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In this work, we have synthesized and characterized a series of Donor−Acceptor (D–A) conjugated polymers (PffBT4T-2DT) with different molecular weights, introduced a microwave method into the synthesis process, shortened the experimental cycle time by over 5 days and increased the molecular weight of the polymers. The conditions affecting the molecular weight of the polymers were investigated. It is shown that the prepared conjugated polymers have excellent thermal stability and solubility, higher molecular weight polymers have broader absorption spectra and stronger inter-chain aggregation, and the strong aggregation ability of polymer chains is dependent on molecular weight and solution temperature, with lower polymer molecular weight and higher solution temperature both causing weaker polymer chain aggregation. The polymer films of the three molecular weights have a uniform surface with a roughness of about 0.83 and good crystallinity. Transistor test results show that the higher molecular weight polymers perform better when applied to field effect transistors, with mobilities as high as 0.124 cm2 V−1 s−1 and threshold voltages as low as 2 V. A series of donor-acceptor conjugated polymers (PffBT4T-2DT) with different molecular weights were synthesized by introducing the microwave method. The thermodynamic, optical, electrochemical and photovoltaic properties of the polymers were characterized, and the effect of molecular weight on the performance of organic field effect transistors (OFETs) was investigated. [ABSTRACT FROM AUTHOR]

Using ZnO nanowires as needle anodes in gas discharge is helpful for maintaining continuous discharge with a relatively low voltage. It is necessary that the ZnO nanowires are far enough apart to guarantee no electric field weakening and that the nanowire anodes are easy to assemble together with the discharging devices. An AC/DC electric-field-assisted wet chemical method is proposed in this paper. It was used to grow ZnO nanowires directly on discharging devices. The nanowires covered the whole electrode in the case in which only a DC field was applied. Moreover, the tips of the nanowires were scattered, similar to the results observed under the application of AC fields. The average distance between the tips of the highest nanowires was approximately equal to 4 μm, which almost meets the requirement of gas discharge. The research concerning growing ZnO nanowires directly on PCBs shown that, at the current time, ZnO nanowires on PCBs did not meet the requirements of gas discharge; however, in this study, the parameters regarding ZnO nanowire growth were established. [ABSTRACT FROM AUTHOR]

Simple Summary: Wilson's disease (WD) is a rare autosomal recessive inherited disorder of copper (Cu) metabolism, which is one of the few neurogenetic diseases with a cure. Cu deposition in the heart tissue is a mechanism of cardiac involvement. Importantly, Gandouling (GDL) effectively promotes the excretion of intracellular Cu. Therefore, the purpose of this study was to evaluate the protective effects of GDL on heart injuries and the underlying mechanisms in a copper sulfate (CuSO4)-induced animal model. The results showed that the protective effect of GDL on the heart was superior to that of penicillamine. We assessed the protective effects of Gandouling (GDL) on copper sulfate (CuSO4)-induced heart injuries in Sprague–Dawley rats, which were randomly divided into the control, CuSO4, GDL + CuSO4 and penicillamine + CuSO4 groups. The rats received intragastric GDL (400 mg/kg body weight) once per day for 42 consecutive days after 56 days of CuSO4 exposure, and penicillamine was used as a positive control. The levels of plasma inflammatory cytokines (IMA, hFABP, cTn-I and BNP) were determined using the enzyme-linked immunosorbent assay. The histopathological symptoms were evaluated using hematoxylin and eosin staining and transmission electron microscopy. To determine the underlying mechanism, Western blotting was conducted for the detection of the heme oxygenase 1 (HO-1) expression. The results revealed that GDL supplementation alleviated the histopathological symptoms of the rat heart tissue, promoted Cu excretion to attenuate impairment, and significantly decreased inflammatory cytokine levels in the plasma (p < 0.01). In addition, GDL increased the HO-1 expression in the rat hepatic tissue. The protective effect of GDL on the heart was superior to that of penicillamine. Overall, these findings indicate that GDL alleviates hepatic heart injury after a Cu overaccumulation challenge, and GDL supplements can be beneficial for patients with Wilson's disease. [ABSTRACT FROM AUTHOR]

Indoor 3D object detection is an essential task in single image scene understanding, impacting spatial cognition fundamentally in visual reasoning. Existing works on 3D object detection from a single image either pursue this goal through independent predictions of each object or implicitly reason over all possible objects, failing to harness relational geometric information between objects. To address this problem, we propose a sparse graph-based pipeline named Explicit3D based on object geometry and semantics features. Taking the efficiency into consideration, we further define a relatedness score and design a novel dynamic pruning method via group sampling for sparse scene graph generation and updating. Furthermore, our Explicit3D introduces homogeneous matrices and defines new relative loss and corner loss to model the spatial difference between target pairs explicitly. Instead of using ground-truth labels as direct supervision, our relative and corner loss are derived from homogeneous transforms, which renders the model to learn the geometric consistency between objects. The experimental results on the SUN RGB-D dataset demonstrate that our Explicit3D achieves better performance balance than the-state-of-the-art. • We propose a sparse graph-based pipeline for single image 3D indoor scene detection. • A novel relatedness score guides dynamic pruning for sparse scene graph generation. • Homogeneous matrices are used to explicitly represent relative spatial relationships. • A novel relative loss boosts spatial offset prediction and overall object detection. [ABSTRACT FROM AUTHOR]

Diesel Particulate Filter (DPF) stands out as a highly effective device for mitigating emissions in engines. To enhance DPF regeneration performance, the numerical model and the GA-BP neural network model are developed, which delves into the impacts of velocity, temperature, oxygen mass fraction, and particles size on particulate conversion. The results show that conversion rate of carbon particles can be elevated by increasing the oxygen mass fraction and inlet velocity. Specifically, the conversion rate demonstrates a remarkable improvement of 37.41% at T in = 600 K, d e = 5 μm, V in = 10 m/s, and m O2 increased from 0.01 to 0.04. Additionally, conversion rates are increased as the size of the carbon particles gradually reduced. Besides, a GA-BP neural network is deployed to analyze and predict the numerical results of 1818 sets of DPFs under different operating conditions. From the analysis and prediction of 132 data sets, and it is discerned that a high state of contamination transformation can be achieved at T in = 525 K, d e = 5 μm, V in = 12 m/s and m O2 = 0.04. This demonstrates the significance of judiciously selecting boundary conditions for realizing effective regenerative emission reduction. • Coupling effects of particle parameters and operating conditions on regeneration performance of DPF are investigated. • A GA-BP neural network is deployed to analyze and predict the numerical results. • The optimal boundary condition for DPF regeneration is obtained to reduce engine emissions. [ABSTRACT FROM AUTHOR]

This document is a correction notice for an article titled "Gandouling Mitigates CuSO4-Induced Heart Injury in Rats" published in the journal Animals. The correction addresses an error in Figure 4 of the original publication, where Figure 4F was unintentionally duplicated. The corrected Figure 4 has been provided, and the authors state that this correction does not affect the scientific conclusions of the study. The authors apologize for any inconvenience caused and express gratitude to a reader for bringing this matter to their attention. [Extracted from the article]

