Search Results (22)

The endogenous neurosteroid (3α,5α)-3-hydroxypregnan-20-one (3α,5α-THP) modulates inflammatory and neuroinflammatory signaling through toll-like receptors (TLRs) in human and mouse macrophages, human blood cells and alcohol-preferring (P) rat brains. Although it is recognized that 3α,5α-THP inhibits TLR4 activation by blocking interactions with MD2 and MyD88, the comprehensive molecular mechanisms remain to be elucidated. This study explores additional TLR4 activation sites, including TIRAP binding to MyD88, which is pivotal for MyD88 myddosome formation, as well as LPS interactions with the TLR4:MD2 complex. Both male and female P rats (n = 8/group) received intraperitoneal administration of 3α,5α-THP (15 mg/kg; 30 min) or a vehicle control, and their hippocampi were analyzed using immunoprecipitation and immunoblotting techniques. 3α,5α-THP significantly reduces the levels of inflammatory mediators IL-1β and HMGB1, confirming its anti-inflammatory actions. We found that MyD88 binds to TLR4, IRAK4, IRAK1, and TIRAP. Notably, 3α,5α-THP significantly reduces MyD88-TIRAP binding (Males: −31 ± 9%, t-test, p < 0.005; Females: −53 ± 15%, t-test, p < 0.005), without altering MyD88 interactions with IRAK4 or IRAK1, or the baseline expression of these proteins. Additionally, molecular docking and molecular dynamic analysis revealed 3α,5α-THP binding sites on the TLR4:MD2 complex, targeting a hydrophobic pocket of MD2 usually occupied by Lipid A of LPS. Surface plasmon resonance (SPR) assays validated that 3α,5α-THP disrupts MD2 binding of Lipid A (Kd = 4.36 ± 5.7 μM) with an inhibition constant (Ki) of 4.5 ± 1.65 nM. These findings indicate that 3α,5α-THP inhibition of inflammatory mediator production involves blocking critical protein-lipid and protein-protein interactions at key sites of TLR4 activation, shedding light on its mechanisms of action and underscoring its therapeutic potential against TLR4-driven inflammation. Full article

This study proposed an event-triggered quantized model predictive control (ETQMPC) method for the dynamic docking of unmanned underwater vehicles (UUVs) and human-occupied vehicles (HOVs). The proposed strategy employed a non-periodic control approach that initiated the non-linear model predictive control (NMPC) optimization and state sampling based on tracking errors and deviations from the predicted optimal state, thereby enhancing computing performance and system efficiency without compromising the control quality. To further conserve communication resources and improve information transfer efficiency, a quantitative feedback mechanism was employed for sampling and state quantification. The simulation experiments were performed to verify the effectiveness of the method, demonstrating excellent docking trajectory tracking performance, robustness against bounded current interference, and significant reductions in computational and communication burdens. The experimental results demonstrated that the method outperformed in the docking trajectory tracking control performance significantly improved the computational and communication performance, and comprehensively improved the system efficiency. Full article

The transition of the vehicle fleet to incorporate AV will be a long and complex process. AVs will gradually form a larger and larger share of the fleet mix, offering opportunities and challenges for improved efficiency and safety. At any given point during this transition a portion of the AV fleet will be consuming roadway capacity while deadheading, which means operating without passengers. Should these unoccupied vehicles simply utilize the shortest paths to their next destination, they will contribute to congestion for the rest of the roadway users without providing any benefit to human passengers. There is an opportunity to develop routing strategies for deadheading AVs that mitigate or eliminate their contribution to congestion while still serving the mobility needs of AV owners or passengers. Some of the AV fleet will be privately owned, while some will be part of a shared AV fleet. In the former, some AVs will be owned by households that are lower-income and benefit from the ability to have fewer vehicles to serve the mobility needs of the household. In these cases, it is especially important that deadheading AVs can meet household mobility needs while also limiting the contribution to roadway congestion. The aim of this study is to develop and evaluate routing strategies for deadheading autonomous vehicles (AVs) that balance the reduction of roadway congestion and the mobility needs of households. By proposing and testing a bi-objective program, this study seeks to identify effective methodologies for routing unoccupied AVs in a manner that mitigates their negative impact on traffic while still fulfilling essential transportation requirements of the household. Three strategies are proposed to deploy AV deadheading methodology to route deadheading vehicles on longer paths, reducing congestion for occupied vehicles, while still meeting the trip-making needs of households. Case studies on two transportation networks are presented alongside their practical implications and computational requirements. Full article

