Measuring high-speed train delay severity: Static and dynamic analysis.

This paper focuses on optimizing the management of delayed trains in operational scenarios by scientifically categorizing train delay levels. It employs static and dynamic models grounded in real-world train delay data from high-speed railways. This classification aids dispatchers in swiftly identifying and predicting delay extents, thus enhancing mitigation strategies' efficiency. Key indicators, encompassing initial delay duration, station impacts, average station delay, delayed trains' cascading effects, and average delay per affected train, inform the classification. Applying the K-means clustering algorithm to standardized delay indicators yields an optimized categorization of delayed trains into four levels, reflecting varying risk levels. This static classification offers a comprehensive overview of delay dynamics. Furthermore, utilizing Markov chains, the study delves into sequential dynamic analyses, accounting for China's railway context and specifically addressing fluctuations during the Spring Festival travel rush. This research, combining static and dynamic approaches, provides valuable insights for bolstering railway operational efficiency and resilience amidst diverse delay scenarios.

Discovery and description of novel phage genomes from urban microbiomes sampled by the MetaSUB consortium.

Bacteriophages are recognized as the most abundant members of microbiomes and have therefore a profound impact on microbial communities through the interactions with their bacterial hosts. The International Metagenomics and Metadesign of Subways and Urban Biomes Consortium (MetaSUB) has sampled mass-transit systems in 60 cities over 3 years using metagenomics, throwing light into these hitherto largely unexplored urban environments. MetaSUB focused primarily on the bacterial community. In this work, we explored MetaSUB metagenomic data in order to recover and analyze bacteriophage genomes. We recovered and analyzed 1714 phage genomes with size at least 40 kbp, from the class Caudoviricetes, the vast majority of which (80%) are novel. The recovered genomes were predicted to belong to temperate (69%) and lytic (31%) phages. Thirty-three of these genomes have more than 200 kbp, and one of them reaches 572 kbp, placing it among the largest phage genomes ever found. In general, the phages tended to be site-specific or nearly so, but 194 genomes could be identified in every city from which phage genomes were retrieved. We predicted hosts for 48% of the phages and observed general agreement between phage abundance and the respective bacterial host abundance, which include the most common nosocomial multidrug-resistant pathogens. A small fraction of the phage genomes are carriers of antibiotic resistance genes, and such genomes tended to be particularly abundant in the sites where they were found. We also detected CRISPR-Cas systems in five phage genomes. This study expands the previously reported MetaSUB results and is a contribution to the knowledge about phage diversity, global distribution, and phage genome content.

Characteristics and circumstances of rail suicides in England 2019-2021: A cluster analysis and autopsy study.

BACKGROUND: Around 4 % of all suicide deaths in Great Britain occur on the railways. This exploratory study was designed to increase understanding of the individuals that take their lives in this way, and the circumstances of their death. METHOD: Data were obtained from fatality investigation files compiled by the British Transport Police (BTP) relating to suspected suicides on the mainline railway in England from April 2019 to March 2021. Cluster analysis was carried out to identify grouped associations of characteristics and circumstances relating to rail suicide. RESULTS: A total of 436 files were analysed, representing 93 % of all suspected railway suicides during this period. Cluster analysis identified four groups of almost equal size, distinguished principally by age, living arrangements, employment status and location of death. The study is novel in the way it integrates individual characteristics and circumstances of death. The identified clusters may provide a multidimensional way of conceptualising suicide risk that could inform more targeted interventions at rail locations. LIMITATIONS: A high proportion of missing data means that the findings need to be interpreted with caution. It also restricted the multivariate analysis to those categories of information for which sufficient information was available. CONCLUSION: The characteristics and circumstances of suicide deaths on the railways are complex and multifaceted. The typology identified in this study may help to target preventative strategies prior to the incident as well as at different location types.

Electromagnetic exposure analysis of the subway passenger under the civil communication system radiation.