Micro-lumps in liver is a pathological stage that occurs in the late stage of the development of a variety of chronic liver diseases ; itis equivalent to liver fibrosis and other diseases in western medicine. According to traditional Chinese medicine (TCM), the basic pathogenesis of micro-lumps in liver is deficiency of the original qi, deficiency of the vital qi, and turbidities of phlegm and blood stasis, the foundation is Qi deficiency, and the presentation is phlegm turbidity and blood stasis, which forming the basic pathogenesis of micro-lumps in liver. Besides, the phlegm turbidity and blood stasis mong which the intermingled phlegm and blood stasis is re the key pathological factors affecting the whole disease throughout the whole process of the disease. The basic principle of the treatment of this disease is to simultaneously treat phlegm and blood stasis. Studies have shown that liver fibrosis in Wilson disease belongs to the category of micro-lumps in liver. Based on the theory of micro-lumps in liver, this paper discusses the TCM etiology, pathogenesis, clinical outcomes, and intervention strategies of liver fibrosis in Wilson disease. It is concluded that the disease is the accumulation of micro-lumps in liver, the intermingled phlegm and blood stasis is the basic pathological feature of the disease, the deficiency of vital qi is the key to its pathogenesis, and the general treatment is aimed at strengthening body resistance to eliminate pathogenic factors and dispel phlegm and remove blood stasis at the same time. We provide a reference for the clinical prevention and treatment of liver fibrosis in Wilson disease. [ABSTRACT FROM AUTHOR]

Background: Wilson's disease (WD) is an autosomal recessive disorder of copper metabolism caused by ATP7B (encoding a copper-transporting P-type ATPase) variants that shows various characteristics according to race and geographical region. This study was aimed to provide a comprehensive analysis of ATP7B variants in China and to investigate a plausible role of common variants in WD manifestations. Methods: A total of 1366 patients (1302 index patients and 64 siblings) clinically diagnosed with WD (Leipzig score ≥ 4) were recruited. They underwent ATP7B gene sequencing and information of age and symptoms at onset was collected. The genotype–phenotype correlation was assessed in the index patients who were examined with two pathogenic variants and onset with hepatic (n = 276) or neurologic (n = 665) symptoms. Results: We identified 294 potentially pathogenic ATP7B variants (112 truncating, 174 missense, 8 in-frame) in the 1302 index patients, including 116 novel variants. The most frequent variant was c.2333G>T (R778L, allele frequency: 28.96%), followed by c.2975C>T (P992L, 13.82%), c.2621C>T (A874V, 5.99%), c.2755C>G (R919G, 2.46%), and c.3646G>A (V1216M, 1.92%). In 1167 patients, both pathogentic variants were identified, of which 532 different variant combinations were found. By binary logistic regression analysis, the factor associated with neurological presentation was high age-at-onset, but not sex, protein-truncating variant (PTV), or the common missense variants (R778L, P992L, and A874V). In the neurological group, low age-at-onset was a factor associated with dystonia, gait abnormality, and salivation; high age-at-onset was a factor associated with tremor; and the sex, low age-at-onset and A874V were independent factors associated with dysarthria. In addition, PTV, R778L, and P992L were predominant in early-onset patients, whereas A874V was predominant in late-onset patients, and patients with R778L/A874V genotype displayed a higher age-at-onset than patients with R778L/R778L or R778L/P992L genotype. Conclusions: Our work expanded the ATP7B variant spectrum and highlighted the differences among patients with WD in age-at-onset and ATP7B variants, which may provide some valuable insights into the diagnosis, counseling, and treatment of patients with WD. [ABSTRACT FROM AUTHOR]

Background: Wilson's disease (WD) is an autosomal recessive disorder of copper metabolism caused by ATP7B (encoding a copper-transporting P-type ATPase) variants that shows various characteristics according to race and geographical region. This study was aimed to provide a comprehensive analysis of ATP7B variants in China and to investigate a plausible role of common variants in WD manifestations. Methods: A total of 1366 patients (1302 index patients and 64 siblings) clinically diagnosed with WD (Leipzig score ≥ 4) were recruited. They underwent ATP7B gene sequencing and information of age and symptoms at onset was collected. The genotype–phenotype correlation was assessed in the index patients who were examined with two pathogenic variants and onset with hepatic (n = 276) or neurologic (n = 665) symptoms. Results: We identified 294 potentially pathogenic ATP7B variants (112 truncating, 174 missense, 8 in-frame) in the 1302 index patients, including 116 novel variants. The most frequent variant was c.2333G>T (R778L, allele frequency: 28.96%), followed by c.2975C>T (P992L, 13.82%), c.2621C>T (A874V, 5.99%), c.2755C>G (R919G, 2.46%), and c.3646G>A (V1216M, 1.92%). In 1167 patients, both pathogentic variants were identified, of which 532 different variant combinations were found. By binary logistic regression analysis, the factor associated with neurological presentation was high age-at-onset, but not sex, protein-truncating variant (PTV), or the common missense variants (R778L, P992L, and A874V). In the neurological group, low age-at-onset was a factor associated with dystonia, gait abnormality, and salivation; high age-at-onset was a factor associated with tremor; and the sex, low age-at-onset and A874V were independent factors associated with dysarthria. In addition, PTV, R778L, and P992L were predominant in early-onset patients, whereas A874V was predominant in late-onset patients, and patients with R778L/A874V genotype displayed a higher age-at-onset than patients with R778L/R778L or R778L/P992L genotype. Conclusions: Our work expanded the ATP7B variant spectrum and highlighted the differences among patients with WD in age-at-onset and ATP7B variants, which may provide some valuable insights into the diagnosis, counseling, and treatment of patients with WD. [ABSTRACT FROM AUTHOR]

A fluorescent probe based on the functionalized carbon quantum dots (CQDs-OPD) was successfully synthesized for selective and sensitive detection of Cu2+. Using O-phenylenediamine (OPD) as the carbon resource and N,N-dimethylformamide (DMF) as the solvent, the CQDs-OPD was prepared by the hydrothermal method. The fluorescence mechanism of CQDs-OPD was studied by the intercept method. Furthermore, the probe was characterized by TEM, UV–Vis, FT-IR and Zeta potentiometric analysis, the fluorescent probe exhibits a good fluorescence properties and stability. The prepared ratio-fluorescent probe shows a good linear range from 0 to 25 μmol/L with a lower LOD of 40 nmol/L. Moreover, the probe also has been successfully applied to the detection of Cu2+ in the real samples with the recovery rate of 96.92–97.80% and the RSD of less than 2.0%. [ABSTRACT FROM AUTHOR]

An innovative molecular imprinted polymer based on KH-570 modified SiO2-coated cadmium telluride quantum dots was prepared as fluorescence sensor for sulfadimidine (SM2) sensitive and selective detection. The quantum dots were firstly encapsulated in silica by sol–gel process, and then the double bond was modified on the surface of silica with KH-570. Finally, the molecular imprinted layer was synthesized on the surface of silica by template molecule, methacrylic acid (MAA) and ethylene glycol dimethyl acrylate. The fluorescence sensors showed good structure when characterized by SEM. Besides, the fluorescence sensors showed a good linear range from 10 to 80 μmol.L−1 with a lower LOD of 0.42 μmol.L−1. These sensors were successfully applied to detect SM2 in the water samples with a recovery rate from 91.6% to 97.8% and the relative standard deviation less than 2.5%, indicating that fluorescence sensors have the potential application in the detection of real samples. [ABSTRACT FROM AUTHOR]

