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Deep neural networks (DNNs) have achieved breakthrough progress in various fields, largely owing to the support of large-scale datasets with manually annotated labels. However, obtaining such datasets is costly and time-consuming, making high-quality annotation a challenging task. In this work, we propose an improved noisy sample selection method, termed "sample selection framework", based on a mixup loss and recalibration strategy (SMR). This framework enhances the robustness and generalization abilities of models. First, we introduce a robust mixup loss function to pre-train two models with identical structures separately. This approach avoids additional hyperparameter adjustments and reduces the need for prior knowledge of noise types. Additionally, we use a Gaussian Mixture Model (GMM) to divide the entire training set into labeled and unlabeled subsets, followed by robust training using semi-supervised learning (SSL) techniques. Furthermore, we propose a recalibration strategy based on cross-entropy (CE) loss to prevent the models from converging to local optima during the SSL process, thus further improving performance. Ablation experiments on CIFAR-10 with 50% symmetric noise and 40% asymmetric noise demonstrate that the two modules introduced in this paper improve the accuracy of the baseline (i.e., DivideMix) by 1.5% and 0.5%, respectively. Moreover, the experimental results on multiple benchmark datasets demonstrate that our proposed method effectively mitigates the impact of noisy labels and significantly enhances the performance of DNNs on noisy datasets. For instance, on the WebVision dataset, our method improves the top-1 accuracy by 0.7% and 2.4% compared to the baseline method. [ABSTRACT FROM AUTHOR]

A series of numerical true triaxial compression tests were carried out on rubber–sand mixtures (RSMs) by means of the 3D discrete element method to study the effect of the intermediate principal stress ratio b on the failure properties of RSMs with different rubber contents (RCs), and to explore the effect mechanism from a microscopic point of view. The numerical simulation results show that as the intermediate principal stress ratio b increases and the peak deviator stress q p e a k gradually increases, while the peak internal friction angle φ b first increases and then decreases. The numerical simulation results were compared with four common strength criteria, including the modified Lade–Duncan criterion, the SMP criterion, the FKZ criterion and the DP criterion. The comparative analysis showed that the existing common criteria cannot accurately predict the damage state of RSMs, suggesting the necessity for further research. At the micro level, the combined effects of the intermediate principal stress ratio b values and RC on the micro-parameters, such as the coordination number, average normal stress between particles, probability density and anisotropy, were investigated. [ABSTRACT FROM AUTHOR]

Reinforced-concrete shear walls stand as the primary construction method for urban residential structures in northern China. In alignment with national carbon neutrality goals for residential construction, this study developed a set of prediction models with which to estimate the building material carbon emissions of reinforced-concrete shear-wall urban residential buildings. Specifically, this study clarified the boundaries, content, and calculation method for carbon emissions in the stage of material production. Using consumption data for building materials from 20 reinforced-concrete shear-wall urban residential buildings in northern China, the study evaluated the composition and distribution of building material carbon emissions. Linear and ridge regression was performed to fit the coupling relationship between spatial design parameters and building material carbon emissions. Adopting two technical approaches of direct and indirect prediction, 10 carbon emission prediction models based on residential design parameters were established and validated. The results indicate that, although the indirect prediction models, based on concrete, steel, cement mortar, and the transparent envelope, had relatively low accuracy in estimating carbon emissions from cement mortar and the transparent envelope, they performed well overall. Additionally, the prediction performance of the four models was similar. In contrast, except for M1 and M3, the other direct prediction models, based on the number of building stories, number of basement levels, number of primary rooms on the standard floor or in the unit, and building width and depth, also had good fitting and prediction performance. These models effectively predicted the total building material carbon emissions in the phases of conceptual design, schematic design, preliminary design, and working drawing. Three prediction models could produce fast and effective data support for the low-carbon design of urban residential buildings. [ABSTRACT FROM AUTHOR]

Granite residual soil has distinctive engineering characteristics due to its unique properties, and the resulting slopes are less stable and less resistant to rain erosion. The granite residual soil was improved by the addition of 5%, 10%, 15% and 20% fly ash, and the effects of fly ash on the intensity index and penetration of granite residual soil were investigated by triaxial strength tests and permeability tests. In combination with scanning electron microscopy measurements, a study of the stability of fly ash-modified granite residual soil slopes by modeling rainfall using the finite element software ABAQUS revealed the following: (1) the permeability coefficients of the residual granitic soils decreased by one order of magnitude when fly ash was added; (2) the improvement in the triaxial strength index of the improved soil was most pronounced when the dosage of fly ash was 15%, so that a dosage of 15% was considered optimal; and (3) numerical simulations concluded that the stability of the slope formed by 15% fly ash-improved soil fill improved significantly relative to the original slope, with the coefficient of safety increasing from 1.06 to 1.42, and the resistance to water seepage also significantly improved. [ABSTRACT FROM AUTHOR]

Indoor triaxial tests on geogrid-reinforced clay elucidate the macroscopic changes in soil strength indices post-reinforcement, yet the underlying mechanisms of strength enhancement require further investigation. By conducting indoor triaxial tests and establishing a corresponding discrete element numerical model, we can delve into the fine-scale mechanisms of geogrid-reinforced soil. This includes analyzing changes in fine-scale parameters such as porosity, the coordination number, and contact stress between soil particles. The findings suggest that an increase in the number of geogrid reinforcement layers leads to a more pronounced improvement in peak strength and cohesion, albeit with minimal impact on the internal friction angle of the specimens. Furthermore, analysis of the triaxial test curves of reinforced soils indicates that the stress–strain relationship adheres to the Duncan–Chang model. Parameters derived from this model have been validated against experimental data, confirming their accuracy. The discrete element model was used to analyze the variations in fine-scale parameters such as porosity and coordination number. It revealed that reinforcement reduces the fluctuation amplitude of porosity and significantly increases the number of particle contacts, resulting in a denser soil structure. Further analysis of the change in contact stress between particles in the discrete element model revealed that the contact force between particles increased significantly after reinforcement and that the reinforcement played a role in restraining the soil particles and dispersing the reinforcement stress, which explains the increase in the strength of the mesh-reinforced clays from another perspective. This further elucidates the strength enhancement mechanism in geogrid-reinforced clay, offering a new perspective on the mechanical behavior and strength development of such materials. [ABSTRACT FROM AUTHOR]

Urban green spaces (UGSs) play a significant role in promoting public health by facilitating outdoor activities, but issues of spatial and socioeconomic inequality within UGSs have drawn increasing attention. However, current methods for assessing UGS inequality still face challenges such as data acquisition difficulties and low identification accuracy. Taking Harbin as a case study, this research employs various advanced technologies, including Python data scraping, drone imagery collection, and Amap API, to gather a diverse range of data on UGSs, including photos, high-resolution images, and AOI boundaries. Firstly, elements related to physical activity within UGSs are integrated into a supply adjustment index (SAI), based on which UGSs are classified into three categories. Then, a supply–demand improved two-step floating catchment area (SD2SFCA) method is employed to more accurately measure the accessibility of these three types of UGSs. Finally, using multiple linear regression analysis and Mann–Whitney U tests, socioeconomic inequalities in UGS accessibility are explored. The results indicate that (1) significant differentiation exists in the types of UGS services available in various urban areas, with a severe lack of small-scale, low-supply UGSs; (2) accessibility of all types of UGSs is significantly positively associated with housing prices, with higher-priced areas demonstrating notably higher accessibility compared to lower-priced ones; (3) children may be at a disadvantage in accessing UGSs with medium-supply levels. Future planning efforts need to enhance attention to vulnerable groups. This study underscores the importance of considering different types of UGSs in inequality assessments and proposes a method that could serve as a valuable tool for accurately assessing UGS inequality. [ABSTRACT FROM AUTHOR]

