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The auto-ignition properties of ammonia (NH 3)/ethanol (C 2 H 5 OH) blends close to engine operating conditions were investigated for the first time. Specifically, the ignition delay times (IDT) of ammonia/ethanol blends were measured in a rapid compression machine (RCM) at elevated pressures of 20 and 40 bar, five C 2 H 5 OH mole fractions from 0% to 100%, three equivalence ratios (ϕ) of 0.5, 1.0 and 2.0, and intermediate temperatures between 820 and 1120 K. The measurements reveal that ethanol can drastically promote the reactivity of ammonia, e.g., the auto-ignition temperature with merely 1% C 2 H 5 OH in fuel decreases accordingly around 110 K at 40 bar as compared to that of neat ammonia. Moreover, the promotion efficiency of ethanol is higher than hydrogen and methane with a factor of 5 and 10 under the same condition. Different dependences of IDT on the equivalence ratio were observed with different ethanol fractions in the blends, i.e., the IDTs of the 5%, 10% and 100% C 2 H 5 OH in fuel decrease with an increase of ϕ , but an opposite trend was observed in the mixture with 1% C 2 H 5 OH. A new chemical kinetic mechanism for NH 3 /C 2 H 5 OH mixtures was developed and it is highlighted that the addition of cross-reactions between the two fuels is necessary to obtain reasonable simulations. Basically, the newly developed mechanism can reproduce the measurements of IDT very well, whereas it overestimates the reactivity of the stoichiometric and fuel-rich mixture with 1% C 2 H 5 OH in fuel. The sensitivity, reaction pathway, as well as rate of production analysis indicated that the ethanol addition to ammonia fuel blends provides key interaction pathways and enriches the O/H radical pool which further promotes the auto-ignition process. [ABSTRACT FROM AUTHOR]

Long intergenic non-protein coding RNA 1426 (LINC01426) is up-regulated in glioma and functions as a tumor promoter. However, the role of LINC01426 in glioma required further exploration. Therefore, this article mainly studied the role and possible mechanism of LINC01426 in glioma. The area under the receiver operating characteristic curve was used to determine the diagnostic value of LINC01426. The effect of LINC01426 on tumor growth was analyzed by tumorigenesis assay and immunohistochemical analysis. Bioinformatics analysis, dual-luciferase assay, RNA pull-down, Pearson test, and real-time quantitative PCR (RT-qPCR) were applied to verify the relationship between target genes. The expressions and effects of LINC01426, miR-661 and MDM2 proto-oncogene (Mdm2) in glioma were examined by bioinformatics analysis combined with molecular and functional experiments (RT-qRCR, 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide, clone formation, BrdU, flow cytometry). The expressions of proliferation and apoptosis-related proteins were determined by Western blot. LINC01426, which was high-expressed in glioma and was related to poor prognosis, could be used as a diagnostic marker for glioma. SiLINC01426 inhibited the malignant phenotype of glioma cells in vitro and attenuated tumor growth and PCNA expression in vivo, while the effects of LINC01426 were the opposite. LINC01426 targeted and inversely correlated with miR-661, which was low-expressed in glioma. MiR-661 inhibitor evidently overturned the effect of siLINC01426 on biological functions, proliferation, and apoptosis-related proteins of glioma cells. Mdm2 bound to miR-661. Moreover, siMdm2 reversed the effects of miR-661 inhibitor on the biological characteristics and Mdm2/p53/p21 expression of glioma cells. LINC01426 aggravated the malignant progression of glioma through miR-661/Mdm2 axis. • LINC01426 was high-expressed in glioma. • siLINC01426 inhibited the malignant phenotype of glioma cells. • MiR-661 inhibitor evidently overturned the effect of siLINC01426 on glioma cells. • LINC01426 aggravates the malignant progression of glioma via miR-661/Mdm2 axis. [ABSTRACT FROM AUTHOR]