An innovative kinetic mechanism reduction method, Species' Participation in Element Fluxes (SPEF), is developed in this study. It utilises species' participation in element fluxes to evaluate the importance of the species during the combustion process. The SPEF method has two main benefits: (1) it targets at C, H and O elements instead of pre-selected target species and has only one variable threshold on species importance, which makes it feasible to obtain satisfactory skeletal mechanisms for researchers even without any mechanism reduction expertise; (2) it shows significantly low time complexity, which helps to achieve high computational efficiency in the reduction process. Three mechanisms with different sizes were reduced and utilised to investigate the reduction capability of the SPEF method. It has been observed that the reduction performance of the SPEF method is competitive with other widely used directed relation graph with error propagation (DRGEP), path flux analysis (PFA) and global pathway selection (GPS) methods. The effectiveness of the SPEF method was further demonstrated by extensively validating the SPEF-reduced mechanisms against the detailed mechanisms. In addition to the application to static reduction, this method could also be easily utilised for dynamic reduction to save computational efforts in reactive flow simulation while retaining satisfactory accuracy. An example was given by integrating the SPEF method into the KIVA4 code package to dynamically reduce chemical mechanisms in 3-D engine simulations. It has been proved that even for 3-D engine simulations with a highly compact mechanism, computational cost can still be saved in a considerable scale using the SPEF method. [ABSTRACT FROM AUTHOR]

Femoral head necrosis (FHN) is a serious complication after femoral neck fractures (FNF), often linked to sclerosis around screw paths. Our study aimed to uncover the proteomic and metabolomic underpinnings of FHN and sclerosis using integrated proteomics and metabolomics analyses. We identified differentially expressed proteins (DEPs) and metabolites (DEMs) among three groups: patients with FNF (Group A), sclerosis (Group B), and FHN (Group C). Using the Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analyses, we examined the roles of these proteins and metabolites. Our findings highlight the significant differences across the groups, with 218 DEPs and 44 DEMs identified between the sclerosis and FNF groups, 247 DEPs and 31 DEMs between the FHN and sclerosis groups, and a stark 682 DEPs and 94 DEMs between the FHN and FNF groups. Activities related to carbonate dehydratase and hydrolase were similar in the FHN and sclerosis groups, whereas extracellular region and lysosome were prevalent in the FHN and FNF groups. Our study also emphasized the involvement of the PI3K-Akt pathway in sclerosis and FHN. Moreover, the key metabolic pathways were implicated in glycerophospholipid metabolism and retrograde endocannabinoid signaling. Using western blotting, we confirmed the pivotal role of specific genes/proteins such as ITGB5, TNXB, CA II, and CA III in sclerosis and acid phosphatase 5 and cathepsin K in FHN. This comprehensive analyses elucidates the molecular mechanisms behind sclerosis and FHN and suggests potential biomarkers and therapeutic targets, paving the way for improved treatment strategies. Further validation of the findings is necessary to strengthen the robustness and reliability of the results. [ABSTRACT FROM AUTHOR]

Data clustering is one of the most fundamental techniques in exploratory data analysis. It is widely used for determining the underlying data structure, classifying natural data and compressing data in engineering, business management, social statistics, computer science, and medicine. Under the assumption that clusters are high density regions in the feature space separated by relatively low density neighbors, a novel approach is proposed for modeling any high dimensional clustering problem as a one-dimensional analysis of the probability distribution. First, a special path between two vertexes, namely eigenpath, is defined in this paper to represent their close connection. Second, we propose the connectedness index based on the eigenpath for quantitatively describing the connection between two vertexes. Third, the connectedness index is applied to the candidates of cluster centers and measures the connection between different candidates. Then an indicative curve can be drawn with the knowledge of connectedness index. This approach not only provides effective indicative curve for unknown data sets but also facilitates eliminating the curse of dimensionality partly as well as correctly recognizes arbitrary cluster forms and automatically excludes outliers. Extensive experiments showed the effectiveness and efficiency of the proposed approach. [ABSTRACT FROM AUTHOR]

Raw point cloud (PC) data acquired by 3D sensors or reconstruction algorithms inevitably contain noise and outliers, which can seriously impact downstream tasks, such as surface reconstruction and target detection. To address this problem, this paper proposes an innovative denoising method including the adaptive feature extraction (AFE) module, the gradient field estimation (GFE) module, and the further accelerated gradient ascent (FAGA) module. The method is based on considering the noisy PC as a convolutional distribution of clean PC and noise, and denoising is achieved by updating the positions of the points through gradient ascent iterations. Specifically, for a given noisy PC as input, we first extract global features in the AFE module, which are used as conditions to dynamically guide the extraction of local and non-local features to achieve adaptive feature acquisition. Next, these adaptive features are used as input to the GFE module to estimate the gradient field of the PCs and combined with our proposed FAGA module for denoising operations. Extensive qualitative and quantitative experiments are conducted on synthetic and natural PC datasets, and the results show that the proposed method exhibits superior performance relative to previous state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The resected tumour specimen is loaded into the specimen bag, and an incision of approximately 4 cm is made in the middle of the upper abdomen to remove the specimen. We present herein Video S1 of total laparoscopic left hemicolectomy using a novel IA method of U-tied end-to-end anastomosis (UEEA). Several studies have demonstrated that intracorporeal anastomosis (IA) has a lower overall complication rate [[1]], shorter hospital stay and less postoperative pain than extracorporeal anastomosis in laparoscopic right hemicolectomy for colorectal cancer [[2]]. [Extracted from the article]

In this paper, we develop a concise but efficient network architecture called linear compressing based skip-connecting network (LCSCNet) for image super-resolution. Compared with two representative network architectures with skip connections, ResNet and DenseNet, a linear compressing layer is designed in LCSCNet for skip connection, which connects former feature maps and distinguishes them from newly-explored feature maps. In this way, the proposed LCSCNet enjoys the merits of the distinguish feature treatment of DenseNet and the parameter-economic form of ResNet. Moreover, to better exploit hierarchical information from both low and high levels of various receptive fields in deep models, inspired by gate units in LSTM, we also propose an adaptive element-wise fusion strategy with multi-supervised training. Experimental results in comparison with state-of-the-art algorithms validate the effectiveness of LCSCNet. [ABSTRACT FROM AUTHOR]

We analyze the magnetization relaxation effects of a ferrofluid film flow governed by the ferrohydrodynamics encompassing the Fokker–Planck magnetization equation in a Couette–Poiseuille configuration subject to an applied uniform stationary magnetic field perpendicular to the boundaries. A solver based on OpenFOAM is programmed to find solutions numerically for the velocity, spin velocity, and magnetization in ferrofluid films under the combined pressure gradient, boundary flow, and magnetic field forcing. The solver is validated by comparison with the classical Couette–Poiseuille flows and the analytic solutions of the magnetization relaxation problem when the product of flow vorticity and relaxation time is much smaller than unit, Ω τ B ≪ 1. We compare the effects of magnetization relaxation obtained from the phenomenological magnetization equation with those from the equation derived microscopically. The results obtained from the former equation are not suitable for the description of ferrofluid film flows. Due to the magnetization relaxation effects, a misalignment between the local magnetization and the local magnetic field is observed. The net effects are that the flow is hampered by magnetic fields and it manifests as diminished slopes of vorticity profiles and reduced volumetric flow rates. The magnetization relaxation effects also slow down the spin velocity of particles or change their direction, which leads to an enhanced effective viscosity. The total tangential stress exerted on the moving boundary is higher than that of the classical Couette–Poiseuille flow owing to the addition of a magnetic stress. The magnetization relaxation effect is more significant in cases of ferrofluids with higher relaxation times. [ABSTRACT FROM AUTHOR]

