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This paper devises a neural-network-based data-driven (NN-DD) algorithm to address the trajectory tracking control (TC) of discrete non-affine MIMO systems with unknown models and repetitive operation patterns. Data-driven control no longer relies on the precise model of the controlled system, thereby breaking free from the limitations of model-based control strategies. Inspired by this, the primary objective of the algorithm is to ensure that the tracking error of the system is uniformly ultimately bounded through a data-driven approach. The algorithm is comprised of a DD modeling approach based on an enhanced stochastic configuration network (ESCN), and a control input solving approach based on radial basis function neural networks (RBFNNs). The numerical simulations indicate that the proposed algorithm achieves a decrease in the modeling error to 3.29 e - 7 and the tracking error to 1 e - 8 after just 20 iterations. In addition, the numerical simulations also demonstrate that the modeling algorithm based on an ESCN reduces the modeling errors by 48.11 % and 99.95 % respectively compared to the modeling algorithms using only stochastic configuration networks (SCNs) or extreme learning machines (ELMs). Regarding tracking errors, the proposed RBFNN-based controller reduces the tracking error by 100 % compared to the backpropagation NN (BPNN)-based controller. Furthermore, the robustness of the algorithm against time-varying interference is tested via the unmanned vehicle simulations. This paper covers several contributions: 1) The proposed algorithm is entirely DD and can directly establish the relationship between inputs and outputs. 2) The designed ESCN fully integrates the advantages of SCNs and ELMs, in contrast to simply combining basic algorithms. 3) The RBFNN-based controller is independent of the actual system structure and exhibits excellent generalization capabilities. [ABSTRACT FROM AUTHOR]

The mechanism underlying seed germination promotion by plant growth-promoting rhizobacteria (PGPR) remains unclear. This study investigated the effects of Bacillus subtilis QM3 (a PGPR) and gibberellic acid (GA3) on germination indexes, seedling growth, and amylase activity in wheat seeds (Triticum aestivum L.) (caryopses) at different germination times. The results showed that B. subtilis QM3 exhibited a significantly greater increase in most measured indicators compared to GA3 (p < 0.05), and the coordinated effect of bacteria QM3 and GA3 was superior. GA3 showed no promotion of radicle length (LR) from day 3 to day 7. Conversely, the addition of uniconazole (U), a gibberellin synthesis inhibitor, significantly reduced all indexes except for fresh weight (FW) and root-shoot ratio (RSR). However, both B. subtilis QM3 and GA3 significantly alleviated the inhibition (p < 0.05), especially in the germination rate and amylase activity. The gibberellin (GA) content and expression of two key biosynthetic enzyme genes were also characterized. Further investigations revealed that the GA content in the B. subtilis QM3 group was significantly higher than in the control group at 12 h, 24 h, and 48 h during seed germination (p < 0.05). Moreover, B. subtilis QM3 significantly increased TaGA3ox-B2 expression (p < 0.05), with 1.44 times that of the control group, while there was no significant effect on TaGA20ox-D2 expression. Furthermore, amylase activity was positively correlated with the germination rate (GR) and GA content was positively correlated with amylase activity according to Pearson's correlation analysis, with R2 values of 0.8102 and 0.8365, respectively. Our results demonstrate that one of the mechanisms by which B. subtilis QM3 promotes wheat seed germination may be the induction of GA biosynthesis. [ABSTRACT FROM AUTHOR]

This paper considers the problem of making Hopfield neural networks (HNNs) generate multi-scroll chaotic attractors (MSCAs) and applying them to privacy protection. To this end, based on HNNs and memristors, a memristive Hopfield switching neural network (MHSNN) is constructed. Firstly, two memristive Hopfield neural networks (MHNNs) are combined into an MHNN with switching topology by designing a weight-switching mechanism. Then, a bias-switching mechanism is designed subsequently according to the states of the neurons, thereby constructing the MHSNN. It is found that the designed switching functions enable the MHSNN to generate 8-to-12–16–20-scroll chaotic attractors. The dynamics analyses verify the existence of the MSCAs, it also exhibits two interesting dynamics phenomena: (1) the number and distribution of the scrolls correspond to the number and the location of the unstable index-2 saddle-focuses (USFs-2); (2) the number of branches in the bifurcation diagrams is half of the number of the scrolls. Moreover, the digital circuit of the MHSNN is designed and verified with the help of a field programmable gate array (FPGA), and the experimental results are displayed on an oscilloscope. Finally, due to the fact that the constructed MHSNN can generate chaotic sequences with higher randomness, an MHSNN-based image encryption scheme is proposed, some comparisons with existing methods verify that the proposed encryption scheme has the advantages of fast operation and easy implementation. [ABSTRACT FROM AUTHOR]

A novel perovskite BaNixCo1‒xO3‒δ (0 ≤ x ≤ 0.1) Negative Temperature Coefficient thermal ceramic material has been successfully synthesized using a solid-phase method. The XRD analysis revealed that the BaNixCo1‒xO3‒δ ceramics possess a hexagonal perovskite structure. Moderate doping with Ni ions facilitates high density in this perovskite ceramic material. The grain size exhibits a pattern of initially increasing and then decreasing with the addition of Ni2+ doping. The electrical resistivity of the perovskite ceramic material decreases and then increases with Ni2+ doping. The electrical conductivity mechanism of perovskite ceramic materials is consistent with the Mott VRH model in the temperature range below 105 K and the thermally activated conduction model in the 105–300 K temperature range. The resistivity, activation energy, and material constant B values of the ceramic material at 125 K range from 50.86–68.09 Ω·cm, 50.45–60.07 meV, and 652.79–687.02 K. A ceramic material with low B value and low resistance was developed for thermal applications, with a measurement temperature range of 10–300 K. The material shows promise for application in the specialized environmental monitoring industry. [ABSTRACT FROM AUTHOR]

Removing high-risk and persistent contaminants from water is challenging, because they typically exist at low concentrations in complex water matrices. Electrified flow-through technologies are viable to overcome the limitations induced by mass transport for efficient contaminant removal. Modifying the local environment of the flow-through electrodes offers opportunities to further improve the reaction kinetics and selectivity for achieving near-complete removal of these contaminants from water. Here, we present state-of-the-art local environment modification approaches that can be incorporated into electrified flow-through technologies to intensify water treatment. We first show methods of nanospace incorporation, local geometry adjustment, and microporous structure optimization that can induce spatial confinement, enhanced local electric field, and microperiodic vortex, respectively, for local environment modification. We then discuss why local environment modification can complement the flow-through electrodes for improving the reaction rate and selectivity. Finally, we outline appropriate scenarios of intensifying electrified flow-through technologies through local environment modification for fit-for-purpose water treatment applications. [ABSTRACT FROM AUTHOR]