Conventional chance-constrained programming methods suffer from the inexactness of the estimated probability distribution of the underlying uncertainty from data. To this end, a distributionally robust approach to the problem allows for a level of ambiguity considered around a reference distribution. In this work, we propose a novel formulation for the distributionally robust chance-constrained programming problem using an ambiguity set constructed from a variant of optimal transport distance that was developed for Gaussian Mixture Models. We show that for multimodal process uncertainty, our proposed method provides an effective way to incorporate statistical moment information into the ambiguity set construction step, thus leading to improved optimal solutions. We illustrate the performance of our method on a numerical example as well as a chemical process case study. We show that our proposed methodology leverages the multimodal characteristics from the uncertainty data to give superior performance over the traditional Wasserstein distance-based method. • Ambiguity set constructed from optimal transport between Gaussian Mixture Models. • Hedging against the right family of candidate distributions to avoid unnecessary conservatism. • A tractable distributionally robust chance constrained optimization formulation. • Applicability to more generate type of uncertain constraints. • Better objective-constraint satisfaction trade-off performance than classical Wasserstein DRCCP model. [ABSTRACT FROM AUTHOR]

• The bacterial communities can be used as ecological and biological indicators. • The bacterial communities correctly determined the categories of OSWs with 94%. • The bacterial codes can provide a better prediction of humification degree. Microbes are the drivers for disposing of organic solid waste (OSW) during aerobic fermentation. Notwithstanding, the significance of microbes is underestimated in numerous studies on aerobic fermentation product assessments. Here, we investigated the humification degree (HD), and the humic acid content was assessed in terms of the bacterial community. The bacterial communities were useful indicators for making predictions and even correctly determined the categories of OSWs with 94% accuracy. The bacterial codes can also provide a better prediction of HD. Our results demonstrate that the bacteria code is a reliable biological method to assess HD effectively. Bacterial codes can be used as ecological and biological indicators to evaluate the quality of aerobic fermentation of different materials. [ABSTRACT FROM AUTHOR]

A recurrent neural network (RNN)-based approach is proposed in this paper to handle joint chance-constrained stochastic optimal control problems (SOCP) and stochastic model predictive control (SMPC) implementations. In the proposed approach, the joint chance constraint (JCC) in a SOCP is first reformulated as a quantile-based inequality. Then, the sample average approximation (SAA) method is used to build the RNN-based surrogate model for the quantile function. Afterwards, the RNN-based model is embedded into the probabilistic constraint of the SOCP. Subsequently, the SOCP involving the RNN-based model can be solved using a deterministic nonlinear optimization solver. Moreover, while applying the proposed approach to the SMPC, the SOCP involving the RNN-based model is solved repeatedly at different sampling instants, based on different initial system states. The proposed approach is applied to a numerical illustrating example and a chemical process case study to demonstrate its capability of handling the SOCP and the SMPC implementation. • Quantile reformulation of joint chance constraints and sample based empirical approximation. • Approximation of quantile function through recurrent neural network based surrogate model. • Stochastic optimal control problem is deterministically solvable though embedded RNN model. • Easy extension and implementation of the proposed approach to stochastic model predictive control problem. [ABSTRACT FROM AUTHOR]

This paper proposes a constraint-tolerant design with sliding mode strategy to improve the stability of aircraft engine control. To handle the difficulties associated with the high-frequency switching laws, merely attenuating the chattering is far from satisfactory. System constraints on input, output, and input rate should be addressed in the design process. For a sort of uncertain nonlinear systems subjected to the constraints, sliding mode regulators are designed using Lyapunov analysis. A turbofan engine is adopted for simulation, which shows that the methodology developed in this paper can handle the speed tracking and limit protection problem in a stable fashion, despite the negative influence posed by the system constraints. [ABSTRACT FROM AUTHOR]

