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In the less developed multi-ethnic regions (LEMRs) of Southwest China, the associations between dietary patterns and blood pressure (BP) values remain unclear. We aimed to investigate such associations and related effect modifiers. This study included 81,433 participants from the China Multi-Ethnic Cohort Study. Dietary intakes during the year before the interview were measured with the Quantitative Food Frequency Questionnaire. Three major dietary patterns that were highly in line with geographical and ethnic distributions of the study population, i.e., "Sichuan Basin," "Yunnan-Guizhou Plateau," and "Qinghai-Tibet Plateau," were derived using principal component factor analysis. The multilinear regression model combined with inverse probability of exposure weighting was used to estimate the associations between dietary patterns and BP values. Comparing the highest with the lowest quintiles, the Sichuan Basin dietary pattern (characterized by urban lifestyles) was associated with 2.67 mmHg lower systolic blood pressure (SBP) (95% CI: −3.07 to −2.27) and 0.89 mmHg lower diastolic blood pressure (95% CI: −1.12 to −0.65). In contrast, both the Yunnan-Guizhou Plateau (characterized by agricultural lifestyles) and the Qinghai-Tibet Plateau dietary patterns (characterized by nomadic lifestyles) showed positive associations with BP. In the stratified analysis, the associations between dietary patterns and SBP were significantly stronger in women than in men for all three kinds of dietary patterns. Both major dietary patterns and their associations with BP showed a substantial disparity in LEMRs of Southwest China. Dietary patterns in regions of higher socioeconomic status are more conducive to reducing the rising of BP, especially for women and urban residents, which might provide insights into the BP control in LEMRs of Southwest China. • Dietary patterns and their associations with BP showed substantial disparity in LEMRs of Southwest China. • The ethnic minorities in the less developed plateau regions adhered to much worse dietary patterns, which were associated with higher BP. • Dietary patterns in regions of higher socioeconomic status are more conducive to reduce the rising of BP, especially for women and urban residents. [ABSTRACT FROM AUTHOR]

The latest progress in SACs prepared by mechanical ball milling strategy and versatile heterogeneous catalysis applications of (including thermocatalysis, photocatalysis and electrocatalysis) are summarized. [Display omitted] A mechanochemical ball milling process will spontaneously generate strong shear force and a high local temperature, which will reconstruct the chemical bonds of materials and renovate the surface chemistry characteristics. The ball milling method is a simple and robust strategy to large scale synthesize nanomaterials, and it can also be used to synthesize single atom catalysts (SACs). In this review, we systematically summarized the methodology and principle of ball milling strategy for the preparation of SACs for the first time, which include the solvent-assisted ball-milling strategy, solvent-free ball-milling strategy, and ball-milling abrasion-thermal atomization joint strategy. At the same time, we also summarized the latest progress in heterogeneous catalysis applications of SACs prepared by mechanical ball milling strategy (including thermocatalysis, photocatalysis and electrocatalysis). The challenges and prospects of the ball milling-derived SACs in practical industrial production and application are pointed out as well. Admittedly, the mechanochemical construction of SACs has become a hot research field in sub-nanometer manufacturing and heterogeneous catalysis. [ABSTRACT FROM AUTHOR]

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jmacro.2009.01.006 Byline: Yifan Hu (a), Timothy Kam (b) Keywords: Optimal fiscal and monetary policy; Sticky prices; Liquid bonds Abstract: We introduce a model of government bonds with transactions services into a standard dynamic stochastic general equilibrium sticky-price monetary economy. This additional feature results in an endogenous interest-rate spread and affects equilibrium allocations and inflation by altering the Ramsey planner's sequence of implementability and sticky-price constraints. Qualitatively, the trade-off confronting a planner in sticky-price models shown in recent literature, between using inflation surprise and labor-income tax, is eliminated by the liquid bond channel. We find that the more sticky prices become, the more the optimal fiscal-monetary policy stabilizes prices and also creates less distortionary and less volatile income taxes by taxing the liquidity service of bonds. Quantitatively, we show that the additional tax instrument created by the bond liquidity channel can yield a sizable welfare gain from an economy without this channel. Author Affiliation: (a) Citic Securities International, 26/F Citic Tower, 1 Tim Mei Avenue, Hong Kong, China (b) School of Economics, H.W. Arndt Building 25A, Australian National University, ACT 0200, Australia Article History: Received 14 August 2008

