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The capabilities of 23 global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 6 were evaluated for six extreme precipitation indices from 1961 to 2010 using interannual variability and Taylor skill scores in the Yellow River Basin and its eight subregions. The temporal variations and spatial distributions of extreme precipitation indices were projected from 2021 to 2050 under the shared socioeconomic pathway scenarios (SSP2–4.5 and SSP5–8.5). The results show that most GCMs perform well in simulating extreme values (1-day maximum precipitation (RX1day) and 5-day maximum precipitation (RX5day)), duration (consecutive dry days), and intensity index (simple daily intensity index (SDII)), and perform poor in simulating the threshold indices (precipitation on very wet days (R95p) and number of heavy precipitation days (R10mm)). The projected changes in extreme precipitation indicate that under the SSP2-4.5 scenario, future extreme precipitation will increase by 15.7% (RX1day), 15.8% (RX5day), 30.3% (R95p), 1d (R10mm), and 6.6% (SDII), respectively, decrease by 2.1d (CDD). The aforementioned changes are further enhanced under the SSP5-8.5 scenario. Extreme precipitation changes widely in Hekou Town to Longmen, in the northeastern part of the region from Longmen to Sanmenxia, below Huayuankou, and in the interflow basin. HIGHLIGHTS The study evaluated the biases of 23 global climate models (GCMs) from observations and the spatial distribution of the biases.; Interannual variability score, Taylor diagram, and Taylor skill score were used to evaluate CMIP6 GCMs.; The future changes of the Yellow River Basin and its subregions extreme precipitation under SSP2-4.5 and SSP5-8.5 scenarios were projected by using six ETCCDI indices.;

Surface water is a crucial part of terrestrial ecosystems and is crucial to maintaining ecosystem health, ensuring social stability, and promoting high-quality regional economic development. The surface water in the Yellow River Basin (YRB) has a high sediment content and spatially heterogeneous sediment distribution, presenting a significant challenge for surface water extraction. In this study, we first analyze the applicability of nine water indexes in the YRB by using the Landsat series images (Landsat 5, 7, 8) and then examine the correlation between the accuracy of the water indexes and suspended particulate matter (SPM) concentrations. On this basis, we propose a surface water extraction method considering the SPM concentrations (SWE-CSPM). Finally, we examine the dynamic variations in the surface water in the YRB at four scales: the global scale, the secondary water resource zoning scale, the provincial scale, and the typical water scale. The results indicate that (1) among the nine water indexes, the MBWI has the highest water extraction accuracy, followed by the AWEInsh and WI2021, while the NDWI has the lowest. (2) Compared with the nine water indexes and the multi-index water extraction rule method (MIWER), the SWE-CSPM can effectively reduce the commission errors of surface water extraction, and the water extraction accuracy is the highest (overall accuracy 95.44%, kappa coefficient 90.62%). (3) At the global scale, the maximum water area of the YRB shows a decreasing trend, but the change amount is small. The permanent water area shows an uptrend, whereas the seasonal water area shows a downtrend year by year. The reason may be that the increase in surface runoff and the construction of reservoir projects have led to the transformation of some seasonal water into permanent water. (4) At the secondary water resource zoning scale, the permanent water area of other secondary water resource zonings shows an increasing trend in different degrees, except for the Interior Drainage Area. (5) At the provincial scale, the permanent water area of all provinces shows an uptrend, while the seasonal water areas show a fluctuating downtrend. The maximum water area of Shandong, Inner Mongolia Autonomous Region, and Qinghai increases slowly, while the other provinces show a decreasing trend. (6) At the typical water scale, there are significant differences in the water area variation process in Zhaling Lake, Eling Lake, Wuliangsuhai, Hongjiannao, and Dongping Lake, but the permanent water area and maximum water area of these waters have increased over the past decade. This study offers significant technical support for the dynamic monitoring of surface water and helps to deeply understand the spatiotemporal variations in surface water in the YRB.

