The hydrological process in the dry–warm valley of the mountainous area of southwest China has unique characteristics and has attracted scientific attention worldwide. Given that this is an area with fragile ecosystems and intensive water resource conflicts in the upper reaches of the Yangtze River, a systematic identification of its hydrological responses to climate and land use variations needs to be performed. In this study, MIKE SHE was employed and calibrated for the Anning River Basin in the dry–warm valley. Subsequently, a deep learning neural network model of the long short-term memory (LSTM) and a traditional multi-model ensemble mean (MMEM) method were used for an ensemble of 31 global climate models (GCMs) for climate projection. The cellular automata–Markov model was implemented to project the spatial pattern of land use considering climatic, social, and economic conditions. Four sets of climate projections and three sets of land use projections were generated and fed into the MIKE SHE to project hydrologic responses from 2021 to 2050. For the calibration and first validation periods of the daily simulation, the coefficients of determination (R) were 0.85 and 0.87 and the Nash–Sutcliffe efficiency values were 0.72 and 0.73, respectively. The advanced LSTM performed better than the traditional MMEM method for daily temperature and monthly precipitation. The average monthly temperature projection under representative concentration pathway 8.5 (RCP8.5) was expected to be slightly higher than that under RCP4.5; this is contrary to the average monthly precipitation from June to October. The variations in streamflow and actual evapotranspiration (ET) were both more sensitive to climate change than to land use change. There was no significant relationship between the variations in streamflow and the ET in the study area. This work could provide general variation conditions and a range of hydrologic responses to complex and changing environments, thereby assisting with stochastic uncertainty and optimizing water resource management in critical regions.
Ultrafiltration (UF) has been increasingly implemented in drinking water treatment plants; however, algae and their secretions can cause severe membrane fouling and pose great challenges to UF in practice. In this study, a simple and practical chemically enhanced backwashing (CEB) process was developed to address such issues using various cleaning reagents, including sodium hypochlorite (NaClO), sodium chloride (NaCl), sodium hydroxide (NaOH), sodium citrate, and their combinations. The results indicate that the type of chemical played a fundamental role in alleviating the hydraulically irreversible membrane fouling (HIMF), with NaClO as the best-performing reagent, followed by NaCl. Furthermore, a CEB process using a combination of NaClO with NaCl, NaOH, or sodium citrate delivered little improvement in the alleviation of membrane fouling compared with NaClO alone. The optimized dosage and dosing frequency of NaClO were 10 mg·L−1 two times per day. Long-term pilot-scale and full-scale experiments further verified the feasibility of the CEB process in relieving algae-derived membrane fouling. Compared with the conventional hydraulic backwashing without chemical involvement, the CEB process can effectively remove the organic foulants including biopolymers, humic substances, and protein-like substances by means of oxidization, thereby weakening the cohesive forces between the organic foulants and the membrane surface. Therefore, the CEB process can efficiently alleviate the algae-related membrane fouling with lower chemical consumption, and is proposed as an alternative to control membrane fouling in treating the algae-containing surface water.
Recognizing the risk of fluvial bank erosion is an important challenge to ensure the early warning and prevention or control of bank collapse in river catchments, including in the Yangtze River. This study introduces a geomorphons-based algorithm to extract river bank erosion information by adjusting the flatness from multibeam echo-sounding data. The algorithm maps 10 subaqueous morphological elements, including the slope, footslope, flat, ridge, peak, valley, pit, spur, hollow, and shoulder. Twenty-one flatness values were used to build an interpretation strategy for the subaqueous features of riverbank erosion. The results show that the bank scarp, which is the erosion carrier, is covered by slope cells when the flatness is 10°. The scour pits and bank scars are indicated by pit cells near the bank and hollow cells in the bank slope at a flatness of 0°. Fluvial subaqueous dunes are considered an important factor accelerating bank erosion, particularly those near the bank toe; the critical flatness of the dunes was evaluated as 3°. The distribution of subaqueous morphological elements was analyzed and used to map the bank erosion inventory. The analysis results revealed that the near-bank zone, with a relatively large water depth, is prone to form large scour pits and a long bank scarp. Arc collapse tends to occur at the long bank scarp to shorten its length. The varied assignment of flatness values among terrestrial, marine, and fluvial environments is discussed, concluding that diversified flatness values significantly enable fluvial subaqueous morphology recognition. Consequently, this study provides a reference for the flatness-based recognition of fluvial morphological elements and enhances the targeting of subaqueous signs and risks of bank failure with a range of multibeam bathymetric data.
