceptual fields. And a novel YOLO detector based on fuzzy attention (YOLO-FA) is proposed. Experimental results show that T1FA can boost 3.2% AP50 on challenging vehicle detection dataset UA-DETRAC, which is better than other commonly used attention mechanisms, especially in scenarios of rain and nighttime with higher uncertainty by 4.2% and 8.1% AP50, respectively. Finally, without pretraining on extra data, YOLO-FA achieves 70.0% AP50 and 50.3% AP on UA-DETRAC, which achieves better balance between accuracy and speed compared with state-of-the-art detectors. The remarkable improvement of T1FA in different detectors and datasets also shows the considerable generalization of T1FA. • A type-1 fuzzy attention (T1FA) mechanism-based YOLO (YOLO-FA) detector is proposed. • Mixed depthwise convolution is employed as a token mixer in MetaFormer. • T1FA can boost 3.2% AP50 in UA-DETRAC by reducing the uncertainty. • YOLO-FA trained from scratch achieves 70.0% AP50 and 50.3% AP on UADETRACA. [ABSTRACT FROM AUTHOR]

With the rising demand for electrification and intelligent functions in automobiles, the interest in passenger-centric air conditioning thermal management systems has swiftly increased. However, predicting personalized passenger comfort and applicability continues to pose challenges. The main challenge is how to use valid data to accurately predict the individual needs and preferences of different passengers. In this paper, we developed a deep learning model for a passenger-centric air conditioning system using ResNet50 (a deep residual network architecture consisting of 50 neural network layers). A spatial attention model was also incorporated (Attention-ResNet50) to enhance thermal comfort prediction accuracy. Experiments were conducted to collect basic image data under various thermal comfort and environmental conditions. Infrared images were gathered and classified into cold, comfortable, and warm categories for training, validation, and testing. The accuracy of thermal comfort prediction on testing sets is approximately 5 % higher when incorporating the spatial attention mechanism module compared to the standard ResNet50 model. Thermal comfort tests and predictions were also conducted for different genders. The female thermal comfort prediction model demonstrated significantly higher accuracy levels, nearing 100 % in situations characterized by cold or warm scenarios. The higher accuracy of female comfort prediction results, verifying that female facial features are more sensitive to temperature variation in their surroundings. • A deep learning model applied for passenger-centered air conditioning system was developed. • Aspatial attention model was added to improve the thermal comfort prediction accuracy. • The thermal comfort test and prediction for different genders were conducted. [ABSTRACT FROM AUTHOR]

The medicinal Dendrobium species of Orchidaceae possess significant pharmaceutical value, and modern pharmacological research has shown that Dendrobium contains many important active ingredients. Alkaloids, the crucial components of medicinal Dendrobium , demonstrate beneficial healing properties in cardiovascular, cataract, gastrointestinal, and respiratory diseases. Members of the cytochrome P450 monooxygenase (CYP) gene family play essential roles in alkaloid synthesis, participating in alkaloid terpene skeleton construction and subsequent modifications. Although studies of the CYP family have been conducted in some species, genome-wide characterization and systematic analysis of the CYP family in medicinal Dendrobium remain underexplored. In this study, we identified CYP gene family members in the genomes of four medicinal Dendrobium species recorded in the Pharmacopoeia: D. nobile , D. chrysotoxum , D. catenatum , and D. huoshanense. Further, we analyzed the motif composition, gene replication events, and selection pressure of this family. Syntenic analysis revealed that members of the clan 710 were present on chromosome 18 in three medicinal Dendrobium species, except for D. nobile , indicating a loss of clan 710 occurring in D. nobile. We also conducted an initial screening of the CYP genes involved in alkaloid synthesis through transcriptome sequencing. Quantitative real-time reverse transcription PCR showed that the expression of DnoNew43 and DnoNew50 , homologs of secologanin synthase involved in the alkaloid synthesis pathway, was significantly higher in the stems than in the leaves. This result coincided with the distribution of dendrobine content in Dendrobium stems and leaves, indicating that these two genes might be involved in the dendrobine synthesis pathway. Our results give insights into the CYP gene family evolution analysis in four medicinal Dendrobium species for the first time and identify two related genes that may be involved in alkaloid synthesis, providing a valuable resource for further investigations into alkaloid synthesis pathway in Dendrobium and other medicinal plants. [ABSTRACT FROM AUTHOR]

