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The simulation of fuel composition requires coupled calculations of neutron transport and burnup. It is generally assumed that the neutron flux density and cross-sections remain constant within a burnup step. However, when there are strong absorber poisons present, the reaction rates of the absorbers change too rapidly over time, necessitating extremely fine step sizes to ensure computational accuracy, which in turn leads to low computational efficiency. As a type of accident tolerant fuel (ATF), fully ceramic micro-encapsulated (FCM) fuel is a promising new type of nuclear fuel. Accelerated algorithms for burnup calculations of FCM fuel containing gadolinium isotopes have been developed based on the ALPHA code, including the projected predictor–corrector (PPC), the log-linear rate (LLR), and the high-order predictor–corrector (HOPC) methods (including CE/LI, CE/QI, LE/LI, and LE/QI). The performances of different algorithms under the two forms of Gd2O3 existence were analyzed. The numerical results show that the LE/QI method performs the best overall. For Gd2O3 existing in both forms, the LE/QI algorithm can maintain accuracy with a burnup step size of up to 1.0 GWd/tU, keeping the infinite multiplication factor kinf within 100 pcm, and it exhibits high accuracy in simulating the atomic number densities of Gd-155 and Gd-157 throughout the burnup process. [ABSTRACT FROM AUTHOR]

Utilizing observed wind speed and direction data from observation stations near the Taiwan Strait and ocean buoys, along with forecast data from the EC model, GRAPES_GFS model, and PanGu weather prediction model within the same period, RMSE, MAE, CC, and other parameters were calculated. To comparatively evaluate the forecasting performance of the PanGu weather prediction model on the sea surface wind field near the Taiwan Strait from 00:00 on 1 June 2023, to 23:00 on 31 May 2024. The PanGu weather prediction model is further divided into the ERA5 (PanGu) model driven by ERA5 initial fields and the GRAPES_GFS (PanGu) model driven by GRAPES_GFS initial fields. The main conclusions are as follows: (1) over a one-year evaluation period, for wind speed forecasts with lead times of 0 h to 120 h in the Taiwan Strait region, the overall forecasting skill of the PanGu weather prediction model is superior to that of the model forecasts; (2) different initial fields input into the PanGu weather prediction model lead to different final forecast results, with better initial field data corresponding to forecast results closer to observations, thus indicating the operational transferability of the PanGu model in smaller regions; (3) regarding forecasts of wind speed categories, the credibility of the results is high when the wind speed level is ≤7, and the PanGu weather prediction model performs better among similar forecasts; (4) although the EC model's wind direction forecasts are closer to the observation field results, the PanGu weather forecasting model also provides relatively accurate and rapid forecasts of the main wind directions within a shorter time frame. [ABSTRACT FROM AUTHOR]

As the areca nut market is expanding, there is a growing concern regarding areca nut toxicity. Areca nut alkaloids are the major risky components in betel nuts, and their toxic effects are not fully understood. Here, we investigated the parental and transgenerational toxicity of varied doses of areca nut alkaloids in Caenorhabditis elegans. The results showed that the minimal effective concentration of arecoline is 0.2–0.4 mM. First, arecoline exhibited transgenerational toxicity on the worms' longevity, oviposition, and reproduction. Second, the redox homeostasis of C. elegans was markedly altered under exposure to 0.2–0.4 mM arecoline. The mitochondrial membrane potential was thereafter impaired, which was also associated with the induction of apoptosis. Moreover, antioxidant treatments such as lycopene could significantly ameliorate the toxic effects caused by arecoline. In conclusion, arecoline enhances the ROS levels, inducing neurotoxicity, developmental toxicity, and reproductive toxicity in C. elegans through dysregulated oxidative stress, cell apoptosis, and DNA damage-related gene expression. Therefore, the drug-induced production of reactive oxygen species (ROS) may be crucial for its toxic effects, which could be mitigated by antioxidants. [ABSTRACT FROM AUTHOR]

Dirigent (DIR) genes play a pivotal role in plant development and stress adaptation. Manihot esculenta Crantz, commonly known as cassava, is a drought-resistant plant thriving in tropical and subtropical areas. It is extensively utilized for starch production, bioethanol, and animal feed. However, a comprehensive analysis of the DIR family genes remains unexplored in cassava, a crucial cash and forage crop in tropical and subtropical regions. In this study, we characterize a total of 26 cassava DIRs (MeDIRs) within the cassava genome, revealing their uneven distribution across 13 of the 18 chromosomes. Phylogenetic analysis classified these genes into four subfamilies: DIR-a, DIR-b/d, DIR-c, and DIR-e. Comparative synteny analysis with cassava and seven other plant species (Arabidopsis (Arabidopsis thaliana), poplar (Populus trichocarpa), soybean (Glycine max), tomato (Solanum lycopersicum), rice (Oryza sativa), maize (Zea mays), and wheat (Triticum aestivum)) provided insights into their likely evolution. We also predict protein interaction networks and identify cis-acting elements, elucidating the functional differences in MeDIR genes. Notably, MeDIR genes exhibited specific expression patterns across different tissues and in response to various abiotic and biotic stressors, such as pathogenic bacteria, cadmium chloride (CdCl2), and atrazine. Further validation through quantitative real-time PCR (qRT-PCR) confirmed the response of DIR genes to osmotic and salt stress. These findings offer a comprehensive resource for understanding the characteristics and biological functions of MeDIR genes in cassava, enhancing our knowledge of plant stress adaptation mechanisms. [ABSTRACT FROM AUTHOR]

In recent years, the progressively escalating incidence and exceptionally high fatality rate of cutaneous melanoma have drawn the attention of numerous scholars. Magnetic induction hyperthermia, as an efficacious tumor treatment modality, has been promoted and applied in the therapy of some tumors. In this paper, the melanoma atop the mice's heads was chosen as the research subject, and a magnetic induction hyperthermia approach based on Helmholtz coils as the magnetic field excitation was investigated and designed. The influence of the electromagnetic field and thermal field on organisms was addressed through modeling by COMSOL simulation software. The results showed that the maximum values of induced electric field and magnetic induction strength in mouse tumor tissues were 63.1 V/m and 8.5621 mT, respectively, which reached the threshold value of magnetic field strength required for magnetic induction hyperthermia. The maxima of the induced electric field and magnetic induction intensity in brain tissues are, respectively, 35.828 V/m and 8.57 mT. Approximately 93% of the tumor tissue can reach 42 °C, and the maximum temperature is 44.2 °C. Within this temperature range, a large quantity of tumor cells can be successfully induced to undergo apoptosis without harming normal cells, and the therapeutic effect is favorable. [ABSTRACT FROM AUTHOR]

