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The axial compressive behaviours of coal gangue concrete-filled steel tube (GCFST) columns after chloride salt corrosion were investigated numerically. Numerical modelling was conducted through the static analysis method by finite element (FE) analysis. The failure mechanism, residual strength, and axial load–displacement curves were validated against tests of the coal gangue aggregate concrete-filled steel tube (GCFST) columns at room and natural aggregate concrete-filled steel tube (NCFST) columns after salt corrosion circumstance. According to the analysis on the stress distribution of the steel tube, the stress value of the steel tube decreased as the corrosion rate increased at the same characteristic point. A parametric analysis was carried out to determine the effect of crucial variation on residual strength. It indicated that material strength, the steel ratio, and the corrosion rate made a profound impact on the residual strength from the FE. The residual strength of the columns exposed to chloride salt was in negative correlation with the corrosion rate. The impact on the residual strength of the column was little, obvious by the replacement rate of the coal gangue. A simplified design formula for predicting the ultimate strength of GCFST columns after chloride salt corrosion exposure was proposed. [ABSTRACT FROM AUTHOR]

Simple Summary: Cas9 is limited by protospacer adjacent motif (PAM) sequences during the application process, which is particularly evident in insect genome editing. Researchers have discovered Cas9 variants with a wider range of recognition due to the development of genome-editing technology. However, the application of these variants in insects has been ineffective and time-consuming. To tackle this issue, this study established a high-throughput assay system capable of rapidly detecting recognizable PAM sequences of different Cas9 variants in Bombyx mori and the corresponding editing efficiency of the sites. We utilized this system to evaluate the editing ability of two protein variants, xCas9 and Cas9-NG, in Bombyx mori cells. Based on the editing ability of these two proteins, the editable range of the Bombyx mori genome can be greatly expanded, accelerating research on the genome's function. This system is also applicable to other insects for detecting the editing ability of Cas9 variants, thus accelerating the study of silkworm genome function. Genome editing provides novel opportunities for the precise genome engineering of diverse organisms. Significant progress has been made in the development of genome-editing tools for Bombyx mori (B. mori) in recent years. Among these, CRISPR/Cas9, which is currently the most commonly used system in lepidopteran insects, recognizes NGG protospacer adjacent motif (PAM) sequences within the target locus. However, Cas9 lacks the ability to target all gene loci in B. mori, indicating the need for Cas9 variants with a larger editing range. In this study, we developed a high-throughput screening platform to validate Cas9 variants at all possible recognizable and editable PAM sites for target sequences in B. mori. This platform enabled us to identify PAM sites that can be recognized by both xCas9 3.7 and SpCas9-NG variants in B. mori and to assess their editing efficiency. Cas9 shows PAM sites every 13 base pairs in the genome, whereas xCas9 3.7 and SpCas9-NG have an average distance of 3.4 and 3.6 base pairs, respectively, between two specific targeting sites. Combining the two Cas9 variants could significantly expand the targeting range of the genome, accelerate research on the B. mori genome, and extend the high-throughput rapid screening platform to other insects, particularly those lacking suitable NGG PAM sequences. [ABSTRACT FROM AUTHOR]

The advent of intelligent technologies, notably Brain–Computer Interfaces (BCIs), has introduced novel privacy dilemmas. Ensuring judicious privacy transfer is imperative for the application of BCI technology and pivotal for fostering economic and technological progress. This study adopts privacy transfer as the research perspective and employs an ethical matrix as the research method. It establishes BCI users as the central core interests, with marketers, developers, and medical personnel as stakeholders. Departing from the binary opposition of public and private in traditional privacy theory, this article proposes ethical principles such as maximizing benefits, minimizing harm, and respecting independent decision-making power. It constructs a judgment matrix for the privacy transfer of BCIs, utilizing this matrix to identify ethical risks like privacy disclosure and hijacking. This study analyzes the reasons for risks, aiming to overcome dilemmas and construct an ethical matrix to explore privacy transfer boundary division methods suitable for BCI technology and tailored to different stakeholders. [ABSTRACT FROM AUTHOR]

Simple Summary: The process of aging itself and the behavioral changes caused by aging have been extensively studied and recognized in the field of biology. In this study, we determined that age had no effect on social behavior in male Tibetan macaques (Macaca thibetana). Old female macaques were less likely to approach other monkeys. This study provides a new perspective on adjusting social interaction strategies in old non-human primates under nature environments. Aging can induce changes in social behaviors among humans and nonhuman primates (NHPs). Therefore, investigating the aging process in primate species can provide valuable evidence regarding age-related concerns in humans. However, the link between aging and behavioral patterns in nonhuman primates remains poorly comprehended. To address this gap, the present research examined aging-related behaviors exhibited by Tibetan macaques (Macaca thibetana) in their natural habitat in Huangshan, China, during the period from October 2020 to June 2021. We collected behavioral data from 25 adult macaques using different data collection methods, including focal animal sampling and ad libitum sampling methods. We found that among adult female macaques, the frequency of being attacked decreased with their age, and that the frequency of approaching other monkeys also decreased as age increased. In males, however, this was not the case. Our findings demonstrate that older female macaques exhibit active conflict avoidance, potentially attributed to a reduction in the frequency of approaching conspecifics and a decreased likelihood of engaging in conflict behaviors. This study provides some important data for investigating aging in NHPs and confirms that Macaca can exhibit a preference for social partners under aging-related contexts similar to humans. [ABSTRACT FROM AUTHOR]

It is important to capture passengers' public transit behavior and their mobility to create profiles, which are critical for analyzing human activities, understanding the social and economic structure of cities, improving public transportation, assisting urban planning, and promoting smart cities. In this paper, we develop a generative adversarial machine learning network to characterize the temporal and spatial mobility behavior of public transit passengers, based on massive smart card data and road network data. The Apriori algorithm is extended with spatio-temporal constraints to extract frequent transit mobility patterns of individual passengers based on a reconstructed personal trip dataset. This individual-level pattern information is used to construct personalized feature vectors. For regular and frequent public transit passengers, we identify similar transit mobility groups using spatio-temporal constraints to construct a group feature vector. We develop a generative adversarial network to embed public transit mobility of passengers. The proposed model's generator consists of an auto-encoder, which extracts a low-dimensional and compact representation of passenger behavior, and a pre-trained sub-generator containing generalization features of public transit passengers. Shenzhen City is taken as the study area in this paper, and experiments were carried out based on smart card data, road network data, and bus GPS data. Clustering analysis of embedding vector representation and estimation of the top K transit destinations were conducted, verifying that the proposed method can profile passenger transit mobility in a comprehensive and compact manner. [ABSTRACT FROM AUTHOR]

In order to study the variation of mechanical properties of steel under acid rain corrosion conditions in northern China, monotonic tensile tests were conducted on Q235 steel with a thickness of 3.0 mm and 4.5 mm using a method of artificially prepared simulated acid rain solution for indoor accelerated corrosion. The results show that the failure mode of corroded steel standard tensile coupon includes normal fault and oblique fault. The failure patterns of the test specimen show that the thickness of the steel and corrosion rate affected the corrosion resistance. Larger thicknesses and lower corrosion rates will delay the failure mode of corrosion on steel. The strength reduction factor (Ru), deformability reduction factor (Rd) and energy absorption reduction factor (Re) decrease linearly with the increasing corrosion rate from 0% to 30%. The results are interpreted also from the microstructural point of view. The number, size, and distribution of the pits are random when the steel is subjected to sulfate corrosion. The higher the corrosion rate, the clearer, denser, and more hemispherical the corrosion pits. The microstructure of steel tensile fracture can be divided into intergranular fracture and cleavage fracture. As the corrosion rate increases, the dimples at the tensile fracture gradually disappear and the cleavage surface gradually increases. An equivalent thickness reduction model is proposed based on Faraday's law and the meso-damage theory. [ABSTRACT FROM AUTHOR]