• Creatively proposes the concept of rural Settlement spatial vulnerability. • Evaluating spatial vulnerability using machine learning methods. • Analyze the factors that truly affect spatial vulnerability. • Analyzing the distribution characteristics of spatial vulnerability. • Propose technical strategies to reduce spatial vulnerability. Geological disasters occur frequently in hilly areas of Sichuan province, and the development of rural settlement production and life may be affected by geological disasters.This study aims to assess the spatial vulnerability of rural settlements in hilly areas of Sichuan Province through Back-propagation neural network, find the main factors that really affect the spatial vulnerability of rural settlements, analyze the distribution characteristics of spatial vulnerability of rural settlements in hilly areas of Sichuan Province, and find methods to reduce the spatial vulnerability of rural settlements. Through research, it can be found that the three main factors affecting the spatial vulnerability of rural settlements in hilly areas of Sichuan are climate factors, soil erosion degree, and geological hazard hidden danger degree. The quantitative climate factor data is the ratio of annual precipitation to population in rural settlements,the higher the annual precipitation, the higher the spatial vulnerability. The second largest influencing factor is the degree of soil erosion,the more severe the soil erosion, the higher the spatial vulnerability in the districts and counties. The third major influencing factor is the degree of geological hazards, and the higher the degree of geological hazards, the higher the spatial vulnerability. Other natural environment and rural settlement spatial factors also have a certain impact on the spatial vulnerability of rural settlements, while socio-economic factors have almost no impact on the spatial vulnerability of rural settlements. Finally, the relationship between the spatial vulnerability of rural settlements and its location are obtained from the relevant data of all sample districts and counties, and combined with the geological environment and climate of the hilly areas of Sichuan, the spatial distribution characteristics of the spatial vulnerability of rural settlements in the hilly areas of Sichuan are summarized: The closer the districts and counties are to the geological fracture zone between Longmen Mountain and Longquan Mountain, the higher the spatial vulnerability of rural settlements.The spatial vulnerability of rural settlements in the west of hilly areas is higher than that in the east, and there is little difference between north and south. Then, based on the above achievements, this study proposes strategies and suggestions to reduce the spatial vulnerability of rural settlements in hilly areas of Sichuan, providing reference materials and data support for local planning departments in rural planning work. [ABSTRACT FROM AUTHOR]

Data-driven distributionally robust chance-constrained optimization (DRCCP) is a powerful technique to handle optimization problems involving uncertainty in constraint functions. However, the outliers and extreme samples in the data set may deteriorate the decision quality of DRCCP. Although there are numerous outlier detection techniques, they are either unable to pinpoint the samples causing overly conservative solutions, or incompatible with DRCCP models. This work proposes a novel and widely compatible algorithm that generates a representative subset of the original data set and removes samples causing overly conservative solutions for the DRCCP problem. With the proposed approach, the DRCCP solution quality can be enhanced while simultaneously ensuring the solution feasibility. To illustrate its effectiveness, we examine two numerical examples and a nonlinear process optimization problem in our study. • Novel algorithm for distributionally robust chance constrained problem (DRCCP). • Refine solution quality via representative subset and removal of detrimental data. • Performance is shown through Wasserstein ambiguity set based DRCCP model. • Algorithm is applicable for general data-driven DRCCP problems. [ABSTRACT FROM AUTHOR]

With the improvement of environmental protection requirements, risk analysis is significant for environmental impact assessment accidents (EIAA) of construction projects. Currently, many risk variables can cause EIAA, and risk probabilities of EIAA are various in different risk scenarios. Therefore, the aim of the study is to explore various risk scenarios with different risk probabilities of EIAA. According to the results of risk variables, which were studied by Grounded Theory (GT), the risk scenarios with high risk probabilities of EIAA are proposed by Bayesian Network (BN) in this study. This study finds that 1) 21 risk variables contained 5 categories involve invalid data, fuzzy evaluation scope, unreasonable evaluation model, unreasonable evaluation conclusion, incomplete assessment report. 2) critical risk variables causing EIAA contain lacking of personnel signature in EIA report, unreasonable project site selection, unreasonable evaluation grade of pollution source. 3) there are 4 risk scenarios with high risk probabilities of EIAA, and their risk probabilities are 90.3%, 90.3%, 89.6%, 89.6%, respectively. These findings offer a good reference for the environmental impact assessment of construction projects. • EIAA contains 21 risk variables. • unreasonable evaluation grade of pollution source is critical. • there are four risk scenarios with higher risk probabilities of EIAA. • four risk scenarios' probabilities 90.3%, 90.3%, 89.6%, 89.6%, respectively. [ABSTRACT FROM AUTHOR]

The conceptual design, modeling, and optimization of a MeOH-to-H 2 processor by an integration of a multi-tube annular membrane methanol reformer (MTAMMR) and the preheating system are presented. The annular membrane methanol reformer (AMMR) is a packed-bed reactor consisting of two concentric cylinders and its surface is covered with the Pd-Cu membranes. When the methanol steam reforming and the preferential oxidation reactions are carried out in the outer and the inner tubes, respectively, the counter-current axial flow in the annular gap can ensure the thermally self-sustaining operation. Under sufficient consideration of the effect of heat integration, three plate-fin heat exchangers (PFHEs) are taken into account in the preheating system. Through a series of optimization algorithms for maximizing the H 2 permeation rate of each AMMR and minimizing the total energy demand of the preheating system, respectively, the optimal operating conditions and specifications of MeOH-to-H 2 processor are obtained. Finally, it is successfully found that the perfect weight of the optimized MeOH-to-H 2 processor is close to the H 2 tank weight for 2016 Toyota Mirai vehicle if the PFHEs use titanium material. [ABSTRACT FROM AUTHOR]