In order to assess the electromagnetic exposure safety of passengers under the civil communication system of the subway, the radio-frequency (RF) electromagnetic environment of subway carriage is established by using COMSOL Multiphysics software, it includes a 1-1/4 " leaky coaxial cable (LCX1) and a 1-5/8" leaky coaxial cable (LCX2), which are designed to be the exposure sources, and twelve passengers at different position. The electromagnetic environment model has been verified through field measurement. The exposure dose distribution of twelve passengers is compared and analyzed, when LCX1 and LCX2 works respectively. The simulated results show that, to compare with LCX2, the electromagnetic dose absorbed by the passengers is reduced by 9.19% and 22.50% at 2100 MHz and 2600 MHz respectively. The specific absorption rate (SAR) of passengers obtains the maximum value of 1.91×10-4 W/Kg and the temperature rise to 0.214 K when the LCX1 works at 3400 MHz. By comparing with the public exposure limitation of the International Commission of Non-Ionizing Radiation Protection (ICNIRP), it demonstrates the electromagnetic exposure safety of the passengers under the civil communication system. More importantly, the proposed LCX1 not only could add the 5G signal cover but also lower the SAR absorbed by the passengers, which indicates that the public electromagnetic exposure dose could be reduced by adjusting the radiation performances of exposure source, which provide a new way for electromagnetic protecting.

The composition of the bacterial communities collected from the PM10 samples inside the Seoul subway and railway station.

Health implications of indoor air quality (IAQ) have drawn more attention since the COVID epidemic. There are many different kinds of studies done on how IAQ affects people's well-being. There hasn't been much research that looks at the microbiological composition of the aerosol in subway transit systems. In this work, for the first time, we examined the aerosol bacterial abundance, diversity, and composition in the microbiome of the Seoul subway and train stations using DNA isolated from the PM10 samples from each station (three subway and two KTX stations). The average PM10 mass concentration collected on the respective platform was 41.862 µg/m3, with the highest average value of 45.95 µg/m3 and the lowest of 39.25 µg/m3. The bacterial microbiomes mainly constituted bacterial species of soil and environmental origin (e.g., Acinetobacter, Brevundimonas, Lysinibacillus, Clostridiodes) with fewer from human sources (Flaviflexus, Staphylococcus). This study highlights the relationship between microbiome diversity and PM10 mass concentration contributed by outdoor air and commuters in South Korea's subway and train stations. This study gives insights into the microbiome diversity, the source, and the susceptibility of public transports in disease spreading.

A pilot study evaluating the preventive effects of platform-end lengthwise fencing on trespassing, person struck by train and traffic delays.

BACKGROUND: Trespassing at train tracks and "person under train" (PUT) incidents are serious health, societal and transportation concerns. There is a need for developing different measures to prevent these events. Here, we hypothesized that platform-end lengthwise fences (PLF) reduce trespassing, the number of PUT incidents (suicides and accidents), and train traffic delays. METHOD: PLFs were installed as the intervention at one station in Stockholm in 2020. The number of trespassers detected using CCTV-cameras was compared before and after at the intervention station over a total period of 29 months (using incidence rate ratio, IRR). The reduction in the number of PUT (over 20 years) and train traffic delays (over 9 years) was also investigated by IRR, and by using three control groups. RESULTS: After installation of PLF there was a significant ∼90% reduction in trespasses (IRR = 0.10, 95%CI 0.04-0.23; one-sided exact p < 0.0001). No PUT incident occurred at the intervention station after the installation, compared to 1.11 per year before installation (IRR = 0.32, 95%CI 0-1.82; one-sided exact p = 0.1216). There was a significant reduction in delay minutes post installation compared to before the installation (Mann Whitney U = 0, upper one-sided exact p = 0.0357). The effect of the PLF was also observable in comparison to the three control groups, suggesting that the preventive effect was not due to wider societal events affecting all stations. CONCLUSION: PLF had a large effect on reducing the number of trespasses and the number of delay minutes due to trespasses and PUT incidents. PLF may also have an effect of reducing PUT incidents. PRACTICAL APPLICATIONS: PLF is deemed to be relatively easy and cheap to install and thus scalable (as compared to full barriers, e.g., platform screen doors) and may be considered at platform-ends having an exit, provided there is enough space to install them.

