Data driven analysis of functional brain networks in fMRI for schizophrenia investigation

The purpose of this article is to present a methodology to identify the sources of activity in brain networks from functional magnetic resonance imaging (fMRI) data using the multiset canonical correlation analysis algorithm. The aim is to lay the foundations for a screening marker to be used as indicator of mental diseases. Group analysis blind source separation methods have proved reliable to extract the latent sources underlying the brain activities but currently there is no recognized biomarker for mental disorders. Recent studies have identified alterations in the so called default mode network (DMN) that are common to several neuropsychiatric disorders, including schizophrenia. In particular, here we account for the hypothesis that the alterations in the DMN activity can be effectively highlighted by analyzing the transient states between two different tasks. A set of fMRI data acquired from 18 subjects performing working memory tasks is investigated for such purpose. Subjects are patients affected by schizophrenia for one half and healthy control subjects for the other. Under these conditions, the proposed methodology provides high discrimination performances in terms of classification error, thereby providing promising results for a preliminary tool able to monitor the disease state or to perform a prescreening for patients at risk for schizophrenia. © 2014 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 24, 239–248, 2014     

一种基于特征相似性的印刷图像质量评价方法

目的提出一种基于特征相似性的印刷图像质量评价方法,解决客观评价印刷图像质量的方法忽略了人眼视觉的底层特征,不能与主观评价达到很好一致性的问题。方法采用能够提取视觉底层特征的特征相似性FSIM算法,应用在印刷图像质量的客观评价中,结合主观实验,对印刷图像质量加以整体评价。结果 FSIM算法的质量评分范围在0.9~1之间,在与主观评价的相关性分析上,皮尔逊相关系数(CC)为0.9490,斯皮尔曼秩相关系数(SROCC)为0.9940,平均绝对值误差(MAE)为0.0049,相较于MSE,PSNR,SSIM和MS-SSIM算法表现出更好的预测稳定性、单调性和一致性。结论实验结果表明,FSIM算法与人眼主观质量评价有着更好的一致性,更接近人类视觉系统,能够有效地进行印刷图像质量评价。     

Differences in brain networks of children with ADHD: Whole-brain analysis of resting-state fMRI

The aim of this study was to investigate changes of functional connectivity (FC) in resting state networks (RSNs) in medication-naive children with attention-deficit/hyperactivity disorder (ADHD). Twenty children with a diagnosis of ADHD (11.8 ± 2.29 years; 16 boys) and 20 age-matched typically developing (TD) children (13 ± 1.78 years; 10 boys) were included. It was found that brain FC differences in children with ADHD are not only in the well known RSNs such as default mode, visual, sensory motor, attentional, frontal, central executive, and frontal networks but also involve interaction among whole brain functional networks. In addition, basal ganglia and cerebellum networks which later gained importance were examined in this study. All RSNs has been shown significant differences in special regions which belongs related RSN. The highest positive (HPC) and negative (HNC) correlation were calculated between 14 independent components including 11 different RSNs. We observed different FC changes (decreased/increased) according to the RSNs between ADHD and control children. The HPC was defined between the visual and cerebellum network in ADHD children and between the dorsal attentional network and sensory motor network in TD children. Also, the HNC was detected between the visual and basal ganglia network in both groups. Investigating intra and inter network FC could provide a framework to better understand the neural basis that underlies core symptom dimensions in ADHD.     

Analysis of objective and subjective data using fuzzy coding and multiple correspondence analysis: principle and example in a sitting posture study

Fuzzy coding vs. crisp coding and then local coding vs. global coding is proposed to transform a quantitative scale into a category scale. Such a transformation technique is seen as the most general one to investigate either heterogeneous but quantitative variables or variables with different scale models (both quantitative and qualitative). A major point of fuzzy coding is that space modalities can be built very early in the statistical analysis process and from a discussion between several specialists. The multiple correspondence analysis (MCA) is proposed to investigate a table where the data come from fuzzy coding; the table rows corresponding to the empirical situations and the columns to the space modalities of the respective variables. Two examples are considered. First, a didactic data set is designed in order to compare the principal component analysis, the MCA with crisp coding and the MCA with fuzzy coding. Second, an example about a sitting posture study is considered in order to show the possibility of achieving relationships between objective and subjective data. The empirical situations correspond to adjustment combinations of the seat, the table and the backrest; the variables are posture indicators and subjective assessments. The main result is that the subjective variables have a much more consistent evolution with the adjustments than the objective ones. Consequently, there is a poor connection between these two sets of variables. The backrest is the furniture setting with the highest influence. From the interpretation of the MCA factor planes, it is possible to find the best and the worst adjustment combinations.     

