State-of-the-art of Longitudinal Travel Surveys – A Comparison of the MOP and MPN

Longitudinal travel surveys are needed to capture individual travel behaviour changes. Only two longitudinal tavel surveys of national relevance are currently in operation, the German Mobility Panel (MOP) since 1994 and the Netherlands Mobility Panel (MPN) since 2013. This paper provides an overview of both panels\u27 differences and similarities in design and data collection. Furthermore, representativeness, diary fatigue and non-random attrition are assessed in both panels to show the challenges panel surveys have to deal with. Overall, this paper shows important aspects of a panel survey that should be considered when designing a new longitudinal travel survey

Defining, measuring, and modeling passenger's in-vehicle experience and acceptance of automated vehicles

Automated vehicle acceptance (AVA) has been measured mostly subjectively by questionnaires and interviews, with a main focus on drivers inside automated vehicles (AVs). To ensure that AVs are widely accepted by the public, ensuring the acceptance by both drivers and passengers is key. The in-vehicle experience of passengers will determine the extent to which AVs will be accepted by passengers. A comprehensive understanding of potential assessment methods to measure the passenger experience in AVs is needed to improve the in-vehicle experience of passengers and thereby the acceptance. The present work provides an overview of assessment methods that were used to measure a driver's behavior, and cognitive and emotional states during (automated) driving. The results of the review have shown that these assessment methods can be classified by type of data-collection method (e.g., questionnaires, interviews, direct input devices, sensors), object of their measurement (i.e., perception, behavior, state), time of measurement, and degree of objectivity of the data collected. A conceptual model synthesizes the results of the literature review, formulating relationships between the factors constituting the in-vehicle experience and AVA acceptance. It is theorized that the in-vehicle experience influences the intention to use, with intention to use serving as predictor of actual use. The model also formulates relationships between actual use and well-being. A combined approach of using both subjective and objective assessment methods is needed to provide more accurate estimates for AVA, and advance the uptake and use of AVs.Comment: 22 pages, 1 figur

A CRISPR-based screen for Hedgehog signaling provides insights into ciliary function and ciliopathies.

Primary cilia organize Hedgehog signaling and shape embryonic development, and their dysregulation is the unifying cause of ciliopathies. We conducted a functional genomic screen for Hedgehog signaling by engineering antibiotic-based selection of Hedgehog-responsive cells and applying genome-wide CRISPR-mediated gene disruption. The screen can robustly identify factors required for ciliary signaling with few false positives or false negatives. Characterization of hit genes uncovered novel components of several ciliary structures, including a protein complex that contains δ-tubulin and ε-tubulin and is required for centriole maintenance. The screen also provides an unbiased tool for classifying ciliopathies and showed that many congenital heart disorders are caused by loss of ciliary signaling. Collectively, our study enables a systematic analysis of ciliary function and of ciliopathies, and also defines a versatile platform for dissecting signaling pathways through CRISPR-based screening

Empowering Global Chemical Biology at the Dawn of the New Decade

On January 22–24, 2020, scientific luminaries across the far-flung corners of chemical biology gathered in Geneva, Switzerland, to deliver their latest and greatest discoveries in the field. Generously supported by the Swiss National Science Foundation (SNSF), our academic partners, and industrial and journal sponsors, this chemical biology symposium in our opinion will remain memorable for several years to come, not only because of the diversity in scientific topics delivered by our invited eminent speakers as detailed herein, but it is also one-of-a-kind conference which reflected multidimensional balance—balance in age and gender, across these speakers. Such a remarkable speaker line-up doubtless attracted >200 attendees from academia and industry in and around Switzerland and beyond, representing a huge swathe of subfields of science interfacing chemistry and biology. Poster presentations from students and postdocs further spotlighted the exciting diversity in the field: spanning biosynthesis, optochemical genetics, genetic code expansion, lipid chemical biology, redox perturbation, microfluidics screening, membrane signaling, immune modulation, DNA circuits, and synthetic and computational biology. This notable heterogeneity in scientific topics also went hand-in-hand with the diverse representations of student/postdoc trainees from 56 institutions covering 14 countries worldwide, allowing us to witness science as a truly global enterprise

