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The present study tackles the linguistic phenomenon of ‘gradability by focus’ in Arabic from a cognitive linguistic perspective. By and large, the early Arab grammarians have not theorized about gradability despite its importance in the semantic relationships. They address some grammatical and morphological forms that convey either ends of the scale of gradability. Gradable forms include ‘‘’at-Tawwkīd’’ (i.e., emphasis), ‘’al-Mafξūl ’al-Muŧlaq” (i.e., the cognate object), şiyagh ’at-Taşghīr’’ (i.e., diminutive forms), “şiyagh ’al-Mubālaghah” (i.e., maximizers) and many other forms. However, they do not use any of the aforesaid forms under the heading of ‘’at-Tadarruj bit-Tarkīz’’ (i.e., gradability by focus). Therefore, the study grounds for ‘focus’ highlighting its salient lexical, grammatical, and morphological features in Arabic. The present paper provides definitions for gradability, focus, prototypicality and precision. Afterwards, it provides a detailed analysis of the sub-categories of prototypicality and precision unearthing their rhetorical functions. In conclusion, gradability by focus plays a key role in identifying the subtle shades of meaning. Tackling such cognitive linguistic features is of an overwhelming importance at the pure linguistic level as well as the sociolinguistic one.

The aim of the present study was to examine the effect of urbanization, purchasing power, and income on motorcycle ownership and the effects of interactions between these factors. Specifically, we examined how the inverse-U relationship between motorcycle ownership and economic development changed in response to different levels of purchasing power and urbanization. We apply a fixed effects negative binomial panel regression analysis on a panel data of 73 countries between 1963 and 2013. Results revealed evidence of an inverse-U relationship between purchasing power and motorcycle ownership. Motorcycle ownership increases during the beginning stages of consumer price index (CPI), due to higher purchasing power. Once a threshold level was exceeded, higher CPI (lesser purchasing power) created an inverted effect, which led to a decline in motorcycle ownership. Importantly, the turning point increased in accordance with an increase in urbanization. The estimation results also suggested that the inverse-U relationship between motorcycle ownership and per capita GDP varied in accordance with both purchasing power and urbanization.

Background: Due to the high prevalence and wide distribution of coronaviruses, their large genetic diversity, frequent recombination of their genomes, and increasing human-animal interface activities, novel coronaviruses are likely to emerge periodically in humans owing to frequent cross-species infections and occasional spillover event. Objectives: The aim of this research is to study the short-term morbidities, mortalities and trends of international spread of the COVID-19 outbreak. In addition, to study the explosiveness and aggressiveness of the outbreak and the gaps in response. Methodology: Outbreak events were observed and followed up over two months. This study used daily statistical reports issued by the World Health Organization, as well as data from different national authorities, regarding mortalities and morbidities from all over the world, with a specific focus on Chinese statistics as the main source of the outbreak. Results: The current study showed that the number of confirmed COVID-19 infected cases started with 41 cases in early January 2020. The number of cases with COVID-19 kept rising to reach 128000 on March 12, 2020. Moreover, the current study has revealed that the number of deaths was only (1) case in early January 2020 and increased to 25 deaths on January 23, and end up with 170 deaths by the end of January. Deaths have dramatically increased to reach 2462 on Feb 23 and 4717 on March 12. In regards to the geographical spread of the COVID-19 infection outbreak, the number of affected countries increased to 100 by mid- March 2020. The number of fatality cases was 0.0368, compared to 0.533 in recovered cases within two months. Conclusion: The natural history and course of the current outbreak revealed a highly explosive nature linked to considerable aggressiveness in terms of complications and mortalities, within only two months, and spread to 100 countries worldwide with 80000 cases within only two months. The study forecasted that the peak of the outbreak is not yet attained, and events that are more dramatic may occur worldwide.