During the cold-start process of a PEMFC, the supply of air and hydrogen in the gas supply system has a great influence on the cold-start performance. The cold-start of a PEMFC is a complex nonlinear coupling process, and the traditional control strategy is not sensitive to the real-time characteristics of the system. Inspired by the strong perception and decision-making abilities of deep reinforcement learning, this paper proposes a cold-start control strategy for a gas supply system based on the MADDPG algorithm, and designs an air supply controller and a hydrogen supply controller based on this algorithm. The proposed strategy can optimize the control parameters of the gas supply system in real time according to the temperature rise rate of the stack during the cold-start process, the fluctuation of the OER, and the voltage output characteristics. After the strategy is trained offline according to the designed reward function, the detailed in-loop simulation experiment results are given and compared with the traditional control strategy for the gas supply system. From the results, it can be seen that the proposed MADDPG control strategy has a more effective coordination control effect. [ABSTRACT FROM AUTHOR]

[3 + 2] Cycloaddition reactions of heteroaromatic N-ylides with electron-deficient olefins have been developed. The heteroaromatic N-ylides, in situ generated from N-phenacylbenzothiazolium bromides, can smoothly react with maleimides under very mild conditions, affording fused polycyclic octahydropyrrolo[3,4-c]pyrroles in good-to-excellent isolated yields. This reaction concept could also be extended to 3-trifluoroethylidene oxindoles and benzylidenemalononitriles as electron-deficient olefins for accessing highly functionalized polyheterocyclic compounds. A gram-scale experiment was also carried out to verify the practicability of the methodology. [ABSTRACT FROM AUTHOR]

Insulator defect detection is of great significance to compromise the stability of the power transmission line. The state-of-the-art object detection network, YOLOv5, has been widely used in insulator and defect detection. However, the YOLOv5 network has limitations such as poor detection rate and high computational loads in detecting small insulator defects. To solve these problems, we proposed a light-weight network for insulator and defect detection. In this network, we introduced the Ghost module into the YOLOv5 backbone and neck to reduce the parameters and model size to enhance the performance of unmanned aerial vehicles (UAVs). Besides, we added small object detection anchors and layers for small defect detection. In addition, we optimized the backbone of YOLOv5 by applying convolutional block attention modules (CBAM) to focus on critical information for insulator and defect detection and suppress uncritical information. The experiment result shows the mean average precision (mAP) is set to 0.5, and the mAP is set from 0.5 to 0.95 of our model and can reach 99.4% and 91.7%; the parameters and model size were reduced to 3,807,372 and 8.79 M, which can be easily deployed to embedded devices such as UAVs. Moreover, the speed of detection can reach 10.9 ms/image, which can meet the real-time detection requirement. [ABSTRACT FROM AUTHOR]

Natural colorants, mostly of plant and fungal origins, offer advantages over chemically synthetic colorants in terms of alleviating environmental pollution and promoting human health. The market value of natural colorants has been increasing significantly across the globe. Due to the ease of artificially culturing most fungi in the laboratory and in industrial settings, fungi have emerged as the organisms of choice for producing many natural colorants. Indeed, there is a wide variety of colorful fungi and a diversity in the structure and bioactivity of fungal colorants. Such broad diversities have spurred significant research efforts in fungi to search for natural alternatives to synthetic colorants. Here, we review recent research on the genetic and environmental factors influencing the production of three major types of natural fungal colorants: carotenoids, melanins, and polyketide-derived colorants. We highlight how molecular genetic studies and environmental condition manipulations are helping to overcome some of the challenges associated with value-added and large-scale productions of these colorants. We finish by discussing potential future trends, including synthetic biology approaches, in the commercial production of fungal colorants. [ABSTRACT FROM AUTHOR]

Passive location technology has been greatly developed because of its low power consumption, long detection distance, good concealment, and strong anti-interference ability. Orthogonal frequency-division multiplexing (OFDM) is an efficient multi-carrier transmission technology, which is an important signal form of 5G communication. Researching passive locations for OFDM signals can realize the location of base stations, which is of great significance in the military. Space-borne passive location technology has a contradiction between wide coverage and high precision. Therefore, a single-satellite passive location algorithm for OFDM radiation sources based on the virtual synthetic aperture is proposed. The algorithm introduces virtual synthetic aperture technology, using antenna movement to accumulate data coherently over a long time period and synthesizing a long azimuth virtual aperture. In addition, it utilizes fast Fourier transform (FFT) to extract phase information at a specific frequency based on the multi-carrier modulation technology of the OFDM signal. Pilot technology of the communication system is used for phase compensation and noise reduction. Thus, the azimuth linear frequency modulation (LFM) signal containing the location information of the radiation source is obtained. The radiation source location can be obtained by range searching and azimuth focusing. Simulation results verify the effectiveness of the algorithm and show that the algorithm can realize high-precision and wide-coverage location for the OFDM radiation sources using a single antenna, turning the hardware structure into software to reduce the cost and complexity of the system. [ABSTRACT FROM AUTHOR]

A novel ZIF-8 assisted polyacrylamide functionalized silica polar stationary phase was prepared by a facile method of adding ZIF-8 nanoparticles and silica into polyacrylamide (PAM) aqueous solution, and then stirring the mixture until the solution was evaporated absolutely with the help of mechanical agitator. Interestingly, the prepared stationary phase (PAM-Sil@ZIF-8/PAM) showed favorable hydrophilicity, as demonstrated by good separation performance and strong retention ability toward several types of polar compounds, such as amino acids, saccharides, and alkaloids. In addition, PAM-Sil@ZIF-8(50 mg)/PAM showed better separation performance compared with amino-modified silica and Sil/PAM stationary phase due to the addition of ZIF-8. Furthermore, it was demonstrated that the addition of ZIF-8 improved the specific surface area and provided extra interaction sites for the stationary phase and analytes, which is beneficial for the separation of samples. In addition, the column efficiency can reach 7861.9 plates/m for colchicine. Moreover, it exhibited good stability and reproducibility under our operation conditions. In short, a novel stationary phase, which can be used for hydrophilic interaction liquid chromatography, was obtained and proved that the separation performance of polymer modifying silica stationary phase can be greatly improved by the addition of MOF nanoparticles. [ABSTRACT FROM AUTHOR]

Simple Summary: The fibroin heavy chain (FibH) is the core protein of silkworm silk, and a systematic analysis of its sequence (primary structure) is essential for understanding silkworm silk fibers. However, only a few FibH sequences have been identified. The recently published high-resolution silkworm pan-genome was useful in analyzing the FibH gene systematically. In this study, we extracted the complete FibH sequences of wild silkworms, local and improved strains from the silkworm pan-genome, bringing the total number of known silkworm FibH genes to 286. We characterized in detail the FibH variation during domestication and breeding and established a silkworm pedigree based on the FibH gene sequence. Additionally, we investigated the relationship between the cis-regulatory elements of FibH gene and silk yield in wild and domesticated silkworms. Our study laid the foundation for artificial silk as well as provided guidance for silkworm breeding. The highly repetitive and variable fibroin heavy chain (FibH) gene can be used as a silkworm identification; however, only a few complete FibH sequences are known. In this study, we extracted and examined 264 FibH gene complete sequences (FibHome) from a high-resolution silkworm pan-genome. The average FibH lengths of the wild silkworm, local, and improved strains were 19,698 bp, 16,427 bp, and 15,795 bp, respectively. All FibH sequences had a conserved 5′ and 3′ terminal non-repetitive (5′ and 3′ TNR, 99.74% and 99.99% identity, respectively) sequence and a variable repetitive core (RC). The RCs differed greatly, but they all shared the same motif. During domestication or breeding, the FibH gene mutated with hexanucleotide (GGTGCT) as the core unit. Numerous variations existed that were not unique to wild and domesticated silkworms. However, the transcriptional factor binding sites, such as fibroin modulator-binding protein, were highly conserved and had 100% identity in the FibH gene's intron and upstream sequences. The local and improved strains with the same FibH gene were divided into four families using this gene as a marker. Family I contained a maximum of 62 strains with the optional FibH (Opti-FibH, 15,960 bp) gene. This study provides new insights into FibH variations and silkworm breeding. [ABSTRACT FROM AUTHOR]

