Engine combustion modeling method based on hybrid drive.

Accurate and comprehensive reconstruction of in-cylinder combustion process is essential for timely monitoring of engine combustion state. This article developed a method based on the zero-dimensional (0-D) physical model integrated with big data. The traditional 0-D prediction model based on cumulative fuel mass is improved, the factor of in-cylinder temperature is introduced to adjust the heat release rate, which solves the problem of difficulty in calibrating the heat release rate. Then, convolutional neural network-gated recurrent unit (CNN-GRU), as a deep neural network, including a special convolutional layer and a gated recurrent unit (GRU) neural network is designed for the parameters to be calibrated in the model. The 0-D predictive combustion model is constructed by combining the physical model with CNN-GRU, the combustion process is simplified and reconstructed. The fitting results show that the 0-D physical model based on improved cumulative fuel mass approach is an effective method to reflect the heat release law. Under non-calibration conditions, the root mean square error (RMSE) value of peak firing pressure (PFP) based on CNN-GRU prediction model is 0.5862. The prediction model is a promising method to realize online fitting and optimization of combustion process.

The gut microbiota in experimental abdominal aortic aneurysm.

Background: Abdominal aortic aneurysm (AAA) is a life-threatening disease and there are no effective treatments to inhibit aneurysm progression and rupture. The gut microbiota has been increasingly recognized, as a new therapeutic target, because of its role in host homeostasis. However, the role of the gut microbiota in AAA has not been clarified. Therefore, we performed 16S rRNA analysis to determine and compare the composition of the gut microbiota between AAA and control groups. Methods: We used the classical angiotensin-II induced AAA mouse model to investigate the role of gut microbiota and abdominal aortic aneurysm. The mice were randomly assigned to 2 groups: the control (n = 7) group received saline (vehicle), while the AAA (n = 13) group received solutions of Ang II. Aortic tissue and fecal samples were harvested 28 days after infusion. Fecal samples were analyzed by 16S rRNA sequencing. Results: The levels of Oscillospira, Coprococcus, Faecalibacterium prausnitzii, Alistipes massiliensis, and Ruminococcus gnavus were increased in the AAA group, while those of Akkermansia muciniphila, Allobaculum, and Barnesiella intestinihominis were increased in the control group. Furthermore, network analysis and ZiPi score assessment highlighted species in the phylum Bacteroidetes as the keystone species. PICRUSt2 analysis revealed that PWY-6629 (a super pathway of L-tryptophan biosynthesis), PWY-7446 (sulfoglycolysis), and PWY-6165 [chorismate biosynthesis II (archaea)] may-be involved in the metabolic pathways that contribute to AAA formation, and E. coli/Shigella may be the key bacteria that influence those three pathways. Conclusion: Alterations in the gut microbiota may be associated with the formation of AAA. Akkermansia and Lactobacillus were significantly decreased in the AAA group, but the keystone species in the phylum Bacteroidetes and the metabolic products of these bacteria should be given more attention in AAA formation research.

4-Octyl Itaconate Alleviates Lipopolysaccharide-Induced Acute Lung Injury in Mice by Inhibiting Oxidative Stress and Inflammation.

BACKGROUND: Acute lung injury (ALI) is a fatal disease in the absence of pharmacological treatment. Oxidative stress and inflammation are closely related to ALI. Innate immune cells are the main source of reactive oxygen species (ROS). Macrophages play an extremely important role in ALI through the activation of inflammation and oxidative stress. Itaconate, a metabolite of tricarboxylic acid, has been reported to have strong antioxidant and anti-inflammatory effects. However, the role of itaconate in ALI is unclear. Herein, we use 4-octyl itaconate (OI), the cellular permeable derivate of itaconate, to study the effects of itaconate in vivo and in vitro. METHODS: We used OI to pretreat C57BL/6 mice and LPS-induced ALI models to illustrate the role of itaconate in acute lung injury. The mice were randomly divided into four groups: control group, OI (100 mg/kg) group, ALI Group, ALI + OI (50 mg/kg) group, and ALI + OI (100 mg/kg) group. RAW264.7 cells were used to further prove the role and mechanism of itaconate in vitro. RESULTS: According to the H&E staining of the lung, OI was observed to significantly reduce lung inflammation. The active oxygen content of tissues was also significantly reduced (P<0.05). OI reduced the accumulation of neutrophils and secretion of inflammatory factors in LPS-induced ALI (P<0.05). At the cellular level, OI also reduced oxidative stress and inflammation. Intervention with OI was also observed to upregulate the expression of nuclear factor erythroid 2-related factor-2 (Nrf-2) and Nrf-2 target genes in the lung tissue and RAW264.7 cells. CONCLUSION: OI alleviates LPS-induced ALI. Moreover, the antioxidant and anti-inflammatory effects of OI might depend on the activation of Nrf-2. Therefore, OI might have therapeutic potential for the treatment of ALI.

