Voice Characteristics in Adults With Neurofibromatosis Type 1

Neurofibromatosis type 1 (NF1) is an autosomal dominant neurocutaneous disorder caused by mutations in the NF1 gene, which is located at the long arm of chromosome 17. Major characteristics include multiple café-au-lait spots and neurofibromas. Voice abnormalities have been reported to occur in this patient group. However, most studies relied on subjective measurements only. The present study reports the results of an objective voice assessment based on a multiparameter approach in 22 adults with NF1. Aerodynamic measurements, voice range profiles, acoustic voice quality and intonation measurements, and dysphonia severity indices were obtained and compared with data from a control group, consisting of 22 healthy adults. It was found that NF1 patients show a poorer overall voice quality compared with controls. Particularly, a reduction of vital capacity and limitations in laryngeal possibilities with respect to frequency and intensity were observed in the NF1 group.     

Rating high‐throughput screening results via h‐index

The quantification of both the impact and quality of a scientist's publication record is an essential step in making decisions concerning hiring, promotion, and allocation of funding. In an attempt to resolve this problem, Hirsh proposed the “h‐index,” a single‐number criterion incorporating both the number of publications and the number of citations per publication. This value facilitates rating of a scientist's performance and is now one of the most commonly used matrices. Here, we would like to propose the rating of high‐throughput screening (HTS) result by the h‐index. Rating HTS result is to estimate how the HTS result is preferred by a medicinal chemist. In this study, we applied the h‐index for rating HTS results and observed an enhanced rating of preferred starting points for drug development. In addition, we developed a new index, the maximum common structure (MCS) index, which is more effective than the h‐index. Copyright © 2014 John Wiley & Sons, Ltd.     

The impact of authorities’ media and rumor dissemination on the evolution of emergency

Rumor dissemination will induce emergencies. Authorities’ information is an essential factor for avoiding rumor dissemination when emergencies occur. The credibility of authorities’ media and audience rating of authorities’ information greatly influence the evolution of emergencies which are induced by rumor dissemination. To explore the interplay mechanism among authorities’ media, rumor dissemination and the evolution of emergency, we propose a new interplay model and perform stability analysis by the Routh stability criterion. We find a stability condition under which the deterioration of emergency can be effectively prevented. Recommendations for policy makers and consulting advice for related commissions are explored in the case study of the iodized sail shortage panic in China. Results show that applying media with high audience rating but low credibility will cause widespread panic and inspire a slew of ancillary rumors. Authorities should choose proper media to release the truth to public according to the seriousness of the situation and the rumor spreading rate. Pertinent countermeasures and appropriate tactics are also brought out for decision makers to alleviate intense feelings of panic.     

网络环境下的医院门诊挂号预约系统改善研究

本文对改善挂号预约系统的模型进行了分析探索。根据病人的自报病情信息及医疗经验信息,通过量化的方法,对挂号预约阶段病人对疾病分类和症状程度划分进行了研究。研究结果有助于改善预约挂号系统。新的方法有助于解决挂号难的问题、有助于医疗服务质量的提高、并且有助于医疗资源的优化利用。     

基于PROMETHEE-II的商户小额贷款信用评级模型及实证

截至2014年底,中国注册个体工商户为4984.06万户,个体私营经济吸纳社会从业人员已达2.5亿人,加上中国商户小额贷款对象的分散性、财务信息不健全等特点和难点,商户小额贷款信用评级体系极不完善,甚至绝大多数银行都没有建立这个体系。本文通过相关分析剔除反映信息重复的指标,通过显著性判别遴选对商户违约状态影响显著的指标,建立了能显著区分商户违约状态的小额贷款信用评级指标体系。在此基础上,结合PROMETHEE-II(偏好顺序结构)和聚类分析方法,构建了商户小额贷款信用评级模型,并对中国某国有商业银行2157个商户小额贷款样本进行了实证。本文创新与特色:一是通过将偏好顺序结构评估法(PROMETHEE-II)引入商户小额贷款信用评级,构建了基于PROMETHEE-II的小额贷款信用评分模型,求解商户的净流量信用得分Φ(a),揭示了商户a与其余商户、评价指标间的相互作用对评价结果的影响,避免了现有研究由于评价指标之间的相互替代性、严重影响评价结果可靠性的不足。二是借鉴模糊聚类“数据越集中、越应该被分为一类”的思想,采用R聚类对商户信用得分进行分类;进而采用K-W检验,对分类数目l进行非参数检验,确定商户的信用等级。既保证了不同等级商户在信用得分数值上存在显著差异,也确保了不同等级商户能反映不同的信用特征;同时,也避免了现有利用信用得分区间、违约概率阈值或客户数分布方法划分信用等级时,得分区间、违约概率阈值或客户数分布分位点人为主观确定的不足。三是实证研究表明,影响商户小额贷款信用风险的重要性排序依次为:X₃偿债能力>X₁基本情况>X₆宏观环境>X₅营运能力>X₂保证联保>X₄盈利能力。     