Decidualization is necessary for the successful establishment of early pregnancy in rodents and humans. Disturbed decidualization results in recurrent implantation failure, recurrent spontaneous abortion, and preeclampsia. Tryptophan (Trp), one of the essential amino acids in humans, has a positive effect on mammalian pregnancy. Interleukin 4-induced gene 1 (IL4I1) is a recently identified enzyme that can metabolize L-Trp to activate aryl hydrocarbon receptor (AHR). Although IDO1-catalyzed kynurenine (Kyn) from Trp has been shown to enhance human in vitro decidualization via activating AHR, whether IL4I1-catalyzed metabolites of Trp are involved in human decidualization is still unknown. In our study, human chorionic gonadotropin stimulates IL4I1 expression and secretion from human endometrial epithelial cells through ornithine decarboxylase-induced putrescine production. Either IL4I1-catalyzed indole-3-pyruvic acid (I3P) or its metabolite indole-3-aldehyde (I3A) from Trp is able to induce human in vitro decidualization by activating AHR. As a target gene of AHR, Epiregulin induced by I3P and I3A promotes human in vitro decidualization. Our study indicates that IL4I1-catalyzed metabolites from Trp can enhance human in vitro decidualization through AHR-Epiregulin pathway. [ABSTRACT FROM AUTHOR]

Lepidopteran species are mostly pests, causing serious annual economic losses. High-quality genome sequencing and assembly uncover the genetic foundation of pest occurrence and provide guidance for pest control measures. Long-read sequencing technology and assembly algorithm advances have improved the ability to timeously produce high-quality genomes. Lepidoptera includes a wide variety of insects with high genetic diversity and heterozygosity. Therefore, the selection of an appropriate sequencing and assembly strategy to obtain high-quality genomic information is urgently needed. This research used silkworm as a model to test genome sequencing and assembly through high-coverage datasets by de novo assemblies. We report the first nearly complete telomere-to-telomere reference genome of silkworm Bombyx mori (P50T strain) produced by Pacific Biosciences (PacBio) HiFi sequencing, and highly contiguous and complete genome assemblies of two other silkworm strains by Oxford Nanopore Technologies (ONT) or PacBio continuous long-reads (CLR) that were unrepresented in the public database. Assembly quality was evaluated by use of BUSCO, Inspector, and EagleC. It is necessary to choose an appropriate assembler for draft genome construction, especially for low-depth datasets. For PacBio CLR and ONT sequencing, NextDenovo is superior. For PacBio HiFi sequencing, hifiasm is better. Quality assessment is essential for genome assembly and can provide better and more accurate results. For chromosome-level high-quality genome construction, we recommend using 3D-DNA with EagleC evaluation. Our study references how to obtain and evaluate high-quality genome assemblies, and is a resource for biological control, comparative genomics, and evolutionary studies of Lepidopteran pests and related species. [ABSTRACT FROM AUTHOR]

Isoorientin (ISO) is a flavonoid compound containing a luteolin structure, which can induce autophagy in some tumor cells. This study investigated the impact of ISO in gastric cancer AGS cells, and performed an experimental analysis on the main signaling pathways and transduction pathways it regulates. CCK–8 assay results showed that ISO reduced the survival rate of gastric cancer AGS cells, but the toxicity to normal cells was minimal. Hoechst 33342/PI double staining assay results showed that ISO induced apoptosis in gastric cancer AGS cells. Further analysis by flow cytometry and Western blot showed that ISO induced apoptosis via a mitochondria-dependent pathway. In addition, the level of reactive oxygen species (ROS) in gastric cancer AGS cells also increased with the extension of the ISO treatment time. However, cell apoptosis was inhibited by preconditioning cells with N–acetylcysteine (NAC). Moreover, ISO arrested the cell cycle at the G2/M phase by increasing intracellular ROS levels. Cell migration assay results showed that ISO inhibited cell migration by inhibiting the expression of p–AKT, p–GSK–3β, and β–catenin and was also related to the accumulation of ROS. These results suggest that ISO-induced cell apoptosis by ROS–mediated MAPK/STAT3/NF–κB signaling pathways inhibited cell migration by regulating the AKT/GSK–3β/β–catenin signaling pathway in gastric cancer AGS cells. [ABSTRACT FROM AUTHOR]

Binary code similarity measurement is a popular research area in binary analysis with the recent development of deep learning-based models. Current state-of-the-art methods often use the pre-trained language model (PTLM) to embed instructions into basic blocks as representations of nodes within a control flow graph (CFG). These methods will then use the graph neural network (GNN) to embed the whole CFG and measure the binary similarities between these code embeddings. However, these methods almost directly treat the assembly code as a natural language text and ignore its code-specific features when training PTLM. Moreover, They barely consider the direction of edges in the CFG or consider it less efficient. The weaknesses of the above approaches may limit the performances of previous methods. In this paper, we propose a novel method called function similarity using code-specific PPTs and order-sensitive GNN (FUSION). Since the similarity of binary codes is a symmetric/asymmetric problem, we were guided by the ideas of symmetry and asymmetry in our research. They measure the binary function similarity with two code-specific PTLM training strategies and an order-sensitive GNN, which, respectively, alleviate the aforementioned weaknesses. FUSION outperforms the state-of-the-art binary similarity methods by up to 5.4% in accuracy, and performs significantly better. [ABSTRACT FROM AUTHOR]

Currently, under supervised learning, a model pre-trained by a large-scale nature scene dataset and then fine-tuned on a few specific task labeling data is the paradigm that has dominated knowledge transfer learning. Unfortunately, due to different categories of imaging data and stiff challenges of data annotation, there is not a large enough and uniform remote sensing dataset to support large-scale pre-training in the remote sensing domain (RSD). Moreover, pre-training models on large-scale nature scene datasets by supervised learning and then directly fine-tuning on diverse downstream tasks seems to be a crude method, which is easily affected by inevitable incorrect labeling, severe domain gaps and task-aware discrepancies. Thus, in this paper, considering the self-supervised pre-training and powerful vision transformer (ViT) architecture, a concise and effective knowledge transfer learning strategy called ConSecutive Pre-Training (CSPT) is proposed based on the idea of not stopping pre-training in natural language processing (NLP), which can gradually bridge the domain gap and transfer large-scale data knowledge to any specific domain (e.g., from nature scene domain to RSD) In addition, the proposed CSPT also can release the huge potential of unlabeled data for task-aware model training. Finally, extensive experiments were carried out on twelve remote sensing datasets involving three types of downstream tasks (e.g., scene classification, object detection and land cover classification) and two types of imaging data (e.g., optical and synthetic aperture radar (SAR)). The results show that by utilizing the proposed CSPT for task-aware model training, almost all downstream tasks in the RSD can outperform the previous knowledge transfer learning strategies based on model pre-training without any expensive manually labeling and even surpass the state-of-the-art (SOTA) performance without any careful network architecture designing. [ABSTRACT FROM AUTHOR]

