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This paper focuses on presenting a new identification algorithm to estimate the parameters and state variables for two‐input two‐output dynamic systems with time delay based on canonical state space models. First, the related input‐output equation is determined and transformed into an identification oriented model, which does not involve in the unmeasurable states, and then a residual based least squares identification algorithm is presented for the estimations. After the parameters being estimated, the system states are subsequently estimated by using the estimated parameters. Through theoretical analysis, the convergence of the algorithm is derived to provide assurance for applicability. Finally, a selected simulation example is given for a meaningful case study to show the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that microRNA‐186 (miR‐186) can be induced under hypoxic conditions, and is associated with apoptosis. This study was undertaken to explore the exact role of this microRNA (miRNA) in the apoptotic death of neurons during cerebral ischemic/reperfusion (I/R) injury. To model cerebral ischemia/reperfusion (I/R) injuries, we utilized a transient middle cerebral artery occlusion approach in rats, as well as a model of oxygen‐glucose deprivation/reoxygenation (OGD/R) in Neuro2a cells. We found that in both in vitro and in vivo models of cerebral I/R injuries, levels of miR‐186 were markedly decreased. When we overexpressed miR‐186, this was associated with a reduction in the apoptotic death of neuroblastoma cells in the OGD/R model system, whereas the opposite was true when this miRNA was instead inhibited. We further found miR‐186 to directly target hypoxia‐inducible factor 1α (HIF‐1α) by interacting with the 3′‐untranslated region of this mRNA. When we knocked down HIF‐1α, this partially overcame the apoptotic death of cells in response to OGD/R injury and associated miR‐186 downregulation. Our findings indicate that miR‐186 is able to reduce ischemic injury to neurons at least in part through downregulating HIF‐1α, suggesting that the miR‐186/HIF‐1α axis is a potential therapeutic target for the treatment of ischemic stroke. [ABSTRACT FROM AUTHOR]

A fast, portable, nondestructive, and simple‐to‐operate method for determination of water cane shoot quality via an electronic nose (E‐nose) system is presented. The responses of E‐nose sensors to cane shoot samples during storage time are measured. Considering that one of the most common problems with fresh aquatic vegetables is the nearly negligible change in volatile organic compounds, a novel swarm clustering based on particle swarm optimization (SWC) algorithm is proposed to extract the effective features of the sensors responses. In SWC, the number of clusters is automatically estimated based on the neighborhood radius of the particles, which reduces the difficulty in determining the number of cluster. Traditional clustering algorithms, such as K‐means clustering (KMC) and hierarchical clustering analysis (HCA), are used for the purposes of comparison, and the changes in quality of cane shoot samples are quantitatively determined according to the hardness and pH. The results suggest that the E‐nose‐based SWC methodology is capable of accurately classifying the cane shoots freshness during the 20‐day storage time, which is much better than that of the comparative KMC and HCA methods. Additionally，quantitative analysis of the sensory evaluation, hardness, and pH is shown to have good agreement with the E‐nose system analysis results. Validation experiments show that unknown samples are successfully grouped into several different categories with a high correlation (R2 =.982) between unknown and known samples, demonstrating the potential use of E‐nose system to predict the freshness of the cane shoots. [ABSTRACT FROM AUTHOR]

The harmonic parameter identification and modelling problem for power signals are studied. In order to model power signals, the multi‐innovation stochastic gradient (MI‐SG) is derived based on the multi‐innovation identification theory. The proposed MI‐SG algorithm repeatedly uses past innovations by expanding the scalar innovation to the innovation vector and can obtain more accurate parameter estimates than the stochastic gradient algorithm. Finally, the simulation results indicate that the proposed algorithm is effective and has a close estimation accuracy compared with the fast Fourier transform analysis. [ABSTRACT FROM AUTHOR]

Na-ion Batteries have been considered as promising alternatives to Li-ion batteries due to the natural abundance of sodium resources. Searching for high-performance anode materials currently becomes a hot topic and also a great challenge for developing Na-ion batteries. In this work, a novel hybrid anode is synthesized consisting of ultrafine, few-layered SnS2 anchored on few-layered reduced graphene oxide (rGO) by a facile solvothermal route. The SnS2/rGO hybrid exhibits a high capacity, ultralong cycle life, and superior rate capability. The hybrid can deliver a high charge capacity of 649 mAh g−1 at 100 mA g−1. At 800 mA g−1 (1.8 C), it can yield an initial charge capacity of 469 mAh g−1, which can be maintained at 89% and 61%, respectively, after 400 and 1000 cycles. The hybrid can also sustain a current density up to 12.8 A g−1 (≈28 C) where the charge process can be completed in only 1.3 min while still delivering a charge capacity of 337 mAh g−1. The fast and stable Na-storage ability of SnS2/rGO makes it a promising anode for Na-ion batteries. [ABSTRACT FROM AUTHOR]

In recent years, research on the qualitative analysis of aquatic product using ultrasonic or biological impedance has received increasing attention. Unfortunately, aquatic product safety incidents occur now and then, thus new kinds of analytical techniques that are fast, nondestructive, and simple to operate would be advantageous. This article addressed a machine olfactory system for recognition of the storage life of a whole living mitten crab. A type of deep learning algorithm, namely stacked denoising auto‐encoders algorithm (SdA), was applied to extract effective features of the machine olfactory system sensors' responses. The traditional feature extraction methods such as principal component analysis and linear discriminant analysis were used for the purposes of comparison. Then the support vector machine (SVM) classifier was implemented for further qualitative classification. In addition, the crabs were analyzed for total volatile basic nitrogen and total viable counts during storage process. Validation experiments showed that the highest recognition rate (96.67%) was achieved by using SdA with SVM. This study may present a promising instruction for the storage life recognition of the living crab. Practical Application: Evaluation of the freshness of mitten crab is of considerable importance to guarantee mitten crab quality. However, to our best knowledge, few reports on the development of an electronic‐nose for nondestructive evaluation of the quality of whole living crab are available. A machine olfactory system for recognition of the storage life of a whole living mitten crab was present in this study. Validation experiments showed the highest recognition rate based on the system. In summary, the metal‐semiconductor sensor‐based machine olfactory system presents some advantages including fast detecting, repeatability, and nondestructive. In the future, with the improvement of sensor performance and development of pattern recognition, it will be a favorable weapon for protecting the interests of consumers in aquatic market. [ABSTRACT FROM AUTHOR]