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Fluidization and Transport of Vibrated Granular Matter:A Review of Landmark and Recent Contributions

Fluid Dynamics & Materials Processing 2024年第1期20卷 1-29页

作者： Peter Watson Sebastien Vincent Bonnieu Marcello Lappa Department of Mechanical and Aerospace Engineering University of StrathclydeGlasgowUK European Space agency European Space Research and Technology CentreNoordwijkNetherland

We present a short retrospective review of the existing literature about the dynamics of(dry)granular matter under the effect of vibrations.The main objective is the development of an integrated resource where vital information about past findings and recent discoveries is provided in a single treatment.Special attention is paid to those works where successful synthetic routes to as-yet unknown phenomena were identified.Such landmark results are analyzed,while smoothly blending them with a history of the field and introducing possible categorizations of the prevalent dynamics.Although no classification is perfect,and it is hard to distillate general properties out of specific observations or realizations,two possible ways to interpret the existing results are defined according to the type of forcing or the emerging(ensuing)regime of motion.In particular,first results concerning the case where vibrations and gravity are concurrent(vertical shaking)are examined,then the companion situation with vibrations perpendicular to gravity(horizontal shaking)is described.Universality classes are introduced as follows:(1)Regimes where sand self-organizes leading to highly regular geometrical“pulsating”patterns(thin layer case);(2)Regimes where the material undergoes“fluidization”and develops an internal multicellular convective state(tick layers case);(3)Regimes where the free interface separating the sand from the overlying gas changes inclination or develops a kind a patterned configuration consisting of stable valleys and mountains or travelling waves;(4)Regimes where segregation is produced,i.e.,particles of a given size tend to be separated from the other grains(deep containers).Where possible,an analogy or parallelism is drawn with respect to the companion field of fluid-dynamics for which the assumption of“continuum”can be applied.

关键词： Granular materials vibrations fluidization flowability symmetry breaking

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Bamboo-derived hard carbon/carbon nanotube composites as anode material for long-life sodium-ion batteries with high charge/discharge capacities

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Rare Metals 2024年第1期43卷 124-137页

作者： Sukanya Pothaya Chatwarin Poochai Nantikan Tammanoon Yaowamarn Chuminjak Tanaporn Kongthong Tanom Lomas Chakrit Sriprachuabwong Adisorn Tuantranont Graphene and Printed Electronics for Dual-Use Applications Research Division(GPERD) National Security and Dual-Use Technology Center(NSD)National Science and Technology Development Agency(NSTDA)Tambon Klong NuengAmphoe Klong LuangPathum Thani 12120Thailand

Hard carbon derived from bamboo for the anode material of sodium-ion batteries has a three-dimensional(3D) open framework structure and has naturally incorporated K-ions into its carbon structure,increasing the dinterlayer spacing of hard carbon materials for facilitating Na^(+) transport.In this work,bamboo-derived hard carbon was prepared via two carbonization temperatures at 700and 1000 ℃ for an hour and employed as an anode for sodium-ion batteries(SIB).X-ray diffraction(XRD) and Fourier transform(FT)-Raman spectroscopic results indicated the disordered structure with d-spacing(d_(002)) around0.36-0.37 nm,which is a benefit for sodium ion insertion/desertion.Herein,the composition between carbon-nanotube(CNT) and bamboo-derived hard carbon(BB) was synthesized by a ball mill with various contents of CNT(1 wt%,5 wt% and 10 wt%).At the optimal CNT content of 5 wt%,the sample exhibited excellent performance and outstanding stability.As the anode,the half-cell SIB using BB(700)w@5%CNT(with a carbonization temperature of700 ℃ and CNT loading of 5 wt%) delivered a high initial specific capacity of 268.9 mAh·g^(-1) at 0.1C and capacity retention of 78.6% after 500 cycles at 1.0C.The full cell SIB fabrication BB(700)w@5%CNT in combination with Na_(3)V_(2)(PO4)_(3) as the cathode demonstrated a high specific capacity of 127.6 mAh·g^(-1) at 0.2C with its capacitive retention remaining of 78% at 1.0C after 1000 cycles.The attained storage performance indicates that hard carbonCNT composite anode material enhanced the conductive path of electron transport and provided long-term cycling stability.The good electrochemical performance as well as the low cost and environment-friendliness of the bambooderived hard carbon proves its suitability for future sodium-ion batteries.

