Search

In this paper, a fault detection and isolation technique for series arc faults in dc microgrids with multiple power electronics loads is proposed using Unknown Input Observers (UIO). The dc microgrid is first modeled as a linear system using its corresponding graph information, including the oriented incidence matrix. The lines are assumed to be in Pi form (resistive, inductive, and capacitive) defining the dynamic states: line currents and node voltages. Sources and loads are considered inputs to the network and details are presented to include the case where these are not measured. DC series arc faults are then analyzed as disturbances affecting any line. An UIO framework is then presented to detect and identify the faulted line using the network model. Simulation and experimental results are then presented.

Araneid spider silk glands can spin seven silk types that have task-specific properties owing to the higher order structure of spider silk proteins. This gives silks superior potential as novel biomaterials. Nephila pilipes, the giant golden orb-weaver, is one of the largest spiders and spins silk with exceptional torsional deformation, toughness, and other properties to support its mass; further investigation relies on a complete amino acid sequence. However, there are no full-length N. pilipes spidroin sequences; in fact, across species, most sequences remain fragmentary because of repetitive region assembly difficulties in short-read sequencing. Here, we develop a hybrid sequencing method that utilizes short-read sequencing to identify seven spidroin terminals in N. pilipes, and long-read sequencing to confirm the full-length pyriform spidroin 1 (PySp1) gene. PySp1 is 11,181 base pairs, with a single exon encoding a 3,726 amino acid protein, the QQ(x)

Objective The treatment of patients with primary Sjogren's syndrome is a clinical challenge. Gene expression profile analysis and comprehensive network methods for complex diseases can provide insight into molecular characteristics in the clinical context. Materials and methods We downloaded gene expression datasets from the Gene Expression Omnibus (GEO) database. We screened differentially expressed genes (DEG) between the pSS patients and the controls by the robust rank aggregation (RRA) method. We explored DEGs' potential function using gene function annotation and PPI network analysis. Results GSE23117, GSE40611, GSE80805, and GSE127952 were included, including 38 patients and 30 controls. The RRA integrated analysis determined 294 significant DEGs (241 upregulated and 53 down-regulated), and the most significant gene aberrantly expressed in SS was CXCL9 (P-value = 6.39E-15), followed by CXCL13 (P-value = 1.53E-13). Immune response (GO:0006955; P-value = 4.29E-32) was the most significantly enriched biological process in GO (gene ontology) analysis. KEGG pathway enrichment analysis showed that cytokine-cytokine receptor interaction (hsa04060; P-value = 6.46E-10) and chemokine signaling pathway (hsa04062; P-value = 9.54E-09) were significantly enriched. We defined PTPRC, CD86, and LCP2 as the hub genes based on the PPI results. Conclusion Our integrated analysis identified gene signatures and helped understand molecular changes in pSS.

Osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs) is an essential stage in bone formation. Autophagy plays a pivotal role in the self-renewal potential and pluripotency of stem cells. This study aimed to explore the function of autophagy-related genes during osteogenic differentiation of BMSCs.The differentially expressed autophagy-related genes (ARGs) were obtained from the GEO and HADb databases. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed using R software. The PPI and hub gene mining networks were constructed using the STRING database and Cytoscape. Finally, the RT-qPCR was conducted to validate the expression level of ARGs in BMSCs.Thirty-seven differentially expressed ARGs were finally obtained, including 12 upregulated and 25 downregulated genes. GO and KEGG enrichment analysis showed that most of these genes were enriched in apoptosis and autophagy. The PPI network revealed strong interactions between differentially expressed ARGs. The expression level of differentially expressed ARGs tested by RT-qPCR showed 6 upregulated ARGs, includingWe identified 37 ARGs during osteogenic differentiation using bioinformatics analysis. FOXO1, MAP1LC3C, CTSB, FOXO3, CALCOCO2, FKBP1A, MAPK8IP1, NRG1, VEGFA, and ITGA6 may regulate osteogenic differentiation of hBMSCs by involving autophagy pathway. This study provides new insight into the osteogenic differentiation of hBMSCs and may be available in developing therapeutic strategies for maxillofacial bone defects.

