A Hierarchical Distributed Data-Driven Adaptive Learning Control for Nonaffine Nonlinear MASs.

This article designs a new hierarchical distributed data-driven adaptive learning control algorithm to accomplish the leader-following tracking control objective for nonaffine nonlinear multiagent systems (MASs). The proposed hierarchical control structure is composed of a distributed observer and a decentralized data-driven adaptive learning controller. Considering that some followers cannot directly receive information from the leader, a distributed observer is designed to estimate the information of the leader. Based on this, a decentralized data-driven adaptive learning controller is further devised to enable the follower to track the estimated information of the leader, where the model parameter learning algorithm is developed to capture the dynamic characteristics of the original system. One advantage of the developed hierarchical control learning algorithm is that neither the leader's system model nor the follower's system model is needed. The other one is the elimination of the noncausal problem without the additional assumption. Simulation results exemplify the merits of the theoretical results by comparisons.

Donor-Derived Transmission of Scedosporiosis in Kidney Transplant Recipients from a Systemic lupus erythematosus donor.

Donor-derived infection (DDI) associated with Scedosporium spp is extremely rare, and results in a very poor prognosis. The present study reports a probable DDI due to Scedosporium boydii (S. boydii) from a donor with neuropsychiatric systemic lupus erythematosus. Two recipients developed Scedosporiosis after kidney transplantation from the same donor. Recipient 1 died of central nervous system infection due to S. boydii based on the clinical presentations, and the positive metagenomic next-generation sequencing (mNGS) and culture results for the cerebrospinal fluid. The other recipient with urinary tract obstruction due to S. boydii, which was identified through the positive culture and mNGS results of the removed stents, was successfully treated by stent replacement and voriconazole administration. Undiagnosed disseminated donor infection and the transmission of S. boydii should be given attention, particularly when the donor and recipients have primary immunodeficiency disease. The screening of donors and recipients for S. boydii using mNGS may be helpful in guiding antifungal prophylaxis and treatment recipients, due to its higher sensitivity and shorter diagnostic time relative to other traditional techniques.

Distributed Model-Free Adaptive Control for Learning Nonlinear MASs Under DoS Attacks.

This article addresses the distributed model-free adaptive control (DMFAC) problem for learning nonlinear multiagent systems (MASs) subjected to denial-of-service (DoS) attacks. An improved dynamic linearization method is proposed to obtain an equivalent linear data model for learning systems. To alleviate the influence of DoS attacks, an attack compensation mechanism is developed. Based on the equivalent linear data model and the attack compensation mechanism, a novel learning-based DMFAC algorithm is developed to resist DoS attacks, which provides a unified framework to solve the leaderless consensus control, the leader-following consensus control, and the containment control problems. Finally, simulation examples are shown to illustrate the effectiveness of the developed DMFAC algorithm.

Model-Free Adaptive Resilient Control for Nonlinear CPSs With Aperiodic Jamming Attacks.

The problem of the model-free adaptive resilient control (MFARC) for nonlinear cyber-physical systems (CPSs) suffered from aperiodic jamming attacks is investigated in this article. First, the MFARC framework subject to aperiodic jamming attacks is established, and an intermediate variable method is introduced to avoid using the unavailable time-varying parameter and further eliminate an extra assumption on the sign limit of it. Then, a MFARC scheme is devised to track the desired output, where the problem of the tracking control can be transformed into solving a feasibility problem, and the controller parameters can be obtained with the aid of the linear matrix inequality technique. What is more, a novel attack compensation mechanism is developed in the MFARC scheme to mitigate the impact of aperiodic jamming attacks. In the last, an example is provided to verify the effectiveness of the devised MFARC scheme.

Characterization of bacterial communities in Coregonus peled fillets during chilled storage and interactions between selected bacterial strains.

