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The significance of this study is to classify and identify the types of ancient glass products according to their chemical composition. The data were selected from the proportion of chemical compositions that have been analyzed for ancient glass, and the best number of clusters (k) for the division was roughly determined using the elbow rule for the five chemical compositions of high potassium and lead barium, respectively, and brought into the k-means++ algorithm for cluster analysis, and then the final determination of k and the evaluation of the rationality of clustering were performed using the contour coefficient, and finally the Fisher discriminant analysis method based on variable meritocracy combined with eigenvalues, Wilke Lambda, and classification function coefficients to identify unknown categories of glass artifacts. The model used was analyzed and evaluated with good results, and the model is applicable to the classification of ancient glass artifacts and identification of the type to which they belong.

Experimental results showed that configuring different baffles (a regular flat, a single- or double-layer perforated plate and a Helmholtz resonator) in the plenum can well suppress the self-excited oscillation in annular combustor. In this paper, a 2D low-order network model is proposed to describe this phenomenon and predict the modal frequencies and growth rates of longitudinal and circumferential thermoacoustic modes for annular combustor with different baffles. In the plenum, only the circumferential acoustic propagation and the influence of baffles on it are accounted for as the longitudinal geometry size is much smaller than the acoustic wavelength of the longitudinal mode. Pure longitudinal acoustic propagation is considered in burners and both longitudinal and circumferential ones are accounted for in the combustion chamber. These three modules are connected by jump conditions. The numerical prediction matches the experimental results. Baffles using Helmholtz resonators feature the best damping performance. The circumferential mode is converted to two unfolded non-degenerate modes when configuring perforated plates baffles. Best damping effect for the configuration of the baffles in the plenum can be achieved based on the proposed model.

Accurate trajectory prediction of surrounding vehicles enables lower risk path planning in advance for autonomous vehicles, thus promising the safety of automated driving. A low-risk and high-efficiency path planning approach is proposed for autonomous driving based on the high-performance and practical trajectory prediction method. A long short-term memory (LSTM) network is trained and tested using the highD dataset, and the validated LSTM is used to predict the trajectories of surrounding vehicles combining the information extracted from vehicle-to-vehicle (V2V) technology. A risk assessment and mitigation-based local path planning algorithm is proposed according to the information of predicted trajectories of surrounding vehicles. Two driving scenarios are extracted and reconstructed from the highD dataset for validation and evaluation, i.e., an active lane-change scenario and a longitudinal collision-avoidance scenario. The results illustrate that the risk is mitigated and the driving efficiency is improved with the proposed path planning algorithm comparing to the constant-velocity prediction and the prediction method of the nonlinear input-output (NIO) network, especially when the velocity and trajectory with sudden changes.

In aerospace engine delivery systems, “one-in-two-out” bifurcation structures are commonly used for flow distribution to downstream pipelines. There are two common “one-in-two-out” bifurcation structures in aircraft engines: the planar orthogonal bifurcation and the spatial orthogonal bifurcation. By adjusting the flow supply upstream and the cross-sectional diameter downstream, the flow distribution in the two branches can be adjusted, i.e., the “splitting ratio” changes. In this paper, a dismantling and flexible experimental system is constructed to measure the pressure signals in each channel and use non-linear dynamic analysis methods to extract pressure characteristics. The particle image velocimetry (PIV) technique combined with the fine rope tracing technique is creatively used to observe the vortex structure in the cross section of the downstream branch. The study found that for spatial orthogonal bifurcation, the pressure signal characteristics in each channel are basically the same at larger splitting ratios, regardless of the chirality. As the splitting ratio decreases, the difference in pressure signal characteristics between the two branches gradually becomes evident and becomes related to the chirality. Moreover, unlike the planar orthogonal bifurcation structure, a complete large vortex structure has not been found in the downstream branch of the spatial orthogonal bifurcation structure, regardless of changes in the splitting ratio, and it is unrelated to the chirality.

