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Trucking is an important production link in most open-pit mines, and its transportation cost accounts for more than 50% of the total production cost of open-pit mines. The quality of the driver's driving behavior plays a crucial role in the fine control of the production cost of transportation. Different from the previous evaluation studies of drivers' driving behavior in open-pit mines, which mainly took safety driving behavior index as a factor variable, this paper puts forward a comprehensive evaluation method of driving behavior of mining truck drivers, which takes both safety driving and transportation cost as factor variables. Taking the mining truck as the research object, firstly, a scientific and reasonable data collection scheme is established, and the data information characterizing the transport state of the mining truck is obtained through data collection and analysis. Secondly, the RKNN algorithm of time series prediction and the wavelet analysis method are used to achieve noise reduction and missing processing of the original data so as to obtain accurate sample data. Then, taking the principal component analysis method as the entry point, through constructing the principal component analysis theory model, the key index system representing safe driving behavior and transportation cost is established to realize the comprehensive evaluation of the driving behavior of mining truck drivers, and the evaluation system of "standard driving", "prudent driving" and "aggressive driving" of mining truck drivers is formulated. The results show that after noise reduction, the accuracy of mining car operation data can be improved by 7~12%, and the transportation cost can be reduced by about 5% after the driver's operation behavior is standardized. [ABSTRACT FROM AUTHOR]

Roundabout crashes are common worldwide but have received little attention. In particular, the investigation remains relatively understudied in distinct collision modes of roundabout crashes, including angle and non-angle crashes. This study investigates differences in factors affecting injury severity between angle and non-angle crashes and how these differences change over time. Random parameter logit models with heterogeneity in mean and variance were estimated using 2012–2019 Florida crash data. Variables considered for the modeling include temporal characteristics, environmental characteristics, road characteristics, spatial characteristics, vehicle characteristics, crash characteristics, and human characteristics. In addition, likelihood ratio tests were used to investigate the temporal instabilities of the models and differences in collision modes. The results showed that only a few variables demonstrated temporally stable effects for angle collisions (weekend and dark-lighted) and non-angle collisions (paved shoulders and cyclists), respectively. Unique influencing factors of injury severity were identified for different collision modes, such as dark-lighted, straight alignment, merge, lane departure, the disabled driver for angle collisions, and clear, fog, commercial vehicles, and aggressive driving for non-angle collisions. The results of the out-of-sample prediction simulations further demonstrate the difference in injury severity over time for angle and non-angle collisions. Overall results suggest that countermeasures can be implemented to reduce the injury severity of angle crashes/non-angle crashes based on the significant variables identified. This study may be used to improve roundabout safety by considering different collision modes. [ABSTRACT FROM AUTHOR]

Obesity and type 2 diabetes are chronic metabolic diseases that impact tens to hundreds of millions of adults, especially in developed countries. Each condition is associated with an elevated risk of breast cancer and with a poor prognosis after treatment. The mechanisms connecting poor metabolic health to breast cancer are numerous and include hyperinsulinemia, inflammation, excess nutrient availability, and adipose tissue dysfunction. Here, we focus on adipose tissue, highlighting important roles for both adipocytes and fibroblasts in breast cancer progression. One potentially important mediator of adipose tissue effects on breast cancer is the fibroblast growth factor receptor (FGFR) signaling network. Among the many roles of FGFR signaling, we postulate that key mechanisms driving aggressive breast cancer include epithelial-tomesenchymal transition and cellular metabolic reprogramming. We also pose existing questions that may help better understand breast cancer biology in people with obesity, type 2 diabetes, and poor metabolic health. [ABSTRACT FROM AUTHOR]

• Driving style correlated positively with traffic violations and crashes retrospectively and prospectively. • Higher scores on risky and angry driving styles were associated with more crashes in the following 12 months. • The predictive validity of bus drivers' driving styles on crash involvement is confirmed. The Multidimensional Driving Style Inventory (MDSI, Taubman-Ben-Ari et al., 2004) is a widely used instrument that assesses private car drivers' driving styles. However, a key validity check for the MDSI is whether the measurement of driving style is associated with drivers' crash liability. A one-year follow-up study was conducted, and one thousand bus drivers were randomly recruited from three cities (Hangzhou, Beijing and Bazhong) in China. The participants were asked to complete the Chinese version of the MDSI and a demographic questionnaire, and they needed to report their traffic violation history 12 months after the survey. Violation history data only included traffic violations and crashes that were caused by the study participants rather than other road users. A confirmatory factor analysis (CFA) was conducted to assess the factorial structure of the MDSI. The relationships between the MDSI and traffic violation history over the previous 12 months and driving patterns over the 12 months immediately following the survey were investigated. CFA results show that the model fitness of the MDSI for bus drivers is acceptable. Both drivers' traffic violations and crashes over the previous 12 months and driving patterns over the following 12 months were positively correlated with dissociative, risky and angry styles and negatively correlated with a careful style. Cluster analysis results show three clusters, with one unsafe driver group characterized by higher scores on dissociative, anxious, risky and angry styles and lower scores on careful driving styles. The number of drivers with traffic violations or crashes in the unsafe cluster is significantly higher than those in the other two clusters. More importantly, drivers in the unsafe cluster experience more traffic violations and crashes over the following 12 months than the other two driver clusters. The findings of the present study not only provide a reliable and valid instrument for assessing bus drivers' driving styles but also show valid evidence for the predictive validity of the MDSI in measuring bus drivers' crash involvement. [ABSTRACT FROM AUTHOR]

Coastal is the coupling of socio-economic and fragile ecosystems area existing development and protection problems, with lots of reserve land resources (i.e., bottomland and tidal flats). Analyzing and predicting the carbon storage changes caused by land use/land cover (LULC) on the Jiangsu coast were critical for revealing the potential problems of land surface changes and sustainable development. Then, we utilized the single dynamic degree and transfer in/out contribution, exploring the characteristics of LULC change in the study area from 1980 to 2018. Using the InVEST model, PLUS-LEAS model, and PLUS-Markov chain module, we assessed the spatiotemporal of the study area at the county level to reveal the LULC change strategy and driving factor contribution, as well as the composition of LULC and carbon storage in 2036. The results show that the LULC structure in the study area significantly changed from 1980 to 2018, in which the tidal flat and high coverage grassland decreased by 552.84 km2 and 383.71 km2 while the reservoir ponds and urban residential land increased by 1210.69 km2 and 101.70 km2. The major driving factor of LULC change has shifted from a single-factor to multi-factor coupling, and the influence contribution of human activity increased by 6.73%, especially the population. The carbon storage of study areas showed a significant decrease trend during 1980–2010, followed by a slight increase during 2010–2018. High-density carbon storage was mainly distributed in Lianyungang and Nantong and presented a decreasing trend along the coastline extending inland. The dry land and reservoir ponds are the main composition of LULC types in 2036, and the carbon storage increased to 2.39 × 108 t. In addition, more than decades of LULC change will cover part or all of the land use change process and trends, especially high-covered grasslands, so we suggest a 10-year LULC change to analyze coastal areas with lots of tidal flats and bottomlands. Therefore, this study can provide reference and theoretical guidance for ecologically sustainable development and future LULC evolution in coastal cities. [ABSTRACT FROM AUTHOR]

