Search

Flexible ammonia (NH3) gas sensors have gained increasing attention for their potential in medical diagnostics and health monitoring, as they serve as a biomarker for kidney disease. Utilizing the pre-designable and porous properties of covalent organic frameworks (COFs) is an innovative way to address the demand for high-performance NH3 sensing. However, COF particles frequently encounter aggregation, low conductivity, and mechanical rigidity, reducing the effectiveness of portable NH3 detection. To overcome these challenges, we propose a practical approach using polyvinyl alcohol-carrageenan (κPVA) as a template for in the situ growth of two-dimensional COF film and particles to produce a flexible hydrogel gas sensor (COF/κPVA). The synergistic effect of COF and κPVA enhances the gas sensing, water retention, and mechanical properties. The COF/κPVA hydrogel shows a 54.4% response to 1 ppm NH3 with a root mean square error of less than 5% and full recovery compared to the low response and no recovery of bare κPVA. Owing to the dual effects of the COF film and the particles anchoring the water molecules, the COF/κPVA hydrogel remained stable after 70 h in atmospheric conditions, in contrast, the bare κPVA hydrogel was completely dehydrated. Our work might pave the way for highly sensitive hydrogel gas sensors, which have intriguing applications in flexible electronic devices for gas sensing. [ABSTRACT FROM AUTHOR]

To improve the wear resistance of TC4 titanium alloy, two types of wear-resistant coatings were applied to the surface using laser melting: Ni60 + 50% WC and d22 powder priming. The phase composition and microstructure of the coatings were characterized by X-ray diffractometry (XRD), scanning electron microscopy (SEM), and energy spectroscopy (EDS). The mechanical properties of the coating were tested using an HV-1000 micro-Vickers hardness tester, an HRS-2M high-speed reciprocating friction and wear tester, and a WDW-100D electronic universal testing machine. The results show that Ni60 + 50% WC composite coating and d22 priming + (Ni60 + 50% WC) composite coating mainly consist of W2C, TiC, Ni17W3, Ni3Ti, and TixW1−x phases. Compared to the TC4 substrate, the microhardness of both coatings is significantly higher, approximately 2.8 times the microhardness of the substrate. In frictional wear experiments, the average friction factors of the two coatings and the TC4 substrate are 0.476, 0.55, and 0.865, respectively, and the wear of the two coatings is only 0.0559–0.0769 that of the TC4 substrate, with a significant increase in wear resistance, nearly 17 times higher than that of the substrate. The coating shows flaking, shallow abrasion marks, and granular debris, dominated by adhesive wear and fatigue wear, while the TC4 substrate shows more furrows on the surface, dominated by abrasive wear. The shear bond strengths of the Ni60 + 50% WC composite coating and the d22 powder primed + (Ni60 + 50% WC) composite coating were 188.19 MPa and 49.11 MPa, respectively. Conclusion: both coatings significantly improve the hardness and wear resistance of the TC4 titanium alloy substrate surface, with the Ni60 + 50% WC composite coating performing better in hardness, wear resistance, and bond strength. [ABSTRACT FROM AUTHOR]

In this study, a machine learning-based method to assess and predict the cracking degree (CD) on wood fiber bundles (WFB) was developed, which is crucial for enhancing the quality control and refining the production process of wood scrimber (WS). By roller-cracking poplar wood one to three times, three distinct CD levels were established, and 361 WFB specimens were analyzed, using their water absorption rate (WAR) as the foundation for CD prediction. Through crack image analysis, four key quantitative parameters were identified—cracking density, coherence degree, crack count, and average width—and this study found through discriminant analysis that the discrimination accuracy on the CD levels by cracking density or coherence degree over 90%, emphasizing their significance in evaluation. Cluster analysis grouped the specimens into three clusters based on four key quantitative parameters, aligning with the CD levels. This study developed specialized prediction models for each CD level, integrating principal component analysis for dimensionality reduction with polynomial fitting, achieving mean squared error (MSE) of 0.0132, 0.0498, and 0.0204 for levels 1, 2, and 3, respectively. An integrated model, with an accuracy of 94.3% and predictions within a 20% error margin, was created, demonstrating the effectiveness of using surface crack image features to predict WAR of WFB. This research establishes a methodological framework for assessing CDs on WFB, contributing to enhancing WS product quality and helping to better understand wood cracking and water absorption mechanisms. [ABSTRACT FROM AUTHOR]

In recent years, both domestic and international research on quadruped robots has advanced towards high dynamics and agility, with a focus on high-speed locomotion as a representative motion in high-dynamic activities. Quadruped animals like cheetahs exhibit high-speed running capabilities, attributed to the indispensable role played by their flexible spines during the flight phase motion. This paper establishes dynamic models of flexible spinal quadruped robots with different degrees of simplification, providing a parameterized description of the flight phase motion for both rigid-trunk and flexible-spine quadruped robots. By setting different initial values for the spine joint and calculating the flight phase results for both types of robots at various initial velocities, the study compares and analyzes the impact of a flexible spine on the flight phase motion of quadruped robots. Through comparative experiments, the research aims to validate the influence of a flexible spine during the flight phase motion, providing insights into how spine flexibility affects the flight phase motion of quadruped robots. [ABSTRACT FROM AUTHOR]

In the change detection (CD) task, the substantial variation in feature distributions across different CD datasets significantly limits the reusability of supervised CD models. To alleviate this problem, we propose an illumination–reflection decoupled change detection multi-scale unsupervised domain adaptation model, referred to as IRD-CD-UDA. IRD-CD-UDA maintains its performance on the original dataset (source domain) and improves its performance on unlabeled datasets (target domain) through a novel CD-UDA structure and methodology. IRD-CD-UDA synergizes mid-level global feature marginal distribution domain alignment, classifier layer feature conditional distribution domain alignment, and an easy-to-hard sample selection strategy to increase the generalization performance of CD models on cross-domain datasets. Extensive experiments conducted on the LEVIR, SYSU, and GZ optical remote sensing image datasets demonstrate that the IRD-CD-UDA model effectively mitigates feature distribution discrepancies between source and target CD data, thereby achieving optimal recognition performance on unlabeled target domain datasets. [ABSTRACT FROM AUTHOR]

The Lhasa to Nyingchi Expressway in Xizang made efforts to protect the ecological environment during its construction, but it still caused varying degrees of damage to the fragile ecosystems along the route. Accurately assessing the process of change in the ecological environment quality in this region holds significant research value. This study selected the Linzhi-to-Gongbo'gyamda section of the Lhasa-to-Nyingchi Expressway as the research area. Firstly, based on the remote sensing ecological index (RSEI), this study constructed an ecological environmental quality evaluation system for the Xizang region. Subsequently, using the Google Earth Engine (GEE) platform, sub-indicators were extracted, and the combination weighting method of game theory was employed to determine indicator weights. This process resulted in the calculation of the MRSEI for the study area from 2012 to 2020. Finally, by utilizing the spatial distribution of the MRSEI, monitoring the level of MRSEI changes, and employing the transition matrix, this study analyzed the changing trend of the ecological environmental quality from 2012 to 2020. The results indicate that the MRSEI are 0.5885, 0.5951, 0.5296, 0.6202, 0.59, 0.5777, 0.5898, 0.5703, and 0.5987, showing a gradual increasing trend with an initial decrease followed by an ascent. This trend is mainly attributed to concentrated road construction and subsequent ecological restoration, leading to an improvement in the restoration effect. Simultaneously, the ecological environmental quality remains relatively stable, with 69.5% of the region showing no change, and the remaining 30.5% experiencing improvement exceeding degradation. Specifically, there were significant improvements in the land with ecological quality levels categorized as poor, fair, moderate, and good. The types of degradation primarily involved lands originally classified as excellent and good degrading to good and moderate levels, respectively. The above results serve as a theoretical reference for the ecological restoration project of the Lhasa-to-Nyingchi Expressway. [ABSTRACT FROM AUTHOR]