Rapid, sensitive, point-of-care detection of pathogenic bacteria is important for food safety. In this study, we developed a novel quantum dot nanobeads-labelled lateral flow immunoassay strip (QBs-labelled LFIAS) combined with strand displacement loop-mediated isothermal amplification (SD-LAMP) for quantitative Salmonella Typhimurium (ST) detection. Quantum dot nanobeads (QBs) served as fluorescence reporters, providing good detection efficiency. The customizable strand displacement (SD) probe was used in LAMP to improve the specificity of the method and prevent by-product capture. Detection was based on a sandwich immunoassay. A fluorescence strip reader measured the fluorescence intensity (FI) of the test (T) line and control (C) line. The linear detection range of the strip was 102–108 CFU·mL−1. The visual limit of detection was 103 CFU·mL−1, indicating that the system was 10-fold more sensitive than AuNPs-labelled test strips. ST specificity was analyzed in accordance with agarose gel outputs of PCR and SD-LAMP. We detected ST in foods with an acceptable recovery of 85%–110%. The method is rapid, simple, almost equipment-free, and suitable for bacterial detection in foods and for clinical diagnosis.
With the coming of the “14th Five-Year Plan”, the coordinated control of particulate matter with an aerodynamic diameter no greater than 2.5 μm (PM2.5) and O3 has become a major issue of air pollution prevention and control in China. The stereoscopic monitoring of regional PM2.5 and O3 and their precursors is crucial to achieve coordinated control. However, current monitoring networks are currently inadequate for monitoring the vertical profiles of both PM2.5 and O3 simultaneously and support air quality control. The University of Science and Technology of China (USTC) has established a nationwide ground-based hyperspectral stereoscopic remote sensing network based on multi-axis differential optical absorption spectroscopy (MAX-DOAS) since 2015. This monitoring network provides a significant opportunity for the regional coordinated control of PM2.5 and O3 in China. One-year vertical profiles of aerosol, NO2 and HCHO monitored from four MAX-DOAS stations installed in four megacities (Beijing, Shanghai, Shenzhen, and Chongqing) were used to characterize their vertical distribution differences in four key regions, Jing–Jin–Ji (JJJ), Yangtze River Delta (YRD), Pearl River Delta (PRD), and Sichuan Basin (SB), respectively. The normalized and yearly averaged aerosol vertical profiles below 400 m in JJJ and PRD exhibit a box shape and a Gaussian shape, respectively, and both show exponential shapes in YRD and SB. The NO2 vertical profiles in four regions all exhibit exponential shapes because of vehicle emissions. The shape of the HCHO vertical profile in JJJ and PRD was Gaussian, whereas an exponential shape was shown in YRD and SB. Moreover, a regional transport event occurred at an altitude of 600–1000 m was monitored in the southwest–northeast pathway of the North China Plain (NCP) by five MAX-DOAS stations (Shijiazhuang (SJZ), Wangdu (WD), Nancheng (NC), Chinese Academy of Meteorological Sciences (CAMS), and University of Chinese Academy of Sciences (UCAS)) belonging to the above network. The aerosol optical depths (AOD) in these five stations decreased in the order of SJZ > WD > NC > CAMS > UCAS. The short-distance regional transport of NO2 in the 700–900 m layer was monitored between WD and NC. As an important precursor of secondary aerosol, the peak of NO2 air mass in WD and NC all occurred 1 h earlier than that of aerosol. This was also observed for the short-distance regional transport of HCHO in the 700–900 m layer between NC and CAMS, which potentially affected the O3 concentration in Beijing. Finally, CAMS was selected as a typical site to determine the O3–NOx–volatile organic compounds (VOCs) sensitivities in vertical space. We found the production of O3 changed from predominantly VOCs-limited conditions to mainly mixed VOCs–NOx-limited condition from the 0–100 m layer to the 200–300 m layer. In addition, the downward transport of O3 could contribute to the increase of ground surface O3 concentration. This ground-based hyperspectral stereoscopic remote sensing network provide a promising strategy to support management of PM2.5 and O3 and their precursors and conduct attribution of sources.
