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Article ; Online: Burns from hair dye in recovered COVID-19 patients, a new presentation for further investigation.

Abdelaty, Mohamed

Burns : journal of the International Society for Burn Injuries

2021 Volume 48, Issue 2, Page(s) 481–482

MeSH term(s)	Burns/therapy ; Burns, Chemical ; COVID-19 ; Hair Dyes/adverse effects ; Humans
Chemical Substances	Hair Dyes
Language	English
Publishing date	2021-11-10
Publishing country	Netherlands
Document type	Letter
ZDB-ID	197308-3
ISSN	1879-1409 ; 0305-4179
ISSN (online)	1879-1409
ISSN	0305-4179
DOI	10.1016/j.burns.2021.10.013
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Article ; Online: Short-term Safety Performance Functions by Random Parameters Negative Binomial-Lindley model for Part-time Shoulder Use.

Hasan, Tarek / Abdel-Aty, Mohamed

Accident; analysis and prevention

2024 Volume 199, Page(s) 107498

Abstract: Part-time Shoulder Use (PTSU) is a traffic management and operation strategy that allows the use of the left or right shoulder as a travel lane, typically during the peak hours of the day. Though PTSU is an effective strategy for increasing roadway ... ...

Abstract	Part-time Shoulder Use (PTSU) is a traffic management and operation strategy that allows the use of the left or right shoulder as a travel lane, typically during the peak hours of the day. Though PTSU is an effective strategy for increasing roadway capacity in congested traffic conditions, there is very limited quantitative information about PTSU design elements and operational strategy in the existing literature, which could impact the occurrence of crashes on freeways. This study contributes to the safety literature by analyzing various potential crash contributing factors related to PTSU operation and design elements through the development of short-term Safety Performance Functions (SPFs). A comparison of the estimated models demonstrated that by utilizing the mixed distribution and allowing the posterior parameter estimates of explanatory variables to vary from one observation to another, the Random Parameters Negative Binomial-Lindley (RPNB-L) model outperformed the traditional NB and fixed coefficient NB-L models. The results of the proposed RPNB-L model indicated that the PTSU implemented sections experienced a lower number of traffic crashes compared to the non-PTSU freeway sections. Among the attributes related to PTSU operation and design elements, the usage of the leftmost shoulder lane as PTSU, the presence of emergency rest areas for damaged vehicles, and adequate shoulder width would significantly reduce crash frequency for the PTSU implemented freeways. Moreover, investigation of the identified hotspots revealed that the transition areas (start/end locations of PTSU) are the most critical sections. The findings from this research could assist transportation agencies to take appropriate countermeasures for preventing and reducing crash occurrences on PTSU implemented freeways.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Safety ; Environment Design ; Shoulder ; Models, Statistical
Language	English
Publishing date	2024-02-14
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2024.107498
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Article ; Online: Exploring the influence of drivers' visual surroundings on speeding behavior.

Abdel-Aty, Mohamed / Ugan, Jorge / Islam, Zubayer

Accident; analysis and prevention

2024 Volume 198, Page(s) 107479

Abstract: Despite awareness campaigns and legal consequences, speeding is a significant cause of road accidents and fatalities globally. To combat this issue, understanding the impact of a driver's visual surroundings is crucial in designing roadways that ... ...

