Heteroclinic Cycles in a Class of 3-Dimensional Piecewise Affine Systems

This paper explores the existence of heteroclinic cycles and corresponding chaotic dynamics in a class of 3-dimensional two-zone piecewise affine systems. Moreover, the heteroclinic cycles connect two saddle foci and intersect the switching manifold at two points and the switching manifold is composed of two perpendicular planes.

Metal organic polymers with dual catalytic sites for oxygen reduction and oxygen evolution reactions

Metal-organic frameworks and covalent organic frameworks have been widely employed in electrochemical catalysis owing to their designable skeletons,controllable porosities,and well-defined catalytic centers.However,the poor chemical stability and low electron conductivity limited their activity,and single-functional sites in these frameworks hindered them to show multifunctional roles in catalytic systems.Herein,we have constructed novel metal organic polymers(Co-HAT-CN and Ni-HAT-CN)with dual catalytic centers(metal-N_(4) and metal-N_(2))to catalyze oxygen reduction reaction(ORR)and oxygen evolution reaction(OER).By using different metal centers,the catalytic activity and selectivity were well-tuned.Among them,Co-HAT-CN catalyzed the ORR in a 4e^(-)pathway,with a half-wave potential of 0.8 V versus RHE,while the Ni-HAT-CN catalyze ORR in a 2e^(-)pathway with H_(2)O_(2) selectivity over 90%.Moreover,the Co-HAT-CN delivered an overpotential of 350 mV at 10 mA cm^(-2) with a corresponding Tafel slope of 24 mV dec^(-1) for OER in a 1.0 M KOH aqueous solution.The experimental results revealed that the activities toward ORR were due to the M-N_(4) sites in the frameworks,and both M-N_(4) and M-N_(2) sites contributed to the OER.This work gives us a new platform to construct bifunctional catalysts.

Dual atomic catalysts from COF-derived carbon for CO_(2)RR by suppressing HER through synergistic effects

The electrochemical carbon dioxide reduction reaction(CO_(2)RR)for highvalue-added products is a promising strategy to tackle excessive CO_(2) emissions.However,the activity of and selectivity for catalysts for CO_(2)RR still need to be improved because of the competing reaction(hydrogen evolution reaction).In this study,for the first time,we have demonstrated dual atomic catalytic sites for CO_(2)RR from a core-shell hybrid of the covalent-organic framework and the metal-organic framework.Due to abundant dual atomic sites(with CoN_(4)O and ZnN_(4) of 2.47 and 11.05 wt.%,respectively)on hollow carbon,the catalyst promoted catalysis of CO_(2)RR,with the highest Faradic efficiency for CO of 92.6%at-0.8 V and a turnover frequency value of 1370.24 h^(-1) at-1.0 V.More importantly,the activity and selectivity of the catalyst were well retained for 30 h.The theoretical calculation further revealed that CoN_(4)O was the main site for CO_(2)RR,and the activity of and selectivity for Zn sites were also improved because of the synergetic roles.

High-resolution assessment of retrogressive thaw slump susceptibility in the Qinghai-Tibet Engineering Corridor

Under the rapidly warming climate in the Arctic and high mountain areas,permafrost is thawing,leading to various hazards at a global scale.One common permafrost hazard termed retrogressive thaw slump(RTS)occurs extensively in ice-rich permafrost areas.Understanding the spatial and temporal distributive features of RTSs in a changing climate is crucial to assessing the damage to infrastructure and decision-making.To this end,we used a machine learning-based model to investigate the environmental factors that could lead to RTS occurrence and create a susceptibility map for RTS along the Qinghai-Tibet Engineering Corridor(QTEC)at a local scale.The results indicate that extreme summer climate events(e.g.,maximum air temperature and rainfall)contributes the most to the RTS occurrence over the flat areas with fine-grained soils.The model predicts that 13%(ca.22,948 km^(2))of the QTEC falls into high to very high susceptibility categories under the current climate over the permafrost areas with mean annual ground temperature at 10 m depth ranging from-3 to-1℃.This study provides insights into the impacts of permafrost thaw on the stability of landscape,carbon stock,and infrastructure,and the results are of value for engineering planning and maintenance.

