Selective organic transformation under mild conditions constitutes a challenge in green chemistry, especially for alcohol oxidation, which typically requires environmentally unfriendly oxidants. ...Here, we report a new plasmonic catalyst of Au supported on BiOCl containing oxygen vacancies. It photocatalyzes selective benzyl alcohol oxidation with O2 under visible light through synergistic action of plasmonic hot electrons and holes. Oxygen vacancies on BiOCl facilitate the trapping and transfer of plasmonic hot electrons to adsorbed O2, producing •O2 – radicals, while plasmonic hot holes remaining on the Au surface mildly oxidize benzyl alcohol to corresponding carbon-centered radicals. The hypothesized concerted ring addition between these two radical species on the BiOCl surface highly favors the production of benzaldehyde along with an unexpected oxygen atom transfer from O2 to the product. The results and understanding acquired in this study, based on the full utilization of hot charge carriers in a plasmonic metal deposited on a rationally designed support, will contribute to the development of more active and/or selective plasmonic catalysts for a wide variety of organic transformations.
Yellow rust is one of the most destructive diseases for winter wheat and has led to a significant decrease in winter wheat quality and yield. Identifying and monitoring yellow rust is of great ...importance for guiding agricultural production over large areas. Compared with traditional crop disease discrimination methods, remote sensing technology has proven to be a useful tool for accomplishing such a task at large scale. This study explores the potential of the Sentinel-2 Multispectral Instrument (MSI), a newly launched satellite with refined spatial resolution and three red-edge bands, for discriminating between yellow rust infection severities (i.e., healthy, slight, and severe) in winter wheat. The corresponding simulative multispectral bands for the Sentinel-2 sensor were calculated by the sensor's relative spectral response (RSR) function based on the in situ hyperspectral data acquired at the canopy level. Three Sentinel-2 spectral bands, including B4 (Red), B5 (Re1), and B7 (Re3), were found to be sensitive bands using the random forest (RF) method. A new multispectral index, the Red Edge Disease Stress Index (REDSI), which consists of these sensitive bands, was proposed to detect yellow rust infection at different severity levels. The overall identification accuracy for REDSI was 84.1% and the kappa coefficient was 0.76. Moreover, REDSI performed better than other commonly used disease spectral indexes for yellow rust discrimination at the canopy scale. The optimal threshold method was adopted for mapping yellow rust infection at regional scales based on realistic Sentinel-2 multispectral image data to further assess REDSI's ability for yellow rust detection. The overall accuracy was 85.2% and kappa coefficient was 0.67, which was found through validation against a set of field survey data. This study suggests that the Sentinel-2 MSI has the potential for yellow rust discrimination, and the newly proposed REDSI has great robustness and generalized ability for yellow rust detection at canopy and regional scales. Furthermore, our results suggest that the above remote sensing technology can be used to provide scientific guidance for monitoring and precise management of crop diseases and pests.
The height of fractured water conducting zone is of significant importance for the safety of underground mining. Because of the conspicuous discrepancy of the height of fractured water conducting ...zone in Bulianta Coal Mine as predicted by the traditional method with those observed in practice, a systematic research has been carried out. The study indicates that two aspects should be taken into account. Firstly, the traditionally proposed empirical formula in prediction of the height of fractured zone was based on the conditions of single-slice mining where the mining height was less than 3
m and the total slice mining height was limited within 15
m. In such a case, it would not be suitable to predict the maximum fractured zone height for the conditions where a single mining height is larger than 3
m. Secondly, the stratum structure such as the thick and strong rock layer termed as
key stratum plays an important role in controlling of the height of movement in the overburden. Physical model tests by making use of a similar material illustrate that if the vertical distance from the primary key stratum to the coal seam is shorter than a certain value, then the developing fracture zone will extend above the key stratum into the top of bedrock, resulting in a larger height of water conducting zone than is calculated by the empirical method. The outcome of the work presented will be helpful in practice to prevent the overburden aquifer inrush and to avoid mine water hazard.
► There are some limitations for the application of the empirical formula (1). ► The key strata has a great impact on the height of movement in the overburden. ► The breakage of key stratum may enlarge the height of the fractured zone.