BACKGROUND: Non-communicable diseases (NCDs) are the leading causes of death worldwide. In the UAE, NCDs account for nearly 77% of all deaths. There is limited empirical research on this topic in the UAE. We aimed to examine the association of non-communicable diseases and the sociodemographic characteristics among the adult population of Dubai. METHODS: The study used secondary data from the Dubai Household Health Survey (DHHS), 2019. DHHS is a cross-sectional complex design, stratified by geographic area, and uses multistage probability sampling. In this survey, 2247 families were interviewed and only adults aged 18+ were included for the analysis. The quasi-binomial distribution was used to identify the socio-demographic characteristics association with NCDs. RESULTS: The prevalence of NCDs among the adult population of Dubai was 15.01%. Individuals aged 60+, local Arabs (Emirati), divorced and widowed individuals, and individuals who were not currently working reported NCDs more than the other groups. In the regression analysis, the association with NCDs were reported among elderly people, males, unmarried individuals, older individuals who are unmarried, and Emiratis. CONCLUSION: The study identified several socio-demographic characteristics associated with reporting NCDs. This is one of the few studies related to NCDs in Dubai. Allocating appropriate resources to the population groups identified is crucial to reduce the incidence of NCDs in the Emirate.

Complex network theory is a multidisciplinary research direction of complexity science which has experienced a rapid surge of interest over the last two decades. Its applications in land-based urban traffic network studies have been fruitful, but have suffered from the lack of a systematic cognitive and integration framework. This paper reviews complex network theory related knowledge and discusses its applications in urban traffic network studies in several directions. This includes network representation methods, topological and geographical related studies, network communities mining, network robustness and vulnerability, big-data-based research, network optimization, co-evolution research and multilayer network theory related studies. Finally, new research directions are pointed out. With these efforts, this physics-based concept will be more easily and widely accepted by urban traffic network planners, designers, and other related scholars.

Research into multi-layer network growth in the detection of urban dynamics provides scholars a new way to discuss the structure changing trends and related impacts. The quantitative research method is applied to examine, the network centrality, network accessibility and network community partition focusing on the upper-layer (rail network) network growth process. We based on the case study of Kuala Lumpur and found that when a rail network grows with a simple tree-like network to a more intricate form, the network diameter and the average shortest path length of multi-layer networks decrease dramatically. The network expansion ability keeps changing and more rail stations in the city centre have higher ability for future expansion. Changes in betweenness centrality and closeness centrality of multi-layer networks essentially hinge on the growth of rail network, with the highest change rate of closeness centrality at around 211.48%. The growth of network allows the remainder of the network to be easily visited, with the highest change rate of network accessibility around 12%. Different performances of these nodes added in the multi-layer network are discussed to show their impact on the repartition of network communities and the number of communities is decreasing. We believe this research can benefit scholars to easily understand and apply these network dynamic computational techniques.

Construction of exclusive motorcycle lanes is one of the measures to reduce motorcycle fatalities. Previous studies highlighted the risk of crashes with roadside objects and the tendency of motorcyclists to ride with excessive speed on exclusive motorcycle lanes. However, the risk of same-direction crashes on exclusive motorcycle lanes was not explored in much detail, especially on the impact of lane geometry and roadside configurations. This study used naturalistic riding data to determine the effects of lane width and roadside configurations on overtaking speed, lateral position and likelihood of comfortable overtaking on tangential sections of an exclusive motorcycle lane. Twenty-nine recruited motorcyclists rode the instrumented motorcycles along a 20km stretch of an exclusive motorcycle lane along a major urban road. Results revealed that both the roadside configurations and lane width significantly affect the participants' lateral position, while the roadside configurations only affects the overtaking speed. Participants' overtaking speeds and the front motorcycles' lateral position contribute significantly to the likelihood of comfortable overtaking in exclusive motorcycle lanes. The findings highlight the importance of micro-level behavior indicators in improving the design and overall safety of the exclusive motorcycle facility.

The design of urban transportation networks plays a key role in the urban planning process, and the coevolution of urban networks has recently garnered significant attention in literature. However, most of these recent articles are based on networks that are essentially planar. In this research, we propose a heuristic multilayer urban network coevolution model with lower layer network and upper layer network that are associated with growth and stimulate one another. We first use the relative neighbourhood graph and the Gabriel graph to simulate the structure of rail and road networks, respectively. With simulation we find that when a specific number of nodes are added, the total travel cost ratio between an expanded network and the initial lower layer network has the lowest value. The cooperation strength Λ and the changeable parameter average operation speed ratio Θ show that transit users’ route choices change dramatically through the coevolution process and that their decisions, in turn, affect the multilayer network structure. We also note that the simulated relation between the Gini coefficient of the betweenness centrality, Θ and Λ have an optimal point for network design. This research could inspire the analysis of urban network topology features and the assessment of urban growth trends.