The high-precision magnetic survey system is crucial for ocean exploration. However, most existing systems face challenges such as high noise levels, low sensitivity, and inadequate magnetic compensation effects. To address these issues, we developed a high-precision magnetic survey system based on the manned submersible “Deep Sea Warrior” for deep-ocean magnetic exploration. This system incorporates a compact optically pumped cesium (Cs) magnetometer sensor to measure the total strength of the external magnetic field. Additionally, a magnetic compensation sensor is included at the front end to measure real-time attitude changes of the platform. The measured data are then transmitted to a magnetic signal processor, where an algorithm compensates for the platform’s magnetic interference. We also designed a deep pressure chamber to allow for a maximum working depth of 4500 m. Experiments conducted in both indoor and field environments verified the performance of the proposed magnetic survey system. The results showed that the system’s sensitivity is ≤0.5 nT, the noise level of the magnetometer sensor is ≤1 pT/√Hz at 1 Hz, and the sampling rate is 10 Hz. The proposed system has potential applications in ocean and geophysical exploration. Full article

Lane changing is a frequent traffic accident scenario. To improve the driving safety in lane changing scenarios, the blind spot display of lane changing is increased through human–machine interaction (HMI) interfaces in intelligent vehicles to improve the driver’s rate of risk perception with regard to the driving environment. However, blind spot information will increase the cognitive load of drivers and lead to driving distraction. To quantify the coupling relationship between blind spot display and drivers’ cognitive load, we proposed a method to quantify the cognitive load of the driver’s interaction by improving the AttenD algorithm, collecting feature data by carrying out a variety of real-vehicle road-testing experiments on three kinds of intelligent vehicles, and then establishing a model blind spot design and driver cognitive load correlation model using Bayesian Logistic Ordinal Regression (BLOR) and Categorical Boosting (CatBoost). The results show that the blind spot image display can reduce the driver’s cognitive load more effectively as it is closer to the driver, has a larger area, and occupies a higher proportion of the center control screen, especially when it is located in the middle and upper regions of the center control screen. The improved AttenD algorithm is able to quantify the cognitive load of the driver, which can be widely used in vehicle testing, HMI interface development and evaluation. In addition, the analytical framework constructed in this paper can help us to understand the complex impact of HMI in intelligent vehicles and provide optimization criteria for lane change blind spot design. Full article

High-precision magnetometers play a crucial role in ocean exploration, geophysical prospecting, and military and security applications. Installing them on human-occupied vehicle (HOV) platforms can greatly enhance ocean exploration capabilities and efficiency. However, most existing magnetometers suffer from low sensitivity and excessively large size. This study presents a high-sensitivity, miniaturized magnetometer based on cesium optically pumped probes. The designed magnetometer utilizes a three-probe design to eliminate the detection dead zone of the cesium optically pumped probe and enable three-dimensional magnetic detection. The proposed magnetometer uses a flux gate probe to detect the three-axis magnetic field and ensure that the probe does not enter the dead zone. The three probes can automatically switch by measuring the geomagnetic elements and real-time attitude of the HOV platform. This article primarily introduces the cesium three-probe optically pump, flux gate sensor, and automatic switching scheme design of the above-mentioned magnetometer. Moreover, it is proven through testing that the core indicators, such as the accuracy and sensitivity of the cesium three-probe optically pumped and flux gate sensor, reach international standards. Finally, the effectiveness of the automatic switching scheme proposed in this study is demonstrated through drone-mounted experiments. Full article

Air pollutants from traffic make an important contribution to human exposure, with pedestrians likely to experience rapid fluctuation and high concentrations on the pavements of busy streets. This monitoring campaign was on Hennessy Road in Hong Kong, a densely populated city with deep canyons, crowded footpaths and low wind speeds. Kerbside NOx concentrations were measured using electrochemical sensors with baseline correction and subsequently deconvoluted to determine concentrations at 1-s resolution to study the dispersion of exhaust gases within the first few metres of their on-road source. The pulses of NOx from passing vehicles were treated as segments of a Gaussian plume originating at the tailpipe. The concentration profiles in segments were fit to a simple analytical equation assuming a continuous line source with R² > 0.92. Least squares fitting parameters could be attributed to vehicle speed and source strength, dispersion, and sensor position. The width of the plume was proportional to the inverse of vehicle speed. The source strength of NOx from passing vehicles could be interpreted in terms of individual emissions, with a median value of approximately 0.18 g/s, but this was sensitive to vehicle speed and exhaust pipe position. The current study improves understanding of rapid changes in pollutant concentration in the kerbside environment and suggests opportunities to establish the contribution from traffic flow to pedestrian exposure in a dynamic heavily occupied urban microenvironment. Full article

