Query the trajectory based on the precise track: a Bloom filter-based approach.

Fast and precise querying in a given set of trajectory points is an important issue of trajectory query. Typically, there are massive trajectory data in the database, yet the query sets only have a few points, which is a challenge for the superior performance of trajectory querying. The current trajectory query methods commonly use the tree-based index structure and the signature-based method to classify, simplify, and filter the trajectory to improve the performance. However, the unstructured essence and the spatiotemporal heterogeneity of the trajectory-sequence lead these methods to a high degree of spatial overlap, frequent I/O, and high memory occupation. Thus, they are not suitable for the time-critical tasks of trajectory big data. In this paper, a query method of trajectory is developed on the Bloom Filter. Based on the gridded space and geocoding, the spatial trajectory sequences (tracks) query is transformed into the query of the text string. The geospace was regularly divided by the geographic grid, and each cell was assigned an independent geocode, converting the high-dimensional irregular space trajectory query into a one-dimensional string query. The point in each cell is regarded as a signature, which forms a mapping to the bit-array of the Bloom Filter. This conversion effectively eliminates the high degree of overlap and instability of query performance. Meanwhile, the independent coding ensures the uniqueness of the whole tracks. In this method, there is no need for additional I/O on the raw trajectory data when the track is queried. Compared to the original data, the memory occupied by this method is negligible. Based on Beijing Taxi and Shenzhen bus trajectory data, an experiment using this method was constructed, and random queries under a variety of conditions boundaries were constructed. The results verified that the performance and stability of our method, compared to R*tree index, have been improved by 2000 to 4000 times, based on one million to tens of millions of trajectory data. And the Bloom Filter-based query method is hardly affected by grid size, original data size, and length of tracks. With such a time advantage, our method is suitable for time-critical spatial computation tasks, such as anti-terrorism, public safety, epidemic prevention, and control, etc.

Ultrasonic-assisted hydrothermal synthesis of cobalt oxide/nitrogen-doped graphene oxide hybrid as oxygen reduction reaction catalyst for Al-air battery.

A persistent ultrasound-assisted hydrothermal method has been developed to prepare cobalt oxide incorporated nitrogen-doped graphene (Co3O4/N-GO) hybrids. The electrochemical behaviors and catalytic activity of the prepared hybrids have been systematically investigated as cathode materials for Al-air battery. The results show that ultrasonication can promote the yield ratio of Co3O4 from 63.1% to 70.6%. The prepared Co3O4/N-GO hybrid with ultrasonication exhibits better ORR activity over that without ultrasonication. The assembled Al-air battery using the ultrasonicated Co3O4/N-GO hybrid exhibited an average working voltage of 1.02 V in 4 M KOH electrolyte at 60 mA∙cm-2, approximately 60 mV higher than that using hybrid without ultrasonication. This should be attributed to large number density of fine Co3O4 particles growing on the dispersed GO sheets under the persistent ultrasonication. The related ultrasonic mechanism has been discussed in details.

African swine fever recovery in China.

African swine fever (ASF) is the number one killer of swine on pig farms and has caused significant harm to pig farming in China since its spread. In this study, we designed a variety of physicochemical factors to explore the biological characteristics of ASF, so as to guide farms to develop disinfection measures.

[Surveying on menstruation status of reproductive age women of Han nationality in Liaoning province in 2008].

OBJECTIVE: To investigate the menstruation status of reproductive age women of Han Nationality in Liaoning province. METHODS: From Apr. 2008 to Dec. 2008, 1611 women at age of 19-45 years from Shenyang, Yingkou, Benxi, Zhangwu were enrolled in this study according to epidemiologic cluster sampling method. The study was performed by questionnaire consisting of age of menarche, regularity of menstruation, menstrual cycle and dysmenorrhea, et al. RESULTS: In the survey of 1611 women, the average menarche age is 14.4 years old, there were significant difference on menarche between (14.2 +/- 1.5) years in women from city and (14.6 +/- 1.5) years in women from country (t = 6.58, P < 0.01). The linear regression statistic method was used to analyze the relationship between age and menarche age, the linear regression equation was gotten as Y = 0.074X + 11.855, which means 1 year increase was associated with decrease by 0.074 years in menarche age approximately. About 86.34% (1391/1611) of women have normal and regular menstrual cycle at range of 21 to 35 days, while 11.05% (178/1611) of women have longer menstrual cycle (> 35 days) and 2.61% (42/1611) of women have shorter menstrual cycle (< 21 days). Of which 65.67% (1058/1611) women have regular menstrual cycle just after menarche, 94.97% (1530/1611) of women would have regular menstruation in 2 years after menarche. The rate of dysmenorrhea was 42.09% (678/1611), of which 13.6% (92/678) women have high severe pelvic pain. CONCLUSION: Our results suggested that the trend went toward younger ages of menarche, which was younger menarche age in women from city than country. About 95% women would have regular menstrual cycle within 2 years after menarche.