Modelling internal combustion engines (ICEs) with multidimensional computational fluid dynamics (CFD) is challenging due to the fuel spray, combustion chemistry and moving piston involved. To accurately simulate ICEs as well as to maintain acceptable computational cost, dynamic mesh refinement techniques could be applied. Although modelling ICEs with staggered mesh is ubiquitous in the engine combustion community, the dynamic refinement of staggered mesh in the context of multidimensional engine simulations is not reported in the literatures due to the numerical difficulties in the momentum solution at the gird fine-coarse interface and to deal with moving boundaries. To address these difficulties, we propose a dynamic refinement scheme to cell-by-cell refine the staggered mesh on-the-fly based on the fuel evaporation and thermochemical state in the multidimensional dynamic staggered mesh and it is able to handle the complexity caused by the moving boundaries in engine simulations and momentum solution at the fine-coarse interface in the dynamic mesh. This mesh refinement scheme is then implemented in the widely-used ICEs simulation codes for engine simulations with fuel sprays. A wide variety of computational examples including shock wave, compression, constant volume fuel spray, constant volume fuel spray combustion are first employed to test the scheme and finally, compression ignition combustion engine simulations are conducted with the proposed methodology. [ABSTRACT FROM AUTHOR]

Objectives: The current clinical pulse lavage technique for flushing fresh osteochondral allografts (OCAs) to remove immunogenic elements from the subchondral bone is ineffective. This study aimed to identify the optimal method for removing immunogenic elements from OCAs. Methods: We examined five methods for the physical removal of immunogenic elements from OCAs from the femoral condyle of porcine knees. We distributed the OCAs randomly into the following seven groups: (1) control, (2) saline, (3) ultrasound, (4) vortex vibration (VV), (5) low‐pulse lavage (LPL), (6) high‐pulse lavage (HPL), and (7) high‐speed centrifugation (HSC). OCAs were evaluated using weight measurement, micro‐computed tomography (micro‐CT), macroscopic and histological evaluation, DNA quantification, and chondrocyte activity testing. Additionally, the subchondral bone was zoned to assess the bone marrow and nucleated cell contents. One‐way ANOVA and paired two‐tailed Student's t‐test are used for statistical analysis. Results: Histological evaluation and DNA quantification showed no significant reduction in marrow elements compared to the control group after the OCAs were treated with saline, ultrasound, or VV treatments; however, there was a significant reduction in marrow elements after LPL, HPL, and HSC treatments. Furthermore, HSC more effectively reduced the marrow elements of OCAs in the middle and deep zones compared with LPL (p < 0.0001) and HPL (p < 0.0001). Macroscopic evaluation revealed a significant reduction in blood, lipid, and marrow elements in the subchondral bone after HSC. Micro‐CT, histological analyses, and chondrocyte viability results showed that HSC did not damage the subchondral bone and cartilage; however, LPL and HPL may damage the subchondral bone. Conclusion: HSC may play an important role in decreasing immunogenicity and therefore potentially increasing the success of OCA transplantation. [ABSTRACT FROM AUTHOR]

Highlights • A four-part scheme to formulate skeletal mechanism for heavy saturated methyl esters was proposed. • A skeletal mechanism for methyl palmitate and methyl stearate was successfully constructed. • Good agreement between the skeletal mechanism and experimental data was observed. Abstract Methyl decanoate, methyl-5-decenoate and methyl-9-decenoate have been widely adopted as biodiesel surrogates for engine simulation. However, these surrogates have relatively short chain length and very different physical properties compared with biodiesel molecules. Additionally, it is difficult to distinguish the unsaturation degree of different biodiesel fuels by using these surrogates. The direct use of the heavy methyl esters in real biodiesel fuels as surrogates is essential to accurately simulate biodiesel fuels. In this work, a four-part scheme to formulate skeletal mechanism for heavy saturated methyl esters has been proposed. Within the scheme, the oxidation mechanism is divided into four parts: low temperature oxidation, high temperature decomposition, ester group reactions and detailed C4-C0 chemistry. A skeletal mechanism for two of the five main methyl esters in real biodiesel fuels, i.e. saturated methyl palmitate and methyl stearate, has been constructed. The obtained skeletal mechanism contains only 6 fuel-dependent species and 13 fuel-dependent reactions for each heavy saturated methyl ester. Extensive validations were performed against shock tube experimental data for ignition delay timing under different initial pressure, temperature and equivalence ratio. The ignition delay behavior at high temperature has been well captured by the developed skeletal mechanism. As for ignition at low to medium temperature (from 650 K to 900 K), there is no experimental data due to the low vapor pressure and high melting point of heavy methyl esters. The comparison of ignition behavior at low temperature has been made between several models. Furthermore, the oxidation of n-decane/methyl palmitate and benzene/methyl stearate in a jet-stirred reactor has been utilized to validate the important species concentration. Good agreements have been observed through the validations. The results indicate that the developed skeletal mechanism is capable of predicting the combustion characteristics of methyl palmitate and methyl stearate. [ABSTRACT FROM AUTHOR]

Highlights • Develop a new finger identification system to synchronously capture a two-modal image of dorsal finger vein and texture by a single camera. • Establish a corresponding two-modal hybrid images database of 210 finger samples. • Present a feature extraction method named by "Polarized depth-Weighted Binary Direction Coding", which explores features of two modalities simultaneously. Abstract Finger identification is increasingly popular in recent years. In this paper, we propose a new finger identification system to acquire a hybrid pattern of dorsal finger vein and texture in a single image by using only one camera. It effectively reduces the cost and volume of the imaging device to acquire multi-modal patterns. The hybrid pattern of dorsal finger vein and texture is both storage-saving and calculation-saving. As there was no existing method specially developed for this kind of pattern, we propose a new feature extraction method called "Polarized depth-Weighted Binary Direction Coding" (PWBDC). We also establish a new database of such hybrid images of 210 finger samples. Experimental results demonstrate that the proposed system and feature are not only storage and calculation saving, but more importantly effective for identification. The proposed PWBDC method performs well on both the newly established database of hybrid images and a popular public database of traditional finger vein images, superior to many established and state-of-the-art methods. [ABSTRACT FROM AUTHOR]

No-reference image quality assessment (NR-IQA) is developing rapidly, but there lacks of research on exploring robust statistics to improve the prediction accuracy and monotonicity of NR-IQA algorithms, in particular for assessing photographic images captured by different digital cameras where a variety of unknown distortions may happen. Hence this paper proposes a novel robust-statistics-based NR-IQA method (termed RSN) for photographic images. In RSN, we present three types of features based on robust statistics: robust natural scene statistics of multiple components, robust multi-order derivatives, and robust complementary features in the frequency domain. Then support vector regression is applied to predict image quality using the extracted features. Experimental results show that RSN remarkably outperforms state-of-the-art NR-IQA methods on the CID2013 database of photographic images, as well as on the popular LIVE and TID2013 databases. [ABSTRACT FROM AUTHOR]

Highlights • A hybrid model based on the classical CTC model and CHEMKIN model was proposed. • The proposed hybrid model is able to model RCCI combustion with detailed chemistry. • The hybrid model is robust and efficient for RCCI combustion simulations. Abstract This study proposed a hybrid model consisting of a characteristic time combustion (CTC) model and a closed reactor model for the combustion modelling with detailed chemistry in RCCI engines. In the light of the basic idea of the CTC model of achieving chemical equilibrium in high temperature, this hybrid model uses the CTC model to solve the species conversion and heat release in the diffusion flame. Except for the diffusion flame, the auto-ignition in RCCI combustion is computed by a closed reactor model with the CHEMKIN library by assuming that the computational cells are closed reactors. The border of the transition between the CTC model and closed reactor model is determined by two criteria, a critical temperature and a critical Damköhler number. On the formulation of this hybrid model, emphasis is placed on coupling detailed chemistry into this hybrid model. A CEQ solver for species equilibrium calculations at certain temperature, pressure was embedded with CTC for detailed chemistry calculation. Then this combustion model was integrated with the CFD framework KIVA4 and the chemical library CHEMKIN-II and validated in a RCCI engine. The predicted in-cylinder pressure and heat release rate (HRR) show a good consistency with the data from the experiment and better accuracy than that computed from the sole closed reactor model. More importantly, it is observed that this model could save computational time compared with closed reactor model due to less stiff ordinary differential equations (ODEs) computation. A sensitivity analysis of the critical temperature and critical Damköhler number was conducted to demonstrate the effect of these two parameters in the current model. [ABSTRACT FROM AUTHOR]

