•The dependencies of mean reaction rate on the EDC constants are presented.•A CH4 MILD combustion furnace is successfully predicted with the EDC constant ratio of 4.•The EDC constant ratio of 2 is ...recommended for the CH4 conventional combustion.•Large differences of excess temperature are found for MILD and conventional combustions.•A criterion is suggested for the MILD combustion attainment.
The indisputable wide use of the Eddy Dissipation Concept (EDC) indicates that the mean reaction rate is reasonably modeled for MILD (Moderate or Intense Low-oxygen Dilution) and conventional combustions. However, RANS (Reynolds-Averaged Navier-Stokes) modelling with the standard EDC constants tends to over-predict maximum temperatures when applied to the MILD combustion regime. Therefore, there is a modification need of the EDC constants to predict properly the mean reaction rate, and then the maximum temperatures. The relation of the mean reaction rate and the EDC constants, including the primary and the secondary, is presented. A lab-scale methane MILD combustion furnace (MCF) with non-preheated air from literature is chosen for the validation of the EDC constants. The modification is done with one of the secondary EDC constants ranging from 1 to 28 where the primary constant is kept at CD1=0.1357. Predictions with the secondary EDC constant of 4 agree quite well with the measurements of the MILD combustion in this furnace. The modified EDC constant of 2 are suggested for the predictions of the conventional combustion in this furnace. Finally, based on the excess temperature or the normalized root mean square excess temperature (NRET), a criterion for the attainment of MILD combustion in this furnace is suggested.
Data-driven fault detection and root cause analysis methods become attractive in modern industrial production that can guarantee the safety and stability of process operation. If process monitoring ...technology is implemented for fault detection, and the root cause of faults is analyzed timely, it is beneficial to maintain and improve the quality of coming batches. In this paper, a framework of fault detection and root cause analysis is proposed to address the aforementioned issue, particularly for a batch process. First, a new algorithm, termed kernel entropy component analysis (KECA)–DISSIM that combines KECA and dissimilarity analysis (DISSIM), is proposed for the batch process monitoring purpose. The KECA can extract nonlinear characteristics of the batch process effectively based on nonlinear mapping with the Renyi quadratic entropy. Then, dissimilarity indices between normal reference datasets and testing datasets can be calculated. If the testing dataset is detected as the non-normal batch by KECA–DISSIM, a novel root cause analysis named comparative Granger causality analysis is introduced for root cause analysis. The testing dataset is decomposed into a series of data slices via the moving window along the time domain. A series of causality values for each pair of variables are obtained by performing Granger causality analysis on these time slices. Lastly, the case studies based on a typical seven-variable nonlinear numerical process and a benchmark fed-batch penicillin fermentation process are studied to illustrate the practicality and effectiveness of the proposed framework.
Metal halide perovskite solar cells (PSCs) have emerged as promising next‐generation photovoltaic devices with the maximum output efficiency exceeding 25%. Despite significant advances, there are ...many challenges to achieve high efficiency, stability, and low‐cost simultaneously. Combating these challenges depends on developing novel materials and modifying conventional device components. Carbon nanotubes (CNTs) have attracted considerable attention for fabricating efficient PSCs owing to their remarkable electrical, optical, and mechanical properties. With their multifunctional features, CNTs can play a wide range of roles and offer unique benefits in various components in PSCs to improve device performance and durability. Here, recent progress concerning the utilizations of CNTs as transparent conductive electrodes, charge‐transporter, perovskite additives, interlayers, hole‐transporting materials, and back electrodes in PSCs is comprehensively reviewed. The application of CNTs toward the development of 1D and 2D flexible PSCs is also discussed. A summary of current challenges and prospective on future research directions of employing CNTs to realize high‐performance PSCs is presented.
Recent progress concerning the uses of carbon nanotubes (CNTs) as transparent conductive electrodes, charge‐transporter, perovskite additives, interlayers, hole‐transporting materials, and back electrodes in perovskite solar cells (PSCs) is reviewed. The application of CNTs toward the development of 1D and 2D flexible PSCs is discussed. Current challenges and prospective on research directions of employing CNTs to realize high‐performance PSCs is presented.