Catalytic ozonation is regarded as a promising technology in the advanced treatment of refractory organic wastewater. Packed-bed reactors are widely used in practical applications due to simple structures, installation and operation. However, mass transfer of packed-bed reactors is relatively restrained and amplified deviations usually occurred in scale-up application. Herein, a multi-scale packed-bed model of catalytic ozonation was established to guide pilot tests. First, a laboratory-scale test was conducted to obtain kinetic parameters needed for modeling. Then, a multi-scale packed-bed model was developed to research the effects of water distribution structure, catalyst particle size, and hydraulic retention time (HRT) on catalytic ozonation. It was found that the performance of packed bed reactor was increased with evenly distributed water inlet, HRT of 60 min, and catalyst diameter of about 3–7 mm. Last, an optimized reactor was manufactured and a pilot-scale test was conducted to treat kitchen wastewater using catalytic ozonation process. In the pilot-scale test with an ozone dosage of 50 mg/L and HRT of 60 min, the packed-bed reactor filled with catalysts I was able to reduce chemical oxygen demand (COD) from 117 to 59 mg/L. The performance of the catalytic ozonation process in the packed-bed reactor for the advanced treatment of actual kitchen wastewater was investigated via both multi-scale simulation and pilot-scale tests in this study, which provided a practical method for optimizing the reactors of treating refractory organic wastewater. [ABSTRACT FROM AUTHOR]

Web image datasets curated online inherently contain ambiguous in-distribution instances and out-of-distribution instances, which we collectively call non-conforming (NC) instances. In many recent approaches for mitigating the negative effects of NC instances, the core implicit assumption is that the NC instances can be found via entropy maximization. For "entropy" to be well-defined, we are interpreting the output prediction vector of an instance as the parameter vector of a multinomial random variable, with respect to some trained model with a softmax output layer. Hence, entropy maximization is based on the idealized assumption that NC instances have predictions that are "almost" uniformly distributed. However, in real-world web image datasets, there are numerous NC instances whose predictions are far from being uniformly distributed. To tackle the limitation of entropy maximization, we propose (α , β) -generalized KL divergence, D KL α , β (p ‖ q) , which can be used to identify significantly more NC instances. Theoretical properties of D KL α , β (p ‖ q) are proven, and we also show empirically that a simple use of D KL α , β (p ‖ q) outperforms all baselines on the NC instance identification task. Building upon (α , β) -generalized KL divergence, we also introduce a new iterative training framework, GenKL, that identifies and relabels NC instances. When evaluated on three web image datasets, Clothing1M, Food101/Food101N, and mini WebVision 1.0, we achieved new state-of-the-art classification accuracies: 81.34 % , 85.73 % and 78.99 % / 92.54 % (top-1/top-5), respectively. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer. HCC with liver fluke infection could harbor unique biological behaviors. This study was aimed at investigating radiomics features of HCC with liver fluke infection and establishing a model to predict the expression of cytokeratin 7 (CK7) and cytokeratin 19 (CK19) as well as prognosis at the same time. A total of 134 HCC patients were included. Gadoxetic acid-enhanced magnetic resonance imaging (MRI) images of all patients were acquired. Radiomics features of the tumor were extracted and then data dimensionality was reduced. The radiomics model was established to predict liver fluke infection and the radiomics score (Radscore) was calculated. There were 11 features in the four-phase combined model. The efficiency of the combined model increased significantly compared to each single-phase MRI model. Radscore was an independent predictor of liver fluke infection. It was also significantly different between different expression of CK7/ CK19. Meanwhile, liver fluke infection was associated with CK7/CK19 expression. A cut-off value was set up and all patients were divided into high risk and low risk groups of CK7/CK19 positive expression. Radscore was also an independent predictor of these two biomarkers. Overall survival (OS) and recurrence free survival (RFS) of negative liver fluke infection group were significantly better than the positive group. OS and RFS of negative CK7 and CK19 expression were also better, though not significantly. Positive liver fluke infection and CK19 expression prediction groups harbored significantly worse OS and RFS, survival of positive CK7 expression prediction was unsatisfying as well. A radiomics model was established to predict liver fluke infection among HCC patients. This model could also predict CK7 and CK19 expression. OS and RFS could be foreseen by this model at the same time. [ABSTRACT FROM AUTHOR]

The crystal orientation effect on the mechanical properties and micro-deformation behavior of single-crystal iron (SC Fe) were revealed by molecular dynamics (MD) simulations. The results show that the surviving defects in the SC Fe models are [110] < [100] < [111], and only the vacancy and interstitial atomic clusters are formed in the [111] SC Fe model. Irradiation leads to the increase of elastic modulus owing to the annihilation of irradiation point defects. However, the non-annihilable irradiation clusters reduced the strength. The decrease of yield strain and yield strength of the [111] SC Fe model is significantly higher than those of [110] and [100] SC Fe models, exhibiting worse radiation damage resistance. This is due to the number and types of operation of slip systems in the [110] and [100] SC Fe after irradiation, which is caused by its poor inhibition of [111] crystal orientation on clusters under irradiation, being much lower than those in the [111] SC Fe. The yield strength of SC Fe increases with the increase of the number and length of 1/2 111 and 100 dislocations, while the plasticity decreases with the increase of the falling gradient of dislocations after yield. The purpose is to provide theoretical guidance for the microstructure design and regulation of radiation-damage-resistant iron-based materials. [ABSTRACT FROM AUTHOR]

Dynamic compression experiments of GH4169 alloy at deformation temperatures of 293–873 K and strain rates of 1000–6000 s−1 were performed based on the split Hopkinson pressure bar (SHPB) experimental platform to analyze its thermal deformation behavior and constitutive models. The experimental results show that the hot deformation behavior of GH4169 alloy is mainly limited by the combined action of temperature softening and strain hardening, and the true stress decreases with the increase in the deformation temperature or the decrease in the strain rate. Based on the experimental data, an improved artificial neural network (IANN) model and the classical Johnson–Cook (J–C) constitutive model were constructed to describe the deformation behavior of the studied GH4169 alloy, and the mean absolute error (MAE) was used to evaluate the accuracy of the two models. Based on the comparison of the experimental and predicted results, at strain rates of 1000–3000 s−1, the MAE of the IANN model was 5, which was only 1/20 that of the J–C model, thereby exhibiting perfect accuracy. At strain rates of 4000–6000 s−1, the MAE of the IANN model was increased to 82 and the accuracy was decreased, but the MAE was still only 1/4 that of the J–C model. Additionally, the IANN method was embedded in a visual operation interface for the construction of constitutive models with high precision and efficiency, and could be extended to constitutive models of other alloy materials. [ABSTRACT FROM AUTHOR]