Bamboo, as an excellent natural material, has received widespread attention and application. However, its defects, including hydrophilicity and poor mold resistance, shorten its service life. Therefore, the best strategy to address the defects of bamboo is to prepare robust and stable superhydrophobic surfaces. This study reports a simple two-step method to prepare superhydrophobic surfaces, using only two materials: rosin and nano-CaCO 3. The method is easy to operate, replicable, cost-effective and safe. The prepared superhydrophobic bamboo (SHB) has a water contact angle (WCA) of 153 ± 3°. After being soaked in water at 0 ℃, 20 ℃, 40 ℃, 60 ℃, 80 ℃ and 100 ℃ for 2 h, the WCA of SHB maintained superhydrophobic in a wide range of 0–80 ℃. After being soaked in water at 100 ℃ for 2 h, the WCA of SHB sightly decreased to 147 ± 3°. After 2000 circles of weight friction, the WCA of SHB was 151°. After 1000 circles of tape peeling, the WCA of SHB was 150°. The WCA of SHB was greater than 151 ± 2° after soaked in acidic or alkaline solutions with pH values of 3, 5, 7, 9 and 11 for 2 h. After 6 weeks of fungal culture, the infection rate of SHB was 0%, while the infection rate of clean bamboo (CB) was 100%. In a word, SHB not only has good robustness, chemical stability, high and low temperature resistance, and mold resistance, but also can self-cleaning the dust on superhydrophobic surfaces through liquid droplets. • A simple two-step method to prepare superhydrophobic surfaces on bamboo. • Safe, non-toxic, and environmentally friendly superhydrophobic bamboo. • A superhydrophobic coating with high wear resistance. • A superhydrophobic coating with excellent mold resistance. [ABSTRACT FROM AUTHOR]

Robotic devices are capable of reducing the physical burden on rehabilitation therapists and providing training programs of good repeatability, high efficiency, and high precision. When designing the kinematic structure for rehabilitation robots, there has been a growing interest toward one-degree-of-freedom (DOF) end-effector mechanisms due to their simpler structure and less complicated control algorithms. Compared with current one-DOF mechanism designs that are mainly customized for multi-joint robotic training, spherical coupled serial chain (SCSC) mechanisms are proposed in this paper to specifically deliver the single-joint robotic training, which is of equal importance to the effective physical recovery. Using kinematic mapping theory, the end-effector motion of SCSC mechanisms can be naturally transformed to two trigonometric curves composed of finite Fourier series in two separate planes of the image space. This novel formulation helps to establish an analytical and direct relationship between the design parameters of the SCSC mechanism and the harmonic parameters of the image-space representation of the task rehabilitation motion. The result is a simple and effective method for kinematic synthesis of SCSC mechanisms for generation of single-joint motion with an arbitrary number of spherical poses. An example of designing SCSC mechanisms for shoulder-joint rehabilitation is presented at the end of this paper to illustrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

The preservation of the native conformation and functionality of membrane proteins has posed considerable challenges. While detergents and liposome reconstitution have been traditional approaches, nanodiscs (NDs) offer a promising solution by embedding membrane proteins in phospholipids encircled by an amphipathic helical protein MSP belt. Nevertheless, a drawback of commonly used NDs is their limited homogeneity and stability. In this study, we present a novel approach to construct covalent annular nanodiscs (cNDs) by leveraging microbial transglutaminase (MTGase) to catalyze isopeptide bond formation between the side chains of terminal amino acids, specifically Lysine (K) and Glutamine (Q). This methodology significantly enhances the homogeneity and stability of NDs. Characterization of cNDs and the assembly of membrane proteins within them validate the successful reconstitution of membrane proteins with improved homogeneity and stability. Our findings suggest that cNDs represent a more suitable tool for investigating interactions between membrane proteins and lipids, as well as for analyzing membrane protein structures. [Display omitted] • Provided a new method for preparing covalent annular nanodiscs. • The new covalent annular nanodiscs exhibit good homogeneity. • The new covalent annular nanodiscs have better stability than traditional nanodiscs. • Assembled membrane proteins using new covalent annular nanodiscs. [ABSTRACT FROM AUTHOR]