Mechanism development is a complex process by itself, and it is usually combined with experimental studies to understand and evaluate the ignition chemistry of the investigated fuel mixtures. In this work, the software Reaction Mechanism Generator (RMG) is used to automatically generate a kinetic mechanism for the auto-ignition of ammonia/methanol blend mixtures. The ignition delay time (IDT) of ammonia/methanol mixtures was measured in a high-pressure shock tube (HPST) at the pressure of 10 bar, equivalence ratios of 0.5, 1.0 and 2.0, and temperatures between 1050 and 1550 K for methanol content of 0–20%. These IDT data were combined with prior literature data for laminar burning velocity (LBV) at 1 atm and 298–448 K and the ignition delay time (IDT) at 20 and 40 bar and 845 – 1100 K. The detailed mechanism, containing 68 species and 467 elementary reactions, satisfactorily predicted the combined set of IDTs and LBVs of ammonia/methanol blends. [ABSTRACT FROM AUTHOR]

• The urban landscape was divided into different urban growth patterns to enhance the prediction of its Land Surface Temperature (LST). • Urban growth patterns were classified based on their shared borders with focal urban patches. • The LST of the growth patterns was modeled using their spatial forms and the LST of the focal patches. • The most significant variables and the performance of LST prediction varied among the different growth patterns. The growing threat of urban heating has attracted considerable scholarly attention to their modeling and prediction. To improve the urban land surface temperature (LST) determination, this study assumed that the spatial pattern of built-up patches matters in LST prediction. To test this idea in a rapidly-urbanizing landscape, different urban growth types including infilling, edge expansion and outlying patterns and their LST layers were extracted from Landsat images in 1992, 2002, 2012, and 2022. The mean LST of each growth pattern was then modeled using the multiple linear regression (MLR) analysis and an array of independent variables related to the spatial formation and LST of the newly-grown and previously-existed urban patches. Results of the best infilling MLR model (R2 = 0.579) showed that the highest mean LST of the infilling growth is expected to be around the center of large focal patches. The mean LST of the edge expansion growth patches were found to be influenced by the mean LST of the edge of their focal patches and their shape structure (R2 = 0.362). The area of the outlying growth patches was also selected as the sole predictor of their mean LST (R2 = 0.334). According to the findings, the mean LST of the outlying, infilling and edge expansion growth patterns are influenced by the landscape composition, configuration and structure, respectively. Our results corroborate the idea that the performance of the urban LST prediction and their practical implications can be improved when the built-up landscape is divided into more spatially similar growth classes. [ABSTRACT FROM AUTHOR]

• Use mobile phone signaling data to assess urban vitality. • Call for temporally and spatially varying policies for urban vitality enhancement. • The spatial distribution of urban vitality is clustered and polycentric. • Urban vitality varies considerably throughout the day. • The effects of metro accessibility are more evenly distributed on weekends. Urban vitality has long been a focus of urban planners and designers. This study portrays the spatiotemporal patterns of urban vitality in Chengdu, China, on weekdays and weekends and examines their relationship with a set of factors using spatial regression and geographically weighted regression models. The results reveal that the spatial distribution of urban vitality displays a clustered and polycentric pattern, which can be attributed to urban spatial structure. Urban vitality varies considerably throughout the day on weekdays and weekends, and it consistently decreases as the distance to the city center increases. Furthermore, weekday vitality is much more predictable (less random) than weekend vitality, indicating that human activity patterns present higher regularity on weekdays than on weekends. The normalized difference vegetation index (NDVI), road density, the number of residential facilities, and land-use mix have positive influences on urban vitality on weekdays and weekends, while the distance to the metro station has negative influences. The influences of NDVI on urban vitality in the city center are negative on weekdays but become positive on weekends. The influences of the distance to the metro station are more homogeneously distributed on weekends than on weekdays. Finally, this study calls for temporally and spatially varying policies for urban vitality enhancement. [ABSTRACT FROM AUTHOR]

