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Pregnancy monitoring is always essential for pregnant women and fetuses. According to the report of WHO (World Health Organization), there were an estimated 287,000 maternal deaths worldwide in 2020. Regular hospital check-ups, although well established, are a burden for pregnant women because of frequent travelling or hospitalization. Therefore, home-based, long-term, non-invasive health monitoring is one of the hot research areas. In recent years, with the development of wearable sensors and related data-processing technologies, pregnancy monitoring has become increasingly convenient. This article presents a review on recent research in wearable sensors, physiological data processing, and artificial intelligence (AI) for pregnancy monitoring. The wearable sensors mainly focus on physiological signals such as electrocardiogram (ECG), uterine contraction (UC), fetal movement (FM), and multimodal pregnancy-monitoring systems. The data processing involves data transmission, pre-processing, and application of threshold-based and AI-based algorithms. AI proves to be a powerful tool in early detection, smart diagnosis, and lifelong well-being in pregnancy monitoring. In this review, some improvements are proposed for future health monitoring of pregnant women. The rollout of smart wearables and the introduction of AI have shown remarkable potential in pregnancy monitoring despite some challenges in accuracy, data privacy, and user compliance.

A third-generation wave model is driven by the synthetic wind field combined with the revised Holland wind and surface wind product from the National Centers for Environmental Prediction (NCEP). The temporal and spatial characteristics of the wind waves and swell during the typhoon are studied, as well as the responses of their wave energy spectra to the source terms. The results show that the typhoon waves have a more complicated asymmetric structure than the wind field, and the maximum significant wave height is always located on the right side of the direction along which the typhoon is moving, where wind waves are dominant, due to the extended fetch. The nonlinear wave–wave interaction helps to redistribute the energy of the wind seas at a high frequency to the remotely generated swells at a low frequency, ensuring that the typhoon wave’s energy spectrum remains unimodal. This process occurs in regions without extended fetch, and a similar continued downshift in frequency as the wave–wave interaction occurs for the wind input as well when the waves outrun the typhoon, due to the nonlinear coupling between the wind and growing swells.

Foundation Models (FMs) are gaining increasing attention in the biomedical artificial intelligence (AI) ecosystem due to their ability to represent and contextualize multimodal biomedical data. These capabilities make FMs a valuable tool for a variety of tasks, including biomedical reasoning, hypothesis generation, and interpreting complex imaging data. In this review paper, we address the unique challenges associated with establishing an ethical and trustworthy biomedical AI ecosystem, with a particular focus on the development of FMs and their downstream applications. We explore strategies that can be implemented throughout the biomedical AI pipeline to effectively tackle these challenges, ensuring that these FMs are translated responsibly into clinical and translational settings. Additionally, we emphasize the importance of key stewardship and co-design principles that not only ensure robust regulation but also guarantee that the interests of all stakeholders—especially those involved in or affected by these clinical and translational applications—are adequately represented. We aim to empower the biomedical AI community to harness these models responsibly and effectively. As we navigate this exciting frontier, our collective commitment to ethical stewardship, co-design, and responsible translation will be instrumental in ensuring that the evolution of FMs truly enhances patient care and medical decision-making, ultimately leading to a more equitable and trustworthy biomedical AI ecosystem.

El Niño–Southern Oscillation (ENSO) usually peaks in the boreal winter—November to January of the following year. This particular feature of ENSO is known as the seasonal phase locking of ENSO. In this study, based on 34 climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), the seasonal phase-locking characteristics of the model-simulated El Niño and La Niña events are evaluated in terms of the evolution of the SST anomalies associated with ENSO and the probability distribution of the peak month—the time at which ENSO peaks. It is found that CMIP6 models underestimate the phase-locking strength of ENSO for both El Niño and La Niña events. The ensemble mean peak month matches the observations, but the inter-model spread is large. The models simulate the phase locking of El Nino events better than that of La Niña events, and the large simulation bias of CMIP6 for La Niña phase-locking in the models may have an impact on the simulation of seasonal phase-locking in the ENSO.

Plant cells’ ability to withstand abiotic stress is strongly linked to modifications in their mechanical characteristics. Nevertheless, the lack of a workable method for consistently tracking plant cells’ mechanical properties severely restricts our comprehension of the mechanical alterations in plant cells under stress. In this study, we used the Double Resonator Piezoelectric Cytometry (DRPC) method to dynamically and non-invasively track changes in the surface stress (ΔS) generated and viscoelasticity (storage modulus G′ and loss modulus G″) of protoplasts and suspension cells of rice under a drought stress of 5–25% PEG6000. The findings demonstrate that rice suspension cells and protoplasts react mechanically differently to 5–15% PEG6000 stress, implying distinct resistance mechanisms. However, neither of them can withstand 25% PEG6000 stress; they respond mechanically similarly to 25% PEG6000 stress. The results of DRPC are further corroborated by the morphological alterations of rice cells and protoplasts observed under an optical microscope. To sum up, the DRPC technique functions as a precise cellular mechanical sensor and offers novel research tools for the evaluation of plant cell adversity and differentiating between the mechanical reactions of cells and protoplasts under abiotic stress.

As social robots become more prevalent, they often employ non-speech sounds, in addition to other modes of communication, to communicate emotion and intention in an increasingly complex visual and audio environment. These non-speech sounds are usually tailor-made, and research into the generation of non-speech sounds that can convey emotions has been limited. To enable social robots to use a large amount of non-speech sounds in a natural and dynamic way, while expressing a wide range of emotions effectively, this work proposes an automatic method of sound generation using a genetic algorithm, coupled with a random forest model trained on representative non-speech sounds to validate each produced sound’s ability to express emotion. The sounds were tested in an experiment wherein subjects rated the perceived valence and arousal. Statistically significant clusters of sounds in the valence arousal space corresponded to different emotions, showing that the proposed method generates sounds that can readily be used in social robots.

Selective laser melting (SLM) forms specimens that often exhibit anisotropic mechanical properties. Most existing research only explains that the mechanical properties of specimens perpendicular to the build direction are superior to those parallel to the build direction. In this paper, the mechanical properties of SLM 316L SS specimens with different surfaces and different directions are compared. Finally, it was found that the mechanical properties of specimens on Face 3 are stronger than those on Face 1 and Face 2, while the mechanical properties of specimens on Face 1 and Face 2 are similar. For specimens in different directions on the same surface, the mechanical properties of Face 1 and Face 2 exhibit clear anisotropy, while the mechanical properties of Face 3 tend to be isotropic. In this paper, the EBSD technique was used to analyze the specimens. It was found that the anisotropy of the mechanical properties of Face 1 and Face 2 are attributed to the presence of texture and columnar crystals in the sample. This paper can provide accurate and reliable material performance data for the practical application of SLM 316L SS, thereby guiding the optimization of engineering design and manufacturing processes.

Since sheet metal exhibits significant anisotropy in processing and forming, which has a significant impact on its performance during processing, forming, and use, we explore the anisotropic behavior of materials in the forming process of sheet metal. The ability of the Yld2000-2d criterion to describe anisotropic behavior is analyzed, and its accuracy for characterization of the anisotropic behavior of metal plates is improved, based on which anisotropic behavior is predicted in three-dimensional space. Theoretical and experimental results on the anisotropy of sheet metal are compared, and two materials, 5754O aluminum alloy and DP980 steel plate, are tested and analyzed, and the anisotropic behaviors, such as three-point bending and cylindrical deep-drawing, are well predicted.

