R-Factor Analysis of Data Based on Population Models Comprising R- and Q-Factors Leads to Biased Loading Estimates

Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.

A Comparison between Major Factor Extraction and Factor Rotation Techniques in Q-Methodology

The statistical analysis in Q-methodology is based on factor analysis followed by a factor rotation. Currently, the most common factor extraction methods are centroid and principal component extractions and the common techniques for factor rotation are manual rotation and varimax rotation. However, there are some other factor extraction methods such as principal axis factoring and factor rotation methods such as quartimax and equamax which are not used by Q-users because they have not been implemented in any major Q-program. In this article we briefly explain some major factor extraction and factor rotation techniques and compare these techniques using three datasets. We applied principal component and principal axis factoring methods for factor extraction and varimax, equamax, and quartimax factor rotation techniques to three actual datasets. We compared these techniques based on the number of Q-sorts loaded on each factor, number of distinguishing statements on each factor, and excluded Q-sorts. There was not much difference between principal component and principal axis factoring factor extractions. The main findings of this article include emergence of a general factor and a smaller number of excluded Q-sorts based on quartimax rotation. Another interesting finding was that a smaller number of distinguishing statements for factors based on quartimax rotation compared to varimax and equamax rotations. These findings are not conclusive and further analysis on more datasets is needed.

Q-factor estimation in CMP gather and the continuous spectral ratio slope method

The attenuation factor or quality factor(Q-factor or Q) has been used to measure the energy attenuation of seismic waves propagating in underground media. Many methods are used to estimate the Q-factor. We propose a method to calculate the Q-factor based on the prestack Q-factor inversion and the generalized S-transform. The proposed method specifies a standard primary wavelet and calculates the cumulative Q-factors; then, it finds the interlaminar Q-factors using the relation between Q and offset(QVO) and the Dix formula. The proposed method is alternative to methods that calculate interlaminar Q-factors after horizon picking. Because the frequency spectrum of each horizon can be extracted continuously on a 2D time–frequency spectrum, the method is called the continuous spectral ratio slope(CSRS) method. Compared with the other Q-inversion methods, the method offers nearly effortless computations and stability, and has mathematical and physical significance. We use numerical modeling to verify the feasibility of the method and apply it to real data from an oilfield in Ahdeb, Iraq. The results suggest that the resolution and spatial stability of the Q-profile are optimal and contain abundant interlaminar information that is extremely helpful in making lithology and fluid predictions.

基于可调Q-因子小波变换的语音增强算法

针对语音增强算法中传统的小波阈值法的局限性,提出一种基于可调Q-因子小波变换和清浊音分离的语音增强算法。首先用过零率和短时能量法判别清音和浊音;然后在可调Q-因子小波变换下,对清、浊音采用不同的阈值处理,在不同尺度上,分别结合系数能量和噪声方差得到的阈值作为清音和浊音的阈值确定准则;再利用改进的阈值函数分别处理清音和浊音的小波系数,估计出不含噪声的系数;最后进行小波逆变换,得到抑制了噪声的语音信号。对含有高斯白噪声和有色噪声的语音进行仿真实验,结果表明:与目前许多经典的去噪方法相比,该方法在去噪效果和提高语音可懂度方面均有一定的改善。

基金的投资技能提高了基金绩效吗?--基于q-因子模型的实证分析

基金的投资技能是否提升了基金绩效是业界和学术界长期关注的问题.应用相对于无风险的超额收益率和对照基准的超额收益率,对2013年1月1日之前成立的437支开放式基金进行了择股和择时的绩效评估.使用2005-01~2017-12的日度数据,基于q-因子模型的实证发现:1)q-因子模型对基金超额收益率具有很好的解释力;2)相对于无风险的超额收益率方法会高估基金的绩效;3)我国开放式基金具有非常弱的择股能力和相对较好的短期择时能力,但不存在长期的择时能力,短期的择时能力对基金的短期绩效有一定的提升;4)我国基金偏好于盈利能力强或投资水平高的公司股票.

