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AbstractAccurately predicting the next track point of vehicle travel is crucial for various Intelligent Transportation System (ITS) applications, such as travel behavior studies, traffic control, and traffic congestion monitoring. Recent works on trajectory prediction follow a paradigm that first represents the raw trajectory and subsequently makes predictions based on that representation. Currently, trajectory representation methods tend to project trajectory points to road networks by map matching and represent trajectories based on the representation of matched roads. However, precisely matching trajectories to roads is a challenge in ITS, as the matching precision is greatly affected by the quality of the trajectory. Meanwhile, since it is difficult to discern whether trajectory matching results are accurate or confounded, how to effectively utilize this type of uncertain geographic context information is also a challenge, which is defined as the Uncertain Geographic Context Problem (UGCoP) in geographic information science. Therefore, we propose a flexible strategy of subgraph learning, referred to as SLM, for predicting the next track point of vehicles. Specifically, a subgraph generation module is first proposed to extract topology contextual information of the roads around historical trajectory points. Secondly, a subgraph learning module is designed to learn rich spatial and temporal features from generated subgraphs. Finally, the extracted spatiotemporal features will be fed into a prediction module to predict the next track points of vehicles on road networks. Our model enables the effective utilization of uncertain geographic context information of trajectories on road networks while avoiding the error brought by map matching. Extensive experiments based on trajectory datasets in two different cities confirm the effectiveness of our approach. [ABSTRACT FROM AUTHOR]

Similarity of point patterns is critical to geographic information retrieval. Many methods depend on measuring the similarity between point patterns within the spatial database. However, previous researches mainly focus on point density which is only one aspect of point patterns. A point distribution can be complex by its numerous alignments of point groups, which usually imply different geographical meanings in reality. In this paper, we propose a new method that uses image analysis techniques to comprehensively consider the characteristics of a point pattern. Specifically, given a set of point datasets falling in the same region, our method first generates the point intensity surfaces to transform the original vector space to raster space; then, the method constructs a matrix to describe all the pattern-related information. Finally, the point pattern similarity is calculated by decomposing this matrix into the lower-order representation and the factorized basis features. Due to the use of matrix decomposition, the proposed method has the merits that it can eliminate noises from the original data and assess the similarity of two patterns with emphasis on their major features. As a case study, our method is effective in discovering regularity from the taxi pick-up/drop-off point datasets. [ABSTRACT FROM AUTHOR]

As one of the classic tasks in information retrieval, the core of image retrieval is to identify the images sharing similar features with a query image, aiming to enable users to find the required information from a large number of images conveniently. Street view image retrieval, in particular, finds extensive applications in many fields, such as improvements to navigation and mapping services, formulation of urban development planning scheme, and analysis of historical evolution of buildings. However, the intricate foreground and background details in street view images, coupled with a lack of attribute annotations, render it among the most challenging issues in practical applications. Current image retrieval research mainly uses the visual model that is completely dependent on the image visual features, and the multimodal learning model that necessitates additional data sources (e.g., annotated text). Yet, creating annotated datasets is expensive, and street view images, which contain a large amount of scene texts themselves, are often unannotated. Therefore, this paper proposes a deep unsupervised learning algorithm that combines visual and text features from image data for improving the accuracy of street view image retrieval. Specifically, we employ text detection algorithms to identify scene text, utilize the Pyramidal Histogram of Characters encoding predictor model to extract text information from images, deploy deep convolutional neural networks for visual feature extraction, and incorporate a contrastive learning module for image retrieval. Upon testing across three street view image datasets, the results demonstrate that our model holds certain advantages over the state‐of‐the‐art multimodal models pre‐trained on extensive datasets, characterized by fewer parameters and lower floating point operations. Code and data are available at https://github.com/nwuSY/svtRetrieval. [ABSTRACT FROM AUTHOR]

In order to facilitate the optimization of the casting process for the large-scaled complex titanium alloy casting (LCTAC), a quantification and statistical analysis method for the LCTAC was developed to elucidate the distribution characteristics of microstructure and mechanical properties throughout the entire casting. The homogeneity coefficient was employed to investigate the relationships between casting structural features and the homogeneity of microstructure-properties. The findings indicate a skewed distribution of grain size in the whole casting, with a notable linear positive correlation between grain size distribution characteristics and wall thickness. Correspondingly, a mere 90% reduction in wall thickness leads to more than a 10% increase in strength or hardness. Furthermore, a comparative analysis revealed that the microstructure homogeneity coefficient for wall thickness exhibited a significant influence of over 50% compared to the homogeneity attributed to wall position, suggesting that wall thickness exerts a more pronounced impact on the homogeneity of LCTAC. [ABSTRACT FROM AUTHOR]

Travel activity data mining is critical to numerous urban applications such as transportation and location‐based services. This article studies the spatial units ranking algorithm for uncovering spatial interaction patterns based on the flow properties of people's travel trajectories. For example, using a taxi origin–destination flow database, a user may want to rank the origin and destination with respect to their functional importance within the urban activity space. In the literature, such an importance concept is usually specified via the frequency function of trip flows. Considering the case that the less frequently visited place in reality may still be an important origin or an important destination, we propose a different method for the ranking of spatial units by introducing the structural property of trip network. The proposed method is inspired from the mutual reinforcing relationship between the trip origins and destinations: important destinations attract travel flows from important origins and at the same time important origins have many flows toward important destinations. Our experimental results show that the proposed method is effective in uncovering spatial interaction patterns of urban activities. [ABSTRACT FROM AUTHOR]

Background Objectives Methods Results and Conclusions Implications Although gender inequality in education is gaining increasing attention, female underrepresentation remains pervasive in STEM fields. Many studies have applied various interventions to narrow the gender gap in STEM education.In this study, we conducted a systematic meta‐analysis to examine the effectiveness of various interventions for gender equality in STEM education and tested the influence of moderator variables.Ten databases—ERIC, IEEE, JSTOR, ProQuest‐Education, SAGE Journals, Scopus, Springer Link, Taylor & Francis, Web of Science, and Wiley Online Library—and seven high‐quality journals in related fields were selected as literature resources. The Preferred Reporting Items for Systematic Reviews and Meta‐analyses (PRISMA) process was used to identify eligible articles for the random‐effects meta‐analysis.The overall effect size (Hedges' g) was 0.434, indicating that the interventions promoting gender equality in STEM education had a near‐medium positive effect. There were significant differences by the type of intervention, but not by the type of intervention outcome. The results of the moderator analysis showed a significant difference in moderator variables, including country, educational level, form of experiment, intervention level, and different measurement methods, whereas there was no significant difference in the moderator variables, including economic development level and sample size.This study examined the effectiveness of gender equality interventions and the impact on it of different types of intervention, intervention outcomes, and moderator variables. These results have implications for the design of gender equality interventions in STEM education. [ABSTRACT FROM AUTHOR]

The application of information technology is ubiquitous in our work and learning, and information technology causes tremendous changes to workplace learning. This systematic review aims to summarize the roles and impacts of information technology on workplace learning. This study is guided by the following three research questions: What are the characteristics and trends of the existing research on information technology in workplace learning(RQ1)? What roles does information technology play in workplace learning(RQ2)? What changes and impacts have information technology brought to workplace learning(RQ3)? We identified 60 eligible articles using the guidelines of the PRISMA procedures. To respond to RQ1, the descriptive analysis of the eligible literature has been delineated. To respond to RQ2, we conducted an in‐depth content analysis, and the roles of information technology were classified into four categories: at the organizational level, exploitative learning and explorative learning and at the individual level, learning resources and learning support. To respond to RQ3, the impacts of information technology were analyzed from both the positive and negative effects at the individual and organizational levels. Finally, we proposed an integrated framework of information technology on workplace learning. Practitioner Points: Explorative learning is higher‐order organizational learning based on exploitative learning at the organizational level, and learning resources and learning support should be matched to synergistically promote the process of workplace learning at the individual level.These aspects of impact in this study provided referencing guidelines for practitioners when applying information technology in workplace learning.The proposed framework which integrated the roles, main changes, impacts, drivers, and barriers showed the whole process of applying information technology in the context of workplace learning, which provided implications for the practice in this field. [ABSTRACT FROM AUTHOR]

