Enhancing thermal comfort prediction in high-speed trains through machine learning and physiological signals integration.

Heating, Ventilation, and Air Conditioning (HVAC) systems in high-speed trains (HST) are responsible for consuming approximately 70% of non-operational energy sources, yet they frequently fail to ensure provide adequate thermal comfort for the majority of passengers. Recent advancements in portable wearable sensors have opened up new possibilities for real-time detection of occupant thermal comfort status and timely feedback to the HVAC system. However, since occupant thermal comfort is subjective and cannot be directly measured, it is generally inferred from thermal environment parameters or physiological signals of occupants within the HST compartment. This paper presents a field test conducted to assess the thermal comfort of occupants within HST compartments. Leveraging physiological signals, including skin temperature, galvanic skin reaction, heart rate, and ambient temperature, we propose a Predicted Thermal Comfort (PTC) model for HST cabin occupants and establish an intelligent regulation model for the HVAC system. Nine input factors, comprising physiological signals, individual physiological characteristics, compartment seating, and ambient temperature, were formulated for the PTS model. In order to obtain an efficient and accurate PTC prediction model for HST cabin occupants, we compared the accuracy of different subsets of features trained by Machine Learning (ML) models of Random Forest, Decision Tree, Vector Machine and K-neighbourhood. We divided all the predicted feature values into four subsets, and did hyperparameter optimisation for each ML model. The HST compartment occupant PTC prediction model trained by Random Forest model obtained 90.4% Accuracy (F1 macro = 0.889). Subsequent sensitivity analyses of the best predictive models were then performed using SHapley Additive explanation (SHAP) and data-based sensitivity analysis (DSA) methods. The development of a more accurate and operationally efficient thermal comfort prediction model for HST occupants allows for precise and detailed feedback to the HVAC system. Consequently, the HVAC system can make the most appropriate and effective air supply adjustments, leading to improved satisfaction rates for HST occupant thermal comfort and the avoidance of energy wastage caused by inaccurate and untimely predictive feedback.

[A review on electroencephalogram based channel selection].

The electroencephalogram (EEG) signal is the key signal carrier of the brain-computer interface (BCI) system. The EEG data collected by the whole-brain electrode arrangement is conducive to obtaining higher information representation. Personalized electrode layout, while ensuring the accuracy of EEG signal decoding, can also shorten the calibration time of BCI and has become an important research direction. This paper reviews the EEG signal channel selection methods in recent years, conducts a comparative analysis of the combined effects of different channel selection methods and different classification algorithms, obtains the commonly used channel combinations in motor imagery, P300 and other paradigms in BCI, and explains the application scenarios of the channel selection method in different paradigms are discussed, in order to provide stronger support for a more accurate and portable BCI system.

Thermal sensation prediction model for high-speed train occupants based on skin temperatures and skin wettedness.

Passenger thermal comfort in high-speed train (HST) carriages presents unique challenges due to factors such as extensive operational areas, longer travel durations, larger spaces, and higher passenger capacities. This study aims to propose a new prediction model to better understand and address thermal comfort in HST carriages. The proposed prediction model incorporates skin wettedness, vertical skin temperature difference (ΔTd), and skin temperature as parameters to predict the thermal sensation vote (TSV) of HST passengers. The experiments were conducted with 65 subjects, evenly distributed throughout the HST compartment. Thermal environmental conditions and physiological signals were measured to capture the subjects' thermal responses. The study also investigated regional and overall thermal sensations experienced by the subjects. Results revealed significant regional differences in skin temperature between upper and lower body parts. By analyzing data from 45 subjects, We analyzed the effect of 25 variables on TSV by partial least squares (PLS), from which we singled out 3 key factors. And the optimal multiple regression equation was derived to predict the TSV of HST occupants. Validation with an additional 20 subjects demonstrated a strong linear correlation (0.965) between the actual TSV and the predicted values, confirming the feasibility and accuracy of the developed prediction model. By integrating skin wettedness and ΔTd with skin temperature, the model provides a comprehensive approach to predicting thermal comfort in HST environments. This research contributes to advancing thermal comfort analysis in HST and offers valuable insights for optimizing HST system design and operation to meet passengers' comfort requirements.