This paper presents a novel two-stage progressive search approach with unsupervised feature learning and Q-learning (TSLL) to enhance surrogate-assisted evolutionary optimization for medium-scale expensive problems. The method attempts to address the challenges posed by multi-polar and multi-variable coupling properties in such problems. During the iteration, TSLL splits the optimization process into two distinct stages. First, two unsupervised feature learning techniques: principal component analysis (PCA) and Autoencoder, are utilized to improve the representation of potential optimal samples in the solution space. PCA is used for feature reduction, extracting the most important features. On the other hand, Autoencoder focuses on reconstructing features within the medium-scale solution space. To ensure comprehensive exploration of the entire solution space, TSLL employs two distinct surrogate modeling approaches along with Q-learning in the second stage to dynamically select the mutation strategy for the differential evolution operator. Numerous experiments demonstrate the superiority of TSLL over five state-of-the-art surrogate-assisted approaches and two sophisticated evolutionary algorithms including the winner of CEC 2017 on medium-scale benchmark problems and a wind farm layout problem. [ABSTRACT FROM AUTHOR]

Precisely introducing topological defects is an important strategy in nanographene crystal engineering because defects can tune π‐electronic structures and control molecular assemblies. The synergistic control of the synthesis and assembly of nanographenes by embedding the topological defects to afford two‐dimensional (2D) crystals on surfaces is still a great challenge. By in‐situ embedding ladder bipyrazinylene (LBPy) into acene, the narrowest nanographene with zigzag edges, we have achieved the precise preparation of 2D nonbenzenoid heteroacene crystals on Au(111). Through intramolecular electrocyclization of o‐diisocyanides and Au adatom‐directed [2+2] cycloaddition, the nonbenzenoid heteroacene products are produced with high chemoselectivity, and lead to the molecular 2D assembly via LBPy‐derived interlocking hydrogen bonds. Using bond‐resolved scanning tunneling microscopy, we determined the atomic structures of the nonbenzenoid heteroacene product and diverse organometallic intermediates. The tunneling spectroscopy measurements revealed the electronic structure of the nonbenzenoid heteroacene, which is supported by density functional theory (DFT) calculations. The observed distinct organometallic intermediates during progression annealing combined with DFT calculations demonstrated that LBPy formation proceeds via electrocyclization of o‐diisocyanides, trapping of heteroarynes by Au adatoms, and stepwise elimination of Au adatoms. [ABSTRACT FROM AUTHOR]

Precisely introducing topological defects is an important strategy in nanographene crystal engineering because defects can tune π‐electronic structures and control molecular assemblies. The synergistic control of the synthesis and assembly of nanographenes by embedding the topological defects to afford two‐dimensional (2D) crystals on surfaces is still a great challenge. By in‐situ embedding ladder bipyrazinylene (LBPy) into acene, the narrowest nanographene with zigzag edges, we have achieved the precise preparation of 2D nonbenzenoid heteroacene crystals on Au(111). Through intramolecular electrocyclization of o‐diisocyanides and Au adatom‐directed [2+2] cycloaddition, the nonbenzenoid heteroacene products are produced with high chemoselectivity, and lead to the molecular 2D assembly via LBPy‐derived interlocking hydrogen bonds. Using bond‐resolved scanning tunneling microscopy, we determined the atomic structures of the nonbenzenoid heteroacene product and diverse organometallic intermediates. The tunneling spectroscopy measurements revealed the electronic structure of the nonbenzenoid heteroacene, which is supported by density functional theory (DFT) calculations. The observed distinct organometallic intermediates during progression annealing combined with DFT calculations demonstrated that LBPy formation proceeds via electrocyclization of o‐diisocyanides, trapping of heteroarynes by Au adatoms, and stepwise elimination of Au adatoms. [ABSTRACT FROM AUTHOR]