In recent years, the rapid development of autonomous driving and intelligent driver assistance has brought about urgent demands on high-precision road maps. However, traditional road map production methods mainly rely on professional survey technologies, such as remote sensing and mobile mapping, which suffer from high costs, object occlusions, and long updating cycles. In the era of ubiquitous mapping, crowdsourced trajectory data offer a new and low-cost data resource for the production and updating of high-precision road maps. Meanwhile, as key nodes in the transportation network, maintaining the currency and integrity of road intersection data is the primary task in enhancing map updates. In this paper, we propose a novel approach for detecting road intersections based on crowdsourced trajectory data by introducing an attention mechanism and modifying the loss function in the YOLOv5 model. The proposed method encompasses two key steps of training data preparation and improved YOLOv5s model construction. Multi-scale training processing is first adopted to prepare a rich and diverse sample dataset, including various kinds and different sizes of road intersections. Particularly to enhance the model's detection performance, we inserted convolutional attention mechanism modules into the original YOLOv5 and integrated other alternative confidence loss functions and localization loss functions. The experimental results demonstrate that the improved YOLOv5 model achieves detection accuracy, precision, and recall rates as high as 97.46%, 99.57%, and 97.87%, respectively, outperforming other object detection models. [ABSTRACT FROM AUTHOR]

Industrialization has increased global carbon emissions, necessitating effective climate change mitigation measures. China, the most populous developing nation, faces the challenge of strategizing emissions to meet national carbon neutrality objectives. However, research on specific regions' carbon emissions drivers and causal factors is limited, particularly across prefectural-level cities. This study estimates the spatial and temporal patterns of carbon emissions across China's prefectural cities and utilizes both OLS regression and stepwise regression models to analyze the impact of various factors influencing carbon emissions in these cities. Results reveal the following: (1) The country's overall 20-year carbon emissions continue to grow from 3020.29 Mt in 2001 to 9169.74 Mt in 2020, with an average annual growth rate of 5.71%; the eastern region has seen a gradual deceleration in emissions, whereas the western region continues to experience an increase. Carbon emissions in cities within each subregion consistently rise. (2) Carbon emissions in Chinese prefectural-level cities exhibit strong spatial autocorrelation and clustering (Z > 1.96, p < 0.05), with hot spots primarily in the eastern coastal areas and cold spots in the northwest to southwest regions. (3) Economic and demographic factors significantly increase carbon emissions, while climate and urbanization effects are more complex and variable. Economic growth and population increase are the most significant influencing factors, but regional variances exist in carbon emissions determinants in subregional prefectural cities. These insights provide valuable insights into national emission dynamics at the prefectural level, providing a theoretical basis for enhancing carbon emission strategies across various jurisdictions. [ABSTRACT FROM AUTHOR]

In agriculture, soil-borne fungal pathogens, especially Fusarium oxysporum strains, are posing a serious threat to efforts to achieve global food security. In the search for safer agrochemicals, silica nanoparticles (SiO2NPs) have recently been proposed as a new tool to alleviate pathogen damage including Fusarium wilt. Hollow mesoporous silica nanoparticles (HMSNs), a unique class of SiO2NPs, have been widely accepted as desirable carriers for pesticides. However, their roles in enhancing disease resistance in plants and the specific mechanism remain unknown. In this study, three sizes of HMSNs (19, 96, and 406 nm as HMSNs-19, HMSNs-96, and HMSNs-406, respectively) were synthesized and characterized to determine their effects on seed germination, seedling growth, and Fusarium oxysporum f. sp. phaseoli (FOP) suppression. The three HMSNs exhibited no side effects on cowpea seed germination and seedling growth at concentrations ranging from 100 to 1500 mg/L. The inhibitory effects of the three HMSNs on FOP mycelial growth were very weak, showing inhibition ratios of less than 20% even at 2000 mg/L. Foliar application of HMSNs, however, was demonstrated to reduce the FOP severity in cowpea roots in a size- and concentration-dependent manner. The three HMSNs at a low concentration of 100 mg/L, as well as HMSNs-19 at a high concentration of 1000 mg/L, were observed to have little effect on alleviating the disease incidence. HMSNs-406 were most effective at a concentration of 1000 mg/L, showing an up to 40.00% decline in the disease severity with significant growth-promoting effects on cowpea plants. Moreover, foliar application of HMSNs-406 (1000 mg/L) increased the salicylic acid (SA) content in cowpea roots by 4.3-fold, as well as the expression levels of SA marker genes of PR-1 (by 1.97-fold) and PR-5 (by 9.38-fold), and its receptor gene of NPR-1 (by 1.62-fold), as compared with the FOP infected control plants. Meanwhile, another resistance-related gene of PAL was also upregulated by 8.54-fold. Three defense-responsive enzymes of POD, PAL, and PPO were also involved in the HMSNs-enhanced disease resistance in cowpea roots, with varying degrees of reduction in activity. These results provide substantial evidence that HMSNs exert their Fusarium wilt suppression in cowpea plants by activating SA-dependent SAR (systemic acquired resistance) responses rather than directly suppressing FOP growth. Overall, for the first time, our results indicate a new role of HMSNs as a potent resistance inducer to serve as a low-cost, highly efficient, safe and sustainable alternative for plant disease protection. [ABSTRACT FROM AUTHOR]