Simple Summary: In this study, we investigated the critical process of cell fate determination in mouse embryos, focusing on the transition from embryonic stem cells (ESC) to trophoblast stem-like cells (TSLC). As ESCs and TSCs have distinct lineage differences and functional boundaries, the natural conversion between them is hindered. Through the inhibition of LATS kinase, we not only facilitated the conversion of inner cell mass (ICM) to trophectoderm (TE), but also successfully transformed ESC into stable self-renewing TSLC. Our findings highlighted the distinct molecular properties of TSLC, including the high expression of marker genes, such as Cdx2 and Eomes, closely resembling those of trophoblast stem cells (TSC). Furthermore, TSLC demonstrated the ability to differentiate into mature trophoblast cells in vitro and actively participated in placenta formation in vivo. Mouse zygotes undergo multiple rounds of cell division, resulting in the formation of preimplantation blastocysts comprising three lineages: trophectoderm (TE), epiblast (EPI), and primitive endoderm (PrE). Cell fate determination plays a crucial role in establishing a healthy pregnancy. The initial separation of lineages gives rise to TE and inner cell mass (ICM), from which trophoblast stem cells (TSC) and embryonic stem cells (ESC) can be derived in vitro. Studying lineage differentiation is greatly facilitated by the clear functional distinction between TSC and ESC. However, transitioning between these two types of cells naturally poses challenges. In this study, we demonstrate that inhibiting LATS kinase promotes the conversion of ICM to TE and also effectively reprograms ESC into stable, self-renewing TS-like cells (TSLC). Compared to TSC, TSLC exhibits similar molecular properties, including the high expression of marker genes such as Cdx2, Eomes, and Tfap2c, as well as hypomethylation of their promoters. Importantly, TSLC not only displays the ability to differentiate into mature trophoblast cells in vitro but also participates in placenta formation in vivo. These findings highlight the efficient reprogramming of ESCs into TSLCs using a small molecular inducer, which provides a new reference for understanding the regulatory network between ESCs and TSCs. [ABSTRACT FROM AUTHOR]

Convolutional neural networks (CNNs) and transformers have boosted the rapid growth of object detection in synthetic aperture radar (SAR) images. However, it is still a challenging task because SAR images usually have the characteristics of unclear contour, sidelobe interference, speckle noise, multiple scales, complex inshore background, etc. More effective feature extraction by the backbone and augmentation in the neck will bring a promising performance increment. In response, we make full use of the advantage of CNNs in extracting local features and the advantage of transformers in capturing long-range dependencies to propose a Swin Transformer-based detector for arbitrary-oriented SAR ship detection. Firstly, we incorporate a convolution-based local perception unit (CLPU) into the transformer structure to establish a powerful backbone. The local-perception-enhanced Swin Transformer (LP-Swin) backbone combines the local information perception ability of CNNs and the global feature extraction ability of transformers to enhance representation learning, which can extract object features more effectively and boost the detection performance. Then, we devise a cross-scale bidirectional feature pyramid network (CS-BiFPN) by strengthening the propagation and integration of both location and semantic information. It allows for more effective utilization of the feature extracted by the backbone and mitigates the problem of multi-scale ships. Moreover, we design a one-stage framework integrated with LP-Swin, CS-BiFPN, and the detection head of R3Det for arbitrary-oriented object detection, which can provide more precise locations for inclined objects and introduce less background information. On the SAR Ship Detection Dataset (SSDD), ablation studies are implemented to verify the effectiveness of each component, and competing experiments illustrate that our detector attains 93.31% in mean average precision (mAP), which is a comparable detection performance with other advanced detectors. [ABSTRACT FROM AUTHOR]

It is time-consuming to acquire complete data by fully phase encoding in two orthogonal directions along with one frequency encoding direction. Under-sampling in the 3D k-space is promising in accelerating such 3D MRI process. Although 3D under-sampling can be conducted according to predefined probability density, the density-based method is not optimal. Because of the large amount of 3D data and computational cost, it is challenging to perform data-driven and learning-based 3D under-sampling and subsequent 3D reconstruction. To tackle this challenge, this paper proposes a deep neural network called EEUR-Net, realized by optimizing specific under-sampling patterns for the fully sampled 3D k-space data. Innovatively, our under-sampling algorithm employs an end-to-end deep learning approach to optimize phase encoding patterns and uses a 3D U-Net for image reconstruction of under-sampled data. Through end-to-end training, we obtain an optimized 3D under-sampling pattern, which significantly enhances the quality of the reconstructed image under the same acceleration factor. A series of experiments on a knee MRI dataset demonstrate that, in comparison to standard random uniform, radial, Poisson and equispaced Cartesian under-sampling schemes, our end-to-end learned under-sampling pattern considerably improves the reconstruction quality of under-sampled MRI images. [ABSTRACT FROM AUTHOR]

With the rapid development of the electronics industry, the scale of the global Internet of Things (IoT) industry has shown an exponential growth trend in recent years. The huge demand for IoT equipment makes low cost an important indicator for the sustainable operation of the entire IoT system. However, IoT chips also require a certain amount of performance to perform complex tasks. Aiming at the above contradiction between performance and cost, this paper proposes a configurable five-stage pipeline processor core based on RV32IM. The proposed processor core has multiple configurable modules to suit different application scenarios. In low-power mode, the proposed architecture implements only an RV32I subset, while in high-performance mode, integer division and multiplication extensions are added. Meanwhile, the processor core will also support super and user privilege levels and is equipped with CSR (Control and Status Registers). The module-level and system-level simulations of the proposed architecture are completed using a fully open-source workflow based on verilator and gtkwave. In addition, the design was prototyped and verified with FPGA. The proposed processor outperforms the performance of the classic MCU-CortexM3. [ABSTRACT FROM AUTHOR]

Deltamethrin, an important pyrethroid insecticide, is frequently detected in human samples. This study aims to assess the potential effects of deltamethrin on human health and investigate the patterns of residue enrichment and elimination in 112 healthy laying hens. These hens were administered 20 mg·kg−1 deltamethrin based on their body weight. Gas chromatography-mass spectrometry (GC-MS) was used to investigate the residue enrichment pattern and elimination pattern of deltamethrin in the hens. The results indicated a significant increase in the concentration of deltamethrin in chicken manure during the treatment period. By the 14th day of administration, the concentration of deltamethrin in the stool reached 13,510.9 ± 172.24 μg·kg−1, with a fecal excretion rate of 67.56%. The pulmonary deltamethrin concentration was the second highest at 3844.98 ± 297.14 μg·kg−1. These findings suggest that chicken feces contain substantial amounts of deltamethrin after 14 days of continuous administration, and that it can easily transfer to the lungs. After 21 days of drug withdrawal, the residual concentration of deltamethrin in the fat of laying hens was 904.25 ± 295.32 μg·kg−1, with a half-life of 17 days and a slow elimination rate. In contrast, the lungs showed relatively low elimination half-lives of 0.2083 days, indicating faster elimination of deltamethrin in this tissue. These results highlight differences in the rate of deltamethrin elimination in different tissues during drug withdrawal. The fat of laying hens exhibited the highest residue of deltamethrin and the slowest elimination rate, while the lungs showed the fastest elimination rate. Moreover, deltamethrin was found to accumulate in the edible tissues of eggs and laying hens, suggesting that humans may be exposed to deltamethrin through food. [ABSTRACT FROM AUTHOR]