The use of gas energy includes a wide range of applications to directly accelerate the liquid in a pipeline without the aid of mechanical equipment, such as marine gas-liquid jet propulsion. To clarify the characteristics of energy transfer by interphase forces for gas-liquid flows in variable cross-section tubes, two-fluid models of annular flow, bubbly flow and homogeneous flow were adopted, respectively, along with four newly elaborated coefficients, which are the work factor of gas fg, reflecting the relative ability of gas to power liquid, the interface work transfer coefficient kg (representing the relative magnitude of mechanical work received by liquid from gas), the interphase work-to-energy conversion coefficient kl (denoting the capability of energy transfer through work performed by interphase forces) and the interphase mechanical efficiency ηw. The results reveal the interphase work transfer is strongly influenced by the structural parameters of the tubes (or nozzles), and an optimized design is necessary to improve the performance. The higher the degree of gas dispersion in the liquid, the more advantageous the conversion of gas work into the liquid’s mechanical energy. Of these three flow patterns, annular flow has the lowest kl and ηw (kl = 0.0797, ηw = 0.9885 in present example), while homogeneous flow displays the limit of interphase mechanical energy conversion because the gas-liquid momentum coupling reaches the maximum (kl = 0.9979, ηw = 1).

Transversal and longitudinal combustion instabilities typically present in gas turbines and rocket engines. It is thus important to investigate the flame responses of the two directional disturbanc...

The carbon coated SnOx with adjustable composition and coating thickness was firstly prepared. The initial coulombic efficiency and cycle stability were improved by chemical prelithiation and the full-cell showed better cycling and rate performance.

Electromagnetically induced transparency (EIT) metamaterials (MTMs) based on the bright-dark mode theory have gained great interest in slow light, sensing, and energy storage in recent years. Typically, various split ring resonators with magnetic response have been proposed as dark resonators in EIT MTMs. Here, we have employed a cut-wire (CW) and two electric-field-coupled inductor-capacitor (ELC) resonators with a pure electrical response on a liquid crystal polymer (LCP) substrate with a low loss tangent to fulfill the EIT effect in the terahertz (THz) region. The former works as the bright mode, and the latter functions as the dark mode. The EIT phenomenon results from the destructive interference between these two modes, which can be verified by numerical simulation and near field distribution. In addition, a Lorentz oscillator model was studied to quantitatively analyze the relationship between the coupling strength and the coupling distance. As a demonstration, an EIT MTM device with 5000 units was fabricated and characterized, which showed a transmission window with a peak value of 0.75 at 0.414 THz. This work may inspire new multifunctional EIT MTMs, especially the flexible applications at THz frequencies.

Background Bacterial viruses, phages, play a key role in nutrient turnover and lysis of bacteria in terrestrial ecosystems. While phages are abundant in soils, their effects on plant pathogens and rhizosphere bacterial communities are poorly understood. Here, we used metagenomics and direct experiments to causally test if differences in rhizosphere phage communities could explain variation in soil suppressiveness and bacterial wilt plant disease outcomes by plant-pathogenic Ralstonia solanacearum bacterium. Specifically, we tested two hypotheses: (1) that healthy plants are associated with stronger top-down pathogen control by R. solanacearum-specific phages (i.e. ‘primary phages’) and (2) that ‘secondary phages’ that target pathogen-inhibiting bacteria play a stronger role in diseased plant rhizosphere microbiomes by indirectly ‘helping’ the pathogen. Results Using a repeated sampling of tomato rhizosphere soil in the field, we show that healthy plants are associated with distinct phage communities that contain relatively higher abundances of R. solanacearum-specific phages that exert strong top-down pathogen density control. Moreover, ‘secondary phages’ that targeted pathogen-inhibiting bacteria were more abundant in the diseased plant microbiomes. The roles of R. solanacearum-specific and ‘secondary phages’ were directly validated in separate greenhouse experiments where we causally show that phages can reduce soil suppressiveness, both directly and indirectly, via top-down control of pathogen densities and by alleviating interference competition between pathogen-inhibiting bacteria and the pathogen. Conclusions Together, our findings demonstrate that soil suppressiveness, which is most often attributed to bacteria, could be driven by rhizosphere phage communities that regulate R. solanacearum densities and strength of interference competition with pathogen-suppressing bacteria. Rhizosphere phage communities are hence likely to be important in determining bacterial wilt disease outcomes and soil suppressiveness in agricultural fields.

