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This paper deals with a recursive filtering problem for a class of discrete time-varying nonlinear networked systems with the encoding-decoding mechanism. The linear fitting method is introduced to handle the nonlinearity. An encoding-decoding mechanism is constructed to describe the data transmission process in wireless communication networks (WCNs). To be specific, the measurement outputs are mapped by a quantizer to unique codewords for transmission in WCNs. Then, the codewords are decoded by the decoder to recover the measurement outputs which are sent to the filter. The processing/encoding delay and network delay have been considered. Firstly, on the premise that the upper bound of the filtering error covariance is minimum, the appropriate filtering gain is calculated. Then, the mean square exponential boundedness of the filtering error is analyzed. Finally, two simulation examples are presented to verify the effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

Cuttings logging is an important technology in petroleum exploration and production. It can be used to identify rock types, oil and gas properties, and reservoir features. However, the cuttings collected during cuttings logging are often small and few. Meanwhile, the surface color of cuttings is dark and the boundary is fuzzy. Traditional image segmentation methods have low accuracy. So it is difficult to identify and classify cuttings. Therefore, it is important to improve the accuracy of cuttings image segmentation. A deep learning-based cuttings image segmentation method is proposed in this paper. Firstly, the MultiRes module concept based on the UNet++ segmentation model is introduced in this paper, which proposes an improved end-to-end UNet++ image semantic segmentation model (called MultiRes-UNet++). Secondly, batch normalization into the input part of each layer's feature convolution layer is introduced too. Finally, a convolutional attention mechanism in the improved MultiRes-UNet++ segmentation model is introduced. Experimental results show that the accuracy between the segmentation results and the original image labels is 0.8791, the dice coefficient value is 0.8785, and the intersection over union is 0.7833. Compared with existing neural network segmentation algorithms, the performance is improved by about 5%. Compared with the algorithm before the fusion of the attention mechanism, the training speed is increased by about 75.2%. Our method can provide auxiliary information for cuttings logging. It is also of great significance for subsequent rock identification and classification. [ABSTRACT FROM AUTHOR]

Glycerol-assisted instant catapult steam explosion (ICSE) of lignocellulose is an effective pretreatment method for enhancing sugar production compared to glycerol-free ICSE. In this study, glycerol-assisted ICSE of corn stover was studied in order to understand the reaction mechanisms and further optimize the process. Results showed that water extraction of corn stover prior to ICSE reduced pseudo-lignin formation. The combination of water extraction and glycerol-assisted ICSE led to the formation of lignin with a lower molecular weight (Mw) of 2851 g/mol than 3521 g/mole of that from the combination of water extraction and glycerol-free ICSE. 1H-13C NMR analysis revealed that glycerol likely reacted with lignin carboxylic OHs through esterification while etherification of aliphatic OHs was not observed in ICSE. These lignin analyses indicated that glycerol protected lignin from condensation/repolymerization during glycerol-assisted ICSE. Enzymatic hydrolysis results showed that without water extraction increasing glycerol usage from 0.2 kg/kg stover to 0.4 kg/kg stover improved glucan digestibility to 78% but further increase to 0.5 kg/kg stover reduced glucan digestibility. In addition, at the glycerol usage of 0.2–0.4 kg/kg stover, washing of pretreated stover for removal of glycerol and other biomass-derived compounds did not improve glucan digestibility compared to unwashed ones. Combination of water extraction and glycerol-assisted ICSE led to a high glucan digestibility of 89.7% and a total glucose yield of 25.5 g glucose/100 g stover, which were 30.1% and 7.5 g/100 g stover higher than those derived from glycerol-free ICSE of stover, respectively. Since glycerol is a low-cost carbon source, the resulting enzymatic hydrolysate that contained both glucose and glycerol may be directly used to produce bioproducts by microbial fermentation. Highlights: Glycerol-assisted ICSE of corn stover improved enzymatic glucose production. Water extraction prior to ICSE further enhanced sugar production. Enzymatic hydrolysis was not affected by glycerol from glycerol-assisted ICSE. Sequential water extraction and ICSE led to a high glucan digestibility of 89.7%. Glycerol likely had a multiple role in ICSE and enzymatic hydrolysis. [ABSTRACT FROM AUTHOR]