外资评级机构进入中国能否发挥“鲶鱼效应”?

近年来,中国信用评级行业逐步对外开放。我国监管部门相继批准标普、惠誉等具有国际影响力的外资评级机构进入我国市场。在此背景下,本文采用博弈模型分析了外资评级机构进入中国市场对本土评级机构评级质量的影响。研究发现,高声誉外资评级机构进入中国市场能够起到激励本土评级机构公正评级并促进评级行业形成良性循环的作用。本文研究结论为我国信用评级行业对外开放以及引入更多具有国际影响力的外资评级机构提供了理论支撑。     

带干扰风险模型的破产严重性及其恢复代价的测量

本文针对带干扰风险模型考虑了由Picard (1994)引进的破产最大严重程度和恢复所需代价的概念以及对它们的测量问题, 并给出了相应于Picard (1994)的各种公式的明确表达.     

考虑噪声烦恼度的机场飞机噪声收费模型和应用研究

随着我国民航运输业的飞速发展,机场噪声影响问题日趋严重。通过向航空公司或旅客收取噪声费来进行治理,是民航发达国家的普遍做法,也是我国未来的发展方向。该文在国外机场飞机噪声收费模型的基础上,提出了基于飞机噪声特性、噪声烦恼度、噪声治理投入费用和资金回收周期等因素的机场噪声收费模型。模型将机场噪声治理费用通过合理的回收周期按一定比例分配到各年度,再根据飞机噪声特性、噪声烦恼度将每年噪声收费分配到每架次飞机(或每位旅客)。飞机噪声特性根据ACI的机场噪声分级R1～R8来确定,噪声烦恼度借助Mamdani模型构建。应用表明,该收费模型关键因素考虑全面,计算方法先进简洁,费率合理。对于噪声较高飞机,夜间起飞收费为1219.06元/架次,客均收费10.16元;对于噪声很低的飞机,昼间着陆收费为66.10元/架次,客均收费仅0.15元。费率确定符合国际民航组织倡导的以支定收原则,有助于形成航空公司/旅客减噪激励机制同时又不致抑制机场航空业务增长。     

A variety of radars designed to explore the hidden structures and properties of the Solar System's planets and bodies

Since the very first observations of the Moon from the Earth with radar in 1946, radars are more and more frequently selected to be part of the payload of exploration missions in the Solar System. They are, in fact, able to collect information on the surface structure of bodies or planets hidden by opaque atmospheres, to probe the planet subsurface or even to reveal the internal structure of a small body comet nucleus.A brief review of radars designed for the Solar System planets and bodies' exploration is presented in the paper. This review does not aim at being exhaustive but will focus on the major results obtained. The variety of radars that have been or are currently designed in terms of frequency or operational modes will be highlighted.     

Nonparametric estimation of operational value-at-risk (OpVaR)

This paper introduces nonparametric methods for estimating 99.9% operational value-at-risk (OpVaR) and its confidence interval (CI), and demonstrates their applications to US business losses. An attractive feature of these new methods is that there is no need to estimate either the entire heavy-tailed loss distribution or the tail region of the distribution. Furthermore, we provide algorithms that facilitate applied researchers and practitioners in risk management area to implement the sophisticated empirical likelihood ratio (ELR) based methodologies to construct the CI of the true underlying 99.9% OpVaR. In a simulation study, we find that the weighted ELR (WELR) CI estimator is more reliable than the ELR CI estimator. The empirical results show that the nonparametric OpVaR estimates are consistently larger than those of other comparable methods, which provide adequate regulatory capitals, particularly during crises. The findings have implications for regulators, and effective and efficient risk financing.