Introduction Super-enhancer-associated lncRNAs play important roles in the occurrence and development of malignant tumors, including hepatocellular carcinoma (HCC). Objectives The current work aimed to identify and characterize super-enhancer-associated lncRNAs in the pathogenesis of HCC. Methods H3K27ac ChIP-seq data from HepG2 cell line and two HCC tissues were used to identify super-enhancer-associated lncRNAs in HCC. JQ-1 treatment and CRISPR-dCas9 system were performed to confirm super-enhancer activity. Quantitative real-time PCR (qPCR), ChIP-qPCR, and dual-luciferase reporter system assay demonstrated the regulation of E2F1 on super-enhancer. Functional loss experiment was used to identify the function of LINC01004. Results In this study, we identified and characterized LINC01004, a novel super-enhancer-associated lncRNA, as a crucial oncogene in HCC. LINC01004 was upregulated in liver cancer tissues and was associated with poor patient prognosis. Moreover, LINC01004 promoted cell proliferation and metastasis of HCC. The binding of E2F1 to the super-enhancer could promote the transcription of LINC01004, while the inhibition of super-enhancer activity decreased LINC01004 expression. Conclusion This finding might provide mechanistic insights into the molecular mechanisms underlying hepatocarcinogenesis and the biological function of super-enhancer. LINC01004 can serve as a potential therapeutic target for HCC patient. Graphical abstract

District heating systems have been widely used in large and medium-sized cities. Typical district heating systems consist of the primary heating system (PHS) and the secondary heating system (SHS) operating in isolation. However, the isolated dispatch of the PHS and the SHS has poor adjustability and large losses, resulting in unnecessary operation costs. To address these issues, a coordinated economic dispatching model (CEDM) for the primary and secondary heating systems considering the boiler’s supplemental heating is proposed in this study, which characterized the physical properties of the PHS and the SHS in detail. Considering that the PHS and the SHS are controlled separately without central operators in practice, it is difficult to dispatch them in a centralized method. Thus, the master-slave splitting algorithm is innovatively introduced to solve the CEDM in a decentralized way. Finally, a P6S12 system is utilized to analyze and verify the effectiveness and optimality of the proposed algorithm.

The quantitative and bifunctional modification of carbon dots is achieved by adjusting the content of precursors through click chemistry. The triazole structure introduced is almost nontoxic and could even promote cell proliferation.

Baffled injectors are widely used to restrain transverse combustion instabilities in liquid rocket engines. However, there is still a lack of theoretical research on the attenuation mechanisms. In ...

Cylindrical ducts with axial mean temperature gradient and mean flows are typical elements in rocket engines, can combustors, and afterburners. Accurate analytical solutions for the acoustic waves of the longitudinal and transverse modes within these ducts can significantly improve the performance of low order acoustic network models for analyses of acoustic behaviours and combustion instabilities in these kinds of ducts. Here, we derive an acoustic wave equation as a function of pressure perturbation based on the linearised Euler equations (LEEs), and the modified WKB approximation method is applied to derive analytical solutions based on very few assumptions. The eigenvalue system is built based on the proposed solutions and applied to predict the resonant frequencies and growth rate for transverse modes. Validations of the proposed solutions are performed by comparing them to the numerical results directly calculated from the LEEs. Good agreements are found between analytical reconstruction and numerical results of three-dimensional transverse modes. The system with both mean temperature profile and mean flow presents a larger absolute value of the growth rate than the condition of either uniform mean temperature or no mean flow.

Long noncoding RNAs (lncRNAs) and circular RNAs (circRNAs) are important classes of small noncoding RNAs that can regulate numerous biological processes. To understand the role of message RNA (mRNAs, lncRNAs and circRNAs) in the regulation of intramuscular fat (IMF) deposition, in this study the expression profiles of longissimus dorsi (LD) muscle from six Laiwu pigs (three with extremely high and three with extremely low IMF content) were sequenced based on rRNA-depleted library construction. In total, 323 differentially expressed protein-coding genes (DEGs), 180 lncRNAs (DELs) and 105 circRNAs (DECs) were detected between the high IMF and low IMF groups. Functional analysis indicated that most DEGs, and some target genes of DELs, were enriched into GO terms and pathways related to adipogenesis, suggesting their important roles in regulating IMF deposition. In addition, 12 DELs were observed to exhibit a positive relationship with stearoyl-CoA desaturase (SCD), phosphoenolpyruvate carboxykinase 1 (PCK1), and adiponectin (ADIPOQ), suggesting they are highly likely to be the target genes of DELs. Finally, we constructed a source gene-circRNA-miRNA connective network, and some of miRNA of the network have been reported to affect lipid metabolism or adipogenesis. Overall, this work provides a valuable resource for further research and helps to understand the potential functions of lncRNAs and circRNAs in IMF deposition.

