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Abstract Aiming at the problem of zero sequence voltage generated by unbalance parameters of line to ground, which affects arc suppression effect of grounding fault of controllable voltage source. By analyzing the influence of ground unbalance parameters on the arc suppression effect of controllable voltage source under different grounding modes, the mechanism of full compensation arc suppression based on zero sequence voltage of neutral point is revealed, and on this basis, a fully compensated arc suppression model of controllable voltage source controlled by double closed loop PI is established, and the deviation control is carried out by using the neutral voltage of distribution network and the voltage of fault phase supply. The residual voltage ring adopts the ground fault phase residual voltage for closed loop control. The simulation results show that the dual-closed-loop PI control algorithm can continuously stabilize the output waveform of the controllable voltage source. When the transition resistance is 0.1 ~ 10 kΩ, the residual voltage stabilization time of the independent controllable voltage source grounding method is 43 ms ~ 2.4 s, and the parallel arc suppression coil grounding method is 43 ms ~ 4.7 s. The proposed dual closed-loop PI control method for neutral point voltage deviation and fault residual voltage can stabilize the residual voltage of the grounded fault phase to below 10 V, forcing reliable arc extinction at the grounded fault point, exhibiting good stability. Low-voltage simulation tests have also proved the feasibility of the algorithm.

Abstract With the widespread application of composite insulators in transmission lines, exploring the accumulation mechanism of pollution particles on composite insulator surfaces is of importance to ensure the safe and steady operation of the power system. Addressing the current theoretical shortcomings, this study categorises the accumulation process of particles on the insulator surface into three stages, namely ‘spatial motion’, ‘surface collision’, and ‘surface motion’. The motion and rotation velocities in a multi‐physics field are calculated in the spatial motion stage. In the surface collision stage, a parameter called ‘neck height’ is introduced to determine the optimum mechanics theory, and the normal deposition criterion is established. For the surface motion stage, the sliding displacement and rolling displacement on the surface are calculated based on the rotation speed of the particles. A dynamic pollution accumulation model of the composite insulator is established based on the normal deposition criterion and tangential displacement. Finally, numerical simulations are performed by using the finite element method. Simulation results show that the proposed model agrees with the actual insulator pollution accumulation, and the deposition model is still applicable for various types of composite insulators operating in different applied voltages. The deposition probability of particles increases with the increasing particle size. In the surface motion stage, particle displacement increases with particle size and wind velocity.

Aiming at the problem of waveform distortion of the secondary traveling wave obtained from the primary traveling wave signal transmitted by the voltage traveling wave sensor, an accurate detection method of voltage traveling wave based on ensemble empirical mode decomposition (EEMD) and L1 norm least squares regularization is proposed in this paper. Firstly, the forward transfer function model of the specialized voltage traveling wave sensor is established, and the inversion model is derived to analyze the phase frequency and amplitude frequency characteristics of the secondary traveling wave after transmission. EEMD is used to decompose the secondary traveling wave into the intrinsic modal function (IMF) components of different frequency bands. The L1 norm least square regularization inversion algorithm was used to invert each IMF component. Finally, the IMF' components after inversion are synthesized to obtain the primary traveling wave. Simulation and experimental results demonstrate that the proposed method is not affected by noise, mode aliasing effect and regularization parameter accuracy, and the obtained waveform has high similarity to the simulated waveform, which enables precise identification of fault traveling wave.

To reduce the distortion effects of traveling wavefronts for fault location in distribution networks, a novel fault traveling wave detection method employing Robust Local Mean Decomposition (RLMD), Teager Energy Operator (TEO) and Incremental Difference Ratio (IDR) is proposed. According to the dispersion characteristic of traveling waves with multi-branch lines, the sampled faulty traveling wave signal is filtered using the RLMD method, then the TEO is used to determine the first half-wave time interval of the fault traveling wave. Finally, the IDR is proposed to detect the initial moment of the faulty traveling wave. And according to the fault traveling wave transmission path of multi-branch lines, the complex multi-branch line fault location problem is transformed into a three-terminal fault location problem. The fault traveling wave location method is proposed based on the three-terminal fault matrix, which achieves the fault location through the gradual reduction of the fault area range. Simulation and experiment results indicate that the method proposed in this paper can effectively calculate the arrival time of faulty traveling waves, and is more suitable for fault detection in multi-branch distribution lines compared to existing methods. The new proposed faulty location method can achieve reliable location to reduce location errors.

Abstract To solve the commutation failure (CF) issues in high voltage direct current (HVDC) transmission systems based on line commutated converter (LCC), this paper proposes a hybrid solution combining the LCC inverter with the continuously controlled IGCT‐based full‐bridge submodules (FBSMs). The scheme can provide the LCC inverter with an additional commutation area, and compensate for the phase‐shift of the grid voltage under faults. Therefore, it shows better CF resistance than the existing scheme. The characteristics of the proposed hybrid converter are modelled and analyzed in both normal and fault conditions. Then a decoupling control strategy is presented for it. With the ability to counteract negative‐sequence grid voltage, the strategy brings good voltage stability to the dc transmission. And when the grid fault occurs, it can switch to suppress CF by rapidly increasing the output voltage of the FBSMs and applying commutation failure prevention (CFPREV) control to the LCC. As a result, the CF issues can be maximally solved with a smaller number of FBSMs than the existing scheme. Simulations in PSCAD verify the effectiveness of the strategy. Furtherly, an experimental platform is built to show the capacity of the proposed scheme to solve the CF issues.

