302 research outputs found
The relationship between case-control differential gene expression from brain tissue and genetic associations in schizophrenia
This is the final version. Available on open access from Wiley via the DOI in this recordData availability statement: The data that supports the findings of this study are available in the supplementary material of this article.Large numbers of genetic loci have been identified that are known to contain common risk alleles for schizophrenia, but linking associated alleles to specific risk genes remains challenging. Given that most alleles that influence liability to schizophrenia are thought to do so by altered gene expression, intuitively, case-control differential gene expression studies should highlight genes with a higher probability of being associated with schizophrenia and could help identify the most likely causal genes within associated loci. Here, we test this hypothesis by comparing transcriptome analysis of the dorsolateral prefrontal cortex from 563 schizophrenia cases and 802 controls with genome-wide association study (GWAS) data from the third wave study of the Psychiatric Genomics Consortium. Genes differentially expressed in schizophrenia were not enriched for common allelic association statistics compared with other brain-expressed genes, nor were they enriched for genes within associated loci previously reported to be prioritized by genetic fine-mapping. Genes prioritized by Summary-based Mendelian Randomisation were underexpressed in cases compared to other genes in the same GWAS loci. However, the overall strength and direction of expression change predicted by SMR were not related to that observed in the differential expression data. Overall, this study does not support the hypothesis that genes identified as differentially expressed from RNA sequencing of bulk brain tissue are enriched for those that show evidence for genetic associations. Such data have limited utility for prioritizing genes in currently associated loci in schizophrenia.Medical Research Council (MRC)National Institute of Mental Health (USA
Effects of local hypothermia-rewarming on physiology, metabolism and inflammation of acutely injured human spinal cord.
In five patients with acute, severe thoracic traumatic spinal cord injuries (TSCIs), American spinal injuries association Impairment Scale (AIS) grades A-C, we induced cord hypothermia (33 °C) then rewarming (37 °C). A pressure probe and a microdialysis catheter were placed intradurally at the injury site to monitor intraspinal pressure (ISP), spinal cord perfusion pressure (SCPP), tissue metabolism and inflammation. Cord hypothermia-rewarming, applied to awake patients, did not cause discomfort or neurological deterioration. Cooling did not affect cord physiology (ISP, SCPP), but markedly altered cord metabolism (increased glucose, lactate, lactate/pyruvate ratio (LPR), glutamate; decreased glycerol) and markedly reduced cord inflammation (reduced IL1β, IL8, MCP, MIP1α, MIP1β). Compared with pre-cooling baseline, rewarming was associated with significantly worse cord physiology (increased ICP, decreased SCPP), cord metabolism (increased lactate, LPR; decreased glucose, glycerol) and cord inflammation (increased IL1β, IL8, IL4, IL10, MCP, MIP1α). The study was terminated because three patients developed delayed wound infections. At 18-months, two patients improved and three stayed the same. We conclude that, after TSCI, hypothermia is potentially beneficial by reducing cord inflammation, though after rewarming these benefits are lost due to increases in cord swelling, ischemia and inflammation. We thus urge caution when using hypothermia-rewarming therapeutically in TSCI
Investigating the potential of novel non-woven fabrics for efficient pollination control in plant breeding
Internal temperature (a) and vapour pressure deficit (hPa, b) response rates to a transition from dark to light (0 to 880 umolm-2s-1) above the pollination control bags. Box plots of the average maximum temperature (c) and VPD (d) are shown for each bag type. Significant differences are denoted by different lower case letters for temperature and VPD and are based on 11 replicates.</p