Background: This study aimed to create a nomogram for predicting the recurrence of small bowel obstruction (SBO) after gastrectomy in patients with gastric cancer (GC) in order to provide better guidance for its diagnosis and treatment. Methods: A total of 173 patients undergone gastrectomy and developed SBO from January 2015 to October 2022 were admitted into this case–control study. The risk factors of postoperative recurrent SBO were analyzed by univariate and multivariate regression, and a nomogram for predicting the recurrent SBO after gastrectomy was developed using R Studio. Results: Thirty-nine cases of postoperative recurrent SBO occurred among the 173 GC patients who underwent radical gastrectomy, and the percentage of recurrent SBO was 22.54% (39/173). Age [odds ratio (OR) = 0.938, p = 0.026], WBC count (OR = 1.547, p < 0.001), tumor size (OR = 1.383, p = 0.024), postoperative metastasis (OR = 11.792, p = 0.030), and the interval from gastrectomy to first SBO (OR = 1.057, p < 0.001) were all identified as independent risk factors for postoperative recurrent SBO by logistic regression analysis. The receiver operating characteristic curve, the calibration curve, the model consistency index, and the decision curve analysis showed that the nomogram had good predictive performance. Conclusion: Based on these factors, we created a nomogram to predict the occurrence of postoperative recurrent SBO. This novel nomogram could serve as a crucial early warning indicator that would guide doctors to make informed decisions while managing patients with gastric cancer. [ABSTRACT FROM AUTHOR]

Learning in the workplace is among the most important forms of lifelong learning. This is because the workplace provides an authentic context for meaningful learning. Expansive learning, proposed by Engeström, focuses on learners as a community, the transformation of culture, and the creation of a new theoretical concept. Expansive learning eventually leads to a transformation in collective expertise. The primary aim of the study was to examine the dimensions of expansive learning and their relationships in the workplace. The cases selected were three Chinese consulting firms that focus on professional learning or talent training and development. I used multiple methods for data collection (e.g., semistructured interviews, observation, and document analysis). The successive analytical induction procedure was based on the constant comparison principle of grounded theory, and the four dimensions of expansive learning (distribution, collectiveness, routine, and expansiveness) emerged and were scrutinized. Based on the principle of activity theory, I constructed and integrated an interactive dynamic process model of expansive learning with its related dimensions. Practitioner points: This study identifies the four dimensions of expansive learning, investigating expansive learning based on various dimensions in workplace practice.The distribution and collectiveness of expansive learning create social interactions in time and space, which determine the boundaries of the zone of proximal development.The tension between routine and expansiveness will be transformed into the tension between distribution and collectiveness, and these two tensions constitute the dynamic relationships among these dimensions. [ABSTRACT FROM AUTHOR]

This retrospective cohort study aimed to assess the effect of chromosomal reciprocal translocation on meiotic segregation products of non-translocation chromosomes. A total of 744 reciprocal translocation carriers and 875 non-carriers were included in this study. A total of 6,832 blastocysts were biopsied and tested by next-generation sequencing. Blastocysts from the carrier group were classified into five subgroups according to the theoretical segregation pattern of quadrivalent structure. For carrier patients, normal meiotic segregation products of the non-translocation chromosome were classified after excluding the segregation modes of the quadrivalent structure. The proportion of normal non-translocation chromosome meiotic segregation products was similar between the carrier and noncarrier groups (p = 0.69). The generalized Estimation Equation revealed that there was no correlation between reciprocal translocation and meiotic segregation products of non-translocation chromosomes. Moreover, subgroup analyses showed that the segregation modes of quadrivalent structure (p = 0.00) and carrier's gender (p = 0.00) may affect the meiotic segregation products of non-translocation chromosomes. In conclusion, reciprocal translocation does not directly reduce the proportion of normal segregation products of non-translocation chromosomes. The difference among subgroups of different quadrivalent segregation patterns implied that interchromosomal effect may exist but the high incidence of chromosomal abnormalities for reciprocal translocation carriers should not be attributed to interchromosomal effect. [ABSTRACT FROM AUTHOR]

Traffic prediction is an important part of smart city projects. Due to the complex topology of urban road network and the dynamic change of traffic data, establishing a spatio-temporal model to accurately predict traffic volume remains a challenging task at present. Recently, Graph Convolution Networks (GCN) have been widely used to extract features from non-grid data, and time sequence models have been used to learn temporal features of traffic distributions. However, current GCN based methods only make use of the natural structure of road network, while ignoring the information of administrative units, neighborhood units and other hierarchical structures of spatial interaction. Therefore, traditional models are typically developed under one single scale, which are far from the prediction of multi-scale systems. To address this issue, we propose a novel framework, named MmgFra, to merge multi-scale information for high-precision urban traffic flow prediction. MmgFra consists of three components: a spatial feature extraction module, a feature clustering fusion module, and a temporal feature extraction module. Specifically, we use stacking GCNs to extract spatial structure information of the city road network, administrative unit road network, and neighborhood units, and employ a DIFFPOOL module to cluster and fuse the above information. Finally, we introduce GRU to capture temporal features. We evaluated its performance on a real city dataset using different time scales. The experimental results indicate that compared with state-of-the-art neural network models and GCN-based variant models, our model exhibits higher predictive accuracy. MmgFra improves by approximately 8.4%-29.5% and 7.5%-30.6% in terms of RMSE and MAPE metrics, respectively. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) is one of the four most common cancers in the world. At present, human beings have stepped into an aging society, and the number of over eighties colorectal cancer patients has increased year by year. However, few high-quality studies focused on the post-operation complications and long-term outcomes of octogenarian patients with colorectal cancer. This meta-analysis, based on published studies, aims to assess the safety of treating octogenarian CRC patients with surgery. Methods: Databases, including PubMed, Embase, and Cochrane Library were searched until July 2022. The incidence of preoperative comorbidities, postoperative complications, and mortality was assessed using odds ratios (ORs) with corresponding 95% confidence intervals (CIs). Furthermore, the hazard ratios (HRs) with 95% CIs were applied for survival outcomes. Results: A total of 13,790 patients with CRC in 21 studies were included. Our results demonstrated that octogenarian patients were associated with a higher burden of comorbidities (OR = 3.03; 95% CI: 2.03, 4.53; P =.000), high incidences of overall postoperative complications (OR = 1.63; 95% CI: 1.29, 2.06; P =.000), high internal medicine postoperative complications (OR = 2.38; 95% CI: 1.76, 3.21; P =.000), high in-hospital mortality (OR = 4.01; 95% CI: 3.06, 5.27; P =.000) and poor overall survival (OR = 2.13; 95% CI: 1.78, 2.55; P =.000). But there is no statistical difference in surgery-related postoperative complications(OR = 1.16; 95% CI: 0.94, 1.43; P =.16) and DFS (OR = 1.03; 95% CI: 0.83, 1.29; P =.775). Conclusions: Extremely elderly patients with colorectal cancer have the high burden of comorbidities, high postoperative complications and mortality. However, survival outcomes (DFS) in patients 80 years and older are similar to younger patients. Clinicians should administer individualized treatment for such patients. Physiologic age rather than chronological age should determine cancer management for each individual. [ABSTRACT FROM AUTHOR]