A 30 portable emission measurement system (PEMS) test was conducted in this study to examine the effect of driving modes (aggressive and normal) and road type (urban and rural) on tailpipe emissions. Driving modes were assessed using relative positive acceleration and velocity × positive acceleration factors. The findings revealed that aggressive and normal driving modes differed significantly on urban and rural roads, as evident from paired sample t-test (p < 0.05). Furthermore, aggressive driving exhibited more prominent speed and acceleration on rural roads, while normal driving modes showed consistent acceleration or speed patterns regardless of road conditions as observed from kernel density estimation and box plot analysis. Emission rates (CO, CO2, HC, and NOx) significantly varied between aggressive and normal driving modes on urban and rural roads, as indicated by paired sample t-test analysis (p < 0.05). Aggressive driving increased CO2, CO, and HC emission rates for acceleration and deceleration modes by 18% to 40% compared to normal driving. Aggressive driving modes increased the emission factors (CO, HC, and CO2) by 5% to 25% compared to the normal driving mode on both urban and rural roads. Moreover, the NOx emission factors were also found significant during normal driving conditions on urban roads. This study provides real-world emission factors of diesel cars considering the impact of route, vehicle familiarity, and driving behavior induced by varying traffic conditions, which will contribute to improve the current emissions inventory on both a local and global level. [ABSTRACT FROM AUTHOR]

Traffic congestion can lead to negative driving emotions, significantly increasing the likelihood of traffic accidents. Reducing negative driving emotions as a means to mitigate speeding, reckless overtaking, and aggressive driving behaviors is a viable approach. Among the potential methods, affective speech has been considered one of the most promising. However, research on humor-based affective speech interventions in the context of driving negative emotions is scarce, and the utilization of electroencephalogram (EEG) signals for emotion detection in humorous audio studies remains largely unexplored. Therefore, our study first designed a highly realistic experiment scenario to induce negative emotions experienced by drivers in congested traffic conditions. Subsequently, we collected drivers' EEG signals and subjective questionnaire ratings during the driving process. By employing one-way analysis of variance (ANOVA) and t tests, we analyzed the data to validate the success of our experiment in inducing negative emotions in drivers during congested road conditions and to assess the effectiveness of humorous audio in regulating drivers' negative emotions. The results indicated that humorous audio effectively alleviated drivers' negative emotions in congested road conditions, with a 145.84% increase in arousal and a 93.55% increase in valence ratings compared to control conditions. However, it should be noted that humorous audio only restored drivers' emotions to the level experienced during normal driving. Our findings offer novel insights into regulating drivers' negative emotions during congested road conditions. [ABSTRACT FROM AUTHOR]

Road traffic accidents are found to be the leading cause of death worldwide. In India, Road traffic injuries claim nearly 1.3 lakh lives annually, and aggressive driving is found to be one of the leading causes of motor vehicle accidents. Despite its importance, only a few studies have investigated this area in India. Aggressive driving has been widely studied through driving anger and driving anger expression. Studies outside the context of driving have demonstrated that forgiveness and empathy are significantly associated with reducing anger and aggressive behaviors. The present study examines the role of forgiveness, empathy, and driving anger on driving anger expression, along with examining their gender differences. A total of 310 participants (187 males, 123 females) between the ages 20-35 completed self-report measures of driving anger, driving anger expression, forgiveness, and empathy. Mann-Whitney U results showed significant gender differences in all four variables. Spearman correlations indicated a significant negative association of forgiveness and empathy with driving anger and anger expression. Step-wise regression revealed that cognitive empathy, driving anger, and specific dimensions of forgiveness (forgiveness of self or situations) predicted maladaptive driving anger expression, and only driving anger predicted adaptive expression of anger. The current study enhances the understanding of the role of forgiveness and empathy in aggressive driving and opens up the possibility of developing interventions to reduce aggressive driving. [ABSTRACT FROM AUTHOR]

Prostate cancer (CaP) remains the second leading cause of cancer-related mortality in American men. Systemic treatments for metastatic CaP, which causes the majority of deaths, include androgen deprivation therapy and chemotherapy. These treatments induce remissions but do not cure CaP. Novel and functionally diverse therapeutic targets that control the cell biology that drives aggressive CaP progression are needed to overcome treatment resistance. Because signal transduction that mediates CaP cell behavior is tightly regulated by phosphorylation, kinases have attracted interest as alternative targets for CaP treatments. Here, we examine emerging evidence from recent NextGen sequencing and (phospho) proteomics analyses on clinical CaP specimens that were obtained during lethal disease progression to determine the role of deregulated kinase action in CaP growth, treatment resistance, and recurrence. We provide an overview of kinases that are impacted by gene amplification, gene deletion or somatic mutations during the progression from localized treatment-naïve CaP to metastatic castration-resistant CaP or neuroendocrine CaP, and the potential impact of such alterations on aggressive CaP behavior and treatment efficacy. Furthermore, we review knowledge on alterations in the phosphoproteome that occur during the progression to treatment-resistant CaP, the molecular mechanisms in the control of these changes, and the signal transduction associated with them. Finally, we discuss kinase inhibitors under evaluation in CaP clinical trials and the potential, challenges, and limitations to moving knowledge on the CaP kinome forward to new therapeutic strategies. [ABSTRACT FROM AUTHOR]

Insurance Telematics is a recent service that is offered to drivers where a sensing platform measures vehicle’s dynamics with the ultimate goal of inferring the level of risk that the driver experiences on the road. For this to happen, a robust set of sensors must be deployed within the vehicle and effective algorithms to process and classify driving patterns must be employed. As feasible as it looks, however, insurance telematics poses a great challenge when sensors offer information that is redundant or even show a low signal/noise ratio. The question here, then, is how to identify what sensing information is really useful and discard that one that only adds overhead. In this study we proposed an algorithmic approach, called minimal Gated Multimodal Unit (mGMU) that learns to filter out the proper amount of data from different input sources, making it an appealing choice for data fusion scenarios. We evaluate mGMU on three public multi modal (multiple sensor) datasets, created to classify driving styles, that comprise 3, 3 and 8 sensor sources. After a very extensive experimental setup that comprised around 30 different pipelines (made of feature extractors, information fusion approaches and a classification layer), results show that configurations based on mGMU obtain the best performance (with an increase of 2% with respect the second best approach and even outperforming the use of AutoEncoders by 5%). Moreover, as a proof of concept we deployed mGMU on three commercial smartphones, thus showing its efficiency given the number of parameters and FLOPS that were dramatically reduced. Given these results, we expect mGMU to be of great use on resource-constrained edge computing devices and rich sensor scenarios where data from different data sources must be exploited.