The Conserved Tarp Actin Binding Domain Is Important for Chlamydial Invasion
The translocated actin recruiting phosphoprotein (Tarp) is conserved among all pathogenic chlamydial species. Previous reports identified single C. trachomatis Tarp actin binding and proline rich domains required for Tarp mediated actin nucleation. A peptide antiserum specific for the Tarp actin binding domain was generated and inhibited actin polymerization in vitro and C. trachomatis entry in vivo, indicating an essential role for Tarp in chlamydial pathogenesis. Sequence analysis of Tarp orthologs from additional chlamydial species and C. trachomatis serovars indicated multiple putative actin binding sites. In order to determine whether the identified actin binding domains are functionally conserved, GST-Tarp fusions from multiple chlamydial species were examined for their ability to bind and nucleate actin. Chlamydial Tarps harbored variable numbers of actin binding sites and promoted actin nucleation as determined by in vitro polymerization assays. Our findings indicate that Tarp mediated actin binding and nucleation is a conserved feature among diverse chlamydial species and this function plays a critical role in bacterial invasion of host cells
The TOBY Study. Whole body hypothermia for the treatment of perinatal asphyxial encephalopathy: A randomised controlled trial
<p>Abstract</p> <p>Background</p> <p>A hypoxic-ischaemic insult occurring around the time of birth may result in an encephalopathic state characterised by the need for resuscitation at birth, neurological depression, seizures and electroencephalographic abnormalities. There is an increasing risk of death or neurodevelopmental abnormalities with more severe encephalopathy. Current management consists of maintaining physiological parameters within the normal range and treating seizures with anticonvulsants.</p> <p>Studies in adult and newborn animals have shown that a reduction of body temperature of 3–4°C after cerebral insults is associated with improved histological and behavioural outcome. Pilot studies in infants with encephalopathy of head cooling combined with mild whole body hypothermia and of moderate whole body cooling to 33.5°C have been reported. No complications were noted but the group sizes were too small to evaluate benefit.</p> <p>Methods/Design</p> <p>TOBY is a multi-centre, prospective, randomised study of term infants after perinatal asphyxia comparing those allocated to "intensive care plus total body cooling for 72 hours" with those allocated to "intensive care without cooling".</p> <p>Full-term infants will be randomised within 6 hours of birth to either a control group with the rectal temperature kept at 37 +/- 0.2°C or to whole body cooling, with rectal temperature kept at 33–34°C for 72 hours. Term infants showing signs of moderate or severe encephalopathy +/- seizures have their eligibility confirmed by cerebral function monitoring. Outcomes will be assessed at 18 months of age using neurological and neurodevelopmental testing methods.</p> <p>Sample size</p> <p>At least 236 infants would be needed to demonstrate a 30% reduction in the relative risk of mortality or serious disability at 18 months.</p> <p>Recruitment was ahead of target by seven months and approvals were obtained allowing recruitment to continue to the end of the planned recruitment phase. 325 infants were recruited.</p> <p>Primary outcome</p> <p>Combined rate of mortality and severe neurodevelopmental impairment in survivors at 18 months of age. Neurodevelopmental impairment will be defined as any of:</p> <p>• Bayley mental developmental scale score less than 70</p> <p>• Gross Motor Function Classification System Levels III – V</p> <p>• Bilateral cortical visual impairments</p> <p>Trial Registration</p> <p>Current Controlled Trials ISRCTN89547571</p
Effects of Marine Reserves versus Nursery Habitat Availability on Structure of Reef Fish Communities
