Toward the multilevel older person's transportation and road safety model: A new perspective on the role of demographic, functional, and psychosocial factors

Objectives Self-regulation refers to the practice of using self-imposed restrictions to protect oneself from situations that are, or are perceived to be, unsafe. Within the driving context, self-regulation refers the compensatory practices that some older adults adopt to restrict their driving to situations in which they feel safe. However, the way in which demographic, functional, and psychosocial factors, and the interactions between these factors, influence older adults’ driving self-regulation is not well understood. Improving this understanding could lead to new ways of considering the mobility concerns faced by older drivers. Method A systematic review of the current literature was conducted to explore this issue. Twenty-nine empirical studies investigating the factors associated with older adults’ self-regulatory driving behaviors were examined. Results The review findings were used to construct the Multilevel Older Persons Transportation and Road Safety (MOTRS) model. The MOTRS model proposes that individual and environmental factors such as age, gender, and the availability of alternative transportation predict older adults’ practice of driving-related self-regulation. However, these variables influence self-regulation through psychosocial variables such as driving confidence, affective attitude, and instrumental attitude toward driving. Discussions The MOTRS model extends previous attempts to model older adults’ driving by focusing on a novel target, driving self-regulation, and by including a wider range of predictors identified on the basis of the systematic literature review. This focus enables consideration of broader mobility issues and may inform new strategies to support the mobility of older adults.

Demand for ecolabeled seafood in the Japanese market: A conjoint analysis of the impact of information and interaction with other labels

The use of seafood ecolabels is expanding in the world marketplace, but so are labels indicating other product attributes, such as country of origin and wild vs. farmed. The interactive effects of these labels and attributes in evaluating consumers' preferences for ecolabeled seafood are relatively unexplored. In this paper we investigate (1) the direct and interactive effects of seafood ecolabels with other common fish labels, and (2) how consumers' perceptions about the state of marine stocks and the valuation of ecolabels may be affected by different information. We find moderate interactive effects between ecolabels and country of origin labels, whereas the valuation for seafood ecolabels is fairly high. In terms of information, we find that consumers' perceptions about fish stock levels changed (negatively) after receiving information on declining stock levels, and more sensationalized information led to increased change. However, valuation for a seafood ecolabel increases only when the information was perceived positively (credible/interesting); whereas exaggerated information (which was also perceived less credible) had insignificant effects on WTP.

A review of hydrothermal liquefaction bio-crude properties and prospects for upgrading to transportation fuels

Hydrothermal liquefaction (HTL) presents a viable route for converting a vast range of materials into liquid fuel, without the need for pre-drying. Currently, HTL studies produce bio-crude with properties that fall short of diesel or biodiesel standards. Upgrading bio-crude improves the physical and chemical properties to produce a fuel corresponding to diesel or biodiesel. Properties such as viscosity, density, heating value, oxygen, nitrogen and sulphur content, and chemical composition can be modified towards meeting fuel standards using strategies such as solvent extraction, distillation, hydrodeoxygenation and catalytic cracking. This article presents a review of the upgrading technologies available, and how they might be used to make HTL bio-crude into a transportation fuel that meets current fuel property standards.

Automatic surveillance in transportation hubs: No Longer just about catching the bad guy

As critical infrastructure such as transportation hubs continue to grow in complexity, greater importance is placed on monitoring these facilities to ensure their secure and efficient operation. In order to achieve these goals, technology continues to evolve in response to the needs of various infrastructure. To date, however, the focus of technology for surveillance has been primarily concerned with security, and little attention has been placed on assisting operations and monitoring performance in real-time. Consequently, solutions have emerged to provide real-time measurements of queues and crowding in spaces, but have been installed as system add-ons (rather than making better use of existing infrastructure), resulting in expensive infrastructure outlay for the owner/operator, and an overload of surveillance systems which in itself creates further complexity. Given many critical infrastructure already have camera networks installed, it is much more desirable to better utilise these networks to address operational monitoring as well as security needs. Recently, a growing number of approaches have been proposed to monitor operational aspects such as pedestrian throughput, crowd size and dwell times. In this paper, we explore how these techniques relate to and complement the more commonly seen security analytics, and demonstrate the value that can be added by operational analytics by demonstrating their performance on airport surveillance data. We explore how multiple analytics and systems can be combined to better leverage the large amount of data that is available, and we discuss the applicability and resulting benefits of the proposed framework for the ongoing operation of airports and airport networks.