Modulating Neuro-Immune-Induced Macrophage Polarization With Topiramate Attenuates Experimental Abdominal Aortic Aneurysm.

The development of abdominal aortic aneurysm (AAA) is attributed to psychological and physical factors. Topiramate, which is an agonist of the GABAA receptor, makes contributions to neuronal disease and is partially involved in immune regulation, may be effective upon abdominal aortic aneurysm progression. We used experimental abdominal aortic aneurysm models: Angiotensin II (Ang II)-induced ApoE-/- male mice (Ang II/APOE model) in our study. In the Ang II/APOE model, all mice (n=64) were divided into four groups: sham group (PBS treatment), control group (Ang II treatment), low-dose group (Ang II + low-dose topiramate, 3 mg/day per mouse), and high-dose group (Ang II + high-dose topiramate, 6 mg/day per mouse). All treatments began on the day after surgery. Moreover, collected tissues and cultured cell were used for histology and biochemical examination. In vitro, the effects of topiramate on bone marrow-derived macrophage stimulated by LPS were investigated. Our data implied that topiramate treatment significantly promoted macrophages preservation and conversion of M1 to M2 macrophage phenotypes in vivo and in vitro. Accordingly, proinflammatory activities mediated by the M1 macrophages were decreased and the repair process mediated by M2 macrophages was enhanced. The low-dose and high-dose groups had abdominal aortic aneurysm incidences of 50% and 37.5%, respectively, compared with 75% in the control group. Topiramate, a promising drug for the psychological disease, that target neuro-immune-induced macrophage polarization may attenuate experimental abdominal aortic aneurysm progression.

All-trans retinoic acid attenuates the progression of Ang II-induced abdominal aortic aneurysms in ApoE-/-mice.

BACKGROUND: To determine whether all-trans retinoic acid (ATRA) can influence the development of Angiotensin II (Ang II) induced experimental abdominal aortic aneurysms (AAAs). METHODS: Apolipoprotein E knock-out (ApoE-/-) mice were randomly assigned to 4 groups. Mice in the AAA and ATRA groups underwent continuous subcutaneous Ang II infusion for 28 days to induce AAA, while the Sham and Control groups were infused with saline. Systolic blood pressure was measured by the tail-cuff technique. The Control and ATRA groups received ATRA treatment. Aortic tissue samples were obtained at 28 days after surgery and evaluated by aortic diameter measurement, Western blotting, immunohistochemistry, and hematoxylin-eosin (H&E) and Verhoeff-Van Gieson (EVG) staining. RESULTS: The abdominal aortic diameter was significantly reduced in the ATRA group compared with the AAA group (3 of 12 (25%) vs 9 of 12 (75%), P < 0.05), and the ATRA group exhibited reduced blood pressure on days 7, 14, and 28. Low expression of angiotensin II receptor type 1 (AT1), matrix metalloproteinase 2 (MMP2), and matrix metalloproteinase 9 (MMP9) and EVG staining revealed a significant reduction in the disruption of elastic fibers in the abdominal aortic tissue of the ATRA group compared to the AAA group. Western blot analysis indicated that protein levels of retinoic acid receptor α (RARα), MMP2, MMP9, and AT1 were dramatically affected by ATRA treatment. CONCLUSIONS: In conclusion, ATRA attenuates the progression of Ang II-induced AAAs, possibly by downregulating MMP2, MMP9, and AT-1 expression.