The analysis and optimization of thermal sensation of train drivers under occupational thermal exposure.

Introduction: Prolonged exposure of train drivers to thermal discomfort can lead to occupational safety and health (OSH) risks, causing physical and mental injuries. Traditional method of treating human skin as a wall surface fail to observe accurate skin temperature changes or obtain human thermal comfort that adapts to the thermal environment. Methods: This study employs the Stolwijk human thermal regulation model to investigate and optimize the thermal comfort of train drivers. To minimize the time-consuming design optimization, a pointer optimization algorithm based on radial basis function (RBF) approximation was utilized to optimize the train cab ventilation system design and enhance drivers' thermal comfort. The train driver thermal comfort model was developed using Star-CCM+ and 60 operating conditions were sampled using an Optimal Latin Hypercube Design (Opt LHD). Results and Discussion: We analyzed the effects of air supply temperature, air supply volume, air supply angle, solar radiation intensity and solar altitude angle on the local thermal sensation vote (LTSV) and overall thermal sensation vote (OTSV) of the train driver. Finally, the study obtained the optimal air supply parameters for the Heating Ventilation and Air Conditioning (HVAC) in the train cabin under extreme summer conditions, effectively improving the thermal comfort of the driver.

Evaluation and prediction method of railway passenger long-term vibration comfort under complex operating conditions.

Vibration contributes large increases in railway passenger discomfort during long-term sitting. Discomfort caused by vibration may differ in different operation conditions. This paper conducted field measurements to investigate the interrelationships between the three. Participants completed a 240-min train journey with their whole-body vibration, subjective comfort ratings and train operating parameters being recorded. A large correlation was observed between the estimated vibration dose value and subjective comfort. The relationship that vibration magnitude significantly increases with increasing the train speed and tunnel density was also found and quantified. A vibration exposure limit of 2.08 m/s1.75 corresponding to the boundary between subjective ratings of comfortable and discomfortable was obtained. Based on the exposure limit and the quantified relationship, a vibration comfort prediction method that can calculate the passenger's maximum tolerance time under a given operation condition was proposed and may help in determining the optimal operating speed and tunnels distribution to alleviate vibration discomfort. Practitioner summary: Similar to the guide to effect of vibration on health in current standard, a vibration exposure limit regarding comfort was provided for reference when assessing long-term vibration comfort. Meanwhile, a prediction method was proposed for determining the best train operating speed and tunnels distribution, thereby alleviating railway passengers' vibration discomfort.

The effects of fucoidan as a dairy substitute on diarrhea rate and intestinal barrier function of the large intestine in weaned lambs.

This paper explores the effects of fucoidan on the frequency of diarrhea, colon morphology, colon antioxidant status, cytokine content, short-chain fatty acids, and microflora of cecal contents in early weaned lambs in order to provide a reference for the intestinal health of young ruminants. Fucoidan is a natural active polysaccharide extracted from kelp and other large brown algae. It has many biological effects, such as improving immunity, nourishing the stomach and intestines, and anti-tumor properties. This study investigated the effects of fucoidan supplementation in milk replacer on the large intestine's ability to act as an intestinal barrier in weaned lambs. With six duplicate pens and one lamb per pen, a total of 24 weaned lambs (average starting body weight of 7.32 ± 0.37 kg) were randomly assigned to one of four milk replacer treatments. Four concentrations of fucoidan supplementation (0, 0.1, 0.3, and 0.6% dry matter intake) were employed to investigate the effects of fucoidan on cecal fermentation and colon microbial organization. The test period lasted 37 days (1 week before the test and 1 month after the test), and lamb cecal contents and colon organization were collected for examination. In addition, the fecal status of all lambs was observed and recorded daily, allowing us to calculate the incidence of diarrhea in weaned lambs. The findings demonstrated that fucoidan may significantly increase the concentration of short-chain fatty acids (propionic acid and butyric acid) in the cecal digesta of weaned lambs. In weaned lambs, 16S rDNA testing showed that fucoidan at 0.3-0.6% (dry matter intake) was beneficial for boosting the variety of the intestinal bacteria and modifying the relative abundance of a few bacterial strains. In addition, fucoidan enhanced colon antioxidant and immune functions and decreased the diarrhea rate to relieve weaning stress. This result demonstrates that milk replacer supplementation with fucoidan contributes to the improvement in the large intestinal health of weaned lambs.