Background Measurement error is a significant challenge in nutritional epidemiology research. Compared with traditional, isolated-nutrient research, dietary-pattern studies provide a more comprehensive approach to chronic disease prevention and have become popular in recent years. However, few studies have examined the impacts of measurement errors on dietary pattern analyses. Objectives We investigated the impacts of measurement errors on the 2 most commonly used dietary pattern derivation methods: principal component factor analysis (PCFA) and K-means cluster analysis (KCA). Methods We conducted a simulation study by taking the dietary data collected in the China Multi-Ethnic Cohort study as the "true values" and adding linear measurement errors for each food group to consider both systematic and random errors. We investigated the impacts of measurement errors from 2 aspects: distortion of the derived dietary patterns and estimated associations between the dietary patterns and disease. Results For both systematic and random errors, larger measurement errors caused more serious distortion of dietary patterns derived by PCFA and KCA, with consistency rates ranging from 67.5% to 100% and from 13.4% to 88.4%, respectively. In addition, for both systematic and random errors, larger measurement errors caused greater attenuation effects on the association coefficients. For a beneficial association (coefficient, −0.5), the estimated coefficients ranged from −0.287 to −0.450 and from −0.231 to −0.394 in the PCFA and KCA, respectively. For a harmful association (coefficient, 0.5), the estimated coefficients ranged from 0.295 to 0.449 and from −0.003 to 0.373 in the PCFA and KCA, respectively. Dietary patterns derived by PCFA with factor loadings of low discrepancies and dietary patterns derived by KCA with small cluster sample sizes are more vulnerable to measurement error. Conclusions Measurement errors could distort dietary patterns and attenuate the dietary pattern–disease association. The stability of dietary patterns under measurement errors differs when using PCFA and KCA. [ABSTRACT FROM AUTHOR]

Rebaudioside D (RD) is a natural low-calorie, high-sweet sweetener and an excellent sugar substitute. In this study, RD was produced by coupling glucosyltransferase (EUGT11) and sucrose synthase (SUS) with a novel strategy of immobilization to enhance the recyclability of enzymes and decrease the production costs of RD. Recombinant EUGT11 from Oryza sativa and SUS from Arabidopsis thaliana were expressed in Escherichia coli and immobilized onto Fe 3 O 4 @Uio-66 nanocomposite. The results of Fourier transform Infrared spectra (FT-IR), X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM), magnetic susceptibility (VSM), thermogravimetric (TG) analysis and Brunauer–Emmett–Teller (BET) indicated that the magnetic nanocomposite Fe 3 O 4 @Uio-66 was successfully fabricated and the two enzymes were separately immobilized on Fe 3 O 4 @Uio-66. The reusability, storage, pH and temperature stabilities of the immobilized enzymes were investigated and compared to that of free enzymes. It was more stable towards temperature compared with free enzyme. The kinetic properties of immobilized EUGT11 showed a lower V m and a higher K m compared to free EUGT11, and immobilized SUS showed a lower V m and K m compared to free SUS. The immobilized SUS had around 56% residual activity upon storage a period of 10 days at 4 °C. After 8 times, the catalytic activity of immobilized double enzyme still retained around 80%, which showed a desirable stability and reduced the overall cost of enzymes, indicating that the immobilized enzymes had a good industrial application prospect in RD production. [Display omitted] • Double-enzyme biocatalyst of glucosyltransferase and sucrose synthase was prepared. • Glucosyltransferase and sucrose synthase were first immobilized on Fe 3 O 4 @Uio-66. • The thermostability of enzyme was improved by immobilization. • The activity of immobilized double enzyme was maintained at 80% after 8 times of recycling. [ABSTRACT FROM AUTHOR]