Simple Summary: The red imported fire ant is an invasive pest worldwide and a social insect that presents a significant risk to agricultural productivity, ecosystems, and human health. This work presents the selection of three nanomaterials out of a total of 16 species. We assessed the toxicity and behavioral alteration effects of these three materials individually, as well as in combination with indoxacarb, on red imported fire ants. The results showed that diatomite and multi-walled carbon nanotubes could enhance the activity of indoxacarb against red imported fire ants and inhibit their colony behavior. Diatomite and multi-walled carbon nanotubes can be added as pesticide additives to improve the control effects on red imported fire ants, reduce the use of indoxacarb, and delay the development of resistance. The red imported fire ant (Solenopsis invicta Buren) is one of the 100 worst invasive alien species in the world. At present, the control of red imported fire ants is still mainly based on chemical control, and the most commonly used is indoxacarb bait. In this study, the contact and feeding toxicity of 16 kinds of nanomaterials to workers, larvae, and reproductive ants were evaluated after 24 h, 48 h, and 72 h. The results showed that the mortality of diatomite, Silica (raspberry-shaped), and multi-walled carbon nanotubes among workers reached 98.67%, 97.33%, and 68%, respectively, after contact treatment of 72 h. The mortality of both larval and reproductive ants was less than 20% after 72 h of treatment. All mortality rates in the fed treatment group were below 20% after 72 h. Subsequently, we evaluated the digging, corpse-removal, and foraging behaviors of workers after feeding with diatomite, Silica (raspberry-shaped), and multi-walled carbon nanotubes for 24 h, which yielded inhibitory effects on the behavior of red imported fire ants. The most effective was diatomite, which dramatically decreased the number of workers that dug, extended the time needed for worker ant corpse removal and foraging activities, decreased the number of workers that foraged, and decreased the weight of the food carried by the workers. In addition, we also evaluated the contact and feeding toxicity of these three nanomaterials in combination with indoxacarb on red imported fire ants. According to contact toxicity, after 12 h of contact treatment, the death rate among the red imported fire ants exposed to the three materials combined with indoxacarb reached more than 97%. After 72 h of exposure treatment, the mortality rate of larvae was more than 73% when the nanomaterial content was above 1% and 83% when the diatomite content was 0.5%, which was significantly higher than the 50% recorded in the indoxacarb control group. After 72 h of feeding treatment, the mortality of diatomite, Silica (raspberry-shaped), and multi-walled carbon nanotubes combined with indoxacarb reached 92%, 87%, and 98%, respectively. The death rates of the three kinds of composite ants reached 97%, 67%, and 87%, respectively. The three kinds of composite food had significant inhibitory effects on the behavior of workers, and the trend was largely consistent with the effect of nanomaterials alone. This study provides technical support for the application of nanomaterials in red imported fire ant control. [ABSTRACT FROM AUTHOR]

Based on the 30-year global hourly sea surface temperature (SST) dataset (MLSST) produced by the National Marine Environmental Forecasting Center, Ministry of Natural Resources of China, we analyzed the variability of diurnal sea surface temperature amplitude (DSST) of the tropical Indian Ocean at multiple time scales, as well as its influencing factors. The results show that the DSST in the Arabian Sea, Bay of Bengal, and equatorial Indian Ocean exhibits a bimodal seasonal variation with a semi-annual cycle, while the DSST in the southern Indian Ocean shows an annual cycle. The seasonal variation of DSST is mainly influenced by factors such as sea surface wind speed, shortwave solar radiation, and precipitation. The DSST in the equatorial Indian Ocean is generally higher during El Niño years compared to La Niña years. At the intraseasonal scale, the large standard deviation of DSST in boreal winter is mainly distributed in the southern hemisphere, while the large standard deviation of DSST in boreal summer shifts northward. The intraseasonal variation amplitude of DSST in boreal winter of the tropical Indian Ocean is greater than that in boreal summer. The DSST in the tropical Indian Ocean exhibits significant variation characteristics at multi-time scales. This study provides reference for numerical simulation of air-sea interaction patterns in the tropical Indian Ocean, as well as improvement of short-term climate prediction. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

An improved recommendation algorithm based on Conditional Variational Autoencoder (CVAE) and Constrained Probabilistic Matrix Factorization (CPMF) is proposed to address the issues of poor recommendation performance in traditional user-based collaborative filtering algorithms caused by data sparsity and suboptimal feature extraction. Firstly, in the data preprocessing stage, a hidden layer is added to CVAE, and random noise is introduced into the hidden layer to constrain the data features, thereby obtaining more accurate latent features and improving the model's robustness and generative capability. Secondly, the category of items is incorporated as auxiliary information in CVAE to supervise the encoding and decoding of item data. By learning the distribution characteristics of the data, missing values in the rating data can be effectively reconstructed, thereby reducing the sparsity of the rating matrix. Subsequently, the reconstructed data is processed using CPMF, which optimizes the feature extraction performance by imposing constraints on user features. Finally, the prediction rating of a user for an item can be obtained through the matrix product of user and item feature matrices. Experimental results on the MovieLens-100K and MovieLens-1M datasets demonstrate the effectiveness and superiority of the proposed algorithm over four comparative algorithms, as it exhibits significant advantages in terms of root mean square error and mean absolute error metrics. [ABSTRACT FROM AUTHOR]

Aiming at the limited degree of revealing vegetation growth pattern by simple topographic factors, it is essential to find an index that can explain the vegetation cover mechanism to a greater extent. By introducing a certainty factor into vegetation cover evaluation, LSW, LS, topographic wetness index, and aspect were also chosen to carry out control group experiments. The grid digital elevation model of 10 disaster-stricken counties (cities) in Sichuan Province was used as the basis to obtain LSW, while vegetation susceptibility levels were categorized using the natural breaks classification. The results of the multi-factor analysis demonstrated that the certainty factor corresponding to LSW climbed linearly from negative to positive values as the susceptibility level rose, indicating that it was highly correlated with vegetation cover and had an obvious advantage in revealing the vegetation growth potential. Statistically, the vegetation occurrence rate increased regularly with the improvement of the susceptibility level, in which the high and very high susceptibility zones corresponded to 83.66% and 89.95% of vegetation coverage respectively, suggesting a good consistency between the delineated high susceptibility areas and the actual vegetation cover. The findings proved that LSW has a substantial advantage in evaluating vegetation cover, with an evaluation model accuracy of 72.9%. It has been established that LSW will serve as a promising new model for assessing vegetation restoration and planning. [ABSTRACT FROM AUTHOR]

Background: this study aimed to utilize various diffusion-weighted imaging (DWI) techniques, including mono-exponential DWI, intravoxel incoherent motion (IVIM), and diffusion kurtosis imaging (DKI), for the preoperative grading of rectal cancer. Methods: 85 patients with rectal cancer were enrolled in this study. Mann–Whitney U tests or independent Student's t-tests were conducted to identify DWI-derived parameters that exhibited significant differences. Spearman or Pearson correlation tests were performed to assess the relationships among different DWI-derived biological markers. Subsequently, four machine learning classifier-based models were trained using various DWI-derived parameters as input features. Finally, diagnostic performance was evaluated using ROC analysis with 5-fold cross-validation. Results: With the exception of the pseudo-diffusion coefficient (Dp), IVIM-derived and DKI-derived parameters all demonstrated significant differences between low-grade and high-grade rectal cancer. The logistic regression-based machine learning classifier yielded the most favorable diagnostic efficacy (AUC: 0.902, 95% Confidence Interval: 0.754–1.000; Specificity: 0.856; Sensitivity: 0.925; Youden Index: 0.781). Conclusions: utilizing multiple DWI-derived biological markers in conjunction with a strategy employing multiple machine learning classifiers proves valuable for the noninvasive grading of rectal cancer. [ABSTRACT FROM AUTHOR]