Stein流形局部q-凸域上带权因子的同伦公式和-方程

本文得到了Ｓｔｅｉｎ流形局部ｑ－凸域上（ｒ，Ｓ）型微分形式的带权因子的同伦公式及其－方程的带权因子的解．

野菊花质量标志物(Q-marker)预测及其一测多评研究

目的 预测野菊花Q-marker,并建立能够同时测定野菊花Q-marker含量的一测多评方法,为野菊花药材质量评价及优质品种选育奠定基础。方法 结合野菊花化学成分及药理学研究,依据Q-marker的“五原则”综合分析、预测野菊花的Q-marker的候选化合物,采用高效液相色谱法构建适用于野菊花品质评价的一测多评体系。结果 从野菊花的功效相关性、可测成分、入血成分及成分特异性等多方面分析,预测了野菊花药材中8个Q-marker的候选化合物,8种成分在测定范围内线性良好,且在不同的实验条件下相对校正因子重现性良好。结论 建议考虑将野菊花药材中4个类黄酮成分(蒙花苷、田蓟苷、芹菜素和木犀草苷)和4个酚酸类成分(绿原酸、异绿原酸A、异绿原酸B和异绿原酸C)作为野菊花药材Q-marker的候选化合物,本研究中一测多评法同时测定野菊花中8种候选Q-marker成分含量准确可行。

q-斜实循环矩阵的谱分解

利用实循环矩阵与实斜循环矩阵可进行酉对角化的结论,研究q-斜实循环矩阵的酉对角化,并给出q-斜实循环矩阵的酉对角化的谱分解结果.

Novel method to measure unloaded quality factor of resonant cavities at room temperature

We demonstrated a novel method to measure the unloaded quality factor(Q factor) of high-Q resonant cavities. This method was used to obtain data with low errors and calculate the unloaded Q factor. This procedure was more reliable than traditional methods. The data required for the method were near the resonant frequency,not at the half-power points of the reflection coefficient curve or Smith chart. We applied the new method to measure a resonant cavity with an unloaded Q factor of^100,000, obtaining good agreement between the measured and theoretical results.

FACTORS AFFECTING SOIL RESPIRATION IN REFERENCE WITH TEMPERATURE'S ROLE IN THE GLOBAL SCALE

Soil respiration is CO 2 evolution process from soil to atmosphere, mainly produced by soil micro organism and plant roots. It is affected not only by biological factors (vegetation, micro organism, etc.) and environmental factors (temperature, moisture, pH, etc.), but also more and more strongly by man made factors. Based on literature survey, main factors affecting soil respiration were reviewed. The relationships of soil respiration to latitude and to mean annual temperature were analyzed by using the data measured from forest vegetation in the world. As a result, soil respiration rate decreased exponentially with an increase of latitude, and increased with increasing temperature. Following the relationship between soil respiration and temperature, Q 10 value (law of Van Hoff) was obtained as 1.57 in the global scale.

半枫荷根对佐剂诱导型关节炎的改善作用及其正丁醇提取物UPLC-Q-TOF-MS分析

目的:本研究探讨了半枫荷根对类风湿性关节炎的治疗作用,明确活性提取物及化学成分。方法:建立SD大鼠佐剂性关节炎模型,测定侧足肿胀容积、关节炎指数变化、胸腺、脾脏指数;ELISA法测定外周血单核细胞(PBMC)中COX-2、5-LOX及血清IL-6、IL-1β、TNF-α、IL-10水平;HE染色观察踝关节病理组织形态,用上述指标筛选半枫荷根活性提取物,UPLC-Q-TOF-MS技术对活性提取物进行定性。结果:与模型组比,半枫荷根醇提物组(1.6 g/kg)的大鼠侧足肿胀度、关节炎指数、脾脏指数降低;COX-2及5-LOX、血清IL-6、IL-1β、TNF-α水平明显降低,IL-10水平明显升高;关节组织炎细胞浸润减少、病理形态改善;半枫荷根正丁醇部位为活性提取物;正丁醇提取物鉴定得到104个成分,包括有机酸类、糖和糖苷类、黄酮类、醌类及香豆素等有机化合物。结论:半枫荷根对佐剂型关节炎具有明显保护作用,在治疗药物和功能性食品的开发方面有广阔的前景。