Mining-induced hydromechanical behavior of sandstone is critical to mining safety and disaster prevention. To investigate the evolution behavior of the mechanical and permeability properties of sandstone, mining-induced stress was imitated by increasing axial stress and decreasing confining stress, and a set of hydromechanical experiments were further performed, incorporating the effect of in situ stress, pore pressure, and mining stress. The results show the similar variation tendencies of the deformation and permeability of sandstone under different loading paths of in situ stress and pore pressure. Most sandstone samples maintain a compression state for the peak stress condition. The failure mode evolved from shear failure to shear–tension failure with the increase in in situ stress. The stress-relief effect significantly effects the permeability, since the permeability of sandstone increases exponentially with decreasing effective confining stress. The growth rate of permeability in Stage II is significantly greater than that in Stage I. One order of magnitude of permeability was presented at the peak stress situation. A fitting exponential model based on the alteration of effective confining stress was proposed to describe the permeability evolution dominated by the stress-relief effect, and the discovered permeability model can accurately describe the experimental results. The research results provide significant guidance for understanding the hydromechanical behavior and water hazard prevention for underground coal mines. [ABSTRACT FROM AUTHOR]

This paper studies the consensus control problem of multiple high-speed trains with nonlinear running resistance based on a distributed event-triggered control protocol. Firstly, the multiple high-speed trains are established as a multi-agent model with a leader–follower. For the system whose leader has an unknown input, the effective state observers are introduced to observe the state of the train. Then, an observer-based event-triggered strategy is designed to determine the time when the train state is transmitted to the local controller and adjacent trains. The proposed control scheme is based on local information, and the solutions of the state observer and the gain symmetric matrices parameters of the distributed event-triggered control strategy are constructed in the form of linear matrix inequalities (LMI). Through the Lyapunov stability theory, sufficient conditions for the stable and safe operation of multiple high-speed trains systems are obtained. Finally, a simulation example is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The electrochemical detection of hydrogen peroxide (H2O2) has become more and more important in industrial production, daily life, biological process, green energy chemistry, and other fields (especially for the detection of low concentration of H2O2). Metal organic frameworks (MOFs) are promising candidates to replace the established H2O2 sensors based on precious metals or enzymes. This review summarizes recent advances in MOF-based H2O2 electrochemical sensors, including conductive MOFs, MOFs with chemical modifications, MOFs-composites, and MOF derivatives. Finally, the challenges and prospects for the optimization and design of H2O2 electrochemical sensors with ultra-low detection limit and long-life are presented. [ABSTRACT FROM AUTHOR]

The hysteretic behavior of square concrete-filled steel tube (CFST) stub columns subjected to sulfate corrosion and freeze-thaw cycle is examined by numerical investigation. The constitutive model of steel considered the Bauschinger effect, and compression (tension) damage coefficient was also adopted for the constitutive model of core concrete. The experimental results are used to verify the finite element (FE) model, which could accurately predict the hysteretic behaviors of the CFST piers. Then, the effects of the yield strength of steel, compressive strength of concrete, steel ratio, axial compression ratio, and alternation time on ultimate horizontal load are evaluated by a parametric study. The results showed that the yield strength of steel and the steel ratio have a positive effect of hysteretic behavior. The compressive strength of concrete and alternation time significantly decreased the unloading stiffness which causes the pinching phenomenon. The yield strength of steel, compressive strength of concrete, and alternation time of environmental factors (corrosion-freeze-thaw cycles) has no obvious effect on the initial stiffness, while the steel ratio has a remarkable effect. The ultimate horizontal load increases with the increasing steel ratio, yield strength of steel and compressive strength of concrete. Meanwhile, the decrement of alternation time led to the increase of ultimate horizontal load. This suggests that the confinement coefficient and alternation time are the two main factors that impact the ultimate horizontal load. A formula which considers the reduction coefficient for the ultimate horizontal load of the CFST columns subjected to sulfate corrosion and freeze-thaw cycles is proposed. The formulae can accurately predict the ultimate horizontal load with mean value of 1.022 and standard deviation of 0.003. [ABSTRACT FROM AUTHOR]

Atractylodin (ATR) has anticancer effects on some tumor cells by inducing apoptosis, but its mechanism in lung cancer remains unclear. This study investigates the inhibitory effect of ATR on A549 lung cancer cells. Cell viability was detected by the Cell Counting Kit-8 assay, and results showed that ATR could significantly inhibit the proliferation of A549 cells. Apoptosis was detected by Annexin V-FITC/PI staining, and apoptosis rate and mitochondrial membrane potential were detected by flow cytometry. Results showed that the effect of ATR on the apoptosis of A549 cells was negatively correlated with the change in mitochondrial membrane potential. Western blot analysis showed that ATR regulated apoptosis induced by mitogen-activated protein kinase, signal transducer and activator of transcription 3, and nuclear factor kappa B signaling pathways. Analyses of reactive oxygen species (ROS), cell cycle, and cell migration showed that ATR induced intracellular ROS accumulation as an initiation signal to induce cell cycle arrest regulated by the AKT signaling pathway and cell migration inhibition regulated by the Wnt signaling pathway. Results showed that ATR can inhibit cell proliferation, induce cell apoptosis, induce cell cycle arrest, and inhibit the migration of A549 cells (p < 0.05 was considered statistically significant, * p < 0.05, ** p < 0.01 and *** p < 0.001). [ABSTRACT FROM AUTHOR]

Graphene has attracted much interest in many scientific fields because of its high specific surface area, Young's modulus, fracture strength, carrier mobility and thermal conductivity. In particular, the graphene oxide (GO) prepared by chemical exfoliation of graphite has achieved low-cost and large-scale production and is one of the most promising for Cu matrix composites. Here, we prepared a high strength, high electrical conductivity and high thermal conductivity reduced graphene oxide (RGO)/Cu composite by directly heating the GO/copper formate. The oxygen-containing functional groups and defects of RGO are significantly reduced compared with those of GO. The tensile yield strength and thermal conductivity of RGO/Cu composite with RGO volume fraction of 0.49 vol.% are as high as 553 MPa and 364 W/(m·K) at room temperature, respectively. The theoretical value of the tensile yield strength of the composite is calculated according to the strengthening mechanism, and the result shows that it agrees with the experimental value. After hot-rolling treatment, the ductility and conductivity of the composite materials have been greatly improved, and the ductility of the RGO/Cu composite with RGO volume fraction of 0.49 vol.% has been increased to four times the original. This work provides a highly efficient way to fabricate a high-performance RGO-reinforced Cu composite for commercial application. [ABSTRACT FROM AUTHOR]

Cross-scene classification focuses on setting up an effective domain adaptation (DA) way to transfer the learnable knowledge from source to target domain, which can be reasonably achieved through the pseudo-label propagation procedure. However, it is hard to bridge the objective existing severe domain discrepancy between source and target domains, and thus, there are several unreliable pseudo-labels generated in target domain and involved into pseudo-label propagation procedure, which would lead to unreliable error accumulation to deteriorate the performance of cross-scene classification. Therefore, in this paper, a novel Masked Image Modeling Auxiliary Pseudo-Label Propagation called MIM-AP 2 with clustering central rectification strategy is proposed to improve the quality of pseudo-label propagation for cross-scene classification. First, in order to gracefully bridge the domain discrepancy and improve DA representation ability in-domain, a supervised class-token contrastive learning is designed to find the more consistent contextual clues to achieve knowledge transfer learning from source to target domain. At the same time, it is also incorporated with a self-supervised MIM mechanism according to a low random masking ratio to capture domain-specific information for improving the discriminability in-domain, which can lay a solid foundation for high-quality pseudo-label generation. Second, aiming to alleviate the impact of unreliable error accumulation, a clustering central rectification strategy is designed to adaptively update robustness clustering central representations to assist in rectifying unreliable pseudo-labels and learning a superior target domain specific classifier for cross-scene classification. Finally, extensive experiments are conducted on six cross-scene classification benchmarks, and the results are superior to other DA methods. The average accuracy reached 95.79%, which represents a 21.87% improvement over the baseline. This demonstrates that the proposed MIM-AP 2 can provide significantly improved performance. [ABSTRACT FROM AUTHOR]