Abstract	Despite awareness campaigns and legal consequences, speeding is a significant cause of road accidents and fatalities globally. To combat this issue, understanding the impact of a driver's visual surroundings is crucial in designing roadways that discourage speeding. This study investigates the influence of visual surroundings on drivers in 15 US cities using 3,407,253 driver view images from Lytx, covering 4,264 miles of roadways. By segmenting and analyzing these images along with vehicle-related variables, the study examines factors affecting speeding behavior. After filtering the images, to ensure an accurate representation of the driver's view, 1,340,035 driver view images were used for analysis. Statistical models, including hurdle beta and bivariate probit models with random driver effects as well as Machine Learning's eXtreme Gradient Boosting (XGBoost), were employed to estimate speeding behavior. The results indicate that factors within the driver's visual environment, weather conditions, and driver heterogeneity significantly impact speeding. Speeding behavior also varies across geographic locations, even within the same city, suggesting a connection between local context and speeding. The study highlights the importance of the driver's environment, showing that more open spaces encourage speeding, while areas with trees and buildings are associated with reduced speeding. Notably, this research differs from previous studies by utilizing real-time data from dash cameras, providing a dynamic and accurate representation of the driver's visual surroundings. This approach enhances the reliability of the findings and empowers transportation engineers and planners to make informed decisions when designing roadways and implementing interventions to address effectively excessive speeding. In addition to examining speeding behavior, the study also analyzes time-headway, a key factor affecting safety and risky driver behavior, to explore its relationship with speeding. The findings offer valuable insights into the factors influencing speeding and the driver's visual environment. These insights can inform efforts to create environments that discourage speeding (and close car following) and ultimately reduce severe accidents caused by excessive speed (and tailgating).
MeSH term(s)	Humans ; Automobile Driving ; Accidents, Traffic/prevention & control ; Reproducibility of Results ; Risk-Taking ; Cities
Language	English
Publishing date	2024-01-20
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2024.107479
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Article ; Online: Insights into vehicle conflicts based on traffic flow dynamics.

Ding, Shengxuan / Abdel-Aty, Mohamed / Wang, Zijin / Wang, Dongdong

Scientific reports

2024 Volume 14, Issue 1, Page(s) 1536

Abstract: The utilization of traffic conflict indicators is crucial for assessing traffic safety, especially when the crash data is unavailable. To identify traffic conflicts based on traffic flow characteristics across various traffic states, we propose a ... ...

Abstract	The utilization of traffic conflict indicators is crucial for assessing traffic safety, especially when the crash data is unavailable. To identify traffic conflicts based on traffic flow characteristics across various traffic states, we propose a framework that utilizes unsupervised learning to automatically establish surrogate safety measures (SSM) thresholds. Different traffic states and corresponding transitions are identified with the three-phase traffic theory using high-resolution trajectory data. Meanwhile, the SSMs are mapped to the corresponding traffic states from the perspectives of time, space, and deceleration. Three models, including k-means, GMM, and Mclust, are investigated and compared to optimize the identification of traffic conflicts. It is observed that Mclust outperforms the others based on the evaluation metrics. According to the results, there is a variation in the distribution of traffic conflicts among different traffic states, wide moving jam (phase J) has the highest conflict risk, followed by synchronous flow (phase S), and free flow (phase F). Meanwhile, the thresholds of traffic conflicts cannot be fully represented by the same value through different traffic states. It reveals that the heterogeneity of thresholds is exhibited across traffic state transitions, which justifies the necessity of dynamic thresholds for traffic conflict analysis.
Language	English
Publishing date	2024-01-17
Publishing country	England
Document type	Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-50017-3
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Article ; Online: Real-time crash prediction on express managed lanes of Interstate highway with anomaly detection learning.

Yang, Samgyu / Abdel-Aty, Mohamed / Islam, Zubayer / Wang, Dongdong

Accident; analysis and prevention

2024 Volume 201, Page(s) 107568

Abstract: To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a need ... ...

