Sensitivity Analysis of Incentive Situations and Personal Attributes to Driving Anger Based on MNL Model: A Naturalistic Experimental Study

Driving anger, called "road rage", has gradually become universal phenomenon nowadays, which has been a concern to traffic management authorities. It is necessary to figure out impacting degree of the influencing factors on driving anger for taking the corresponding intervening measures. Forty drivers were enrolled to conduct naturalistic experiments on a busy route in Wuhan, China, where drivers\u27 anger can be induced by various incentive situations including jaywalking, weaving/cutting in line, traffic congestion and red light with extra paid if completing the experiment ahead of reference time. According to behavioral theory and disaggregation theory, the influencing factors including the incentive situations and personal attributes (i.e. gender, age, temperament) were determined for proposing driving anger prediction model based on MNL (multinomial logit). Then, the sensitivity of each influencing factor on driving anger was analyzed by elasticity theory on the basis of the proposed model. The result indicates that age, temperament and illegal behaviors from surrounding people are decisive influencing factors to driving anger sates with different intensity because their average elasticity values for none anger (neutral), low anger, medium anger, high anger are 1.254, 2.713, 2.914, respectively, which are all bigger than 1. Moreover, the accuracy of the proposed model is 78.30%. The results can provide theoretical support for developing key monitoring or targeted intervention to deal with the decisive influencing factors for traffic management authorities

Impact of Temperament Types and Anger Intensity on Drivers\u27 EEG Power Spectrum and Sample Entropy: An On-road Evaluation Toward Road Rage Warning

"Road rage", also called driving anger, is becoming an increasingly common phenomenon affecting road safety in auto era as most of previous driving anger detection approaches based on physiological indicators are often unreliable due to the less consideration of drivers\u27 individual differences. This study aims to explore the impact of temperament types and anger intensity on drivers\u27 EEG characteristics. Thirty-two drivers with valid license were enrolled to perform on-road experiments on a particularly busy route on which a variety of provoking events like cutting in line of surrounding vehicle, jaywalking, occupying road of non-motor vehicle and traffic congestion frequently happened. Then, muti-factor analysis of variance (ANOVA) and post hoc analysis were utilized to study the impact of temperament types and anger intensity on drivers\u27 power spectrum and sample entropy of θ and β waves extracted from EEG signals. The study results firstly indicated that right frontal region of the brain has close relationship with driving anger. Secondly, there existed significant main effects of temperament types on power spectrum and sample entropy of β wave while significant main effects of anger intensity on power spectrum and sample entropy of θ and β wave were all observed. Thirdly, significant interactions between temperament types and anger intensity for power spectrum and sample entropy of β wave were both noted. Fourthly, with the increase of anger intensity, the power spectrum and sample entropy both decreased sufficiently for θ wave while increased remarkably for β wave. The study results can provide a theoretical support for designing a personalized and hierarchical warning system for road rage

Secondary school = 中學

Film Director: Cheung Tammy (張虹) Film Release Year: 2003https://commons.ln.edu.hk/ccs_worksheet/1003/thumbnail.jp

Enhanced hydrogen storage properties of LiAlH4 catalyzed by CoFe2O4 nanoparticles

The catalytic effects of CoFe2O4 nanoparticles on the hydrogen storage properties of LiAlH4 prepared by ball milling were investigated. The onset desorption temperature of the LiAlH4 + 2 mol% CoFe2O4 sample is 65 °C, which is 90 °C lower that of the as-received LiAlH4, with approximately 7.2 wt% hydrogen released at 250 °C. The isothermal desorption results show that for the 2 mol% CoFe2O4 doped sample dehydrogenated at 120 °C, 6.8 wt% of hydrogen can be released within 160 min, which is 6.1 wt% higher than that of the as-received LiAlH4 under the same conditions. Through the differential scanning calorimetry (DSC) and the Kissinger desorption kinetics analyses, the apparent activation energy, Ea, of the 2 mol% CoFe2O4 doped sample is calculated as 52.4 kJ mol -1 H2 and 86.5 kJ mol-1 H2 for the first two decomposition processes. This is 42.4 kJ mol-1 H 2 and 86.1 kJ mol-1 H2 lower compared with the pristine LiAlH4, respectively, indicating considerably improved dehydrogenation kinetics by doping the CoFe2O4 catalyst in the LiAlH4 matrix. From the Fourier transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) analyses, a series of finely dispersed Fe and Co species with a range of valence states, produced from the reactions between LiAlH4 and CoFe2O4, play a synergistic role in remarkably improving LiAlH4 dehydrogenation properties. The rehydrogenation properties of the LiAlH4 + 2 mol% CoFe 2O4 sample have also been investigated at 140 °C under 6.5 MPa pressure held for 2.5 hPeer ReviewedPostprint (published version

Safety, tolerability, and pharmacokinetics of TG-1000, a new molecular entity against influenza virus: first-in-human study