This study explores the diversity in emotional tendencies and needs toward urban green spaces (UGSs) among people from different cultural backgrounds in the wave of cultural integration. We utilized social media data as research tools, gathering a wide range of perspectives and voices. Utilizing geolocation data from 176 UGSs in Macau, we collected 139,162 social media comments to analyze the emotional perceptions of different cultural groups. Furthermore, we conducted regression analysis on the number of posts and emotional intensity values from four linguistic groups—Chinese, English, Southeast Asian languages, and Portuguese—in UGSs, correlating them with ten locally relevant landscape features. Our findings reveal diverse attitudes, emotional inclinations, and functional and design needs of different linguistic groups toward UGSs, as follows: (1) there were significant differences in emotional intensity and tweet counts across 176 UGSs; (2) Chinese and Portuguese speakers showed a more positive attitude toward plazas and natural ecological areas, whereas English- and Southeast-Asian-language speakers tended to favor recreational areas and suburban parks; (3) Chinese speakers exhibited a more positive emotional intensity toward sports facilities, while English speakers placed more emphasis on green space areas, architecture, sports infrastructure, and plant landscapes; (4) there was no specific landscape feature preference for Portuguese- and Southeast-Asian-language speakers. This research not only deepens our understanding of the emotional perceptions and preferences of UGSs among different cultural groups but also explores the association between these groups and various urban landscape features. This provides important theoretical and practical insights for future UGS planning, construction, and promoting multicultural coexistence for sustainable urban development.

In today’s context of flourishing tourism, the development of urban tourism leads to a continuous influx of population. Existing empirical evidence highlights the interaction between tourists’ and residents’ perception of urban spaces and the local society and living spaces. This study, focusing on Macau, utilizes the region’s streetscape images to construct a deep learning-based model for quantifying the urban street perception of tourists and local residents. To obtain more refined perceptual evaluation data results, during the training phase of the model, we intentionally categorized tourist activities into natural landscape tours, historical sightseeing, and entertainment area visits, based on the characteristics of the study area. This approach aimed to develop a more refined perception evaluation method based on the classification of urban functional areas and the types of urban users. Further, to improve the streetscape environment and reduce visitor and resident dissatisfaction, we delved into the differences in perception between tourists and residents in various functional urban areas and their relationships with different streetscape elements. This study provides a foundational research framework for a comprehensive understanding of residents’ and tourists’ perceptions of diverse urban street spaces, emphasizing the importance of exploring the differentiated perceptions of streetscapes held by tourists and residents in guiding scientific urban tourism development policies and promoting social sustainability in cities, particularly those where tourism plays a significant role.

Micro-LED is considered an emerging display technology with significant potential for high resolution, brightness, and energy efficiency in display applications. However, its decreasing pixel size and complex manufacturing process create challenges for its integration with driving units. Recently, researchers have proposed various methods to achieve highly integrated micro-structures with driving unit. Researchers take advantage of the high performance of the transistors to achieve low power consumption, high current gain, and fast response frequency. This paper gives a review of recent studies on the new integration methods of micro-LEDs with different types of transistors, including the integration with BJT, HEMT, TFT, and MOSFET.

Identifying the parameters of multispan rigid frames is challenging because of their complex structures and large computational workloads. This paper presents a stiffness separation method for the static response parameter identification of multispan rigid frames. The stiffness separation method segments the global stiffness matrix of the overall structure into the stiffness matrices of its substructures, which are to be computed, thereby reducing the computational workload and improving the efficiency of parameter identification. Loads can be applied individually to each separate substructure, thereby guaranteeing obvious local static responses. The veracity and efficacy of the proposed methodology are substantiated by applying it to three- and eight-span continuous rigid frame structures. The findings indicate that the proposed approach significantly enhances the efficiency of parameter identification for multispan rigid frames.

Background: Pancreatic ductal adenocarcinoma (PDAC) is the most prevalent subtype of pancreatic cancer and one of the most malignant tumors worldwide. Due to the heterogeneity of its genomics and proteomics, the prognosis of PDAC remains disappointing despite advances in surgery and medicines. Recently, a novel form of programmed cell death, cuproptosis, was proposed, although its role in PDAC has not been investigated. This study aimed to quantify the expression of cuproptosis-related genes and characterize the novel subtypes of PDAC. Methods: To evaluate the pattern of cuproptosis in PDAC, the gene expression data and clinical information of 372 samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. A consensus cluster analysis was performed using the transcriptional levels, genetic alterations, and individual prognostic values of seven pre-selected cuproptosis-related genes (DLAT, LIPT1, FDX1, DLD, PDHB, PDHA1, and LIAS) to identify the novel subtypes associated with cuproptosis in PDAC. A univariate Cox regression analysis was used to determine the significant prognostic indicators and cuproptosis scores among the differentially expressed genes (DEGs) between the dividing subclusters, followed by a principal component analysis. The prognostic values, immune profiles, treatment sensitivities, and cuproptosis scores were evaluated between the different subgroups. Results: Seven cuproptosis-related genes showed aberrant expression levels and genetic alterations in the PDAC tumor microenvironment. Among them, LIPT1, LIAS, DLAT, PDHA1, and DLD were significantly correlated with overall survival. Based on the expression profiles of the seven cuproptosis-related genes, three cuproptosis clusters (Clusters A, B, and C) were identified, which were represented by different clinicopathologic features, gene expression levels, and biological processes. A total of 686 DEGs were identified among the three cuproptosis clusters, of which 35 prognosis-related DEGs were selected to further classify the PDAC samples into two subgroups with different survival rates, clinicopathologic features, immune infiltration levels, and drug sensitivities. Higher cuproptosis scores were associated with a significantly poorer prognosis. Conclusion: The cuproptosis subtypes, scores, and relevant genes represent valuable information for assessing the heterogeneity, treatment, and prognosis of PDAC.

The antimicrobial quantitative structure–activity relationship of plant flavonoids against Gram-positive bacteria was established in our previous works, and the cell membrane was confirmed as a major site of action. To investigate whether plant flavonoids have similar antibacterial effects and mechanisms against both Gram-negative and Gram-positive bacteria, here, the minimum inhibitory concentrations (MICs) of 37 plant flavonoids against Escherichia coli were determined using the microdilution broth method, and then the correlation between their lipophilic parameter ACD/LogP or LogD7.40 value and their MIC was analyzed. Simultaneously, the correlation between the ACD/LogP or LogD7.40 value and the MIC of 46 plant flavonoids reported in the literature against E. coli was also analyzed. Both sets of results showed that there is a significant correlation between the LogP value and the MIC of plant flavonoids against Gram-negative bacteria. However, it is difficult to effectively predict the MIC of plant flavonoids against Gram-negative bacteria from their lipophilic parameters. By comparing two regression curves derived from plant flavonoids against Gram-negative and Gram-positive bacteria, it was further discovered that the antibacterial activities of most plant flavonoids against Gram-negative bacteria are stronger than those against Gram-positive bacteria when their LogP values are less than approximately 3.0, but the opposite is true when their LogP values are more than approximately 3.6. Moreover, this comparison also suggests that unlike mainly acting on the cell membrane of Gram-positive bacteria, plant flavonoids have multiple mechanisms against Gram-negative species, while the cell membrane is also an important action site among them. Combined with the correlation analyses between the enzyme inhibitory activity and the LogP value of the reported flavonoids, it was further suggested that DNA gyrase is another important target of plant flavonoids against Gram-negative bacteria.