Abstract	To facilitate efficient transportation, I-4 Express is constructed separately from general use lanes in metropolitan area to improve mobility and reduce congestion. As this new infrastructure would undoubtedly change the traffic network, there is a need for more understanding of its potential safety impact. Unfortunately, many advanced real-time crash prediction models encounter an important challenge in their applicability due to their demand for a substantial volume of data for direct modeling. To tackle this challenge, we proposed a simple yet effective approach - anomaly detection learning, which formulates model as an anomaly detection problem, solves it through normality feature recognition, and predicts crashes by identifying deviations from the normal state. The proposed approach demonstrates significant improvement in the Area Under the Curve (AUC), sensitivity, and False Alarm Rate (FAR). When juxtaposed with the prevalent direct classification paradigm, our proposed anomaly detection learning (ADL) consistently outperforms in AUC (with an increase of up to 45%), sensitivity (experiencing up to a 45% increase), and FAR (reducing by up to 0.53). The most performance gain is attained through the combination of Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) in an ensemble, resulting in a 0.78 AUC, 0.79 sensitivity, and a 0.22 false alarm rate. Furthermore, we analyzed model features with a game-theoretic approach illustrating the most correlated features for accurate prediction, revealing the attention of advanced convolution neural networks to occupancy features. This provided crucial insights into improving crash precaution, the findings from which not only benefit private stakeholders but also extend a promising opportunity for governmental intervention on the express lane. This work could promote express lane with more efficient resource allocation, real-time traffic management optimization, and high-risk area prioritization.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Accidents, Traffic/statistics & numerical data ; Neural Networks, Computer ; Automobile Driving ; Environment Design ; Area Under Curve ; Machine Learning
Language	English
Publishing date	2024-04-05
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2024.107568
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Article ; Online: Multi-vehicle safety functions for freeway weaving segments using lane-level traffic data.

Rim, Heesub / Abdel-Aty, Mohamed / Mahmoud, Nada

Accident; analysis and prevention

2023 Volume 188, Page(s) 107113

Abstract: This study develops Safety Performance Functions (SPFs) for freeway weaving segments. Due to the coexistence of three different movements including through, merging, and divering traffic, the probability of crashes in weaving segments is higher compared ... ...

Abstract	This study develops Safety Performance Functions (SPFs) for freeway weaving segments. Due to the coexistence of three different movements including through, merging, and divering traffic, the probability of crashes in weaving segments is higher compared to other segment types. Further, the traffic flow in this section is the most unstable. Hence, to analyze detailed traffic conditions, this study utilized lane-level traffic data. The SPFs were developed using the Poisson Lognormal (PLN) regression model technique. The results showed that different traffic parameters were significant based on the types of crashes. For the rear-end crashes model, more general traffic conditions of the weaving segment were found to be significantly associated with the crash frequency such as the natural logarithm of average speed of through lanes. Nevertheless, for the sideswipe and angle crashes models, the traffic variables which are directly related to the weaving movements were selected as significant factors such as the off-ramp volume ratio, and standard deviation of speed of the rightmost lane. The results presented in this study can be meaningful in that they can serve as a basis for the weaving segments related safety evaluation studies. In addition, the developed models' results can be a great source to establish operational strategies to improve traffic safety on freeway weaving segments.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Regression Analysis ; Probability ; Safety
Language	English
Publishing date	2023-05-12
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2023.107113
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Article ; Online: The impact of target speed on pedestrian, bike, and speeding crash frequencies.

Mahmoud, Nada / Abdel-Aty, Mohamed / Abdelraouf, Amr

Accident; analysis and prevention

2023 Volume 192, Page(s) 107263

Abstract: This research aims to investigate the influence of adopting the target speed concept on different types of crashes including pedestrian, bike, and speeding-related crashes. The Target speed is the highest speed that vehicles should operate on a roadway ... ...