The weak characteristics of high-impedance faults and the complex attributes of cross-country faults make faulty feeder detection of cross-country high-impedance faults difficult in medium-voltage networks. This paper deduces the zero-sequence equivalent circuit of cross-country faults through a three-sequence two-port network, analyzes the influence of grounding resistance on cross-country faults, and then explores the limitations of the traditional passive feeder detection methods. Moreover, this paper proposes a novel faulty feeder detection method for cross-country high-impedance faults based on zero-sequence active power regulation. First, based on the zero-sequence current varying characteristics under the regulation of zero-sequence voltage, construct a continuous adjustment region of zero-sequence voltage within the feeder insulation tolerance range. Next, based on the zero-sequence active power varying characteristics in each feeder, propose a discriminant formula for the zero-sequence active power fluctuation coefficient. Finally, adjusting zero-sequence voltage can actively amplify the differences in zero-sequence active power fluctuations between healthy feeders and faulty feeders and accurately select faulty feeders of cross-country high-impedance faults in medium-voltage networks. Various fault conditions are simulated in the PSCAD/EMTDC simulation and field test to verify the effectiveness of the proposed method. The proposed method can accurately identify all faulty feeders of cross-country high-impedance faults in the medium-voltage distribution network.

Accurate fault detection and classification help to analyze fault causes and quickly restore faulty phases. Deep learning can automatically extract fault features and identify fault types from the original three-phase voltage and current signals. However, this still imposes challenges such as recognition accuracy and computational complexity. More importantly, high level fault features cannot be extracted in the one-dimensional time series. This paper presents a robust fault classification method based on SA-MobileNetV3 for transmission systems. Considering that the SE (Squeeze-and-Excitation) attention module cannot aggregate the spatial dimension information on the channel, SA (shuffle attention) module is introduced into MobileNetV3, which can effectively fuse the importance of pixels in different channels and in different locations at the same channel. Also, transforming the time series three-phase voltage and current signals into two-dimensional images based on CWT (continuous wavelet transform) makes the proposed method be similar to image recognition, which can mine high level fault features and classify the faults visually. To verify the effectiveness of the method, a 735kV transmission line model is built for data generation through Simulink. Various kinds of fault conditions and factors are considered to verify the adaptability and generalizability. Simulation results show that the method can quickly and accurately identify 11 types of faults, and the accuracy rate is as high as 99.90%. A comparison between the proposed method and other existing techniques shows the superiority of the proposed SA- MobileNetV3, and better anti-noise performance makes it more suitable for real fault signals taken on-site.

Summary: Aging is considered a critical factor of poor prognosis in allogenic hemopoietic stem cell transplantation (allo-HSCT). To elucidate the underlying mechanisms, we comprehensively reintegrated our clinical data from patients after allo-HSCT and public single-cell transcriptomic profile from post-allo-HSCT and healthy individuals, demonstrating that old donors were more prone to acute GVHD (aGVHD) with pronounced inflammation accumulation and worse overall survival (OS). We also found the presence of inflammation-related CXCL2+ HSC subpopulation during aging with significantly enriched pro-inflammatory pathways. Shifting attention to the HSC microenvironment, we deciphered that IL-1/IL-6 and TRAIL (i.e., TNFSF10) ligand‒receptor pair serves as the crucial bridge between CD14/CD16 monocytes and hematopoietic stem/progenitor cells (HSPCs). The profound upregulation of these signaling pathways during aging finally causes HSC dysfunction and lineage-biased differentiation. Our findings provide the theoretical basis for achieving tailored GVHD management and enhancing allo-HSCT regimens efficacy for aged donors.

Abstract Aiming at the problems of noise interference and too many network parameters for power quality disturbances' (PQDs') classification based on deep learning, the lightweight convolutional neural network combining maximum likelihood Kalman filter and continuous wavelet transform is proposed. In this proposed method, the disturbed PQD signals are denoised by maximum likelihood Kalman filter, and then the denoised PQDs are converted to time‐frequency diagrams, which can provide rich time and frequency domain information, and finally the lightweight convolution neural network is used for automatically extracting and classifying multiple PQDs. To verify the effectiveness and superiority of the proposed method, a variety of PQDs were tested under different noise levels, the experiment results indicate that the average classification accuracy can reach more than 99% even in the case of 10 dB noise. Compared with the existing classification methods, the accuracy and noise immunity ability are improved. Additionally, the proposed method has decided advantages, as evidenced by its low parameter count of 0.73M and short average test time with only 0.7 ms.

Due to the overlap of initial traveling wave signals, the traveling wave propagation process in hybrid distribution lines is complicated to analyze. The most significant challenge posed by the traditional passive traveling wave-locating method for hybrid distribution lines lies in identifying the fault section and distinguishing the reflected wave from the fault point or the hybrid connection points. Based on this approach, with the application of the aerial-mode component of the pulse signal generated at the fault point, a fault-section-identification and fault-locating scheme for hybrid distribution feeders with active pulse injection is proposed. When power in a line is cut after a single-to-line ground (SLG) fault occurs, the same pulse is injected into the three phases from the neutral point of the coupling capacitor bank to construct the zero-mode component, which propagates to the SLG fault three-phase asymmetrical point, producing an aerial-mode component that is reflected back to the first end of the line. With the application of the arrival time of an aerial-mode wavefront, it is simple to locate the SLG fault for arbitrary forms of hybrid lines. The simulation results confirm the feasibility of the fault-locating scheme under different feeders, different fault locations, and fault resistances. The results of the experiments confirm the high practical value of the proposed method.

Abstract Current active suppression technology of arc overvoltage in distribution network has small capacity of controllable voltage source and complex control and cannot flexibly adjust the zero‐sequence voltage of neutral point. This study proposes a controllable voltage source system to fully compensate the arc current of ground fault for solving these problems. A controllable voltage source model based on passive supply voltage converter is established, utilising Dyn transformer to carry unbalanced load for a long time. The model output voltage is the same amplitude and frequency as that of single‐phase ground fault phase, but opposite phase. The compensation switch is operated when a ground fault occurs. The output voltage amplitude of the controllable voltage source is controlled, the fault phase voltage is controlled to be 0 in the closed loop, the grounding fault arc current is eliminated and the arc grounding overvoltage is suppressed. The control strategy was verified by the PSCAD/EMTDC simulation model of single‐phase grounding fault arc in 10 kV distribution network and the real single‐phase fault experiment platform of 0.4 kV distribution network. Results proved the model and strategy's accuracy and effectiveness. It provides an engineering practical method for active suppression of arc grounding overvoltage in distribution network.