Prediction model of land surface settlement deformation based on improved LSTM method: CEEMDAN-ICA-AM-LSTM (CIAL) prediction model.

The uneven settlement of the surrounding ground surface caused by subway construction is not only complicated but also liable to cause casualties and property damage, so a timely understanding of the ground settlement deformation in the subway excavation and its prediction in real time is of practical significance. Due to the complex nonlinear relationship between subway settlement deformation and numerous influencing factors, as well as the existence of a time lag effect and the influence of various factors in the process, the prediction performance and accuracy of traditional prediction methods can no longer meet industry demands. Therefore, this paper proposes a surface settlement deformation prediction model by combining noise reduction and attention mechanism (AM) with the long short-term memory (LSTM). The complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and independent component analysis (ICA) methods are used to denoise the input original data and then combined with AM and LSTM for prediction to obtain the CEEMDAN-ICA-AM-LSTM (CIAL) prediction model. Taking the settlement monitoring data of the construction site of Urumqi Rail Transit Line 1 as an example for analysis reveals that the model in this paper has better effectiveness and applicability in the prediction of surface settlement deformation than multiple prediction models. The RMSE, MAE, and MAPE values of the CIAL model are 0.041, 0.033 and 0.384%; R2 is the largest; the prediction effect is the best; the prediction accuracy is the highest; and its reliability is good. The new method is effective for monitoring the safety of surface settlement deformation.

Metal and oxidative potential exposure through particle inhalation and oxidative stress biomarkers: a 2-week pilot prospective study among Parisian subway workers.

OBJECTIVE: In this pilot study on subway workers, we explored the relationships between particle exposure and oxidative stress biomarkers in exhaled breath condensate (EBC) and urine to identify the most relevant biomarkers for a large-scale study in this field. METHODS: We constructed a comprehensive occupational exposure assessment among subway workers in three distinct jobs over 10 working days, measuring daily concentrations of particulate matter (PM), their metal content and oxidative potential (OP). Individual pre- and post-shift EBC and urine samples were collected daily. Three oxidative stress biomarkers were measured in these matrices: malondialdehyde (MDA), 8-hydroxy-2'deoxyguanosine (8-OHdG) and 8-isoprostane. The association between each effect biomarker and exposure variables was estimated by multivariable multilevel mixed-effect models with and without lag times. RESULTS: The OP was positively associated with Fe and Mn, but not associated with any effect biomarkers. Concentration changes of effect biomarkers in EBC and urine were associated with transition metals in PM (Cu and Zn) and furthermore with specific metals in EBC (Ba, Co, Cr and Mn) and in urine (Ba, Cu, Co, Mo, Ni, Ti and Zn). The direction of these associations was both metal- and time-dependent. Associations between Cu or Zn and MDAEBC generally reached statistical significance after a delayed time of 12 or 24 h after exposure. Changes in metal concentrations in EBC and urine were associated with MDA and 8-OHdG concentrations the same day. CONCLUSION: Associations between MDA in both EBC and urine gave opposite response for subway particles containing Zn versus Cu. This diverting Zn and Cu pattern was also observed for 8-OHdG and urinary concentrations of these two metals. Overall, MDA and 8-OHdG responses were sensitive for same-day metal exposures in both matrices. We recommend MDA and 8-OHdG in large field studies to account for oxidative stress originating from metals in inhaled particulate matter.

Acoustic performance evaluation of railway boundary walls using a computational fluid dynamics-based simulation approach.