Road network matching that detects arc-to-arc relations is a crucial prerequisite for the update of road data. The increasing complexity of multi-source and multi-scale road network data challenges the existing methods on accuracy and efficiency. This paper focuses on the interactive-based probabilistic relaxation approach. It is difficult to obtain satisfactory results by using completely automatic matching algorithm in some complicated road networks such as multi-lane carriageways. We try to improve the matching accuracy by combining optimization matching model with manual interaction. The method uses the module of active learning to construct unlabeled sample pool from preliminary matching of probabilistic relaxation, and then selects the arcs with the highest uncertainty by query function. The selected road is then handed over to humans to determine its arc-to-arc relations in the other road network. Finally, the matching parameters are automatically adjusted according to the user's feedback information, so as to realize the dynamic optimization of the model. Our interaction method is efficient as it only needs to specify few arc-to-arc mappings and others can be amended automatically. Our experimental results reveal that active learning can substantially improve the performance of standard probabilistic relaxation algorithms in road network matching. [ABSTRACT FROM AUTHOR]

This study was to determine whether multiple vitrification-warming procedures and insemination method are associated with pregnancy and neonatal outcomes in preimplantation genetic testing for aneuploidy (PGT-A). This was a retrospective, single-center, observational study of 112 patients who underwent standard PGT-A practice and 154 patients who desired PGT-A for their vitrified unbiopsied blastocysts. A total of 97 euploid blastocysts biopsied and vitrified-warmed once and 117 euploid blastocysts biopsied once but vitrified-warmed twice (83 in vitro fertilization [IVF]–derived and 34 intracytoplasmic sperm injection [ICSI]–derived euploid blastocysts) were transferred. The primary outcome was the blastocyst survival rate for transfer, live birth rate, and neonatal outcomes. The results showed that an additional vitrification-warming procedure on blastocysts resulted in a lower but not statistically different survival rate for transfer. Compared with euploid blastocysts vitrified-warmed once, those vitrified-warmed twice provided statistically similar live birth rate. Neonatal outcomes, including the sex ratio, gestational age, birthweight, preterm birth rate, and low birthweight rate, did not differ between single and double vitrification. No significant differences were observed in rates of blastocyst survival, blastocyst euploid and live birth, and neonatal outcomes resulting from either conventional IVF or ICSI. The neonatal follow-up of babies live-born so far did not report any congenital malformations. In conclusion, an additional vitrification-warming on blastocysts had no detectable adverse impact on clinical outcomes after frozen-thawed single euploid blastocyst transfer in PGT-A cases; and ICSI did not confer any benefit in improving clinical outcomes compared with conventional IVF in cases requiring PGT-A on already vitrified nonbiopsied blastocysts. [ABSTRACT FROM AUTHOR]

[Display omitted] • Spray pyrolysis is used for lead-acid battery recycling for the first time. • Low-impurity PbO@C is prepared from the recovered lead acetate solution. • Recovered PbO@C shows better electrochemical performance than commercial PbO. • Computational fluid dynamics (CFD) is used for study of spray pyrolysis mechanisms. • The cell made from PbO@C runs 295 charging/discharging cycles (100%DOD). A one-step spray pyrolysis process is investigated for the first time in the field of spent lead-acid batteries (LABs) recycling. The spent lead paste that derived from spent LAB is desulfurized and then leached to generate the lead acetate (Pb(Ac) 2) solution, which is then sprayed directly into a tube furnace to prepare the lead oxide (PbO) product by pyrolysis. The low-impurity lead oxide product (9 mg/kg Fe and 1 mg/kg Ba) is obtained under the optimized conditions (the temperature of 700 °C, the pumping rate of 50 L/h, and the spray rate of 0.5 mL/min). The major crystalline phases of the synthesized products are identified to be α-PbO and β-PbO. In the spray pyrolysis process, Pb(Ac) 2 droplets are sequentially transformed into various intermediate products: H 2 O(g)@Pb(Ac) 2 solution, Pb(Ac) 2 crystals@PbO, and the final PbO@C product. Owning its carbon skeleton structure, the recovered PbO@C product (carbon content of 0.14%) shows better performance than the commercial ball-milled lead oxide powder in battery tests, with higher initial capacity and better cycling stability. This study could provide a strategy for the short-route recovery of spent LABs. [ABSTRACT FROM AUTHOR]

The addition of aluminum particles in composite propellants has a positive effect on the performance of solid rocket motor, while it also brings some changes in the ignition behaviors. To clarify the ignition process and performance of aluminized propellants, a visualization experimental system was built. It is found that the ignition process of aluminized propellants mainly includes heating and melting of the solid phase, evaporation, mixing and ignition of decomposed gas. Besides, few aluminum particles agglomerate together and they are not ignited during the ignition process of propellants. According to the process of ignition, the ignition delay time can be described as the sum of pyrolysis time, mixing time and chemical reaction time. After the propellants is ignited and the stable flame is formed, the aluminum particles on the burning surface mainly undergo exposure – accumulation – fusion – separation – ignition – combustion. And the structure of the agglomerate transitions from a coral-like to an oxidized cap. At the same time, the ignition of agglomerated products occurs in the stable flame. With the increase of aluminum content and initial aluminum particle size, the ignition delay time also increases, but the proportion of these three times in the ignition delay is not very much related to the formulation of propellants. With the increase of power density of ignition, the ignition delay time decreased markedly, but the decreasing trends continuously became more gradual and eventually flattened out. As the power density of ignition increases, the percentage of pyrolysis time in the ignition delay time decreases rapidly and gradually stabilizes, while the percentage of mixing time gradually increases and the chemical reaction time does not change much. A sufficiently large and reasonable ignition energy power can reduce the ignition delay time and also reduce the impact of the differences between formulations on ignition performance. • The full ignition process of composite propellants with aluminum particles was revealed. • The ignition moment of aluminum particles during the combustion of propellants was analyzed. • The effect of aluminum particle characteristics on the ignition delay time and each fraction time was studied. [ABSTRACT FROM AUTHOR]

It is significant to develop catalysts with high‐density and adjacent frustrated Lewis pair (FLP) sites. Herein, a method is designed to construct FLPs on an intermetallic alloy (IMA) with regulable acidity and basicity by using the Mott–Schottky effect. By dint of the high‐density FLP site and suitable acidity and basicity on IMA, the fct‐PtCo@NC displays excellent hydrogen evolution reaction performance. The catalyst fct‐PtCo@NC, with high‐density FLP sites, exhibits a fast water adsorption and decomposition rate, which is derived from the synergistic effect of FLP‐acid sites and FLP‐base sites significantly reducing the energy barrier between the two processes. Due to the FLP‐base Pt site, fct‐PtCo@NC has the best binding energy of hydrogen intermediates, the H3O+ generated during the reaction can accumulate on it and form an acid‐like environment, and thus speed up the kinetics of the reaction. In comparison, the catalyst without FLP shows lower binding energy and the formation of H3O+ is not observed. This work opens a new horizon for the design of new‐style heterogeneous FLP catalysts and the catalysts with high‐density and adjacent FLP sites are expected to be used in a variety of multistep catalytic reactions. [ABSTRACT FROM AUTHOR]