In recent years, the greenhouse effect has emerged as a major environmental concern. As a result, the utilization and capture of greenhouse gases have become urgent tasks. The dry reforming of methane (DRM) reaction is a technology that directly converts greenhouse gases (CH4 and CO2) into valuable products. Ni-based catalysts have gained significant attention and industrial prospects in DRM reactions due to their excellent performance and cost-effectiveness compared to noble metals. However, challenges such as metal sintering and carbon deposition hinder its industrialization. This paper provides a review of the recent advancements in catalyst design for DRM reactions, with a focus on the impact of additives, supports, and preparation methods on Ni-based catalysts. It also describes the reaction and deactivation mechanisms, as well as the thermodynamics and kinetics of DRM reactions. Furthermore, this paper envisions the main challenges and opportunities associated with Ni-based catalysts in DRM research. [ABSTRACT FROM AUTHOR]

Based on the hourly ERA5 reanalysis dataset of the European Centre for Medium-Range Weather Forecasts (ECMWF) from 1 January 1979 to 31 December 2019, the climatology of the planetary boundary layer height (PBLH) in Jiangsu, China, is studied. The PBLH based on ERA5 is verified by using radiosonde data, and the results show that the PBLH based on ERA5 fits very well with the PBLH diagnosed by the radiosonde data. Overall, the daytime average PBLH is between 700 and 1200 m, which is higher in the north and lower in the south. It is between 100 and 400 m at night, and it is lower in the north and higher in the south. The PBLH exhibits complex spatiotemporal variation. In the daytime, the PBLH in inland areas is highest in spring, followed by fall and summer, and lowest in winter. At night, the seasonal variation in the PBLH is less obvious. The seasonal variation in the PBLH in coastal areas is higher in fall and winter and lower in spring and summer. The PBLH shows an obvious diurnal cycle, usually reaching its peak at 14:00 (LST) or 15:00 (LST). The diurnal cycle of the PBLH is significantly positively correlated with the near-surface temperature and wind speed and significantly negatively correlated with the relative humidity and lower tropospheric stability. Over these 41 years, the daytime PBLH has increased significantly in most areas. The increase in the PBLH can be attributed to the increase in near-surface temperature and the decrease in near-surface relative humidity and lower tropospheric stability. [ABSTRACT FROM AUTHOR]

The harmonic constants of long-period tidal constituents are critical for simulating the tide process, obtaining theoretical datum sounding reduction, and conducting further ocean research. In this paper, the equidistant node orthogonal polynomial fitting (ENOPF) method is employed to fit the harmonic constants of the T/P satellite altimeter data and the gridded altimeter data from the Data Unification and Altimeter Combination System (DUACS) to obtain the full-field harmonic constants of the long-period tidal constituents (Sa and Ssa) in the Bohai Sea, Yellow Sea, and East China Sea (BYECS). To verify the validity of the ENOPF method, the long-period tidal harmonic constants of the ENOPF method, the Finite Element Solutions 2014 (FES2014) model, the Empirical Ocean Tide 20 (EOT20) model, and the DUACS data were compared with the observations of the X-TRACK products and the tide gauges. In addition, the root-mean-square errors (RMSEs), amplitude differences ( Δ H ), and phase-lag differences ( Δ G ) of the comparison results were calculated. According to the error analysis and the cotidal charts, the ENOPF method is better than the other three methods or models for comparing tide gauges (6.19 cm, 5.85 cm, 25.44°; 1.10 cm, 0.72 cm, 59.09°, respectively. The cotidal charts obtained by the ENOPF method are smoother and have better consistency with the actual track data. The results indicate that, due to the polynomial fitting method adopted in ENOPF method, which has the characteristics of improving the resolution infinitely, it is easier to obtain the harmonic constant of full field than with other models or methods. This study proves that the ENOPF method is a reasonable and simple tool in extracting the harmonic constants of the BYECS. [ABSTRACT FROM AUTHOR]

The land surface temperature (LST), defined as the radiative skin temperature of the ground, plays a critical role in land surface systems, from the regional to the global scale. The commonly utilized daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product at a resolution of one kilometer often contains missing values attributable to atmospheric influences. Reconstructing these missing values and obtaining a spatially complete LST is of great research significance. However, most existing methods are tailored for reconstructing clear-sky LST rather than the more realistic cloudy-sky LST, and their computational processes are relatively complex. Therefore, this paper proposes a simple and effective real LST reconstruction method combining Thermal Infrared and Microwave Remote Sensing Based on Temperature Conservation (TMTC). TMTC first fills the microwave data gaps and then downscales the microwave data by using MODIS LST and auxiliary data. This method maintains the temperature of the resulting LST and microwave LST on the microwave pixel scale. The average Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R2 of TMTC were 3.14 K, 4.10 K, and 0.88 for the daytime and 2.34 K, 3.20 K, and 0.90 for the nighttime, respectively. The ideal MAE of the TMTC method exhibits less than 1.5 K during daylight hours and less than 1 K at night, but the accuracy of the method is currently limited by the inversion accuracy of microwave LST and whether different LST products have undergone time normalization. Additionally, the TMTC method has spatial generality. This article establishes the groundwork for future investigations in diverse disciplines that necessitate real LSTs. [ABSTRACT FROM AUTHOR]

Exploring spatiotemporal patterns of traffic accidents from historic crash databases is one essential prerequisite for road safety management and traffic risk prevention. Presently, with the emergence of GIS and data mining technologies, numerous geospatial analysis methods have been successfully adopted for traffic accident analysis. As characterized by high driving speeds, diverse vehicle types, and isolated traffic environments, expressways are confronted with more serious accident risks than urban roads. In this paper, we propose a combined method based on improved density clustering and the Bayesian inference network to explore spatiotemporal patterns of expressway accidents. Firstly, the spatiotemporal accident neighborhood is integrated into the DBSCAN clustering algorithm to discover multi-scale expressway black spots. Secondly, the Bayesian network model is separately employed in both local-scale black spots and regional-scale expressway networks to fully explore spatially heterogenous accident factors in various black spots and expressways. The experimental results show that the proposed method can correctly extract spatiotemporal aggregation patterns of multi-scale expressway black spots and meanwhile efficiently discover diverse causal factors for various black spots and expressways, providing a comprehensive analysis of accident prevention and safety management. [ABSTRACT FROM AUTHOR]