Transportation disadvantage impedance indexing: A methodological approach to reduce policy shortcomings

Access to transport systems and the connection to such systems provided to essential economic and social activities are critical to determine households' transportation disadvantage levels. In spite of the developments in better identifying transportation disadvantaged groups, the lack of effective policies resulted in the continuum of the issue as a significant problem. This paper undertakes a pilot case investigation as test bed for a new approach developed to reduce transportation policy shortcomings. The approach, ‘disadvantage-impedance index’, aims to ease transportation disadvantages by employing representative parameters to measure the differences between policy alternatives run in a simulation environment. Implemented in the Japanese town of Arao, the index uses trip-making behaviour and resident stated preference data. The results of the index reveal that even a slight improvement in accessibility and travel quality indicators makes a significant difference in easing disadvantages. The index, integrated into a four-step model, proves to be highly robust and useful in terms of quick diagnosis in capturing effective actions, and developing potentially efficient policies.

Revisiting the Task-Capability interface model for incorporating human factors into car-following models

Human factors such as distraction, fatigue, alcohol and drug use are generally ignored in car-following (CF) models. Such ignorance overestimates driver capability and leads to most CF models’ inability in realistically explaining human driving behaviors. This paper proposes a novel car-following modeling framework by introducing the difficulty of driving task measured as the dynamic interaction between driving task demand and driver capability. Task difficulty is formulated based on the famous Task Capability Interface (TCI) model, which explains the motivations behind driver’s decision making. The proposed method is applied to enhance two popular CF models: Gipps’ model and IDM, and named as TDGipps and TDIDM respectively. The behavioral soundness of TDGipps and TDIDM are discussed and their stabilities are analyzed. Moreover, the enhanced models are calibrated with the vehicle trajectory data, and validated to explain both regular and human factor influenced CF behavior (which is distraction caused by hand-held mobile phone conversation in this paper). Both the models show better performance than their predecessors, especially in presence of human factors.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

A framework for freeway incident modeling and traffic re-routing

This paper proposes an analytical Incident Traffic Management framework for freeway incident modeling and traffic re-routing. The proposed framework incorporates an econometric incident duration model and a traffic re-routing optimization module. The incident duration model is used to estimate the expected duration of the incident and thus determine the planning horizon for the re-routing module. The re-routing module is a CTM-based Single Destination System Optimal Dynamic Traffic Assignment model that generates optimal real-time strategies of re-routing freeway traffic to its adjacent arterial network during incidents. The proposed framework has been applied to a case study network including a freeway and its adjacent arterial network in South East Queensland, Australia. The results from different scenarios of freeway demand and incident blockage extent have been analyzed and advantages of the proposed framework are demonstrated.

Photochemical design of stimuli-responsive nanoparticles prepared by supramolecular host–guest chemistry

We introduce the design of a thermoresponsive nanoparticle via sacrificial micelle formation based on supramolecular host–guest chemistry. Reversible addition–fragmentation chain transfer (RAFT) polymerization was employed to synthesize well-defined polymer blocks of poly(N,N-dimethylacrylamide) (poly(DMAAm)) (Mn,SEC = 10 700 g mol–1, Đ = 1.3) and poly(N-isopropylacrylamide) (poly(NiPAAm)) (Mn,SEC = 39 700 g mol–1, Đ = 1.2), carrying supramolecular recognition units at the chain termini. Further, 2-methoxy-6-methylbenzaldehyde moieties (photoenols, PE) were statistically incorporated into the backbone of the poly(NiPAAm) block as photoactive cross-linking units. Host–guest interactions of adamantane (Ada) (at the terminus of the poly(NiPAAm/PE) chain) and β-cyclodextrin (CD) (attached to the poly(DMAAm chain end) result in a supramolecular diblock copolymer. In aqueous solution, the diblock copolymer undergoes micellization when heated above the lower critical solution temperature (LCST) of the thermoresponsive poly(NiPAAm/PE) chain, forming the core of the micelle. Via the addition of a 4-arm maleimide cross-linker and irradiation with UV light, the micelle is cross-linked in its core via the photoinduced Diels–Alder reaction of maleimide and PE units. The adamantyl–cyclodextrin linkage is subsequently cleaved by the destruction of the β-CD, affording narrowly distributed thermoresponsive nanoparticles with a trigger temperature close to 30 °C. Polymer chain analysis was performed via size exclusion chromatography (SEC), nuclear magnetic resonance (NMR) spectroscopy, and dynamic light scattering (DLS). The size and thermoresponsive behavior of the micelles and nanoparticles were investigated via DLS as well as atomic force microscopy (AFM).