No-take marine fishery reserves sustain commercial stocks by acting as buffers against overexploitation and enhancing fishery catches in adjacent areas through spillover. Likewise, nursery habitats such as mangroves enhance populations of some species in adjacent habitats. However, there is lack of understanding of the magnitude of stock enhancement and the effects on community structure when both protection from fishing and access to nurseries concurrently act as drivers of fish population dynamics. In this study we test the separate as well as interactive effects of marine reserves and nursery habitat proximity on structure and abundance of coral reef fish communities. Reserves had no effect on fish community composition, while proximity to nursery habitat only had a significant effect on community structure of species that use mangroves or seagrass beds as nurseries. In terms of reef fish biomass, proximity to nursery habitat by far outweighed (biomass 249% higher than that in areas with no nursery access) the effects of protection from fishing in reserves (biomass 21% lower than non-reserve areas) for small nursery fish (≤25 cm total length). For large-bodied individuals of nursery species (>25 cm total length), an additive effect was present for these two factors, although fish benefited more from fishing protection (203% higher biomass) than from proximity to nurseries (139% higher). The magnitude of elevated biomass for small fish on coral reefs due to proximity to nurseries was such that nursery habitats seem able to overrule the usually positive effects on fish biomass by reef reserves. As a result, conservation of nursery habitats gains importance and more consideration should be given to the ecological processes that occur along nursery-reef boundaries that connect neighboring ecosystems
Age is no barrier: predictors of academic success in older learners
Although predictors of academic success have been identified in young adults, such predictors are unlikely to translate directly to an older student population, where such information is scarce. The current study aimed to examine cognitive, psychosocial, lifetime, and genetic predictors of university-level academic performance in older adults (50–79 years old). Participants were mostly female (71%) and had a greater than high school education level (M = 14.06 years, SD = 2.76), on average. Two multiple linear regression analyses were conducted. The first examined all potential predictors of grade point average (GPA) in the subset of participants who had volunteered samples for genetic analysis (N = 181). Significant predictors of GPA were then re-examined in a second multiple linear regression using the full sample (N = 329). Our data show that the cognitive domains of episodic memory and language processing, in conjunction with midlife engagement in cognitively stimulating activities, have a role in predicting academic performance as measured by GPA in the first year of study. In contrast, it was determined that age, IQ, gender, working memory, psychosocial factors, and common brain gene polymorphisms linked to brain function, plasticity and degeneration (APOE, BDNF, COMT, KIBRA, SERT) did not influence academic performance. These findings demonstrate that ageing does not impede academic achievement, and that discrete cognitive skills as well as lifetime engagement in cognitively stimulating activities can promote academic success in older adults
Monitoring Winter and Summer Abundance of Cetaceans in the Pelagos Sanctuary (Northwestern Mediterranean Sea) Through Aerial Surveys
Systematic long-term monitoring of abundance is essential to inform conservation measures and evaluate their effectiveness. To instigate such work in the Pelagos Sanctuary in the Mediterranean, two aerial surveys were conducted in winter and summer 2009. A total of 467 (131 in winter, 336 in summer) sightings of 7 species was made. Sample sizes were sufficient to estimate abundance of fin whales in summer (148; 95% CI = 87–254) and striped dolphins in winter (19,462; 95% CI = 12 939–29 273) and in summer (38 488; 95% CI = 27 447–53 968). Numbers of animals within the Sanctuary are significantly higher in summer, when human activities and thus potential population level impacts are highest. Comparisons with data from past shipboard surveys suggest an appreciable decrease in fin whales within the Sanctuary area and an appreciable increase in striped dolphins. Aerial surveys proved to be more efficient than ship surveys, allowing more robust estimates, with smaller CIs and CVs. These results provide essential baseline data for this marine protected area and continued regular surveys will allow the effectiveness of the MPA in terms of cetacean conservation to be evaluated and inform future management measures. The collected data may also be crucial in assessing whether ship strikes, one of the main causes of death for fin whales in the Mediterranean, are affecting the Mediterranean population