A statistical law in the perception of risks and physical quantities in traffic

This paper suggests that a universal psychophysical law influences the perception of risks and physical quantities in traffic. This law states that there will be a tendency to overestimate low probabilities or small quantities, while high probabilities or large quantities may be underestimated. Studies of the perception of risk and physical quantities in traffic have found a highly consistent pattern, which shows that:

• 1.Pedestrians intending to cross the road overestimate the stopping distance of cars travelling at low speed and underestimate the stopping distance of cars travelling at high speed.
• 2.Car drivers intending to overtake overestimate the distance needed at low speed, but underestimate it at high speed.
• 3.Car drivers asked to accelerate from standstill to a given speed overshoot the target speed; when asked to slow down to a stated speed, drivers also overshoot the target speed.
• 4.When asked what speed to choose to save a given amount of time on a trip of given length, drivers overestimate target speed when initial speed is low and underestimate it when initial speed is high.
• 5.Drivers overestimate the increase in risk associated with a small increase in speed and underestimate the increase in risk associated with a larger increase in speed.
• 6.Drivers overestimate the risk of apprehension for traffic offences when it is low and underestimate it when it is high.
• 7.Road users overestimate the risk associated with comparatively safe modes of transport and underestimate the risk associated with comparatively hazardous modes of transport.

The paper gives examples of all these misperceptions of physical quantities and risk.     

Application of independent component analysis with mixture density model to localize brain alpha activity in fMRI and EEG

Independent component analysis (ICA) is an approach to solve the blind source separation problem. In the original and extended versions of ICA, nonlinearity functions are fixed to have specific density forms such as super‐Gaussian or sub‐Gaussian, thereby limiting their performance when sources with different classes of densities are mixed in multichannel data. In this article, we have incorporated a mixture density model such that no assumption about source density would be required. We show that this leads to better source separation due to increased flexibility in handling source‐ densities with flexible parametric nonlinearity. The algorithm was validated through simulation studies and its performance was compared to other versions of ICA. The modified mixture density ICA was then applied to functional magnetic resonance imaging (fMRI) and electroencephalography (EEG) data to localize independent sources of alpha activity in the human brain. A good spatial correlation was found in the spatial distribution of alpha sources derived independently from fMRI and EEG, suggesting that spontaneous alpha rhythm can be imaged by fMRI using ICA without concurrent acquisition of EEG. © 2004 Wiley Periodicals, Inc. Int J Imaging Syst Technol 14, 170–180, 2004; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ima.20021     

Complex approach to the vibrodiagnostic analysis of excessive vibration of the exhaust fan

The paper deals with the analysis of causes of excessive vibration of one of the two fans that in the steelworks provide exhaustion of vapor and residues produced during melting of steel scrap. During operation, the excessive vibration of the problematic fan led to the initiation of cracks in the concrete foundation and the repeated damage to the bearings. Under such circumstances, long-time operation could cause further significant damages or collapse of the whole equipment. The solution of the given task required to apply a complex approach, including experimental and numerical modal analysis of the fan’s rotating wheel as well as a series of operational measurements to assess the actual technical condition of the problematic fan and determine possible damages. The output is a series of measures developed to ensure safe and long-time operation of the fan.     

泽尼克像差组合对人眼光学质量的影响

基于人眼光学质量客观评价标准区域调制传递函数（AreaMTF）、斯特列尔比（SRX）和同心相对瞳孔平面（PFWc）,分析了波前像差RMS为0．25μm时泽尼克像差项组合对人眼光学质量的影响。C4（离焦）与C12（球差）等组合后,像差比例在1．33到4．90的范围内AreaMTF和SRX有极大值;C6（三叶草）与C7（彗差）等组合后,像差比例在0．20到1．00的范围内它们有极小值。二阶像差（离焦和像散）组合时,C4（离焦）起着主导作用。三阶像差（彗差和三叶草）组合时,SRX和PFWc值的变化范围均较大,分别为0．066到0．228和0．048到0．656。     

关联度分析在东方音乐厅音质评价中的应用

用东方音乐厅客观音质参数的测试结果和访谈得到的主观评价结果对东方音乐厅与世界上14个大型音乐厅的音质效果进行了分析,虽然东方音乐厅的音质效果令人满意,但其音质究竟能够达到怎样的满意度却缺乏可参照的目标。按照音质相近等级相同的原则可以判定东方音乐厅的音质效果与柏林交响乐厅最为接近,文章应用灰色系统关联度分析方法推断东方音乐厅的音质效果达到了优异级。     

Effects of excessive use of mobile phone technology in India on human health during COVID-19 lockdown