In this work, we demonstrated a new type of biomimetic multispectral curved compound eye camera (BM3C) inspired by insect compound eyes for aerial multispectral imaging in a large field of view. The proposed system exhibits a maximum field of view (FOV) of 120 degrees and seven-waveband multispectral images ranging from visible to near-infrared wavelengths. Pinhole imaging theory and the image registration method from feature detection are used to reconstruct the multispectral 3D data cube. An airborne imaging experiment is performed by assembling the BM3C on an unmanned aerial vehicle (UAV). As a result, radiation intensity curves of several objects are successfully obtained, and a land type classification is performed using the K-means method based on the aerial image as well. The developed BM3C is proven to have the capability for large FOV aerial multispectral imaging and shows great potential applications for distant detecting based on aerial imaging. [ABSTRACT FROM AUTHOR]

High-throughput phenotype monitoring systems for field crops can not only accelerate the breeding process but also provide important data support for precision agricultural monitoring. Traditional phenotype monitoring methods for field crops relying on artificial sampling and measurement have some disadvantages including low efficiency, strong subjectivity, and single characteristics. To solve these problems, the rapid monitoring, acquisition, and analysis of phenotyping information of field crops have become the focus of current research. The research explores the systematic framing of phenotype monitoring systems for field crops. Focusing on four aspects, namely phenotyping sensors, mobile platforms, control systems, and phenotyping data preprocessing algorithms, the application of the sensor technology, structural design technology of mobile carriers, intelligent control technology, and data processing algorithms to phenotype monitoring systems was assessed. The research status of multi-scale phenotype monitoring products was summarized, and the merits and demerits of various phenotype monitoring systems for field crops in application were discussed. In the meantime, development trends related to phenotype monitoring systems for field crops in aspects including sensor integration, platform optimization, standard unification, and algorithm improvement were proposed. [ABSTRACT FROM AUTHOR]

The current popular approach to the extraction of document-level relations is mainly based on either a graph structure or serialization model method for the inference, but the graph structure method makes the model complicated, while the serialization model method decreases the extraction accuracy as the text length increases. To address such problems, the goal of this paper is to develop a new approach for document-level relationship extraction by applying a new idea through the consideration of so-called "Local Relationship and Global Inference" (in short, LRGI), which means that we first encode the text using the BERT pre-training model to obtain a local relationship vector first by considering a local context pooling and bilinear group algorithm and then establishing a global inference mechanism based on Floyd's algorithm to achieve multi-path multi-hop inference and obtain the global inference vector, which allow us to extract multi-classified relationships with adaptive thresholding criteria. Taking the DocRED dataset as a testing set, the numerical results show that our proposed new approach (LRGI) in this paper achieves an accuracy of 0.73, and the value of F1 is 62.11, corresponding to 28% and 2% improvements by comparing with the classical document-level relationship extraction model (ATLOP), respectively. [ABSTRACT FROM AUTHOR]

The automotive electronic throttle (AET) control system has been widely applied in modern automotive engines, and accurate control of AET can improve engine performance as well as reduce pollution emissions. However, the noise in the sensor circuit and the variation in automotive driving conditions seriously affect the control performance of the AET system, making controller designing challenging. This paper proposes a self-tuning backstepping control with a Kalman-like filter (SBCKLF) strategy. First, the noise affecting the position sensor measurement is verified to be non-Gaussian by acquiring and processing the noise signal. To eliminate its influence on control precision, a Kalman-like filter is introduced to estimate the real position of the valve. Then, a self-tuning backstepping controller is designed to automatically adapt to the variation in vehicle driving conditions. A self-tuning algorithm based on fuzzy control is used to tune the parameters of the backstepping controller online, so as to optimize the controller performance. Finally, an experimental platform based on dSPACE for the AET control system is built to perform the controller comprehensive test in a real-time environment. Experimental results and performance analysis demonstrate the effectiveness of the proposed SBCKLF strategy. Compared to the best results of other methods, the proposed method reduces the maximum and root mean square tracking errors by 21.65% and the average error by 12.89%. The steady-state and tracking error bounds are controlled to 0.9° and 2.3°, respectively. It also shows that the SBCKLF strategy has the strongest robustness as well as the best response speed. [ABSTRACT FROM AUTHOR]

The lithium–sulfur (Li-S) battery is considered to be one of the attractive candidates for breaking the limit of specific energy of lithium-ion batteries and has the potential to conquer the related energy storage market due to its advantages of low-cost, high-energy density, high theoretical specific energy, and environmental friendliness issues. However, the substantial decrease in the performance of Li-S batteries at low temperatures has presented a major barrier to extensive application. To this end, we have introduced the underlying mechanism of Li-S batteries in detail, and further concentrated on the challenges and progress of Li-S batteries working at low temperatures in this review. Additionally, the strategies to improve the low-temperature performance of Li-S batteries have also been summarized from the four perspectives, such as electrolyte, cathode, anode, and diaphragm. This review will provide a critical insight into enhancing the feasibility of Li-S batteries in low-temperature environments and facilitating their commercialization. [ABSTRACT FROM AUTHOR]

Blockchain techniques have been introduced to achieve decentralized and transparent traceability systems, which are critical components of food supply chains. Academia and industry have tried to enhance the efficiency of blockchain-based food supply chain traceability queries. However, the cost of traceability queries remains high. In this paper, we propose a dual-layer index structure for optimizing traceability queries in blockchain, which consists of an external and an internal index. The dual-layer index structure accelerates the external block jump and internal transaction search while preserving the original characteristics of the blockchain. We establish an experimental environment by modeling the blockchain storage module for extensive simulation experiments. The results show that although the dual-layer index structure introduces a little extra storage and construction time, it significantly improves the efficiency of traceability queries. Specifically, the dual-layer index improves the traceability query rate by seven to eight times compared with that of the original blockchain. [ABSTRACT FROM AUTHOR]

Based on morphological methods, MODIS satellite remote sensing data were used to establish a dataset of the local roughness length (Z0) of vegetation-covered surfaces in Guangdong Province. The local Z0 was used to update the mesoscale Weather Research and Forecasting (WRF) model in order to quantitatively evaluate its impact on the thermodynamic environment of vegetation-covered surfaces. The specific results are as follows: evergreen broad-leaved forests showed the largest average Z0 values at 1.27 m (spring), 1.15 m (summer), 1.03 m (autumn), and 1.15 m (winter); the average Z0 values of mixed forests ranged from 0.90 to 1.20 m; and those for cropland-covered surfaces ranged from 0.17 to 0.20 m. The Z0 values of individual vegetation coverage types all exhibited relatively high values in spring and low values in autumn, and the default Z0 corresponding to specific vegetation-covered surfaces was significantly underestimated in the WRF model. Modifying the default Z0 of surfaces underlying evergreen broad-leaved forests, mixed forests, and croplands in the model induced only relatively small changes (<1%) in their 2 m temperature, relative humidity, skin surface temperature, and the planetary boundary layer height. However, the average daily wind speed of surfaces covered by evergreen broad-leaved forests, mixed forests, and croplands was reduced by 0.48 m/s, 0.43 m/s, and 0.26 m/s, respectively, accounting for changes of 12.0%, 11.1%, and 6.5%, respectively. [ABSTRACT FROM AUTHOR]