Experimental abdominal aortic aneurysm growth is inhibited by blocking the JAK2/STAT3 pathway.

BACKGROUND: The JAK/STAT pathway is a vital transcription signaling pathway that regulates gene expression and cellular activity. Our recently published study highlighted the role of IL-17A in abdominal aortic aneurysm (AAA) formation and rupture. IL-17A has been proven to upregulate vascular endothelial growth factor (VEGF) expression in some diseases. However, no study has demonstrated the relationships among JAK2/STAT3, IL-17A and VEGF. Therefore, we hypothesized that IL-17A may up-regulate VEGF expression via the JAK2/STAT3 signaling pathway to amplify the inflammatory response, exacerbate neovascularization, and accelerate AAA progression. METHODS: To fully verify our hypothesis, two separate studies were performed: i) a study investigating the influence of JAK2/STAT3 on AAA formation and progression. ii) a study evaluating the relationship among IL-17A, JAK2/STAT3 and VEGF. Human tissues were collected from 7 AAA patients who underwent open surgery and 7 liver transplantation donors. All human aortic tissues were examined by histological and immunohistochemical staining, and Western blotting. Furthermore, mouse aortic tissues were also examined by histological and immunohistochemical staining and Western blotting, and the mouse aortic diameters were assessed by high-resolution Vevo 2100 microimaging system. RESULTS: Among human aortic tissues, JAK2/STAT3, IL-17A and VEGF expression levels were higher in AAA tissues than in control tissues. Group treated with WP1066 (a selective JAK2/STAT3 pathway inhibitor), IL-17A, and VEGF groups had AAA incidences of 25%, 40%, and 65%, respectively, while the control group had an incidence of 75%. Histopathological analysis revealed that the IL-17A- and VEGF-related inflammatory responses were attenuated by WP1066. Thus, blocking the JAK2/STAT3 pathway with WP1066 attenuated experimental AAA progression. In addition, in study ii, we found that IL-17A siRNA seemed to attenuate the expression of IL-17A and VEGF in vivo study; treatment with VEGF siRNA decreased the expression of VEGF, while IL-17A expression remained high. In an in vitro study, rhIL-17A treatment increased JAK2/STAT3 and VEGF expression in macrophages in a dose-dependent manner. CONCLUSION: Blocking the JAK2/STAT3 pathway with WP1066 (a JAK2/STAT3 specific inhibitor) attenuates experimental AAA progression. During AAA progression, IL-17A may influence the expression of VEGF via the JAK2/STAT3 signaling pathway. This potential mechanism may suggest a novel strategy for nonsurgical AAA treatment.

Measurement Method for Height-Independent Vegetation Indices Based on an Active Light Source.

A coefficient CW, which was defined as the ratio of NIR (near infrared) to the red reflected spectral response of the spectrometer, with a standard whiteboard as the measuring object, was introduced to establish a method for calculating height-independent vegetation indices (VIs). Two criteria for designing the spectrometer based on an active light source were proposed to keep CW constant. A designed spectrometer, which was equipped with an active light source, adopting 730 and 810 nm as the central wavelength of detection wavebands, was used to test the Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) in wheat fields with two nitrogen application rate levels (NARLs). Twenty test points were selected in each kind of field. Five measuring heights (65, 75, 85, 95, and 105 cm) were set for each test point. The mean and standard deviation of the coefficient of variation (CV) for NDVI in each test point were 3.85% and 1.39% respectively, the corresponding results for RVI were 2.93% and 1.09%. ANOVA showed the measured VIs possessed a significant ability to discriminate the NARLs and had no obvious correlation with the measurement heights. The experimental results verified the feasibility and validity of the method for measuring height-independent VIs.

Experimental study on diesel engine exhaust gas recirculation performance and optimum exhaust gas recirculation rate determination method.