It is necessary to recognize the spatial distribution of ion density and temperature in some practical applications. While numerical modeling is a useful method to fulfill this task, a self-consistent numerical model based on the first few moments of the Boltzmann transport equation coupled to Poisson’s equation was built using COMSOL Multiphysics to simulate the dc discharge of a needle-to-plane geometry in atmospheric pressure. Simulation of the discharge was carried out for an actual geometry in aerosol sensors when only the main compositions of air and the main collisional populating and depopulating processes were considered. The simulation results demonstrated that the space occupied by the positive ions with a density of sufficiently charging aerosol particles was very limited. In the meanwhile, the electron temperature in the vicinity of the entire plane electrode was higher than the melting point of most metals. Experiments of measuring the current inducted by charged particles with a diameter of 95 nm using devices with narrowed channels showed that the specific current increased to nearly five times when the width of the channel in the charging stage decreases from 5 to 2 mm. Furthermore, the ablation of the plane electrode used in the experiments occurred on almost the entire surface, which was agreed with the prediction by simulation. [ABSTRACT FROM AUTHOR]

Two jet fuel surrogates (S1 and S2) were proposed in this work, aimed at improving the quantitative accuracy of fuel properties that affect both premixed and spray-guided combustion modes under engine relevant conditions by emulating real jet fuel properties including physical, gas phase chemical properties and threshold sooting index (TSI). An intelligent optimization approach was employed to calculate the composition that inherently satisfies both the physical and gas phase chemical characteristics as well as sooting tendency. The jet fuel surrogate S1 was composed of five components including decalin, n-dodecane, iso-cetane, iso-octane and toluene (0.005/0.4011/0.1249/0.098/0.371 by mole fraction), while surrogate S2 is a mixture of the same components but different in proportions (0.1449/0.3706/0.2059/0.0195/0.2591 by mole fraction). Based on the newly proposed surrogates, a skeletal jet fuel surrogate chemical reaction mechanism was developed by describing the chemistries for the oxidation of large molecules C 4 C n and smaller H 2 /CO/C 1 molecules respectively. The skeletal jet fuel surrogate mechanism was significantly compacted into 74 species and 189 reactions, making it practical to be used in 3-dimensional (3-D) engine combustion simulations. This newly developed mechanism was verified against the experimental results of ignition delay times, species concentrations and laminar flame speed under a wide range of conditions, while 3-D validations were conducted for spray liquid and vapor penetrations in a constant volume chamber. As a result, the proposed fuel surrogate is capable of predicting the spray and combustion characteristics and main species profiles under engine relevant circumstance. Due to the stringent target properties used in this work, the surrogate S1 performed best in assessing ignition characteristics attributed to its elaborate chemical properties, making it the most suitable candidate for chemical dominated combustion like premixed engine combustion. Alternatively, S2 displayed outstanding spray-guided combustion behavior because of the stringent chemical and physical target properties assigned. It is worthwhile to note that this new method of formulating surrogates for different applications was efficient and time-saving. Finally, we aim to perform experimental validation tests for CN, density, viscosity, surface tension, TSI, sooting tendency and particle size distribution to further support the validity of the current proposed jet fuel surrogates (S1 and S2) in the future. [ABSTRACT FROM AUTHOR]

Dibutyl phthalate (DBP), as a plasticizer, has been widely used in the manufacture of plastic products. However, it is generally acknowledged that DBP is an endocrine disruptor, which would cause harm to both humans and wildlife. Generally, trace DBP in river water, soil or food is hard to be detected accurately. To solve this case, a core-shell hollow structured molecularly imprinting polymer, PH-MIPs, was synthesised via surface imprinting technology. It is noteworthy that the prepared PH-MIPs can specifically absorb and release DBP irradiated by different wavelengths of light. More importantly, the absorption capacity of PH-MIPs reaches up to 5.2 mg·g−1 without obvious attenuation in absorption performance after 4 loops of photo-controlled uptake and release of DBP. Furthermore, the PH-MIPs exhibit excellent selective absorption properties, supported by an imprinting factor of 3.4. Finally, the prepared PH-MIPs were applied to enrich and extract DBP in river water samples with the recovery rate of 83.2%. In general, the proposed PH-MIPs exhibit excellent practicability, which offers a method for the content determination of DBP as a high-efficiency solid-phase extractant for the enrichment and extraction of target pollutants. [Display omitted] • A functional photoresponsive monomer, MAPASA, was synthesised, the conformation of which can change under the light of 365 nm and 440 nm (or darkness). • Hollow-structured PH-MIPs synthesised on the surface of SiO 2 carriers with MAPASA provide assurance of photoresponsive selectivity adsorption and release of dibutyl phthalate (DBP). • To establish a photo-controllable extraction and enrichment method for determining the content of DBP. [ABSTRACT FROM AUTHOR]

In this study, numerical analysis of fuel structures on engine soot particles’ mass and size were done by CFD combustion modelling using diesel and different levels of unsaturated biodiesel fuels through the KIVA4-CHEMKIN platform. The proposed numerical approach, with a quad-component skeletal mechanism of biodiesel blend surrogates along with a multi-step phenomenological soot particle model, could capture the soot particle characteristics of test fuels with acceptable accuracy under engine combustion conditions. The reduction of exhaust soot from biodiesel combustion, compared to diesel fuel, was attributed to the suppressed soot precursors formation and lower number of particles in total. However, it was concluded that the biodiesel fuel with a higher fraction of unsaturated FAMEs (more double carbon bonds C C) contributed more to the formation of soot precursors, thus producing a higher amount of soot particles in mass and numbers as a consequence of accelerated soot particle nucleation and soot surface growth. [ABSTRACT FROM AUTHOR]

The concept of heterogeneous multiscale method (HMM) is applied into combustion chemistry integration in reactive flows in this study. It adopts a macro solver to integrate the slow variables with global time steps and a micro solver to integrate the fast variables with smaller inner time steps. Explicit or implicit schemes with different orders of accuracy could be applied in the macro and micro solvers. In this study, we formulated HMM with a first-order Euler forward scheme in the micro solver and a second-order trapezoidal rule in the macro solver. An adaptive time step method was proposed to better evaluate a proper time step and control the error in this HMM. This formulation of HMM with the adaptive time step method has been implemented and tested in homogeneous constant volume auto-ignition in hydrogen, methane and butane mixture under various initial temperatures, pressures and equivalence ratios. The speed-up factor of 100–700 has been achieved compared with the implicit solver DASAC. In addition, the numerical accuracy and stability of this HMM formulation have been discussed. It was also applied into multi-dimensional Reynolds-averaged Navier–Stokes (RANS) engine simulations and good efficiency and accuracy was accomplished. In order to better optimize its efficiency performance in multi-dimensional reactive flow simulations, a hybrid scheme with VODE and HMM was proposed and tested in non-homogeneous charged engine simulations. In sum, the concept of HMM in stiff combustion chemistry integration is numerically stable, accurate and efficient. [ABSTRACT FROM AUTHOR]

