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6. List of Contributors to Volume 4

Author

Pinjari, Abdul Rawoof, primary, Karimpour, Abolfazl, additional, Davis, Adam Wilkinson, additional, Adebisi, Adekunle, additional, Ferreira, Amanda Fernandes, additional, Falamarzi, Amir, additional, Kumar, Anil, additional, Yadav, Ankit Kumar, additional, Enam, Annesha, additional, Bhaskar, Ashish, additional, Verma, Ashish, additional, Toriumi, Azusa, additional, Sridhar, Banavar, additional, De Schutter, Bart, additional, Loo, Becky P.Y., additional, Assemi, Behrang, additional, Farooq, Bilal, additional, Morency, Catherine, additional, Shirke, Chaitrali, additional, Bhat, Chandra R., additional, Choudhury, Charisma F., additional, Advani, Chintan, additional, Wu, Chunliang, additional, Garcia, Cristiano P, additional, Chen, Cynthia, additional, Boyce, David, additional, López, David, additional, Ory, David T., additional, L, Deepa, additional, Baker, Douglas, additional, Groth, Sören, additional, Chung, Edward, additional, Frejinger, Emma, additional, Naznin, Farhana, additional, Zhang, Feiyang, additional, de Souza, Felipe, additional, Dias, Felipe F., additional, Sprei, Frances, additional, Witlox, Frank, additional, Chatterji, Gano B., additional, Shivaraman, Gayathri, additional, Sciara, Gian-Claudia, additional, Circella, Giovanni, additional, Asaithambi, Gowri, additional, Yang, Guang, additional, Zhang, H. Michael, additional, Yang, Hai, additional, Zurlinden, Hendrik, additional, Shao, Hu, additional, Kim, Inhi, additional, Banerjee, Ipsita, additional, Pawlak, Jacek, additional, Bourdeau, Jean-Simon, additional, Li, Jia, additional, Xie, Jiani, additional, Ma, Jiaqi, additional, Yao, Jiarong, additional, Freedman, Joel, additional, Gaffney, John, additional, Frejo, José Ramón D., additional, Auld, Joshua, additional, Chen, Jun, additional, Xie, Jun, additional, Geistefeldt, Justin, additional, Khanali, Kamal, additional, Deutsch-Burgner, Kathleen, additional, Wada, Kentaro, additional, Tang, Keshuang, additional, Habib, Khandker Nurul, additional, Chin, Kian Keong, additional, Suzuki, Koji, additional, Goulias, Konstadinos G., additional, Vanajakshi, Lelitha, additional, Weigang, Li, additional, Wang, Lijiao, additional, Wang, Ling, additional, Cheng, Long, additional, Zimmermann, Maëlle, additional, Kashyap, Madhuri, additional, Mesbah, Mahmoud, additional, Salari, Mahmoud, additional, Guerrieri, Marco, additional, Burns, Maria G., additional, Taylor, Michael A.P., additional, Iryo-Asano, Miho, additional, Thomas, Milan Mathew, additional, Balac, Milos, additional, Ha, Min-Ho, additional, Zhang, Ming, additional, Menendez, Monica, additional, Stinson, Monique, additional, Velaga, Nagendra R, additional, McGuckin, Nancy, additional, Iraganaboina, Naveen Chandra, additional, Eluru, Naveen, additional, Verbas, Omer, additional, Wittowsky, Dirk, additional, Lin, Qiheng, additional, Mauro, Raffalele, additional, Benekohal, Rahim F., additional, Paleti, Rajesh, additional, Pendyala, Ram M., additional, Javid, Ramina Jahanbakhsh, additional, Guadamuz, Renato, additional, Javid, Roxana J., additional, Guo, Rui-jun, additional, Li, Ruimin, additional, Wong, S.C., additional, Chang, S.K. Jason, additional, Moridpour, Sara, additional, Raveau, Sebastián, additional, Thyagarajan, Senthilmurugan, additional, Banik, Sharmili, additional, Tanaka, Shinji, additional, Habibi, Shiva, additional, Bekhor, Shlomo, additional, Cao, Shuhan, additional, Chen, Shuyan, additional, Kaplan, Sigal, additional, Balakrishnan, Srijith, additional, Bricka, Stacey G., additional, Boyles, Stephen D., additional, Rashidi, Taha Hossein, additional, Tsubota, Takahiro, additional, Rossi, Thomas F., additional, Hau, Timothy D., additional, Seo, Toru, additional, Kanagaraj, Venkatesan, additional, Alhajyaseen, Wael K.M., additional, Ma, Wanjing, additional, Yang, Wenruifan, additional, Lam, William H.K., additional, Wu, Yao-Jan, additional, Shiomi, Yasuhiro, additional, Murat, Yetis Sazi, additional, Guo, Yi, additional, Pan, Yingjiu, additional, Seo, Young-Joon, additional, Nie, Yu (Marco), additional, Cao, Yumin, additional, Susilo, Yusak, additional, Yang, Zaili, additional, Zhang, Zhanmin, additional, and Li, Zhi-Chun, additional

Published
2021
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12. Zika and SARS-CoV-2: neuroinflammation and neurodegenerative outcomes.