There is a great demand for transparent films, membranes, or substrates in the fields of intelligent wearables, electronic skins, air filtration, and tissue engineering. Traditional materials such as glass and plastics cannot satisfy these requirements because of the lack of interconnected pores, undesirable porosity, and flexibility. Electrospun fibrous membranes offset these shortcomings because they contain small pores and have high porosity as well as outstanding flexibility. Thus, the development of transparent electrospun fibrous membranes is of great value. This work reports a simple and effective way to develop flexible and porous transparent fibrous membranes (TFMs) directly from electrospun fibrous membranes via mechanical pressing, without employing any other additives. In addition, the relationship between the transparency performance and the molecular structure of the polymers after pressing was summarized for the first time. After mechanical pressing, the membranes maintained fibrous morphology, micron-sized pores, and desired porosity. Polystyrene fibrous membranes, which exhibited excellent optical and mechanical properties, were used as a reference. The TFMs possessed high transparency (∼89% visible light transmittance at 550 nm), high porosity (10%–30%), and strong mechanical tensile strength (∼148 MPa), nearly 78 times that of the pristine electrospun fibrous membranes. Moreover, this study demonstrated that transparent and conductive membranes can be fabricated based on TFMs using vacuum-assisted filtration of silver nanowires followed by mechanical pressing. Compared with indium tin oxide films, conductive TFMs exhibited good electrical conductivities (9 Ω per square (Ω·sq−1), 78% transmittance at 550 nm) and notable mechanical performance (to bear abundant bending stresses).
A large-span steel–concrete composite beam with precast hollow core slabs (CBHCSs) is a relatively new floor structure that can be applied to various long-span structures. However, human-induced vibrations may present serviceability issues in such structures. To alleviate vibrations, both the walking forces excited by humans and the associated floor responses must be elucidated. In this study, 150 load–time histories of walking, excited by 25 test participants, are obtained using a force measuring plate. The dynamic loading factors and phase angles in the Fourier series functions for one-step walking are determined. Subsequently, walking tests are performed on seven CBHCS specimens to capture the essential dynamic properties of mode shapes, natural frequencies, damping ratios, and acceleration time histories. The CBHCS floor system generally exhibits a high frequency (> 10 Hz) and low damping (damping ratio < 2%). Sensitivity studies using the finite element method are conducted to investigate the vibration performance of the CBHCS floor system, where the floor thickness, steel beam type, contact time, and human weight are considered. Finally, analytical expressions derived for the fundamental frequency and peak acceleration agree well with the experimental results and are hence proposed for practical use.
Three-dimensional (3D) microdisplacement monitoring plays a crucial role in the assembly of large aircraft. This paper presents a broadly applicable high-precision online 3D microdisplacement monitoring method and system based on proximity sensors as well as a corresponding in situ calibration method, which can be applied under various extreme working conditions encountered in the aircraft assembly process, such as compact and obstructed spaces. A 3D monitoring model is first established to achieve 3D microdisplacement monitoring based only on the one-dimensional distances measured by proximity sensors, which concerns the extrinsic sensor parameters, such as the probe base point (PBP) and the unit displacement vector (UDV). Then, a calibration method is employed to obtain these extrinsic parameters with high precision by combining spatial transformation principles and weighted optimization. Finally, calibration and monitoring experiments performed for a tailplane assembly process are reported. The calibration precision for the PBP is better than ±10 μm in the X and Y directions and ±2 μm in the Z direction, and the calibration precision for the UDV is better than 0.07°. Moreover, the accuracy of the 3D microdisplacement monitoring system can reach ±15 μm. In general, this paper provides new insights into the modeling and calibration of 3D microdisplacement monitoring based on proximity sensors and a precise, efficient, and low-cost technical means for performing related measurements in compact spaces during the aircraft assembly process.
There is an unprecedented need for new treatments for renal failure, as the incidence of this disease is increasing disproportionately to advancements in therapies. Current treatments are limited by the availability of viable organs, for which there is a worldwide lack. These treatment modalities also require a substantial amount of infrastructure, significantly limiting the access to care in most countries. Kidney tissue engineering approaches promise to develop alternative solutions that address many of the inadequacies in current care. Although many advancements have been made—primarily in the past decade—in biofabrication and whole-organ tissue engineering, many challenges remain. One major hindrance to the progress of current tissue engineering approaches is establishing successful vascularization of developed engineered tissue constructs. This review focuses on the recent advancements that address the vascular challenge, including the biofabrication of vasculature, whole-organ engineering through decellularization and recellularization approaches, microscale organogenesis, and vascularization using organoids in the context of kidney tissue engineering. We also highlight the specific challenges that remain in developing successful strategies capable of clinical translation.