H2O2 was produced at an appreciable rate in microbial reverse-electrodialysis cells (MRCs) coupled with thermolytic solutions, which can simultaneously capture waste heat as electrical energy. To determine the optimal cathode and membrane stack configurations for H2O2 production, different catalysts, catalyst loadings and numbers of membrane cell pairs were tested. Carbon black (CB) outperformed activated carbon (AC) for H2O2 production, although AC showed higher catalytic activity for oxygen reduction. The optimum CB loading was 10 mg/cm2 in terms of both the H2O2 production rate and power production. The optimum number of cell pairs was determined to be three based on a tradeoff between H2O2 production and capital costs. A H2O2 production rate as high as 0.99 ± 0.10 mmol/(L·h) was achieved with 10 mg/cm2 CB loading and 3 cell pairs, where the H2O2 recovery efficiency was 52 ± 2% and the maximum power density was 780 ± 37 mW/m2. Increasing the number of cell pairs to five resulted in an increase in maximum power density (980 ± 21 mW/m2) but showed limited effects on H2O2 production. These results indicated that MRCs can be an efficient method for sustainable H2O2 production. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) brought a healthy crisis all around the world. It's not only affected healthcare utilization, but also some disease's incidence. We collected pre-hospital emergency data in Chengdu from January 2016 to December 2021, and studied the demand for emergency medical services (EMSs), emergency response times (ERTs), and the disease spectrum in the city proper of Chengdu as a whole. A total of 1,122,294 prehospital emergency medical service (EMS) instances met the inclusion criteria. Under the influence of COVID-19, notably in 2020, the epidemiological characteristics of prehospital emergency services in Chengdu were considerably altered. However, as the pandemic was brought under control, they returned to normal or even earlier in 2021.The COVID-19 pandemic had an effect on people's medical care-seeking behavior and the performance of prehospital emergency services. Although the indicators associated with prehospital emergency services eventually recovered as the epidemic was brought under control, they remained marginally different from before the outbreak. [ABSTRACT FROM AUTHOR]

Membrane separation technology has made great progress in various practical applications, but the unsatisfactory separation performance of prevailing membrane materials hampers its further sustainable growth. This study proposed a novel nonpolar super-aligned carbon nanotube (SACNT) membrane, which was prepared with a layer-by-layer cross-stacking method. Through controlling the number of stacked SACNT layers, three kinds of SACNT membranes (SACNT 200, SACNT 300, and SACNT_400) were prepared. Systematic characterizations and filtration tests were performed to investigate their physico-chemical properties, surface wetting behavior, and filtration performance. Compared with two commercial membranes (Com_0.22 and Com_0.45), all the SACNT membranes achieved smoother and more uniform structures. Due to the hexagonal graphene structure of CNTs, the surface chemistry of the SACNT membranes is simple and inert, thereby potentially eliminating the covalent-bonding-induced membrane fouling. Besides, the SACNT membranes exhibited a typical nonpolar wetting behavior, with high contact angles for polar liquids (water: ∼124.9°–126.5°; formamide: ∼80.0°–83.9°) but low contact angles for nonpolar diiodomethane (∼18.8°–20.9°). This unique nonpolar feature potentially leads to weak interactions with polar substances. Furthermore, compared with the commercial membranes, the SACNT membranes obtained a significantly higher selectivity while achieving a comparable or higher permeability (depending on the number of stacked layers). Moreover, the SACNT membranes exhibited superior separation performance in various application scenarios, including municipal wastewater treatment (>2.3 times higher cleaning efficiency), electro-assistant fouling inhibition (or even self-cleaning), and oil/water separation (>99.2 % of separation efficiency), suggesting promising application prospects in various fields. [ABSTRACT FROM AUTHOR]

In this article, we study the secure control of the Markovian jumping neural networks (MJNNs) subject to deception attacks. Considering the limitation of the network bandwidth and the impact of the deception attacks, we propose two memory-based adaptive event-trigger mechanisms (AETMs). Different from the available event-trigger mechanisms, these two memory-based AETMs contain the historical triggered data not only in the triggering conditions, but also in the adaptive law. They can adjust the data transmission rate adaptively so as to alleviate the impact of deception attacks on the controlled system and to suppress the peak of the system response. In view of the proposed memory-based AETMs, a time-dependent Lyapunov functional is constructed to analyze the stability of the error system. Some sufficient conditions to ensure the asymptotical synchronization of master-slave MJNNs are obtained, and two easy-to-implement co-design algorithms for the feedback gain matrix and the trigger matrix are given. Finally, a numerical example is given to verify the feasibility and superiority of the two memory-based AETMs. [ABSTRACT FROM AUTHOR]

Purpose: Financial toxicity has become a global public health issue. The purpose of the study is to investigate and analyze the influencing factors of financial toxicity in patients with non-metastatic colorectal cancer. Methods: A convenient sample of 250 patients with stage I-III colorectal cancer was investigated in the study. They completed a set of questionnaires, including the Comprehensive Score for Financial Toxicity questionnaire, the Perceived Social Support Scale, and the Hospital Anxiety and Depression Scale. Univariate and multivariate linear regression were performed to investigate the influencing factors of financial toxicity. Results: Over half (52.8%, n = 132) of the colorectal cancer survivors experienced financial toxicity. Multivariate regression analysis showed that the factors associated with financial toxicity were young age, unemployment, low annual household income, chemotherapy, and the lack of sufficient social support (p < 0.05). Conclusions: Financial toxicity is common among non-metastatic colorectal cancer survivors. Young age, lower annual household income, unemployment, chemotherapy, and insufficient social support were associated with financial toxicity. [ABSTRACT FROM AUTHOR]

Gibbons are more sensitive to habitat loss and degradation than langurs, because gibbons have a frugivorous diet, smaller group size, and longer life history. Although I Trachypithecus francoisi i is not completely black, and both males and females have white cheeks, which is unlike the black Yuan, Niu et al. ([2]) concluded that Yuan refers to langurs because male langurs have a crest, langur morphology matches the description of the three types of Yuan, and male langurs produce a series of loud calls. [Extracted from the article]