Nuclear factor erythroid-2 related factor 2 (Nrf2), a nuclear transcription factor, modulates genes responsible for antioxidant responses against toxic and oxidative stress to maintain redox homeostasis and participates in varieties of cellular processes such as metabolism and inflammation during myocardial ischemia and reperfusion injuries (MIRI). The accumulation of reactive oxygen species (ROS) from damaged mitochondria, xanthine oxidase, NADPH oxidases, and inflammation contributes to depraved myocardial ischemia and reperfusion injuries. Considering that Nrf2 played crucial roles in antagonizing oxidative stress, it is reasonable to delve into the up or down-regulated molecular mechanisms of Nrf2 in the progression of MIRI to provide the possibility of new therapeutic medicine targeting Nrf2 in cardiovascular diseases. This review systematically describes the generation of ROS, the regulatory metabolisms of Nrf2 as well as several natural or synthetic compounds activating Nrf2 during MIRI, which might provide novel insights for the anti-oxidative stress and original ideas targeting Nrf2 for the prevention and treatment in cardiovascular diseases.

Abstract Background In vertebrates, hematopoietic stem and progenitor cells (HSPCs) emerge from hemogenic endothelium in the floor of the dorsal aorta and subsequently migrate to secondary niches where they expand and differentiate into committed lineages. Glia maturation factor γ (gmfg) is a key regulator of actin dynamics that was shown to be highly expressed in hematopoietic tissue. Our goal is to investigate the role and mechanism of gmfg in embryonic HSPC development. Methods In-depth bioinformatics analysis of our published RNA-seq data identified gmfg as a cogent candidate gene implicated in HSPC development. Loss and gain-of-function strategies were applied to study the biological function of gmfg. Whole-mount in situ hybridization, confocal microscopy, flow cytometry, and western blotting were used to evaluate changes in the number of various hematopoietic cells and expression levels of cell proliferation, cell apoptosis and hematopoietic-related markers. RNA-seq was performed to screen signaling pathways responsible for gmfg deficiency-induced defects in HSPC initiation. The effect of gmfg on YAP sublocalization was assessed in vitro by utilizing HUVEC cell line. Results We took advantage of zebrafish embryos to illustrate that loss of gmfg impaired HSPC initiation and maintenance. In gmfg-deficient embryos, the number of hemogenic endothelium and HSPCs was significantly reduced, with the accompanying decreased number of erythrocytes, myelocytes and lymphocytes. We found that blood flow modulates gmfg expression and gmfg overexpression could partially rescue the reduction of HSPCs in the absence of blood flow. Assays in zebrafish and HUVEC showed that gmfg deficiency suppressed the activity of YAP, a well-established blood flow mediator, by preventing its shuttling from cytoplasm to nucleus. During HSPC initiation, loss of gmfg resulted in Notch inactivation and the induction of Notch intracellular domain could partially restore the HSPC loss in gmfg-deficient embryos. Conclusions We conclude that gmfg mediates blood flow-induced HSPC maintenance via regulation of YAP, and contributes to HSPC initiation through the modulation of Notch signaling. Our findings reveal a brand-new aspect of gmfg function and highlight a novel mechanism for embryonic HSPC development.

Abstract With the rapid development of social economy, power supply reliability of the distribution network has become particularly important. The distribution network has long been faced with problems such as overvoltage, single‐phase grounding failure and grounding protection. Passive, active, and hybrid arc suppression devices (ASDs) are proposed to solve these problems. Passive ASDs have the advantages of high reliability, low control complexity and good economic benefits, and have been widely used in distribution networks. With the wide application of power electronic components in distribution network, the active part and harmonic part of ground current, which cannot be effectively eliminated by passive ASDs, increase sharply. Therefore, an active arc suppression method is proposed. However, due to the high cost and low reliability of the active equipment, the hybrid ASD has better arc suppression effect. In this paper, the existing ASDs are reviewed, and specific simulation models are established to verify the principle and performance of three different ASDs. The advantages and disadvantages of the three ASDs are compared in detail, and the possible problems and research directions in the future research of arc suppression technology are prospected.

Anomaly detection based on the data collected from the supervisory control and data acquisition (SCADA) system is crucial to reduce the failure rate of wind turbines (WTs). The difficulty of this kind of methods is to dynamically identify the threshold for anomaly detection under changing operating conditions. In this paper, a generalized WT anomaly detection method based on the combined probability estimation model (CPEM) is proposed. The CPEM can estimate the conditional probability density function (PDF) of the target variable given changing conditions. Its generalization and accuracy are better than those of the independent probability estimation model because it combines the advantages of various kinds of probability estimation models through linear combination. By using the CPEM, the normal operating bounds under different operating conditions can be obtained, which dynamically form the thresholds for anomaly detection. Meanwhile, with respect to the thresholds, hypothesis testing (HT) is adopted to identify the anomaly by inspecting whether the observations exceed the thresholds at a given significance level, providing sound mathematical support for anomaly detection and making the detection results more reliable. The effectiveness of the proposed method is tested by using the actual data of WTs with known faults. The results illustrate that the proposed method can detect the abnormal operating state of the gearbox and generator much more early than the system fault alarm.

An advanced metering infrastructure (AMI) system plays a key role in the smart grid (SG), but it is vulnerable to cyberattacks. Current detection methods for AMI cyberattacks mainly focus on the data center or a distributed independent node. On one hand, it is difficult to train an excellent detection intrusion model on a self-learning independent node. On the other hand, large amounts of data are shared over the network and uploaded to a central node for training. These processes may compromise data privacy, cause communication delay, and incur high communication costs. With these limitations, we propose an intrusion detection method for AMI system based on federated learning (FL). The intrusion detection system is deployed in the data concentrators for training, and only its model parameters are communicated to the data center. Furthermore, the data center distributes the learning to each data concentrator through aggregation and weight assignments for collaborative learning. An optimized deep neural network (DNN) is exploited for this proposed method, and extensive experiments based on the NSL-KDD dataset are carried out. From the results, this proposed method improves detection performance and reduces computation costs, communication delays, and communication overheads while guaranteeing data privacy.

