Observer-based hierarchical distributed model predictive control for multi-linear motor traction systems.

This paper proposes an observer-based hierarchical distributed model predictive control (MPC) strategy for ensuring speed consistency in multi-linear motor traction systems. First, a communication topology is considered to ensure information exchange. Secondly, the control architecture of each agent is divided into upper layers and lower layers. The upper layer utilizes a distributed MPC method to track the leader's speed. The lower layer uses a decentralized MPC method to track the command signals sent by its upper layer controller. In addition, to eliminate the negative impact of disturbance, a nonlinear disturbance observer is designed. We then prove the asymptotic stability of the entire system by properly designing the Lyapunov equation. Finally, the feasibility of the proposed strategy is verified based on several simulations.

The new morphologic classification of the hand motor cortex with magnetic resonance imaging in glioma patients.

Purpose: The hand motor cortex (HMC) is a reliable anatomical landmark for identifying the precentral gyrus. The current study aimed to investigate the morphology of HMC on axial MRI of glioma patients, propose a new morphological classification of HMC and analyze the effect of tumors on the morphology of HMC. Methods: A retrospective study of 276 adult right-handed glioma patients was conducted. The morphology of HMC was assessed using T2 axial images. Subsequently, the distribution of morphological subtypes was compared between the bilateral hemispheres and the tumor-affected and healthy hemispheres. Finally, the influence of tumor pathology on the morphology of HMC was investigated. Results: A new morphological classification of HMC with four subtypes (Ω, ε, Ω-ε and ε-Ω) was proposed. No significant difference was identified in the distribution of morphological subtypes between the bilateral hemispheres (p = 0.0901, Chi-square test), or between the tumor-affected and healthy hemispheres (p = 0.3507, Chi-square test), and the morphology of HMC between the bilateral hemispheres were consistent (p < 0.0001, Kappa test). In addition, a significant difference was identified in the distribution of morphological subtypes between astrocytic and oligodendroglial tumors (p = 0.0135, Chi-square test). Conclusion: In the current study, we proposed a new morphological classification of HMC, and found that tumor could affect the morphology of HMC in glioma patients. The results can help our clinical practice, enabling us to further understand the spatial structure of the cerebral hemispheres.

Cooperative Adaptive Command Filtered Backstepping Control for EVs to UPS-Microgrid via Virtual Synchronous Generator.

Multiple batteries in uninterruptible power supply (UPS)-microgrid systems based on multiagents composed of multiple electric vehicles (EVs) can encounter state of charge (SoC) consistency problems. To solve this differential expansion and controller saturation problem, an adaptive command filter sliding-mode control strategy based on virtual synchronous generators (VSGs) and considering the power allocation principle is proposed. First, based on directed graph theory, an SoC consistency algorithm and power allocation strategy for multiple EVs were proposed, forming a dc power system with a fixed communication topology. Second, the rotor motion equation of synchronous generator (SG) is introduced into the inverter control algorithm to form the mathematical model of VSG. Third, a low-pass filter (LFP) was introduced in the voltage control process to simulate the excitation attenuation characteristics of the SG. Based on the above, a backstepping control strategy, including a command filter and sliding mode controller is proposed, which improves the operating stability of the system based on the system errors of angle, frequency, and power output. Finally, the UPS-microgrid system based on multiagents is simulated to demonstrate the stability of the system and the effectiveness of the proposed control strategy.

The complete plastid genome and characteristics analysis of Achillea millefolium.

Achillea is a crop with Chinese herbal characteristics and horticultural values. Its leaves and flowers contain aromatic oil, and the ripe herb can also be used as medicine to induce sweat and relieve rheumatic pains. It is seen cultivated in gardens all over China. Currently, the most comprehensive chloroplast genome sample involved in the study refers to New World clades of Achillea, which are used for marker selection and phylogenetic research. We completely sequenced the chloroplast genomes of Achillea millefolium. These sequencing results showed that the plastid genome is 149,078 bp in size and possesses a typical quadripartite structure containing one large single copy (LSC) with 82,352 bp, one small single copy (SSC) with 18,426 bp, and a pair of inverted repeat (IR) regions with 24,150 bp in Achillea millefolium. The chloroplast genome encodes a common number of genes, of which 88 are protein-coding genes, 37 transfer ribonucleic acid genes, and 8 ribosomal ribonucleic acid genes, which are highly similar in overall size, genome structure, gene content, and sequence. The exact similarity was observed when compared to other Asteraceae species. However, there were structural differences due to the restriction or extension of the inverted repeat (IR) regions-the palindromic repeats being the most prevalent form. Based on 12 whole-plastomes, 3 hypervariable regions (rpoB, rbcL, and petL-trnP-UGG) were discovered, which could be used as potential molecular markers.