The escalating frequency and severity of extreme climate greatly impact the carbon dynamics of terrestrial ecosystems worldwide. To understand the multi-temporal response of net ecosystem productivity (NEP) to extreme climate, we investigated 11 temperature and precipitation extreme indices across different vegetation types in China. From 1981 to 2019, the results showed that NEP in China increased at a rate of 0.64 g·m−2·a−2. Extreme climate demonstrated a significant warming trend and a non-significant moistening trend; specifically, maximum daily minimum temperature (TNx) exhibited a significant increase at a rate of 0.34 °C/10 a, while maximum 5-day precipitation (Rx5day) showed an insignificant increase at a rate of 1.78 mm/10 a. NEP was significantly impacted by extreme temperature at the annual, seasonal, and monthly scales, but moderately impacted by extreme precipitation. Specifically, extreme temperature had the most significant effect on grassland, with minimal influence on cropland. In contrast, extreme precipitation had the most significant effect on forest, with minimal impact on cropland. Moreover, the lagged time for extreme precipitation was longer than that for extreme temperature. Extreme precipitation exhibited a corresponding lagged time of at least 2 months (p < 0.01), while extreme temperature exhibited a lagged time of at least 1 month (p < 0.01). The maximum lag time observed was 4 months (p < 0.01). Our findings provide valuable insights into the multi-temporal response of NEP to extreme climate in China and inform sustainable development practices in the region. [ABSTRACT FROM AUTHOR]

With the development of fuel cell vehicle technology, an effective testing method that can be applied to develop and verify the fuel cell vehicle powertrain system is urgently required. This paper presents the X-in-the-Loop (XiL) testing method in the fuel cell vehicle (FCV) hybrid degree test to resolve the first and key issues for the powertrain system design, and the test process and scenarios were designed. The hybrid degree is redefined into the static hybrid degree for system architecture design and the dynamic hybrid degree for vehicle control strategy design, and an integrated testing platform was introduced and a testing application was implemented by following the designed testing flowchart with two loops. Experimental validations show that the sizing of the FCE (Fuel Cell Engine), battery pack, and traction motor with the powertrain architecture can be determined, the control strategy can be evaluated seamlessly, and a systematic powertrain testing solution can be achieved through the whole development process. This research has developed a new testing platform and proposed a novel testing method on the fuel cell vehicle powertrain system, which will be a contribution to fuel cell vehicle technology and its industrialization. [ABSTRACT FROM AUTHOR]

Dielectric elastomers (DEs) are a class of electro-active polymers (EAPs) that can deform under electric stimuli and have great application potential in bionic robots, biomedical devices, energy harvesters, and many other areas due to their outstanding deformation abilities. It has been found that stretching rate, temperature, and electric field have significant effects on the stress-strain relations of DEs, which may result in the failure of DEs in their applications. Thus, this paper aims to develop a thermo-electro-viscoelastic model for DEs at finite deformation and simulate the highly nonlinear stress-strain relations of DEs under various thermo-electro-mechanical loading conditions. To do so, a thermodynamically consistent continuum theoretical framework is developed for thermo-electro-mechanically coupling problems, and then specific constitutive equations are given to describe the thermo-electro-viscoelastic behaviors of DEs. Furthermore, the present model is fitted with the experimental data of VHB4905 to determine a temperature-dependent function of the equilibrium modulus. A comparison of the nonlinear loading-unloading curves between the model prediction and the experimental data of VHB4905 at various thermo-electro-mechanical loading conditions verifies the present model and shows its ability to simulate the thermo-electro-viscoelastic behaviors of DEs. Simultaneously, the results reveal the softening phenomena and the instant pre-stretch induced by temperature and the electric field, respectively. This work is conducive to analyzing the failure of DEs in functionalities and structures from theoretical aspects at various thermo-electro-mechanical conditions. [ABSTRACT FROM AUTHOR]

In recent years, various network attacks have emerged. These attacks are often recorded in the form of Pcap data, which contains many attack details and characteristics that cannot be analyzed through traditional methods alone. Therefore, restoring the network attack scenario through scene reconstruction to achieve data regeneration has become an important entry point for detecting and defending against network attacks. However, current network attack scenarios mainly reproduce the attacker's attack steps by building a sequence collection of attack scenarios, constructing an attack behavior diagram, or simply replaying the captured network traffic. These methods still have shortcomings in terms of traffic regeneration. To address this limitation, this paper proposes an SDN-based network attack scenario recovery method. By parsing Pcap data and utilizing network topology reconstruction, probability, and packet sequence models, network traffic data can be regenerated. The experimental results show that the proposed method is closer to the real network, with a higher similarity between the reconstructed and actual attack scenarios. Additionally, this method allows for adjusting the intensity of the network attack and the generated topology nodes, which helps network defenders better understand the attackers' posture and analyze and formulate corresponding security strategies. [ABSTRACT FROM AUTHOR]

In this study, star anise (Illicium verum) essential oils (SAEOs) were extracted by hydrodistillation (HD), ethanol solvent extraction (ESE), supercritical CO2 (SCD) and subcritical extraction (SE) via electronic nose (E-nose), gas chromatography-mass spectrometry (GC-MS), and GC-ion mobility spectrometry (GC-IMS). GC-MS and GC-IMS were used to identify the volatile compounds, and GC-MS was also used to determine their concentrations. Principal component analysis (PCA) and linear discriminant analysis (LDA) were used to visualise volatile compounds and differentiate samples. The results showed that anethole and limonene were the main volatile compounds in SAEOs extracted using the four methods and their components were similar, albeit in different proportions. In addition, the fingerprints of their volatile components were established via E-nose and GC-IMS analyses. In general, GC-MS, GC-IMS, and E-nose combined with PCA and LDA analysis could accurately distinguish SAEOs extracted using different extraction methods, and GC-IMS was identified as the most suitable method because of its accuracy and rapidity. [ABSTRACT FROM AUTHOR]

Safflower (Carthamus tinctorius. L) possesses anti-tumor, anti-thrombotic, anti-oxidative, immunoregulatory, and cardio-cerebral protective effects. It is used clinically for the treatment of cardio-cerebrovascular disease in China. This study aimed to investigate the effects and mechanisms of action of safflower extract on myocardial ischemia–reperfusion (MIR) injury in a left anterior descending (LAD)-ligated model based on integrative pharmacology study and ultra-performance liquid chromatography–quadrupole time-of-flight-tandem mass spectrometer (UPLC-QTOF-MS/MS). Safflower (62.5, 125, 250 mg/kg) was administered immediately before reperfusion. Triphenyl tetrazolium chloride (TTC)/Evans blue, echocardiography, terminal deoxynucleotidyl transferase-mediated dUTP nick-end labeling (TUNEL) assay, lactate dehydrogenase (LDH) ability, and superoxide dismutase (SOD) levels were determined after 24 h of reperfusion. Chemical components were obtained using UPLC-QTOF-MS/MS. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting were used to analyze mRNA and protein levels, respectively. Safflower dose-dependently reduced myocardial infarct size, improved cardiac function, decreased LDH levels, and increased SOD levels in C57/BL6 mice. A total of 11 key components and 31 hub targets were filtered based on the network analysis. Comprehensive analysis indicated that safflower alleviated inflammatory effects by downregulating the expression of NFκB1, IL-6, IL-1β, IL-18, TNFα, and MCP-1 and upregulating NFκBia, and markedly increased the expression of phosphorylated PI3K, AKT, PKC, and ERK/2, HIF1α, VEGFA, and BCL2, and decreased the level of BAX and phosphorylated p65. Safflower shows a significant cardioprotective effect by activating multiple inflammation-related signaling pathways, including the NFκB, HIF-1α, MAPK, TNF, and PI3K/AKT signaling pathways. These findings provide valuable insights into the clinical applications of safflower. [ABSTRACT FROM AUTHOR]