ObjectiveThe global health crisis in the form of COVID-19 has forced people to shift their routine activities into a remote environment with the help of technology. The outbreak of the COVID-19 has caused several organizations to be shut down and forced them to initiate work from home employing technology. Now more than ever, it's important for people and institutions to understand the impact of excessive use of mobile phone technology and electronic gadgets on human health, cognition, and behavior. It is important to understand their perspective and how individuals are coping with this challenge in the wake of the COVID-19 pandemic. The investigation is an effort to answer the research question: whether dependency on technology during lockdown has more effects on human health in comparison to normal times.MethodsThe study included participants from India (n = 122). A questionnaire was framed and the mode of conducting the survey chosen was online to maintain social distancing during the time of the Pandemic. The gathered data was statistically analysed employing RStudio and multiple regression techniques.ResultsThe statistical analysis confirms that lockdown scenarios have led to an increase in the usage of mobile phone technology which has been confirmed by around 90% of participants. Moreover, 95% of the participants perceive an increased risk of developing certain health problems due to excessive usage of mobile phones and technology. It has been evaluated that participants under the age group 15–30 years are highly affected (45.9%) during lockdown due to excessive dependence on technology. And, amongst different professions, participants involved in online teaching-learning are the most affected (42.6%).ConclusionThe findings indicate that dependency on technology during lockdown has more health effects as compared to normal times. So, it is suggested that as more waves of pandemics are being predicted, strategies should be planned to decrease the psychological and physiological effects of the overuse of technology during lockdown due to pandemics. As the lockdown situation unfolds, people and organization functioning styles should be rolled back to the limited dependency on technology.     

主换热器热端温差过大的原因分析和处理

介绍了4500m3/h空分设备主换热器热端温差过大的故障现象,经分析得出原因是:氮封管线泄漏,珠光砂进入污氮管线,而后进入主换热器,使换热面积减少。最后介绍了处理措施。     

民航飞行员工作负荷影响因素体系研究

飞行员工作负荷作为一个多维且较为复杂的研究对象,其受大量影响因素的影响。本文将建立完整的民航飞行员工作负荷影响因素体系,并对各影响因素的相对重要度进行分析。首先在工作负荷及其影响因素的分析研究基础上,结合飞机驾驶舱环境和飞行环境,通过与飞行员面谈的方法建立了影响因素体系。然后结合专家主观评估对飞行员工作负荷的影响因素指标进行筛选,采用5点Likert型标度获得各影响因素的相对重要性。最终建立了由飞行任务,飞行环境,驾驶舱人机界面,个体因素四大类下的完整的民航飞行员工作负荷影响体系。通过因素的重要度分析结果发现,影响程度最大的前四个影响因素依次为:时间压力、飞机类型(真机、模拟)、飞行时间、飞行阶段。完整的飞行员工作负荷影响因素体系对飞行员工作负荷的研究工作的开展有着重要的指导作用,同时提高工作负荷预测模型的精度。     

VDT作业视觉环境质量的评价方法

从照度、亮度、眩光、视屏显示质量、光色等方面设计了评价VDT作业视觉环境的指标体系。建立了VDT作业视觉环境质量的综合评价模型，并利用该模型对某些企业VDT作业场所的视觉环境进行了评价。应用实例的结果表明，本文建立的模型能够对VDT作业场所的视觉环境做出正确的评价。     

The effect of viscoelastic brain on the dynamic characteristics of the human skull-brain system

Summary In this paper, we present a solution to the problem of free vibrations of the human head system taking into account the dissipative behaviour of the brain. The mathematical model is based on the three-dimensional theory of viscoelasticity and the representation of the displacement field in terms of the Navier eigenvectors. The frequency equation is solved numerically and the results for eigenfrequencies and damping coefficients are presented for various geometrical and physical parameters of the system. The results obtained are in excellent agreement with the measured eigenfrequencies, and the predicted damping coefficients are within the order of magnitude of the measured ones. From the proposed analysis we have obtained the information that the role of the viscoelastic neck as well as the viscoelastic properties of the skull-brain system have to be simultaneously taken into account in the study of the frequency spectrum of the human head. The analysis of the realistic model is under preparation.     

Human reliability data, human error and accident models—illustration through the Three Mile Island accident analysis

Our first objective is to provide a panorama of Human Reliability data used in EDF's Safety Probabilistic Studies, and then, since these concepts are at the heart of Human Reliability and its methods, to go over the notion of human error and the understanding of accidents. We are not sure today that it is actually possible to provide in this field a foolproof and productive theoretical framework. Consequently, the aim of this article is to suggest potential paths of action and to provide information on EDF's progress along those paths which enables us to produce the most potentially useful Human Reliability analyses while taking into account current knowledge in Human Sciences.The second part of this article illustrates our point of view as EDF researchers through the analysis of the most famous civil nuclear accident, the Three Mile Island unit accident in 1979. Analysis of this accident allowed us to validate our positions regarding the need to move, in the case of an accident, from the concept of human error to that of systemic failure in the operation of systems such as a nuclear power plant. These concepts rely heavily on the notion of distributed cognition and we will explain how we applied it. These concepts were implemented in the MERMOS Human Reliability Probabilistic Assessment methods used in the latest EDF Probabilistic Human Reliability Assessment. Besides the fact that it is not very productive to focus exclusively on individual psychological error, the design of the MERMOS method and its implementation have confirmed two things: the significance of qualitative data collection for Human Reliability, and the central role held by Human Reliability experts in building knowledge about emergency operation, which in effect consists of Human Reliability data collection. The latest conclusion derived from the implementation of MERMOS is that, considering the difficulty in building ‘generic’ Human Reliability data in the field we are involved in, the best data for the analyst consist of the knowledge built up through already existing probabilistic analyses.     

