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Cotton fabric is widely used on many occasions, but it is flammable with high fire risk. To meet the great fire safety demands of cotton fabric, a novel Lignocellulosic-based P–N synergistic (LFPN) flame-retardant coating with high efficiency and environment friendly was developed via mechanochemistry strategy in the aqueous phase. The characterisation results showed the stable P–O–C bond formed to bind both lignocellulosic fibre and Ammonium polyphosphate (APP). Meanwhile, LFPN has an excellent dispersion in water with a nanometer-scale enveloping rod structure. The cotton fabric treated by the LFPN coating showed outstanding flame-retardant properties, the Peak heat release rate (PHRR) was reduced by 84.4%, and the Limiting oxygen index (LOI) value was increased by 150.7% compared with control cotton fabric. Moreover, there was a self-extinction phenomenon during the Vertical flammability test (VFT) of flame retardant cotton. Based on the analysis of the combustion and pyrolysis process, a gas-condensed two-phase flame retardant mechanism model was proposed, which could explain the action process of LFPN for cotton fabric during combustion. Graphical abstract

With the increasing utilization of space related data, the demand for spatial big data sharing and trading is growing rapidly, which promotes the emergence of spatial data market. However, in conventional data markets, both data buyers and data sellers have to use a centralized trading platform which might be dishonest. Blockchain is a decentralized distributed data storage technology, which uses the traceability and unforgeability to confirm and record each transaction, and can solve partial disadvantages of the centralized data market; unfortunately, it also introduces the problems of security and privacy. To address this issue, in this paper, we propose a blockchain-based spatial data trading framework with trusted execution environment to provide a trusted decentralized platform, including data storage, data query, data pricing, data reputation and security computing. Based on this framework, we use an auction pricing mechanism to ensure data trading authenticity and efficiency. At last, a spatial data trading framework was implemented and its effectiveness and security were verified.

IOTA is a new public chain system specifically designed for the Internet of Things (IoT), which provides strong support for the high concurrency, scalability, and zero handling fees of the IoT. The distributed ledger of IOTA, called the tangle, adopts a Directed Acyclic Graph (DAG) structure. However, compared to the single-chain architecture, the tangle is more complex and highly vulnerable to security threats. The existing transaction verification methods still cannot simultaneously meet the need for accelerating approval speed and improving security to resist illegal transactions, such as lazy tips and permanent tips. In this work, we propose TDTS, a tip-selection algorithm based on time division to improve the efficiency of transaction verification. The main idea of the algorithm is to quickly determine two tips of an incoming transaction that need to be confirmed by sorting tip values in a time slot. It shortens the transaction verification time and reduces the number of lazy tips and permanent tips. A comprehensive theoretical analysis confirmed the effectiveness of our proposed algorithm. Based on 1000 IOTA nodes, the evaluations showed that TDTS can select tips quickly like URTS and resist lazy tips like MCMC.

IOTA is a new cryptocurrency system designed for the Internet of Things based on directed an acyclic graph structure. It has the advantages of supporting high concurrency, scalability, and zero transaction fees; however, due to the particularity of the directed acyclic graph structure, IOTA faces more complex security threats than the sequence blockchain, in which a parasite chain attack is a common double-spending attack. In this work, we propose a scheme that can effectively prevent parasite chain attacks to improve the security of the IOTA ledger. Our main idea is to analyze the behavior strategies of IOTA nodes based on evolutionary game theory and determine the key factors affecting the parasite chain attack and the restrictive relationship between them. Based on the above research, we provide a solution to resist the parasite chain attack and further prove the effectiveness of the scheme by numerical simulation. Finally, we propose the parasite chain attack prevention algorithms based on price splitting to effectively prevent the formation of the parasite chain.

IOTA is an emerging decentralized computing paradigm for developing blockchain-based Internet of Things (IoT) applications. It has the advantages of zero transaction fees, incremental scalability, and high-performance transaction rates. Despite its well-understood benefits, IOTA nodes need to withstand considerable resource costs to generate the distributed ledger. The main reason for this is that IOTA abandons the original blockchain reward mechanism and does not charge transaction fees. Therefore, in this paper we address the cost optimization issue for IOTA based on Lyapunov optimization theory. We take the first step in investigating the cost optimization problem of IOTA and exploring a new optimization scheme using Lyapunov optimization theory. Our proposed scheme enables IOTA to minimize the total cost of IOTA nodes through a computational optimization algorithm. Then, an optimized transaction rate control algorithm can be designed based on the large deviation theory to reduce orphan tangles that waste computational costs. In addition, we define and deduce the effective width of the tangle to monitor the total throughput and reduce the time spent on cost optimization to avoid unnecessary waste of resources. Lastly, a comprehensive theoretical analysis and simulation experiments demonstrate that the proposed strategy is both efficient and practical.