Author

Martins, Jenniffer R., Rocha, Felipe E. O., Costa, Vivian V., and Dias, Felipe F.

Subjects
EMERGING infectious diseases, MYELIN oligodendrocyte glycoprotein, SARS-CoV-2, ZIKA virus infections, COMMUNICABLE diseases, T cells, MONOCYTES
Abstract

Through the emergence of new viral infectious diseases, epidemics and pandemics have brought great impacts on public health in recent decades. In this review, we sought to understand the association between the neurological outcomes of two relevant infectious diseases, Zika and COVID-19. Zika can trigger neurological and ophthalmic damage in children born from infected mothers, as well as, Guillain-Barré syndrome, encephalitis, and myelitis in adults. On the other hand, the SARS-CoV-2 virus has great potential to trigger an inflammatory process in the optic nerve, with optic neuritis as the most reported pathology. Although Zika and SARS-CoV-2 infections are associated with different clinical manifestations, both may trigger similar pathogenic processes, through the induction of pro-inflammatory chemokines and cytokines release, triggering neurological and ophthalmological damage in infected patients. Elements in common have been found in both infections, such as antibodies against myelin oligodendrocyte glycoprotein, and the production of CXCL10, a chemokine responsible for the activation of several cellular types (T cells, eosinophils, monocytes and NK cells) in which are responsible to the induction of a cytokine cascade in the body. Based on these last findings, we suggest that both infections have similar activation characteristics as well as common pathogenic mechanisms associated with central nervous system involvement. [ABSTRACT FROM AUTHOR]

Published
2022
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13. ¿Cuáles son los factores que explican la adopción y frecuencia de uso de los servicios de ride-hailing? Aplicación al caso de Madrid

Author

Gómez Sánchez, Juan, Aguilera García, Álvaro, Dias, Felipe F., Bhat, Chandra R., and Vassallo Magro, José Manuel

Subjects
Ingeniería civil, Vehículos, Formas de movilidad, Vehicles, Transportation, Civil engineering, Transporte, Means of mobility
Abstract

Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de Burgos, Los nuevos servicios de movilidad basados en aplicaciones están revolucionando el transporte urbano. En particular, el servicio de ride-hailing ha experimentado un auge mundial en la última década, ya que ofrece un servicio cómodo y a la carta para los desplazamientos urbanos. Paralelamente, se ha llevado a cabo un número creciente de estudios que analizan principalmente el comportamiento de los individuos hacia esta opción de transporte, los patrones de movilidad, así como los efectos del ride-hailing en la sostenibilidad urbana. Sin embargo, la mayoría de estas contribuciones se centran en ciudades estadounidenses, mientras que casi no se han dedicado esfuerzos a otras áreas geográficas, como Europa. Las ciudades de este continente presentan algunas características particulares que las convierten en un caso digno de ser investigado, como una mayor presencia de los modos de transporte público o una mayor preocupación ciudadana por las cuestiones medioambientales. El objetivo de este trabajo es explorar el comportamiento de viaje hacia los servicios de ridehailing en una ciudad europea. A partir de la información recogida en una campaña de encuestas en la ciudad de Madrid (España), estimamos un enfoque de Modelo de Datos Heterogéneo Generalizado para identificar los factores clave que motivan la adopción de ride-hailing y la frecuencia de uso. El trabajo identifica una mayor adopción de los servicios de ride-hailing entre los jóvenes, con un buen nivel de estudios y ricos, que están familiarizados con las nuevas tecnologías. Y lo que es más interesante, la investigación sugiere que la conciencia medioambiental desempeña un papel notable en la frecuencia de uso de los servicios de ride-hailing, en comparación con las ciudades estadounidenses. En particular, los individuos con menor conciencia medioambiental están más orientados al uso del coche, lo que también está relacionado con un uso más intenso del ride-hailing. Por el contrario, los individuos con una mayor conciencia medioambiental tienden a reducir el uso del transporte compartido, lo que refleja su propensión al transporte público en un entorno de tránsito intensivo., Esta investigación se ha desarrollado dentro del proyecto Co-Mov (Caracterización de las nuevas formas de movilidad urbana colaborativa a través del procesado de fuentes de datos: diseño de medidas para que contribuyan a una movilidad conectada y eficiente), cofinanciado por la Comunidad de Madrid (España), el Fondo Social Europeo y el Fondo Europeo de Desarrollo Regional, con número de subvención [Y2018/EMT-4818].