Water security, as a crucial component of national security, plays a significant role in maintaining regional stability and ensuring the healthy and rapid development of the economy and society. The Yellow River water-receiving area of Henan Province (YRWAR-HN) is selected as the research area in this study. Firstly, a comprehensive evaluation index system is constructed based on the actual water security problems of the research area, and the single index quantification–multiple indices syntheses–poly-criteria integration method (SMI-P) is introduced to quantify the water security degree of 14 cities in the YRWAR-HN from 2010 to 2021. Then, the obstacle degree model is used to identify the key obstacle indexes that restrict the improvement of water security. Finally, the harmonious behavior set optimization method is adopted to carry out the regulation of water security, and the improvement path of water security in the YRWAR-HN is formulated. The results indicate the following: (1) the water security degree of the YRWAR-HN shows a fluctuating upward trend, increasing from 0.4348 (2010) to 0.6766 (2021), a significant rise of 55.61%. The water security level improves from the relatively unsafe level to the relatively safe level. Hebi City exhibits the fastest rate of water security improvement, while Xinxiang City shows the slowest rate. (2) The density of the river network (X1) and the proportion of investment in water conservancy and environmental protection in the total investment (X15) are the two indexes with the highest obstacle degree, with the average obstacle degrees being 15.09% and 10.79%, respectively. (3) The combination of the composite regulation scenario and improvement Path 2 is the optimal regulation strategy for water security in the YRWAR-HN. From the implementation process, Luoyang, Sanmenxia, Jiyuan, Xuchang, and Shangqiu may prioritize improving their flood and drought disaster defense capabilities and emergency response capabilities, continuously enhancing the flood prevention and disaster reduction system. Zhengzhou, Kaifeng, Xinxiang, Jiaozuo, Anyang, Hebi, Pingdingshan, and Zhoukou may prioritize resolving the regional water supply and demand conflicts, balancing development and conservation, actively seeking transboundary and external water transfers, and strengthening the capacity for water conservation and intensive utilization. Puyang City may prioritize enhancing its comprehensive water environment management capabilities, increasing investment in water conservancy and the environment, improving production processes, reducing pollutant emissions, and mitigating agricultural non-point source pollution.

This paper proposes a novel adaptive finite-time controller for a quadrotor unmanned aerial vehicle (UAV) model with stochastic perturbations and parameter-unknown terms, under the constraints of a state-constrained system. The controller is designed based on full-state quantization, where the error system is defined to be a function of the quantized error signal. An adaptive method is employed to address the quadrotor UAV system model with nonlinear terms and unknown perturbations. The controller utilizes Barrier Lyapunov function (BLF) bounds with adaptive effective time performance to ensure full-state constraint of the system. The stability of the system is proven using Lyapunov’s stability theorem. The effectiveness of the designed full-state constrained controller for quadrotor UAV based on full-state quantization is verified through a physical experimental simulation platform.

The issue of finite-time stability has garnered significant attention in the control systems of quadrotor aerial vehicles. However, existing techniques for achieving finite-time control often fail to consider the system’s state constraint characteristics and rarely address input quantization issues, thereby limiting their practical applicability. To address these problems, this paper proposes a finite-time adaptive neural network tracking control scheme based on a novel barrier Lyapunov function for the quadrotor unmanned aerial vehicle (UAV) system. Firstly, an adjustable boundary for the barrier Lyapunov function is introduced in the control system of a quadrotor UAV, enabling convergence of all states within finite-time constraints during trajectory tracking. Subsequently, a filter compensation signal is incorporated into the recursive design process of the controller to mitigate errors caused by filtering. Finally, a smoothing intermediate function is employed to alleviate the impact of input quantization on the quadrotor system. Experimental validation is conducted on the Quanser QDrone experimental platform to demonstrate the efficacy of the proposed control scheme.

An adaptive dynamic surface trajectory tracking control method based on the Nussbaum function is proposed for a class of quadrotor UAVs encountering unknown external disturbances and unidentified nonlinearities. By transforming controller expressions into numerical solutions, the challenge of overly complex controller design expressions is addressed, simplifying the overall controller design process and enhancing the efficiency of simulation programs. Additionally, an adaptive controller based on Nussbaum gain is introduced to effectively resolve actuator saturation issues. This approach mitigates complexities associated with traditional control design and ensures smooth operation of the quadrotor UAVs. The proposed methodology offers promising prospects for enhancing the robustness and performance of quadrotor UAVs under uncertain operating conditions. Finally, to validate the effectiveness of the proposed control scheme, a hardware-in-the-loop experimental setup is constructed. The dynamic model of the quadrotor UAVs and the proposed controller scheme are implemented on the Rapid Control Prototype (RCP) and Real-Time Simulator (RTS), respectively. This facilitates a semi-physical simulation experiment, providing a basis for the subsequent application of the control scheme to actual aerial vehicles. The concluding experimental results affirm the effectiveness of the proposed control scheme and highlight its potential for practical applications.

