All‑Covalent Organic Framework Nanofilms Assembled Lithium‑Ion Capacitor to Solve the Imbalanced Charge Storage Kinetics

Free-standing covalent organic framework(COFs)nanofilms exhibit a remarkable ability to rapidly intercalate/de-intercalate Li^(+) in lithium-ion batteries,while simultaneously exposing affluent active sites in supercapacitors.The development of these nanofilms offers a promising solution to address the persistent challenge of imbalanced charge storage kinetics between battery-type anode and capacitor-type cathode in lithium-ion capacitors(LICs).Herein,for the first time,custom-made COFBTMB-TP and COFTAPB-BPY nanofilms are synthesized as the anode and cathode,respectively,for an all-COF nanofilm-structured LIC.The COFBTMB-TP nanofilm with strong electronegative–CF3 groups enables tuning the partial electron cloud density for Li^(+) migration to ensure the rapid anode kinetic process.The thickness-regulated cathodic COFTAPB-BPY nanofilm can fit the anodic COF nanofilm in the capacity.Due to the aligned 1D channel,2D aromatic skeleton and accessible active sites of COF nanofilms,the whole COFTAPB-BPY//COFBTMB-TP LIC demonstrates a high energy density of 318 mWh cm^(−3) at a high-power density of 6 W cm^(−3),excellent rate capability,good cycle stability with the capacity retention rate of 77%after 5000-cycle.The COFTAPB-BPY//COFBTMB-TP LIC represents a new benchmark for currently reported film-type LICs and even film-type supercapacitors.After being comprehensively explored via ex situ XPS,7Li solid-state NMR analyses,and DFT calculation,it is found that the COFBTMB-TP nanofilm facilitates the reversible conversion of semi-ionic to ionic C–F bonds during lithium storage.COFBTMB-TP exhibits a strong interaction with Li^(+) due to the C–F,C=O,and C–N bonds,facilitating Li^(+) desolation and absorption from the electrolyte.This work addresses the challenge of imbalanced charge storage kinetics and capacity between the anode and cathode and also pave the way for future miniaturized and wearable LIC devices.

Accelerating Oxygen Electrocatalysis Kinetics on Metal-Organic Frameworks via Bond Length Optimization

Metal-organic frameworks(MOFs)have been developed as an ideal platform for exploration of the relationship between intrinsic structure and catalytic activity,but the limited catalytic activity and stability has hampered their practical use in water splitting.Herein,we develop a bond length adjustment strategy for optimizing naphthalene-based MOFs that synthesized by acid etching Co-naphthalenedicarboxylic acid-based MOFs(donated as AE-CoNDA)to serve as efficient catalyst for water splitting.AE-CoNDA exhibits a low overpotential of 260 mV to reach 10 mA cm^(−2)and a small Tafel slope of 62 mV dec^(−1)with excellent stability over 100 h.After integrated AE-CoNDA onto BiVO_(4),photocurrent density of 4.3 mA cm^(−2)is achieved at 1.23 V.Experimental investigations demonstrate that the stretched Co-O bond length was found to optimize the orbitals hybridization of Co 3d and O 2p,which accounts for the fast kinetics and high activity.Theoretical calculations reveal that the stretched Co-O bond length strengthens the adsorption of oxygen-contained intermediates at the Co active sites for highly efficient water splitting.

Hollow Metal-Organic Framework/MXene/Nanocellulose Composite Films for Giga/Terahertz Electromagnetic Shielding and Photothermal Conversion

With the continuous advancement of communication technology,the escalating demand for electromagnetic shielding interference(EMI)materials with multifunctional and wideband EMI performance has become urgent.Controlling the electrical and magnetic components and designing the EMI material structure have attracted extensive interest,but remain a huge challenge.Herein,we reported the alternating electromagnetic structure composite films composed of hollow metal-organic frameworks/layered MXene/nanocellulose(HMN)by alternating vacuum-assisted filtration process.The HMN composite films exhibit excellent EMI shielding effectiveness performance in the GHz frequency(66.8 dB at Kaband)and THz frequency(114.6 dB at 0.1-4.0 THz).Besides,the HMN composite films also exhibit a high reflection loss of 39.7 dB at 0.7 THz with an effective absorption bandwidth up to 2.1 THz.Moreover,HMN composite films show remarkable photothermal conversion performance,which can reach 104.6℃under 2.0 Sun and 235.4℃under 0.8 W cm^(−2),respectively.The unique micro-and macrostructural design structures will absorb more incident electromagnetic waves via interfacial polarization/multiple scattering and produce more heat energy via the local surface plasmon resonance effect.These features make the HMN composite film a promising candidate for advanced EMI devices for future 6G communication and the protection of electronic equipment in cold environments.