Atherosclerosis is one of the leading causes of cardiovascular diseases and mortality around the world. One exciting strategy for atherosclerosis treatment is immunotherapy, especially active immunization. Active immunization relies on the delivery of antigens in a vaccine platform to introduce humoral and cellular immunity alleviating atherosclerotic progression. TRPM2 is an ROS-activated Ca2+-permeable ion channel that can promote atherosclerosis via stimulating vascular inflammation. In the present study, we developed a strategy of active immunization with TRPM2 E3 domain peptide in a vaccine platform, aiming to induce endogenous production of anti-TRPM2 blocking antibody in mice in vivo, consequently inhibiting TRPM2 channel activity to alleviate atherosclerotic progression. The results show that immunization with a pig TRPM2 E3 region-based peptide (P1) could effectively alleviate high cholesterol diet-induced atherosclerosis in ApoE-/- mice. We worked out the best vaccine formulation for most effective atheroprotection, namely P1 at the dose of 67.5 µg per mouse (2.5 mg/kg body weight) with aluminium salts as adjuvant. The present study laid the foundation for future clinical trials using TRPM2 E3 vaccine for potential therapeutic option against atherosclerosis.

Energy efficiency evaluation of industrial park customers is carried out to help customers develop optimization strategies and improve the energy efficiency level. The evaluation indexes are proposed based on pressure-state-response (PSR) model and the redundant indexes are selected by combining principal component analysis (PCA) and correlation analysis. Thus the dynamic energy efficiency index system is constructed. The weight of indexes is calculated by the entropy weight method (EWM). An energy efficiency evaluation model based on improved Grey-technique for order preference by similarity to ideal solution (TOPSIS) is proposed, which replaces the Euclidean distance by weighted grey correlation degree and can accurately evaluate customers’ energy efficiency level. An energy efficiency optimization model is proposed, which can maximize optimization benefits while improving energy efficiency. The validity of the evaluation and optimization models is verified by the case study of an industrial park.

The influencing factors of kite culture inheritance form a complex system that is influenced by many factors, such as the inheritance mode, audience preferences, communication mode and social environment, and the influencing factors are plentiful and nonlinear. In this paper, we use the literature search method and Delphi method to determine the set of influencing factors and clarify the direct binary relationships between each of them. Based on the results of these methods, the Adversarial Interpretive Structure Model (AISM) is modeled and used, and the AISM model with a cause-effect reachable hierarchy is obtained by comparing the directed topological diagram of a pair of up and down diagrams and conducting a comprehensive analysis of the influencing factors of kite culture inheritance. Finally, the validity of the model is proved through the project practice of talent training in the National Art Foundation of China. The results of this study show the following: policies and regulations and product characteristics are the root cause elements affecting the inheritance of intangible cultural heritage.

Early studies revealed relationships between barium (Ba), particulate organic carbon and silicate, suggesting applications for Ba as a paleoproductivity tracer and as a tracer of modern ocean circulation. But, what controls the distribution of barium (Ba) in the oceans? Herein, we investigated the Arctic Ocean Ba cycle through a one-of-a-kind data set containing dissolved (dBa), particulate (pBa), and stable isotope Ba ratio (δ138Ba) data from four Arctic GEOTRACES expeditions conducted in 2015. We hypothesized that margins would be a substantial source of Ba to the Arctic Ocean water column. The dBa, pBa, and δ138Ba distributions all suggest significant modification of inflowing Pacific seawater over the shelves, and the dBa mass balance implies that ∼50% of the dBa inventory (upper 500 m of the Arctic water column) was supplied by nonconservative inputs. Calculated areal dBa fluxes are up to 10 µmol m-2 d-1 on the margin, which is comparable to fluxes described in other regions. Applying this approach to dBa data from the 1994 Arctic Ocean Survey yields similar results. The Canadian Arctic Archipelago did not appear to have a similar margin source; rather, the dBa distribution in this section is consistent with mixing of Arctic Ocean-derived waters and Baffin Bay-derived waters. Although we lack enough information to identify the specifics of the shelf sediment Ba source, we suspect that a sedimentary remineralization and terrigenous sources (e.g., submarine groundwater discharge or fluvial particles) are contributors. Plain Language Summary We investigated the barium cycle in the Arctic Ocean. The oceanic barium cycle is supported by the interplay of seawater mixing, river inputs, sediment inputs, and particle formation and export from the water column. We determined that the distribution of dissolved barium in the upper 500 m of the Arctic Ocean is largely set by a shelf sediment source; this is newly described, as previous literature assumed rivers and seawater mixing were the predominant contributors to the distribution. This discovery fits in with recent findings that the shelf sediments are a major source of radium and other trace metals to the surface Arctic Ocean. This is important to consider as the warming climate continues to erode Arctic ice cover (sea ice or glacial). Monitoring the relative sources of Ba to the water column can help define how warming impacts Arctic Ocean biogeochemistry.