Ferroelectric resistive switching (RS) devices with functional oxide electrodes allow controlled emergent phenomena at an interface. Here, we demonstrate RS polarity reversal due to ferroelectrically induced phase transition at a doped charge transfer insulator interface. For BiFeO3/Ca0.96Ce0.04MnO3 bilayers grown on a NdAlO3 substrate, by applying voltages to a Ca0.96Ce0.04MnO3 bottom electrode, the resistance changes from a high resistance state (HRS) to a low resistance state (LRS) during a positive voltage cycle (0 → 3 → 0 V), and from a LRS to a HRS during a negative voltage cycle (0 → −3 → 0 V). The RS polarity is completely opposite the expected RS behavior in ferroelectric heterostructures induced by polarization reversal. It is proposed that the unique resistance switching polarity is attributed to the band-filling controlled metal-insulator transition in a Ca0.96Ce0.04MnO3 film, triggered by ferroelectric based electrostatic doping. The results address the importance of ferroelectric field effect on the electronic properties of the interfacial system in ferroelectric/complex oxide-based resistive memory devices. [ABSTRACT FROM AUTHOR]

Geospatial studies must address spatial data quality, especially in data-driven research. An essential concern is how to fill spatial data gaps (missing data), such as for cartographic polylines. Recent advances in deep learning have shown promise in filling holes in images with semantically plausible and context-aware details. In this paper, we propose an effective framework for vector-structured polyline completion using a generative model. The model is trained to generate the contents of missing polylines of different sizes and shapes conditioned on the contexts. Specifically, the generator can compute the content of the entire polyline sample globally and produce a plausible prediction for local gaps. The proposed model was applied to contour data for validation. The experiments generated gaps of random sizes at random locations along with the polyline samples. Qualitative and quantitative evaluations show that our model can fill missing points with high perceptual quality and adaptively handle a range of gaps. In addition to the simulation experiment, two case studies with map vectorization and trajectory filling illustrate the application prospects of our model. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid expansion of urban space and the explosion of population within communities in China, fire stations face challenges in providing timely response to potential demands throughout their service coverage. To ensure speedy and equitable provision of fire services, it is essential to evaluate the accessibility of fire stations under the current fire service systems. Traditional accessibility analysis is often based on the aggregated large areal units, such as the census tracks, failing to assess accessibility of individual buildings. In this regard, this study seeks to analyze potential accessibility to urban fire stations at a fine scale, i.e., the building level, and to provide valuable information to assist in strategic planning of fire stations in urban areas and within local communities. Because the detailed intra-community roads are not stored in the official city map database, we propose to use a classic GIS technology, the Delaunay triangulation model, to automatically extract the intra-community roads from building footprints. With these private roads integrated into the existing city roads, a simulated road network is constructed. Then, the Voronoi-based method and buffering method are used to assess accessibility to urban fire stations. Results reveal that the current layout of fire stations in the study area is not sufficient to achieve a complete coverage of potential demands in the stipulated time, and the traditional central areas enjoy better access to fire services compared to the periphery areas. The building-level analyses will not only enable decision-makers to strategically allocate new fire stations in the urban areas, but also help local authorities to enhance fire safety management within the community. The proposed method can also be applied to fine-scale analysis of neighborhood services' accessibility in other cities. [ABSTRACT FROM AUTHOR]

Objective: Smoking and obesity are established risk factors of dyslipidemia, however, the interplay between them has not been well studied. This study aims to explore the joint effect of smoking and body mass index (BMI) on serum lipid profiles. Methods: The study consisted of 9846 Chinese adults (mean age = 49.9 years, 47.6% males, 31.2% ever smokers), based on the China Health and Nutrition Survey. Serum lipid profiles included total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (APO-A), and apolipoprotein B (Apo-B). The joint effect of smoking and BMI on serum lipids were examined by the four-way decomposition analysis and multivariate linear regression models. Results: The four-way decomposition showed that the interplay between smoking and BMI was complicated. There was only indirect effect (the mediated effect) between smoking and BMI on TC, LDL-C and APO-B. The pure indirect effect was -0.023 for TC, -0.018 for LDL-C, and -0.009 for APO-B. For TG, HDL-C and APO-A, the interaction effect was dominant. The reference interaction (the interactive effect when the mediator is left to what it would be in the absence of exposure) was 0.474 (P < 0.001) for TG, -0.245 (P = 0.002) for HDL-C, and -0.222 (P < 0.001) for APO-A, respectively. The effect of BMI on TG, HDL-C and APO-A were significantly higher in smokers than in nonsmokers (TG: 0.151 in smokers versus 0.097 in nonsmokers, HDL-C: -0.037 versus -0.027, APO-A: -0.019 versus -0.009, P for difference < 0.001 for all). Conclusion: These findings illustrate the joint effects of smoking and BMI on serum lipid profiles. There were significant interaction effects of smoking and BMI on TG, HDL-C and APO-A, while BMI maybe a mediator for the association of smoking with TC, LDL-C and APO-B. The effects between them were rather complex. Smoking cessation is necessary, especially for those overweight. [ABSTRACT FROM AUTHOR]

Automatic simplification of polylines is an important issue in spatial database and mapping. Traditional rule‐based methods are usually limited in performance, especially when the man‐made rules have to be adapted to different polylines with different shapes and structures. Compared to the existing neural network methods focusing only on the output layer or the code layers for classification or regression, our proposed method generates multi‐level abstractions of polylines by extracting features from multiple hidden layers. Specifically, we first organize the cartographic polylines into the form of feature vectors acceptable to the neural network model. Then, a stacked autoencoder‐based deep neural network model is trained to learn the pattern features of polyline bends and omit unimportant details layer by layer. Finally, the multi‐level abstractions of input polylines are generated from different hidden layers of a single model. The experimental results demonstrate that, compared with the classic Douglas–Peucker and Wang and Muller algorithms, the proposed method is able to properly simplify the polylines while representing their essential shapes smoothly and reducing areal displacement. [ABSTRACT FROM AUTHOR]

Traditional feature-based classification methods require objects to have the explicit, independent, and identifiable set of features, while most geo-referenced objects do not have the explicit features required by classifiers. Therefore, developing classificatory features under geospatial context is a prerequisite for effective spatial classification. Considering the spatial dependency, objects are correlated with each other, and for the object of interest its features (e.g., the distribution of neighboring objects) exist in a wide range of neighboring areas. However, the uncertainty of neighborhood size makes the dimensionality of potential feature set particularly high for spatial classification. Therefore, we propose a new model to automatically select a subset of spatially explicit features through continuous decision making by multiple agents in reinforcement learning (RL). A novel reward mechanism is developed to feed the knowledge of the downstream classification task back to the loop of feature selection. Through extensive experiments with facility points-of-interest datasets, we demonstrate that the subset of classificatory features selected by our RL model can help significantly improve the accuracy of spatial classification. Moreover, our feature selection has potential explainability for the spatial classification rules as it can determine the neighboring areas which have an impact on the classification result. [ABSTRACT FROM AUTHOR]

Both E. multilocularis and host-derived exosomes are involved in the pathogenic process of alveolar echinococcosis (AE). Exosomes secrete miRNAs that have regulatory roles in host-pathogen interactions in multiple ways. In the present study, we collected and purified supernatants of E. multilocularis cultures, as well as human plasma exosomes. High-throughput sequencing showed the identities of 45 exosomal miRNAs in E. multilocularis. The lengths of these miRNAs ranged from 19 to 25 nucleotides (nt), with the majority (n = 18) measuring 22 nt. Notably, emu-let-7-5p emerged as the most abundant among these miRNAs, with a detected count of 33,097 and also length of 22 nt. Nanoparticle tracking analysis (NTA) showed that the concentration of exosomes in the plasma of AE patients was lower compared to that in the healthy individuals. This result suggested that the concentration of plasma exosomes was able to distinguish AE patients from healthy individuals. Using qRT-PCR to assess the relative expression of 10 miRNAs of E. multilocularis , we showed that the expression of miR-184-3p was downregulated significantly in the exosomes of plasma from AE patients compared to that in the control group. In summary, this study indicates that AE induces a reduction in the concentration of human plasma exosomes, as well as downregulating miR-184-3p in infected individuals. [Display omitted] • High-throughput sequencing identified 45 exosomal miRNAs in E. multilocularis. • Exosome levels are lower in Alveolar echinococcosis patients than in healthy controls. • Alveolar echinococcosis reduces miR-184-3p expression in human plasma exosomes. [ABSTRACT FROM AUTHOR]