The presence of massive amounts of toxic volatiles and smoke during combustion is a very serious problem facing epoxy resin (EP) composites. Therefore, flame retardants (FRs) can simultaneously enhance flame retardancy and reduce the release of smoke and fatal gases. Herein, a novel sulfur–phosphorous reactive flame retardant (SPMS) was synthesized for epoxy resin. The high efficiency of smoke suppression and flame retardancy of the EP/SPMS-APP hybrid was investigated using a cone calorimeter, a vertical burning test, and limited oxygen index measurements. Compared with those of pure EP, the composite with 20 wt% SPMS-APP reduced the peak heat release rate (pHRR), the peak smoke production rate (SPR), and total smoke production rate (TSR) by 82%, 94%, and 84%, respectively. The results showed a remarkable suppressed effect of alleviating the fire hazard of EP using a sulfur–phosphorus flame retardant. [ABSTRACT FROM AUTHOR]

Today's intruders usually send attacking commands to a target system through several stepping-stone hosts, for the purpose of decreasing the probability of being caught. Using stepping-stone intrusion (SSI), the intruder's identity is very difficult to discover as it is concealed by a long interactive connection chain of hosts. An effective approach for SSI detection (SSID) is to determine how many connections are contained in a connection chain. This type of method is called network-based SSID. Most existing network-based SSID only worked for network traffic without intruders' session manipulation. These known SSID algorithms are either weak to resist intruders' chaff-perturbation manipulation or have very limited capability in resisting attacker's session manipulation. This paper develops a novel network-based SSID algorithm resistant to intruders' chaff-perturbation by using packet crossover. The SSID approach proposed in this paper is simple and easy to implement as the number of packet crossovers can be easily computed. Our proposed algorithm is verified by rigorous technical proofs as well as well-designed network experiments. Our experimental results show that the proposed SSID algorithm works effectively and perfectly in resisting intruders' chaff-perturbation up to a chaff rate of 50%. [ABSTRACT FROM AUTHOR]

In order to compare and analyze the seismic response characteristics of a safety-related nuclear structure on a non-rock site in the condition of raft and pile group foundations under unidirectional and multidirectional seismic motion input, a large-scale shaking table test of the soil-nuclear structure system was carried out in this paper. In the test, the soil was uniform silted clay, and the shear wave velocity was 213 m/s. Considering the similarity of the superstructure natural frenquency, the actual nuclear power structure was simplified to a three-story frame shear wall structure model. The annular laminated shear model box was used to take the boundary effect of soil into consideration; the seismic motions = were input in only one horizontal direction or three directions at the same time for the shaking table test, and the results were analyzed. The results of the test show that the acceleration response of the safety-related nuclear plant is affected by the directions of input seismic motion and the forms of the foundation. When the seismic motion is input simultaneously in three directions, the acceleration responses of the horizontal motion and vertical rocking of the safety-related plant are larger than those of the single-direction input. The acceleration response of the horizontal motion and vertical rocking of the safety-related structure with the pile group foundation is smaller than that with the raft foundation. The values of most frequency bands in the horizontal acceleration Fourier amplitude spectrum at the top of the pile-foundation structure are smaller than that at the top of the raft-foundation structure, while the displacement is basically the same as that of the raft-foundation structure. This is related to the relation between the frequency component of input seismic motion and the natural frequency of the structure system. Therefore, it is more reasonable to use three-dimensional seismic input in the seismic response analysis of nuclear power plants. The seismic performance of nuclear power plants can be enhanced by using pile group foundations. [ABSTRACT FROM AUTHOR]

Two-dimensional (2D) phthalocyanine-based covalent organic frameworks (COFs) provide an ideal platform for efficient and rapid gas sensing—this can be attributed to their regular structure, moderate conductivity, and a large number of scalable metal active centers. However, there remains a need to explore structural modification strategies for optimizing the sluggish desorption process caused by the extensive porosity and strong adsorption effect of metal sites. Herein, we reported a 2D bimetallic phthalocyanine-based COF (COF-CuNiPc) as chemiresistive gas sensors that exhibited a high gas-sensing performance to nitrogen dioxide (NO2). Bimetallic COF-CuNiPc with an asymmetric synergistic effect achieves a fast adsorption/desorption process to NO2. It is demonstrated that the COF-CuNiPc can detect 50 ppb NO2 with a recovery time of 7 s assisted by ultraviolet illumination. Compared with single-metal phthalocyanine-based COFs (COF-CuPc and COF-NiPc), the bimetallic structure of COF-CuNiPc can provide a proper band gap to interact with NO2 gas molecules. The CuNiPc heterometallic active site expands the overlap of d-orbitals, and the optimized electronic arrangement accelerates the adsorption/desorption processes. The concept of a synergistic effect enabled by bimetallic phthalocyanines in this work can provide an innovative direction to design high-performance chemiresistive gas sensors. [ABSTRACT FROM AUTHOR]

Vehicle ad-hoc network (VANET) is interconnected through message forwarding and exchanging among vehicle nodes. Due to its highly dynamic topology and its wireless and heterogeneous communication mode, VANET is more vulnerable to security threats from multiple parties. Compared to entity-based security authentication, it is essential to consider how to protect the security of the data itself. Existing studies have evaluated the reliability of interactive data through reputation quantification, but there are still some issues in the design of secure reputation management schemes, such as its low efficiency, poor security, and unreliable management. Aiming at the above-mentioned issues, in this paper we propose an effective VANET model with a secure reputation based on a blockchain, and it is called the double-layer blockchain-based reputation evaluation & management model (DBREMM). In the DBREMM, we design a reputation management model based on two parallel blockchains that work collaboratively, and these are called the event chain and reputation chain. A complete set of reputation evaluation schemes is presented. Our schemes can reduce observation errors and improve evaluation reliability during trust computation by using direct trust calculation based on the multi-factor Bayesian inference. Additionally, we propose an indirect trust calculation based on the historical accumulated reputation value with an attenuation factor, and a secure a reputation fusion scheme based on the number threshold with the fluctuation factor, which can reduce the possibility of attacks, such as collusive attacks and false information injection. Theoretical analysis and extensive simulation experiments reflect the DBREMM's security algorithm effectiveness, accuracy, and ability to resist several attacks. [ABSTRACT FROM AUTHOR]

Attackers can exploit compromised hosts to launch attacks over the Internet. This protects an intruder, placing them behind a long connection chain consisting of multiple compromised hosts. Such attacks are called stepping-stone intrusions. Many algorithms have been proposed to detect stepping-stone intrusions, but most detection algorithms are weak in resisting intruders' session manipulation, such as chaff-perturbation. This paper proposes a novel detection algorithm: Packet Cross-Matching and RTT-based two-dimensional random walk. Theoretical proof shows network traffic cross matching can be effective in resisting attackers' chaff attack. Our experimental results over the AWS cloud show that the proposed algorithm can resist attackers' chaff attacks up to a chaff rate of 100%. [ABSTRACT FROM AUTHOR]

Frequent emergencies highlight the importance of corporate resilience, and relationship governance behaviors have received much attention for improving firms' resilience. This study uses structural equation modeling to test hypotheses based on trust theory and synergy theory. It investigates the impact of the behavioral operations management approach of collaborative action on manufacturers' resilience in Chinese manufacturing firms during the COVID-19 pandemic. Environmental uncertainty is used as a moderating variable to explore its role between the trust relationship with suppliers and collaborative action, which are two types of relationship management behaviors. The results show that collaborative action positively affects each of the three stages of manufacturer resilience. Moreover, collaborative action mediates between the trust relationship with suppliers and the different dimensions of manufacturer resilience. Environmental uncertainty does not moderate the facilitative effect of the trust relationship with suppliers on collaborative action. This study examines the relational governance behavior of firms in the context of a particular Chinese culture to build a bridge between relational governance behavioral science and firm resilience management. This study tries to provide inspiration for managers to improve the risk management ability of manufacturing enterprises by using relationship management theory and behavioral science. [ABSTRACT FROM AUTHOR]