Clean and sustainable H2 production is crucial to a carbon–neutral world. H2 generation by Chlamydomonas reinhardtii is an attractive approach for solar-H2 from H2O. However, it is currently not large-scalable because of lacking desirable strains with both optimal H2 productivity and sufficient knowledge of underlying molecular mechanism. We hereby carried out extensive and in-depth investigations of H2 photoproduction of hpm91 mutant lacking PGR5 (Proton Gradient Regulation 5) toward its up-scaling and fundamental mechanism issues. We show that hpm91 is at least 100-fold scalable (up to 10 L) with continuous H2 collection of 7287 ml H2/10L-HPBR in averagely 26 days under sulfur deprivation. Also, we show that hpm91 is robust and active during sustained H2 photoproduction, most likely due to decreased intracellular ROS relative to wild type. Moreover, we obtained quantitative proteomic profiles of wild type and hpm91 at four representing time points of H2 evolution, leading to 2229 and 1350 differentially expressed proteins, respectively. Compared to wild type, major proteome alterations of hpm91 include not only core subunits of photosystems and those related to anti-oxidative responses but also essential proteins in photosynthetic antenna, C/N metabolic balance, and sulfur assimilation toward both cysteine biosynthesis and sulfation of metabolites during sulfur-deprived H2 production. These results reveal not only new insights of cellular and molecular basis of enhanced H2 production in hpm91 but also provide additional candidate gene targets and modules for further genetic modifications and/or in artificial photosynthesis mimics toward basic and applied research aiming at advancing solar-H2 technology. [ABSTRACT FROM AUTHOR]

Bronze has been used for various applications since ancient times, and therefore, its preservation is critical. However, preserving bronze is challenging. The traditional inhibitor sealing method is limited by its toxicity and sealing effects. In this study, a benzotriazole (BTA) inhibitor loaded with a composite hydrogel of sodium alginate and cyclic-peptide-grafted β-cyclodextrin was prepared. The chemical structure of the components of the composite hydrogel coating was characterized through Fourier-transform infrared spectroscopy. The microstructure of the coating on bronzeware was characterized through scanning electronic microscopy. The thermal analysis of the composite hydrogel coating confirmed that BTA was introduced successfully into the composite hydrogel, and the coating exhibited the liquid crystalline property because of the mesogenic unit—cyclic peptide. Electrochemical impedance spectroscopy revealed that the modified β-cyclodextrin-loaded benzotriazole considerably improved the corrosion resistance. In a certain range, the higher was the BTA-loaded Cyc-g-β-CD ratio, the stronger was the protective effect of the gel coating. In conclusion, corrosion inhibitors can considerably improve the corrosion resistance of gel coatings. [ABSTRACT FROM AUTHOR]

The rapid global spread of coronavirus disease 2019 (COVID-19) has promoted concern over human pathogens and their significant threats to public health security. The monitoring and control of human pathogens in public sanitation and health facilities are of great importance. Excessive sludge is an inevitable byproduct of sewage that contains human and animal feces in wastewater treatment plants (WWTPs). It is an important sink of different pollutants and pathogens, and the proper treatment and disposal of sludge are important to minimize potential risks to the environment and public health. However, there is a lack of comprehensive analysis of the diversity, exposure risks, assessment methods and inactivation techniques of pathogenic microorganisms in sludge. Based on this consideration, this review summarizes the control performance of pathogenic microorganisms such as enterovirus, Salmonella spp., and Escherichia coli by different sludge treatment technologies, including composting, anaerobic digestion, aerobic digestion, and microwave irradiation, and the mechanisms of pathogenic microorganism inactivation in sludge treatment processes are discussed. Additionally, this study reviews the diversity, detection methods, and exposure risks of pathogenic microorganisms in sludge. This review advances the quantitative assessment of pathogenic microorganism risks involved in sludge reuse and is practically valuable to optimize the treatment and disposal of sludge for pathogenic microorganism control. [ABSTRACT FROM AUTHOR]

While a growing number of wastewater treatment plants (WWTPs) are being retrofitted from the conventional activated sludge (CAS) process to the membrane bioreactor (MBR) process, the debate on the techno-economy of MBR vs. CAS has continued and calls for a thorough assessment based on techno-economic valuation. In this study, we analyzed the operating data of 20 large-scale WWTPs (capacity ⩾ 10000 m3/d) and compared their techno-economy before and after the retrofitting from CAS to MBR. Through cost-benefit analysis, we evaluated the net profit by subtracting the operating cost from the environmental benefit (estimated by the shadow price of pollutant removal and water reclamation). After the retrofitting, the removal rate of pollutants increased (e.g., from 89.0% to 93.3% on average for NH3-N), the average energy consumption increased from 0.40 to 0.57 kWh/m3, but the operating cost did not increase significantly. The average marginal environmental benefit increased remarkably (from 0.47 to 0.66 CNY/g for NH3-N removal), leading to an increase in the average net profit from 19.4 to 24.4 CNY/m3. We further scored the technical efficiencies via data envelopment analysis based on non-radial directional distance functions. After the retrofitting, the relative cost efficiency increased from 0.70 to 0.73 (the theoretical maximum is 1), while the relative energy efficiency did not change significantly. The techno-economy is closely related to the effluent standard adopted, particularly when truncating the extra benefit of pollutant removal beyond the standard in economic modeling. The modeling results suggested that MBR is more profitable than CAS given stricter effluent standards. [ABSTRACT FROM AUTHOR]

The distribution of antibiotic resistance genes (ARGs) has been intensively studied in large-scale wastewater treatment plants and livestock sources. However, small-scale decentralized sewage treatment facilities must also be explored due to their possible direct exposure to residents. In this study, six wastewater treatment facilities in developed rural areas in eastern China were investigated to understand their risks of spreading ARGs. Using metagenomics and network analysis tools, ARGs and bacterial and viral communities were identified in the influent (INF) and effluent (EFF) samples. The dominant ARGs belonged to the bacitracin class, which are different from most of municipal wastewater treatment plants (WWTPs). The dominant hosts of ARGs are Acidovorax in bacterial communities and Prymnesiovirus in viral communities. Furthermore, a positive relationship was found between ARGs and phages. The ARGs significantly correlated with phages were all hosted by specific genera of bacteria, indicating that phages had contributed to the ARG's proliferation in sewage treatment facilities. Paying significant concern on the possible enhanced risks caused by bacteria, viruses and their related ARGs in decentralized sewage treatment facilities is necessary. [ABSTRACT FROM AUTHOR]