Localization Algorithm of Indoor Wi-Fi Access Points Based on Signal Strength Relative Relationship and Region Division

Precise localization techniques for indoor Wi-Fi access points(APs)have important application in the security inspection.However,due to the interference of environment factors such as multipath propagation and NLOS(Non-Line-of-Sight),the existing methods for localization indoor Wi-Fi access points based on RSS ranging tend to have lower accuracy as the RSS(Received Signal Strength)is difficult to accurately measure.Therefore,the localization algorithm of indoor Wi-Fi access points based on the signal strength relative relationship and region division is proposed in this paper.The algorithm hierarchically divide the room where the target Wi-Fi AP is located,on the region division line,a modified signal collection device is used to measure RSS in two directions of each reference point.All RSS values are compared and the region where the RSS value has the relative largest signal strength is located as next candidate region.The location coordinate of the target Wi-Fi AP is obtained when the localization region of the target Wi-Fi AP is successively approximated until the candidate region is smaller than the accuracy threshold.There are 360 experiments carried out in this paper with 8 types of Wi-Fi APs including fixed APs and portable APs.The experimental results show that the average localization error of the proposed localization algorithm is 0.30 meters,and the minimum localization error is 0.16 meters,which is significantly higher than the localization accuracy of the existing typical indoor Wi-Fi access point localization methods.

In-situ testing study on convection and temperature characteristics of a new crushed-rock slope embankment design in a permafrost region

For the purpose of enhancing air convection and controlling solar radiation, a new crushed-rock slope embankment design combined with a sun-shade measure is proposed. A newly designed embankment was constructed in the Tuotuohe section of the Qinghai-Tibet Railway and a field-testing experiment was carried out to determine its convection and temperature characteristics. The results show that distinct air convection occurred in the crushed-rock layer of the new embankment, especially in cold seasons, which was enhanced when it flowed upwards along the slope. This preliminarily indicated that the new design of the embankment slope was good for reinforcing air convection in the crushed-rock layer. The frequent fluctuations of the convection speed and the environmental wind speed were in good agreement, suggesting that the convection in the crushed rock primarily came from the ambient wind. It was also preliminarily determined that the new embankment had a better cooling effect and sun-shade effect for decreasing the temperature of the embankment slope compared with a traditional crushed-rock slope embankment, and the mean temperature difference between them was up to 1.7 °C. The mean annual temperature at the bottom boundary of the crushed-rock layer was obviously lower than that at the top boundary, and heat flux calculation showed that the shallow soil beneath the embankment slope was weakly releasing heat, all of which indicated that the new embankment slope design was beneficial to the thermal stability of the embankment. This study is helpful in providing some references for improved engineering design and maintenance of roadbeds in permafrost regions.

Dating of two thermokarst lakes in Beiluhe Basin, Qinghai-Tibetan Plateau

Most of the thermokarst lakes are spread appreciably in Beiluhe Basin,Qinghai-Tibet Plateau,China,where ice-rich permafrost exists.Two typical thermokarst lakes with differing area and depth were examined to ascertain their age.We obtained lake-bottom samples of 50 cm length from lake BLH-A and 25 cm length from lake BLH-B.Environmental 137 Cs and 210 Pb and radiocarbon age dating techniques were applied to the 50 cm and 25 cm samples,respectively.The results indicate that the initiation of BLH-A is about 800-900 a B.P.,and approximately 1,450±30 a B.P.to 2,230±30 a B.P.for BLH-B.These results will provide scientific bases for sedimentological study and thermokarst activity in Beiluhe Basin.