Neural networks (NNs) have demonstrated the potential to recover finer textural details from lower-resolution images by superresolution (SR). Given similar grid-based data structures, some researchers have transferred image SR methods to digital elevation models (DEMs). These efforts have yielded better results than traditional spatial interpolation methods. However, terrain data present inherently different characteristics and practical meanings compared with natural images. This makes it unsuitable for existing SR methods on perceptually visual features of images to be directly adopted for extracting terrain features. In this paper, we argue that the problem lies in the lack of explicit terrain feature modeling and thus propose a terrain feature-aware superresolution model (TfaSR) to guide DEM SR towards the extraction and optimization of terrain features. Specifically, a deep residual module and a deformable convolution module are integrated to extract deep and adaptive terrain features, respectively. In addition, explicit terrain feature-aware optimization is proposed to focus on local terrain feature refinement during training. Extensive experiments show that TfaSR achieves state-of-the-art performance in terrain feature preservation during DEM SR. Specifically, compared with the traditional bicubic interpolation method and existing neural network methods (SRGAN, SRResNet, and SRCNN), the RMSE of our results is improved by 1.1% to 23.8% when recovering the DEM from 120 m to 30 m, by 4.9% to 22.7% when recovering the DEM from 60 m to 30 m, and by 7.8% to 53.7% when recovering the DEM from 30 m to 10 m. The source code that has been developed is shared on Figshare (https://doi.org/10.6084/m9.figshare.19597201). [ABSTRACT FROM AUTHOR]

Developing high‐performance Pt‐based catalysts with strong metal‐support interaction (SMSI) is significant for hydrogen production by water electrolysis working at high current density conditions, but still challenging. Herein, Pt/X‐NCNT (X = 4, 8, 12, 16) with SMSI is designed and developed by combining the advantages of Platinum‐based catalysts and nitrogen‐doped carbon material. In‐situ and ex‐situ experiments and density functional theory simulations illustrate that the Gibbs free energies (ΔG) of reaction intermediates (H2O*, OH*, H*) are optimized by the synergistic effect of various N functional groups and Pt under SMSI. The Pt/8‐NCNT only needs overpotentials of 17, 107, and 153 mV to reach current densities of 10, 500, and 1000 mA cm−2. Concurrently, the Pt/8‐NCNT exhibits brilliant stability after 100 h current–time (i–t) tests at 500 mA cm−2. More importantly, this work demonstrates the function of pyrrolic‐N and pyridinic‐N in the reaction, and provides new ideas for the design of advanced SMSI electrocatalysts for various electrochemical and catalytic applications. [ABSTRACT FROM AUTHOR]

Previous research has tended to use a global threshold of proximity to determine neighbors, neglecting spatial heterogeneity. Flexible thresholds implemented by adaptive search radii methods account for either the spatial structures or the non-spatial similarities of objects, but few consider both. By combining the spatial and non-spatial information of objects, we propose a novel approach that can automatically determine the neighbors that are strongly related to the object of interest. We introduce the sparse reconstruction technique from the signal processing domain, which aims to remove trivial relationships in a dataset. We extend the sparse reconstruction model by assuring three principles in spatial data, including retention of the correlation of data in the non-spatial attribute domain, preservation of local dependencies in the spatial domain, and removal of trivial relationships. Extensive experiments, based on road network missing value imputation and building clustering, show that our approach can make better use of both spatial and non-spatial information than a simple addition of them. [ABSTRACT FROM AUTHOR]

Graphitic carbon nitride (g-C 3 N 4) is a promising metal-free photocatalyst; however, its high carrier recombination rate and insufficient redox capacity limit its degradation effect on antibiotics. In order to overcome these shortcomings, the photocatalytic activity is improved by regulating the spin polarization state, constructing the internal electric field, and applying the external piezoelectric field. In this paper, the chlorine-doped and nitrogen-deficient porous carbon nitride composite carbon quantum dots (N v -Cl/UPCN@CQD) has been synthesized successfully. The doping position of chlorine and spin polarization properties are verified by DFT calculation. The key intermediates *O 2 − and *OOH for the synthesis of reactive oxygen species were detected by in-situ infrared testing, which promotes the production of •O 2 − and H 2 O 2. The degradation rate constant of N v -Cl/UPCN@CQD for removal of tetracycline is 8.45 times higher than that of g-C 3 N 4. The active oxygen production and degradation efficiency of piezoelectric photocatalysis under the synergistic effect of intense stirring and vis-light irradiation are much higher than those of photocatalysis and piezoelectric catalysis, and the conversion of H 2 O 2 to •OH is promoted by piezoelectric field. This paper provides a reliable way to improve the performance of piezoelectric photocatalysts by adjusting their energy band, electronic structure and piezoelectric force. • A metal-free piezoelectric photocatalyst was constructed to realize electron transfer efficiently under the control of electric field and internal magnetic field. • The electron spin polarization caused by element doping and defect can effectively inhibit carrier recombination, and the locations of doping and defect are verified by experiments and calculations. • The effect of piezoelectric field on the production of reactive oxygen species was described, and a reasonable conversion method of ROS was proposed based on in-situ testing. [ABSTRACT FROM AUTHOR]

The superimposition of multiple factors has presented a formidable challenge in establishing the salient features of grain size distribution for the large-scaled complex titanium alloy casting (LCTAC). In this study, an anatomical analysis within a LCTAC was conducted to acquire microstructure and mechanical properties distribution characteristics in typical zones. Through the progressive convergence, variable selection, and data dimensionality reduction techniques employed in the LASSO regression of microstructure characteristics and mechanical properties, the efficacious establishment of microstructural attributes has been accomplished. Consequently, a quantitative relationship between the microstructure and properties of the LCTAC has been formulated, predicated on the characteristics of grain size distribution. The findings unequivocally illustrate that the order of convergence for the microstructural parameters affecting the tensile strength of the LCTAC is as follows: expectation of grain size, mean grain size, full width at half maximum of grain size distribution, and the 99th percentile grain size. There exists a linear negative correlation between the 99th percentile grain size and tensile strength for the LCTAC, with a root mean square error in tensile strength prediction of less than 2%. • An anatomical analysis is performed within the large-scaled complex titanium alloy casting (LCTAC). • LASSO regression is introduced to augment the precision of quality assessment and control for the LCTAC. • A novel microstructural determinant influencing the tensile strength of the LCTAC is discovered. • A quantitative correlation between grain size distribution and mechanical properties within the LCTAC is established. [ABSTRACT FROM AUTHOR]