Background: Lupus erythematosus is an autoimmune disease that causes damage to multiple organs ranging from skin lesions to systemic manifestations. Cutaneous lupus erythematosus (CLE) is a common type of lupus erythematosus (LE), but its molecular mechanisms are currently unknown. The study aimed to explore changes in the gene expression profiles and identify key genes involved in CLE, hoping to uncover its molecular mechanism and identify new targets for CLE. Method: We analyzed the microarray dataset (GSE109248) derived from the Gene Expression Omnibus (GEO) database, which was a transcriptome profiling of CLE cutaneous lesions. The differentially expressed genes (DEGs) were identified, and the functional annotation of DEGs was performed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) network was also constructed to identify hub genes involved in CLE. Result: A total of 755 up-regulated DEGs and 405 down-regulated DEGs were identified. GO enrichment analysis showed that defense response to virus, immune response, and type I interferon signaling pathway were the most significant enrichment items in DEGs. The KEGG pathway analysis identified 51 significant enrichment pathways, which mainly included systemic lupus erythematosus, osteoclast differentiation, cytokine-cytokine receptor interaction, and primary immunodeficiency. Based on the PPI network, the study identified the top 10 hub genes involved in CLE, which were CXCL10, CCR7, FPR3, PPARGC1A, MMP9, IRF7, IL2RG, SOCS1, ISG15, and GSTM3. By comparison between subtypes, the results showed that ACLE had the least DEGs, while CCLE showed the most gene and functional changes. Conclusion: The identified hub genes and functional pathways found in this study may expand our understanding on the underlying pathogenesis of CLE and provide new insights into potential biomarkers or targets for the diagnosis and treatment of CLE. Key Points • The bioinformatics analysis based on CLE patients and healthy controls was performed and 1160 DEGs were identified • The 1160 DEGs were mainly enriched in biological processes related to immune responses, including innate immune response, type I interferon signaling pathway, interferon-γ-mediated signaling pathway, positive regulation of T cell proliferation, regulation of immune response, antigen processing, and presentation via MHC class Ib and so on • KEGG pathway enrichment analysis indicated that DEGs were mainly enriched in several immune-related diseases and virus infection, including systemic lupus erythematosus, primary immunodeficiency, herpes simplex infection, measles, influenza A, and so on • The hub genes such as CXCL10, IRF7, MMP9, CCR7, and SOCS1 may become new markers or targets for the diagnosis and treatment of CLE [ABSTRACT FROM AUTHOR]

Tissue-engineered vascular grafts are increasing in popularity in the treatment of cardiovascular disease. However, poor mechanical strength, brittle texture and other defects restrict their extensive application. In the present work, oligopeptide hybrid films were prepared by L-tyrosine-derivative oligopeptide (TEA), polyethylene glycol (PEG) and polyvinyl alcohol (PVA). The films were prepared with different PEG molecular weights and TEA contents. The chemical structures were characterized using Fourier-transform infrared spectroscopy, while the micromorphology and self-assembly behaviour were examined using scanning electron microscopy and differential scanning calorimetry. The mechanical properties of the films were investigated, and the cellular behaviour was observed using polarized optical microscopy. The experimental results indicated that the degree of microphase separation depended on the molecular weight of the PEG and TEA content. The biocompatibility of the films improved as the TEA content increased. The liquid crystalline properties of the TEA affected the cell orientation. The films are expected to be incorporated into applications in the vascular tissue engineering field. [ABSTRACT FROM AUTHOR]

Purpose: To compare the outcomes of macular buckling (MB) surgery between myopic foveal detachment (FD) eyes with and without ellipsoid zone (EZ) disruption. Methods: A retrospective, case-control study. Forty-four consecutive eyes from 44 patients received MB surgery for myopic FD between November 2017 and January 2019 were included. The eyes were divided into two groups according to the integrity of EZ on spectral-domain optical coherence tomography (SD-OCT): 28 eyes with disrupted EZ band and 16 eyes with intact EZ band. Main outcome measures were visual acuity and the duration of subfoveal fluid (SFF) after MB. Results: The mean follow-up time was 17.64 ± 6.61 and 16.06 ± 5.78 months in the disrupted EZ and intact EZ group, respectively (P = 0.430). The logMAR best-corrected visual acuity (BCVA) improved significantly, from 1.13 ± 0.46 and 1.12 ± 0.39 at baseline to 0.85 ± 0.65 (P = 0.002) and 0.53 ± 0.33 (P = 0.000) for the disrupted EZ group and intact EZ group, respectively. The mean visual improvement was 15.00 ± 14.14 Early Treatment Diabetic Retinopathy Study (ETDRS) letters for the disrupted EZ group and 26.88 ± 19.48 ETDRS letters for the intact EZ group. Significant difference was found on both final postoperative BCVA (P = 0.035) and visual improvement (P = 0.025). At 6 months, SFF remained in 53.57% (15/28) of the eyes in the disrupted EZ group and in only 12.50% (2/16) of the eyes in the intact EZ group (P = 0.018). Conclusion: The intact EZ group showed better functional and anatomical outcomes than the disrupted EZ group after MB surgery. [ABSTRACT FROM AUTHOR]

Anodic aluminum oxide (AAO) templates have been intensively investigated during the past decades and have meanwhile been widely applied through both sacrificial and non-sacrificial pathways. In numerous non-sacrificial applications, the AAO membrane is maintained as part of the obtained composite materials; hence, the template structure and topography determine to a great extent the potential applications. Through-hole isotropic AAO features nanochannels that promote transfer of matter, while anisotropic AAO with barrier layer exhibits nanocavities suitable as independent and homogenous containers. By combining the two kinds of AAO membranes with diverse organic and inorganic materials through physical interactions or chemical bonds, AAO composites are designed and applied in versatile fields such as catalysis, drug release platform, separation membrane, optical appliances, sensors, cell culture, energy, and electronic devices. Therefore, within this review, a perspective on exhilarating prospect for complementary advancement on AAO composites both in preparation and application is provided. [ABSTRACT FROM AUTHOR]