This study presents experimental results on the influence of cellulose particles on the breakdown characteristics of transformer oil in a highly non-uniform field under lightning impulse voltage. The experimental results show that as the particle content increases, the breakdown voltage reduces with little change in the breakdown time lag. At the same cellulose particle content, the oil breakdown voltage under oscillating lightning impulse (OLI) is lower than that under standard lightning impulse (SLI) and the breakdown time lag under OLI is longer than that under SLI. The impulse wave oscillation has a large effect on the accumulation of particles around the high voltage electrode and cellulose particles affect the development of the streamer process. At mid to high particle content the accumulation of particles around the high voltage electrode causes a decrease in the conductivity of the surrounding oil. This work contributes to the understanding of the effect of cellulose particles in oil and breakdown and on oscillating waveforms and provides guidance for lightning impulse tests on oil-immersed power transformers in the field.

Accumulating evidence shows that pleomorphic adenoma (PA) exhibits a unique capsular invasion and with a crucial role in recurrence. This study was designed to explore RNA expression profiles in salivary gland PA in an attempt to further analyse genes associate with capsule invasion.We evaluated the expression profiles of 4 salivary gland PA patients by RNA-sequencing. The principal functions of the differentially expressed mRNAs (DEGs) were explored using GO and KEGG analysis. Then, RT-qPCR and correlation analyses were performed to verify the candidate DEGs in 59 PA patients, and immunohistochemical examinations were conducted to validate candidate DEGs. Finally, the COMP-related genes were screened using correlation and biological pathway enrichment analysis, and further validated by RT-qPCR.A total of 974 DEGs were significantly upregulated, and 1464 were downregulated (fold change ≥2.0; p 0.05). Based on GO and KEGG analyses, extracellular matrix organization and the PI3K-Akt signalling pathway might play pivotal roles in the tumorigenesis of PA. 40 DEGs were screened and validated by RT-qPCR, 11 upregulated and 5 downregulated DEGs were consistent with the sequencing results. Cartilage oligomeric matrix protein (COMP) was identified to have a significant correlation with the capsular invasion of PA and expression of COMP in patients with invasive capsular PA was significantly stronger than PA. Finally, further results could reveal that 5 highest scoring genes were screened as hub genes for COMP.These findings suggested that COMP may be a prognostic target for PA and might contribute to its capsular invasion.

Series dc arc fault creates a fire hazard and negative impacts on the distribution bus if not detected and isolated quickly. However, the detection of a series arc fault is challenging due to the low fault current, lack of zero-crossing, and the erratic behavior of arc discharge based on different power electronic loads and controllers in modern power applications. This article presents a practical and versatile series dc arc fault detection method based on ensemble machine learning (EML) algorithms. A buck converter constant power load (CPL) and a boost converter CPL are designed and built to study the different arc fault behaviors and generate training data for the machine learning algorithms. A set of time domain features is extracted from the experimental data and analyzed using the feature importance attribute. An adaptive normalization function then processed the features to mitigate false positive classification caused by load changes. A two-step algorithm is proposed to recognize the arc fault in different load types. Various EML algorithms and the associated hyperparameters are benchmarked to select the most accurate hyperparameters for a detection algorithm for low-cost hardware implementation. Finally, the detection algorithm's effectiveness is verified with CPL testbed.

Objective: This study aimed to explore the regulatory mechanism of miR-139-5p on the biological characteristics of breast cancer cells by targeting Collagen type XI alpha 1 chain (COL11A1). Method: GEO2R was used to identify the differentially expressed genes (DEGs) of breast cancer in GEO database. miRDB, miRanda and TargetScan databases were used to predict the miRNAs that regulate COL11A1. qRT-PCR was used to detect the expressions of COL11A1 and miR-139-5p in breast cancer cells, and western blot was used to detect the protein level of COL11A1. RNA binding protein immunoprecipitation assay was employed to test the targeted relationship between miR-139-5p and COL11A1, which was further verified by dual-luciferase reporter gene assay. CCK-8 assay was performed to detect the cell proliferation, and flow cytometry was carried out to examine the cell apoptosis. Moreover, western blot was used for the detection of caspase-3, Bax and Bcl-2 protein levels. Results: A total of five DEGs were screened from the GEO database, of which COL11A1 was the only highly expressed in breast cancer. According to the database analysis, we predicted that miR-139-5p was much likely to target the expression of COL11A1. MiR-139-5p was poorly expressed in breast cancer cells and targeted inhibited COL11A1. Silencing COL11A1 or overexpressing miR-139-5p both could inhibit the proliferation and promote the apoptosis, while overexpressing the two factors simultaneously could reverse such effect. Conclusion: Overexpression of miR-139-5p inhibits the proliferation and promotes the apoptosis of breast cancer cells by inhibiting the expression of COL11A1.