While bacterial diversity is beneficial for the functioning of rhizosphere microbiomes, multi-species bioinoculants often fail to promote plant growth. One potential reason for this is that competition between inoculated consortia members create conflicts for their survival and functioning. To circumvent this, we used transposon mutagenesis to increase the functional diversity within Bacillus amyloliquefaciens bacterial species and tested if we could improve plant growth-promotion by assembling consortia of closely related but functionally specialized mutants. While most insertion mutations were harmful, some improved strains’ plant growth-promotion traits without increasing antagonism between them. Crucially, plant growth-promotion could be improved by applying these specialist mutants as consortia, leading to clear positive relationships between consortia richness, plant root colonization and protection from bacterial wilt disease. Together, our results suggest that increasing intra-species diversity could be an effective way to increase probiotic consortia multifunctionality, leading to more stable plant growth-promotion throughout growth cycle via insurance effects.

Transient receptor potential channel M2 (TRPM2) is a Ca2+-permeable channel that is activated by reactive oxygen species (ROS). In many cell types, ROS activate TRPM2 to induce excessive Ca2+ influx, resulting in Ca2+ overload and consequent cell death. Recent studies suggest that TRPM2 may also regulate autophagy in pericytes and cancer cells by acting on the early step of autophagy, i.e. autophagic induction. However, there is no report on the role of TRPM2 in autophagic degradation, which is the late stage of autophagy. In the present study, we found abundant TRPM2 expression in lysosomes/autolysosomes in the primary cultured mouse aortic smooth muscle cells (mASMCs). Nutrient starvation stimulated autophagic flux in mASMCs mainly by promoting autophagic degradation. This starvation-induced autophagic degradation was reduced by TRPM2 knockout. Importantly, starvation-induced lysosomal/autolysosomal acidification and cell death were also substantially reduced by TRPM2 knockout. Taken together, the present study uncovered a novel mechanism that lysosomal TRPM2 facilitates lysosomal acidification to stimulate excessive autolysosome degradation and consequent cell death.

In order to further improve the accuracy of facial expression recognition in small samples, a small sample expression recognition method based on deep learning and fusion of different models is proposed. In this method, a single CNN (convolutional neural network) model is compared, and the relatively appropriate CNN is selected by preserving probability [p] of different nodes in the dropout layer. Then, the scale-invariant feature transformation (SIFT) algorithm is used to extract features. The purpose of extracting features with SIFT is to improve the performance of small data. And then, in order to reduce the error, and avoid over fitting, all the models are carried on summary，and the model CNN-SIFT-AVG (convolutional neural network and scale-invariant feature trans-formation average) is obtained by simple average model fusion method. Finally, only a few sample data are used to train the model. The model is tested on FER2013, CK+ and JAFFE datasets. Experimental results show that this model can greatly improve the accuracy of small sample facial expression recognition, and produce excellent results in FER2013, CK+ and JAFFE datasets, with a maximum improvement of about 6% compared with other facial expression recognition methods.

Al2O3 greatly influences the formation of complex calcium ferrite, which is the main binder and iron-bearing phase in sinter. Experiments were carried out in air at 1200 °C with different amounts of Al2O3 mixed with CaO·Fe2O3 (calcium ferrite). The samples contained two phases: CaFe2O4 and Ca3.18Fe15.38Al1.34O28 (CFA). The results showed that the morphology of the complex calcium ferrite was massive (w(Al2O3) = 0 pct), columnar and plate-like (w(Al2O3) = 0.5 and 1 pct), and acicular and plate-like (w(Al2O3) = 2, 3, and 5 pct). A small amount of Al2O3 solid solution in CaFe2O4 increased the preferred orientation of the crystal. The gradual increase in Al2O3 in the sintered samples caused the complex calcium ferrite composition to be closer to that of silico-ferrite of calcium and aluminum (acicular SFCA-I). When Al2O3 dissolved into calcium ferrite, complex calcium ferrite was formed, which increased the hardness of the sample. The fracture toughness of the sample increased with increasing Al2O3 content from 0 to 2 pct, possibly due to a decrease in grain size. When the Al2O3 content exceeded 3 pct, Al2O3 dissolved into calcium ferrite and decreased the fracture toughness of the sample.

