隆乳术的演变与进步

隆乳术不仅可以重塑女性的形体美,而且可以增强女性的自信心,在当前具有广阔的市场。纵观隆乳术的发展演变史,从最初的注射隆乳术到自体组织隆乳术,再到当前的假体隆乳术和自体脂肪移植隆乳术,经历了“实践、认识、再实践、再认识”的多次反复。各种隆乳方式各具特色,其间既有成功的经验,又有失败的教训。针对隆乳术安全性的改进推动了隆乳术的不断向前发展。寻找一种安全有效的隆乳方式和理想的隆乳材料成为当前隆乳术发展的关键和整形外科医师关注的重点。     

Eyewitness identification discriminability: ROC analysis versus logistic regression

To reach conclusions regarding the respective accuracy of two conditions, eyewitness researchers evaluate correct and false identification rates computed across participants. Two approaches typically are employed. One approach relies on ratio-based probative value measures; but Wixted and Mickes (2012) and Gronlund, Wixted, and Mickes (2014) showed that these measures fail to disentangle an assessment of accuracy (i.e., discriminability between guilty and innocent suspects) from response bias (i.e., a willingness to make a response). Our focus is on a second approach, logistic regression analyses of the correct and of the false identification rates. Logistic regression also fails to disentangle discriminability from bias. Therefore, it only can denote the most accurate condition in limited circumstances. The best approach for reaching the proper conclusion regarding which condition is most accurate is to use receiver operator characteristic (ROC) analysis. Simulated ROC data illustrate the problem with a reliance on logistic regression to assess accuracy.     

Crossing road intersections in old age—With or without risks? Perceptions of risk and crossing behaviours among the elderly

Pedestrians aged over 65 are known to be a critical group in terms of road safety because they represent the age group with the highest number of fatalities or injured persons in road accidents. It is widely recognized that the latter is due to the physical vulnerability of this age group in case of injury. However, physical and cognitive decline come into play during the action of crossing a street. Various studies have attempted to connect the crossing behaviours of the elderly with variables such as age, gender, sensory acuity, level of attentiveness, physical decline and the design of intersections. In demonstrating the complexity of the relationship between people and their environments, the literature suggests that age, physical ability, and the spatial configuration of roads are major components of road safety. Moreover, people’s knowledge and mastery of their environments, as well as their ability to adapt to change affects how they move through space. Taking these factors into account, this study examines the perceptions of elderly pedestrians with regards to the quality and risks of road crossings in the context of Montréal, Québec, in Canada. The analyze are based on observations and questionnaires in order to bring to light a better understanding of the relationship between the crossing behaviours, characteristics and perceptions of the elderly. While previous studies have examined perception and observation separately, this study is unique in having looked at both angles simultaneously. Five profiles of elderly people in both urban and suburban environments were established. A sample of 181 elderly pedestrians (65–93 years of age, AVG = 74) were surveyed using a questionnaire. In addition to close-ended questions, respondents were asked to evaluate 17 environmental ambiance and risk behaviours according to various scales. Using principal component analysis (PCA) and hierarchical cluster analysis (HCA), the data was grouped into 6 categories that define and distinguish 7 profiles of elderly people. These profiles were explored according to the socioeconomic status and crossing behaviours of respondents. The probabilities of adopting different crossing behaviours were tested by employing logistic regression models. The results reveal greater variability in the perceptions of the elderly in terms of risk related to crossing behaviours and type of signalisation at intersections. Even among seniors, the perceptions of risk varied greatly, which may have had an impact on their behaviours. While some of the behaviours observed coincided with the perceptions of respondents, the results of this study suggest that they only play a marginal role.     

