Search

Intelligent plant cultivation robots play a vital role in plant intelligent cultivation. Aiming at the problem of low accuracy and low efficiency of intelligent plant cultivation robots in searching for target plants in unknown environments, this paper proposes an intelligent plant cultivation robot based on key marker algorithm and improved A* algorithm. In terms of target plant positioning, a key marker algorithm based on YOLOV5 is proposed. Accurately find the target plant in the location environment, mark the key coordinate location of the target plant, and plan the routes. In terms of route planning, the self-node search strategy for the traditional A* algorithm has disadvantages such as many path turning points and large turning angles. By ant colony algorithm and A* algorithm, this paper proposes an improved A* algorithm and combined with DEEPSORT algorithm and YOLOV5 algorithm, the variable path planning is carried out.

Introduction: At the end of 2019, the COVID-19 broke out, and spread to Guizhou province in January of 2020. Methodology: To acquire the epidemiologic characteristics of COVID-19 in Guizhou province, we collected data from 169 laboratory-confirmed COVID-19 related cases. We described the demographic characteristics of the cases and estimated the incubation period, serial interval and the effective reproduction number. We also presented two representative case studies in Guizhou province: Case Study 1 was an example of the asymptomatic carrier; while Case Study 2 was an example of a large and complex infection chain that involved four different regions, spanning three provinces and eight families. Results: Two peaks in the incidence distribution associated with COVID-19 in Guizhou province were related to the 6.04 days (95% CI: 5.00 – 7.10) of incubation period and 6.14±2.21 days of serial interval. We also discussed the effectiveness of the control measures based on the instantaneous effective reproduction number that was a constantly declining curve. Conclusions: As of February 2, 2020, the estimated effective reproduction number was below 1, and no new cases were reported since February 26. These showed that Guizhou Province had achieved significant progress in preventing the spread of the epidemic. The medical isolation of close contacts was consequential. Meanwhile, the asymptomatic carriers and the super-spreaders must be isolated in time, who would cause a widespread infection.

Hysteresis-based energy management strategy for microgrid containing photovoltaic, ESS and heating loads is proposed in this study. In this real-time optimisation method, economic cost, operation cost, comfort level, renewable energy penetration and other performance indices are optimised in real time. To solve the complex energy management problem, when power forecasting is unavailable, different operational cases are clarified and calculated accordingly. In this way, the management process is turned into a finite-solution problem. Furthermore, a hysteresis loop is also established based on the cost function to optimise the system continuously, of which the loop width is offline designed. As a result, the computation burden is reduced. Finally, simulation results are presented to verify the effectiveness of the proposed energy management method. The application of the proposed method can reduce the economic cost and improve the operational performances of a microgrid significantly, including comfort, power quality and health of ESS.

In this study, we carried out a series of physical experiments using a submersed flume model to investigate how sand/clay content influences the depositional mechanism of submarine debris flows. A three-dimensional biphasic numerical model, with a Herschel-Bulkley rheology, was used to back-analyze the physical experiments. The calibrated numerical model was then used in a back-calculation to investigate the effects of viscosity on the deposition process. The results show that as submarine debris flows mix with water during the deposition process, shear stress at the slurry-water interface generates a vortex that leads to a swirl-wedge front head. High-viscosity slurry flows with a swirl-wedge front head travel at a higher aspect ratio and with a greater radius of rotation. Hydroplaning was observed when the front head was lifted by water during flow. The lifting height increased with flow depth fluctuation. Higher viscosity slurry was found to lift more rapidly due to its larger vortex and the decrease in density at the front head over time, both of which promote fluctuation. Although a high-density slurry has a greater lifting height, the ratio of lifting height to front head height is lower, indicating a smaller lifting force influence. Lower density flows have higher kinetic energy as the transfer of potential energy into kinetic energy is more efficient. Kinetic energy dissipation comprises three stages: (1) gravity-dominated coherent flow and hydroplaning lead to a rapid increase in kinetic energy; (2) sharp reduction in kinetic energy as slurry mixes with water, coherence and hydroplaning are reduced, and the influence of the shear stress increases; (3) slurry mixed very well with water, turbidity current dominates the kinetic energy dissipation. High-density slurry dissipates quicker in the last two stages. In stage 3, which dominates the temporal evolution of the debris flow, the Froude number is lower than 1, the flow thins and elongates, and the deposition process of submarine debris flows is dominated by gravity, and the difference of morphology of the different cases become clear.