In the present work, a new kind of porous polyvinyl alcohol/sodium alginate/hydroxyapatite (PVA/SA/HA) composite hydrogels with tunable structure and mechanical properties have been fabricated by dual-crosslinking method. The morphologies, moisture content, porosity and mechanical properties of the composite hydrogels have been investigated in detail. The PVA/SA/HA hydrogels present uniform, interpenetrating porous structure. The FTIR and XRD results indicate that PVA, SA and HA could be uniformly compounded. The mechanical properties, moisture content and porosity of the samples could be controlled by changing the mass ratio of PVA/SA/HA. The optimized compression modulus (41.74 ± 7.86 kPa), moisture content (86.99 ± 0.72%) and porosity (79.98 ± 1.61%) of the composite hydrogels could be achieved

Modern society is undergoing rapid technological growth and urbanisation. Despite the positive changes, there are still vulnerable categories of the population that cannot adapt so quickly to the new realities. The ageing process in the developed countries of Europe, America and Southeast Asia raises the issue of further labour market development. In this regard, it is vital to understand the linguistic picture of a quickly ageing labour market, such as China. Drawing on Conversation Analysis, this study aims to investigate the impact of the ageing process on the labour market and identify age-related trends in communication, behaviour and attitude. The focus is on the socio-economic context. The most important finding is that in most contexts, the language behaviour of ageing labour market participants leaned on three underpinning factors: age, social status and exposure to emotional pressure. Older adults in the Chinese labour market value their informal status, accept social hierarchy, follow strict etiquette rules, tend to self-victimise, and complain about feeling vulnerable. The present findings can help social workers in China improve care for ageing adults and allow other researchers to investigate older people’s participation in the labour market.

Blockchain technology has been changing the trust system through machine endorsement and mathematical algorithms, laying a technical foundation for network identity from centralized to decentralized management. The decentralized identity with core features, such as “no need for a management center and self-managed identities” have become a key direction for the evolution of a new generation of digital identity based on blockchain. Internationally, the United States, the EU, and other countries have promoted the technological exploration and application innovation of the decentralized identity, aiming to seize the international discourse power in the digital space. This paper establishes an evaluation model of international engagement in the decentralized identity field and takes the United States as a case to analyze the current development status and international engagement of the decentralized identity from multiple dimensions. Furthermore, it proposes some suggestions for other countries to improve the international engagement in the decentralized identity field.

Bluff-body swirling flows have been widely employed in gas-turbine combustors to achieve flame stabilization. Meanwhile, considerable efforts have been made to understand swirling flow dynamics, the effects of swirl number and bluff body on flow structure and dynamics are still not well understood. To this end, a series of direct numerical simulations of isothermal swirling flows have been conducted in this work in order to investigate the impact of swirl numbers and bluff-body diameters on the flow structure, Reynolds stresses, and turbulent kinetic energy (TKE) transport. It is found that a change in the swirl number can affect the inner recirculation zone (IRZ) and hence momentum transport. Specifically, as the swirl number increases, the vortex core formed at downstream locations can merge with the IRZ. Moreover, including the bluff body not only contributes to the formation of the IRZ but also serves as a disturbance source for the flow, which is favorable for the formation of large-scale vortex structures. Then, the impact of swirl number and bluff body on Reynolds shear stresses and anisotropy invariants is investigated to identify the locations of the inter shear layer (ISL), the outer shear layer (OSL), and the main swirling zone (MSZ). The results show that as the swirl number increases, both the ISL and MSZ shift to the wall, indicating a large IRZ. Furthermore, the analysis of TKE indicates that for cases with a bluff body, TKE mainly occurs in the ISL and OSL, featuring a dual peak distribution. However, for cases without a bluff body, the distribution of TKE is primarily concentrated in the ISL. These results suggest that both increasing the swirl number and/or including the bluff body could help with TKE transport, which can lead to a wide range of TKE distribution.

This paper demonstrates the ability of the neural network trained on frequency-sweeping signals with different amplitudes to reconstruct the flame nonlinear response. The neural network architecture consists of a decreasing sequence increasing dimension model and a sequence model; the latter one uses the long short-term memory (LSTM) and encoder of Transformer. Results show that the neural network trained using the proposed sweeping method with limited training data can reconstruct realistic signals over the envisaged range of frequencies and amplitudes. The nonlinear flame responses obtained by the neural network are further embedded into the closed-loop thermoacoustic feedback to quantify the reconstruction performance of sequence signals. It is demonstrated that the neural network can accurately capture the evolution of the limit cycle. This paper has also compared the effect of different types and sizes of datasets on trained neural networks model; the results show that models trained with our proposed datasets perform better. For small-size datasets, LSTM performs significantly better than the encoder of Transformer. The encoder of Transformer is more suitable for large-size datasets.