It is necessary to develop a new strategy for treatment of lung cancer since it is the main cause of cancer death. Tanshinone IIA (Tan IIA), an active ingredient of a commonly used traditional Chinese herb Salvia miltiorrhiza, provides a new direction to develop a new strategy for the treatment. It has been found that Tan IIA could inhibit lung cancer in vitro and in vivo by inducing autophagic apoptosis. Tan IIA increased apoptotic cells and the expression of cleaved caspase 3 and cleaved caspase 9, decreased B-cell lymphoma-2 (Bcl-2)/Bcl-2 associated X protein (Bax) ratio in human non-small cell lung cancer (NSCLC) cell lines, which was promoted by an autophagy activator Rapamycin, and weaken by autophagy inhibitor 3-methyladenine (3-MA). In addition, Tan IIA induced more autophagosomes, up-regulated light chain 3β (LC-3B) I and LC-3B II conversion and less sequestosome 1 (SQSTM1/p62) expression, which cannot be weakened by the caspase 3 antagonist. Moreover, overexpression of LC-3B gene (LC3B) and downregulation of autophagic gene 5 (ATG5) further confirmed that Tan IIA induced autophagic apoptosis in NSCLC cell lines. Beclin-1 gene (BECN1) overexpression and silence attenuated the effects of Tan IIA, suggesting autophagic apoptosis that Tan IIA induced was dependent on Beclin-1. Overall, our study demonstrated a new treatment mechanism of Tan IIA and suggested that Tan IIA is a potential new anti-cancer therapeutic option.
Traditional Chinese medicine (TCM) has been successfully applied worldwide in the treatment of coronavirus disease 2019 (COVID-19), which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the pharmacological mechanisms underlying this success remain unclear. Hence, the aim of this review is to combine pharmacological assays based on the theory of TCM in order to elucidate the potential signaling pathways, targets, active compounds, and formulas of herbs that are involved in the TCM treatment of COVID-19, which exhibits combatting viral infections, immune regulation, and amelioration of lung injury and fibrosis. Extensive reports on target screening are elucidated using virtual prediction via docking analysis or network pharmacology based on existing data. The results of these reports indicate that an intricate regulatory mechanism is involved in the pathogenesis of COVID-19. Therefore, more pharmacological research on the natural herbs used in TCM should be conducted in order to determine the association between TCM and COVID-19 and account for the observed therapeutic effects of TCM against COVID-19.
Accurately assessing and tracking the progression of liver-specific injury remains a major challenge in the field of biomarker research. Here, we took a retrospective validation approach built on the mutuality between serum and tissue biomarkers to characterize the liver-specific damage of bile duct cells caused by a-naphthyl isothiocyanate (ANIT). We found that carboxylesterase 1 (CES1), as an intrahepatic marker, and dipeptidyl peptidase 4 (DPP-IV), as an extrahepatic marker, can reflect the different pathophysiologies of liver injury. Levels of CES1 and DPP-IV can be used to identify liver damage itself and the inflammatory state, respectively. While the levels of the conventional serological biomarkers alkaline phosphatase (ALP), alanine aminotransferase (ALT), and aspartate aminotransferase (AST) were all concomitantly elevated in serum and tissues after ANIT-induced injury, the levels of bile acids decreased in bile, increased in serum, and ascended in intrahepatic tissue. Although the level of γ-glutamyl transpeptidase (γ-GT) changed in an opposite direction, the duration was much shorter than that of CES1 and was quickly restored to normal levels. Therefore, among the abovementioned biomarkers, only CES1 made it possible to specifically determine whether the liver cells were destroyed or damaged without interference from inflammation. CES1 also enabled accurate assessment of the anti-cholestasis effects of ursodeoxycholic acid (UDCA; single component) and Qing Fei Pai Du Decoction (QFPDD; multicomponent). We found that both QFPDD and UDCA attenuated ANIT-induced liver damage. UDCA was more potent in promoting bile excretion but showed relatively weaker anti-injury and antiinflammatory effects than QFPDD, whereas QFPDD was more effective in blocking liver inflammation and repairing liver damage. Our data highlights the potential of the combined use of CES1 (as an intrahepatic marker of liver damage) and DPP-IV (as an extrahepatic marker of inflammation) for the accurate evaluation and tracking of liver-specific injury–an application that allows for the differentiation of liver damage and inflammatory liver injury.
