Deriving heart rate variability indices from cardiac monitoring—An indicator of driver sleepiness

Objective: Driver fatigue is considered to be a major contributor to road traffic crashes. Cardiac monitoring and heart rate variability (HRV) analysis is a candidate method for early and accurate detection of driver sleepiness. This study has 2 objectives: to evaluate the (1) suitability of different preprocessing strategies for detecting and removing outlier heartbeats and spectral transformation of HRV signals and their impact of driver sleepiness assessment and (2) relation between common HRV indices and subjective sleepiness reported by a large number of drivers in real driving situations, for the first time.

Methods: The study analyzed >3,500 5-min driving epochs from 76 drivers on a public motorway in Sweden. The electrocardiograph (ECG) data were recorded in 3 studies designed to evaluate the physiological differences between awake and sleepy drivers. The drivers reported their perceived level of sleepiness according to the Karolinska Sleepiness Scale (KSS) every 5?min. Two standard methods were used for identifying outlier heartbeats: (1) percentage change (PC), where outliers were defined as interbeat intervals deviating >30% from the mean of the four previous intervals and (2) standard deviation (SD), where outliers were defined as interbeat interval deviating >4 SD from the mean interval duration in the current epoch. Three standard methods were used for spectral transformation, which is needed for deriving HRV indices in the frequency domain: (1) Fourier transform; (2) autoregressive model; and (3) Lomb-Scargle periodogram. Different preprocessing strategies were compared regarding their impact on derivation of common HRV indices and their relation to KSS data distribution, using box plots and statistical tests such as analysis of variance (ANOVA) and Student’s t test.

Results: The ability of HRV indices to discriminate between alert and sleepy drivers does not differ significantly depending on which outlier detection and spectral transformation methods are used. As expected, with increasing sleepiness, the heart rate decreased, whereas heart rate variability overall increased. Furthermore, HRV parameters representing the parasympathetic branch of the autonomous nervous system increased. An unexpected finding was that parameters representing the sympathetic branch of the autonomous nervous system also increased with increasing KSS level. We hypothesize that this increment was due to stress induced by trying to avoid an incident, because the drivers were in real driving situations.

Conclusions: The association of HRV indices to KSS did not depend on the preprocessing strategy. No preprocessing method showed superiority for HRV association to driver sleepiness. This was also true for combinations of methods for frequency domain HRV indices. The results prove clear relationships between HRV indices and perceived sleepiness. Thus, HRV analysis shows promise for driver sleepiness detection.     

Gender and career success: A typology and analysis of dual paradigms

Despite women's advancements in the workplace, gender inequality persists. We classify and test two frameworks used to explain gender differences in career success: unequal attributes and unequal effects. The unequal attributes framework suggests that gender is related to other attributes, which result in unequal career outcomes for men and women (i.e., a mediated effect). The unequal effects framework suggests that even when men and women share the same attribute or circumstances, they are rewarded differently, such that individual attributes have unequal effects on career outcomes for men and women (i.e., a moderated effect). We collected survey data from a gender‐balanced sample of 394 business school alumni. Using structural equation modeling to test the unequal attributes framework, we found that work hours, career orientation, having a nonemployed spouse, and working in a predominantly female job were unequal attributes that explained gender differences in career success. Using multigroup path analysis to examine unequal effects, we found that being agentic, married, having children at home, and working in a predominantly female workplace had unequal effects in relation to career success for men and women. We find support for both models across three categories of career success antecedents (i.e., personal, family, and job attributes).     

城市生活垃圾的DSC和TGA分析与热值估算

利用微分扫描量热仪（ＤＳＣ）准确地测定了城市生活垃圾的含水率；热重分析仪（ＴＧＡ）测定了垃圾的水和低温下有机物总含量、难挥发性有机物和灼烧残渣的含量。根据量热和热量分析结果，可方便地计算垃圾的水和低温条件下易挥发性有机物含量，结合６０９种有机物的燃烧热，估算了垃圾的热值。     

耗散结构理论在土壤科学上应用途径的探索

本文根据耗散结构的基本理论，结合生产实践经验，提出了表征土壤肥力的非线性微分方程：＝（Ｋ－ｂ）ｘ－βｘ２Ｘ─土壤生物活性，ｔ─时间，Ｋ─生物繁殖系数，ｂ─生物死亡系数，β─生物饱和系数．解这个并不复杂的非线性微分方程，便可知道土壤是处于热力学分枝，还是耗散结构分枝．这对研究土壤肥力的动态变化、土壤肥力的分类、土壤的管理、土壤退化的防止等方面有着无法预测的应用前景．     