In order to study the exhaust gas recirculation (EGR) performance of marine diesel engines, a venturi high-pressure EGR device was established to overcome the exhaust gas reflow problem based on a certain type of turbocharged diesel engine. The EGR performance test is accomplished and an optimal EGR decision-making optimization method based on grey correlation coefficient modified is proposed. The results show that the venturi tube EGR can basically meet the injection requirements of high-pressure exhaust gas and achieve good results. Through the venturi tube EGR, the NO X emissions reduce significantly with the maximum drop of 30.6%. The explosive pressure in cylinder reduces with the EGR rate increases and the cylinder pressure curve shows a single peak at low-speed conditions and double peaks at high-speed condition. However, the fuel consumption rate, NO X and smoke have been negatively affected. Due to small samples, the traditional evaluation method is difficult to determine the optimal EGR rate reasonably, while the proposed method can effectively solve this problem. It can weaken the shortcomings of subjective judgement and greatly improve the rationality of decision-making results.

A performance degradation evaluation method for a turbocharger in a diesel engine.

As one of the key systems of the marine power plant diesel engine, the turbocharger directly affects whether the diesel engine can continuously and stably provide the power required for the ship. Owing to a number of uncontrollable factors, such as harsh working conditions and complex structures, the turbocharger may have various failures, causing it to lose its intended function. At present, the fault diagnosis of the marine turbocharger has not been paid enough attention yet and in most cases, the method of 'ex post diagnosis' is still adopted. When analysing the nonlinear correspondence between the failure symptoms and failure causes, it is difficult for the existing theories to meet the actual diagnostic requirements. This paper introduces the concept of gas-path diagnosis into the condition monitoring for a marine turbocharger for the first time and proposes the flow capacity index which characterizes the flow capacity of the component and the isentropic efficiency index which characterizes the operating efficiency of the component as two dimensionless evaluation indicators for turbocharger health status. Moreover, the nonlinear mapping relationship between these two health parameters and the gas-path measurable parameters of the turbocharger is studied, and a novel performance degradation evaluation method for a turbocharger is established. The proposed method has been tested in three test cases where the degradation of a model turbocharger has been analysed. These case studies have illustrated that the proposed method can accurately isolate the degraded components and further quantify the degradation of the components.

Preferred Revascularization Strategies in Patients with Ischemic Heart Failure: A Meta-Analysis.

Clinically, coronary artery bypass grafting (CABG) or percutaneous coronary intervention (PCI) is generally used to treat patients with ischemic heart failure. However, the optimal treatment strategy remains unknown. This study examined the efficacy of the two coronary revascularization strategies for severe ischemic heart failure by using a meta-analysis. Studies comparing the efficacy of CABG and PCI were obtained from PubMed, EMBASE, Google Scholar and Cochrane Central Register of Controlled Trials (CENTRAL). The quality of each eligible article was evaluated by Newcastle-Ottawa Quality Assessment Scale (NOS), and the meta-analysis was performed using Stata version 12.0 software. Eventually, 12 studies involving 9248 patients (n=4872 in CABG group; n=4376 in PCI group) were subject to the meta-analysis for subsequent pooling calculation. The pooled hazard ratio (HR) [HR=0.83, 95% CI (0.76, 0.90), P<0.001; heterogeneity, P=0.218, I2=22.9%] of CABG compared with that of PCI revealed a statistical superiority of CABG to PCI in terms of the long-term mortality. Furthermore, CABG showed more advantages over PCI with respect to the incidence of myocardial infarction [HR=0.51, 95% CI (0.39, 0.67), P<0.001; heterogeneity, P=0.707, I2=0%] and repeat revascularization [HR=0.40, 95% CI (0.27, 0.59), P<0.001; heterogeneity, P<0.001, I2=80.1%]. It was concluded that CABG appears to be more advantageous than PCI for the treatment of ischemic heart failure in the given clinical setting.

Compressor map regression modelling based on partial least squares.