Tectonic framework of Qilian orogen: reveal from an aeromagnetic anomaly feature

The Qilian Orogenic belt is one of the typical orogenic belts globally and a natural laboratory for studying plate tectonics.Many researchers have studied the ophiolite and high pressure and ultra-high pressure metamorphic rocks in the Qilian orogen and obtained valuable achievements.However,a hot debate exists on the basement property,the distribution of ophiolite,and the boundaries of tectonic units.Large-scale high-precision aeromagnetic surveys have recently been conducted in the Qilian Orogenic belt and adjacent areas.In this study,we are trying to analysis the tectonic framework of the Qilian Orogen using 1:500,000 aeromagnetic data.The results provide geophysical perspectives for studying the structural framework and deformation of this area.According to the aeromagnetic∆T anomaly map,the central and Southern Qilian have the same magnetic anomaly feature that noticeably differs from the North Qilian Orogenic belt and the Qaidam Block.This result indicates that the central and Southern Qilian have a unified magnetic basement and differ from the North Qilian orogenic belt and Qaidam Block.The map shows the distribution of ophiolite in the North Qilian orogenic belt.Linear magnetic anomalies represent the ophiolites because the mafic–ultramafic rocks usually have high magnetic susceptibility.The ophiolite belts are continuously distributed in the western part of North Qilian orogenic belt and have a large scale.However,the scale of the ophiolite belt and the outcropping of mafic–ultramafic rocks reduces when they pass through Qilian County to the east.The results indicate differences in the evolution process between the eastern and western parts of North Qilian,with Qilian County as the transition zone.This study also systematically defines the geophysical boundaries of the Qaidam Block,Qilian Block,North Qilian Orogenic belt,and Alxa block.It is proposed that the sinistral displacement of the Altun Fault is adjusted and absorbed by the series of NE-trending faults in the Qilian orogen and merge into the Longshoushan–Gushi Fault.The extension of the North Qilian Orogenic belt is strengthened by the neotectonics movement along the shearing direction,which separated the North Qilian Orogenic belt into several segments and formed a series of northeast-trending faults.

Research on the Legal Framework of Content Regulations for Network Platforms

In the era of the Internet,various network platforms have evolved into new hubs for information dissemination.Currently,China has established a platform-centered content regulation framework,wherein platforms proactively enforce content regulations in accordance with legal censorship obligations.Additionally,platform policies and user agreements augment their authority in content regulation.The platforms can achieve cost-effective and highly efficient content regulation by leveraging their strategic advantages enabled by their own technical capabilities and extensive coverage.The platform self-regulation model,however,still faces challenges.First,accurately evaluating content remains a formidable task;second,ensuring effective platform publicity through self-regulation poses difficulties;third,users may potentially face disadvantages due to the platform’s right of self-regulation;and fourth,digital copyright owners face challenges when defending digital copyright disputes under the safe harbor rule.Therefore,it is imperative to establish,review,and revise the legal framework for content regulation of network platforms in order to enhance the efficiency of their governance systems.The formulation of the legal framework for content regulation of network platforms may encompass the following aspects:rationalizing obligations pertaining to platform content regulations,enhancing supervision over platform self-regulation,and establishing a dual-track responsibility system for digital copyright content regulation.This will ensure a harmonious balance among public interests,users’personal rights and interests,and commercial benefits through regulating the content on network platforms.

