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It has been globally recognized that obesity has become a major public health concern, especially childhood obesity. There is limited information, however, regarding the exposure risk of organic ultraviolet (UV) filters, a kind of emerging contaminant, on childhood obesity. This study would be made on 284 obese and 220 non-obese Chinese children with eight organic UV filters at urinary levels. The eight organic UV filters, including 2-Ethylhexyl 4-aminobenzoate (PABA-E), octisalate (EHS), homosalate (HMS), 2-Ethylhexyl- p -methoxycinnamate (EHMC), benzophenone-3 (BP-3), amiloxate (IAMC), octocrylene (OC) and 4-Methylbenzylidene camphor (4-MBC) were identified in urine samples with detection rates ranged from 35.32% to 100%, among which PABA-E, HMS, IAMC and OC were firstly detected in children' s urine. And the urinary UV filters concentration was associated with genders, living sites, guardian education levels, household income, and dietary factors. Urinary EHMC concentrations and childhood obesity were positively associated for girls [Adjusted OR = 2.642 (95% CI: 1.019, 6.853)], while OC concentrations and childhood obesity were negatively associated for girls [Adjusted OR = 0.022 (95% CI: 0.001, 0.817)]. The results suggest that EHMC exposure may be an environmental obesogen for girls. Moreover, two statistical models were used separately to evaluate the impact of UV filter mixtures on childhood obesity, including the Bayesian kernel machine regression (BKMR) model and the quantile g-computation (qgcomp) model. The negative association between UV filter mixtures and childhood obesity was proposed from both BKMR and qgcomp models. Further experimental and epidemiological studies are called upon to discern the individual and mixture impacts of organic UV filters on childhood obesity. [Display omitted] • Chinese children have been widely exposed to multiple kinds of UV filters. • EHMC exposure could be an environmental pathogenic factor for girls. • OC exposure could be an environmental antagonistic factor for girls. • Co-exposure to organic UV filters was inversely associated with childhood obesity. [ABSTRACT FROM AUTHOR]

In this paper, a compact and low-loss diplexer is designed and fabricated using integrated passive device (IPD) technique. This IPD-based diplexer can be utilized in antenna system for WLAN and WiMAX applications. It is composed of a low-pass filter and a high-pass filter, built on the GaAs substrate with the overall size of 0.95 × 0.95 mm2. The IPD diplexer realizes a dual-mode operation of 2.4 GHz for WLAN and 3.3 GHz to 3.8 GHz for WiMAX, respectively. The measurement results match well with the simulation results, in which the insertion loss at operation bands are below 0.5 dB (2.4 GHz) and 0.64 dB (3.3 GHz to 3.8 GHz), and the stopband suppression keeps higher than 20 dB. [ABSTRACT FROM AUTHOR]

Abstract: The belief rule-base inference methodology using evidential reasoning (RIMER) approach has been proved to be an effective extension of traditional rule-based expert systems and a powerful tool for representing more complicated causal relationships using different types of information with uncertainties. With a predetermined structure of the initial belief rule-base (BRB), the RIMER approach requires the assignment of some system parameters including rule weights, attribute weights, and belief degrees using experts’ knowledge. Although some updating algorithms were proposed to solve this problem, it is still difficult to find an optimal compact BRB. In this paper, a novel updating algorithm is proposed based on iterative learning strategy for delayed coking unit (DCU), which contains both continuous and discrete characteristics. Daily DCU operations under different conditions are modeled by a BRB, which is then updated using iterative learning methodology, based on a novel statistical utility for every belief rule. Compared with the other learning algorithms, our methodology can lead to a more optimal compact final BRB. With the help of this expert system, a feedforward compensation strategy is introduced to eliminate the disturbance caused by the drum-switching operations. The advantages of this approach are demonstrated on the UniSim™ Operations Suite platform through the developed DCU operation expert system modeled and optimized from a real oil refinery. [Copyright &y& Elsevier]

Abstract: Delayed coking is the most effective process to decarbonize and demetallize heavy petroleum residues. However, it relies much on the field engineers’ experiences and expertise in practice for operating the controllers effectively and compatibly in delayed coking. This study establishes a knowledge database of intelligent switching expert system by analyzing the on-site data and operator’s experiences. A feed-forward control strategy based on iterative learning is introduced to erase disturbances arising from switching operation. The intelligent switching expert system (ISES) proposed here is guaranteed to be converged by introducing a convergence factor. The effectiveness and maneuverability of the ISES are proved by the simulation results on Shadow Plant Simulation Platform. [Copyright &y& Elsevier]

This paper presents a method of nonlinear dynamic matrix control based on multiple operating models. Its closed-loop stability and asymptotically unbiased tracking properties are proved. The application software (SMART-NLS) is developed using this method, and the simulation results of two nonlinear benchmark processes verify the feasibility and effectiveness of the proposed method. [Copyright &y& Elsevier]