MeTACAST: Target- and Context-Aware Spatial Selection in VR.

We propose three novel spatial data selection techniques for particle data in VR visualization environments. They are designed to be target- and context-aware and be suitable for a wide range of data features and complex scenarios. Each technique is designed to be adjusted to particular selection intents: the selection of consecutive dense regions, the selection of filament-like structures, and the selection of clusters-with all of them facilitating post-selection threshold adjustment. These techniques allow users to precisely select those regions of space for further exploration-with simple and approximate 3D pointing, brushing, or drawing input-using flexible point- or path-based input and without being limited by 3D occlusions, non-homogeneous feature density, or complex data shapes. These new techniques are evaluated in a controlled experiment and compared with the Baseline method, a region-based 3D painting selection. Our results indicate that our techniques are effective in handling a wide range of scenarios and allow users to select data based on their comprehension of crucial features. Furthermore, we analyze the attributes, requirements, and strategies of our spatial selection methods and compare them with existing state-of-the-art selection methods to handle diverse data features and situations. Based on this analysis we provide guidelines for choosing the most suitable 3D spatial selection techniques based on the interaction environment, the given data characteristics, or the need for interactive post-selection threshold adjustment.

Chuankezhi injection for asthma: Protocol of a systematic review and meta-analysis.

BACKGROUND: Asthma is a chronic inflammatory disease characterized by recurrent attacks of breathlessness and wheezing, which often worsen at night or in the early morning and vary from person to person in severity and frequency. Chuankezhi injection (CKZ), as a new Chinese medicine, was recently found to have a good clinical effect on asthma. Whereas neither systematic nor meta-analysis of randomized controlled trials (RCTs) explain the efficacy of CKZ in treating asthma. Therefore, we provide a protocol to evaluate the efficacy and safety of CKZ for asthma. METHODS: From inception until April 2019, a systematic and comprehensive literature search will be conducted in both 4 Chinese databases and 3 English databases. RCTs will be included related to CKZ for asthma. We will assess the quality of the included trials in accordance with the risk of bias tools in Cochrane manual 5.1.0. We will use the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) method to assess the certainty of the estimated evidence. Data analysis will be performed using the STATA 15.0. RESULTS: This systematic review aims to assess the effectiveness and safety of CKZ for the treatment of asthma, in order to provide evidence for the clinical practice of Chinese medicine. This protocol will be conducted and reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocols (PRISMA-P) statement. The results of this meta-analysis will be submitted to a peer-reviewed journal once it is completed. CONCLUSION: The consequence of this study will furnish proof to evaluate if CKZ is effective in the treatment of asthma. PROSPERO REGISTRATION NUMBER: ROSPERO CRD42019134458.

Traditional Chinese exercise (TCE) on pulmonary rehabilitation in patients with stable chronic obstructive pulmonary disease: Protocol for a systematic review and network meta-analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) has the characteristics of high incidence, mortality, disability rate, and heavy economic burden. Symptomatic measures such as anti-inflammatory, antispasmodic and anti-asthmatic are widely used in the treatment of COPD, and pulmonary rehabilitation has not been fully utilized. It is reported that up to 10 different kinds of Traditional Chinese exercises (TCEs) are often used for treating stable COPD. There are many randomized controlled trials (RCTs) and systematic reviews that have evaluated the efficacy of various TCEs for COPD. However, most of these studies were designed in comparison with conventional western medicine or health education. There are rarely studies to compare different TCEs head to head. Therefore, there remains uncertainty regarding the comparative efficacy among different TCEs. Thus, we plan to conduct a systematic review and Network meta-analysis (NMA) to compare the efficacy among 5 different TCEs and rank their benefits relative to each other. It is hoped that the findings of this study will facilitate the management and application of TCEs in the treatment of COPD. METHODS: A systematic and comprehensive literature search will be performed from inception to April 2019 in both English and Chinese databases, involving Medline, Cochrane Library, Embase, China National Knowledge Infrastructure Database, Wanfang Database, China Biomedical Literature Database, and Chongqing VIP information. RCTs related to TCE in the treatment of COPD will be included. Quality of included trials will be assessed according to the risk of bias tool of Cochrane Handbook 5.1.0. The GRADE approach will be used to rate the certainty of the evidence of estimates derived from NMA. Data analysis will be conducted by using STATA 14.0. RESULTS: This systematic review and NMA aims to summarize the direct and indirect evidence for different kinds of TCEs and to rank these TCEs. The findings of this NMA will be reported according to the PRISMA-NMA statement. The results of the NMA will be submitted to a peer-reviewed journal once completed. CONCLUSION: Using NMA, this study will provide an evidence profile which will be helpful to inform the selection of TCE for treating patients with COPD. The results will inform clinicians, bridge the evidence gaps, and identify promising TCE for future trials. PROSPERO REGISTRATION NUMBER: PROSPERO CRD 42019132970.