Comparative Investigations on Properties of Three Kinds of FDM 3D-Printed Natural Plant Powder/Poly(lactic acid) Biocomposites.

In order to further explore the feasibility of the application of the residue of Chinese herbal medicine in FDM 3D technology and enrich the kinds of printing materials, Astragalus residue powder(ARP)/poly(lactic acid) (PLA) biocomposite was FDM 3D-printed, meanwhile, two traditional biocomposites, i.e., wood flour (WF)/PLA and rice straw powder (RSP)/PLA, were prepared by the same method, and the properties of the biocomposites were comparatively investigated. The results showed that, the tensile and flexural strengths of ARP/PLA were 28.33 MPa and 97.60 MPa, respectively, which were 2.85% and 10.89% smaller than those of WF/PLA, while 15.73% and 7.04% greater than those of RSP/PLA. WF/PLA showed typical brittle fracture characteristics, ARP/PLA and RSP/PLA both showed ductile fracture, but not obviously. Among the three kinds of biocomposites, ARP/PLA was the most thermally stable, followed by WF/PLA and RSP/PLA in turn. The incorporation of natural plant powder had no significant effect on the glassy transition, melting, and cold-crystallization behaviors of PLA, but the crystallinity of PLA could be increased from 0.3% to 2.0% and 1.9%, respectively, by adding ARP and WF. At 20 °C, the storage modulus of ARP/PLA, WF/PLA and RSP/PLA was 2759.4 MPa, 3361.3 MPa, and 2691.5 MPa, respectively, indicating that WF/PLA has the greatest stiffness, and the stiffness of RSP/PLA was the least. In addition to these, all the biocomposites were hydrophilic, the contact angle of the distilled water on the surface of ARP/PLA, WF/PLA or RSP/PLA was correspondingly 73.5°, 77.6° and 71.2°. Overall, it can be concluded that ARP/PLA has moderate strengths, stiffness and wettability, meanwhile, it is the most thermal stable among the three biocomposites, and can be processed at a temperature close to that of PLA. ARP/PLA is suitable as a new kind of feedstock material for FDM 3D printing.

Event-Triggered Bipartite Time-Varying Formation Control for Multiagent Systems With Unknown Inputs.

This article addresses the issues of the bipartite time-varying formation (BTVF) control for multiagent systems (MASs) on signed digraphs. All the designs are performed under the assumptions that the leader and followers suffer from external disturbances, the control input signal of the leader is unreachable to any follower, and the state variables of the followers are unmeasurable. To begin with, an unknown input observer (UIO) is designed for each follower using a traditional interval observer to obtain the state estimates. To realize the BTVF tracking, a distributed consensus error dynamic system is constructed. Furthermore, a distributed unknown input reconstruction method is developed to estimate the multiple disturbances in the consensus error system. Then, an event-triggered BTVF control protocol is proposed which allows two antagonistic time-varying formations to be formed, while excluding Zeno behavior. A simulation of a group of wheeled robots is used to demonstrate the performance of the proposed methods.

Excess sludge biochar facilitates persulfate activation for highly efficient tetracycline removal.

This study proposed a novel advanced oxidation system to treat metal and antibiotic pollution in water simultaneously. Meanwhile, the enhancement effect of absorbed metal pollution on the activation of persulfate in the system was also investigated. As the most widely used and polluting material, tetracycline (TC) and metal Fe were used as the pollutant models. In this study, a carbonaceous material (BC) was prepared from excess sludge and then combined with the persulfate system (Fe/BC/PS). It was found that the best biochar was obtained when the pyrolysis temperature reached 500 °C (BC500), with the specific surface area of 39.712 m2/g. Combining it with 300 mg/L PS, the removal rate of 120 mg/L TC reached 70.6%. Moreover, the sludge biochar itself possessed numerous reaction sites and good defective structure, which provided a perfect reaction site for the variable metals absorbed by BC. They accelerated electron conduction greatly, which led to the activation of PS very active and generating far more active radicals than normal. In addition, it also proposed the rational pathway and potential mechanism of TC degradation based on the degradation intermediates. This study has a high reference value for resource utilization of sewage sludge and antibiotics removal from water.