This paper is concerned with the distributed resilient fusion filtering (DRFF) problem for a class of time-varying multi-sensor nonlinear stochastic systems (MNSSs) with random sensor delays (RSDs). The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features. In addition, the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem. The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that, for both RSDs and estimator gain perturbations, certain upper bounds of estimation error covariance (EEC) are given and locally minimized at every sample time. In the light of the obtained local filters, a new DRFF algorithm is developed via the matrix-weighted fusion method. Furthermore, a sufficient condition is presented, which can guarantee that the local upper bound of the EEC is bounded. Finally, a numerical example is provided, which can show the usefulness of the developed DRFF approach. [ABSTRACT FROM AUTHOR]

Former evidence regarding the associations of serum calcium (Ca) and magnesium (Mg) levels with apolipoproteins (Apos) in Chinese adults with coronary artery disease (CAD) were scarce. A total of 6781 patients with CAD were included in this cross-sectional study; mean age was 61.0 years. The associations of serum Ca, Mg, and Ca/Mg ratio with Apos (e.g., ApoA1, ApoB, and ApoB/A1 ratio) were determined using multivariate analysis of covariance. Serum Ca, Mg, and Ca/Mg ratio tended to have positive associations with ApoA1, while negative associations of serum Ca, Mg, and Ca/Mg ratio with ApoB and ApoB/A1 ratio were detected. In multivariate analysis, serum Ca, Mg, and Ca/Mg ratio were positively associated with ApoA1 levels (Q [quintile] 5 vs. Q1: 1.245 vs. 1.151 g/L for Ca, 1.207 vs. 1.188 g/L for Mg, 1.202 vs. 1.171 g/L for Ca/Mg ratio). In contrast, negative associations of serum Mg and Ca/Mg ratio with ApoB and ApoB/A1 ratio were shown. The corresponding ApoB and ApoB/A1 ratio values were 0.856 (vs. 0.887 g/L) and 0.728 (vs. 0.771) for Mg, and 0.814 (vs. 0.854 g/L) and 0.695 (vs. 0.751) for Ca/Mg ratio in Q5 compared with Q1. Serum Ca was inversely associated with ApoB and ApoB/A1 ratio (Q5 vs. Q4: 0.804 vs. 0.847 g/L for ApoB; Q5 vs. Q1: 0.662 vs. 0.732 for ApoB/A1 ratio). Path analysis showed that mediating effects of BMI on the "Ca or Mg-Apos" associations were not found. In summary, serum Ca and Mg tended to have positive associations with ApoA1 levels in patients with CAD, but had inverse associations with ApoB levels and ApoB/A1 ratio. Serum Ca/Mg ratio may be a more precise marker than serum Mg or serum Ca measures alone in assessing Apos measures of CAD risk. [ABSTRACT FROM AUTHOR]

In this paper, a novel proportion-integral-derivative-like particle swarm optimization (PIDLPSO) algorithm is presented with improved terminal convergence of the particle dynamics. A derivative control term is introduced into the traditional particle swarm optimization (PSO) algorithm so as to alleviate the overshoot problem during the stage of the terminal convergence. The velocity of the particle is updated according to the past momentum, the present positions (including the personal best position and the global best position), and the future trend of the positions, thereby accelerating the terminal convergence and adjusting the search direction to jump out of the area around the local optima. By using a combination of the Routh stability criterion and the final value theorem of the Z-transformation, the convergence conditions are obtained for the developed PIDLPSO algorithm. Finally, the experiment results reveal the superiority of the designed PIDLPSO algorithm over several other state-of-the-art PSO variants in terms of the population diversity, searching ability and convergence rate. [ABSTRACT FROM AUTHOR]