With the increase of mass customization, flexible job shop scheduling problem considering assembly stage has widely existed in many manufacturing industries, such as die-casting mould factories. This problem is to find a reasonable machine assignment and operation sequence both in fabrication and assembly stages and simultaneously maximize production efficiency. In reality, energy shortages and environmental pollution have given an impetus to the development of energy-aware production scheduling problems. In this study, we address an energy-aware flexible assembly job shop scheduling problem (EFAJSP) with the objectives of minimizing flow time and energy consumption and first develop a mixed-integer linear programming (MILP) model to solve EFAJSP problem. Then, the model-specific characteristics are extracted and applied to a matheuristic decoding method for exploring the Pareto optimal solution. Due to the complexity of EFAJSP problem, a matheuristic and learning-oriented multi-objective artificial bee colony algorithm (MLABC), which combines the advantages of mathematical programming, reinforcement learning and meta-heuristic algorithm, is proposed. In addition, an initialization, destruction/construction operator and population update operator are proposed and work together to improve the exploration and exploitation performance of the proposed MLABC. Finally, numerical experimental results demonstrate the effectiveness of the proposed MILP model and the superiority of the MLABC over other algorithms in the literature. [ABSTRACT FROM AUTHOR]

Sample efficiency is a limiting factor for existing distributed multi-agent reinforcement learning (MARL) algorithms over networked multi-agent systems. In this paper, the sample efficiency problem is tackled by formally incorporating the entropy regularization into the distributed MARL algorithm design. Firstly, a new entropy-regularized MARL problem is formulated under the model of networked multi-agent Markov decision processes with observation-based policies and homogeneous agents, where the policy parameter sharing among the agents provably preserves the optimality. Secondly, an on-policy distributed actor–critic algorithm is proposed, where each agent shares its parameters of both the critic and actor for consensus update. Then, the convergence analysis of the proposed algorithm is provided based on the stochastic approximation theory under the assumption of linear function approximation of the critic. Furthermore, a practical off-policy version of the proposed algorithm is developed which possesses scalability, data efficiency and learning stability. Finally, the proposed distributed algorithm is compared against the solid baselines including two classic centralized training algorithms in the multi-agent particle environment, whose learning performance is empirically demonstrated through extensive simulation experiments. [ABSTRACT FROM AUTHOR]

Variation and seasonal reduction in the Upstream Kuroshio Transport (UKT) have important impacts on surrounding climate and oceanic circulation systems. Therefore, reliable UKT prediction is crucial. In this paper, we propose an intelligent UKT prediction model, KuroshioNet, which is firstly pre-trained with simulation data generated by the Regional Ocean Modeling System (ROMS) and then fine-tuned with reanalysis data of the Simple Ocean Data Assimilation (SODA). Operating at a five-day time resolution and a 0.5°spatial resolution, KuroshioNet has the capability to predict multivariate fields associated with upstream Kuroshio, including 3D variables like velocity, temperature, as well as salinity and 2D variables like sea surface height. Subsequently, the UKT is computed from the predicted fields. We evaluate and analyze the experimental results, which show that KuroshioNet has a lead time of 55 days for UKT prediction. In order to enhance the physical interpretability of KuroshioNet, we conduct an ablation experiment to evaluate the impact of each predictor on prediction skill. It demonstrates that selecting zonal velocity, meridional velocity, temperature, salinity, and SSH contributes to UKT prediction by KuroshioNet. Besides, by analyzing model performance and visualizing what the convolutional kernels learn, we find that KuroshioNet, which has learned from ROMS data, is capable of obtaining better initial performance and acquiring more active kernels to better learn the features in SODA data. Furthermore, we identify the targeted observation sensitive area of UKT seasonal reduction by KuroshioNet with the saliency map method, which is situated to the east of upstream kuroshio. The sensitive area is consistent with the result identified by numerical models and yields 38.1% improvement on prediction demonstrated by observing system simulation experiments. • KuroshioNet predicts multivariate 3D/2D fields associated with Upstream Kuroshio. • KuroshioNet is firstly trained with ROMS data and then with SODA data. • Lead time of prediction is 55 days for UKT, 15–30 days for UKT seasonal reduction. • KuroshioNet is physically interpretable by analyzing what it learns and predictors. • The identified targeted observation sensitive area has a 38.1% gain by OSSE. [ABSTRACT FROM AUTHOR]

