Boosting High-Voltage Dynamics Towards High-Energy-Density Lithium-Ion Capacitors

Lithium-ion capacitors(LICs)are becoming important electrochemical energy storage systems due to their great potential to bridge the gap between supercapacitors and lithium-ion batteries.However,capacity lopsidedness and low output voltage greatly hinder the realization of high-energy-density LICs.Herein,a strategy of balancing capacity towards fastest dynamics is proposed to enable high-voltage LICs.Through electrochemical prelithiation of Nb_(2)C to be 1.1 V with 165 mAh g^(-1),Nb_(2)C//LiFePO_(4) LICs show a broadened potential window from 3.0 to 4.2 V and an according high energy density of 420 Wh kg^(-1).Moreover,the underlying mechanism between prelithiation and high voltage is disclosed by electrochemical dynamic analysis.Prelithiation declines the Nb_(2)C anode potential that facilitates electron transmission in the interlayer of two-dimensional Nb_(2)C MXene.This effect induces small drive force for Li^(+)ions deposition and hence weakens the repulsive force from adsorbed ions on the electrode surface.Benefiting from even more Li^(+)ions deposition,a higher voltage is eventually delivered.In addition,prelithiation significantly increases Coulomb efficiency of the 1st cycle from 74%to 90%,which is crucial to commercial application of LICs.

NH_(3)‑Induced In Situ Etching Strategy Derived 3D‑Interconnected Porous MXene/Carbon Dots Films for High Performance Flexible Supercapacitors

2D MXene(Ti_(3)CNT_(x))has been considered as the most promising electrode material for flexible supercapacitors owing to its metallic conductivity,ultra-high capacitance,and excellent flexibility.However,it suffers from a severe restacking problem during the electrode fabrication process,limiting the ion transport kinetics and the accessibility of ions in the electrodes,especially in the direction normal to the electrode surface.Herein,we report a NH_(3)-induced in situ etching strategy to fabricate 3D-interconnected porous MXene/carbon dots(p-MC)films for high-performance flexible supercapacitor.The pre-intercalated carbon dots(CDs)first prevent the restacking of MXene to expose more inner electrochemical active sites.The partially decomposed CDs generate NH_(3)for in situ etching of MXene nanosheets toward 3D-interconnected p-MC films.Benefiting from the structural merits and the 3D-interconnected ionic transmission channels,p-MC film electrodes achieve excellent gravimetric capacitance(688.9 F g^(-1)at 2 A g^(-1))and superior rate capability.Moreover,the optimized p-MC electrode is assembled into an asymmetric solid-state flexible supercapacitor with high energy density and superior cycling stability,demonstrating the great promise of p-MC electrode for practical applications.

Predicting the Popularity of Online News Based on the Dynamic Fusion of Multiple Features

Predicting the popularity of online news is essential for news providers and recommendation systems.Time series,content and meta-feature are important features in news popularity prediction.However,there is a lack of exploration of how to integrate them effectively into a deep learning model and how effective and valuable they are to the model’s performance.This work proposes a novel deep learning model named Multiple Features Dynamic Fusion(MFDF)for news popularity prediction.For modeling time series,long short-term memory networks and attention-based convolution neural networks are used to capture long-term trends and short-term fluctuations of online news popularity.The typical convolution neural network gets headline semantic representation for modeling news headlines.In addition,a hierarchical attention network is exploited to extract news content semantic representation while using the latent Dirichlet allocation model to get the subject distribution of news as a semantic supplement.A factorization machine is employed to model the interaction relationship between metafeatures.Considering the role of these features at different stages,the proposed model exploits a time-based attention fusion layer to fuse multiple features dynamically.During the training phase,thiswork designs a loss function based on Newton’s cooling law to train the model better.Extensive experiments on the real-world dataset from Toutiao confirm the effectiveness of the dynamic fusion of multiple features and demonstrate significant performance improvements over state-of-the-art news prediction techniques.