The RAMS (reliability, availability, maintainability, and security) of the air braking system is an important indicator to measure the safety performance of the system; it can reduce the life cycle cost (LCC) of the rail transit system. Existing safety analysis methods are limited to the level of relatively simple factual descriptions and statistical induction, failing to provide a comprehensive safety evaluation on the basis of system structure and accumulated data. In this paper, a new method of safety analysis is described for the failure mode of the air braking system, GO-Bayes. This method combines the structural modeling of the GO method with the probabilistic reasoning of Bayes methods, introduces the probability into the analysis process of GO, performs reliability analysis of the air braking system, and builds a big data platform for the air braking system to guide the system maintenance strategy. An automatic train air braking system is taken as an example to verify the usefulness and accuracy of the proposed method. Using ExtendSim software shows the feasibility of the method and its advantages in comparison with fault tree analysis.

PurposeThe purpose of this study is to establish a grey-entropy-catastrophe progression method (CPM) model to assess the photovoltaic (PV) industry chain resilience of Jiangsu Province in China.Design/methodology/approachFirst, we designed the resilience evaluation index system of such a chain from two aspects: the external environment and internal conditions. We then constructed a PV industry chain resilience evaluation model based on the grey-entropy-CPM. Finally, the feasibility and applicability of the proposed model were verified via an empirical case study analysis of Jiangsu Province in China.FindingsAs of the end of 2022, the resilience level of its PV industry chain is medium-high resilience, which indicates a high degree of adaptability to the current unpredictable and competitive market, and can respond to the uncertain impact of changes in conditions effectively and in a timely manner.Practical implicationsThe construction of this model can provide reference ideas for related enterprises in the PV industry to analyze the resilience level of the industrial chain and solve the problem of industrial chain resilience.Originality/valueFirstly, an analysis of the entire industrial chain structure of the PV industry, combined with its unique characteristics is needed to design a PV industry chain resilience evaluation index system. Second, grey relational analysis (GRA) and the entropy method were adopted to improve the importance of ranking the indicators in the evaluation of the CPM, and a resilience evaluation model based on grey-entropy-CPM was constructed.

The high flammability of cotton fabric limits its wide application in interior decoration and clothing. In this work, a phosphorus/nitrogen compound named chitosan modified ammonium polyphosphate (CS@APP) was facilely prepared by mechanochemical strategy and used for flame retardant finishing of cotton fabric (CF). The characterization results showed that CS@APP was successfully synthesized through the –NH3+–O−P– bond. The CF with CS@APP showed remarkable reductions of 88.7% and 61.3% in peak heat release rate (pHRR) and total heat release rate than CF. Also, the limiting oxygen index of flame retardant CF reached 53.5%, and the damaged length during the vertical flammability test was 84 mm. The flame-retardant mechanism was speculated on char residues and pyrolysis gas. The work provides new sights on the facile synthesis of phosphorylated chitosan and explores a new way to the utilization of biological resources.

ObjectivesTo characterise the prevalence and distribution of human papillomavirus (HPV) types in genital warts in Xi’an, China.MethodsThis prospective study was conducted in Shaanxi Provincial Institute for Skin Disease and STD Control (SPISSC) between September 2014 and April 2017. Genital wart samples were obtained from 879 patients, including 512 men and 367 women. HPV genotyping was performed by using an automatic nucleic acid hybridisation system.ResultsOf the 879 patients with genital warts, the detectable rates of low-risk, high-risk and total HPV types were 45.4%, 34.5% and 57.8%, respectively. The detectable rate of low-risk HPV types (45.4%) was significantly higher than that of high-risk HPV types (34.5%) (χ2=21.85, p<0.01). The detectable rate of low-risk HPV types of men (52.3%) was significantly higher than that of women (35.7%) (χ2=23.90, p<0.01). The detectable rates of one HPV type infection and two and three or more HPV type coinfections were 26.1%, 17.5% and 14.2%, respectively. HPV6 (24.9%), HPV11 (17.9%), HPV52 (9.9%) and HPV16 (7.3%) were the four most common HPV types.ConclusionsThe results of this study suggest that low-risk HPV types are major pathogens of genital warts, but high-risk HPV type infections and multiple HPV type coinfections are also common in genital warts. HPV6, 11, 52 and 16 are the four most common HPV types in genital wart in Xi’an, China.

Fibrous dysplasia (FD) of the bone is rare and self-limiting. However, lesion expansion may occur, causing pain, deformity and pathological fracture, in which case surgery is occasionally required. Indicators of FD have not been previously described, although there are several surgical procedures reported (curettage, curettage and graft, and internal fixation). In this study we discuss whether intramedullary nailing of these lesions could result in more favorable outcomes in correcting deformities, including the prevention of secondary fractures and maintenance of the bone, compared to other internal fixation methods. A total of 39 patients with FD of the bone treated with intramedullary nailing were retrospectively analyzed. The surgical procedures involved curettage, grafting and intramedullary nailing. No infection, thromboembolism or other notable complications occurred. The patients resumed full activities of daily living. At the last follow-up, 33 patients presented no pain and seven patients had occasional mild pain. The clinical score according to the modified criteria of Guille improved from an average of 4.4 points prior to surgery to an average of 8 points following surgery. The neck shaft angle of the femur improved from an average of 90˚ prior to surgery to 125˚ following surgery. Intramedullary nailing may be used to correct deformity and prevent pain and refracture in FD of the bone of the lower limbs with large lesions, pathological fracture or deformities. All patients were allowed full athletic recovery following surgery.