3D human action recognition is crucial in broad industrial application scenarios such as robotics, video surveillance, autonomous driving, or intellectual education, etc. In this paper, we present a new point cloud sequence network called PointMapNet for 3D human action recognition. In PointMapNet, two point cloud feature maps symmetrical to depth feature maps are proposed to summarize appearance and motion representations from point cloud sequences. Specifically, we first convert the point cloud frames to virtual action frames using static point cloud techniques. The virtual action frame is a 1D vector used to characterize the structural details in the point cloud frame. Then, inspired by feature map-based human action recognition on depth sequences, two point cloud feature maps are symmetrically constructed to recognize human action from the point cloud sequence, i.e., Point Cloud Appearance Map (PCAM) and Point Cloud Motion Map (PCMM). To construct PCAM, an MLP-like network architecture is designed and used to capture the spatio-temporal appearance feature of the human action in a virtual action sequence. To construct PCMM, the MLP-like network architecture is used to capture the motion feature of the human action in a virtual action difference sequence. Finally, the two point cloud feature map descriptors are concatenated and fed to a fully connected classifier for human action recognition. In order to evaluate the performance of the proposed approach, extensive experiments are conducted. The proposed method achieves impressive results on three benchmark datasets, namely NTU RGB+D 60 (89.4% cross-subject and 96.7% cross-view), UTD-MHAD (91.61%), and MSR Action3D (91.91%). The experimental results outperform existing state-of-the-art point cloud sequence classification networks, demonstrating the effectiveness of our method. [ABSTRACT FROM AUTHOR]

Maintaining the data freshness and completeness of road intersection information is the key task of urban road map production and updating. Compared to professional surveying methods, crowdsourced trajectory data provide a low-cost, wide-coverage and real-time data resource for road map construction. However, there may exist the problems of spatio-temporal heterogeneity and uneven density distribution in crowdsourced trajectory data. Hence, in light of road hierarchies, the paper proposes a hierarchical segmentation method to generate road intersections from crowdsourced trajectories. The proposed method firstly implements an adaptive density homogenization processing on raw trajectory data in order to decrease the uneven density discrepancy. Then, a hierarchical segmentation strategy is developed to extract multi-level road intersection elements from coarse scale to fine scale. Finally, the structural models of road intersections are delineated by an iterative piecewise fitting method. Experimental results show that the proposed method can accurately and completely extract road intersections of different shapes and scales, with an accuracy of about 87–90%. Particularly, the precision and recall of road intersection detection are obviously increased by about 7% and 20% by adaptive density homogenization, indicating the advantages of dealing with uneven trajectory data. [ABSTRACT FROM AUTHOR]

High-performance electrochemical biosensors for the rapid detection of aflatoxin B1 (AFB1) are urgently required in the food industry. Herein, a multi-scaled electrochemical biosensor was fabricated by assembling carboxylated polystyrene nanospheres, an aptamer and horseradish peroxidase into a free-standing carbon nanofiber/carbon felt support. The resulting electrochemical biosensor possessed an exceptional performance, owing to the unique structures as well as the synergistic effects of the components. The 3D porous carbon nanofiber/carbon felt support served as an ideal substrate, owing to the excellent conductivity and facile diffusion of the reactants. The integration of carboxylated polystyrene nanospheres with horseradish peroxidase was employed as a signal amplification probe to enhance the electrochemical responses via catalyzing the decomposition of hydrogen peroxide. With the aid of the aptamer, the prepared sensors could quantitatively detect AFB1 in wine and soy sauce samples via differential pulse voltammetry. The recovery rates of AFB1 in the samples were between 87.53% and 106.71%. The limit of detection of the biosensors was 0.016 pg mL−1. The electrochemical biosensors also had excellent sensitivity, reproducibility, specificity and stability. The synthetic strategy reported in this work could pave a new route to fabricate high-performance electrochemical biosensors for the detection of mycotoxins. [ABSTRACT FROM AUTHOR]

Furanocoumarins, the secondary metabolites of plants, are considered to be natural insecticides and fungicides because they prevent the invasion of plant pathogenic microorganisms and the predation of herbivorous insects. In this study, novel 2-arylfuranocoumarin derivatives were designed to synthesize by condensation, esterification, bromination, and Wittig reaction. The results showed an excellent photosensitive activity of 2-thiophenylfuranocoumarin (I34). Cell Counting Kit-8 detected that I34 could inhibit the proliferation of Spodoptera frugiperda (Sf9) cells in a time- and concentration-dependent manner under ultraviolet A (UV-A) light for 3 min. The inverted microscope revealed that cells treated with I34 swelled, the membrane was ruptured, and apoptotic bodies appeared. The flow cytometry detected that I34 could induce apoptosis of Sf9 cells, increase the level of intracellular reactive oxygen species (ROS), decrease the mitochondrial membrane potential, and block cell cycle arrest in the G2/M phase. Transmission electron microscopy detected cell mitochondrial cristae damage, matrix degradation, and mitochondrial vacuolation. Further enzyme activity detection revealed that the enzyme activities of apoptosis-related proteins caspase-3 and caspase-9 increased significantly (p < 0.05). Finally, Western blotting analysis detected that the phosphorylation level of Akt and Bad and the expression of the apoptosis inhibitor protein Bcl-XL were inhibited, cleaved-PARP and P53 were increased, and cytochrome C was released from the mitochondria into the cytoplasm. Moreover, under UV-A irradiation, I34 promoted the increase in ROS in Sf9 cells, activated the mitochondrial apoptotic signal transduction pathway, and finally, inhibited cell proliferation. Thus, novel furanocoumarins exhibit a potential application prospect as a biochemical pesticide. [ABSTRACT FROM AUTHOR]

Featured Application: The practical calculation method of tower load in arch bridge cable lifting construction proposed in this paper, including its engineering application on the analysis of tower mechanical properties, has the characteristics of high calculation efficiency and operability, and may be widely applied to the analysis of cable lifting construction of large-span arch bridges. The cable lifting construction method is the most widely used construction method for large-span arch bridges. The correct calculation and analysis of cable lifting construction is essential to ensure the safety and linearity in the construction of arch bridges. The existing research mainly focuses on the construction scheme and finite element analysis of cable lifting for large-span arch bridges. There is relatively little research on calculation theory, and there is no analytical method for cable lifting construction of arch bridges. To calculate and analyze cable lifting construction more quickly and accurately, based on the deformation coordination principle and suspension cable theory, a practical calculation method is proposed to calculate the load of the tower acting by a cable system in the cable lifting construction of arch bridges. A large-span arch bridge under construction was used as a case study, and the correctness of the calculation method was verified by measuring the displacements of the tower top. A brief description of the structure, verification method, and verification process is presented. The displacement results are calculated by the numerical calculation software SAP2000, the actual measured displacement data are discussed and comparatively analyzed, and the correctness and calculation accuracy of the proposed calculation method are also evaluated. The results show that the calculation method has sufficient accuracy. The tower load calculation is mainly undertaken to prepare for the analysis of the tower mechanical properties; therefore, the calculation method is applied to towers of the case engineering, and the stability, load carrying capacity, and deformation of the tower are analyzed to verify whether its mechanical properties meet the engineering requirements. The results show that steel pipe columns of the buckle tower are prone to twisting instability. The normal stress of the tower's part of the pressurized rod or pressurized bending rod is larger. Wind cable load calculation models and tower design-related recommendations are presented in this tower analysis. The tower load calculation method and tower mechanics analysis method in this study can provide guidance for the calculation and analysis of the cable lifting construction of large-span arch bridges. [ABSTRACT FROM AUTHOR]