LncRNA NEAT1 facilitates glioma progression via stabilizing PGK1.

BACKGROUND: Long noncoding RNA NEAT1 has been implicated in glioma progression. However, the effect of NEAT1 on glycolysis of glioma cell and the potential mechanism remain unclear. METHODS: In vitro experiments, including CCK-8, colony formation, ECAR, and lactate detection assays were performed to evaluate the effect of NEAT1 on proliferation and glycolysis of glioma cell. RNA pulldown and RIP assays were performed to identify the interaction between NEAT1 and PGK1. Truncated mutation of NEAT1 and PGK1 was used to confirm the specific interactive domains between NEAT1 and PGK1. Animal studies were performed to analyze the effect of NEAT1/PGK1 on glioma progression. RESULTS: NEAT1 knockdown significantly suppressed the proliferation and glycolysis of glioma cells. NEAT1 could specifically interact with PGK1, which promotes PGK1 stability. Hairpin A of NEAT1 is essential for interaction with M1 domain of PGK1. Depletion of NEAT1 markedly inhibited tumor growth in mice, while PGK1 could reverse this effect. Higher expression of NEAT1 was associated with poor overall survival of GBM patients. CONCLUSIONS: NEAT1 over expression promotes glioma progression through stabilizing PGK1. NEAT1/PGK1 axis is a candidate therapeutic target for glioma treatment.

Incipient Fault Diagnosis for High-Speed Train Traction Systems via Stacked Generalization.

Diagnosing the fault as early as possible is significant to guarantee the safety and reliability of the high-speed train. Incipient fault always makes the monitored signals deviate from their normal values, which may lead to serious consequences gradually. Due to the obscure early stage symptoms, incipient faults are difficult to detect. This article develops a stacked generalization (stacking)-based incipient fault diagnosis scheme for the traction system of high-speed trains. To extract the fault feature from the faulty data signals, which are similar to the normal ones, the extreme gradient boosting (XGBoost), random forest (RF), extra trees (ET), and light gradient boosting machine (LightGBM) are chosen as the base estimators in the first layer of the stacking. Then, the logistic regression (LR) is taken as the meta estimator in the second layer to integrate the results from the base estimators for fault classification. Thanks to the generalization ability of stacking, the incipient fault diagnosis performance of the proposed stacking-based method is better than that of the single model (XGBoost, RF, ET, and LightGBM), although they can be used to detect the incipient faults, separately. Moreover, to find out the optimal hyperparameters of the base estimators, a swarm intelligent optimization algorithm, pigeon-inspired optimization (PIO), is employed. The proposed method is tested on a semiphysical platform of the CRH2 traction system in CRRC Zhuzhou Locomotive Company Ltd. The results show that the fault diagnosis rate of the proposed scheme is over 96%.

A data calibration method for micro air quality detectors based on a LASSO regression and NARX neural network combined model.

Studies have shown that there is a certain correlation between air pollution and various human diseases, especially lung diseases, so it is very meaningful to monitor the concentration of pollutants in the air. Compared with the national air quality monitoring station (national control point), the micro air quality detector has the advantage that it can monitor the concentration of pollutants in real time and grid, but its measurement accuracy needs to be improved. This paper proposes a model combining the least absolute selection and shrinkage operator (LASSO) regression and nonlinear autoregressive models with exogenous inputs (NARX) to calibrate the data measured by the micro air quality detector. Before establishing the LASSO-NARX model, correlation analysis is used to test whether the correlation between the concentration of air pollutants and its influencing factors is significant, and to find out the main factors that affect the concentration of pollutants. Due to the multicollinearity between various influencing factors, LASSO regression is used to further screen the influencing factors and give the quantitative relationship between the pollutant concentration and various influencing factors. In order to improve the prediction accuracy of pollutant concentration, the predicted value of each pollutant concentration in the LASSO regression model and the measurement data of the micro air quality detector are used as input variables, and the LASSO-NARX model is constructed using the NARX neural network. Several indicators such as goodness of fit, root mean square error, mean absolute error and relative mean absolute percent error are used to compare various air quality models. The results show that the prediction results of the LASSO-NARX model are not only better than the LASSO model alone and the NARX model alone, but also better than the commonly used multilayer perceptron and radial basis function neural network. Using this model to calibrate the measurement data of the micro air quality detector can increase the accuracy by 61.3-91.7%.