In recent years, ozone and PM 2.5 pollution has often occured in the Fenwei Plain due to heavy emission and favorable geographical conditions. In this study, we used the weather research and forecasting/chemistry (WRF-Chem) model to reproduce the complex air pollution of the ozone and PM 2.5 in the Fenwei Plain (FWP) from 20 May to 29 May 2015. By comparing the simulation results with the observed data, we found that although in some cities there was a bias between the simulated values and observed data, the model captured the trend of pollutants generally. Moreover, according to the assessment parameters, we validated that the deviations are acceptable. However, according to these parameters, we found that the WRF-Chem performed better on ozone simulation rather than PM 2.5 . Based on the validation, we further analyzed the pollutant distribution during the contaminated period. Generally speaking, the polluted area is mainly located in the cities of the Shanxi province and Henan province. Moreover, in this time period, pollution mainly occurred on 27 May and 28 May. In addition, due to different formation conditions of ozone and PM 2.5 pollution, the distribution characteristics of these two pollutants were also found to be different. Ozone pollution mainly occurred north of FWP due to the prevailing wind and the chemistry of ozone production. As for PM 2.5 , the pollution occurred at night and the polluted area was located in the FWP. Furthermore, high PM 2.5 areas were closed to emission sources in the FWP, showing a high correlation with primary emissions. [ABSTRACT FROM AUTHOR]

The reactive-transportation of radioactive elements in fractured rock mass is critical to the storage of radioactive elements. To describe the reactive-transportation and distribution morphology of a uranium-containing solution, a stress-dependent reactive transport model was developed, and the simulator of FLAC3D-CFD was employed. The uranium transport experiment subjected to the variation of confining stress of 5–19 MPa and hydraulic pressure of 0.5–3.5 MPa was conducted in fractured rock mass. The results show that the uranium-containing solution transport and distribution is significantly dependent on the evolution of the connected channel in rough-walled fracture, which is significantly influenced by the confining stress and hydraulic pressure. In more detail, the increase of confining stress resulted in the anisotropic of seepage channel in aperture, and corresponding turbulence flow and uranium retention were presented at the fracture aperture of 2–5 μm. As the increase of hydraulic pressure, flow regime evolved from the inertial flow to vortex flow, and the transformation region is 16 MPa confining stress and 1.5 MPa hydraulic pressure. The evolution of loading paths also dominates the flow and solute transport, and high seepage speed and strong solute transport were presented at the k = 1 (ratio of vertical stress loading to horizontal stress unloading), and a laminar flow and weak solute transport were presented at k = 0. [ABSTRACT FROM AUTHOR]

Thermally conductive and electrically insulating materials have attracted much attention due to their applications in the field of microelectronics, but through-plane thermal conductivity of materials is still low at present. In this paper, a simple and environmentally friendly strategy is proposed to improve the through-plane thermal conductivity of epoxy composites using a 3D boron nitride (3D-BN) framework. In addition, the effect of filler sizes in 3D-BN skeletons on thermal conductivity was investigated. The epoxy composite with larger BN in lateral size showed a higher through-plane thermal conductivity of 2.01 W/m·K and maintained a low dielectric constant of 3.7 and a dielectric loss of 0.006 at 50 Hz, making it desirable for the application in microelectronic devices. [ABSTRACT FROM AUTHOR]

Cyanidin-3-O-glucoside (C3G), an active ingredient in anthocyanins, mainly exists in dark cereals. C3G was investigated for its effect on human gastric cancer (GC) cells, together with its molecular mechanism. The CCK-8 assay results showed that C3G had significant antiproliferative effects on GC cells, but it had little effect on normal cells. Western blot and flow cytometry results showed that C3G regulated the reduction of mitochondrial membrane potential and arrested the cell cycle in the G2/M phase through the AKT signaling pathway, causing the cells to undergo apoptosis. Additionally, in MKN-45 cells, C3G markedly raised intracellular reactive oxygen species (ROS) levels. The wound healing assay and Transwell assay results showed that MKN-45 cell migration was significantly inhibited. Western blot results showed that the expression of E-cadherin protein was upregulated and the expressions of β-catenin, N-cadherin, and Vimentin were downregulated. Additionally, following N-acetylcysteine treatment, the expression levels of these proteins were reduced. In conclusion, C3G caused MKN-45 cells to undergo apoptosis; arrested the cell cycle in the G2/M phase; hindered cell migration; and activated the MAPK, STAT3, and NF-κB signaling pathways, by inducing an increase in ROS levels. Thus, C3G may be a promising new medication for the treatment of GC. [ABSTRACT FROM AUTHOR]

Population distribution data with high spatiotemporal resolution are of significant value and fundamental to many application areas, such as public health, urban planning, environmental change, and disaster management. However, such data are still not widely available due to the limited knowledge of complex human activity patterns. The emergence of location-based service big data provides additional opportunities to solve this problem. In this study, we integrated ambient population data, nighttime light data, and building volume data; innovatively proposed a spatial downscaling framework for Baidu heat map data during work time and sleep time; and mapped the population distribution with high spatiotemporal resolution (i.e., hourly, 100 m) in Beijing. Finally, we validated the generated population distribution maps with high spatiotemporal resolution using the highest-quality validation data (i.e., mobile signaling data). The relevant results indicate that our proposed spatial downscaling framework for both work time and sleep time has high accuracy, that the distribution of the population in Beijing on a regular weekday shows "centripetal centralization at daytime, centrifugal dispersion at night" spatiotemporal variation characteristics, that the interaction between the purpose of residents' activities and the spatial functional differences leads to the spatiotemporal evolution of the population distribution, and that China's "surgical control and dynamic zero COVID-19" epidemic policy was strongly implemented. In addition, our proposed spatial downscaling framework can be transferred to other regions, which is of value for governmental emergency measures and for studies about human risks to environmental issues. [ABSTRACT FROM AUTHOR]

Humidity sensors are important in industrial fields and human activities. Metal−organic frameworks (MOFs) and their derivatives are a class of promising humidity−sensing materials with the characteristics of a large specific surface area, high porosity, modifiable frameworks, and high stability. The drawbacks of MOFs, such as poor film formation, low electrical conductivity, and limited hydrophilicity, have been gradually overcome with the development of material science. Currently, it is moving towards a critical development stage of MOF−based humidity sensors from usability to ease of use, of which great challenges remain unsolved. In order to better understand the related challenges and point out the direction for the future development of MOF−based humidity sensors, we reviewed the development of such sensors based on related published work, focusing on six primary types (impedance, capacitive, resistive, fluorescent, quartz crystal microbalance (QCM), and others) and analyzed the sensing mechanism, material design, and sensing performance involved, and presented our thoughts on the possible future research directions. [ABSTRACT FROM AUTHOR]

A mangrove is a unique ecosystem with abundant resources, in which fungi are an indispensable microbial part. Numerous mangrove fungi-derived secondary metabolites are considerable sources of novel bioactive substances, such as polyketides, terpenoids, alkaloids, peptides, etc., which arouse people's interest in the search for potential natural anti-tumor drugs. This review includes a total of 44 research publications that described 110 secondary metabolites that were all shown to be anti-tumor from 39 mangrove fungal strains belonging to 18 genera that were acquired from the South China Sea between 2016 and 2022. To identify more potential medications for clinical tumor therapy, their sources, unique structures, and cytotoxicity qualities were compiled. This review could serve as a crucial resource for the research status of mangrove fungal-derived natural products deserving of further development. [ABSTRACT FROM AUTHOR]

