Search

The distributed observer problem is motivated by the case where the output information of the system is decentralized in different subsystems. In this scene, all the subsystems form an observer network, and each of them has access to only a part of output information and the information exchanged via the given communication networks. Due to the limitation of communication conditions among subsystems, the communication network is often time varying and disconnected. However, the existing research about the aforementioned scene is still not enough to solve this problem. To this end, this article is concerned with the challenge of the distributed observer design for linear systems under time-variant disconnected communication networks. The design method is successfully established by fixing both completely decentralized output information and incompletely decentralized output information into account. Our work overcomes the limitation of the existing results that the distributed observer can only reconstruct the full states of the underlying systems by means of fast switching. In the case of completely decentralized output information, a group of sufficient conditions is put forward for the system matrix, and it is proved that the asymptotical omniscience of the distributed observer could be achieved as long as anyone of the developed conditions is satisfied. Furthermore, unlike similar problems in multiagent systems, the systems that can meet the proposed conditions are not only stable and marginally stable systems but also some unstable systems. As for the case where the output information is not completely decentralized, the results show with the observable decomposition and states reorganization technology that the distributed observer could achieve omniscience asymptotically without any constraints on the system matrix. The validity of the proposed design method is emphasized in two numerical simulations.

An updated LncTarD 2.0 database provides a comprehensive resource on key lncRNA–target regulations, their influenced functions and lncRNA-mediated regulatory mechanisms in human diseases. LncTarD 2.0 is freely available at (http://bio-bigdata.hrbmu.edu.cn/LncTarD or https://lnctard.bio-database.com/). LncTarD 2.0 was updated with several new features, including (i) an increased number of disease-associated lncRNA entries, where the current release provides 8360 key lncRNA–target regulations, with 419 disease subtypes and 1355 lncRNAs; (ii) predicted 3312 out of 8360 lncRNA–target regulations as potential diagnostic or therapeutic biomarkers in circulating tumor cells (CTCs); (iii) addition of 536 new, experimentally supported lncRNA–target regulations that modulate properties of cancer stem cells; (iv) addition of an experimentally supported clinical application section of 2894 lncRNA–target regulations for potential clinical application. Importantly, LncTarD 2.0 provides RNA-seq/microarray and single-cell web tools for customizable analysis and visualization of lncRNA–target regulations in diseases. RNA-seq/microarray web tool was used to mining lncRNA–target regulations in both disease tissue samples and CTCs blood samples. The single-cell web tools provide single-cell lncRNA–target annotation from the perspectives of pan-cancer analysis and cancer-specific analysis at the single-cell level. LncTarD 2.0 will be a useful resource and mining tool for the investigation of the functions and mechanisms of lncRNA deregulation in human disease.

BackgroundMetastasis is the major cause of high recurrence and mortality of hepatocellular carcinoma (HCC). Unfortunately, there are few reports on effective biomarkers of HCC metastasis. Previous studies have reported that SAA1 may be a predictor and prognostic biomarker for multiple malignant tumors. However, the role of SAA1 in HCC has not yet been investigated.MethodsWe applied RNA sequencing and proteomics analysis to investigate the expression landscape of HCC cell lines and patient serum, respectively. SAA1 is a common key gene and listed as a candidate biomarker of HCC metastasis. It was validated in two cell lines, 107 participants serum, and 63 matched HCC and adjacent non-tumorous liver tissues. Human Protein Atlas (HPA), Genotype-Tissue Expression (GTEx), and The Cancer Genome Atlas (TCGA) datasets were integrated to explore SAA1 expression among various cell types and organs. The diagnostic and prognostic value of SAA1 in HCC were determined through receiver operating characteristic (ROC) and Kaplan–Meier curves. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, and protein-protein interaction (PPI) network were constructed for SAA1, as well as for its co−expressed genes. We further analyzed the correlation between SAA1 and co-expression genes.ResultsWe found 7 differentially expressed genes (DEGs) and 14 differentially expressed proteins (DEPs) were related to HCC metastasis. SAA1, a key candidate biomarker, was highly enriched in hepatocytes and liver organ, and it was also highly expressed in HCC cells and the serum and tissues of HCC patients. The results of ROC curve analysis indicated that SAA1 had better predictive values for distinguishing HCC metastasis from non-metastasis. Kaplan-Meier curve analysis revealed that HCC patients with higher SAA1 expression had worse overall survival.ConclusionsOur findings provide new insights into HCC metastasis by identifying candidate gene prediction biomarkers for HCC metastasis.

