Van Bavel, J.; Cichocka, A.; Capraro, V.; Sjåstad, H.; Nezlek, J.; Pavlović, T.; Alfano, M.; Gelfand, M.; Azevedo, F.; Birtel, M.; Cislak, A.; Lockwood, P.; Ross, R.; Abts, K.; Agadullina, E.; Aruta, J.; Besharati, S.; Bor, A.; Choma, B.; Crabtree, C.; Cunningham, W.; De, K.; Ejaz, W.; Elbaek, C.; Findor, A.; Flichtentrei, D.; Franc, R.; Gjoneska, B.; Gruber, J.; Gualda, E.; Horiuchi, Y.; Huynh, T.; Ibanez, A.; Imran, M.; Israelashvili, J.; Jasko, K.; Kantorowicz, J.; Kantorowicz-Reznichenko, E.; Krouwel, A.; Laakasuo, M.; Lamm, C.; Leygue, C.; Lin, M.; Mansoor, M.; Marie, A.; Mayiwar, L.; Mazepus, H.; McHugh, C.; Minda, J.; Mitkidis, P.; Olsson, A.; Otterbring, T.; Packer, D.; Perry, A.; Petersen, M.; Puthillam, A.; Riaño-Moreno, J.; Rothmund, T.; Santamaría-García, H.; Schmid, P.; Stoyanov, D.; Tewari, S.; Todosijević, B.; Tsakiris, M.; Tung, H.; Umbreș, R.; Vanags, E.; Vlasceanu, M.; Vonasch, A.; Yucel, M.; Zhang, Y.; Abad, M.; Adler, E.; Akrawi, N.; Mdarhri, H.; Amara, H.; Amodio, D.; Antazo, B.; Apps, M.; Ay, F.; Ba, M.; Barbosa, S.; Bastian, B.; Berg, A.; Bernal-Zárate, M.; Bernstein, M.; Białek, M.; Bilancini, E.; Bogatyreva, N.; Boncinelli, L.; Booth, J.; Borau, S.; Buchel, O.; Cameron, C.; Carvalho, C.; Celadin, T.; Cerami, C.; Chalise, H.; Cheng, X.; Cian, L.; Cockcroft, K.; Conway, J.; Córdoba-Delgado, M.; Crespi, C.; Crouzevialle, M.; Cutler, J.; Cypryańska, M.; Dabrowska, J.; Daniels, M.; Davis, V.; Dayley, P.; Delouvee, S.; Denkovski, O.; Dezecache, G.; Dhaliwal, N.; Diato, A.; Di Paolo, R.; Drosinou, M.; Dulleck, U.; Ekmanis, J.; Ertan, A.; Etienne, T.; Farhana, H.; Farkhari, F.; Farmer, H.; Fenwick, A.; Fidanovski, K.; Flew, T.; Fraser, S.; Frempong, R.; Fugelsang, J.; Gale, J.; Garcia-Navarro, E.; Garladinne, P.; Ghajjou, O.; Gkinopoulos, T.; Gray, K.; Griffin, S.; Gronfeldt, B.; Gümren, M.; Gurung, R.; Halperin, E.; Harris, E.; Herzon, V.; Hruška, M.; Huang, G.; Hudecek, M.; Isler, O.; Jangard, S.; Jørgensen, F.; Kachanoff, F.; Kahn, J.; Dangol, A.; Keudel, O.; Koppel, L.; Koverola, M.; Kubin, E.; Kunnari, A.; Kutiyski, Y.; Laguna, O.; Leota, J.; Lermer, E.; Levy, J.; Levy, N.; Li, C.; Long, E.; Longoni, C.; Maglić, M.; McCashin, D.; Metcalf, A.; Mikloušić, I.; El Mimouni, S.; Miura, A.; Molina-Paredes, J.; Monroy-Fonseca, C.; Morales-Marente, E.; Moreau, D.; Muda, R.; Myer, A.; Nash, K.; Nesh-Nash, T.; Nitschke, J.; Nurse, M.; Ohtsubo, Y.; Oldemburgo de Mello, V.; O’Madagain, C.; Onderco, M.; Palacios-Galvez, M.; Palomäki, J.; Pan, Y.; Papp, Z.; Pärnamets, P.; Paruzel-Czachura, M.; Pavlović, Z.; Payán-Gómez, C.; Perander, S.; Pitman, M.; Prasad, R.; Pyrkosz-Pacyna, J.; Rathje, S.; Raza, A.; Rêgo, G.; Rhee, K.; Robertson, C.; Rodríguez-Pascual, I.; Saikkonen, T.; Salvador-Ginez, O.; Sampaio, W.; Santi, G.; Santiago-Tovar, N.; Savage, D.; Scheffer, J.; Schönegger, P.; Schultner, D.; Schutte, E.; Scott, A.; Sharma, M.; Sharma, P.; Skali, A.; Stadelmann, D.; Stafford, C.; Stanojević, D.; Stefaniak, A.; Sternisko, A.; Stoica, A.; Stoyanova, K.; Strickland, B.; Sundvall, J.; Thomas, J.; Tinghög, G.; Torgler, B.; Traast, I.; Tucciarelli, R.; Tyrala, M.; Ungson, N.; Uysal, M.; Van Lange, P.; van Prooijen, J.; van Rooy, D.; Västfjäll, D.; Verkoeijen, P.; Vieira, J.; von Sikorski, C.; Walker, A.; Watermeyer, J.; Wetter, E.; Whillans, A.; Willardt, R.; Wohl, M.; Wójcik, A.; Wu, K.; Yamada, Y.; Yilmaz, O.; Yogeeswaran, K.; Ziemer, C.; Zwaan, R.; Boggio, P.