Celtis sinensis is a highly versatile species that is commonly cultivated in the southern regions of China. In June 2022, leaf spot disease was detected in C. sinensis in Nanjing, Jiangsu, China. Based on morphological characteristics, three isolates were determined to be of the Alternaria species. A phylogenetic analysis of combined ITS, GAPDH, TEF1-α, RPB2, and Alt a 1 sequences identified the three isolates we obtained as Alternaria alternata and A. koreana. We determined the pathogenicity of A. alternata and A. koreana in C. sinensis leaves using inoculation through in vivo experiments. Symptoms of inoculation onset in indoor pots were in accordance with those observed in the open country. A. alternata and A. koreana can grow at 15–35 °C, with the best growth occurring at 25 °C. The findings from fungicide susceptibility experiments demonstrated that A. alternata and A. koreana were the most sensitive to prochloraz, which could offer an effective approach for future prevention and control measures against A. alternata and A. koreana. This study provides the initial step toward further research on A. alternata and A. koreana as pathogens of C. sinensis and provides the stage for future control strategy development.

Understanding the impact of irradiation and temperature on the mechanical properties of GaN single crystals holds significant relevance for rational designs and applications of GaN-based transistors, lasers, and sensors. This study systematically investigates the influence of C-ion irradiation and temperature on pop-in events, hardness, Young’s modulus, and fracture behavior of GaN single crystals through nanoindentation experiments. In comparison with unirradiated GaN samples, the pop-in phenomenon for ion-irradiated GaN samples is associated with a larger critical indentation load, which decreases with increasing temperature. Both unirradiated and ion-irradiated GaN samples exhibit a decline in hardness with increasing indentation depth, while Young’s moduli do not exhibit a clear size effect. In addition, intrinsic hardness displays an inverse relationship with temperature, and ion-irradiated GaN single crystals exhibit greater intrinsic hardness than their unirradiated counterparts. Our analysis further underscores the significance of Peierls stress during indentation, with this stress decreasing as temperature rises. Examinations of optical micrographs of indentation-induced fractures demonstrate an irradiation embrittlement effect. This work provides valuable insights into the mechanical behavior of GaN single crystals under varying irradiation and temperature conditions.

Considering the current problems related to the utilization of agricultural water resources in the Yellow River Basin, we propose the definition of the safe utilization of agricultural water resources based on the summary and analysis of recent studies on water resources security. Through the analysis of water resources development and utilization in the basin over the years, an evaluation index system for agricultural water resources security in the basin was constructed, and a weighted cooperative game method combination was used to evaluate the agricultural water resources security in the basin using the weighted TOPSIS model. The evaluation results show that the utilization of agricultural water resources in the areas under the jurisdiction of Sichuan and Shandong Provinces in the basin was in a secure or a relatively higher state, whereas Ningxia was in a relatively unsecure state, and the remaining provinces were in a basic secure state. Based on the evaluation results, we have provided the corresponding countermeasures for the safe utilization of agricultural water resources in terms of water-saving irrigation technology, water resources monitoring system, and water resources management system to support the effective implementation of efficient water-saving irrigation of agricultural water resources in the Yellow River Basin. HIGHLIGHTS The definition of safe water utilization in agriculture is proposed.; An index system suitable for the safe utilization of agricultural water resources in the Yellow River Basin is constructed.; The corresponding countermeasures for the safe utilization of agricultural water resources are put forward from the aspects of agricultural water use mode and water-saving irrigation technology.;

This study evaluates the performance of Global Climate Models (GCMs) in simulating extreme climate in three northeastern provinces of China (TNPC). A total of 23 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) were selected and compared with observations from 1961 to 2010, using the 12 extreme climate indices defined by the Expert Team on Climate Change Detection and Indicators. The Interannual Variability Skill Score (IVS), Taylor diagrams and Taylor Skill Scores (S) were used as evaluation tools to compare the outputs of these 23 GCMs with the observations. The results show that the monthly minimum of daily minimum temperature (TNn) is overestimated in 55.7% of the regional grids, while the percentage of time when the daily minimum temperature is below the 10th percentile (TN10p) and the monthly mean difference between the daily maximum and minimum temperatures (DTR) are underestimated in more than 95% of the regional grids. The monthly maximum value of the daily maximum temperature (TXx) and the annual count when there are at least six consecutive days of the minimum temperature below the 10th percentile (CSDI) have relatively low regional spatial biases of 1.17 °C and 1.91 d, respectively. However, the regional spatial bias of annual count when the daily minimum temperature is below 0 °C (FD) is relatively high at 9 d. The GCMs can efficiently capture temporal variations in CSDI and TN10p (IVS < 0.5), as well as the spatial patterns of TNn and FD (S > 0.8). For the extreme precipitation indices, GCMs overestimate the annual total precipitation from days greater than the 95th percentile (R95p) and the annual count when precipitation is greater than or equal to 10 mm (R10 mm) in more than 90% of the regional grids. The maximum number of consecutive days when precipitation is below 1 mm (CDD) and the ratio of annual total precipitation to the number of wet days (greater than or equal to 1 mm) (SDII) are underestimated in more than 80% and 54% of the regional grids, respectively. The regional spatial bias of the monthly maximum consecutive 5-day precipitation (RX5day) is relatively small at 10.66%. GCMs are able to better capture temporal variations in the monthly maximum 1-day precipitation (RX1day) and SDII (IVS < 0.6), as well as spatial patterns in R95p and R10mm (S > 0.7). The findings of this study can provide a reference that can inform climate hazard risk management and mitigation strategies for the TNPC.