SNV was detected by whole-exome sequencing of 19 ccRCC samples.

Table S3, S5-S7, S10-S18, S21

qPCR results of the expression of 4 deferent lncRNA in cytoplasm and nucleus. Three PCR by-wells were prepared for each sample.

INDEL was detected by whole-exome sequencing of 19 ccRCC samples.

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC.Significance:A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

qPCR results after ASO (5717 and 5608) treatment of 2 lncRNAs in caki-2 and 786-O cell lines.Three or six PCR by-wells were prepared for each sample. NC, negative control.

Details of each sample

Kawasaki disease (KD) is a childhood disease associated with serious coronary artery complications. It is the most common cause of pediatric acquired heart disease in developed countries and is increasingly reported from many developing countries. The etiology of KD is still uncertain; interaction between a genetic predisposition and several environmental and immunological factors has been hypothesized. The Centers for Disease Control and Prevention reported that many children with MIS-C were infected with the new coronavirus or had close contact with people with the new coronavirus. Children with MIS-C show symptoms similar to severe cases of Kawasaki disease. An early discussion of similarities and differences between the novel coronavirus and Kawasaki disease was initiated towards the end of March 2020 between Dr. Karim Elakabawi, Benha university, Egypt; Prof. Manuel Katz, the chairman of the global CIP, Israel; and Prof. Jiao Fuyong, the head of the Center of Kawasaki disease diagnosis and treatment, shaanxi province, China. The three doctors discussed their strong observations about the epidemiologic distribution of KD cases and global affection of the Corona viruses family: SARS, MERS, and the most recently COVID-19. This article mainly summarizes the similarities and differences between KD and MIS-C.

Clear cell renal cell carcinoma (ccRCC) frequently features a high level of tumor heterogeneity. Elucidating the chromatin landscape of ccRCC at the single-cell level could provide a deeper understanding of the functional states and regulatory dynamics underlying the disease. Here, we performed single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on 19 ccRCC samples, and whole-exome sequencing was used to understand the heterogeneity between individuals. Single-cell transcriptome and chromatin accessibility maps of ccRCC were constructed to reveal the regulatory characteristics of different tumor cell subtypes in ccRCC. Two long noncoding RNAs (RP11-661C8.2 and CTB-164N12.1) were identified that promoted the invasion and migration of ccRCC, which was validated with in vitro experiments. Taken together, this study comprehensively characterized the gene expression and DNA regulation landscape of ccRCC, which could provide new insights into the biology and treatment of ccRCC.Significance:A comprehensive analysis of gene expression and DNA regulation in ccRCC using scATAC-seq and scRNA-seq reveals the DNA regulatory programs of ccRCC at the single-cell level.

Breast cancer is a cancer of high complexity and heterogeneity, with differences in prognosis and survival among patients of different subtypes. Copy number variations (CNVs) within enhancers are crucial drivers of tumorigenesis by influencing expression of their targets. In this study, we performed an integrative approach to identify CNA-driven enhancers and their effect on expression of target genes in four breast cancer subtypes by integrating expression data, copy number data and H3K27ac data. We identified 672, 555, 531, 361 CNA-driven enhancer-gene pairs and 280, 189, 113 and 98 CNA-driven enhancer-lncRNA pairs in the Basal-like, Her2, LumA and LumB subtypes, respectively. We then reconstructed a CNV-driven enhancer-lncRNA-mRNA regulatory network in each subtype. Functional analysis showed CNA-driven enhancers play an important role in the progression of breast cancer subtypes by influencing P53 signaling pathway, PPAR signaling pathway, systemic lupus erythematosus and MAPK signaling pathway in the Basal-like, Her2, LumA and LumB subtypes, respectively. We characterized the potentially prognostic value of target genes of CNV-driven enhancer and lncRNA-mRNA pairs in the subtype-specific network. We identified MUM1 and AC016876.1 as prognostic biomarkers in LumA and Basal-like subtypes, respectively. Higher expression of MUM1 with an amplified enhancer exhibited poorer prognosis in LumA patients. Lower expression of AC016876.1 with a deleted enhancer exhibited poorer survival outcomes of Basal-like patients. We also identified enhancer-related lncRNA-mRNA pairs as prognostic biomarkers, including AC012313.2-MUM1 in the LumA, AC026471.4-PLK5 in the LumB, AC027307.2-OAZ1 in the Basal-like and AC022431.1-HCN2 in the Her2 subtypes. Finally, our results highlighted target genes of CNA-driven enhancers and enhancer-related lncRNA-mRNA pairs could act as prognostic markers and potential therapeutic targets in breast cancer subtypes.