An analytical solution is presented for scattering nonplanar SH waves emanating from a fault source using a lined tunnel. The lined tunnel is assumed to be an annular elastic solid in half-space. A simplified circular arc fault model is employed to represent the wave source. By means of the separation of variables method, all wave fields are given in terms of the wave function series with unknown coefficients. Taking advantage of the method of images, the zero-stress boundary condition on the horizontal ground surface is satisfied automatically. By applying Graf's addition formula, a system of equations for seeking the unknowns is derived by taking advantage of the boundary conditions. The problem of wave scattering is finally solved after seeking solutions for the system of equations through standard matrix techniques. The effects of fault distance, fault curvature, and fault orientation are revealed with numerical results. It is found that the plane waves provide a good approximation to the fault-induced cylindrical waves when the source-receiver distance or fault radius of curvature is larger enough. Fault-induced topographic effects are strongly affected by source orientation. [ABSTRACT FROM AUTHOR]

This paper presents a flux-weakening model predictive control (FW-MPC) for the interior permanent magnet synchronous motor (IPMSM) drive system. The FW control is a strategy to extend the IPMSM's operating region. However, the primary FW needs to track the torque reference and maximize the electrical torque per current amplitude with the current and voltage limitations. The two objects make it impossible to solve the FW problem using the optimization method. We proposed an equivalent optimization problem to simplify the complex FW problem, including two objective functions. The MPC is selected as the controller due to its high robustness and transient performance. The constraints from the equivalent optimization problem are added in the MPC to control the IPMSM in the FW region. The simulation and experiment results indicate that the proposed FW-MPC is feasible and effective in driving the IPMSM in the FW region. The proposed FW-MPC can find the optimal point with the maximum electrical torque satisfying the current and voltage limitations. Therefore, the proposed FW-MPC can extend the IPMSM's operating region, benefiting the IPMSM's application. [ABSTRACT FROM AUTHOR]

Under most engineering conditions, soil disturbance due to pile installation may cause soil properties to vary within the region adjacent to the pile in the radial direction. This paper derives a rigorous solution to investigate the kinematic response of end-bearing piles under the excitation of vertical P-waves considering the construction effect. The displacement responses of piles and soil, governed by the dynamic equilibrium equation, are theoretically derived with the separation of variables method. The scattered waves induced by the pile–soil system, which is the key factor of the problem, are decoupled from the total wavefields. Moreover, the friction occurring at the interface of the soil and pile shaft are directly obtained. Thus, the present solution can accurately account for the pile–soil interaction. Comparisons between the numerical results of the present method and the available results are performed. A detailed discussion on the kinematic response coefficient, amplification factor, and soil motion is provided. [ABSTRACT FROM AUTHOR]

As an important component of vehicle design and energy conservation, electric vehicle dynamics simulation is essential, especially under complicated testing conditions. The current commercial vehicle simulation software is mostly used for fuel vehicle dynamics simulation, which lacks accurate electric powertrain parts and open sources. To address this problem, this paper proposes an open-source and flexible vehicle dynamics simulation platform that includes 27 degrees of freedom (DOFs) based on Simulink, which can compatibly support both traditional vehicle dynamics simulations and electric vehicle dynamics simulations. In addition, the platform can support module customization, which is convenient for researchers. Although this platform still needs some iterations to reach industrial and commercial standards, it can already achieve parameter consistency under the stability demands in general scenarios. We believe this work should receive research attention and participation to provide lower thresholds and more references to the dynamic simulation of electric vehicles to reduce vehicle energy consumption. [ABSTRACT FROM AUTHOR]

Porcine deltacoronavirus (PDCoV) is a novel coronavirus that causes diarrhea in nursing piglets. Studies showed that PDCoV uses porcine aminopeptidase N (pAPN) as an entry receptor, but the infection of pAPN-knockout cells or pigs with PDCoV revealed that pAPN might be not a critical functional receptor, implying there exists an unidentified receptor involved in PDCoV infection. Herein, we report that sialic acid (SA) can act as an attachment receptor for PDCoV invasion and facilitate its infection. We first demonstrated that the carbohydrates destroyed on the cell membrane using NaIO4 can alleviate the susceptibility of cells to PDCoV. Further study showed that the removal of SA, a typical cell-surface carbohydrate, could influence the PDCoV infectivity to the cells significantly, suggesting that SA was involved in the infection. The results of plaque assay and Western blotting revealed that SA promoted PDCoV infection by increasing the number of viruses binding to SA on the cell surface during the adsorption phase, which was also confirmed by atomic force microscopy at the microscopic level. In in vivo experiments, we found that the distribution levels of PDCoV and SA were closely relevant in the swine intestine, which contains huge amount of trypsin. We further confirmed that SA-binding capacity to PDCoV is related to the pre-treatment of PDCoV with trypsin. In conclusion, SA is a novel attachment receptor for PDCoV infection to enhance its attachment to cells, which is dependent on the pre-treatment of trypsin on PDCoV. This study paves the way for dissecting the mechanisms of PDCoV–host interactions and provides new strategies to control PDCoV infection. [ABSTRACT FROM AUTHOR]