Abstract Insulated conductors are used widely in overhead power transmission due to the stability and reduced construction space. However, the ordinary protection devices are not able to detect the phase‐to‐ground faults without overcurrent. Insulated overhead conductor (IOC) faults are often accompanied by partial discharge (PD) phenomenon. Thus, PD monitoring and recognition plays an important role in evaluating the condition of insulation degradation or detecting power line faults. This paper presents a new approach based on a multi‐channel CNN‐LSTM (convolutional neural network, long short term memory) network for fault detection by determining whether there is local discharge phenomenon on the IOC, in which the three‐phase voltage signals are processed with FFT to obtain low frequency and high frequency components, and then the two components together with the original three‐phase signals are fed into three parallel CNNs having different filter lengths, and finally LSTM is used to compose those different‐scale features sequentially. Then, the fault types are determined according to the result of fault detection. This proposed method is tested on the ENET public data set with eight types of faults, and simulation results indicate that the method can improve the detection and classification accuracy of IOC faults compared with other classification methods.

In the neutral ungrounded distribution network, the removal of permanent single-line-to-ground (SLG) fault easily leads to saturation of the electromagnetic voltage transformers (PT), which may cause ferroresonance overvoltage and PT failure. This paper analyzes the zero-sequence voltage after the removal of the SLG fault and reveals the mechanism of ferroresonance excited by the removal of the SLG fault. Then, the total power and transient energy of the zero-sequence circuit under the SLG fault are analyzed. It is deduced that the energy reaches the minimum value at the zero-cross point (ZCP) of the neutral voltage. Based on this, a permanent SLG fault removal method to avoid ferroresonance is proposed, which uses the ZCP point as the fault removal instant. Simulations in ATP-EMTP show that the proposed method can effectively avoid ferroresonance on subharmonic mode. It can also enhance the ferroresonance suppression performance of the ferroresonance suppression resistor in the fundamental-frequency and high-frequency conditions.

Abstract In the non‐effectively grounding distribution system, residual current under single‐line‐to‐ground (SLG) fault threatens the safety of human being and power supply equipment. Active arc suppression device has been proved to be effective for SLG fault arc suppression when the line impedance is ignored. However, in practice, line impedance varies with the fault location and the load current flowing through the impedance brings about additional voltage drop, which increases the fault current and is not dealt with by the conventional methods. To achieve accurate SLG fault arc suppression with the existence of line impedance, the neutral‐to‐ground voltage reference for full ground‐fault current compensation is firstly derived and a detection method is then proposed. The pre‐fault and post‐fault line currents are used to eliminate the influence of load current on the line impedance voltage drop. A dual‐loop voltage and current controller is then designed. The prototype of active arc suppression device was developed. The results of simulation and prototype experiment validate the effectiveness of the proposed method.

Abstract Cytokine release syndrome (CRS) embodies a mixture of clinical manifestations, including elevated circulating cytokine levels, acute systemic inflammatory symptoms and secondary organ dysfunction, which was first described in the context of acute graft-versus-host disease after allogeneic hematopoietic stem-cell transplantation and was later observed in pandemics of influenza, SARS-CoV and COVID-19, immunotherapy of tumor, after chimeric antigen receptor T (CAR-T) therapy, and in monogenic disorders and autoimmune diseases. Particularly, severe CRS is a very significant and life-threatening complication, which is clinically characterized by persistent high fever, hyperinflammation, and severe organ dysfunction. However, CRS is a double-edged sword, which may be both helpful in controlling tumors/viruses/infections and harmful to the host. Although a high incidence and high levels of cytokines are features of CRS, the detailed kinetics and specific mechanisms of CRS in human diseases and intervention therapy remain unclear. In the present review, we have summarized the most recent advances related to the clinical features and management of CRS as well as cutting-edge technologies to elucidate the mechanisms of CRS. Considering that CRS is the major adverse event in human diseases and intervention therapy, our review delineates the characteristics, kinetics, signaling pathways, and potential mechanisms of CRS, which shows its clinical relevance for achieving both favorable efficacy and low toxicity.

Summary: The gut microbiota and metabolites play pivotal roles in the pathobiology of various diseases. Here, we describe a protocol to profile the gut microbiome and meta-metabolome of a mouse disease model for acute graft-versus-host disease. We describe steps for fecal sample collection and processing for 16S sequencing and UPLC-MS. Finally, we detail the steps for data analysis and exhibit multi-omic associations to correlate with pathology.For complete details on the use and execution of this protocol, please refer to Li et al. (2020). : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Abstract Background Decades of efforts have attempted to differentiate the pluripotent stem cells (PSCs) into truly functional hematopoietic stem cells (HSCs), yet the problems of low differentiation efficiency in vitro and poor hematopoiesis reconstitution in vivo still exist, mainly attributing to the lack of solid, reproduced, or pursued differentiation system. Methods In this study, we established an in vitro differentiation system yielding in vivo hematopoietic reconstitution hematopoietic cells from mouse PSCs through a 3D induction system followed by coculture with OP9 stromal cells. The in vivo hematopoietic reconstitution potential of c-kit+ cells derived from the mouse PSCs was evaluated via m-NSG transplantation assay. Flow cytometry analysis, RNA-seq, and cell cycle analysis were used to detect the in vitro hematopoietic ability of endothelial protein C receptor (EPCR, CD201) cells generated in our induction system. Results The c-kit+ cells from 3D self-assembling peptide induction system followed by the OP9 coculture system possessed apparently superiority in terms of in vivo repopulating activity than that of 3D induction system followed by the 0.1% gelatin culture. We interestingly found that our 3D+OP9 system enriched a higher percentage of CD201+c-kit+cells that showed more similar HSC-like features such as transcriptome level and CFU formation ability than CD201-c-kit+cells, which have not been reported in the field of mouse PSCs hematopoietic differentiation. Moreover, CD201+ hematopoietic cells remained in a relatively slow cycling state, consistent with high expression levels of P57 and Ccng2. Further, we innovatively demonstrated that notch signaling pathway is responsible for in vitro CD201+ hematopoietic cell induction from mouse PSCs. Conclusions Altogether, our findings lay a foundation for improving the efficiency of hematopoietic differentiation and generating in vivo functional HSC-like cells from mouse PSCs for clinical application.