The construction of a cut-off wall is a common reinforcement method for earth rock dams. At present, compared with the in-depth study on homogeneous earth dams, more and more attention is being paid to the stability and deformation of earth dams strengthened by a concrete cut-off wall. In this study, aiming at the Wujing project of the earth dam strengthened by cut-off wall, the influence of the water level rise and fall on the stability of the dam slope, the deformation of the dam body, and the crack width on dam crest were analyzed by numerical calculation and in situ measurement. The analysis results show that when the reservoir encounters a sudden drawdown, the safety factor of the dam slope decreases sharply. The faster the sudden drawdown, the faster the safety factor decreases. When the reservoir water level rises, the dam's horizontal displacement shifts to the upstream direction, and the change of horizontal displacement of the downstream slope is significantly larger than that at the measuring point of the upstream slope. The water level of the reservoir rises, and the surface of the dam body rises, and the fluctuation of settlement deformation shows that the upstream side is larger than the downstream side, especially during the period of abrupt change in the reservoir water level. The longitudinal cracks on the dam crest show a tendency of shrinkage when the reservoir water level rises, and opening decreases with the decrease of deformation gradient increment and increases with the increase of gradient increment. [ABSTRACT FROM AUTHOR]

The comprehensive index method has difficulties in evaluating the influence of air pollutant concentration changes on ambient air quality. Thus, a comprehensive evaluation method based on pollutant entropy weights and trend-regulating factors is proposed. According to the information entropy rates of 6 pollutants, the single entropy weight index is proposed by integrating it with the single-quality index, which reflects pollutant variations in evaluation periods. The Spearman's rank correlation coefficient between the pollutant and Air Quality Index (AQI) is defined as the trend-regulating factor, which indicates the correlations between pollutants and improvements or retrogressions in ambient air quality. The covariance is used to determine the variation trend of ambient air quality, which decides the positive or negative of trend-regulating factor. This method is used to study the ambient air quality rates in 10 cities of Shaanxi Province from 2017 to 2022. The trends of air quality improvements vary among the central, northern, and southern cities. The central cities have more spaces for air quality improvements in terms of PM2.5 and O3. Although prevention efforts have reduced the impacts of pollutants, PM2.5 is still the key factor affecting improvements in ambient air quality in most cities in winter. Additionally, the O3 pollution in summer was not controlled effectively. The contribution to air pollution of O3 increased, on the contrary with the improvement in air quality. The coordinated control of PM2.5 and O3 is still an important method of ambient air quality improvement. [ABSTRACT FROM AUTHOR]

Drought is one of the most devastating disasters and a serious constraint on agricultural development. The reflectance-based vegetation indices (VIs), such as Normalized Difference Vegetation Index (NDVI), have been widely used for drought monitoring, but there is a lag in the response of VIs to the changes of photosynthesis induced by drought. Solar-induced chlorophyll fluorescence (SIF) is closely related to photosynthesis of vegetation and can capture changes induced by drought timely. This study investigated the capability of SIF for drought monitoring. An intelligent irrigation control system (IICS) utilizing the Internet of Things was designed and constructed. The soil moisture of the experiment plots was controlled at 60–80% (well-watered, T1), 50–60% (mild water stress, T2), 40–50% (moderate water stress, T3) and 30–40% (severe water stress, T4) of the field water capacity using the IICS based on data collected by soil moisture sensors. Meanwhile, SIF, NDVI, Normalized Difference Red Edge (NDRE) and Optimized Soil Adjusted Vegetation Index (OSAVI) were collected for a long time series using an automated spectral monitoring system. The differences in the responses of SIF, NDVI, NDRE and OSAVI to different drought intensities were fully analyzed. This study illustrates that the IICS can realize precise irrigation management strategies and the construction of regulated deficit irrigation treatments. SIF significantly decreased under mild stress, while NDVI, NDRE and OSAVI only significantly decreased under moderate and severe stress, indicating that SIF is more sensitive to drought. This study demonstrates the excellent ability of SIF for drought monitoring and lays the foundation for the future application of SIF in agricultural drought monitoring. [ABSTRACT FROM AUTHOR]

Simple Summary: Neuroblastoma (NB) is the most common extracranial solid tumor in children, and the majority of patients with high-risk disease are unable to be cured. There is an urgent need to design novel therapeutics for NB patients. In NB, the RAS-MAPK pathway plays a crucial role in essential processes such as cell proliferation, survival, and chemoresistance. In the present study, we determined the therapeutic potential of the ERK inhibitor ulixertinib in NB using a panel of NB cell lines, patient-derived xenograft (PDX) cell lines, and NB xenograft mouse models. Ulixertinib significantly and potently inhibited NB cell proliferation and tumor growth, as well as prolonged survival in the treated mice. Additionally, ulixertinib synergistically sensitized NB cells to the conventional chemotherapeutic drug doxorubicin. This study provides proof-of-concept pre-clinical evidence for exploring ulixertinib as a novel therapeutic approach for NB. Neuroblastoma (NB) is a pediatric tumor of the peripheral nervous system. Approximately 80% of relapsed NB show RAS-MAPK pathway mutations that activate ERK, resulting in the promotion of cell proliferation and drug resistance. Ulixertinib, a first-in-class ERK-specific inhibitor, has shown promising antitumor activity in phase 1 clinical trials for advanced solid tumors. Here, we show that ulixertinib significantly and dose-dependently inhibits cell proliferation and colony formation in different NB cell lines, including PDX cells. Transcriptomic analysis revealed that ulixertinib extensively inhibits different oncogenic and neuronal developmental pathways, including EGFR, VEGF, WNT, MAPK, NGF, and NTRK1. The proteomic analysis further revealed that ulixertinib inhibits the cell cycle and promotes apoptosis in NB cells. Additionally, ulixertinib treatment significantly sensitized NB cells to the conventional chemotherapeutic agent doxorubicin. Furthermore, ulixertinib potently inhibited NB tumor growth and prolonged the overall survival of the treated mice in two different NB mice models. Our preclinical study demonstrates that ulixertinib, either as a single agent or in combination with current therapies, is a novel and practical therapeutic approach for NB. [ABSTRACT FROM AUTHOR]

In order to solve the problem of vegetation restoration in the traditional heap leaching of rare earths, a novel heap leaching technology is proposed. In the novel technology, leaching liquid is laterally injected into the rare earth pile from the side end so that vegetation restoration can be carried out quickly on the top of the pile. In this study, a laboratory test was performed to investigate the permeability of the ion-adsorbed rare earth pile under lateral liquid injection conditions. Four rare earth samples with varied combinations of the mineral particles at different sizes were adopted in the test to emphatically discuss the influence of the particle composition on permeability. The experimental results show that the permeability of the rare earth pile under the lateral liquid injection conditions is governed by the migration of fine particles. As the hydraulic head of the leaching liquid increases, the fine particles undergo a motion process of stabilization, migration initiation, deposition, and remigration. Accordingly, the permeability coefficient of the rare earth pile exhibits a variation of stabilization, a gradual increase, a re-stabilization, and a re-increase. The fine particle migration and exudation causes the permeability of the rare earth pile to be non-uniform in space. The permeability coefficients near the liquid injection end and the liquid outlet end are much greater than those are at the middle positions of the pile. The particle composition of the rare earth has an important effect on the permeability of the pile. In the rare earth with a combination of coarse and fine particles, preferential flow paths are easy to develop as in this soil, the fine particles easily migrate and they cannot block the pore channels. By contrast, the fine particles find it difficult to migrate, and the permeability coefficient is relatively stable in the fine-medium particle rare earth. This particle composition is conducive to the heap leaching of the rare earth under lateral liquid injection conditions. [ABSTRACT FROM AUTHOR]