The integration of an Energy Storage System (ESS) is difficult to commercialize within the current Chinese market mainly because of the lacking of supporting policy and breakthrough technologies. However, it is considered an appropriate approach in a certain circumstance, for instance, in a remote rural area. This work presents a power-balanced ESS integration model and its control method. By using a rural distributed network in southern China, the results show that the proposed model is able to improve the three-phase power imbalance issue.

Land use activities mainly for economic and agricultural purposes have converted one third to one half of our planet's land surface into urban expansion and agricultural practice, which has had significant impacts on natural ecosystems, food production, and environmental quality, attracting the attention of researchers and policymakers. Consequently, land use is emerging as a fundamental issue in global environmental change and sustainable development. This study represents an addition to the prevailing literature by investigating the asymmetric impacts of land-use and land-cover changes on environmental quality in Pakistan using time series data from 1961 to 2016. Carbon dioxide (CO2) emissions were deemed a dependent variable (a proxy for environmental quality), whereas built-up land, cropland, water bodies, and grazing land were considered independent. A nonlinear ARDL bound testing technique (NARDL) was used to investigate dynamic cointegration among the study variables. Moreover, this study used the BDS test and structural break unit root test to confirm nonlinearity and stationarity of the data set. The results confirm that the variables exhibit asymmetrical co-integration. There is a symmetric unidirectional causation, running from built-up land and grazing land towards CO2 emissions with coefficients of 10.570 and 17.045, respectively. Furthermore, asymmetric causality shows that any positive shocks to built-up land (6.134) and water bodies (20.335) significantly cause CO2 emissions. Similarly, a negative shock to grazing land (16.470) also causes CO2 emissions. By contrast, a neutral effect was found between cropland and CO2 emissions.

What is already known on this topic? Brucellosis is a zoonotic infectious disease caused by Brucella spp. The main source of infection in human brucellosis is sick animals, mainly including sheep, goat, and cattle, but sika deer (Cervus nippon) can also cause human brucellosis. The first human brucellosis case in Guizhou Province was reported in 2009, and no brucellosis outbreak was reported caused by sika deer ever before. What is added by this report? This is the first reported outbreak of human brucellosis caused by sika deer in Guizhou Province. Inappropriate regulation of animal movement may be the main driver of introducing and spreading brucellosis in southern areas. The ability to diagnose brucellosis in both humans and animals was weak in the county where the outbreak took place. What are the implications for public health practice? It was suggested to prioritize occupational protection and health education for sika deer breeders. The inspection of the movement of animals and the reimbursement policy need to be improved.

Introduction: Coronavirus disease 2019 (COVID-19) has caused an outbreak around the world. Early detection of severe illness is crucial for patients’ survival. We analysed initial clinical characteristics of 146 patients with COVID-19 reported in Guizhou province, China to explore risk factors for transforming mild illness to severe. Methodology: Data of 146 laboratory-confirmed cases were collected and evaluated by the survival analysis of univariate and multivariate Cox proportional hazards model. Results: On initial presentation, patients had fever (51.05%), dry cough (45.45%), headache (16.08%), shortness of breath (7.75%) and gastrointestinal symptoms (13.99%). Among 146 laboratory-confirmed cases, 30 patients (20.55%) had severe illness and needed Intensive Care Unit care for supportive treatment. The remaining patients (116, 79.45%) were non-severe cases. Nineteen (19/146, 13.01%) of 30 patients in the Intensive Care Unit had comorbidities, including hypertension (12, 40.00%), diabetes (5, 16.67%), cardiovascular disease (5, 16.67%) and pulmonary disease (4, 13.33%). For survival analysis, patients who had fever (HR = 3.30, 95% CI = 1.31, 8.29) and comorbidities (HR = 9.76, 95% CI = 4.28, 22.23) at baseline were more likely to be admitted into the Intensive Care Unit. Few variables were not related to the survival time of discharge from baseline to discharge and from Intensive Care Unit care to discharge. Conclusions: Severe patients with COVID-19 should be paid more attention. On initial symptoms, many patients did not have fever, but those with fever were more likely to be admitted to the Intensive Care Unit. Comorbidities were likewise a risk factor of severe COVID-19.