Objectives: Comparing the diagnostic efficacy of diffusion kurtosis imaging (DKI) derived from different region of interest (ROI) methods in tumor parenchyma for grading and predicting IDH-1 mutation and 1p19q co-deletion status of glioma patients and correlating with their survival data. Methods: Sixty-six patients (29 females; median age, 45 years) with pathologically proved gliomas (low-grade gliomas, 36; high-grade gliomas, 30) were prospectively included, and their clinical data were collected. All patients underwent DKI examination. DKI maps of each metric were derived. Three groups of ROIs (ten spots, ROI-10s; three biggest tumor slices, ROI-3s; and whole-tumor parenchyma, ROI-whole) were manually drawn by two independent radiologists. The interobserver consistency, time spent, diagnostic efficacy, and survival analysis of DKI metrics based on these three ROI methods were analyzed. Results: The intraexaminer reliability for all parameters among these three ROI methods was good, and the time spent on ROI-10s was significantly less than that of the other two methods (p < 0.001). DKI based on ROI-10s demonstrated a slightly better diagnostic value than the other two ROI methods for grading and predicting the IDH-1 mutation status of glioma, whereas DKI metrics derived from ROI-10s performed much better than those of the ROI-3s and ROI-whole in identifying 1p19q co-deletion. In survival analysis, the model based on ROI-10s that included patient age and mean diffusivity showed the highest prediction value (C-index, 0.81). Conclusions: Among the three ROI methods, the ROI-10s method had the least time spent and the best diagnostic value for a comprehensive evaluation of glioma. It is an effective way to process DKI data and has important application value in the clinical evaluation of glioma. Key Points: • The intraexaminer reliability for all DKI parameters among different ROI methods was good, and the time spent on ROI-10 spots was significantly less than the other two ROI methods. • DKI metrics derived from ROI-10 spots performed the best in ROI selection methods (ROI-10s, ten-spot ROIs; ROI-3s, three biggest tumor slices ROI; and ROI-whole, whole-tumor parenchyma ROI) for a comprehensive evaluation of glioma. • The ROI-10 spots method is an effective way to process DKI data and has important application value in the clinical evaluation of glioma. [ABSTRACT FROM AUTHOR]

The practical application of the capacitive deionization (CDI) enhanced ultrafiltration (CUF) technology is hampered due to low performance of electrodes. The current study demonstrated a novel super-aligned carbon nanotube (SACNT)/activated carbon (AC) composite electrode, which was prepared through coating AC on a cross-stacked SACNT film. The desalination capability and water purification performance of the prepared electrode were systematically investigated at different applied voltages (0.8–1.2 V) with a CDI system and a CUF system, respectively. In the CDI tests, as compared with the control AC electrode, the SACNT/AC electrode achieved an approximately 100% increase in both maximum salt adsorption capacity and average salt adsorption rate under all the applied voltage conditions, demonstrating a superior desalination capability. Meanwhile, a conspicuous increase by an average of ∼26% in charge efficiency was also achieved at all the voltages. In the CUF tests, as compared with the control run at 0 V, the treatment runs at 0.8, 1.0, and 1.2 V achieved a 2.40-fold, 2.08-fold, and 2.43-fold reduction in membrane fouling (calculated according to the final transmembrane pressure (TMP) data at the end of every purification stage), respectively. The average TMP increasing rates at 0.8, 1.0, and 1.2 V were also roughly two times smaller than that at 0 V, indicating a dramatical reduction of membrane fouling. The SACNT/AC electrode also maintained its superior desalination capability in the CUF process, resulting in an overall improved water purification efficiency. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of l 2 – l ∞ asynchronous filtering for a class of discrete-time fuzzy neural networks subject to Markov jump parameters and unreliable communication links. Due to the fact that neural networks possess the nonlinear dynamic characteristic, it is difficult to deal with such a nonlinear characteristic directly, so the Takagi–Sugeno fuzzy model is introduced to approximate the system. Directed against the unreliable communication links, the data packet loss depicted by a stochastic variable with Bernoulli distribution and the signal quantization phenomenon occurring in communication channels are taken into consideration simultaneously. The attention of this paper is mainly centered on devising an asynchronous l 2 – l ∞ filter for ensuring the l 2 – l ∞ performance of the studied system under asynchronous conditions. Some sufficient conditions for the existence of the asynchronous l 2 – l ∞ filter are presented. Finally, a numerical example is given to carry out the simulation experiment, which can verify the effectiveness of the obtained results. [ABSTRACT FROM AUTHOR]

This paper studies the stabilization problem of delayed memristive neural networks under event-triggered control. A refined switching event-trigger scheme that switches between variable sampling and continuous event-trigger can be designed by introducing an exponential decay term into the threshold function. Compared with the existing mechanisms, the proposed scheme can enlarge the interval between two successively triggered events and therefore can reduce the amount of triggering times. By constructing a time-dependent and piecewise-defined Lyapunov functional, a less-conservative criterion can be derived to ensure global stability of the closed-loop system. Based on matrix decomposition, equivalent conditions in linear matrix inequalities form of the above stability criterion can be established for the co-design of both the trigger matrix and the feedback gain. A numerical example is provided to demonstrate the effectiveness of the theoretical analysis and the advantages of the refined switching event-trigger scheme. [ABSTRACT FROM AUTHOR]

This paper studies the exponential synchronization of chaotic delayed neural networks (CDNNs) under aperiodic sampled-data control. First, an aperiodic sampled-data controller with exponentially decaying gain is designed to enlarge the maximum sampling period and the maximum allowable delay while still preserving the stability of the closed-loop system. Then, a novel time-dependent Lyapunov functional that consists of the information of the exponential decay rate η is elaborately designed to analyze the stability of the closed-loop system instead of using the common "change of coordinates" method.With the aid of Lyapunov theory and some inequality techniques, the sufficient conditions are established to guarantee the exponential synchronization of master-slave CDNNs. Based on matrix transformation, the equivalent conditions in LMI form are established to design the feedback gain. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed controller and the obtained synchronization criteria. [ABSTRACT FROM AUTHOR]

We consider positive solutions to the weighted elliptic problem - div (| x | θ ∇ u) = | x | ℓ u p in R N \ B ¯ , u = 0 on ∂ B , where B is the standard unit ball of R N . We give a complete answer for the existence question for N ′ : = N + θ > 2 and p > 0 . In particular, for N ′ > 2 and τ : = ℓ - θ > - 2 , it is shown that for 0 < p ≤ p s : = N ′ + 2 + 2 τ N ′ - 2 , the only nonnegative solution to the problem is u ≡ 0 . This nonexistence result is new, even for the classical case θ = ℓ = 0 and N N - 2 < p ≤ N + 2 N - 2 , N ≥ 3 . The interesting feature here is that we do not require any behavior at infinity or any symmetry assumption. [ABSTRACT FROM AUTHOR]