Against the current social and technological background dominated by services and technology, new opportunities are opening up for the industrial transformation and upgrading of the construction industry. Considering the successful transformation and upgrading of the manufacturing industry through servitization, scholars and practitioners have begun to explore the possibility of servitization in the construction industry. Current practices and theory show that different understandings of servitization in the construction sector exist; however, they are still in their infancy and lack a deep and systematic awareness, which does not benefit the transformation and upgrading of construction through servitization. Therefore, this paper systematically analyzes the motivation, definition, and implications of servitization in construction based on the value-adding nature of servitization and considers the problems confronting the construction industry. To facilitate this development, transformation pathways for servitization in construction are analyzed from multiple angles, including value co-creation, service innovation, and networked operation, which are in line with the new trends in digital construction. In addition, based on the supporting elements of construction, which include finance, human resources, technology, materials, and equipment, this paper examines the impact of servitization on the construction industry's ecology. In short, we expect that this systematic analysis and exposition can provide a holistic view of servitization in construction from the inside out for scholars and practitioners and can help to promote servitization in construction.
Hydrodynamic cavitation is considered to be a promising technology for process intensification, due to its high energy efficiency, cost-effective operation, ability to induce chemical reactions, and scale-up possibilities. In the past decade, advancements have been made in the fundamental understanding of hydrodynamic cavitation and its main variables, which provide a basis for applications of hydrodynamic cavitation in radical-induced chemical reaction processes. Here, we provide an extensive review of these research efforts, including the fundamentals of hydrodynamic cavitation, the design of cavitation reactors, cavitation-induced reaction enhancement, and relevant industrial applications. Two types of hydrodynamic cavitation reactors—namely, stationary and rotational—are compared. The design parameters of a hydrodynamic cavitation reactor and reactor performance at the laboratory and pilot scales are discussed, and recommendations are made regarding optimal operation and geometric conditions. The commercial cavitation reactors that are currently on the market are reviewed here for the first time. The unique features of hydrodynamic cavitation have been widely applied to various chemical reactions, such as oxidization reactions and wastewater treatment, and to physical processes, such as emulsion generation and component extraction. The roles of radicals and gas bubble implosion are also thoroughly discussed.
Practical application of a Si anode in a high-energy-density battery cannot be achieved due to the huge volume expansion of these anodes. Researchers have focused on adding binders to the anode to restrict volume expansion in order to address this issue, as the hydrogen bonds and mechanical properties of binders can be used to enhance adhesion and accommodate the volume changes of a Si anode. Herein, we comprehensively consider binders' hydrogen bonds, mechanical properties, stability, and compatibility with the electrolyte solution, and design an ether-/ester-/fluorine-rich composite polymer, P(TFEMA-co-IBVE). The proposed binder formula possesses outstanding stability, adhesion, and mechanical strength; moreover, it can accommodate the dramatic volume changes of a Si electrode and exhibits excellent electrochemical performance, achieving a high areal capacity of about 5.4 mA∙h∙cm−2. This novel polymer design may be applied to other electrode materials in the next generation of lithium-ion batteries.
Lipase-catalyzed stereoselective resolution of cis-(±)-dimethyl 1-acetylpiperidine-2,3-dicarboxylate (cis-(±)-1) is an attractive route for the synthesis of (S,S)-2,8-diazobicyclo[4.3.0]nonane, an important chiral intermediate of the fluoroquinolone antibiotic, moxifloxacin. In our previous study, a lipase from Sporisorium reilianum (SRL) was identified to possess excellent thermostability and pH stability. However, the low enzymatic activity of the SRL is a challenge that must be addressed. A rational design was initially employed for SRL tailoring according to the engineered Candida antarctica lipase B (CALB), resulting in a beneficial variant called SRL-I194N/V195L. Subsequently, two key amino acid residues in loop 6, L145 and L154, which might modulate the lid conformation between open and closed, were identified. A tetra-site variant, SRL-I194N/V195L/L145V/L154G (V13), with a significantly enhanced activity of 87.8 U∙mg−1 was obtained; this value was 2195-fold higher than that of wild-type SRL. Variant V13 was used to prepare optically pure (2S,3R)-dimethyl 1-acetylpiperidine-2,3-dicarboxylate ((2S,3R)-1), resolving 1 mol∙L−1 cis-(±)-1 with a conversion of 49.9% in 2 h and absolute stereoselectivity (E > 200). Excellent stability with a half-life of 92.5 h was also observed at 50 °C. Overall, the study findings reveal a lipase with high activity toward cis-(±)-1 at an industrial level and may offer a general strategy for enhancing the enzyme activity of other lipases and other classes of enzymes with a lid moiety.