National identity predicts public health support during a global pandemic

Article

Van Bavel, J., Cichocka, A., Capraro, V., Sjåstad, H., Nezlek, J., Pavlović, T., Alfano, M., Gelfand, M., Azevedo, F., Birtel, M., Cislak, A., Lockwood, P., Ross, R., Abts, K., Agadullina, E., Aruta, J., Besharati, S., Bor, A., Choma, B., Crabtree, C., Cunningham, W., De, K., Ejaz, W., Elbaek, C., Findor, A., Flichtentrei, D., Franc, R., Gjoneska, B., Gruber, J., Gualda, E., Horiuchi, Y., Huynh, T., Ibanez, A., Imran, M., Israelashvili, J., Jasko, K., Kantorowicz, J., Kantorowicz-Reznichenko, E., Krouwel, A., Laakasuo, M., Lamm, C., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Minda, J., Mitkidis, P., Olsson, A., Otterbring, T., Packer, D., Perry, A., Petersen, M., Puthillam, A., Riaño-Moreno, J., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Yucel, M., Zhang, Y., Abad, M., Adler, E., Akrawi, N., Mdarhri, H., Amara, H., Amodio, D., Antazo, B., Apps, M., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Bernal-Zárate, M., Bernstein, M., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., Cameron, C., Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvee, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., Etienne, T., Farhana, H., Farkhari, F., Farmer, H., Fenwick, A., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., Garcia-Navarro, E., Garladinne, P., Ghajjou, O., Gkinopoulos, T., Gray, K., Griffin, S., Gronfeldt, B., Gümren, M., Gurung, R., Halperin, E., Harris, E., Herzon, V., Hruška, M., Huang, G., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Kachanoff, F., Kahn, J., Dangol, A., Keudel, O., Koppel, L., Koverola, M., Kubin, E., Kunnari, A., Kutiyski, Y., Laguna, O., Leota, J., Lermer, E., Levy, J., Levy, N., Li, C., Long, E., Longoni, C., Maglić, M., McCashin, D., Metcalf, A., Mikloušić, I., El Mimouni, S., Miura, A., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nesh-Nash, T., Nitschke, J., Nurse, M., Ohtsubo, Y., Oldemburgo de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomäki, J., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Pavlović, Z., Payán-Gómez, C., Perander, S., Pitman, M., Prasad, R., Pyrkosz-Pacyna, J., Rathje, S., Raza, A., Rêgo, G., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., Schönegger, P., Schultner, D., Schutte, E., Scott, A., Sharma, M., Sharma, P., Skali, A., Stadelmann, D., Stafford, C., Stanojević, D., Stefaniak, A., Sternisko, A., Stoica, A., Stoyanova, K., Strickland, B., Sundvall, J., Thomas, J., Tinghög, G., Torgler, B., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Lange, P., van Prooijen, J., van Rooy, D., Västfjäll, D., Verkoeijen, P., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Wetter, E., Whillans, A., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R. and Boggio, P. 2022. National identity predicts public health support during a global pandemic. Nature Communications. 13 (1), pp. 1-14. https://doi.org/10.1038/s41467-021-27668-9