Professional drivers’ fatigue as a problem of the modern era

ObjectiveAll around the world numerous studies have been carried out and indicated that 20–50% of commercial vehicle accidents occur because of fatigue. Professional drivers represent an important category of drivers who are present in traffic on a daily basis transporting passengers or goods and their responsibility is at a very high level. These drivers are most exposed to the impact of fatigue. The review of the literature has provided three main factors which can influence the onset of fatigue: sleep factors, work factors, health factors. The main aim of this study was to determine the influence of the three main factors of fatigue between bus and truck drivers in the Republic of Serbia.MethodsThe survey has been conducted among bus and truck drivers who are employed in transportation companies across the Republic of Serbia. The research consists of collecting and analyzing bus and truck drivers’ answers according to the above mentioned factors which influence the occurrence of fatigue.ResultsIn this study we have found that circadian rhythm, sleep and work factors have an impact on drivers’ fatigue. On the other side, time of going to sleep has no impact on the quality of sleep and on fatigue. The results show that if the drivers work over the legal limit, they are 3 times more likely to sleep less than 6 h in 24 h and if they sleep less than 6 h, it is likely that the poor quality of their sleep will be 8 times higher. The poor quality of sleep reduces driver performance, and therefore increases the risk of accidents.Conclusions2 of 3 investigated factors have an impact on the occurrence of fatigue. The third factor, health factor, should be examined in more detail, and other elements should be analysed in order to determine their influence on the fatigue.     

Investigation of drivers’ thresholds of a subjectively accepted driving performance with a focus on automated driving

Lately, the development and implementation of automated driving moved to the center of interest in the automotive industry. In this context, one of the central issues – the configuration of adequate trajectories – is mainly tackled using a technical approach. However, it appears that a technically ideal driving performance does not necessarily coincide with the drivers’ subjective preferences. This study strives to determine thresholds of a subjectively accepted driving performance regarding lateral vehicle control. A second objective is to analyze the influence of selected personal and situational factors on these thresholds. An empirical online survey with 161 participants rating video sequences of driving performances was conducted. The video sequences differed not only with regard to the lateral offset of the ego-vehicle but also concerning the weather (sun/rain) and traffic conditions (existence/driving behavior of oncoming traffic). Additionally, the participants’ driving experience and sensation seeking were considered in the data evaluation. To analyze the data, binary logistic regression analyses were calculated. They revealed that the subjective evaluation of driving performances varies primarily depending on the lateral offset of both the ego-vehicle and the oncoming traffic. The results indicate that regarding the lateral offset certain thresholds of subjectively accepted driving performances do exist. Regarding the development of automated driving systems, two issues need to be considered in order to ultimately guarantee user acceptance. First, the subjective thresholds need to be integrated into the systems’ trajectory planning. Second, the oncoming traffic’s driving behavior has to be considered.     

Investigating cycling kinematics and braking maneuvers in the real world: e-bikes make cyclists move faster,brake harder,and experience new conflicts

Pedelecs (e-bikes), which facilitate higher speeds with less effort in comparison to traditional bicycles (t-bikes), have grown considerably in popularity in recent years. Despite the large expansion of this new transportation mode, little is known about the behavior of e-cyclists, or whether cycling an e-bike increases crash risk and the likelihood of conflicts with other road users, compared to cycling on t-bikes. In order to support the design of safety measures and to maximize the benefits of e-bike use, it is critical to investigate the real-world behavior of riders as a result of switching from t-bikes to e-bikes.Naturalistic studies provide an unequaled method for investigating rider cycling behavior and bicycle kinematics in the real world in which the cyclist regularly experiences traffic conflicts and may need to perform avoidance maneuvers, such as hard braking, to avoid crashing. In this paper we investigate cycling kinematics and braking events from naturalistic data to determine the extent to which cyclist behavior changes as a result of transferring from t-bikes to e-bikes, and whether such change influences cycling safety.Data from the BikeSAFE and E-bikeSAFE naturalistic studies were used in this investigation to evaluate possible changes in the behavior of six cyclists riding t-bikes in the first study and e-bikes in the second one. Individual cyclists’ kinematics were compared between bicycle types. In addition, a total of 5092 braking events were automatically extracted after identification of dynamic triggers. The 286 harshest braking events (136 cases for t-bike and 150 for e-bike) were then validated and coded via video inspection.Results revealed that each of the cyclists rode faster on the e-bike than on the t-bike, increasing his/her average speed by 2.9–5.0 km/h. Riding an e-bike also increased the probability to unexpectedly have to brake hard (odds ratio = 1.72). In addition, the risk of confronting abrupt braking and sharp deceleration were higher when riding an e-bike than when riding a t-bike.Our findings provide evidence that cyclists’ behavior and the way cyclists interact with other road users change when cyclists switch from t-bikes to e-bikes. Because of the higher velocity, when on e-bikes, cyclists appear to have harder time predicting movements within the traffic environment and, as a result, they need to brake abruptly more often to avoid collisions, compared with cycling on t-bikes. This study provides new insights into the potential impact on safety that a cycling society moving to e-bikes may have, indicating that e-cycling requires more reactive maneuvers than does cycling traditional bicycles and suggesting that any distractive activity may be more critical when riding e-bikes compared to traditional bikes.     