• The efficiency of iron-carbon hydrogels for nitrate remediation was investigated. • The nitrate removal performance within the PRB and its downgradient aquifer was evaluated. • The microbial communities within the PRB and its downgradient aquifer were interpreted. • The response mechanisms of microbial communities and iron-carbon hydrogels were analyzed. Permeable Reactive Barriers (PRBs) have been utilized for mitigating nitrate pollution in groundwater systems through the use of solid carbon and iron fillers that release diverse nutrients to enhance denitrification efficiency. We conduct laboratory column tests to evaluate the effectiveness of PRBs in remediating nitrate pollution both within the PRB and in the downgradient aquifer. We use an iron-carbon hydrogel (ICH) as PRB filler, which has different weight ratios of polyhydroxybutyrate (PHB) and microscale zero-valent iron (mZVI). Results reveal that denitrification in the downgradient aquifer accounts for at least 19.5 % to 32.5 % of the total nitrate removal. In the ICH, a higher ratio of PHB to mZVI leads to higher contribution of the downgradient aquifer to nitrate removal, while a lower ratio results in smaller contribution. Microbial community analysis further reveals that heterotrophic and mixotrophic bacteria dominate in the downgradient aquifer of the PRB, and their relative abundance increases with a higher ratio of PHB to mZVI in the ICH. Within the PRB, autotrophic and iron-reducing bacteria are more prevalent, and their abundance increases as the ratio of PHB to mZVI in the ICH decreases. These findings emphasize the downgradient aquifer's substantial role in nitrate removal, particularly driven by dissolved organic carbon provided by PHB. This research holds significant implications for nutrient waste management, including the prevention of secondary pollution, and the development of cost-effective PRBs. [Display omitted] [ABSTRACT FROM AUTHOR]

Point feature selection aims at preserving global patterns of point cluster during map scaling. This is an important technique for clear presentation of points in multi-scale maps. However, existing methods tend to include single point features ignoring the spatial interactions between two types of points. For example, based on the Input Sharing mechanism in agglomeration economics, different types of facilities are usually co-located together to reinforce their functions in business competition. In this respect, generalization of a point feature should consider not only its own importance but also the reinforcing effects from other features. In this paper, an improved method is proposed by including the spatial contextual information. Experiments suggest that our method can preserve service patterns after generalization. [ABSTRACT FROM AUTHOR]

A series of experiments is conducted to study the combustion characteristics of aluminum particle-laden flow in a propulsion system that uses powder as the main fuel. A laminar flame produced by hydrocarbon fuel provides a high-temperature environment for the combustion of the aluminum particle-laden flow. The oxidant concentrations of the hot gas are adjusted by varying the mass flow rates of three gases. The combustion behaviors of aluminum particle-laden flow are analyzed in detail. The burning times and burning rates for aluminum particles can be obtained according to the variations in the light spot profiles of the burning particle. In addition, the micro-explosion phenomenon of the aluminum particle is observed in the higher oxidant content which is an important evidence that causes the shorter burning time. The research is helpful to develop and optimize the propulsion system using the powder as the main fuel. [Display omitted] • A low-density powder feeder is developed. • The behaviors of the aluminum particle-laden flow are analyzed at different oxidant concentration. • The burning law of the aluminum particle in the particle-laden flows is revealed at different oxidant concentration. • The agglomeration and separation processes of the aluminum particle-laden flow are analyzed in detail. [ABSTRACT FROM AUTHOR]

A series of experiments was conducted to study the ignition and combustion characteristics of aluminum particle-laden flows in a propulsion system that used powder as the main fuel. In these experiments, a laminar flame produced by hydrocarbon fuel provided a high-temperature environment for the ignition and combustion of the aluminum particles. The effective oxidant content and flow velocity were adjusted by varying the mass flow rates of three gases (methane, air, and oxygen), and the ignition delay and burning time of the aluminum particles in the particle-laden flow were determined using a high-speed camera. The total time was the sum of the ignition delay time and burning time. The experimental results showed that the ignition delay time could be fitted as a function of the particle diameter, expressed as t i = a 0 + b 0 D ; the burning time and total time could also be fitted as functions of the particle diameter, expressed as t b = aD b . As the effective oxidant content increased, the burning time decreased significantly, and the total time decreased slightly. The ignition delay time, burning time, and total time were obviously decreased with an increase in the flow velocity of the hot gas. Compared with the effective oxidant content, the flow velocity of the hot gas played a greater role in the reduction of the total time for the aluminum particles in a low-oxidant environment. The agglomeration and separation processes for the burning particles in aluminum particle-laden flows were analyzed in detail. • A low-density powder feed device is developed. • The time of dynamic ignition delay and combustion is used to assess the combustion characteristics of aluminum particle. • The effects of oxidant concentration and velocity of hot gas on the total time are studied in low oxidant environment. • The agglomeration and separation processes of aluminum particle-laden flow are analyzed in detail. [ABSTRACT FROM AUTHOR]

Predicting wind speed in advance at bridge sites is essential for ensuring bridge construction safety under high wind conditions. This study proposes a short-term speed prediction model based on outlier correction, Wavelet Denoising, the Osprey Optimization Algorithm (OOA), and the Transformer model. The outliers caused by data entry and measurement errors are processed by the interquartile range (IQR) method. By comparing the performance of four different wavelets, the best-performing wavelet (Bior2.2) was selected to filter out sharp noise from the data processed by the IQR method. The OOA-Transformer model was utilized to forecast short-term wind speeds based on the filtered time series data. With OOA-Transformer, the seven hyperparameters of the Transformer model were optimized by the Osprey Optimization Algorithm to achieve better performance. Given the outstanding performance of LSTM and its variants in wind speed prediction, the OOA-Transformer model was compared with six other models using the actual wind speed data from the Xuefeng Lake Bridge dataset to validate our proposed model. The experimental results show that the mean absolute percentage error (MAPE), root mean square error (RMSE), and coefficient of determination ( R 2 ) of this paper's method on the test set were 4.16%, 0.0152, and 0.9955, respectively, which are superior to the other six models. The prediction accuracy was found to be high enough to meet the short-term wind speed prediction needs of practical projects. [ABSTRACT FROM AUTHOR]

Under considerations of material abundance, cost, redox potential, higher performance, and safety, solid-state sodium-metal batteries hold much promise. The development of solid electrolytes with superior electrical performances for the solid-state sodium batteries is at the infant stage and still remains a challenge. Herein, we for the first time report a synthetic strategy of Na 3 Zr 2 Si 2 PO 12 ceramic microtubes via a sol gel process with natural cotton fiber template. Moreover, an inorganic-organic composite electrolyte Na 3 Zr 2 Si 2 PO 12 microtube/poly (ethylene oxide) (PEO)-poly (vinylidene fluoride- co -hexafluoropropylene) (PVdF-HFP)-sodium perchlorate (NaClO 4)-1-ethyl-3-methylimidazolium bis(fluorosulfonyl)imide (EmimFSI) is developed. The phase, microstructure, and electrochemical properties of the Na 3 Zr 2 Si 2 PO 12 microtubes and their composite electrolytes are systematically investigated based on X-ray diffraction, scanning electron microscope, energy dispersive spectroscopy, electrochemical impedance spectroscopy, linear sweep voltammetry, direct-current polarization, and galvanostatic cycling. The finding implies that the characteristic Na 3 Zr 2 Si 2 PO 12 microtubes and their composite electrolytes are promising for solid-state sodium-metal batteries. [ABSTRACT FROM AUTHOR]

In recent years, with the rapid development of urbanization, the urban public emergency management faces increasing challenges, and the number of fire incidents has increased largely. For mitigating injury risk and reducing property loss, fire station locations need to be optimized to provide efficient fire emergency services. However, the locations of fire facilities in China are mainly determined according to administrative divisions, lacking effective data-driven applications. In addition, existing location models are designed for general purpose, and few have taken into account the unique characteristics of fire services with multiple objectives, i.e., maximum coverage, minimum overlapping coverage and balanced workloads. With the recent development of geospatial big data, lots of fire risk related data (e.g. fire incidents data and travel time data) can be obtained, which provides an unprecedented opportunity for urban fire emergency facilities planning. In this paper, we propose to establish the multi-objective maximal covering location model by accurately estimating fire rescuing demands and travel cost from geospatial big data. A case study was carried out in Nanjing, China, and the result shows that our method is effective in optimizing the locations of fire stations. [ABSTRACT FROM AUTHOR]