Aiming at the problems of heavy workload of medical staff in the process of venous thrombosis prevention and treatment, error evaluation, missed evaluation, and inconsistent evaluation, we propose a joint extraction model of Chinese electronic medical records based on deep learning. The approach was to first construct the handshake annotation, then use bidirectional encoder representations from transformers (BERT) as the word vector embedding, then use the bidirectional long short-term memory network (BiLSTM) to extract the contextual features, and then integrate the contextual information into the process of normalizing the word vector. Experiments show that our proposed method achieves 93.3% and 94.3% of entity and relation F1 on the constructed electronic medical record dataset, which effectively improves the effect of medical information extraction. At the same time, the venous thromboembolism (VTE) risk factors extracted from the electronic medical record were used to judge the risk factors of venous thrombosis by means of rule reasoning. Compared with the assessment of clinicians on the Wells and Geneva scales, the accuracy rates of 84.7% and 86.1% were obtained. [ABSTRACT FROM AUTHOR]

The criteria-based sand and dust weather determination method has the problem ofbeing a cumbersome and time-consuming process when processing a large amount of raw data, and cannot avoid the problems of repeatability and reproducibility. On the basis of statistical analysis of the air automatic monitoring data in the cities affected by sand and dust, this paper proposes a k-means optimization algorithm (MDPD-k-means) based on maximum density and percentage distance, which can quickly filter the characteristic data of sand and dust in a short time, and identify the days affected by sand and dust. This method effectively improves the data processing efficiency, solves the problems of poor reproducibility and large artificial error of traditional methods, and can support the business application of sand and dust data elimination. This paper uses the method to identify the sand and dust data of 10 cities in Shaanxi Province from 2016 to 2022, determines a total of 1107 sand and dust days, and points out that the number of days affected by sand and dust is increasing year by year. After excluding the effect of sand and dust, the urban PM10 concentration decreases by 18.42~1.41% respectively, which provides important data information for accurately evaluating the effectiveness of air pollution prevention and control. [ABSTRACT FROM AUTHOR]

In order to address the discontinuity caused by the direct application of the infrared and visible image fusion anti-halation method to a video, an efficient night vision anti-halation method based on video fusion is proposed. The designed frame selection based on inter-frame difference determines the optimal cosine angle threshold by analyzing the relation of cosine angle threshold with nonlinear correlation information entropy and de-frame rate. The proposed time-mark-based adaptive motion compensation constructs the same number of interpolation frames as the redundant frames by taking the retained frame number as a time stamp. At the same time, considering the motion vector of two adjacent retained frames as the benchmark, the adaptive weights are constructed according to the interframe differences between the interpolated frame and the last retained frame, then the motion vector of the interpolated frame is estimated. The experimental results show that the proposed frame selection strategy ensures the maximum safe frame removal under the premise of continuous video content at different vehicle speeds in various halation scenes. The frame numbers and playing duration of the fused video are consistent with that of the original video, and the content of the interpolated frame is highly synchronized with that of the corresponding original frames. The average FPS of video fusion in this work is about six times that in the frame-by-frame fusion, which effectively improves the anti-halation processing efficiency of video fusion. [ABSTRACT FROM AUTHOR]

Satellite clock offsets are the critical parameters for The Global Navigation Satellite Systems (GNSSs) to provide position and timing (PNT) service. Unlike other GNSSs, BDS-3 uses the two-way superimposition strategy to measure satellite clock offsets. However, affected by some deficiencies of the two-way superimposition strategy, the accuracy of BDS-3 clock offsets parameters is 1.29 ns (RMS), which is the main bottleneck for BDS-3 to improve its space signal accuracy. After analyzing problems in the clock offsets measurement process of BDS-3, the paper proposes a new strategy to real-time estimate high-accuracy satellite clock offsets. The clock offsets estimated by the new strategy show a good consistency with GBM clock offsets. The averaged STD of their differences in MEO is 0.14 ns, and the clock offsets estimated by the new strategy present less fluctuation in the 1-day fitting residuals. Applying the new clock offsets to prediction, BDS-3 can reduce its clock offsets errors from 1.05 ns to 0.29 ns (RMS), about 72%. The above results indicate that the new clock offsets estimated strategy can improve the accuracy of clock offsets parameters of BDS-3 effectively. [ABSTRACT FROM AUTHOR]

During blasting in deep mining and excavation, the rock masses usually suffer from high in situ stress. The initial seismic energy generated in deep rock blasting and its attenuation with distance is first theoretically analyzed in this study. Numerical modeling of the multiple-hole blasting in a circular tunnel excavation under varied in situ stress conditions is then conducted to investigate the influences of in situ stress levels and anisotropy on the blasting seismic energy generation and attenuation. The case study of the deep rock blasting in the China Jinping Underground Laboratory (CJPL) is finally presented to demonstrate the seismic energy attenuation laws under varied in situ stress levels. The results show that with the increase in the in situ stress level, the explosive energy consumed in the rock fracture is reduced, and more explosive energy is converted into seismic energy. The increasing in situ stress causes the seismic Q of the rock mass medium to first increase and then decrease, and consequently, the seismic energy attenuation rate first decreases and then increases. Compared to the condition without in situ stress, the blasting seismic energy decays more slowly with distance under in situ stress. Then the seismic waves generated in deep rock blasting are more likely to reach and exceed the peak particle velocity (PPV) limits stipulated in the blasting vibration standards. Under non-hydrostatic in situ stress, the generation and attenuation of the blasting seismic energy are anisotropic. The highest seismic energy density is generated in the rock mass in the minimum principal stress orientation. Its attenuation is dependent upon the in situ stress aligning the wave propagation orientation. [ABSTRACT FROM AUTHOR]

Precise point positioning can provide accurate coordinates to users without reference stations, and the high-precision real-time clock offset product is necessary for real-time precise point positioning application. As an integral part of the third generation BeiDou Navigation Satellite System, Precision Point Positioning Service provides dual systems (BDS-3 and GPS) real-time PPP services with centimeter- and decimeter-level accuracy for static and kinematic positioning users around China, respectively. However, there exist inconsistent biases in the clock offset of Precision Point Positioning Service, which will negatively affect the positioning and timing performance of the service. By comparing with the post-processing clock offset, this paper verifies that the broadcast clock offset has smaller and more stable biases in the long term and proposes a regional clock offset estimation strategy using broadcast clock offset for a priori constraint. The results show that the new algorithm can effectively reduce the bias in PPP-B2b clock offset. The new clock offset product could improve convergence speed by 25% and 10% in the horizontal and vertical directions. For positioning accuracy, the improvement is 22% and 17%. The absolute error of timing can also be reduced by 60%. [ABSTRACT FROM AUTHOR]

With the frequent occurrence of emergencies such as the COVID-19 pandemic in recent years, resilience has become increasingly important for the stable and sustainable development of the manufacturing companies. Despite growing interest in supply chain resilience, less attention has been paid to manufacturer resilience and how to improve it through supplier relationship governance. Based on resource-based view (RBV) theory, trust theory and the literature on resilience, this study developed new constructs of measuring manufacturer resilience by temporal logic and sheds light on how the trust relationship with suppliers affect manufacturer resilience via the information-sharing level. The data is collected from 351 respondents who are independent directors or managers of manufacturing companies in China. This study adopted exploratory factor analysis (EFA) and structural equation modeling (SEM) to explore the dimensions of manufacturer resilience and to test the hypotheses. The results reveal that the trust relationship with suppliers has significant positive impacts on three dimensions of manufacturer resilience, that is, preparedness, responsiveness, and recovery capability. In addition, the information-sharing level partially mediates the impact of the trust relationship with suppliers on manufacturer resilience. Specifically, the information-sharing level positively affects preparedness, responsiveness, and recovery capability. Moreover, the trust relationship with suppliers facilitates the information-sharing level. Finally, the study contributes to the manufacturer resilience literature and provides useful guidance for the manufacturing enterprises in enhancing resilience quickly. [ABSTRACT FROM AUTHOR]