An End-To-End Hyperbolic Deep Graph Convolutional Neural Network Framework

Graph Convolutional Neural Networks(GCNs)have been widely used in various fields due to their powerful capabilities in processing graph-structured data.However,GCNs encounter significant challenges when applied to scale-free graphs with power-law distributions,resulting in substantial distortions.Moreover,most of the existing GCN models are shallow structures,which restricts their ability to capture dependencies among distant nodes and more refined high-order node features in scale-free graphs with hierarchical structures.To more broadly and precisely apply GCNs to real-world graphs exhibiting scale-free or hierarchical structures and utilize multi-level aggregation of GCNs for capturing high-level information in local representations,we propose the Hyperbolic Deep Graph Convolutional Neural Network(HDGCNN),an end-to-end deep graph representation learning framework that can map scale-free graphs from Euclidean space to hyperbolic space.In HDGCNN,we define the fundamental operations of deep graph convolutional neural networks in hyperbolic space.Additionally,we introduce a hyperbolic feature transformation method based on identity mapping and a dense connection scheme based on a novel non-local message passing framework.In addition,we present a neighborhood aggregation method that combines initial structural featureswith hyperbolic attention coefficients.Through the above methods,HDGCNN effectively leverages both the structural features and node features of graph data,enabling enhanced exploration of non-local structural features and more refined node features in scale-free or hierarchical graphs.Experimental results demonstrate that HDGCNN achieves remarkable performance improvements over state-ofthe-art GCNs in node classification and link prediction tasks,even when utilizing low-dimensional embedding representations.Furthermore,when compared to shallow hyperbolic graph convolutional neural network models,HDGCNN exhibits notable advantages and performance enhancements.

基于.NET Framework技术的测试用例系统设计

软件测试环节直接影响着产品的成败,本文所介绍的测试用例系统设计是使用基于.NET的面向对象的可视化编程工具与SQL Server数据库相结合,采用应用服务器技术的C/S架构,按项目测试流程进行设计,把测试用例融入项目设计中,贯穿整个开发过程,大大减少重复工作量以及充分发挥每个人的效率,提高测试效率和速度。所设计的系统包括用户管理,项目管理,测试用例库管理,缺陷管理等功能模块,集成安全性与可维护性,实现集中管理,使整个软件系统开发的业务周期缩短、开发成本降低,也同步提高项目的核心竞争力。

构建基于Microsoft.Net Framework的组件化Internet应用系统

介绍了Microsoft.Net Framework的技术架构和三层应用解决方案,从系统体系结构、组件技术两个方面综合考虑,结合一个实际的应用系统的实例提出了构建Internet应用系统的方案.该方案便于开发维护,并且性能优良.

基于Microsoft.NET Framework 2.0技术图书馆期刊发布系统的研究与实现

本文论述了图书馆期刊发布系统的计算机软件结构,介绍了在Microsof.tNET Framework2.0技术下图书馆期刊发布系统的优点与缺点,并结合本馆自身实例介绍了如何利用Microsoft公司最新的开发工具Visual Studio 2005来实现图书馆期刊发布系统的计算机软件。

Microsoft.NET Compact Framework 2.0中数据访问模型解析

Microsoft.NET Compact Framework2.0数据访问模型的对象为DataSet、TableAdapter和BindingSouce。三个对象的应用为:首先使用TableAdapter的Fill方法,将数据库中的数据填充到DataSet中;然后使用BindingSouce对象,将DataSet中数据绑定到用户控件,BindingSouce的Position属性可控制DataSet数据光标的移动。

Challenges and Opportunities in Preserving Key Structural Features of 3D-Printed Metal/Covalent Organic Framework

Metal-organic framework(MOF)and covalent organic framework(COF)are a huge group of advanced porous materials exhibiting attractive and tunable microstructural features,such as large surface area,tunable pore size,and functional surfaces,which have significant values in various application areas.The emerging 3D printing technology further provides MOF and COFs(M/COFs)with higher designability of their macrostructure and demonstrates large achievements in their performance by shaping them into advanced 3D monoliths.However,the currently available 3D printing M/COFs strategy faces a major challenge of severe destruction of M/COFs’microstructural features,both during and after 3D printing.It is envisioned that preserving the microstructure of M/COFs in the 3D-printed monolith will bring a great improvement to the related applications.In this overview,the 3D-printed M/COFs are categorized into M/COF-mixed monoliths and M/COF-covered monoliths.Their differences in the properties,applications,and current research states are discussed.The up-to-date advancements in paste/scaffold composition and printing/covering methods to preserve the superior M/COF microstructure during 3D printing are further discussed for the two types of 3D-printed M/COF.Throughout the analysis of the current states of 3D-printed M/COFs,the expected future research direction to achieve a highly preserved microstructure in the 3D monolith is proposed.

Parallel Light Fields: A Perspective and A Framework

Dear Editor,Light fields give relatively complete description of scenes from perspective of angles and positions of rays. At present time, most of the computer vision algorithms take 2D images as input which are simplified expression of light fields with depth information discarded. In theory, computer vision tasks may achieve better performance as long as complete light fields are acquired.