As a key focus of cartography and terrain analysis, the simplification of a digital elevation model (DEM) is used to preserve the pattern features of the terrain surface while suppressing its details over multiple scales. Statistical filtering and structural analysis methods are commonly used for this process. The structural analysis method performs well in identifying terrain structural edges, while it tends to discard the smooth morphology of a terrain surface. In addition, the filter that aims to reduce noise on a surface may over-smooth the terrain structural edges. Therefore, to preserve both the terrain structural edges and smooth morphology, we propose to combine the techniques of statistical filtering and structural analysis. Specifically, all the critical elevation points and structural edges are first detected from the DEM surface by using the structural analysis method. Then, the iterative guided normal filter is used to smooth the generalized DEM with the guidance of the structure of the original surface. After this process, the terrain structure is retained in the smooth surface of the DEM. The experimental results with a real-world dataset show that our method can inherit the merits of both structural analysis and statistical filter in preserving terrain features for multi-scale DEM representations. [ABSTRACT FROM AUTHOR]

The photography auction market in China has experienced the early stage from the 1990s to 2005, the development stage from 2006 to 2018, and the current stages from 2019 to the present. In the domestic auction market at the early stage, the auction of photography was not rare, but the special session of photography auction had not yet been formed. Photographs were auctioned in the session of Ancient Books, Stamps, Chinese Painting and Calligraphy, as well as Oil Paintings. In 2006, Chinese contemporary art rose rapidly: Sotheby's held a special auction of contemporary Asian art on March 31 during the Asia Week New York in the spring of this year, the first large-scale Asian art special session in North America. In September of the same year, the photography work of Wang Qingsong, titled "Follow Me," was sold at Sotheby's in New York for 310,000 US dollars, which offers further drive to China's photography market. Against the backdrop of the development of the markets both home and abroad, Beijing Huachen Auctions hosted the first photography session in China in November 2006, with a total of 365 lots auctioned for a total turnover of 350,857 US dollars. At this point, the photography auction market in China was officially established and entered the era of special session auctions. While Chinese contemporary photography works enjoy huge popularity in overseas markets, the domestic photography auction session shows its uniqueness from the beginning. According to the statistics of the highest-priced auction lots in the first three photography auction sessions of Huachen Auctions, the domestic secondary photography market favors historical old photos and documentary photographs more. [ABSTRACT FROM AUTHOR]

The generalization of building footprints acts as the basis of multi-scale mapping. Most of the previous studies focus on the generalization of regular building clusters within a wide neighbourhood, but only few has concerned about the generalization of cluttered building clusters within the narrow space such as urban village. The buildings in urban villages show special characteristics in terms of individual properties and group properties, and thus their map generalization processes are often limited. This study proposes a framework to generalize the cluttered building clusters that allows for multi-scale mapping. It first adopts a heuristic method to group adjacent buildings based on the Delaunay triangulation model and then aggregates and simplifies each building group separately. Given that the aggregated buildings in urban villages often show cluttered alignments, our method further trims the jagged boundaries of building footprints by extracting the gap space between neighbouring buildings from the Delaunay triangulation model. [ABSTRACT FROM AUTHOR]

Mg 3 (VO 4) 2 (MVO) microwave dielectric ceramics were fabricated by a conventional solid-state sintering method at different sintering temperatures (T s) between 1000 °C and 1100 °C. The effects of T s on the phase evolution, the crystal structures, the dielectric responses, and the lattice vibrational characteristics of MVO were investigated. XRD patterns after Rietveld refinement were applied to analyze the phase evolution and the crystal structures of the samples, which shows the orthorhombic structure with the space group of Cmca for the MVO ceramics. Micrograph from scanning electron microscopy shows a uniform and dense crystal structure with the highest bulk density for the MVO sample sintered at 1050 °C. Raman scattering spectroscopy and infrared reflectance spectroscopy were used to dissect the lattice vibrational characteristics of the MVO ceramics. There are two types of vibrational modes of the MVO samples, i.e. , the external modes caused by the deformation of [VO 4 ]3- and the rotational and translational vibrations of the lattices, the internal modes attributed to the asymmetric stretching vibrations of V-O bonds. The intrinsic dielectric properties were determined by fitting the data with a four-parameter semi-quantum (FPSQ) model. Modes 1, 2, and 4, associated with the external modes, have the greatest contribution coefficient of 65.58% to the dielectric constant, and Mode 1 has the greatest contribution coefficient of 51.40% to the dielectric loss. The structure-property relationships were semi-quantitatively mathematically established according to the Raman modes. The MVO sample sintered at 1050 °C has the best dielectric properties of ε r = 9.59 and Q × f = 41,193 GHz (f = 13.69 GHz). • Mg 3 (VO 4) 2 microwave dielectric ceramics of crystal structures, dielectric properties, and phonon characteristics were studied. • The lattice vibrational characteristics were analyzed utilizing Raman and infrared reflection spectroscopy. • The physical mechanism of the dielectric response was clarified. • Relationships of structures-properties were established using Raman active modes as a media. [ABSTRACT FROM AUTHOR]

As one of the major concerns in cartographic generalization, road network generalization aims at maintaining the patterns of road networks across map scales. Previous methods define the pattern of road networks mainly from the perspectives of geometry and topology. However, for navigation purposes, traffic flow information is also important to generalize road networks. More specifically, road segments that have a proximity relationship in the traffic flow system should be retained together on small-scale maps to preserve the completeness of the driving route. In this regard, this study proposes an improved method for road network generalization that considers network geometry, topology, and traffic flow patterns. First, strokes are constructed from the road network data based on the 'every best fit' geometric principle. Then, the relationships among strokes are developed on the basis of traffic flow patterns, which are extracted from taxi trajectory data. The strokes are then selected in sequence based on the indicators of geometry, topology, and traffic flow. Our experimental results demonstrate that the proposed method can preserve both the 'Good Continuity' principle and the transport function relationship of roads after generalization. [ABSTRACT FROM AUTHOR]

Antigen‐presenting cells (APCs) play a crucial role in the anti‐tumor immunity as they are responsible for capturing, processing, and presenting tumor antigens to T cells. However, their activation is often limited by the absence of adjuvants and the suppressive effects of immune checkpoints, such as CD47‐SIRPα. Herein, we present a nanoadjuvant that is self‐assembled from long RNA building blocks generated through rolling circle transcription (RCT) reaction and further modified with cationic liposomes. Owing to the high load of densely packed RNA, this nanoadjuvant could robustly activate RIG‐I/MDA5 signaling in APCs, leading to the maturation of dendritic cells (DCs) and the polarization of tumor‐associated macrophages (TAMs) toward an anti‐tumor M1‐like phenotype. In addition, with a well‐designed template, the generated long RNA from RCT reaction includes two kinds of siRNA targeting both CD47 in tumor cells and SIRPα in APCs. This dual gene silencing results in efficient inhibition of the CD47‐SIRPα checkpoint. Collectively, the robust activation of RIG‐I/MDA5 signaling and efficient inhibition of CD47‐SIRPα checkpoint enhance the phagocytic activity of APCs, which in turn promotes the cross‐priming of effector T cells and the activation of anti‐tumor immune responses. This study therefore provides a simple and robust RNA nanoadjuvant for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