This study aims to analyze the perceptions and driving factors behind villagers’ changing perceptions of landscape values in the context of drastic landscape changes in traditional Chinese villages. Empirical evidence emphasizes the interplay between local residents’ values and the local policy framework. This study establishes a method to capture the landscape values and preferences of rural community residents by combining participatory mapping with questionnaire interviews. We identified the evaluation of changing landscape values by rural residents and extracted four categories of rural development orientations, namely, economic benefits, emotional culture, public participation, and environmental protection. Furthermore, we delved into the significant heterogeneity in landscape value changes among different social groups. This study highlights the role of villagers’ value judgments in guiding the scientific formulation of traditional village conservation and development policies and promoting the socially sustainable development planning of traditional villages. The research contributes to a more comprehensive understanding of the rural community’s needs and preferences for the local landscape as well as the convergence and divergence between these needs and the government-led rural development trajectory.

This paper presents an anti-swing control method to prevent situations where inspection robots detach and fall off transmission lines during obstacle crossing due to excessive swing angles caused by the rotation of the robot around the transmission line. Firstly, an obstacle-crossing model for the inspection robot was constructed and the causes of robot swinging phenomena were analyzed, in addition to their impact on obstacle crossing stability. By combining this with the obstacle-crossing model, a moment balance equation was established for the inspection robot. This equation can be used to solve mapping relationships between body offset and the tilt angle of transmission line gripping arms. We propose an anti-swing control strategy by adjusting the angle of the transmission line gripping arm’s pitching joint to make the body offset approach zero, and by utilizing the advantages of fuzzy logic in the fuzzy PID algorithm compared with the traditional PID algorithm, it can adaptively avoid the occurrence of robot swinging phenomena. The experimental results of obstacle-crossing experiments under no wind and wind turbulence conditions indicated that the proposed anti-swing control method in this study can effectively keep the body offset to within 3 mm. Compared with the methods of not using anti-swing control and using traditional PID anti-swing control, in the absence of wind effects, the peak values of body offset were reduced by 96.53% and 18.85%, respectively. Under the influence of wind turbulence, the peak values of body offset were reduced by 97.02% and 27.12%, respectively. The effectiveness of the anti-swing control method proposed in this paper has thus been verified.

In the field of finance and insurance, addressing the optimal investment and reinsurance issue is a focal point for researchers. This paper contemplates the optimal strategy for insurance companies within a model where wealth dynamics adhere to a jump–diffusion process. The fractional structure of the diffusion term is extremely interpretative. This model encompasses elements of risky assets, risk-free assets, and proportional reinsurance. Based on this model and grounded in the principles of stochastic control, the corresponding HJB equation is derived and solved. Consequently, explicit expressions for the optimal investment and reinsurance ratios are obtained, and the solution’s verification theorem is proven. Finally, through a numerical analysis with varying parameters, results consistent with real-world scenarios are achieved.

A large perpendicular magnetic anisotropy and a high Curie temperature (TC) are crucial for the application of two-dimensional (2D) intrinsic ferromagnets to spintronic devices. Here, we investigated the electronic and magnetic properties of carrier-doped Van der Waals layered CrSX (X = Cl, Br, I) ferromagnets using first-principles calculations. It was found that hole doping can increase the magnitude of the magnetic anisotropy energy (MAE) and change the orientation of the easy magnetization axis at small doping amounts of 2.37 × 1013, 3.98 × 1012, and 3.33 × 1012/cm2 for CrSCl, CrSBr, and CrSI monolayers, respectively. The maximum values of the MAE reach 57, 133, and 1597 μeV/u.c. for the critical hole-doped CrSCl, CrSBr, and CrSI with spin orientation along the (001) direction, respectively. Furthermore, the Fermi energy level of lightly hole-doped CrSX (X = Cl, Br, I) moves into the spin-up valence band, leading to the CrSX (X = Cl, Br, I) magnetic semiconductor monolayer becoming first a half-metal and then a metal. In addition, the TC can also be increased up to 305, 317, and 345 K for CrSCl, CrSBr, and CrSI monolayers at doping amounts of 5.94 × 1014, 5.78 × 1014, and 5.55 × 1014/cm2, respectively. These properties suggest that the hole-doping process can render 2D CrSX (X = Cl, Br, I) monolayers remarkable materials for application to electrically controlled spintronic devices.

Sheath blight (ShB) disease, caused by Rhizoctonia solani Kühn, is one of the most serious rice diseases. Rice breeding against ShB has been severely hindered because no major resistance genes or germplasms are available in rice. Here, we report that introduction of Gastrodia antifungal protein (GAFP) genes from Gastrodia elata B1 into rice significantly enhances resistance to rice ShB. Four GAFP genes were cloned from G. elata B1, and all displayed a strong ability to inhibit R. solani growth in plate assays. Two versions, with or without a signal peptide, for each of the four GAFP genes were introduced into XD3 and R6547 rice cultivars, and all transgenic lines displayed stronger ShB resistance than the corresponding wild-type control in both greenhouse and field conditions. Importantly, GAFP2 showed the highest ShB resistance; GAFPs with and without its signal peptide showed no significant differences in enhancing ShB resistance. We also evaluated the agronomic traits of these transgenic rice and found that ectopic expression of GAFPs in rice at appropriate levels did not affect agronomic traits other than enhancing ShB resistance. Together, these results indicate that GAFP genes, especially GAFP2, have great potential in rice breeding against ShB disease.

Piezoelectric thin films grown on a mechanical, flexible mica substrate have gained significant attention for their ability to convert mechanical deformation into electrical energy though a curved surface. To extract the generated charge from the PZT thin films, bottom electrodes are typically grown on mica substrates. However, this bottom electrode also serves as a buffering layer for the growth of PZT films, and its impact on the piezoelectric properties of PZT thin films remains understudied. In this work, the effect of Pt and LaNiO3 bottom electrodes on the piezoelectric effect of a Pb(Zr0.52,Ti0.48)O3 thin film was investigated. It was observed that the PZT thin films on LNO/Mica substrate possessed weaker stress, stronger (100) preferred orientation, and higher remanent polarization, which is beneficial for a higher piezoelectric response theoretically. However, due to insufficient grain growth resulting in more inactive grain boundaries and lattice imperfections, the piezoelectric coefficient of the PZT thin film on LNO/Mica was smaller than that of the PZT thin film on a Pt/Mica substrate. Therefore, it is concluded that, under the current experimental conditions, PZT films grown with Pt as the bottom electrode are better suited for applications in flexible piezoelectric sensor devices. However, when using LNO as the bottom electrode, it is possible to optimize the grain size of PZT films by adjusting the sample preparation process to achieve piezoelectric performance exceeding that of the PZT/Pt/Mica samples.