Assessment of human reliability based on evaluation of plant experience: requirements and implementation

A major problem in assessment of human failures in probabilistic safety assessment is the lack of empirical data needed for human reliability analysis (HRA). This problem is aggravated by the fact that different HRA methods use different parameters for the assessment and that HRA is currently enforced to provide data and methods for assessment of human reliability in new technical environments such as computerized control rooms, in accident management situations, or in low-power and shut down situations. Plant experience is one source to deal with this problem. In this paper, a method is presented that describes how plant experience about human failures and human performance may be used to support the process of analyzing and assessing human reliability. Based on considerations of requirements of HRA, a method is presented first which is able to describe and analyze human interactions that were observed within events. Implementation of the approach as a database application is outlined. Second, the main results of the application of the method to 165 boiling water reactor events are presented. Observed influencing factors on human performance are discussed; estimates for probabilities are calculated and compared with the data tables of the THERP handbook. An outline is given for using the presented method for the analysis of cognitive errors or organizational aspects.     

本科教学工作水平评估工程的高校主体性探析

文章认为高校在本科教学工作水平评估过程中既是客体又是主体。提出要充分发挥高校在本科教学工作水平评估过程中的主体性作用，以利于评估功能的发挥和评估效果的获得。     

Review of advances in human reliability analysis of errors of commission, Part 1: EOC identification

In close connection with examples relevant to contemporary probabilistic safety assessment (PSA), a review of advances in human reliability analysis (HRA) of post-initiator errors of commission (EOCs), i.e. inappropriate actions under abnormal operating conditions, has been carried out. The review comprises both EOC identification (part 1) and quantification (part 2); part 1 is presented in this article. Emerging HRA methods addressing the problem of EOC identification are: A Technique for Human Event Analysis (ATHEANA), the EOC HRA method developed by Gesellschaft für Anlagen- und Reaktorsicherheit (GRS), the Misdiagnosis Tree Analysis (MDTA) method, and the Commission Errors Search and Assessment (CESA) method. Most of the EOCs referred to in predictive studies comprise the stop of running or the inhibition of anticipated functions; a few comprise the start of a function. The CESA search scheme—which proceeds from possible operator actions to the affected systems to scenarios and uses procedures and importance measures as key sources of input information—provides a formalized way for identifying relatively important scenarios with EOC opportunities. In the implementation however, attention should be paid regarding EOCs associated with familiar but non-procedural actions and EOCs leading to failures of manually initiated safety functions.     

Fast Fault Tree Analysis for Hybrid Uncertainties Using Stochastic Logic Implemented on Field‐Programmable Gate Arrays: An Application in Quantitative Assessment and mitigation of Welding Defects Risk

This paper presents a stochastic logic‐based method for quantitative risk assessment using fault tree analysis (FTA) that can take into account both types of uncertainties including objective and subjective uncertainties. In the proposed method, each fault tree gate is translated to its corresponding stochastic logic template and then is implemented on a field programmable gate array (FPGA). Because the analysis does not utilize any transformation methods, the results of analysis are more accurate than those methods which are based on transformation from possibility to probability distributions or vice versa. Experimental results for a benchmark fault tree show that this method accelerates analysis time compared to conventional hybrid uncertainty analysis method and transformation methods. The efficiency of the proposed method is demonstrated by implementation in a real steel structure project. The quantitative risk assessment is performed for the incomplete penetration as one of the defects encountered in arc welding process, and its results are compared with transformation methods. The comparison results show the proposed hybrid uncertainty analysis method is also more accurate in comparison to the transformation‐based approaches. Copyright © 2016 John Wiley & Sons, Ltd.     

视野培训对视觉搜索绩效的影响

视觉搜索在质检、安检等领域有着广泛应用。本研究应用2（培训强度：高,低）×2（反馈：有,无）组间实验进行了视野培训对视觉搜索绩效的影响的研究。结果表明,高强度或有反馈的视野培训能够增大视野面积,改善视野形状,从而显著提高视觉搜索绩效。高强度的培训对视觉搜索绩效的改善幅度显著大于低强度培训。培训强度与反馈对视觉搜索绩效的影响有交互作用,高强度有反馈的视野培训对视觉搜索绩效改善幅度最大。