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Background Acute bacterial meningitis (ABM) is a serious health issue in Yemen where civil war, which continues unabated, has crippled the healthcare system. We conducted a nationwide retrospective observational study in Yemeni sentinel hospitals to identify the prevalence, aetiology, vaccination coverage and spatio-temporal pattern of ABM in children aged Methods Cerebrospinal fluid samples were collected from hospitalized children and were analysed macroscopically for appearance and microscopically by Gram stain and white blood cell count. Culture and latex agglutination tests were performed. Data on the prevalence of and vaccination coverage for ABM were obtained from the Ministry of Health. Joinpoint regression was used to assess the annual percent change (APC) of ABM prevalence and vaccination coverage. Pearson's correlation was used to evaluate the association between ABM prevalence and vaccination coverage. Results In total, 11 339 hospitalized children had suspected cases of ABM (prevalence, 40.07/100 000 of the whole Yemeni population) and 2.6% (293/11 339) of suspected ABM cases were confirmed (prevalence, 1.04/100 000 of the whole Yemeni population). The dominant pathogens were Streptococcus pneumoniae, Neisseria meningitidis and Haemophilus influenzae type b (Hib). The civil war reduced the Hib and pneumococcal vaccination coverage (APC = –1.92), reaching its lowest (79.5%) in 2018. The prevalence of suspected ABM increased (APC = 3.46), reaching its maximum (6.08/100 000 of the whole Yemeni population) in 2019. The conflict inversely correlated with the ABM prevalence and vaccination coverage (Pearson correlation coefficient (r), –0.69 to –0.53). Ta'izz region, which was severely affected by the civil war, had the highest prevalence of suspected ABM (120.90/100 000 of the whole Yemeni population) and lowest vaccination coverage (60%). Conclusions The civil war had a negative impact on vaccination coverage and coincided with increasing prevalence of ABM in Yemen. Streptococcus pneumoniae is the dominant causative pathogen.

Introduction Vaccination coverage is widely used as metric of vaccination programme performance. However, VPDs outbreaks were reported in areas with high vaccination coverage. Timeliness and completeness have been considered more important assessment indicators of routine vaccination than overall vaccination coverage, but little is known in rural China. This study aimed to assess the timeliness and completeness of serial routine vaccinations among children in rural Southwest China. Methods A multi-stage stratified cluster survey was conducted among 1062 children aged 18–48 months in rural Guangxi. Vaccination status was obtained from child’s vaccination certificate. We calculated timely vaccination coverage, complete vaccination coverage, timely-and-complete vaccination coverage and 95% CI for routine vaccination through weighted estimation analysis. Weighted Kaplan-Meier analyses were applied to estimate the median delay periods for each dose of serial routine vaccines, including one-dose BCG, three-dose HepB, three-dose OPV, four-dose DTP, two-dose MCV, two-dose JEV and two-dose MPV-A. Complete coverage, and timely-and-complete coverage for combined 5-vaccine series were calculated. Results For each dose of routine vaccines, overall vaccination coverages were over 90%, but timely vaccination coverage ranged from the lowest of 44.4% for JEV1 to the highest of 92.5% for MPV-A1. For multi-dose routine vaccines, complete vaccination coverages varied from the lowest of 92.9% for MCV to the highest of 100% for HepB, and timely-and-complete vaccination coverages were lower than 80%, ranging from the lowest of 30% for JEV to the highest of 77.2% for MPV-A. For combined 5-vaccine series, complete coverage was 77%, while timely-and-complete coverage was 12.1%. MPV-A1 had the longest median delay of 176 days, but BCG and HepB1 had the shortest of 1 day. Conclusions The overall coverages of serial routine vaccinations were high, but the timeliness and completeness were poor. Relevant agencies of vaccination service should address timeliness-and-completeness into the assessment indicators of routine vaccination service quality.