Graphene oxide (GO) acted as an inorganic filler has attracted great attention in the construction of polymer-based composite coating film. Nevertheless, the high surface area, obvious van der Waals forces, and abundant hydrophilic groups of GO result in its poor dispersion behavior and compatibility in hydrophobic polymer, which greatly limits its widespread practical application. To solve the above issue, we have prepared SiO 2 -decorated GO (GO-SiO 2) nanoparticles using the sol-gel hydrolysis method. The FTIR, Raman spectra, XPS and SEM analysis displayed that GO-SiO 2 nanoparticles were successfully constructed and the SiO 2 nanoparticles are covalently grafted onto GO sheet surfaces. Moreover, the GO-SiO 2 nanoparticles are further employed as inorganic fillers into the non-solvent UV-curable castor oil-based polyurethane acrylate (COPUA) systems for the preparation of composite coating films. Herein, the GO-SiO 2 nanoparticles can be uniformly dispersed in hydrophobic COPUA-based coating precursor, and have favorable compatibility with COPUA resin. The incorporation of GO-SiO 2 nanoparticles into the coating film matrix would slightly decrease the gel content of coating films (all gel contents are above 91.5 %) while improving the hydrophobic property of coating films. Furthermore, the thermal stability and mechanical performance of coating films have reasonably enhanced trends by the incorporation of GO-SiO 2 nanoparticles. The prepared coating films display favorable acid, alkali, and solvent resistance, and the high content of GO-SiO 2 nanoparticles is beneficial to aggrandize the anticorrosion performance of coating films. This work provides a universal approach to modify GO sheets and construct multifunctional modified GO/polyurethane composite film for coating application. [Display omitted] • SiO 2 -decorated GO sheets (GO-SiO 2) are prepared by the sol-gel hydrolysis method. • GO-SiO 2 has nice suspendability and compatibility in hydrophobic coating system. • GO-SiO 2 /castor oil-based polyurethane film is formed by non-solvent UV-curing way. • GO-SiO 2 avails to enhance thermal, mechanical and anticorrosive properties of film. • This work provides a facile method to prepare GO/polyurethane-based coating film. [ABSTRACT FROM AUTHOR]

Predicting the location where a protein resides within a cell is important in cell biology. Computational approaches to this issue have attracted more and more attentions from the community of biomedicine. Among the protein features used to predict the subcellular localization of proteins, the feature derived from Gene Ontology (GO) has been shown to be superior to others. However, most of the sights in this field are set on the presence or absence of some predefined GO terms. We proposed a method to derive information from the intrinsic structure of the GO graph. The feature vector was constructed with each element in it representing the information content of the GO term annotating to a protein investigated, and the support vector machines was used as classifier to test our extracted features. Evaluation experiments were conducted on three protein datasets and the results show that our method can enhance eukaryotic and human subcellular location prediction accuracy by up to 1.1% better than previous studies that also used GO-based features. Especially in the scenario where the cellular component annotation is absent, our method can achieved satisfied results with an overall accuracy of more than 87%. [ABSTRACT FROM AUTHOR]

Litchi ( Litchi chinenis Sonn.) is a woody mycorrhizal fruit tree. Hypha and root hairs are the most important structures for nutrition and water absorption in litchi. Girdling is an important technique in litchi cultivation. However, the effects of girdling on arbuscular mycorrhiza (AM) colonization and root hair development remain unknown. To understand the effects of girdling on AM and root hairs in litchi, the carbohydrate content, enzyme activities related to sucrose metabolism, AM colonization, and length and density of root hairs were measured under girdling, wounding and control conditions in the roots of one-year-old seedlings. Results showed that sufficient carbohydrates were available for AM and root hairs in the mycorrhizal roots of litchi in the wounding and control groups. Girdling significantly decreased the concentrations of glucose at 3 days (3D), 1 week (1W), 2 weeks (2W), 1 month (1M) and 2 months (2M) after treatment, of fructose at 3D, 1W, 2W, 1M and 2 M after treatment, of sucrose at 1W, 2W, 1M and 2M after treatment, and of starch at 2W, 1M and 2M after treatment. Consistent with its effects on carbohydrates, girdling significantly reduced arbuscular colonization (1M and 2M) and root hair length (1M). The correlations of arbuscular colonization and root hair length with concentrations of carbohydrates (fructose, sucrose and starch) were significant only under girdling treatment. Under conditions of hexose starvation caused by girdling, litchi seedlings exhibited significantly upregulated neutral invertase activity in sucrose-cleaving parts and downregulated sucrose phosphate synthase and sucrose synthase (synthesis direction) in sucrose synthesis parts. The correlations of arbuscular colonization with levels of sucrose-cleaving enzymes (neutral invertase and acid invertase) and root hair length with levels of sucrose-cleaving enzymes (neutral invertase and acid invertase) were also significant only under girdling treatment. Our findings indicated that AM colonization was more sensitive to carbohydrates than root hair length in litchi seedlings. Furthermore, girdling likely affected AM colonization and root hair length by decreasing the carbohydrate contents and regulating the activities of sucrose-metabolising enzymes. [ABSTRACT FROM AUTHOR]