Urban 3D modeling using mobile laser scanning:a review

Mobile laser scanning(MLS)systems mainly comprise laser scanners and mobile mapping platforms.Typical MLS systems can acquire three-dimensional point clouds with 1-10cm point spacings at a normal driving or walking speed in streets or indoor environments.The efficiency and stability of these systems make them extremely useful for application in three-dimensional urban modeling.This paper reviews the latest advances of the LiDAR-based mobile mapping system(MMS)point cloud in the field of 3D modeling,including LiDAR simultaneous localization and mapping,point cloud registration,feature extraction,object extraction,semantic segmentation,and processing using deep learning.Furthermore,typical urban modeling applications based on MMS are also discussed.

Investigation of DRA and non-DRA in locust compound eye on the phototactic response of locust

New approaches are required to prevent the plagues of locusts that threaten crop security in many areas of the world. One such approach is to exploit the phototactic response of locusts, enabling their aggregation and effective removal from agricultural sites. This study examined the effect of the dorsal rim area (DRA) of the locust compound eye on the phototactic response of locusts to spectral light. Locusts with intact DRA showed increased phototactic responses to blue, green or orange light but decreased responses to UV and violet light, whereas locusts with blacked-out DRA (non-DRA vision) showed the strongest phototactic responses to orange followed by violet light. The combined results revealed that phototactic push-pull effect triggered by responses of DRA versus non-DRA vision was strongest in response to violet light. Compound vision in the locust is the result of the synergism between DRA versus non-DRA vision, causing a push-pull phototactic effect that is most stimulated by exposure to violet light, with light intensity enhancing this effect. These results provide theoretical support for the induction of phototaxis and polarotaxis in response to light in locusts, which could be useful for the development of light-based control systems in the field.

Cross-Modal Graph Semantic Communication Assisted by Generative AI in the Metaverse for 6G

Recently, the development of the Metaverse has become a frontier spotlight, which is an important demonstration of the integration innovation of advanced technologies in the Internet. Moreover, artificial intelligence (AI) and 6G communications will be widely used in our daily lives. However, the effective interactions with the representations of multimodal data among users via 6G communications is the main challenge in the Metaverse. In this work, we introduce an intelligent cross-modal graph semantic communication approach based on generative AI and 3-dimensional (3D) point clouds to improve the diversity of multimodal representations in the Metaverse. Using a graph neural network, multimodal data can be recorded by key semantic features related to the real scenarios. Then, we compress the semantic features using a graph transformer encoder at the transmitter, which can extract the semantic representations through the cross-modal attention mechanisms. Next, we leverage a graph semantic validation mechanism to guarantee the exactness of the overall data at the receiver. Furthermore, we adopt generative AI to regenerate multimodal data in virtual scenarios. Simultaneously, a novel 3D generative reconstruction network is constructed from the 3D point clouds, which can transfer the data from images to 3D models, and we infer the multimodal data into the 3D models to increase realism in virtual scenarios. Finally, the experiment results demonstrate that cross-modal graph semantic communication, assisted by generative AI, has substantial potential for enhancing user interactions in the 6G communications and Metaverse.

气波引射器压力端口设计及其对性能的影响

气波引射器是一种高效的压力能综合利用装备,在诸多工业过程中具有广阔的应用前景。压力端口作为气波引射器必备的核心部件,其开、闭位置的合理设计是保证设备高效运行的前提。本工作介绍了以波系理论为基础的压力端口设计方法,并通过数值模拟与实验相结合,获得了完整的端口位置对设备性能的影响机理及规律。研究结果表明,满足理想波系的压力端口位置可使设备性能在相同条件下达到最优;端口偏离设计位置则会引起中压产气返流、低压进气不充分等现象,从而造成性能下降。由于不同端口位置对性能的影响机理不同,各端口位置偏离所造成的性能下降幅度有所不同。本工作丰富了气波引射器的参数设计理论,对该设备的研究应用具有重要指导意义。

Dimensional engineering of covalent organic frameworks derived carbons for electrocatalytic carbon dioxide reduction