Railway noise has become a significant concern for trackside residents due to increased volume of high-speed passenger and freight train traffic. To address this, active measures, such as reducing noise at the source, and passive measures, such as installing noise barriers along the transmission path, are widely being used. In urban areas, railway boundary walls are constructed to prevent encroachments of railway lands and to avoid pedestrian trespassing of railway tracks. This study aims to evaluate the effectiveness of such a boundary wall for reducing noise and proposes an improved alternative through computational fluid dynamics (CFD) simulations. Various noise barriers with different geometry, shape, and surface materials were simulated and validated with the field conditions based on a rectangular wall of height 2.75 m. Noise attenuation was evaluated by measuring railway noise spectra at different positions, including 0.5 m in front and behind the barrier and at the facade of the residential area. The insertion loss based on field measurements for a rectangular barrier of height 2.75 m was observed to be 5.2 dBA. The simulation results indicated a positive correlation between barrier height and insertion loss, with a maximum attenuation of 17 dBA achieved with a barrier of height 6 m. The most effective noise barrier for reducing railway noise was a T-shaped barrier with a height of 6 m and a projection length of 2 m, with an insertion loss of 22 dBA. This study recommends constructing the barrier with soft materials on its surface to reflect and absorb sound waves effectively. These findings have potential implications for urban planners and policymakers in designing effective noise barriers in residential areas near railway lines.

Sociodemographic and psychosocial risk factors of railway suicide a mixed-methods study combining data of all suicide decedents in the Netherlands with data from a psychosocial autopsy study.

BACKGROUND: Railway suicide has profound implications for the victims and their family, and affects train drivers, railway personnel, emergency services and witnesses. To inform a multilevel prevention strategy, more knowledge is required about psychosocial and precipitating risk factors of railway suicide. METHODS: Data from Statistics Netherlands of all suicides between 2017 and 2021 (n = 9.241) of whom 986 died by railway suicide and interview data from a psychosocial autopsy of railway suicide decedents (n = 39) were integrated. We performed logistic regression analyses to identify sociodemographic predictors of railway suicide compared to other methods of suicide. The Constant Comparative Method was subsequently employed on interview data from the psychosocial autopsy to identify patterns in psychosocial risk factors for railway suicide. RESULTS: The strongest predictors of railway suicide compared to other suicide methods were young age (< 30 years old), native Dutch, a high educational level, living in a multi-person household (especially living with parents or in an institution), living in a rural area and a high annual household income of > 150.000 euros. Several subgroups emerged in the psychosocial autopsy interviews, which specifically reflect populations at risk of railway suicide. These subgroups were [1] young adult males with autism spectrum disorder who strived for more autonomy and an independent life, [2] young adult females with persistent suicidal thoughts and behaviours, [3] middle-aged males with a persistent mood disorder who lived with family and who faced stressors proximal to the suicide in personal and professional settings, [4] male out-of-the-blue suicides and [5] persons with psychotic symptoms and a rapid deterioration. CONCLUSIONS: based on our findings we propose and discuss several recommendations to prevent railway suicide. We must continue to invest in a safe railway environment by training personnel and installing barriers. Additionally, we should adopt prevention strategies that align the needs of subgroups at increased risk, including young females who have attempted other methods of suicide and young males with autism spectrum disorder. Future research should determine the cost-effectiveness and feasibility of low-maintenance, automated interventions near crossings and psychiatric facilities.

Safety risk assessment of subway shield construction under-crossing a river using CFA and FER.

Numerous subway projects are planned by China's city governments, and more subways can hardly avoid under-crossing rivers. While often being located in complex natural and social environments, subway shield construction under-crossing a river (SSCUR) is more susceptible to safety accidents, causing substantial casualties, and monetary losses. Therefore, there is an urgent need to investigate safety risks during SSCUR. The paper identified the safety risks during SSCUR by using a literature review and experts' evaluation, proposed a new safety risk assessment model by integrating confirmatory factor analysis (CFA) and fuzzy evidence reasoning (FER), and then selected a project to validate the feasibility of the proposed model. Research results show that (a) a safety risk list of SSCUR was identified, including 5 first-level safety risks and 38 second-level safety risks; (b) the proposed safety risk assessment model can be used to assess the safety risk of SSCUR; (c) safety inspection, safety organization and duty, quicksand layer, and high-pressure phreatic water were the high-level risks, and the onsite total safety risk was at the medium level; (d) management-type safety risks, environment-type safety risks, and personnel-type safety risks have higher expected utility values, and manager-type safety risks were expected have higher risk-utility values when compared to worker-type safety risks. The research can enrich the theoretical knowledge of SSCUR safety risk assessment and provide references to safety managers for conducting scientific and effective safety management on the construction site when a subway crosses under a river.