Plant-parasitic nematodes significantly threaten agriculture and forestry, causing various diseases. They cause annual losses of up to 178 billion dollars worldwide due to their parasitism. Nematophagous fungi (NF) are valuable in controlling or reducing parasitic nematode diseases by killing nematodes through predatory behavior. This article summarizes the strategic approaches adopted by NF to capture, poison, or consume nematodes for food. NF are classified based on their attacking strategies, including nematode trapping, endoparasitism, toxin production, and egg and female parasitism. Moreover, extracellular enzymes such as serine proteases and chitinases also play an important role in the fungal infection of nematodes by disrupting nematode cuticles, which act as essential virulence factors to target the chemical constituents comprising the nematode cuticle and eggshell. Based on the mentioned approaches, it is crucial to consider the mechanisms employed by NF to control nematodes focused on the use of NF as biocontrol agents.

The research on plant endophytes has been drawing a lot of attention in recent years. Pantoea belongs to a group of endophytes with plant growth-promoting activity and has been widely used in agricultural fields. In our earlier studies, Pantoea eucalypti FBS135 was isolated from healthy-growing Pinus massoniana and was able to promote pine growth. P. eucalypti FBS135 can grow under extremely low nitrogen conditions. To understand the mechanism of the low-nitrogen tolerance of this bacterium, the transcriptome of FBS135 in the absence of nitrogen was examined in this study. We found that FBS135 actively regulates its gene expression in response to nitrogen deficiency. Nearly half of the number (4475) of genes in FBS135 were differentially expressed under this condition, mostly downregulated, while it significantly upregulated many transportation-associated genes and some nitrogen metabolism-related genes. In the downregulated genes, the ribosome pathway-related ones were significantly enriched. Meanwhile, we constructed a Tn5 transposon library of FBS135, from which four genes involved in low-nitrogen tolerance were screened out, including the gene for the host-specific protein J, RNA polymerase σ factor RpoS, phosphoribosamine-glycine ligase, and serine acetyltransferase. Functional analysis of the genes revealed their potential roles in the adaptation to nitrogen limitation. The results obtained in this work shed light on the mechanism of endophytes represented by P. eucalypti FBS135, at the overall transcriptional level, to an environmentally limited nitrogen supply and provided a basis for further investigation on this topic.

To learn the deep relationship implicit in load data and improve the accuracy of load prediction, this paper presents a new Seq2seq framework based on dual attention and a bidirectional gated recurrent unit (BiGRU). The authors also introduce the Distortion Loss including Shape and Time (DILATE) loss function. Firstly, a dual attention mechanism is added to the Seq2seq architecture. The first layer of the attention mechanism enables the encoder to output multiple intermediate states, making the decoder more targeted when calculating the predicted values at different times. The second layer is an automatic attention mechanism, which reduces the possibility of errors accumulated during a long-time span prediction by calculating the internal correlation of the decoder output sequence data. Secondly, the DILATE loss function is introduced to improve the prediction lag problem caused by the mean square error (MSE) loss function. Finally, the proposed model is tested using power load data from a region in northern China. The simulation results show that the method proposed in this paper has a better prediction effect than LSTM, GRU and LS-SVR.

Cryphalus piceae attacks various economically important conifers. Similar to other bark beetles, Cr. piceae plays a role as a vector for an assortment of fungi and nematodes. Previously, several ophiostomatoid fungi were isolated from Cr. piceae in Poland and Japan. In the present study, we explored the diversity of ophiostomatoid fungi associated with Cr. piceae infesting pines in the Shandong Province of China. We isolated ophiostomatoid fungi from both galleries and beetles collected from our study sites. These fungal isolates were identified using both molecular and morphological data. In this study, we recovered 175 isolates of ophiostomatoid fungi representing seven species. Ophiostoma ips was the most frequently isolated species. Molecular and morphological data indicated that five ophiostomatoid fungal species recovered were previously undescribed. Thus, we proposed these five novel species as Ceratocystiopsis yantaiensis, C. weihaiensis, Graphilbum translucens, Gr. niveum, and Sporothrix villosa. These new ophiostomatoid fungi add to the increasing number of fungi known from China, and this evidence suggests that numerous novel taxa are awaiting discovery in other forests of China.