Exploring the potential of phone call data to characterize the relationship between social network and travel behavior
[EN] Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users' mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 318367 (EUNOIA project) and no 611307 (INSIGHT project). The work of ML has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013-2017.Picornell Tronch, M.; Ruiz Sánchez, T.; Lenormand, M.; Ramasco, JJ.; Dubernet, T.; Frías-Martínez, E. (2015). Exploring the potential of phone call data to characterize the relationship between social network and travel behavior. Transportation. 42(4):647-668. https://doi.org/10.1007/s11116-015-9594-1S647668424Ahas, R., Aasa, A., Silm, S., Tiru, M.: Daily rhythms of suburban commuters’ movements in the tallinn metropolitan area: case study with mobile positioning data. Transp. Res. Part C 18, 45–54 (2010)Arentze, T.,Timmermans, H. J.: social networks, social interactions and activity-travel behavior: a framework for micro-simulation. Paper presented at the 85th annual meeting of the Transportation Research Board, Washington, D. C., Jan 2006 (2006)Arentze, T., Timmermans, H.: Social networks, social interactions, and activity-travel behavior: a framework for microsimulation. Environ. Plan. 35, 1012–1027 (2008)Axhausen, K.W.: Social networks and travel: some hypotheses. In: Donaghy, K.P., Poppelreuter, S., Rudinger, G. (eds.) Social Aspects of Sustainable Transport: Transatlantic Perspectives, pp. 90–108. Ashgate, Aldershot (2005)Bagrow, J.P., Lin, Y.-R.: Mesoscopic structure and social aspects of human mobility. PLoS One 7(5), 1–11 (2012)Bar-Gera, H.: Evaluation of a cellular phone-based system for measurements of traffic speeds and travel times: a case study from israel. Transp. Res. Part C 15(2007), 380–391 (2007)Becker, R.A., Cáceres, R., Hanson, K., Loh, J.M., Urbanek, S., Varshavsky, A., Volinsky, C.: A tale of one city: using cellular network data for urban planning. Pervasive Comput. IEEE 10(4), 18–26 (2011)Brockmann, D., Hufnagel, L., Geisel, T.: The scaling laws of human travel. Nature 439, 462 (2006)Caceres, N., Wideberg, J.P., Benitez, F.G.: Deriving origin–destination data from a mobile phone network. IET Intell. Transp. Syst. 1(1), 5–26 (2007)Caceres, N., Wideberg, J.P., Benitez, F.G.: Review of traffic data estimations extracted from cellular networks. IET Intell. Transp. Syst. 2(3), 179–192 (2008)Caceres, N., Romero, L.M., Benitez, F.G., Castillo, J.M.D.: Traffic flow estimation models using cellular phone data. IEEE Trans. Intell. Transp. Syst. 13(3), 1430–1441 (2012)Calabrese, F., Pereira, F. C., Lorenzo, G. D., Liu, L., Ratti, C.: The geography of taste: analyzing cell-phone mobility and social events. In: Proceedings of IEEE International Conference on Pervasive Computing (2010)Calabrese, F., Smoreda, Z., Blondel, V.D., Ratti, C.: Interplay between telecommunications and face-to-face interactions: a study using mobile phone data. PLoS One 6(7), e20814 (2011a). doi: 10.1371/journal.pone.0020814Calabrese, F., Lorenzo, G.D., Liu, L., Ratti, C.: Estimating origin-destination flows using mobile phone location data. Pervasive Comput. IEEE 10(4), 36–44 (2011b)Carrasco, J.A., Miller, E.J.: Exploring the propensity to perform social activities: social networks approach. Transportation 33, 463–480 (2006)Carrasco, J.A., Hogan, B., Wellman, B., Miller, E.J.: Collecting social network data to study social activity-travel behaviour: an egocentric approach. Environ. Plan. B 35(6), 961–980 (2008a)Carrasco, J.A., Hogan B., Wellman B., Miller E. J.: Agency in social activity and ICT interactions: The role of social networks in time and space, Tijdschrift voor Economische en Sociale Geografie (J. Eco. Soc. Geogr.), 99(5), 562–583 (2008b)Carrasco, J.A., Miller, E.J., Wellman, B.: How far and with whom do people