基于包络特征的非圆齿轮数字化设计与齿形优化研究

基于齿轮啮合原理和微分几何理论，获得插齿刀具与非圆齿轮齿坯的运动坐标转换关系，模拟了非圆齿轮齿廓获取的插齿加工过程；同时，针对非圆齿轮传动过程中的冲击振动和噪声问题，以插齿刀具修形为手段，以非圆齿轮齿廓修形为目的，得到了一种精确、高效、通用的非圆齿轮齿廓的修形设计方法；利用动力学仿真软件，对修形前后的非圆齿轮进行了运动学仿真。结果说明，修形后的非圆齿轮在传动过程中的冲击振动现象明显减弱，能够有效降低齿面磨损，较好地增加轮齿的使用寿命，验证了该修形方法的正确性。为非圆齿轮的实际应用与发展提供了重要的理论研究方法和设计依据

Human-Computer Interaction Based on Semantic Focus+Context for Information Visualization

大数据成为继云计算和物联网之后,国际学术界和产业界所共同瞩目的又一个研究热点.信息可视化是辅助用户洞悉大数据背后隐藏的知识和规律的重要方法和有力 工具.如何在图形用户界面中对大规模信息以符合认知规律的方式进行可视化,并且使得计算机能够智能化的理解用户意图以配合其进行高效的人机交互,是信息可 视化面临的挑战之一.文中提出一种面向信息可视化的语义Focus+Context人机交互技术.首先,在基于空间距离的经典Focus+Context 数学模型基础上对其进行语义建模和扩展,建立了面向信息空间和可视化表征空间的语义距离模型以及语义关注度模型,定义了交互中的焦点对象与语义上下文.其 次,在此基础上建立了语义Fcous + Conext用户界面模型,给出了界面抽象元素和实体元素以及映射关系的形式化描述,同时建立了Focus+Context交互循环机制.最后,给出了应 用于经典Focus+Context及鱼眼数学模型的描述,表明文中提出方法具有很好的兼容性描述能力;同时,给出了面向文件系统主题聚集的语义Focu s+Context应用,给出了基于主题语义关注度与嵌套圆鱼眼视图的动态可视化实例,应用实例表明文中提出技术能够有效支持用户在信息可视化界面中对大 规模信息进行智能化的可视化和交互探索.Big data has become another revolutionary technology following the booming of cloud computing and internet of things. Information visualization is regarded as an essential approach and powerful tool for users to get insight from big data. However, great challenges still exist in information visualization and smart interaction in small interfaces according to cognitive law. This paper proposes a semantic Focus+Context interaction technology for information visualization in user interface. Firstly, a semantic distance model and a semantic Degree -Of-Interest (DOI) model towards information space and visual representation space are presented. And based on the models, semantic context related to a focus is defined. Secondly, the paper proposes a semantic Focus + Context based user interface model, defining both abstract and entity elements as well as the mappings in this kind of user interface. Finally, the proposed technology is applied to semantic theme clustering for exploration of large scale file systems. Application examples show that the proposed technology can effectively support large scale information visualization in small interface and intelligent interaction for semantic exploration of complex data

基于改进变分模态分解的齿轮点蚀故障诊断

针对齿轮点蚀故障特征难以提取的问题，提出了一种基于改进变分模态分解的齿轮点蚀故障诊断方法。利用经验模态分解自适应分解的特点，将各分量的能量占比作为有效分量的判断依据，并据此设定变分模态分解算法的模态个数，在此基础上，以变分模态分解分量的排列熵和最小值作为适应度函数，用遗传算法对惩罚因子进行搜索；根据所得结果设置变分模态分解参数，并对齿轮点蚀信号进行处理；筛选合适的本征模态函数进行包络调解，通过包络谱图分析齿轮点蚀故障的特征信息。对齿轮实验信号的分析表明，与现有方法相比，本文中提出的改进变分模态分解算法能够更加准确地识别出齿轮点蚀故障，在传动系统故障诊断方面具有一定实用价值