AIM: Coregonus peled fillets were used as a model to evaluate the dominant bacterial growth of chilled fish during storage after shipping and interactions of selected bacterial strains. METHODS AND RESULTS: Coregonus peled fillets were transported by air and land in ice boxes about 48 h from aquatic products company in Xinjiang, China, to the laboratory located in Dalian, China. Both culture-dependent (plate counts on nonselective media) based on 16S rRNA gene sequencing and culture-independent (Illumina-MiSeq high-throughput sequencing) methods were used. To detect interactions among bacterial populations from chilled fish, the influence of 18 test strains on the growth of 12 indicator isolates was measured by a drop assay and in liquid culture medium broth. The results showed that bacterial counts exceeded 7.0 log CFU/g following storage for 4 days at 4 °C. When the bacterial counts exceeded 8.5 log CFU/g after 12 days, the predominant micro-organisms were Aeromonas, Pseudomonas, Carnobacterium, Psychrobacter and Shewanella, as measured by the culture-independent method. All test strains showed inhibiting effects on the growth of other strains in liquid culture. Pseudomonas isolates showed antibacterial activity for approximately 60% of the indicator strains on nutritional agar plates. The majority of test isolates enhancing indicator strain growth were the strains isolated on day 0. CONCLUSIONS: High-throughput sequencing approach gives whole picture of bacterial communities in chilled C. peled fillets during storage, while growth interferences between selected bacterial strains illustrate the complexity of microbial interactions. SIGNIFICANCE AND IMPACT OF THE STUDY: We determined the bacterial communities and growth interferences in chilled Coregonus peled after shipping and these are the first data concerning microbiota in C. peled using a culture-independent analysis. The present study will be useful for manufacture and preservation of C. peled products by providing with valuable information regarding microbiological spoilage of C. peled.

Observer-Based Event-Triggered Containment Control for MASs Under DoS Attacks.

This article studies the observer-based event-triggered containment control problem for linear multiagent systems (MASs) under denial-of-service (DoS) attacks. In order to deal with situations where MASs states are unmeasurable, an improved separation method-based observer design method with less conservativeness is proposed to estimate MASs states. To save communication resources and achieve the containment control objective, a novel observer-based event-triggered containment controller design method based on observer states is proposed for MASs under the influence of DoS attacks, which can make the MASs resilient to DoS attacks. In addition, the Zeno behavior can be eliminated effectively by introducing a positive constant into the designed event-triggered mechanism. Finally, a practical example is presented to illustrate the effectiveness of the designed observer and the event-triggered containment controller.

Unveiling the Pharmacological Mechanisms of Eleutheroside E Against Postmenopausal Osteoporosis Through UPLC-Q/TOF-MS-Based Metabolomics.

Postmenopausal osteoporosis (PMOP) is a common metabolic bone disease in postmenopausal women in the Worldwide, and seriously affects the quality of life of middle-aged and elderly women. Therefore, there is an urgent need to discover a highly effective drug for PMOP treatment. In this study, ultra-high performance liquid tandem quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) was used to analyze the urine metabolic profiling and potential biomarkers, the relevant metabolic network of PMOP rats, and further to evaluate the intervention effect of Eleutheroside E (EE) against PMOP. Using multivariate statistical analysis combined with UPLC-Q/TOF-MS, a total of 27 biomarkers were identified, which related with 16 metabolic pathways, mainly involving steroidogenesis, beta oxidation of very long chain fatty acids, glutathione metabolism, carnitine synthesis, estrone metabolism, oxidation of branched chain fatty acids, etc. After treatment of EE, these biomarkers were markedly regulated, mainly involving steroid hormone biosynthesis, arachidonic acid metabolism, primary bile acid biosynthesis, indicating that EE had the therapeutic effect on PMOP. This study identified the potential urine metabolic markers and related metabolic pathways of the PMOP, explained the metabolic effect and pharmacological mechanisms of EE against PMOP, and provided a basis for the pharmacological study of EE.

Achieving better connections between deposited lines in additive manufacturing via machine learning.