socialize? Empirical evidence about the distance between social network members. Transp. Res. Rec. 2076, 114–122 (2008b)Carrasco, J.A., Miller, E.J.: The social dimension in action: a multilevel, personal networks model of social activity frequency. Transp. Res. Part A 43(1), 90–104 (2009)Chen, C., Mei, Y.: Does distance still matter in facilitating social ties? The roles of mobility patterns and the built environment. Presented at 93rd TRB annual meeting (2014)Cho E., Myers S.A., Leskovek J.: Friendship and mobility: user movement in location-based social networks. In: KDD ‘11 Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1082–1090 (2011)Clifton, K.J.: The social context of travel behavior. In: Zmud, J., et al. (eds.) Transport Survey Methods: Best Practice for Decision Making, pp. 441–448. Emerald Press, London (2013)Do T., Gatica-Perez D.: Contextual conditional models for smartphone-based human mobility prediction. In: Proceedings ACM International Conference on Ubiquitous Computing, Pittsburgh, Sept (2012)Doyle, J., Hung, P., Kelly, D., Mcloone, S., Farrell, R.: Utilising mobile phone billing records for travel mode discovery. ISSC 2011, Trinity College Dublin, June (2011)Dubernet, T., Axhausen K. W.: Solution concepts for the simulation of household-level joint descision making in multi-agent travel simulation tools, paper presented at the 14th Swiss Transport Research Conference (STRC), Ascona (2014)Dugundji, E., Walker, J.: Discrete choice with social and spatial network interdependencies: an empirical example using mixed GEV models with field and “panel” effects. Transp. Res. Rec. 1921, 70–78 (2005)Eagle, N., Pentland, A., Lazer, D.: Inferring social network structure using mobile phone data. Proc. Natl. Acad. Sci. (PNAS) 106(36), 15274–15278 (2009)González, M.C., Hidalgo, C.A., Barabási, A.-L.: Understanding individual human mobility patterns. Nature 453(2008), 779–782 (2008)Gould, J.: Cell phone enabled travel surveys: the medium moves the message. In: Zmud, J., et al. (eds.) Transport Survey Methods: Best Practice for Decision Making, pp. 51–70. Emerald Press, Bingley (2013)Habib, K.N., Carrasco, J.A.: Investigating the role of social networks in start time and duration of activities: a trivariate simultaneous econometric model. Transportation Research Record: Journal of the Transportation Research Board 2230, 1–8 (2011)Hackney, Jeremy K., Kay W. Axhausen: An agent model of social network and travel behavior interdependence. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto, Aug (2006)Hackney, J., Marchal, F.: A model for coupling multi-agent social interactions and traffic simulation, in: TRB 2009 annual meeting (2009)Hackney, J., Marchal, F.: A coupled multi-agent microsimulation of social interactions and transportation behavior. Transp. Res. Part A 45, 296–309 (2011)Horni, A.: Destination choice modeling of discretionary activities in transport microsimulations, Ph.D. Thesis, ETH Zurich, Zurich (2013)Isaacman, S.,Becker, R., Caceres, R., Kobourov, S., Martonosi, M., Rowland, J., Varshavsky, A.: Identifying important places in people’s lives from cellular network data. In: Procedings International Conference on Pervasive Computing, San Francisco, June (2011)Lane, N.D., Miluzzo, E., Lu, H., Peebles, D., Choudhury, T., Campbell, A.T.: A survey of mobile phone sensing. Commun. Mag. IEEE 48(9), 140–150 (2010)Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabasi, A.-L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., Van Alstyne, M.: Computational Social Science. Science 323, 721 (2009)Ma, H., Ronald, N., Arentze, T.A., Timmermans, H.J.P.: New credit mechanism for semicooperative agent-mediated joint activity-travel scheduling. Transp. Res. Rec. 2230, 104–110 (2011)Ma, H., Arentze, T. A., Timmermans, H. J. P.: Incorporating selfishness and altruism into dynamic joint activity-travel scheduling. Paper presented at the 13th international conference on Travel Behaviour Research (IATBR), Toronto, July (2012)Marchal, F., Nagel, K.: Allowed cooperative agents in a microsimulation to share information with each other about activity locations and about other agents, in order to optimize trip chains (2006)Molin, E.J.E., Arentze, T.A., Timmermans, H.J.P.: Social activities and travel demands : a model-based analysis of social-network data. Transp. Res. Rec. 2082, 168–175 (2007)Moore, J., Carrasco, J.A., Tudela, A.: Exploring the links between personal networks, time use, and the spatial distribution of social contacts. Transportation 40(4), 773–788 (2013)Onnela, J.