Synthesis of structurally controlled graphene materials is critical for realizing their practical applications. The electrochemical exfoliation of graphite has emerged as a simple method to produce ...graphene materials. This review examines research progress in the last 5 years, from 2015 to 2019. Graphene material synthesis methods generally have a trade‐off between increasing production yield and achieving better material property control. The synthesis conditions for synthesizing pristine graphene, graphene oxide (GO), and graphene composites are significantly different. Thus, in this review, we first discuss synthesis methods for graphene materials with high C/O ratios from four aspects: graphite electrodes, equipment engineering, electrolytes, and additional reduction methods. Next, we survey synthesis methods for GO and examine how the pretreatment of the graphite electrodes, electrolytes, and operation parameters, such as applied voltages, electrolyte temperatures, and mechanical forces, affect the quality of GO. Further, we summarize electrochemical exfoliation methods used to dope graphene materials, introduce covalent functional groups, incorporate various nanoparticles, and assembly of graphene architectures. For all synthesis methods, we compare the properties of resulting graphene materials such as C/O ratios, lateral size, layer numbers, and quality characterized by Raman spectroscopy. Lastly, we propose our perspectives on further research. We hope this review stimulates more studies to realize the on‐demand production of graphene materials with desired properties using electrochemical exfoliation methods.
Electrochemical exfoliation of graphite has emerged as a simple and efficient method for the on‐demand production of various graphene materials from pristine graphene, graphene oxide (GO), heteroatom doped graphene, functionalized graphene, and graphene‐based composites.
Premature ovarian insufficiency (POI) poses a great threat to reproductive-age women. Ovarian fibrogenesis is a basic histologic feature of POI. Ovarian theca-stroma cells are responsible for ovarian ...fibrosis, but few studies have focused on the ovarian microenvironment. The role and mechanism of chemokines in the development of POI remain unclear. Here, we evaluated C-X-C motif chemokine ligand 10 (CXCL10) in biochemical POI patients, POI patients, and a POI mouse model. CXCL10 levels in serum and follicular fluid were higher in both bPOI and POI patients than in controls. An increased level of CXCL10 was also observed in a POI mouse model. CXCL10 concentrations in serum and follicular fluid were positively associated with follicle-stimulating hormone and negatively associated with antral follicle count. Our study for the first time found that CXCL10 induced COL1A1 and COL1A2 production, two subunits of collagen I in mouse theca-stroma cells by activating the JNK/c-Jun pathway. Inhibition of JNK and c-Jun attenuated the increases of COL1A1 and COL1A2 caused by CXCL10. Moreover, CXCL10 had no effects on hormone synthesis, proliferation, and apoptosis in human luteinized granulosa (hGL) cells. Our findings revealed a potential diagnostic value of CXCL10 in the early stage of POI and shed new insights into the biological function of CXCL10 in ovarian fibrosis.
Bladder cancer (BC) is one of the most frequent cancer in the world, and its incidence is rising worldwide, especially in developed countries. Urine metabolomics is a powerful approach to discover ...potential biomarkers for cancer diagnosis. In this study, we applied an ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) method to profile the metabolites in urine from 29 bladder cancer patients and 15 healthy controls. The differential metabolites were extracted and analyzed by univariate and multivariate analysis methods. Together, 19 metabolites were discovered as differently expressed biomarkers in the two groups, which mainly related to the pathways of phenylacetate metabolism, propanoate metabolism, fatty acid metabolism, pyruvate metabolism, arginine and proline metabolism, glycine and serine metabolism, and bile acid biosynthesis. In addition, a subset of 11 metabolites of those 19 ones were further filtered as potential biomarkers for BC diagnosis by using logistic regression model. The results revealed that the area under the curve (AUC) value, sensitivity and specificity of receiving operator characteristic (ROC) curve were 0.983, 95.3% and 100%, respectively, indicating an excellent discrimination power for BC patients from healthy controls. It was the first time to reveal the potential diagnostic markers of BC by metabolomics, and this will provide a new sight for exploring the biomarkers of the other disease in the future work.