The influence of forest fire on soil hydrology and mechanical effects promotes the occurrence of post-fire debris flow. However, the variation of soil properties with time has not been much studied. In order to determine the temporal variation characteristics of soil hydrology and mechanical effects after forest fires under different fire severities, and link them to the initiation of post-fire debris flows, a two-year continuous testing of samples from the source area of post-fire debris flows in Muli County, China, were investigated. Saturated direct shear test, saturated permeability experiment and scanning electron microscope experiments of undisturbed soil were carried out. The results showed that the burning of organic matter occurred, which reduced soil permeability sharply. In addition, high temperatures destroyed the structure of soil, causing the internal collapse of aggregates and reducing soil shear strength. While the herbaceous plants can quickly regenerate after fire, improving the hydrological and mechanical properties of soil, and reducing the frequency of post-fire debris flow. These results can evaluate the changes of soil physical and mechanical properties in short term after fire, and also explain the formation mechanism of post-fire debris flow.

Loose wide-grading soils are commonly found in the source areas of debris flows, and in landslides after an earthquake. During rainfall events, fine particles (fines) in the soils gradually migrate downward, and eventually the loss of fines results in an increase in the pore volume of the soil and a reduction in the stability of the soil skeleton, which can lead to subsequent slope failure. To gain more understanding of the fine migration process at the microscopic scale, a 3D discrete element-fluid flow sequentially coupled model is developed, based on Darcy’s Law, to simulate fluid flow through a porous medium and calculate the transportation of soil solids. The erosion model is verified using experimental data. Parametric studies are carried out to investigate the effects of coarse particle size. The results reveal that changes in pore structure caused by fine particle migration can change the local permeability of the material. For the case of the average pore throat diameter to fine particle ratio ( $$J$$ ) of 2.41, changes in local porosity with time from internal erosion in the sample can be divided into four stages: (1) a rapid increase with some variations in porosity, (2) a slow increase in porosity, (3) a rapid increase in porosity, and (4) a steady state with no change in porosity. Not all stages are present for all value of $$J$$ . Stages (1) (2) (4) are present for 2.48 ≤ $$J\le$$ 2.58 and stages (1) (4) are present for $$J$$ ≤ 2.24 and $$J\hspace{0.17em}$$ ≥ 2.74. A sharp increase in the fine’s erosion possibility occurs for a $$J$$ value lies between 2.58 and 2.74. The erosion possibility sensibility shows an exponential relationship with $$J$$ . The model provides an effective and efficient way to investigate the process of pore blockage and internal soil erosion.

Intelligent plant cultivation robots play a vital role in plant intelligent cultivation. Aiming at the problem of low accuracy and low efficiency of intelligent plant cultivation robots in searching for target plants in unknown environments, this paper proposes an intelligent plant cultivation robot based on key marker algorithm and improved A* algorithm. In terms of target plant positioning, a key marker algorithm based on YOLO V3 is proposed. Accurately find the target plant in the location environment, mark the key coordinate location of the target plant, and plan the routes. In terms of route planning, the self-node search strategy for the traditional A* algorithm has disadvantages such as many path turning points and large turning angles. By analyzing annealing algorithm, ant colony algorithm and A* algorithm, this paper proposes an improved A* algorithm. Finally, experiments with many different scenes prove that the intelligent plant cultivation robot proposed in this paper can effectively improve the accuracy of target plant detection and the efficiency of route planning.

Water is a fundamental and essential resource for sustainable and healthy development of natural environment and human society. China boasts considerable water resources but is below world average on a per capita basis, and is challenged by the disparity in temporal and geographical distribution and poor utilization of water resources, severe water pollution, etc. As water is closely associated with climate change, change in water resources amid climate change in the future might affect China’s water security. Based on the reality and challenges of China’s water resources, this chapter shall discuss the evolution of China’s water management system and the current water demand, as well as the trend in future. Next, a study of water resources risk and its temporal and spatial distribution in China’s power industry are introduced, concluding with policy recommendations for China to address the challenges.