In this work, tailored Mn–Zn ferrite ceramics are prepared by stereolithography (SLA) 3D printing technology, and its performances are measured utilizing the printing accuracy, magnetic properties, density, and microstructures. The major obstacle forming difficultly by single curing of self-made ferrite pastes with increasing solid content in the printing process is removed by using six scanning numbers. In addition, the prediction formulas of the linewidth and curing depth are established. The printing process parameters, namely scanning space, scanning speed, and laser power, are optimized at 2 μm, 2500 mm/s, and 240 mW, respectively. The size of convex platform bigger than 1 mm × 1.2 mm possessing circular and square holes with a diameter and a side length of 0.2 mm can be printed using the printing process parameters above. Specifically, the sintering temperature and holding time below 1200 °C and 90 min, respectively, are optimized conducive limits. The sintered parts show a density of 4.04 g/cm3 and a saturation magnetization of 58.6 emu/g, along with a small value of coercivity and remanence. The SLA-3D printing, debinding, and sintering technologies can print the complex shapes Mn–Zn ferrite ceramics using the proposed process. [ABSTRACT FROM AUTHOR]

The overuse and misuse of antibiotics have resulted in the pollution of antibiotics and antibiotic resistance genes (ARGs) in municipal wastewater treatment plants (WWTPs), posing threats to ecological security and human health. Thus, a comprehensive investigation was conducted to assess the occurrence, removal efficiency, and ecological risk of antibiotics, along with the diversity, abundance, and co-occurrence of ARGs, and their correlations in 13 WWTPs along the Yangtze River Basin. Among 35 target antibiotics, 23 antibiotics within 6 categories were detected in all the samples. Amoxicillin (AMO), ofloxacin (OFL), and pefloxacin (PEF) were predominant in influents, while AMO exhibited dominance with the highest concentration of 1409 ng/L in effluents. Although antibiotic removal performance varied among different WWTPs, a significant decrease in each antibiotic category and overall antibiotics was observed in effluents compared with that in influents (p < 0.05). Remarkably, ecological risk assessment revealed high risks associated with AMO and ciprofloxacin (CIP) and medium risks linked to several antibiotics, notably including OFL, roxithromycin (ROX), clarithromycin (CLA), and tetracycline (TC). Furthermore, 96 ARG subtypes within 12 resistance types were detected in this study, and the total absolute abundance and diversity of ARGs were significantly decreased from influents to effluents (p < 0.05). Enrichment of 38 ARGs (e.g., bla NDM , erm A, vat A, mex A, and dfrA 25) in effluents indicated potential health risks. Various mobile genetic elements (MGEs), exhibited significant correlations with a majority of ARGs in both influents and effluents, such as int Ⅰ1, tnp A1, tnp A5, and tp 614, underscoring the important role of MGEs in contributing to the ARG dissemination. Many antibiotics displayed lower correlations with corresponding ARGs, but exhibited higher correlations with other ARGs, suggesting complex selective pressures influencing ARG propagation. Overall, the incomplete elimination of antibiotics and ARGs in WWTPs is likely to pose adverse impacts on aquatic ecosystems in the Yangtze River Basin. [Display omitted] • Explore antibiotics, ARGs and their associations in WWTPs along the Yangtze River. • Antibiotics in effluents exhibited high risk (8.70%) and moderate risk (34.78%). • WWTP treatment reduced ARG abundance and diversity and altered ARG co-occurrence. • Several antibiotics and MGEs were correlated to the dissemination of ARGs. • WWTP effluents contributed to antibiotic and ARG pollution in the Yangtze River. [ABSTRACT FROM AUTHOR]