Yellow rust, a widely known destructive wheat disease, affects wheat quality and causes large economic losses in wheat production. Hyperspectral remote sensing has shown potential for the detection ...of plant disease. This study aimed to analyze the spectral reflectance of the wheat canopy in the range of 350⁻1000 nm and to develop optimal spectral indices to detect yellow rust disease in wheat at different growth stages. The sensitive wavebands of healthy and infected wheat were located in the range 460⁻720 nm in the early-mid growth stage (from booting to anthesis), and in the ranges 568⁻709 nm and 725⁻1000 nm in the mid-late growth stage (from filling to milky ripeness), respectively. All possible three-band combinations over these sensitive wavebands were calculated as the forms of PRI (Photochemical Reflectance Index) and ARI (Anthocyanin Reflectance Index) at different growth stages and assessed to determine whether they could be used for estimating the severity of yellow rust disease. The optimal spectral index for estimating wheat infected by yellow rust disease was PRI (570, 525, 705) during the early-mid growth stage with R² of 0.669, and ARI (860, 790, 750) during the mid-late growth stage with R² of 0.888. Comparison of the proposed spectral indices with previously reported vegetation indices were able to satisfactorily discriminate wheat yellow rust. The classification accuracy for PRI (570, 525, 705) was 80.6% and the kappa coefficient was 0.61 in early-mid growth stage, and the classification accuracy for ARI (860, 790, 750) was 91.9% and the kappa coefficient was 0.75 in mid-late growth stage. The classification accuracy of the two indices reached 84.1% and 93.2% in the early-mid and mid-late growth stages in the validated dataset, respectively. We conclude that the three-band spectral indices PRI (570, 525, 705) and ARI (860, 790, 750) are optimal for monitoring yellow rust infection in these two growth stages, respectively. Our method is expected to provide a technical basis for wheat disease detection and prevention in the early-mid growth stage, and the estimation of yield losses in the mid-late growth stage.
Numerous sudden surface collapses induced by shallow partial mining in the Datong Jurassic coal seam have caused fatalities, significant property losses and brought about harmful results to the ...environment. By introducing efficient pillar widths and using the Voronoi diagram, irregular pillar stability can be estimated rationally. Theoretical analysis and numerical simulation demonstrate that the failure of a single pillar increases the load on surrounding pillars. If the magnitude of the transferred load is sufficiently high, the adjoining pillars will also fail in a chain reaction. This can be interpreted by the merger of inner stress arches combined with the external stress arch. In this paper, the evolution mode of sudden surface collapse caused by shallow partial mining is proposed and has been verified by ‘similar material simulation.’ Finally, the potential of sudden surface collapse is determined and an example of collapse prediction and prevention of surface building damage with relocation is given.
It is of significant importance to prevent and control mining damage by quantitatively investigating the dynamic development law of overburden movement and deformation. Based on the principle of ...probability integral, a static prediction model of overlying strata movement and deformation was firstly derived in this study, and a subsidence coefficient model of overlying strata was then established. By combining the new static prediction model with periodic fracture characteristics of main roof and Knothe time function, a dynamic prediction model was proposed to predict mining-induced overburden movement and deformation, which is capable of achieving the dynamic and quantitative prediction of the behavior of the overlying strata. A Knothe time function parameter evaluation method was also constructed based on the main influence radius of surface mining subsidence. Taking the geological and mining conditions of T2195 working face of a coal mine as a case study, applicability of the model was studied for real prediction, and the reliability of the model was verified by comparing the measured data with the predicted results. The results showed that there is high consistency between the measured and predicted data, indicating the effectiveness and reliability of the proposed model. The research results not only provide technical support for the prevention and control of mining damage, but also further improve and enrich the theoretical system of mining subsidence.
•A static prediction model of mining-induced overburden subsidence is derived.•The model of subsidence coefficient in overburden is established.•A dynamic prediction method of overburden subsidence is proposed.•A method for calculating the parameter of Knothe time function is established.•The prediction effect and accuracy of the proposed model are studied.
A robust and effective method for the identification of point-distributed coded targets (IPCT) in a video-simultaneous triangulation and resection system (V-STARS) was reported recently. However, its ...limitations were the setting of critical parameters, it being non-adaptive, making misidentifications in certain conditions, having low positioning precision, and its identification effect being slightly inferior to that of the V-STARS. Aiming to address these shortcomings of IPCT, an improved IPCT, named I-IPCT, with an adaptive binarization, a more precise ellipse-center localization, and especially an invariance of the point–line distance ratio (PLDR), was proposed. In the process of edge extraction, the adaptive threshold Gaussian function was adopted to realize the acquisition of an adaptive binarization threshold. For the process of center positioning of round targets, the gray cubic weighted centroid algorithm was adopted to realize high-precision center localization. In the template point recognition procedure, the invariant of the PLDR was used to realize the determination of template points adaptively. In the decoding procedure, the invariant of the PLDR was adopted to eliminate confusion. Experiments in indoor, outdoor, and unmanned aerial vehicle (UAV) settings were carried out; meanwhile, sufficient comparisons with IPCT and V-STARS were performed. The results show that the improvements can make the identification approximately parameter-free and more accurate. Meanwhile, it presented a high three-dimensional measurement precision in close-range photogrammetry. The improved IPCT performed equally well as the commercial software V-STARS on the whole and was slightly superior to it in the UAV test, in which it provided a fantastic open solution using these kinds of coded targets and making it convenient for researchers to freely apply the coded targets in many aspects, including UAV photogrammetry for high-precision automatic image matching and three-dimensional real-scene reconstruction.
