Soil cadmium (Cd) pollution is a worldwide environmental issue. Biochar which is commonly reported to reduce soil available Cd (SA-Cd) and Cd uptake by plants (Cd-UP) has become one of the hot topics in bioremediation field. In this paper, effects of biochar, including feedstock materials, application rates, production conditions (time, temperature and pH) as well as the target soil characteristics on SA-Cd and Cd-UP were analyzedby using the meta-analysis based on 84 related papers. The results showed that the application of biochar significantly (P<0.05) decreased the concentration of SA-Cd in loamy and clayey soils by 33.06% and 17.00%, respectively, while the effects were not significant (P>0.05) in sandy soils. The effects of biochar on SA-Cd and Cd-UP were more significant in weakly acidic soils (5.5<pH≤6.5) compared with other soils, resulting in decreases of the SA-Cd concentration by 36.72%. Biochar application leaded to decreases of the SA-Cd concentration and Cd-UP by 23.18% and 40.01%, respectively. Domestic residue-derived biochar was regarded as the most suitable biochar, which decreased the SA-Cd concentration and Cd-UP by 36.04% and 53.17%, respectively. The biochar produced with the pyrolysis temperature higher than 600 ℃ and the residence time ≥3.5 h had the most efficient decrease of the SA-Cd concentration and Cd-UP by 45.10% and 50.26%, and 25.13% and 56.54%, respectively. Biochar with pH values between 9 and 10 was more effective on the decrease of the SA-Cd concentration and Cd-UP, and the suitable biochar application rate was abut 3%. Biochar application can effectively reduce the SA-Cd concentrations and Cd-UP, which provides useful guidelines for the selection and application of biochar in Cd contaminated soil-plant system.

Energy consumption and environmental pollution made biodiesel production from microalgae a hot spot. Comprehensive utilization of microalgae by simultaneously extracting carotenoid and oil, can effectively reduce the production cost of microalgae biodiesel. Although carotenoids are important active substances, little has been known about carotenoid biosynthesis and its metabolic regulation in microalgae so far. In order to better understand and manipulate carotenoid metabolism for enhancement of carotenoid production in microalgae, presented an overview of research advances on carotenoid biosynthesis and its metabolic regulation in microalgae were presented, including carotenoid biosynthesis pathway, strategies for improving carotenoid accumulation (biochemical regulation, mutagenesis and genetic engineering strategy). Effects of environmental factors on carotenoid accumulation were illustrated. Two genetic engineering strategies were summarized, including enhancement of expression of key enzyme genes in carotenoid biosynthesis pathway, enhancement of expression of transcription factor genes related to regulation of carotenoid biosynthesis pathway. The prospect of research on carotenoid metabolism was also discussed in microalgae.

Under the COVID-19 epidemic situation, the volume of road freight has declined significantly, and road operations have changed complexly. It is urgent to scientifically predict the volume of road freight. Through gray correlation analysis, the main factors affecting road freight volume during the epidemic period are determined, and a road freight volume forecast method based on the gray combination (GC)-revised BP neural network (rBPNN) model is constructed. The BP neural network is trained and tested based on the statistical data of China’s road freight volume from July 2017 to May 2020 as the original data, and the “correction coefficient” H_M is introduced to modify the predicting result. Based on the data of the past five months during the epidemic, the gray combined model is used to predict the value of the main factors affecting the road freight volume in the next month, and the BP neural network is used to predict China’s road freight volume in June 2020. Compared the GC-rBPNN model with other prediction methods, the PE and MAPE of the GC-rBPNN model are 0.21% and 3.21%, respectively. The results show that the prediction accuracy of the GC-rBPNN model is higher, and the method has certain feasibility and effectiveness.