-P., Saramaki, J., Hyvonen, J., Szabo, G., Lazer, D., et al.: Structure and tie strengths in mobile communication networks. Proc. Natl. Acad. Sci. U.S.A. 104, 7332–7336 (2007)Páez, A., Scott, D.M.: Social influence on travel behavior: a simulation example of the decision to telecommute. Environ. Plan. A 39(3), 647–665 (2007)Phithakkitnukoon, S., Calabrese, F., Smoreda, Z., Ratti, C.: Out of sight out of mind: how our mobile social network changes during migration. Proceedings of the IEEE International Conference on Social Computing, pp. 515–520. Cambridge University Press, Cambridge (2011)Phithakkitnukoon, S., Smoreda, Z., Olivier, P.: Socio-geography of human mobility: a study using longitudinal mobile phone data. PLoS One 7(6), e39253 (2012). doi: 10.1371/journal.pone.0039253Ronald, N.A., Arentze, T.A., Timmermans, H.J.P.: Modeling social interactions between individuals for joint activity scheduling. Transp. Res. Part B 46, 276–290 (2012a)Ronald, N.A., Dignum, V., Jonker, C., Arentze, T.A., Timmermans, H.J.P.: On the engineering of agent-based simulations of social activities with social networks. Inf. Softw. Technol. 54(6), 625–638 (2012b)Rose, G.: Mobile phones as traffic probes: practices, prospects and issues. Transp. Rev. 26(3), 275–291 (2006)Sharmeen, F., Arentze, T., Timmermans, H.: A multilevel path analysis of social network dynamics and the mutual interdependencies between face-to-face and ICT modes of social interaction in the context of life-cycle events. In: Roorda, M.J., Miller, E.J. (eds.) Travel Behaviour Research: Current Foundations, Future Prospects, pp. 411–432. Lulu Press, Toronto (2013)Sharmeen, F., Arentze, T.A., Timmermans, H.J.P.: Dynamics of face-to-face social interaction frequency: role of accessibility, urbanization, changes in geographical distance and path dependence. J. Transp. Geogr. 34, 211–220 (2014)Silm, S., Ahas, R.: The seasonal variability of population in estonian municipalities. Environ. Plan. A 42, 2527–2546 (2010)Silvis, J., Niemeier, D., D’Souza, R.: Social networks and travel behavior: report from an integrated travel diary. Paper presented at the 11th international conference on Travel Behaviour Research, Kyoto, Aug (2006)Sobolevsky, S., Szell, M., Campari, R., Couronné, T., Smoreda, Z., et al.: Delineating geographical regions with networks of human interactions in an extensive set of countries. PLoS One 8(12), e81707 (2013)Sohn, K., Kim, D.: Dynamic origin–destination flow estimation using cellular communication system. IEEE Trans. Veh. Technol. 57(5), 2703–2713 (2008)Song, C., Koren, T., Wang, P., Barabási, A.-L.: Modelling the scaling properties of human mobility. Nat. Phys. 6(2010), 818–823 (2010a)Song, C., Qu, Z., Blumm, N., Barabási, L.-L.: Limits of predictability in human mobility. Science 327(5968), 1018–1021 (2010b)Steenbruggen, J., Borzacchiello, M.T., Nijkamp, P., Scholten, H.: Mobile phone data from gsm networks for traffic parameter and urban spatial pattern assessment: A review of applications and opportunities. GeoJournal 78, 223–243 (2011). doi: 10.1007/s10708-011-9413-yVan den Berg, P., Arentze, T., Timmermans, H.J.P.: A path analysis of social networks, telecommunication and social activity–travel patterns. Transp. Res. Part C 26(2013), 256–268 (2013)Wang, H., Calabrese, F., Lorenzo, G. D., Ratti, C.: Transportation mode inference from anonymized and aggregated mobile phone call detail records. In: 13th international IEEE annual conference on intelligent transportation systems, 318–323 (2010)White, J. and Wells, I.: Extracting origin destination information from mobile phone data. Road transport information and Control, 19–21 Mar (2002)Yim, Y.: The state of cellular probes. California PATH Working Paper, UCB-ITS-PRR-2003-25 (2003)Ythier, J., Walker, J.L., Bierlaire, M.: The influence of social contacts and communication use on travel behavior: a smartphone-based study. In: Transportation Research Board annual meeting (2013
- …