A control strategy for a certain class of hypersonic flight aircraft dynamic models with unknown parameters is proposed in this article. The strategy is adaptive dynamic surface input quantization control. To address the issues in conventional inversion control, a first-order low-pass filter and an adaptive parameter minimum learning law are introduced in the control system design process. This method has the following features: (1) it solves the problem of repeated differentiation of the virtual control law in the conventional back-stepping method, greatly simplifying the control law structure; (2) by using the norm of the neural network weight vector as the adaptive adjustment parameter instead of updating each element online, the number of adaptive adjustment parameters is significantly reduced, improving the execution efficiency of the controller; (3) the introduced hysteresis quantizer overcomes the disadvantage of the quantization accuracy deterioration when the input value is too low in the logarithm quantizer, improving the accuracy of the quantizer. Stability analysis has shown that all signals in the closed-loop system are semi-globally uniformly bounded, and simulation results have verified the effectiveness of the proposed adaptive quantized control scheme.

Affected by global climate change and rapid socio-economic development, China faces serious water security issues, especially in terms of water shortages, flood disasters, and water-related ecological and environmental problems [...]

Fungi of the genus Geosmithia are frequently associated with bark beetles that feed on phloem on various woody hosts. Most studies on Geosmithia were carried out in North and South America and Europe, with only two species being reported from Taiwan, China. This study aimed to investigate the diversity of Geosmithia species in China. Field surveys in Fujian, Guangdong, Guangxi, Hunan, Jiangsu, Jiangxi, Shandong, Shanghai, and Yunnan yielded a total of 178 Geosmithia isolates from 12 beetle species. The isolates were grouped based on morphology. The internal transcribed spacer, β-tubulin, and elongation factor 1-α gene regions of the representatives of each group were sequenced. Phylogenetic trees were constructed based on those sequences. In total, 12 species were identified, with three previously described species (Geosmithia xerotolerans, G. putterillii, and G. pallida) and nine new species which are described in this paper as G. luteobrunnea, G. radiata, G. brevistipitata, G. bombycina, G. granulata (Geosmithia sp. 20), G. subfulva, G. pulverea (G. sp. 3 and Geosmithia sp. 23), G. fusca, and G. pumila sp. nov. The dominant species obtained in this study were G. luteobrunnea and G. pulverea. This study systematically studied the Geosmithia species in China and made an important contribution to filling in the gaps in our understanding of global Geosmithia species diversity.

A composite learning dynamic surface control is proposed for a class of multi-machine power systems with uncertainties and external disturbances by using fuzzy logic systems (FLSs) and disturbance observer (DOB). The main characteristics of the proposed strategy are as follows: (1) The approximation ability of FLSs for nonlinear model of multi-machine power systems is enhanced considerably by using the composite learning method and providing additional correction information for the FLSs. These findings differ considerably from previous designs that focus directly on the system's tracking performance. (2) The filtering errors caused by the utilizations of the first-order low-pass filters in dynamic surface control (DSC) are compensated effectively by designing the compensating signals in the control law design process. (3) The compound disturbances including the FLSs' approximation error and external disturbances are estimated and mitigated by constructing DOB. Finally, the proposed control algorithm is verified on the StarSim Hardware-in-loop experimental platform, and the experimental results validate the effectiveness of the proposed control strategy in suppressing disturbances and enhancing the robustness of the controller.

Unbalanced and inadequate development has led to challenges such as resource shortage, ecological fragility, and economic backwardness in the water-receiving area of Henan Province, which has hindered the high-quality development of the region. This research aims to construct a high-quality development regulation model. The single-indicator quantification–multi-indicator synthesis–multicriteria integration (SMI-P) method was used to evaluate the level of regional development; using the method of embedded system dynamics, the regulation model was constructed and applied. The results show that (1) from 2011 to 2020, the degree of regional high-quality development showed an increasing trend, rising from a low level (0.34) to a medium level (0.57), an increase of one level, but the level of high-quality development still has a lot of room for improvement and faces great challenges; (2) the development of a resource–ecology–economy–social system was in a state of non-harmonious balance, and the proportion of contributions of each system was very different, but the system was developing towards a state of harmony and balance; (3) based on the constructed high-quality development regulation model, the key constraints affecting the high-quality development of the Yellow River water supply area in Henan Province are per capita water consumption, per capita energy consumption, carbon emissions per capita, GDP per capita, etc. The model constructed in this paper can improve the quality development level through the application of examples. The high-quality development degree of the study area was increased from 0.57 to 0.8.