This article proposes an observer-based reinforcement learning (RL) control approach to address the optimal attitude-tracking problem and application for hypersonic vehicles in the reentry phase. Due to the unknown uncertainty and nonlinearity caused by parameter perturbation and external disturbance, accurate model information of hypersonic vehicles in the reentry phase is generally unavailable. For this reason, a novel synchronous estimation is proposed to construct a composite observer for hypersonic vehicles, which consists of a neural-network (NN)-based Luenberger-type observer and a synchronous disturbance observer. This solves the identification problem of nonlinear dynamics in the reference control and realizes the estimation of the system state when unknown nonlinear dynamics and unknown disturbance exist at the same time. By synthesizing the information from the composite observer, an RL tracking controller is developed to solve the optimal attitude-tracking control problem. To improve the convergence performance of critic network weights, concurrent learning is employed to replace the traditional persistent excitation condition with a historical experience replay manner. In addition, this article proves that the weight estimation error is bounded when the learning rate satisfies the given sufficient condition. Finally, the numerical simulation demonstrates the effectiveness and superiority of the proposed approaches to attitude-tracking control systems for hypersonic vehicles.

The exploitation and utilization of clean energy such as wind and photovoltaic power plays an important role in the reduction in carbon emissions to achieve the goal of “emission peak and carbon neutral”, but such a quantity of clean energy accessing the electric system will foster the transition of the electric power system structure. The intelligentization of power equipment will be an inevitable trend of development. High breaking performance, remote control and a digital detection platform of miniature circuit breaker, a protective equipment of a power distribution system, have also been inevitable requirements of the power Iot system. Based on the above, this paper studies three aspects: high-performance AC and DC general switching technology, remote control technology and operation status’ digital monitoring. A new DC non-polar breaking technology is proposed, which improves the short circuit breaking ability. An experimental prototype using the above techniques was fabricated and passed the DC 1000 V/10 kA short-circuit breaking test. On the basis of the above, an intelligent circuit breaker is developed, which contains multiple functions: remote switching, real-time temperature detection, energy metering and fault warning. Moreover, a software for digital condition monitoring and remote control is developed. This work has certain theoretical and practical significance for the development of the power Internet of things.

Brain metastasis occurs in approximately 30% of patients with lung adenocarcinoma (LUAD) and is closely associated with poor prognosis, recurrence, and death. However, dynamic gene regulation and molecular mechanism driving LUAD progression remain poorly understood. In this study, we performed a comprehensive single-cell transcriptome analysis using data from normal, early stage, advanced stage, and brain metastasis LUAD. Our single-cell-level analysis reveals the cellular composition heterogeneity at different stages during LUAD progression. We identified stage-specific risk genes that could contribute to LUAD progression and metastasis by reprogramming immune-related and metabolic-related functions. We constructed an early advanced metastatic dysregulated network and revealed the dynamic changes in gene regulations during LUAD progression. We identified 6 early advanced (