Investigating the effectiveness of perceptual treatments on a crest vertical curve: A driving simulator study

Rural roads are characterized by a high percentage of run-off-the-road accidents and head-on collisions, mainly caused by inappropriate speeds and failure to maintain a proper lateral position along the roadway alignment. Among several road safety treatments, low-cost perceptual measures are considered an effective tool, as they generally increase the risk perceived by drivers, or even alter the drivers’ speed perception, and consequently tempting them to decrease their speeds. Their effectiveness has been widely recognized in a number of studies, especially with respect to road intersections and curves.The overall aim of this study is to investigate the effects of different perceptual treatments on driving speed, along a crest vertical curve of an existing two-lane rural road, in order to identify the most effective measure to reduce speed and define its subsequent implementation in the field. Three perceptual treatments were tested using a driving simulator: white peripheral transverse bars, red peripheral transverse bars and optical speed bars, with each one being painted along the approaching tangent to the crest vertical curve. The effects of these speed-reducing measures were investigated using a sample of forty-four participants, by comparing the driving speeds with those recorded under a baseline condition (without a treatment); these were also used to validate the driving simulator’s speed measurements with those found in the field. Moreover, subjective measures were collected, consisting of the driver’s static evaluation of the desired speed, risk perception and markings comprehension, based on screen shot pictures that represented the simulated configurations of the treatments.The findings demonstrated an overall effectiveness of the perceptual treatments, although only the red peripheral transverse bars were found to significantly reduce the driving speeds (−6 km/h). The analysis of the questionnaire yielded interesting information and demonstrated the importance of performing driving simulation tests for evaluating the effectiveness of perceptual treatments.Finally, the results confirmed the enormous potential of using driving simulators to pinpoint a number of speed-reducing measures, and consequently select the most effective one that reduces cost and promotes safety before its actual implementation in the field.     

Traction-energy balancing adaptive control with slip optimization for wheeled robots on rough terrain

On rough terrain, excessive wheel slippage is easily generated by changes of surface conditions such as soil types and geometries. It induces considerable loss of wheel traction and battery energy. To prevent this, wheeled robots should consistently recognize the current situation generated between wheel and surface. And also wheeled robots are required to optimally control wheel motion in limited wheel traction and battery capacity. Therefore, this paper proposes a novel wheel control algorithm based on slip optimization of traction and energy, which is adaptive to change of surface condition. Proposed wheel control algorithm is called Traction-Energy Balancing Adaptive Control (TEB) in this paper and TEB assigns optimized rotation speed to each wheel by observing wheel slip ratio which is a key parameter of TEB. As functions of TEB, TEB is largely divided into three main parts; (1) slip optimizer (2) slip controller (3) SC-compensator. In the slip optimizer, two optimal slip models were derived as a function of slip ratios regarding maximum traction and tractive efficiency using experimental data about wheel-terrain interaction in three types of soil (grass, gravel and sand). And the optimal slip models were employed in order to determine a desired slip value of wheel with observation of a change in actual robot velocity as control input in the slip controller. For optimal slip control, the proposed slip controller is based on conventional PID controller with compensating disturbance in the controller (SC-compensator) which occurs by change of surface shapes. In the SC-compensator, radial function networks (RBFN) was applied in the slip controller and RBFN was of help to readjust previously set PID gains depending on occurred slip error. Finally, TEB was experimentally verified by controlling a real robot having four wheels on various terrain types.