Electromagnetic rail launch technology has attracted increasing attention owing to its advantages in terms of range, firepower, and speed. However, due to electricity-magnetism-heat-force coupling, the surface of the armature–rail friction pair becomes severely damaged, which restricts the development of this technology. A series of studies have been conducted to reduce the damage of the armature–rail friction pair, including an analysis of the damage mechanism and protection strategies. In this study, various types of surface damage were classified into mechanical, electrical, and coupling damages according to their causes. This damage is caused by factors such as mechanical friction, mechanical impact, and electric erosion, either individually or in combination. Then, a detailed investigation of protection strategies for reducing damage is introduced, including material improvement through the use of novel combined deformation and heat treatment processes to achieve high strength and high conductivity, as well as surface treatment technologies such as structural coatings for wear resistance and functional coatings for ablation and melting resistance. Finally, future development prospects of armature–rail friction pair materials are discussed. This study provides a theoretical basis and directions for the development of high-performance materials for the armature–rail friction pair. [ABSTRACT FROM AUTHOR]

Objective: Salmonella enterica serovar Typhimurium (S. Typhimurium) is a representative model organism for investigating host–pathogen interactions. It was reported that S. Typhimurium spvC gene alleviated intestinal inflammation to aggravate systemic infection, while the precise mechanisms remain unclear. In this study, the influence of spvC on the antibacterial defense of macrophage/neutrophil mediated by gasdermin D (GSDMD) was investigated. Methods: Mouse macrophage-like cell lines J774A.1 and RAW264.7, neutrophil-like cells derived from HL-60 cells (human promyletic leukemia cell lines) were infected with S. Typhimurium wild type, spvC deletion and complemented strains. Cell death was evaluated by LDH release and Annexin V-FITC/PI staining. Macrophage pyroptosis and neutrophil NETosis were detected by western blotting, live cell imaging and ELISA. Flow cytometry was used to assess the impact of spvC on macrophage-neutrophil cooperation in macrophage (dTHP-1)-neutrophil (dHL-60) co-culture model pretreated with GSDMD inhibitor disulfiram. Wild-type and Gsdmd−/− C57BL/6J mice were utilized for in vivo assay. The degree of phagocytes infiltration and inflammation were analyzed by immunofluorescence and transmission electron microscopy. Results: Here we find that spvC inhibits pyroptosis in macrophages via Caspase-1/Caspase-11 dependent canonical and non-canonical pathways, and restrains neutrophil extracellular traps extrusion in GSDMD-dependent manner. Moreover, spvC could ameliorate macrophages/neutrophils infiltration and cooperation in the inflammatory response mediated by GSDMD to combat Salmonella infection. Conclusions: Our findings highlight the antibacterial activity of GSDMD in phagocytes and reveal a novel pathogenic mechanism employed by spvC to counteract this host defense, which may shed new light on designing effective therapeutics to control S. Typhimurium infection. [ABSTRACT FROM AUTHOR]

Rice blast is a disastrous fungal disease affecting rice (Oryza sativa L.) and undermines world food security. Different ecological conditions and genetic backgrounds altered the effectiveness of rice blast resistance genes. Anhui (China) is a high‐incidence area and has long been affected by rice blast. Despite chemical or other control methods of rice blast, analyzing the effects of specific rice blast resistance genes within the Anhui region, identifying favorable genes (combinations), and incorporating them into the process of new variety selection and breeding programs are effective ways to improve rice blast resistance. This research study examined the distribution of 16 rice blast resistance genes (i.e., Pi‐ta, Pi5, Pi1, Pia, etc.) in a recombinant self‐cross population of japonica rice and analyzed their correlation to panicle neck blast resistance. Five genes, Pit, Pi‐ta, Pik, Pb1, and Pi54, were identified and evaluated as dominant genes to improve panicle neck blast resistance. Further comparisons of the neck blast resistance levels between various gene combinations revealed that Pi54, when combined with Pb1/Pi‐ta (Pi54 + Pb1, Pi54 + Pi‐ta), could further increase resistance to panicle neck blast; and the highest resistance level was found with the three‐gene combination of Pi54 + Pi‐ta + Pb1. Meanwhile, the neck blast resistance capacity of Pi54 and Pb1 was significantly improved after polymerization with Pit and Pik (Pik + Pi54, Pit + Pi54, Pit + Pb1). Therefore, gene polymerization is widely regarded as a successful strategy to breed varieties with long‐lasting and broad‐spectrum resistance. It is anticipated that rice blast tolerance capacity will be considerably improved by gene polymerization of dominant genes. [ABSTRACT FROM AUTHOR]

