Self-optimization wavelet-learning method for predicting nonlinear thermal conductivity of highly heterogeneous materials with randomly hierarchical configurations

In the present work, we propose a self-optimization wavelet-learning method (SO-W-LM) with high accuracy and efficiency to compute the equivalent nonlinear thermal conductivity of highly heterogeneous materials with randomly hierarchical configurations. The randomly structural heterogeneity, temperature-dependent nonlinearity and material property uncertainty of heterogeneous materials are considered within the proposed self-optimization wavelet-learning framework. Firstly, meso- and micro-structural modeling of random heterogeneous materials are achieved by the proposed computer representation method, whose simulated hierarchical configurations have relatively high volume ratio of material inclusions. Moreover, temperature-dependent nonlinearity and material property uncertainties of random heterogeneous materials are modeled by a polynomial nonlinear model and Weibull probabilistic model, which can closely resemble actual material properties of heterogeneous materials. Secondly, an innovative stochastic three-scale homogenized method (STSHM) is developed to compute the macroscopic nonlinear thermal conductivity of random heterogeneous materials. Background meshing and filling techniques are devised to extract geometry and material features of random heterogeneous materials for establishing material databases. Thirdly, high-dimensional and highly nonlinear material features of material databases are preprocessed and reduced by wavelet decomposition technique. The neural networks are further employed to excavate the predictive models from dimension-reduced low-dimensional data

Ground Spring with Electrically Conductive Bristles

Due to the relatively small size and shape of a knob, some portion of its internal circuitry is placed close to its external metal controller ring (bangle), making the circuitry vulnerable to electrostatic discharge (ESD). This disclosure describes techniques to establish a dedicated ESD pathway between electrical parts in relative motion (e.g., a controller bangle around a knob and the electronics housed within the knob) by using a spring-like metal structure comprising conductive bristles to receive electric charge from the bangle and to conduct it to ground via a trace on a printed circuit board (PCB) within the knob. ESD current is deflected from sensitive electronics and prevented from damaging it. The ESD current is carried away from the bangle to the PCB by conductive bristles, such that the smooth rotary movement of the bangle is unaffected and occurs without the production of unwanted noise or vibrations

Conceptual Design of Non-ideal Mixtures Separation with Light Entrainers

A method is proposed to study the separation of minimum-, maximum-boiling azeotropic, and low volatility mixtures with a light entrainer, to investigate feasible regions of the key operating parameters reboil ratio (S) and entrainer - feed flowrate ratio (FE/F) for continuous processes. The thermodynamic topological predictions are carried out for 1.0–2, 1.0–1a, and 0.0–1 Serafimov’s class diagrams. It relies upon the knowledge of residue curve maps, along with the univolatility line, and it enables the prediction of possible products at the bottom of the column and limiting values of FE/F. The profiles of the stripping, extractive, and rectifying sections are calculated by equations considering S and FE/F, and they bring information about the location of singular points and possible composition profile separatrices that could impair process feasibility. Providing specified product composition and recovery, the approximate calculations are compared with rigorous simulations of extractive distillation processes. Separating non-ideal mixtures using a light entrainer provides more opportunities for the case when it is not easy to find an appropriate heavy or intermediate entraine

Novel Procedure for Assessment of Feasible Design Parameters of Dividing-Wall Columns: Application to Non-azeotropic Mixtures

Dividing wall columns (DWCs), as a subset of fully thermally coupled distillation systems (FTCDS), is considered as one of most appealing distillation technologies to the chemical industry, because it can bring about substantial reduction in the capital investment, as well as savings in the operating costs. This study targets on how to improve the energy efficiency of DWCs by achieving their well-designed feasible parameters. Two methods are applied to study the effect of liquid and vapor split ratios including a shortcut method and a method of systematic calculations by using differential equation profiles. In the latter approach, differential composition profiles in each column section are obtained by considering feasible key design parameters. The finding of pinch points for each section profiles allowed determining the limiting values of the operating parameters. The intersections of these profiles are used to get well-designed feasible parameters of the liquid and vapor split ratios in an attempt to obtain the desired purities of the top, bottom, and side-stream products. The obtained parameters are validated by rigorous simulations. Three types of case studies involve the separation of hydrocarbons (n-pentane, n-hexane, n-heptane), aromatics (benzene, toluene, p-xylene), and alcohols (ethanol, propanol, butanol)

Orexigenic Hormone Ghrelin Attenuates Local and Remote Organ Injury after Intestinal Ischemia-Reperfusion