The complete chloroplast genome and characteristics analysis of Musa basjoo Siebold.

BACKGROUND: An ornamental plant often seen in gardens and farmhouses, Musa basjoo Siebold can also be used as Chinese herbal medicine. Its pseudostem and leaves are diuretic; its root can be decocted together with ginger and licorice to cure gonorrhea and diabetes; the decoct soup of its pseudostem can help relieve heat, and the decoct soup of its dried flower can treat cerebral hemorrhage. There have not been many chloroplast genome studies on M. basjoo Siebold. METHODS AND RESULTS: We characterized its complete chloroplast genome using Novaseq 6000 sequencing. This paper shows that the length of the chloroplast genome M. basjoo Siebold is 172,322 bp, with 36.45% GC content. M. basjoo Siebold includes a large single-copy region of 90,160 bp, a small single-copy region of 11,668 bp, and a pair of inverted repeats of 35,247 bp. Comparing the genomic structure and sequence data of closely related species, we have revealed the conserved gene order of the IR and LSC/SSC regions, which has provided a very inspiring discovery for future phylogenetic research. CONCLUSIONS: Overall, this study has constructed an evolutionary tree of the genus Musa species with the complete chloroplast genome sequence for the first time. As can be seen, there is no obvious multi-branching in the genus, and M. basjoo Siebold and Musa itinerans are the closest relatives.

Biochar produced from the co-pyrolysis of sewage sludge and waste tires for cadmium and tetracycline adsorption from water.

Application of sewage sludge biochar as an adsorbent for pollutant removal has obtained special attention due to their low cost and surface functionality. In this research, sludge-tire composite biochar (STB) was successfully prepared through co-pyrolysis at 300, 500 and 700 °C, respectively. Cadmium (Cd) and tetracycline (TC) were selected as the target pollutant. The results indicated that STB has the highest surface area (49.71 m2/g), more inorganic minerals (Kaolinite) as well as relatively stable physicochemical properties with 10% tire particles (TP) at 700 °C. The adsorption results indicated that the pseudo-second-order equation and Langmuir isotherm model could better describe the adsorption of Cd2+ and TC by STB. The maximum adsorption capacity of Cd2+ and TC was 50.25 mg/g and 90.09 mg/g, respectively. The main mechanism of the adsorption process of STB for Cd mainly involves anion binding adsorption and ion exchange. The main mechanism of the adsorption process of STB for TC mainly involves complexation and cation exchange. The present study could set a scientific foundation for further research on the recycle of sewage sludge and tires.

Adsorption and desorption behaviors of antibiotics by tire wear particles and polyethylene microplastics with or without aging processes.

Tire wear particles (TWP), as the significant proportion of microplastics (MPs), has adsorbed much attention due to its widespread presence in aquatic ecosystem. However, compared with traditional MPs, few studies have investigated the interaction between TWP and coexisting contaminants. The adsorption-desorption behavior of chlortetracycline (CTC) and amoxicillin (AMX) by original and aged TWP was studied, and polyethylene (PE) was studied for comparison. After aging, small holes and cracks were produced on the surfaces of the TWP and PE. Meanwhile, the specific surface areas (SBET) of TWP and PE increased, but the aged TWP had a larger SBET than the aged PE, which indicated that TWP was more likely to degrade than PE. The adsorption kinetics results showed that the adsorption of CTC and AMX by TWP and PE conformed to the pseudo-second-order model. The adsorption isotherm results showed that the Freundlich model could describe the adsorption isotherm data of TWP and PE. The adsorption capacity of antibiotics by TWP increased by 1.13-23.40 times, and by 1.08-14.24 times on PE, after aging. Desorption experiments showed that the desorption amount of antibiotics on TWP and PE in simulated gastric fluid was greater than that in ultrapure water. The desorption amount and rate of CTC and AMX from TWP were higher than those of PE, indicating that TWP might be more harmful to the aquatic environment and organisms. These findings indicated that, compared with PE, TWP might have stronger carrier effects on antibiotics, which might pose more serious potential risks to the aquatic environment and organisms, especially considering the effects of the aging process. This study would expand the research on environmental risk of MPs and contribute to providing new insights into the evaluation of tire material particles.