Background & Aims: Nowadays, traffic accidents are one of the major causes of death worldwide. Therefore, it is essential to determine the modifiable risk factors in order to reduce traffic accidents. This study aimed to investigate the relationship between the psychological factors, the spiritual health, and the drivers' behavior of the employees of Shahid Beheshti University of Medical Sciences. Materials & Methods: This cross-sectional study examined the data on 3245 participants in the Health Cohort Study of Shahid Beheshti University of Medical Sciences. The required information was collected using general health questionnaire (GHQ-28), Manchester driving behavior questionnaire (MDBQ), spiritual health questionnaire (SHEL), aggression questionnaire (AGQ), and Beck's anxiety and depression questionnaires. The data were analyzed with the help of structural equation modeling using SPSS 25 and Amos 24 software. Results: The study used the information on 1386 people. Moreover, 754 of these people were men. All of the correction indices highlighted the good fit of the hypothesized model (CMIN/DF=3.3, GFI=0.96, AGFI=0.94, CFI=0.97, TLI=0.97, IFI=0.97, NFI=0.95, SRMR=0.03, RMSEA=0.04). According to the model, aggression (β=0.45, p

Introduction: Traffic accidents are a leading cause of death globally, with substantial economic impact particularly in low-and-middle-income countries (LMIC). Adolescents are at particular risk, partly due to their tendency to engage in risky driving. However, most research designed to identify potential causes of risky adolescent driving has been conducted in Western, high-income countries, which often have substantial cultural differences from LMIC that potentially influence risky adolescent driving. Methods: The present study, one of the first focused on this topic in Southeast Asia, cross-sectionally assessed 425 adolescent motorbike drivers in the Southeast Asian LMIC Cambodia. Adolescents' (a) beliefs about peers' driving (social norms) and (b) driving risk perception were assessed as predictors of four risky driving behaviors: aggressive driving; distracted driving; intoxicated driving; violating driving laws. Results: Canonical correlation analysis identified a general relation between (a) beliefs about peers' driving, and (b) all four risky driving behaviors, with R² = 0.35 indicating over one-third of the variance in risky driving was explained by perceptions of peers' driving. Risk perception was not involved in the significant canonical relation, however. Gender moderated two of the underlying relations, with females showing larger relations between perceptions of friends' driving, and distracted driving and violating driving laws. Discussion: These findings provide useful directions for future research (e.g., assessing the accuracy of Cambodian adolescents' perceptions of peers' driving) useful for helping stakeholders tailor road safety programs (e.g., providing adolescent drivers with accurate information regarding their peers' actual driving behaviors) for adolescent motorcyclists in Cambodia and similar countries. [ABSTRACT FROM AUTHOR]

• The Italian adaptation of the DAX appears to be a reliable and valid instrument to assess individual differences in driving anger expression, supporting the four original factors. • The DAX subscales were associated with measures of trait anger and aggressive driving. • Young drivers reported expressing more aggression while driving. • The DAX factors were associated with crashes and crash-related conditions (i.e., fines). • The associations between the different forms of driving anger expression, aggressive driving, and crash involvement remained significant when controlling for socially desirable responding. This study examined the factor structure and the psychometric properties of the Driving Anger Expression Inventory (DAX) in a large sample of Italian drivers. After removing several items and allowing six error pairs to correlate, Confirmatory Factor Analysis (n = 1007) supported a four-factor solution that broadly confirmed the four original factors, and this was confirmed in a second group (N = 1047) of drivers. The three aggressive factors (physical aggressive expression, use of a vehicle and verbal aggressive expression) were positively related, while the adaptive/constructive subscale was negatively related to measures of trait anger and aggressive driving. In addition, younger drivers reported engaging in the aggressive forms of expression more frequently, while older drivers reported more frequently engaging in the adaptive/constructive form of expression. Finally, those who had crashed in the past three years reported more frequently engaging in the three aggressive forms of expression, while those that had not crashed reported more frequently engaging in the adaptive/constructive form of expression. Although the DAX factors showed moderate correlations with social desirability, the associations between the different forms of driving anger expression, aggressive driving and crash involvement remained significant when controlling for socially desirable responding. [ABSTRACT FROM AUTHOR]

The paper aims to examine the interdependent relationship between the usage of the seatbelt restraint system and severities of the driver-injury in single-vehicle crashes. This paper developed a comprehensive joint econometric structure − a joint random parameters binary probit-binary probit model − that allows for the simultaneous examination of injury severity of the driver in a crash, and taking into account the fact that seat belt use can be endogenous to the outcomes of driver injury. The developed model is tested using data on drivers-injury severities involved in single-vehicle crashes in Thailand from 2012-2017. In terms of the interdependent relationship between seatbelt use status and driver-injury severities, the findings suggest that drivers who do not use seat belts may demonstrate more dangerous or aggressive driving behaviors (such as speeding), subsequently increasing their likelihood of involvement in severe or fatal crashes. Additionally, the result also shows that drivers who are involved in speeding-related crashes are less likely to wear a seatbelt and have a higher risk of sustaining severe and fatal injuries. The findings also reveal that in crashes, drivers who are young, or operating trucks are less likely to be wearing their seat belts. The study also indicates that severe and fatal crashes are associated with factors such as elderly drivers, alcohol involvement, unbelted drivers, fatigue, depressed medians, and barrier medians. Conversely, a crash in a U-turn area, driving a passenger car, pickup truck, or large truck, or colliding with a guardrail reduces the likelihood of severe and fatal injuries. Neglecting the hidden endogenous effect in statistical analyses could result in an overestimation of the impact of seat belt usage on crash-injury outcomes. The findings of this study can provide valuable insights for relevant authorities aiming to improve driver safety. [ABSTRACT FROM AUTHOR]

A new microscopic traffic model is proposed that characterizes driver response according to reaction and sensitivity. Driver response in the intelligent driver (ID) model is based on a fixed acceleration exponent and so does not follow traffic physics. This inadequate characterization results in unrealistic traffic behavior. With the proposed model, drivers can be aggressive, sluggish, or typical. It is shown to be string stable, and for appropriate distance headway and velocity (speed), the traffic flow is smooth. Furthermore, the proposed model has better stability than the ID model because it is based on driver reaction and sensitivity, while the ID model is based on a fixed exponent. The ID and proposed models are evaluated on a circular road of length 1200 m with a platoon of 21 vehicles for 150 s. The results obtained show that the proposed model characterizes traffic more realistically than the ID model. [ABSTRACT FROM AUTHOR]

For those who cannot afford vehicles, motorcycles are a common mode of transportation in Pakistan. Although many motorcycle riders also drive vehicles, they continue to engage in dangerous behaviors such as speeding, weaving through traffic, and disobeying traffic laws, which can result in accidents. The purpose of this study was to investigate the relationship between prior motorcycle-riding experience, dangerous driving behaviors, and traffic accidents. A total of 623 drivers in Pakistan participated in a study in which questions on their demographics, involvement in accidents, and dangerous driving practices were posed. Two statistical models were employed to analyze the data and ascertain how motorcycle-riding experience affected dangerous driving behaviors and accidents. Drivers with past motorcycle-riding experience were found to be more likely to exhibit aggressive and risky driving behaviors, as validated by principal component analysis. Certain demographic characteristics were also linked to dangerous driving behaviors, and prior motorcycle experience was identified as a crucial factor in anticipating traffic collisions. The probability of a traffic accident increased by 67% for each unit rise in motorcycle-riding experience. To lower the incidence of accidents, the study suggests that the government and road safety regulatory authorities impose strict rules and regulations for motorcycle riders. [ABSTRACT FROM AUTHOR]

Driving behavior analysis has become crucial for traffic safety. In addition, more abundant driving data are needed to analyze driving behavior more comprehensively and thus improve traffic safety. This paper proposes an approach to image data extraction and driving behavior analysis that uses geographic information and driving data. Information derived from geographic and global positioning systems was used for image data extraction. In addition, we used an onboard diagnostic II and a controller area network bus logger to record driving data for driving behavior analysis. Driving behavior was analyzed using sparse automatic encoders and data exploration to detect abnormal and aggressive behavior. A regression analysis was performed to derive the relationship between aggressive driving behavior and road facilities. The results indicated that lane ratios, no lane markings, and straight lane markings are important features that affect aggressive driving behaviors. Several traffic improvements were proposed for specific intersections and roads to make drivers and pedestrians safer. [ABSTRACT FROM AUTHOR]