关键词： Hard carbon Bamboo Sodium-ion battery(SIB) Full cell

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Harnessing endothelial cells and vascularization strategies for nerve regeneration

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Neural Regeneration Research 2024年第11期19卷 2337-2338页

作者： Papon Muangsanit Poppy Smith Virology and Cell Technology Research Team National Center for Genetic Engineering and Biotechnology(BIOTEC)National Science and Technology Development Agency(NSTDA)PathumthaniThailand UCL Centre for Nerve Engineering UCLLondonUK Department of Pharmacology UCL School of PharmacyUCLLondonUK

Peripheral nerves are essential components of the human body’s communication system,transmitting signals between the central nervous system and various body parts.Damage resulting from trauma or disease can result in debilitating sensory and motor deficits.Nerve injuries,particularly those resulting in significant gaps in the nerve tissue,pose a formidable challenge for clinicians and researchers.Despite their limitations,including limited availability and donor site morbidity,nerve autografts remain the clinical gold standard for treating nerve injuries.

关键词： injuries nerves donor

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Air traffic monitoring using optimized ADS-B CubeSat constellation

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Astrodynamics 2024年第1期8卷 189-208页

作者： Ghulam Jaffer Rameez AMalik Elias Aboutanios Nazish Rubab Ronnie Nader Hans U.Eichelberger Guy A.E.Vandenbosch Interdisciplinary Centre for security Reliability and Trust(SnT)University of LuxembourgLuxembourg1855Luxembourg

The primary technique used for air traffic surveillance is radar.However,nowadays,its role in surveillance is gradually being replaced by the recently adopted Automatic Dependent Surveillance-Broadcast(ADS-B).ADS-B offers a higher accuracy,lower power consumption,and longer range than radar,thus providing more safety to aircraft.The coverage of terrestrial radar and ADS-B is confined to continental parts of the globe,leaving oceans and poles uncovered by real-time surveillance measures.This study presents an optimized Low-Earth Orbit(LEO)-based ADS-B constellation for global air traffic surveillance over intercontinental trans-oceanic flight routes.The optimization algorithm is based on performance evaluation parameters,i.e.,coverage time,satellite availability,and orbit stability(precession and perigee rotation),and communication analysis.The results indicate that the constellation provides ample coverage in the simulated global oceanic regions.The constellation is a feasible and cost-effective solution for global air supervision,which can supplement terrestrial ADS-B and radar systems.

关键词： constellation automatic dependent surveillance-broadcast (ADS-B) air traffic surveillance precession perigee rotation.

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A Survey on Event Tracking in Social Media Data Streams

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Big Data Mining and Analytics 2024年第1期7卷 217-243页

作者： Zixuan Han Leilei Shi Lu Liu Liang Jiang Jiawei Fang Fanyuan Lin Jinjuan Zhang John Panneerselvam Nick Antonopoulos School of Computer Science and Communication Engineering and Jiangsu Key Laboratory of security Technology for Industrial Cyberspace Jiangsu UniversityZhenjiang 212013China School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Ocean College Jiangsu University of Science and TechnologyZhenjiang 212100China University Executive Office Edinburgh Napier UniversityEdinburghEH114BNUK

Social networks are inevitable parts of our daily life,where an unprecedented amount of complex data corresponding to a diverse range of applications are generated.As such,it is imperative to conduct research on social events and patterns from the perspectives of conventional sociology to optimize services that originate from social networks.Event tracking in social networks finds various applications,such as network security and societal governance,which involves analyzing data generated by user groups on social networks in real time.Moreover,as deep learning techniques continue to advance and make important breakthroughs in various fields,researchers are using this technology to progressively optimize the effectiveness of Event Detection(ED)and tracking algorithms.In this regard,this paper presents an in-depth comprehensive review of the concept and methods involved in ED and tracking in social networks.We introduce mainstream event tracking methods,which involve three primary technical steps:ED,event propagation,and event evolution.Finally,we introduce benchmark datasets and evaluation metrics for ED and tracking,which allow comparative analysis on the performance of mainstream methods.Finally,we present a comprehensive analysis of the main research findings and existing limitations in this field,as well as future research prospects and challenges.

