This paper proposes a distributed adaptive dynamic programming scheme to investigate the optimal tracking control problem for finite‐horizon non‐linear interconnected systems with constraint inputs ...under aperiodic sampling. A N‐player nonzero‐sum differential game system is constructed with the presented non‐linear interconnected system and the tracking error system by introducing the augment vectors. To address the problems of constrained‐input and finite‐horizon control, a non‐quadratic utility function and a finite‐horizon cost function are utilized which will arise in the time‐varying Hamilton–Jacobi (HJ) equation. Then, a periodic event‐triggered scheme is designed to realize aperiodic sampling, where the consumption of communication resources is reduced and the Zeno behavior is avoided. Under the designed periodic event‐triggered scheme, the time‐varying HJ equation is almost impossible to get an analytical solution due to its hybrid properties and non‐linearity. Therefore, the critic neural networks are used to estimate the optimal solution of the HJ equation, and the weight update law is constructed to guarantee the uniformly ultimate bounded of approximated errors. Further, the hybrid nonzero‐sum differential game is confirmed to be uniformly ultimate bounded by using the Lyapunov theory. Finally, the obtained distributed PET control strategy is successfully applied to dispose the missile‐target intercepter problem.
Histone lysine demethylase 1 (LSD1), the first identified histone demethylase, is overexpressed in multiple tumor types, including breast cancer. However, the mechanisms that cause LSD1 dysregulation ...in breast cancer remain largely unclear. Here, we report that protein arginine methyltransferase 4 (PRMT4 or CARM1) dimethylates LSD1 at R838, which promotes the binding of the deubiquitinase USP7, resulting in the deubiquitination and stabilization of LSD1. Moreover, CARM1‐ and USP7‐dependent LSD1 stabilization plays a key role in repressing E‐cadherin and activating vimentin transcription through promoter H3K4me2 and H3K9me2 demethylation, respectively, which promotes invasion and metastasis of breast cancer cells. Consistently, LSD1 arginine methylation levels correlate with tumor grade in human malignant breast carcinoma samples. Our findings unveil a unique mechanism controlling LSD1 stability by arginine methylation, also highlighting the role of the CARM1‐USP7‐LSD1 axis in breast cancer progression.
Synopsis
The protein arginine methyltransferase CARM1 targets the histone lysine demethylase LSD1 and promotes its stabilization via USP7‐dependent deubiqutination. Stabilised LSD1 enhances migration and invasion of breast cancer cells, further facilitating metastasis.
Methylation of LSD1 by CARM1 recruits USP7, which results in the deubiquitination and stabilisation of LSD1.
LSD1 methylation catalyzed by CARM1 promotes breast cancer cell invasion and metastasis.
Methylated LSD1 binds to the E‐cadherin and vimentin genes, leading to their respective repression or activation.
LSD1 arginine methylation levels correlate with tumor grade in human breast cancer samples.
The protein arginine methyltransferase CARM1 targets the histone lysine demethylase LSD1 and promotes its stabilization via USP7‐dependent deubiqutination. Stabilised LSD1 enhances migration and invasion of breast cancer cells, further facilitating metastasis.
In this paper, the optimal control problem for finite-time missile-target interception systems is posed in a finite-horizon two-player zero-sum (ZS) differential game framework using a periodic ...event-triggered (PET) scheme. To solve the optimal control problem, a time-varying Hamilton-Jacobi-Issac (HJI) equation and a time-dependent cost function are constructed to deal with finite-horizon constraints, and an event-based periodic adaptive dynamic programming (ADP) algorithm is employed to find the Nash equilibrium solution for the designed HJI equation. Comparing with the traditional continuous event-triggered (ET) scheme, the proposed PET scheme only verifies the event-triggered conditions at periodic sampling instants, which reduces resource consumption in monitoring and excludes the Zeno behavior. A single critic neural network (CNN) is used to implement the proposed event-based optimal control algorithm, which reduces approximate errors bust also simplifies structures. Further, an additional error term is added in the designed weight updating law to such that the terminal constraint is also minimized over time. By resorting to Lyapunov function approach, some sufficient conditions are derived to achieve the uniformly ultimately bounded (UUB) of the ET closed-loop system and the estimation weight error of CNN. Finally, a missile-target interception system is introduced to illustrate the efficiency of the presented methods.