Being one typical cyclo-alkane class component of commercial jet and diesel fuels, decalin has two fused six-membered rings and so far few studies of decalin were accessible to its oxidation mechanism. So that this study aims to propose a skeletal mechanism of decalin oxidation that facilitates the formulating of surrogate fuels applicable in power device like engines. In this study, a skeletal mechanism of decalin oxidation was developed based on the decoupling methodology. It contains 42 species and 163 reactions, in which a simplified mechanism for the oxidation of C 2 –C 10 is used to model the oxidation of heavy hydrocarbons for the prediction of the ignition characteristics, while the mechanism of H 2 /CO/C 1 was considered in details for the prediction of intermediate species concentrations. Among all intermediate combustion products, C 2 H 2 is designated as the most important soot precursor and will be used to predict soot tendency in the future study. The present skeletal mechanism was extensively validated against available fundamental experiments in regard of decalin oxidation under engine relevant conditions, wherein the temperature and pressure were relatively high. The computational results indicated that the predicted ignition delay in shock tubes and species concentrations in jet stirred reactors as well as in laminar premixed flames agree reasonably well with the measurements. [ABSTRACT FROM AUTHOR]

As the world faces energy shortages, it is highly desirable to look for alternative fuels that are sustainable and renewable. Ammonia is one such candidate. In this numerical study, ammonia is applied to a diesel engine via fumigation and a pilot fuel is used to ignite the premixed ammonia. Numerical simulations are carried out using the KIVA4-CHEMKIN code in order to better understand the effects of ammonia combustion on engine performance and emissions. It is seen from this study that ammonia reduces carbon monoxide and carbon dioxide emissions as it replaces the carbon-based pilot fuels. Moreover, nitrogen oxide emissions decrease with little ammonia fumigation and increase with high ammonia fumigation. This is due to combustion temperature, ammonia quantity and ammonia-air kinetics. Furthermore, it is interesting to note that as the injection timing is advanced, primary as well as secondary heat-release peaks are observed. The secondary heat-release peak is due to the combustion of residual fuel near the cylinder liner as well as in the crevice region and this is caused by an increase in in-cylinder temperature as injection timing advances. [ABSTRACT FROM AUTHOR]

In the two limits of a well-mixed charge (e.g. homogenous charge compression ignition (HCCI)) engine, and a well separated charge (e.g. conventional diesel combustion (CDC)) engine, the CHEMKIN coupled computational fluid dynamics (CFD) codes approach has been proved to work well in predicting both chemistry controlled combustion and mixing controlled combustion. In this study, it is shown that for some certain cases in the new combustion mode reactivity controlled compression ignition (RCCI) engine where flame propagation exists, the CHEMKIN approach could fail to predict the combustion characteristics. To extend the capability of the existing CHEMKIN models in combustion, a flame propagation model (FPM) accounting for combustion in partially premixed mixtures was proposed and coupled into the CFD framework KIVA4. In this FPM model, the turbulent flame speed was calculated and the heat release and species conversion rate in the turbulent flame brush was solved with detailed chemical kinetics. A NOx sub-mechanism and a nine-step phenomenological soot model were also coupled into the current integrated model for emission prediction. This model was validated in 3 different dual-fuel experimental engines by comparing the in-cylinder pressure, heat release rate (HRR), NOx emissions and soot emissions. The CHEMKIN and CHEMKIN-FPM were also compared in terms of their capability of predicting the combustion in different combustion regimes. The results show that under certain operating conditions when CHEMKIN failed in the combustion prediction, the current CHEMKIN-FPM shows a superior ability in predicting combustion characteristics. [ABSTRACT FROM AUTHOR]

In this work, the effects of boot injection rate-shapes on the combustion process and emissions formation of a direct injection compression ignition engine fueled with kerosene and diesel are investigated through numerical simulations. Boot injection rate-shapes with varying boot injection velocity and boot injection duration are used. The KIVA4-CHEMKIN code is used in conjunction with a phenomenological soot model and an improved kerosene-diesel reaction mechanism to study the combustion process and emissions formation. The phenomenological soot model consists of a number of sub-models from literature that accounts for soot particle inception, soot coagulation, soot surface growth via the hydrogen-abstraction-carbon-addition (HACA) mechanism and soot surface oxidation by oxygen (O 2 ) and hydroxyl radical (OH). It should be noted that the improved kerosene-diesel reaction mechanism is robust enough to predict the combustion and emissions trends of kerosene with respect to diesel. From this study, boot injection rate-shapes are seen to cause combustion phasing and cause lower nitrogen oxide (NO) emissions in general. Furthermore, it is observed that when kerosene replaces diesel, engine efficiency and NO emissions increase while carbon monoxide (CO) and soot emissions decrease. Soot mass quantity, soot particle number and soot particle size are the lowest for pure kerosene combustion. Finally, detailed analyses of the effects of boot injection rate-shapes on soot particle dynamics are also presented. [ABSTRACT FROM AUTHOR]

In this paper, we present a new learning-based single-image super-resolution (SR) approach, inspired by existing sparse representation-based methods. As a promising image modeling theory, sparse representation has been effectively applied to solve the image SR problem, usually with the use of pretrained coupled or semi-coupled dictionaries. In our proposed method, we train independent dictionaries for high-resolution (HR) and low-resolution (LR) image patches to endow them more flexibility of expression. We use local subdictionaries to adaptively code image patches, which can characterize image local structures better and ensure the sparsity property of the image. Furthermore, we use kernel regression to relate HR and LR coding coefficients to capture and map the intrinsic nonlinear relationship between them. Such mapping is of central importance in the image SR problem, because high-order statistics play a significant role in the reconstruction of the detail structure of an HR image. The proposed model is generic for image SR in terms of two categories of blurring kernel. Experimental results show that our method can effectively reconstruct image details and outperform state-of-the-art algorithms in both quantitative and visual comparisons. [ABSTRACT FROM AUTHOR]

While recently published face alignment algorithms mainly focused on occlusion, low image quality, and complex head poses, subtle variances of facial components were often overlooked. In this correspondence paper, we propose a new approach called cascaded elastically progressive model aiming for pixel-wise landmark localization. First of all, elastically progressive model (EPM) is designed to synthesize the prior knowledge of face shape and appearance of test image. More specifically, a novel framework referred to as inherent linear structure (ILS) is explored for capturing the characteristics of the shape, which is more plastic and flexible than extensively used principle component analysis-based modeling. A locally linear support vector machine (LL-SVM) is used as local expert for searching candidate feature points. In order to optimally integrate ILS with localization results of LL-SVM, we introduce Kalman filter (KF) to dynamically estimate the true shape in the sense of least mean square error. Two schemes are utilized based on our modeling of KF. First, we embedded heuristic line-like search strategy into the framework to guarantee and accelerate the convergence. Second, Kalman gain is manipulated adaptively in accordance with the confidence of the localizers so that poorly localized points are more subject to global constraint than well localized ones. To further improve robustness to initializations, two EPMs are cascaded, in which primary EPM detects the global structure and secondary EPM captures the details. Validation experiments are conducted on in-the-wild LFPW and HELEN databases. Our method shows advantages for accurate landmark localization compared with prevailing methods. [ABSTRACT FROM AUTHOR]

The levitation phenomenon of permanent magnets immersed in ferrofluid is the foundation of ferrofluid dampers. According to the model built using bipolar coordinates, the analytical equation describing the force exerted on the cylindrical magnets in ferrofluid dampers is obtained, which is different from that of the previous results. The analysis of the equation indicates that the magnetic levitation force increases with the eccentricity of the magnet, the radius of the magnet and the permeability of ferrofluid, respectively, when other factors are definite. As a result, we can increase the permeability of ferrofluid and decrease the radius ratio of the magnet and the tube to enhance the levitation stability. [ABSTRACT FROM AUTHOR]