Influencing factors and mechanism of high-speed railway passenger overall comfort: Insights from source functional brain network and subjective report.

Overall comfort is the priority for the high-speed railway (HSR) passengers, while its influencing factors and mechanism are not yet apparent. According to the source functional brain network and subjective report, this study revealed the potential influencing factors and mechanisms of passengers overall comfort in high-speed railway environments. Here, an ergonomics field test with 20 subjects was conducted where subjective reports and electroencephalography (EEG) were collected. The electric-source imaging and functional connectivity were used to build the source functional brain network from EEG and network indices were extracted. Statistics analysis results showed that static comfort played the most critical role in the overall comfort, followed by emotional valence, emotional arousal, aural pressure comfort, vibration comfort, and noise comfort. Thermal and visual comfort were insignificant due to the well-designed heating, ventilation, and air conditioning (HVAC) and lighting system of HSR. In addition, the source functional brain network of passengers who felt uncomfortable had the higher clustering coefficient, assortativity coefficient and global efficiency, which meant greater activation of brain compared with passengers who were in a state of comfort. According to the local attributes indices analysis, most key brain regions were located in the frontal and hippocampus, which revealed emotion and spatial perception contribute to the whole comfort degradation process. This work proposed novel insights into HSR passengers overall comfort according to subjective and objective methods. Our findings demonstrate emotional regulation and seat improvements are key factors for future improvement of HSR passengers overall comfort.

The Application of Electroencephalogram in Driving Safety: Current Status and Future Prospects.

The driver is one of the most important factors in the safety of the transportation system. The driver's perceptual characteristics are closely related to driving behavior, while electroencephalogram (EEG) as the gold standard for evaluating human perception is non-deceptive. It is essential to study driving characteristics by analyzing the driver's brain activity pattern, effectively acquiring driver perceptual characteristics, creating a direct connection between the driver's brain and external devices, and realizing information interchange. This paper first introduces the theories related to EEG, then reviews the applications of EEG in scenarios such as fatigue driving, distracted driving, and emotional driving. The limitations of existing research have been identified and the prospect of EEG application in future brain-computer interface automotive assisted driving systems have been proposed. This review provides guidance for researchers to use EEG to improve driving safety. It also offers valuable suggestions for future research.

EEG-TNet: An End-To-End Brain Computer Interface Framework for Mental Workload Estimation.

The mental workload (MWL) of different occupational groups' workers is the main and direct factor of unsafe behavior, which may cause serious accidents. One of the new and useful technologies to estimate MWL is the Brain computer interface (BCI) based on EEG signals, which is regarded as the gold standard of cognitive status. However, estimation systems involving handcrafted EEG features are time-consuming and unsuitable to apply in real-time. The purpose of this study was to propose an end-to-end BCI framework for MWL estimation. First, a new automated data preprocessing method was proposed to remove the artifact without human interference. Then a new neural network structure named EEG-TNet was designed to extract both the temporal and frequency information from the original EEG. Furthermore, two types of experiments and ablation studies were performed to prove the effectiveness of this model. In the subject-dependent experiment, the estimation accuracy of dual-task estimation (No task vs. TASK) and triple-task estimation (Lo vs. Mi vs. Hi) reached 99.82 and 99.21%, respectively. In contrast, the accuracy of different tasks reached 82.78 and 66.83% in subject-independent experiments. Additionally, the ablation studies proved that preprocessing method and network structure had significant contributions to estimation MWL. The proposed method is convenient without any human intervention and outperforms other related studies, which becomes an effective way to reduce human factor risks.