Publication dates
Type	Article
Title	National identity predicts public health support during a global pandemic
Authors	Van Bavel, J., Cichocka, A., Capraro, V., Sjåstad, H., Nezlek, J., Pavlović, T., Alfano, M., Gelfand, M., Azevedo, F., Birtel, M., Cislak, A., Lockwood, P., Ross, R., Abts, K., Agadullina, E., Aruta, J., Besharati, S., Bor, A., Choma, B., Crabtree, C., Cunningham, W., De, K., Ejaz, W., Elbaek, C., Findor, A., Flichtentrei, D., Franc, R., Gjoneska, B., Gruber, J., Gualda, E., Horiuchi, Y., Huynh, T., Ibanez, A., Imran, M., Israelashvili, J., Jasko, K., Kantorowicz, J., Kantorowicz-Reznichenko, E., Krouwel, A., Laakasuo, M., Lamm, C., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Minda, J., Mitkidis, P., Olsson, A., Otterbring, T., Packer, D., Perry, A., Petersen, M., Puthillam, A., Riaño-Moreno, J., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Yucel, M., Zhang, Y., Abad, M., Adler, E., Akrawi, N., Mdarhri, H., Amara, H., Amodio, D., Antazo, B., Apps, M., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Bernal-Zárate, M., Bernstein, M., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., Cameron, C., Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvee, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., Etienne, T., Farhana, H., Farkhari, F., Farmer, H., Fenwick, A., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., Garcia-Navarro, E., Garladinne, P., Ghajjou, O., Gkinopoulos, T., Gray, K., Griffin, S., Gronfeldt, B., Gümren, M., Gurung, R., Halperin, E., Harris, E., Herzon, V., Hruška, M., Huang, G., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Kachanoff, F., Kahn, J., Dangol, A., Keudel, O., Koppel, L., Koverola, M., Kubin, E., Kunnari, A., Kutiyski, Y., Laguna, O., Leota, J., Lermer, E., Levy, J., Levy, N., Li, C., Long, E., Longoni, C., Maglić, M., McCashin, D., Metcalf, A., Mikloušić, I., El Mimouni, S., Miura, A., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nesh-Nash, T., Nitschke, J., Nurse, M., Ohtsubo, Y., Oldemburgo de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomäki, J., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Pavlović, Z., Payán-Gómez, C., Perander, S., Pitman, M., Prasad, R., Pyrkosz-Pacyna, J., Rathje, S., Raza, A., Rêgo, G., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., Schönegger, P., Schultner, D., Schutte, E., Scott, A., Sharma, M., Sharma, P., Skali, A., Stadelmann, D., Stafford, C., Stanojević, D., Stefaniak, A., Sternisko, A., Stoica, A., Stoyanova, K., Strickland, B., Sundvall, J., Thomas, J., Tinghög, G., Torgler, B., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Lange, P., van Prooijen, J., van Rooy, D., Västfjäll, D., Verkoeijen, P., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Wetter, E., Whillans, A., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R. and Boggio, P.
Abstract	Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.
Publisher	Nature Publishing Group
Journal	Nature Communications
ISSN	2041-1723
Online	26 Jan 2022
Print	31 Dec 2022
Publication process dates
Deposited	11 Apr 2022
Accepted	14 Oct 2021
Output status	Published
Publisher's version	41467_2021_Article_27668.pdf 41467_2021_27668_MOESM2_ESM.pdf 41467_2021_27668_MOESM3_ESM.pdf 41467_2021_27668_MOESM1_ESM.pdf 41467_2021_Article_27668_nlm.xml License CC BY 4.0
Copyright Statement	© The Author(s) 2022, corrected publication 2022 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Additional information	06 April 2022 - A correction to this paper: National identity predicts public health support during a global pandemic, has been published: https://doi.org/10.1038/s41467-022-29658-x, see repository record https://eprints.mdx.ac.uk/id/eprint/34955
Digital Object Identifier (DOI)	https://doi.org/10.1038/s41467-021-27668-9
Language	English