Background: The cap-snatching mechanism of influenza virus mRNA transcription is strongly suppressed by TG-1000, a prodrug rapidly metabolized into TG-0527, is a potent cap-dependent nucleic acid endonuclease inhibitor. Herein, we aimed to assess the safety, tolerability, and pharmacokinetics of TG-1000 in healthy participants and the effect of food on the pharmacokinetics and safety of TG-1000.Method: The study was divided into 2 parts: Part A [Single Ascending-Dose (SAD) study, 10–160 mg] and Part B [Food-Effect (FE) study, 40 mg] were launched sequentially. The study included 66 participants for both investigations. We administered different TG-1000 capsules or placebo doses per the study protocol and collected blood samples for pharmacokinetic assessments at specific times. In plasma, TG-1000 and its active metabolite TG-0527 were assayed, and PK parameters were determined.Results: In SAD, the increase in AUC was less than the proportional increase in dose over the 20–160 mg dose range, while the increase in Cmax was proportional to the increase in dose. In the 10–160 mg dose range, T1/2, λz and Tmax of TG-0527 were dose-independent; and T1/2 and Tmax were within 33.8–39.4 h and 3.02–6 h, respectively. In FE, the AUC0-inf, AUC0-last, and Cmax of TG-0527 decreased by approximately 17.52%, 18.76%, and 41.35%, respectively, and the Tmax delay was around 1.50 h. No serious adverse events occurred during the studies.Conclusion: Overall, TG-1000 was well tolerated and exhibited an acceptable safety and PK profile, supporting further clinical investigation of TG-1000 for the treatment of influenza

PRRT2 gene mutations associated with infantile convulsions induced by sucking and the genotype-phenotype correlation

IntroductionPRRT2 is a major causative gene for self-limited familial neonatal-infantile epilepsy, paroxysmal kinesigenic dyskinesia, and paroxysmal kinesigenic dyskinesia with infantile convulsions. Voluntary movement trigger is prominent in adolescence and adulthood, but the triggers are unknown in infants.MethodsA gene panel designed for targeted next-generation sequencing (NGS) was used to screen genetic abnormalities in a cohort of 45 cases with infantile convulsions. The copy number variation was detected by a computational method based on the normalized depth of coverage and validated by a quantitative real-time polymerase chain reaction (RT-qPCR) method. The genotype-phenotype correlation of the PRRT2 mutation gene was analyzed.ResultsA de novo heterozygous PRRT2 deletion was identified in a child who had infantile convulsions induced by vigorous sucking. Seizures happened during the change of feeding behavior from breast to formula, which led to hungry and vigorous sucking. Ictal electroencephalograms recorded seizures with focal origination, which provided direct evidence of epileptic seizures in infants with PRRT2 mutations. Seizures stopped soon after the feeding behavior was changed by reducing feeding interval time and extending feeding duration. Data reanalysis on our previously reported cases with PRRT2 mutations showed that six of 18 (33.3%) patients had infantile convulsions or infantile non-convulsion seizures during feeding. The mutations included two truncating mutations (c.579dupA/p.Glu194Argfs*6, and c.649dupC/p.Arg217Profs*8) that were identified in each of the three affected individuals.ConclusionsThis study suggests that feeding, especially vigorous sucking, is potentially a trigger and highlights the significance of feeding behavior in preventing seizures in infants with PRRT2 mutations. Identification of PRRT2 haploinsufficiency mutations in the patients with infantile convulsions induced by sucking suggested a potential genotype-phenotype correlation

2023 Low-Power Computer Vision Challenge (LPCVC) Summary

This article describes the 2023 IEEE Low-Power Computer Vision Challenge (LPCVC). Since 2015, LPCVC has been an international competition devoted to tackling the challenge of computer vision (CV) on edge devices. Most CV researchers focus on improving accuracy, at the expense of ever-growing sizes of machine models. LPCVC balances accuracy with resource requirements. Winners must achieve high accuracy with short execution time when their CV solutions run on an embedded device, such as Raspberry PI or Nvidia Jetson Nano. The vision problem for 2023 LPCVC is segmentation of images acquired by Unmanned Aerial Vehicles (UAVs, also called drones) after disasters. The 2023 LPCVC attracted 60 international teams that submitted 676 solutions during the submission window of one month. This article explains the setup of the competition and highlights the winners' methods that improve accuracy and shorten execution time.Comment: LPCVC 2023, website: https://lpcv.ai

Measurements of the observed cross sections for e+e−→e^+e^-\to exclusive light hadrons containing π0π0\pi^0\pi^0 at s=3.773\sqrt s= 3.773, 3.650 and 3.6648 GeV

By analyzing the data sets of 17.3, 6.5 and 1.0 pb$^{-1}$ taken, respectively, at $\sqrt s= 3.773$, 3.650 and 3.6648 GeV with the BES-II detector at the BEPC collider, we measure the observed cross sections for $e^+e^-\to \pi^+\pi^-\pi^0\pi^0$, $K^+K^-\pi^0\pi^0$, $2(\pi^+\pi^-\pi^0)$, $K^+K^-\pi^+\pi^-\pi^0\pi^0$ and $3(\pi^+\pi^-)\pi^0\pi^0$ at the three energy points. Based on these cross sections we set the upper limits on the observed cross sections and the branching fractions for $\psi(3770)$ decay into these final states at 90% C.L..Comment: 7 pages, 2 figure