SOSNet:一种非对称编码器-解码器结构的非小细胞肺癌CT图像分割模型

非小细胞肺癌严重损害人类健康,早期非小细胞肺癌CT(Computed Tomography)图像中的肿瘤结节体积小,不易发现,极易造成漏诊和误诊.为了精确分割非小细胞肺癌CT图像中的小体积肿瘤结节,本文提出SOSNet(Small Object Segmentation Networks)自动分割模型,利用ResNet(Residual Network)基础层和空洞卷积构造非对称编码器-解码器结构作为分割主网络,利用轴向取反注意力模块ARA(Axial Reverse Attention)逐步擦除背景中对分割有影响的结构,再使用结构细化模块SR(Structure Refinement)对主网络输出的粗略特征图进行结构细化,从而实现非小细胞肺癌肿瘤结节分割.在非小细胞肺癌公开数据集的实验测试表明,本文提出的小目标自动分割模型SOSNet可以有效分割出非小细胞肺癌CT图像中的小体积肿瘤结节,其mDice(mean-Dice)、mIoU(mean Intersection over Union)、Sensitivity、F1、Specificity、平均绝对误差MAE(Mean Absolute Error)均优于当前最先进的小目标分割模型CaraNet(Context Axial Reverse Attention Network).

Carbon nanocages bridged with graphene enable fast kinetics for dual-carbon lithium-ion capacitors

Lithium-ion capacitors(LICs) combining the advantages of lithium-ion batteries and supercapacitors are considered a promising nextgeneration energy storage device. However, the sluggish kinetics of battery-type anode cannot match the capacitor-type cathode, restricting the development of LICs. Herein, hierarchical carbon framework(HCF) anode material composed of 0D carbon nanocage bridged with 2D graphene network are developed via a template-confined synthesis process. The HCF with nanocage structure reduces the Li^(+) transport path and benefits the rapid Li^(+) migration, while 2D graphene network can promote the electron interconnecting of carbon nanocages. In addition, the doped N atoms in HCF facilitate to the adsorption of ions and enhance the pseudo contribution, thus accelerate the kinetics of the anode. The HCF anode delivers high specific capacity, remarkable rate capability. The LIC pouch-cell based on HCF anode and active HCF(a-HCF) cathode can provide a high energy density of 162 Wh kg^(-1) and a superior power density of 15.8 kW kg^(-1), as well as a long cycling life exceeding 15,000cycles. This study demonstrates that the well-defined design of hierarchical carbon framework by incorporating 0D carbon nanocages and 2D graphene network is an effective strategy to promote LIC anode kinetics and hence boost the LIC electrochemical performance.

A computational framework for improving genetic variants identification from 5,061 sheep sequencing data

Background Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation.Joint calling is routinely used to combine identified variants across multiple related samples.However,the improvement of variants identification using the mutual support information from mul-tiple samples remains quite limited for population-scale genotyping.Results In this study,we developed a computational framework for joint calling genetic variants from 5,061 sheep by incorporating the sequencing error and optimizing mutual support information from multiple samples’data.The variants were accurately identified from multiple samples by using four steps:(1)Probabilities of variants from two widely used algorithms,GATK and Freebayes,were calculated by Poisson model incorporating base sequencing error potential;(2)The variants with high mapping quality or consistently identified from at least two samples by GATK and Freebayes were used to construct the raw high-confidence identification(rHID)variants database;(3)The high confidence variants identified in single sample were ordered by probability value and controlled by false discovery rate(FDR)using rHID database;(4)To avoid the elimination of potentially true variants from rHID database,the vari-ants that failed FDR were reexamined to rescued potential true variants and ensured high accurate identification variants.The results indicated that the percent of concordant SNPs and Indels from Freebayes and GATK after our new method were significantly improved 12%-32%compared with raw variants and advantageously found low frequency variants of individual sheep involved several traits including nipples number(GPC5),scrapie pathology(PAPSS2),sea-sonal reproduction and litter size(GRM1),coat color(RAB27A),and lentivirus susceptibility(TMEM154).Conclusion The new method used the computational strategy to reduce the number of false positives,and simulta-neously improve the identification of genetic variants.This strategy did not incur any extra cost by using any addi-tional samples or sequencing data information and advantageously identified rare variants which can be important for practical applications of animal breeding.