Published
2021

14. Adoption and frequency of use of ride-hailing services in a European city: The case of Madrid

Author

Gómez Sánchez, Juan, Aguilera García, Álvaro, Dias, Felipe F., Bhat, Chandra R., Vassallo Magro, José Manuel, Gómez Sánchez, Juan, Aguilera García, Álvaro, Dias, Felipe F., Bhat, Chandra R., and Vassallo Magro, José Manuel

Abstract

New app-based mobility services are revolutionizing urban transport. Particularly, ride-hailing has experienced a worldwide boom in the last decade since it provides a convenient, on-demand door-to-door service for urban trips. In parallel, an increasing number of studies have been conducted, mainly analyzing individuals’ behavior towards this transport option, mobility patterns, as well as ride-hailing effects on urban sustainability. Nevertheless, the majority of these contributions focus on US cities, while almost no efforts have been devoted to other geographic areas, such as Europe. Cities in this continent present some particular characteristics that make them a case worth investigating, such as a higher presence of public transport modes or a great public concern on environmental issues. The aim of this paper is to explore travel behavior towards ride-hailing services in a European city. Based on the information collected from a survey campaign in the city of Madrid (Spain), we estimate a Generalized Heterogeneous Data Model approach to identify the key factors motivating ride-hailing adoption and frequency of use. The paper identifies a higher adoption of ride-hailing services among young, well-educated, wealthy individuals, who are familiar with new technologies. More interestingly, the research suggests a noticeable role played by environmental consciousness in ride-hailing frequency of use, compared to US cities. Particularly, individuals with lower environmental consciousness are more car-oriented, which is also linked to a more intense use of ride-hailing. By contrast, individuals with a higher environmental consciousness tend to reduce their use of ride-hailing, which reflects their propensity towards public transport in a transit-intensive background.

Published
2021

16. Incorporating Autonomous Vehicles in the Traditional Four-Step Model

Author

Dias, Felipe F., Nair, Gopindra S., Juri, Natalia Ruiz, Bhat, Chandra R., and Mirzaei, Arash

Subjects
ComputingMilieux_GENERAL, self-driving vehicles, four-step model, ComputingMilieux_PERSONALCOMPUTING, Autonomous vehicles, demand model, GeneralLiterature_MISCELLANEOUS
Abstract

You're viewing a piece from the Good Systems Grand Challenge team at The University of Texas at Austin.

Published
2020
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20. Identification of Piecemeal Degranulation and Vesicular Transport of MBP-1 in Liver-Infiltrating Mouse Eosinophils During Acute Experimental Schistosoma mansoni Infection

Author

Dias, Felipe F., primary, Amaral, Kátia B., additional, Malta, Kássia K., additional, Silva, Thiago P., additional, Rodrigues, Gabriel S. C., additional, Rosa, Florence M., additional, Rodrigues, Gisele O. L., additional, Costa, Vivian V., additional, Chiarini-Garcia, Hélio, additional, Weller, Peter F., additional, and Melo, Rossana C. N., additional

Published
2018
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21. The synthetic peptide LyeTxI-b derived from Lycosa erythrognatha spider venom is cytotoxic to U-87 MG glioblastoma cells

Author

Abdel-Salam, Mostafa A. L., primary, Carvalho-Tavares, Juliana, additional, Gomes, Kamila Sousa, additional, Teixeira-Carvalho, Andrea, additional, Kitten, Gregory T., additional, Nyffeler, Johanna, additional, Dias, Felipe F., additional, dos Reis, Pablo V. Mendes, additional, Pimenta, Adriano M. C., additional, Leist, Marcel, additional, de Lima, Maria Elena, additional, and de Souza-Fagundes, Elaine Maria, additional

Published
2018
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23. Modeling the Evolution of Ride-Hailing Adoption and Usage: A Case Study of the Puget Sound Region

Author

Dias, Felipe F., Kim, Taehooie, Bhat, Chandra R., Pendyala, Ram M., Lam, William H. K., Pinjari, Abdul R., Srinivasan, Karthik K., and Ramadurai, Gitakrishnan