Stochastic Model (SM) is a typical profiling attack where in building template, the covariance matrix may become singular and cause exponentiation calculation, which is identical to traditional Template Attacks (TA). In addition, the reference device is fully controlled to set up random plaintexts and keys for many times, and captured power consumption data are used to build templates, which limits the usage of SM and traditional TA. In order to solve these problems, stochastic attack based on Mahalanobis distance is proposed in this paper. By studying the techniques of TA, the template is built on reference device where random plaintexts and fixed keys are used as the input, and Mahalanobis distance (statistical tool) is applied to SM to recover keys. The proposed algorithm is used to attack AES which is implemented on Atmel XMEGA128D4 microcontroller. Attack results indicate that the proposed attack method can verify that fixed or random keys have identical distribution of AES sensitive intermediate values when template is built, which can be used to restore the correct keys. Compared with CPA and traditional TA, the correct key can be recovered by the proposed attack algorithm with less power traces, and 100% of success rate can be reached with about 50 traces. The analyzing efficiency of hardware cryptosystem can be improved.

Contact angle is an important characteristic quantity to measure the wetting of liquid on solid surface. Although many methods can be used to simulate the contact angle phenomenon and measure the contact angle, there is still no simple method for measuring the contact angle on a curved surface. Based on the chemical potential lattice Boltzmann method, this paper proposes a method to measure the contact angle of droplets on curved surfaces. A series of chemical potentials are set for the curved substrate to calculate the contact angle of a fixed drop on the curved surface to observe the wettability under different chemical potentials. Under the ideal condition without considering the gravity, compared with the calculation result of the spherical cap method, the contact angle obtained by the new method has a maximum error of about 3 degrees, which is in good agreement. When the influence of gravity is considered, the droplet of different sizes undergo different deformation, and the spherical cap method is no longer applicable, but the contact angle obtained by the model in this paper is basically unchanged, which is consistent with the theoretical expectation that the microscopic contact angle and gravity are independent.

Most of the sweeping robots have the problems of high repetition rate and low coverage rate. When planning the full coverage path and encountering dense and scattered obstacle areas, the route planning is messy and even can’t be covered. Therefore, this paper designs a full coverage path planning algorithm based on divide and conquer idea. By constructing a number of line segments on the map, the local path segments are connected according to the principle of minimum Manhattan distance between the endpoints of line segments to form a number of arcuate circuit blocks. Then, divide and conquer algorithm is used to realize the global matching of the nearest end points of each bow block and connect them. A full coverage route with uniform path is generated. Compared with the cow tillage unit decomposition combined with bio inspired neural network coverage algorithm, the analysis shows that in the dense and scattered obstacle areas, the algorithm can plan a neat and smooth passable path, the coverage rate can reach 91.3%, the repetition rate is reduced by 39.3%, and the time cost is reduced by 28.1%.

Aiming at the problem of low task completion caused by task completion time constraints in the scenario where tasks are randomly assigned, a distributed and dynamic multi-UAV task allocation method based on deep reinforcement learning is proposed. The method uses the interaction between UAVs to quantify the time constraints, task size, task priority and other characteristics of the tasks being performed and new tasks in real time. At the same time, new task priority features are generated dynamically during task execution. Then, the task features after UAV interaction are regarded as the global task shared by UAV, and constantly updated to form a dynamic decision-making basis. Finally, according to the real-time task completion and the time constraints, the behavioral decision-making of the UAV is made based on the deep reinforcement learning, so as to improve the task completion by achieving the dynamic allocation of new tasks and ongoing tasks. This behavioral decision is to realize the dynamic assignment of tasks to improve the task completion. Simulation results show that this method can improve the overall task completion of the system under time constraints.

