Research on University’s Cyber Threat Intelligence Sharing Platform Based on New Types of STIX and TAXII Standards

With the systematization of cyber threats, the variety of intrusion tools and intrusion methods has greatly reduced the cost of attackers’ threats to network security. Due to a large number of colleges and universities, teachers and students are highly educated and the Internet access rate is nearly 100%. The social status makes the university network become the main target of threat. The traditional defense method cannot cope with the current complex network attacks. In order to solve this problem, the threat intelligence sharing platform based on various threat intelligence sharing standards is established, which STIX and TAXII It is a widely used sharing standard in various sharing platforms. This paper analyzes the existing standards of STIX and TAXII, improves the STIX and TAXII standards based on the analysis results, and proposes a new type of STIX and TAXII based on the improved results. The standard design scheme of threat intelligence sharing platform suitable for college network environment features. The experimental results show that the threat intelligence sharing platform designed in this paper can be effectively applied to the network environment of colleges and universities.

“Lifting More” is Associated with Lower Risks of Depression in University Students

Research on the population in western world showed that,MSE(muscle-strengthening exercise)is beneficial to the treatment of mental disorders.However,the situation in Chinese adults is little known.For this reason,the study is performed to understand the connection between depression and MSE among college and university students in China aged between 18 to 24.1793 college students have been recruited,and their average age is 20.67.A questionnaire has been developed and it is self-reported and designed to collect information about MSE and participants,including body mass index and sex and so on.Sleep and physical activity have been evaluated by introducing two scales,that is,Pittsburgh Sleep Quality Index and International Physical Activity Questionnaire-Short Form,respectively.Moreover,Patient Health Questionnaire-9 has been adopted to indicate the severity of depression of participants.The link between depression and MSE has been studied by introducing multilevel linear regression.Among all these study participants,just 24.87%of them met the MSE standards of World Health Organization,that is,more than 2 days every week.The average depression score was 6.80(±5.19).Greater num-ber of days for MSE shows negative association with the depression,with (beta=-0.17,95%CI:-0.31 to-0.03,p=0.015).Those students failing to meet MSE standards are more susceptible to the depression risk(beta=0.63,95%CI:0.09–0.19,p=0.027).The results show that,there is a relationship between MSE participation and relieved status of depression among young adults in China.Interventions designed to relieve depression can be developed on the basis of MSE.

生态农产品品牌形象对消费者信任的影响——基于消费者社交网络参与度的调节效应

本文基于信号传递理论阐述了生态农产品品牌形象影响消费者信任的逻辑机理,并利用全国1113位有机牛奶消费者的微观调查数据,实证检验了生态农产品品牌形象对消费者信任的影响效应及其传导机制。结果表明:(1)品牌作为一种能够降低消费者选择成本的排他性品类符号,具有重要的信息传递功能,对于解决生态农产品市场的信息不对称问题有积极意义,但不同品牌的影响力和号召力不同,其原因在于品牌形象存在差异,品牌形象越好,消费者对产品信任度越高。(2)在品牌形象对消费者信任的影响关系中,消费者社交网络参与度发挥着一定程度的正向调节作用,品牌形象对社交网络参与度较高的消费者产品信任影响较为强烈。(3)品牌形象对消费者信任的影响存在一定的异质性,对于社会信任水平较低和生态认知水平较高的消费者而言,品牌形象对其产品信任的影响较为显著。

Interworking between Modbus and internet of things platform for industrial services

In the era of rapid development of Internet of Things(IoT),numerous machine-to-machine technologies have been applied to the industrial domain.Due to the divergence of IoT solutions,the industry is faced with a need to apply various technologies for automation and control.This fact leads to a demand for an establishing interworking mechanism which would allow smooth interoperability between heterogeneous devices.One of the major protocols widely used today in industrial electronic devices is Modbus.However,data generated by Modbus devices cannot be understood by IoT applications using different protocols,so it should be applied in a couple with an IoT service layer platform.oneM2M,a global IoT standard,can play the role of interconnecting various protocols,as it provides flexible tools suitable for building an interworking framework for industrial services.Therefore,in this paper,we propose an interworking architecture between devices working on the Modbus protocol and an IoT platform implemented based on oneM2M standards.In the proposed architecture,we introduce the way to model Modbus data as oneM2M resources,rules to map them to each other,procedures required to establish interoperable communication,and optimization methods for this architecture.We analyze our solution and provide an evaluation by implementing it based on a solar power management use case.The results demonstrate that our model is feasible and can be applied to real case scenarios.