Aripiprazole versus other atypical antipsychotics for schizophrenia

BACKGROUND: In most western industrialised countries, second generation (atypical) antipsychotics are recommended as first line drug treatments for people with schizophrenia. In this review we specifically examine how the efficacy and tolerability of one such agent - aripiprazole - differs from that of other comparable second generation antipsychotics. OBJECTIVES: To evaluate the effects of aripiprazole compared with other atypical antipsychotics for people with schizophrenia and schizophrenia-like psychoses. SEARCH METHODS: We searched the Cochrane Schizophrenia Group Trials Register (November 2011), inspected references of all identified studies for further trials, and contacted relevant pharmaceutical companies, drug approval agencies and authors of trials for additional information. SELECTION CRITERIA: We included all randomised clinical trials (RCTs) comparing aripiprazole (oral) with oral and parenteral forms of amisulpride, clozapine, olanzapine, quetiapine, risperidone, sertindole, ziprasidone or zotepine for people with schizophrenia or schizophrenia-like psychoses. DATA COLLECTION AND ANALYSIS: We extracted data independently. For dichotomous data we calculated risk ratios (RR) and their 95% confidence intervals (CI) on an intention-to-treat basis based on a random-effects model. Where possible, we calculated illustrative comparative risks for primary outcomes. For continuous data, we calculated mean differences (MD), again based on a random-effects model. We assessed risk of bias for each included study. MAIN RESULTS: We included 12 trials involving 6389 patients. Aripiprazole was compared to olanzapine, risperidone and ziprasidone. All trials were sponsored by an interested drug manufacturer. The overall number of participants leaving studies early was 30% to 40%, limiting validity (no differences between groups).When compared with olanzapine no differences were apparent for global state (no clinically important change: n = 703, 1 RCT, RR short-term 1.00 95% CI 0.81 to 1.22; n = 317, 1 RCT, RR medium-term 1.08 95% CI 0.95 to 1.22) but mental state tended to favour olanzapine (n = 1360, 3 RCTs, MD total Positive and Negative Syndrome Scale (PANSS) 4.68 95% CI 2.21 to 7.16). There was no significant difference in extrapyramidal symptoms (n = 529, 2 RCTs, RR 0.99 95% CI 0.62 to 1.59) but fewer in the aripiprazole group had increased cholesterol levels (n = 223, 1 RCT, RR 0.32 95% CI 0.19 to 0.54) or weight gain of 7% or more of total body weight (n = 1095, 3 RCTs, RR 0.39 95% CI 0.28 to 0.54).When compared with risperidone, aripiprazole showed no advantage in terms of global state (n = 384, 2 RCTs, RR no important improvement 1.14 95% CI 0.81 to 1.60) or mental state (n = 372, 2 RCTs, MD total PANSS 1.50 95% CI -2.96 to 5.96).One study compared aripiprazole with ziprasidone (n = 247) and both the groups reported similar change in the global state (n = 247, 1 RCT, MD average change in Clinical Global Impression-Severity (CGI-S) score -0.03 95% CI -0.28 to 0.22) and mental state (n = 247, 1 RCT, MD change PANSS -3.00 95% CI -7.29 to 1.29).When compared with any one of several new generation antipsychotic drugs the aripiprazole group showed improvement in global state in energy (n = 523, 1 RCT, RR 0.69 95% CI 0.56 to 0.84), mood (n = 523, 1 RCT, RR 0.77 95% CI 0.65 to 0.92), negative symptoms (n = 523, 1 RCT, RR 0.82 95% CI 0.68 to 0.99), somnolence (n = 523, 1 RCT, RR 0.80 95% CI 0.69 to 0.93) and weight gain (n = 523, 1 RCT, RR 0.84 95% CI 0.76 to 0.94). Significantly more people given aripiprazole reported symptoms of nausea (n = 2881, 3 RCTs, RR 3.13 95% CI 2.12 to 4.61) but weight gain (7% or more of total body weight) was less common in people allocated aripiprazole (n = 330, 1 RCT, RR 0.35 95% CI 0.19 to 0.64). Aripiprazole may have value in aggression but data are limited. This will be the focus of another review. AUTHORS' CONCLUSIONS: Information on all comparisons are of limited quality, are incomplete and problematic to apply clinically. Aripiprazole is an antipsychotic drug with a variant but not absent adverse effect profile. Long-term data are sparse and there is considerable scope for another update of this review as new data emerges from the many Chinese studies as well as from ongoing larger, independent pragmatic trials

JUNO Sensitivity on Proton Decay p→νˉK+p\to \bar\nu K^+ Searches

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this paper, the potential on searching for proton decay in $p\to \bar\nu K^+$ mode with JUNO is investigated.The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits to suppress the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar\nu K^+$ is 36.9% with a background level of 0.2 events after 10 years of data taking. The estimated sensitivity based on 200 kton-years exposure is $9.6 \times 10^{33}$ years, competitive with the current best limits on the proton lifetime in this channel

JUNO sensitivity on proton decay p → ν K + searches*

The Jiangmen Underground Neutrino Observatory (JUNO) is a large liquid scintillator detector designed to explore many topics in fundamental physics. In this study, the potential of searching for proton decay in the $p\to \bar{\nu} K^+$ mode with JUNO is investigated. The kaon and its decay particles feature a clear three-fold coincidence signature that results in a high efficiency for identification. Moreover, the excellent energy resolution of JUNO permits suppression of the sizable background caused by other delayed signals. Based on these advantages, the detection efficiency for the proton decay via $p\to \bar{\nu} K^+$ is 36.9% ± 4.9% with a background level of $0.2\pm 0.05({\rm syst})\pm$$0.2({\rm stat})$ events after 10 years of data collection. The estimated sensitivity based on 200 kton-years of exposure is $9.6 \times 10^{33}$ years, which is competitive with the current best limits on the proton lifetime in this channel and complements the use of different detection technologies