Dynamic, invivo, real-time detection of retinal oxidative status in a model of elevated intraocular pressure using a novel, reversibly responsive, profluorescent nitroxide probe

Changes to the redox status of biological systems have been implicated in the pathogenesis of a wide variety of disorders including cancer, Ischemia-reperfusion (I/R) injury and neurodegeneration. In times of metabolic stress e.g. ischaemia/reperfusion, reactive oxygen species (ROS) production overwhelms the intrinsic antioxidant capacity of the cell, damaging vital cellular components. The ability to quantify ROS changes in vivo, is therefore essential to understanding their biological role. Here we evaluate the suitability of a novel reversible profluorescent probe containing a redox-sensitive nitroxide moiety (methyl ester tetraethylrhodamine nitroxide, ME-TRN), as an in vivo, real-time reporter of retinal oxidative status. The reversible nature of the probe's response offers the unique advantage of being able to monitor redox changes in both oxidizing and reducing directions in real time. After intravitreal administration of the ME-TRN probe, we induced ROS production in rat retina using an established model of complete, acute retinal ischaemia followed by reperfusion. After restoration of blood flow, retinas were imaged using a Micron III rodent fundus fluorescence imaging system, to quantify the redox-response of the probe. Fluorescent intensity declined during the first 60 min of reperfusion. The ROS-induced change in probe fluorescence was ameliorated with the retinal antioxidant, lutein. Fluorescence intensity in non-Ischemia eyes did not change significantly. This new probe and imaging technology provide a reversible and real-time response to oxidative changes and may allow the in vivo testing of antioxidant therapies of potential benefit to a range of diseases linked to oxidative stress

Cyclosporin-responsive enteropathy and protracted diarrhea

We describe a child bom to unrelated parents who developed severe protracted secretory type diarrhea associated with subtotal villus atrophy and intestinal inflammation at the age of 19 months. No infectious, metabolic, or anatomical basis for this condition was identified and the child required total parenteral nutrition for a period of 18 months despite trials of special enteral formulas, steroids, and anti-inflammatory agents. This refractory “enteropathy” responded dramatically to the introduction of cyclosporin, with cessation of the secretory diarrhea, recovery from the enteropathy, and cessation of parenteral nutrition. The symptoms relapsed when cyclosporin was briefly discontinued and improved following reintroduction of this drug. This experience suggests a role for immune factors in the pathogenesis of the enteropathy in this case and that a trial of cyclosporin is worthy of consideration in similar cases. © 1990 Raven Press, Ltd., New York.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.

Demand for, and impediments to, the disclosure of information about climate change-related corporate governance practices

Based on a survey of climate change experts in different stakeholder groups and interviews with corporate climate change managers, this study provides insights into the gap between what information stakeholders expect, and what Australian corporations disclose. This paper focuses on annual reports and sustainability reports with specific reference to the disclosure of climate change-related corporate governance practices. The findings culminate in the governance practises. Interview results indicate that the low levels of disclosures made by Australian companies may be due to a number of factors. A lack of proactive stakeholder engagement and an apparent preoccupation with financial performance and advancing shareholders interest, coupled with a failure by managers to accept accountability, seems to go a long way to explaining low levels of disclosure.

Links between emotional job demands and occupational well-being: Age differences depend on type of demand

In the growing health care sector, meeting emotional job demands is crucial to organizational outcomes but may negatively affect employees’ well-being. Drawing on the emotional aging literature, we predicted that two common emotional job demands, display demands (expressing positive, negative, and neutral emotions toward clients) and sensitivity demands (knowing what the client is feeling), affect older health care workers’ occupational well-being differently than young workers, as indicated by their job satisfaction and need for recovery. Survey data from employees of senior care homes (N = 141, aged between 17 and 62 years) confirmed the moderating role of age for links between emotional job demands and occupational well-being indicators. Emotional display demands were generally positively associated with emotional dissonance; however, the association between demands to display neutral emotions and emotional dissonance was stronger among young compared with older employees. In contrast, among older but not young employees, emotional dissonance was negatively associated with job satisfaction, and emotional sensitivity demands were positively associated with need for recovery. These findings suggest that age may confer both advantages (facing neutral display demands) and vulnerabilities (facing emotional dissonance and sensitivity demands) in managing emotional job demands.

Comparing China's city transportation and economic networks

The city system has been a prevailing research issue in the fields of urban geography and regional economics. Not only do the relationships between cities in the city system exist in the form of rankings, but also in a more general network form. Previous work has examined the spatial structure of the city system in terms of its separate industrial networks, such as in transportation and economic activity, but little has been done to compare different networks. To rectify this situation, this study analyzes and reveals the spatial structural features of China’s city system by comparing its transportation and economic urban networks, thus providing new avenues for research on China’s city network. The results indicate that these two networks relate with each other by sharing structural equivalence with a basic diamond structure and a layered intercity structure decreasing outwards from the national centers. A decoupling effect also exists between them as the transportation network contributes to a balanced regional development, while the economic network promotes agglomeration economies. The law of economic development and the government both play important roles in the articulation between these two networks, and the gap between them can be shortened by related policy reforms and the improvement of the transportation network.