Sustainable development policies and spatial planning for maintaining greenery are crucial for all major cities in the world, and the measurement of green space indicators in planning practice needs to evolve in response to the demands of the times and technological drivers. This study explores an informal urban green space indicator, the green view index (GVI), which uses the visual perception of an observer to measure the quality of urban space by simulating the pedestrian perspective of the road in street-view image data and then calculating the proportion of vegetation in the road landscape. The GVI is different from macro indicators, such as public recreational green space, forest coverage, and green space rate, which are derived from planning data or remote sensing data in traditional urban planning; it starts from the bottom-up perception of individual residents and is more relevant to their subjective demands. At present, most international cities have made outstanding achievements in controlling public recreational green space, forest coverage, green space rates, and other macrolevel indicators of urban spatial quality; however, with the promotion of the concept of "human-oriented" urban planning, the potential restoration of urban spatial quality at the microlevel is gradually being recognized. To ensure the efficiency and reliability of this study, inspired by computer vision techniques and related GVI studies, a research method based on chromaticity was built to identify the proportions of green vegetation in street view images, and the credibility was improved by eliminating unreliable data. By using this method, we could evaluate a city at an overall scale instead of the previous block scale. The final research result showed that Shenzhen is friendly to human visual senses, and the GVI of the streets in developed areas is generally higher than that in developing areas. The geostatistical analysis of the green viewpoint data provides a more intuitive guide for researchers and planners, and it is believed to inform the planning and design of environmentally friendly, smart, and sustainable future cities. [ABSTRACT FROM AUTHOR]

In this study, localised and non-uniform urban morphology (UM) and urban fraction (UF) parameters are implemented in a single-layer urban canopy scheme in the Weather Research and Forecasting (WRF) mesoscale meteorological model. The purpose of this research is to evaluate the effect of the refined parameterisation scheme on the simulation of dynamic and thermal fields in the urban canopy of the Guangzhou metropolitan area. The results showed that, compared with the default urban canopy parameters of the WRF model, using the localised UM parameters resulted in the most significant improvement in the 10 m wind speed simulation. In urban districts, the mean bias between the observed and simulated 10 m wind speed was reduced significantly by 59% from 2.63 m/s to 1.09 m/s during the daytime. For the thermal environment simulation during the daytime, higher UF and UM values resulted in lower surface albedos and generated narrower street canyons compared with the default modelling setting, which caused more heat to be trapped in the urban canopy and ultimately led to an increase in the surface skin temperature (TSK) and a largely increased ground heat flux (GRD). As a result, at night, more heat was transferred from the ground to the surface, producing a higher TSK. The effect of the localised UF on the sensible heat flux (HFX) was closely related to the near-surface temperature gradient. The UM caused the HFX to increase during the daytime, which was related to the near-surface heat exchange coefficient in the lower model layers. As the high-resolution UM significantly altered the urban geometry, the dynamic environment simulation resulted in a large increase in friction velocity and a decrease in wind speed. [ABSTRACT FROM AUTHOR]

As set in the maximum residue limit regulations of the European Commission, this study aimed to obtain the residual parameters in milk with optimized UPLC-MS/MS conditions and to determine the conclusive drug withdrawal period to ensure food safety. In this research, an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed to study cefquinome sulfate's residue elimination in milk and to calculate cefquinome's withdrawal period. Twelve healthy cows free of endometritis were selected for the experiment. Before using the drug, the vaginal orifice and perineum of each cow was disinfected. One dose of intrauterine perfusion was used for each cow, followed by an additional dose after 72 h. Before administration and 12 h, 18 h, 24 h, 36 h, 42 h, 48 h, 60 h, 66 h, 72 h, 84 h, 90 h, and 96 h after the last dose, milk (10 mL) was gathered from each cow's teat and pooled. For the measurement of cefquinome concentrations in milk, UPLC-MS/MS was performed. A calibration curve was generated using linear regression as follows: Y = 250.86X − 102.29, with a correlation coefficient of 0.9996; the limits of detection and the limits of quantitation were 0.1 μg·kg−1 and 0.2 μg·kg−1, respectively. The average recovery of cefquinome was 88.60 ± 16.33% at 0.2 μg·kg−1, 100.95 ± 2.54% at 10 μg·kg−1, and 97.29 ± 1.77% at 50 μg·kg−1. For 5 consecutive days at the three spiking levels, the intra and inter-day relative standard deviations (RSD) were 1.28%–13.73% and 1.81%–18.44%, respectively; the residual amount of cefquinome was less than the maximum residue limit of 20 μg·kg−1, 36 h after administration; and the residual amount was less than the limit of detection (0.1 μg·kg−1) 48 h after administration. The withdrawal time of cefquinome in cow's milk was 39.8 h, as calculated using WTM1.4 software. In terms of clinical practical use, the withdrawal period of milk was temporarily set at 48 h after the administration of the cefquinome sulfate uterus injection to cows, in accordance with the recommended dose and course. [ABSTRACT FROM AUTHOR]

In the far-field wake of a ship, the intensity of the scattering of bubbles is relatively weak. In addition, the wake is relatively thin, and the hole phenomenon is prominent. Thus, it is difficult to detect the wake at a long distance. On this basis, this paper studies a broadband 1–3 high-performance composite transceiver sub-array for the improved detection of a ship's far wake flow field. The content includes frequency characteristics, transmission performance, power tolerance, the beam width of the transmitting array, and the frequency characteristics, reception performance, and beam width of the receiving array. The frequency bandwidth of the transmission array developed in this paper can reach a value of 180 kHz (the center frequency is 390 kHz). The maximum sound source level can reach a value of 228 dB. In the same frequency band, the sensitivity of the receiving array can reach a value of 184 dB, and the fluctuation is less than 5 dB. Compared with the narrowband 1–3 composite array of the same size, the acoustic performance of this sub-array has obvious advantages. Finally, to improve the effective sound path (before the first interface reflection of the sound wave) of the emitted sound wave in the ship's far-field wake, combined with the speed of the moving carrier and the wide-band detection method of the ship's wake, the configuration method of the detection array for the width and direction of the ship's far-field wake is proposed. The results of this research have an important reference value for the research on broadband 1–3 high-performance composite arrays and their application in the far-field wake detection of ships. [ABSTRACT FROM AUTHOR]

