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Azidation of alkenes is an efficient protocol to synthesize organic azides which are important structural motifs in organic synthesis. Enantioselective radical azidation, as a useful strategy to install a C-N3 bond, remains challenging due to the inherently instability and unique structure of radicals. Here, we disclose an efficient enantioselective radical carboazidation and diazidation of α,β-unsaturated ketones and amides catalyzed by chiral N,N'-dioxide/Fe(OTf)2 complexes. An array of substituted alkenes was transformed to the corresponding α-azido carbonyl derivatives in good to excellent enantioselectivities, benefiting the preparation of chiral α-amino ketones, vicinal amino alcohols, and vicinal diamines. Control experiments and mechanistic studies proved the radical pathway in the reaction process. The DFT calculations showed that the azido transferred to the radical intermediate via an intramolecular five-membered transition state with the internal nitrogen of the Fe-N3 species.

Atomic layer etching (ALE) of GaN on silicon substrates has been investigated using fluorine-based chemistry. The ALE process used for this study consists of a modification step using SF6 plasma and a removal step using argon plasma. Two configurations were studied in which the distance between the sample and the plasma source was modified. The energy scan, synergy, selective etching of GaFx by Ar+ ion bombardment, and self-limiting etching regime of the ALE of GaN were first investigated. An etch per cycle of 0.50 nm/cycle averaged over 100 cycles was reached for GaN ALE. The self-limiting regime was also obtained for both SF6 and argon plasma steps. Moreover, a synergy rate as high as 78% was achieved. It was found that the GaFx-modified layer can be selectively sputtered by applying a self-bias voltage while the argon ion energy is maintained below the sputtering threshold of GaN.

Two hydrogen-bonded azo-macrocycles with little disparity of the side chains in steric hindrance exhibited a substantial difference in complexation (slow/fast exchange) towards bipyridinium. Inspired by this finding, these macrocycles were applied to efficiently and selectively construct [2]- and [3]rotaxanes through one-pot synthesis. The origin of the selectivity in this novel approach was elucidated by comparing single crystal structures, DFT calculations and stepwise synthesis.

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Several unique chiral 3,4-dihydro-2H-pyrrole-2-thiones were made readily available by carrying out, in each case, a chiral-Mg(OTf)2/N,N′-dioxide-complex-promoted formal [2+1+2] cycloaddition in the presence of tetraethylenediamine. Control experiments revealed that in situ-generated ammonium thiocyanate was crucial for maintaining high enantioselectivity through its inhibition of the HNCS-induced racemization of the products.

Rib spalling disaster at the coal mining faces severely restricted the safe and efficient output of coal resources. In order to solve this problem, based on the analysis of the current status of rib spalling in the three-soft coal seam 1508 Working Face of Heyang Coal Mine, a mechanical model of sliding-type rib spalling was established and the main influencing factors that affect rib spalling are given. The mechanism of grouting technology to prevent and control rib spalling has been theoretically analyzed. A similarity simulation experiment is used to analyze the change law of roof stress under the condition of three-soft coal seam mining. The optimal grouting pressure is determined by a numerical simulation experiment. And, silicate-modified polymer grouting reinforcement materials (SMPGMs) are used in field experiments. After twice grouting operations in the 1508 Working Face, the coal wall was changed from the original soft and extremely easy rib spalling to a straight coal wall and the amount of rib spalling has been reduced by 57.45% and 48.43, respectively. And, the mining height has increased by 0.16 m and 0.23 m, respectively. The experimental results show that the rib spalling disaster of the three-soft coal seam has been effectively controlled.