Purpose: This interdisciplinary study explores attitudes toward health-related misbehaviors from a criminological point of view by comparing attitudes toward COVID-19 misbehaviors to the attitudes toward reckless behaviors related to driving and Human Immunodeficiency Virus (HIV) patients’ sexual behavior and identifying the predictors of attitudes toward COVID-19 misbehaviors. Methods: An online factorial survey included 679 respondents aged 18–89  years. The participants read various scenarios related to the violation of COVID-19 restrictions, reckless sexual behavior among HIV patients, and reckless driving. The participants evaluated the seriousness of each behavior and the appropriate severity of the punishment in each scenario. Within the scenarios about COVID-19 misbehaviors, we manipulated such variables as the type of COVID-19 misbehavior and violators’ gender, ethnicity, and religiosity. Additionally, participants answered questions about their demographic characteristics, vaccination, fear of COVID-19, and perceived contribution of COVID-19 misbehaviors to COVID-19-related morbidity. Results: The results indicated that participants perceived COVID-19 misbehaviors as less serious (Mean = 8.11, S.D. = 2.49) and deserving a less severe punishment (Mean = 7.57, S.D. = 2.59) than reckless driving (Mean = 9.36, S.D. = 1.25; Mean = 9.09, S.D. = 1.30; respectively). Additionally, the key factor predicting public opinion regarding COVID-19-related misbehaviors was the perceived contribution of these misbehaviors to virus-related morbidity. The perceived contribution to morbidity explained 52% of the variance in the seriousness of misbehavior and 53% of the severity of appropriate punishment. Conclusions: The findings suggest that it is critical to advocate for and reinforce the public’s understanding of the association between the increase in morbidity and the violation of restrictions preventing the transmission of viruses. Our findings also support the notion that the definitions of “crime” and “deviance” are not inherent or intrinsic but are created by the social context. [ABSTRACT FROM AUTHOR]

The epidemiology of invasive fungal infections (IFIs) is currently changing, driven by aggressive immunosuppressive therapy, leading to an expanded spectrum of patients at risk of IFIs. Aspergillosis is a leading cause of IFIs, which usually affects immunocompromised patients. There are a limited number of antifungal medications available for treating IFIs, and their effectiveness is often hindered by rising resistance rates and practical limitations. Consequently, new antifungals, especially those with novel mechanisms of action, are increasingly required. This study assessed the activity of four novel antifungal agents with different mechanisms of activity, namely, manogepix, rezafungin, ibrexafungerp, and olorofim, against 100 isolates of Aspergillus section Terrei, containing amphotericin-B (AmB)-wildtype/non-wildtype and azole-susceptible/-resistant strains, according to the European Committee on Antimicrobial Susceptibility Testing (EUCAST) method. In general, all tested agents showed potent and consistent activity against the tested isolates, exhibiting geometric mean (GM) and minimum effective concentration (MEC)/minimum inhibitory concentration (MIC) ranges, respectively, as follows: manogepix (0.048 mg/L, 0.032–0.5 mg/L), rezafungin (0.020 mg/L, 0.016–0.5 mg/L), ibrexafungerp (0.071 mg/L, 0.032–2 mg/L), and olorofim (0.008 mg/L, 0.008–0.032 mg/L). In terms of MIC90/MEC90, olorofim had the lowest values (0.008 mg/L), followed by rezafungin (0.032 mg/L), manogepix (0.125 mg/L), and ibrexafungerp (0.25 mg/L). All the antifungals tested demonstrated promising in vitro activity against Aspergillus section Terrei, including A. terreus as well as azole-resistant and AmB-non-wildtype cryptic species. [ABSTRACT FROM AUTHOR]

Analyzing road risks and developing targeted countermeasures are essential for a safe and orderly traffic flow. However, previous intersection safety analyses were conducted based on crash data. Little research has been conducted on surrogate safety measures based on risky driving behavior. In this study, categorical boosting (CatBoost) and Shapley additive explanation (SHAP) were used to analyze the impact of features on traffic order using a set of multisource data that include roadway geometry, signal control, and land use. The traffic data for intersection entrances in Beijing were collected from navigation systems, field investigations, and application programming interfaces. The model results showed that CatBoost exhibits a prediction accuracy of 83.5%, a recall of 83.5%, and an F1 score of 81.1%. Moreover, the importance, total effects, main effects, and interaction effects of influence factors were analyzed by using SHAP. It was found that the congestion index (CI) has significant negative effects on traffic order. A larger number of lanes and more electronic traffic control were found to have a positive effect on traffic order. Intersection entrances with three-phase signals or off-peak intersection entrances helped increase traffic order. Moreover, a high green ratio for through vehicles can reduce the positive impact of CI on traffic order when the value of CI is 1.1–1.4, and the signal control scheme with a high left-turn green ratio would result in a safe and orderly traffic flow. The results from this study can be used for further studies on improving traffic safety at signalized intersections. [ABSTRACT FROM AUTHOR]

In this work, an in-vehicle deep learning-based driver assistance system is proposed to monitor driver behavior to reduce the risk of road traffic accidents. A two-layer gated recurrent stacked long short-term memory (LSTM) network is implemented to detect and classify driver behaviors such as normal, aggressive and drowsy driving. The methodology to develop the proposed model is based on a many-to-one architecture, where two LSTM layers (LSTM and Bi-LSTM) and two gated recurrent units (GRUs) are stacked with 32 hidden cells in each layer and one fully connected output layer. Python and the Keras-TensorFlow libraries are used to build various deep-learning models. A publicly available benchmark smartphone dataset, the UAH-DriveSet dataset, is used to evaluate the performance of the proposed model, which achieves good estimation with a driver behavior classification accuracy of 92%. The performance comparison showed superiority over state-of-the-art techniques when the cascaded deep-learning architecture was evaluated and validated in a simulation environment. This model can be used with an in-vehicle dashboard-mounted smartphone that is set to monitor driving behavior and alert the driver to maintain normal driving. [ABSTRACT FROM AUTHOR]

• Dutch drivers behave less aggressively and committed fewer violations. • Iranian drivers were more inclined to commit risky behaviors such as speeding or illegal overtaking. • Iranian drivers were more prone to breaking traffic laws across a range of situations. • The SEM results indicated a higher probability of crashes for those committing more violations. • Drivers who made more driving errors were more likely to be involved in crashes. Introduction : The rates of road traffic injuries and fatalities in developing countries are significantly higher than in developed countries. This study examines the differences in driving behavior, road safety attitudes, and driving habits between a developed country (the Netherlands) and a developing country (Iran), which bear major differences in terms of crash involvement per population. Method : In this context, this study assesses the statistical association of crash involvement with errors, lapses, aggressive driving incidents, and non-compliance with traffic rules, attitudes, and habits. Structural equation modeling was used to evaluate data obtained from 1,440 questionnaires (720 samples for each group). Results : The results revealed that more insecure attitudes toward traffic-regulation observance, negative driving habits, and risky behaviors, such as traffic rule violations act as influential factors of crash involvement. Iranian participants showed a greater likelihood to get involved in violations and driving habits with a higher level of risk. In addition, lower levels of safety attitudes toward traffic-regulation observance were observed. On the other hand, Dutch drivers were more likely to report lapses and errors. Dutch drivers also reported safer behavior in terms of unwillingness to engage in risky behaviors such as violations (speeding and no-overtaking). The structural equation models for crash involvement based on behaviors, attitudes, and driving habits were also evaluated for their accuracy and statistical fit using relevant indicators. Practical Applications : Finally, the findings of the present study point out the need for extensive research in some areas to foster policies that can effectively enhance safer driving. [ABSTRACT FROM AUTHOR]