Chlorophyll and nitrogen contents were used as leaf physiological parameters. Based on multispectral images from multiple detection angles and the stoichiometric data of tea (Camellia sinensis) ...leaves in different positions on plants, the spatial differences in tea physiological parameters were explored, and the full channel difference vegetation index was established to effectively remove soil and shadow noise. Support vector machine, random forest (RF), partial least square, and back-propagation algorithms from the multispectral images of leaf and canopy scales were then used to train the tea physiological parameter detection model. Finally, the detection effects of the multispectral images obtained from different angles on the physiological parameters of the top, middle, and bottom tea leaves were analysed and compared. The results revealed distinct spatial differences in the physiological parameters of tea leaves in individual plants. Chlorophyll content was lowest at the top and relatively high at the middle and bottom; nitrogen content was the highest at the top and relatively low at the middle and bottom. The horizontal distribution of physiological parameters was similar, i.e., the values in the east and south were high, whereas those in the west and north were low. The multispectral detection accuracy of the physiological parameters at the leaf scale was better than that at the canopy scale; the model trained by the RF algorithm had the highest comprehensive accuracy. The coefficient of determination between the predicted and measured values of the spad-502 plus instrument was (R2) = 0.79, and the root mean square error (RMSE) was 0.11. The predicted result for the nitrogen content and the measured value was R2 = 0.36 and RMSE = 0.03. The detection accuracy of the multispectral image taken at 60° for the physiological parameters of tea was generally superior to those taken at other shooting angles. These results can guide the high-precision remote sensing detection of tea physiological parameters.
Kerogen was isolated from the Maoming shale at different temperatures to understand changes in chemical, structural and porosity characteristics during artificial maturation. Advanced solid-state 13C ...nuclear magnetic resonance (NMR) techniques were employed along with Fourier transform infrared (FT-IR), Raman spectroscopy (RS), stable carbon isotopes, and Rock-Eval pyrolysis to characterize the organic matter (OM), whereas the microporosity and surface properties were elucidated using N2 and CO2 adsorption techniques. As the temperature increased, the aliphatic and carbonyl carbons of the kerogen samples showed remarkable decreases in abundance together with an increase of non-protonated and protonated aromatic carbons. Moreover, the kerogen became more enriched in 13C and had a higher degree of crystallization with increasing Ro and Tmax. The aromaticity ranged from 46.9% to 94.7% and the minimum aromatic cluster size varied from 10 carbons at 350 °C to 38 carbons at 500 °C, which was significantly related to the microporosity (Vo, d-co2) of the kerogen samples and their nonlinear sorption of phenanthrene and benzene. The microporosity was extensively affected by the loss of aliphatic carbon and the increase of aromatic fused carbon. When the temperature reached 500 °C, the collapse of aromatic interlayer remarkably reduced the micropore volume in the kerogen, and then resulted in the decreasing adsorption of hydrophobic organic chemicals (HOCs). The above observation confirms the molecular sieve effect in the kerogen samples. In addition, the micro-filling adsorption for HOCs is dominant on the thermally simulated kerogen samples.
•Structures of thermally matured kerogen were investigated by solid carbon-13 NMR.•Aromatic cluster size and aromaticity increases with the increasing maturation.•Alkyl carbon is rearranged and attached into the increasing aromatic cluster.•Protonated or nonprotonated carbon increases with increasing temperature.•Aromatic cluster size is related to the microporosity on the kerogen.
Abstract
Previous studies on the relationship between dietary minerals and preeclampsia (PE) have given inconsistent results. The aim of this study was to further clarify the relationship between ...dietary minerals intake and PE in Chinese pregnant women. In this study, 440 pairs of hospital–based preeclamptic and healthy women were matched 1:1. Dietary intake was obtained through a 78–item semi–quantitative food frequency questionnaire. Multivariate conditional logistic regression was used to estimate the odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic splines were plotted to evaluate the dose–response relationship between dietary minerals intake and PE. This study found significant inverse associations for dietary intake of calcium, magnesium, phosphorus, iron, copper, manganese and zinc and the risk of PE in both univariate and multivariate models (all
P-
trend < 0.05). After adjusting for possible confounders, compared with the lowest quartile, the odds ratio of the highest quartile was 0.74 (95% CI 0.56–0.98) for calcium, 0.63 (95% CI 0.42–0.93) for magnesium, 0.45 (95% CI 0.31–0.65) for phosphorus, 0.44 (95% CI 0.30–0.65) for iron, 0.72 (95% CI 0.53–0.97) for copper, 0.66 (95% CI 0.48–0.91) for manganese and 0.38 (95% CI 0.25–0.57) for zinc. In addition, a reverse J–shaped relationship between dietary minerals intake and PE risk was observed (
P
–overall association < 0.05). In Chinese pregnant women, a higher intake of dietary minerals, including calcium, magnesium, phosphorus, copper, iron, manganese, and zinc was associated with a lower odds of PE.