ObjectivesAcute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy with widely variable prognosis. For this reason, a more tailored-stratified approach for prognosis is urgently needed to improve the treatment success rates of AML patients.MethodsIn the investigation of metabolic pattern in AML patients, we developed a metabolism-related prognostic model, which was consisted of metabolism-related gene pairs (MRGPs) identified by pairwise comparison. Furthermore, we analyzed the predictive ability and clinical significance of the prognostic model.ResultsGiven the significant differences in metabolic pathways between AML patients and healthy donors, we proposed a metabolism-related prognostic signature index (MRPSI) consisting of three MRGPs, which were remarkedly related with the overall survival of AML patients in the training set. The association of MRPSI with prognosis was also validated in two other independent cohorts, suggesting that high MRPSI score can identify patients with poor prognosis. The MRPSI and age were confirmed to be independent prognostic factors via multivariate Cox regression analysis. Furthermore, we combined MRPSI with age and constructed a composite metabolism-clinical prognostic model index (MCPMI), which demonstrated better prognostic accuracy in all cohorts. Stratification analysis and multivariate Cox regression analysis revealed that the MCPMI was an independent prognostic factor. By estimating the sensitivity of anti-cancer drugs in different AML patients, we selected five drugs that were more sensitive to patients in MCPMI-high group than those in MCPMI-low group.ConclusionOur study provided an individualized metabolism-related prognostic model that identified high-risk patients and revealed new potential therapeutic drugs for AML patients with poor prognosis.

Single-line-to-ground (SLG) fault arcs cause the intermittent over-voltages, leading to short circuits within large-scale area. In this paper, a flexible arc suppression device is proposed, which adopts a zigzag grounding transformer, multi-terminal breakers and an isolation transformer to regulate zero-sequence voltage. Principle of zero-sequence voltage regulation (ZVR) and arc suppression method is presented. By carefully choosing the secondary side voltages of grounding transformer as the input of isolation transformer, the zero-sequence voltage is nearly constrained to the opposite of faulty phase supply voltage, and the ground-fault current is limited to a very small value. This device has high adaptability for low-resistance ground fault as it doesn't adopt any electronic apparatus. A 10kV prototype was established and multiple fault conditions were experimented to verify the effectiveness of the proposed ZVR device and its arc suppression principle.

Abstract In recent years, the quantity and proportion of heating defects have increased significantly with more composite insulators used in transmission lines and deterioration of early composite insulators. End heating is the main characteristic of this kind of defect in high‐temperature and high‐humidity areas. In this paper, microstructures of the housing material were observed through scanning electron microscopy and the key factors leading to temperature rise were studied through water absorption and power loss experiments. The results show that polarisation loss is the main cause of temperature rise and power loss increases exponentially with higher electric field intensity. The microporous structures of the housing material not only enhance the moisture absorption effect, but also affect the uniform distribution of the electric field. Due to the concentration of the local electric fields at high‐voltage end, the effect of porosity on temperature rise is more significant. By adjusting the shielding depth (i.e. installation height) of grading ring or adding a racetrack ring to restrain electric field intensity at high‐voltage end of composite insulator, the temperature rise in high‐humidity areas can be effectively reduced.

The Ubiquitous Power Internet of Things (UPIoT) is a concrete manifestation of the Internet of things (IoT) in the power industry, which is a deep integration of the interconnected power network and communication network, realizing full perception of the system status and full business penetration in all links of power production, transmission, and consumption. The introduction of edge computing in UPIoT fully meets the requirements of rapid response, real-time perception, and to some extent, privacy protection. However, there is currently no comprehensive investigation on the application of edge computing technology in UPIoT. First, this paper introduces the development background and construction of UPIoT and its technical architecture. Then the challenges faced by UPIoT in the process of construction are analyzed. Furthermore, the paper elaborates on the functions and features of edge computing, proposes that the support of edge computing technology can solve the challenges of efficient, fast, and secure processing of massive edge data faced by the traditional cloud-based centralized big data processing technology of UPIoT, and analyzes the architecture of the edge computing-assisted UPIoT. For the three typical scenarios of UPIoT, namely power monitoring system, smart energy system and power metering system, the edge computing architecture of the three scenarios are analyzed, and the specific application methods and roles played by edge computing in the three scenarios are also elaborated. Finally, we discuss the challenges of edge computing in UPIoT, in terms of policy challenges, market challenges, and technical challenges, as well as outline the outlooks of the technical challenges.

Abstract Hematopoietic stem cell (HSC) aging, which is accompanied by reduced self-renewal ability, impaired homing, myeloid-biased differentiation, and other defects in hematopoietic reconstitution function, is a hot topic in stem cell research. Although the number of HSCs increases with age in both mice and humans, the increase cannot compensate for the defects of aged HSCs. Many studies have been performed from various perspectives to illustrate the potential mechanisms of HSC aging; however, the detailed molecular mechanisms remain unclear, blocking further exploration of aged HSC rejuvenation. To determine how aged HSC defects occur, we provide an overview of differences in the hallmarks, signaling pathways, and epigenetics of young and aged HSCs as well as of the bone marrow niche wherein HSCs reside. Notably, we summarize the very recent studies which dissect HSC aging at the single-cell level. Furthermore, we review the promising strategies for rejuvenating aged HSC functions. Considering that the incidence of many hematological malignancies is strongly associated with age, our HSC aging review delineates the association between functional changes and molecular mechanisms and may have significant clinical relevance.