Aims: Large cell calcifying Sertoli cell tumour (LCCSCT) is a type of testicular sex cord‐stromal tumour that may occur sporadically or in the context of Carney complex and other genetic syndromes. A subset is clinically malignant, and the molecular mechanisms that drive such aggressive behaviour remain unknown. Methods and results: We analysed 21 samples from 20 patients with LCCSCT (12 non‐metastasising and eight metastasising) using PRKAR1A immunohistochemistry (IHC) and next‐generation sequencing. All tumours except two (cases 17 and 20, both metastasising) demonstrated loss of PRKAR1A expression. Among 11 cases with interpretable sequencing results, all harboured pathogenic single nucleotide variants of PRKAR1A. Evidence of loss of heterozygosity (LOH) of PRKAR1A was present in all tumours with interpretable zygosity data, but the mechanisms of LOH were different for non‐metastasising and metastasising tumours. Non‐metastasising tumours demonstrated only copy‐neutral LOH, while metastasising tumours demonstrated a spectrum of mechanisms of LOH, including copy‐loss LOH, two concurrent mutations or copy‐neutral LOH. Relevant molecular findings in non‐metastasising LCCSCT were limited to PRKAR1A variants. In contrast, all metastasising LCCSCTs with interpretable data harboured additional pathogenic variants, including (but not restricted to) BRCA2 mutations with evidence of LOH and bi‐allelic CDKN2A/B deletions. Three patients harboured PRKAR1A variants of inferred germline origin, including one with Carney complex and two without known syndromic features. Conclusions: This study further confirms that PRKAR1A IHC is a useful diagnostic tool for both non‐metastasising and metastasising tumours and suggests that molecular analyses can be helpful to identify non‐metastasising tumours with malignant potential in selected patients. Importantly, these results highlight that germline assessment could be beneficial for all patients presenting with LCCSCT. [ABSTRACT FROM AUTHOR]

Aggressive driving has emerged as one of the most studied behaviors in the traffic safety field, due to its association with the odds of motor vehicle crashes and especially fatal crashes. Previous research has investigated the situations which provoke anger while driving, as well as the emotional (anger) and behavioral (aggression) aspects of aggressive driving. However, surprisingly the cognitive aspects of aggressive driving have largely been neglected. This study investigated the psychometric properties of the short-forms of the Driver's Angry Thoughts Questionnaire (DATQ) and the Driving Anger Expression Inventory (DAX) in a sample of professional drivers. Furthermore, the study aimed to investigate the mediation effects of aggressive thoughts, as the cognitive aspect of aggressive driving, on the relationship between traffic congestion and driving aggression. To this end, 613 public transport bus drivers completed the DATQ and DAX and were also asked to report the level of traffic congestion they normally faced in their daily driving, using six pictures. Confirmatory factor analysis (CFA) supported the four factor DAX and the five factor DATQ, which largely replicated the original factors. The four forms of maladaptive thoughts on the road were positively associated with aggressive driving, while the positive factor (coping self-instruction) was negatively associated with aggressive driving and traffic violations. Moreover, the results indicated that traffic congestion does not contribute directly to anger expression on the road, but rather through aggressive thoughts. This study suggests that cognitive interventions may help to eliminate aggressive driving and its adverse outcomes on traffic safety.

Riskful and aggressive driving are significant problems in road transportation. Numerous studies prove drivers' behavior is critical in most road accidents and contributes significantly to fuel consumption and emissions. In an attempt to improve road safety, it is important to be able to detect such unskilful and irresponsible drivers on a mass scale. Thus an automated onboard driving safety assessment system is required. Transmitting amounts of telemetric data required to assess driving style is unpractical and economically unjustified, thus some data processing must take place in an Onboard Unit (OBU). As a first step in driving safety assessment is detecting maneuvers, this is the task, that can be done in the OBU. In this paper, we propose a Finite State Machine based algorithm, which could run on OBU and allows marking of basic maneuvers in the telemetry datastream. This allows the calculation of additional features, aggregation, and transmission of data useful for classification the of driving safety, and thus a vast reduction in data volume sent over the air. Also, an example of detecting unsafe maneuver using such aggregated data is given. [ABSTRACT FROM AUTHOR]

Because of heavy traffic on urban expressways, the exits of expressway interchanges have become accident-prone sites. This study explores the impacts of various traffic control devices and road conditions on road safety at interchange exits based on driving behavior data from navigation software. The traffic order index (TOI) based on driving behavior and speed variation is used to evaluate road safety. The general safety characteristics and partitioned safety characteristics of interchange exit sections for different traffic control devices and under different road conditions were described, and a structural equation model (SEM) was constructed to observe the influences of the traffic control devices, road conditions, congestion degree, and time on road safety. The results show that traffic control devices (the number of warning signs, number of advance exit signs and complexity of diagrammatic guide signs) and road conditions (the number of lanes and merging conflicts within 500 m) have significant influences on the road safety of interchange exits. Road conditions have the greatest impact on the safety of interchange exits, followed by the congestion index, traffic control devices, and time. The results could help traffic management departments reconstruct or rehabilitate traffic control devices and enable reasonable road planning at interchange exits. The safety evaluation method for traffic control devices and road conditions based on driving behavior data collected from navigation software could be further used on other roads. [ABSTRACT FROM AUTHOR]

Clear cell renal cell carcinoma (ccRCC) incidence has been rising in recent years, with strong association between differential microRNA (miRNA) expression and neoplastic progression. Specifically, overexpression of miR-155-5p has been associated with promoting aggressive cancer in ccRCC and other cancers. In this study, we further investigate the role of this miRNA and one of its protein targets, Jade-1, to better understand the mechanism behind aggressive forms of ccRCC. Jade-1, a tumor suppressor, is stabilized by Von-Hippel Lindau (VHL), which is frequently mutated in ccRCC. Experiments featuring downregulation of miR-155-5p in two ccRCC cell lines (786-O and Caki-1) attenuated their oncogenic potential and led to increased levels of Jade-1. Conversely, knockdown experiments with an anti-Jade-1 shRNA in 786-O and Caki-1 cells showed increased metastatic potential through elevated proliferation, migration, and invasion rates. In a mouse xenograft model, downregulation of miR-155 decreased the rate of tumor implantation and proliferation. Direct interaction between miR-155-5p and Jade-1 was confirmed through a 3′UTR luciferase reporter assay. These findings further elucidate the mechanism of action of miR-155-5p in driving an aggressive phenotype in ccRCC through its role in regulating Jade-1. [ABSTRACT FROM AUTHOR]