Partial discharge (PD) in gas insulated switchgear (GIS) has been studied extensively under AC voltage or transient voltage applied alone. However, the transient voltage in an actual system is superimposed on the AC operating voltage, which has rarely been studied. In this paper, the effect of AC and switching impulse superimposed voltage on PD characteristics was studied in SF6 gas. A test platform of generating superimposed voltage with controllable phase was used to study free particle and floating potential defect models. When the AC voltage was 90 and 110% of PD inception voltage (PDIV), the standard switching impulse with amplitude of about twice the PDIV was superimposed on different phases of the AC voltage. When the AC voltage is below the PDIV, results show that PDs of free particle defect model can be initiated when switching impulse is superimposed on 45 and 90° of AC. The PDs in the subsequent cycles of AC reignited into a self-sustaining discharge. For the floating potential defect, PDs have a marked difference duration, which is initiated by switching impulse in different phase. However, there is no change in PDs in each model when the AC voltage is above the PDIV.

In this paper we explore the problem of series arc fault detection and localization on dc microgrids. Through a statistical model of the microgrid obtained by nodal equation, the injection currents are modeled as a random vector whose distribution depends on the nodal voltages and the admittance matrix. A series arc fault causes a change in the admittance matrix, which further leads to a change in the data generating distribution of injection currents. The goal is to detect and localize faults on different lines in a timely fashion subject to false alarm constraints. The model is formulated as a quickest change detection problem, and the classical Cumulative Sum algorithm (CUSUM) is employed. The proposed framework is tested on a dc microgrid with active (constant power) loads. Furthermore, a case considering fault detection in the presence of an internal node is presented. Finally, we present an experimental result on a four node dc microgrid to verify the practical application of our approach.

We investigated the effects of tea plantation age on soil microbial community structure and diversity with surface and subsurface soil samples (0-20 and 20-40 cm) from tea plantation at different ages (0, 20, 25, 38 and 48 years). We analyzed soil bacterial and fungal communities by terminal restriction fragment length polymorphism (T-RFLP) and real-time quantitative PCR techniques. The results showed that soil physicochemical properties changed significantly after planting tea. The contents of soil organic carbon, available nitrogen, and available phosphorus increased at first, and gradually decreased with the increases of tea plantation age. The contents of organic carbon and total nitrogen in the topsoil were significantly higher than those in the subsoil. Moreover, soil bacterial community composition varied across tea plantation age. Bacterial diversity index decreased with increasing tea plantation age. The composition and diversity of soil fungal communities did not show a clear relationship with the tea plantation age. Overall, soil bacterial communities was more sensitive to the tea plantation age than fungal communities. With the increases of tea plantation age, the ratio of soil fungi to bacteria showed increasing trend. Soil microbial community in the tea plantation changed from a "bacterial type" with low fungi/bacteria ratio (F/B) to a "fungal type" with high F/B.为探明植茶年限对土壤微生物群落结构及多样性的影响,以0、20、25、38和48年茶园土壤表层(0～20 cm)、亚表层(20～40 cm)土壤样品为研究对象,采用T-RFLP技术及qPCR方法对土壤细菌(B)、真菌(F)群落进行分析。结果表明: 植茶后土壤理化性质明显改变,随植茶年限的增加土壤有机碳、碱解氮及有效磷含量呈先升高后降低的趋势,表层土壤有机碳和全氮含量均显著高于亚表层土壤。不同植茶年限土壤细菌群落组分存在差异且多样性指数随植茶年限的增加呈下降趋势,而不同植茶年限土壤真菌群落组分差异不明显且多样性指数无显著差异。总体来看,土壤细菌群落对植茶年限的响应比真菌群落敏感。随植茶年限的增加,茶园土壤微生物群落有从F/B较低的“细菌型”向F/B较高的“真菌型”转变的趋势。.