• A new finite volume method is developed for ferrohydrodynamic problems. • The model involving the microscopic magnetization equation is employed and solved. • Iteratively uncoupled strategy is adopted to treat global coupled ferrohydrodynamics. • The method takes into account non-orthogonal surface vectors for unstructured grids. A finite volume method is developed for the ferrohydrodynamics (FHD) dealing with the mechanics of fluid motion influenced by strong forces of magnetic polarization. The Shliomis model consisting of the continuity equation, the momentum equation, the angular momentum equation, the magnetization equations, and the Poisson's equation of magnetostatics is adopted to describe the FHD problems, where the hydrodynamics are strongly coupled with the magnetization dynamics. Unlike most of the previous FHD simulations, where the Debye-like magnetization equation was frequently used, we employ the microscopically derived magnetization equation to describe the evolution of ferrofluid magnetization in order to be valid in a wide range of flow rates, magnetic field strengths and oscillating frequencies. In the proposed method, each governing equation is discretized by employing the finite-volume scheme, and the variables in FHD, including the magnetic field, velocity, pressure, and magnetization are uncoupled by using an iteratively uncoupled strategy. The magnetization field is obtained by iteratively solving a Langevin equation using Newton method and the microscopical magnetization equation employing finite volume method in an inner iterative loop. Comparisons of the results obtained by the proposed method with the corresponding analytic or asymptotic solutions for the Couette–Poiseuille flows of ferrofluids in the absence or subjected to magnetic fields validate its feasibility in solving the pure hydrodynamics, pure magnetization dynamics, and the general FHD problems with hydrodynamic-magnetic coupling effects. [ABSTRACT FROM AUTHOR]

Nevertheless, restoration of bowel continuity is not only the patients' desire for an improved quality of life but a major goal for colorectal surgeons. The American Society of Colon and Rectal Surgeons Clinical Practice Guidelines for the Treatment of Left-Sided Colonic Diverticulitis. I Dear Editor i , Hartmann's procedure (HP) remains a common treatment approach for patients with Hinchey III-IV left-side colon diverticulitis [1, 2]. [Extracted from the article]

ABSTRACT New ionic liquid-mediated molecularly imprinted polymers (ILMIPs) for phthalate esters were developed in this study by the situ thermal polymerization method using methacrylic acid as a functional monomer and dibutyl phthalate (DBP) as a template. The polymer was characterized by scanning electron microscopy and Fourier transform infrared spectrometry. Batch static binding adsorption experiments were carried out to analyze its adsorption performance. The selectivity and adsorption of molecularly imprinted polymers were improved by the ionic liquids 1-butyl-3-methylimidazolium hexafluorophosphate as an excellent auxiliary porogen and solvent. The adsorption process conformed to pseudo-first-order model by kinetics analysis and Sips model by isotherm analysis. Using the prepared ILMIPs as a solid-phase extraction (SPE) sorbent, which indicated that ILMIPs-SPE had a higher enrichment efficiency and a better selectivity for DBP, and the average recoveries of DBP at four spiked levels were in a range of 96.4-101.3% ( n = 5) with relative standard deviation (RSD) ≤6.9%. [ABSTRACT FROM AUTHOR]

ABSTRACT Magnetic molecularly imprinted polymers (MMIPs) were synthesized for selective recognition and rapid enrichment of indole from a model fuel. The MMIPs were synthesized by precipitation polymerization and a surface molecular imprinting technique, using indole as the template molecule, Fe3O4 nanoparticles as magnetically susceptible components, methylacrylic acid as the functional monomer, and ethylene glycol dimethacrylate as a cross-linker. The properties of the MMIPs were characterized by Fourier-transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, vibrating sample magnetometry, and thermogravimetric analysis. The adsorption capacity of indole-molecularly imprinted polymers (MIPs) was 50.25 mg g−1 at 303 K and reached adsorption equilibrium in a short time. Experimental data were modeled with a pseudo-second-order, Langmuir isotherm model. The selective adsorption performance of MIPs was favorable. [ABSTRACT FROM AUTHOR]

Refractory materials based frequency selective emission/absorption is extremely encouraging for various applications, especially the combustion based thermophotovoltaics (TPV) and solar-TPV systems. The frequency selective emitters/absorbers also face the challenges of robust operation at elevated temperatures. Here, we report titanium nitride based thermal stable emitters/absorbers with good selectivity in the near infrared wavelength range. The titanium nitride nanocavitity array provides high emissivity/absorptivity at the desired short wavelength range but suppressed emissivity/absorptivity at the long wavelength range, and this design could be used to obtain high power density of the TPV system. The cut-off wavelength could be adjusted by encapsulating the cavities with different dielectrics. Meanwhile, the encapsulating layer protects the nanocavity structure from deformation at high temperatures. The thermal stability at 1073 K and 1273 K for two hours in Argon was demonstrated for the encapsulated nanocavity structure. [ABSTRACT FROM AUTHOR]

Soot and NO emissions are considered as major pollutants to the atmosphere from compression ignition engines. Researchers have been dedicated to the reduction of soot and NO emissions. Thus, an advance combustion regime, i.e. reactivity controlled compression ignition (RCCI), was proposed to mitigate the formation of these emissions. In this study, the dynamic ϕ-T (equivalence ratio vs. temperature) map analysis was applied to visualise the combustion processes associated with the in-cylinder temperature and equivalence ratio in an RCCI engine. Therefore, the soot and NO emissions can be efficiently reduced by controlling the combustion process out of the emissions islands on the ϕ-T map. This analysis method employs KIVA4-CHEMKIN and SENKIN code to construct ϕ-T maps under various conditions. To find out the significant parameters of controlling combustion process and emissions formation, four parameters were taken into consideration in a natural gas (NG) and diesel fuelled RCCI engine: NG percentage, the first start of injection (SOI) timing, split fraction of diesel and exhaust gas recirculation (EGR) rate. Each parameter was varied at three levels. Finally, the ϕ-T maps and final soot and NO emissions were compared among varied conditions for each parameter. It is found that the increased NG percentage can significantly reduce soot because of the absence of C-C bond in NG and the reduced diesel fuel impingement on the surface of the piston or cylinder wall. Increasing EGR can decrease the peak combustion temperature due to the dilution effect and thermal effect, consequently maintaining RCCI at low temperature combustion region. This study also indicates that dynamic ϕ-T map analysis is efficient at manipulating the combustion process to mitigate the soot and NO emissions formation. [ABSTRACT FROM PUBLISHER]

Analytical and numerical calculation methods of the radial magnetic levitation force on the cylindrical magnets in cylindrical vessels filled with ferrofluid was reviewed. An experimental apparatus to measure this force was designed and tailored, which could measure the forces in a range of 0–2.0 N with an accuracy of 0.001 N. After calibrated, this apparatus was used to study the radial magnetic levitation force experimentally. The results showed that the numerical method overestimates this force, while the analytical ones underestimate it. The maximum deviation between the numerical results and the experimental ones was 18.5%, while that between the experimental results with the analytical ones attained 68.5%. The latter deviation narrowed with the lengthening of the magnets. With the aids of the experimental verification of the radial magnetic levitation force, the effect of eccentric distance of magnets on the viscous energy dissipation in ferrofluid dampers could be assessed. It was shown that ignorance of the eccentricity of magnets during the estimation could overestimate the viscous dissipation in ferrofluid dampers. [ABSTRACT FROM AUTHOR]