Data-driven mathematical simulation analysis of emergency evacuation time in smart station's operations management.

This research establishes an emergency evacuation time model specifically designed for subway stations with complex structures. The model takes into account multiple factors, including passenger flow rate, subway facility parameters, and crowd density, to accurately assess evacuation times. It considers the impact of horizontal walking distance, flow rate, subway train size, and stair parameters on the overall evacuation process. By identifying bottleneck points such as gates, car doors, and stairs, the model facilitates the evaluation of evacuation capacity and the formulation of effective evacuation plans, particularly in multiline subway transfer stations. The good consistency is achieved between the calculated evacuation time and simulated results using the Pathfinder software (with the relative error of 5.4%). To address urban traffic congestion and enhance subway station safety, the study recommends implemented measures for emergency diversion and passenger flow control. Additionally, the research presents characteristic mathematical models for various evacuation routes by considering the structural and temporal characteristics of metro systems. These models provide valuable guidance for conducting large-scale passenger evacuation simulations in complex environments. Future research can further enhance the model by incorporating psychological factors, evacuation signage, and strategies for vulnerable populations. Overall, this study contributes to a better understanding of evacuation dynamics and provides practical insights to improve safety and efficiency in subway systems.

Interplay of xenobiotic-degrading and antibiotic-resistant microorganisms among the microbiome found in the air, handrail, and floor of the subway station.

Investigating the quality of the subway environment, especially regarding antibiotic resistance genes (ARGs) and xenobiotics, conveys ecological and health impacts. In this study, compositions and relations of microorganisms harboring ARGs and xenobiotic degradation and metabolism genes (XDGs) in the Sukhumvit subway station (MRT-SKV) in Bangkok was assessed by analyzing the taxonomic and genetic diversity of the microbiome in the air and on the surfaces of floor and handrail. The major bacteria in the MRT-SKV (including Moraxella, which was abundant in the bioaerosol and handrail samples, and Staphylococcus, which was abundant in the bioaerosol samples) were found to contain both ARGs and XDGs. The co-abundance correlation network revealed notable relationships among bacteria harboring antibiotic resistance genes (ARGs) and xenobiotic degradation genes (XDGs). Significant associations were observed between ARGs linked to glycopeptide and fluoroquinolone resistance and genes associated with benzoate, styrene, and atrazine degradation pathways, as well as between ARGs related to cephamycin, cephalosporin, and MLS resistance and XDGs associated with the cytochrome P450-dependent drug metabolism pathway. These correlations suggested that selective pressure exerted by certain xenobiotics and antibiotics can simultaneously affect both ARGs and XDGs in the environment and should favor correlations and co-survival among ARG- and XDG-containing bacteria in the environments. The correlations may occur via shared mechanisms of resistance to both xenobiotics and antibiotics. Finally, different correlation pairs were seen in different niches (air, handrail, floor) of the subway environment or different geolocations. Thus, the relationship between ARG and XDG pairs most likely depends on the unique characteristics of the niches and on the prominent types of xenobiotics and antibiotics in the subway environment. The results indicated that interactions and connections between microbial communities can impact how they function. These microorganisms can have profound effects on accumulation of xenobiotics and ARGs in the MRT-SKV.

Rescheduling trains by crossover tracks to promote service quality of urban rail transit under partial blockages.

This study focuses on the rescheduling problem with disruptions that cause partial blockages in the urban rail transit (URT), contributing to extending the relative train rescheduling studies. The alternative driving measure (ADM), which could be regarded as one train rerouting measure, is used to skip the blocked section, and a mixed-integer nonlinear programming (MINLP) model is built based on it. Time-varying passenger flow as well as the turnaround process of rolling stocks is taken into consideration. To solve the model, a customized genetic algorithm is used to quickly generate high-quality solutions. Real-world data is studied and sensitivity analyses are taken to verify the feasibility and advantage of ADM. The results validate the proposed model and algorithm, as well as confirm that ADM shows significantly better performance than the practical operation measure in promoting passenger service quality of URT under partial blockage.