In recent years in Malaysia, severe road crashes involving intercity buses have been increasing. With increased public concerns about intercity bus safety, effectively managing travel risk has become critical for both intercity bus operators and road safety policy makers. Intercity bus drivers are generally at a higher risk for crashes due to long hours of driving and exposure to different road conditions. Therefore, understanding and quantifying their risks and taking steps to manage them could improve intercity bus safety. The aim of this study is to establish a safety performance index for each risk domain to measure and compare intercity bus safety in terms of risk factors. The risk domains considered in this study were road environment conditions, bus driver driving behaviors and bus safety conditions. The weighted indicators were aggregated into the safety performance index for each risk domain was done using the Exploratory Factor Analysis method. The paired sample t-test was then applied to determine which safety performance indices were significantly different from each other. The results indicate that road environment conditions have contributed more to intercity bus safety risks on the east coast than on the west coast of peninsular Malaysia. The evidence presented in this study shows that different intercity bus companies showed mixed safety performance in different risk domains. Therefore, we suggest the development of targeted road safety programs for each intercity bus company to address intercity bus safety problems.

Light detection and ranging (LiDAR) data classification provides useful thematic maps for numerous geospatial applications. Several methods and algorithms have been proposed recently for LiDAR data classification. Most studies focused on object-based analysis because of its advantages over per-pixel-based methods. However, several issues, such as parameter optimization, attribute selection, and development of transferable rulesets, remain challenging in this topic. This study contributes to LiDAR data classification by developing an approach that integrates ant colony optimization (ACO) and rule-based classification. First, LiDAR-derived digital elevation and digital surface models were integrated with high-resolution orthophotos. Second, the processed raster was segmented with the multiresolution segmentation method. Subsequently, the parameters were optimized with a supervised technique based on fuzzy analysis. A total of 20 attributes were selected based on general knowledge on the study area and LiDAR data; the best subset containing 12 attributes was then selected via ACO. These attributes were utilized to develop rulesets through the use of a decision tree algorithm, and a thematic map was generated for the study area. Results revealed the robustness of the proposed method, which has an overall accuracy of ∼95% and a kappa coefficient of 0.94. The rule-based approach with all attributes and the k nearest neighbor (KNN) classification method were applied to validate the results of the proposed method. The overall accuracy of the rule-based method with all attributes was ∼88% (kappa = 0.82), whereas the KNN method had an overall accuracy of

Recent empirical studies indicated that motorcycle ownership grows as a nation’s economy develops, but decreases once incomes have passed a threshold level. The aim of this study was to assess the impacts of relative improvements in road mobility over road accessibility (MPA) and income inequality on motorcycle to passenger car ownership ratio (MPC). Particularly, we investigated how the reverse U-shaped relationship between MPC and economic expansion varied in response to changes in the MPA and income inequality. A fixed-effects panel linear regression analysis was performed on a panel of 53 countries over the period of 1963–2013. This study highlights four key findings in relation to the impact of per capita Gross Domestic Product (GDP) on MPC. Firstly, the effect of MPA on MPC differs by per capita GDP levels. Results indicated that a rise in MPA is likely to lead to increases in MPC at lower per capita GDP, specifically increases in the number of small power motorcycles, but lead to decreases in MPC once per capita GDP levels have exceeded US$3,081. However, as per capita GDP rises beyond US$44,767, an increase in MPA would lead to increases in MPC and one would expect increases in the number of high-power motorcycles. Secondly, there is a reverse U-shaped relationship between MPC and income inequality. That is, a rise in income inequality is initially accompanied by increases in MPC, but MPC decreases once per capita GDP levels have passed a specific level. Thirdly, under lower income inequality, there is a U-shaped relationship between MPC and per capita GDP, and fourthly, under higher income inequality, this relationship becomes reverse U-shaped.

This study investigates the power of deep learning in predicting the severity of injuries when accidents occur due to traffic on Malaysian highways. Three network architectures based on a simple feedforward Neural Networks (NN), Recurrent Neural Networks (RNN), and Convolutional Neural Networks (CNN) were proposed and optimized through a grid search optimization to fine tune the hyperparameters of the models that can best predict the outputs with less computational costs. The results showed that among the tested algorithms, the RNN model with an average accuracy of 73.76% outperformed the NN model (68.79%) and the CNN (70.30%) model based on a 10-fold cross-validation approach. On the other hand, the sensitivity analysis indicated that the best optimization algorithm is “Nadam” in all the three network architectures. In addition, the best batch size for the NN and RNN was determined to be 4 and 8 for CNN. The dropout with keep probability of 0.2 and 0.5 was found critical for the CNN and RNN models, respectively. This research has shown that deep learning models such as CNN and RNN provide additional information inherent in the raw data such as temporal and spatial correlations that outperform the traditional NN model in terms of both accuracy and stability.