Dielectric elastomer actuators exhibit butterfly-shaped hysteresis effects under unbiased periodic input signals. In comparison with single hysteresis effects, butterfly-shaped hysteresis effects are more complicated, which include two single hysteresis loops, and the directions of both loops are different. Hence, it is a great challenge to build a hysteresis model to describe the butterfly-shaped behavior. To this end, a butterfly-shaped relay operator is newly proposed as an elementary operator to construct the butterfly-shaped Preisach model, and the weighting functions/weights of the developed model are positively defined, which facilitates the construction of the unique inverse model and the controller design. To further improve the modeling accuracy, a piecewise-defined butterfly-shaped Preisach model considering the variation of asymmetric nonlinear hysteresis effects with different input amplitudes is proposed. Experiments with the fabricated elastomer actuator-actuated system are conducted to validate the effectiveness of the developed modeling approach.

The transition from natural forest to plantations has increased dramatically in the past decades. Forest conversion will affect soil properties and thus soil ecosystem services. Based on soil indicators, we studied the differences of soil ecosystem services among three forest types in Liuxihe National Forest Park and analyzed the effects of conversion from natural forest to artificial forest on soil ecosystem services. The results showed that the soil carbon sequestration of evergreen broadleaf forest (EBF) was stronger, and the soil organic carbon density (36.43 ± 0.97 kg m−3) was significantly higher than that of moso bamboo forest (MBF) (25.46 ± 1.72 kg m−3) and sugar orange forest (SOF) (19.31 ± 2.68 kg m−3) in the 0–10 cm soil layer. The soil water conservation of MBF was higher, and its soil water content was significantly higher than that of EBF in the three soil layers, which was more than 20% higher than that of EBF. There was no significant difference in soil total nitrogen content among the three forest types, while the soil total phosphorus content of MBF and SOF was more than twice that of EBF. It is important to consider soil ecosystem services in forest protection and restoration in forest parks.

This study contrives a discrete-time adaptive decentralized control algorithm with input quantization for interconnected multi-machine power systems with SVC. First, a dynamic surface scheme is applied to the excitation controller design, in which first-order digital low-pass filters are used to predict the next virtual control law, which overcomes the model conversion problem in backstepping. Therefore, the controller design and structure are simplified. Further, an improved hysteresis quantizer is utilized for amplitude quantization of control input signals; along with the discretization of time, this achieves digital decentralized control. Finally, semi-global uniformly ultimately boundedness (SGUUB) of the whole control system is demonstrated based on the Lyapunov stability theory, and the effectiveness of the proposed control algorithm is verified on the ModelingTech real-time simulation experimental platform for power electronics.

While the growing population in the world has a large demand for food, agriculture and forestry are currently facing severe challenges due to phytopathogens and pests along with global warming. For half a century chemical pesticides and fertilizers have made a great contribution to agricultural production. However, the excessive use of chemical agents has caused obvious side effects on the environment and the sustainable development of agriculture in the long term. China has recorded one of the fastest economic growths for more than 20 years but at the cost of a seriously polluted environment. Since a decade ago, China has paid increasing attention to environment protection and taken intensified measures for pollution control and ecological restoration. In this context, the biocontrol agent industry in China has experienced a golden decade of rapid development. In this minireview, we will introduce the application and development of microorganism-based biocontrol agents in China over the past two decades.

This article aims at designing an adaptive estimated inverse control scheme to realize precise tracking control for a class of discrete-time nonlinear system with hysteresis nonlinearities. To this end, firstly, the dynamic surface control technology with digital first-order low-pass filter is designed and the original control system does not need to be transformed into an unknown special form. Then, the procedures of the controller design are greatly simplified. Secondly, the hysteresis nonlinearity is mitigated by constructing an discrete-time estimated inverse hysteresis compensator. Finally, the validity of the proposed adaptive control scheme is verified by the computer control experiments on a hardware-in-the-loop simulation platform. It is proved that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SUUB).

With the aim of addressing the problem of the trajectory tracking control of quadrotor unmanned aircraft robots (UARs), in this study, we developed a neural network and event-triggering mechanism-based adaptive control scheme for a quadrotor UAR control system. The main technologies included this scheme are as follows. (1) Under the condition that only the quadrotor’s position information can be obtained, a modified high-gain state observer-based adaptive dynamic surface control (DSC) method was applied and the tracking control of quadrotor UARs was acquired. (2) An event-triggered mechanism for UARs was designed, in which the energy consumption was greatly reduced and the communication efficiency between the system and the control terminal was improved. (3) By selecting appropriate parameters, appropriate initial conditions for the adaptive laws, and establishing a high-gain state observer, a tracking performance of L∞ could be achieved. Finally, simulation results of the hardware-in-loop strategy are presented. The control method we propose here outperformed the traditional backstepping sliding mode control (BSMC) scheme.