巢湖水体悬浮物含量与光谱反射率的关系

利用高光谱地物光谱仪在巢湖进行了反射光谱测量和同步水质采样分析，在分析巢湖水体反射光谱特征的基础上，分别研究了悬浮物浓度与水体光谱反射率和光谱反射率的一阶微分之间的关系，结果表明在近红外波段范围，单波段反射率和一阶微分光谱反射率都与悬浮物的浓度有较好的相关性，而且利用微分光谱估算内陆水体悬浮物浓度有较大潜力。     

丝栗栲种群生命过程及谱分析

以种群生命表及生存分析理论为基础，编制丝栗栲种群静态生命表，绘制存活曲线，死亡率曲线，亏损度曲线，死亡密度函数曲线。积累死亡函数曲线和危险率函数曲线，分析种群生命过程。结果表明，丝栗栲有2个死亡高峰，存活曲线趋于Deevey-Ⅱ型。并应用谱分析方法研究丝栗栲种群动态，结果表明，在丝栗栲种群自然更新过程中存在着明显的周期性。     

研究星载IPDA激光雷达探测CO2光谱纯度

光谱纯度是积分路径差分吸收激光雷达最重要的系统参数之一,光谱纯度直接影响CO₂数据的探测精度.在模式研究中要求输入观测的CO₂数据误差小于1×10^-6,对激光器光谱纯度参数设计提出很高要求.本文采用有效吸收截面分析探测反演误差的方法,研究了由光谱纯度带来的CO₂柱浓度探测误差,并基于窄带滤波器对光谱不纯能量的抑制作用,对不同带宽的窄带滤波器进行选择和分析,从而达到降低对光谱纯度的要求,提升探测精度的目的,最后讨论了由于窄带滤波器造成的能量衰减所对随机误差的影响.结果表明：当光谱纯度为99.9%,窄带滤波器带宽1GHz,透射率为0.86,脉冲能量为100mJ时CO₂探测的系统误差小于0.084×10^-6,随机误差小于0.02×10^-6,满足探测精度要求.     

合肥市典型交通干道大气苯系物的特征分析

为研究合肥市交通干道大气苯系物污染状况,采用自主研制的差分吸收光谱(DOAS)系统,于2016年3月期间对合肥市交通主干道大气苯系物(苯、甲苯、间二甲苯和邻二甲苯)以及常规污染物NO_2、SO_2等进行了连续观测.观测结果显示,观测期间苯、甲苯、间二甲苯和邻二甲苯的平均浓度分别为:21.7、63.6、33.9和98.7μg·m~(-3).与国内外其它城市比较显示,合肥市交通干道大气苯和甲苯的污染处于中等水平,二甲苯的污染较为严重.结合观测期的间风速风向、T/B特征比值以及与CO等污染物的相关性,对上述苯系物来源进行了分析,结果显示观测期间T/B值为0.8~4.5,苯、甲苯与CO的相关性系数R分别为0.55和0.34.表明机动车尾气排放是观测区域苯和甲苯的主要排放源之一,同时也受到周边工业园区排放的影响,二甲苯的主要排放源为观测地点北偏东方向的涂料行业工业园区.苯和甲苯的夜间高浓度峰值分析结果表明,夜间的高浓度苯和甲苯可能主要来源于观测地点周边工业园区的排放.观测区域苯系物的臭氧生成潜势(OFP)表现为邻二甲苯间二甲苯甲苯苯,其中二甲苯的OFP占总OFP的85%,表明周边工业园区的排放对该地区臭氧生成的贡献较大.     

城市黑臭水体的吸收特性分析

黑臭水体是城市水环境的一个严重问题,对城市黑臭水体光学特性进行分析,是利用遥感技术手段进行黑臭识别的前提与基础.2016~2017年采集了长沙、南京和无锡的城市黑臭水体共计85个样点,非黑臭水体共计80个样点,并对水样的悬浮物等水质参数浓度以及水体组分的吸收系数进行了测量.结果表明:(1)黑臭水体的总颗粒物吸收系数、非色素颗粒物吸收系数总体上高于非黑臭水体.(2)黑臭水体与非黑臭水体的CDOM吸收系数有明显的差异.由此可用CDOM吸收特征波段440 nm和不同波段范围内拟合的吸收系数曲线斜率对黑臭水体进行区分.城市黑臭水体吸收特性的分析,将为黑臭水体的遥感识别和监测提供有效的技术支撑.黑臭水体中的高CDOM浓度,可以作为遥感识别黑臭水的一个重要参考.     

不同类型降解地膜的热解特性及热动力学研究

采用差热分析 (DTA)法分析 1种普通地膜和 3种可降解地膜的组成 ,并对地膜的热解过程进行热动力学研究 .结果表明 ,4种地膜的差热曲线有许多相似 ,但也略有差异 ,说明降解膜与普通膜的基本组分相同 ,而添加组分不同 .各地膜热解的反应级数约为 0 93.各地膜热解活化能和指前因子的大小顺序均为 :普通膜 >光降解膜 >光钙型降解膜 >生物降解膜 .