Permalink -

https://repository.mdx.ac.uk/item/89vvx

Log in to edit

Download files

Publisher's version

	41467_2021_Article_27668.pdf
	41467_2021_27668_MOESM2_ESM.pdf
	41467_2021_27668_MOESM3_ESM.pdf
	41467_2021_27668_MOESM1_ESM.pdf
	41467_2021_Article_27668_nlm.xml
License: CC BY 4.0

61
total views
23
total downloads
2
views this month
1
downloads this month

Export as

Related outputs

Residual network-based deep learning framework for diabetic retinopathy detection

Kaushik, K., Bhardwaj, A., Cheng, X., Dahiya, S., Shankar, A., Kumar, M. and Mehrotra, T. 2025. Residual network-based deep learning framework for diabetic retinopathy detection. Journal of Database Management. 36 (1), pp. 1-21. https://doi.org/10.4018/jdm.368006

From outcome-based to language-based preferences

Capraro, V., Halpern, J. and Perc, M. 2024. From outcome-based to language-based preferences. Journal of Economic Literature. 62 (1), pp. 115-154. https://doi.org/10.1257/jel.20221613

Social and moral psychology of COVID-19 across 69 countries

Azevedo, F., Pavlović, T., Rêgo, G., Ay, F., Gjoneska, B., Etienne, T., Ross, R., Schönegger, P., Riaño-Moreno, J., Cichocka, A., Capraro, V., Cian, L., Longoni, C., Chan, H., Van Bavel, J., Sjåstad, H., Nezlek, J., Alfano, M., Gelfand, M., Birtel, M., Cislak, A., Lockwood, P., Abts, K., Agadullina, E., Aruta, J., Besharati, S., Bor, A., Choma, B., Crabtree, C., Cunningham, W., De, K., Ejaz, W., Elbaek, C., Findor, A., Flichtentrei, D., Franc, R., Gruber, J., Gualda, E., Horiuchi, Y., Huynh, T., Ibanez, A., Imran, M., Israelashvili, J., Jasko, K., Kantorowicz, J., Kantorowicz-Reznichenko, E., Krouwel, A., Laakasuo, M., Lamm, C., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Minda, J., Mitkidis, P., Olsson, A., Otterbring, T., Packer, D., Perry, A., Petersen, M., Puthillam, A., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbres, R., Vanags, E., Vlasceanu, M., Vonasch, A., Yucel, M., Zhang, Y., Abad, M., Adler, E., Akrawi, N., Mdarhri, H., Amara, H., Amodio, D., Antazo, B., Apps, M., Ba, M., Barbosa, S., Bastian, B., Berg, A., Bernal-Zárate, M., Bernstein, M., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., Cameron, C., Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvée, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., Farhana, H., Farkhari, F., Farmer, H., Fenwick, A., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., Garcia-Navarro, E., Garladinne, P., Ghajjou, O., Gkinopoulos, T., Gray, K., Griffin, S., Gronfeldt, B., Gümren, M., Gurung, R., Halperin, E., Harris, E., Herzon, V., Hruška, M., Huang, G., Hudecek, M., Isler, O., Jangard, S., Jorgensen, F., Kachanoff, F., Kahn, J., Dangol, A., Keudel, O., Koppel, L., Koverola, M., Kubin, E., Kunnari, A., Kutiyski, Y., Laguna, O., Leota, J., Lermer, E., Levy, J., Levy, N., Li, C., Long, E., Maglić, M., McCashin, D., Metcalf, A., Mikloušić, I., El Mimouni, S., Miura, A., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nesh-Nash, T., Nitschke, J., Nurse, M., Ohtsubo, Y., de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomöki, J., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Pavlović, Z., Payán-Gómez, C., Perander, S., Pitman, M., Prasad, R., Pyrkosz-Pacyna, J., Rathje, S., Raza, A., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., Schultner, D., Schutte, E., Scott, A., Sharma, M., Sharma, P., Skali, A., Stadelmann, D., Stafford, C., Stanojević, D., Stefaniak, A., Sternisko, A., Stoica, A., Stoyanova, K., Strickland, B., Sundvall, J., Thomas, J., Tinghög, G., Torgler, B., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Lange, P., van Prooijen, J., van Rooy, D., Västfjäll, D., Verkoeijen, P., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Wetter, E., Whillans, A., White, K., Habib, R., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R., Boggio, P. and Sampaio, W. 2023. Social and moral psychology of COVID-19 across 69 countries. Scientific Data. 10 (1), p. 272. https://doi.org/10.1038/s41597-023-02080-8