Understanding the meanings and identifying the controls for the stormflow generation with complex and nonlinear behaviors is essential for the development of threshold-based hydrological theory, as well as accurate assessment and prediction for flash flood risks. However, the study of catchment emergent patterns with three-linear threshold behaviors associated with hydrological connectivity has received little attention. Therefore, utilizing soil water storage, rainfall, and streamflow data spanning 3 years in a humid forest experimental watershed, Dujiangyan city, China, we elucidated how and where stormflow was generated with nonlinear behaviors, which were affected by antecedent wetness and rainfall amounts. Stormflow threshold behavior was taken as a function of combined gross precipitation and antecedent soil water storage, which was isolated using piecewise regression analysis with the identification of two breakpoints (i.e., generation threshold, Tg and rising threshold, Tr). It was found that the initial emergent behavior of rainfall-runoff was generally activated at the Tg, and then an abrupt shift from slow to fast flood response was possibly triggered at the Tr. These processes are important to understand the formation and development of flash floods at the watershed scale. It was noted that, above the Tr, considerably higher stormflow amounts generally occurred due to the lateral-connectivity extension of runoff contributing area from stream to neighboring hillslopes. Meanwhile, gravity-driven water movements in soil and better hydrological connectivity during the above-Tr phase readily triggered the huge flash flood disasters. The above-Tr flash floods with abrupt shifts were predominantly controlled by rainfall amounts, while initial below-Tg stormflow generation was mainly controlled by unsaturated soil water storage. More noteworthy, under heavy rainstorm conditions, the above-Tr stormflow was dominantly generated by subsurface flow, as was demonstrated at hillslope and watershed scales. These findings contribute to increasing our understanding of the controls on three-linear threshold-based hydrological behaviors, as well as of subsurface stormflow generation mechanism associated with hydrological connectivity in humid forest watersheds.

An energy management strategy (EMS) for hybrid AC/DC microgrid is proposed in this paper. Since the accuracy of microgrid management is affected by the error of power prediction, this proposal is aiming to improve the economic performances of a microgrid while considering the prediction error. The management process is divided into 3 stages: day-ahead scheduling, intraday pre-scheduling and intraday scheduling. Economic performance is considered as the most important factor in the day-ahead scheduling stage. In this situation, the power forecast results are used to calculate the management command. Neural network is introduced in the management strategy of intraday pre-scheduling stage. In this process, the model of power generation, energy storage and other devices of microgrid is proposed, which is important for the dispatch of next stage. This process can reduce the error of management caused by power forecast. In the stage of intraday scheduling, the models of microgrid are taken used to calculate the dispatching command. The power forecasting results are used in this stage. Simulation results are shown in this paper and verified the effectiveness of the proposed strategy. The economic performances and operation reliability of the microgrid are both improved.

What is already known on this topic? Brucellosis is a zoonotic infectious disease caused by Brucella spp. The main source of infection in human brucellosis is sick animals, mainly including sheep, goat, and cattle, but sika deer (Cervus nippon) can also cause human brucellosis. The first human brucellosis case in Guizhou Province was reported in 2009, and no brucellosis outbreak was reported caused by sika deer ever before. What is added by this report? This is the first reported outbreak of human brucellosis caused by sika deer in Guizhou Province. Inappropriate regulation of animal movement may be the main driver of introducing and spreading brucellosis in southern areas. The ability to diagnose brucellosis in both humans and animals was weak in the county where the outbreak took place. What are the implications for public health practice? It was suggested to prioritize occupational protection and health education for sika deer breeders. The inspection of the movement of animals and the reimbursement policy need to be improved.

Recently, the development of deep learning brings new opportunities for hyperspectral unmixing. In this paper, we propose a new architecture based on Recurrent Neural Networks and Bidirectional-LSTM (BiLSTM) that consists of two blocks: the feature extraction stage based on BiLSTM and the abundance estimation stage via Chain Classifier. BiLSTM can capture the long-distance relation among spectral bands better and Chain Classifier is more suitable to deal with multi-label task that exists in abundance estimation process. We evaluate the proposed method on two real HSI data sets including Jasper Ridge and Urban compared with three state-of-the-art approaches, and the results show significant improvements in accuracy of unmixing.