The advanced or recurrent endometrial cancer (EC) has a poor prognosis because of chemoresistance. 6-Phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a glycolytic enzyme, is overexpressed in a variety of human cancers and plays important roles in promoting tumor cell growth. Here, we showed that high expression of PFKFB3 in EC cell lines is associated with chemoresistance. Pharmacological inhibition of PFKFB3 with PFK158 and or genetic downregulation of PFKFB3 dramatically suppressed cell proliferation and enhanced the sensitivity of EC cells to carboplatin (CBPt) and cisplatin (Cis). Moreover, PFKFB3 inhibition resulted in reduced glucose uptake, ATP production, and lactate release. Notably, we found that PFK158 with CBPt or Cis exerted strong synergistic antitumor activity in chemoresistant EC cell lines, HEC-1B and ARK-2 cells. We also found that the combination of PFK158 and CBPt/Cis induced apoptosis- and autophagy-mediated cell death through inhibition of the Akt/mTOR signaling pathway. Mechanistically, we found that PFK158 downregulated the CBPt/Cis-induced upregulation of RAD51 expression and enhanced CBPt/Cis-induced DNA damage as demonstrated by an increase in γ-H2AX levels in HEC-1B and ARK-2 cells, potentially revealing a means to enhance PFK158-induced chemosensitivity. More importantly, PFK158 treatment, either as monotherapy or in combination with CBPt, led to a marked reduction in tumor growth in two chemoresistant EC mouse xenograft models. These data suggest that PFKFB3 inhibition alone or in combination with standard chemotherapy may be used as a novel therapeutic strategy for improved therapeutic efficacy and outcomes of advanced and recurrent EC patients.

Converting sustainable solar energy into hydrogen energy over semiconductor-based photocatalytic materials provides an alternative to fossil fuel consumption. However, efficient photocatalytic splitting of water to realize carbon-free hydrogen production remains a challenge. Heterojunction photocatalysts with well-defined dimensionality and perfectly matched interfaces are promising for achieving highly efficient solar-to-hydrogen conversion. Herein, we report the fabrication of a novel type of protonated graphitic carbon nitride (PCN)/Ti3C2 MXene heterojunctions with strong interfacial interactions. As expected, the two-dimensional (2D) PCN/2D Ti3C2 MXene interface heterojunction achieves a highly improved hydrogen evolution rate (2181 μmol·g−1) in comparison with bulk g-C3N4 (393 μmol·g−1) and protonated g-C3N4 (816 μmol·g−1). The charge-regulated surfaces of PCN and the accelerated charge transport at the face-to-face 2D/2D Schottky heterojunction interface are the major contributors to the excellent hydrogen evolution performance of the composite photocatalyst.

In the context of providing better stability and enhancing the mechanical properties of natural polysaccharides, self-healing hydrogels have attracted much attention because of their ability to spontaneously repair after damage. In this study, cellulose was modified to improve its solubility and cellulose acetoacetate (CAA) was obtained. Immediately, the acetoacetyl group of CAA reacts with the amine group of carboxymethyl chitosan (CMC) to generate enamine linkages, which formed the hydrogel (CAA/CMC) with self-healing capacity. Furthermore, to enhance the strength and accelerate the self-healing rate of the CAA/CMC hydrogel, CAA was oxidized to form dialdehyde groups and then reacted with CMC and oxalyl dihydrazide (ODH) to produce an enamine and acylhydrazone connected complex hydrogel (CMC/OCAA), a novel dual dynamic covalent bond crosslinked polysaccharide hydrogel. The mechanical and rheological properties of the hydrogels were investigated with different volume ratios of CMC. As the ratio of CMC and OCAA was 4 : 1, the tensile strength and storage modulus of the OCAA composite hydrogel increased to 242 kPa and 17.07 kPa from 15 kPa and 1.50 kPa of the CAA hydrogel. The self-healing time of the OCAA hydrogel reduced to 30 min compared with that of the CAA hydrogel of 12 h. Moreover, the cyclic tensile results demonstrated that the CMC/OCAA hydrogel exhibited very good fatigue resistance with 83.3% self-healing efficiency after self-healing for 48 h, much higher than 58.4% of the CMC/CAA hydrogel. Together with the existence of blood compatibility, cytocompatibility, and antibacterial and antioxidant properties, the complex hydrogel is highly attractive for biomedical, controlled release, and other applications.