Conventional quenching and tempering were employed to achieve the optimal strength and toughness of low-carbon low-alloy steel. The fracture behavior (crack initiation and propagation) of the steel in the impact process was also analyzed. It was found that the microstructures of the steel after different tempering treatments were mainly composed of martensite, and its mechanical properties were dependent on the tempering temperature. With the increase in tempering temperature, martensitic laths merged and coarsened. Moreover, recovery occurred, causing a decrease in dislocation density. Subsequently, the strength of the steel gradually decreased, and the impact energy increased. When the tempering temperature was 600 °C, the optimal yield strength (557 MPa) and the impact energy (331 J) were achieved. In addition, high angle grain boundaries (HAGBs) affected the impact energy and crack propagation. Cracks were easily deflected when they encountered high angle grain boundaries, and linearly expanded when they encountered low angle grain boundaries (LAGBs). [ABSTRACT FROM AUTHOR]

Accurate knowledge of soil moisture is crucial for agricultural drought monitoring. Data assimilation has proven to be a promising technique for improving soil moisture estimation, and various studies have been conducted on soil moisture data assimilation based on land surface models. However, crop growth models, which are ideal tools for agricultural simulation applications, are rarely used for soil moisture assimilation. Moreover, the role of data assimilation in agricultural drought monitoring is seldom investigated. In the present work, we assimilated the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture product into the Decision Support System for Agro-technology Transfer (DSSAT) model to estimate surface and root-zone soil moisture, and we evaluated the effect of data assimilation on agricultural drought monitoring. The results demonstrate that the soil moisture estimates were significantly improved after data assimilation. Root-zone soil moisture had a better agreement with in situ observation. Compared with the drought index based on soil moisture modeled without remotely-sensed observations, the drought index based on assimilated data could improve at least one drought level in agricultural drought monitoring and performed better when compared with winter wheat yield. In conclusion, crop growth model-based data assimilation effectively improves the soil moisture estimation and further strengthens soil moisture-based drought indices for agricultural drought monitoring. [ABSTRACT FROM AUTHOR]

With the growth in demand for energy and the boom in energy internet (EI) technologies, comes the multi-energy complementary system. In this paper, we first model the components of the micro-energy-grid for a greenhouse, and then analyzed two types of protected agriculture load: time-shifting load and non-time-shifting load. Next, multi-scenario technology is directed against the uncertainty of photovoltaic (PV). Latin Hypercube Sampling (LHS) and the backward reduction algorithm are the two main methods we use to generate the representative scenarios and their probabilities, which are the basis for PV prediction in day-ahead scheduling. Third, besides the time of day (TOD) tariff, we present a model using real-time pricing of consumers' electricity load, which is proposed to compare consumers' demand response (DR). Finally, we establish a new optimization model of micro-energy-grid for greenhouses. By calculating the dispatch of electricity, heat, energy storage and time-shifting load under different conditions, the local consumption of PV and the comprehensive operational cost of micro-energy-grid can be analyzed. The results show that a storage device, time-shifting load and real-time pricing can bring more possibilities to the micro-energy-grid. By optimizing the time schedule of time-shifting load, the cost of the greenhouse is reduced. [ABSTRACT FROM AUTHOR]

Featured Application: A bi-level optimal model and relevant algorithm is proposed in the paper to achieve the safe, stable, and economical operation of the distribution network comprising a micro energy grid. The model and algorithm proposed in the paper can provide useful theoretical reference for the integrated energy service company to achieve optimal operation and control of the distribution network comprising a micro energy grid. With a focus on the safe, stable, and economical operation of a micro energy grid and a distribution network, this study proposes a bi-level optimal model for the integrated operation of a micro energy grid and a distribution network. The upper model used the minima of three objectives, including the integrated operating cost of the distribution network, the network’s active power loss, and the standard deviation of the voltage deviation in the distribution network. The lower model used the minimum integrated operating cost for the micro energy grid as the objective function. Considering the large number of objectives in the upper model, and that no single optimal solution existed, the judgment-matrix method was used to obtain the weight factors of each objective, and the upper multi-objective optimization problem was transformed into a single-objective problem in this paper. A grey wolf optimization algorithm based on the dynamic adjustment of the proportional weight and convergence factor was proposed to solve the operating model of the distribution network comprising the micro energy grid. This algorithm offers a high solution precision, a high convergence speed, and a strong global searching ability. The nonlinear convergent factor formula proposed in this paper dynamically adjusted the global searching ability of the algorithm, while the proposed proportional weight sped up the convergence of the algorithm. The superiority of the proposed algorithm was verified mathematically by six test functions. The simulation results demonstrated that the model and algorithm proposed in this paper improved the economic benefits, and voltage stability of the distribution network, reduced the active power loss of the distribution network, and enabled the safe, stable, and economical operation of the distribution network comprising a micro energy grid. [ABSTRACT FROM AUTHOR]

Due to satellite signal deformations, there are different constant biases in the same satellite signal that are measured by different technical types of receivers and different satellite signals that are measured by the same type of receiver, which are named pseudorange biases. These biases cannot be transmitted to users with existing navigation parameters, such as satellite time group delay (TGD) and receiver differential code biases (DCB). With the improvement of the signal-in-space accuracy of the Global Navigation Satellite System (GNSS), the pseudorange bias has become one of the primary error sources affecting the accuracy of GNSS services. To ensure the accuracy for users under the wide area differential services (WADS), we extracted the pseudorange biases of Beidou Satellite Navigation System (BDS) B1I, B3I and B1I/B3I signals and analyzed the impact of those biases on users under the WADS. Finally, we tried to eliminate this influence. The results show that the pseudorange biases of the B3I signal are smaller than those of the B1I signal at the centimeter level, but the pseudorange biases of the B1I/B3I signal can reach the meter level. Due to the large pseudorange bias of the B1I/B3I signal, the average user equivalent ranging error (UERE) under the WADS is 1.19 m, which is no better than the average UERE under open services (OS). Influenced by the pseudorange biases, the average positioning accuracies of the B1I/B3I signal are 4.17 m and 4.24 m under the WADS and the OS. When the pseudorange biases are deducted, these accuracies are 3.03 m and 3.50 m, respectively. [ABSTRACT FROM AUTHOR]

A long interactive TCP connection chain has been widely used by attackers to launch their attacks and thus avoid detection. The longer a connection chain, the higher the probability the chain is exploited by attackers. Round-trip Time (RTT) can represent the length of a connection chain. In order to obtain the RTTs from the sniffed Send and Echo packets in a connection chain, matching the Sends and Echoes is required. In this paper, we first model a network traffic as the collection of RTTs and present the rationale of using the RTTs of a connection chain to represent the length of the chain. Second, we propose applying MMD data mining algorithm to match TCP Send and Echo packets collected from a connection. We found that the MMD data mining packet-matching algorithm outperforms all the existing packet-matching algorithms in terms of packet-matching rate including sequence number-based algorithm, Yang's approach, Step-function, Packet-matching conservative algorithm and packet-matching greedy algorithm. The experimental results from our local area networks showed that the packet-matching accuracy of the MMD algorithm is 100%. The average packet-matching rate of the MMD algorithm obtained from the experiments conducted under the Internet context can reach around 94%. The MMD data mining packet-matching algorithm can fix the issue of low packet-matching rate faced by all the existing packet-matching algorithms including the state-of-the-art algorithm. It is applicable to network-based stepping-stone intrusion detection. [ABSTRACT FROM AUTHOR]