Inflammatory bowel disease (IBD) was a chronic intestinal disease related to autoimmunity, and its pathogenesis was complex. Forsythia suspensa (F. suspensa) had good anti-inflammatory and antioxidant effects. The active component polyphenols had significant effects in the treatment of intestinal inflammation. Researches had found that polarization, pyroptosis and apoptosis of macrophages can drive the occurrence and development of colitis. In this study, we examined whether F. suspensa polyphenols (FPP) mitigated DSS-induced colitis, and explored its potential mechanisms. The potential targets of F. suspensa in intestinal inflammation were predicted through network pharmacology. Using LPS and IFN-γ induced macrophage M1 polarization in J774A.1 cells. Macrophage polarization was detected through RT-qPCR, flow cytometry and ELISA. Ulcerative colitis (UC) in mice was induced by 2.5% DSS for 7 days, and then oral administrated different doses of FPP for another 7 days. Then we assessed the body weight, diarrhea, bleeding in stool, colon length, cytokines of serum and pathology of colon. The effects of FPP on the gut microbiota in mice also tested and evaluated. Our results showed that the main active ingredient of F. suspensa in protecting intestinal inflammation were polyphenols and F. suspensa was multi-targeted in the treatment of intestinal inflammation. FPP inhibited M1 polarization and polarizes towards M2 in J774A.1 cells. FPP inhibited pyroptosis and apoptosis to exert anti-inflammatory effects. FPP had a good protective effect on DSS induced UC in mice. In unison, FPP inhibited M1 polarization, apoptosis, and pyroptosis in UC mice. FPP regulated intestinal homeostasis in mice with UC by improving the gut microbiota and enhancing the intestinal metabolites short-chain fatty acid (SCFAs). These data indicated that FPP may alleviate UC by inhibiting M1 polarization in mice. Collectively, these findings suggest that the reduction of colitis by FPP may related to macrophage polarization, pyroptosis and apoptosis. [Display omitted] [ABSTRACT FROM AUTHOR]

In this paper, a novel composite adaptive fuzzy control (AFC) based on the command filtered backstepping and event-triggered mechanism is proposed for nonstrict-feedback nonlinear systems with input saturation and time-varying full-state constraints. A fuzzy observer is designed to estimate the unmeasured states. Simultaneously, by introducing a serial-parallel estimation model, a fuzzy control tactic with the composite adaptive law of parameters is established which greatly increases the precision of unknown term estimation. In addition, the command filtering technique is employed to solve the issue of "explosion of complexity" and compensate for the errors caused by the command filters. The event-triggered mechanism is utilized to effectively decrease the data redundancy. By using the time-varying barrier Lyapunov functions (BLFs), all the states can remain within a prescribed time-varying interval. The designed controller can guarantee the convergence of the tracking error at the origin and the boundedness of all closed-loop signals. Finally, two simulation examples are carried out to validate the effectiveness of the proposed control scheme. [ABSTRACT FROM AUTHOR]

• Different with the relevant literature, the nonlinear systems in the existence of computation burden while sustaining dead-zone constraints is considered in this paper. An adaptive controller and an auxiliary system are cooperatively constructed to compensate for the mismatch between the controller signal and the actuator signal and offset the effect of dead-zone nonlinear function. Integrated with the backstepping method, an adaptive compensation control scheme is developed. • By utilizing the DSC technique combined with the ETC algorithm, the system's operating rate can be effectively promoted and transmission resources can be greatly saved. Accordingly, the control property of the system can be well enhanced. Moreover, the collaborative devise of the adaptive fuzzy controller and the ETC algorithm eliminates the input-to-state stability hypothesis in the existing literature. • The BLF candidates proposed in this article can make the state variables maintain within the prescribed ranges, which is aligned with the requirements of the actual engineering. Furthermore, a variable separation technology is adopted to handle the algebraic loop issue generated by nonstrict-feedback nonlinear systems. Compared with the existing literature, by employing the characteristics of the fuzzy membership function in the FLSs, the construction procedure for the nonstrict-feedback system is simplified. Therefore, the difficulty coefficient of establishing the control algorithm is reduced. In this paper, a novel adaptive fuzzy dynamic surface control (DSC) via the event-triggered mechanism is developed for nonstrict-feedback nonlinear state constrained systems preceded by actuator dead-zone. The utilization of the dynamic surface technique avoids the issue of repeated differentiation of virtual control law and eliminates the drawback of the explosion of complexity with the backstepping technique. By utilizing the universal approximation property of fuzzy logic systems (FLSs), the unknown function is approximated successfully. By combining the DSC and event-triggered control (ETC) scheme, communication and computation strain are alleviated contemporaneously. An adaptive controller and an auxiliary system are cooperatively constructed to offset the effect of dead-zone nonlinear function. By employing the barrier Lyapunov functions (BLFs), all the states can remain within a prescribed interval. The tracking error can be restricted at the origin and all signals of closed-loop systems can be kept within the boundaries by the designed parameter adaptive laws and event-triggered controller. Finally, a numerical simulation result and a practical simulation result of the pendulum are proposed to guarantee the effectiveness of the presented control theory. [ABSTRACT FROM AUTHOR]