In this paper, a fuzzy adaptive output feedback dynamic surface sliding-mode control scheme is presented for a class of quadrotor unmanned aerial vehicles (UAVs). The framework of the controller design process is divided into two stages: the attitude control process and the position control process. The main features of this work are (1) a nonlinear observer is employed to predict the motion velocities of the quadrotor UAV; therefore, only the position signals are needed for the position tracking controller design; (2) by using the minimum learning technology, there is only one parameter which needs to be updated online at each design step and the computational burden can be greatly reduced; (3) a performance function is introduced to transform the tracking error into a new variable which can make the tracking error of the system satisfy the prescribed performance indicators; (4) the sliding-mode surface is introduced in the process of the controller design, and the robustness of the system is improved. Stability analysis proved that all signals of the closed-loop system are uniformly ultimately bounded. The results of the hardware-in-the-loop simulation validate the effectiveness of the proposed control scheme.

A robust adaptive fuzzy nonlinear controller based on dynamic surface and integral sliding mode control strategy (ADSISMC) is proposed to realize trajectory tracking for a class of quadrotor UAVs. In this study, the composite factors including parametric uncertainties and external disturbances are added to controller design, which make it more realistic. The quadrotor model is divided into two subsystems of attitude and position that make the control design become feasible. The main contributions of the proposed ADSISMC strategy are as follows: (1) The combination of dynamic surface and integral sliding mode makes the system always in sliding stage by finding the appropriate initial position compared with the common sliding mode, and the complexity of explosion in backstepping method is eliminated. (2) By introducing the fuzzy system, the unknown functions and uncertainties can be approximated which significantly improves the robustness and the tracking performance. (3) The switching control strategy is utilized to compensate for the errors between estimated and ideal inputs; the tracking performance of the whole system has been significantly improved. The simulation results show the effectiveness of the proposed control method.

Mechanical properties of gallium nitride (GaN) single crystals upon carbon ion irradiation are examined using nanoindentation analysis at room temperature. Pop-in events in the load-depth curves are observed for unirradiated and irradiated GaN samples. A statistical linear relationship between the critical indentation load for the occurrence of the pop-in event and the associated displacement jump is exhibited. Both the slope of linear regression and the measured hardness increase monotonically to the ion fluence, which can be described by logistic equations. Moreover, a linear relationship between the regression slope as a micromechanical characterization and the hardness as a macroscopic mechanical property is constructed. It is also found that the maximum resolved shear stress of the irradiated samples is larger than that of the unirradiated samples, as the dislocation loops are pinned by the irradiation-induced defects. Our results indicate that the nanoindentation pop-in phenomenon combined with a statistical analysis can serve as a characterization method for the mechanical properties of ion-irradiated materials.

Abstract Seasonal precipitation changes under the influence of large-scale climate oscillations in the East River basin were studied using daily precipitation data at 29 rain stations during 1959–2010. Seasonal and global models were developed and evaluated for probabilistic precipitation forecasting. Generalized additive model for location, scale, and shape was used for at-site precipitation forecasting. The results indicate that: (1) winter and spring precipitation processes at most stations are nonstationary, while summer and autumn precipitation processes at few of the stations are stationary. In this sense, nonstationary precipitation processes are dominant across the study region; (2) the magnitude of precipitation is influenced mainly by the Arctic Oscillation, the North Pacific Oscillation, and the Pacific Decadal Oscillation (PDO). The El Niño / Southern Oscillation (ENSO) also has a considerable effect on the variability of precipitation regimes across the East River basin; (3) taking the seasonal precipitation changes of the entire study period as a whole, the climate oscillations influence precipitation magnitude, and this is particularly clear for the PDO and the ENSO. The latter also impacts the dispersion of precipitation changes; and (4) the seasonal model is appropriate for modeling spring precipitation, but the global model performs better for summer, autumn, and winter precipitation.

Piezo-actuated stages are widely applied in the field of high-precision positioning. However, piezo-actuated stages produce hysteresis between the input voltage and the output displacement that negatively influences the positioning accuracy. In this paper, the Bouc-Wen model is established and identified using the bat-inspired optimization algorithm. Subsequently, based on the established hysteresis model, we propose a sliding mode control method with a new reaching law to suppress the hysteresis nonlinearity and achieve high-precision tracking control for the piezo-actuated stages. In addition, the proposed control method contains the perturbation estimation part, which can estimate online the modeling uncertainty and the unknown external disturbances. The stability of the proposed control method is demonstrated through the Lyapunov theory. Finally, to validate the effectiveness of the proposed control method, experiments are conducted on the piezo-actuated stages. Experimental results demonstrate that the proposed control method is superior to the feed-forward control and the conventional sliding mode control method.