This paper addresses the problem for fine-grained video super-resolution (FGVSR) to suppress temporal flickering caused by separately processed consecutive frames and enhance the quality of restored video frame details when upsizing videos. Some existing video SR methods fail to sufficiently utilize spatial-temporal information from input low-resolution (LR) videos, while others may generate undesirable artifacts or cannot well reconstruct image details. To overcome these problems, we present a novel deep learning framework for FGVSR, which takes a set of consecutive LR video frames and generate the corresponding super-resolved frames. Our deep FGVSR framework focuses on reconstructing missing information from the LR sources based on the proposed multi-frame alignment and refinement strategies. More specifically, we propose an alignment module, where multiple frames are aligned at feature level, to prevent the output videos from flickering. Then, we introduce a feature fusion module, where aligned features generated from our alignment module are fused and refined in a multi-scale manner. Finally, the proposed refinement module is used to reconstruct missing information based on the fused features. In addition, we also embed an image enhancement module on the skip connection from the input layer to the output layer of our network for further enhancing the SR results. Experimental results show that the proposed deep FGVSR, compared with existing deep learning-based VSR methods, achieves state-of-the-art performances on the three well-known benchmarks, including REDS, Vid4, and Vimeo90k. More specifically, compared with the state-of-the-art VSR methods in our experiments, our FGVSR achieves quantitative improvements from 0.70 dB to 9.54 dB in PSNR. On the other hand, our method has also been shown to be efficient to other image restoration tasks, such as image inpainting. • End-to-end trainable deep learning-based fine grained video super-resolution model is proposed. • The temporal dependency is implicitly obtained without performing explicit motion compensation. • Image details are reconstructed and further sharpened by our refinement and enhancement modules. • Adaptively integrated into other deep image restoration model for further boosting performances. [ABSTRACT FROM AUTHOR]

The exploiting of bifunctional transition metal electrocatalysts for the oxygen reduction reaction (ORR) and the oxygen evolution reaction (OER) is of significance for the commercialization of rechargeable zinc-air batteries (ZABs). Herein, the N and S atoms-doped hierarchical carbon framework hosting the Co 3 Fe 7 /Fe 0.8 Co 0.2 S heterojunction is synthesized by employing porous g-C 3 N 4 as framework and spacer, and FeCo-ZIF as metal source followed by sulfidation and pyrolysis. The detailed characterization confirms that the porous g-C 3 N 4 plays a crucial role in improving the dispersion of metal nanoparticles. The obtained FeCo-S x @NSC-900 catalysts exhibit layered accumulation configuration with uniformly distributed metal nanoparticles. Moreover, the typical carbon@metal nanoparticles and heterojunction structure can be observed from the HRTEM (High-Resolution Transmission Electron Microscopy) and HAADF-STEM (high-angle annular dark-field STEM) analysis results. The optimal FeCo-S x @NSC-900 catalysts deliver exceptional ORR and OER performance with a potential difference between ORR and OER of merely 0.713 V, which is superior to the commercial Pt/C+RuO 2 catalysts and other monometallic catalysts. Additionally, the ZAB assembled with the optimal FeCo-Sx@NSC-900 catalysts as cathode affords a good battery performance with high OCV (1.50 V), large power density (172 mW/cm2), good discharge stability, large specific capacity, and long-term charge/discharge stability (>300 cycles). [Display omitted] • N, S co-doped FeCo-S x @NSC is obtained with g-C 3 N 4 @ZIF as framework and template. • g-C 3 N 4 serves as a framework and spacer to promote the dispersion of nanoparticles. • FeCo-S x @NSC shows a layered accumulation structure and uniform metal nanoparticles. • FeCo-S x @NSC-900 displays excellent ORR-OER performances with the ΔE of 0.713 V. • FeCo-S x @NSC-900-based aqueous ZAB exhibits high specific capacity and cyclability. [ABSTRACT FROM AUTHOR]