• Drivers' acceptance of and interaction with FAVs were investigated. • Three models were developed for positive, disregardful and aggressive interactions. • Drivers' characteristics are associated with their interaction tendency with FAVs. • The current driving behaviour on roads reflects future interactions with FAVs. • Drivers' acceptance and trust of FAVs influence their behavioural responses. Automated vehicles have started to be integrated into the road transportation system and operate in a mixed traffic environment. To ensure a smooth and successful integration, it is vital to have a good understanding of the human factor challenges involved in the process, especially the issues related to other road users who will share roads with automated vehicles. The study focuses on conventional vehicle drivers' acceptance of and interaction with fully automated vehicles (FAV). An online survey with experimental scenarios showing an FAV's lane-changing intention was designed to test the interaction responses of participants. The survey also collected the participants' demographic information (e.g., age, gender, driving experience), self-reported general driving behaviours (e.g., errors, lapses and violations), past benchmark behaviour in the same situation and their acceptance of FAVs. The study recruited 838 participants in total, comprising 465 participants from Australia (216 males vs. 249 females) and 373 participants from China (172 males vs. 201 females). Ordered probit models were developed to predict three types of behavioural responses of drivers in the lane-changing scenario, i.e., positive, disregardful and aggressive responses. The results showed that older drivers, females, and drivers who had less driving experience were more likely to adopt positive interactions with FAVs than their counterparts. Drivers who reported frequent risky driving behaviours (e.g., aggressions, lapses and errors) were less likely to report positive interaction but more likely to report disregardful and aggressive interactions. Drivers reporting more positive/favourable attitudes and a higher trust toward FAVs demonstrated a higher possibility of positive interaction, and those with higher perceived behaviour control were more likely to restrain disregardful interaction. The study helps to form a greater understanding of conventional vehicle drivers' perception of FAVs and the underlying factors that may influence their interaction behavioural tendency. [ABSTRACT FROM AUTHOR]

• Aggressive behaviour on the road was compared with aggression in intimate relationships. • Convergence in maladaptive ways of expressing anger was observed. • There was no convergence in the adaptive way of expressing anger. • Aggression in both contexts was highly correlated. • Situational specificity should be considered when aggression is assessed. Aggressive behaviour is a common response in different contexts all around the world. General aggression theories, such as the frustration-aggression theory, try to explain this behaviour in any context. However, situational specificity could play a relevant role in this issue, so proneness to behave aggressively may depend more on the context than on a general root or personality trait. With the aim of shedding light in this field, the current research aimed to analyse the relationship between aggressive behaviour on the road and intimate relationships. A sample composed of 275 participants who had a driving license and lived with an intimate partner completed a set of self-reports regarding aggressive behaviour in both contexts. The results suggested a convergence in the way of expressing anger, except in the case of adaptive aggression. A SEM-based approach indicated that the measured aggressive variables fitted better in two highly correlated factors rather than a single one, suggesting the relevance of the situational specificity in the prediction of aggressive behaviour in both contexts. Practical implications regarding evaluation and intervention for aggression reduction are discussed, as well as the limitations of the current research. [ABSTRACT FROM AUTHOR]

Virtual testing requires hazardous scenarios to effectively test autonomous vehicles (AVs). Existing studies have obtained rarer events by sampling methods in a fixed scenario space. In reality, heterogeneous drivers behave differently when facing the same situation. To generate more realistic and efficient scenarios, we propose a two-stage heterogeneous driver model to change the number of dangerous scenarios in the scenario space. We trained the driver model using the HighD dataset, and generated scenarios through simulation. Simulations were conducted in 20 experimental groups with heterogeneous driver models and 5 control groups with the original driver model. The results show that, by adjusting the number and position of aggressive drivers, the percentage of dangerous scenarios was significantly higher compared to that of models not accounting for driver heterogeneity. To further verify the effectiveness of our method, we evaluated two driving strategies: car-following and cut-in scenarios. The results verify the effectiveness of our approach. Cumulatively, the results indicate that our approach could accelerate the testing of AVs. [ABSTRACT FROM AUTHOR]

Previous research on personality in the driving context mostly focused on the negative and maladaptive personality traits. The present study investigated the links between the Light Triad traits with driving style and driving anger expression. The Light Triad framework emphasizes the positive side of the personality and it consists of humanism, faith in humanity, and Kantianism. A total of 376 active drivers (50.3 % women) aged between 18 and 70 completed the online questionnaire including the Light Triad Scale (Kaufman et al., 2019), Driver Behavior Questionnaire (DBQ; Reason et al., 1990), and Driving Anger Expression Inventory (DAX, Deffenbacher et al., 2002). Ordinary violations, aggressive violations, and positive driver behaviors subscales of the DBQ were used to measure driving style, and the DAX was used to measure the aggressive and adaptive/constructive forms of driving anger expression. Hierarchical multiple regression analyses were conducted to examine the associations of the Light Triad traits with each driving style and driving anger expression dimension after controlling for age, gender, and total mileage. The findings generally supported the expected associations. That is, some traits of the Light Triad yielded negative associations with aberrant driver behaviors and aggressive forms of driving anger. On the other hand, the opposite pattern was found in the analyses with positive driver behaviors and adaptive/constructive expression of driving anger. The findings are discussed in the light of relevant literature. [ABSTRACT FROM AUTHOR]

Aggressive driving behaviors have been gaining in notoriety in recent years, with US drivers identifying aggressive driving as a serious problem. Researchers have called for understanding the contextual factors that contribute to drivers engaging in such behaviors. If individuals engage in aggressive driving behaviors during their work-to-home commutes, it is possible that some aspects of work may be associated with these behaviors. The present study examined the influence of employee's experienced workplace incivility on aggressive driving behaviors, as well as the mechanisms and conditional factors that might shed light on the nature of this relationship through the lens, and extension, of affective events theory. Data were collected via a baseline survey and daily diaries administered over the course of one working week (five days), from employees (N = 109) who worked full-time and commuted by private vehicle alone on a daily basis. Results indicate that on days when employees experience incivility at work, they engage in aggressive driving behaviors during their work-to-home commutes, through the negative emotions they experience during their commute. Perceived psychological contract violation during the commute was found to exacerbate this relationship. Overall, the present findings suggest that spillover effects due to experiencing workplace incivility have the potential to impact behaviors elicited during the commute, raising the risk of detrimental consequences for both the employee and employer. Practical implications and future lines of research are discussed. [ABSTRACT FROM AUTHOR]

• Explores how driving anger expression (DAX) can explain traffic locus of control (T-LOC) and crash involvement. • Males, younger drivers, and those with<10 years of driving experience reported more aggressive anger expression. • External T-LOC was significantly higher in middle-aged drivers and those with 11–20 years of driving experience. • Drivers with adaptive anger expression orientation were less likely to report a high level of external T-LOC. • The use of the vehicle to express anger increased the probability of external T-LOC and crash involvement. Since driving anger expression and its adverse consequences is an issue that has not been resolved over the last years or even has increased among Iranian drivers over time, this study aimed to evaluate the driving anger expression (DAX) and its impacts on the traffic locus of control (T-LOC) and crash involvement among drivers in Tehran, Iran. By collecting data from 1035 participants, exploratory factor analysis identified significant constructs of DAX including "Adaptive, "Verbal anger expression", "Use of the vehicle to express anger", and "Personal physical anger expression" and T-LOC including "Self", "Other drivers", "Vehicle/environment", and "Fate/luck". A two-phase approach of K-means clustering and a logistic regression model was then used to evaluate the effects of driving anger expression on T-LOC and crash involvement. The results revealed that while males and younger drivers reported more aggressive orientation in driving anger situations, females, older drivers, and those with higher driving experience significantly showed a higher level of adaptive orientation in driving anger situations. The logistic regression models showed that external T-LOC (believing that other people and factors are responsible for an accident, not themselves) was significantly higher in middle-aged drivers and those with 11–20 years of driving experience. Also, drivers with adaptive anger expression were less likely to report a high level of external T-LOC. On the other hand, the use of the vehicle to express anger increased the probability of external T-LOC. According to the results, using the vehicle to express anger can significantly increase the probability of crash involvement among drivers. [ABSTRACT FROM AUTHOR]