Abstract	This research aims to investigate the influence of adopting the target speed concept on different types of crashes including pedestrian, bike, and speeding-related crashes. The Target speed is the highest speed that vehicles should operate on a roadway segment in a specific context. Based on the reviewed literature, this is the first study to investigate the relationship between target speed and crash frequency. Hence, big data including probe-vehicle data, traffic characteristics, geometric features, and land use attributes were utilized to develop crash prediction models. The main contributions of this research are to quantify the impacts of target speed on traffic safety considering context categories and to conclude the potential recommendations to lower different types of crashes. The 85th percentile speed was calculated and utilized in the developed models. Three crash prediction models were developed for pedestrian, bike, and speeding-related crashes. They were used in the analysis to quantify the impact of adopting target speed on different crash types. The results showed a significant reduction in the three crash types when using the target speed. Most of the improvements took place in three context categories: C3C: Suburban Commercial Segments, C3R: Suburban Residential Segments, and C4: Urban General Segments. Hence, this research recommends adopting target speed specifically in urban and suburban areas. Further, it suggests considering some measures to lower vulnerable road users' and speeding-related crashes. Following the recommendations of this research would help to reduce different types of crash frequency, hence, improving the mobility and safety for all users in different context classifications.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Automobile Driving ; Safety ; Bicycling ; Pedestrians
Language	English
Publishing date	2023-08-11
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2023.107263
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Article ; Online: A comparative clinico-dermoscopic study of intralesional injection of combined digoxin and furosemide, Candida antigen, and vitamin D3 for multiple warts.

Nasr, Mohamed / Abdelaty, Sara / Elkholy, Basma M

Journal of cosmetic dermatology

2023 Volume 22, Issue 4, Page(s) 1344–1353

Abstract: Background: Immunostimulatory and antiproliferative therapies have been widely used for the treatment of multiple warts. Recently, anti-HPV activity of ionic contra viral therapy (ICVT) which is comprised of combined digoxin and furosemide has been ... ...

Abstract	Background: Immunostimulatory and antiproliferative therapies have been widely used for the treatment of multiple warts. Recently, anti-HPV activity of ionic contra viral therapy (ICVT) which is comprised of combined digoxin and furosemide has been demonstrated. Aim: To evaluate and compare the effectiveness and safety of intralesional injection of Candida antigen, vitamin D3, and combined digoxin and furosemide in the treatment of multiple warts. Patients and methods: Seventy-five patients with numerous warts were randomly assigned to one of three equal groups: Candida antigen, vitamin D3, or a combination of digoxin and furosemide. In the Candida antigen group, injections into the biggest wart were done. In the vitamin D3 and combined digoxin/furosemide groups, the agent was injected into each wart with a maximum of five injected warts. Injections were repeated every 2 weeks until clearance or for a total of five sessions. Results: There was a statistically significant difference in the overall therapeutic response among the studied groups in favor of the intralesional Candida antigen group (60%), followed by the vitamin D3 group (48%) and the ionic contraviral therapy group (28%) (p = 0.02). However, the difference between both Candida antigen and vitamin D groups was not significant (p = 0.59). Conclusions: Intralesional Candida antigen immunotherapy and vitamin D3 antiproliferative therapy are significantly more effective than ICVT. Limitations: Short follow-up period and relatively small sample size.
MeSH term(s)	Humans ; Cholecalciferol ; Furosemide/therapeutic use ; Injections, Intralesional ; Digoxin/therapeutic use ; Warts/drug therapy ; Antigens, Fungal ; Candida ; Treatment Outcome
Chemical Substances	Cholecalciferol (1C6V77QF41) ; Furosemide (7LXU5N7ZO5) ; Digoxin (73K4184T59) ; Antigens, Fungal
Language	English
Publishing date	2023-01-06
Publishing country	England
Document type	Randomized Controlled Trial ; Journal Article
ZDB-ID	2280551-5
ISSN	1473-2165 ; 1473-2130
ISSN (online)	1473-2165
ISSN	1473-2130
DOI	10.1111/jocd.15581
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Article ; Online: Effectiveness of bicycle helmets and injury prevention: a systematic review of meta-analyses.

Büth, Carlson Moses / Barbour, Natalia / Abdel-Aty, Mohamed

Scientific reports

2023 Volume 13, Issue 1, Page(s) 8540

Abstract: To mitigate the risk of injuries, many countries recommend bicycle helmets. The current paper seeks to examine the effectiveness of bicycle helmets by performing a systematic review focusing on meta-analyses. First, the current paper explores the ... ...