Enhancing Mild Cognitive Impairment Detection through Efficient Magnetic Resonance Image Analysis

Neuroimaging has emerged over the last few decades as a crucial tool in diagnosing Alzheimer’s disease(AD).Mild cognitive impairment(MCI)is a condition that falls between the spectrum of normal cognitive function and AD.However,previous studies have mainly used handcrafted features to classify MCI,AD,and normal control(NC)individuals.This paper focuses on using gray matter(GM)scans obtained through magnetic resonance imaging(MRI)for the diagnosis of individuals with MCI,AD,and NC.To improve classification performance,we developed two transfer learning strategies with data augmentation(i.e.,shear range,rotation,zoom range,channel shift).The first approach is a deep Siamese network(DSN),and the second approach involves using a cross-domain strategy with customized VGG-16.We performed experiments on the Alzheimer’s Disease Neuroimaging Initiative(ADNI)dataset to evaluate the performance of our proposed models.Our experimental results demonstrate superior performance in classifying the three binary classification tasks:NC vs.AD,NC vs.MCI,and MCI vs.AD.Specifically,we achieved a classification accuracy of 97.68%,94.25%,and 92.18%for the three cases,respectively.Our study proposes two transfer learning strategies with data augmentation to accurately diagnose MCI,AD,and normal control individuals using GM scans.Our findings provide promising results for future research and clinical applications in the early detection and diagnosis of AD.

Women’s Social Roles and Peace Building in Al-Abassiya Locality:2012-2024

This research focused on the social roles of women in Al-Abassiya locality,South Kordofan State,examining the obstacles they face and the impact on their participation in peace building.Using qualitative methods,data were collected through various means,revealing that conflicts have significantly affected women’s lives,particularly in rural areas.Women play key roles in family,education,health services,and humanitarian aid,but their involvement in conflict resolution and peace building activities is limited.Obstacles include cognitive,economic,social,and institutional barriers.Recommendations include providing education and training programs,strengthening economic status,ensuring women’s representation in decision-making bodies,advocating for legal reforms promoting gender equality,improving access to information technologies,educating communities on women’s involvement in peace building,and providing support services for women affected by conflicts.

基于数学形态学的围棋形势判断算法

形势判断是人类棋手必不可少的抽象概念,计算机围棋可以建立此概念以提高搜索效率.该文在数学形态学的形式化基础上探讨了对围棋实地和外势进行估算的过程,并结合实战对局评价了此算法的性能,指出了此算法的应用价值.

85Al2O3/SiC纳米复合陶瓷的表面抛光性能

以工业中广泛使用的85氧化铝陶瓷原料粉为原料,加入纳米碳化硅,通过控制无压埋烧制备了85Al2O3/SiC纳米复合陶瓷,研究了其表面抛光行为,讨论了纳米碳化硅对复合陶瓷表面抛光性能的影响.结果表明,纳米复合陶瓷表现出显著优于基体材料的表面抛光响应,在同样的磨料尺寸下,复合陶瓷能够得到更好的表面抛光质量.SEM分析表明,纳米碳化硅的加入使材料的抛光去除机制发生了改变,由大范围的深层晶粒拔出变为小尺寸的浅层去除和塑性变形.

85Al_2O_3／SiC纳米复合陶瓷的耐磨损性能研究

通过控制无压埋烧条件制备了85Al2O3／SiC纳米复合陶瓷,重点研究了纳米碳化硅对复合陶瓷耐磨损性能的影响。结果表明,纳米复合陶瓷表现出显著优于基体材料的表面耐磨损特性。SEM分析表明,纳米碳化硅的加入使材料的磨损去除机制发生了改变,由大范围的深层晶粒拔出变为小尺寸的浅层去除和塑性变形。