Antigen‐presenting cells (APCs) play a crucial role in the anti‐tumor immunity as they are responsible for capturing, processing, and presenting tumor antigens to T cells. However, their activation is often limited by the absence of adjuvants and the suppressive effects of immune checkpoints, such as CD47‐SIRPα. Herein, we present a nanoadjuvant that is self‐assembled from long RNA building blocks generated through rolling circle transcription (RCT) reaction and further modified with cationic liposomes. Owing to the high load of densely packed RNA, this nanoadjuvant could robustly activate RIG‐I/MDA5 signaling in APCs, leading to the maturation of dendritic cells (DCs) and the polarization of tumor‐associated macrophages (TAMs) toward an anti‐tumor M1‐like phenotype. In addition, with a well‐designed template, the generated long RNA from RCT reaction includes two kinds of siRNA targeting both CD47 in tumor cells and SIRPα in APCs. This dual gene silencing results in efficient inhibition of the CD47‐SIRPα checkpoint. Collectively, the robust activation of RIG‐I/MDA5 signaling and efficient inhibition of CD47‐SIRPα checkpoint enhance the phagocytic activity of APCs, which in turn promotes the cross‐priming of effector T cells and the activation of anti‐tumor immune responses. This study therefore provides a simple and robust RNA nanoadjuvant for cancer immunotherapy. [ABSTRACT FROM AUTHOR]

• Epoxidized cyclotriphosphazene and modified lignin for PLA flame retardants. • High flame retardancy was achieved with low loadings of HCCP-HEP and Lignin(P). • The flame-retardant mechanism of HCCP-HEP and lignin(P) was described. • The incorporation of lignin(P) greatly improves the UV shielding properties of PLA. • PLA/H/L composites maintain superior mechanical properties. Poly(lactic acid) (PLA) is one of the most promising sustainable bioplastics for its superior processibility and mechanical strength. However, the inherent flammability and poor UV shielding severely inhibit its widespread application. Traditional solutions usually require a high content of additives, which results in the sacrifice of mechanical properties. In this work, we propose an efficient strategy to overcome these challenges by incorporating epoxy-functionalized hexa -cyclotriphosphazene (HCCP-HEP) and diphenylphosphinyl chloride modified lignin (Lignin(P)) into PLA. The synergistic effect of HCCP-HEP and Lignin(P) through free radical quenching, non-flammable gas dilution and charring promotion significantly impedes combustion and enhances the flame retardance of PLA/HCCP-HEP/Lignin(P) (PLA/H/L) composites. Consequently, the PLA/H/L composite with 1 wt% HCCP-HEP and 1 wt% Lignin(P) loading exhibits a limiting oxygen index of 28.3 % and achieves UL-94 V-0 rating. Moreover, the composite provides over 97 % shielding against UV-A and UV-B radiation with an increased ultraviolet protection factor (UPF) from 1 to 700, while maintaining superior tensile strength (59 MPa). This work presents a new approach to prepare high-performance and multi-functional PLA composites, which is expected to broaden the application of PLA. [ABSTRACT FROM AUTHOR]

The MnO/C@CoPPc composite is prepared by facile surface-vacancy filling engineering. CoPPc is strategically impregnated into the empty space among the needles of MnO/C and simultaneously coated on the surface of MnO/C micro-rods. This structure not only guarantee the active center of MnO/C from the direct contact with electrolytes, but also efficiently alleviate its conductive disconnection on cycling. The presence of CoPPc can also effectively inhibit the volume expansion of MnO. The MnO/C@CoPPc composite has high reversible capacity and high stability. [Display omitted] • CoPPc not only guarantee the active center of MnO/C from the direct contact with electrolytes, but also efficiently alleviate its conductive disconnection on cycling. • The configuration of CoPPc-impregnated MnO/C composite effectively improved the electrochemical performance of MnO/C. • CoPPc can effectively inhibit the volume expansion of MnO during the charge-discharge cycle. • The MnO/C@CoPPc composite has high capacity and high stability. MnO has the advantages of high theoretical capacity, abundant resources and environmental friendliness, which is a potential material for lithium-ion storage. However, severe volume expansion and sluggish kinetics make MnO difficult to maintain long-term stability. In this study, MnO/C@CoPPc micro-rods composed of coral-like MnO/C nanobundles coated with CoPPc was synthesized via facile method. CoPPc impregnated into the empty space and simultaneously coated on the surface of the needles of MnO/C functions as an elastic layer to accommodate the mechanical stress caused by volume expansion of MnO/C, and simultaneously function as a buffering layer to keep electric disconnection on cycling. The volume of MnO/C is dramatically suppressed from 370% to 120%, and the reversible capacity is improved. Therefore, the configured MnO/C@CoPPc exhibits a high stability and delivers a high reversible capacity of 679.6 mAh/g after 200 cycles. [ABSTRACT FROM AUTHOR]

The CuF 2 @CoPPc lamellar hybrid was prepared by the recrystallization of CoPPc on the surface of CuF 2. This configuration can efficiently prevent CuF 2 from contacting directly with electrolyte and improve the reaction activity by weakening the bonding strength of Cu-F. CoPPc can catalyze the invertibility and surface reaction of CuF 2 , resulting in long cyclability, high capacity and high reversibility. [Display omitted] • A new strategy of tailoring the intrinsic Cu-F bond strength of CuF 2 is introduced to improve its durable reversibility. • As a catalyst, CoPPc enhances and improves the reversibility and surface reaction of CuF 2. • The synergistic effect of CuF 2 and CoPPc drastically promotes the charge transfer kinetics of the composite. • CuF 2 @CoPPc has long cyclability, high capacity and high reversibility. CuF 2 is a promising candidate of electrode materials for lithium-ion batteries due to its high specific capacity, high power density and environmental friendliness. However, the irreversible phase conversion and sluggish kinetics caused by serious copper dissolution and low conductivity make CuF 2 difficult to achieve long cycling life. A facile strategy to incorporate CoPPc into CuF 2 was proposed firstly to regulate the Cu-F bonding force to realize the high reversibility of CuF 2 for lithium-ion storage. The results of DFT calculation, differential charge density simulation, work function calculation and COHP bond level calculation show that the existence of CoPPc can improve the surface charge distribution of CuF 2 and thus improve the reversibility for durable lithium-ion storage. The cycle life performance of the CuF 2 @CoPPc composite electrode obtained by this method reached staggering 500 cycles and the capacity remained at 594.8 mAh/g. [ABSTRACT FROM AUTHOR]

Highlights • Reaction of volatiles decreases the tar yield and increases the gas and coke yield. • Reaction of volatiles has a significant effect on the composition of tar. • The effect of reaction temperature is significantly greater than residence time. • Volatile composition affect significantly the reaction behavior of volatiles. Abstract The reactions of volatiles generated from coal pyrolysis determined the tar yield and composition. In order to investigate the effect of the reaction behavior of volatiles on the distribution of pyrolysis products, especially the tar yield and composition, the reactions of volatiles generated from the Shengli lignite (SL) pyrolysis using a two-stage fixed-bed reactor, with the first stage for lignite pyrolysis and the second stage for reactions of volatiles, were investigated in this paper. It was found that the reactions of volatiles resulted in an increase in gas and coke yield and a decrease in tar yield during lignite pyrolysis. And the effect of reaction temperature in the range of 700–900 °C on the distribution of light tar is significantly greater than that of the volatiles' residence time in the range of 4–14 s. Reactions of volatiles shortened the carbon chain length of alkanes and increased the content of arenes and phenols in light tar under certain conditions. When the volatiles' reaction temperature was 700 °C and the volatile's residence time was 8 s during coal SL pyrolysis at the heating rate of 10 °C/min, the phenols content was 1.5 times higher than that of raw light tar. It was found that the more heavy components content the volatiles contained, the more heavy components content the final tar contained after the volatiles reaction. [ABSTRACT FROM AUTHOR]