A rollover safety margin-based approach for quantifying the tractor-semitrailers’ emergency lane-changing response on expressway curves
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ABSTRACT:
SUBMITTER: Lv W
PROVIDER: S-EPMC10511121 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
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Project description:Lane-changing (LC) behavior is investigated on Chinese freeways, where the driving circumstances are relatively aggressive. Three data sets were collected from urban expressways and an intercity highway in the form of traffic videos. Different aspects of LC behaviors are analyzed, i.e., the LC rate, motivation, target lane choice and impact on traffic. The results suggest that LC is a transient behavior that randomly occurs with high frequency, which is the main feature of aggressive driving. Several LC patterns and the combination effect of ramps, fast lanes and various vehicle types are presented. The influence of LC on local traffic endures for approximately 15 to 30 s, which rapidly increases and slowly declines. LC behavior will increase the risk of high-speed car-following. All results are obtained from the empirical data; they will be useful for traffic management and traffic modeling.
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Project description:BackgroundIn Ireland, the agriculture sector reports the highest number of fatalities even though farmers constitute only 6% of the working population. Tractor-related behaviours are implicated in 55% of all vehicle work-related fatalities and 25% of reported injuries, and many of these occur in farmyards. There is limited research on the feasibility and acceptability of behaviour change interventions to improve tractor safety. Target behaviours that promote safe operation in farmyards, determining and addressing blind spots of tractors, were identified, and an intervention was developed following the Behaviour Change Wheel Approach. The objective of the study is to examine the feasibility, fidelity and acceptability of a behaviour change intervention to enhance the safe operation of tractors in farmyards with a particular focus on tractor blind spots.MethodA single group feasibility study will be undertaken. Approximately 16 farmers from four major farm types will be recruited for the study between August and September 2022. The intervention involves an in-person demo session, facilitated discussion and personalised safety training procedure with safety goals. The study will collect data from participants at three time points: baseline (3-10 days prior to the intervention), during the intervention and at the follow-up session (7-30 days post-intervention). Quantitative data will be collected through a pre-intervention interview and feedback surveys. A pre- and post-intervention qualitative interview will also be conducted with the participants and will be supplemented with qualitative data from recruitment logs, observational memos and logs and feedback from recruiters. Evaluation of the feasibility, acceptability and fidelity of the intervention will be guided by a pre-determined feasibility checklist, fidelity framework and theoretical framework of acceptability, respectively. Interviews will be analysed using the content analysis.DiscussionThe current study can determine the feasibility and fidelity of delivering a systematic, theoretically driven, tailored behaviour change intervention. It will also assess whether the intervention, its ingredients and delivery are acceptable to the farming population. This study will also inform the development of a future larger trial to test the effectiveness of the intervention.Trial registrationISRCTN Identifier: ISRCTN22219089. Date applied 29 July 2022.
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Project description:The rapid development of the economy has promoted the growth of freight transportation. The truck service areas on expressways, as the main places for truck drivers to rest, play an important role in ensuring the driving safety of trucks. If these service areas are constructed densely or provide a plentiful supply of parking areas, they are costly to construct. However, if the distance between two adjacent truck service areas is very large or the number of truck parking spaces in service areas is small, the supply will fail to meet the parking needs of truck drivers. In this situation, the continuous working time of truck drivers will be longer, and this is likely to cause driver fatigue and even traffic accidents. To address these issues, this paper established a non-linear optimization model for truck service area planning of expressways to optimize truck driving safety. An improved genetic algorithm is proposed to solve the model. A case study of a 215.5-kilometers-length section of the Guang-Kun expressway in China was used to demonstrate the effectiveness of the model and algorithm. As validated by this specific case, the proposed model and solution algorithm can provide an optimal plan for the layout of truck service areas that meet the parking needs of truck drivers while minimizing the service loss rate. The research results of this paper can contribute to the construction of truck service areas and the parking management of trucks on expressways.