The adverse effects of the transportation of O3 and its precursors on local air quality under certain meteorological conditions has long been recognized. Previous studies covered the effects of their transport without distinguishing specific forms (direct transport, via air pollutants originating from emissions outside the target regions; indirect transport, via air pollutants generated from chemical reactions between local and outside precursors) and processes (chemical and physical). This study aimed to figure out the effects of different scales of emissions on O3 pollution in the Guanzhong basin (GZB) by quantifying the forms and processes of transport using the CAMx model. The results showed that the emissions on different scales had various pathways for influencing O3 formation under two polluted, synoptic circulation types (southeast high and northeast ridge). Under the southeast high type, the meteorological conditions favored the chemical production of O3, which led to the highest local O3 contributions from the GZB. The prominent cross-regional transport was positive for indirect transport from south Shaanxi, implying the synergistic impacts of biogenic VOCs and urban pollutants in the GZB. With the southerly winds in the GZB, the downwind cities of Xi’an were impacted by positive direct and indirect transport from the emissions of Xi’an. These impacts occurred through the processes of gas-phase chemistry (especially O3P + O2 and O3 + NO) and vertical advection. For the northeast ridge type, positive direct transport from the emissions of Henan Province was important for O3 pollution in the GZB, as there were remarkable easterly airflows. From the east to the west of the GZB, the impacts from the emissions from Henan Province on cities in the GZB were reduced, which occurred through the processes of horizontal advection and vertical dispersion. This work highlights significant differences in the forms and processes of O3 formation in downwind areas impacted by the emissions from different-scale emissions, and advances our knowledge of atmospheric pollutant transport and its impact on O3 pollution.

Alite dissolution plays a crucial role in cement hydration. However, quantitative investigations into alite powder dissolution are limited, especially regarding the influence of chemical admixtures. This study investigates the impact of particle size, temperature, saturation level, and mixing speed on alite powder dissolution rate, considering the real-time evolution of specific surface area during the alite powder dissolution process. Furthermore, the study delves into the influence of two organic toughening agents, chitosan oligosaccharide (COS) and anionic/non-ionic polyester-based polyurethane (PU), on the kinetics of alite powder dissolution. The results demonstrate a specific-surface-area change formula during alite powder dissolution: SS0=0.348e1−m/m0/0.085+0.651. Notably, the temperature and saturation level significantly affect dissolution rates, whereas the effect of particle size is more complicated. COS shows dosage-dependent effects on alite dissolution, acting through both its acidic nature and surface coverage. On the other hand, PU inhibits alite dissolution by blocking the active sites of alite through electrostatic adsorption, which is particularly evident at high temperatures.

Diamond-based transistors have been considered as one of the best choices due to the numerous advantages of diamond. However, difficulty in the growth and fabrication of diamond needs to be addressed. In this paper, high quality diamond film with an atomically flat surface was grown by microwave plasma chemical vapor deposition. High growth rate, as much as 7 μm/h, has been acquired without nitrogen doping, and the root mean square (RMS) of the surface roughness was reduced from 0.92 nm to 0.18 nm by using a pre-etched process. H-terminated diamond MOSFETs were fabricated on a high-quality epitaxial diamond layer, of which the saturated current density was enhanced. The hysteresis of the transfer curve and the shift of the threshold voltage were significantly reduced as well.

In recent years, the rapid progress in the field of GaN-based power devices has led to a smaller chip size and increased power usage. However, this has given rise to increasing heat aggregation, which affects the reliability and stability of these devices. To address this issue, diamond substrates with nanostructures were designed and investigated in this paper. The simulation results confirmed the enhanced performance of the device with diamond nanostructures, and the fabrication of a diamond substrate with nanostructures is demonstrated herein. The diamond substrate with square nanopillars 2000 nm in height exhibited optimal heat dissipation performance. Nanostructures can effectively decrease heat accumulation, resulting in a reduction in temperature from 121 °C to 114 °C. Overall, the simulation and experimental results in this work may provide guidelines and help in the development of the advanced thermal management of GaN devices using diamond micro/nanostructured substrates.

Prostate-specific membrane antigen (PSMA)-based low-molecular-weight agents using beta(β)-particle-emitting radiopharmaceuticals is a new treatment paradigm for patients with metastatic castration-resistant prostate cancer. Although results have been encouraging, there is a need to improve the tumor residence time of current PSMA-based radiotherapeutics. Albumin-binding moieties have been used strategically to enhance the tumor uptake and retention of existing PSMA-based investigational agents. Previously, we developed a series of PSMA-based, β-particle-emitting, low-molecular-weight compounds. From this series, 177Lu-L1 was selected as the lead agent because of its reduced off-target radiotoxicity in preclinical studies. The ligand L1 contains a PSMA-targeting Lys-Glu urea moiety with an N-bromobenzyl substituent in the ε-amino group of Lys. Here, we structurally modified 177Lu-L1 to improve tumor targeting using two known albumin-binding moieties, 4-(p-iodophenyl) butyric acid moiety (IPBA) and ibuprofen (IBU), and evaluated the effects of linker length and composition. Six structurally related PSMA-targeting ligands (Alb-L1–Alb-L6) were synthesized based on the structure of 177Lu-L1. The ligands were assessed for in vitro binding affinity and were radiolabeled with 177Lu following standard protocols. All 177Lu-labeled analogs were studied in cell uptake and selected cell efficacy studies. In vivo pharmacokinetics were investigated by conducting tissue biodistribution studies for 177Lu-Alb-L2–177Lu-Alb-L6 (2 h, 24 h, 72 h, and 192 h) in male NSG mice bearing human PSMA+ PC3 PIP and PSMA− PC3 flu xenografts. Preliminary therapeutic ratios of the agents were estimated from the area under the curve (AUC0-192h) of the tumors, blood, and kidney uptake values. Compounds were obtained in >98% radiochemical yields and >99% purity. PSMA inhibition constants (Kis) of the ligands were in the ≤10 nM range. The long-linker-based agents, 177Lu-Alb-L4 and 177Lu-Alb-L5, displayed significantly higher tumor uptake and retention (p < 0.001) than the short-linker-bearing 177Lu-Alb-L2 and 177Lu-Alb-L3 and a long polyethylene glycol (PEG) linker-bearing agent, 177Lu-Alb-L6. The area under the curve (AUC0-192h) of the PSMA+ PC3 PIP tumor uptake of 177Lu-Alb-L4 and 177Lu-Alb-L5 were >4-fold higher than 177Lu-Alb-L2, 177Lu-Alb-L3, and 177Lu-Alb-L6, respectively. Also, the PSMA+ PIP tumor uptake (AUC0-192h) of 177Lu-Alb-L2 and 177Lu-Alb-L3 was ~1.5-fold higher than 177Lu-Alb-L6. However, the lowest blood AUC0-192h and kidney AUC0-192h were associated with 177Lu-Alb-L6 from the series. Consequently, 177Lu-Alb-L6 displayed the highest ratios of AUC(tumor)-to-AUC(blood) and AUC(tumor)-to-AUC(kidney) values from the series. Among the other agents, 177Lu-Alb-L4 demonstrated a nearly similar ratio of AUC(tumor)-to-AUC(blood) as 177Lu-Alb-L6. The tumor-to-blood ratio was the dose-limiting therapeutic ratio for all of the compounds. Conclusions: 177Lu-Alb-L4 and 177Lu-Alb-L6 showed high tumor uptake in PSMA+ tumors and tumor-to-blood ratios. The data suggest that linker length and composition can be modulated to generate an optimized therapeutic agent.