关键词： Event Detection(ED) event propagation event evolution social networks

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DCEL:classifier fusion model for Android malware detection

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Journal of Systems Engineering and Electronics 2024年第1期35卷 163-177页

作者： XU Xiaolong JIANG Shuai ZHAO Jinbo WANG Xinheng Jiangsu Key Laboratory of Big Data security&Intelligent Processing Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Computer Science Nanjing University of Posts and TelecommunicationsNanjing 210023China School of Computing and Engineering University of West LondonLondon W55RFUK

The rapid growth of mobile applications,the popularity of the Android system and its openness have attracted many hackers and even criminals,who are creating lots of Android malware.However,the current methods of Android malware detection need a lot of time in the feature engineering phase.Furthermore,these models have the defects of low detection rate,high complexity,and poor practicability,etc.We analyze the Android malware samples,and the distribution of malware and benign software in application programming interface(API)calls,permissions,and other attributes.We classify the software’s threat levels based on the correlation of features.Then,we propose deep neural networks and convolutional neural networks with ensemble learning(DCEL),a new classifier fusion model for Android malware detection.First,DCEL preprocesses the malware data to remove redundant data,and converts the one-dimensional data into a two-dimensional gray image.Then,the ensemble learning approach is used to combine the deep neural network with the convolutional neural network,and the final classification results are obtained by voting on the prediction of each single classifier.Experiments based on the Drebin and Malgenome datasets show that compared with current state-of-art models,the proposed DCEL has a higher detection rate,higher recall rate,and lower computational cost.

关键词： Android malware detection deep learning ensemble learning model fusion

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Nitrate reduction capacity of the oral microbiota is impaired in periodontitis:potential implications for systemic nitric oxide availability

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International Journal of Oral Science 2024年第1期16卷 52-61页

作者： Bob T.Rosier William Johnston Miguel Carda-Diéguez Annabel Simpson Elena Cabello-Yeves Krystyna Piela Robert Reilly Alejandro Artacho Chris Easton Mia Burleigh Shauna Culshaw Alex Mira Department of Genomics and health FISABIO FoundationCenter for Advanced Research in Public HealthValenciaSpain Department of Biological and Biomedical Sciences Glasgow Caledonian UniversityGlasgowUK Oral Sciences University of Glasgow Dental SchoolSchool of MedicineDentistry and NursingCollege of MedicalVeterinary and Life SciencesUniversity of GlasgowGlasgowUK Sport and Physical Activity Research Institute University of the West of ScotlandBlantyreScotland Instituto de Biomedicina de Valencia Consejo Superior de Investigaciones Científicas(IBV-CSIC)ValenciaSpain CIBER Center for Epidemiology and Public health MadridSpain

The reduction of nitrate to nitrite by the oral microbiota has been proposed to be important for oral health and results in nitric oxide formation that can improve cardiometabolic conditions. Studies of bacterial composition in subgingival plaque suggest that nitrate-reducing bacteria are associated with periodontal health, but the impact of periodontitis on nitrate-reducing capacity(NRC)and, therefore, nitric oxide availability has not been evaluated. The current study aimed to evaluate how periodontitis affects the NRC of the oral microbiota. First, 16S rRNA sequencing data from five different countries were analyzed, revealing that nitratereducing bacteria were significantly lower in subgingival plaque of periodontitis patients compared with healthy individuals(P healthy individuals. Salivary NRC was found to be diminished in periodontal patients before treatment(P healthy levels 90 days post-treatment. Additionally, the subgingival levels of nitrate-reducing bacteria increased after treatment and correlated negatively with periodontitis-associated bacteria(P health should be explored in future studies.

关键词： impaired intake nitrate

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HEN:a novel hybrid explainable neural network based framework for robust network intrusion detection

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Science China(Information Sciences) 2024年第7期67卷 72-90页

作者： Wei WEI Sijin CHEN Cen CHEN Heshi WANG Jing LIU Zhongyao CHENG Xiaofeng ZOU School of Computer Science and Engineering Xi'an University of TechnologyShaanxi Key Laboratory for Network Computing and Security Technology School of Computer Science and Technology Wuhan University of Science and Technology School of Future Technology South China University of Technology Shenzhen Research Institute of Hunan University School of Computer Science Hunan University of Technology and Business Institute for Infocomm Research (I2R) Agency for Science Technology and Reseach (A*STAR)

With the rapid development of network technology and the automation process for 5G, cyberattacks have become increasingly complex and threatening. In response to these threats, researchers have developed various network intrusion detection systems(NIDS) to monitor network traffic. However, the incessant emergence of new attack techniques and the lack of system interpretability pose challenges to improving the detection performance of NIDS. To address these issues, this paper proposes a hybrid explainable neural network-based framework that improves both the interpretability of our model and the performance in detecting new attacks through the innovative application of the explainable artificial intelligence(XAI)method. We effectively introduce the Shapley additive explanations(SHAP) method to explain a light gradient boosting machine(Light GBM) model. Additionally, we propose an autoencoder long-term short-term memory(AE-LSTM) network to reconstruct SHAP values previously generated. Furthermore, we define a threshold based on reconstruction errors observed during the training phase. Any network flow that surpasses the specified threshold is classified as an attack flow. This approach enhances the framework's ability to accurately identify attacks. We achieve an accuracy of 92.65%, a recall of 95.26%, a precision of 92.57%,and an F1-score of 93.90% on the dataset NSL-KDD. Experimental results demonstrate that our approach generates detection performance on par with state-of-the-art methods.