Apolipoproteins exert a key role on glucose metabolism; however, scarce data have examined the relationship between apolipoproteins and glycated haemoglobin (HbA1c) in Chinese adults. This study determined the cross-sectional and longitudinal associations of serum Apolipoprotein A1 (ApoA1), Apolipoprotein B (ApoB) and the ApoB/A1 ratio with HbA1c in Chinese adults. A total of 1448 subjects (584 men and 864 women) aged 54.8 years were included in a baseline survey, and the concentrations of Apo and HbA1c were measured. A total of 826 participants were followed up approximately once after 3.94 ± 0.62 years. In cross-sectional analysis, serum ApoA1 was inversely associated with HbA1c, while ApoB and the ApoB/A1 ratio were positively associated with HbA1c. After further adjusting for the potential covariates, a higher ApoA1 was associated with lower HbA1c (Quartile 4 [Q4] vs. Q1 = 5.673% vs. 5.796%, P-trend = 0.014). In contrast, positive association of ApoB concentration and the ApoB/A1 ratio with HbA1c level were showed (Q4 vs. Q1 = 5.805% vs. 5.589% for ApoB; Q4 vs. Q1 = 5.841% vs. 5.582% for ApoB/A1 ratio). The longitudinal results showed no significant associations of ApoA1, ApoB levels and the ApoB/A1 ratio with HbA1c changes (all P-trends > 0.05). Path analysis suggested that body mass index did not have mediating effect on Apo-HbA1c association. Our findings revealed that higher ApoA1, lower ApoB concentrations and the ApoB/A1 ratio were associated with lower HbA1c level in Chinese adults. [ABSTRACT FROM AUTHOR]

This paper addresses state estimation issues of large-scale systems with measurements subject to deception attacks, where the communication topology among sub-estimators is the same as the physical coupling structure of the subsystems. In consideration of the limited channel bandwidth, a novel adaptive event-triggered scheme is proposed for governing the data transmission among sub-estimators. With the help of Lyapunov analysis approaches, sufficient conditions are derived to ensure the input-to-state stability of the dynamics of estimation errors. Meanwhile, the bound of the estimation errors is obtained in the mean-square sense. The desired estimator parameters are presented in an analytical form dependent on the solution of a set of matrix inequalities. The developed scheme is related to the local information of the subsystems and thus satisfies the requirement of scalability. Finally, a simulation example of power systems is given to reveal the usefulness and effectiveness of the developed design scheme. [ABSTRACT FROM AUTHOR]

Seed number per pod (SNPP) and seed weight (SW) are two components of seed yield in rapeseed (Brassica napus). Here, a natural population of rapeseed was employed for genome-wide association analysis for SNPP and SW across multi-years. A total of 101 and 77 SNPs significantly associated with SNPP and SW with the phenotypic variances (R2) ranging from 1.35 to 29.47% and from 0.78 to 34.58%, respectively. And 43 and 33 homologs of known genes from model plants were located in the 65 and 49 haplotype blocks (HBs) for SNPP and SW, respectively. Notably, we found 5 overlapping loci and 3 sets of loci with collinearity for both SNPP and SW, of which 4 overlapping loci harbored the haplotypes with the same direction of genetic effects on SNPP and SW, indicating high possibility to simultaneously improve SNPP and SW in rapeseed. Our findings revealed both overlapping and independent loci controlling seed number per pod and seed weight in rapeseed. [ABSTRACT FROM AUTHOR]

In this paper, the event-triggered non-fragile state estimation problem is considered for a class of uncertain discrete-time neural networks with random delays and state-dependent stochastic disturbances. The norm-bounded uncertainty goes into all the parameters of the addressed neural network model. A Bernoulli stochastic variable is introduced to characterize the probability distribution of the occurrence of the time delays. The phenomenon of estimator gain variations is considered to account for the potential implementation error of the state estimator. An event-triggered mechanism is proposed with hope to mitigate the network load and orchestrate the bandwidth utilization. We aim to design a non-fragile state estimator such that the error dynamics of the neuron state estimation is globally asymptotically stable in the mean square. By means of the Lyapunov stability theory, delay-distribution-dependent sufficient conditions are established to ensure the existence of the desired event-triggered non-fragile state estimators and the estimator parameters are then derived in terms of the solution to a set of linear matrix inequalities. An illustrative example is utilized to show the usefulness and applicability of the proposed algorithm. [ABSTRACT FROM AUTHOR]