Deep Learning Model for News Quality Evaluation Based on Explicit and Implicit Information

Recommending high-quality news to users is vital in improving user stickiness and news platforms’reputation.However,existing news quality evaluation methods,such as clickbait detection and popularity prediction,are challenging to reflect news quality comprehensively and concisely.This paper defines news quality as the ability of news articles to elicit clicks and comments from users,which represents whether the news article can attract widespread attention and discussion.Based on the above definition,this paper first presents a straightforward method to measure news quality based on the comments and clicks of news and defines four news quality indicators.Then,the dataset can be labeled automatically by the method.Next,this paper proposes a deep learning model that integrates explicit and implicit news information for news quality evaluation(EINQ).The explicit information includes the headline,source,and publishing time of the news,which attracts users to click.The implicit information refers to the news article’s content which attracts users to comment.The implicit and explicit information affect users’click and comment behavior differently.For modeling explicit information,the typical convolution neural network(CNN)is used to get news headline semantic representation.For modeling implicit information,a hierarchical attention network(HAN)is exploited to extract news content semantic representation while using the latent Dirichlet allocation(LDA)model to get the subject distribution of news as a semantic supplement.Considering the different roles of explicit and implicit information for quality evaluation,the EINQ exploits an attention layer to fuse them dynamically.The proposed model yields the Accuracy of 82.31%and the F-Score of 80.51%on the real-world dataset from Toutiao,which shows the effectiveness of explicit and implicit information dynamic fusion and demonstrates performance improvements over a variety of baseline models in news quality evaluation.This work provides empirical evidence for explicit and implicit factors in news quality evaluation and a new idea for news quality evaluation.

Transcription factor ZmNAC126 plays an important role in transcriptional regulation of maize starch synthesis-related genes

Maize(Zea mays L.)is one of the most important food crops in the world,and starch is the main component of its endosperm.Transcriptional regulation plays a vital role in starch biosynthesis.However,it is not well understood in maize.We report the identification of the transcription factor ZmNAC126 and its role in regulation of starch synthesis in maize.Transcriptional expression of ZmNAC126 was higher in maize endosperm and kernels than in roots or stems.ZmNAC126 shared a similar expression pattern with starch synthesis genes during seed development,and its expression pattern was also consistent with the accumulation of starch.ZmNAC126 is a typical transcription factor with a transactivation domain between positions 201 and 227 of the amino acid sequence,is located in the nucleus,and binds to CACG repeats in vitro.Yeast one-hybrid assay revealed that ZmNAC126 bound the promoters of ZmGBSSI,ZmSSIIa,ZmSSIV,ZmISA1,and ZmISA2.Transient overexpression of ZmNAC126 in maize endosperm increased the activities of promoters pZmSh2,pZmBt2,pZmGBSSI,pZmSSIIIa,and pZmBT1 but inhibited the activities of pZmISA1 and pZmISA2.ZmNAC126 thus acts in starch synthesis by transcriptionally regulating targeted starch synthesis-related genes in maize kernels.

Effective electroelastic constants for three-phase confocal elliptical cylinder model in piezoelectric quasicrystal composites

A three-phase confocal elliptical cylinder model is proposed to analyze micromechanics of one-dimensional hexagonal piezoelectric quasicrystal （PQC） compos- ites. Exact solutions of the phonon, phason, and electric fields are obtained by using the conformal mapping combined with the Laurent expansion technique when the model is subject to far-field anti-plane mechanical and in-plane electric loadings. The effective elec- troelastic constants of several different composites made up of PQC, quasicrystal （QC）, and piezoelectric （PE） materials are predicted by the generalized self-consistent method. Numerical examples are conducted to show the effects of the volume fraction and the cross-sectional shape of inclusion （or fiber） on the effective electroelastic constants of these composites. Compared with other micromechanical methods, the generalized self- consistent and Mori-Tanaka methods can predict the effective electroelastic constants of the composites consistently.

Visual Relationship Detection with Contextual Information

Understanding an image goes beyond recognizing and locating the objects in it,the relationships between objects also very important in image understanding.Most previous methods have focused on recognizing local predictions of the relationships.But real-world image relationships often determined by the surrounding objects and other contextual information.In this work,we employ this insight to propose a novel framework to deal with the problem of visual relationship detection.The core of the framework is a relationship inference network,which is a recurrent structure designed for combining the global contextual information of the object to infer the relationship of the image.Experimental results on Stanford VRD and Visual Genome demonstrate that the proposed method achieves a good performance both in efficiency and accuracy.Finally,we demonstrate the value of visual relationship on two computer vision tasks:image retrieval and scene graph generation.