An automobile-motorcycle crash most commonly results when an automobile pulls out of a side road into the path of an oncoming motorcycle and violates the motorcyclist's right-of-way. One of the reasons for this could be that motorists misjudged the motorcycle arrival time. Motorcyclists are particularly vulnerable to injury in crashes with truck due to substantial differences in vehicle mass, protection degree and speed. We investigated truck drivers' judgments of motorcycle time-to-arrival (TTA) across a number of visual treatments. Participants watched a series of video clips captured at a T-intersection, and they were instructed to respond by clicking the computer mouse at the time they estimated the front wheels of an oncoming vehicle (motorcycle or car) to reach the T-intersection. The results showed that, at long distance between the target motorcycle and the viewer, the motorcycle with daytime running headlights (DRH) was estimated to arrive sooner than the motorcycle whose motorcyclist wore a black helmet with a reflective sticker. However, the opposite is true at a short distance. We also found that a motorcyclist wearing a white helmet and riding a motorcycle with DRH, as well as a motorcyclist wearing a white helmet and white outfit, would improve truck drivers' judgment with respect to motorcycle TTA. Consequently, truck drivers would be less likely to pull out into a small gap in front of a motorcycle, resulting in a higher safety margin for the motorcycle.

Cross-country statistics have revealed steady growth in the number of motorcycles in many less advanced economic countries (LAEC) with emerging economies due to increased urbanisation and personal wealth. In contrast, an opposite trend is occurring in advanced economic countries (AEC), with cars replacing motorcycles as income grows. Motor vehicle crashes and injuries are an inevitable consequence of a high motorcycle population. This study focused on understanding how economic growth affects the motorcycle to passenger car (MPC) ownership ratio and what factors underlie this relationship. The data used in this analysis contained a sample of 80 countries at various levels of economic developmental growth over the 48-year period between 1963 and 2010. The results pointed to an inverted U-shaped relationship between the MPC ownership ratio and the per capita Gross Domestic Product (GDP). Generally, the MPC ownership ratio increased with income at a lower level and decreased with income at a higher level. The evidence indicated that urbanisation, the total road length per thousand population, and a proxy for purchasing power with regard to vehicle purchases were the underlying factors that contributed to this relationship.

Road traffic accidents represented as the third cause of “death and disease” also the major cause of death among young people aged 15-29 years. In recent decade consequential investigation has been conducted on road crash contributing factors. All these researches showed that the recurrence and severity of accidents depend on many causes, such as vehicle performance, roadway environment, and characteristics of road users. Despite many studies in this field, the function of human factors on road accidents, is still unclear, due to the complex human characteristics. The lack of comprehensive model or procedure for scrutiny and evaluating the human characteristics which contributed to road incidents, motivate us to review on previous studies in order to indicate the relationships between human factors and road safety. This paper focus on the natural driving behavior of drivers including hazard perception and risk-taking of drivers which is affected by age, perceptual/cognitive abilities and driving experience. The study clearly shows that the mentioned factors have a huge impact on road incidents. Therefore, this paper indicate and recommend a number of solutions in order to mitigate the severity and frequency of accidents caused by human errors. Also previous road safety studies will provide series of crucial information for improvement of driver licensing and their training procedure.

Road safety issue has become a major concern worldwide due to the serious consequences of road accidents on countries socio-economics and human lives. The main aim of this paper is to discuss and review the effects of geometric design elements on road accidents including statistical models used over the years and to compare the outcomes of the studies conducted in several countries. A way to improve road safety is improving road geometric design to mitigate accidents occurrence and severity on roadways. In order to improve the road design, it is crucial to evaluate and define the relationship between road geometric design elements and road accidents. Studies have tried to relate road geometric design elements such as lane number, sight distance, super-elevation, median width and type, lane and shoulder width, curve radius, gradient, and horizontal and vertical alignments to accident rates. Due to the interrelations between geometric design elements with each other and with other road accident factors, and also lack of reliable methodology of relationship estimation between road geometric design and safety. Ongoing enhancement of statistical methods has resulted in many road design-accidents analysis models which have been developed using a variety of statistical modelling approaches such as linear regression models, multiple linear regression models, Poisson regression models, Poisson-Gamma models, negative binomial models, bivariate and multivariate models, generalized estimation regression models, random parameters models, etc. However, some limitations have been encountered using the mentioned statistical models, thereby there are opportunities for road safety researchers to overcome the limitation challenges.