关键词： explainable artificial intelligence light gradient boosting machine machine learning network intrusion detection Shapley additive explanation hybrid explainable neural network (HEN)

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Effective Utilization of Government-Provided CTI by Small Businesses within the Defense Industrial Base

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Journal of Information security 2024年第2期15卷 196-217页

作者： Josiah Dykstra Lawrence A. Gordon Martin P. Loeb Benjamin Wall Lei Zhou National security agency Fort Meade MD USA Robert H. Smith School of Business University of Maryland College Park MD USA

There are two broad objectives of the research reported in this paper. First, we assess whether government-provided cyber threat intelligence (CTI) is helpful in preventing, or responding to, cyber-attacks among small businesses within the U.S. Defense Industrial Base (DIB). Second, we identify ways of improving the effectiveness of government-provided CTI to small businesses within the DIB. Based on a questionnaire-based survey, our findings suggest that government-provided CTI helps businesses within the DIB in preventing, or responding to, cyber-attacks providing a firm is familiar with the CTI. Unfortunately, a large percentage of small firms are not familiar with the government-provided CTI feeds and consequently are not utilizing the CTI. This latter situation is largely due to financial constraints confronting small businesses that prevent firms from having the wherewithal necessary to effectively utilize the government-provided CTI. However, we found a significant positive association between a firm’s familiarity with the government-provided CTI and whether a firm is being periodically reviewed by the Defense Counterintelligence and security agency (DCSA) or is compliant with the Cybersecurity Maturity Model Certification (CMMC) program. The findings from our study also show that the participating firms believe that external cyber threats are more likely to be the cause of a future cybersecurity breach than internal cybersecurity threats. Finally, our study found that the portion of the IT budget that small businesses within the DIB spend on cybersecurity-related activities is dependent on the perception that a firm would be the target of an external cyber-attack.

关键词： Government-Provided CTI Small Businesses Defense Industrial Base

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Seasonal variations in dissolved organic matter concentration and composition in an outdoor system for bank filtration simulation

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Journal of Environmental Sciences 2024年第1期135卷 252-261页

作者： Muhammad Zeeshan Omamah Ali Shamas Tabraiz Aki Sebastian Ruhl German Environment agency Section II 3.3Schichauweg 5812307BerlinGermany Technische Universitat Berlin Water TreatmentKF4Str.des 17.Juni 13510623BerlinGermany Natural and Applied Sciences Section School of Psychology and Life SciencesCanterbury Christ Church UniversityCanterburyCT11QUUK

Dissolved organic matter(DOM)in surface waters can vary markedly in character depending on seasonal variations such as rainfall intensity,UV radiations and temperature.Changes in DOM as well as temperature and rainfall intensity over the year can affect the biochemical processes occurring in bank filtration(BF).Identification and characterization of DOM in the surface water could help to optimize the water treatment and provide stable and safe drinking water.This study investigated year-long variations of DOM concentrations and compositions in a surface water of a circulated outdoor pond(research facility)connected to a BF passage.DOM was dominated by humic substances and a changing pattern of DOM in surface water was observed throughout the year.A significant increase of DOM(~38%)in surface water was noted in August compared to November.The fluorescent DOM showed that DOM in summer was enriched with the degradable fraction whilst non-degradable fraction was dominated in winter.A constant(1.7±0.1 mg/L)effluent DOM was recirculated in the system throughout the year.DOM removal through BF varied between 4%to 39%and was achieved within a few meters after infiltration and significantly correlated with influent DOM concentration(R^(2)=0.82,p0.05)change in the removal of DOM was observed in two subsurface layers(upper and lower).This study highlights the presence of a constant non-degradable DOM in the bank filtrate,which was not affected by temperature,redox conditions and UV radiations.

关键词： Bank filtration Dissolved organic matter Dissolved oxygen Fluorescence spectroscopy Excitation-emission matrix

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