Background The application of calcium phosphate (CaP)-based bone substitutes plays an important role in periodontal regeneration, implant dentistry and alveolar bone reconstruction. The incorporation of strontium (Sr) into CaP-based bone substitutes appears to improve their biological properties, but the reported in vivo bone repair performance is inconsistent among studies. Herein, we conducted a systematic review and meta-analysis to investigate the in vivo performance of Sr-doped materials. Methods We searched PubMed, EMBASE (via OVIDSP), and reference lists to identify relevant animal studies. The search, study selection, and data extraction were performed independently by two investigators. Meta-analyses and sub-group analyses were conducted using Revman version 5.4.1. The heterogeneity between studies were assessed by I2. Publication bias was investigated through a funnel plot. Results Thirty-five studies were finally enrolled, of which 16 articles that reported on new bone formation (NBF) were included in the meta-analysis, covering 31 comparisons and 445 defects. The overall effect for NBF was 2.25 (95% CI 1.61–2.90, p 2 = 80%). Eight comparisons from 6 studies reported the outcomes of bone volume/tissue volume (BV/TV), with an overall effect of 1.42 (95% CI 0.65–2.18, p = 0.0003, I2 = 75%). Fourteen comparisons reported on the material remaining (RM), with the overall effect being -2.26 (95% CI − 4.02 to − 0.50, p = 0.0009, I2 = 86%). Conclusions Our study revealed that Sr-doped calcium phosphate bone substitutes improved in vivo performance of bone repair. However, more studies are also recommended to further verify this conclusion.

Stacking devices in series allows to achieve higher blocking voltage in power applications. However, an unequal voltage sharing issue among devices is critical which may lead to failure of the devices. The unbalance can be caused by different device characteristics and mismatch of gate signals due to different parasitic components of circuits. In this paper, a dv/dt control method with the active gate driver (AGD) is proposed for voltage balancing of stacked SiC MOSFETs. The dv/dt is actively controlled by modulating the turn-off gate resistance (R off ) during turn-off transient. The proposed method is experimentally validated by achieving voltage balancing with six series connected SiC MOSFETs at 3 kV dc voltage.

In this letter, a test platform capable of generating superimposed voltage with controllable phase is presented. Surface partial discharge(PD) of epoxy insulation was measured and analyzed in SF6. The applied voltage is AC and switching impulse superimposed voltage. Results show that only PD of the negative cycles of the AC voltage is excited or accelerated after impulse. With AC voltage at 90% of partial discharge inception voltage(PDIV), AC PDIV is reduced after imposing the switching impulse. When AC voltage is kept at 110% of PDIV, AC PDs are obviously promoted after impulse.

A cavity is a typical defect in a solid insulator which may cause the appearance of partial discharge (PD) activity in power equipment [1–4]. It is mainly caused by imperfections in the manufacturing process as well as by the creep during equipment operation [5]. In epoxy resin insulators, the creep brings irreversible deformations that increase with time at elevated temperatures and external stress [6,7]. Once a cavity has been formed, the PD can lead to insulation failure. Many studies on PDs in void defects, a type of gas-filled cavity, have been performed by pasting together three epoxy laminates and demonstrated factors that affect their intensity, including void size, shape and interface roughness [8–12]. However, such a test void is quite different in its structure and composition from what we further consider in this article, i.e., cavities appearing during actual insulator operation. Moreover, the pressure in a real cavity is usually very low, because of air leakage and polymerization shrinkage, whereas the test void typically remains under atmospheric pressure. Considering the above mentioned differences, we prepared experimental model insulators, containing various low-pressure cavities. The insulators were manufactured by means of automatic pressure gelation (APG) technique by changing the pressure and temperature during the resin pouring process, which allowed for simulating a more realistic operating environment.

Magnolia sinostellata Chiu & Chen is a rare and endangered species endemic to subtropical China. Here we assembled and annotated the complete chloroplast (cp) genome of M. sinostellata. The chloroplast genome of M. sinostellata is 160,076 bp in length and encodes 79 protein-coding genes, 30 transfer RNA (tRNA) genes and four ribosomal RNA (rRNA) genes. The maximum-likelihood (ML) phylogenetic analysis result reveals that M. sinostellata is most closely related to M. biondii.