A new color image encryption algorithm based on a coupled chaotic map is presented. Firstly, the initial secret keys are produced by combining the information which is extracted from plain image and external keys. Secondly, the color image is decomposed into three components of R, G, and B, and three one-dimensional sequences are obtained at the same time. The elements in each sequence are grouped and scrambled. Then, three index sequences are constructed by using the pseudo-random sequences generated by the chaotic map, and the three components of R, G, and B are sequentially scrambled by using the index sequences again; the final cipher image is obtained according to xor operation. Experimental results and security analysis prove that the encryption scheme has a good encryption effect as it can resist common cryptanalysis attacks, such as statistical analysis attack, differential attack, cropping attack and noise attack, etc. In addition, compared with other literatures, the results show that the cipher image information entropy obtained by this scheme is closer to the ideal value of 8, the correlation coefficient is closer to 0, and the encryption efficiency is higher than other schemes.

Web Services is an application based on the Web environment with self-adaptation, self-description, modularization, and interoperability. These features make it extremely reusable. Software reuse is a promising method to reduce software development costs. The automatic classification of Web services plays a vital role in software reuse. In recent years, machine learning techniques are widely used in service classification and have achieved some results. But the performance of traditional machine learning methods highly depends on the quality of feature engineering. This paper proposes a Bert DPCNN deep neural network model, which is based on the combination of Bert pre-training model and DPCNN deep pyramid convolutional neural network. This model can automatically extract low-level representations of service descriptions and abstract them into high-level features without feature engineering. In order to demonstrate the effectiveness of the proposed method, a comprehensive comparison is made with the traditional machine learning method and some deep neural network models on the datasets of 50 categories and 10 184 real Web services. The results show that the proposed model has higher accuracy rate than the other methods.

In this paper, conditional quantiles are used to study the feature screening problem of ultra-high dimensional data when response variables are randomly censored and nonrandomly censored, respeclively. Then, a corresponding feature screening method is proposed. Through theoretical and simulation study, it is verified that the variable set created by this method satisfies the sure screening and ranking consistency properties. Compared with the existing methods, this method has some advantages when covariates and censored variables are correlative.

The crossing numbers of a graph is a vital parameter. Garey and Johnson showed that the problem of determining the crossing numbers of an arbitrary graph is NP-complete. Because of its difficultly, the classes of graphs whose crossing numbers have been determined are very scarce at present. Based on the result of the crossing number of complete bipartite graph cr(K₆,n)=Z(6,n) given by Kleitman, in this paper, for a 6-vertex graph H, it is shown that the crossing numbers of its join with n isolated vertices as well as the path P_n on n vertices and with the cycle C_n are $c r\left(H+n K_{1}\right)=Z(6, n)+2\left\lfloor\frac{n}{2}\right\rfloor$, $c r\left(H+P_{n}\right)=Z(6, n)+2\left\lfloor\frac{n}{2}\right\rfloor$, and $c r\left(H+C_{n}\right)=Z(6, n)+2\left\lfloor\frac{n}{2}\right\rfloor$.

Generalized Howell design is a kind of double resolvable designs, which are closely related to permutation arrays and multiply constant-weight codes. By making full use of the direct construction method of transitive starter-adder, intransitive starter-adder and generalized Howell frames as recursive tool, some new constructions for generalized Howell designs are given in this paper. The problem of existence of the generalized Howell design GHD(n+5,3n)s with exactly 5 empty cells in each row and column is solved with 53 possible exceptions. Then, the existence of the corresponding optimal multiply constant-weight codes MCWC(3,3n;1,n+5;1,n+5;8) is given by using the relationship between the generalized Howell designs and the multiply constant-weight codes.

The electronic and optical properties of Li-doped Janus MoSSe monolayer were investigated based on first-principles calculations. The calculations showed that the binding energy values after Li doped were all negative values, indicating that energy is released during the doping process, and the Li-doped Janus MoSSe system was stable. The electronic structure analysis showed that there were impurity levels introduced into the forbidden band gap of Janus MoSSe. Therefore, the material changed from a direct band gap semiconductor to an indirect band gap semiconductor, and the band gap decreased accordingly. When the doping concentration reached 6.25%, the band gap reduced more, showing a better modulation effect for the electronic structure. The study of optical properties showed that the doping of Li can change the absorption coefficient and static dielectric constant ε(0) of the material. Li substitution doping increased the light absorption intensity, and enhanced its visible light absorption intensity. The results indicated that the Li doped Janus MoSSe has potential applications in solar energy harvesting or photocatalysis.