The effective tire-pavement contact area affects the relative damage of asphalt pavement and should be incorporated in both mechanistic and empirical response analyses of pavements. A new machine called ROTOCOM Wheel Tracker (RCWT) was designed and fabricated to capture the effective tire contact area apart from slab compacting, and conducting simulative laboratory wheel tracking tests. The main focus of this paper is laboratory measurement of effective tire contact areas for various tread patterns. Seven tire treads were selected for the footprint image analyses at five tire loads and four tire inflation pressures. An image processing MATLAB-based program was coded to calculate the contact areas of the 280 imprints obtained from both sides of the RCWT. Factorial analysis indicated significant effects of tire tread, tire load, and inflation pressure on the resulting contact area. Comparison between effective and traditional contact areas indicated that the current pavement design procedure with traditiona...

Motorcycle braking distance is one of the main components of motorcycle stopping sight distance. Motorcycle braking performance in different situations was not consistent in published literature. This research measured the riders' braking distances and decelerations to both unexpected and expected objects. For braking maneuvers to an expected object, 89 motorcycle riders released the accelerator and applied the brake as quickly as possible following activation of a light beside the road of both dry and wet pavements. As for an unexpected object, 16 nonalerted subjects were confronted with the need to stop for an unexpected object along the roadway. Vehicle speeds, braking distances, and average deceleration were computed for each braking maneuver. RESULTS showed that the deceleration varied among the riders in which 90% of riders' decelerations were at least 2.75 m/s2 under wet conditions, whereas 90% of all riders decelerated at least 3.3 m/s2 on dry pavements. Overall, the motorcycle braking distance is more than the braking distance of passenger cars. These findings suggest that in countries where motorcycles are heavily used, their roads should be investigated for provisions of adequate motorcycle stopping sight distance, especially if the roads were designed according to AASHTO guidelines. Language: en

Cordon pricing is an effective policy to alleviate congestion and manage travel demand in city centres. However, different responses among road users to certain policies are inevitable. This paper presents a study evaluating the possible consequences of cordon and parking pricing on road users with different trip purposes, i.e., workers and non-workers. Different models have been developed and calibrated with data from the central business district of Mashhad, Iran, using revealed and stated preference methods. The analysis of the interviewee responses to the hypothetical situations shows that workers comprise the dominant proportion using each mode of travel to the Mashhad CBD. The commuters were provided with alternative choices, and their preferences were examined using multinomial logit. The results show that the cost-based policy such as parking and cordon pricing is good to reduce congestion as it affects workers, but the impact is more evident for non-workers travelling to the CBD. Furthermore, the model suggests that workers are more likely to shift mode in response to changes in travel time. The model was also developed to obtain different willingness-to-pay measures, which indicate that workers have a greater willingness to pay for parking and cordon pricing than non-workers.

The purpose of this study was to explore travellers’ responsiveness to congestion pricing (cordon pricing) and parking attributes (especially parking pricing) in deciding whether to drive and park in the central business district (CBD). Employing the stated-preference method, data were collected by personal interviews in Mashhad City CBD. The respondents were requested to report their current trip to the CBD by answering a set of questions and scenarios to consider five alternatives, including two parking locations in the CBD: park inside the cordon-pricing zone or outside and access the cordon area by walking or public transport, shift to public transport (taxi and bus), or cancelling of their trip to the CBD. The two parking locations were categorised by cordon and parking tariff schedule, search and queue time for a parking space, and access time from the parking space to the final destination. The preferences regarding mode of transportation and parking choices were determined using a multinomial logit model, which was used to estimate elasticity values and the willingness-to-pay among attributes. The results indicate that drivers are highly sensitive to cordon charge (−1.145), significantly more than to parking cost, search and egress times in switching mode and parking choice. Furthermore, respondents’ reactions suggest that drivers’ willingness to pay for parking fees is higher than their tendency to pay for cordon tolls.