In order to solve the problem of inaccurate fault location in the transmission network under some abnormal conditions, such as traveling wave location device faults, startup failure and time recording error, a novel traveling wave fault location method based on directed tree model and linear fitting is proposed. A directed tree model of the fault traveling wave transmission along the shortest path is established based on graph theory analysis of traveling wave transmission network. Two straight lines are fitted on the coordinate plane where the accurate fault location is obtained direct by coordinate information of the intersection of these two fitted straight lines (FSLs), according to the transmission characteristics of the fault traveling wave in the directed tree model. The wave velocity is used as the slope of the fitted straight line, and the influence of its uncertainty on the fault location is eliminated. The time record error points of the location device are automatically eliminated in the linear fitting. PSCAD simulation results prove that fault information of the entire transmission network is comprehensively utilized by the proposed method and the ring network is automatically unlooped. The reliability and accuracy of fault location are remarkably improved, particularly for the fault scenarios with recorded information abnormity.

In order to achieve selective ground fault protection for bus-connected Powerformers and improve the reliability of the protection scheme, this paper presents a novel stator single-line-to-ground (SLG) fault protection scheme for bus-connected Powerformers based on S-transform (ST) and bagging ensemble learning algorithm. The scheme utilizes ST to decompose the zero-sequence current signals acquired from the Powerformer terminal to obtain the amplitude-time-frequency matrix. Then, fault features extraction is presented, and three features including the transient energy, the comprehensive correlation coefficient, and the zero-sequence active power are discussed and selected as feature vectors. The calculated data set is then extracted from feature vectors and used as inputs to the bagging ensemble learning algorithm to detect faults. Simulation results have shown that, under different fault conditions, the novel scheme can detect in which Powerformer a stator SLG fault is occurring and can detect internal faults from external faults reliably even if the fault resistance is at 8000 Ω. The proposed protection scheme does not need to set the threshold value and has noise-tolerant ability. Furthermore, the proposed technique performs better than support vector machine (SVM), random forest (RF) and k-Nearest Neighbor (KNN) techniques in detecting faults.

Graft-versus-host disease (GVHD) remains the major cause of mortality and morbidity in non-relapse patients after allogeneic hematopoietic cell transplantation (allo-HCT). As the number of patients undergoing allo-HCT increases, it will become imperative to determine safe and effective treatment options for patients with GVHD, especially those who become refractory to systemic steroid therapy. Daratumumab (Dara), a humanized IgG1 (ĸ subclass) monoclonal antibody targeting the CD38 epitope, is used for the treatment of multiple myeloma. CD38 is a multifunctional ectoenzyme that behaves either as an enzyme, a cell adhesion molecule or a cell surface receptor involved in cell signaling. CD38 is also expressed on various immune effector and suppressor cells. However, the role of CD38 in the immune response remains elusive. We questioned whether CD38 is a potential therapeutic target against alloreactive T cells in the GVHD pathological process. Here, we investigated the impact of Dara on xenogeneic GVHD (xeno-GVHD) and graft-versus-leukemia (GVL) effects in a humanized murine model of transplantation, where human peripheral blood mononuclear cells were adoptively transplanted into immunocompromised NOD.SCID.gc-null (NSG) mice. Mice receiving Dara treatment experienced less weight loss, longer survival and lower GVHD scores compared with those in the control group. Histological evaluations, flow cytometry, RNA-sequencing and RT-qPCR analysis revealed that Dara efficaciously mitigated GVHD through multiple mechanisms including inhibition of the proliferation, activation and differentiation of CD8+ cytotoxic T cells, reduced expression of cytotoxic effector molecules, pro-inflammatory cytokines, chemokines and chemoattractant receptors by T cells and promotion of immunosuppressive T cells. More importantly, Dara preserved the GVL effect in a humanized mouse model of leukemia by metabolic reprograming of T cells to promote the induction of Th17, Th1/17and Tc1/17 cells. Our findings indicate that Dara may be an attractive therapeutic option to separate GVHD from GVL effects in patients with hematopoietic malignancies receiving allo-HCT.

Field electron emission vacuum photodiode is promising for converting free-space electromagnetic radiation into electronic signal within an ultrafast timescale due to the ballistic electron transport in its vacuum channel. However, the low photoelectric conversion efficiency still hinders the popularity of vacuum photodiode. Here, we report an on-chip integrated vacuum nano-photodiode constructed from a Si-tip anode and a single-crystal CsPbBr3 cathode with a nano-separation of ~30 nm. Benefiting from the nanoscale vacuum channel and the high surface work function of the CsPbBr3 (4.55 eV), the vacuum nano-photodiode exhibits a low driving voltage of 15 V with an ultra-low dark current (50 pA). The vacuum nano-photodiode demonstrates a high photo responsivity (1.75 AW−1@15 V) under the illumination of a 532-nm laser light. The estimated external quantum efficiency is up to 400%. The electrostatic field simulation indicates that the CsPbBr3 cathode can be totally depleted at an optimal thickness. The large built-in electric field in the depletion region facilitates the dissociation of photoexcited electron–hole pairs, leading to an enhanced photoelectric conversion efficiency. Moreover, the voltage drop in the vacuum channel increases due to the photoconductive effect, which is beneficial to the narrowing of the vacuum barrier for more efficient electron tunneling. This device shows great promise for the development of highly sensitive perovskite-based vacuum opto-electronics.

Hematopoietic stem cell (HSC) aging, which is accompanied by loss of self-renewal capacity, myeloid-biased differentiation and increased risks of hematopoietic malignancies, is an important focus in stem cell research. However, the mechanisms underlying HSC aging have not been fully elucidated. In the present study, we integrated 3 independent single-cell transcriptome datasets of HSCs together and identified Stat3 and Ifngr1 as two markers of apoptosis-biased and inflammatory aged HSCs. Besides, common differentially expressed genes (DEGs) between young and aged HSCs were identified and further validated by quantitative RT-PCR. Functional enrichment analysis revealed that these DEGs were predominantly involved in the cell cycle and the tumor necrosis factor (TNF) signaling pathway. We further found that the Skp2-induced signaling pathway (Skp2→Cip1→CycA/CDK2→DP-1) contributed to a rapid transition through G1 phase in aged HSCs. In addition, analysis of the extrinsic alterations on HSC aging revealed the increased expression levels of inflammatory genes in bone marrow microenvironment. Colony formation unit assays showed that inflammatory cytokines promoted cellular senescence and that blockade of inflammatory pathway markedly rejuvenated aged HSC functions and increased B cell output. Collectively, our study elucidated the biological characteristics of HSC aging, and the genes and pathways we identified could be potential biomarkers and targets for the identification and rejuvenation of aged HSCs.