Ontology is a research for machine understandable semantic information, which is the foundation for semantic web service description. Efforts are being made to research fuzzy ontology for expressing inherent fuzzy/imprecise information. But the description language for fuzzy ontology is still under discussion and there is no widely agreed standard yet. In this context, a fuzzy description language - fuzzy owl for Fuzzy SROIQ(D) with self-defined fuzzy data type and fuzzy modifier is proposed. Fuzzy owl is equipped with independent terminologies and grammars, that it's able to express fuzzy concepts, extended fuzzy data types, variables and fuzzy modifiers. A parser and an editor are developed to edit fuzzy ontology visibly and generate fuzzy owl files automatically, which eases the trouble of creating fuzzy ontology manually.

With the development of semantic Web service, the service registry has expanded constantly to cater for new demands. How to improve the efficiency of service discovery is treated as one of the top priorities to be solved. Semantic Web service clustering can organizes and manages the service registry to narrow the scope of service search. This paper has proposed a framework of semantic Web service clustering, designed and implemented an algorithm of semantic Web service clustering by using the Single-Linkage Thinking. This algorithm clusters the services of service registry in order to narrow the scope of service search and improve the efficiency of service discovery. Experimental results show that the clustering framework and algorithm in this paper is efficient, accurate and easy to implement.

Proper QoS selection method helps consumers find more appropriate service and increases their success in invoking the service. In this paper we propose an extended fuzzy multi-criteria group decision making model to solve the QoS selection problem. It takes experts' opinion as the base data of decision making and receives consumer's preference to yield the most fitted service for consumers. Consumers' feedback is also considered to help make a right choice. The method is effective that among services of equal competence it selects the one that most meets consumer's expectation and among those that equally satisfy a consumer, the one with greatest competence will be chosen. Experiments are carried out to proof the effectiveness of the method.

Semantic similarity between ontological concepts plays an important role in service discovery and composition. In this paper, using the ontological relation, a novel intuitionistic fuzzy set model is proposed to interpret concepts on the ontology with three intuitionistic fuzzy sets of different weights, and an effective similarity measure of which is selected to calculate the concept similarity. The model successfully translates all the semantic information of a concept into mathematical expressions of intuitionistic fuzzy sets, thus concept similarity is easily calculated. It is designed to handle not only simple ontologies where only atomic concepts are presented, but also complex ones where concepts could inherit from multiple concepts and have semantic relations other than is-a with other concepts. The experimental result has shown that the model is effective, and it's easy to implement.

Fuzzy Description Logic is a fuzzified extension of classical description logic to allow fuzzy expression and reasoning of knowledge. Owing to the limitation of traditional description logic applied to precise knowledge only, there have been a lot of researches on the fuzzification of classical description logic. However, so far, the results are still very limited in the ability of expression. In this paper, we use variable, a new data type, to extend a fuzzy customized datatype. Meanwhile, we also discuss how this extension can be used to enhance the expression ability of fuzzy modifiers.

With the rapid development of RFID (Radio Frequency Identification) technology, RFID middleware has increasingly become the focus. How to process massive RFID data with high-performance is a key issue. This paper analyzes the characteristics of the RFID event filtering in RFID middleware, proposes a RFID EPC Sub-Pattern Match Model using Automata Theory and presents a high-performance matching algorithm for RFID event filtering with bit-parallelism, which has been implemented in our RFID middleware system. Performance evaluation results have indicated that this algorithm is more efficient than the regular expression matching algorithm used before.

The integration of RFID technology and mobile smart device stimulates the daily increasingly popularity of mobile RFID-based applications, which makes its way to become a new hot zone of research and development. However, the diversities of the hardware and software as well as the resource constraints on devices are the first problems developer needs to resolve. One of the most highly effective solutions is the middleware technology. This paper presents a design and implementation of lightweight-ALE-based embedded RFID middleware, which provides a unified interface, event processing mechanism and other mechanisms. Featured with reconfigurable, scalable and transplantable capability, the middleware can provide a unified platform for applications and make the development much more convenient.