Recent discoveries of oil and gas have principally been located in the central part of the Ordos Basin, which is a petroliferous basin with the largest discovered reserves and annual production of tight sandstone gas in China. For tight sandstone gas reservoirs in the transition zone of the basin margin, the process of natural gas accumulation has remained relatively vaguely understood, because of the transitional accumulation of geological conditions such as structure, sedimentation, and preservation. In this study, thin-section identification and scanning electron microscopic observations of the reservoir core, measurement of the physical properties of the reservoir, microscopic petrography research and measurement of the homogenization temperature of fluid inclusions, digital simulations, and laser Raman spectroscopy analysis were combined to analyze the process of natural gas accumulation of the Permian Lower Shihezi Formation in Duguijiahan block, Hangjinqi area, northern Ordos Basin. The results showed that the Lower Shihezi Formation reservoir in the Duguijiahan block began gas charging in the southern part as early as the Early Cretaceous (130–128 Ma), and then gradually charged in the northern part. Three stages were identified in the digital simulations of gas charging, i.e., the breakthrough, rapid, and fully saturated stages. The initial porosity of the Lower Shihezi Formation reservoir ranged between 28% and 40%. Later, because of strong compaction and interstitial filling during burial, the sandstone porosity decreased rapidly, and densification (porosity < 10%) occurred in the mid–late Jurassic. This late tectonic uplift caused a continuous reduction in ground temperature, and diagenesis had a weak effect on pore transformation. The present porosity of the Lower Shihezi Formation reservoir basically inherited its characteristics in the late Early Cretaceous. The current average porosity of the reservoir is 8.58%, and the average permeability is 0.88 mD, and it can thus be characterized as a tight reservoir. The gas accumulation process of the Lower Shihezi Formation has three stages: (1) the depositional stage (C–P), corresponding to the depositional stage of the source-reservoir-cap combination in gas reservoir; (2) the natural gas accumulation stage (T–K1), corresponding to the period of rapid source rock maturation and natural gas charging step-by-step; and (3) the gas reservoir adjustment stage (K2–present), corresponding to the period of uplift and natural gas charging in the early stage that gradually migrated and accumulated northward along the fracture zone. Finally, the gas accumulation model in the transition zone at the margin of basin was established. [ABSTRACT FROM AUTHOR]

Simple Summary: Bovine protozoal disease is a common disease that causes huge economic losses to the cattle breeding industry. Imidocarb (IMD) can be used to treat protozoal parasite diseases in cattle including babesiosis, anaplasmosis, and eperythrozoonosis. However, residues of imidocarb in bovine tissues pose a risk to food safety. This study conducted a residue depletion of imidocarb in cattle based on an ultra-high performance liquid chromatography-tandem mass spectrometry method and obtained the IMD withdrawal time in cattle by the calculation through the WT1.4 software. The results show that the liver and kidney may be the target tissues for IMD and the withdrawal time of IMD in cattle is 224 days at the dosage of 3.0 mg/kg. This will guide farmers in the proper use of imidocarb and ensure human food safety. In this study, an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed for the residue depletion of imidocarb (IMD) in bovine tissues, and the drug withdrawal time of IMD was determined. Twenty-five clinically healthy cattle (body weight 300 kg ± 15 kg) were randomly divided into five groups of five cattle each. The cattle were treated subcutaneously injecting a single dose of a generic IMD formulation, at the recommended dosage of 3.0 mg/kg. The five groups of cattle were slaughtered respectively at 96, 160, 198, 213, and 228 days after IMD administration. Samples from the liver, kidney, muscle, fat, and injection site were collected from each animal. After subtilis proteinase was used to digest the tissue, the content of IMD in the samples was analyzed by UPLC-MS/MS method. In conclusion, the method validation results showed that the method meets the criteria, and the longest withdrawal time of 224 days for the liver can be selected as the conclusive withdrawal time to guarantee consumer safety. [ABSTRACT FROM AUTHOR]

Grain quality involves the appearance, nutritional, and safety attributes of grains. With the improvement of people's living standards, problems pertaining to the quality of grains have received greater attention. Modern quality detection techniques feature unique advantages including rapidness, non-destructiveness, accuracy, and efficiency in detecting grain quality. This review summarizes research progress of these techniques in detection of quality indices of grains. Particularly, the review focuses on detection techniques based on physical properties including acoustic, optical, thermal, electrical, and mechanical properties, and those simulating sensory analysis such as electronic noses, electronic tongues, and electronic eyes. According to the current technological development and application, the challenges and prospects of these techniques are demonstrated. [ABSTRACT FROM AUTHOR]

Point-of-interest (POI) recommendation is the prevalent personalized service in location-based social networks (LBSNs). A single use of matrix factorization (MF) or deep neural networks cannot effectively capture the complex structure of user–POI interactions. In addition, to alleviate the data-sparsity problem, current methods primarily introduce the auxiliary information of users and POIs. Auxiliary information is often judged to be equally valued, which will dissipate some of the valuable information. Hence, we propose a novel POI recommendation method fusing auxiliary attribute information based on the neural matrix factorization, integrating the convolutional neural network and attention mechanism (NueMF-CAA). First, the k-means and term frequency–inverse document frequency (TF-IDF) algorithms are used to mine the auxiliary attribute information of users and POIs from user check-in data to alleviate the data-sparsity problem. A convolutional neural network and an attention mechanism are applied to learn the expression of auxiliary attribute information and distinguish the importance of auxiliary attribute information, respectively. Then, the auxiliary attribute information feature vectors of users and POIs are concatenated with their respective latent feature vectors to obtain the complete latent feature vectors of users and POIs. Meanwhile, generalized matrix factorization (GMF) and multilayer perceptron (MLP) are used to learn the linear and nonlinear interactions between users and POIs, respectively, and the last hidden layer is connected to integrate the two parts to alleviate the implicit feedback problem and make the recommendation results more interpretable. Experiments on two real-world datasets, the Foursquare dataset and the Weibo dataset, demonstrate that the proposed method significantly improves the evaluation metrics—hit ratio (HR) and normalized discounted cumulative gain (NDCG). [ABSTRACT FROM AUTHOR]

A new type of flexible web with a spatial symmetry structure is proposed to address the interception and acquisition of UAVs. It is different from the existing flexible web structure. According to the mechanical characteristics of the flexible web, the dynamic analysis model of the flexible web is established through theoretical deduction. Through finite element simulation calculation, the flexible webs of three different spatial symmetric structures are compared and analyzed. The internal force and air attitude of the three flexible webs are discussed. Among them, the new flexible web has a lag time of 0.162 s and a flight height of 11.624 m. The above simulation parameters are better than those of the other two symmetrical structures. It was proved that the new spatial symmetric flexible web has good traction and deployment performance. In addition, a ground verification test is designed and carried out. The web attitude and flight altitude parameters are compared with the simulation and test results. It is found that the simulation and experimental process of the new symmetric structure web are in good agreement, the synchronization of attitude change is good, and the flight altitude error of the two is controlled at about 5%. The feasibility and effectiveness of this method are proven and it can provide a reference for the research of flexible interception and acquisition of UAVs. [ABSTRACT FROM AUTHOR]

The field mobile platform is an important tool for high-throughput phenotype monitoring. To overcome problems in existing field-based crop phenotyping platforms, including limited application scope and low stability, a rolling adjustment method for the wheel tread was proposed. A self-propelled three-wheeled field-based crop phenotyping platform with variable wheel tread and height above ground was developed, which enabled phenotypic information of different dry crops in different development stages. A three-dimensional model of the platform was established using Pro/E; ANSYS and ADAMS were used for static and dynamic performance. Results show that when running on flat ground, the platform has a vibration acceleration lower than 0.5 m/s2. When climbing over an obstacle with a height of 100 mm, the vibration amplitude of the platform is 88.7 mm. The climbing angle is not less than 15°. Field tests imply that the normalized difference vegetation index (NDVI) and the ratio vegetation index (RVI) of a canopy measured using crop growth sensors mounted on the above platform show favorable linear correlations with those measured using a handheld analytical spectral device (ASD). Their R2 values are 0.6052 and 0.6093 and root-mean-square errors (RMSEs) are 0.0487 and 0.1521, respectively. The field-based crop phenotyping platform provides a carrier for high-throughput acquisition of crop phenotypic information. [ABSTRACT FROM AUTHOR]