PurposeThe purpose of this paper is to investigate the design method of partial observer canonical form (POCF), which is one of the important research tools for industrial plants.Design/methodology/approachMotivated by the two-steps method proposed in Xu et al. (2020), this paper extends this method to the case of Multi-Input Multi-Output (MIMO) nonlinear system. It decomposes the original system into two subsystems by observable decomposition theorem first and then transforms the observable subsystem into OCF. Furthermore, the necessary and sufficient conditions for the existing of POCF are proved.FindingsThe proposed method has a wide range of applications including completely observable nonlinear system, noncompletely observable nonlinear system, autonomous nonlinear system and forced nonlinear system. Besides, comparing to the existing results (Saadi et al., 2016), the method requires less verified conditions.Originality/valueThe new method concerning design POCF has better plants compatibility and less validation conditions.

Brain-computer interface (BCI) is a revolutionary human-computer interaction technology, which includes both BCI that can output instructions directly from the brain to external devices or machines without relying on the peripheral nerve and muscle system, and BCI that bypasses the peripheral nerve and muscle system and inputs electrical, magnetic, acoustic and optical stimuli or neural feedback directly to the brain from external devices or machines. With the development of BCI technology, it has potential application not only in medical field, but also in non-medical fields, such as education, military, finance, entertainment, smart home and so on. At present, there is little literature on the relevant application of BCI technology, the current situation of BCI industrialization at home and abroad and its commercial value. Therefore, this paper expounds and discusses the above contents, which are expected to provide valuable information for the public and organizations, BCI researchers, BCI industry translators and salespeople, and improve the cognitive level of BCI technology, further promote the application and industrial transformation of BCI technology and enhance the commercial value of BCI, so as to serve mankind better.脑机接口（BCI）是一种变革性的人机交互技术，其中既有不依赖外周神经和肌肉系统即可从大脑直接向外部设备或机器输出指令的BCI，也包括绕过外周神经和肌肉系统从外部设备或机器直接向大脑输入电、磁、声和光等刺激或神经反馈的BCI。随着BCI技术的发展，其不仅在医学领域具有潜在的应用，而且在非医学领域，如教育、军事、金融、娱乐、智能家居等方面也具有应用前景。目前，鲜有对BCI技术的相关应用、国内外BCI产业化现状以及其商业价值进行详细论述的文献，为此本文对上述内容展开阐述和讨论，可望为社会公众及组织、BCI研究人员、BCI产业转化者和销售人员提供有价值的信息，提高对BCI技术的认知水平，进一步促进BCI技术的应用和产业转化，提升BCI的商业价值，以便更好地为人类服务。.

The real-time, in-line analysis of light polarization is critical in optical networks, currently suffering from complex systems with numerous bulky opto-electro-mechanical elements tandemly arranged along the optical path. Here, we design and fabricate a fiber-integrated polarimeter by vertically stacking three photodetection units based on six-layer van der Waals materials, including one bismuth selenide (Bi 2 Se 3 ) layer for power calibration, two twisted black phosphorus (BP) layers for polarization detection, and three hexagonal boron nitride (hBN) layers for encapsulation. The self-power-calibrated, self-driven, and unambiguous detection of both linearly polarized (LP) and circularly polarized (CP) light is realized by the broken symmetry–induced linear photogalvanic effects (LPGEs) and circular photogalvanic effects (CPGEs) in the two BP units. Moreover, the device enables single-pixel polarimetric imaging to acquire spatial polarization information. The ultracompact device structure, free from external optical and mechanical modules, may inspire the development of miniaturized optical and optoelectronic systems.

