State estimation for discrete-time neural networks with Markov-mode-dependent lower and upper bounds on the distributed delays

Copyright @ 2012 Springer VerlagThis paper is concerned with the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters and mixed time-delays. The parameters of the neural networks under consideration switch over time subject to a Markov chain. The networks involve both the discrete-time-varying delay and the mode-dependent distributed time-delay characterized by the upper and lower boundaries dependent on the Markov chain. By constructing novel Lyapunov-Krasovskii functionals, sufficient conditions are firstly established to guarantee the exponential stability in mean square for the addressed discrete-time neural networks with Markovian jumping parameters and mixed time-delays. Then, the state estimation problem is coped with for the same neural network where the goal is to design a desired state estimator such that the estimation error approaches zero exponentially in mean square. The derived conditions for both the stability and the existence of desired estimators are expressed in the form of matrix inequalities that can be solved by the semi-definite programme method. A numerical simulation example is exploited to demonstrate the usefulness of the main results obtained.This work was supported in part by the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 60774073 and 61074129, and the Natural Science Foundation of Jiangsu Province of China under Grant BK2010313

Flexural performance tests and machine learning analysis of prestressed high strength steel reinforced concrete beams

This paper reports a study on the flexural performance of prestressed high strength steel reinforced concrete (PHSSRC) beams and proposes machine learning (ML) models for predicting the flexural bearing capacity of steel reinforced concrete (SRC) beams. Seven prestressed steel reinforced concrete (PSRC) beams were tested under a four-point bending load to investigate the effect of steel strength grade, steel ratio, and longitudinal reinforcement ratio on the flexural load capacity of beams. The test results indicated that increasing the steel strength grade and steel ratio significantly enhanced the bearing capacity of PSRC beams. A database consisting of 112 sets of experimental data on the flexural performance of SRC beams, including the test data in this study, was established for training and validating the ML models. Artificial Neural Network (ANN) model and eXtreme Gradient Boosting (XGBoost) model were respectively developed to predict the flexural load capacity of SRC beams, and the accuracy of the flexural load capacity values predicted by the design specification, the ANN model and the XGBoost model were compared. The results show that the XGBoost model has the best prediction performance. Finally, the sensitivity analysis of the parameters was performed using the Shapley Additivity (SHAP) interpretation method

Co-infection with hepatitis B virus among tuberculosis patients is associated with poor outcomes during anti-tuberculosis treatment

Abstract Background Tuberculosis (TB) and chronic Hepatitis B virus (HBV) infection are common in China. Fist-line anti-TB medications often produce drug-induced liver injury (DILI). This study sought to investigate whether TB patients with chronic HBV co-infection are more susceptible to liver failure and poor outcomes during anti-TB treatment. Methods Eighty-four TB patients developed DILI during anti-TB treatment and were enrolled, including 58 with chronic HBV co-infection (TB-HBV group) and 26 with TB mono-infection (TB group). Clinical data and demographic characteristics were reviewed. The severity of DILI and incidences of liver failure and death were compared. Risk factors of clinical outcomes were defined. Results The patterns of DILI were similar in both groups. Compared with patients in the TB group, patients in the TB-HBV group who did not receive anti-HBV therapy before anti-TB treatment were more susceptible to Grade-4 severity of DILI (36.2% vs. 7.7%, P = 0.005), liver failure (67.2% vs. 38.5%, P = 0.013) and poor outcomes (37.9% vs. 7.7%, P = 0.005). Age > 50 years (48.1% vs. 22.6%, P = 0.049), cirrhosis (50.0% vs. 15.4%, P = 0.046) and total bilirubin > 20 mg/dl (51.6% vs. 14.8%, P = 0.005) were independent risk factors for the rate of death in the TB-HBV group, and HBV DNA > 20,000 IU/ml had borderline significance (44.1% vs. 20.8%, P = 0.081). In the TB-HBV group, nucleos(t)ide analogues as rescue therapy were not able to reduce short-term death (33.3% vs. 36.8%, P = 0.659) once liver failure had occurred. Conclusions Patients on anti-TB therapy with chronic HBV co-infection are more susceptible to developing liver failure and having poor outcomes during anti-TB treatment. Regular monitoring of liver function and HBV DNA level is mandatory. Anti-HBV treatment should be considered in those with high viral levels before anti-TB treatment