• Strawberry showed wilting phenomenon after a week of Colletotrichum siamense infection. • Phenylpropanoid biosynthesis were upregulated in crown with C. siamense infection. • Phenolic acids of phenylpropanoid biosynthesis increased susceptibility of crown rot. Crown rot caused by Colletotrichum siamense is a serious disease affecting strawberry that leads to large-scale losses, both in their quality and yield, in the Yangtze River Basin, China. Secondary metabolites are known to play pivotal roles in defense responses against invading pathogens, and identifying metabolites involved in crown rot is necessary for understanding induced resistance and developing improved genetic resistance against strawberry crown rot. To explore this research topic, the infection process was verified via observation of the phenotypes and histopathology of susceptible 'Benihoppe' strawberry inoculated with C. siamense. Following this, metabolomic analysis was used that identified phenolic acids, flavonoids, and amino acids as the metabolites accumulated in the rotten crown caused by the C. siamense infection process. Furthermore, the transcripts encoding enzymes involved in the 'phenylpropanoid biosynthesis' of phenolic acids, trans -cinnamate 4-monooxygenase, caffeoylshikimate esterase, and caffeic acid 3-O-methyltransferase were all upregulated in the rotten crown, as shown by transcriptomic analysis and qRT-PCR. In addition, the metabolites p -coumaric acid, caffeic acid, and ferulic acid in the 'phenylpropanoid biosynthesis' pathway all enhanced C. siamense infection, as shown by an exogenous validation experiment. Together, the results demonstrate that the 'phenylpropanoid biosynthesis' pathway was induced during crown rot and thus highlight the potentially crucial regulatory role of this pathway in plant immunity. [ABSTRACT FROM AUTHOR]

Na–CO 2 battery is one of the most promising energy storage devices for the exploration of Mar. To fix the evaporation problem of liquid electrolytes in an open system, solid-state electrolyte Na 3 Zr 2 Si 2 PO 12 (NZSP) is used to fabricate a solid-state Na–CO 2 battery. In the battery, the interface between the Na-metal anode and NZSP plays a vital role in improving electrochemical performance. The interfacial parasitic reaction between NZSP and Na-metal results in a Na-rich kinetically stable interphase. (200) and (−111) planes are the preferentially etched crystal planes of NZSP, as SiO 4 and PO 4 tetrahedrons on the planes are easily broken by extra Na-ion injection. Aside from the interfacial reaction, the poor contact between Na-metal and NZSP is a more serious problem, which leads to large interfacial resistance and poor cycling stability. To fix this problem, carbon black is mixed with melted Na-metal to prepare a composite anode (Na@C). The Na@C composite anode easily wets NZSP, thus decreasing the interfacial resistance from 918 to 98 Ω cm2. Symmetrical cells stably cycled 1100 h at 0.1 mA cm−2, when using Na@C as the electrode. Furthermore, Na–CO 2 battery with Na@C composite anode also shows a prolonged cycling life. [Display omitted] ● (200) and (−111) planes are found as preferentially etched crystal planes of NZSP. ● Kinetically stable interphase between Na and NZSP has been found. ● Poor interfacial contact between Na and NZSP results in poor cycling stability. ● Na@C composite anode makes intimate contact with NZSP. ● The solid-state Na–CO 2 battery shows better performance by using Na@C. [ABSTRACT FROM AUTHOR]