This research addresses the synchronization of delayed fractional-order memristive neural networks (DFMNNs) via quantized control. The motivations are twofold: (1) the transmitted information may be constrained by limited bandwidths; (2) the existing analysis techniques are difficult to establish LMI-based synchronization criteria for DFMNNs within a networked control environment. To overcome these difficulties, the logarithmic quantization is adopted to design two types of energy-saving and cost-effective quantized controllers. Then, under the framework of sector bound approach, the closed-loop drive-response DFMNNs can be represented as an interval system with uncertain feedback gains. By utilizing appropriate fractional-order Lyapunov functional and some inequality techniques, two LMI-based synchronization criteria for DFMNNs are derived to establish the relationship between the feedback gain and the quantization parameter. Finally, two illustrative examples are presented to validate the effectiveness of the proposed control schemes. [ABSTRACT FROM AUTHOR]

This study aims to propose a multi-point integrated real-time control method based on discrete dynamic water level variations, which can be realized only based on the programmable logic controller (PLC) system without using a complex mathematical model. A discretized water level control model was developed to conduct the real-time control based on data-automation. It combines the upstream pumping stations and the downstream influent pumping systems of wastewater treatment plant (WWTP). The discretized water level control method can regulate dynamic wastewater pumping flow of pumps following the dynamic water level variation in the sewer system. This control method has been successfully applied in practical integrated operations of sewer-WWTP following the sensitive flow disturbances of the sewer system. The operational results showed that the control method could provide a more stabilized regulate pumping flow for treatment process; it can also reduce the occurrence risk of combined sewer overflow (CSO) during heavy rainfall events by increasing transport capacity of pumping station and influent flow in WWTP, which takes full advantage of storage space in the sewer system. [ABSTRACT FROM AUTHOR]

The membrane bioreactor (MBR) technology is a rising star for wastewater treatment. The pollutant elimination and membrane fouling performances of MBRs are essentially related to the dissolved organic matter (DOM) in the system. Three-dimensional excitation-emission matrix (3D-EEM) fluorescence spectroscopy, a powerful tool for the rapid and sensitive characterization of DOM, has been extensively applied in MBR studies; however, only a limited portion of the EEM fingerprinting information was utilized. This paper revisits the principles and methods of fluorescence EEM, and reviews the recent progress in applying EEM to characterize DOM in MBR studies. We systematically introduced the information extracted from EEM by considering the fluorescence peak location/ intensity, wavelength regional distribution, and spectral deconvolution (giving fluorescent component loadings/scores), and discussed how to use the information to interpret the chemical compositions, physiochemical properties, biological activities, membrane retention/fouling behaviors, and migration/ transformation fates of DOM in MBR systems. In addition to conventional EEM indicators, novel fluorescent parameters are summarized for potential use, including quantum yield, Stokes shift, excited energy state, and fluorescence lifetime. The current limitations of EEM-based DOM characterization are also discussed, with possible measures proposed to improve applications in MBR monitoring. [ABSTRACT FROM AUTHOR]

Developing high activity, low-cost and long durability catalysts for oxygen reduction reaction is of great significance for the practical application of microbial fuel cells. The full exposure of active sites in catalysts can enhance catalytic activity dramatically. Here, novel Fe-N-doped graphene is successfully synthesized via a one-step in situ ball milling method. Pristine graphite, ball milling graphene, N-doped graphene and Fe-N-doped graphene are applied in air cathodes, and enhanced performance is observed in microbial fuel cells with graphene-based catalysts. Particularly, Fe-N-doped graphene achieves the highest oxygen reduction reaction activity, with a maximum power density of 1380±20 mW/m2 in microbial fuel cells and a current density of 23.8 A/m2 at −0.16 V in electrochemical tests, which are comparable to commercial Pt and 390% and 640% of those of pristine graphite. An investigation of the material characteristics reveals that the superior performance of Fe-N-doped graphene results from the full exposure of Fe2O3 nanoparticles, pyrrolic N, pyridinic N and excellent Fe-N-G active sites on the graphene matrix. This work not only suggests the strategy of maximally exposing active sites to optimize the potential of catalysts but also provides promising catalysts for the use of microbial fuel cells in sustainable energy generation. [ABSTRACT FROM AUTHOR]

This paper is devoted to investigating the H ∞ filtering problem for Markov jump neural networks with hidden-Markov mode observation and packet dropouts, in which the information regarding to the Markov state can not be completely acquired. To address this circumstance, a hidden Markov model (HMM)-based technique is established. That is employing a detector to detect the information of the Markov state and then giving an estimated signal of the Markov state for the filter design. Some H ∞ performance analysis criteria for filtering error systems and the corresponding HMM-based filter design procedure are given. An improved activation function dividing method (AFDM) is presented for neural networks to reduce the conservatism of the obtained results. The superiority of the improved AFDM and the validity of obtained results are verified by an illustrative example. [ABSTRACT FROM AUTHOR]

Objectives: Computed tomography (CT) and magnetic resonance imaging (MRI) are the most commonly selected methods for imaging gliomas. Clinically, radiotherapists always delineate the CT glioma region with reference to multi-modal MR image information. On this basis, we develop a deep feature fusion model (DFFM) guided by multi-sequence MRIs for postoperative glioma segmentation in CT images.Methods: DFFM is a multi-sequence MRI-guided convolutional neural network (CNN) that iteratively learns the deep features from CT images and multi-sequence MR images simultaneously by utilizing a multi-channel CNN architecture, and then combines these two deep features together to produce the segmentation result. The whole network is optimized together via a standard back-propagation. A total of 59 CT and MRI datasets (T1/T2-weighted FLAIR, T1-weighted contrast-enhanced, T2-weighted) of postoperative gliomas as tumor grade II (n = 24), grade III (n = 18), or grade IV (n = 17) were included. Dice coefficient (DSC), precision, and recall were used to measure the overlap between automated segmentation results and manual segmentation. The Wilcoxon signed-rank test was used for statistical analysis.Results: DFFM showed a significantly (p < 0.01) higher DSC of 0.836 than U-Net trained by single CT images and U-Net trained by stacking the CT and multi-sequence MR images, which yielded 0.713 DSC and 0.818 DSC, respectively. The precision values showed similar behavior as DSC. Moreover, DSC and precision values have no significant statistical difference (p > 0.01) with difference grades.Conclusions: DFFM enables the accurate automated segmentation of CT postoperative gliomas of profit guided by multi-sequence MR images and may thus improve and facilitate radiotherapy planning.Key Points: • A fully automated deep learning method was developed to segment postoperative gliomas on CT images guided by multi-sequence MRIs. • CT and multi-sequence MR image integration allows for improvements in deep learning postoperative glioma segmentation method. • This deep feature fusion model produces reliable segmentation results and could be useful in delineating GTV in postoperative glioma radiotherapy planning. [ABSTRACT FROM AUTHOR]