IHWC: intelligent hidden web crawler for harvesting data in urban domains

Kaur, S., Singh, A., Geetha, G. and Cheng, X. 2021. IHWC: intelligent hidden web crawler for harvesting data in urban domains. Complex & Intelligent Systems. https://doi.org/10.1007/s40747-022-00839-x

A tamper-resistant broadcasting scheme for secure communication in internet of autonomous vehicles

Sun, J., Tao, J., Zhang, H., Zhao, Y., Nie, L., Cheng, X. and Zhang, T. 2023. A tamper-resistant broadcasting scheme for secure communication in internet of autonomous vehicles. IEEE Transactions on Intelligent Transportation Systems. 25 (3), pp. 2837-2846. https://doi.org/10.1109/TITS.2023.3265403

Privacy-preserving and fine-grained data sharing for resource-constrained healthcare CPS devices

Bao, Y., Qiu, W. and Cheng, X. 2023. Privacy-preserving and fine-grained data sharing for resource-constrained healthcare CPS devices. Expert Systems. 40 (6). https://doi.org/10.1111/exsy.13220

A novel framework for melanoma lesion segmentation using multiparallel depthwise separable and dilated convolutions with swish activations

Bukhari, M., Yasmin, S., Habib, A., Cheng, X., Ullah, F., Yoo, J. and Lee, D. 2023. A novel framework for melanoma lesion segmentation using multiparallel depthwise separable and dilated convolutions with swish activations. Journal of Healthcare Engineering. 2023 (1). https://doi.org/10.1155/2023/1847115

Fake news stance detection using selective features and FakeNET

Aljrees, T., Cheng, X., Ahmed, M., Umer, M., Majeed, R., Alnowaiser, K., Abuzinadah, N. and Ashraf, I. 2023. Fake news stance detection using selective features and FakeNET. PLoS ONE. 18 (7). https://doi.org/10.1371/journal.pone.0287298

PIGNUS: a deep learning model for IDS in industrial internet-of-things

Jayalaxmi, P., Saha, R., Kumar, G., Alazab, M., Conti, M. and Cheng, X. 2023. PIGNUS: a deep learning model for IDS in industrial internet-of-things. Computers and Security. 132. https://doi.org/10.1016/j.cose.2023.103315

Generative recorrupted-to-recorrupted: an unsupervised image denoising network for arbitrary noise distribution

Liu, Y., Wan, B., Shi, D. and Cheng, X. 2023. Generative recorrupted-to-recorrupted: an unsupervised image denoising network for arbitrary noise distribution. Remote Sensing. 15 (2). https://doi.org/10.3390/rs15020364

Cooperative conflict detection and resolution and safety assessment for 6G enabled unmanned aerial vehicles

Li, S., Cheng, X., Huang, X., Otaibi, S. and Wang, H. 2023. Cooperative conflict detection and resolution and safety assessment for 6G enabled unmanned aerial vehicles. IEEE Transactions on Intelligent Transportation Systems. 24 (2), pp. 2183-2198. https://doi.org/10.1109/TITS.2021.3137458