Simple Summary: One of the major characteristics of the circadian clock is temperature compensation, and previous studies suggested a single clock gene may determine the temperature compensation. In this study, we report the first full collection of clock gene knockout cell lines using CRISPR/Cas9 tools. Our full collections indicate that the temperature compensation is a complex gene regulation system instead of being regulated by any single gene. Besides, we systematically compared the proliferation rates and circadian periods using our full collections, and we found that the cell growth rate is not dependent on the circadian period. Therefore, complex interaction between clock genes and their protein products may underlie the mechanism of temperature compensation, which needs further investigations. Mammalian circadian genes are capable of producing a self-sustained, autonomous oscillation whose period is around 24 h. One of the major characteristics of the circadian clock is temperature compensation. However, the mechanism underlying temperature compensation remains elusive. Previous studies indicate that a single clock gene may determine the temperature compensation in several model organisms. In order to understand the influence of each individual clock gene on the temperature compensation, twenty-three well-known mammalian clock genes plus Timeless and Myc genes were knocked out individually, using a powerful gene-editing tool, CRISPR/Cas9. First, Bmal1, Cry1, and Cry2 were knocked out as examples to verify that deleting genes by CRISPR is effective and precise. Cell lines targeting twenty-two genes were successfully edited in mouse fibroblast NIH3T3 cells, and off-target analysis indicated these genes were correctly knocked out. Through measuring the luciferase reporters, the circadian periods of each cell line were recorded under two different temperatures, 32.5 °C and 37 °C. The temperature compensation coefficient Q10 was subsequently calculated for each cell line. Estimations of the Q10 of these cell lines showed that none of the individual cell lines can adversely affect the temperature compensation. Cells with a longer period at lower temperature tend to have a shorter period at higher temperature, while cells with a shorter period at lower temperature tend to be longer at higher temperature. Thus, the temperature compensation is a fundamental property to keep cellular homeostasis. We further conclude that the temperature compensation is a complex gene regulation system instead of being regulated by any single gene. We also estimated the proliferation rates of these cell lines. After systematically comparing the proliferation rates and circadian periods, we found that the cell growth rate is not dependent on the circadian period. [ABSTRACT FROM AUTHOR]

In recent years, hyperspectral image classification (HSI) has attracted considerable attention. Various methods based on convolution neural networks have achieved outstanding classification results. However, most of them exited the defects of underutilization of spectral-spatial features, redundant information, and convergence difficulty. To address these problems, a novel 3D-2D multibranch feature fusion and dense attention network are proposed for HSI classification. Specifically, the 3D multibranch feature fusion module integrates multiple receptive fields in spatial and spectral dimensions to obtain shallow features. Then, a 2D densely connected attention module consists of densely connected layers and spatial-channel attention block. The former is used to alleviate the gradient vanishing and enhance the feature reuse during the training process. The latter emphasizes meaningful features and suppresses the interfering information along the two principal dimensions: channel and spatial axes. The experimental results on four benchmark hyperspectral images datasets demonstrate that the model can effectively improve the classification performance with great robustness. [ABSTRACT FROM AUTHOR]

Although magnetorheological finishing (MRF) is being widely utilized to achieve ultra-smooth optical surfaces, the mechanisms for obtaining such extremely low roughness after the MRF process are not fully understood, especially the impact of finishing stresses. Herein we carefully investigated the relationship between the stresses and surface roughness. Normal stress shows stronger impacts on the surface roughness of fused silica (FS) when compared with the shear stress. In addition, normal stress in the polishing zone was found to be sensitive to the immersion depth of the magnetorheological (MR) fluid. Based on the above, a fine tuning of surface roughness (RMS: 0.22 nm) was obtained. This work fills gaps in understanding about the stresses that influence surface roughness during MRF. [ABSTRACT FROM AUTHOR]

The dwell time algorithm is one of the key technologies that determines the accuracy of a workpiece in the field of ultra-precision computer-controlled optical surfacing. Existing algorithms mainly consider meticulous mathematics theory and high convergence rates, making the computation process more uneven, and the flatness cannot be further improved. In this paper, a reasonable elementary approximation algorithm of dwell time is proposed on the basis of the theoretical requirement of a removal function in the subaperture polishing and single-peak rotational symmetry character of its practical distribution. Then, the algorithm is well discussed with theoretical analysis and numerical simulation in cases of one-dimension and two-dimensions. In contrast to conventional dwell time algorithms, this proposed algorithm transforms superposition and coupling features of the deconvolution problem into an elementary approximation issue of function value. Compared with the conventional methods, it has obvious advantages for improving calculation efficiency and flatness, and is of great significance for the efficient computation of large-aperture optical polishing. The flatness of φ150 mm and φ100 mm workpieces have achieved PVr150 = 0.028 λ and PVcr100 = 0.014 λ respectively. [ABSTRACT FROM AUTHOR]

The two-sided disassembly line is popular for its high-efficiency disassembly of large-volume end-of-life products. However, in the process of two-sided disassembly, some parts and components need to be disassembled in parallel, and the uncertainty of disassembly time lacks certain research. This paper constructs a fuzzy multiobjective two-sided disassembly line balance problem model based on parallel operation constraint, which aims to reduce the balance loss rate, smoothness index, and energy consumption of disassembly activities. A multiobjective flatworm algorithm based on the Pareto-dominance relationship is developed. To increase the diversity of feasible solutions in the evolution process and accelerate the convergence of Pareto-optimal solutions to prevent the random search of solution space, growth, splitting and regeneration mechanisms are embedded in the algorithm. The working mechanism and efficiency of the multiobjective flatworm algorithm are proved on a series of two-sided disassembly cases, and the excellent performance of the proposed model and algorithm are demonstrated by an actual automobile two-sided disassembly line. [ABSTRACT FROM AUTHOR]

Aerosol vertical profiling is crucial to understand the formation mechanism and evolution processes of haze, which have not yet been comprehensively clarified. In this study, we investigated a severe, persistent haze event in Wuhan (30.5° N, 114.4° E), China during 5–18 January 2013 by the use of a polarization lidar, a Cimel sun photometer, meteorological datasets, and the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) model, focusing on the time–height evolution of aerosols in both the atmospheric boundary layer (ABL) and elevated layers. During the haze period, the integrated particle depolarization ratio was 0.05 ± 0.02, and the fine mode fraction reached 0.91 ± 0.03, indicating haze particles were rather spherical and predominately submicron, that is, of anthropogenic nature. Compared with the clear period, columnar aerosol optical depth at 500 nm tripled to 1.32 ± 0.31, and the strongest enhancement in aerosol concentration occurred from near the ground to an altitude of 1.2 km during the haze period. The daytime evolution of aerosol vertical distribution in the ABL exhibited a distinct pattern under haze weather. Abundant particles accumulated below 0.5 km in the morning hours due to stable meteorological conditions, including a strong surface-based inversion (4.4–8.1 °C), late development (from 1000–1100 LT) of the convective boundary layer, and weak wind (<4 m∙s−1) in the lowermost troposphere. In the afternoon, improved ventilation delivered an overall reduction in boundary layer aerosols but was insufficient to eliminate haze. Particularly, the morning residual layer had an optical depth of 0.29–0.56. It influenced air quality indirectly by weakening convective activities in the morning and directly through the fumigation process around noon, suggesting it may be an important element in aerosol–ABL interactions during consecutive days with haze. Our lidar also captured the presence of the elevated aerosol layers (EALs) embodying regional/long-range transport. Most of the EALs were observed to subside to <1.2 km and exacerbate the pollution level. Backward trajectory analysis and lidar data revealed the EALs originated from the transport of anthropogenic pollutants from the Sichuan Basin, China, and of dust from the deserts in the northwest. They were estimated to contribute ~19% of columnar aerosol-loading, pointing to a non-negligible role of transport during the intense pollution episode. The results could benefit the complete understanding of aerosol–ABL interactions under haze weather and air quality forecasting and control in Wuhan. [ABSTRACT FROM AUTHOR]