Analyzing Drivers’ Mental Patterns Using Q-Methodology

The human factor is the most important cause of road accidents. Investigating the drivers’ mental patterns can lead to a better understanding of the factors that affect drivers to make a mistake and thus increase the likelihood of an accident. In this study, mental patterns of drivers as a human characteristic are determined through a questionnaire survey. To do this, 166 participants (18 - 65 years) were asked to express their opinion on the possible effect of 25 factors on the occurrence of accidents. These factors were selected through the investigation of the accident database during the last three years in different areas of the case study. To analyze the data extracted from the survey, Q-methodology was used. The results of the factor analysis showed that there are 5 mental patterns among the participants. Based on the driver’s opinion, human factors and road conditions were the most and least influential accident-generating items, respectively. The most significant reason for accidents determined by drivers was human errors including 1) unauthorized overtaking, 2) unauthorized speed, 3) driver distractions (such as cell phone), and 4) driver physical disability (such as visual impairment). Moreover, the failure of the vehicle was mostly reported as another influential contributor to accidents. It is worth mentioning that the results of this study can be used to minimize accidents resulted from drivers’ behavioral errors by suggesting strategies for enhancing their performance through new manuals which is a step towards a safer road.

A Backward Stable Hyperbolic QR Factorization Method for Solving Indefinite Least Squares Problem

We present a numerical method for solving the indefinite least squares problem. We first normalize the coefficient matrix. Then we compute the hyperbolic QR factorization of the normalized matrix. Finally we compute the solution by solving several triangular systems. We give the first order error analysis to show that the method is backward stable. The method is more efficient than the backward stable method proposed by Chandrasekaran, Gu and Sayed.

Control of Unit Power Factor PWM Rectifier

To solve the problem of harmonic pollution to the power grid that caused by traditional diode rectifier and phase controlled rectifier, the unit power factor PWM rectifier is designed. The topology structure of the rectifier circuit is introduced and the double closed-loop control strategy in three-phase stationary coordinate system is analyzed. For the deficiency of control strategy, the control strategy in two-phase synchronous rotating coordinate system is proposed. This makes the independent control of active current and reactive current to be realized. The simulation model of the PWM rectifier is built and the effectiveness of the control method proposed in this paper is verified by simulation.

基于LMDI和系统聚类的电力行业碳排放影响因素分析

电力行业作为直接使用一次能源的最大部门,是落实我国碳减排目标的重点行业。为厘清电力行业碳排放的主要驱动或抑制来源,论文构建了LMDI模型,从国家及省域两个层面对2006—2020年电力行业碳排放的影响因素进行了分解。研究结果表明,从国家及省域两个层面来看,经济发展效应均为电力碳排放的主要促进因素,火电燃料转化效应和产业结构效应均为电力碳排放的抑制因素,电源结构效应、工业电耗强度效应在全国层面为电力碳排放的抑制因素,但在各省份中的影响效果及程度各有不同。论文以主要抑制因素为变量,利用系统聚类法将30个省份划分为六大区域,针对各区域影响因素的作用效果提出了因地制宜的减排政策。

Coordination Control of Greenhouse Environmental Factors

Optimal control of greenhouse climate is one of the key techniques in digital agriculture.Greenhouse climate,a nonlinear and uncertain system,consists of several major environmental factors such as temperature,humidity,light intensity,and CO 2 concentration.Due to the complex coupled correlations,it is a challenge to achieve coordination control of greenhouse environmental factors.This paper proposes a model-free coordination control approach for greenhouse environmental factors based on Q-learning.Coordination control policy is found through systematic interaction with the dynamic environment to achieve optimal control for greenhouse climate with the control cost constraints.In order to decrease systematic trial-and-error risk and reduce the computational complexity in Q-learning algorithm,case-based reasoning （CBR） is seamlessly incorporated into the Q-learning process.The experimental results demonstrate that this approach is practical,highly effective and efficient.