We conducted a pot experiment to investigate the effects of planting broadleaf tree species (i.e.,为探明种植阔叶树种和毛竹对土壤有机碳矿化与微生物群落特征的影响,本研究通过盆栽试验和室内培养法比较分析种植香樟、木荷、青冈等阔叶树种与毛竹的土壤有机碳矿化速率和累计矿化量,并结合末端限制性片段长度多态性(T-RFLP)以及荧光定量PCR技术,分析土壤细菌、真菌群落组分与数量特征。结果表明: 与种植阔叶树种的土壤相比,种植毛竹的土壤活性碳组分和碳矿化总量显著提高,且其地下生物量高于阔叶树种。种植毛竹的土壤真菌/细菌丰度比也高于种植阔叶树种的土壤,土壤细菌群落组分对树种的响应比真菌群落更加敏感。种植毛竹的土壤真菌群落多样性显著低于阔叶树种;与细菌群落相比,真菌群落多样性与pH、有机碳含量、碳矿化速率更为相关。与阔叶树种相比,种植毛竹能显著增加土壤碳矿化总量,而毛竹土壤真菌群落结构是导致碳矿化量较高的原因之一。.

Device series connection is a method to achieve higher blocking voltage with multiple devices. However, a voltage unbalance among the series connected devices is a critical issue that may lead to a failure of the devices. The unbalance can be caused by difference of device characteristics and mismatch of gate signals due to delay of external gate drive circuit. In this work, a voltage balancing control (VBC) for series connected SiC MOSFET submodules is studied to solve the unbalance issue. One submodule consists of two switches and one shunt capacitor. By charging or discharging the shunt capacitor, voltage balancing can be achieved. The VBC is experimentally verified with four series connected SiC MOSFET submodules up to 3 kV DC voltage. Voltage balancing is achieved within 5 % of an expected balanced voltage.

Series dc arc fault detection and localization in the modern power electronics system that comprises multiple loads is a difficult task due to the arcing noise cross-talk. The arcing noises can propagate to the adjacent loads and mistrigger the detector units. This paper proposes a master controller to compare all the Random Forest (RF) based detector units’ predicted class probabilities for arc fault detection and localization. The predicted probability comes from one of the RF’s attributes, where the largest probability becomes the final decision. The master controller also sends out a control signal to create synchronization between detectors. This step arranges the detectors to monitor all input currents simultaneously, and provide predicted probability correlation accurately. The master controller capability was emulated and verified using an experimental testbed of two parallel- connected constant power loads.

One major challenge regarding series-connected IGBTs is the protection against over-current faults, besides voltage balancing among the devices. In this paper, an over-current protection method based on desaturation detection is proposed for series-connected IGBTs which are controlled by a digital signal processor (DSP) to realize voltage sharing. A hardware test platform was built, which is capable of generating current spikes of various magnitudes and durations. Different aspects of system behavior under fault are characterized to provide design guidance to ensure safety. Finally, experimental results show that the proposed series IGBT control can achieve voltage balance without slowing down the switching transients. Additionally, the desaturation circuit can detect an over-current in less than 1 μs. Furthermore, with the proposed protection method, the fault can be fully cleared depending solely on voltage balancing circuits, while maintaining voltage balance during the entire process.

In this paper, a detection and localization technique based on dual State and Parameter Estimation (SE and PE respectively) for series dc arc faults is presented. Detection of series arc faults in dc microgrids is challenging due to its low fault current. By using the available set of sensor measurement data over a period of time, a Least Squares (LS) based SE algorithm estimates the dc microgrid’s bus voltages and injection currents. Kalman Filter (KF) is then used to estimate the line conductances in the network, which are used to detect and localize (with respect to the faulted line) the series arc fault. Simulation results are presented with different case studies to demonstrate the robustness of the algorithm to normal operating conditions and different number and placement of sensors. Finally, Control Hardware in the Loop (CHIL) results are shown.