An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches

Mittal, M., Kobielnik, M., Gupta, S., Cheng, X. and Wozniak, M. 2022. An efficient quality of services based wireless sensor network for anomaly detection using soft computing approaches. Journal of Cloud Computing. 11 (1), pp. 1-21. https://doi.org/10.1186/s13677-022-00344-z

Evolution of honesty in higher-order social networks

Kumar, A., Chowdhary, S., Capraro, V. and Perc, M. 2021. Evolution of honesty in higher-order social networks. Physical Review E. 104 (5-1). https://doi.org/10.1103/PhysRevE.104.054308

Efficient, revocable, and privacy-preserving fine-grained data sharing with keyword search for the cloud-assisted medical IoT system

Bao, Y., Qiu, W., Tang, P. and Cheng, X. 2022. Efficient, revocable, and privacy-preserving fine-grained data sharing with keyword search for the cloud-assisted medical IoT system. IEEE Journal of Biomedical and Health Informatics. 26 (5), pp. 2041-2051. https://doi.org/10.1109/JBHI.2021.3100871

Large-size data distribution in IoV based on 5G/6G compatible heterogeneous network

Yin, X., Liu, J., Cheng, X. and Xiong, X. 2022. Large-size data distribution in IoV based on 5G/6G compatible heterogeneous network. IEEE Transactions on Intelligent Transportation Systems. 25 (7), pp. 9840-9852. https://doi.org/10.1109/TITS.2021.3118701

A differentiated learning environment in domain model for learning disabled learners

Thapliyal, M., Ahuja, N., Shankar, A., Cheng, X. and Kumar, M. 2022. A differentiated learning environment in domain model for learning disabled learners. Journal of Computing in Higher Education. 34, pp. 60-82. https://doi.org/10.1007/s12528-021-09278-y

Offline signature verification using deep neural network with application to computer vision

Sharma, N., Gupta, S., Mehta, P., Cheng, X., Shankar, A., Singh, P. and Nayak, S. 2022. Offline signature verification using deep neural network with application to computer vision. Journal of Electronic Imaging (JEI). 31 (4). https://doi.org/10.1117/1.JEI.31.4.041210

Intrusion detection and prevention system for an IoT environment

Kumar, A., Abhishek, K., Ghalib, M., Shankar, A. and Cheng, X. 2022. Intrusion detection and prevention system for an IoT environment. Digital Communications and Networks. 8 (4), pp. 540-551. https://doi.org/10.1016/j.dcan.2022.05.027

An empirical study on Retinex methods for low-light image enhancement

Rasheed, M., Guo, G., Shi, D., Khan, H. and Cheng, X. 2022. An empirical study on Retinex methods for low-light image enhancement. Remote Sensing. 14 (18). https://doi.org/10.3390/rs14184608

A tagging SNP set method based on network community partition of linkage disequilibrium and node centrality

Wan, Q., Cheng, X., Zhang, Y., Lu, G., Wang, S. and He, S. 2022. A tagging SNP set method based on network community partition of linkage disequilibrium and node centrality. Current Bioinformatics. 17 (9), pp. 825-834. https://doi.org/10.2174/1574893617666220324155813

Cyber-threat detection system using a hybrid approach of transfer learning and multi-model image representation

Ullah, F., Ullah, S., Naeem, M., Mostarda, L., Rho, S. and Cheng, X. 2022. Cyber-threat detection system using a hybrid approach of transfer learning and multi-model image representation. Sensors. 22 (15), pp. 1-26. https://doi.org/10.3390/s22155883

A deep convolutional neural network stacked ensemble for malware threat classification in internet of things

Naeem, H., Cheng, X., Ullah, F., Jabbar, S. and Dong, S. 2022. A deep convolutional neural network stacked ensemble for malware threat classification in internet of things. Journal of Circuits, Systems and Computers. 31 (17). https://doi.org/10.1142/s0218126622503029

"I think this news is accurate": endorsing accuracy decreases the sharing of fake news and increases the sharing of real news