Types, Risk Factors, Consequences, and Detection Methods of Train Driver Fatigue and Distraction.

Train drivers' inattention, including fatigue and distraction, impairs their ability to drive and is the major risk factor for human-caused train accidents. Many experts have undertaken numerous studies on train driver exhaustion and distraction, but a systematic study is still missing. Through a systematic review, this work aims to outline the types, risk factors, consequences, and detection methods of train driver fatigue and distraction. The effects of central nervous fatigue and cognitive distraction in train drivers during driving are caused by rest and sleep schedules, workload, automation levels, and mobile phones. Furthermore, train drivers' fatigue and distraction can cause loss of concentration and slow reaction, resulting in dangerous driving behaviour such as speeding and SPAD. Researchers have combined subjective reporting, physiological parameters, and physical factors to construct detection algorithms with good results to detect train driver fatigue and distraction. This review offers recommendations for researchers looking into train driver fatigue and distraction. And it can also make valuable recommendations for future studies about railway traffic safety.

Assessment of passenger long-term vibration discomfort: a field study in high-speed train environments.

This study revealed the mechanism of long-term passenger vibration discomfort in high-speed trains and proposed a novel evaluation model to assess it, while the most popular international standard ISO 2631-1 is unsuitable. Here, a field test was conducted to investigate the long-term passenger vibration comfort in high-speed trains under different operation environments by the measurement of the whole-body vibration (WBV) and the subjective ratings of passenger comfort. During the whole sitting period of high-speed train passengers, the phenomena 'compensatory degradation' and 'discomfort accumulation' were found, which meant that the brief termination of vibration cannot fundamentally alleviate passenger vibration comfort. And the vibration comfort can be evaluated by the product of exposure time and the novel vibration acceleration index we proposed. Meanwhile, high-speed trains with higher velocities or running in tunnel environments have higher frequency-weighted WBV amplitude than open-air and lower velocities, which caused more vibration discomfort of passengers. Practitioner Summary: This field study provided data support for ensuring the occupational health of train drivers whose work routes involve a large number of tunnels and improving passenger vibration comfort. Meanwhile, a novel idea was provided for evaluating the vibration comfort of passengers who prolonged exposure to low-amplitude environments.

Tunnel driving occupational environment and hearing loss in train drivers in China.

OBJECTIVE: Hearing loss caused by high levels of noise is a potential occupational health disorder among train drivers around the world. This study aims to investigate the relationship between tunnel driving occupational environment and hearing loss in train drivers, to provide some insights into helping reduce hearing loss among train drivers. METHODS: This study analysed cross-sectional data for 1214 train drivers who work at China Railway Guangzhou Group. Health examination was taken by physicians with professional licences, and audiometric testing was performed by health technicians in a sound-isolated room. T/R is defined as the ratio of the length of the tunnels to the length of the railway along drivers' work routes. Different multivariate models and stratified models were established for sensitivity analysis. A multivariable logistic regression model was used to estimate the ORs of hearing loss associated with tunnel driving occupational environment. RESULTS: The adjusted OR for high-frequency hearing loss in association with the highest T/R levels (30%-45%) versus the lowest T/R levels (<15%) was 3.72 (95% CI 1.43 to 9.69). The corresponding OR for speech-hearing loss was 1.75 (95% CI 0.38 to 8.06). The sensitivity analysis shows our results are suitable for various alternative models. CONCLUSIONS: This study found that there was a significant association between tunnel driving occupational environment and hearing loss. Train drivers who work in a higher T/R environment have worse hearing loss.

An Investigation of Dynamic Responses and Head Injuries of Standing Subway Passengers during Collisions.