Land-surface temperature (LST) plays a key role in the physical processes of surface energy and water balance from local through global scales. The widely used one kilometre resolution daily Moderate Resolution Imaging Spectroradiometer (MODIS) LST product has missing values due to the influence of clouds. Therefore, a large number of clear-sky LST reconstruction methods have been developed to obtain spatially continuous LST datasets. However, the clear-sky LST is a theoretical value that is often an overestimate of the real value. In fact, the real LST (also known as cloudy-sky LST) is more necessary and more widely used. The existing cloudy-sky LST algorithms are usually somewhat complicated, and the accuracy needs to be improved. It is necessary to convert the clear-sky LST obtained by the currently better-developed methods into cloudy-sky LST. We took the clear-sky LST, cloud-cover duration, downward shortwave radiation, albedo and normalized difference vegetation index (NDVI) as five independent variables and the real LST at the ground stations as the dependent variable to perform multiple linear regression. The mean absolute error (MAE) of the cloudy-sky LST retrieved by this method ranged from 3.5–3.9 K. We further analyzed different cases of the method, and the results suggested that this method has good flexibility. When we chose fewer independent variables, different clear-sky algorithms, or different regression tools, we also achieved good results. In addition, the method calculation process was relatively simple and can be applied to other research areas. This study preliminarily explored the influencing factors of the real LST and can provide a possible option for researchers who want to obtain cloudy-sky LST through clear-sky LST, that is, a convenient conversion method. This article lays the foundation for subsequent research in various fields that require real LST. [ABSTRACT FROM AUTHOR]

With the rapid development of urban traffic, accurate and up-to-date road maps are in crucial demand for daily human life and urban traffic control. Recently, with the emergence of crowdsourced mapping, a surge in academic attention has been paid to generating road networks from spatio-temporal trajectory data. However, most existing methods do not explore changing road patterns contained in multi-temporal trajectory data and it is still difficult to satisfy the precision and efficiency demands of road information extraction. Hence, in this paper, we propose a hybrid method to incrementally extract urban road networks from spatio-temporal trajectory data. First, raw trajectory data were partitioned into K time slices and were used to initialize K-temporal road networks by a mathematical morphology method. Then, the K-temporal road networks were adjusted according to a gravitation force model so as to amend their geometric inconsistencies. Finally, road networks were geometrically delineated using the k-segment fitting algorithm, and the associated road attributes (e.g., road width and driving rule) were inferred. Several case studies were examined to demonstrate that our method can effectively improve the efficiency and precision of road extraction and can make a significant attempt to mine the incremental change patterns in road networks from spatio-temporal trajectory data to help with road map renewal. [ABSTRACT FROM AUTHOR]

The land surface temperature (LST) is a key parameter used to characterize the interaction between land and the atmosphere. Therefore, obtaining highly accurate, spatially consistent and temporally continuous LSTs in large areas is the basis of many studies. The Moderate Resolution Imaging Spectroradiometer (MODIS) LST product is commonly used to achieve this. However, it has many missing values caused by clouds and other factors. The current gap-filling methods need to be improved when applied to large areas. In this study, we used the Bayesian maximum entropy (BME) method, which considers spatial and temporal correlation, and takes multiple regression results of the Normalized Difference Vegetation Index (NDVI), Digital Elevation Model (DEM), longitude and latitude as soft data to reconstruct space-complete daily clear-sky LSTs with a 1 km resolution for China's landmass in 2015. The average Root Mean Square Error (RMSE) of this method was 1.6 K for the daytime and 1.2 K for the nighttime when we simultaneously covered more than 10,000 verification points, including blocks that were continuous in space, and the average RMSE of a single discrete verification point for 365 days was 0.4 K for the daytime and 0.3 K for the nighttime when we covered four discrete points. Urban and snow land cover types have a higher accuracy than forests and grasslands, and the accuracy is higher in winter than in summer. The high accuracy and great ability of this method to capture extreme values in urban areas can help improve urban heat island research. This method can also be extended to other study areas, other time periods, and the estimation of other geographical attribute values. How to effectively convert clear-sky LST into real LST requires further research. [ABSTRACT FROM AUTHOR]

Invar alloys with both high strength and low thermal expansion are urgently needed in fields such as overhead power transmission, aero-molds, and so on. In this paper, Cr was introduced as a cost-efficient alloying element into the Fe-36Ni binary invar alloy to increase its mechanical strength. Our results confirmed that fine Cr7C3 precipitants, together with some Fe3C, in the invar alloy aged at 425 °C could be obtained with a short aging time. Those precipitants then grew and aggregated at grain or sub-grain boundaries with an increase in aging time. Simultaneously, mechanical strength and coefficient of thermal expansion (CTE) parabolically varied with the increase in aging time. The sample aged at 425 °C for 7 h presented a maximum strength of 644.4 MPa, together with a minimum coefficient of thermal expansion of 3.30 × 10−6 K−1 in the temperature range of 20–100 °C. This optimized result should be primarily attributed to the precipitation of the nanoscaled Cr7C3. [ABSTRACT FROM AUTHOR]

With the increasingly urgent demand for map conflation and timely data updating, data matching has become a crucial issue in big data and the GIS community. However, non-rigid deviation, shape homogenization, and uncertain scale differences occur in crowdsourced and official building data, causing challenges in conflating heterogeneous building datasets from different sources and scales. This paper thus proposes an automated building data matching method based on relaxation labelling and pattern combinations. The proposed method first detects all possible matching objects and pattern combinations to create a matching table, and calculates four geo-similarities for each candidate-matching pair to initialize a probabilistic matching matrix. After that, the contextual information of neighboring candidate-matching pairs is explored to heuristically amend the geo-similarity-based matching matrix for achieving a contextual matching consistency. Three case studies are conducted to illustrate that the proposed method obtains high matching accuracies and correctly identifies various 1:1, 1:M, and M:N matching. This indicates the pattern-level relaxation labelling matching method can efficiently overcome the problems of shape homogeneity and non-rigid deviation, and meanwhile has weak sensitivity to uncertain scale differences, providing a functional solution for conflating crowdsourced and official building data. [ABSTRACT FROM AUTHOR]

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 LaNiO 3 bottom electrodes on the piezoelectric effect of a Pb(Zr 0.52 ,Ti 0.48 )O 3 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.