Shear deformation plays an important role in certain structures, and neglecting shear deformation can affect the accuracy of structural response. This paper proposes a non-destructive damage evaluation method that considers shear deformation, based on static response, for identifying corrosion in beam-like structures. The influence of shear deformation on nodal displacement for simply supported beams with different cross-sections was analyzed. The results indicate that even small errors yield inaccurate identification results when neglecting shear deformation. To solve this problem, analytical displacements of the structure were determined based on the Timoshenko beam theory, and the objective function was established. Additionally, the damage identification results were obtained by minimizing the objective function using the interior point method. Several progressively complex examples were used to demonstrate the effectiveness of the proposed method in identifying damage in beam-like structures.

A damage identification methodology considering shear deformation was presented in this paper to identify damage to semi-rigid frames with slender beams. On the basis of the successful identification of structural joint damage, the combined joint and member damage of the structure was identified. The objective function was formulated to minimize the discrepancies between the analytical and measured nodal displacements. Damage identification was performed on semi-rigid frame structures with different cross-sectional shapes, and the results were compared with those of ignoring shear deformation. Several frame structures were employed to verify the advantages and efficiency of the proposed method. The results demonstrate that the present method could significantly improve the accuracy of damage identification for semi-rigid frames compared with the method ignoring shear deformation.

Plant flavonoids have attracted increasing attention as new antimicrobial agents or adjuvants. In our previous work, it was confirmed that the cell membrane is the major site of plant flavonoids acting on the Gram-positive bacteria, which likely involves the inhibition of the respiratory chain. Inspired by the similar structural and antioxidant characters of plant flavonoids to hydro-menaquinone (MKH2), we deduced that the quinone pool is probably a key target of plant flavonoids inhibiting Gram-positive bacteria. To verify this, twelve plant flavonoids with six structural subtypes were preliminarily selected, and their minimum inhibitory concentrations (MICs) against Gram-positive bacteria were predicted from the antimicrobial quantitative relationship of plant flavonoids to Gram-positive bacteria. The results showed they have different antimicrobial activities. After their MICs against Staphylococcus aureus were determined using the broth microdilution method, nine compounds with MICs ranging from 2 to 4096 μg/mL or more than 1024 μg/mL were eventually selected, and then their MICs against S. aureus were determined interfered with different concentrations of menaquinone−4 (MK−4) and the MKs extracted from S. aureus. The results showed that the greater the antibacterial activities of plant flavonoids were, the more greatly their antibacterial activities decreased along with the increase in the interfering concentrations of MK−4 (from 2 to 256 μg/mL) and the MK extract (from 4 to 512 μg/mL), while those with the MICs equal to or more than 512 μg/mL decreased a little or remained unchanged. In particular, under the interference of MK−4 (256 μg/mL) and the MK extract (512 μg/mL), the MICs of α-mangostin, a compound with the greatest inhibitory activity to S. aureus out of these twelve plant flavonoids, increased by 16 times and 8 to 16 times, respectively. Based on the above, it was proposed that the quinone pool is a key target of plant flavonoids inhibiting Gram-positive bacteria, and which likely involves multiple mechanisms including some enzyme and non-enzyme inhibitions.

The corrosion behavior of reinforcing steel in the ITT under a submarine environment was investigated. Electrochemical tests were carried out to separately determine the linear polarization curves and the AC impedance spectra of rebars in the ITT scaled-down models subjected to pressurized seawater erosion, from which key parameters were obtained, including the self-corrosion potential (Ecorr), corrosion current density (icorr), polarization resistance (Rp), concrete resistance (Rc), and charge migration resistance (Rct). The results show that in the process of pressurized seawater erosion, the rebars on the seawater side of the ITT models corroded earlier than the rebars on the cavity side, and it is recommended that anti-chloride ion penetration measures be taken on the surface of the seawater side as a priority in the project. The corrosion rate of rebars on the seawater side was significantly higher than that on the cavity side, and the corrosion rate of rebars on the cavity side increased as the erosion time increased. The corrosion rate of rebars in the ITT models was affected by chloride ions to a greater extent than by oxygen. Furthermore, by regression equation, a linear function between Rp obtained from the polarization curves and Rct obtained from the AC impedance spectra was established.

This paper presents a numerical study on the static behavior and cyclic behavior of UHPC-filled steel tube (UHPCFST) columns. A novel fiber element model is developed based on the effective distribution width method to consider the influence of local buckling. The parameters of the descending branch of the stress–strain curve of constrained concrete have been modified and proposed according to the existing experimental results. Thereafter, the impact parameter analysis of the seismic performance of UHPCFST columns under the pseudo static load is conducted, and the strength of steel and UHPC, width–thickness ratio, length–diameter ratio and axial compression ratio are considered. The results indicate that the proposed fiber element model can accurately predict the static and cyclic nonlinear behaviors of the UHPCFST columns. The bearing capacity and the post-peak ductility of UHPCFST columns can be overestimated, such as neglecting the local buckling of the steel tube, which will lead to the insecurity of structures.

As the first waterproof component of the immersed tunnel, it is very important to ensure the remaining compression of the GINA gasket to resist external water intrusion. This paper proposed a method for determining warning thresholds for the remaining compression of the GINA gasket based on a material-to-mechanical analysis. In terms of material analysis, two factors that affect the GINA gasket are investigated: rubber hardness and cross-sectional shape, and they are adopted as the basis for subsequent mechanical analysis. In terms of mechanical analysis, uneven settlement during the operation period is considered to be the major cause of joint deformation, which is further divided into four modes: bending, shear, expansion, and torsion, with the computation model of the GINA gasket established to obtain the warning threshold. After that, a graded early warning method is adopted, and corresponding thresholds are given after an investigation of previous studies, which are validated by a three-dimensional finite element analysis. The deformation monitoring data between the E28 and E29 elements of the Hong Kong–Zhuhai–Macao Bridge Immersed Tunnel are used to verify the proposed method. The results show that the GINA gasket of the Hong Kong–Zhuhai–Macao Bridge Immersed Tunnel is currently in a safe state, and its deformation is much lower than the minimum warning level.