In order to find out the influence of the hybridization of Fe and P atoms on the stability of Fe₄P clusters and the relationship between the polarizability and the stability of the optimized configurations, according to the density functional theory and the principle of topology, a total of 16 initial configurations of Fe₄P in binary and quadruple states are designed under B3LYP/lanl2dz high quantum chemistry level chemical configuration. The polarizability and density of states of eight configurations are studied, and the following conclusions are drawn: configuration 5⁽⁴⁾ has the largest anisotropy invariant, which has the strongest response to the external field and is easily affected by the external field; configuration 2⁽²⁾ has the largest polarizability and the largest degree of deformation; configuration 2⁽⁴⁾ has the smallest value of polarizability, which is the least prone to deformation, and it also shows that the multiplicity will affect the polarizability of the response configuration to a certain extent. There are five main hybridization modes of Fe—P bond, which are p-p, p-d, p-p-d, p-d-d and s-s-p-p, and the p-d and p-p-d hybridizations play an important role in promoting the stability of Fe—P bond in cluster Fe₄P.

In the peripheral blood leukocyte separation experiment, the red blood cells of tumor-bearing male mice with Lewis cancer cell (Lewis lung carcinoma, LLC) did not sink to the bottom but were stagnated in the middle layer,which was different from that of normal mice. To explore the further function of the Sdr9c7 gene and the possible mechanism of erythrocyte abnormality in tumor-bearing male mice, the expression of the Sdr9c7 gene was detected by real-time fluorescence quantitative PCR in red blood cells and lymphocyte isolated from the peripheral blood, and some tissues such as skin, liver, bone marrow, and blood vessels. Compared with the control group, the expression level of the Sdr9c7 gene in erythrocytes of tumor-bearing mice increased significantly, which was 2.60±0.44 times as that of normal mice. Although its expression showed no significant difference in skin and blood vessels, its expression in blood, bone marrow, liver, and lymphocyte of tumor-bearing mice were significantly down-regulated, which was 0.31±0.05, 0.44±0.04, 0.36±0.04 and 0.35±0.08 times as that of normal mice separately. The results suggested that the occurrence of erythrocyte abnormality in tumor-bearing mice might be related to the increased of Sdr9c7 gene expression. This result broadens the horizon for further study of the biological function of Sdr9c7 gene and provides a new perspective for the mechanism of erythrocyte abnormalities in the tumor-bearing state.

Pomaea canaliculata, as one of the invasive species in China, has caused serious harm to the agriculture and ecological environment of many provinces in China. In this paper, the antibacterial peptides from the viscera of P. canaliculata were prepared by enzyme method to investigate the resistance of P. canaliculata to environmental microorganisms during invasion. The inhibition of antimicrobial peptides from the viscera of P. canaliculata on Escherichia coli BL21, E.coli DH5α, Vibrio parahaemolyticus and Aeromonas hydrophila were determined by filter paper diffusion method. The results showed that the antibacterial peptides from the visceral of P. canaliculata prepared by trypsin and pepsin had significant inhibitory effects on the four strains. In this study, the result showed that the optimal enzymolysis time of trypsin for E. coli BL21, E. coli DH5α, V. parahaemolyticus and A. hydrophila was all determined to be 4 h. The optimal enzymolysis time of pepsin was determinded to be 4 h for E. coli DH5α and 6 h for E. coli BL21, V. parahaemolyticus and A. hydrophila. This study lays the foundation for further isolation, purification of the crude extract with antibacterial activity from the viscera of P. canaliculata.