Additive manufacturing is becoming increasingly popular because of its unique advantages, especially fused deposition modelling (FDM) which has been widely used due to its simplicity and comparatively low price. All the process parameters of FDM can be changed to achieve different goals. For example, lower print speed may lead to higher strength of the fabricated parts. While changing these parameters (e.g. print speed, layer height, filament extrusion speed and path distance in a layer), the connection between paths (lines) in a layer will be changed. To achieve the best connection among paths in a real printing process, how these parameters may result in what kind of connection should be studied. In this paper, a machine learning (deep neural network) model is proposed to predict the connection between paths in different process parameters. Four hundred experiments were conducted on an FDM machine to obtain the corresponding connection status data. Among them, there are 280 groups of data that were used to train the machine learning model, while the rest 120 groups of data were used for testing. The results show that this machine learning model can predict the connection status with the accuracy of around 83%. In the future, this model can be used to select the best process parameters in additive manufacturing processes with corresponding objectives.

[The molecular identification of licorice species and the quality evaluation of licorice slices].

Licorice is one of the most common herbs in traditional Chinese medicine, and classified as top grade in Shen Nong Ben Cao Jing. There are three different original plants of licorice stipulated in Chinese Pharmacopeia, Glycyrrhiza uralensis Fisch., Glycyrrhiza glabra L., and Glycyrrhiza inflata Bat. However, previous investigation showed that the pharmacodynamic effects of the three licorices were quite different. It is very difficult to identify them by the classical identification methods. In order to establish a fast and effective identification method, we collected 240 licorice plants from 21 populations of 7 provinces, and amplified their ITS and psbA-trnH sequences. ITS sequences with a full length of 616 bp and psbA-trnH sequences with a full length of 389 bp were obtained separately. Using DNAMAN to analyze these sequences, 4 variable sites were found in ITS sequences and 2 ITS haplotypes were determined, and 3 variable sites were found in psbA-trnH sequences and 4 psbA-trnH haplotypes were determined. With the combination analysis of ITS and psbA-trnH sequences, the molecular identification method of original licorice was established. Using this method, 40 samples of licorice slices collected from 4 main herbal material markets in China were identified successfully. Furthermore, the contents of 2 triterpenes, 18α-glycyrrhizic acid and 18ß-glycyrrhizic acid, and 4 flavonoids, liquiritin, isoliquiritin, liquiritigenin, and isoliquiritigenin in these licorice pieces were examined by HPLC and the results were analyzed using SPSS 21.0. This study provides a new method in identification of licorice, which may serve as a guideline for quality control of licorice slices.

[The molecular identification of Bupleurum medicinal species and the quality investigation of Bupleuri Radix].

Bupleuri Radix is one of the most frequently used herbal medicines in China with a 2 000-year medicinal history. However, the use of Bupleuri Radix is very confused. Twenty-five species and eight varieties of Bupleurum have been used as Bupleuri Radix in different regions of China. It is very difficult to identify these Bupleurum species using traditional morphological method. In order to establish a fast and effective method to identify these Bupleurum species, we collected 168 Bupleurum medicinal plants from 14 populations of 9 provinces, and amplified their ITS sequences. 168 ITS sequences with a full length of 600-606 bp were obtained. DNAMAN analyzing results showed that 86 variable sites were present in these sequences and 19 haplotypes (TH1-TH19) were determined. After calculating K2P distance and analyzing an NJ tree, we established a molecular identification method based on ITS sequence. Using this method, 52 samples of Bupleuri Radix were identified successfully. Furthermore, we tested saikosaponin a, c, d content in these Bupleuri Radix by HPLC and analyzed the results by ANOVA and LSD T test to evaluate the quality of Bupleuri Radix. This method is significant for effective identification of Bupleurum medicinal plants, and quality control of Bupleuri Radix in the market.

The anti-inflammatory activity of licorice, a widely used Chinese herb.