Developing a catalyst with high SO2 and H2O resistance to achieve high-performance CO oxidation for specific industrial applications is highly desirable. Here, three catalysts were prepared using cerium titanium composite oxide (CeTi), molybdophosphate with Keggin structure-modified CeTi (Keg-CeTi), and molybdophosphate without Keggin structure-modified CeTi (MoP-CeTi) as supports, and their sulfur and water resistance in CO oxidation were tested. The characterization of XRD, BET, SO2/H2O-DRIFTS, XPS, TEM, SEM, NH3/SO2-TPD, H2-TPR, and ICP techniques revealed that the high SO2 and H2O resistance of Pt/Keg-CeTi in CO oxidation was related to its stronger surface acidity, better reduction of surface cerium and molybdenum species, and lower SO2 adsorption and transformation compared to Pt/CeTi and Pt/MoP-CeTi. [ABSTRACT FROM AUTHOR]

Zirconium oxide (ZrO2) is widely used as the thermal barrier coating in turbines and engines. Accurate emissivity measurement of ZrO2 coating at high temperatures, especially above 1000 °C, plays a vital role in thermal modelling and radiation thermometry. However, it is an extremely challenging enterprise, and very few high temperature emissivity results with rigorously estimated uncertainties have been published to date. The key issue for accurately measuring the high temperature emissivity is maintaining a hot surface without reflection from the hot environment, and avoiding passive or active oxidation of material, which will modify the emissivity. In this paper, a novel modified integrated blackbody method is reported to measure the high temperature normal spectral emissivity of ZrO2 coating in the temperature range 1000 °C to 1200 °C and spectral range 8 μm to 14 μm. The results and the associated uncertainty of the measurement were estimated and a relative standard uncertainty better than 7% (k = 2) is achieved. [ABSTRACT FROM AUTHOR]

In this article, the sum secure degrees-of-freedom (SDoF) of the multiple-input multiple-output (MIMO) X channel with confidential messages (XCCM) and arbitrary antenna configurations is studied, where there is no channel state information (CSI) at two transmitters and only delayed CSI at a multiple-antenna, full-duplex, and decode-and-forward relay. We aim at establishing the sum-SDoF lower and upper bounds. For the sum-SDoF lower bound, we design three relay-aided transmission schemes, namely, the relay-aided jamming scheme, the relay-aided jamming and one-receiver interference alignment scheme, and the relay-aided jamming and two-receiver interference alignment scheme, each corresponding to one case of antenna configurations. Moreover, the security and decoding of each scheme are analyzed. The sum-SDoF upper bound is proposed by means of the existing SDoF region of two-user MIMO broadcast channel with confidential messages (BCCM) and delayed channel state information at the transmitter (CSIT). As a result, the sum-SDoF lower and upper bounds are derived, and the sum-SDoF is characterized when the relay has sufficiently large antennas. Furthermore, even assuming no CSI at two transmitters, our results show that a multiple-antenna full-duplex relay with delayed CSI can elevate the sum-SDoF of the MIMO XCCM. This is corroborated by the fact that the derived sum-SDoF lower bound can be greater than the sum-SDoF of the MIMO XCCM with output feedback and delayed CSIT. [ABSTRACT FROM AUTHOR]

Waterborne polyurethane, renowned for its lightweight properties, excellent insulation capabilities, and corrosion resistance, has found extensive application in fields such as construction, automotive, leather, and thermal insulation. Nevertheless, during operational usage, waterborne polyurethane materials, akin to other polymeric substances, are susceptible to oxidative aging manifestations like yellowing, cracking, and diminished mechanical performance, significantly curtailing their utility. Consequently, the synthesis of yellowing-resistant polyurethane assumes pivotal significance. This study integrates dynamic reversible reactions into the synthesis process of polyurethane by introducing the dynamic reversible compound 2-hydroxyethyl disulfide as a chain extender, alongside the incorporation of a UV absorber to enhance the polyurethane's resistance to yellowing. When the disulfide bonds absorb heat, they undergo cleavage, yielding thiols that spontaneously recombine into disulfide bonds at ambient temperatures, allowing for the continuous breaking and reformation of disulfide bonds to absorb heat. Concurrently, in collaboration with the UV absorber, the detrimental effects of ultraviolet radiation on the polyurethane material are mitigated, thereby augmenting its resistance to yellowing. This study scrutinizes the positioning of UV absorber addition, the quantity of UV absorber, and the molar ratio of 1,4-butanediol to 2-hydroxyethyl disulfide, characterizing the functional groups of polyurethane through infrared and Raman spectroscopy. It is observed that the successful preparation of yellowing-resistant polyurethane is achieved, and evaluations on the modified polyurethane through color difference, tensile, and centrifugal tests reveal that the optimal yellowing resistance is attained by adding a UV absorber at a mass fraction of 1% to 3% prior to chain extension, resulting in a color change grade of 2, denoting slight discoloration. Simultaneously, the other properties of polyurethane exhibit relative stability. Notably, when the molar ratio of 1,4-butanediol to 2-hydroxyethyl disulfide is 3:2, the overall performance of the polyurethane remains stable, with exceptional yellowing resistance capabilities attaining a color change grade of 2. [ABSTRACT FROM AUTHOR]

Since the Industrial Revolution, fossil fuels have become the main energy source for economic development. However, fossil fuels have also been linked to serious environmental impacts. China has recently undergone rapid economic growth, but its development model demands large amounts of energy and causes severe pollution. Therefore, there has been a recent shift toward the development of coordinated strategies to achieve economic growth while minimizing energy consumption and preserving the environment. This study sought to explore the spatiotemporal evolution of the coordination degree between economic growth, energy consumption, and environmental conservation (i.e., the "3E" system) in China, thus establishing a basis to improve coordinated development and minimize regional differences. This study evaluated 30 Chinese provinces using mathematical models. Between 2000 and 2019, the coordinated development level of the components of the 3E system in China increased steadily but remained generally low. Clear spatial agglomeration was also identified at the provincial scale, with the highest values occurring on the east coast and lower values occurring in the west and middle provinces. [ABSTRACT FROM AUTHOR]

Deep-learning technologies, especially convolutional neural networks (CNNs), have achieved great success in building extraction from areal images. However, shape details are often lost during the down-sampling process, which results in discontinuous segmentation or inaccurate segmentation boundary. In order to compensate for the loss of shape information, two shape-related auxiliary tasks (i.e., boundary prediction and distance estimation) were jointly learned with building segmentation task in our proposed network. Meanwhile, two consistency constraint losses were designed based on the multi-task network to exploit the duality between the mask prediction and two shape-related information predictions. Specifically, an atrous spatial pyramid pooling (ASPP) module was appended to the top of the encoder of a U-shaped network to obtain multi-scale features. Based on the multi-scale features, one regression loss and two classification losses were used for predicting the distance-transform map, segmentation, and boundary. Two inter-task consistency-loss functions were constructed to ensure the consistency between distance maps and masks, and the consistency between masks and boundary maps. Experimental results on three public aerial image data sets showed that our method achieved superior performance over the recent state-of-the-art models. [ABSTRACT FROM AUTHOR]

Vegetation in the terrestrial ecosystem, sensitive to climate change and human activities, exerts a crucial influence on the carbon cycles in land, ocean, and atmosphere. Discrimination between climate and human-induced vegetation dynamics is advocated but still limited, especially in coastal China, which is characterized by a developed economy, a large population, and high food production, but also by unprecedented climate change and warming. Taking coastal China as the research area, our study used the normalized difference vegetation index (NDVI) in growing seasons, as well as precipitation, temperature, and sunlight hours datasets, adopted residual trend analysis at pixel and regional scales in coastal China from 2000–2019 and aims to (1) delineate the patterns and processes of vegetation changes, and (2) separate the relative contributions of climate and human activities by adopting residual trend analysis. The results indicated that (1) coastal China experienced the most vegetation greening (83.04% of the whole region) and partial degradation (16.86% of the whole region) with significant spatial heterogeneity; (2) compared with climate change, human activities have a greater positive impact on NDVI, and the regions were mainly located in the north of the North China Plain and the south of southern China; (3) the relative contribution rates of climate change and human activities were detected to be 0–60% and 60–100%, respectively; (4) in the northern coastal areas, the improvement of cultivated land management greatly promoted the greening of vegetation and thus the increase of grain yield, while in southern coastal areas, afforestation and the restoration of degraded forest were responsible for vegetation restoration; and (5) similar results obtained by partial correlation between nighttime lights and NDVI indicated the reliability of the residual trend analysis. The linear relationships of precipitation, temperature, and radiation on NDVI may limit the accurate estimation of climate drivers on vegetation, and further ecosystem process-modeling approaches can be used to estimate the relative contribution of climate change and human activities. The findings in our research emphasized that the attribution for vegetation dynamics with heterogeneity can provide evidence for the designation of rational ecological conservation policies. [ABSTRACT FROM AUTHOR]