Abstract	To mitigate the risk of injuries, many countries recommend bicycle helmets. The current paper seeks to examine the effectiveness of bicycle helmets by performing a systematic review focusing on meta-analyses. First, the current paper explores the findings of studies that employ meta-analyses using bicycle crash data. Second, the results are discussed considering the findings from research analyzing bicycle helmet effectiveness in a laboratory using simulation, and then are complemented with key methodological papers that address cycling and the overall factors contributing to the injury severity. The examined literature confirms that wearing a helmet while cycling is beneficial, regardless of age, crash severity, or crash type. The relative benefit is found to be higher in high-risk situations and when cycling on shared roads and particularly preventing severe head injuries. The results from the studies performed in laboratories also suggest that the shape and size of the head itself play a role in the protective effects of helmets. However, concerns regarding the equitability of the test conditions were found as all reviewed studies used a fifty-percentile male head and body forms. Lastly, the paper discusses the literature findings in a broader societal context.
MeSH term(s)	Male ; Humans ; Head Protective Devices ; Bicycling ; Craniocerebral Trauma/prevention & control ; Surveys and Questionnaires ; Laboratories
Language	English
Publishing date	2023-05-26
Publishing country	England
Document type	Systematic Review ; Journal Article
ZDB-ID	2615211-3
ISSN	2045-2322 ; 2045-2322
ISSN (online)	2045-2322
ISSN	2045-2322
DOI	10.1038/s41598-023-35728-x
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Article ; Online: Full data imputation for freeway time-specific safety performance functions' estimation.

Fu, Jingwan / Abdel-Aty, Mohamed / Yan, Xin

Accident; analysis and prevention

2023 Volume 190, Page(s) 107178

Abstract: Time-specific Safety Performance Functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions. Unfortunately, some states do not have or archive the needed high-resolution traffic data to develop time-specific SPFs. This ... ...

Abstract	Time-specific Safety Performance Functions (SPFs) were proposed to achieve accurate and dynamic crash frequency predictions. Unfortunately, some states do not have or archive the needed high-resolution traffic data to develop time-specific SPFs. This study proposes a novel iterative imputation method to impute the 100% missing volume and speed data from different states with similar crash rates. First, this study calculated the crash rates for 18 states and applied the One-Way Analysis of variance (ANOVA) test to group the states with similar crash rates. Second, as an example FL and VA, which both have traffic data, were used to test the proposed iterative imputation method. The results indicated that the imputed traffic data could capture the same traffic pattern as the real-collected traffic data. Further, the Mean Absolute Error (MAE) between the imputed Ln Volume and the real-collected Ln Volume for FL is only 2.47 vehicles for each segment for three hours. The MAE between the imputed Ln AvgSpeed and the real-collected Ln AvgSpeed for FL is only 1.36 mph. The Mean Absolute Percentage Error (MAPE) between the imputed Ln Volume and the real-collected Ln Volume is 11.07%. Meanwhile, the MAPE between the imputed Ln AvgSpeed and the real-collected Ln AvgSpeed is 7.40%. Finally, this study applied the proposed iterative imputation method to develop time-specific SPFs for the state without traffic data and compared the results. The results illustrated that the time-specific SPFs developed by imputed traffic data perfectly reflected the significant variables for both morning and afternoon peak models, with a prediction accuracy of 87.1% for the morning peak model.
MeSH term(s)	Humans ; Accidents, Traffic/prevention & control ; Models, Statistical ; Environment Design ; Safety ; Analysis of Variance
Language	English
Publishing date	2023-06-24
Publishing country	England
Document type	Journal Article
ZDB-ID	210223-7
ISSN	1879-2057 ; 0001-4575
ISSN (online)	1879-2057
ISSN	0001-4575
DOI	10.1016/j.aap.2023.107178
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