Maternal diet is an important potential factor associated with the risk of preeclampsia. However, it is unclear whether adherence to a Dietary Approaches to Stop Hypertension (DASH)-style diet can ...reduce the development of preeclampsia. To examine the potential association, we conducted a hospital-based case-control study at the First Affiliated Hospital of Zhengzhou University, China. A total of 449 cases with preeclampsia and 449 controls were studied. Dietary information was collected using a validated food frequency questionnaire (FFQ). DASH scores were calculated according to nutrients/food emphasised or minimised in the DASH diet. The calculated DASH scores ranged from 11 to 38 for all of the participants, and the DASH scores of the cases were significantly lower than those of the controls (23.48 ± 4.58 vs 24.51 ± 4.51; p = 0.001). Participants in the fourth quartile of the DASH score were 45% less likely to have preeclampsia than those in the first quartile in the crude model (Q4 vs Q1, odds ratio OR: 0.55; 95% confidence interval CI: 0.38, 0.80; p
= 0.001). The relationship remained significant in the model adjusted for multiple confounders, especially for major risk factors of preeclampsia (OR: 0.53; 95% CI: 0.36, 0.78; p
= 0.001). Our findings suggest an inverse relationship between adherence to a DASH-style diet and the odds of preeclampsia. Further larger-scale cohort studies or randomised controlled trials are warranted to confirm these relationships.
The production of high-quality tea by Camellia sinensis (L.) O. Ktze is the goal pursued by both producers and consumers. Rapid, nondestructive, and low-cost monitoring methods for monitoring tea ...quality could improve the tea quality and the economic benefits associated with tea. This research explored the possibility of monitoring tea leaf quality from multi-spectral images. Threshold segmentation and manual sampling methods were used to eliminate the image background, after which the spectral features were constructed. Based on this, the texture features of the multi-spectral images of the tea canopy were extracted. Three machine learning methods, partial least squares regression, support vector machine regression, and random forest regression (RFR), were used to construct and train multiple monitoring models. Further, the four key quality parameters of tea polyphenols, total sugars, free amino acids, and caffeine content were estimated using these models. Finally, the effects of automatic and manual image background removal methods, different regression methods, and texture features on the model accuracies were compared. The results showed that the spectral characteristics of the canopy of fresh tea leaves were significantly correlated with the tea quality parameters (r ≥ 0.462). Among the sampling methods, the EXG_Ostu sampling method was best for prediction, whereas, among the models, RFR was the best fitted modeling algorithm for three of four quality parameters. The R2 and root-mean-square error values of the built model were 0.85 and 0.16, respectively. In addition, the texture features extracted from the canopy image improved the prediction accuracy of most models. This research confirms the modeling application of a combination of multi-spectral images and chemometrics, as a low-cost, fast, reliable, and nondestructive quality control method, which can effectively monitor the quality of fresh tea leaves. This provides a scientific reference for the research and development of portable tea quality monitoring equipment that has general applicability in the future.
•SPM and COM in annually dry and wet deposition samples were separated.•Deposition flux of heavy metals varied largely among the investigated seasons.•The enrichment factors (EF) of COM were much ...higher than those of SPM.•Street dust, non-ferrous metal production, and heavy fuel oil were major sources.•Positive matrix factorization (PMF) model was used for source apportionment.
Suspended particulate matter (SPM) and colloidal matter (COM) in annual dry and wet deposition samples in urban Guangzhou were for the first time collected, and their trace metals were investigated by using inductively coupled plasma mass spectrometry (ICP-MS). The deposition flux of SPM and of metal elements varied largely among the investigated seasons, and reached the maximum in spring. The correlation analysis indicated that significant correlations existed among some of the metal elements in the deposition samples. The enrichment factors (EF) of metals in COM in the deposition ranging from 79.66 to 130,000 were much higher than those of SPM ranging from 1.65 to 286.48, indicating the important role of COM. The factor analysis showed that emissions from street dust, non-ferrous metal production, and heavy fuel oil were major sources of the trace metals. Positive matrix factorization (PMF) model was used to quantitatively estimate anthropogenic source.
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