We are interested in the qualitative properties of positive entire solutions of the equation (1) It is known from [13, Theorem 4.2] that any positive entire solution u of (0.1) is radially symmetric with respect to x = 0, i.e., u(x) = u(|x|), and equation (0.1) also admits a special positive entire solution . We first show that u - us changes signs infinitely many times in (0, ∞) for any positive singular entire solution u ≠= us in ℛN{0} of (0.1). Moreover, equation (0.1) admits a positive entire singular solution u(x) = u(|x|)) such that the scalar curvature of the conformal metric with conformal factor is positive and is 2T-periodic with suitably large T. [ABSTRACT FROM AUTHOR]

This paper deals with the issue of mixed ℋ∞ and ℒ2 — ℒ∞ anti-synchronization control for chaotic delayed recurrent neural networks with unknown parameters and stochastic noise. By means of the Lyapunov- Krasovskii functional method and some stochastic analysis techniques, an adaptive controller strategy is proposed to guarantee the mixed ℋ∞ and ℒ2 — ℒ∞ anti-synchronization of the drive and response systems. When there is no stochastic noise, it is shown that the present control strategy is less conservative and less complex than a previously reported adaptive control method. Finally, a numerical example is employed to illustrate the applicability of the proposed adaptive control strategy. [ABSTRACT FROM AUTHOR]

This paper thoroughly investigates the synchronization control issue for the switched neural networks. The more comprehensive comparatively switching rule, persistent dwell-time, is applied to actuate the aforementioned neural networks. For tackling the problem caused by the transmission of tremendous data, the quantizer is utilized. The objective is to establish the mixed controller with multi quantization densities for the synchronization error neural networks to meet the various accuracy requirements of the transmitted data. Whereafter, the sufficient conditions of the extended H ∞ performance and global uniform exponential stability for the synchronization error neural networks are constructed. Conclusively, the capability of the proposed mixed controller is elucidated through a numerical example. [ABSTRACT FROM AUTHOR]

In this work, the influence of solvothermal crystallization processes on the microstructure, pore characteristic, and adsorption/photocatalysis of SiO2-W0.02TiO2.06 composite aerogels synthesized via ambient pressure drying have been investigated. It has been clarified that the composite aerogels prepared via solvothermal crystallization at 120 °C for 0.5 h and 180 °C for 3 h exhibited high-specific surface area (416–729 m2/g) and pore volume (2.26–2.70 cm3/g). With the increase of solvothermal crystallization temperature and time, the crystallinity of composite aerogels increased gradually, but excessive solvothermal crystallization time at higher temperature decreased the pore volume greatly. Furthermore, it is found that bacterial cellulose (BC) in the composite gel plays an important role in enhancing the pore volume and crystallization of the SiO2-W0.02TiO2.06 composite aerogels as a pore-expanding agent and structure-directing agent. The as-synthesized SiO2-W0.02TiO2.06 composite aerogels exhibited higher adsorption and removal efficiency for RhB than the commercial P25-TiO2, which can be ascribed to its high pore volume and specific surface area, as well as the synergistic action of adsorption and photocatalysis. Highlights: Effects of solvothermal crystallization on preparing SiO2-W0.02TiO2.06 aerogels were investigated. Solvothermal process can greatly promote the crystallization of the composite aerogels. Appropriate solvothermal process is favorable infor achieving higher pore volume of aerogels. The SiO2-W0.02TiO2.06 composite aerogels showed synergistic effect of adsorption and photocatalysis. [ABSTRACT FROM AUTHOR]

Aiming to reduce the energy input, oxygen supply by trickling filter was employed in a biocathode microbial fuel cell (MFC) to examine its performance of electricity production and sewage treatment. During batch operation, trickling MFC (TMFC) could start and aerate effectively (DO>3.60 mg/L). During continuous operation, TMFC produced a maximum current density of 71.8 A/m3 and maximum power density of 26.2 W/m3 under the hydraulic retention time (HRT) of 10 h. By increasing the HRT to 15 h, 90.6% of COD and 99.0% of ammonia in simulated domestic sewage were efficiently removed and the maximum power density was 19.4 W/m3. Continuous purification of real municipal wastewater achieved 85.9% of COD removal rate and 91.6% of ammonia removal rate. Sequencing result of biocathodic microorganisms indicated that it consisted of four major classes and the dominant class was γ-proteobacteria, which accounted for up to 84.38%. The dominant genus was Acinetobacter, which accounted for 57.81%. The phylogenetic tree showed different relationships among the 19 species of biocathode microorganisms and the predominant species was Acinetobacter calcoaceticus. [ABSTRACT FROM AUTHOR]

In the work, a class of Markov jump neural networks in the discrete-time domain with fading channels are taken into account. The main aim is to investigate the H ∞ state estimation issue when the Rice fading occurs in measured networks. In the first place, the analyses of the finite-time boundedness and the H ∞ performance for the estimation error system with the aid of finite-time stability theory are presented. Some conditions which guarantee the solvability of the addressed problem are established. Furthermore, by applying an unique decoupling method, the gains of the presented estimator are obtained under the feasible solutions of the conditions derived before. Finally, the validity of the presented approach is verified by a numerical example. [ABSTRACT FROM AUTHOR]

Using 28-year satellite-borne Special Sensor Microwave Imager observations, features of high-wind frequency (HWF) over the southern Indian Ocean are investigated. Climatology maps show that high winds occur frequently during austral winter, located in the open ocean south of Polar Front in subpolar region, warm flank of the Subantarctic Front between 55°E–78°E, and south of Cape Agulhas, where westerly wind prevails. The strong instability of marine atmospheric boundary layer accompanied by increased sensible and latent heat fluxes on the warmer flank acts to enhance the vertical momentum mixing, thus accelerate the surface winds. Effects of sea surface temperature (SST) front can even reach the entire troposphere by deep convection. HWF also shows distinct interannual variability, which is associated with the Southern Annual Mode (SAM). During positive phase of the SAM, HWF has positive anomalies over the open ocean south of Polar Front, while has negative anomalies north of the SST front. A phase shift of HWF happened around 2001, which is likely related to the reduction of storm tracks and poleward shift of westerly winds in the Southern Hemisphere. [ABSTRACT FROM AUTHOR]