Differences in genetic molecular features including mutation, copy number alterations and DNA methylation, can explain interindividual variability in response to anti-cancer drugs in cancer patients. However, identifying genetic alteration-driven genes and characterizing their functional mechanisms in different cancer types are still major challenges for cancer studies. Here, we systematically identified functional regulations between genetic alteration-driven genes and drug target genes and their potential prognostic roles in breast cancer. We identified two mutation and copy number-driven gene pairs (PARP1-ACSL1 and PARP1-SRD5A3), three DNA methylation-driven gene pairs (PRLR-CDKN1C, PRLR-PODXL2 and PRLR-SRD5A3), six gene pairs between mutation-driven genes and drug target genes (SLC19A1-SLC47A2, SLC19A1-SRD5A3, AKR1C3-SLC19A1, ABCB1-SRD5A3, NR3C2-SRD5A3 and AKR1C3-SRD5A3), and four copy number-driven gene pairs (ADIPOR2-SRD5A3, CASP12-SRD5A3, SLC39A11-SRD5A3 and GALNT2-SRD5A3) that all served as prognostic biomarkers of breast cancer. In particular, RARP1 was found to be upregulated by simultaneous copy number amplification and gene mutation. Copy number deletion and downregulated expression of ACSL1 and upregulation of SRD5A3 both were observed in breast cancers. Moreover, copy number deletion of ACSL1 was associated with increased resistance to PARP inhibitors. PARP1-ACSL1 pair significantly correlated with poor overall survival in breast cancer owing to the suppression of the MAPK, mTOR and NF-kB signaling pathways, which induces apoptosis, autophagy and prevents inflammatory processes. Loss of SRD5A3 expression was also associated with increased sensitivity to PARP inhibitors. The PARP1-SRD5A3 pair significantly correlated with poor overall survival in breast cancer through regulating androgen receptors to induce cell proliferation. These results demonstrate that genetic alteration-driven gene pairs might serve as potential biomarkers for the prognosis of breast cancer and facilitate the identification of combination therapeutic targets for breast cancers.

Brain-computer interaction (BCI) is a transformative human-computer interaction, which aims to bypass the peripheral nerve and muscle system and directly convert the perception, imagery or thinking activities of cranial nerves into actions for further improving the quality of human life. Magnetoencephalogram (MEG) measures the magnetic field generated by the electrical activity of neurons. It has the unique advantages of non-contact measurement, high temporal and spatial resolution, and convenient preparation. It is a new BCI driving signal. MEG-BCI research has important brain science significance and potential application value. So far, few documents have elaborated the key technical issues involved in MEG-BCI. Therefore, this paper focuses on the key technologies of MEG-BCI, and details the signal acquisition technology involved in the practical MEG-BCI system, the design of the MEG-BCI experimental paradigm, the MEG signal analysis and decoding key technology, MEG-BCI neurofeedback technology and its intelligent method. Finally, this paper also discusses the existing problems and future development trends of MEG-BCI. It is hoped that this paper will provide more useful ideas for MEG-BCI innovation research.脑机交互（BCI）是一种变革性的人机交互，旨在绕过外周神经和肌肉系统直接把脑神经的感知觉、表象或思维活动转化为动作，以进一步改善或提高人类的生活质量。脑磁图（MEG）测量神经元电活动产生的磁场，具有非接触式测量、时空分辨率高和准备方便等独特优势，是一种新的BCI驱动信号，基于脑磁图的脑机交互（MEG-BCI）研究具有重要脑科学意义和潜在应用价值。迄今为止，少有文献阐述MEG-BCI涉及的关键技术问题，为此本文聚焦MEG-BCI关键技术，详述了实用MEG-BCI系统中涉及的信号采集技术、MEG-BCI实验范式设计、MEG信号分析和解码关键技术、MEG-BCI神经反馈技术及其智能化方法。最后，本文还讨论了MEG-BCI存在的问题和未来发展趋势，期望本文为MEG-BCI创新研究提供更多有益思路。.

This paper focuses on the geological adaptive control of tunneling boring machine (TBM). To deal with the issue that the geological condition is uncertain, clustering analysis is used to identify geological types based on two important indices indicating the strength of rock. Based on the results from above, the principles of variation and range of tunneling parameters under different rock condition are determined. Furthermore, considering several vital performances of TBM during tunneling operation, a multi-objective optimization problem is proposed. In the light of non-dominated sorting and crowded distance evaluation concepts in non-dominated sorting genetic algorithm-II, the proposed multi-objective optimization problem is solved by using differential evolution algorithm. Based on the practical construction data, the simulation results show that the proposed method is effective in improving the performance of tunneling operation of TBM, compared with unoptimized operating actions from current systems.

Spark discharge ignition can be effectively enhanced by increasing the plasma volume and its duration, but evaluation and realization of an optimal ignition performance under engine working conditi...