In this work, two kinds of partial least squares modelling methods are applied to predict a compressor map: one uses a power function polynomial as the basis function (PLSO), and the other uses a trigonometric function polynomial (PLSN). To demonstrate the potential capabilities of PLSO and PLSN for a typical interpolated prediction and an extrapolated prediction, they are compared with two other classical data-driven modelling methods, namely the look-up table and artificial neural network (ANN). PLSO and PLSN are also compared with each other. The results show that PLSO and PLSN have a better prediction performance than the look-up table and the ANN, especially for the extrapolated prediction. The computational time is also decreased sharply. Compared with PLSO, PLSN is characterized by a higher prediction accuracy and shorter computational time than PLSO. It is expected that PLSN could save computational time and also improve the accuracy of a thermodynamic model of a diesel engine.

Optimized modelling and application of exhaust gas recirculation performance evaluation of turbocharged diesel engine.

Aimed at the problem of exhaust gas recirculation (EGR) performance evaluation and optimal EGR rate determination of turbocharged diesel engines, an optimized decision-making method, based on grey theory and entropy weight, was proposed. The internal combustion pressure, fuel consumption rate, NOX, CO and smoke were selected as the decision-making targets and the initial decision-making model was established based on the traditional grey decision-making theory. According to the characteristics and optimization requirements of EGR, the optimal compromise between combustion and emission performance is proposed to transform into decision-making target weighting problem, then an optimized subjective weighting method based on expert scoring and grey relational analysis is proposed. Finally, the entropy weight method was used to solve the objective weight and the optimized multi-objective grey decision-making model was established, which can not only weaken the human error of subjective empowerment, but also fully explore the intrinsic relationship of the evaluation indexes. At last, an optimization simulation platform for EGR performance evaluation based on MATLB/GUIDE was designed and established. The results show that the optimization simulation platform can effectively improve the efficiency of simulation calculation, which is more convenient for practical engineering applications. The optimized method can successfully realize EGR performance evaluation and optimal EGR rate determination under different working conditions. The decision-making result was consistent with the present EGR control strategies, which provide a new research idea for EGR performance optimization.

Improving rolling bearing online fault diagnostic performance based on multi-dimensional characteristics.

As the main cause of failure and damage to rotating machinery, rolling bearing failure can result in huge economic losses. As the rolling bearing vibration signal is nonlinear and has non-stationary characteristics, the health status information distributed in the rolling bearing vibration signal is complex. Using common time-domain or frequency-domain approaches cannot easily enable an accurate assessment of rolling bearing health. In this paper, a novel rolling bearing fault diagnostic method based on multi-dimensional characteristics was developed to meet the requirements for accurate diagnosis of different fault types and severities with real-time computational performance. First, a multi-dimensional feature extraction algorithm based on entropy characteristics, Holder coefficient characteristics and improved generalized fractal box-counting dimension characteristics was performed to extract the health status feature vectors from the bearing vibration signals. Second, a grey relation algorithm was employed to achieve bearing fault pattern recognition intelligently using the extracted multi-dimensional feature vector. This experimental study has illustrated that the proposed method can effectively recognize different fault types and severities after integration of the improved fractal box-counting dimension into the multi-dimensional characteristics, in comparison with existing pattern recognition methods.

Targeting the class IA PI3K isoforms p110α/δ attenuates heart allograft rejection in mice by suppressing the CD4+ T lymphocyte response.

Acute rejection is the most important factor causing allograft loss, which remains a challenge for patients undergoing organ transplantation. There is considerable evidence indicating that the activity of PI3K and its downstream positive and negative regulators plays a major role in regulating the activation of different subsets of effector CD4+ T cells. Thus, we investigated whether class A PI3Ks are involved in the development of acute allograft rejection, we found that p110α protein expression levels in the allograft group were significantly up-regulated on day 7 post-transplantation, while p110ß and p110δ expression was significantly increased on days 5 and 7 post-transplantation. Treatment with PIK and IC but not TGX significantly prolonged allograft survival and altered pathological grades. The percentages of Th1 and Th2, Th17 and Tfh cells/monocytes in the spleens from the IC treatment group were all down-regulated. In contrast, the percentage of Treg cells in the spleens from IC treatment group was remarkably increased. IL-17A and IL-21 and IFN-γ expression levels were significantly decreased in the IC group. Moreover, IC significantly reduced P70 S6 Kinase ß and 4E-BP1 protein expression. In conclusion, small-molecule inhibitors of p110δ and p110α suppress acute heart allograft rejection in mice. These inhibitors may play a role in anti-rejection by impacting the phosphorylation and expression of proteins in the AKT/mTOR pathway to modulate CD4+ T cell subsets levels in recipients, reduce proinflammatory factor expression and increase anti-inflammatory cytokine expression. These findings indicate that some small-molecule inhibitors of p110 can serve as novel targets in acute allograft rejection treatment.