Susceptibility and exposure risk to airborne aerosols in intra-urban microclimate: Evidence from subway system of mega-cities.

The health of intra-urban population in modern megacities relies largely on the biosafety within the microclimate of subway system, which can be vulnerable to epidemical challenges brought by virus-laden bioaerosols under varying factors. The literature has yet to address the association between the exposure risks to infectious pathogens and the dynamic changes of boundary conditions in this densely populated microclimate. This study aims at characterizing the bioaerosol dispersion, evaluating the exposure risks under various train arrival scenarios and hazard releasing positions in a real-world double-decker subway station. The results provide the evidence for the dominating airflow pattern, bioaerosols dispersion behaviors, exposure risk, and evacuation guidance in a representative microclimate of mega-cities. The tunnel effects of nearby pedestrian passageways are found to be dominating the airflow pattern, leading to the discharging of airborne bioaerosols. At least 60 % increasing of discharging rate of bioaerosol is attributed to the arrival of one or two trains at the subway platform compared with the scenario with no train arriving. Results from risk assessment with improved Wells-Riley model estimate 57.62 % of maximum infectivity probability with no train arriving. Large areas near the source at the platform floor still cannot be considered safe within 20 min. For the other two scenarios where trains arrive at the platform, the maximum probability of infection is below 5 %. Moreover, the majority of train carriages can be regarded as safe zones, as the ventilation across the screen door are mostly directed towards the platform. Additionally, releasing the bioaerosols at the platform floor poses the most severe threats to human health, and the corresponding evacuation strategies are suggested. These findings offer practical guidance for the design of the intra-urban microclimate, reinforcing the need for exposure reduction device or contingency plans, and providing potential evacuation strategy towards improved health outcomes.

Chinese Railroad Workers, the Transcontinental Railroad, and the Indispensability of Immigration to America.

Asian migration to America began with Chinese railroad workers on the transcontinental railroad (1862-1869). Their labor saved the foundering Central Pacific Railroad, challenged by building a rail line through the Sierra Nevada. By mid-1864 only 50 miles of track had been laid, grueling work that dissuaded its white workforce from going any further. To save the railroad 50 Cantonese workers were hired in early 1864 from neighboring mines to lay rail through forests, canyons, and granite mountains. High explosives, rockslides, cave-ins, and winter avalanches were constant dangers. The trial worked so well that thousands of Chinese joined the effort, many from the rural districts surrounding Guangzhou (Canton). The wages, less than half of that paid to white workers, were beyond the imaginations of subsistence farmers escaping abject poverty, plague, and famine. A good proportion of their earnings were remitted to families back home. As many as 20,000 may have worked on the railway. The death toll was staggering, estimated in the thousands. After Promontory Summit in 1869, Chinese were in great demand, building scores of rail lines throughout the country and Canada. Just 13 years later rising anti-Asian sentiment led to the passage of the Chinese Restriction Act of 1882 that for the first time barred a racial group from American shores. But they opened America to Asian immigrants that includes today's Asian surgical community, which owes its present-day success to the hardworking forebears that created a global country with ribbons of steel rail.

Single-cell transcriptomics reveals the pulmonary inflammation induced by inhalation of subway fine particles.

People generally take the subway and inevitably inhale the fine particles (PM2.5) on subway platforms. This study revealed whether and how subway PM2.5 causes lung inflammation. Herein, the pulmonary inflammatory response to subway PM2.5 was observed in mice, manifesting as the inflammatory cells infiltration and collagen deposition in tissue, inflammatory cytokine enhancement in bronchoalveolar lavage fluid and Toll-like receptors signal pathway activation in the lungs. Furthermore, single-cell RNA sequencing unearthed subway PM2.5-induced cell-specific responses in the lungs. Twenty immune subsets were identified by the molecular and functional properties. Specific cell populations of CD4+ T and γδ T cells were regarded as the predominant sources of pneumonitis induced by subway PM2.5. Moreover, we demonstrated that the lung inflammatory injury was significantly more attenuated in Rag1-/- mice lacking functional T cells and B cells than that in wild type mice. We proved the slight inflammation of lung tissue in Rag1-/- mice may be dependent on monocytes and neutrophils by activation of the intracellular molecular network. This is the first experimental study on subway PM2.5 causing pulmonary inflammatory damage. It will set an alarm for people who usually travel by subway and efficient measures to reduce PM2.5 should be developed in subway stations.

