Zonotopic fault detection observer design for Takagi–Sugeno fuzzy systems

This paper considers zonotopic fault detection observer design in the finite-frequency domain for discrete-time Takagi–Sugeno fuzzy systems with unknown but bounded disturbances and measurement noise. We present a novel fault detection observer structure, which is more general than the commonly used Luenberger form. To make the generated residual sensitive to faults and robust against disturbances, we develop a finite-frequency fault detection observer based on generalised Kalman–Yakubovich–Popov lemma and P-radius criterion. The design conditions are expressed in terms of linear matrix inequalities. The major merit of the proposed method is that residual evaluation can be easily implemented via zonotopic approach. Numerical examples are conducted to demonstrate the proposed methodPeer ReviewedPostprint (author's final draft

A model of rotating hotspots for 3:2 frequency ratio of HFQPOs in black hole X-ray binaries

We propose a model to explain a puzzling 3:2 frequency ratio of high frequency quasi-periodic oscillations (HFQPOs) in black hole (BH) X-ray binaries, GRO J1655-40, GRS 1915+105 and XTE J1550-564. In our model a non-axisymmetric magnetic coupling (MC) of a rotating black hole (BH) with its surrounding accretion disc coexists with the Blandford-Znajek (BZ) process. The upper frequency is fitted by a rotating hotspot near the inner edge of the disc, which is produced by the energy transferred from the BH to the disc, and the lower frequency is fitted by another rotating hotspot somewhere away from the inner edge of the disc, which arises from the screw instability of the magnetic field on the disc. It turns out that the 3:2 frequency ratio of HFQPOs in these X-ray binaries could be well fitted to the observational data with a much narrower range of the BH spin. In addition, the spectral properties of HFQPOs are discussed. The correlation of HFQPOs with jets from microquasars is contained naturally in our model.Comment: 8 pages, 4 figures. accepted by MNRA

The preparation, characterization, and pharmacokinetic studies of chitosan nanoparticles loaded with paclitaxel/dimethyl-β-cyclodextrin inclusion complexes.

A novel biocompatible and biodegradable drug-delivery nanoparticle (NP) has been developed to minimize the severe side effects of the poorly water-soluble anticancer drug paclitaxel (PTX) for clinical use. PTX was loaded into the hydrophobic cavity of a hydrophilic cyclodextrin derivative, heptakis (2,6-di-O-methyl)-β-cyclodextrin (DM-β-CD), using an aqueous solution-stirring method followed by lyophilization. The resulting PTX/DM-β-CD inclusion complex dramatically enhanced the solubility of PTX in water and was directly incorporated into chitosan (CS) to form NPs (with a size of 323.9–407.8 nm in diameter) using an ionic gelation method. The formed NPs had a zeta potential of +15.9–23.3 mV and showed high colloidal stability. With the same weight ratio of PTX to CS of 0.7, the loading efficiency of the PTX/DM-β-CD inclusion complex-loaded CS NPs was 30.3-fold higher than that of the PTX-loaded CS NPs. Moreover, it is notable that PTX was released from the DM-β-CD/CS NPs in a sustained-release manner. The pharmacokinetic studies revealed that, compared with reference formulation (Taxol(®)), the PTX/DM-β-CD inclusion complex-loaded CS NPs exhibited a significant increase in AUC(0→24h) (the area under the plasma drug concentration–time curve over the period of 24 hours) and mean residence time by 2.7-fold and 1.4-fold, respectively. Therefore, the novel drug/DM-β-CD inclusion complex-loaded CS NPs have promising applications for the significantly improved delivery and controlled release of the poorly water-soluble drug PTX or its derivatives, thus possibly leading to enhanced therapeutic efficacy and less severe side effects

Sustainability and ecological efficiency of low-carbon power system: A concentrating solar power plant in China

Low-carbon power generation has been proposed as the key to address climate change. However, the sustainability and ecological efficiency of the generating plants have not been fully understood. This study applies emergy analysis and systems accounting to a pilot solar power tower plant in China for the first time to elaborate its sustainable and ecological performances. Emergy analysis covers virtually all aspects of sustainability and ecological efficiency by considering different forms of materials inputs, environmental support and human labor on the same unit of "solar joule". The input-output analysis based systems accounting is applied to trace the complete emergy embodied in the supply chain for all product materials of the given plant against the back ground of complex economic network, which improved the accuracy of accounting. This analysis illustrated unexpectedly low sustainability and ecological efficiency of this particular plant compared with the emergy analysis based on the primary materials (steel, iron, cement, etc.). Purchased emergy responses more than 95% of the total and emergy input in the construction phase is more than twice as much as that in the operation phase. Comparisons with other kinds of clean energy technologies indicate previous studies may have overestimated the sustainability and ecological benefits of low-carbon power plants. Thus, it is necessary to establish this kind of unified accounting framework. In addition, sensitivity analysis suggests that strictly controlling monetary costs of purchased inputs, extending service lifetime and improving power generation efficiency can promote higher sustainability and ecological efficiency for solar power tower plants. This study provides a more comprehensive framework for quantitative emergy-based evaluation of the sustainability and ecological efficiency for low-carbon power systems

A de Bruijn graph approach to the quantification of closely-related genomes in a microbial community

The wide applications of next-generation sequencing (NGS) technologies in metagenomics have raised many computational challenges. One of the essential problems in metagenomics is to estimate the taxonomic composition of a microbial community, which can be approached by mapping shotgun reads acquired from the community to previously characterized microbial genomes followed by quantity profiling of these species based on the number of mapped reads. This procedure, however, is not as trivial as it appears at first glance. A shotgun metagenomic dataset often contains DNA sequences from many closely-related microbial species (e.g., within the same genus) or strains (e.g., within the same species), thus it is often difficult to determine which species/strain a specific read is sampled from when it can be mapped to a common region shared by multiple genomes at high similarity. Furthermore, high genomic variations are observed among individual genomes within the same species, which are difficult to be differentiated from the inter-species variations during reads mapping. To address these issues, a commonly used approach is to quantify taxonomic distribution only at the genus level, based on the reads mapped to all species belonging to the same genus; alternatively, reads are mapped to a set of representative genomes, each selected to represent a different genus. Here, we introduce a novel approach to the quantity estimation of closely-related species within the same genus by mapping the reads to their genomes represented by a de Bruijn graph, in which the common genomic regions among them are collapsed. Using simulated and real metagenomic datasets, we show the de Bruijn graph approach has several advantages over existing methods, including (1) it avoids redundant mapping of shotgun reads to multiple copies of the common regions in different genomes, and (2) it leads to more accurate quantification for the closely-related species (and even for strains within the same species)

Financing and investing in sustainable infrastructure: A review and research agenda

Financing and investing in sustainable infrastructure play a pivotal role in achieving the United Nations Sustainable Development Goals, particularly considering their multifaceted benefits to the environment, society, and economy. This systematic literature review applies the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology to explore the financing and investment aspects of sustainable infrastructure. With support of a comprehensive collection of 4,308 publications dated from 2009 to 2023, we analyse various types of sustainable infrastructure and their investment and financing strategies by employing bibliometric analysis on 74 most closely related journal articles in a network approach setting. Results show the growing significance of green finance as a central research theme and a prevailing trend within this domain. Drawing upon these findings, we propose a conceptual framework for the integration of green finance into sustainable infrastructure development, offering insights to policy makers and guide future research agendas aimed at advancing green finance in infrastructure sectors