• The effect mechanism of solution heating rate on grain structure of aviation Al-Li alloy was explained in detail. • The variation of texture intensity in aviation Al-Li alloy with various solution heating rates was revealed. • The mechanism of grain size on formation of dislocation structure and its effect on fatigue crack propagation behavior during fatigue loading were discussed in detail. • The linear relationship between the grain size and the initial ΔK entering the rapid propagation region was firstly revealed in aviation Al-Li alloy. In this study, the effects of grain structure on the fatigue crack propagation (FCP) behaviors in the aviation Al-Li alloy sheets prepared by varying solution heating rates are discussed systematically. The results reveal that both the intensity of Goss texture and grain dimensions are improved with the decreased solution heating rates. Upon an identical stress intensity factor range (ΔK), the increased Goss texture of the sample with a solution heating rate of 2 ℃/min (2HR) promotes crack deflection, causing a decrease in FCP rates compared to that of the sample with a solution heating rate of about 100 ℃/min (FHR). The dislocations clustered near grain boundaries are more significant with increasing grain size during cyclic loading, which intensifies the strain localization. The accumulation of dislocations increases the possibility of micro-voids formation and creates the conditions for crack deflection, which results in a decrease in FCP rate. Besides, based on the calculation of the reversible plastic zone (RPZ) size, the initial ΔK entering the rapid propagation region increases with decreasing solution heating rates and exhibits a strong linear relationship with grain size. [ABSTRACT FROM AUTHOR]

• SOC inversion models were established for various land-use in an arid mining area. • SOC spatiotemporal variability and its effect factors were analyzed. • Changes in vegetation and soil erosion dominate the spatial distribution of SOC. • Coal mining affects plant, terrain and soil erosion, then weakens SOC accumulation. Soil organic carbon (SOC) undergoes rapid changes due to human production activities, which have an impact on the land carbon cycle and ultimately global change. As one of the main human production activities, coal mining significantly impacts the soil carbon cycle. However, due to the lack of remote sensing modeling of soil carbon in mining areas, the spatio-temporal changes and driving mechanisms of SOC in mining areas remain unclear. Therefore, this study investigated and determined SOC data from 300 sampling points (depth of 0–20 cm) located in an arid mining area of China. Remote sensing images were then used to established a soil organic carbon density (SOCD) prediction model within the Random Forest (RF) model to achieve digital mapping of soil organic carbon stocks (SOCS). The spatiotemporal changes of SOCS were analyzed using SOCS digital mapping, and the influencing mechanism of SOCS was revealed using path analysis. The results showed that the constructed SOCD predictive model meets the demand for SOCD prediction (R2 ≥ 0.74, p < 0.01, RMSE ≤ 1.72 kg/m2). Under the combined influence of coal mining and land reclamation, the total amount of surface SOCS in the mining area exhibited a fluctuating upward trend from 1990 (6.34 Tg) to 2021 (7.73 Tg), with an annual growth rate of 0.038 Tg/a. The spatial distribution of SOCS generally increased from southeast to northwest. Precipitation, Normalized Difference Vegetation Index (NDVI), and land use were positively correlated to SOCS spatial distribution, while temperature, elevation, soil erosion, and mining intensity were negatively correlated to SOCS. The impact degree of factors on SOCS was as follows: NDVI > soil erosion > mining intensity > precipitation > elevation > land use > temperature. The negative impact of coal mining on SOCS was mainly indirect, through disturbance to elevation, vegetation, and soil erosion. The uneven ground subsidence and stretching caused by coal mining contribute to intensified soil erosion and vegetation degradation in the affected area, leading to a reduction in SOCS. However, SOCS did not decrease under high intensity mining, which was related to the increase in vegetation and the reduction in soil erosion in the mining area. In this study, a soil carbon prediction model was established based on remote sensing modeling to evaluate the temporal and spatial distribution of soil carbon in an arid mining area. The results can serve as valuable references for the scientific improvement of the ecological environment in mining areas, the rational planning of mining area construction, as well as low-carbon land reclamation and ecological compensation assessments. [ABSTRACT FROM AUTHOR]