In this paper, a neural decentralized adaptive quantized dynamic surface control scheme is proposed for a class of large-scale multi-machine power systems with static var compensator (SVC) and unknown line-transmission time delays. The main contributions of the proposed method are summarized as follows: (1) a decentralized dynamic surface quantized control scheme with simple structure is proposed for the large-scale multi-machine systems with SVC, where the “explosion of complexity”problem in backstepping method and the complexities introduced by SVC are overcome; (2) the unknown line-transmission time delays between different generators are considered and dealt with by introducing the finite-cover lemma with radial basis function neural networks (RBFNNs) approximator, which leads to the arbitrarily small £∞a tracking performance; (3) the strong nonlinearities, uncertain parameters and external disturbances of the system are considered and the number of the estimated parameters is greatly reduced by estimating the weight vector norm of neural networks instead of estimating the weighted vector itself. It is proved that all the signals in the control system are ultimately uniformly boundedb and can be made arbitrarily small. Simulation results show the validity of the proposed method.

CuZnO (CZO) films have attracted increasing amounts of attention due to their promising potential applications in semiconductor devices. ZnO shows n-type conductivity, and attempts have been made to dope several elements in ZnO to improve the electrical properties. This study investigated the electrical property transitions of CZO films and determined the copper concentration at which the conductivity of CZO films will change from n-type to p-type. In this study, CZO films were fabricated by ultrasonic spray pyrolysis with copper acetate, zinc acetate, and ammonium acetate precursor solution. The concentrations of Cu ions in the CZO films were controlled by the concentration ratios of copper acetate to zinc acetate in the precursor solutions. In addition, these samples were analyzed by Hall effect measurements, X-ray diffraction, transmittance measurements, and photoluminescence measurements. The results show that the conductivity of the CZO film changes from n-type to p-type when the copper ion concentration in the film is 5%.

CuZnO (CZO) films have received considerable attention, owing to their potential applications in semiconductor devices, including gas sensors or solar cells. However, exactly how these films affect the properties of CZO films by using different Cu sources has seldom been investigated. This study demonstrates the feasibility of preparing CZO films by using different Cu sources via a simple ultrasonic spray method, in which copper nitrate and copper acetate were used as copper sources. Optical properties of CZO films prepared by copper nitrate and copper acetate were also investigated, based on transmittance and photoluminescence measurements. Additionally, the composition and the morphology of the films were investigated using the X-ray diffraction analysis and field emission scanning electron microscopy. The results of this study demonstrate that the CZO films prepared by using copper acetate exhibit better optical properties.

Viral genotype shift in chronic hepatitis B (CHB) patients during antiviral therapy has been reported, but the underlying mechanism remains elusive.38 CHB patients treated with ADV for one year were selected for studying genotype shift by both deep sequencing and Sanger sequencing method.Sanger sequencing method found that 7.9% patients showed mixed genotype before ADV therapy. In contrast, all 38 patients showed mixed genotype before ADV treatment by deep sequencing. 95.5% mixed genotype rate was also obtained from additional 200 treatment-naïve CHB patients. Of the 13 patients with genotype shift, the fraction of the minor genotype in 5 patients (38%) increased gradually during the course of ADV treatment. Furthermore, responses to ADV and HBeAg seroconversion were associated with the high rate of genotype shift, suggesting drug and immune pressure may be key factors to induce genotype shift. Interestingly, patients with genotype C had a significantly higher rate of genotype shift than genotype B. In genotype shift group, ADV treatment induced a marked enhancement of genotype B ratio accompanied by a reduction of genotype C ratio, suggesting genotype C may be more sensitive to ADV than genotype B. Moreover, patients with dominant genotype C may have a better therapeutic effect. Finally, genotype shifts was correlated with clinical improvement in terms of ALT.Our findings provided a rational explanation for genotype shift among ADV-treated CHB patients. The genotype and genotype shift might be associated with antiviral efficiency.

ZnO:YAG-based metal-insulator-semiconductor (MIS) diodes with various insulators were synthesized on an indium tin oxide (ITO) glass by ultrasonic spray pyrolysis. SiO2 and MnZnO (MZO) were separately used as insulators. X-ray diffraction revealed the crystalline structure of the ZnO:YAG film. The photoluminescence (PL) properties of the ZnO:YAG film were studied and the color of photoluminescence was found to be almost white. The electrical properties of the diodes with different insulators and thicknesses were compared. The diode with the SiO2 insulator had a lower threshold voltage, smaller leakage current, and a higher series resistance than that with the MZO insulator layer.