At the end of 2019, a coronavirus disease 2019 (COVID-19) outbroke in Wuhan, China, and spread to Guizhou province on January of 2020. To acquire the epidemiologic characteristics of COVID-19 in Guizhou, China, we collected data on 162 laboratory-confirmed cases related to COVID-19. We described the demographic characteristics of the cases and estimated the incubation period, serial interval and basic reproduction number. We also presented two representative case studies in Guizhou province -- Case Study 1 was an example of asymptomatic carrier; and Case Study 2 was an example of a large and complex infection chain that involved four different districts spanning three provinces and eight families. With an estimation of 8 days incubation period and 6 days serial interval, our results indicate that there may exist infectiousness during the incubation period for 2019-nCoV. This increases the difficulty of screening or identifying cases related to COVID-19.

Plant roots generally enhance soil strength and stabilize slopes through hydro-mechanical effects, especially in forested areas prone to shallow slope failure. Forest fires can severely weaken the hydro-mechanical contribution of roots to slopes, however, the hydro-mechanical characteristics of soil–root systems (SRS) affected by wildfire remain poorly understood. To obtain insight into the post-fire hydro-mechanical characteristics of SRS, a subalpine conifer forested area in Sichuan Province, China that suffered a wildfire on March 30, 2019 was continuously monitored over two consecutive years. Samples from zones with different degrees of burn severity were collected and tests both for roots and SRS were performed. The results revealed a substantial decline in root number, which decreased by 46%–58% two years after the wildfire in the medium- and high-severity areas. The tensile strength tests indicated a reduction of root tensile strength by 36%–47% for roots with diameters less than 2 mm. The shear strength of the SRS determined from saturated direct shear tests strongly and had degraded by 55%–82% two years after the wildfire because of root death and reduced root reinforcement. The results of hydraulic conductivity tests over the same time period indicated an abrupt reduction of SRS hydraulic conductivity within several months after the fire owing to ash clogging and the formation of a hydrophobic layer. After more time had elapsed, however, hydraulic conductivity had increased unexpectedly by a factor of 2.2–3.2 greater than that of unburned soil. We attribute this observation to the formation of macropore flow pathways from decayed roots, which was observed by scanning electron microscopy. The findings presented here provide important insight into the temporal changes of the hydro-mechanical characteristics of SRS in burned areas and their associated mechanisms and could be a useful reference to better evaluate post-wildfire stability of subalpine conifer forest in similar environmental conditions.

Random fluctuation in photovoltaic (PV) power plants is becoming a serious problem affecting the power quality and stability of the grid along with the increasing penetration of PVs. In order to solve this problem, by the adding of energy storage systems (ESS), a grid-connected microgrid system can be performed. To make this system feasible, this paper proposes a model predictive control (MPC) based on power/voltage smoothing strategy. With the receding horizon optimization performed by MPC, the system parameters can be estimated with high accuracy, and at the same time the optimal ESS power reference is obtained. The critical parameters, such as state of charge, are also taken into account in order to ensure the health and stability of the ESSs. In this proposed control strategy, communication between PVs and ESS is not needed, since control command can be calculated with local measured data. At the same time, MPC can make a great contribution to the accuracy and timeliness of the control. Finally, experimental results from a grid-connected lab-scale microgrid system are presented to prove effectiveness and robustness of the proposed approach.

In this paper, an energy management strategy for residential microgrid with PV, controllable thermal loads and energy storage system is proposed. In order to realize the management and power dispatching for a microgrid, the proposal takes economic and comfort performances into account. In order to reduce the computation of management process, the energy management commands are classified and different calculation methods are adopted for different cases. By simplifying the system models and cost functions, energy management system can select the optimal power command. Finally, simulation results are presented and verify that the proposal can improve the operation performances: reducing the economic cost, avoiding large scale of power exchanged with grid and lowering the computation burden.