Comparative cytogenetics in three Sciaenid species (Teleostei, Perciformes): evidence of interspecific chromosomal diversification

Abstract Background Species belonging to the Sciaenidae family present a karyotype composed by 48 acrocentric chromosomes and are thus considered a striking example of chromosomal conservation. In this family, three species are extensively studied including Larimichthys crocea, Larimichthys polyactis and Nibea albiflora due to their importance in fishery and aquaculture in East Asia. Despite abundant data of population genetics available for some of them, cytogenetic information on these species is still scarce and obtained by conventional cytogenetic protocols. Therefore, a more detailed cytogenomic investigation was performed in these species to analyze their karyotype differentiation using conventional staining techniques and fluorescence in situ hybridization to map several repetitive DNAs. Results The three species showed a slight karyotype differentiation with 4sm + 2st + 42a in L. polyactis, 20st + 28a in L. crocea and 48a in N. albiflora. Additionally, the mapping of repetitive sequences further revealed a number of interspecific differences among them. Particularly, 18S and 5S rDNA sites showed syntenic arrangements in N. albiflora and non-syntenic arrangements in both Larimichthys species. The microsatellites (CA)15 and (GA)15 showed conspicuous terminal clusters in some chromosomes of all species. On the other hand, (CGG)10 repeats, Rex6 elements and U2 snRNA displayed a scattered distribution on the chromosomes. Conclusions Although the three Sciaenid species examined displayed a general pattern of karyotypic conservatism, we explored chromosomal diversification among them. The diversificated karyotypic macrostructure is followed by intergeneric evolutionary diversification of the repetitive sequences. The data indicate some degree of intergeneric evolutionary diversification at chromosomal level, and suggest the evolutionary dynamics among Sciaenid species, higher than previously thought. The present cytogenetic data provide new insight into the chromosomal diversification in Sciaenidae, and contribute to inferring the chromosomal rearrangements and trends of karyotype evolution in this fish group

Arabidopsis VILLIN5, an Actin Filament Bundling and Severing Protein, Is Necessary for Normal Pollen Tube Growth[W]

Villin is a major regulator of actin dynamics. This article reports that Arabidopsis thaliana VILLIN5 (VLN5) is a typical member of the villin/gelsolin/framin family and retains a full suite of activities in vitro, including capping, severing, and bundling of actin filaments. Moreover, using reverse genetics, we show that VLN5 is required for the stabilization of actin filaments in the pollen tube

Additional file 2: of Co-infection with hepatitis B virus among tuberculosis patients is associated with poor outcomes during anti-tuberculosis treatment

Table S2. Demographics and characteristics of patients in TB-HBV group with different clinical outcomes. Compared with those with better clinical outcomes, the proportions of patients with advanced age (Mean [years]: 53.9 vs. 45.5, P = 0.017; age > 50 years old: 63.6% vs. 36.1%, P = 0.041), severe hyperbilirubinemia (Median of TBIL [μmol/L]: 478.8 vs. 251.0, P = 0.000), cirrhosis (77.3% vs. 41.7%, P = 0.008) and HBV DNA > 20,000 IU/L (77.3% vs. 47.2%, P = 0.024) in the TB-HBV group were significantly higher. (DOCX 22 kb

Machine Learning‐Assisted Microfluidic Synthesis of Perovskite Quantum Dots

The quality and property control of nanomaterials are center themes to guarantee and promote their applications. Different synthesis methods and reaction parameters are control factors for their properties. However, the vast combination number of the factors with multilevels leads to the obstacle that trying all‐through the data space is nearly impossible. Herein, the combination of microfluidic synthesis method with machine learning (ML) models to address this challenge in case of perovskite quantum dots (PQDs) with tunable photoluminescence (PL) is reported. The ML‐assisted synthesis not only helps to elucidate the nucleation growth‐ripening mechanisms, but also successfully guides to synthesize PQDs with precise wavelength and full width of half maximum (FWHM) of the PL by optimizable conditions to match the time‐saving, energy‐saving, and minimal environmental pressure goals