A ground natural gas leaking event at the Fuling shale gas field is reported in this paper. Thirteen leakage spots were discovered in two places near the SW-1 and SW-2 drilling wells. The biggest leak rate was above 1000 m3 per day, and no H2S was identified in any of the 13 leaking spots, according to the field study. The chemical components, carbon isotope properties of the leaking gases, and the geological context of the leaking location were researched in order to determine the reason for the leaking incident. From the geological conditions, the Shimen 1# fault belt cuts the whole strata from bottom to top, according to seismic reverse time migration (RTM), and the fault and leaking spots are located in the range of the surface projection of the horizontal section of the adjacent shale gas well. The fracture development evaluation shows that the Wufeng–Longmaxi Formation, which is also the producing layer of the Fuling shale gas field, has a very high possibility of fracture development. From the geochemical view, the carbon isotope of the leaking gases lies in the range of the Wufeng–Longmaxi Formation, showing that the Wufeng–Longmaxi Formation is the gas source of the leaking gas. [ABSTRACT FROM AUTHOR]

The concentration changes of aerosols have attracted wide-ranging attention during the COVID-19 lockdown (CLD) period, but the studies involving aerosol optical properties (AOPs) are relatively insufficient, mainly AOD (fine-mode AOD (AODf) and coarse-mode AOD (AODc)), aerosol absorption optical depth (AAOD), and aerosol extinction coefficient (AEC). Here, the remote-sensing observations, Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) products, backward-trajectory, and potential-source-contribution models are used to assess the impact of AOPs, vertical distribution, and possible sources on the atmosphere environment in North China Plain (NCP), Central China (CC), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB) during the CLD period. The results demonstrate that both AOD (MODIS) and near-surface AEC (CALIPSO, <2 km) decreased in most areas of China. Compared with previous years (average 2017–2019), the AOD (AEC) of NCP, CC, YRD, PRD, and SB reduced by 3.33% (10.76%), 14.36% (32.48%), 10.80% (29.64%), 31.44% (22.68%), and 15.50% (8.44%), respectively. In addition, MODIS (AODc) and MERRA-2 (AODc) decreased in the five study areas compared with previous years, so the reduction in dust activities also contributed to improving regional air quality during the epidemic. Despite the reduction of anthropogenic emissions (AODf) in most areas of China during the CLD periods, severe haze events (AODf > 0.6) still occurred in some areas. Compared to previous years, there were increases in BC, OC (MERRA-2), and national raw coal consumption during CLD. Therefore, emissions from some key sectors (raw coal heating, thermal power generation, and residential coal) did not decrease, and this may have increased AODf during the CLD. Based on backward -rajectory and potential source contribution models, the study area was mainly influenced by local anthropogenic emissions, but some areas were also influenced by northwestern dust, Southeast Asian biomass burning, and marine aerosol transport. This paper underscores the importance of emissions from the residential sector and thermal power plants for atmospheric pollution in China and suggests that these sources must be taken into account in developing pollution-mitigation plans. [ABSTRACT FROM AUTHOR]

Conductive intracardiac communication (CIC) has become one of the most promising technologies in multisite leadless pacemakers for cardiac resynchronization therapy. Existing studies have shown that cardiac pulsation has a significant impact on the attenuation of intracardiac communication channels. In this study, a novel variable-volume circuit-coupled electrical field heart model, which contains blood and myocardium, is proposed to verify the phenomenon. The influence of measurements was combined with the model as the equivalent circuit. Dynamic intracardiac channel characteristics were obtained by simulating models with varying volumes of the four chambers according to the actual cardiac cycle. Subsequently, in vitro experiments were carried out to verify the model's correctness. Among the dependences of intracardiac communication channels, the distance between pacemakers exerted the most substantial influence on attenuation. In the simulation and measurement, the relationship between channel attenuation and pulsation was found through the variable-volume heart model and a porcine heart. The CIC channel attenuation had a variation of less than 3 dB. [ABSTRACT FROM AUTHOR]

This article presents a chip-scale package (CSP) based filament light-emitting diodes (LEDs) with a stacked-type structure and a segmented-type luminescence design for higher luminous efficiency and better electrical stability. The innovation strategy improves the luminous efficiency by 7.69% and 18.97% than the traditional dispensing packaged LED filament when the current is at 30 mA and 210 mA, respectively, and reduces the use of red phosphors and green phosphors by 66.7% and 26.2%, respectively. With the increase of the current, the luminous efficiency variations of the stacked-packaged filament are lower than that of the traditional dispensing packaged filament. Moreover, the color temperature of the filament is no longer determined by the calculation of the ratio of various phosphors. The stacked structure and the segmented design can help us to adjust the specified color temperature quickly by changing the proportion and position of the blue chips and the red CSP LEDs. [ABSTRACT FROM AUTHOR]

Mg-9Al-1Si-1SiC composites with various initial microstructures prior to equal channel angular pressing (ECAP) were obtained by different pre-treatments (without and with homogenization treatment), and the resultant grain size, second phase and tensile properties of ECAPed composites were reported. The ECAPed composite with homogenization treatment (HT) exhibited finer grain size, higher fraction of dynamically recrystallized (DRXed) grains, weaker texture intensity, as well as the presence of dynamic precipitated Mg17Al12 phase compared to that without HT. Besides, the morphology of pre-existing Mg2Si changed from massive-like to needle-like in the ECAPed composite with HT. Room-temperature tensile test results showed that ultimate tensile strength (UTS), yield strength (YS), and elongation (El) of ECAPed composites with HT were 16.1%, 23%, and 27.3% larger than that without HT, respectively. [ABSTRACT FROM AUTHOR]

The healthy development of the ecosystem and tourism in destinations plays an essential role in sustainable development. Taking Shennongjia as an example, we analyzed the spatial–temporal variation in the ecosystem services value (ESV) and investigated the impacts of tourism on ESV and their spatial heterogeneity using the geographically weighted regression (GWR) and boosting regression tree (BRT) models. The results showed that (1) the types of ecosystem services (ESs) were dominated by climate regulation and biodiversity. The ESV increased from 3.358 billion yuan to 8.910 billion yuan from 2005 to 2018 and showed significant spatial divergence, maintaining a long-term distribution pattern of high in the center and low at the border. (2) The GWR and BRT results showed that the Distance to Scenic Spots (DSS) and the Distance to Residential Areas (DRA) are important factors influencing ESV, with the Distance to Hotels (DH) and the Distance to Roads (DR) having a relatively weak influence on ESV. (3) The influencing factors presented positive and negative effects, and the degree of influence has spatial heterogeneity. The DRA and DH inhibited the increase in ESV in nearby areas, while DR was the driving factor for increasing ESV. The assessment results of DSS vary according to the models. [ABSTRACT FROM AUTHOR]