Primary angular vibration calibration devices based on laser interferometers play a crucial role in evaluating the dynamic performance of inertial sensing devices. Here, we propose a sinusoidal phase-modulated angle interferometer (SPMAI) to realize angular vibration measurements over a frequency range of 1–1000 Hz, in which the sinusoidal measurement retro-reflector (SMR) and the phase generation carrier (PGC) demodulation algorithm are adopted to track the dynamic angle variation. A comprehensive theoretical analysis is presented to reveal the relationship between demodulation performance of the SPMAI and several factors, such as phase modulation depth, carrier phase delay and sampling frequency. Both the simulated and experimental results demonstrate that the proposed SPMAI can achieve an angular vibration measurement with amplitude of sub-arcsecond under given parameters. Using the proposed SPMAI, the frequency bandwidth of an interferometric fiber-optic gyroscope (IFOG) is successfully determined to be 848 Hz. [ABSTRACT FROM AUTHOR]

A novel design method for time series modeling and prediction with fuzzy cognitive maps (FCM) is proposed in this paper. The developed model exploits the least square method to learn the weight matrix of FCM derived from the given historical data of time series. A fuzzy c-means clustering algorithm is used to construct the concepts of the FCM. Compared with the traditional FCM, the least square fuzzy cognitive map (LSFCM) is a direct solution procedure without iterative calculations. LSFCM model is a straightforward, robust and rapid learning method, owing to its reliable and efficient. In addition, the structure of the LSFCM can be further optimized with refinements the position of the concepts for the higher prediction precision, in which the evolutionary optimization algorithm is used to find the optimal concepts. Withal, we discussed in detail the number of concepts and the parameters of activation function on the impact of FCM models. The publicly available time series data sets with different statistical characteristics coming from different areas are applied to evaluate the proposed modeling approach. The obtained results clearly show the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

The problem of classification for imbalanced datasets is frequently encountered in practical applications. The data to be classified in this problem are skewed, i.e., the samples of one class (the minority class) are much less than those of other classes (the majority class). When dealing with imbalanced datasets, most classifiers encounter a common limitation, that is, they often obtain better classification performances on the majority classes than those on the minority class. To alleviate the limitation, in this study, a fuzzy rule-based modeling approach using information granules is proposed. Information granules, as some entities derived and abstracted from data, can be used to describe and capture the characteristics (distribution and structure) of data from both majority and minority classes. Since the geometric characteristics of information granules depend on the distance measures used in the granulation process, the main idea of this study is to construct information granules on each class of imbalanced data using Minkowski distance measures and then to establish the classification models by using "If-Then" rules. The experimental results involving synthetic and publicly available datasets reflect that the proposed Minkowski distance-based method can produce information granules with a series of geometric shapes and construct granular models with satisfying classification performance for imbalanced datasets. [ABSTRACT FROM AUTHOR]

Simple Summary: Neuroblastoma is a malignant tumor of the sympathetic nervous system that causes aggressive disease in children. The overall survival rate of high-risk patients is very low, therefore developing effective and safe therapies for neuroblastoma is an urgent unmet medical need. The mouse double minute 2 (MDM2) homolog gene is amplified and overexpressed in neuroblastoma and contributes to the poor response to treatment and poor prognosis in patients with high-risk neuroblastoma. Therefore, targeting MDM2 provides a promising approach to neuroblastoma therapy, especially for advanced disease. In the present study, we tested a unique MDM2 inhibitor, SP141, for its therapeutic efficacy and safety in neuroblastoma tumor models. We found that SP141 has significant anti- neuroblastoma activity in cell culture and inhibits tumor growth in animal models of human neuroblastoma, without any noticeable host toxicity. These results provide the basis for targeting MDM2 to treat high-risk neuroblastoma. Background: Neuroblastoma is an aggressive pediatric solid tumor with an overall survival rate of <50% for patients with high-risk disease. The majority (>98%) of pathologically-diagnosed neuroblastomas have wild-type p53 with intact functional activity. However, the mouse double minute 2 (MDM2) homolog, an E3 ubiquitin ligase, is overexpressed in neuroblastoma and leads to inhibition of p53. MDM2 also exerts p53-independent oncogenic functions. Thus, MDM2 seems to be an attractive target for the reactivation of p53 and attenuation of oncogenic activity in neuroblastoma. Methods: In this study, we evaluated the anticancer activities and underlying mechanisms of action of SP141, a first-in-class MDM2 inhibitor, in neuroblastoma cell lines with different p53 backgrounds. The findings were confirmed in mouse xenograft models of neuroblastoma. Results: We demonstrate that SP141 reduces neuroblastoma cell viability, induces apoptosis, arrests cells at the G2/M phase, and prevents cell migration, independent of p53. In addition, in neuroblastoma xenograft models, SP141 inhibited MDM2 expression and suppressed tumor growth without any host toxicity at the effective dose. Conclusions: MDM2 inhibition by SP141 results in the inhibition of neuroblastoma growth and metastasis, regardless of the p53 status of the cells and tumors. These findings provide proof-of-concept that SP141 represents a novel treatment option for both p53 wild-type and p53 null neuroblastoma. [ABSTRACT FROM AUTHOR]

Understanding the winter wheat yield responses to drought are the keys to minimizing drought-related winter wheat yield losses under climate change. The research goal of our study is to explore the response patterns of winter wheat yield to drought in the North China Plain (NCP) and then further to study which climatic factors drive the response patterns. For this purpose, winter wheat yield was simulated by the Environmental Policy Integrated Climate (EPIC) crop model. Drought was quantified by standardized precipitation evapotranspiration index (SPEI), and the contributions of the various climatic factors were evaluated using predictive discriminant analysis (PDA) method. The results showed that the responses of winter wheat yield to different time-scale droughts have obvious spatial differences from the north part to the south part in the NCP. Winter wheat yield is more sensitive to the medium (6–9 months) and long (9–12 months) time-scale droughts that occurred in the key growth periods (April and May). The different response patterns of winter wheat yield to the different time-scale droughts are mainly controlled by temperature and water balance (precipitation minus potential evapotranspiration) in winter in the NCP. Compared with the water balance, temperature plays a more important role in driving the response pattern characteristics. These findings can provide a reference on how to reduce drought influences on winter wheat yield in the NCP. [ABSTRACT FROM AUTHOR]

Drought has become one of the major constraints to agricultural development, particularly in areas that lack water. Studying the effects of different water stresses on the photosynthesis, growth, yield, water use efficiency (WUE) and irrigation water productivity (IWP) of winter wheat will provide data for the development of scientific irrigation strategies for water-saving agricultural methods. According to the size of the field water capacity, four different water stress levels were set, i.e., 30–40% (severe stress), 40–50% (moderate stress), 50–60% (mild stress) and 60–80% (well-watered) of field water capacity, controlling the amount of irrigation through an automatic irrigation system. The results showed that the seasonal changes in photosynthetic parameters, such as net photosynthetic rate (Pn), intercellular carbon concentration (Ci), stomatal conductance (Gs) and transpiration (E), significantly decreased under moderate and severe stress. As a result, the height, biomass and grain size of winter wheat decreased significantly, which led to low WUE and IWP. The Pn of the mild stress group only slightly decreased compared to that of the well-watered group, and was actually higher during the flowering and grain-filling stages, resulting in increases in dry biomass and 1000 grain weight of 2.07% and 1.95%, respectively. Higher WUE and IWP were attributed to higher yields and less water use. Thus, mild stress (60–80% field water capacity) resulted in the optimal use of water resources without a significant reduction in yield in the North China Plain (NCP). Therefore, mild stress can be considered a suitable environment for winter wheat growth in arid areas. [ABSTRACT FROM AUTHOR]