In this paper, an innovative recursive filtering algorithm (RFA) is proposed for a class of nonlinear systems (NSs) subject to multiplicative noises (MNs) and measurement outliers (MOs). Initially, the MNs are employed to formulate the random influence on the NSs with the stochastic noises. Next, the outlier phenomenon could occur unpredictably during measurement transmission. Then, a self-adaptive saturation function is introduced to the constructed filter to mitigate the influence of MOs on the filter performance. In this paper, we design a resistant-outlier filter for NSs with MNs and MOs, and the filter gain ensures that the trace of the filtering error covariance matrix is minimized by solving the constructed Riccati-like difference equations. Moreover, the exponential boundedness of the filtering error in the sense of mean square is analyzed. Finally, the feasibility of the proposed RFA is illustrated by a simulation example when the MOs occur. [ABSTRACT FROM AUTHOR]

In this paper, the passivity analysis problem is investigated for a class of discrete-time stochastic neural networks (DSNNs) with randomly occurring mixed time delays (ROMDs). The mixed delays comprise time-varying discrete delays, infinite-distributed delays as well as finite-distributed delays. A set of Bernoulli-distributed white sequences is used to account for the random nature of the occurrence of the mixed time delays. In addition, stochastic disturbances are taken into consideration to describe the state-dependent noises caused possibly by electronic devices and hardware implementation of neural networks. By using a combination of Lyapunov-Krasovskii functional, free-weighting matrix approach and stochastic analysis technique, we establish sufficient conditions guaranteeing the passivity performance of the underlying DSNNs. Furthermore, a delay-dependent robust passivity criterion is presented to deal with the parameter uncertainties in the DSNNs with ROMDs. A simulation example is provided to verify the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This paper proposes a finite-horizon state estimation method for a kind of complex network that suffers from randomly occurring gain variations. The method involves utilizing integral measurements from a portion of nodes in such complex networks. Integral measurements are carried out to characterize time delays that occur in signal acquisition together with real-time signal processing. Measurements from only partial nodes reflect the fact that signals of several sensors are unacquirable. A Gaussian random variable is utilized to depict the random appearance of gain variations during the practical implementation of estimators. The aim of this paper is to construct finite-horizon resilient estimators for complex networks in view of integral measurements from a portion of nodes that fulfill the specified H∞ performance demand involving a specified disturbance attenuation level. Necessary and sufficient conditions are put forward to ensure that such ideal estimators exist by employing stochastic analysis as well as using the completing squares method. The gain parameters of the finite-horizon estimators are expressed by adopting the Moore-Penrose pseudoinverse and acquired through solving the solutions to a group of coupled backward recursive Riccati difference equations with constraint conditions. A confirmatory instance is carried out that demonstrates the feasibility of the newly developed estimation algorithm. [ABSTRACT FROM AUTHOR]

The associations of levels of apolipoprotein A1 (ApoA1) and apolipoprotein B and ApoB/A1 ratio and risk of a first stroke have not been reliably documented. We performed a meta-analysis to summarize the relationships and confirmed them in a case-control study. We identified relevant publications in PubMed and Embase databases up to June 1, 2015. A Dersimonian-Laird random effects model was used to compute summary relative risks (RRs) and 95 % confidence intervals (CIs). A case-control study was conducted in a southern Chinese population. We included 8 cohort and 4 case-control studies (222,774 subjects; 10,032 first stroke events) in the meta-analysis. Reduced ApoA1 level and increased ApoB level and ApoB/A1 ratio was associated with a first stroke in cohort studies (RR 0.86 [95 % CI 0.79-0.94], 1.66 [1.62-1.69], and 1.66 [1.63-1.70], respectively) and reduced ApoA1 level and increased ApoB/A1 ratio in case-control studies (0.68 [0.47-0.99] and 1.76 [1.50-2.06], respectively). When stratified by stroke type in cohort studies, the RR for ischemic stroke was 0.83 (0.76-0.90), 1.36 (1.32-1.40), and 1.38 (1.35-1.42) for the 3 factors, respectively. In our case-control study (1013 cases; 1029 controls), the OR for a first ischemic stroke was 0.83 (0.74-0.92), 1.33 (1.18-1.48) and 2.10 (1.76-2.51), respectively, with increased ApoA1 level associated with hemorrhagic stroke (1.37 [1.06-1.78]). Meta-analysis suggests that reduced ApoA1 level and increased ApoB level and ApoB/A1 ratio are risk factors for a first ischemic but not hemorrhagic stroke. Elevated ApoA1 level may be a risk factor for a first hemorrhagic stroke. [ABSTRACT FROM AUTHOR]