Non-syndromic cleft lip and/or palate (NSCL/P) is a common maxillofacial birth defect, and the etiology of which is complex and still unclear. Accumulating studies indicate that long non-coding RNAs(lncRNAs) and microRNAs(miRNAs) play important roles in NSCL/P. However, the potential regulatory associations remain largely unknown. In this study, we screened differentially expressed miRNAs and constructed competing endogenous RNA (ceRNA) networks to lay a foundation for further research on the regulatory mechanism of ncRNAs in NSCL/P. NSCL/P plasma RNA was analyzed by miRNA sequencing. The bioinformatics database, GEO and STRING database, GO and KEGG enrichment analysis and Cytoscape software were used to analyze and screen lncRNAs and mRNAs potentially related to differential miRNAs. The expression levels of lncRNA, miRNA and mRNA in ceRNA network were detected by RT-qPCR. In NSCL/P plasma samples, there were 47 differentially expressed miRNAs in CPO group and 36 differentially expressed miRNAs in CL/P group. GO and KEGG enrichment analysis showed that cell cycle, cell response to DNA damage stimulation, and the TGF-βsignaling pathway were relevant to the formation of NSCL/P. The RT-qPCR results showed that the expression levels of lncRNA NEAT1, hsa-miR-130 b-3p, hsa-miR-212–3p, hsa-miR-200 b-3p and SMAD2 were different in NSCL/P. We found that differentially expressed miR-212–3p, miR-200 b-3p and miR-130 b-3p may be involved in the pathogenesis of cleft palate by regulating related target genes. [ABSTRACT FROM AUTHOR]

Measuring the similarity between pairs of biological entities is important in molecular biology. The introduction of Gene Ontology (GO) provides us with a promising approach to quantifying the semantic similarity between two genes or gene products. This kind of similarity measure is closely associated with the GO terms annotated to biological entities under consideration and the structure of the GO graph. However, previous works in this field mainly focused on the upper part of the graph, and seldom concerned about the lower part. In this study, we aim to explore information from the lower part of the GO graph for better semantic similarity. We proposed a framework to quantify the similarity measure beneath a term pair, which takes into account both the information two ancestral terms share and the probability that they co-occur with their common descendants. The effectiveness of our approach was evaluated against seven typical measurements on public platform CESSM, protein–protein interaction and gene expression datasets. Experimental results consistently show that the similarity derived from the lower part contributes to better semantic similarity measure. The promising features of our approach are the following: (1) it provides a mirror model to characterize the information two ancestral terms share with respect to their common descendant; (2) it quantifies the probability that two terms co-occur with their common descendant in an efficient way; and (3) our framework can effectively capture the similarity measure beneath two terms, which can serve as an add-on to improve traditional semantic similarity measure between two GO terms. The algorithm was implemented in Matlab and is freely available from http://ejl.org.cn/bio/GOBeneath/ . [ABSTRACT FROM AUTHOR]

Partial oxidation of hydrocarbons under well-controlled conditions opens a path to higher-value chemicals from natural gas with small exergy losses if the chemical conversion proceeds in an internal combustion engine as a polygeneration process (Gossler et al., 2015). For the relevant reaction conditions, kinetics models are not sufficiently validated due to the atypical reaction conditions, e.g., high equivalence ratios and pressures. The purpose of this study is to obtain experimental validation data for chemical reaction mechanisms that can be used to predict polygeneration processes in practical applications. In case of methane these processes proceed under fuel-rich conditions and yield primarily syngas (CO/H 2 ). In this study, the partial oxidation of methane was investigated for an equivalence ratio of ϕ = 2 in a shock-tube and a plug-flow reactor (PFR) in order to cover a wide temperature range. Time-resolved CO mole fractions were measured in shock-heated mixtures between 1600 and 2100 K at ∼1 bar. Good agreement was found between the experiment and the models (Yasunaga et al., 2010; Burke et al., 2015; Zhao et al., 2008). Stable reaction products were monitored by time-of-flight mass spectrometry between 532 and 992 K at 6 bar in a tubular flow reactor at reaction times >4 s. The influence of dimethyl ether (DME) and n-heptane addition on methane reactivity and conversion was investigated. The additives significantly lower the initial reaction temperature by producing significant amounts of OH. The results were compared to simulations and serve as validation data for the development of reaction mechanisms for these atypical reaction conditions. Good agreement was found between the experiment and the models for most of species. [ABSTRACT FROM AUTHOR]