Checkpoint blockade therapy targeting the programmed-death ligand 1 (PD-L1) and its receptor programmed cell death 1 promotes T-cell-mediated immunosurveillance against tumours, and has been ...associated with marked clinical benefit in cancer patients. Antibodies against PD-L1 function by blocking PD-L1 on the cell surface, but intracellular storage of PD-L1 and its active redistribution to the cell membrane can minimize the therapeutic benefits, which highlights the importance of targeting PD-L1 throughout the whole cell. Here, we show that PD-L1 is palmitoylated in its cytoplasmic domain, and that this lipid modification stabilizes PD-L1 by blocking its ubiquitination, consequently suppressing PD-L1 degradation by lysosomes. We identified palmitoyltransferase ZDHHC3 (DHHC3) as the main acetyltransferase required for the palmitoylation of PD-L1, and show that the inhibition of PD-L1 palmitoylation via 2-bromopalmitate, or the silencing of DHHC3, activates antitumour immunity in vitro and in mice bearing MC38 tumour cells. We also designed a competitive inhibitor of PD-L1 palmitoylation that decreases PD-L1 expression in tumour cells to enhance T-cell immunity against the tumours. These findings suggest new strategies for overcoming PD-L1-mediated immune evasion in cancer.
A combined severity factor (
R
CSF
) which is usually used to evaluate the effectiveness of hydrothermal pretreatment at above 100 °C had been developed to assess the influence of temperature, time, ...and alkali loading on pretreatment and enzymatic hydrolysis of lignocellulose. It is not suitable for evaluating alkaline pretreatment effectiveness at lower than 100 °C. According to the reported deducing process, this study modified the expression of
R
CSF
=
log
C
OH
−
n
×
t
×
e
T
r
−
T
b
/
14.75
as
R
CSF
=
log
C
OH
−
×
t
×
e
−
13700
/
Tr
+
273
+
36.2
which is easier and more reasonable to assess the effectiveness of alkaline pretreatment. It showed that
R
CSF
exhibited linear trend with lignin removal, and quadratic curve relation with enzymatic hydrolysis efficiency (EHE) at the same temperature. The EHE of alkali-treated SCB could attain the maximum value at lower
R
CSF
, which indicated that it was not necessary to continuously enhance strength of alkaline pretreatment for improving EHE. Within a certain temperature range, the alkali loading was more important than temperature and time to influence pretreatment effectiveness and EHE. Furthermore, the contribution of temperature, time, and alkali loading to pretreatment cost which was seldom concerned was investigated in this work. The alkali loading contributed more than 70% to the pretreatment cost. This study laid the foundation of further optimizing alkaline pretreatment to reduce cost for its practical application.
Prostate cancer is the only human malignancy that generates predominantly osteoblastic bone metastases, and osteoblastic bone metastases account for more than 90% of osseous metastases of prostate ...cancer. Prostate-specific antigen (PSA) plays an important role in the osteoblastic bone metastasis of prostate cancer, which can promote osteomimicry of prostate cancer cells, suppress osteoclast differentiation, and facilitate osteoblast proliferation and activation at metastatic sites. In the meantime, it can activate osteogenic factors, including insulin-like growth factor, transforming growth factor β2 and urokinase-type plasminogen activator, and meanwhile suppress osteolytic factors such as parathyroid hormone-related protein. To recapitulate, PSA plays a significant role in the osteoblastic predominance of prostate cancer bone metastasis and bone remodeling by regulating multiple cells and factors involved in osseous metastasis.
Distinguishing and characterizing different landscape patterns have long been the primary concerns of quantitative landscape ecology. Information theory and entropy-related metrics have provided the ...deepest insights in complex system analysis, and have high relevance in landscape ecology. However, ideal methods to compare different landscape patterns from an entropy view are still lacking. The overall aim of this research is to propose a new form of spatial entropy
H
) in order to distinguish and characterize different landscape patterns. H
is an entropy-related index based on information theory, and integrates proximity as a key spatial component into the measurement of spatial diversity. Proximity contains two aspects, i.e., total edge length and distance, and by including both aspects gives richer information about spatial pattern than metrics that only consider one aspect. Thus, H
provides a novel way to study the spatial structures of landscape patterns where both the edge length and distance relationships are relevant. We compare the performances of H
and other similar approaches through both simulated and real-life landscape patterns. Results show that H
is more flexible and objective in distinguishing and characterizing different landscape patterns. We believe that this metric will facilitate the exploration of relationships between landscape patterns and ecological processes.
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