With the development of the subway and the pressing demand of environmentally friendly transportation, more and more people travel by subway. In recent decades, the issues about passenger passive safety on the train have received extensive attention. In this research, the head injury of a standing passenger in the subway is investigated. Three MADYMO models of the different standing passenger postures, defined as baseline scenarios, are numerically set up. HIC15 values of passengers with different postures are gained by systematic parametric studies. The injury numerical simulation results of various scenarios with different friction coefficients, collision acceleration, standing angle, horizontal handrail height, and ring handrail height are analyzed. Results show that the horizontal handrail provides better protection in the three different standing passenger postures. Different friction coefficients and the standing angle have great impact on the head injuries of passengers in three different scenarios. The handrail height also has some effects on head injury of passengers with different standing postures, so it is necessary to be considered when designing the interior layout of the subway. This study may provide guidance for the safety design of the subway and some advices for standing subway passengers.

Effects of volatile organic compounds and carbon monoxide mixtures on learning and memory, oxidative stress, and monoamine neurotransmitters in the brains of mice.

In this study, we investigated the effect of inhaled mixtures of volatile organic compounds (VOCs) and carbon monoxide (CO) on neuroethology. Fifty 6-week-old male Kunming mice were exposed in five similar static chambers; zero (control) and four different doses of VOC and CO mixtures (G1-G4) for 10 consecutive days and 2 h/day. The compounds and concentrations were as follows: formaldehyde, benzene, toluene, xylene, and CO as 0.10 + 0.11 + 0.20 + 0.20 + 10.00 mg/m3, 0.20 + 0.22 + 0.40 + 0.40 + 20.00 mg/m3, 1.00 + 1.10 + 2.00 + 2.00 + 100.00 mg/m3, and 5.00 + 5.50 + 10.00 + 10.00 + 500.00 mg/m3, respectively, which corresponded to 1, 2, 10, and 50 times the indoor air quality standard in China. Morris water maze and grip strength tests were performed during the exposure experiment. One day following the final exposure, oxidative damage levels, monoamine neurotransmitters, monoamine oxidase (MAO), and morphology of mice brain were analyzed. Escape latency, dopamine, norepinephrine (NE), and serotonin decreased significantly, while total antioxidant capacity, glutathione peroxidase, and MAO increased significantly in G3 and G4. In addition, there were morphological changes and degeneration of neurons in the dentate gyrus regions of the hippocampus in G4. Results showed that the inhaled mixtures of VOCs and CO affected learning and memory of mice. The impairment of monoamine neurotransmitter associated with MAO may be one of the mechanisms of learning and memory impairment of the mice induced by the mixtures of VOCs and CO.

Effects of triclosan on hormones and reproductive axis in female Yellow River carp (Cyprinus carpio): Potential mechanisms underlying estrogen effect.

Triclosan (TCS), a member of the class of compounds called pharmaceutical and personal care products (PPCPs), is a broad antibacterial and antifungal agent found in a lot of consumer products. However, TCS hormone effect mechanism in teleost female fish is not clear. Female Yellow River carp (Cyprinus carpio) were exposed to 1/20, 1/10 and 1/5 LC50 TCS (96h LC50 of TCS to carp) under semi-static conditions for 42days. Vitellogenin (Vtg), 17ß-estradiol (E2), testosterone(T), estrogen receptor (Er), gonadotropin (GtH), and gonadotropin-releasing hormone (GnRH) levels were measured by enzyme-linked immunosorbent assay (ELISA). Meanwhile, we also examined the mRNA expressions of aromatase, GtHs-ß, GnRH, and Er by quantitative real-time PCR (qRT-PCR). The results indicated that 1/5 LC50 TCS induced Vtg in hepatopancreas of female carps by interference with the hypothalamic-pituitary-gonadal (HPG) axis at multiple potential loci through three mechanisms: (a) TCS exposure enhanced the mRNA expression of hypothalamus and gonadal aromatase which converts androgens into estrogens, subsequently increasing serum concentrations of E2 to induce Vtg in hepatopancreas; (b) TCS treatment increased GnRH and GtH-ß mRNA expression and secretion, causing the disturbance of reproductive endocrine and the increase of E2 to induce Vtg in hepatopancreas; (c) TCS exposure enhanced synthesis and secretion of Er, then it bound to Er to active Vtg synthesis. These mechanisms showed that TCS may induce Vtg production in female Yellow River carp by Er-mediated and non-Er-mediated pathways.