Long-term exposure to PM10 and respiratory health among Parisian subway workers.

Exposure to ambient PM10 may increase the risk of chronic obstructive pulmonary disease (COPD) and lung function decline. We evaluated the long-term exposure to PM10 and its relationship with COPD prevalence and lung function in Parisian subway workers. Participants were randomly selected from a 15,000-subway worker cohort. Individual annual external exposure to PM10 (ePM10) was estimated using a company-specific job-exposure-matrix based on PM10 measurements conducted between 2004 and 2019 in the Parisian subway network. Mean annual inhaled PM10 exposure (iPM10) was modeled as function of ePM10 exposure, inhalation rate, and filtration efficiency of the respiratory protection used. COPD diagnosis was performed in March-May 2021 based on post-bronchodilator spirometry. The relationship between iPM10 and outcomes was assessed using logistic and linear regression models, adjusted for exposure duration and potential confounders. Amongst 254 participants with complete data, 17 were diagnosed as COPD. The mean employment duration was 23.2 ± 7.3years, with annual mean ePM10 of 71.8 ± 33.7 µg/m3 and iPM10 of 0.59 ± 0.27 µg/shift, respectively. A positive but statistically non-significant association was found for COPD prevalence with iPM10 (OR = 1.034, 95%-CI = 0.781; 1.369, per 100 ng/shift) and ePM10 (OR = 1.029, 95%-CI = 0.879; 1.207, per 10 µg/m3). No decline in lung function was associated with PM10 exposure. However, forced expiratory volume during the first second and forced vital capacity lower than normal were positively associated with exposure duration (OR = 1.125, 95%-CI = 1.004; 1.260 and OR = 1.171, 95%-CI = 0.989; 1.386 per year, respectively). Current smoking was strongly associated with COPD prevalence (OR = 6.85, 95%-CI = 1.87; 25.10) and most lung function parameters. This is the first study assessing the relationship between long-term exposure to subway PM10 and respiratory health in subway workers. The risk estimates related with subway PM10 exposure are compatible with those related to outdoor PM10 exposure in the large recent studies. Large cohorts of subway workers are necessary to confirm these findings.

Evaluating a Human Detection Model in a Behaviour Analysis Pipeline for Suicide Prevention.

Suicides in public places, such as railways, can have a significant impact on bystanders, railway staff, first responders and the surrounding communities. Behaviours prior to a suicide attempt have been identified, that could potentially be detected automatically. As a first step, the algorithm is required to accurately identify individuals exhibiting these behaviours in different settings. Our study analyses a human detection model focussing on pedestrian detection at railway stations as one component of a broader project to detect pre-suicidal behaviours. Closed-circuit television footage from two stations collected for the same 24-hour period were manually analysed to obtain parameters (true positives, false positives, and false negatives) which were then used to compute performance measures (sensitivity, precision, and F1 score). The model performed differently in both stations with a sensitivity of 0.73 and F1 score of 0.84 in Station A and a sensitivity of 0.48 and F1 score of 0.65 in Station B. Root causes of false negatives identified include differing body postures and occlusion. Although the model was adequate, its performance is dependent on the view captured by the cameras in stations. Collectively, these findings can be used to improve the model's performance.Clinical Relevance-Detecting behaviours prior to a suicide attempt offers a critical period for intervention by bystanders or first responders, potentially interrupting the attempt. This offers the potential to directly reduce suicide attempts, as well as reduce third-party exposure to these traumatic events.