An interval-estimation-based anti-disturbance sliding mode control strategy for rigid satellite with prescribed performance.

This paper investigates an anti-disturbance sliding mode control strategy for a rigid satellite system with external disturbance under the prescribed performance constraints. An interval observer is firstly introduced to generate the interval estimation of the attitude angular velocity. Then a finite time identical disturbance reconstruction strategy is developed by using the interval estimation. Based on the novel performance function and error transformation constraints, the attitude tracking error is converted into a new error system that guarantees the desired transient and steady-state responses for the tracking error. Then, by introducing the reconstructed disturbance, a finite time anti-disturbance controller is constructed with the backstepping method. The stability of the strategy is guaranteed by the Lyapunov stability method. Finally, simulation results demonstrate the effectiveness of the proposed approach.

Model-Free Cooperative Adaptive Sliding-Mode-Constrained-Control for Multiple Linear Induction Traction Systems.

In order to deal with the speed cooperative control problem in the multiple linear induction traction systems consists of multiple linear induction motors, a model-free cooperative adaptive sliding-mode-constrained-control strategy is proposed considering the input magnitude and rate constraints which may cause the problem of actuator and integral saturation. First, the equivalent circuit topology of the single motor in the system is investigated. Besides, the system is considered as the multiagent system with fixed communication topology due to the interaction between adjacent motors. Then, the output observer is presented to estimate the output and the estimation algorithm of pseudo-partial derivative parameter and uncertainties is proposed. Based on the above, the proposed control scheme is presented by designing an integral sliding-mode surface containing the systematic error and an anti-windup compensator is added to eliminate the saturation. Finally, the simulations of the proposed control strategy for multiagent systems are carried out to demonstrate the effectiveness and superiority of the proposed control strategy.

Distributed fault detection and estimation in cyber-physical systems subject to actuator faults.

The fault detection and estimation problems for the physical layer network in the cyber-physical systems with unknown external disturbances are investigated in this study. Both bias fault and loss of efficiency scenarios are considered for the actuators. Based on the adaptive threshold method and sliding mode observer approach, a distributed fault detection observer (DFDO) is constructed for each physical layer node to detect the occurrence of actuator faults. Then a relative global estimation error system is defined for the distributed fault estimation observer (DFEO). Compared with the existing results, the proposed DFEO can provide the estimation for not only the actuator bias faults but also the actuators' efficiency factors under the impact of exogenous disturbance with two gain dynamic update processes. Finally, the feasibility and effectiveness of the given DFDO and the DFEO are examined by Lyapunov stability method and the simulation results.

T-cell factor (TCF/LEF1) binding elements (TBEs) of FasL (Fas ligand or CD95 ligand) bind and cluster Fas (CD95) and form complexes with the TCF-4 and b-catenin transcription factors in vitro and in vivo which result in triggering cell death and/or cell activation.

T-cell factor 4 (TCF4) is an important transcription factor of the Wnt signaling system. ß-catenin, an upstream protein of TCF4, accumulates in the cytoplasm, then translocates to the nucleus to activate the ß-catenin/T-cell factor/lymphoid enhancer factor (TCF/LEF) transcriptional machinery and regulates target genes. Previous studies showed that TCF4 was involved in cell proliferation and apoptosis. However, its expression and function in central nervous system injury are unclear. We performed a traumatic brain injury (TBI) model in adult rats. The expression of TCF4 in the brain cortex detected by Western blot increased after TBI. Double immunofluorescence staining revealed that TCF4 was expressed by neurons and microglia. In addition, co-localization of TCF4 with active caspase-3 or proliferating cell nuclear antigen was observed in neurons and microglia, respectively, suggesting that TCF4 might participate in neuronal apoptosis and microglial proliferation after TBI. To further investigate the functions of TCF4, PC12 and HAPI cells were employed to establish a neuronal apoptosis and microglial proliferation model in vitro, respectively. Knocking down TCF4 with siRNA proved the pro-apoptotic and pro-proliferation effect of TCF4 in PC12 and HAPI cells, respectively. Taken together, TCF4 might promote neuronal apoptosis and microglial proliferation after TBI.

