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1.
Environ Res ; 236(Pt 1): 116745, 2023 Nov 01.
Artículo en Inglés | MEDLINE | ID: mdl-37500040

RESUMEN

The activation of persulfate technology using carbon-based materials doped with heteroatoms has been extensively researched for the elimination of refractory pollutants in wastewater. In this study, metal-organic frameworks were utilized as precursors to synthesize P, N dual-doped carbon material (PNC), which was employed to activate peroxymonosulfate (PMS) for the degradation of tetracycline hydrochloride (TCH). The results demonstrated a 90.2% removal efficiency of total organic carbon within 60 min. The significant increase of surface defects on the nitrogen self-doped porous carbon materials anchored with phosphorus promoted the conversion of superoxide radical to singlet oxygen during PMS activation, which was identified as the key active species of PNC/PMS system. Additionally, the enhanced direct electron transfer also facilitated the degradation of TCH. Consequently, TCH was successfully degraded into nontoxic and harmless inorganic small molecules. The findings of this research provide valuable insights into improving the performance of heteroatom-doped carbon materials for pollutant degradation by activating PMS and transforming the non-radical pathway. The results highlight the potential of metal-organic frameworks derived heteroatoms dual-doped porous carbon catalysts for the development of advanced treatment technologies in wastewater treatment.

2.
Artículo en Inglés | MEDLINE | ID: mdl-35954988

RESUMEN

The safety situation of hazardous materials (hazmat) accidents during road transportation in China is severe and very serious accidents occurred frequently. Such accidents not only have a huge impact on the environment but also have serious consequences for people and the economy, such as fires and explosions. Therefore, it is necessary to understand the characteristics and laws of road transport accidents of hazmat systematically. This paper investigated 2777 hazmat transportation accidents in China from 2013 to 2019 to identify the characteristics, consequences, and causes of the accident. The results show that August (10.05%) and December (9.76%) are the peak periods of hazmat transportation accidents, while most hazmat transportation accidents occurred in the early morning (6:00-9:00 a.m.) and at noon (9:00 a.m.-12:00 p.m.) hours. For the geographical location, the accidents mainly occurred in the east China (34.35%) and the northwest China areas (14.87%). The main types of hazmat transportation accidents were rollover (35.36%), rear-end (22.58%), and collision (14.87%), where the probability of a major leak was high. The most common hazmat transportation accidents involve gas (17.79%), flammable liquid (56.07%), and corrosive substance (12.28%). The most common consequences of the hazmat transportation accidents were leakage (80.34%), followed by fire release (8.32%) and explosion release (2.34%). Human factor (26.74%) is the main cause of hazmat transportation accidents. These findings could help hazmat transportation managers and planners develop appropriate measures for improving hazmat transportation safety.


Asunto(s)
Sustancias Peligrosas , Transportes , Accidentes , China/epidemiología , Humanos , Probabilidad
3.
Traffic Inj Prev ; 22(2): 158-161, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-33497285

RESUMEN

OBJECTIVE: Hit-and-run behavior in crashes is a severe offense worldwide because the identification and emergency rescue of any injured road user is delayed. A motorist's run from the crash scene is especially serious for a cyclist who would be more prone to be physically injured in a bicycle-vehicle (BV) crash. The objective of this paper is to explore potential risk factors that contribute to the hit-and-run (HR) behavior of a driver after a two-unit BV collision. METHODS: The data used in this study are extracted from traffic crash records in the city of Durham, North Carolina in 2007-2014. This study uses the skewed logistic (Scobit) model to account for the skewness of the dependent variable (i.e., HR) in the dataset. RESULTS: The Likelihood ratio test, AIC and BIC results show that the Scobit model is preferred to the standard binary logistic model for modeling a driver's decision to run from a two-unit BV crash scene. Estimation results indicate that, the driver's tendency to run from a crash scene without reporting it in Durham increases if the bicyclist is a teenager or an adult, a drunk-driving or a speeding driver is involved, when the crash happens at night (19:00-6:59), on a local street, or when the automobile overtakes the bicycle. HR behavior will decrease if the cyclist is drunk, an SUV is involved, or the bicyclist fails to yield. CONCLUSIONS: The findings of this study are important and useful when developing countermeasures to prevent BV-HR crashes and to improve cycling safety.


Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Conducción de Automóvil/estadística & datos numéricos , Ciclismo/estadística & datos numéricos , Conducir bajo la Influencia/estadística & datos numéricos , Adolescente , Adulto , Intoxicación Alcohólica/epidemiología , Automóviles , Ciclismo/lesiones , Servicio de Urgencia en Hospital , Humanos , Funciones de Verosimilitud , Modelos Logísticos , North Carolina , Factores de Riesgo
4.
Comput Med Imaging Graph ; 79: 101684, 2020 01.
Artículo en Inglés | MEDLINE | ID: mdl-31812132