• Self-compiled DARQ has good reliability and validity. • The correctness of right-of-way attitude have significant gender, age and driving experience effects. • The drivers' right-of-way attitudes could screen the professional and non-professional drivers. • The drivers' right-of-way attitudes could screen the professional drivers with and without accidents. • Drivers' right-of-way attitudes could predict prosocial and aggressive driving behavior. This study explored differences in the right-of-way attitudes of different drivers and the utility of right-of-way attitudes for predicting drivers' driving behaviors through the development of the Drivers' Attitudes of Right-of-way Questionnaire (DARQ). DARQ is a tool to judge the negative attitudes of drivers of the right-of-way and hence assist in the selection of excellent professional drivers. Moreover, the study defined drivers' attitudes of the right-of-way and determines the psychological components of such attitudes. A total of 614 drivers participated in the study. After two tests, the DARQ was established, consisting of assessments of three dimensions: cognition, behavioral tendency, and emotion. We assessed Cronbach's alpha, split-half reliability, and structural and criterion validity of the questionnaire; the DARQ had a sound theoretical construction and good reliability and validity. Results revealed that professional drivers and professional drivers without accidents had higher correctness of right-of-way attitudes. This shows that the questionnaire had good criterion validity and could be used to effectively screen professional drivers, especially those without accidents. The results also revealed differences in the correctness of drivers' right-of-way attitudes according to gender, age, and driving experience (cognition and behavioral tendency). Male drivers, older drivers, and experienced drivers had more correct cognitions and behavioral tendencies than did female drivers, young drivers, and novice drivers. Finally, we conducted a third test with 214 drivers. The results revealed that the correctness of drivers' right-of-way attitudes predicted prosocial and aggressive driving behavior. The higher the correctness of drivers' right-of-way attitudes (cognition and behavioral tendency), the higher the level of prosocial driving behavior, and the lower the level of aggressive driving behavior. The more positive drivers' emotions regarding right-of-way attitudes, the higher the level of prosocial driving behavior and the lower level of aggressive driving behavior. The study helps advance the measurement of right-of-way attitudes and automatic driving research. For example, this provides reference data and a model of human traffic participants' right-of-way attitudes that could help inform research on automatic driving. Moreover, the results of this study could provide guidance for the screening and training of professional drivers, especially professional drivers without accidents, to reduce the rate of traffic accidents. [ABSTRACT FROM AUTHOR]

Traffic waves, known also as stop-and-go waves or phantom jams, appear naturally as traffic instabilities, also in confined environments as a ring-road. A multi-population traffic is studied on a ring-road, comprised of drivers with stable and unstable behavior. There exists a critical penetration rate of stable vehicles above which the system is stable, and under which the system is unstable. In the latter case, stop-and-go waves appear, provided enough cars are on the road. The critical penetration rate is explicitly computable, and, in reasonable situations, a small minority of aggressive drivers is enough to destabilize an otherwise very stable flow. This is a source of instability that a single population model would not be able to explain. Also, the multi-population system can be stable below the critical penetration rate if the number of cars is sufficiently small. Instability emerges as the number of cars increases, even if the traffic density remains the same (i.e., number of cars and road size increase similarly). This shows that small experiments could lead to deducing imprecise stability conditions. [ABSTRACT FROM AUTHOR]

The article intends to explore the pathways from youth radicalization into violent extremism in the post-war context of Sri Lanka based on the qualitative evidence collected from four provinces in 2018. Our results show that lack of opportunities, fragmented social and ethnic identity, complex identity formation, corruption, low quality of governance, marginality in economic and political spheres, ethnoreligious politics, and securitization of state appear to be key potential driving factors that are more likely to propel radicalization and violent extremism in the post-war scenario. The article finds the causal mechanism among the potential push factors and how each of these drivers are interconnected and influence one another negatively. Based on the evidence, we argue that no single pathway implicates radicalization into violent extremism –various forms of vulnerabilities, including individual, group, and socio-economic and political, are more likely to increase the propensity to radicalization. It informs that post-war Sri Lanka's youth radicalization into violent extremism is multifaceted, contextually driven, and constantly evolving and exist in a complex reality. In deeply divided societies, collective crisis plays a critical role in radicalization, suggesting that policy measures considering violence prevention must pay attention to address community grievances and marginalization. [ABSTRACT FROM AUTHOR]

Aggressive driving is of increasing concern in modern society. This study investigated the potential for the presence of an ambient aroma to reduce aggressive responses in a simulated driving situation. Previous literature has demonstrated the beneficial effect of peppermint (Mentha piperita) aroma on driver alertness and we aimed to identify any impact on aggressive driver behaviour. Fifty volunteers were randomly assigned to one of two conditions (peppermint essential oil aroma and no aroma). Aggressive driving behaviours were measured in a virtual reality driving simulator. The analysis indicated that the peppermint aroma significantly reduced aggressive driving behaviours. The presence of the aroma also produced medium sized effects on some aspects of mood from pre‐test levels. These results provide support for the use of ambient aromas for the modification of driving behaviours. It is proposed that applying peppermint into daily driving may be a beneficial for reducing driver aggression. [ABSTRACT FROM AUTHOR]

The fatal or incapacitating injury caused by overturn crashes involving sport utility vehicles (SUVs) is irreparable. The purpose of this study is to identify potential factors that affect the injury severity of overturn crashes involving SUVs and develop adequate preventive strategies. Given the unobserved heterogeneity existing in the data set, crash data in North Carolina from Highway Safety Information System (HSIS) is analyzed and separated by Latent Class Clustering into six relatively homogeneous groups. To further explore the heterogeneity, random parameter logit models are developed for each cluster, and the impacts of significant factors are estimated with marginal effects. The results reveal the heterogeneity across the clusters and the homogeneity within the same cluster. Variables (including females, people over fifty years old, improper or aggressive behavior, rural areas, high-speed limit, curved roadway, rolling and mountainous terrain, adverse weather, and poor light conditions) are associated with the injury severity of the overturn crashes involving SUVs. The findings of this study can further provide decision makers with insightful countermeasures to improve transportation safety and mitigate the injuries of overturn crashes involving SUVs. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to examine the links between primary psychopathic traits and driving behavior on the one hand, and driving anger expression on the other hand, through the specific contribution of empathy, impulsiveness, and sensation seeking, in a sample of French driving offenders. Methods: One thousand six hundred and eighty‐six driving offenders completed a paper‐and‐pencil questionnaire during 110 drivers' rehabilitation programs. Results: Primary psychopathic traits were positively associated with violations and aggressive driving anger expression, and negatively associated with prosocial driving behaviors. These associations were partially mediated by empathy, impulsiveness, and sensation seeking. In addition, the negative relation between primary psychopathic traits and adaptive anger expression was fully mediated by these three personal dispositions. Conclusion: Low empathy, high impulsiveness and sensation seeking are important characteristics of driving offenders with high psychopathic traits. Our results provide a better understanding of French driving offenders' risky behaviors and the role of primary psychopathic traits. [ABSTRACT FROM AUTHOR]