Abstract

Ride-hailing services have grown in cities around the world. There are, however, few studies and even fewer publicly available data sources that provide a basis to understand and quantify changes in ride-hailing usage over time. Ride-hailing use may change over time because of socio-demographic shifts, economic and technological changes, and service attribute enhancements, as well as changes in unobserved attributes such as attitudes and perceptions, lifestyle preferences, technology savviness, and social influences. It is important to quantify the effects of these different forces on ride-hailing frequency so that robust forecasts of ride-hailing use can be developed. This paper uses repeated cross-sectional data collected in 2015 and 2017 in the Puget Sound region to analyze the differential effects of socio-demographic variables on the evolution of ride-hailing adoption and usage. By doing so, the study is able to isolate and quantify the pure effect of the passage of time on adoption of ride-hailing services. A joint binary probit-ordered probit model is estimated on the pooled dataset to explicitly account for sample-selection differences between the 2015 and 2017 surveys that may affect estimates of ride-hailing adoption in the two years. Model estimation results are used to compute average treatment effects of different variables on ride-hailing usage over time. It is found that the effects of most demographic variables on individuals’ propensity to use ride-hailing are softening over time, leading to reduced differences in ride-hailing use among market segments. This suggests that there is a “democratization” of ride-hailing services over time.

Published
2021
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28. Natural Schistosoma mansoni Infection in the Wild Reservoir Nectomys squamipes Leads to Excessive Lipid Droplet Accumulation in Hepatocytes in the Absence of Liver Functional Impairment

Author

Amaral, Kátia B., primary, Silva, Thiago P., additional, Malta, Kássia K., additional, Carmo, Lívia A. S., additional, Dias, Felipe F., additional, Almeida, Mariana R., additional, Andrade, Gustavo F. S., additional, Martins, Jefferson S., additional, Pinho, Roberto R., additional, Costa-Neto, Sócrates F., additional, Gentile, Rosana, additional, and Melo, Rossana C. N., additional

Published
2016
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29. Role of Childhood Context and Experience in Shaping Activity-Travel Choices in Adulthood

Author

Long, Kamryn, Capasso da Silva, Denise, Dias, Felipe F., Khoeini, Sara, Bhat, Aarti C., Pendyala, Ram M., and Bhat, Chandra R.

Abstract

To what extent do experiences in childhood and parental influences shape mobility choices and behaviors in adulthood? This is the central question that this research seeks to answer through an analysis of a unique survey data set that includes variables describing a number of contextual factors from the individual’s childhood. The study presents a joint model of vehicle ownership and transit usage in adulthood as a function of childhood influences and experiences, while controlling for other socio-economic and demographic variables.

Published
2019
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33. Communications and Radar-Supported Transportation Operations and Planning (CAR-STOP) [Phase 2 Project Summary]

Author

Texas Department of Transportation. Research and Technology Implementation Office, United States. Department of Transportation. Federal Highway Administration, Jensen, Darrin, Bhat, Chandra R., Motro, Michael, Kim, Taewan, Kalantari, Rahi, Park, Jinsoo, Oza, Saharsh, Ghosh, Joydeep, Ali, Anum, Kumari, Preeti, Va, Vutha, Prelcic, Nuria G., Heath, Robert W., Lavieri, Patricia S., Dias, Felipe F, Astroza, Sebastian, Vinayak, Pragun, Nair, Gopindra S, Hutchinson, Joseph, Mondal, Aupal, University of Texas at Austin. Center for Transportation Research, Texas Department of Transportation. Research and Technology Implementation Office, United States. Department of Transportation. Federal Highway Administration, Jensen, Darrin, Bhat, Chandra R., Motro, Michael, Kim, Taewan, Kalantari, Rahi, Park, Jinsoo, Oza, Saharsh, Ghosh, Joydeep, Ali, Anum, Kumari, Preeti, Va, Vutha, Prelcic, Nuria G., Heath, Robert W., Lavieri, Patricia S., Dias, Felipe F, Astroza, Sebastian, Vinayak, Pragun, Nair, Gopindra S, Hutchinson, Joseph, Mondal, Aupal, and University of Texas at Austin. Center for Transportation Research

Abstract

A recent report from the National Highway Traffic Safety Administration indicates that more than 80% of all annual car crashes could be prevented by vehicular communications. To that end, the focus of this project was to develop a framework (conceptualizations, processes, procedures, and algorithms) to harness and mature sensing and communication technology to improve transportation safety, primarily focused on the development of an advanced driver assistance system (ADAS).

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