• Compared with the similar non-finite time control methods in the relevant literature, the finite-time adaptive controller designed in this paper has the merits that it can and enhance the transient performance of the entire control system and avoid the ISS assumption. • The nonlinear parametric system proposed in this paper is more general than the relevant literature, since the unknown external disturbances, uncertain system parameters, unknown control gain and unpredictable actuator faults are considered in this work simultaneously. The parameter updated laws are designed to estimate the unknown control gain and uncertain system parameters. Moreover, the FLSs are introduced to approximate the uncertain bias fault, which can compensate for the faults in a wider range, with better accuracy. • In the design of the ETC scheme, compared with the existing literature, the intermediate variable is introduced to embed the ETC signal into the actuator fault model and the adaptive control laws to further effectively eliminate the redundant items and avoid the tedious. In this article, the issue of adaptive finite-time event-triggered tracking control is investigated for nonlinearly parameterized systems with unknown faults and unknown control gain. By establishing the proper parameter adaptive laws with the intermediate variable, the problem of system instability caused by the uncertainty of the parametric system and the unknown faults of the actuator can be effectively handled. Simultaneously, the unknown nonlinear term denotes the bias fault is approximated by the fuzzy logic systems (FLSs). Accordingly, an improved event-triggered controller with a varying threshold strategy is developed to rule out the Zeno phenomenon and demonstrate that all the signals in the closed-loop system are semi-globally practically finite-time stable (SGPFS). Finally, a simulation result of the manipulator system is carried out to validate the proposed control scheme. [ABSTRACT FROM AUTHOR]

• A new class of multi-stress acceleration models with interaction effects is designed. • A multi-stress accelerated degradation model is further developed by incorporating a generalized Wiener process. • Simulation and a real-world case are performed to validate the effectiveness and practical values of the proposed model. Most products operate under multiple stresses. The influences of multi-stress factors on products are commonly not independent and promote a more violent degradation through interactions, referred to as stress interaction effects. However, few studies consider such effects in multi-stress acceleration models, which may reduce the extrapolation precision and further lead to an inaccurate reliability assessment. In this paper, a new class of multi-stress acceleration models with interaction effects is designed to extrapolate more accurate reliability metrics under multi-stress operating conditions. The main stress effect terms are determined by two criteria: physical stress-based ageing law and statistical correlation. The interaction effects are interpreted as the influences of other stress variables on the main stress effects. In particular, the explicit functions of interaction effects are alternative, which can be identified by adaptive optimization using the maximum likelihood criterion. Furthermore, this multi-stress acceleration model is extended to an accelerated degradation model by integrating a generalized Wiener process with nonlinear time scale functions and random effects. The acceleration factor constant principle is utilized to identify the stress-dependent parameters, facilitating a more appropriate model development. Finally, simulation and a real-world case are performed to validate the effectiveness and practical values of the proposed model. [ABSTRACT FROM AUTHOR]

As a key component in power electronic systems, the accurate reliability assessment of metallized film capacitors (MFC) is very critical to assure the system reliability and safety. In most operating conditions, the gradual capacitance decrease induced by dielectric film aging and the accumulation of each sudden capacitance loss by random self-healing events under elevated temperature and voltage are the main degradation mechanisms of MFC. However, most investigations tend to directly fit the MFC degradation data by some statistical means, which ignores the specific degradation mechanisms. Such treatments for degradation data often perform a lower modeling accuracy, which may also bring an obvious deviation of reliability assessment result. In this article, we design a degradation mechanisms-based reliability modeling approach for MFC under temperature and voltage stresses. The dielectric film aging is characterized by Wiener process, where the aging rate is dependent with temperature. The compound Poisson process is developed to capture the random self-healing events, where the arrival rate and each sudden capacitance loss are related to the operating voltage as well as the dielectric film aging rate. Finally, an ADT with temperature and voltage acceleration for MFC is conducted to validate the effectiveness of the proposed approach. • A degradation mechanisms-based reliability model for metallized film capacitor is designed. • The dielectric film aging and self-healing process are quantitatively characterized. • An ADT with temperature and voltage acceleration is conducted to validate the proposed model. [ABSTRACT FROM AUTHOR]