Advances in information and signal processing, driven by artificial intelligence techniques and recent breakthroughs in deep learning, have significantly impacted autonomous driving by enhancing safety and reducing the dependence on human intervention. Generally, prevailing ADASs (advanced driver assistance systems) incorporate costly components, making them financially unattainable for a substantial portion of the population. This paper proposes a solution: an embedded system designed for real-time pedestrian and priority sign detection, offering affordability and universal applicability across various vehicles. The suggested system, which comprises two cameras, an NVIDIA Jetson Nano B01 low-power edge device and an LCD (liquid crystal system) display, ensures seamless integration into a vehicle without occupying substantial space and provides a cost-effective alternative. The primary focus of this research is addressing accidents caused by the failure to yield priority to other drivers or pedestrians. Our study stands out from existing research by concurrently addressing traffic sign recognition and pedestrian detection, concentrating on identifying five crucial objects: pedestrians, pedestrian crossings (signs and road paintings separately), stop signs, and give way signs. Object detection was executed using a lightweight, custom-trained CNN (convolutional neural network) known as SSD (Single Shot Detector)-MobileNet, implemented on the Jetson Nano. To tailor the model for this specific application, the pre-trained neural network underwent training on our custom dataset consisting of images captured on the road under diverse lighting and traffic conditions. The outcomes of the proposed system offer promising results, positioning it as a viable candidate for real-time implementation; its contributions are noteworthy in advancing the safety and accessibility of autonomous driving technologies. Full article

In order to quantitatively analyze the electromagnetic exposure dose of an inverter in a pure electric vehicle to the driver’s body and assess the safety of the electromagnetic exposure, based on a real human anatomy model in the virtual home project, a real human model with several organs and tissues, including muscles, bones, a heart, lungs, a liver, kidneys, a bladder, a skull, a scalp, white matter, and a cerebellum, was constructed. The inverter of a pure electric vehicle is considered to be the electromagnetic exposure source; for this study, an equivalent electromagnetic environment model composed of a real human body, an inverter, and a vehicle body was built. The distribution of induced fields in the driver’s tissues and organs was calculated and analyzed using the finite element method. The results show that the distribution of the magnetic flux density, induced electric field, and induced current density in the driver’s body was affected by the spatial distance of the inverter. The farther the distance was, the weaker the value was. Specifically, due to the different dielectric properties of the different tissues, the induced field in the different tissues was significantly different. However, the maximum magnetic flux density over the space occupied by the driver’s body and induced electric field in the driver’s trunk and central nervous system satisfied the exposure limits of the International Commission on Non-Ionization Radiation Protection, indicating that the electromagnetic environments generated by the inverter proposed in this paper are safe for the vehicle driver’s health. The numerical results of this study could also effectively supplement the study of the electromagnetic environments of pure electric vehicles and provide some references for protecting the drivers of pure electric vehicles from electromagnetic radiation. Full article

China is currently in a rapid urbanization phase, and road traffic accidents occur frequently, with vulnerable road users often being easily injured. Traditional road traffic safety research often focuses on environmental and structural safety issues or considers human factors as the cause of accidents. This study organized 30 vulnerable road users to travel in a quadrangular road area in the Wudaokou area of Beijing, collected language data from the subjects for analysis, and attempted to apply schema theory and the perceptual cycle model from the field of cognitive psychology to analyze the perception and decision-making processes of vulnerable road users, thus discovering accident risks in the traffic environment and their underlying causes from the perspective of vulnerable road users. The study found that factors such as disorderly placement of shared bicycles, food delivery vehicles occupying the road, damaged road infrastructure, and unreasonable road design affect traffic safety and order, and proposes targeted improvement suggestions. Full article

Minimal risk maneuvers (MRMs), as part of highly automated systems, aim at minimizing the risk during a transition phase from automated to manual driving. Previous studies show that many drivers have an urge to intervene in transition phases despite the system’s capability to safely come to a standstill. A human–machine interface (HMI) concept was developed to support driver decisions by providing environmental information and action recommendations. This was investigated in a static driving simulator experiment with 36 participants. Two scenarios that differed in the traffic on the adjacent left lane were implemented and the HMI concept displayed the content accordingly. Results of the study again show a high intervention rate of drivers overtaking the obstacle from the left, even if the lane is occupied by other vehicles. The HMI concept had a positive influence on the manner of intervention by encouraging a standstill in the shoulder lane. Nevertheless, negative consequences included accidents and dangerous situations, but at lower frequencies and proportions during drives with the HMI concept. In conclusion, the risk during the transition phase was reduced. Furthermore, the results showed a significant decrease in the subjective workload and a positive influence on the drivers’ understanding and predictability of the automated system. Full article