Background. Meningiomas constitute one-third of all primary brain tumors. Although typically benign, about 20% of these tumors recur despite surgery and radiation, and may ultimately prove fatal. There are currently no effective chemotherapies for meningioma. We, therefore, set out to develop patient-derived orthotopic xenograft (PDOX) mouse models of human meningioma using tumor. Method. Of nine patients, four had World Health Organization (WHO) grade I tumors, five had WHO grade II tumors, and in this second group two patients also had recurrent (WHO grade III) meningioma. We also classified the tumors according to our recently developed molecular classification system (Types A, B, and C, with C being the most aggressive). We transplanted all 11 surgical samples into the skull base of immunodeficient (SCID) mice. Only the primary and recurrent tumor cells from one patient—both molecular Type C, despite being WHO grades II and III, respectively—led to the formation of meningioma in the resulting mouse models. We characterized the xenografts by histopathology and RNA-seq and compared them with the original tumors. We performed an in vitro drug screen using 60 anti-cancer drugs followed by in vivo validation. Results. The PDOX models established from the primary and recurrent tumors from patient K29 (K29P-PDOX and K29R-PDOX, respectively) replicated the histopathology and key gene expression profiles of the original samples. Although these xenografts could not be subtransplanted, the cryopreserved primary tumor cells were able to reliably generate PDOX tumors. Drug screening in K29P and K29R tumor cell lines revealed eight compounds that were active on both tumors, including three histone deacetylase (HDAC) inhibitors. We tested the HDAC inhibitor Panobinostat in K29R-PDOX mice, and it significantly prolonged mouse survival (p < 0.05) by inducing histone H3 acetylation and apoptosis. Conclusion. Meningiomas are not very amenable to PDOX modeling, for reasons that remain unclear. Yet at least some of the most malignant tumors can be modeled, and cryopreserved primary tumor cells can create large panels of tumors that can be used for preclinical drug testing. [ABSTRACT FROM AUTHOR]

The combined study of vegetation coverage (VC) and land use change provides important scientific guidance for the restoration and protection of arid regions. Taking Hongjian Nur (HJN) Lake in the desert region as a case study, the VC of this area was calculated using a normalized difference vegetation index (NDVI), which is based on a mixed pixel decomposition method. A grey forecasting model (GM) (1, 1) was used to predict future VC. The driving factors of VC and land use change were analyzed. The results indicate that the average VC of the whole watershed showed a gradual increase from 0.29 to 0.49 during 2000–2017. The prediction results of the GM VC showed that the greening trend is projected to continue until 2027. The area of farmland in the watershed increased significantly and its area was mainly converted from unused land, grassland, and forest. The reason for increased VC may be that the combination of the exploitation of unused land and climate change, which is contrary to the country's sustainable development goals (SDG; goal 15). Therefore, the particularities of the local ecological environment in China's desert area needs to be considered in the development of ecological engineering projects. [ABSTRACT FROM AUTHOR]

It has been demonstrated that solar-induced chlorophyll fluorescence (SIF) is linearly related to the primary production of photosynthesis (GPP) in various ecosystems. However, it is unknown whether such linear relationships have been established in senescent crops. SIF and GPP can be expressed as the products of absorbed photosynthetically active radiation (APAR) with the SIF yield and photosystem II (PSII) operating efficiency, respectively. Thus, the relationship between SIF and GPP can be represented by the relationship between the SIF yield and PSII operating efficiency when the APAR has the same value. Therefore, we analyzed the relationship between the SIF yield and the PSII operating efficiency to address the abovementioned question. Here, diurnal measurements of the canopy SIF (760 nm, F760) of soybean and sweet potato were manually measured and used to calculate the SIF yield. The PSII operating efficiency was calculated from measurements of the chlorophyll fluorescence at the leaf level using the FluorImager chlorophyll fluorescence imaging system. Meanwhile, field measurements of the gas exchange and other physiological parameters were also performed using commercial-grade devices. The results showed that the SIF yield was not linearly related to the PSII operating efficiency at the diurnal scale, reflecting the nonlinear relationship between SIF and GPP. This nonlinear relationship mainly resulted from the heterogeneity and diurnal dynamics of the PSII operating efficiency and from the intrinsic diurnal changes in the maximum efficiency of the PSII photochemistry and the proportion of opened PSII centers. Intensifying respiration was another factor that complicated the response of photosynthesis to the variation in environmental conditions and negatively impacted the relationship between the SIF yield and the PSII operating efficiency. The nonlinear relationship between the SIF yield and PSII efficiency might yield errors in the estimation of GPP using the SIF measurements of senescent crops. [ABSTRACT FROM AUTHOR]

Neat asphalt emulsions have poor physicochemical properties. In order to endow neat asphalt emulsions with excellent physicochemical properties and broaden their application as pavement, this study adopted the composite modification method using waterborne epoxy resin (WER) and styrene–butadiene rubber (SBR) latex. Firstly, a waterborne-epoxy–SBR composite modified asphalt emulsions (WESAEs) with different amounts of WER were prepared, and the storage stability, workability, and residual properties were characterized with a series of tests. Then, the performance of the WESAEs was comprehensively evaluated by multiobjective gray target decision-making method, through which the optimal amount of WER in WESAE was determined. Lastly, the modification mechanism of WER was revealed by Fourier-transform infrared spectroscopy test. The results show that the incorporation of WER improves the high-temperature performance, thermal stability, rheological property, and adhesion of the SBR modified asphalt emulsion (SBRAE) residues. However, an excessive amount of WER will adversely affect the storage stability, particle distribution uniformity, and workability of the WESAE binder. The WESAE with 3% WER showed the best comprehensive performance; thus, the optimal amount of WER is 3% of the weight of the WESAE. Additionally, modification of the SBRAE by WER is a physical blending process, meaning no chemical reaction occurs in the blending process. [ABSTRACT FROM AUTHOR]

Increased drought frequency in Australia is a pressing concern for scholars. In 2018, a severe drought in eastern Australia was recorded by the Emergency Events Database (EM-DAT). To investigate the main causes and impacts of this drought across southeastern Australia, this work presents an overview of the drought mechanism and depicts its evolutionary process. The Standardized Precipitation Evapotranspiration Index (SPEI) from the Global Drought Monitor was used to identify the drought event and characterize its spatiotemporal distribution. The Normalized Difference Vegetation Index (NDVI) and the sun-induced chlorophyll fluorescence (SIF) were used to investigate the drought impacts on vegetation growth. In addition, the effects of drought response measures on Sustainable Development Goals (SDGs) were analyzed. Our results showed that the exceptional drought occurred across southeastern Australia from April to December, and it was most severe in July, owing to an extreme lack of precipitation and increase in temperature. Moreover, we identified profound and long-lasting impacts of the drought on NDVI and SIF levels, especially for cropland. Furthermore, we also found that SIF was superior to NDVI in detecting drought impacts. This study advised on how to formulate timely and effective drought-response measures and supports sustainable socioeconomic development in Australia. [ABSTRACT FROM AUTHOR]

To overcome the inherent deficiencies of hearing aids, implantable middle ear hearing devices (IMEHDs) have emerged as a new treatment for hearing loss. However, clinical results show that the IMEHD performance varies with its transducer's stimulating site. To numerically analyze the influence of the piezoelectric transducer's stimulating sites on its hearing compensation performance, we constructed a human ear finite element model and confirmed its validity. Based on this finite element model, the displacement stimulation, which simulates the piezoelectric transducer's stimulation, was applied to the umbo, the incus long process, the incus body, the stapes, and the round window membrane, respectively. Then, the stimulating site's effect of the piezoelectric transducer was analyzed by comparing the corresponding displacements of the basilar membrane. Besides, the stimulating site's sensitivity to the direction of excitation was also studied. The result of the finite element analysis shows that stimulating the incus body is least efficient for the piezoelectric transducer. Meanwhile, stimulating the round window membrane or the stapes generates a higher basilar membrane displacement than stimulating the eardrum or the incus long process. However, the performance of these two ideal sites' stimulation is sensitive to the changes in the excitation's direction. Thus, the round window membrane and the stapes is the ideal stimulating sites for the piezoelectric transducer regarding the driving efficiency. The direction of the excitation should be guaranteed for these ideal sites. [ABSTRACT FROM AUTHOR]