Rapid and accurate crop chlorophyll content estimation and the leaf area index (LAI) are both crucial for guiding field management and improving crop yields. This paper proposes an accurate monitoring method for LAI and soil plant analytical development (SPAD) values (which are closely related to leaf chlorophyll content; we use the SPAD instead of chlorophyll relative content) based on the fusion of ground–air multi-source data. Firstly, in 2020 and 2021, we collected unmanned aerial vehicle (UAV) multispectral data, ground hyperspectral data, UAV visible-light data, and environmental cumulative temperature data for multiple growth stages of summer maize, respectively. Secondly, the effective plant height (canopy height model (CHM)), effective accumulation temperature (growing degree days (GDD)), canopy vegetation index (mainly spectral vegetation index) and canopy hyperspectral features of maize were extracted, and sensitive features were screened by correlation analysis. Then, based on single-source and multi-source data, multiple linear regression (MLR), partial least-squares regression (PLSR) and random forest (RF) regression were used to construct LAI and SPAD inversion models. Finally, the distribution of LAI and SPAD prescription plots was generated and the trend for the two was analyzed. The results were as follows: (1) The correlations between the position of the hyperspectral red edge and the first-order differential value in the red edge with LAI and SPAD were all greater than 0.5. The correlation between the vegetation index, including a red and near-infrared band, with LAI and SPAD was above 0.75. The correlation between crop height and effective accumulated temperature with LAI and SPAD was above 0.7. (2) The inversion models based on multi-source data were more effective than the models made with single-source data. The RF model with multi-source data fusion achieved the highest accuracy of all models. In the testing set, the LAI and SPAD models’ R2 was 0.9315 and 0.7767; the RMSE was 0.4895 and 2.8387. (3) The absolute error between the extraction result of each model prescription map and the measured value was small. The error between the predicted value and the measured value of the LAI prescription map generated by the RF model was less than 0.4895. The difference between the predicted value and the measured value of the SPAD prescription map was less than 2.8387. The LAI and SPAD of summer maize first increased and then decreased with the advancement of the growth period, which was in line with the actual growth conditions. The research results indicate that the proposed method could effectively monitor maize growth parameters and provide a scientific basis for summer maize field management.

Hydrogen energy, a green renewable energy, has shown great potential in developing new energy and alleviating environmental problems. Water electrolysis is an effective method to achieve large-scale clean hydrogen production, but this process needs to consume a huge amount of electric energy. It is urgent to develop high-activity, high-stability and low-cost catalysts to reduce the consumption of electric energy. At present, the noble metal catalyst is the star material in the hydrogen evolution reaction (HER), but its stability and high cost restrict its large-scale application. In this review, we comprehensively discussed the research progress on noble metal-based heterogeneous electrocatalysts used in water electrolysis for hydrogen production. Firstly, we analyzed the influence factors for hydrogen production performance, including the mass transfer process, the adsorption–desorption process, the catalytic process, and the influence of the working electrode and electrolyte. Then, we discussed the relationship between catalytic activity and electronic structure and chemical composition in view of theoretical calculations and summarized the strategies for developing efficient catalysts (alloying and interface engineering). Finally, we highlighted the challenges for the practical application of noble metal-based hydrogen evolution electrocatalysts.

This study aimed to develop a noninvasive, economical and effective subclinical renal damage (SRD) risk assessment tool to identify high-risk asymptomatic people from a large-scale population and improve current clinical SRD screening strategies. Based on the Hanzhong Adolescent Hypertension Cohort, SRD-associated variables were identified and the SRD risk assessment score model was established and further validated with machine learning algorithms. Longitudinal follow-up data were used to identify child-to-adult SRD risk score trajectories and to investigate the relationship between different trajectory groups and the incidence of SRD in middle age. Systolic blood pressure, diastolic blood pressure and body mass index were identified as SRD-associated variables. Based on these three variables, an SRD risk assessment score was developed, with excellent classification ability (AUC value of ROC curve: 0.778 for SRD estimation, 0.729 for 4-year SRD risk prediction), calibration (Hosmer—Lemeshow goodness-of-fit test p = 0.62 for SRD estimation, p = 0.34 for 4-year SRD risk prediction) and more potential clinical benefits. In addition, three child-to-adult SRD risk assessment score trajectories were identified: increasing, increasing-stable and stable. Further difference analysis and logistic regression analysis showed that these SRD risk assessment score trajectories were highly associated with the incidence of SRD in middle age. In brief, we constructed a novel and noninvasive SRD risk assessment tool with excellent performance to help identify high-risk asymptomatic people from a large-scale population and assist in SRD screening.

GaN-based Micro-LED has been widely regarded as the most promising candidate for next generation of revolutionary display technology due to its advantages of high efficiency, high brightness and high stability. However, the typical micro-fabrication process would leave a great number of damages on the sidewalls of LED pixels, especially for Micro-LEDs, thus reducing the light emitting efficiency. In this paper, sidewall passivation methods were optimized by using acid-base wet etching and SiO2 layer passivation. The optical and electrical characteristics of optimized Micro-LEDs were measured and analyzed. The internal quantum efficiency (IQE) of Micro-LED was increased to 85.4%, and the reverse leakage current was reduced down to 10−13 A at −5 V. Optimized sidewall passivation can significantly reduce the non-radiative recombination centers, improving the device performance and supporting the development of high-resolution Micro-LED display.

This paper comprehensively reviews the progress of static aeroelastic effect prediction and correction methods for aircraft, including the damage and protection of aeroelastic. It is significantly important to determine the similarity conditions and static aeroelastic scaling modeling in wind tunnel experiments to obtain accurate aerodynamic characteristics. Meanwhile, similar stiffness distribution, manufacturing materials, and processing technology are strongly associated with the simulation of aircraft structural dynamics. The structural layout of the static aeroelastic model, including plate type, beam type, bearing skin type, and full structural similarity type, are described in detail. Furthermore, the wind tunnel and test technique also play an important role in static aeroelastic experiments. It is worth noting that computational fluid dynamics (CFD) and computational structure dynamics (CSD) have attracted increasing attention from researchers for application in aeroelastic analysis of the flow field. The research status and key technologies of aeroelastic numerical simulation of aircraft are introduced in detail. Additionally, this paper briefly introduces the static aeroelastic prediction and correction method, especially the widely practiced K-value method.

To produce antioxidant substances from agricultural waste Camellia spp. fruit shells before their further utilization, gallic acid from five kinds of Camellia spp. fruit shells was separated on specific recognition by deep eutectic solvent molecularly imprinted polymers (DES@MIPs), which were prepared by bulk polymerization using gallic acid as the template and deep eutectic solvents (α-methylacrylic acid and choline chloride) as functional monomers. The optimized DES@MIPs were characterized by scanning electron microscopy, particle size analysis, nitrogen sorption porosimetry, elemental analysis, Fourier transform infrared spectroscopy, and thermal gravimetric analysis. The adsorptive behavior of gallic acid on DES@MIPs was also investigated. The results indicated that DES@MIPs were successfully prepared as mesoporous materials with average pore diameter of 9.65 nm and total pore volume of 0.315 cm3 g−1, and the adsorption behavior was multilayer adsorption and pseudo-second-order kinetics with the saturation adsorptive capacity of gallic acid reaching 0.7110 mmol g−1. Although the content of gallic acid in five fruit shells was quite different, the purification recovery of gallic acid was high, ranging from 87.85–96.75% with a purity over 80%. Thus, the purification of gallic acid from Camellia spp. fruit shells could be realized feasibly using DES@MIPs with favorable economic and environmental benefits.