Adding an expansive agent to ordinary grout can cause an expansion in volume, but also reduces its strength. In order to improve the strength of expansive grout, quartz sand is used as the strength enhancement additive. In this study, the expansion behavior and mechanical properties of the expansive grout with quartz sand are explored, through expansion development monitoring, uniaxial compression strength (UCS), acoustic emission (AE), SEM and XRD test methods. The results showed that: (1) The final expansion ratio and expansion development of the samples are related to the use of an expansive agent, but not affected by quartz sand. With the increase in expansion agent content, the average expansion ratios of the samples are 0.03%, 0.16%, 0.67%, 1.06% and 1.48%; (2) The UCS of the samples decreases with the increase in expansive agent content but increases with the increase in quartz sand content. Compared with no quartz sand, and with the increase in quartz sand content, the average strength of the samples increased by 10.51%, 29.88%, and 37.92%; (3) Quartz sand does not effectively participate in the hydration reaction, but it can effectively enhance the strength of the expansive grout without affecting its volume expansion, which makes it an ideal expansive grout strength enhancement additive. [ABSTRACT FROM AUTHOR]

After the Belt and Road Initiative (BRI) was put forward, the tourism industry between Azerbaijan and China developed rapidly, and gradually became an important area of cooperation between the two countries to promote economic cooperation, non-governmental exchange, and cultural exchange. However, there is currently a lack of research on the development strategy of tourism cooperation between the two countries under the BRI. This paper aims to explore the development strategy of sustainable tourism cooperation between Azerbaijan and China under BRI through a hybrid model of SWOT (Strengths, Weaknesses, Opportunities, and Threats) and AHP (Analytic Hierarchy Process). The factor elements of the SWOT matrix introduce ambiguity due to the complex layering of elemental importance. Therefore, the AHP method was used to systematically evaluate the importance of strategic factors and reduce the subjective bias caused by the SWOT analysis method. By constructing the Delphi-AHP-SWOT strategic quadrilateral and calculating the azimuth of the strategy type, the type and intensity map of the tourism cooperation development strategy between Azerbaijan and China under the BRI is drawn. Finally, it is concluded that the development strategy of tourism cooperation between Azerbaijan and China is a pioneering development strategy. Suggestions are given for future development. This paper provides a valuable experience for the sustainable development of tourism cooperation among countries under the BRI. [ABSTRACT FROM AUTHOR]

The commonly-used large-scale knowledge bases have been facing challenges in open domain question answering tasks which are caused by the loose knowledge association and weak structural logic of triplet-based knowledge. To find a way out of this dilemma, this work proposes a novel metaknowledge enhanced approach for open domain question answering. We design an automatic approach to extract metaknowledge and build a metaknowledge network from Wiki documents. For the purpose of representing the directional weighted graph with hierarchical and semantic features, we present an original graph encoder GE4MK to model the metaknowledge network. Then, a metaknowledge enhanced graph reasoning model MEGr-Net is proposed for question answering, which aggregates both relational and neighboring interactions comparing with R-GCN and GAT. Experiments have proved the improvement of metaknowledge over main-stream triplet-based knowledge. We have found that the graph reasoning models and pre-trained language models also have influences on the metaknowledge enhanced question answering approaches. [ABSTRACT FROM AUTHOR]

Agricultural greenhouse (AG), one of the fastest-growing technology-based approaches worldwide in terms of controlling the environmental conditions of crops, plays an essential role in food production, resource conservation and the rural economy, but has also caused environmental and socio-economic problems due to policy promotion and market demand. Therefore, long-term monitoring of AG is of utmost importance for the sustainable management of protected agriculture, and previous efforts have verified the effectiveness of remote sensing-based techniques for mono-temporal AG mapping in a relatively small area. However, currently, a continuous annual AG remote sensing-based dataset at large-scale is generally unavailable. In this study, an annual AG mapping method oriented to the provincial area and long-term period was developed to produce the first Landsat-derived annual AG dataset in Shandong province, China from 1989 to 2018 on the Google Earth Engine (GEE) platform. The mapping window for each year was selected based on the vegetation growth and the phenological information, which was critical in distinguishing AG from other misclassified categories. Classification for each year was carried out initially based on the random forest classifier after the feature optimization. A temporal consistency correction algorithm based on classification probability was then proposed to the classified AG maps for further improvement. Finally, the average User's Accuracy, Producer's Accuracy and F1-score of AG based on visually-interpreted samples over 30 years reached 96.56%, 86.64% and 0.911, respectively. Furthermore, we also found that the ranked features via calculating the importance of each tested feature resulted in the highest accuracy and the strongest stability in the initial classification stage, and the proposed temporal consistency correction algorithm improved the final products by approximately five percent on average. In general, the resultant AG sequence dataset from our study has revealed the expansion of this typical object of "Human–Nature" interaction in agriculture and has a potential application in use of greenhouse-related technology and the scientific planning of protected agriculture. [ABSTRACT FROM AUTHOR]

In this paper, an InGaZnO thin-film transistor (TFT) based on plasma oxidation of silicon nitride (SiNx) gate dielectric with small subthreshold swing (SS) and enhanced stability under negative bias illumination stress (NBIS) have been investigated in detail. The mechanism of the high-performance InGaZnO TFT with plasma-oxidized SiNx gate dielectric was also explored. The X-ray photoelectron spectroscopy (XPS) results confirmed that an oxygen-rich layer formed on the surface of the SiNx layer and the amount of oxygen vacancy near the interface between SiNx and InGaZnO layer was suppressed via pre-implanted oxygen on SiNx gate dielectric before deposition of the InGaZnO channel layer. Moreover, the conductance method was employed to directly extract the density of the interface trap (Dit) in InGaZnO TFT to verify the reduction in oxygen vacancy after plasma oxidation. The proposed InGaZnO TFT with plasma oxidation exhibited a field-effect mobility of 16.46 cm2/V·s, threshold voltage (Vth) of −0.10 V, Ion/Ioff over 108, SS of 97 mV/decade, and Vth shift of −0.37 V after NBIS. The plasma oxidation on SiNx gate dielectric provides a novel approach for suppressing the interface trap for high-performance InGaZnO TFT. [ABSTRACT FROM AUTHOR]

With the intensification of global warming, the development of low-carbon tourism is not only an inevitable requirement for human development, but also an important way to enhance tourism, improve the quality of tourism, and obtain greater economic and social benefits from tourism. Scientifically and effectively constructing a low-carbon tourism development level evaluation index system is conducive to the healthy and sustainable development of the tourism industry. However, the current evaluation of the development level of low-carbon tourism mainly focuses on low-carbon development, energy conservation, and emission reduction. There are few studies and a lack of specific empirical research evaluating the development of low-carbon tourism. In this research, the Delphi method and analytic hierarchy process were used for data collection and corresponding weight analysis. This research refers to the results of existing studies on low-carbon tourism evaluation index systems, and constructs an objective and quantitative evaluation model. It establishes a low-carbon tourism development evaluation model with 34 specific indicators from the three dimensions of the tourism economic support level, the tourism low-carbon development level, and the tourism policy support level. The research results were applied to the Daxinganling region for verification. The results show that the development of tourism in the Daxinganling region has changed from a mode dominated by economic interests to a mode in which tourism-related parties begin to seek effective low-carbon methods to maintain low-carbon tourism activities. In addition, the Daxinganling region has the lowest level of low-carbon tourism development and the highest level of financial support. Based on the research conclusions, corresponding suggestions for the development of low-carbon tourism in the Daxinganling region are provided. The results are also intended to provide a reference point in the optimization of low-carbon tourism development models in this and other regions. [ABSTRACT FROM AUTHOR]