The second largest holy city of the world, Mashhad, attracts high volumes of tourists and pilgrims every year. Most visitors travel by private car and are a source of considerable funds for the local economy. Among road users, tourists as one of the major traveller categories in Mashhad city behave differently due to the particular trip purpose. The aim of this research is to model tourist's shifting modes of travel behaviour when policy measures, such as the parking and cordon fares, are implemented. The tourists’ preferences were examined using binary logit analysis when different options of travel cost and time scenarios were provided. Results indicate that travel time, parking cost, cordon cost, education level and vehicle price influence tourist's modal choice. In addition, the finding shows that congestion pricing will be more effective than a parking pricing strategy in encouraging switching of modes.

One of the most effective engineering measures is the provision of an exclusive motorcycle lane that separates motorcycles from other mixed traffic to reduce traffic congestion and motorcycle crashes. Even though the existing exclusive motorcycle lanes in Malaysia reduced the incidents of motorcycle crashes with other vehicles, the design of this special motorcycle lane was based on a cross reference between a bicycle track and a highway. Thus, a suitable design guide is yet to be developed for the geometrical design of a proper and safer exclusive motorcycle lane. Safe stopping sight distance (SSD) has been recognized as a criterion for road design and should be taken into account. Motorcyclist perception response time (PRT) is the time from detection object until the rider reduces motorcycle speed in braking action is an essential component of motorcycle SSD. Two road experiments were conducted to obtain empirical values of motorcycle PRT to expected and unexpected objects. In the expected condition, 89 motorcyclists applied brake as quickly as possible following activation of a light beside the road. In the unexpected condition, 16 riders responded by braking in response to an obstacle that appeared suddenly in their lane. The mean PRT to expected and unexpected object is 0.71 s and 1.25 s respectively. The 85th percentile PRT to unexpected object is 2.12 s. This study found that most riders are capable of responding to an unexpected object along the roadway in 2.5 s or less. Therefore, PRT of 2.5 s is an appropriate value for motorcycle lane geometric design.

In developing Association of Southeast Asian Nations (ASEAN) countries, the motorcycle is a popular means of transportation because it is cheap and provides flexible door-to-door mobility. However, motorcyclists are also highly involved in road accidents. Separating motorcycles from other vehicles in traffic by providing motorcycle lanes is a good engineering measure to improve the safety of motorcyclists. In designing motorcycle lanes, considerations of geometrical elements such as horizontal and vertical curve lengths, stopping distances, and passing sight distances are essential. This study attempts to quantify the eye levels and head levels of motorcycle riders and motorcycle headlight and taillight height characteristics that influenced these geometrical elements. Characteristics of the motorcycles observed along the existing exclusive motorcycle lanes in Selangor state of Malaysia were transcribed from a camcorder, using reference dimension. Findings recommend a design motorcycle eye height of 1,350 mm (5th percentile), headlight height of 800 mm (5th percentile), and taillight height of 625 mm (5th percentile). A motorcyclist height of 1,525 mm (10th percentile) is recommended for the design of sight distance. Recommended heights reduce the cost of motorcycle lane construction with demonstrated safety compared with the current criteria.

Motorcyclists are particularly vulnerable to injury in crashes with heavy vehicles due to substantial differences in vehicle mass, the degree of protection and speed. There is a considerable difference in height between motorcycles and trucks; motorcycles are viewed by truck drivers from downward angles, and shorter distances between them mean steeper downward angles. Hence, we anticipated that the effects of motorcycle conspicuity treatments would be different for truck drivers. Therefore, this study aims to evaluate the effects of motorcycle conspicuity treatments on the identification and detection of motorcycles by truck drivers. Two complementary experiments were performed; the first experiment assessed the impact of motorcycle sensory conspicuity on the ability of un-alerted truck drivers to detect motorcycles, and the second experiment assessed the motorcycle cognitive conspicuity to alerted truck drivers. The sensory conspicuity was measured in terms of motorcycle detection rates by un-alerted truck drivers when they were not anticipating a motorcycle within a realistic driving scene, while the cognitive conspicuity was determined by the time taken by alerted truck drivers to actively search for a motorcycle. In the first experiment, the participants were presented with 10 pictures and were instructed to report the kinds of vehicles that were presented in the pictures. Each picture was shown to the participants for 600ms. In the second experiment, the participants were presented with the same set of pictures and were instructed to respond by clicking the right button on a mouse as soon as they detected a motorcycle in the picture. The results indicate that the motorcycle detection rate increases, and the response time to search for a motorcycle decreases, as the distance between the targeted motorcycle and the viewer decreases. This is true regardless of the type of conspicuity treatment used. The use of daytime running headlights (DRH) was found to increase the detection rate and the identification of a motorcycle by a truck driver at a farther distance, but effect deteriorates as the distance decreases. The results show that the detection rate and the identification of a motorcyclist wearing a black helmet with a reflective sticker increases as the distance between the motorcycle and the truck decreases. We also found that a motorcyclist wearing a white helmet and a white outfit is more identifiable and detectable at both shorter and longer distances. In conclusion, although this study provides evidence that the use of appropriate conspicuity treatments enhances motorcycle conspicuity to truck drivers, we suggest that more attention should be paid to the effect of background environment on motorcycle conspicuity.Copyright © 2016. Published by Elsevier Ltd. Language: en