Lightning strikes are the significant cause of transient, faults, and outages in electric power transmission and distribution systems. The double-exponential function is proposed to simulate the decaying part of the measured lightning current. The transient characteristic difference (such as the gradient and waveform) between the common fault current and the lightning fault current is described in this paper. Thus, the criterion, which is to compare the peak value of transient current with the amplitude of transient current at the following 200 μs, is proposed to distinguish the short-circuit fault and the lightning stroke fault. The traveling wave location method, which uses the estimated residuals by the Kalman filter based on maximum likelihood (KF-ML), has been proposed for lightning location and fault location in various conditions, such as different lightning points, different fault points, and different lightning sides. The estimated residuals exhibit the sharp singularity when traveling wave front arrives. Thus, the lightning side and the fault side can be differentiated by comparing the time when the initial traveling wave reaches the two substations. Also, the lightning distance can be calculated by the time when the initial lightning traveling wave surge reaches the substations M and N, and the fault distance can be obtained by the time of lightning initial traveling wave arriving at the fault side and the reflection wave from fault point which gets from the lightning side. The effectiveness of exacting mutation feature using the proposed method has been demonstrated by the simulated lightning current and has also been tested with the accuracy of lightning location and fault location under various conditions.

Widely known for self-renewal and multilineage differentiation, stem cells can be differentiated into all specialized tissues and cells in the body. In the past few years, a number of researchers have focused on deriving hematopoietic stem cells (HSCs) from pluripotent stem cells (PSCs) as alternative sources for clinic. Existing findings demonstrated that it is feasible to obtain HSCs and certain mature blood lineages from PSCs, except for several issues to be addressed. This short review outlines the technologies used for hematopoietic differentiation in recent years. In addition, the therapeutic value of PSCs as a potential source of various blood cells is also discussed as well as its challenges and directions in future clinical applications.

Legacy protection schemes face new challenges as Inverter Interfaced Distribution Generation (IIDG) significantly changes the transient fault response of the distribution grid. The performance of the protection near the IIDG side is adversely affected by Low Voltage Ride Through (LVRT) and the negative sequence current suppression control characteristics of the IIDG. The operational characteristics of the protection are very different from those of the legacy protection schemes used in the distribution grid. Traditional overcurrent protection schemes cannot meet the requirements of selectivity and sensitivity. This paper analyses the influence of the IIDG on the protection schemes used in the distribution grid. Based on the positive sequence voltage polarization impedance criterion this study proposes a polarizing impedance criterion based on the fault component of positive sequence voltage, which can adaptively follow the fault resistance variation to satisfy the requirements of grid operation. The simulation results show that: (a) the proposed criterion is immune to the adverse effects of the transient characteristics of the IIDG; and, (b) it can adaptively follow the change of fault resistance making it suitable for application in short distribution lines. Using specialized System-on-Chip technology, a new distance protection device has been developed and tested on an industrial site. Simulation results and field tests showed that the new distance protection meets the requirements of the distribution grid with IIDGs.

Abstract Cloud computing technology is used in traveling wave fault location, which establishes a new technology platform for multi-terminal traveling wave fault location in complicated power systems. In this paper, multi-terminal traveling wave fault location network is developed, and massive data storage, management, and algorithm realization are implemented in the cloud computing platform. Based on network topology structure, the section connecting points for any lines and corresponding detection placement in the loop are determined first. The loop is divided into different sections, in which the shortest transmission path for any of the fault points is directly and uniquely obtained. In order to minimize the number of traveling wave acquisition unit (TWU), multi-objective optimal configuration model for TWU is then set up based on network full observability. Finally, according to the TWU distribution, fault section can be located by using temporal correlation, and the final fault location point can be precisely calculated by fusing all the times recorded in TWU. PSCAD/EMTDC simulation results show that the proposed method can quickly, accurately, and reliably locate the fault point under limited TWU with optimal placement.

Abstract Purpose To investigate the effect of tanshinone IIA (TIIA) on ventricular remodeling in rats with pressure overload-induced heart failure. Methods Pressure overload-induced heart failure model (abdominal aortic coarctation) was established in 40 rats, which were divided into model and 5, 10 and 20 mg/kg TIIA groups. Ten rats receiving laparotomy excepting abdominal aortic coarctation were enrolled in sham-operated group. The 5, 10 and 20 mg/kg TIIA groups were treated with 5, 10 and 20 mg/kg TIIA, respectively, for 8 weeks. Results Compared with model group, in 20 mg/kg TIIA group the left ventricular ejection fraction, left ventricular fractional shortening, left ventricular systolic pressure, ±maximum left ventricular pressure rising and dropping rate, and myocardial B-cell lymphoma-2 and cleaved cysteinyl aspartate specific proteinase-3 protein levels were increased, respectively (P

Electric vehicles (EVs) will play a vital role in the future's transportation systems since this technology is promising for environment, energy security, and improved fuel economy. EVs have huge potential of serving as the energy storage for the power grid as well as inhabitants in vehicle-to-grid (V2G) or vehicle-to-house (V2H) scenario. In this study, a control method is proposed for EV charging and discharging by using the synchronverter technology and H^∞ repetitive controller, where synchronverter technology is used to generate the reference voltage to decide the power angle and amplitude of the AC side voltage of the charging/discharging port, so that the power flow between EV and the grid is controlled. In order to ensure the power quality of EVs provided for the grid and the load while EVs are with local loads, a H^∞ repetitive controller is designed to control the voltage between EVs and the grid to follow the reference voltage. Simulation results have shown that the proposed controller is not only able to realise bi-directional real power and reactive power control, but also keep the output voltage of EVs in V2G or V2H scenario stable and clear while they are with different kinds of local loads.