In this work, the combustion characteristics of a direct injection compression ignition (DICI) engine fueled with kerosene-diesel blends, using different piston bowl geometries together with varying injection rate-shapes were investigated. A total of three combustion bowl geometries, namely the omega combustion chamber (OCC), the shallow-depth combustion chamber (SCC) and the shallow-depth re-entrant combustion chamber (SRCC), were used together with six different ramp injection rate-shapes and pure diesel, kerosene-diesel and pure kerosene fuels. It is seen that the SRCC geometry, which has the shortest throat length, gives the highest turbulence kinetic energy (TKE) and this resulted in two peak heat-releases, with a primary peak heat-release during the premixed combustion phase and a secondary peak heat-release during the mixing-controlled combustion phase. In addition, the SCC geometry gives rather distinct premixed combustion and mixing-controlled combustion phases due to the fact that combustion is predominantly controlled by the injected fuel spray itself because of less turbulence. Also, when kerosene is used in place of diesel, the heat-release during the premixed combustion phase increases and diminishes during the mixing-controlled and late combustion phases. It is interesting to note that the effect of injection rate-shaping on the heat-release rate is more obvious for bowl geometries that generate less TKE. Moreover, bowl geometries that generate higher TKEs as well as fuels with lower viscosities generally give lower carbon monoxide (CO) emissions and higher nitrogen oxide (NO) emissions. More importantly, it is possible to achieve low NO and CO emissions simultaneously by using the appropriate bowl geometry, injection rate-shape and fuel, although a slight decrease in power is inevitable. [ABSTRACT FROM AUTHOR]

RCCI (reactivity controlled compression ignition) engines are found to be capable of achieving higher thermal efficiency and ultra-low NOx and PM emissions. The reactivity controlled combustion is accomplished by creating reactivity stratification in the cylinder with the use of two fuels characterized by distinctly different cetane numbers. The low reactivity (i.e., low cetane number) fuel is firstly premixed with air and then charged into the cylinder through the intake manifold; later, the high reactivity (i.e., high cetane number) fuel is injected into the charged mixture through a direct injector. Subsequently, the reactivity stratification is formed. By strategically adjusting the ratio of two fuels and injection timings, the produced reactivity gradient is able to control the combustion phasing and mitigate the pressure rise rate, as well as the heat release rate. Alternatively, structural factors such as CR (compression ratio) and piston bowl geometries can also affect the combustion characteristics of RCCI. Besides the engine management, the fuels that could be utilized in RCCI engines are also crucial to determine the evaporation, mixing, and combustion processes. To gain a comprehensive knowledge on the state-of-the-art of RCCI combustion, detailed review on the management of RCCI engines has been presented in this paper. This review covers the up-to-date research progress of RCCI including the use of alternative fuels and cetane number improvers, and the effects of fuel ratio, different injection strategies, EGR rate, CR and bowl geometry on engine performance and emissions formation. Moreover, the controllability issues are addressed in this article. [ABSTRACT FROM AUTHOR]

Modelling soot formation and oxidation in diesel engines has been a long-standing challenge. In this study, soot particle characteristics in terms of particle dynamics, particle size and number density were modelled by integrating a multi-step phenomenological soot model into the KIVA-CHEMKIN CFD code for compression ignition engine combustion simulations. This semi-detailed soot model is dedicated to solving rate equations using sub-models to account for precursor formation, soot particle inception and coagulation as well as soot surface growth and oxidation. Soot growth and oxidation is inherently derived from the concentration of certain species found in the chemical reaction mechanism used, namely H, O 2 , C 2 H 2 and the nucleating polycyclic aromatic hydrocarbon (PAH). Acetylene is taken as the core precursor species in nucleating PAH, soot inception as well as acetylene-assisted soot surface growth. The integrated multi-step phenomenological soot model has been validated under gasoline and diesel dual-fuel engine conditions. The predicted histograms of soot particle number along with size distribution contribute towards the understanding of dominant factors that affect soot formation. The factors affecting soot particle under varying engine loads and fuel conditions were extensively investigated. Generally, the predicted soot particle size was larger for heavy-sooting conditions as compared to low-sooting conditions. For port-injected gasoline-dominated combustion, there is less soot being discharged. This might be attributed to two reasons. First, a more homogenous mixture is realized with less diesel fuel, thus effectively reducing the formation of soot precursors. The other reason is the intensive heat release which enhances the depletion of soot precursors, thereby impeding the growth of soot particles in terms of size and mass. [ABSTRACT FROM AUTHOR]

In this work, the spray characteristics of ether fuels such as dimethyl ether (DME) and diethyl ether (DEE) have been numerically investigated using KIVA-4 CFD code. A new hybrid spray model developed by coupling the standard KHRT model to cavitation sub model was used. The detailed thermo-physical properties of ether fuels have been predicted and validated with experimental results available from literature. The cavitation inception inside the injector nozzle hole has been studied for ether fuels in comparison with diesel fuel. It was found that ether fuels cavitates higher compared to that of conventional diesel fuel because of its low viscosity. The spray tip penetration of diesel fuel was longer than that of ether fuels due to high viscosity and density of diesel fuel. Ether fuels characterized by low Ohnesorge number and high Reynolds number showed better atomization behavior compared to that of the diesel fuel. [ABSTRACT FROM AUTHOR]

In this study, the performance of piezoelectric and solenoid injectors were compared. With a piezoelectric injector, the spray characteristics of kerosene and G50 (gasoline/diesel blend fuel), which are kinds of WDF, were investigated and compared to diesel. The characteristics such as spray penetration, spray velocity, spray angle and air entrainment were used to understand the spray behaviour of the test fuels. The results indicate that the piezoelectric injector shows significant improvement over the conventional solenoid injector in injection response and needle opening speed, which enables precise and rapid control of injection. The trade-off effects of charge density and injection pressure on spray penetration and spray velocity are quite clear, while spray angle is almost insensitive to injection pressure. Kerosene and G50 give smaller but similar spray penetration and velocity compared to diesel. The spray angle of kerosene and G50 are larger compared to diesel. The spray volume and mass of entrained air for kerosene and G50 are higher compared to diesel, which indicates kerosene and G50 can form better fuel–air mixing, which is very important for the performance of engine when fuelled by WDF. [ABSTRACT FROM AUTHOR]

A comprehensive simulation approach is important in order to better replicate the complex combustion process over a wide range of engine operating conditions. This will allow a more accurate understanding of crucial factors that affect engine combustion. In this study, the entire engine combustion process was systematically considered and a three-step hybrid simulation approach (THSA) was proposed in order to achieve a more accurate engine combustion simulation. For this approach, a so-called “full cavitation” model was selected for 3-dimensional (3D) internal nozzle flow study and a Kelvin-Helmholtz/Rayleigh-Taylor (KH-RT) model was used for 3D spray prediction wherein the flow variables at the nozzle outlet obtained through internal nozzle flow simulations were used as the input information in the KIVA4 code. Besides, a compact and accurate primary reference fuel (PRF) mechanism with 46 species and 144 reactions, which is coupled with a multi-step phenomenon soot model and energy balance analysis, was used for engine combustion simulation. Based on it, a numerical study was conducted for a comparison between conventional direct injection combustion (CDIC) and partially premix combustion (PPC) fueled with diesel, gasoline and diesel/gasoline blend fuel (GD). The final result indicates that with PPC and gasoline fuel, an optimized and high thermal efficiency of 52.5% can be realized along with extremely low NOx and soot emissions. [ABSTRACT FROM AUTHOR]