Covalent organic frameworks(COFs)have been developed as the precursors to construct porous carbons for electrocatalytic systems.However,the influences of carbon dimensions on the catalytic performance are still underexplored.In this work,we have first constructed COF-derived carbons by template-synthesis strategy in different dimensions to catalyze the carbon dioxide reduction(CO_(2)RR).By using different templates,the one-dimensional(1D),two-dimensional(2D),and three-dimensional(3D)COF-derived carbons have been employed to anchor Co-porphyrin to form the Co-N5 sites to catalyze CO_(2)RR.The 1D catalyst templated by carbon nano tubes presents high binding ability of CO_(2),more defective sites,and higher electronic conductivity,resulting in a higher catalytic activity for CO_(2)and selectivity of CO than 2D and 3D carbon-based catalysts.The 1D catalyst delivers the turnover frequency values of 1150 h^(−1)and the FECO of 94.5%at 0.7 V versus RHE,which is significantly better than those of 2D and 3D carbon-based catalysts.

When liver disease diagnosis encounters deep learning:Analysis,challenges,and prospects

The liver is the second-largest organ in the human body and is essential for digesting food and removing toxic substances.Viruses,obesity,alcohol use,and other factors can damage the liver and cause liver disease.The diagnosis of liver disease used to depend on the clinical experience of doctors,which made it subjective,difficult,and time-consuming.Deep learning has made breakthroughs in various fields;thus,there is a growing interest in using deep learning methods to solve problems in liver research to assist doctors in diagnosis and treatment.In this paper,we provide an overview of deep learning in liver research using 139 papers from the last 5 years.We also show the relationship between data modalities,liver topics,and applications in liver research using Sankey diagrams and summarize the deep learning methods used for each liver topic,in addition to the relations and trends between these methods.Finally,we discuss the challenges of and expectations for deep learning in liver research.

Critical impact of nanocellulose on the synthesis of porous cellulose monolith with oriented microchannels:Structure control,mechanics,mass transport

Nanocellulose harvested from biomass has attractive properties that have promoted research on its practical applications.Herein,we investigated nanocellulose-based porous monoliths with oriented microchannels that can be fabricated via a unidirectional freezing method.In this method,water-dispersed cellulose nanofibers(CNFs)were immersed into a cold source at a controlled speed,followed by subsequent freeze-drying.The structure of porous cellulose monoliths mainly depends on two factors:the freezing conditions and properties of the dispersed CNFs.The former has been investigated previously.However,the effects of the latter remain unclear.In this study,CNF suspensions prepared by 2,2,6,6-tetramethylpiperidine-1-oxylmediated oxidation cellulose nanofibers(TOCNs)with different aspect ratios and concentrations were used.The effects of these variables on the resulting structure,including the pore shape,size,wall thickness,were examined.Based on the results,the impact of TOCNs on the structure of porous cellulose monoliths was investigated.Our findings suggested that depending on their structure,the porous cellulose monoliths exhibit different mechanical strengths and mass transport properties.In particular,porous cellulose monoliths synthesized from 5.1 wt.%short TOCNs exhibited a low density(55.9 mg∙cm^(−3)),high mechanical strength(8687 kPa),fast mass transport.

气波引射器反馈结构的功能机理及性能实验

气波引射器是一种利用气体压力波实现能量交换过程的新型动态设备,因其具有效率较高、结构简单以及能耗低等优点,在诸多生产过程中具有广阔的应用前景。为提升气波引射器在中压背压较高工况下的应用性能,提出了一种简单易行的反馈结构,并对其功能机理与性能进行了模拟及实验研究。通过数值模拟考察了此结构通过预压缩作用来削弱反向压缩波不良影响的功能机理,得出此结构的适用条件以及应用效果判定条件。通过实验验证了数值模拟的正确性,并获得了反馈结构的实际应用效果。实验范围内,反馈结构获得的最大效率及引射率提升量分别可达6.93%和5.43%。

RiceENCODE:A comprehensive epigenomicdatabase as a rice Encyclopedia of DNA Elements