Genetic links of porphyry Mo-epithermal Pb–Zn–Ag mineralization system:a case study of the Shipingchuan polymetallic deposit,South China

Compared with the porphyry Cu-epithermal Au mineralization system,detailed studies on the porphyry Mo-epithermal Pb–Zn–Ag–Au mineralization are rare due to limited exposures.The Shipingchuan polymetallic deposit,located in the South China Mo Province(SCMP)represents a typical example containing both porphyry Mo and epithermal Pb–Zn–Ag mineralization.The Mo mineralization mainly occurs as molybdenite-quartz veins in veinlets or as disseminated molybdenite within the potassic,silicic,and sericitic syenogranite.The Pb–Zn–Ag mineralization is characterized by veinlet-type sphalerite–galena–pyrite–quartz–calcite vein within the volcanic rocks accompanied with silicifi cation and propylitization.Five molybdenite samples yield a Re–Os isochron age of 104.7±0.7 Ma that is consistent with the zircon age(107.5±2.1 Ma)of the ore-bearing syenogranite within errors.Together with previous reported Ar–Ar ages(106.6–121.8 Ma)of Pb–Zn–Ag related volcanic rocks,the Mo and Pb–Zn–Ag mineralization belong to a magmatic-hydrothermal event in the Early Cretaceous.Meanwhile,the total Re contents of molybednite range from 1.28 to 45.55 ppm,indicating the ore-forming materials were from a mixture between the mantle and crustal material.Moreover,previous sulfur isotopic values(3.7–4.3‰)of the pyrites from the porphyry Mo mineralization were consistent with the reported range of 4.0–6.1‰of the sphalerites from the Pb–Zn–Ag mineralization,implying that the sulfur of two-types of mineralization was derived from magma.The above-mentioned spatial,temporal,and isotopic lines of evidence suggest that the Mo and Pb–Zn–Ag mineralization of the Shipingchuan deposit was formed from the same metallogenic system.In consideration of regional tectonic evolution history,we propose that the porphyry Mo-epithermal Pb–Zn–Ag mineralization formed in an extensional tectonic setting caused by the continued rollback and the eventual slab break-off of the subducting PaleoPacifi c plate.

Two-step homogenization for the effective thermal conductivities of twisted multi-filamentary superconducting strand

For the accurate prediction of the effective thermal conductivities of the twisted multi-filamentary superconducting strand,a two-step homogenization method is adopted.Based on the distribution of filaments,the superconducting strand can be decomposed into a set of concentric cylinder layers.Each layer is a two-phase composite composed of the twisted filaments and copper matrix.In the first step of homogenization,the representative volume element(RVE)based finite element(FE)homogenization method with the periodic boundary condition(PBC)is adopted to evaluate the effective thermal conductivities of each layer.In the second step of homogenization,the generalized self-consistent method is used to obtain the effective thermal conductivities of all the concentric cylinder layers.The accuracy of the developed model is validated by comparing with the local and full-field FE simulation.Finally,the effects of the twist pitch on the effective thermal conductivities of twisted multi-filamentary superconducting strand are studied.

Investigations on Simultaneously Secure IBE Scheme and Security Proofs under RO and Non-RO Model

This paper analyses security mechanism and authentication, key agreement protocol of 3G system amply, puts forward a amelioration scheme. This scheme assures security communications without credible VLR. This paper analyses ameliorative protocol and resolves the security communications problem between MS and HLR.

A Unified Monitoring Framework for Distributed Environment

Distributed computing is a field of computer science that studies distributed systems. With the increasing computing capacity of computers it is widely used to solve large problems. Monitoring system is one of the key components in distributed computing. Although there have been varieties of monitoring systems developed by different organizations, it is still a great challenge to monitor a heterogeneous distributed environment in a unified and transparent way. In this paper, we present a unified monitoring framework for distributed environment (UMFDE) with heterogeneous monitoring systems, and then propose a comprehensive method based on the Enterprise Service Bus (ESB) to integrate the monitoring systems in the environment as a unified monitoring system. A representative case study is given to show the feasibility of this framework.

SPN-Based Performance Analysis of Multiple Users’Behaviors for SNS

With the rapid development of various applications of Information Technology,big data are increasingly generated by social network services(SNS)nowadays.The designers and providers of SNS distribute different client applications for PC,Mobile phone,IPTV etc.,so that users can obtain related service via mobile or traditional Internet.Good scalability and considerably short time delay are important indices for evaluating social network systems.As a result,investigating and mining the principle of users’behaviors is an important issue which can guide service providers to establish optimal systems with SNS.On the basis of analyzing the characteristics of social network system,this paper constructed a Stochastic Petri Net(SPN)model for describing the behaviors of three users for SNS.Moreover,the scalability of users’behaviors of SNS was studied by extending the SPN model of three users to the one of four users.Furthermore,average time delay was chosen as the performance index to evaluate the performance of these two constructed SPN models with Stochastic Petri Net Package(SPNP)6.0.For different parameters of number of connections,traffic load and buffer size,various trends and numerical results are derived thereby.The methodology of modeling and simulation in this paper can be further used to study the performance of SNS.