Hemodynamic status has been perceived as an important diagnostic value as fundamental physiological health conditions, including decisive signs of fatal diseases like arteriosclerosis, can be diagnosed by monitoring it. Currently, the conventional hemodynamic monitoring methods highly rely on imaging techniques requiring inconveniently large numbers of operation procedures and equipment for mapping and with a high risk of radiation exposure. Herein, an ultra-thin, noninvasive, and flexible electronic skin (e-skin) hemodynamic monitoring system based on the thermal properties of blood vessels underneath the epidermis that can be portably attached to the skin for operation is introduced. Through a series of thermal sensors, the temperatures of each subsection of the arrayed sensors are observed in real-time, and the measurements are transmitted and displayed on the screen of an external device wirelessly through a Bluetooth module using a graphical user interface (GUI). The degrees of the thermal property of subsections are indicated with a spectrum of colors that specify the hemodynamic status of the target vessel. In addition, as the sensors are installed on a soft substrate, they can operate under twisting and bending without any malfunction. These characteristics of e-skin sensors exhibit great potential in wearable and portable diagnostics including point-of-care (POC) devices. [ABSTRACT FROM AUTHOR]

Social influence analysis is a very popular research direction. This article analyzes the social network of musicians and the many influencing factors when musicians create music to rank the influence of musicians. In order to achieve the practical purpose of the model making accurate predictions in the broad music market, the algorithm adopts a macromodel and considers the social network topology network. The article adds the time decay function and the weight of genre influence to the traditional PageRank algorithm, and thus, the MRGT (Musician Ranking based on Genre and Time) algorithm appears. Considering the timeliness of social networks and the continuous development of music, we realized the importance of evolving MRGT into a dynamic social network. Therefore, we adopted audio data analysis technology and used Gaussian distance to classify and study the evolution of music properties at different times and different genres and finally formed the dynamic influence ranking algorithm based on musicians' social and personal information networks. As a macromodel heuristic algorithm, our model is explanatory, can handle batch data and can avoid unfavorable factors, so as to provide fast speed and improved accuracy. The network can obtain an era indicator DMI (Dynamic Music Influence) that measures the degree of music revolution. DMI is the indicator we provide for music companies to invest in musicians. [ABSTRACT FROM AUTHOR]

In this paper, a multiband noncontact temperature-measuring microwave radiometer system is developed. The system can passively receive the microwave signal of the core temperature field of the human body without removing the clothes of the measured person. In order to accurately measure the actual temperature of multilayer tissue in human core temperature field, four frequency bands of 4–6 GHz, 8–12 GHz, 12–16 GHz, and 14–18 GHz were selected for multifrequency design according to the internal tissue depth model of human body and the relationship between skin depth and electromagnetic frequency. Used to measure the actual temperature of human epidermis, dermis, and subcutaneous tissue, a small and highly directional multiband angular horn antenna was designed for the radiometer front end. After the error analysis of the full-power microwave radiometer, a novel hardware architecture of the microwave interferometric temperature-measuring radiometer is proposed, and it is proven that the novel interferometric microwave radiometer has less error uncertainty through theoretical deduction. The experimental results show that the maximum detection sensitivity of the novel interferometric microwave temperature-measuring radiometer is 215 mV/dBm, and the temperature sensitivity is 0.047 K/mV. Compared with the scheme of the full-power radiometer, the detection sensitivity is increased 7.45-fold, and the temperature sensitivity is increased 13.89-fold. [ABSTRACT FROM AUTHOR]

Recently, deep learning-based image deblurring and deraining have been well developed. However, most of these methods fail to distill the useful features. What is more, exploiting the detailed image features in a deep learning framework always requires a mass of parameters, which inevitably makes the network suffer from a high computational burden. We propose a lightweight fusion distillation network (LFDN) for image deblurring and deraining to solve the above problems. The proposed LFDN is designed as an encoder–decoder architecture. In the encoding stage, the image feature is reduced to various small-scale spaces for multi-scale information extraction and fusion without much information loss. Then, a feature distillation normalization block is designed at the beginning of the decoding stage, which enables the network to distill and screen valuable channel information of feature maps continuously. Besides, an information fusion strategy between distillation modules and feature channels is also carried out by the attention mechanism. By fusing different information in the proposed approach, our network can achieve state-of-the-art image deblurring and deraining results with a smaller number of parameters and outperform the existing methods in model complexity. [ABSTRACT FROM AUTHOR]

China was the first country to undergo large-scale lockdowns in response to the pandemic in early 2020 and a progressive return to normalization after April 2020. Spaceborne observations of atmospheric nitrogen dioxide (NO2) and oxygenated volatile organic compounds (OVOCs), including formaldehyde (HCHO), glyoxal (CHOCHO), and peroxyacetyl nitrate (PAN), reveal important changes over China in 2020, relative to 2019, in response to the pandemic-induced shutdown and the subsequent drop in pollutant emissions. In February, at the peak of the shutdown, the observed declines in OVOC levels were generally weaker (less than 20%) compared to the observed NO2 reductions (−40%). In May 2020, the observations reveal moderate decreases in NO2 (−15%) and PAN (−21%), small changes in CHOCHO (−3%) and HCHO (6%). Model simulations using the regional model MAGRITTEv1.1 with anthropogenic emissions accounting for the reductions due to the pandemic explain to a large extent the observed changes in lockdown-affected regions. The model results suggest that meteorological variability accounts for a minor but non-negligible part (~−5%) of the observed changes for NO2, whereas it is negligible for CHOCHO but plays a more substantial role for HCHO and PAN, especially in May. The interannual variability of biogenic and biomass burning emissions also contribute to the observed variations, explaining e.g., the important column increases of NO2 and OVOCs in February 2020, relative to 2019. These changes are well captured by the model simulations. [ABSTRACT FROM AUTHOR]

The engineering behaviour of ballast is an important factor to determine the stability and safety of railway tracks. This paper examines the stress–strain, shear strength, peak deflection stress and reinforcement strength ratio of different reinforcement materials and reinforcement locations in ballast track bed layers based on large scale static triaxial shear tests. The results show that geogrid and waste tyre reinforcement have a significant effect on the peak deviator stress of railway track bed layers and the stress–strain relationship is strain-hardened. The peak deviator stress and shear strength of geogrid reinforcement are greater under the same conditions compared with waste tyres. The reinforcement of geogrid and waste tires increases the shear strength of the track bed significantly. The more layers of geogrid reinforcement, the more energy is required for the deformation of the track bed. The energy required for deformation is greater in the centre of the waste tyre than in the other reinforced forms, and the energy required for deformation is minimal in the fully reinforced form. Excessive tyre reinforcement changes the stiffness of the track bed layer, leading to an increase in the settlement rate. The reinforcement strength ratio between geogrid and waste tyre increases significantly with the increasing of the confining pressure and reinforcement layers. Moreover, the reinforcement strength ratio of the geogrid is significantly higher than that of the waste tyre. [ABSTRACT FROM AUTHOR]