Iron and liver fibrosis: Mechanistic and clinical aspects

Liver fibrosis is characterised by excessive deposition of extracellular matrix that interrupts normal liver functionality. It is a pathological stage in several untreated chronic liver diseases such as the iron overload syndrome hereditary haemochromatosis, viral hepatitis, alcoholic liver disease, non-alcoholic fatty liver disease, non-alcoholic steatohepatitis and diabetes. Interestingly, regardless of the aetiology, iron-loading is frequently observed in chronic liver diseases. Excess iron can feed the Fenton reaction to generate unquenchable amounts of free radicals that cause grave cellular and tissue damage and thereby contribute to fibrosis. Moreover, excess iron can induce fibrosis-promoting signals in the parenchymal and non-parenchymal cells, which accelerate disease progression and exacerbate liver pathology. Fibrosis regression is achievable following treatment, but if untreated or unsuccessful, it can progress to the irreversible cirrhotic stage leading to organ failure and hepatocellular carcinoma, where resection or transplantation remain the only curative options. Therefore,understanding the role of iron in liver fibrosis is extremely essential as it can help in formulating iron-related diagnostic, prognostic and treatment strategies. These can be implemented in isolation or in combination with the current approaches to prepone detection, and halt or decelerate fibrosis progression before it reaches the irreparable stage. Thus, this review narrates the role of iron in liver fibrosis. It examines the underlying mechanisms by which excess iron can facilitate fibrotic responses. It describes the role of iron in various clinical pathologies and lastly,highlights the significance and potential of iron-related proteins in the diagnosis and therapeutics of liver fibrosis.

Data-Driven Anomaly Diagnosis for Machining Processes

To achieve zero-defect production during computer numerical control(CNC)machining processes,it is imperative to develop effective diagnosis systems to detect anomalies efficiently.However,due to the dynamic conditions of the machine and tooling during machining processes,the relevant diagnosis systems currently adopted in industries are incompetent.To address this issue,this paper presents a novel data-driven diagnosis system for anomalies.In this system,power data for condition monitoring are continuously collected during dynamic machining processes to support online diagnosis analysis.To facilitate the analysis,preprocessing mechanisms have been designed to de-noise,normalize,and align the monitored data.Important features are extracted from the monitored data and thresholds are defined to identify anomalies.Considering the dynamic conditions of the machine and tooling during machining processes,the thresholds used to identify anomalies can vary.Based on historical data,the values of thresholds are optimized using a fruit fly optimization(FFO)algorithm to achieve more accurate detection.Practical case studies were used to validate the system,thereby demonstrating the potential and effectiveness of the system for industrial applications.

Urban and river flooding:Comparison of flood risk management approaches in the UK and China and an assessment of future knowledge needs

Increased urbanisation,economic growth,and long-term climate variability have made both the UK and China more susceptible to urban and river flooding,putting people and property at increased risk.This paper presents a review of the current flooding challenges that are affecting the UK and China and the actions that each country is undertaking to tackle these problems.Particular emphases in this paper are laid on(1)learning from previous flooding events in the UK and China,and(2)which management methodologies are commonly used to reduce flood risk.The paper concludes with a strategic research plan suggested by the authors,together with proposed ways to overcome identified knowledge gaps in flood management.Recommendations briefly comprise the engagement of all stakeholders to ensure a proactive approach to land use planning,early warning systems,and water-sensitive urban design or redesign through more effective policy,multi-level flood models,and data driven models of water quantity and quality.

Isogeometric analysis of free-form Timoshenko curved beams including the nonlinear effects of large deformations

In the present paper, the isogeometric analysis（IGA） of free-form planar curved beams is formulated based on the nonlinear Timoshenko beam theory to investigate the large deformation of beams with variable curvature. Based on the isoparametric concept, the shape functions of the field variables（displacement and rotation） in a finite element analysis are considered to be the same as the non-uniform rational basis spline（NURBS） basis functions defining the geometry. The validity of the presented formulation is tested in five case studies covering a wide range of engineering curved structures including from straight and constant curvature to variable curvature beams. The nonlinear deformation results obtained by the presented method are compared to well-established benchmark examples and also compared to the results of linear and nonlinear finite element analyses. As the nonlinear load-deflection behavior of Timoshenko beams is the main topic of this article, the results strongly show the applicability of the IGA method to the large deformation analysis of free-form curved beams. Finally, it is interesting to notice that, until very recently, the large deformations analysis of free-form Timoshenko curved beams has not been considered in IGA by researchers.

