Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections

Interactions between motorized and nonmotorized vehicles have drawn considerable attention from researchers. They are commonly seen at mixed flow intersections where nonmotorized vehicles, without the restriction of lane markers or physical barriers, may disperse into adjacent lanes and thus lead to complex interactions with motorized vehicles. Such a dispersion phenomenon between heterogeneous participants (e-bikes and bicycles as nonmotorized vehicles versus motorized vehicles) is difficult to model. In this paper, we were inspired by the dispersion of charged particles in an electric field and modeled the dispersion phenomenon of go-straight, nonmotorized vehicles at mixed flow intersections accordingly, as it was discovered in this research that these two dispersion phenomena share three underlying commonalities with each other. A novel particle dispersion model (PDM) based on a particle’s movement in an electric field is proposed. The model is calibrated and validated using 1,490 high-definition sets of trajectory data for go-straight, nonmotorized vehicles during 43 cycles at two typical mixed flow intersections. The PDM is compared with the social force model (SFM) on their dispersion characteristics that are used to describe the nonmotorized bicycles’ behavior. The results show that the PDM performs better than the SFM with regard to depicting the dispersion characteristic indices of the nonmotorized vehicles, such as the travel time, the dispersion intensity of heterogeneous nonmotorized vehicles, the sectional dispersion degree, and other dispersion characteristics. Document type: Articl

Brain Activation of Elite Race Walkers in Action Observation, Motor Imagery, and Motor Execution Tasks: A Pilot Study

Walking plays an important role in human daily life. Many previous studies suggested that long-term walking training can modulate brain functions. However, due to the use of measuring techniques such as fMRI and PET, which are highly motion-sensitive, it is difficult to record individual brain activities during the movement. This pilot study used functional near-infrared spectroscopy (fNIRS) to measure the hemodynamic responses in the frontal-parietal cortex of four elite race walkers (experimental group, EG) and twenty college students (control group, CG) during tasks involving action observation, motor imagery, and motor execution. The results showed that activation levels of the pars triangularis of the inferior frontal gyrus (IFG), dorsolateral prefrontal cortex (DLPFC), premotor and supplementary motor cortex (PMC and SMC), and primary somatosensory cortex (S1) in the EG were significantly lower than in the CG during motor execution and observation tasks. And primary motor cortex (M1) of EG in motor execution task was significantly lower than its in CG. During the motor imagery task, activation intensities of the DLPFC, PMC and SMC, and M1 in the EG were significantly higher than in the CG. These findings suggested that the results of motor execution and observation tasks might support the brain efficiency hypothesis, and the related brain regions strengthened the efficiency of neural function, but the results in motor imagery tasks could be attributed to the internal forward model of elite race walkers, which showed a trend opposed to the brain efficiency hypothesis. Additionally, the activation intensities of the pars triangularis and PMC and SMC decreased with the passage of time in the motor execution and imagery tasks, whereas during the action observation task, no significant differences in these regions were found. This reflected differences of the internal processing among the tasks

Low-Theta Electroencephalography Coherence Predicts Cigarette Craving in Nicotine Addiction

Addicts are often vulnerable to drug use in the presence of drug cues, which elicit significant drug cue reactivity. Mounting neuroimaging evidence suggests an association between functional magnetic resonance imaging connectivity networks and smoking cue reactivity; however, there is still little understanding of the electroencephalography (EEG) coherence basis of smoking cue reactivity. We therefore designed two independent experiments wherein nicotine-dependent smokers performed a smoking cue reactivity task during EEG recording. Experiment I showed that a low-theta EEG coherence network occurring 400–600 ms after onset during long-range (mainly between frontal and parieto-occipital) scalp regions, which was involved in smoking cue reactivity. Moreover, the average coherence of this network was significantly correlated with participants’ level of cigarette craving. In experiment II, we tested an independent group of smokers and demonstrated that the low-theta coherence network significantly predicted changes in individuals’ cigarette craving. Thus, the low-theta EEG coherence in smokers’ brains might be a biomarker of smoking cue reactivity and can predict addiction behavior

The Relationship Between Cognitive Dysfunction and Symptom Dimensions Across Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

Background: Cognitive dysfunction is considered a core feature among schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Despite abundant literature comparing cognitive dysfunction among these disorders, the relationship between cognitive dysfunction and symptom dimensions remains unclear. The study aims are a) to identify the factor structure of the BPRS-18 and b) to examine the relationship between symptom domains and cognitive function across SZ, BD, and MDD.Methods: A total of 716 participants [262 with SZ, 104 with BD, 101 with MDD, and 249 healthy controls (HC)] were included in the study. One hundred eighty participants (59 with SZ, 23 with BD, 24 with MDD, and 74 HC) completed the MATRICS Consensus Cognitive Battery (MCCB), and 507 participants (85 with SZ, 89 with BD, 90 with MDD, and 243 HC) completed the Wisconsin Card Sorting Test (WCST). All patients completed the Brief Psychiatric Rating Scale (BPRS).Results: We identified five BPRS exploratory factor analysis (EFA) factors (“affective symptoms,” “psychosis,” “negative/disorganized symptoms,” “activation,” and “noncooperation”) and found cognitive dysfunction in all of the participant groups with psychiatric disorders. Negative/disorganized symptoms were the most strongly associated with cognitive dysfunctions across SZ, BD, and MDD.Conclusions: Our findings suggest that cognitive dysfunction severity relates to the negative/disorganized symptom domain across SZ, BD, and MDD, and negative/disorganized symptoms may be an important target for effective cognitive remediation in SZ, BD, and MDD

Detecting and Searching for subglacial lakes through airborne radio-echo sounding in Princess Elizabeth Land (PEL), Antarctica

Over 400 subglacial lakes were discovered in Antarctica through radio-echo sounding (RES) method and remote sensing. Subglacial lakes have significance in lubricating ice-bedrock interface and enhancing ice flow. Moreover, ancient lives may exist in the extreme environment. Since 2015, the “Snow Eagle 601” BT-67 airborne platform has been deployed and applied to map ice sheet and bedrock of Princess Elizabeth Land. One of great motivations of airborne surveys is to detect and search for subglacial lakes in the region. In this paper, we provided preliminary results of RES over both old and new discovered lakes, including Lake Vostok, a potential second large subglacial lake and other lakes beneath interior of the ice sheet in Antarctica

An Improved Ship Weather Routing Framework for CII Reduction Accounting for Wind-Assisted Rotors

With the increasingly strict regulations for the energy-saving and emission-reduction technology of ships, minimizing fuel cost and thus reducing the carbon intensity index (CII) is one of the most critical issues in the design and operation of merchant ships. More recently, many wind-assisted devices, such as rotors, wind sails, etc., have been investigated and designed to utilize renewable wind energy. With the equipment of wind-assisted rotors, the optimization of ship routes becomes more important because the effect of this wind-assisted device highly depends on the local wind field along the shipping route. In this paper, an improved ship weather routing framework based on the A* algorithm has been proposed to determine the optimal ship route and ship operations with wind-assisted rotors. The proposed framework effectively utilizes different sources of data, including ship design, weather forecasting and historical sailing information, to produce a better estimation of fuel consumption under the effect of sea states. Several improvements on the classic A* algorithm, including directed searching and three-dimensional extension, are proposed to improve the routing effect and efficiency. Finally, the proposed method was applied to test cases of a VLCC operating from China to the Middle East and the results show that the total fuel consumption could be reduced compared to the minimum distance route