CONTEXT: Increasing incidence and impact of inflammatory diseases have encouraged the search of new pharmacological strategies to face them. Licorice has been used to treat inflammatory diseases since ancient times in China. OBJECTIVE: To summarize the current knowledge on anti-inflammatory properties and mechanisms of compounds isolated from licorice, to introduce the traditional use, modern clinical trials and officially approved drugs, to evaluate the safety and to obtain new insights for further research of licorice. METHODS: PubMed, Web of Science, Science Direct and ResearchGate were information sources for the search terms 'licorice', 'licorice metabolites', 'anti-inflammatory', 'triterpenoids', 'flavonoids' and their combinations, mainly from year 2010 to 2016 without language restriction. Studies were selected from Science Citation Index journals, in vitro studies with Jadad score less than 2 points and in vivo and clinical studies with experimental flaws were excluded. RESULTS: Two hundred and ninety-five papers were searched and 93 papers were reviewed. Licorice extract, 3 triterpenes and 13 flavonoids exhibit evident anti-inflammatory properties mainly by decreasing TNF, MMPs, PGE2 and free radicals, which also explained its traditional applications in stimulating digestive system functions, eliminating phlegm, relieving coughing, nourishing qi and alleviating pain in TCM. Five hundred and fifty-four drugs containing licorice have been approved by CFDA. The side effect may due to the cortical hormone like action. CONCLUSION: Licorice and its natural compounds have demonstrated anti-inflammatory activities. More pharmacokinetic studies using different models with different dosages should be carried out, and the maximum tolerated dose is also critical for clinical use of licorice extract and purified compounds.

Aucubin prevents loss of hippocampal neurons and regulates antioxidative activity in diabetic encephalopathy rats.

In this study, the neuroprotection of aucubin and its mechanism were evaluated in the rat model of diabetic encephalopathy. Diabetes mellitus (DM) rats were stratified by cognitive capability (CC), and assigned to four treatment groups for aucubin treatment (doses of 0, 1, 5 or 10 mg/kg aucubin), with a further two groups of non-DM rats ranked by CC as controls for aucubin (doses of 0 or 5 mg/kg aucubin). Neuroprotection was estimated by the indexes of behavior and histology. Behavioral testing was performed in a Y-maze. The surviving neurons in CA1-CA4 and subiculum (SC) of the hippocampus were counted under a microscope. In addition, the apoptotic neurons in the CA1 of the hippocampus were also examined by using TUNEL staining. In order to clarify the mechanism of aucubin's neuroprotection, the activities of endogenous antioxidants and nitric oxide synthase (NOS) together with the content of lipid peroxide in the hippocampus were assayed. The results proved that aucubin significantly reduced the content of lipid peroxide, regulated the activities of antioxidant enzymatic and decreased the activity of NOS. All these effects indicated that aucubin was a potential neuroprotective agent and its neuroprotective effects were achieved, at least in part, by promoting endogenous antioxidant enzymatic activities.

Acanthopanax senticosus inhibits nitric oxide production in murine macrophages in vitro and in vivo.

Excess nitric oxide (NO) production has been implicated in inflammatory diseases. The present study investigated the inhibitory effect of the stem bark extract of Acanthopanax senticosus (A. senticosus) on NO production in murine macrophages in vitro and in vivo. In vitro exposure of RAW264.7 cells to 1, 10, 50, 100, 250, 500 and 1000 microg/mL of A. senticosus extract significantly suppressed NO production induced by lipopolysaccharide (LPS) and interferon gamma (IFN-gamma) in a dose-dependent manner. In vitro exposure of mouse resident peritoneal macrophages to 1, 10, 100 and 1000 microg/mL of A. senticosus extract significantly suppressed NO production induced by LPS and IFN-gamma in a dose-dependent manner. In vivo administration of A. senticosus extract (50, 100 and 200 mg/kg) to KM mice dose-dependently inhibited LPS and IFN-gamma induced production of NO in isolated mouse peritoneal macrophages ex vivo. Exposure to A. senticosus extract had no effect on cell viability and systemic toxicity. The results demonstrated that the stem bark extract of A. senticosus extract inhibits NO production in murine macrophages in vitro and in vivo.