39 research outputs found

    Modeling public acceptance of demand-responsive transportation: An integrated UTAUT and ITM framework

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    Demand-responsive transportation (DRT) is a flexible form of shared mobility in which service provision is shaped by the user demand. DRT has been considered a sustainable mobility solution, as it reduces CO2 emissions from fixed-route services and encourages a mode shift from private cars to shared mobility. Given that public acceptance is a key for the wider diffusion of DRT, this study explored the factors affecting usage intention for DRT in the Republic of Korea. Drawing on the unified theory of acceptance and use of technology (UTAUT) and the initial trust model (ITM), a conceptual framework was developed that linked attitudinal and psychological factors to behavioral intention for DRT usage. 1168 valid observations were collected from adults aged 19–64 years in the Republic of Korea using a structured online survey, and analyzed using structural equation modeling. The results showed that the four UTAUT constructs (performance expectancy, social influence, facilitating conditions, and environmental concerns) were directly related to intention for DRT usage. Indirect impacts of perceived safety, structural assurance, familiarity, performance expectancy, and effort expectancy on initial trust were also found. Consequently, the constructs with the greatest total effect on usage intention were (in order of relevance) initial trust, performance expectancy, social influence, and structural assurance. As one of the few attempts to examine public acceptance of DRT, it is expected that findings from this study could contribute to the literature by providing insights into potential users’ attitudes toward DRT. This study further offers guidance on designing interventions intended to promote a transition toward increased operational efficiency through policy developments for DRT, thereby achieving sustainable development

    Light-Responsive, Shape-Switchable Block Copolymer Particles

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    A robust strategy is developed for preparing light-responsive block copolymer (BCP) particles in which shape and color can be actively controlled with high spatial and temporal resolution. The key to achieving light-responsive shape transitions of BCP particles is the design and synthesis of surfactants containing light-active groups (i.e., nitrobenzyl esters and coumarin esters) that modulate the amphiphilicity and interfacial activity of the surfactants in response to light of a specific wavelength. These light-induced changes in surfactant structure modify the surface and wetting properties of BCP particles, affording both shape and morphological transitions of the particles, for example from spheres with an onion-like inner morphology to prolate or oblate ellipsoids with axially stacked nanostructures. In particular, wavelength-selective shape transformation of the BCP particles can be achieved with a mixture of two light-active surfactants that respond to different wavelengths of light (i.e., 254 and 420 nm). Through the use of light-emitting, photoresponsive surfactants, light-induced changes in both color and shape are further demonstrated. Finally, to demonstrate the potential of the light-triggered shape control of BCP particles in patterning features with microscale resolution, the shape-switchable BCP particles are successfully integrated into a patterned, free-standing hydrogel film, which can be used as a portable, high-resolution display

    Orbit Determination of KOMPSAT-1 and Cryosat-2 Satellites Using Optical Wide-field Patrol Network (OWL-Net) Data with Batch Least Squares Filter

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    The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic\ud satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte\ud Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were\ud analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly\ud depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while\ud the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were\ud determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known\ud orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit\ud determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data\ud were determined to be tens of arcsec and sub-degree level, respectively

    Orbit Determination of KOMPSAT-1 and Cryosat-2 Satellites Using Optical Wide-field Patrol Network (OWL-Net) Data with Batch Least Squares Filter

    No full text
    The optical wide-field patrol network (OWL-Net) is a Korean optical surveillance system that tracks and monitors domestic\ud satellites. In this study, a batch least squares algorithm was developed for optical measurements and verified by Monte\ud Carlo simulation and covariance analysis. Potential error sources of OWL-Net, such as noise, bias, and clock errors, were\ud analyzed. There is a linear relation between the estimation accuracy and the noise level, and the accuracy significantly\ud depends on the declination bias. In addition, the time-tagging error significantly degrades the observation accuracy, while\ud the time-synchronization offset corresponds to the orbital motion. The Cartesian state vector and measurement bias were\ud determined using the OWL-Net tracking data of the KOMPSAT-1 and Cryosat-2 satellites. The comparison with known\ud orbital information based on two-line elements (TLE) and the consolidated prediction format (CPF) shows that the orbit\ud determination accuracy is similar to that of TLE. Furthermore, the precision and accuracy of OWL-Net observation data\ud were determined to be tens of arcsec and sub-degree level, respectively

    Bicontinuous Block Copolymer Morphologies Produced by Interfacially Active, Thermally Stable Nanoparticles

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    Polymeric bicontinuous morphologies were created by thermal annealing mixtures of poly(styrene-<i>b</i>-2-vinylpyridine) (PS-<i>b</i>-P2VP) block copolymers and stabilized Au-core/Pt-shell (Au–Pt) nanoparticles. These Au–Pt nanoparticles have a cross-linked polymeric shell to promote thermal stability and are designed to adsorb strongly to the interface of the PS-<i>b</i>-P2VP block copolymer due to the favorable interaction between P2VP block and the exterior of the cross-linked shell of the nanoparticle. The interfacial activity of these Au–Pt nanoparticles under thermal annealing conditions leads to decrease in domain size of the lamellar diblock copolymer. As nanoparticle volume fraction ϕ<sub>p</sub> was increased, a transition from a lamellar to a bicontinuous morphology was observed. Significantly, the effect of these shell-cross-linked Au–Pt nanoparticles under thermal annealing conditions was similar to those of traditional polymer grafted Au nanoparticles under solvent annealing conditions reported previously. These results suggest a general strategy for producing bicontinuous block copolymer structures by thermal processing through judicious selection of polymeric ligands, nanoparticle core, and block copolymer
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