With the rapid development of unmanned aerial vehicle (UAV) technology and the drastic growth of multi-UAV collaborative applications, research on UAV Ad-Hoc Network (UAVNET) has received extensive attention in recent years. Due to the decentralization nature and being prone to failure and high dynamics, the performance of traditional contention-based carrier sense multiple access (CSMA) protocols and variants is far from satisfaction for UAVNETs. In this paper, we propose an intelligent access mechanism based on actor-critic (AC) algorithm, called AC-CSMA, with aim of achieving low access collision rate and high throughput for UAVNETs in dynamic environments. The UAVs are modeled as decision-making agents without priori information about the network (e.g., the number of nodes, link conditions, and other agents’ strategies). Individual UAV agents learn their optimal strategy by using the historical sensory information including the number of collisions or successful transmissions. Numerical results show that the proposed AC-CSMA mechanism significantly outperforms traditional access mechanism in terms of collision rate and throughput for UAVNETs without compromising access fairness.

In the inclination direction, the fracture law of a longwall face roof is very important for roadway control. Based on the W1123 working face mining of Kuangou coal mine, the roof structure, stress and energy characteristics of W1123 were studied by using mechanical analysis, model testing and engineering practice. The results show that when the width of W1123 is less than 162 m, the roof forms a rock beam structure in the inclined direction, the floor pressure is lower, the energy and frequency of microseismic (MS) events are at a low level, and the stability of the section coal pillar is better. When the width of W1123 increases to 172 m, the roof breaks along the inclined direction, forming a double-hinged structure, the floor pressure is increased, and the frequency and energy of MS events also increases. The roof gathers elastic energy release, and combined with the MS energy release speed it can be considered that the stability of the section coal pillar is better. As the width of W1123 increases to 184 m, the roof in the inclined direction breaks again, forming a multi-hinged stress arch structure, and the floor pressure increases again. MS high-energy events occur frequently, and are not conducive to the stability of the section coal pillar. Finally, through engineering practice we verified the stability of the section coal pillar when the width of W1123 was 172 m, which provides a basis for determining the width of the working face and section coal pillar under similar conditions.

The automatic classification technology of remote sensing images is the key technology to extract the rich geo-information in remote sensing images and to monitor the dynamic changes of land use and ecological environment. Remote sensing images have the characteristics of large amount of information and many dimensions. Therefore, how to classify and extract the information in remote sensing images has become a crucial issue in the field of remote sensing science. With the development of neural network theory, many scholars have carried out research on the application of neural network models in remote sensing image classification. However, there are still some problems to be solved in artificial neural network methods. In this study, considering the problem of large-scale land classification for medium resolution and multi-spectral remote sensing imagery, an improved machine learning algorithm based on extreme learning machine for remote sensing classification has been developed via regularization theory. The improved algorithm is more suitable for the application of post-classification change monitoring of features in large scale imaging. In this study, our main job is to evaluate the performance of ELM with A-optimal design regularization (here we call it simply as A-optimal RELM). So the accuracy and efficiency of A-optimal RELM algorithm for remote sensing imagery classification, as well as the algorithms of support vector machine (SVM) and original ELM are compared in the experiments. The experimental results show that A-optimal RELM performs the best on all three different images with overall accuracy of 97.27% and 95.03% respectively. Besides, the A-optimal RELM performs better on the details of distinguish similar and confusing terrestrial object pixels.

Remote Sensing (RS) and Geography Information System (GIS) technologies are widely used in ecological analysis and regional planning. With the advantages of large scale monitoring, combination of point and area, multiple time-phases and repeated observation, they are suitable for monitoring and analysis of environmental information in a large range. In this study, support vector machine (SVM) classification algorithm is used to monitor the land use and land cover change (LUCC), and then to perform the ecological evaluation for Chaohu lake tourism area quantitatively. The automatic classification and the quantitative spatial-temporal analysis for the Chaohu Lake basin are realized by the analysis of multi-temporal and multispectral satellite images, DEM data and slope information data. Furthermore, the ecological buffer zone analysis is also studied to set up the buffer width for each catchment area surrounding Chaohu Lake. The results of LUCC monitoring from 1992 to 2015 has shown obvious affections by human activities. Since the construction of the Chaohu Lake basin is in the crucial stage of the rapid development of urbanization, the application of RS and GIS technique can effectively provide scientific basis for land use planning, ecological management, environmental protection and tourism resources development in the Chaohu Lake Basin.