It is of great significance for improving electron transmission performance by changing of the outer ring structure of iron phthalocyanine. Herein, 4 (pyridine-2, 3-yl) iron phthalocyanine (FepyPc), as N-rich pyridyl-iron phthalocyanine derivative, was introduced to degrade pharmaceutical contaminants. The catalytic degradation of organic pollutants with FepyPc was studied by activating peroxymonosulfate (PMS) at room temperature. The results clarified that the removal rate of carbamazepine (CBZ) was close to 100% within 60 min and the calculated apparent rate constant was about 2 times larger than FePc, which proved that FepyPc had superior performance. Four active species were identified for the degradation of CBZ, including superoxide radical (•O

It is very necessary for an intelligent heavy truck to have the ability to prevent rollover independently. However, it was rarely considered in intelligent vehicle motion planning. To improve rollover stability, a motion planning strategy with autonomous anti rollover ability for an intelligent heavy truck is put forward in this paper. Considering the influence of unsprung mass in the front axle and the rear axle and the body roll stiffness on vehicle rollover stability, a rollover dynamics model is built for the intelligent heavy truck. From the model, a novel rollover index is derived to evaluate vehicle rollover risk accurately, and a model predictive control algorithm is applicated to design the motion planning strategy for the intelligent heavy truck, which integrates the vehicle rollover stability, the artificial potential field for the obstacle avoidance, the path tracking and vehicle dynamics constrains. Then, the optimal path is obtained to meet the requirements that the intelligent heavy truck can avoid obstacles and drive stably without rollover. In addition, three typical scenarios are designed to numerically simulate the dynamic performance of the intelligent heavy truck. The results show that the proposed motion planning strategy can avoid collisions and improve vehicle rollover stability effectively even under the worst driving scenarios.

Code completion is widely used by software developers to provide coding suggestions given a partially written code snippet. Apart from the traditional code completion methods, which only support single token completion at minimal positions, recent studies show the ability to provide longer code completion at more flexible positions. However, such frequently triggered and longer completion results reduce the overall precision as they generate more invalid results. Moreover, different studies are mostly incompatible with each other. Thus, it is vital to develop an ensemble framework that can combine results from multiple models to draw merits and offset defects of each model. This paper conducts a coding simulation to collect data from code context and different code completion models and then apply the data in two tasks. First, we introduce an acceptance model which can dynamically control whether to display completion results to the developer. It uses simulation features to predict whether correct results exist in the output of these models. Our best model reduces the percentage of false-positive completion from 55.09% to 17.44%. Second, we design a fusion ranking scheme that can automatically identify the priority of the completion results and reorder the candidates from multiple code completion models. This scheme is flexible in dealing with various models, regardless of the type or the length of their completion results. We integrate this ranking scheme with two frequency models and a GPT-2 styled language model, along with the acceptance model to yield 27.80% and 37.64% increase in TOP1 and TOP5 accuracy, respectively. In addition, we propose a new code completion evaluation metric, Benefit-Cost Ratio(BCR), taking into account the benefit of keystrokes saving and hidden cost of completion list browsing, which is closer to real coder experience scenario., Comment: 10 pages, 7 figures, accepted by ICSME 2021

The bifurcation process of self-sustained combustion instability pressure perturbations in a liquid rocket combustor is investigated based on the Helmholtz equations and a pressure dependent flame describing function. The modal frequency and growth rates are numerically resolved by the commercial software COMSOL multiphysics. Validation of the numerical approach is firstly conducted on a Rijke tube combustor, and a supercritical bifurcation for the first longitudinal mode is observed. The bifurcation diagrams for the first transverse mode for different time delays and gain index of the flame describing function are analyzed. Only the supercritical bifurcation presents for this configuration. The trajectory of Hopf points and the bifurcation diagram feature period motions with increasing the time delay. The effect of flame length distributions on the bifurcation diagrams is analyzed by considering a non-uniform flame length distribution model. Results show that the distribution has a large impact on the bifurcation process, e.g., the first transverse mode is more unstable for the non-uniform distribution. Finally, a subcritical bifurcation is found when a more complicated flame describing function is considered; the bistable region presents and the condition for this is discussed.