RESUMEN

Image-to-image translation is considered a new frontier in the field of medical image analysis, with numerous potential applications. However, a large portion of recent approaches offers individualized solutions based on specialized task-specific architectures or require refinement through non-end-to-end training. In this paper, we propose a new framework, named MedGAN, for medical image-to-image translation which operates on the image level in an end-to-end manner. MedGAN builds upon recent advances in the field of generative adversarial networks (GANs) by merging the adversarial framework with a new combination of non-adversarial losses. We utilize a discriminator network as a trainable feature extractor which penalizes the discrepancy between the translated medical images and the desired modalities. Moreover, style-transfer losses are utilized to match the textures and fine-structures of the desired target images to the translated images. Additionally, we present a new generator architecture, titled CasNet, which enhances the sharpness of the translated medical outputs through progressive refinement via encoder-decoder pairs. Without any application-specific modifications, we apply MedGAN on three different tasks: PET-CT translation, correction of MR motion artefacts and PET image denoising. Perceptual analysis by radiologists and quantitative evaluations illustrate that the MedGAN outperforms other existing translation approaches.


Asunto(s)
Diagnóstico por Imagen/métodos , Procesamiento de Imagen Asistido por Computador/métodos , Redes Neurales de la Computación , Encéfalo/diagnóstico por imagen , Humanos
5.
Traffic Inj Prev ; 20(2): 146-151, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-30946617

RESUMEN

OBJECTIVE: Phantom vehicle crashes (PVCs), or miss-and-run crashes, are a topical issue in car insurance coverage because of controversies over testimony and compensation. However, no peer-reviewed literature has examined the perceptions and deliberations involved in this infrequent type of car crash. A novel taxonomy of roadway traffic crashes is proposed in this study on the basis of whether physical collisions did occur (hit or miss) and whether the perpetrators stayed at the crash scene (stay or run). In this way, this study poses the issue of PVCs within the scope of traffic safety research and aims to investigate the statistically significant factors that are likely to induce PVCs. METHODS: A binary logistic regression method was adopted to model the probability and occurrence of 2-vehicle PVCs (TV-PVCs) in Florida. Data derived from the Crash Analysis Reporting system in 2012-2014 consisted of 45,319 2-vehicle crashes, of which 1,376 (3.04%) were confirmed as positive TV-PVCs. Sixteen factors with 50 variables on crash information, roadway characteristics, and environmental conditions were included in the original consideration of the TV-PVC model. RESULTS: The results indicated that a 2-vehicle crash is more likely to be a PVC when the crash happens on weekends, on roadways with no traffic control or speed control, full access control; on curving and sloping roadways; on roadways of National Highway System; and in low-density and other areas. A TV-PVC is less likely to occur on dry roads, in daylight, or at intersections or driveways. Moreover, alcohol involvement in a 2-vehicle crash is associated with hit-and-stay crashes than PVCs, and uninsured motorists are more likely to be the victims of PVCs because they tend to avoid physical collisions due to the potential self-paid loss. CONCLUSIONS: Several conclusions for better understanding the occurrence of PVCs are proposed for traffic management departments and car insurers. Cautious driving behavior including concentrated attention and deliberate lane changes should be encouraged for motorists to engage in appropriate levels of driving freedom, and drunk driving should be strictly supervised to keep motorists behind the wheel conscious. Car insurance is encouraged to compensate for economic loss resulting from roadway crashes. Road monitoring systems with well-performing illumination devices are recommended to help drivers provide potent testimony for compensation claims.


Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Entorno Construido/estadística & datos numéricos , Conducir bajo la Influencia/estadística & datos numéricos , Florida , Humanos , Seguro/estadística & datos numéricos , Modelos Logísticos , Probabilidad
6.
Accid Anal Prev ; 95(Pt B): 373-380, 2016 Oct.
Artículo en Inglés | MEDLINE | ID: mdl-26411325

RESUMEN

Hit-and-run crashes are a relatively infrequent but severe offense worldwide because the identification and emergency rescue of victims is delayed, which increases the injury severities and the mortality rate. However, no studies have been conducted on hit-and-run crashes in urban river-crossing road tunnels (URCRTs), which can greatly threaten the safety of motorists driving in the tunnels. This study, which employs a dataset of vehicle crashes that happened in thirteen urban road tunnels traversing the Huangpu River, established a binary logistic regression model to identify thirteen factors that contribute to escaping after crashes in Shanghai related to the offending drivers, the vehicular and environmental conditions, the tunnel characteristics and crash information. Among the thirty-five variables considered, this study found that a perpetrator's tendency to leave the crash scene without reporting an accident was higher at night, in the tunnel exit, near to or in short tunnels, when a two-wheeled vehicle or heavy goods vehicle (HGV) was involved and when alcohol was involved. While a perpetrator was more likely to remain on the scene in the tunnel entrance, on a rainy day, in a rear end collision, when a bus was involved, in a single vehicle or a multi-vehicle accident. Based on these findings, several countermeasures for better supervision and hit-and-run prevention are proposed.


Asunto(s)
Accidentes de Tránsito/estadística & datos numéricos , Conducción de Automóvil/psicología , Seguridad , Accidentes de Tránsito/prevención & control , China , Planificación Ambiental , Humanos , Modelos Logísticos , Vehículos a Motor , Curva ROC , Factores de Riesgo , Ríos , Población Urbana
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