The asymmetric faults often cause the power grid current imbalance and power grid oscillation, which brings great instability risk to the power grid. To address this problem, this paper presented a modeling and parameter optimization method of grid-connected photovoltaic (PV) systems, considering the low voltage ride-through (LVRT) control. The harmonics of the grid current under asymmetric faults were analyzed based on the negative-sequence voltage feedforward control method. The notch filter was added to the voltage loop to filter out the harmonic components of the DC bus voltage and reduce the harmonic contents of the given grid current value. The proportional resonant (PR) controller was added to the current loop. The combination of these two components could reduce the 3rd, 5th, and 7th harmonics of the grid current and the output power fluctuation. Then, the parameters of the inverter controller were identified by the adaptive differential evolution (ADE) algorithm based on the sensitivity analysis. The effectiveness of the proposed method was compared with two other strategies under the asymmetric grid faults. The suppression of DC bus voltage fluctuation, power fluctuation, and low-order harmonics of the grid current all had better results, ensuring the safe and stable operation of the PV plant under grid faults.

Background/Aims: Epoxyeicosatrienoic acids (EETs), a type of lipid mediators produced by cytochrome P450 epoxygenases, exert anti-inflammatory, angiogenic, anti-oxidative and anti-apoptotic effects. However, the role of EETs in cigarette smoke-induced lung injury and the underlying mechanisms are not fully known. The aim of this study was to explore the effects of CYP2J2-EETs on cigarette smoke extracts (CSE)-induced apoptosis in human bronchial epithelial cell line (Beas-2B) and the possible mechanisms involved. Methods: Cytochrome P450 epoxygenase 2J2 (CYP2J2) and its metabolites EETs were assessed by western blotting or LC-MS-MS. Cell viability and apoptosis were determined by MTT assay and AnnexinV-PI staining. Reactive oxygen species (ROS) were assessed by measuring H2DCFDA. Caspase-3, HO-1, MAPK and endoplasmic reticulum (ER) stress-related markers GRP78, p-elF2a, and CHOP were evaluated by western blotting. Results: CSE suppressed expression of both CYP2J2 and EET by Beas-2B cells. CSE also induced apoptosis, the generation of ROS and the ER stress in Beas-2B cells. These changes were abolished by pretreatment with exogenous 14,15-EET while pretreatment with 14,15-EEZE, a selective EET antagonist, abolished the protective effects of 14,15-EET. In addition, EETs increased the expression of antioxidant enzyme HO-1. Furthermore, 14,15-EET reduced CSE-induced activation of p38 and JNK. Conclusion: The data suggest that CYP2J2-derived EETs protect against CSE-induced lung injury possibly through attenuating ER stress.

Sm-doped BiFeO3 (BFO) material was prepared using a modified solid-state-reaction method, which used fast heating and cooling during the sintering process. The Sm doping level varied between 1 mol % to 8 mol %. Processing parameters, such as sintering temperature and annealing temperature, were optimized to obtain high-quality samples. Based on their dielectric properties, the optimum sintering and annealing temperatures were found to be 300 °C and 825 °C, respectively. Leakage-free square-shaped ferroelectric hysteresis loops were observed in all samples. The remnant polarization was maximized in the 5 mol %-doped sample (~35 μC/cm2). Furthermore, remnant magnetization was increased after the Sm doping and the 8 mol%-doped sample possessed the largest remnant magnetization of 0.007 emu/g. Our results demonstrated how the modified solid-state-reaction method proved to be an effective method for preparing high-quality BiFeO3 ceramics, as well as how the Sm dopant can efficiently improve ferroelectric and magnetic properties.

Severe myocardial dysfunction and tissue damage resulting from ischemia/reperfusion (I/R) is a common clinical scenario in patients with certain types of heart diseases and therapies such as thrombolysis, percutaneous coronary intervention, coronary artery bypass grafting, and cardiac transplantation. The underlining mechanism of endogenous cardiac protection after I/R injury has been a focus of current research. Growing evidences suggests that soluble receptor for advanced glycation end-products (sRAGE) has a cardioprotective effect; however, its role in I/R injury remains unclear. We hypothesized that exogenous administration of sRAGE during hypoxia/reoxygenation (H/R) induces cardioprotection by inhibiting cardiomyocyte apoptosis via multiple signals, involving mitochondrial membrane potential (MMP), the mitochondrial permeability transition pore (mPTP), mitochondrial cytochrome c, caspase-3, Bcl-2 and Bax. Neonatal rat cardiomyocytes underwent hypoxia for 3-h followed by 2-h reoxygenation or were treated with sRAGE for 10 min before H/R. Compared with H/R alone, sRAGE pretreatment reduced H/R-induced cardiomyocyte apoptosis from 27.9% ± 5.9% to 9.4% ± 0.7% (p < 0.05). In addition, sRAGE treatment significantly inhibited H/R-induced mitochondrial depolarization and mPTP opening, reduced mitochondrial cytochrome c leakage, caspase-3 and caspase-9 activity, and decreased the ratio of Bax to Bcl-2. Therefore, we conclude that the exogenous administration of sRAGE during H/R is involved in cardioprotection by inhibiting apoptosis via the mitochondrial pathway, which, if further confirmed in vivo, may have important clinical implications during H/R.

With the increasing interaction between physical devices and communication components, the substation based on the IEC 61850 standard is a type of cyber–physical system. This paper proposes a reliability analysis method for substations with a cyber–physical interface matrix (CPIM). This method calculates the influences from both the physical device failures and the communication devices failures. Two indices, Probability of Load Curtailments and Expected Demand Not Supplied, are used in the reliability analysis. Given the simplified model of the practical substation based on the Chinese IEC 61850 standard, the results show that the substation system had a potential risk of cascading failure under the cyber–physical fusion trend, as the failure in cyber layer would increase the power loss of the whole system. The changing magnitude of Expected Demand Not Supplied increased significantly with increasing transmission delay rate of the process bus.