Dear Editor,Rice(Oryza sativa)is one of the most important crops in the worldand a common model plant for genomic research.The genomesofXian/IndicaandGeng/Japonicahave been completelysequenced and annotated with accurate genome information.Over the past few years,epigenomic information,including DNAmethylation,histone modification,and chromatin accessibility,has been characterized in theXian/IndicaandGeng/Japonicage-nomes(Zhao et al.,2020).Quite a few rice three-dimensionalgenome studies have been published in the meantime(Zhaoet al.,2019).However,it is still a big challenge for many groupsthat lack dedicated bioinformatic personnel or sufficientcomputational resources to utilize such epigenetic data.

Promoting the protonation step on the interface of titanium dioxide for selective photocatalytic reduction of CO_(2)to CH_(4)by using red phosphorus quantum dots

Enhancing the selectivity of hydrocarbon in CO_(2)is a great challenge.Herein,taking widely-used and highly-stable TiO_(2)as an example,we found that the protonation step,the key step for CH_(4)production,can change from endoergic to exoergic by using red phosphorus quantum dots.Consequently,the main product in CO_(2)reduction can be shifted from CO into CH_(4).The preparation method is very simple,which just ultrasonically treating the red P in the presence of TiO_(2).With an initial rate of CH_(4)production of 4.69μmol·g^(-1)·h^(-1),under simulated solar light,it manifests a significant 49.4-fold enhancement of CH_(4)yield over TiO_(2).Density functional calculation indicates that the red P optimizes the surface electronic structure.The Gibbs free energy for CHO^(*)formation(^(-1).12 eV)becomes lower than the desorption energy of the CO(-0.01 eV)when red P is introduced.This indicates that the CO intermediates on the surface are rapidly protonated to produce CHO^(*).Subsequently,the CHO^(*)will be converted into CH_(4)instead of being desorbed from the surface to produce CO.This study demonstrates that red P quantum dot is a promising candidate for the development of efficient photocatalyst for CO_(2)photoreduction to CH_(4)under solar light irradiation.

Lithium Ion Conduction in Covalent Organic Frameworks

Ion conduction plays key roles in electrochemical systems,including fuel cells,lithium ion batteries,and metal-air batteries.Covalent organic frameworks(COFs),as a new class of porous polymers,constructed by pre-designable building blocks,are ideal hosts to accommodate ionic carries for conduction because of their straightforward pore channels,tunable pore size,controllable pore environment,and good chemical and thermal stability.Different from proton conduction,how to achieve high lithium ion conduction is still a challenge as it is difficult to dissociate ionic bonds of the lithium salts.To facilitate the dissociation of lithium salts,COFs with different pores and skeletons are well designed and constructed.This review focuses on emerging developments of lithium ion conduction in COFs,and discusses the structures of these COFs and conductive performance to elucidate the structure-property correlations.Furthermore,we have concluded the remaining challenge and future direction in these COF-based lithium conductive areas.This review provides deeper insight into COFs for ionic conduction.

Representation Learning with Deconvolution for Multivariate Time Series Classification and Visualization

We propose a new model based on the convolutional networks and SAX(Symbolic Aggregate Approximation)discretization to learn the representation for multivariate time series.The deep neural networks has excellent expressiveness,which is fully exploited by the convolutional networks with means of unsupervised learning.We design a network structure to obtain the cross-channel correlation with means of convolution and deconvolution,the pooling operation is utilized to perform the dimension reduction along each position of the channels.Discretization which based on the Symbolic Aggregate Approximation is applied on the feature vectors to extract the bag of features.We collect two different representations from the convolutional networks,the compression from bottle neck and the last convolutional layers.We show how these representations and bag of features can be useful for classification.We provide a full comparison with the sequence distance based approach on the standard datasets to demonstrate the effectiveness of our method.We further build the Markov matrix according to the discretized representation abstracted from the deconvolution,time series is visualized to complex networks through Markov matrix visualization,which show more class-specific statistical properties and clear structures with respect to different labels.