Summary Solid electrolytes, as a promising replacement for the flammable liquid electrolyte in conventional Li-ion batteries, may greatly alleviate the safety issues and improve the energy density. However, mainstream electrodes are also solid. If solid electrolytes were employed, creating intimate electrode-electrolyte contact similar to that between solid and liquid would be quite difficult. Here we discovered that, by forming epitaxial interfaces, such a seamless solid-solid contact can happen between two widely studied systems: the Li-rich layered electrode and perovskite solid electrolyte. Atomic-resolution electron microscopy unambiguously demonstrated that the former can be epitaxially embedded into the latter. The solid-solid composite electrode formed this way exhibited a rate capability no lower than the one based on solid-liquid contact. With the periodic misfit dislocations reconciling structural differences, such epitaxy can tolerate large lattice mismatch, and thus may occur between many layered electrodes and perovskite solid electrolytes.

Vehicle rollover, and its resulting fatalities, is an actively researched topic especially for multi-axle vehicles in the field of vehicle dynamics and control. This paper first presents a new rollover index for a triaxle bus to accurately evaluate its rollover possibility and then discusses the influence laws of the vehicle rollover dynamics to explore the mechanism of its stability. First, a six degree of freedom rollover model of the triaxle bus is developed, including lateral, yaw, roll motion of the sprung mass of the front/rear axle, and roll motion of the unsprung mass of the front/rear axle. Next, some key parameters of the vehicle rollover model are identified. A new rollover index is deduced according to the basics of vehicle dynamics, to predict vehicle rollover risk for the triaxle bus, which is verified by TruckSim. Furthermore, the influence laws of vehicle rollover dynamics by vehicle parameters and road parameters are discussed based on the simulation results. More importantly, the results show that the new method of modeling can precisely describe the rollover dynamics of the studied bus, and the proposed new index can effectively evaluate the rollover possibility. Therefore, this study provides a theoretical basis to improve anti-rollover ability for triaxle buses.

Muscle growth and fat deposition are the two important biological processes in the development of pigs which are closely related to the pig production performance. Long intergenic noncoding RNAs (lincRNAs), with lack of coding potential and the length of at least 200nt, have been extensively studied to play important roles in many biological processes. However, the importance and molecular regulation mechanism of lincRNAs in the process of muscle growth and fat deposition in pigs are still to be further studied comprehensively. In our study, we used the data, including liver, abdominal fat, and longissimus dorsi muscle of 240 days’ age of two F2 full-sib female individuals from the white Duroc and Erhualian crossbreed, to identify 581 putative lincRNAs associated with pig muscle growth and fat deposition. The 581 putative lincRNAs shared many common features with other mammalian lincRNAs, such as fewer exons, lower expression levels, and shorter transcript lengths. Cross-tissue comparisons showed that many transcripts were tissue-specific and were involved in the important biological processes in their corresponding tissues. Gene ontology and pathway analysis revealed that many potential target genes (PTGs) of putative lincRNAs were involved in pig muscle growth and fat deposition-related processes, including muscle cell proliferation, lipid metabolism, and fatty acid degradation. In Quantitative Trait Locus (QTLs) analysis, some PTGs were screened from putative lincRNAs, MRPL12 is associated with muscle growth, GCGR and SLC25A10 were associated with fat deposition, and PPP3CA, DPYD, and FGGY were related not only to muscle growth but also to fat deposition. Therefore, it implied that these lincRNAs might participate in the biological processes related to muscle growth or fat deposition through homeostatic regulation of PTGs, but the detailed molecular regulatory mechanisms still needed to be further explored. This study lays the molecular foundation for the in-depth study of the role of lincRNAs in the pig muscle growth and fat deposition and further provides the new molecular markers for understanding the complex biological mechanisms of pig muscle growth and fat deposition.

Robots manipulating in domestic environments generally need to interact with articulated objects, such as doors, drawers, laptops and swivel chairs. The rigid bodies that make up these objects are connected by a revolute pair or a prismatic pair. Robots are expected to learn and understand the objects' articulated constraints with a simple interaction method. In this way, the autonomy of robot manipulation will be greatly improved in an environment with unstructured constraints. In this paper, a method is proposed to obtain the articulated objects' constraint model by learning from a one-shot continuous visual demonstration which contains multistep movements, and this enables human teacher to continuously demonstrate several tasks at once without manual segmentation. At the end of this paper, a six-degree-of-freedom robot uses the constraint model obtained by demonstration learning to achieve manipulation planning of various tasks based on the AG-CBiRRT algorithm.