A high-resolution (∼500 m) numerical model was used to study the reef and atoll wakes in the Xisha Archipelago (XA) during 2009. Statistical analyses of simulation data indicated strong cyclonic dominance in the mixing layer (above ∼35 m) and weak anticyclonic dominance in the subsurface layer (35∼160 m) for both eddies and filaments in the XA. The intrinsic dynamical properties of the flow, such as the vertical stratification and velocity magnitude, and the terrain of reefs and atolls had a significant effect on the asymmetry. Without considering the existence of reefs and atolls, the “background cyclonic dominance” generated under local planetary rotation (f≈4.1×10−5 s−1) and vertical stratification (with mean Brunt–Väisälä frequency N = 0.02 s−1 at 75 m) was stronger for filaments than eddies in the upper layer from 0∼200 m, and the larger vorticity amplitude in the cyclonic filaments could greatly enhance the cyclonic wake eddies. Furthermore, inertial–centrifugal instability induced selective destabilization of anticyclonic wake eddies in different water layers. As the Rossby number (Ro) and core vorticity (Burger number, Bu) decreased (increased) with the water depth, a more stable state was achieved for the anticyclonic wake eddies in the deeper layer. The stratification and slipping reefs and atolls also led to vertical decoupled shedding, which intensified the asymmetry.

Electroconvulsive therapy (ECT) is an effective therapy for many psychiatric illnesses. However, intracranial occupying lesions are a relative contraindication to ECT. Arachnoid cysts are benign, congenital, and space-occupying lesions. Our study aimed to evaluate the efficacy and tolerability of ECT in psychiatric patients with arachnoid cysts. We retrospectively identified 62 psychiatric patients with arachnoid cysts; 43 of them underwent ECT and 19 did not. Their conditions were assessed by CGI-S and different scales depending on different diagnoses (PANSS for schizophrenia; HAMD for depression; YMRS for bipolar disorder). The side effect was assessed by TESS. Significant differences were shown in the reduced scores of the CGI-S between patients who underwent ECT and those who did not (p = 0.001), while, at the same time, there was no significant difference in their TESS score (p = 0.297). The current study found that ECT is an effective and tolerable therapy for psychiatric patients with arachnoid cysts.

Antimicrobial resistance (AMR) has been a serious threat to human health, and combination therapy is proved to be an economic and effective strategy for fighting the resistance. However, the abuse of drug combinations conversely accelerates the spread of AMR. In our previous work, we concluded that the mutant selection indexes (SIs) of one agent against a specific bacterial strain are closely related to the proportions of two agents in a drug combination. To discover probable correlations, predictors and laws for further proposing feasible principles and schemes guiding the AMR-preventing practice, here, three aspects were further explored. First, the power function (y = axb, a > 0) correlation between the SI (y) of one agent and the ratio (x) of two agents in a drug combination was further established based on the mathematical and statistical analyses for those experimental data, and two rules a1 × MIC1 = a2 × MIC2 and b1 + b2 = −1 were discovered from both equations of y = a1xb1 and y = a2xb2 respectively for two agents in drug combinations. Simultaneously, it was found that one agent with larger MPC alone for drug combinations showed greater potency for narrowing itself MSW and preventing the resistance. Second, a new concept, mutation-preventing selection index (MPSI) was proposed and used for evaluating the mutation-preventing potency difference of two agents in drug combination; a positive correlation between the MPSI and the mutant prevention concentration (MPC) or minimal inhibitory concentration (MIC) was subsequently established. Inspired by this, the significantly positive correlation, contrary to previous reports, between the MIC and the corresponding MPC of antimicrobial agents against pathogenic bacteria was established using 181 data pairs reported. These results together for the above three aspects indicate that the MPCs in alone and combination are very important indexes for drug combinations to predict the mutation-preventing effects and the trajectories of collateral sensitivity, and while the MPC of an agent can be roughly calculated from its corresponding MIC. Subsequently, the former conclusion was further verified and improved via antibiotic exposure to 43 groups designed as different drug concentrations and various proportions. The results further proposed that the C/MPC for the agent with larger proportion in drug combinations can be considered as a predictor and is the key to judge whether the resistance and the collateral sensitivity occur to two agents. Based on these above correlations, laws, and their verification experiments, some principles were proposed, and a diagram of the mutation-preventing effects and the resistant trajectories for drug combinations with different concentrations and ratios of two agents was presented. Simultaneously, the reciprocal of MPC alone (1/MPC), proposed as the stress factors of two agents in drug combinations, together with their SI in combination, is the key to predict the mutation-preventing potency and control the trajectories of collateral sensitivity. Finally, a preliminary scheme for antimicrobial combinations preventing AMR was further proposed for subsequent improvement research and clinic popularization, based on the above analyses and discussion. Moreover, some similar conclusions were speculated for triple or multiple drug combinations.

Fe-Ni-Cr austenitic alloys are widely used in hydrogen environments as structural materials. Their weld normally shows higher hydrogen-embrittlement sensitivity than the base metal, endangering large-scale applications. Herein, by using electron microscopy and numerical calculations, the influence of applied load on the fracture mode of hydrogen-embrittled JBK-75 alloy weldment is revealed and correlated with a competition between hydrogen-prompted intergranular decohesion (HPID) and hydrogen-enhanced localized plasticity (HELP). Therefore, independent of the load levels, the weld featuring a lower strength and smaller grain sizes is always more vulnerable to hydrogen embrittlement than the base metal.

The performance of monochromatic perovskite light-emitting diodes (PeLEDs) has undergone rapid development in recent years, while white PeLEDs are still in their infancy. The tandem devices prepared by connecting light-emitting units of different colors with intermediate connectors comprise one of the promising approaches for realizing white light emission. The intermediate connector plays a crucial role in determining the effectiveness of the light-emitting units. In this work, all-perovskite-based white LEDs are assembled by employing sky-blue (490 nm) and red (690 nm) perovskite emitters as active layers. With mixed p-type and n-type organic charge transport materials as the intermediate connector, the highest external quantum efficiency (EQE) of the device was 1.4%, the electroluminescence (EL) peak position of the blue light part was shifted to 512 nm, and the red light part was shifted to 673 nm. In contrast, with organic and inorganic charge transport materials as the intermediate connector, the devices exhibited better charge generation/injection capabilities and a record EQE of 8.5%. The EL peak position of the device prepared from the stored film was not shifted, implying that the organic/inorganic layer effectively suppresses halide migration. Our work paves the way for highly efficient tandem white PeLEDs.

Let (X,d) be a directionally (γ,m)-limited space with every γ∈(0,∞). In this setting, we aim to study an analogue of the classical theory of Ap(μ) weights. As an application, we establish some weighted estimates for the Hardy–Littlewood maximal operator. Then, we introduce the relationship between directionally (γ,m)-limited spaceand geometric doubling. Finally, we obtain the weighted norm inequalities of the Calderón–Zygmund operator and commutator in non-homogeneous space.

The source apportionment of fine particulate matters, especially PM2.5, has drawn great attention worldwide. Since rare earth elements (REEs) and Nd isotopes can serve as source tracers, in this study, the characteristics and provenance implications of REEs and Nd isotopes in PM2.5 of four seasons in Xiamen city, China, were investigated. The range of the ratios of ΣREE to PM2.5 was 1.04 × 10−5 to 8.06 × 10−4, and the mean concentration of REEs in PM2.5 were in the order of spring > autumn > winter > summer. According to the geoaccumulation index (Igeo), spring was the season in which anthropogenic sources had the greatest impact on the REEs in PM2.5. The chondrite-normalized REE distribution patterns exhibited light rare earth elements (LREEs, including La, Ce, Pr, Nd, Pm, Sm and Eu) enrichment and a flat heavy rare earth elements (HREEs, including Gd, Tb, Dy, Ho, Er, Tm, Yb and Lu) pattern. Significant negative Eu anomalies and no significant Ce anomalies were observed in the PM2.5. The results of La-Ce-Sm ternary plots indicated that the REEs in the PM2.5 might be related to both natural and anthropogenic sources. Combined with the Nd isotope, the 143Nd/144Nd versus Ce/Ce* plot further illustrated that the REEs in the PM2.5 seemed to mostly originate from multiple potential sources, in which vehicle exhaust emissions, coal burning and cement dust made a great contribution to REEs in PM2.5.