两类费马型q-差分微分方程的整函数解

运用Nevanlinna值分布理论和复微分方程理论,研究了2类费马型q-差分微分方程f2(qz+c)+(f(k)(z))2=1,[f(qz+c)-f(z)]2+(f(k)(z))2=1的有限级超越整函数解的存在性.在一定条件下,获得解的精确表达式.

一种数据库查询的多标签电能质量混合扰动识别与分类新方法

该文针对电能质量混合扰动的复杂性及当前分类识别的准确率不够高等问题,提出一种数据库查询的多标签电能质量混合扰动分类与识别方法,该方法能够更加科学准确地识别混合扰动,可为电能质量治理、扰动事件责任追究等提供有力决策辅助。首先,该方法基于可调Q因子小波变换(tunable Q-factor wavelet transform,TQWT)和时变均方根(rootmeansquare,RMS)的特征提取方法有效提取扰动信号基频时域特征量,较好地克服了当前基频幅值特征提取准确率不够高的难点问题;其次,提出频域特征曲线分割新方法,高效地提取扰动信号的高频特征曲线;然后,建立基频幅值特征数据库和高频特征曲线数据库;最后,利用快速动态时间规整(dynamictimewarping,DTW)结合多标签的分类思想进行混合电能质量扰动的多标签分类。仿真实验结果表明,新方法具有如下优势:几乎不受限值范围内基频偏移的影响,抗噪性较强,对单一扰动及包含双重、三重、四重扰动在内的27种扰动具有较高的分类准确率。电网实测扰动数据的分析,进一步验证了该方法的扰动识别有效性。

基于自适应短时傅里叶变换的品质因子Q值估算方法

品质因子Q是描述地下介质对地震波吸收衰减强弱程度的参数,同时也是地层含油气性的重要标志。在地震资料Q估算中,常用的方法是短时傅里叶变换方法,当窗函数被选定以后,其时频分辨率就固定了。针对该问题,提出一种自适应窗短时傅里叶变换的方法,以获得更准确的瞬时中心频率,并利用峰值频移法来估算品质因子Q。首先,利用固定窗长的短时傅里叶变换来提取信号的瞬时中心频率作为初始频率;然后,根据初始频率自适应计算不同频率的窗长,并利用自适应窗长短时傅里叶变换来求取瞬时中心频率;最后,结合峰值频移法得到高分辨率的品质因子Q值。利用合成数据和实际数据进行了测试,结果表明,相比于固定时窗短时傅里叶变换方法,自适应短时傅里叶变换方法具有更好的时间和频率分辨率,可以获得更高分辨率的品质因子Q值。该结果可以为地下介质的研究提供更准确、可靠的工具,有助于更好地了解地下结构和油气资源分布情况。

重组牛碱性成纤维细胞生长因子凝胶联合调Q激光治疗面部脂溢性角化病

目的:探讨重组牛碱性成纤维细胞生长因子(Recombinant bovine basic fibroblast grow,rb-bFGF)凝胶联合调Q激光治疗面部脂溢性角化病(Seborrheic keratosis,SK)的效果。方法:选笔者医院2020年6月-2023年6月收治的82例面部SK患者为研究对象。按随机数字表法分为对照组(n=41)与观察组(n=41),两组均进行调Q激光治疗(波长532 nm),观察组在对照组基础上给予rb-bFGF凝胶治疗。观察对比两组疗效、疼痛程度、痂皮完全脱落时间、遗留红斑持续时间、皮肤病生活质量量表(Dermatology life quality index,DLQI)及不良反应发生情况。结果:观察组有效率较对照组高,差异有统计学意义(P<0.05);观察组疼痛视觉模拟评分法(Visual analogue scale,VAS)评分较对照组低,创面痂皮完全脱落时间、遗留红斑持续时间均较对照组短,差异均有统计学意义(P<0.05)。治疗后,两组DLQI除治疗维度外其他维度评分均较治疗前降低(P<0.05),且观察组均低于对照组(P<0.05);观察组不良反应发生率为0.93%,对照组为6.03%,差异无统计学意义(P>0.05)。结论:rb-bFGF凝胶联合调Q激光治疗面部SK疗效显著,可促进创面恢复,减轻恢复期疼痛,提高患者生活质量。