We study the behavior of the commensurate-incommensurate (CI) transitions by using a phase field crystal model. The model is capable of modeling both elastic and plastic deformation and can simulate the evolution of the microstructure of the material at the atomic scale and the diffusive time scale, such as for adsorbed monolayer. Specifically, we study the behavior of the CI transitions as a function of lattice mismatch and the amplitude of substrate pinning potential. The behavior of CI phase transitions is revealed with the increase of the amplitude of pinning potential in some certain lattice mismatches. We find that for the negative lattice mismatch absorbed monolayer undergoes division, reorganization and displacement as increasing the amplitude of substrate pinning potential. In addition, for the positive mismatch absorbed monolayer undergoes a progress of phase transformation after a complete grain is split. Our results accord with simulations for atomic models of absorbed monolayer on a substrate surface.

Non-point source (NPS) pollution has greatly threatened socio-economic development and human health due to water environment degradation. It is very important to quantitatively analyze spatio-temporal variation rules of NPS pollution sources surrounding drinking water source area (DWSA) and their impact on the water environment with time-series satellite images. In this paper, we study a systematic remote sensing monitoring method on DWSA of upper Huangpu River, Shanghai. Firstly, an optimized Extreme Learning Machine (ELM) classification algorithm, namely Mixed Kernel ELM with Particle Swarm Optimization (PSO-MK-ELM) was constructed. Based on the PSO-MK-ELM, four NPS pollution sources- farmland, building land, woodland, and water were identified accurately and efficiently. Then their corresponding spatiotemporal analysis was performed with 30 years (1989–2019) Landsat images. On the basis of NPS pollution source area and census data from 1989 to 2017, the principal pollutants discharged into DWSA were also calculated with the common Export Coefficient Model (ECM). Finally, the contributions of the spatial and temporal changes of NPS pollution sources on pollutant emissions were analyzed. The result indicates the PSO-MK-ELM has an advantage of efficiency and accuracy in NPS pollution source extraction and our results are expected to provide a scientific basis and data support for NPS pollution control and DWSA protection for better practices for environmental management in megacities worldwide.

Human settlements are guided by the proximity or availability of a natural resource such as river or lake basins containing set of streams. The harmonious development of human activity and natural conditions along watershed areas needs close attention and in-depth study. In this paper, the urban agglomerations and ecological spaces in the Yangtze River Delta, China, the Chao Lake Basin and its surrounding watershed ecosystem is taken as research subject for its serious environmental degradation problems during social and economic development. This paper adopted an effective machine learning algorithm (kernel-ELM) to extract land use and land /cover information, and to analyze the land use/cover pattern evolution rules of the Chao Lake Basin with long term Landsat imagery. Subsequent studies were then carried out to demonstrate the flood-affected area and its ecological impact in the basin in 2020, to reveal the occupation on land cover types. The results indicate Conclusions are drawn from the experiment results: (1) There has been significant change in cultivated land, forest land and construction land out of six key land cover types with dynamic degree of −10.17%, 4.61, 67.04% respectively. (2) Algae bloom pollution was extracted from pattern classification results and it was up to 15% of the total water area by the year 2018. (3) The occupation on land use/cover types of the flood was revealed. The results prove effective application of remote sensing technology in environmental analysis and planning for data-driven evaluation of governing policy. This work serves as a scientific basis for environmental management and regional planning in the Chao Lake Basin and can be served as a basis and a reference for evaluating an ecological policy and its impact for other economic developing watershed human settlements with ecological issues.