Aiming at the operation control strategy of photovoltaic energy storage microgrid system. According to the "self-generated self-use, excess electricity sent to grid" mode, this paper proposes an economic optimization operation control strategy that can considering the cost of energy storage system in real time. The simulation verification the strategy can be used. The energy storage system has two working modes, a grid-connected mode and an independent mode. A seamless energy storage converter mode switching control technique is proposed, and the experimental results are given to verify the correctness of the theory. In response to the time-of-use price, the self-adjusting control strategy can achieve better economic operation benefits. The historical data of a practical project case in a characteristic town in Qinghai was used to simulate the whole year operational status of the strategy. The results show that the proposed strategy can greatly improve the life of energy storage system. And strategy can make the photovoltaic energy storage microgrid system achieve better operating income.

Understanding the causality between energy consumption, carbon emissions and economic growth is helpful for policymakers to formulate energy, environmental and economic policies. For the first time, based on nonlinear dynamics, this paper employs multispatial convergent cross mapping (CCM) to revisit the energy-carbon-economy causation for China, India and the G7 countries using both aggregate data and per capita data. The findings indicate that there are significant differences between developing countries and developed countries. A bidirectional nexus between energy consumption, carbon emissions and economic growth is found in China and India, but various causal relationships are identified in the G7 countries, including bidirectional, unidirectional and neutral nexus. The results confirm that the decoupling phenomenon is common in most G7 countries. By leveraging a variety of samples and a new approach, this study provides new evidence for policy authorities to formulate country-specific policies to obtain better environmental quality while achieving sustainable economic growth.

Many viruses can cause respiratory diseases in humans. Although great advances have been achieved in methods of diagnosis, it remains challenging to identify pathogens in unexplained pneumonia (UP) cases. In this study, we applied next-generation sequencing (NGS) technology and a metagenomic approach to detect and characterize respiratory viruses in UP cases from Guizhou Province, China. A total of 33 oropharyngeal swabs were obtained from hospitalized UP patients and subjected to NGS. An unbiased metagenomic analysis pipeline identified 13 virus species in 16 samples. Human rhinovirus C was the virus most frequently detected and was identified in seven samples. Human measles virus, adenovirus B 55 and coxsackievirus A10 were also identified. Metagenomic sequencing also provided virus genomic sequences, which enabled genotype characterization and phylogenetic analysis. For cases of multiple infection, metagenomic sequencing afforded information regarding the quantity of each virus in the sample, which could be used to evaluate each viruses’ role in the disease. Our study highlights the potential of metagenomic sequencing for pathogen identification in UP cases.

Energy storage system (ESS) are playing a more important role in renewable energy integration, especially in micro grid system. In this paper, the integrated scheme of energy storage system is designed. And a demonstration project of 1MWh energy storage power station which was accessed to a photovoltaic system was built. The structure of the storage system was given. Two control strategies of the storage system: smoothing the power fluctuation photovoltaic power and following Time-Of-Use electricity price were studied. The control strategy is tested on the 1MWh demonstration project, and the test results were described and analyzed in detail. The test results verify the correctness and feasibility of the control strategy.

This paper proposes a novel current control method based on Model Predictive Control (MPC) for three-phase inverters. The proposed method is based on an Adaptive MPC (A-MPC) with a PWM modulation. An innovative model parameter estimation and modification method is also proposed, leading to enhanced control accuracy. Comparing with traditional current control methods, such as PI and PR control, the proposed method has better dynamic performance. The transient dynamics, i.e., recovery time and overshoot, have been considerably improved. Simulation and experimental results are presented to validate the effectiveness of the proposal.

Random fluctuation of PV power is becoming a more and more serious problem affecting the power quality and stability of grid as the PV penetration keeps increasing recentyears. Aiming at this problem, this paper proposed a control strategy of energy storage system based on Model Predictive Control (MPC). By the continuous optimizing of MPC, we can obtain the system parameters accurately, and then calculate the energy storage power. At the same time, this control took state of charge (SOC) and other parameters into account to ensure the health and stability of the energy storage units. Finally, simulation results proved the proposed control strategy had good performance and robustness.