To understand the niche characteristics of the main woody plant populations in the Cyclobalanopsis glauca community in Lingqu basin, quantitative analysis was carried for the niche of the main species in the arbor layer and shrub layer of the C. glauca community by using the niche breadth of Levins and Shannon-Wiener, the niche overlap of pianka and the niche proportional similarity of Schoener. The results showed that:1) The species with larger importance values generally had larger niche breadth,but the rank orders of which were not exactly the same. 2)C. glauca and Pistacia weinmannifolia in the arbor layer, Alchornea trewioides and Loropetalum chinense in the shrub layer had higher niche breadth than other species. 3)In the C. glauca community, the niche overlap and niche proportional similarity of the main plant populations were concentrated at a low level, (niche overlap values: 0.1-0.4 for arbor layer species, 0-0.2 for shrub layer species; niche proportional similarity value: 0.2-0.5 for arbor layer species, 0-0.4 for shrub layer species), which indicated that the similarity degree of species’ utilization of environmental resources was not high. 4)There was no significant correlation between niche breadth and niche overlap, when the niche breadth of species was large but the niche overlap was not necessarily high, and when the niche breadth was small, the niche overlap was not necessarily low. 5) The niche proportional similarity of species with large niche overlap value was also large. The C. glauca community belongs to the top zone community. The competition among species is not fierce and the inter specific relationship is harmonious, but the species regeneration is slow and demonstrates a declining trend.

To study the spatial and temporal dynamics of soil carbon pool is one of the important parts of the research on the distribution pattern of forest soil organic carbon along the altitude gradient in the climate transition zone. In order to study the distribution characteristics of typical forest soil organic carbon in the northern subtropical and warm-temperate climate transition zone, 10 sampling points were set up at five different altitudes on the south and north slopes of Guifeng Mountain in easternHubei province with a height difference of 100 meters. Soil samples were collected stratified[0,20)、[20,30)、[30,40) and [40,50)(cm) to measure SOC content and soil physical and chemical properties, and to study the distribution characteristics and influencing factors of SOC. The results indicated that: (1) the surface soil organic carbon content and organic carbon density showed a strong regularity along the altitude gradient, that is, the soil organic carbon content and organic carbon density increased significantly with the elevation (P< 0.01). (2) SOC decreased with the increase of soil depth, but the decreasing amplitude of SOC was different at different soil depth at different altitudes. (3) Correlation analysis showed that there was a significant correlation between soil organic carbon content and soil bulk density and gravel content. The study has an important reference value for the evaluation of soil organic carbon storage and its change characteristics in the northern subtropical mountainous region.

Based on the historical literature from 1650 to 1911 in Qing Dynasty, this paper evaluates the drought and waterlogging disasters in the three provinces of Northeast China, and analyzes the mutagenicity characteristics of drought and waterlogging time series by means of sliding average and cumulative anomaly method. Ensemble empirical mode decomposition (EEMD) was used to study the periodic characteristics of drought and flood disasters in the three provinces of Northeast China in the Qing Dynasty. By analyzing the rate and frequency of drought and flood disasters, using the inverse distance weight (IDW) method and calculating the average annual drought and flood disaster ratio of the three provinces of Northeast China, the spatial distribution of drought and flood disasters in the three provinces of Northeast China in the Qing Dynasty were studied. The results showed that the number of droughts and floods in the three northeastern provinces in the Qing Dynasty was less and alternating, and the number of floods was more than that of droughts. The periodic characteristics of drought and flood disasters of the three provinces of Northeast China in the Qing Dynasty can be roughly divided into two drought periods and two flood periods. The changes in drought and flood disasters were quasi 3 a, quasi 7 a interannual cycle, quasi 22 a, quasi 29 a interdecadal cycle, and quasi 87 a in the cycle. In the Qing Dynasty, the spatial distribution of drought and flood disasters in the three provinces of Northeast China was uneven. The frequency of drought and flood disasters increased from north to south and was mainly concentrated in Liaoning Province.