Exploring the influences of personal attitudes on the intention of continuing online grocery shopping after the COVID-19 pandemic.

The unprecedented COVID-19 pandemic has brought drastic changes in our daily activities. One of these essential activities is grocery shopping. In compliance with the recommended social distancing standards, many people have switched to online grocery shopping or curbside pickup to minimize possible contagion. Although the shift to online grocery shopping is substantial, it is not clear whether this change would last in the long term. This study examines the attributes and underlying attitudes that may influence individuals' future decisions on online grocery shopping. An online survey was conducted in May 2020 in South Florida to collect data for this study. The survey contained a comprehensive set of questions related to respondents' sociodemographic attributes, shopping and trip patterns, technology use, as well as attitudes toward telecommuting and online shopping. A structural equation model (SEM) was applied to examine the intervening effects of observed as well as latent attitude variables on the likelihood of online grocery shopping after the outbreak. The results indicated that those with more experience in using online grocery shopping platforms were more likely to continue purchasing their groceries online. Individuals with positive attitudes toward technology and online grocery shopping in terms of convenience, efficiency, usefulness, and easiness were more likely to adopt online grocery shopping in the future. On the other hand, pro- driving individuals were less likely to substitute online grocery shopping for in-store shopping. The results suggested that attitudinal factors could have substantial impacts on the propensity toward online grocery shopping.

Injury severity of single-vehicle large-truck crashes: accounting for heterogeneity.

This research examines the injury severity of single-vehicle large-truck crashes in Florida while exploring the role of heterogeneity. A random parameter ordered logit (RPOL) model was applied to 27,505 single-vehicle large-truck crashes from 2007 to 2016 in Florida, and the contributing factors were identified. Random parameters and interaction effects were introduced to the model to determine the heterogeneity and its potential sources. The results suggested that driving speed of 76-120 mph and defective tires were the most influential factors in crash injury severity, increasing the probability of severe crashes. Regarding truckers' attributes, asleep or fatigued conditions and driving under the influence were correlated with a higher possibility of severe crashes. Interestingly, the results showed that truckers from outside the state of Florida were less likely to cause severe single-vehicle large-truck crashes compared to their Floridian counterparts. Y-intersections were also found as a high-risk location for single-vehicle large-truck crashes, leading to more severe outcomes. Regarding heterogeneity, the results indicated that the impacts of driving speed (26-50 mph) and light condition (dark - not lighted) significantly varied among the observations, and these variations could be attributed to driver action, vision obstruction, driver distraction, roadway type and roadway alignment.

Exploring the attitudes of Millennials and Generation Xers toward ridesourcing services.

This paper presents a study investigating the potential market of ridesourcing services, with a focus on the attitudinal and preferential differences between Millennials and Generation Xers. Data obtained from a stated preference survey were utilized, where the respondents were asked to choose between a conventional mode (private vehicle driver, transit, or private vehicle passenger) and ridesourcing modes (exclusive ride and shared ride). Error component nested logit models were developed for Generation Xers and Millennials, respectively. Latent attitudes derived through factor analysis were incorporated into models. A wide range of attitudinal indicators, including general mobility attitudes, perceived benefits and concerns of shared mobility services, reasons for or against owning a car, reasons for ridings Autonomous Vehicles (AV), and the most desired AV features were considered to extract latent attitudes. Model results indicated distinct mode choice behavior between Millennials and Generation Xers. For Generation Xers, the choice to switch to ridesourcing was highly dependent on the perceived time and cost benefits of shared mobility. On the other hand, Millennials' choices were more likely to be influenced by their attitudes or desire toward technology, on-demand services, and driving stress relief. Interestingly, the joy of driving showed a negative impact on Millennials' use of shared-ride services only. The findings from this study provide a more in-depth understanding of the distinct behavior of Generation Xers and Millennials toward shared mobility services, which could help develop strategies and policies to focus more effectively on the needs and concerns of individuals based on their characteristics and attitudes and help promote sustainable transportation system.

Upregulation of VEGF-A and correlation between VEGF-A and FLT-1 expressions in Iranian multiple sclerosis patients.

Multiple sclerosis (MS) is among the most common diseases affecting brain and spinal cord. MS progression is characterized by breakdown of blood brain barrier which leads to increased vascular permeability and angiogenesis. Consequently, vascular endothelial growth factor A (VEGF) and its receptors are considered to be important components of MS progression. VEGFA and fms-related tyrosine kinase 1 (FLT1) play important roles in various aspects of MS. In this study, we investigated the relationship between these genes and MS. For this purpose, the expression levels of VEGFA and FLT1 were measured in the blood of 50 relapsing-remitting MS (RR-MS) patients and 50 healthy individuals using TaqMan quantitative real-time PCR. A significant upregulation of VEGFA expression was observed among MS patients compared with controls (p = 0.04). However, the difference in FLT1 gene expression between study groups was insignificant (p = 0.947). In addition, there was a significant positive correlation between VEGFA and FLT1 genes expressions (r = 0.769, p < 0.0001). In spite of the highly complex molecular mechanisms behind this, the findings imply participation of VEGFA in the pathogenesis of MS.

Severity analysis for large truck rollover crashes using a random parameter ordered logit model.

Large truck rollover crashes present significant financial, industrial, and social impacts. This paper presents an effort to investigate the contributing factors to large truck rollover crashes. Specific focus was placed on exploring the role of heterogeneity and the potential sources of heterogeneity regarding their impacts on injury-severity outcomes. The data used in this study contained large truck rollover crashes that occurred between 2007 and 2016 in the state of Florida. A random parameter ordered logit (RPOL) model was applied. Various driver, vehicle, roadway, and crash attributes were explored as potential predictors in the model. Their impacts were examined for the presence of heterogeneity. Interaction effects were then added to the random variables in order to detect potential sources of heterogeneity. Model results showed that the impacts of lighting conditions and driving speed had significant variation across observations, and this variation could be attributed to driver actions and driver conditions at the time of the crash, as well as driver vision obstruction. Findings from this study shed light on the direction, magnitude, and randomness of the factors that contribute to large truck rollover crashes. Findings associated with heterogeneity could help develop more effective and targeted countermeasures to improve freight safety. Driver education programs could be planned more efficiently, and advisory and warning signs could be designed in a more insightful manner by taking into account specific roadway attributes, such as sandy surfaces, downhill, curved alignment, unpaved shoulders, and lighting conditions.

Expression analysis of protein inhibitor of activated STAT (PIAS) genes in IFNß-treated multiple sclerosis patients.

Objectives: Protein inhibitors of activated STAT (PIAS) are transcription co-regulator of the Janus kinase/signal transducer and activator of transcription signaling pathway as well as nuclear factor-κB family of transcription factors. Both of them are involved in cytokine release during inflammatory response. Patients and methods: Considering the role of cytokine imbalance in the pathogenesis of multiple sclerosis (MS), we compared blood expressions of PIAS1-4 genes in 48 interferon ß (IFNß)-treated MS patients with those of healthy subjects by means of real time PCR. Results: Although the expression levels of these genes were not significantly different between MS patients and healthy subjects, significant inverse correlations have been found between PIAS1 expression and age at disease onset. PIAS2 and PIAS3 expressions were inversely correlated with Expanded Disability Status Scale (EDSS) in patients. Moreover, PIAS3 expression was correlated with disease duration in patients and with age in controls. In addition, PIAS4 expression was inversely correlated with EDSS and age at disease onset while it was positively correlated with disease duration. Conclusion: The present study provides evidences for altered expression of PIAS genes in IFNß-treated MS patients compared with healthy subjects. However, future studies are needed for elaboration of their exact function in this disorder.