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Project description:Next-generation sequencing has become an essential tool in molecular biology that has been successfully applied to a broad variety of experimental approaches. While several platforms for next-generation sequencing exist, the most commonly used approach is sequencing-by-synthesis, implemented on Illumina's Genome Analyzer II (GAII) and HiSeq2000 systems. A key constraint of these sequencers is the need to run multiple lanes of samples with identical parameters as part of a single flowcell. Here, we present a series of modifications to the Illumina Genome Analyzer II, along with a script generating tool, that allow users to run the GAII in a lane-by-lane manner. Any number of lanes can be run at one time. Repeated use of the same flowcell on multiple sequencing runs does not appreciably reduce the intensity, cluster density, or accuracy of the run. These modifications will enable smaller-scale experiments with unusual design parameters to be run routinely on the GAII.
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Project description:Extreme climatic events are growing more severe and frequent, calling into question how prepared our infrastructure is to deal with these changes. Current infrastructure design is primarily based on precipitation Intensity-Duration-Frequency (IDF) curves with the so-called stationary assumption, meaning extremes will not vary significantly over time. However, climate change is expected to alter climatic extremes, a concept termed nonstationarity. Here we show that given nonstationarity, current IDF curves can substantially underestimate precipitation extremes and thus, they may not be suitable for infrastructure design in a changing climate. We show that a stationary climate assumption may lead to underestimation of extreme precipitation by as much as 60%, which increases the flood risk and failure risk in infrastructure systems. We then present a generalized framework for estimating nonstationary IDF curves and their uncertainties using Bayesian inference. The methodology can potentially be integrated in future design concepts.
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Project description:ImportanceComplete (R0) resection is the dominant prognostic factor for survival across solid tumor types. Achieving adequate tumor clearance with appropriate margins is particularly difficult in nonpalpable tumors or in situ disease. Previous methods to address this problem have proven time consumptive, impractical, or ineffective.ObjectiveTo assess the capability of intraoperative molecular imaging (IMI), a novel technology using a fluorescent tracer targeted to malignant cells, to localize visually occult, nonpalpable tumors and quantify margin distances during resection.Design, setting, and participantsThis nonrandomized open-label trial of IMI using a folate receptor-targeted fluorescent tracer enrolled patients between May 2017 and June 2020 at a single referral center. Eligible patients included those with a small (T1) lung lesion suspicious for malignant neoplasms and with radiographic features suggestive of a nonpalpable lesion.InterventionsPatients were preoperatively infused with a folate receptor-targeted near-infrared tracer. Intraoperatively, surgeons used thoracoscopic visualization and palpation to identify lesions. IMI was performed to detect the lesion in situ, and lesions were imaged ex vivo. Margins were assessed by IMI before comparison with those reported on final histopathologic analysis.Main outcomes and measuresThe main outcomes were whether IMI could (1) localize nonpalpable lung lesions in situ and (2) quantify margin distance with comparison with final pathology as the criterion standard. Patient demographic information and lesion characteristics were prospectively recorded.ResultsOf 40 patients, 26 (65%) were female, and the median (interquartile range) age was 66.5 (62-72) years. Conventional surgical methods localized 22 of 40 lesions (55%), while IMI localized 36 of 40 (90%). Of 18 nonpalpable lesions, 15 (83.3%) were identified by IMI. Both palpable and nonpalpable lesions demonstrated mean signal-to-background ratio more than 2. An IMI margin was able to be calculated for 39 of 40 patients (95%). IMI margins were nearly identical to margins reported on final pathology (R2 = 0.9593), with median (interquartile range) difference of 1.3 (0.7-2.0) mm. IMI detected 2 margins in nonpalpable tumors that were clinically unacceptable and would have had a high probability of recurrence.Conclusions and relevanceTo our knowledge, this study presents the first clinical use of IMI for nonpalpable tumors and provides proof of principle for the utility of IMI across the field of surgical oncology in identifying occult disease and tumor-positive margins.