Upregulation of Interferon Regulatory Factor 6 Promotes Neuronal Apoptosis After Traumatic Brain Injury in Adult Rats.

The interferon regulatory factor (IRF) family was first discovered as a set of transcriptional regulators of the type I interferon system in 1988. In mammals, the IRF family includes nine members that play important roles in the immune system, oncogenesis, and apoptosis. However, the distribution and the function of IRF6 in the central nervous system are limited. In this study, we established an adult rat traumatic brain injury (TBI) model. Compared to the sham brain cortex, Western blot and immunohistochemistry showed significant upregulation of IRF6 in the ipsilateral brain cortex after TBI. Immunofluorescence double-labeling showed that IRF6 completely co-localized with neurons, not astrocytes or oligodendrocytes. Furthermore, we detected that the neuronal apoptosis marker active caspase-3 co-localized with IRF6 in neurons. Additionally, IRF6 knockdown in PC12 cells in vitro resulted in a decrease in active caspase-3 expression and an increase in Bcl-2 and p-Akt expression. We conclude that IRF6 might promote neuronal apoptosis by inhibiting Akt phosphorylation after TBI.

Phase II trial of temozolomide plus concurrent whole-brain radiation followed by TNV regimen as adjuvant therapy for patients with newly diagnosed primary CNS lymphoma.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) is an aggressive extranodal non-Hodgkin's lymphoma limited to the CNS. Treatment of PCNSL with high-dose methotrexate (HD-MTX)-based chemotherapy and whole-brain radiotherapy (WBRT) is associated with high rates of relapse and severe treatment-related neurotoxicity. AIM: To report our experience of treating newly diagnosed PCNSL with temozolomide, nedaplatin, and vincristine (TNV), as the replacement of HD-MTX, in combination with concurrent chemoradiotherapy. MATERIALS AND METHODS: Newly diagnosed PCNSL patients were given concurrent temozolomide (75 mg/m 2 , orally) daily during WBRT. Then, the TNV regimen was given after four weeks. The TNV regimen consisted of temozolomide (200 mg/m 2 orally: Days 1-5), nedaplatin (80 mg/m 2 intravenous: Day 1), and vincristine (1.4 mg/m 2 intravenous: Day 1). Each cycle was of a duration of four weeks and a maximum of six cycles were applied. The primary end point was response to treatment obtained by magnetic resonance imaging (MRI). Secondary end points were progression-free survival (PFS) and fewer toxic effects. RESULTS: The study subjects included 14 patients (median age: 53.5, median Karnofsky Performance Scale (KPS): 75). The median number of TNV cycles given was five. RESPONSE TO TREATMENT: Complete response in 12 (85.7%) patients, partial response in 2 (14.3%) patients, and none with progressive disease. The objective response rate was 100%, and median PFS was 21.4 months. Toxicity was relatively mild, which mainly included nausea in six and fatigue in five, grade 3-4 hematotoxicity in one, and abnormal liver functions in five patients. No neurotoxicity has been observed till date. CONCLUSION: The efficacy outcomes in this study are comparable to other reported HD-MTX-based regimens plus WBRT, with an added favorable toxicity profile. Prospective, randomized controlled trials are warranted to confirm such results.

Synthesis and characterization of ß-CD-coated polystyrene microspheres by γ-ray radiation emulsion polymerization.

Polystyrene (PS) microspheres coated with ß-cyclodextrin (ß-CD) were fabricated via γ-ray-induced emulsion polymerization in a ternary system of styrene/ß-CD/water (St/ß-CD/water). The solid inclusion complex of St and ß-CD particles formed at the St droplets-water interface can stabilize the emulsion as the surfactant. TEM and XPS results showed that ß-CD remains on the surface of PS particles. The average size of the PS particles increases from 186 to 294 nm as the weight ratio of ß-CD to St rises from 5% to 12.5%. The water contact angle (CA) of PS latex film is lower than 90°, and reduces with the ß-CD content even to 36°. Thus, this work provides a new and one-pot strategy to surface hydrophilic modification on hydrophobic polymer particles with cyclodextrins through radiation emulsion polymerization.