Objective. This study aimed to construct a 5-year survival prediction model of coronary heart disease (CHD) induced chronic heart failure (CHF), which is supported by the traditional Chinese medicine (TCM) factor, and to verify the model. Methods. Inpatients from January 1, 2012, to December 31, 2017, in seven hospitals in Shandong Province were studied. The random number table was used to randomly divide the seven hospitals into two groups (training set and verification set). In the training set, the least absolute shrinkage selection operator regression was first used to screen the independent variables. Logistic regression was then applied to construct a survival prediction model. The following nomogram visualizes the prediction model results. Finally, C-indices, calibration curves, and decision curves were used to discriminate and calibrate the established model and evaluate its practicability in the clinic. Bootstrap resampling and the verification set were used for internal and external verification, respectively. Results. A total of 424 eligible patients were included in the model construction and verification. In this 5-year survival prediction model of patients with CHF induced by CHD, eight independent predictors were included. The series of C-indices for the training set, bootstrap resamples, and verification set was 0.885, 0.867, and 0.835, respectively, demonstrating the credibility of our model. Additionally, the receiver operating characteristic curve, calibration curve, and clinical decision curve analysis of the training and verification sets showed that this 5-year survival prediction model was good in discrimination, calibration, and clinical practicability. Conclusion. This work highlights eight independent factors affecting 5-year mortality in patients with CHF induced by CHD after discharge and further helps reallocate medical resources rationally by precisely identifying high-risk groups. The constructed prediction model not only plays a credible role in prediction but also demonstrates TCM intervention as a protective factor for the 5-year death of patients with CHF induced by CHD, thereby advancing the use of TCM in CHF.

Modular multilevel converters (MMC) and series-connected IGBTs are two promising solutions to high-voltage dc (HVDC) transmission. It has been shown that, when integrated with series IGBTs, a MMC can benefit from a reduced number of sub-modules (SMs), simpler control, and improved reliability. In this paper, a MMC prototype, with the capability to integrate series IGBTs to replace single IGBTs in the sub-modules, is designed and developed. The MMC control is realized with a real-time simulator for versatile software implementation. The voltage sharing among the series IGBTs is regulated locally without the intervention of the central control. Furthermore, voltage balance under bi-directional current through the series strings is achieved. Experiments were conducted where individual IGBTs in one sub-module were replaced with a series of three IGBTs each. The results verify that the MMC is functional since the local series IGBT control and the MMC central control are independent. It is also verified that both series strings can maintain voltage balance at the same time even though the string currents shift directions.

Silicon carbide (SiC) device is expected to replace silicon (Si) device in many high voltage and power application due to potentially higher switching frequency and voltage capabilities. Even though its potential voltage capability, the highest voltage rating of a single commercial SiC MOSFET is 1.7 kV. An alternative method to achieve higher voltage is a device series connection. However, it causes a voltage unbalance issue during turn-off state that can harm the devices. Therefore, the voltage balancing control (VBC) must be considered in device series connection. In this paper, a VBC method with active gate driver (AGD) is proposed. A gate resistance modulation method with a signal time delay is adopted for dynamic voltage sharing. The proposed method is experimentally verified.

Series arc fault detection in a dc system is a challenging task due to the randomness of arc discharge and the dynamic behavior dependence on the system current level. DC arc faults could potentially create a fire hazard if not detected and isolated quickly. This paper introduces two ways to improve the predictive performance of existing conventional machine learning (ML) algorithms as an arc fault detection method. A semi-supervised ML ensures sufficient training data when there is a vast number of unlabeled data and limited labeled data. An ensemble ML method further superimposes on a conventional ML algorithm to create a better classifier, which reduces the bias and decision variance. The goal is to evaluate the effectiveness of both methods in dc arc fault detection. Accuracy, precision, and recall scores are used as the key performance metrics. Finally, an experimental arc fault detection was conducted using a microcontroller Udoo X86 with detection latency time as a performance metric.

A partial discharge (PD) detection method for SF6 insulated inverted current transformers (SIICTs) adopting an inner shield case as an ultra-high frequency (UHF) sensor is proposed in this paper. The inner shield case is a component of the SIICT. Its structure is similar to that of an antenna and can be used as a UHF sensor to measure the PD UHF signal. A 110 kV current transformer is used as an experimental object and the voltage standing-wave ratio of the inner shield case is calculated. The validity and sensitivity of this method are proved by experiments with ac voltage. This PD detection method solves the problem that the UHF sensor is difficult to mount inside current transformers and provides a novel method for PD detection of SIICTs.