Electrostatic Interaction-directed Construction of Hierarchical Nanostructured Carbon Composite with Dual Electrical Conductive Networks for Zinc-ion Hybrid Capacitors with Ultrastability

Metal-organic framework(MOF)-derived carbon composites have been considered as the promising materials for energy storage.However,the construction of MOF-based composites with highly controllable mode via the liquid-liquid synthesis method has a great challenge because of the simultaneous heterogeneous nucleation on substrates and the self-nucleation of individual MOF nanocrystals in the liquid phase.Herein,we report a bidirectional electrostatic generated self-assembly strategy to achieve the precisely controlled coatings of single-layer nanoscale MOFs on a range of substrates,including carbon nanotubes(CNTs),graphene oxide(GO),MXene,layered double hydroxides(LDHs),MOFs,and SiO_(2).The obtained MOF-based nanostructured carbon composite exhibits the hierarchical porosity(V_(meso)/V_(micro)∶2.4),ultrahigh N content of 12.4 at.%and"dual electrical conductive networks."The assembled aqueous zinc-ion hybrid capacitor(ZIC)with the prepared nanocarbon composite as a cathode shows a high specific capacitance of 236 F g^(-1)at 0.5 A g^(-1),great rate performance of 98 F g^(-1)at 100 A g^(-1),and especially,an ultralong cycling stability up to 230000 cycles with the capacitance retention of 90.1%.This work develops a repeatable and general method for the controlled construction of MOF coatings on various functional substrates and further fabricates carbon composites for ZICs with ultrastability.

基于ASP.NET MVC架构在精炼炉RH二级客户端设计与实现

为了实现基于B/S框架的精炼炉RH二级客户端系统,采用基于.NET平台的ASP.NET MVC的Web开发框架,使用了MVC(Model-View-Controller)三层模式,利用基于ADO.NET为基础的Entity Framework对象关系映射器(简称ORM)框架技术,与数据库之间进行交互,Web界面采用Razor视图引擎,使得代码开发更加简洁、规范。基于MVC分层模式开发的精炼炉RH二级客户端系统,具有较好的可复用性、可扩展性,并且易于部署和维护。

Managing the surge:A comprehensive review of the entire disposal framework for retired lithium-ion batteries from electric vehicles

Anticipating the imminent surge of retired lithium-ion batteries(R-LIBs)from electric vehicles,the need for safe,cost-effective and environmentally friendly disposal technologies has escalated.This paper seeks to offer a comprehensive overview of the entire disposal framework for R-LIBs,encompassing a broad spectrum of activities,including screening,repurposing and recycling.Firstly,we delve deeply into a thorough examination of current screening technologies,shifting the focus from a mere enumeration of screening methods to the exploration of the strategies for enhancing screening efficiency.Secondly,we outline battery repurposing with associated key factors,summarizing stationary applications and sizing methods for R-LIBs in their second life.A particular light is shed on available reconditioning solutions,demonstrating their great potential in facilitating battery safety and lifetime in repurposing scenarios and identifying their techno-economic issues.In the realm of battery recycling,we present an extensive survey of pre-treatment options and subsequent material recovery technologies.Particularly,we introduce several global leading recyclers to illustrate their industrial processes and technical intricacies.Furthermore,relevant challenges and evolving trends are investigated in pursuit of a sustainable end-of-life management and disposal framework.We hope that this study can serve as a valuable resource for researchers,industry professionals and policymakers in this field,ultimately facilitating the adoption of proper disposal practices.

Microsoft.NET Framework结构解析

Microsoft.NET Framework是构造、配置和运行下一代XML Web服务和其它应用的核心组件。文章详细分析了NET Framework的体系结构,重点阐述了其跨语言、跨平台的特点。借助.NET Framework,可实现各种语言的无缝综合,从而可以方便地构建基于Internet标准的松散耦合的Web服务。

Research on Weighted Directed Dynamic Multiplexing Network of World Grain Trade Based on Improved MLP Framework

As the main food source for humans, the global movement of the three major grains significantly impacts human survival and development. To investigate the evolution of the world cereal trade network and its development trend, a weighted directed dynamic multiplexed network was established using historical data on cereal trade, cereal import dependency ratio, and arable land per capita. Inspired by the MLP framework, we redefined the weight determination method for computing layer weights and edge weights of the target layer, modified the CN, RA, AA, and PA indicators, and proposed the node similarity indicator for weighted directed networks. The AUC metric, which measures the accuracy of the algorithm, has also been improved in order to finally obtain the link prediction results for the grain trading network. The prediction results were processed, such as web-based presentation and community partition. It was found that the number of generalized trade agreements does not have a decisive impact on inter-country cereal trade. The former large grain exporters continue to play an important role in this trade network. In the future, the world trade in cereals will develop in the direction of more frequent intercontinental trade and gradually weaken the intracontinental cereal trade.