The automation of our vehicles is an all-present topic with great benefits for society, particularly in the area of public transport and pilot projects of automated shuttle buses are already underway. However, they do not show the full potential of using them as a supplement to public transport, since single-occupancy registration of the vehicles usually allows only slow speeds and also requires a substitute driver on board. In our study, we aim to (1) examine the status quo of its user acceptance and (2) identify the roles of the operators and their tasks in automated urban shuttle buses. We conducted a mixed-method study including in-depth interviews, questionnaires, and in-the-field observations visiting pilot projects of the two most widespread pilot projects on German streets. Our results uncover the multiple roles and tasks the human operators currently assume. Furthermore, we developed design approaches for a digital companion substituting the operator in a long run and evaluated these concepts. A remote operator or a hologram were preferred solutions and we propose further design requirements for such companions. This work helps to understand the individual roles that operators currently occupy and provides a good basis for concepts of technologies that will perform these tasks in the future. Full article

Different from traditional transport systems, such as cars or trains, which are limited by land transit space, flying cars (such as UAS, drones, and air taxis) do not occupy space with traffic. They have a degree of freedom in space and time, smaller displacement, and consequently, less stress for their users. Large companies and researchers around the world are working with different architectures, algorithms, and techniques to test air taxi transport to serve a significant proportion of people safely and autonomously. One of the main issues surrounding the diffusion of air taxis is safety and security, since a simple failure can lead to the loss of high-value assets, loss of the vehicle, and/or injuries to human lives, including fatalities. In this sense, despite significant efforts, the literature is still specific and limited regarding air taxi safety and security. Therefore, this study aimed to carry out an extensive systematic literature review of the main modern advances in techniques, architectures, and research carried out around the world focused on these types of vehicles. More than 210 articles from between 2015 and January 2022 were individually reviewed. In addition, this study also presents gaps that could serve as a direction for future research. As far as the authors are aware, no other study performs this type of review focused on air taxi safety. Full article

The characterization of prehistoric human behavior in terms of habitation practices using GIS cartography methods is an important aspect of any modern geoarchaeological approach. Furthermore, using unmanned aerial vehicle (UAV) surveys to identify archaeological sites with temporal resolution during the spring agro-technical works and automated mapping of the geomorphological features based on LiDAR-derived DEM can provide valuable information about the human–landscape relationships and lead to accurate archaeological and cartographic products. In this study, we applied a GIS-based landform classification method to relief characterization of 362 Late Bronze Age (LBA) settlements belonging to Noua Culture (NC) (cal. 1500/1450-1100 BCE) located in the Jijia catchment (NE Romania). For this purpose, we used an adapted version of Topographic Position Index (TPI) methodology, abbreviated DEV, which consists of: (1) application of standard deviation of TPI for the mean elevation (DEV) around each analyzed LBA site (1000 m buffer zone); (2) classification of the archaeological site’s location using six slope position classes (first method), or ten morphological classes by combining the parameters from two small-DEV and large-DEV neighborhood sizes (second method). The results indicate that the populations belonging to Noua Culture preferred to place their settlements on hilltops but close to the steep slope and on the small hills/local ridges in large valleys. From a geoarchaeological perspective, the outcomes indicate a close connection between occupied landform patterns and habitation practices during the Late Bronze Age and contribute to archaeological predictive modelling in the Jijia catchment (NE Romania). Full article

Due to the strong absorption and attenuation of electromagnetic waves by water, radio communications and global positioning systems are lacking in the deep-sea environment. Therefore, underwater long-distance communications, positioning, detection and other functions depend on acoustic technology. In order to realize the above functions, the acoustic system of the Fendouzhe human occupied vehicle (HOV) is composed of eight kinds of sonars and sensors, which is one of the core systems of manned submersible. Based on the Jiaolong/Shenhai Yongshi HOVs, the acoustic system of the Fendouzhe HOV has been developed. Compared with the previous technology, there are many technical improvements and innovations: 10,000-m underwater acoustic communication, 10,000-m underwater acoustic positioning, multi-beam forward-looking imaging sonar, an integrated navigation system, etc. This study introduces the structure of the acoustic system of the Fendouzhe HOV and the technical improvements compared with the Jiaolong/Shenhai Yongshi HOVs. The results of the acoustic system are illustrated by the 10,000-m sea trails in the Mariana Trench from October to December 2020. Full article