Capraro, V. and Celadin, T. 2022. "I think this news is accurate": endorsing accuracy decreases the sharing of fake news and increases the sharing of real news. Personality and Social Psychology Bulletin. https://doi.org/10.1177/01461672221117691

RFAP: a revocable fine-grained access control mechanism for autonomous vehicle platoon

Zhao, Y., Wang, Y., Cheng, X., Chen, H., Yu, H. and Ren, Y. 2022. RFAP: a revocable fine-grained access control mechanism for autonomous vehicle platoon. IEEE Transactions on Intelligent Transportation Systems. 23 (7), pp. 9668-9679. https://doi.org/10.1109/TITS.2021.3105458

Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

Pavlović, T., Azevedo, F., De, K., Riaño-Moreno, J., Maglić, M., Gkinopoulos, T., Donnelly-Kehoe, P., Payán-Gómez, C., Huang, G., Kantorowicz, J., Birtel, M., Schönegger, P., Capraro, V., Santamaría-García, H., Yucel, M., Ibanez, A., Rathje, S., Wetter, E., Stanojević, D., van Prooijen, J., Hesse, E., Elbaek, C., Franc, R., Pavlović, Z., Mitkidis, P., Cichocka, A., Gelfand, M., Alfano, M., Ross, R., Sjåstad, H., Nezlek, J., Cislak, A., Lockwood, P., Abts, K., Agadullina, E., Amodio, D., Apps, M., Aruta, J., Besharati, S., Bor, A., Choma, B., Cunningham, W., Ejaz, W., Farmer, H., Findor, A., Gjoneska, B., Gualda, E., Huynh, T., Imran, M., Israelashvili, J., Kantorowicz-Reznichenko, E., Krouwel, A., Kutiyski, Y., Laakasuo, M., Lamm, C., Levy, J., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Olsson, A., Otterbring, T., Packer, D., Palomäki, J., Perry, A., Petersen, M., Puthillam, A., Rothmund, T., Schmid, P., Stadelmann, D., Stoica, A., Stoyanov, D., Stoyanova, K., Tewari, S., Todosijević, B., Torgler, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Zhang, Y., Abad, M., Adler, E., Mdarhri, H., Antazo, B., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., de Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Davis, V., Minda, J., Dayley, P., Delouvée, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Dulleck, U., Ekmanis, J., Etienne, T., Farhana, H., Farkhari, F., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., García-Navarro, E., Garladinne, P., Gray, K., Griffin, S., Gronfeldt, B., Gruber, J., Halperin, E., Herzon, V., Hruška, M., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Keudel, O., Koppel, L., Koverola, M., Kunnari, A., Leota, J., Lermer, E., Li, C., Longoni, C., McCashin, D., Mikloušić, I., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nitschke, J., Nurse, M., de Mello, V., Palacios-Galvez, M., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Perander, S., Pitman, M., Raza, A., Rêgo, G., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Schultner, D., Schutte, E., Scott, A., Skali, A., Stefaniak, A., Sternisko, A., Strickland, B., Thomas, J., Tinghög, G., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Rooy, D., Västfjäll, D., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R., Boggio, P., Whillans, A., Van Lange, P., Prasad, R., Onderco, M., O'Madagain, C., Nesh-Nash, T., Laguna, O., Kubin, E., Gümren, M., Fenwick, A., Ertan, A., Bernstein, M., Amara, H. and Van Bavel, J. 2022. Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning. PNAS Nexus. 1 (3), pp. 1-15. https://doi.org/10.1093/pnasnexus/pgac093

Adaptive weighted dynamic differential evolution algorithm for emergency material allocation and scheduling

Wang, T., Wu, K., Du, T. and Cheng, X. 2022. Adaptive weighted dynamic differential evolution algorithm for emergency material allocation and scheduling. Computational Intelligence. 38 (3), pp. 714-730. https://doi.org/10.1111/coin.12389

Author Correction: National identity predicts public health support during a global pandemic