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Project description:To develop a method to quantify the margin sharpness of lesions on CT and to evaluate it in simulations and CT scans of liver and lung lesions.The authors computed two attributes of margin sharpness: the intensity difference between a lesion and its surroundings, and the sharpness of the intensity transition across the lesion boundary. These two attributes were extracted from sigmoid curves fitted along lines automatically drawn orthogonal to the lesion margin. The authors then represented the margin characteristics for each lesion by a feature vector containing histograms of these parameters. The authors created 100 simulated CT scans of lesions over a range of intensity difference and margin sharpness, and used the concordance correlation between the known parameter and the corresponding computed feature as a measure of performance. The authors also evaluated their method in 79 liver lesions (44 patients: 23 M, 21 F, mean age 61) and 58 lung nodules (57 patients: 24 M, 33 F, mean age 66). The methodology presented takes into consideration the boundary of the liver and lung during feature extraction in clinical images to ensure that the margin feature do not get contaminated by anatomy other than the normal organ surrounding the lesions. For evaluation in these clinical images, the authors created subjective independent reference standards for pairwise margin sharpness similarity in the liver and lung cohorts, and compared rank orderings of similarity used using our sharpness feature to that expected from the reference standards using mean normalized discounted cumulative gain (NDCG) over all query images. In addition, the authors compared their proposed feature with two existing techniques for lesion margin characterization using the simulated and clinical datasets. The authors also evaluated the robustness of their features against variations in delineation of the lesion margin by simulating five types of deformations of the lesion margin. Equivalence across deformations was assessed using Schuirmann's paired two one-sided tests.In simulated images, the concordance correlation between measured gradient and actual gradient was 0.994. The mean (s.d.) and standard deviation NDCG score for the retrieval of K images, K = 5, 10, and 15, were 84% (8%), 85% (7%), and 85% (7%) for CT images containing liver lesions, and 82% (7%), 84% (6%), and 85% (4%) for CT images containing lung nodules, respectively. The authors' proposed method outperformed the two existing margin characterization methods in average NDCG scores over all K, by 1.5% and 3% in datasets containing liver lesion, and 4.5% and 5% in datasets containing lung nodules. Equivalence testing showed that the authors' feature is more robust across all margin deformations (p < 0.05) than the two existing methods for margin sharpness characterization in both simulated and clinical datasets.The authors have described a new image feature to quantify the margin sharpness of lesions. It has strong correlation with known margin sharpness in simulated images and in clinical CT images containing liver lesions and lung nodules. This image feature has excellent performance for retrieving images with similar margin characteristics, suggesting potential utility, in conjunction with other lesion features, for content-based image retrieval applications.
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Project description:The thermal limit of ectotherms provides an estimate of vulnerability to climate change. It differs between contrasting microhabitats, consistent with thermal ecology predictions that a species' temperature sensitivity matches the microclimate it experiences. However, observed thermal limits may differ between ectotherms from the same environment, challenging this theory. We resolved this apparent paradox by showing that ectotherm activity generates microclimatic deviations large enough to account for differences in thermal limits between species from the same microhabitat. We studied upper lethal temperature, effect of feeding mode on plant gas exchange, and temperature of attacked leaves in a community of six arthropod species feeding on apple leaves. Thermal limits differed by up to 8 °C among the species. Species that caused an increase in leaf transpiration (+182%), thus cooling the leaf, had a lower thermal limit than those that decreased leaf transpiration (-75%), causing the leaf to warm up. Therefore, cryptic microclimatic variations at the scale of a single leaf determine the thermal limit in this community of herbivores. We investigated the consequences of these changes in plant transpiration induced by plant-insect feedbacks for species vulnerability to thermal extremes. Warming tolerance was similar between species, at ±2 °C, providing little margin for resisting increasingly frequent and intense heat waves. The thermal safety margin (the difference between thermal limit and temperature) was greatly overestimated when air temperature or intact leaf temperature was erroneously used. We conclude that feedback processes define the vulnerability of species in the phyllosphere, and beyond, to thermal extremes.
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