Almost all deaths from breast cancer arise from metastasis of the transformed cells to other sites in the body. Hence, uncovering a means of inhibiting breast cancer cell migration would provide a significant advance in the treatment of this disease. Stimulation of the cAMP signaling pathway has been shown to inhibit migration and motility of a number of cell types. A very effective way of selectively stimulating cAMP signaling is through inhibition of cyclic nucleotide phosphodiesterases (PDEs). Therefore, we examined full expression profiles of all known PDE genes at the mRNA and protein levels in four human breast cancer cell lines and eight patients' breast cancer tissues. By these analyses, expression of almost all PDE genes was seen in both cell lines and tissues. In the cell lines, appreciable expression was seen for PDEs 1C, 2A, 3B, 4A, 4B, 4D, 5A, 6B, 6C, 7A, 7B, 8A, 9A, 10A, and 11A. In patients' tissues, appreciable expression was seen for PDEs 1A, 3B, 4A, 4B, 4C, 4D, 5A, 6B, 6C, 7A, 7B, 8A, 8B, and 9A. PDE8A mRNA in particular is prominently expressed in all cell lines and patients' tissue samples examined. We show here that stimulation of cAMP signaling with cAMP analogs, forskolin, and PDE inhibitors, including selective inhibitors of PDE3, PDE4, PDE7, and PDE8, inhibit aggressive triple negative MDA-MB-231 breast cancer cell migration. Under the same conditions, these agents had little effect on breast cancer cell proliferation. This study demonstrates that PDE inhibitors inhibit breast cancer cell migration, and thus may be valuable therapeutic targets for inhibition of breast cancer metastasis. Since PDE8A is expressed in all breast cancer samples, and since dipyridamole, which inhibits PDE8, and PF-04957325, a selective PDE8 inhibitor, both inhibit migration, it suggests that PDE8A may be a valuable novel target for treatment of this disease. [ABSTRACT FROM AUTHOR]

Silique length (SL) and seed weight (SW) are important yield-associated traits in rapeseed (Brassica napus). Although many quantitative trait loci (QTL) for SL and SW have been identified in B. napus, comparative analysis for those QTL is seldom performed. In the present study, 20 and 21 QTL for SL and SW were identified in doubled haploid (DH) and DH-derived reconstructed F2 populations in rapeseed, explaining 55.1-74.3% and 24.4-62.9% of the phenotypic variation across three years, respectively. Of which, 17 QTL with partially or completely overlapped confidence interval on chromosome A09, were homologous with two overlapped QTL on chromosome C08 by aligning QTL confidence intervals with the reference genomes of Brassica crops. By high density selective genotyping of DH lines with extreme phenotypes, using a Brassica single-nucleotide polymorphism (SNP) array, the QTL on chromosome A09 was narrowed, and aligned into 1.14-Mb region from 30.84 to 31.98 Mb on chromosome R09 of B. rapa and 1.05-Mb region from 27.21 to 28.26 Mb on chromosome A09 of B. napus. The alignment of QTL with Brassica reference genomes revealed homologous QTL on A09 and C08 for SL. The narrowed QTL region provides clues for gene cloning and breeding cultivars by marker-assisted selection. [ABSTRACT FROM AUTHOR]