Aiming at the serious problems caused by coal mine mining activities causing the rock burst accidents, this paper is based on rock mechanics and material mechanics to establish the key layer breaking by the double-key layer beam breaking structural mechanics model of a single working face and double working face under repeated mining. The theoretical calculation formula of the angle was used as the theoretical basis for the elevation angle of the pre-reloading hole of the hard roof. The rationality and reliability of the formula were verified by the physical similarity simulation experiment and the 3 Dimension Distinct Element Code numerical simulation experiment, revealing the rock formation under the influence of repeated mining. The results show that the derived key layer breaking angle formula is suitable for the theoretical calculation of the breaking angle of the key layer of a single coal seam when the repeated disturbance coefficient is λ = 1; when it is λ = 2, it is suitable for the repeated mining of the short-distance double-coal mining. The rationality and reliability of the theoretical formula of the breaking angle of the double key layer of single coal seam and double coal seam were verified by the physical similarity simulation experiment. Through the 3DEC numerical simulation results and theoretical calculation results, the W1123 working face hard top pre-cracking pressure relief drilling elevation angle was 78°. The drilling peeping method was used to verify the results. The results show that the theoretical formula of the critical layer breaking angle is well applied in engineering practice.

The Li3V2(PO4)3/C cathode materials for lithium-ion batteries are synthesized by sol–gel method using three different compounds (citric acid, glycine and oxalic acid) as the chelating agents. The effects of chelating agents on the physical properties and electrochemical performances of the Li3V2(PO4)3/C composites are investigated by thermogravimetric analysis, infrared spectrometry, X-ray diffraction, scanning electron microscope and various electrochemical techniques. The results show the electrochemical properties of Li3V2(PO4)3/C prepared using citric acid as chelating agent are better. In the voltage range of 3.0–4.3 V (vs. Li+/Li), the citric acid chelated Li3V2(PO4)3 displays large reversible capacity with an initial discharge capacity of 126.7 mAh g−1 at 0.5 C, and 91.3% of the initial discharge capacity is retained after 50 charge–discharge cycles.

The spatiotemporal changes of lake water resources objectively reflect not only the process of the water resources balance, but also the ecological environment changes in the lake area. In recent decades, climate changes and human activities have caused great impacts on the spatial distribution of the earth’s water resources and the spatiotemporal process of the surface water cycle, which has caused a series of ecological crises and environmental problems, such as the drying-up of inland lakes, the disappearance of the oasis, water shortage or flooding and water pollution. Therefore, monitoring and fully understanding the dynamic changes of lakes is of great scientific significance for grasping regional water balance, water resources management, and sustainable development of the ecological environment. In this study, we focus on using multi-source satellite data on the estimation of water volume and multi-timescale variations analysis for large scale lakes. This study combines the problems in the practical application of “African Water Action”, taking the largest lake in Africa, Lake Victoria, as the study area, and utilizes long-term serial multi-source satellite data of the past 15 years (2003–2017), including Moderate-resolution Imaging Spectroradiometer (MODIS), Jason-1/-2/-3 and Gravity Recovery and Climate Experiment (GRACE) to perform the comprehensive analysis on the water volume change estimation. Firstly, the satellite altimetry data of Jason-1/-2/-3 and MODIS imagery was used to calculate series of water level, and to extract series of water surface area, respectively. On this basis, a more accurate regression model between the area and water level variation (ΔH) was constructed. Then, the model between water volume variation (ΔV) and ΔH, derived from area-ΔH model, was applied to calculate the relative water volume of Lake Victoria. Meanwhile, terrestrial water storage (TWS) changes between 2003 and 2016, derived from GRACE data, were also used for a comparative verification of the ΔV results. The results show the long-term series change trends of ΔV and the TWS are the same. Finally, the multi-timescale analysis of water volume changes was carried out on different time scales, such as the inter-annual, inter-monthly, and variation period.

The stabilization of magnetic domains and their temporal evolution in FeGa alloys are predicted by combining micromagnetic model with phase-field method in this paper. The total free energy includes magnetocrystalline anisotropy energy, exchange energy, magnetostatic energy, external field energy and elastic energy. Under the diverse magnetic fields, domain structures are various because of the different total free energy and magnetization processes. The results show that when magnetic field direction along [1 0 0], with different magnetic strength, the directions of magnetization vectors all parallel to the magnetic field direction and the magnetized area forms a single domain structure eventually. When the magnetic field along [1 1 1] direction, the magnetic domains form striped domains. The direction and strength of magnetic field can effectively control the structures of magnetic domains. The total free energy increases with the increase of magnetic field strength and evolutionary steps. The system is stable with the stabilization of total free energy.