3D printing of PEEK–cHAp scaffold formedical bone implant

The major drawback associated with PEEK implants is their biologically inert surface,which caused unsatisfactory cellular response and poor adhesion between the implants and surrounding soft tissues against proper bone growth.In this study,polyetheretherketone(PEEK)was incorporated with calcium hydroxyapatite(cHAp)to fabricate a PEEK-cHAp biocomposite,using the fused deposition modeling(FDM)method and a surface treatment strategy to create microporous architectures onto the filaments of PEEK lattice scaffold.Also,nanostructure and morphological tests of the PEEK-cHAp biocomposite were modeled and analyzed on the FDM-printed PEEK-cHAp biocomposite sample to evaluate its mechanical and thermal strengths as well as in vitro cytotoxicity via a scanning electron microscope(SEM).A technique was used innovatively to create and investigate the porous nanostructure of the PEEK with controlled pore size and distribution to promote cell penetration and biological integration of the PEEK-cHAp into the tissue.In vivo tests demonstrated that the surface-treated micropores facilitated the adhesion of newly regenerated soft tissues to form tight implant-tissue interfacial bonding between the cHAp and PEEK.The results of the cell culture depicted that PEEK-cHAp exhibited better cell proliferation attachment spreading and higher alkaline phosphatase activity than PEEK alone.Apatite islands formed on the PEEK-cHAp composite after immersion in simulated body fluid of Dulbecco’s modified Eagle medium(DMEM)for 14 days and grew continuously with more or extended periods.The microstructure treatment of the crystallinity of PEEK was comparatively and significantly different from the PEEK-cHAp sample,indicating a better treatment of PEEK-cHAp.The in vitro results obtained from the PEEK-cHAp biocomposite material showed its biodegradability and performance suitability for bone implants.This study has potential applications in the field of biomedical engineering to strengthen the conceptual knowledge of FDM and medical implants fabricated from PEEK-cHAp biocomposite materials.

石墨烯增强铝基复合材料硬度的研究

为了提高铝合金的性能,提出把石墨烯作为增强相制备铝基复合材料的新方法。球磨工艺是复合材料制备的核心环节,研究了球磨工艺参数(球磨介质、球磨转速、球料比、球磨时间)对复合粉体形貌的影响,对比分析确定了最佳球磨参数。利用热等静压方式制备质量分数为0.05%和0.1%的铝基复合材料并进行了硬度测试。实验结果表明:在球磨转速240 r/min、球料比6∶1、球磨时间16 h下进行湿法球磨获得的复合粉体石墨烯包裹均匀;质量分数为0.1%时硬度最高,成形的铝基复合材料硬度较纯Zl114A提高了23.59%。

Modeling the dose-response rate/associations between VO2max and self-reported Physical Activity Questionnaire in children and adolescents

Background'. This study sought to explore the dose—response rate/association between aerobic fitness (VC)2max) and self-reported physical activity(PA) and to assess whether this association varies by sex, age, and weight status.Methods. VO2max was assessed using the 20・m shuttle・run test. PA was assessed using the Physical Activity Questionnaire (PAQ) for Adolescents(aged > 11 years, PAQ-A) or for Children (aged <11 years, PAQ-C). The associations between V02raax and PAQ were analyzed using analysisof covariance (ANCOVA), adopting PAQ and PAQ2 as covariates but allowing the intercepts and slope parameters of PAQ and PAQ2 tovary with the categorical variables sex, age group, and weight status.Results: ANCOVA identified a curvilinear association between VO2max and PAQ, with positive linear PAQ terms that varied for both sex andweight status but with a negative PAQ2 term of —0.39 (95% confidence interval (CI): —0.57 to —0.21) that was common for all groups in regardto age, sex, and weight status. These curvilinear (inverted U) associations suggest that the benefits of increasing PA (same dose) on VO2max isgreater when children report lower levels of PA compared to children who report higher levels of PA. These dose-response rates were alsosteeper for boys and were steeper for lean children compared to overweight/obese children.Conclusion'. Health practitioners should be aware that encouraging greater PA (same dose) in inactive and underweight children will result ingreater gains in V02max (response) compared with their active and overweight/obese counterparts.