Solar-induced chlorophyll fluorescence (SIF) is considered to be a potential indicator of photosynthesis. However, the impact of growth and environmental parameters on SIF at different time-scales remains unclear, which has greatly restricted the application of SIF in detecting photosynthesis variations. Thus, in this study, the impact of growth and environmental parameters on SIF was thoroughly clarified. Here, continuous time series of canopy SIF (760 nm, F760) over wheat and maize was measured based on an automated spectroscopy system. Meanwhile, field measurements of growth and environmental parameters were also collected using commercial-grade devices. Relationships of these parameters with F760, apparent SIF (F760/solar radiance, AF760), and SIF yield (F760/canopy radiance of 685 nm, Fy760) were analyzed using principal component analysis (PCA) and Pearson correlation to reveal their impacts on SIF. Results showed that F760 at seasonal and diurnal scales were mainly driven by solar radiation (SWR), leaf area index (LAI), chlorophyll content (Chl), mean leaf inclination angle (MTA), and relative water content (RWC). Other environmental parameters, including air temperature (Ta), relative humidity (Rh), vapor pressure deficit (VPD), and soil moisture (SM), contribute less to the variation of seasonal or diurnal F760. AF760 and Fy760 are likely to be less dependent on Ta, Rh, and VPD due to the removal of the impact from SWR, but an enhanced relationship of AF760 (and Fy760) with SM was observed, particularly under water stress. Compared with F760, wheat AF760 was better correlated to LAI and RWC as expected, while maize AF760 did not show an enhanced relationship with all growth parameters, probably due to its complicated canopy structure. The relationship of wheat Fy760 with canopy structure parameters was further reduced, except for maize measurements. Furthermore, SM-induced water stress and phenological stages should be taken into consideration when we interpret the seasonal and diurnal patterns of SIF since they were closely related to photosynthesis and plant growth (e.g., LAI in our study). To our knowledge, this is the first exploration of the impacts of growth and environmental parameters on SIF based on continuous ground measurements, not only at a seasonal scale but also at a diurnal scale. Our results could provide deep insight into the variation of SIF signals and also promote the further application of SIF in the health assessments of terrestrial ecosystems. [ABSTRACT FROM AUTHOR]

Advancing the background-subtraction method in dynamic scenes is an ongoing timely goal for many researchers. Recently, background subtraction methods have been developed with deep convolutional features, which have improved their performance. However, most of these deep methods are supervised, only available for a certain scene, and have high computational cost. In contrast, the traditional background subtraction methods have low computational costs and can be applied to general scenes. Therefore, in this paper, we propose an unsupervised and concise method based on the features learned from a deep convolutional neural network to refine the traditional background subtraction methods. For the proposed method, the low-level features of an input image are extracted from the lower layer of a pretrained convolutional neural network, and the main features are retained to further establish the dynamic background model. The evaluation of the experiments on dynamic scenes demonstrates that the proposed method significantly improves the performance of traditional background subtraction methods. [ABSTRACT FROM AUTHOR]

Background subtraction plays a fundamental role for anomaly detection in video surveillance, which is able to tell where moving objects are in the video scene. Regrettably, the regular rotating pumping unit is treated as an abnormal object by the background-subtraction method in pumping-unit surveillance. As an excellent classifier, a deep convolutional neural network is able to tell what those objects are. Therefore, we combined background subtraction and a convolutional neural network to perform anomaly detection for pumping-unit surveillance. In the proposed method, background subtraction was applied to first extract moving objects. Then, a clustering method was adopted for extracting different object types that had more movement-foreground objects but fewer typical targets. Finally, nonpumping unit objects were identified as abnormal objects by the trained classification network. The experimental results demonstrate that the proposed method can detect abnormal objects in a pumping-unit scene with high accuracy. [ABSTRACT FROM AUTHOR]

Round window (RW) stimulation is a new application of middle ear implants for treating hearing loss, especially for those with middle ear disease. However, most reports on it are based on the use of the floating mass transducer (FMT), which was not originally designed for round window stimulation. The mismatch of the FMT's diameter and the round window membrane's diameter and the uncontrollable preload of the transducer, leads to a high variability in its clinical outcomes. Accordingly, a new piezoelectric transducer for the round-window-stimulating-type middle ear implant is proposed in this paper. The transducer consists of a piezoelectric stack, a flextensional amplifier, a coupling rod, a salver, a plate, a titanium housing and a supporting spring. Based on a constructed coupling finite element model of the human ear and the transducer, the influences of the transducer design parameters on its performance were analyzed. The optimal structure of the supporting spring, which determines the transducer's resonance frequency, was ascertained. The results demonstrate that our designed transducer generates better output than the FMT, especially at low frequency. Besides this, the power consumption of the transducer was significantly decreased compared with a recently reported RW-stimulating piezoelectric transducer. [ABSTRACT FROM AUTHOR]

Due to the randomness of the intermittent distributed energy output and load demand of a micro-energy-grid, micro-sources cannot fully follow the day-ahead micro-energy-grid optimal dispatching plan. Therefore, a micro-energy-grid is difficult to operate steadily and is challenging to include in the response dispatch of a distribution network. In view of the above problems, this paper proposes an integrated optimal dispatch method for a micro-energy-grid based on model predictive control. In the day-ahead optimal dispatch, an optimal dispatch model of a micro-energy-grid is built taking the daily minimum operating cost as the objective function, and the optimal output curve of each micro-source of the next day per hour is obtained. In the real-time dispatch, rolling optimization of the day-ahead optimal dispatching plan is implemented based on model predictive control theory. The real-time state of the system is sampled, and feedback correction of the system is implemented. The influence of uncertain factors in the system is eliminated to ensure steady operation of the system. Finally, the validity and feasibility of the integrated optimal dispatching method are verified by a case simulation analysis. [ABSTRACT FROM AUTHOR]

The research on the factors of heat recovery performance of Enhanced Geothermal Systems (EGS) is an important issue, especially in the well position optimization in EGS, because it can maximize the economic benefits of EGS. Based on the three-dimensional thermo and hydro (TH) single-fracture model, a flow field in the EGS is added to the model, the thermal energy mining of the EGS thermal reservoir is realized through the double well and better study of the impact of regional flow on EGS well placement. To verify the reliability of the three-dimensional numerical model, the comparison between the two-dimensional single fracture model and the single fracture analytical model is performed under the same conditions, and it is found that there is a good agreement between the numerical and the analytical solutions. The influence of the direction of regional flow on the thermal recovery performance of EGS is studied, and the operating lifetime, power generation and heat production rate of the system are used as the evaluation indicators. It is found that there are two stagnation points in the flow field under regional flow conditions, and the stagnation point position changes regularly with regional flow direction. The direction of regional flow has a great influence on the heat extraction ratio and service lifetime of the geothermal system, the layout of the double well must take into account the regional flow. When only considered the influence of regional flow on EGS, after 50 years of EGS operation, the production well temperature and system operating lifetime increase with the increase of β (the angle between the direction of the regional flow and the line connecting the centers of the two wells). When it has regional flow, the greater the well spacing, the greater the temperature of the production well, but when the well spacing increases to a certain value, the well spacing will not affect the temperature of the production well. [ABSTRACT FROM AUTHOR]