Gut ischemia/reperfusion (I/R) injury is a serious condition in intensive care patients. Activation of immune cells adjacent to the huge endothelial cell surface area of the intestinal microvasculature produces initially local and then systemic inflammatory responses. Stimulation of the vagus nerve can rapidly attenuate systemic inflammatory responses through inhibiting the activation of macrophages and endothelial cells. Ghrelin, a novel orexigenic hormone, is produced predominately in the gastrointestinal system. Ghrelin receptors are expressed at a high density in the dorsal vagal complex of the brain stem. In this study, we investigated the regulation of the cholinergic anti-inflammatory pathway by the novel gastrointestinal hormone, ghrelin, after gut I/R.Gut ischemia was induced by placing a microvascular clip across the superior mesenteric artery for 90 min in male adult rats. Our results showed that ghrelin levels were significantly reduced after gut I/R and that ghrelin administration inhibited pro-inflammatory cytokine release, reduced neutrophil infiltration, ameliorated intestinal barrier dysfunction, attenuated organ injury, and improved survival after gut I/R. Administration of a specific ghrelin receptor antagonist worsened gut I/R-induced organ injury and mortality. To determine whether ghrelin's beneficial effects after gut I/R require the intact vagus nerve, vagotomy was performed in sham and gut I/R animals immediately prior to the induction of gut ischemia. Our result showed that vagotomy completely eliminated ghrelin's beneficial effect after gut I/R. To further confirm that ghrelin's beneficial effects after gut I/R are mediated through the central nervous system, intracerebroventricular administration of ghrelin was performed at the beginning of reperfusion after 90-min gut ischemia. Our result showed that intracerebroventricular injection of ghrelin also protected the rats from gut I/R injury.These findings suggest that ghrelin attenuates excessive inflammation and reduces organ injury after gut I/R through activation of the cholinergic anti-inflammatory pathway

Identifying the most influential roads based on traffic correlation networks

Prediction of traffic congestion is one of the core issues in the realization of smart traffic. Accurate prediction depends on understanding of interactions and correlations between different city locations. While many methods merely consider the spatio-temporal correlation between two locations, here we propose a new approach of capturing the correlation network in a city based on realtime traffic data. We use the weighted degree and the impact distance as the two major measures to identify the most influential locations. A road segment with larger weighted degree or larger impact distance suggests that its traffic flow can strongly influence neighboring road sections driven by the congestion propagation. Using these indices, we find that the statistical properties of the identified correlation network is stable in different time periods during a day, including morning rush hours, evening rush hours, and the afternoon normal time respectively. Our work provides a new framework for assessing interactions between different local traffic flows. The captured correlation network between different locations might facilitate future studies on predicting and controlling the traffic flows. © 2019, The Author(s)

Pharmacokinetics of lansoprazole injection in peptic ulcer and healthy volunteers

The pharmacokinetics of lansoprazole after a single intravenous dose of 30 mg was determined in 10 healthy volunteers and 10 peptic ulcers patients. In this work, a liquid-liquid extraction and enrichment method with RP-HPLC determination route was taken with high sensitivity and low limit detection of 5 ng/mL. The concentration-time curves in the two groups were best fitted to a two-compartment model, but their main kinetic parameters were remarkably different between healthy and ulcers volunteers. The mean maximum plasma concentration (Cmax ) and area under the curve (AUC0t ) were increased from 975.8 ng/mL to 1298.7 ng/mL and from 1439 ng·h/mL to 2301 ng·h/mL, respectively, and peak time (tmax ) decreased from 0.36 h to 0.26 h. Meanwhile, the half life (t1/2 ) prolonged from 2.25 h to 2.91 h and the clearance (CL) reduced from 20.04 L/h to 13.96 L/h. That variability of lansoprazole pharmakinetic parameter indicates that ulcers have significant effect on its metabolic process.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Pre-Treatment of Recombinant Mouse MFG-E8 Downregulates LPS-Induced TNF-α Production in Macrophages via STAT3-Mediated SOCS3 Activation

Milk fat globule-epidermal growth factor factor 8 (MFG-E8) regulates innate immune function by modulating cellular signaling, which is less understood. Herein, we aimed to investigate the direct anti-inflammatory role of MFG-E8 in macrophages by pre-treatment with recombinant murine MFG-E8 (rmMFG-E8) followed by stimulation with LPS in RAW264.7 cells and in peritoneal macrophages, isolated from wild-type (WT) or MFG-E8−/− mice. RAW264.7 cells and mouse peritoneal macrophages treated with rmMFG-E8 significantly downregulated LPS-induced TNF-α mRNA by 25% and 24%, and protein levels by 29% and 23%, respectively (P<0.05). Conversely, peritoneal macrophages isolated from MFG-E8−/− mice produced 28% higher levels of TNF-α, as compared to WT mice when treated with LPS. In in vivo, endotoxemia induced by intraperitoneal injection of LPS (5 mg/kg BW), at 4 h after induction, serum level of TNF-α was significantly higher in MFG-E8−/− mice (837 pg/mL) than that of WT (570 pg/mL, P<0.05). To elucidate the direct anti-inflammatory effect of MFG-E8, we examined STAT3 and its target gene, SOCS3. Treatment with rmMGF-E8 significantly induced pSTAT3 and SOCS3 in macrophages. Similar results were observed in in vivo treatment of rmMFG-E8 in peritoneal cells and splenic tissues. Pre-treatment with rmMFG-E8 significantly reduced LPS-induced NF-κB p65 contents. These data clearly indicated that rmMFG-E8 upregulated SOCS3 which in turn interacted with NF-κB p65, facilitating negative regulation of TLR4 signaling for LPS-induced TNF-α production. Our findings strongly suggest that MFG-E8 is a direct anti-inflammatory molecule, and that it could be developed as a therapy in attenuating inflammation and tissue injury