The purpose of this study was to determine the baseline motorcycle riders' perception-response times (PRTs) in an expected object braking task and to determine the significant difference between PRTs of older and younger riders.Fifty-nine participants sat on their motorcycles in exactly the same way as they would when riding and then they awaited activation of the taillights of the passenger car (parked) in front of them. PRTs of the motorcyclists were transcribed from the camcorder when the riders hit the brakes as quickly as possible following the activation of the car's brake lights.Results of PRT were calculated by taking the average of both male and female older and younger riders. The study demonstrates that the mean and standard deviation of the motorcycle baseline PRTs are 0.44 and 0.11 s, respectively. Riders' age and gender were not found to be significant variables for PRT.The mean of baseline perception-reaction time of motorcycle riders is smaller than that of passenger car drivers. If traffic facilities are designed based on passenger car drivers' simple perception-reaction times where drivers are generally more alert (for example, in traffic signal design), they can provide the required PRT for motorcyclists. This suggests that the utilization of more powerful brake lights on motorcycles could be highly effective for preventing rear-end motorcycle collisions.

Traffic congestion is a perennial problem at seasonal tourist destinations throughout the world. Meanwhile, understanding the mode choices of tourist's traveler will help to identify effective solutions. This analysis contributes to that effort by characterizing the mode preferences of tourists under parking and cordon polices in central business district (CBD) of Mashhad city. With respect to the research methodology, this research employs econometric model, discrete choice model. Using a stated preference survey of visitors, the results presented that travel time, parking fare, cordon cost, education levels and vehicle price type are characteristics in Mashhad city that determine tourist's modal choice and influence the modal shift from congestion pricing in central business area. In addition, the finding shows that congestion pricing has more effective response than the parking strategy.

Aim: To evaluate the sensitivity and specificity of noncontrast helical computerized tomography (CT) in ureteric colic with comparative evaluation of KUB and ultrasonography (USG). Setting: Tertiary care university hospital. Materials and Methods: One hundred patients aged between 20 and 75 years referred from the emergency department as acute ureteric colic were evaluated with KUB and USG followed by noncontrast helical CT. Results: Noncontrast helical CT was 91% sensitive and 98% specific in detecting urolithiasis compared to a sensitivity of 20% and 30% for KUB and USG and specificity of 94% and 98% respectively. Conclusion: Noncontrast helical CT is a very sensitive and specific investigation for evaluation of acute flank pain due to urolithiasis, besides helping in the detection of nonrenal causes of pain.

Background The effectiveness of trauma services provided by three hospitals operating at different levels of care, district general (DGH), tertiary care, and central tertiary, were compared in Malaysia. Methods Cases were recruited prospectively for 1 month. Outcome measures included death or, among survivors, disability at discharge. Results Leading causes of injuries were road traffic (72%), falls (9%), industrial (6%), and assaults (5%). Fifty-nine percent of cases were direct admissions and 41% were interhospital transfers. Of the 286 direct admissions, 12% arrived by ambulance and the remainder mostly by private car. For direct admissions, logistic regression identified an increased odds of dying associated with admission to DGH (compared with central tertiary) (odds ratio [OR], 9.8; 95% confidence interval [CI], 1.3-73.7), severe injuries (Injury Severity Score > 15) (OR, 33.1; 95% CI, 7.5-146.7), and older age (> or = 55 years) (OR, 10.8; 95% CI, 2.0-56.8). Disability at discharge was associated with being severely injured (OR, 6.4; 95% CI, 2.4-17.1). Conclusion In this study in Malaysia, admission to DGH, older age, and severe injuries are associated with increased odds of fatality.