Modeling Transfers in Multimodal Trips: Explaining Correlations

Transfers are essential parts of multimodal trips. A detailed description of the transfer process identifies time, costs, and effort related to the different stages of the transfer process. Since inclusion of multiple transfer attributes generally leads to high correlations between parameter estimates, most travel choice models only distinguish a small number of transfer attributes. When attributes are highly correlated, it is difficult to establish their impact on the travel choice process, especially when more advanced random utility models are used. By analyzing path-size logit models that differ in the way the transfer process is accounted for, combinations of transfer attributes that best reflect the role of transfers in the travel choice process are established. The analysis uses revealed-preference data on interurban multimodal train trip making in the Netherlands. Apart from log likelihood values, correlations between different classes of transfer attributes are used to evaluate the different models. It is shown that it is better to exclude the number of transfers from the utility specification because its inclusion results in high correlations with other transfer attributes. Correlations are explained from the different stages in the transfer process to which transfer attributes relate. In addition, it is demonstrated that transfers can alternatively be accounted for by representing the transfer process in travel choice models at a high detail level and thereby prevent high correlations. It turns out that the best model contains mode indicators, railway station indicators, parking costs, transfer walking times, and transfer waiting times

From Phenotypic Hit to Chemical Probe: Chemical Biology Approaches to Elucidate Small Molecule Action in Complex Biological Systems

Biologically active small molecules have a central role in drug development, and as chemical probes and tool compounds to perturb and elucidate biological processes. Small molecules can be rationally designed for a given target, or a library of molecules can be screened against a target or phenotype of interest. Especially in the case of phenotypic screening approaches, a major challenge is to translate the compound-induced phenotype into a well-defined cellular target and mode of action of the hit compound. There is no “one size fits all” approach, and recent years have seen an increase in available target deconvolution strategies, rooted in organic chemistry, proteomics, and genetics. This review provides an overview of advances in target identification and mechanism of action studies, describes the strengths and weaknesses of the different approaches, and illustrates the need for chemical biologists to integrate and expand the existing tools to increase the probability of evolving screen hits to robust chemical probes

MULTIMODAL CHOICE SET COMPOSITION: ANALYSIS OF REPORTED AND GENERATED CHOICE SETS

Multimodal trips are common in today\u27s travel and are expected to become more important. An individual embarking on a multimodal trip faces a number of choice dimensions, such as access and egress mode or modes, origin and destination railway stations, train service types, and transfer stations. For each of these choice dimensions, multiple alternatives are available. To gain insight into the structure and complexity of multimodal trips, a dedicated survey was conducted. Its results include detailed data on chosen trips and reported trip alternatives of 511 multimodal home-bound trips in which the train is the main transport mode. Furthermore, objective choice sets were generated for these respondents and compared with the chosen trips and the reported trip alternatives. It can be concluded that many alternatives are available to travelers, whereas only a limited subset of those alternatives is actually perceived. Even fewer alternatives are actually considered in the choice process. The obtained knowledge of the chosen trips and subjective choice sets can be used to improve choice set generation algorithms and to define strategies for modeling route choice in multimodal networks

Modelling Route Choice Behaviour in Multi-Modal Transport Networks

Few studies on interurban train journeys have models that specifically reflect the route choice behavior of interurban train users. This paper presents findings from model estimations using revealed choice data giving detailed insights into interurban multimodal choice behavior of train users. The study also seeks to determine the influence of trip attributes on the quality and competitiveness of multimodal alternatives. The analysis covers the entire trip from origin to destination, including access and egress legs to and from the train network. The focus is on preferences for different feeder modes, railway station types and train service types as well as on the relative influence of time elements and transfer penalties. Data from dedicated surveys are used including individual objective choice sets of 235 multi-modal homebound trips in which train is the main transport mode. The observed trips have origins and destinations within the Rotterdam-Dordrecht region in the Netherlands with an average total trip time of 50 minutes. Hierarchical nested logit models are estimated to take account of unobserved similarities between alternatives at the home-end and the activity-end of the trip respectively, resulting in two-level nesting structures which differentiate between intercity and non-intercity railway station types at the upper level and between transit and private access modes at the lower level. In order to reflect the multi-dimensional structure of the data, a more advanced so-called multi-nested generalized extreme value model according to the principles of differentiation has been estimated. This significantly improves the explanatory power and stresses the importance of the home-end of the multimodal trip. Findings show that the average traveler attaches different weights to the observable trip resistance attributes