The BABAR Collaboration BABAR, the detector for the SLAC PEP-II asymmetric e + e − B Factory operating at the Υ (4S) resonance, was designed to allow comprehensive studies of CP -violation in B-meson decays. Charged particle tracks are measured in a multi-layer silicon vertex tracker surrounded by a cylindrical wire drift chamber. Electromagnetic showers from electrons and photons are detected in an array of CsI crystals located just inside the solenoidal coil of a superconducting magnet. Muons and neutral hadrons are identified by arrays of resistive plate chambers inserted into gaps in the steel flux return of the magnet. Charged hadrons are identified by dE/dx measurements in the tracking detectors and in a ring-imaging Cherenkov detector surrounding the drift chamber. The trigger, data acquisition and data-monitoring systems , VME-and network-based, are controlled by custom-designed online software. Details of the layout and performance of the detector components and their associated electronics and software are presented.

Background Various types of near work have been suggested to promote the incidence and progression of myopia, while outdoor activity appears to prevent or retard myopia. However, there is a lack of consensus on how to interpret these results and translate them into effective intervention strategies. This study examined the association between visual acuity and time allocated to various activities among school-going children. Methods Population-based survey of 19,934 students in grade 4 and 5 from 252 randomly selected rural primary schools in Northwest China in September 2012. This survey measured visual acuity and collected self-reported data on time spent outdoors and time spent doing various types of near activities. Results Prolonged (>60 minutes/day) computer usage (-0.025 LogMAR units, P = .011) and smartphone usage (-0.041 LogMAR units, P = .001) were significantly associated with greater refractive error, while television viewing and after-school study were not. For time spent outdoors, only time around midday was significantly associated with better uncorrected visual acuity. Compared to children who reported no midday time outdoors, those who spent time outdoors at midday for 31–60 minutes or more than 60 minutes had better uncorrected visual acuity by 0.016 LogMAR units (P = .014) and 0.016 units (P = .042), respectively. Conclusions Use of smart phones and computers were associated with declines in children’s vision, while television viewing was not. Statistically significant associations between outdoor time at midday and reduced myopia may support the hypothesis that light intensity plays a role in the protective effects of outdoor time.

This study examines the impact of social engagement on elderly health in China. A two-stage residual inclusion (2SRI) regression approach was used to examine the causal relationship. Our dataset comprises 9253 people aged 60 or above from the China Health and Retirement Longitudinal Survey (CHARLS) conducted in 2011 and 2013. Social engagement significantly improved the self-rated health of the elderly and reduced mental distress, but had no effect on chronic disease status. Compared with the rural areas, social engagement played a more important role in promoting the elderly health status in urban areas. Social engagement could affect the health status of the elderly through health behavior change and access to health resources. To improve the health of the elderly in China and promote healthy aging, the government should not only improve access to effective medical care but also encourage greater social engagement of the elderly.

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In light of the problems of low recognition efficiency, high false rates and poor localization accuracy in traditional pipeline security detection technology, this paper proposes a type of hierarchical leak detection and localization method for use in natural gas pipeline monitoring sensor networks. In the signal preprocessing phase, original monitoring signals are dealt with by wavelet transform technology to extract the single mode signals as well as characteristic parameters. In the initial recognition phase, a multi-classifier model based on SVM is constructed and characteristic parameters are sent as input vectors to the multi-classifier for initial recognition. In the final decision phase, an improved evidence combination rule is designed to integrate initial recognition results for final decisions. Furthermore, a weighted average localization algorithm based on time difference of arrival is introduced for determining the leak point’s position. Experimental results illustrate that this hierarchical pipeline leak detection and localization method could effectively improve the accuracy of the leak point localization and reduce the undetected rate as well as false alarm rate.