Blending as a process of creating neologisms in modern English: a study based on electronic media

http://tartu.ester.ee/record=b2694560~S1*es

What is the market potential for on-demand services as a train station access mode?

Ride-hailing and other on-demand mobility services are often proposed as a solution for improving the accessibility of public transport by offering first/last mile connectivity. We study the potential of using on-demand services to improve train station access by means of a three-step sequential stated preference survey. We compare the preferences for on-demand services with the bicycle, car and public transport for accessing two alternative train stations at different access distances. We estimate a joint access mode and train station choice model. By estimating a latent class choice model, we uncover five distinct segments in the population. We describe the classes based on their stated preferences, travel behaviour, attitudes towards new mobility and their socio-demographic characteristics. The two largest classes, accounting for over half of the sample, are the most likely to adopt on-demand services. Having an average willingness-to-pay, they would choose these services for longer access distances, competing mainly with the car and local public transport. Applying the model estimates, we observe that while on-demand services mainly compete with public transportation (obtaining most of its travellers from it), they are not able to fully substitute a public transport service for train station access, as many users would switch to cycling or driving a car, rather than opting for the on-demand service

Potential of on-demand services for urban travel

On-demand mobility services are promising to revolutionise urban travel, but preliminary studies are showing that they may actually increase the total vehicle miles travelled, thereby worsening road congestion in cities. In this study, we assess the demand for on-demand mobility services in urban areas, using a stated preference survey, to understand the potential impact of introducing on-demand services on the current modal split. The survey was carried out in the Netherlands and offered respondents a choice between bike, car, public transport and on-demand services. 1,063 valid responses are analysed with a multinomial logit and a latent class choice model. By means of the latter, we uncover four distinctive groups of travellers based on the observed choice behaviour. The majority of the sample (55%) are avid cyclists and do not see on-demand mobility as an alternative for making urban trips. Two classes (27% and 9% of the sample) would potentially use on-demand services: the former is fairly time-sensitive and would thus use on-demand service if they were sufficiently fast. The latter class however is highly cost-sensitive, and would therefore use on-demand mobility primarily if it is cheap. The fourth class (9%) shows very limited potential for using on-demand services

Edge Guided Reconstruction for Compressive Imaging

We propose EdgeCS—an edge guided compressive sensing reconstruction approach—to recover images of higher quality from fewer measurements than the current methods. Edges are important image features that are used in various ways in image recovery, analysis, and understanding. In compressive sensing, the sparsity of image edges has been successfully utilized to recover images. However, edge detectors have not been used on compressive sensing measurements to improve the edge recovery and subsequently the image recovery. This motivates us to propose EdgeCS, which alternatively performs edge detection and image reconstruction in a mutually beneficial way. The edge detector of EdgeCS is designed to faithfully return partial edges from intermediate image reconstructions even though these reconstructions may still have noise and artifacts. For complex-valued images, it incorporates joint sparsity between the real and imaginary components. EdgeCS has been implemented with both isotropic and anisotropic discretizations of total variation and tested on incomplete k-space (spectral Fourier) samples. It applies to other types of measurements as well. Experimental results on large-scale real/complex-valued phantom and magnetic resonance (MR) images show that EdgeCS is fast and returns high-quality images. For example, it exactly recovers the 256×256 Shepp–Logan phantom from merely 7 radial lines (3.03% k-space), which is impossible for most existing algorithms. It is able to accurately reconstruct a 512 × 512 MR image with 0.05 white noise from 20.87% radial samples. On complex-valued MR images, it obtains recoveries with faithful phases, which are important in many medical applications. Each of these tests took around 30 seconds on a standard PC. Finally, the algorithm is GPU friendly

Identification of a Unique TGF-β Dependent Molecular and Functional Signature in Microglia

Microglia are myeloid cells of the central nervous system (CNS) that participate both in normal CNS function and disease. We investigated the molecular signature of microglia and identified 239 genes and 8 microRNAs that were uniquely or highly expressed in microglia vs. myeloid and other immune cells. Out of 239 genes, 106 were enriched in microglia as compared to astrocytes, oligodendrocytes and neurons. This microglia signature was not observed in microglial lines or in monocytes recruited to the CNS and was also observed in human microglia. Based on this signature, we found a crucial role for TGF-β in microglial biology that included: 1) the requirement of TGF-β for the in vitro development of microglia that express the microglial molecular signature characteristic of adult microglia; and 2) the absence of microglia in CNS TGF-β1 deficient mice. Our results identify a unique microglial signature that is dependent on TGF-β signaling which provides insights into microglial biology and the possibility of targeting microglia for the treatment of CNS disease

Expression of LIM kinase 1 is associated with reversible G1/S phase arrest, chromosomal instability and prostate cancer

<p>Abstract</p> <p>Background</p> <p>LIM kinase 1 (LIMK1), a LIM domain containing serine/threonine kinase, modulates actin dynamics through inactivation of the actin depolymerizing protein cofilin. Recent studies have indicated an important role of LIMK1 in growth and invasion of prostate and breast cancer cells; however, the molecular mechanism whereby LIMK1 induces tumor progression is unknown. In this study, we investigated the effects of ectopic expression of LIMK1 on cellular morphology, cell cycle progression and expression profile of LIMK1 in prostate tumors.</p> <p>Results</p> <p>Ectopic expression of LIMK1 in benign prostatic hyperplasia cells (BPH), which naturally express low levels of LIMK1, resulted in appearance of abnormal mitotic spindles, multiple centrosomes and smaller chromosomal masses. Furthermore, a transient G1/S phase arrest and delayed G2/M progression was observed in BPH cells expressing LIMK1. When treated with chemotherapeutic agent Taxol, no metaphase arrest was noted in these cells. We have also noted increased nuclear staining of LIMK1 in tumors with higher Gleason Scores and incidence of metastasis.</p> <p>Conclusion</p> <p>Our results show that increased expression of LIMK1 results in chromosomal abnormalities, aberrant cell cycle progression and alteration of normal cellular response to microtubule stabilizing agent Taxol; and that LIMK1 expression may be associated with cancerous phenotype of the prostate.</p