Tungsten–copper (W–Cu) composites containing 10 wt.% Cu (W–10Cu) were prepared by pressing and sintering a type of ultrafine composite powder. Constituent phases, grain size and orientation relationship between W and Cu grains were characterized and investigated. The results show that W–10Cu composites are composed of W and Cu elementary substance and orientation relationship between W and Cu grains is defined as 1 ¯ 1 ¯ 4 Cu / / 0 1 ¯ 1 W and (131)Cu//(200)W. The existence of the orientation relationship depends largely on the two factors. First, the grain sizes of both W and Cu were in the nanoscale range. Secondly, the interplanar spacing between both phases can match well owing to the residual stress of the W/Cu interface. Consequently, the obtained composites exhibited high density and excellent thermal conductivity.

Determination of sequence similarity is one of the major steps in computational phylogenetic studies. One of the major tasks of computational biologists is to develop novel mathematical descriptors for similarity analysis. DNA clustering is an important technology that automatically identifies inherent relationships among large-scale DNA sequences. The comparison between the DNA sequences of different species helps determine phylogenetic relationships among species. Alignment-free approaches have continuously gained interest in various sequence analysis applications such as phylogenetic inference and metagenomic classification/clustering, particularly for large-scale sequence datasets. Here, we construct a novel and simple mathematical descriptor based on the characterization of cis sequence complex DNA networks. This new approach is based on a code of three cis nucleotides in a gene that could code for an amino acid. In particular, for each DNA sequence, we will set up a cis sequence complex network that will be used to develop a characterization vector for the analysis of mitochondrial DNA sequence phylogenetic relationships among nine species. The resulting phylogenetic relationships among the nine species were determined to be in agreement with the actual situation.

Microsoft Kinect is a new and robust 3D camera, which can be used for indoor scene and 3D model reconstruction. It contains an infrared projector, an infrared camera and a RGB camera, color and depth map can be captured in one scene at the same time and run at a speed of 30 frames per second. As a handhold device, Kinect is low-cost and portable compared with lidar, but its accuracy is low. The internal parameters of both infrared camera and RGB camera, as well as their relative pose, are pre-calibrated in factory, however these average values can't meet the need of high-precision applications and parameters vary from device to device. So if we want to improve the precision of Kinect, the calibration should be done at first. In this article, we attempt to use indoor control field to calibrate Kinect sensor, and get the accurate internal parameters of both cameras and their relative pose. Different from some compute vision methods, the 3d coordinate of control points should be measured in our coordinated system and one image is enough fine to compute the internal and external parameters. As Kinect can't get the IR stream and color stream simultaneously, we get the depth and color image at first, then cover the infrared projector and get the IR image, while an infrared compensation lamp is used to make the IR map clear. We separately detect the control points in the color and IR image for getting their corresponding image points, then gain their distance values from depth image based-on IR image points. Our algorithm contains four steps: 1) Initializing the internal parameters of infrared camera and RGB camera with Zhang's method. For RGB camera, collinearity equation is applied to establish the relationship between control points and their RGB image points, then estimating external parameters and refining internal parameters based-on least square adjustment. For infrared camera, transform IR image points to Kinect 3D coordinate with their distance value and initialized internal parameters to establish the point-to-point correspondence with control points, then calculate external parameters and refining internal parameters using iterative closest points method. Furthermore, we assume a model to improve the precision of distance value, in which three additional parameters should be estimated. 2)Projecting the control points to IR and RGB image coordinate separately which consider as ideal points, and regard the corresponding image points as real points, we can estimate the distortion parameters of infrared and RGB camera. 3) Iterating 1)2) steps until it is convergence. 4) Using the external parameters of both cameras to calculate their relative pose. In our experiment, 36 control points are measured, part of them (about 20) can be seen in one image. We usually use 15 points of them to estimate parameters and others consider as check points. The results show that our method can get high precision calibration parameters which projection mean square error lower than 0.5 pixels, and the mean square error of transforming depth image points to RGB image points lower than 1.0 pixels.