Van Bavel, J., Cichocka, A., Capraro, V., Sjåstad, H., Nezlek, J., Pavlović, T., Alfano, M., Gelfand, M., Azevedo, F., Birtel, M., Cislak, A., Lockwood, P., Ross, R., Abts, K., Agadullina, E., Aruta, J., Besharati, S., Bor, A., Choma, B., Crabtree, C., Cunningham, W., De, K., Ejaz, W., Elbaek, C., Findor, A., Flichtentrei, D., Franc, R., Gjoneska, B., Gruber, J., Gualda, E., Horiuchi, Y., Huynh, T., Ibanez, A., Imran, M., Israelashvili, J., Jasko, K., Kantorowicz, J., Kantorowicz-Reznichenko, E., Krouwel, A., Laakasuo, M., Lamm, C., Leygue, C., Lin, M., Mansoor, M., Marie, A., Mayiwar, L., Mazepus, H., McHugh, C., Minda, J., Mitkidis, P., Olsson, A., Otterbring, T., Packer, D., Perry, A., Petersen, M., Puthillam, A., Riaño-Moreno, J., Rothmund, T., Santamaría-García, H., Schmid, P., Stoyanov, D., Tewari, S., Todosijević, B., Tsakiris, M., Tung, H., Umbreș, R., Vanags, E., Vlasceanu, M., Vonasch, A., Yucel, M., Zhang, Y., Abad, M., Adler, E., Akrawi, N., Mdarhri, H., Amara, H., Amodio, D., Antazo, B., Apps, M., Ay, F., Ba, M., Barbosa, S., Bastian, B., Berg, A., Bernal-Zárate, M., Bernstein, M., Białek, M., Bilancini, E., Bogatyreva, N., Boncinelli, L., Booth, J., Borau, S., Buchel, O., Cameron, C., Carvalho, C., Celadin, T., Cerami, C., Chalise, H., Cheng, X., Cian, L., Cockcroft, K., Conway, J., Córdoba-Delgado, M., Crespi, C., Crouzevialle, M., Cutler, J., Cypryańska, M., Dabrowska, J., Daniels, M., Davis, V., Dayley, P., Delouvee, S., Denkovski, O., Dezecache, G., Dhaliwal, N., Diato, A., Di Paolo, R., Drosinou, M., Dulleck, U., Ekmanis, J., Ertan, A., Etienne, T., Farhana, H., Farkhari, F., Farmer, H., Fenwick, A., Fidanovski, K., Flew, T., Fraser, S., Frempong, R., Fugelsang, J., Gale, J., Garcia-Navarro, E., Garladinne, P., Ghajjou, O., Gkinopoulos, T., Gray, K., Griffin, S., Gronfeldt, B., Gümren, M., Gurung, R., Halperin, E., Harris, E., Herzon, V., Hruška, M., Huang, G., Hudecek, M., Isler, O., Jangard, S., Jørgensen, F., Kachanoff, F., Kahn, J., Dangol, A., Keudel, O., Koppel, L., Koverola, M., Kubin, E., Kunnari, A., Kutiyski, Y., Laguna, O., Leota, J., Lermer, E., Levy, J., Levy, N., Li, C., Long, E., Longoni, C., Maglić, M., McCashin, D., Metcalf, A., Mikloušić, I., El Mimouni, S., Miura, A., Molina-Paredes, J., Monroy-Fonseca, C., Morales-Marente, E., Moreau, D., Muda, R., Myer, A., Nash, K., Nesh-Nash, T., Nitschke, J., Nurse, M., Ohtsubo, Y., Oldemburgo de Mello, V., O’Madagain, C., Onderco, M., Palacios-Galvez, M., Palomäki, J., Pan, Y., Papp, Z., Pärnamets, P., Paruzel-Czachura, M., Pavlović, Z., Payán-Gómez, C., Perander, S., Pitman, M., Prasad, R., Pyrkosz-Pacyna, J., Rathje, S., Raza, A., Rêgo, G., Rhee, K., Robertson, C., Rodríguez-Pascual, I., Saikkonen, T., Salvador-Ginez, O., Sampaio, W., Santi, G., Santiago-Tovar, N., Savage, D., Scheffer, J., Schönegger, P., Schultner, D., Schutte, E., Scott, A., Sharma, M., