Monitoring the physiological inflammatory alertness in horse after road transport.

The aim of this study was to assess the changes of pro-inflammatory interleukins in 10 horses subjected to road transport practices (distance of 150 km) from the training site (Messina, Sicily) to the competition centre in Syracuse (Sicily). Blood sampling and interleukins analysis were performed during a round trip transportation (transport 1 and transport 2). In particular, blood samples were collected before the transport took place (Pre), five minutes later (Post) and one hour later (Post 1 h), for each transport, in order to assess the serum concentration of IL-1α, IL-1ß, IL-2 and IL-6. The results showed that the serum concentration of IL-1α decreased at Post and Post 1 h compared to the values obtained at rest condition (P < 0.05). The other interleukins analysed (i.e. IL-1ß, IL-2 and IL-6) showed increased levels at Post than Rest and Post 1 h in transport 1 (P < 0.05). In transport 2 the analysed parameters showed no change throughout the analysed time points (P > 0.05); however, higher levels of IL-1α at Pre and higher IL-1ß, IL-2 and IL-6 values at Post were found in transport 1 than transport 2 (P < 0.05). The increase in pro-inflammatory cytokines after transport 1 suggests the triggering of the inflammatory event and this may show that, although horses are animals accustomed to transport, this is a stressful event that could activate the well-orchestrated inflammation cascade, albeit physiological and temporary, as highlighted by the lower serum concentrations of the investigated interleukins found in transport 1 than transport 2 and by the lack of significant differences in the serum concentrations of the investigated interleukins among the time points of transport 2. It must be taken into account that enrolled animals are well-trained and healthy athletic horses participating to a jumper competition, thus, such inflammation did not occur thanks to a good balance between pro-inflammatory and anti-inflammatory cytokines which allowed a prompt restoration of homeostasis eventually impaired by the stressful event.

Neuroprotective effects of flavonoids: endoplasmic reticulum as the target.

The incidence of neurological disorders, particularly age-related neurodegenerative pathologies, exhibits an alarming upward trend, while current pharmacological interventions seldom achieve curative outcomes. Despite their diverse clinical presentations, neurological diseases often share a common pathological thread: the aberrant accumulation of misfolded proteins within the endoplasmic reticulum (ER). This phenomenon, known as ER stress, arises when the cell's intrinsic quality control mechanisms fail to cope with the protein-folding burden. Consequently, misfolded proteins accumulate in the ER lumen, triggering a cascade of cellular stress responses. Recognizing this challenge, researchers have intensified their efforts over the past two decades to explore natural compounds that could potentially slow or even reverse these devastating pathologies. Flavonoids constitute a vast and heterogeneous class of plant polyphenols, with over 10,000 identified from diverse natural sources such as wines, vegetables, medicinal plants, and organic products. Flavonoids are generally divided into six different subclasses: anthocyanidins, flavanones, flavones, flavonols, isoflavones, and flavonols. The diverse family of flavonoids, featuring a common phenolic ring backbone adorned with varying hydroxyl groups and additional modifications, exerts its antioxidant activity by inhibiting the formation of ROS, as evidenced by research. Also, studies suggest that polyphenols such as flavonoids can regulate ER stress through apoptosis and autophagy. By understanding these mechanisms, we can unlock the potential of flavonoids as novel therapeutic agents for neurodegenerative disorders. Therefore, this review critically examines the literature exploring the modulatory effects of flavonoids on various steps of the ER stress in neurological disorders.

A semantic segmentation model for road cracks combining channel-space convolution and frequency feature aggregation.

In transportation, roads sometimes have cracks due to overloading and other reasons, which seriously affect driving safety, and it is crucial to identify and fill road cracks in time. Aiming at the defects of existing semantic segmentation models that have degraded the segmentation performance of road crack images and the standard convolution makes it challenging to capture the spatial and channel coupling relationship between pixels. It is difficult to differentiate crack pixels from background pixels in complex backgrounds; this paper proposes a semantic segmentation model for road cracks that combines channel-spatial convolution with the aggregation of frequency features. A new convolutional block is proposed to accurately identify cracked pixels by grouping spatial displacements and convolutional kernel weight dynamization while modeling pixel spatial relationships linked to channel features. To enhance the contrast of crack edges, a frequency domain feature aggregation module is proposed, which uses a simple windowing strategy to solve the problem of mismatch of frequency domain inputs and, at the same time, takes into account the effect of the frequency imaginary part on the features to model the deep frequency features effectively. Finally, a feature refinement module is designed to refine the semantic features to improve the segmentation accuracy. Many experiments have proved that the model proposed in this paper has better performance and more application potential than the current popular general model.

Decelerating catalyst aging of natural gas engines using organic Rankine cycle under road conditions.

High exhaust temperature is an intrinsic nature of natural gas engines which underlies power de-rating and thermal aging of after-treatment system; therefore, this study integrates an organic Rankine cycle (ORC) system between engine and it's three-way catalyst (TWC) to address these challenges. ORC facilitates power output enhancement through exhaust energy recovery and alleviates thermal aging by reducing exhaust temperature. To estimate the effectiveness of this hypothesized system, a simulation-based investigation is performed. First, simulation models, including engine, TWC, and vehicle dynamic models, are built and validated by experimental data. According to the temperature characteristics of different TWCs, three scenarios, representing old, current, and prospective TWC technology, are formulated to estimate the ORC performance under Worldwide Harmonized Light Vehicles Test Cycle. Results show that ORC system can substantially alleviate the thermal damage caused by high exhaust temperature and extend TWC lifespan. It is estimated that over 98.5 % of thermal damage can be decreased by proper ORC setting, and the average TWC lifespan extension can be at least 55.4, making a reduced noble metal usage and cost of TWC. Meanwhile, with the decrease of the working temperature of TWC, ORC can recover exhaust energy under more road conditions, further improving the net power and shortening the payback period of extra ORC hardware costs. A reduction in the working temperature of TWC from 770.5 K to 618 K yields a 109 % enhancement in maximum power, coupled with a 62.30 % reduction in the payback period. These findings fully reflect the advantage of ORC-TWC coupling and indicate that ORC is supposed to be used more for the TWC with a low working temperature to maximize economic effectiveness. This study provides a novel pathway for thermal aging alleviation of TWC and a valuable reference for prospective studies on matching ORC with TWC under road conditions.

Driving risk identification of urban arterial and collector roads based on multi-scale data.

Urban arterial and collector roads, while interconnected within the urban transportation network, serve distinct purposes, leading to different driving risk profiles. Investigating these differences using advanced methods is of paramount significance. This study aims to achieve this by primarily collecting and processing relevant vehicle trajectory data alongside driver-vehicle-road-environment data. A comprehensive risk assessment matrix is constructed to assess driving risks, incorporating multiple conflict and traffic flow indicators with statistically temporal stability. The Entropy weight-TOPSIS method and the K-means algorithm are employed to determine the risk scores and levels of the target arterial and collector roads. Using risk levels as the outcome variables and multi-scale features as the explanatory variables, random parameters models with heterogeneity in means and variances are developed to identify the determinants of driving risks at different levels. Likelihood ratio tests and comparisons of out-of-sample and within-sample prediction are conducted. Results reveal significant statistical differences in the risk profiles between arterial and collector roads. The marginal effects of significant parameters are then calculated separately for arterial and collector roads, indicating that several factors have different impacts on the probability of risk levels for arterial and collector roads, such as the number of movable elements in road landscape pictures, the standard deviation of the vehicle's lateral acceleration, the average standard deviation of speed for all vehicles on the road segment, and the number of one-way lanes on the road segment. Some practical implications are provided based on the findings. Future research can be implemented by expanding the collected data to different regions and cities over longer periods.

Implementation of the new acts on driving under the influence of alcohol and clinical outcomes for patients severely injured in road traffic crashes.

OBJECTIVE: Driving under the influence (DUI) of alcohol is a major risk factor for fatal road traffic injuries (RTIs) worldwide. This study aimed to investigate the relationship between the implementation of new acts on DUI of alcohol and the clinical outcomes of patients with severe RTIs in Korea. METHODS: This is a community-based cross-sectional study using a nationwide severe trauma registry in Korea. In 2018, 2 acts with the Yoon Chang-Ho Act (Yoon's Act) were passed to strengthen the punishment for drunk driving fatal RTIs (first Yoon's act) and lower the blood alcohol concentration limit to restrict driver's licenses (second Yoon's act). The first Yoon's act was implemented on December 18, 2018, and the second Yoon's act was implemented on June 25, 2019. The study periods were categorized as pre-Act-1, pre-Act-2, Act-1, and Act-2 according to the application of Yoon's Act, and the study outcome was in-hospital mortality. Multivariable logistic regression analysis was conducted to estimate the relationship of the new acts and in-hospital mortality. RESULTS: Among a total of 20,376 patients with severe RTIs and 7,928 patients (drivers) with RTIs (hereafter drivers), the in-hospital mortality rates were 20.8% and 17.0%, and alcohol-related RTIs accounted for 9.7% and 8.1%, respectively. Severe RTIs tended to increase with each period (25.5 cases/day, 24.5 cases/day, 26.8 cases/day, and 30.4 cases/day, P for trend <.01). In-hospital mortality significantly decreased during the Act-2 period compared to the pre-Act-2 period for all patients with severe RTIs (adjusted odds ratio = 0.54, 95% confidence interval 0.43-0.67) and drivers with RTIs (adjusted odds ratio = 0.50, 95% confidence interval 0.34-0.73). CONCLUSIONS: Implementation of the new acts on DUI of alcohol was associated with lower odds for in-hospital mortality for patients with severe RTIs. Further studies are needed to evaluate the long-term impact of the new acts on reducing alcohol-related RTIs.

Microplastic loads in Eurasian otter (Lutra lutra) feces-targeting a standardized protocol and first results from an alpine stream, the River Inn.

Microplastics (MP) are omnipresent in a wide range of environments, constituting a potential threat for aquatic and terrestrial wildlife. Effects in consumers range from physical injuries to pathological reactions. Due to potential bioaccumulation of MP, predators are of particular concern for MP induced health effects. The Eurasian otter is an apex predator in (semi-)aquatic habitats feeding primarily on fish. Furthermore, the species is classified as "near threatened" on the IUCN Red List. Thus, the Eurasian otter is of conservation concern and may serve as a bioindicator for MP pollution. Feces can be used to detect pollutants, including MP. Initial studies confirmed the presence of MP in otter feces (= spraints). However, as specific, validated protocols targeting at an efficient and standardized extraction of MP from otter spraints are missing, experimental results reported from different groups are challenging to compare. Therefore, we (i) present steps towards a standardized protocol for the extraction of MP from otter feces, (ii) give recommendations for field sample collection of otter spraints, and (iii) provide a user-friendly step-by-step workflow for MP extraction and analysis. Applying this framework to field samples from five study sites along the River Inn (n = 50), we detected MP of different sizes and shapes (ranging from microfibers to road abrasion and tire wear) in all otter spraint samples.

Applying the multiphase optimization strategy to evaluate the feasibility and effectiveness of an online road safety education intervention for children and parents: a pilot study.

BACKGROUND: Reports of children's engagement in active transportation outline low participation rates in many countries despite many associated mental, physical, and social health benefits. One of the main contributors to this phenomenon is a cited lack of education and knowledge among children regarding active travel (AT), specifically road safety. To address this issue, the aim of this study was to evaluate the feasibility and effectiveness of an online road safety education intervention to promote AT among children and their parents. METHODS: Applying the Multiphase Optimization Strategy (MOST) for intervention development, implementation, and evaluation, we designed and assessed a four-module online road safety education intervention with a sample of 57 parent-child dyads using a 23 factorial design featuring both qualitative and quantitative analyses. RESULTS: Main intervention feasibility findings include positive and critical feedback on the program's content and design, and moderate participant engagement as reflected by program retention and completion rates. With respect to the preliminary intervention effectiveness on children, a significant improvement in road safety knowledge scores was observed for groups that feature the "wheeling safety and skills" module. Slight improvements in AT knowledge scores across all the intervention groups were observed, but were not of significance. Preliminary intervention effectiveness on select parental AT practices and perceptions saw significant improvements in some groups. Groups that featured the 'wheeling safety and skills' module exhibited significantly higher guided choice scores upon completion of the program than those who did not receive this component. CONCLUSION: The MOST framework allowed us to design and evaluate the feasibility and preliminary effectiveness of an online road safety education intervention. The developed intervention has demonstrated that it has the potential to improve children's road safety knowledge and some areas of parental AT practices and perceptions, to which improvements may be attributed to the inclusion of the "wheeling safety and skills" module, suggesting that the targeted focus on cycling skills is a prioritized area. AT programming and practice implications are discussed. Future research is encouraged to refine modules to better reflect the priorities of children and parents and to test these refined components among larger samples. WORD COUNT: 9,391 (excludes abstract, tables, figures, abbreviations, and references).

Carbon emissions from road transportation in China: from past to the future.

Road transportation is an important contributor to carbon emissions. China's car ownership is rapidly increasing, ranking first worldwide; however, there are limited data about carbon emission inventories. This study assesses carbon emissions from road transportation from the past to the future across China, using market survey, COPERT (Computer Programme to Calculate Emissions from Road Transport) model, and a combination method of principal component analysis and backpropagation neural network. From 2000 to 2020, the national carbon emissions from road transportation grew from 11.9 to 33.8 Mt CO2e, accounting for 0.47% of national total emissions by then. Trucks generally emit a higher proportion (77.3%) of total emissions than passenger cars (18.9%); however, the emission proportion of passenger cars (18.9-31.0%) has increased yearly. The carbon emissions at the prefecture level show an urban agglomeration trend, decreasing from the eastern coastal areas to central China. Future car ownership is expected to grow rapidly at 3.1% during 2021-2049, but only half of that growth rate during 2051-2060. Those vehicles are expected to contribute carbon emissions of 27.2-39.1 Mt CO2e under different scenarios in 2060. Scientifically reducing emissions and innovatively reducing the carbon emission coefficient, combined with a reasonable new energy vehicle growth scenario, are efficient methods for reducing national carbon levels. This study demonstrates that the uncertainty is within an acceptable range. This work details the carbon emission inventories associated with road transportation in China and provides basic data for developing a better carbon reduction policy for China's car industry.

An in vitro comparison of the toxicological profiles of ground tire particles (TP) and actual tire and road wear particles (TRWP) emissions.

There is currently limited data on the potential effects of tire and road wear particles (TRWP) on human health. TRWP include tire fragments, but also road wear materials, dust, adsorbed gaseous pollutants and different types of inclusions that could affect their hazard profiles. Due to their availability and lower complexity, ground tire particles (TP) are often used in toxicological studies. However, this makes it difficult to draw firm conclusions about the potential hazard of actual TRWP. Here, we compared the in vitro toxicological profile of ground TP and actual TRWP emissions of similar size collected from road traffic. For this purpose, TP and TRWP were separately incubated with alveolar macrophages for 24 h, and the cellular response was evaluated in terms of cytotoxicity, proinflammatory response and oxidative stress. Both TP and TRWP induced neither significant cytotoxicity nor oxidative stress, but triggered a concentration-dependent proinflammatory response, as evidenced by increased TNF-α production. The level of TNF-α production was slightly higher with TRWP than with TP, independent of the particle dose. All in all, the pulmonary toxicity of TRWP could be due primarily to the tire tread inclusions and only marginally to other particle components (i.e. road wear materials, dust …). Although these preliminary results need to be confirmed by further analysis, they could be useful for tire manufacturers in the production of safer-by-design tires.

The impact of the Qinghai-Tibet highway on plant community and diversity.

Roads are an increasingly prevalent form of human activity that drives the decrease in plant community functions and threatens global biodiversity. However, few studies have focused on the changes in the function and diversity of alpine meadows caused by road infrastructure in the Tibetan Plateau. In this study, the changes in species diversity, functional diversity, and community stability were examined at different distances from the Qinghai-Tibet highway. The results showed that the road intensified the degradation of vegetation, which significantly altered species diversity and community structure. This effect gradually decreased from near to far from the highway. Plant community cover and species diversity were highest at intermediate distances (50-100 m) from the roadway; species diversity and stability were lowest in the grassland most disturbed by the road (0 m), and species diversity and functional diversity tended to stabilize farther away from the road (250 m). Our findings indicate that changes in species diversity are synchronized with changes in functional diversity, which largely determines the outcome of degraded grassland community diversity and stability. Our results provide a reference point for restoring degraded alpine areas and mitigating the ecological impacts of roads.

The association between county ordinances allowing off-road vehicles on public roads and crash rates.

BACKGROUND: Legislative bodies across the country have increasingly allowed off-road vehicles (ORVs) including all-terrain vehicles (ATVs) and utility task vehicles (UTVs) on public roads, an environment for which they are not designed. In 2004, Iowa gave individual counties the discretion to pass ordinances allowing ORVs on public roadways. The objective of this study was to evaluate the relationship between the passage of ORV ordinances and ORV crash rates, especially on public roads. METHODS: An Iowa ORV roadway ordinance database and an Iowa ORV crash database (2002-2018) for all 99 counties were compiled. Crashes for which county location could not be determined were excluded. Utilizing a zero-inflated Poisson model, correcting for background crash frequency trends and population, investigators compared the relative rates of crashes after ordinance passage to time points before ordinance implementation and to counties without such ordinances. Sub-analyses, including that focused on more recent years (2008-2018), were also performed. RESULTS: Forty-five county ORV roadway ordinances went into effect between 2011 and 2018 and 2,347 crashes (69%) met inclusion criteria. Adjusted for year, there was a 58% greater ORV crash rate in counties after passing an ORV roadway ordinance (incidence rate ratio (IRR) 1.58, 95% CI 1.32-1.90). Roadway crashes (n = 834) increased 48% after ordinance passage (IRR 1.48, 95% CI 1.14-1.94). This roadway crash association remained statistically significant when analysis was limited to the years 2008-2018 (IRR 1.39, CI 1.06-1.83, n = 544); to ATV crashes only (IRR 1.70, CI 1.20-2.40, n = 683); and to ATV crashes excluding counties with UTV-only ordinances (IRR 1.74, CI 1.40-2.15, n = 2,011). CONCLUSIONS: ORV roadway and total crashes increased significantly after implementation of county ordinances allowing ORVs on public roadways and when compared to counties without such ordinances. It is likely that these increased crashes have resulted in more injuries and possibly deaths. Results from this study may help inform policymakers as they consider legislation regarding ORV usage on public roads.

Impact analysis of dust evolution pattern and determination of key ventilation parameters in highland highway construction tunnels.

In order to study the influence of ventilation parameters on the ventilation of plateau highway construction tunnels, a highway tunnel construction section in Yunnan is taken as the research background, and Fluent software is used for simulation. The results of the study show that: under the conditions of press-in ventilation, the wind speed in the center of the vortex area in the wind flow field is smaller than the wind speed in the surrounding area, and with the diffusion of the flow field, the average wind speed in the tunnel section gradually decreases, and ultimately stabilizes at the level of 0.5 m/s. After blasting, the dust mass concentration on the return side of the tunnel is higher than that on the duct side. Dust with a particle size of 30 µm or more settled rapidly within 100 m from the boring face, while dust with a particle size of 30 µm or less gradually diffused outward under the action of the wind flow. In the vicinity of the tunnel boring face, reducing the distance from the air outlet to the boring face and increasing the air velocity can improve the dust removal effect. This conclusion can provide theoretical basis and certain guidance for the evolution of dust and dust prevention in the tunnel construction process in plateau area.

New generation vehicles: The impact of electric scooter trauma on the severity of facial fractures assessed by FISS score. A multicentre study.

With the increasing use of sustainable energy sources, the electric scooter has become a widely used vehicle. The aim of the study is to analyse the types of facial fracture related to road traffic accidents to outline the need of dedicated road rules. An observational, retrospective, multicentre study was carried out at the Maxillofacial Surgery Units of six Italian hospitals. Fifty patients (mean age was 34.76 years) from January 2020 to January 2024 were enrolled. The severity of trauma was evaluated by the Facial Injury Severity Scale (FISS) by Bagheri et al. Most of the accidents occurred during the day and the weekend in spring or summer; 24 drivers collided with infrastructures or pedestrians, while 26 involved other vehicles. A total of 33 vehicles were rented, and 17 were privately owned. A total of 43 subjects were not wearing helmets, five patients were drunk, and three patients took drugs. In order of frequency, the facial fractures involved: zygomatico-maxillary-orbital complex (ZMOC) (n = 16), mandibular condyle (n = 13), nasal bone (n = 11), orbit floor (n = 8), and mandibular body (n = 7). Fractures such as Le Fort I (n = 4), naso-orbito-ethmoidal NOE (n = 4) and mandibular ramus (n = 4) were less common. Other types of facial fracture were rare. Thirty patients reported multiple facial fractures. The vast majority of the cases showed a low severity grade FISS score. Fifteen patients suffered polytrauma. The mean hospitalisation time was 8.3 days. As accidents with electric scooters are increasing, it is important to characterise the most frequent facial fractures to improve patient management and encourage the introduction of new road rules.

Potential deterioration of chemical water quality due to trace metal adsorption onto tire and road wear particles - environmentally representative experiments.

Tire wear particles are an increasing issue in particle emissions to the environment. Germany-wide approximately 100,000 t tire wear particles are emitted every year into the environment which are estimated to be one third of the microplastic emissions. Up to 20% are estimated to reach inland surface waters. Their behavior in the aquatic environment is understudied. Tire wear particles have an overly hydrophobic surface that is capable of adsorbing substances like trace elements. In this study we investigated the adsorption and desorption of trace metals onto and from the particle surface of tire-related samples in water samples of the Freiberger Mulde, a river with naturally elevated concentration of trace elements. The priority trace metals Cr, Ni, Zn, Cd and Pb show a significant adsorption onto the particle surface of tire-related samples. Tire wear particles themselves revealed adsorption of mainly Ni, Cd and Pb. Regarding the German classification for suspended matter in freshwaters, an endangering of the chemical water quality is expected due to the adsorption process and not due to the particles themselves. Upcoming electromobility is expected to increase the Zn (increased tire abrasion) and decrease the Cu amount (reduced brake abrasion) released to freshwaters.

Road traffic noise pollution and prevalence of ischemic heart disease: modelling potential association and abatement strategies in noise-exposed areas.

In many developing countries with surging vehicular traffic and inadequate traffic management, excessive road traffic noise exposure poses substantial health concerns, linked to increased stress, insomnia and other metabolic disorders. This study aims to assess the linkage between sociodemographic factors, traffic noise levels in residential areas and health effects using a cross-sectional study analyzing respondents' perceptions and reports. Noise levels were measured at 57 locations in Srinagar, India, using noise level meter. Sound PLAN software was employed to generate noise contour maps, enabling the visualization of noise monitoring locations and facilitating the assessment of noise levels along routes in proximity to residential areas. Correlation analysis showed a strong linear relationship between field-measured and modelled noise (r2 = 0.88). Further, a questionnaire-based survey was carried out near the sampling points to evaluate the association of ischemic heart disease with traffic noise. Residents exposed to noise levels (Lden > 60 dB(A)) were found to have a 2.24 times higher odds ratio. Compared to females, males reported a 16% higher prevalence of the disease. Multi-faceted policy strategies involving noise mapping initiatives, source noise standards, traffic flow urban mobility optimization, smart city initiatives and stringent litigatory measures could significantly reduce its detrimental impact on public health. Finally, this study envisions a region-specific strong regulatory framework for integrating noise pollution mitigation strategies into the public health action plans of developing nations.

Tire-derived contaminants 6PPD and 6PPD-Q: Analysis, sample handling, and reconnaissance of United States stream exposures.

The environmental ubiquity of tire and road wear particles (TRWP) underscores the need to understand the occurrence, persistence, and environmental effects of tire-related chemicals in aquatic ecosystems. One such chemical is 6PPD-quinone (6PPD-Q), a transformation product of the tire antioxidant 6PPD. In urban stormwater runoff 6PPD-Q can exceed acute toxicity thresholds for several salmonid species and is being implicated in significant coho salmon losses in the Pacific Northwest. There is a critical need to understand the prevalence of 6PPD-Q across watersheds to identify habitats heavily affected by TRWPs. We conducted a reconnaissance of 6PPD and 6PPD-Q in surface waters across the United States from sites (N = 94) with varying land use (urban, agricultural, and forested) and streamflow to better understand stream exposures. A rapid, low-volume direct-inject, liquid chromatography mass spectrometry method was developed for the quantitation of 6PPD-Q and screening for 6PPD. Laboratory holding times, bottle material, headspace, and filter materials were investigated to inform best practices for 6PPD-Q sampling and analysis. Glass bottles with PTFE-lined caps minimized sorption and borosilicate glass fiber filters provided the highest recovery. 6PPD-Q was stable for at least 5 months in pure laboratory solutions and for 75 days at 5 °C with minimal headspace in the investigated surface water and stormwaters. Results also indicated samples can be frozen to extend holding times. 6PPD was not detected in any of the 526 analyzed samples and there were no detections of 6PPD-Q at agricultural or forested sites. 6PPD-Q was frequently detected in stormwater (57%, N = 90) and from urban impacted sites (45%, N = 276) with concentrations ranging from 0.002 to 0.29 µg/L. The highest concentrations, above the lethal level for coho salmon, occurred during stormwater runoff events. This highlights the importance of capturing episodic runoff events in urban areas near ecologically relevant habitat or nursery grounds for sensitive species.