Subcellular localization of proteins can provide key hints to infer their functions and structures in cells. With the breakthrough of recent molecule imaging techniques, the usage of 2D bioimages has become increasingly popular in automatically analyzing the protein subcellular location patterns. Compared with the widely used protein 1D amino acid sequence data, the images of protein distribution are more intuitive and interpretable, making the images a better choice at many applications for revealing the dynamic characteristics of proteins, such as detecting protein translocation and quantification of proteins. In this paper, we systematically reviewed the recent progresses in the field of automated image-based protein subcellular location prediction, and classified them into four categories including growing of bioimage databases, description of subcellular location distribution patterns, classification methods, and applications of the prediction systems. Besides, we also discussed some potential directions in this field.

The field impulse voltage withstand test plays one of the most important roles to ensure the safety of the gas insulated equipments. It is hard to carry out the standard impulse voltage test for the equipments because the generator is very large and difficult to transport. The oscillating impulse voltage waveform has high efficiency and has been recommended by the IEC 60060-3 as the field test waveform. SF6 gas is the insulation medium of gas insulated equipments. Its insulation characteristics under different types of impulse waveforms have great influence to the design, operation and test amplitude. This paper focuses on the breakdown characteristics of SF6 gas in a quasi-uniform field under oscillating impulse voltages (OIV). Four types of oscillating impulse lightning voltage waveforms with oscillating frequency of 100, 200, 300 and 400 kHz were adopted as the test waveforms. The standard lightning impulse (SLI) voltage was also adopted as the reference waveform. A calculation model is established to explain the results. The experiment and calculation results show that the breakdown waveforms in time domain drop quickly and then have a recovery with low amplitude to zero under OIV for the influence of circuit inductor. 50% probability breakdown voltages (BDVs0%) under OIV are higher than that under SLI. The minimum breakdown voltage and BDVs0% both increase with oscillating frequency. The voltage-time distributions show that breakdowns under OIV occur in the vicinity of each wave peak of the applied voltage. OIV have a longer time lag than SLI due to the oscillation of the waveforms.

The field impulse voltage test plays the most important role to ensure the safe of the power transformer. It is hard to carry out the standard impulse voltage test for the power equipment because the generator is very huge. The oscillating impulse voltage waveform has high efficiency and be recommended by IEC 60060-3 as the field test waveform. Transformer oil is the main insulation part of power transformer insulation system. The insulation characteristics of transformer oil under different type impulse waveform have great influence to the design, operation and test amplitude for the power transformer. This paper focuses on the breakdown characteristics of transformer oil in a uniform field under oscillating impulse voltage (OIV). Three type oscillating impulse voltage waveforms with oscillating frequency of 14, 117 and 373 kHz were adopted as the test waveforms. The standard lightning impulse (SLI) voltage was also adopted as the reference waveform. The experiment results show the breakdown waveforms have large oscillation under OIV but little oscillation under SLI for the influence of circuit inductor. The minimum breakdown voltage increase with the increase of oscillating frequency and the 117 kHz impulse waveform has the similar breakdown voltage with SLI waveform. The voltage-time distributions were obtained through lab test and the results shown that the OIV have the longer time lag than SLI for the influence of the oscillation of waveform. The experimental results were explained through streamer mechanism. The study provides the foundation for the field impulse test using oscillating impulse waveform.

HVDC transmission has been adopted widely for its large energy transport capacity, high stability and more economical in long-distance power transmission. Converter transformer is the key equipment in HVDC transmission system. The insulation of converter transformer valve side endures a composite voltage including AC, DC and pulsating component etc. Partial discharge (PD) occurring in a void surrounded by insulating material is believed to be one of the main causes of insulation breakdown and it is the main factor of electrical aging of materials. Therefore, it is important to recognize the prebreakdown phenomena and to evaluate the lifetime of insulating materials. Much research has been carried out to study the partial discharge characteristics under pure AC or DC voltage. Only a few investigations were focused on composite voltage. In order to obtain more understanding of PD characteristics under composite voltage, the PD detection and analysis of oil-pressboard insulation under pulsating DC voltage waveform are studied in this paper. The voltage waveform of converter transformer is analyzed through computer simulation. A 6-pulse DC voltage generator and PD detection system are set up. Influence of the DC component and pulsating component to the PD characteristics is studied in lab test. The experimental results show the DC component and pulsating component affect the PD inception voltage, but the pulsating component has more significant influence to PD characteristics than DC component. The study provides an experimental foundation for the converter transformer insulation breakdown mechanism analysis.