Virtual reality (VR)-based rehabilitation is a growing technological field, which gradually becomes integrated into existing programs. However, technology has to support human behavior and -needs, including social relatedness, to achieve health-related outcomes. Elderly people have high risk of loneliness, and VR has technological affinity for natural social interaction. Previous studies have relied on competitiveness rather than collaborative elements, but research shows that competitiveness can lead to (feelings of) stress and aggressive behavior in some individuals. This article presents a mixed methods study to gather end-user feedback on a social VR scenario that encourages inter-player collaboration on a virtual tandem bike. Outpatients ( n = 11 , 64% males, 60 ± 11 years) were invited to participate with a co-player (friend or family). Participants biked on average 10.7 (± 3) minutes with a mean speed of 14.8 kmph (± 5.8). The results indicate potential and feasibility for the collaborative social biking application. Participants reported excellent usability-scores (85 ± 5), high intrinsic motivation in all categories: enjoyment (6.5 ± 0.5), effort/importance (6.4 ± 0.3), relatedness (6.3 ± 0.7) and minimal increase in symptoms of nausea, oculomotor and disorientation. Furthermore, participants found the social aspect enjoyable, agreed that collaboration eased tasks and that they lost track of exercise duration. Interpersonal interaction between participants varied, but was mostly positively rated valence, even if the sense of copresence was limited by physical constraints and avatar representation. Most participants expressed that they would use the program again, but future studies should explore how to improve location and appearance of the virtual coactor, as well as implement additional tasks. [ABSTRACT FROM AUTHOR]

Persistent androgen receptor (AR) signalling is the main driver of prostate cancer (PCa). Truncated isoforms of the AR called androgen receptor variants (AR-Vs) lacking the ligand binding domain often emerge during treatment resistance against AR pathway inhibitors such as Enzalutamide. This review discusses how AR-Vs drive a more aggressive form of PCa through the regulation of some of their target genes involved in oncogenic pathways, enabling disease progression. There is a pressing need for the development of a new generation of AR inhibitors which can repress the activity of both the full-length AR and AR-Vs, for which the knowledge of differentially expressed target genes will allow evaluation of inhibition efficacy. This review provides a detailed account of the most common variant, AR-V7, the AR-V7 regulated genes which have been experimentally validated, endeavours to understand their relevance in aggressive AR-V driven PCa and discusses the utility of the downstream protein products as potential drug targets for PCa treatment. [ABSTRACT FROM AUTHOR]

This study quantifies the spatio-temporal distribution of electric buses' (EBs) electricity consumption characteristics and identifies the most electricity-saving operations from both instantaneous movements and driving conditions considering road types and bus routes. First, the real-world EB operating data collected from four EBs are divided into segments. Factors that influence the value of two energy consumption indexes (electricity consumption rate, ECR, and electricity consumption factor, ECF) are assessed. The study finds that an increasing average speed of a bus leads to a lower value of ECF, suggesting a less aggressive and a more efficient driving style. Further, ECFs are clustered into four states (very low/low/medium/high) to identify the energy-saving situation. The result shows that the most energy-saving speed ranges for expressways, arterial roads, and local roads during peak hours are 45–50 km/h, 35-40 km/h and 25-30 km/h, respectively. Findings from this study can be applied for eco-driving suggestions to drivers in order to improve the efficiency of EB operation system. [ABSTRACT FROM AUTHOR]

Li-ion battery is emerging as a promising alternative to fossil fuel-driven Internal Combustion Engine(ICE). The significant challenge of Li-ion batteries is maintaining the temperature for proper functioning and long life. A novel curved inverted-L grooved channel cold plate design is proposed in the present work that uses an anti-freeze based alumina nanofluid to cool Li-ion battery packs effectively. The proposed design is compared with a reference design and serpentine channel pattern in a mini-channel cooling plate and systematically evaluated for thermal performance by varying parameters such as the number of channels, channel width, and coolant type. The equivalent circuit model is used to imitate the behavior of batteries. The best thermal performance is achieved with five 6 mm wide channels engraved on the aluminum cold plate by circulating 1 % Al 2 O 3 in 20:80 ethylene glycol-water nanofluid as the coolant. This optimized configuration is then tested in the 1P6S battery pack subjected to static (constant 5C-rate) and dynamic (aggressive drive cycle) loading conditions. At the 5C-rate, the proposed cooling system drastically reduces the maximum temperature of the battery pack from 341.4 K to 300.7 K at the end of discharge. Under aggressive driving conditions, the proposed system restricts the maximum temperature to less than 298.5 K. [ABSTRACT FROM AUTHOR]

Road rage is a social phenomenon that involves risks for drivers and has an impact on road safty. Aggressive driving is one of the major causes of road accidents hence, it is important to investigate the factors that may promote both, identifying and avoiding aggressive driving and road rage behaviors. This study presents empirical evidence for conceptualizing road rage by exploring the relation between aggressive driving behaviors and drivers’ anxiety while driving. Responses from drivers who were observed driving their cars indicated an association between state-trait anxiety and aggressive driving style. Hostile aggressive behaviours were related to higher levels of state-trait anxiety and problem-focused coping style was more common among drivers with instrumental aggression than those with hostile aggression. These findings contribute to our understanding of the interplay between drivers’ coping styles and road rage, highlighting problem-focused coping as a strategy that can reduce hostile aggressive driving. Hence, this research has implications for promoting road safety and the prevention of traffic accidents.

With the popularization of autonomous vehicle (AV) technology, mixed traffic flows that consist of AVs and human-driven vehicles (HDVs) will appear in the real world. Although many studies of the features of mixed traffic flow have been carefully evaluated, few studies have focused on the effect of aggressive driving performance on mixed traffic flow. This study aims to develop an approach to evaluate the effects of aggressive driving on the stability and capacity performance under the conditions of AV and HDV mixed traffic flow. First, since a car-following model can describe the relationship between vehicles, we calibrate a car-following model for aggressive driving and nonaggressive driving behaviors based on real traffic data and previous research results. Then, in a mixed traffic flow environment, a basic linear stability formula and capacity calculation expression are developed that consider the effects of vehicle order on the capacity. Finally, because the proportion of aggressive driving and aggressive driving parameters may change, nine combinations of three aggressive driving proportions and three driving parameter cases are used for the sensitivity analysis. The results indicate that the effect of aggressive driving on mixed traffic flow is complex. When the proportion of aggressive driving is less than 35%, the increase in the proportion of aggressive driving increases the traffic capacity and reduces the unstable part. However, when the proportion of aggressive driving is greater than 35%, the increase in the proportion of aggressive driving increases the unstable part. When the penetration rate of AVs exceeds 0.490, mixed traffic flow remains stable at all aggressive driving proportions. In addition, the capacity of a mixed traffic flow may be improved as the penetration rate of AVs increases. To a certain extent, these conclusions provide a theoretical basis for formulating different management modes of AVs and HDVs. [ABSTRACT FROM AUTHOR]

Aggressive driving behavior is one of the main reasons for traffic crashes in China. However, how cognitive interventions affect impulsive driving behavior is still unknown. In this study, a simulated drive was constructed to evaluate the influence of different cognitive interventions. In addition to speeding behavior in limit zones, speed when passing pedestrians, at intersections, and on the whole drive was adopted as a measure to evaluate aggressive driving behaviors. Forty-eight young drivers were recruited with monetary rewards. Compared to the control group, the penalty feedback intervention significantly reduced the mean speed in the 40 km/h zone, the 80 km/h zone, and when passing pedestrians. The combined feedback intervention significantly reduced the distance ratio of speeding in the 40 km/h and 80 km/h zones, as well as the mean speed at the intersection and on the whole drive. However, the interaction effects between the driving task and intervention method were not remarkably observed during aggressive driving behaviors. The findings from this study provide evidence that different cognitive interventions contribute distinctively to improving aggressive driving behaviors. These conclusive results have possible implications for the design of vehicle warning systems and traffic safety interventions. [ABSTRACT FROM AUTHOR]