Due to the proliferation of precision agriculture, the obstacle of estimating evapotranspiration (ET) and its components from shadow pixels acquired from remote sensing technology should not be neglected. To accurately detect shaded soil and leaf pixels and quantify the implications of shadow pixels on ET inversion, a two-year field-scale observation was carried out in the growing season for a pinot noir vineyard. Based on high-resolution remote sensing sensors covering visible light, thermal infrared, and multispectral light, the supervised classification was applied to detect shadow pixels. Then, we innovatively combined the normalized difference vegetation index with the three-temperature model to quantify the proportion of plant transpiration (T) and soil evaporation (E) in the vineyard ecosystem. Finally, evaluated with the eddy covariance system, we clarified the implications of the shadow pixels on the ET estimation and the spatiotemporal patterns of ET in a vineyard system by considering where shadow pixels were presented. Results indicated that the shadow detection process significantly improved reliable assessment of ET and its components. (1) The shaded soil pixels misled the land cover classification, with the mean canopy cover ignoring shadows 1.68–1.70 times more often than that of shaded area removal; the estimation accuracy of ET can be improved by 4.59–6.82% after considering the effect of shaded soil pixels; and the accuracy can be improved by 0.28–0.89% after multispectral correction. (2) There was a 2 °C canopy temperature discrepancy between sunlit leaves and shaded leaves, meaning that the estimation accuracy of T can be improved by 1.38–7.16% after considering the effect of shaded canopy pixels. (3) Simultaneously, the characteristics showed that there was heterogeneity of ET in the vineyard spatially and that E and T fluxes accounted for 238.05 and 208.79 W·m−2, respectively; the diurnal variation represented a single-peak curve, with a mean of 0.26 mm/h. Our findings provide a better understanding of the influences of shadow pixels on ET estimation using remote sensing techniques. [ABSTRACT FROM AUTHOR]

Remote sensing images contain complex backgrounds and multi-scale objects, which pose a challenging task for scene classification. The performance is highly dependent on the capacity of the scene representation as well as the discriminability of the classifier. Although multiple models possess better properties than a single model on these aspects, the fusion strategy for these models is a key component to maximize the final accuracy. In this paper, we construct a novel dual-model architecture with a grouping-attention-fusion strategy to improve the performance of scene classification. Specifically, the model employs two different convolutional neural networks (CNNs) for feature extraction, where the grouping-attention-fusion strategy is used to fuse the features of the CNNs in a fine and multi-scale manner. In this way, the resultant feature representation of the scene is enhanced. Moreover, to address the issue of similar appearances between different scenes, we develop a loss function which encourages small intra-class diversities and large inter-class distances. Extensive experiments are conducted on four scene classification datasets include the UCM land-use dataset, the WHU-RS19 dataset, the AID dataset, and the OPTIMAL-31 dataset. The experimental results demonstrate the superiority of the proposed method in comparison with the state-of-the-arts. [ABSTRACT FROM AUTHOR]

Wind profiling within operating wind farms is important for both wind resource assessment and wind power prediction. With increasing wind turbine size, it is getting difficult to obtain wind profiles covering the turbine-affecting area due to the limited height of wind towers. In this study, a stepwise quality control and optimizing process for deriving high-quality near-surface wind profiles within wind farms is proposed. The method is based on the radial wind speed obtained by the Doppler Wind Lidar velocity-azimuth display (VAD) technique. The method is used to obtain the whole wind profile from ground level to the height affected by wind turbines within a utility-scale onshore wind farm, in northern China. Compared with the traditional carrier-to-noise ratio (CNR) filter-based quality control method, the proposed data processing method can significantly improve the accuracy of the derived wind. For a 10 m wind speed, an increase in coefficient of determination (R2) from 0.826 to 0.932, and a decrease in mean absolute error (MAE) from 1.231% to 0.927% are obtained; while for 70 m wind speed, R2 increased from 0.926 to 0.958, and MAE decreased from 1.023% to 0.771%. For wind direction, R2 increased from 0.978 to 0.992 at 10 m, and increased from 0.983 to 0.995 at 70 m. The optimized method also presents advantages in improving the accuracy of derived wind under complex wind environments, e.g., inside a wind farm, and increasing the data availability during clear nights. The proposed method could be used to derive wind profiles from below the minimum range of a vertically operating scanning Doppler Lidar to a height affected by wind turbines. Combined with Doppler beam-swinging (DBS) scanning data, the method could be used to obtain the complete wind profile in the boundary layer. These wind profiles could be further used to predict wind power and evaluate the climate and environmental effects of wind farms. [ABSTRACT FROM AUTHOR]

Aqueous zinc ion batteries (AZIBs) have emerged as a promising battery technology due to their excellent safety, high capacity, low cost, and eco-friendliness. However, the cycle life of AZIBs is limited by severe side reactions and zinc dendrite growth on the zinc electrode surface, hindering large-scale application. Here, an electrolyte optimization strategy utilizing the simplest dipeptide glycylglycine (Gly-Gly) additive is first proposed. Theoretical calculations and spectral analysis revealed that, due to the strong interaction between the amino group and Zn atoms, Gly-Gly preferentially adsorbs on zinc's surface, constructing a stable and adaptive interfacial layer that inhibits zinc side reactions and dendrite growth. Furthermore, Gly-Gly can regulate zinc ion solvation, leading to a deposition mode shift from dendritic to lamellar and limiting two-dimensional dendrite diffusion. The symmetric cell with the addition of a 20 g/L Gly-Gly additive exhibits a cycle life of up to 1100 h. Under a high current density of 10 mA cm−2, a cycle life of 750 cycles further demonstrates the reliable adaptability of the interfacial layer. This work highlights the potential of Gly-Gly as a promising solution for improving the performance of AZIBs. [ABSTRACT FROM AUTHOR]

In this study, crumpled graphene balls (CGB), a kind of nano-material, was used as an additive to improve the tribological properties of base oil. Nano-magnesium silicate hydroxide (MSH)/CGB composites were prepared by ultrasound-assisted liquid-phase exfoliation. The loading of MSH significantly increased the number of pleats and reduced the lamellar thickness of CGB. Then, in order to improve the compatibility with the base oil, the MSH/CGB composites were decorated with oleic acid and stearic acid to get modified lipophilic composites (ML-MSH/CGB). The ML-MSH/CGB were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM). In addition, the tribological properties of the ML-MSH/CGB in base oils were investigated using a ball-on-disc setup tribometer. It indicated that the fantastic tribological behavior of the ML-MSH/CGB in base oil may contribute to a smaller and extremely wrinkled laminated structure. Furthermore, the base oil with 0.005 wt% ML-MSH/CGB composites exhibited the best anti-friction effect, and its average friction coefficient, wearing capacity and wear scar diameter were reduced by 25.4%, 22.1% and 16.7%, respectively. The introduction of ML-MSH/CGB composed materials is an excellent strategy to optimize the friction performance of lubricating oil. [ABSTRACT FROM AUTHOR]