A monetary model is established to introduce that bitcoin does have the characteristics of a price rise when the economic situation is terrible under high risk aversion. At this time, Bitcoin has the property of a safe-haven asset, and when economic conditions are good and risk aversion is low, Bitcoin has a pro-cyclical nature. At this time, Bitcoin has a stronger property as a medium of exchange. To show the movement law of the bitcoin price, we make a logarithmic linearization of the model and simulation, and the result is consistent with the theoretical analysis. To better understand the role of bitcoin in the real economy, several standard portfolio models are used to measure the similarities and differences between gold and bitcoin in an investment portfolio. After the outbreak of COVID-19, bitcoin has shown stronger safe-haven asset properties.

Structural health monitoring (SHM) is gradually replacing traditional manual detection and is becoming a focus of the research devoted to the operation and maintenance of tunnel structures. However, in the face of massive SHM data, the autonomous early warning method is still required to further reduce the burden of manual analysis. Thus, this study proposed a dynamic warning method for SHM data based on ARIMA and applied it to the concrete strain data of the Hong Kong–Zhuhai–Macao Bridge (HZMB) immersed tunnel. First, wavelet threshold denoising was applied to filter noise from the SHM data. Then, the feasibility and accuracy of establishing an ARIMA model were verified, and it was adopted to predict future time series of SHM data. After that, an anomaly detection scheme was proposed based on the dynamic model and dynamic threshold value, which set the confidence interval of detected anomalies based on the statistical characteristics of the historical series. Finally, a hierarchical warning system was defined to classify anomalies according to their detection threshold and enable hierarchical treatments. The illustrative example of the HZMB immersed tunnel verified that a three-level (5.5 σ, 6.5 σ, and 7.5 σ) dynamic warning schematic can give good results of anomalies detection and greatly improves the efficiency of SHM data management of the tunnel.

Satellite-based normalized difference vegetation index (NDVI) time series data are useful for monitoring the changes in vegetation ecosystems in the context of global climate change. However, most of the current NDVI products cannot effectively reconcile high spatial resolution and continuous observations in time. Here, to produce a global-scale, long-term, and high-resolution NDVI database, we developed a simple and new data downscaling approach. The downscaling algorithm considers the pixel-wise ratios of the coefficient of variation (CV) between the coarse- and fine-resolution NDVI data and relative changes in the NDVI against a baseline period. The algorithm successfully created a worldwide monthly NDVI database with 250 m resolution from 1982 to 2018 by translating the fine spatial information from MODIS (Moderate-resolution Imaging Spectroradiometer) data and the long-term temporal information from AVHRR (Advanced Very High Resolution Radiometer) data. We employed the evaluation indices of root mean square error (RMSE), mean absolute error (MAE), and Pearson’s correlation coefficient (Pearson’s R) to assess the accuracy of the downscaled data against the MODIS NDVI. Both the RMSE and MAE values at the regional and global scales are typically between 0 and 0.2, whereas the Pearson’s R values are mostly above 0.7, which implies that the downscaled NDVI product is similar to the MODIS NDVI product. We then used the downscaled data to monitor the NDVI changes in different plant types and places with significant vegetation heterogeneity, as well as to investigate global vegetation trends over the last four decades. The Google Earth Engine platform was used for all the data downscaling processes, and here we provide a code for users to easily acquire data corresponding to any part of the world. The downscaled global-scale NDVI time series has high potential for the monitoring of the long-term temporal and spatial dynamics of terrestrial ecosystems under changing environments.

Ferroelectrics with a high dielectric constant are ideal materials for the fabrication of miniaturized and integrated electronic devices. However, the dielectric constant of ferroelectrics varies significantly with the change of temperature, which is detrimental to the working stability of electronic devices. This work demonstrates a new strategy to design a ferroelectric dielectric with a high temperature stability, that is, the design of a multilayer relaxor ferroelectric thin film with a composition gradient. As a result, the fabricated up-graded (Pb,La)(Zr0.65,Ti0.35)O3 multilayer thin film showed a superior temperature stability of the dielectric constant, with variation less than 7% in the temperature range from 30 °C to 200 °C, and more importantly, the variation was less than 2.5% in the temperature range from 75 °C to 200 °C. This work not only develops a dielectric material with superior temperature stability, but also demonstrates a promising method to enhance the temperature stability of ferroelectrics.

In interstitial-free (IF) steel with a certain microtexture, the micro-orientation of grains is essential to understand the occurrence of hydrogen-induced cracking in body-centered cubic (BCC) structural steels. In this study, the hydrogen embrittlement (HE) susceptibility of IF steels was determined by slow strain rate tensile (SSRT) tests and hydrogen microprinting (HMT) experiments from the perspective of crystal orientation. The strength of the specimen with hydrogen was slightly higher than that without hydrogen, while the ductility and toughness were drastically reduced by hydrogen charging during the SSRT test. The HE susceptibility was characterized by the loss of elongation (Iδ) and toughness (Iψ), with losses of 46.3% and 70%, respectively. The microstructural observations indicate that cracks initiated along grains oriented in the {100} || normal direction (ND), and grain boundaries (GBs) around {100}||ND were prone to be enriched in hydrogen atoms; that is, {100} || ND showed poor resistance to intergranular cracking and susceptible to hydrogen segregation. HMT was used to confirm the above viewpoints. Meanwhile, the statistical results showed those high-angle misorientations of 50–60° deviation are the locations most vulnerable to fracture.

Tribocorrosion behaviours of nickel (Ni) and niobium (Nb) in sodium sulfate (Na2SO4) solution under potentiodynamic and potentiostatic conditions were studied. Under the potentiodynamic condition, the passivation was early broken, accompanied by a sharp increase in frictional coefficient on Nb. The current was more fluctuant, and larger material loss appeared at the higher potential in the potentiostatic condition. However, these phenomena did not occur for Ni, and it even showed lower material loss at the higher potential in the potentiostatic tribocorrosion test. The differences in tribocorrosion behaviour had a close relationship to the passive film growth mechanism, which decided the passive film/metal interface structure. Nb with anionic diffusion dominated mechanism in passive growth would cause the accumulation of oxygen vacancies at the passive film/metal interface. This may weaken the adhesion between the metal and the passive film. However, with the cationic diffusion dominated passive film growth on Ni, cation vacancies concentrated at the passive film/tribo-film interface, and this did not affect the adhesion between metal and passive film. Ni or other passive elements with the cationic diffusion-dominated mechanism in passive film growth were recommended as the alloying element for improving the tribocorrosion resistance of alloys.