The prevalence of soil transmitted helminths and its infuential factors in Shandong Province, China: an analysis of surveillance data from 2016 to 2020

Background Soil-transmitted helminths(STHs)were previously endemic in Shandong Province,China.This study aimed to analyze the STHs prevalence trend and the natural,social,and human cognitive and behavioural factors infuencing the discrepancies between high and low infection levels from 2016 to 2020 in Shandong Province in eastern China.Methods STHs surveillance data of Shandong Province from 2016 to 2020 were obtained from China Information Management System for Prevention and Control of Parasitic Diseases.STHs infections were detected by modifed Kato–Katz method.Comprehensive information on the natural and social factors,STHs-related knowledge and behaviours were collected through questionnaire surveys.Retrospective spatial scan analysis was performed using SaTScan v10.1 to evaluate any identifed spatial clusters of STHs infection for statistical signifcance and Bayes discriminant analysis was used to discriminate the high or low infection groups of the villages.Results In total,72,160 participants were involved in our survey from 2016 to 2020.The overall STHs prevalence rate was 1.13%,with the eastern region of Shandong Province having the highest rate(2.02%).The predominant species was T.trichiura,with the prevalence rate of 0.99%and the≥70-year age group possessed the highest rate of 2.21%.The STHs prevalence rate showed an annual linear downward trend from 2016 to 2020(χ_(trend)^(2) =127.600,P<0.001).Respondents aged≥60 years had the lowest awareness level of STHs-related prevention knowledge(all P<0.05),and were the most likely to adopt the practice of fertilizing with fresh stool(χ^(2)=28.354,P<0.001).Furthermore,the southern region demonstrated the highest temperature and rainfall level and the lowest GNP and annual net income per capita(all P<0.05).Conclusions There is a remarkable declining in STHs prevalence in Shandong Province from 2016 to 2020.However,the prevalence rates of STHs especially T.trichiura in the southern and eastern regions were still high,and the elderly were more susceptible to be infected with STHs owning to their low awareness level of STHS-related prevention knowledge and high adoption rate of dangerous production and living behaviours.Integrated approaches of health education,environment improvement and behaviour change should be strengthened to obtain a further reduction of STHs prevalence in China.

月球着陆器着陆过程的DEM-FEM耦合分析

实现月球着陆器的安全软着陆是宇航员、搭载设备、仪器安全以及着陆器后续正常工作的重要保证.论文采用离散元-有限元方法建立月壤与着陆器相互作用的耦合模型,其中月壤采用具有粘结作用的球体离散元单元,着陆器采用壳单元和梁单元组合的有限元模型,与缓冲垫连接的支撑腿采用可压缩弹簧模型,以实现着陆器自身的缓冲功能;为分析着陆于不同月表的过程,建立平坦、斜坡月球表面;针对不同坡度的斜坡月表,研究不同着陆模式下着陆器与月壤的相互作用,分析冲击力峰值的大小与作用时间的关系,并从能量方面讨论和解释大坡度下冲击力峰值小的原因.以上研究为月球着陆器的安全着陆分析提供有益的参考.

Synthesis of New Substituted 4-Amino-3,5-dinitropyridine Derivatives

Facile synthetic routes for the preparation of some new 4-amino-3,5-dinitropyridine derivatives have been revealed. Nitration of 2-chloropyridin-4-amine （1） as a starting material, in an unexpected one-step reaction, to give dinitrated derivatives, followed by nucleophilic substitution reactions with sodium azide, potassium fluoride, ammonia, methylamine, and 4-nitroimidazol, respectively, gave substituted 4-amino-3,5-dinitropyridine derivatives. Meanwhile, its azide derivative underwent a ring closure conversion into 7-amino-6-nitro-[1,2,5]oxadiazolo[3,4-b]- pyridine-1-oxide. It is of significance that all of the nucleophilic substitution reactions were carried out under mild conditions.