As a special type of mobile ad hoc network (MANET), the flying ad hoc network (FANET) has the potential to enable a variety of emerging applications in both civilian wireless communications (e.g., 5G and 6G) and the defense industry. The routing protocol plays a pivotal role in FANET. However, when designing the routing protocol for FANET, it is conventionally assumed that the aerial nodes move randomly. This is clearly inappropriate for a mission-oriented FANET (MO-FANET), in which the aerial nodes typically move toward a given destination from given departure point(s), possibly along a roughly deterministic flight path while maintaining a well-established formation, in order to carry out certain missions. In this paper, a novel cyber-physical routing protocol exploiting the particular mobility pattern of an MO-FANET is proposed based on cross-disciplinary integration, which makes full use of the mission-determined trajectory dynamics to construct the time sequence of rejoining and separating, as well as the adjacency matrix for each node, as prior information. Compared with the existing representative routing protocols used in FANETs, our protocol achieves a higher packet-delivery ratio (PDR) at the cost of even lower overhead and lower average end-to-end latency, while maintaining a reasonably moderate and stable network jitter, as demonstrated by extensive ns-3-based simulations assuming realistic configurations in an MO-FANET.
In mixed and dynamic traffic environments, accurate long-term trajectory forecasting of surrounding vehicles is one of the indispensable preconditions for autonomous vehicles (AVs) to accomplish reasonable behavioral decisions and guarantee driving safety. In this paper, we propose an integrated probabilistic architecture for long-term vehicle trajectory prediction, which consists of a driving inference model (DIM) and a trajectory prediction model (TPM). The DIM is designed and employed to accurately infer the potential driving intention based on a dynamic Bayesian network. The proposed DIM incorporates the basic traffic rules and multivariate vehicle motion information. To further improve the prediction accuracy and realize uncertainty estimation, we develop a Gaussian process (GP)-based TPM, considering both the short-term prediction results of the vehicle model and the driving motion characteristics. Afterward, the effectiveness of our novel approach is demonstrated by conducting experiments on a public naturalistic driving dataset under lane-changing scenarios. The superior performance on the task of long-term trajectory prediction is presented and verified by comparing with other advanced methods.
Recently developed fault classification methods for industrial processes are mainly data-driven. Notably, models based on deep neural networks have significantly improved fault classification accuracy owing to the inclusion of a large number of data patterns. However, these data-driven models are vulnerable to adversarial attacks; thus, small perturbations on the samples can cause the models to provide incorrect fault predictions. Several recent studies have demonstrated the vulnerability of machine learning methods and the existence of adversarial samples. This paper proposes a black-box attack method with an extreme constraint for a safe-critical industrial fault classification system: Only one variable can be perturbed to craft adversarial samples. Moreover, to hide the adversarial samples in the visualization space, a Jacobian matrix is used to guide the perturbed variable selection, making the adversarial samples in the dimensional reduction space invisible to the human eye. Using the one-variable attack (OVA) method, we explore the vulnerability of industrial variables and fault types, which can help understand the geometric characteristics of fault classification systems. Based on the attack method, a corresponding adversarial training defense method is also proposed, which efficiently defends against an OVA and improves the prediction accuracy of the classifiers. In experiments, the proposed method was tested on two datasets from the Tennessee–Eastman process (TEP) and Steel Plates (SP). We explore the vulnerability and correlation within variables and faults and verify the effectiveness of OVAs and defenses for various classifiers and datasets. For industrial fault classification systems, the attack success rate of our method is close to (on TEP) or even higher than (on SP) the current most effective first-order white-box attack method, which requires perturbation of all variables.
Renewable energy transmission by high-voltage direct current (HVDC) has attracted increasing attention for the development and utilization of large-scale renewable energy under the Carbon Peak and Carbon Neutrality Strategy in China. High-penetration power electronic systems have gradually formed at the sending end of HVDC transmission. The operation of such systems has undergone profound changes compared with traditional power systems dominated by synchronous generators. New stability issues, such as broadband oscillation and transient over-voltage, have emerged, causing tripping accidents in large-scale renewable energy plants. The analysis methods and design principles of traditional power systems are no longer suitable for HPPESs. In this paper, the mechanisms of broadband oscillation and transient over-voltage are revealed, and analytical methods are proposed for HPPESs, including small-signal impedance analysis and electromagnetic transient simulation. Validation of the theoretical research has been accomplished through its application in several practical projects in north, northwest, and northeast region of China. Finally, suggestions for the construction and operation of the future renewable-energy-dominated power system are put forward.