Incorporation of a nanotechnology-based additive in cementitious products for clay stabilisation

The mechanical performances and water retention characteristics of clays,stabilised by partial substitution of cement with by-products and inclusion of a nanotechnology-based additive called RoadCem(RC),are studied in this research.The unconfined compression tests and one-dimensional oedometer swelling were performed after 7 d of curing to understand the influence of addition of 1%of RC material in the stabilised soils with the cement partially replaced by 49%,59%and 69%of ground granulated blast furnace slag(GBBS)or pulverised fuel ash(PFA).The moisture retention capacity of the stabilised clays was also explored using the soil-water retention curve(SWRC)from the measured suctions.Results confirmed an obvious effect of the use of RC with the obtained strength and swell properties of the stabilised clays suitable for road application at 50%replacement of cement.This outcome is associated with the in-depth and penetrating hydration of the cementitious materials by the RC and water which results in the production of needle-like matrix with interlocking filaments e a phenomenon referred to as the‘wrapping’effect.On the other hand,the SWRC used to describe the water holding capacity and corresponding swell mechanism of clays stabilised by a proportion of RC showed a satisfactory response.The moisture retention of the RC-modified clays was initially higher but reduced subsequently as the saturation level increased with decreasing suction.This phenomenon confirmed that clays stabilised by including the RC are water-proof in nature,thus ensuring reduced porosity and suction even at reduced water content.Overall,the stabilised clays with the combination of cement,GGBS and RC showed a better performance compared to those with the PFA included.

An Enhanced Direct Anonymous Attestation Scheme with Mutual Authentication for Network-Connected UAV Communication Systems

In network-connected UAV(NCUAV) communication systems, user authentication is replaced by platform identity authentication and integrity check because many NC-UAVs are operated without human intervention. Direct anonymous attestation(DAA) is an attractive cryptographic scheme that provides an elegant balance between platform authentication and anonymity. However, because of the low-level computing capability and limited transmission bandwidth in UAV, the existing DAA schemes are not suitable for NC-UAV communication systems. In this paper, we propose an enhanced DAA scheme with mutual authentication(MA-DAA scheme), which meets the security requirements of NC-UAV communication systems. The proposed MA-DAA scheme, which is based on asymmetric pairings, bundles the identities of trusted platform module(TPM) and Host to solve the malicious module changing attacks. Credential randomization, batch proof and verification, and mutual authentication are realized in the MA-DAA scheme. The computational workload in TPM and Host is reduced in order to meet the low computation and resource requirements in TPM and Host.The entire scheme and protocols are presented,and the security and efficiency of the proposed MA-DAA scheme are proved and analyzed.Our experiment results also confirm the high efficiency of the proposed scheme.

Simulation Based Energy-resource Efficient Manufacturing Integrated with In-process Virtual Management

As energy efficiency is one of the key essentials towards sustainability, the development of an energy-resource efficient manufacturing system is among the great challenges facing the current industry. Meanwhile, the availability of advanced technological innovation has created more complex manufacturing systems that involve a large variety of processes and machines serving different functions. To extend the limited knowledge on energy-efficient scheduling, the research presented in this paper attempts to model the production schedule at an operation process by considering the balance of energy consumption reduction in production, production work flow （productivity） and quality. An innovative systematic approach to manufacturing energy-resource efficiency is proposed with the virtual simulation as a predictive modelling enabler, which provides real-time manufacturing monitoring, virtual displays and decision-makings and consequentially an analytical and multidimensional correlation analysis on interdependent relationships among energy consumption, work flow and quality errors. The regression analysis results demonstrate positive relationships between the work flow and quality errors and the work flow and energy consumption. When production scheduling is controlled through optimization of work flow, quality errors and overall energy consumption, the energy-resource efficiency can be achieved in the production. Together, this proposed multidimensional modelling and analysis approach provides optimal conditions for the production scheduling at the manufacturing system by taking account of production quality, energy consumption and resource efficiency, which can lead to the key competitive advantages and sustainability of the system operations in the industry.

End-cloud collaboration method enables accurate state of health and remaining useful life online estimation in lithium-ion batteries

Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network.