For mobile robots, the high-precision integrated calibration and structural robustness of multi-sensor systems are important prerequisites for ensuring healthy operations in the later stage. ...Currently, there is no well-established validation method for the calibration accuracy and structural robustness of multi-sensor systems, especially for dynamic traveling situations. This paper presents a novel validation method for the calibration accuracy and structural robustness of a multi-sensor mobile robot. The method employs a ground–object–air cooperation mechanism, termed the “ground surface simulation field (GSSF)—mobile robot -photoelectric transmitter station (PTS)”. Firstly, a static high-precision GSSF is established with the true north datum as a unified reference. Secondly, a rotatable synchronous tracking system (PTS) is assembled to conduct real-time pose measurements for a mobile vehicle. The relationship between each sensor and the vehicle body is utilized to measure the dynamic pose of each sensor. Finally, the calibration accuracy and structural robustness of the sensors are dynamically evaluated. In this context, epipolar line alignment is employed to assess the accuracy of the evaluation of relative orientation calibration of binocular cameras. Point cloud projection and superposition are utilized to realize the evaluation of absolute calibration accuracy and structural robustness of individual sensors, including the navigation camera (Navcam), hazard avoidance camera (Hazcam), multispectral camera, time-of-flight depth camera (TOF), and light detection and ranging (LiDAR), with respect to the vehicle body. The experimental results demonstrate that the proposed method offers a reliable means of dynamic validation for the testing phase of a mobile robot.
At present, GNSS (Global Navigation Satellite System) positioning technology is widely used for outdoor positioning services because of its high-precision positioning characteristics. However, in ...indoor environments, effective position information cannot be provided, because of the signals being obscured. In order to improve the accuracy and continuity of indoor positioning systems, in this paper, we propose a PDR/UWB (Pedestrian Dead Reckoning and Ultra Wide Band) integrated navigation algorithm based on an adaptively robust EKF (Extended Kalman Filter) to address the problem of error accumulation in the PDR algorithm and gross errors in the location results of the UWB in non-line-of-sight scenarios. First, the basic principles of UWB and PDR location algorithms are given. Then, we propose a loose combination of the PDR and UWB algorithms by using the adaptively robust EKF. By using the robust factor to adjust the weight of the observation value to resist the influence of the gross error, and by adjusting the variance of the system adaptively according to the positioning scene, the algorithm can improve the robustness and heading factor of the PDR algorithm, which is constrained by indoor maps. Finally, the effectiveness of the algorithm is verified by the measured data. The experimental results showed that the algorithm can not only reduce the accumulation of PDR errors, but can also resist the influence of gross location errors under non-line-of-sight UWB scenarios.
In the indoor and outdoor transition area, due to its poor availability in a complex positioning environment, the BDS/GPS SPP (single-point positioning by combining BeiDou Navigation Satellite System ...(BDS) and Global Positioning System (GPS)) is unable to provide an effective positioning service. In view of the poor positioning accuracy and low sampling rate of the BDS/GPS SPP and the gross error, such as the non-line-of-sight error of UWB (Ultra-Wide-Band), making the accuracy of positioning results poor, a BDS/GPS/UWB tightly coupled navigation model considering pedestrian motion characteristics is proposed to make positioning results more reliable and accurate in the transition area. The core content of this paper is divided into the following three parts: (1) Firstly, the dynamic model and positioning theories of BDS/GPS SPP and UWB are introduced, respectively. (2) Secondly, the BDS/GPS/UWB tightly coupled navigation model is proposed. An environment discrimination factor is introduced to adaptively adjust the variance factor of the system state. At the same time, the gross error detection factor is constructed by using the a posteriori residuals to make the variance factor of the measurement information of the combined positioning system able to be adjusted intelligently for the purpose of eliminating the interference of gross error observations on positioning results. On the other hand, pedestrian motion characteristics are introduced to establish the constraint equation to improve the consistency of positioning accuracy. (3) Thirdly, the actual measured data are used to demonstrate and analyze the reliability of the positioning model proposed by this paper. The experimental results show that the BDS/GPS/UWB tightly coupled navigation model can effectively improve the accuracy and availability of positioning. Compared with BDS/GPS SPP, the accuracy of this model is improved by 57.8%, 76.0% and 56.5% in the E, N and U directions, respectively.
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