Study on preparation and properties of antifreeze compound road dust suppressant.

Open-pit mine pavement dust dries and breaks easily. As such, a composite pavement dust suppressant with good wettability, moisturizing, coagulation, and antifreezing properties in winter was investigated. Monomer screening and orthogonal experiments were conducted, using evaporation rate, permeability rate, viscosity, and freezing point as evaluation indexes. Consequently, a dust suppressant solution is a mixture of glycerol (GLY), sodium dodecylbenzene sulfonate (SDBS), polyacrylamide (PAM), compound propylene glycol (PG), and potassium acetate (PA). The characteristics of the dust suppressant and its interaction mechanism with road dust were measured and analyzed. The results showed that the optimal ratio of the antifreeze-type composite dust suppressant is 3%GLY, 0.30%SDBS, 0.07% PAM, and 50%PG + 10%PA; the contact angle is 27.62°, which can effectively wet coal dust. Moreover, it easily forms hydrogen bonds with water molecules to release free -OH, which increases the oxygen-containing functional groups in the dust. The maximum viscosity is 25.4 mPa·s, and the hydrophobic groups adsorbed on the surface of the dust can condense and agglomerate the dust to form large particles, and effectively inhibit the occurrence of dust. It freezes at - 34.2 â„ƒ, resists a temperature of - 30 â„ƒ without freezing, and improves dust suppression efficiency and antifreezing effect in cold areas.

Urban Road Surface Condition Sensing from Crowd-Sourced Trajectories Based on the Detecting and Clustering Framework.

Roads play a crucial role in urban transportation by facilitating the movement of materials within a city. The condition of road surfaces, such as damage and road facilities, directly affects traffic flow and influences decisions related to urban transportation maintenance and planning. To gather this information, we propose the Detecting and Clustering Framework for sensing road surface conditions based on crowd-sourced trajectories, utilizing various sensors (GPS, orientation sensors, and accelerometers) found in smartphones. Initially, smartphones are placed randomly during users' travels on the road to record the road surface conditions. Then, spatial transformations are applied to the accelerometer data based on attitude readings, and heading angles are computed to store movement information. Next, the feature encoding process operates on spatially adjusted accelerations using the wavelet scattering transformation. The resulting encoding results are then input into the designed LSTM neural network to extract bump features of the road surface (BFRSs). Finally, the BFRSs are represented and integrated using the proposed two-stage clustering method, considering distances and directions. Additionally, this procedure is also applied to crowd-sourced trajectories, and the road surface condition is computed and visualized on a map. Moreover, this method can provide valuable insights for urban road maintenance and planning, with significant practical applications.

Using Support Vector Machines to Classify Road Surface Conditions to Promote Safe Driving.

Accurate detection of road surface conditions in adverse winter weather is essential for traffic safety. To promote safe driving and efficient road management, this study presents an accurate and generalizable data-driven learning model for the estimation of road surface conditions. The machine model was a support vector machine (SVM), which has been successfully applied in diverse fields, and kernel functions (linear, Gaussian, second-order polynomial) with a soft margin classification technique were also adopted. Two learner designs (one-vs-one, one-vs-all) extended their application to multi-class classification. In addition to this non-probabilistic classifier, this study calculated the posterior probability of belonging to each group by applying the sigmoid function to the classification scores obtained by the trained SVM. The results indicate that the classification errors of all the classifiers, excluding the one-vs-all linear learners, were below 3%, thereby accurately classifying road surface conditions, and that the generalization performance of all the one-vs-one learners was within an error rate of 4%. The results also showed that the posterior probabilities can analyze certain atmospheric and road surface conditions that correspond to a high probability of hazardous road surface conditions. Therefore, this study demonstrates the potential of data-driven learning models in classifying road surface conditions accurately.