A prediction model of compressor with variable-geometry diffuser based on elliptic equation and partial least squares.

To achieve a much more extensive intake air flow range of the diesel engine, a variable-geometry compressor (VGC) is introduced into a turbocharged diesel engine. However, due to the variable diffuser vane angle (DVA), the prediction for the performance of the VGC becomes more difficult than for a normal compressor. In the present study, a prediction model comprising an elliptical equation and a PLS (partial least-squares) model was proposed to predict the performance of the VGC. The speed lines of the pressure ratio map and the efficiency map were fitted with the elliptical equation, and the coefficients of the elliptical equation were introduced into the PLS model to build the polynomial relationship between the coefficients and the relative speed, the DVA. Further, the maximal order of the polynomial was investigated in detail to reduce the number of sub-coefficients and achieve acceptable fit accuracy simultaneously. The prediction model was validated with sample data and in order to present the superiority of compressor performance prediction, the prediction results of this model were compared with those of the look-up table and back-propagation neural networks (BPNNs). The validation and comparison results show that the prediction accuracy of the new developed model is acceptable, and this model is much more suitable than the look-up table and the BPNN methods under the same condition in VGC performance prediction. Moreover, the new developed prediction model provides a novel and effective prediction solution for the VGC and can be used to improve the accuracy of the thermodynamic model for turbocharged diesel engines in the future.

An EGR performance evaluation and decision-making approach based on grey theory and grey entropy analysis.

Exhaust gas recirculation (EGR) is one of the main methods of reducing NOX emissions and has been widely used in marine diesel engines. This paper proposes an optimized comprehensive assessment method based on multi-objective grey situation decision theory, grey relation theory and grey entropy analysis to evaluate the performance and optimize rate determination of EGR, which currently lack clear theoretical guidance. First, multi-objective grey situation decision theory is used to establish the initial decision-making model according to the main EGR parameters. The optimal compromise between diesel engine combustion and emission performance is transformed into a decision-making target weight problem. After establishing the initial model and considering the characteristics of EGR under different conditions, an optimized target weight algorithm based on grey relation theory and grey entropy analysis is applied to generate the comprehensive evaluation and decision-making model. Finally, the proposed method is successfully applied to a TBD234V12 turbocharged diesel engine, and the results clearly illustrate the feasibility of the proposed method for providing theoretical support and a reference for further EGR optimization.

Organ transplantation and gut microbiota: current reviews and future challenges.

Organ transplantation is often the only effective treatment for patients with end-stage diseases, such as heart, liver, kidney and small bowel failure and is carried out frequently worldwide. Still the post-transplantation complications remain health- and life-threatening outcome that needed to be resolved. With the rapid development of molecular technologies in recent years, more and more researchers realize that the gut microbiota may play a critical role in human diseases. The intestinal microbiome has been proved to provide a lot of functions to the host, such as digesting food, modulating metabolism, promoting angiogenesis and regulating the immune system. Several studies have investigated the alteration of intestinal microbiota in post-transplantation patients and observed significant changes in the intestinal microbiome compared to the pre-transplant condition. Due to the abovementioned features that the gut microbiota may be used in the prognosis of clinical outcome of organ transplantation. In addition, the FMT (fecal microbiota transplantation), probiotics and prebiotics as the newest therapy methods, effectiveness of which has been verified in some diseases, such as Clostridium difficile infection, inflammatory bowel disease and other chronic disorders, might be used as the prognosis tool in organ transplantation as well. The purpose of this present review is to elucidate the relationship between gut microbiota and organ transplantation as well as the potential use of new therapies like fecal microbiota transplantation, probiotic and prebiotic administration after the transplantation, and provide some ideas for future researches in field of organ transplantation.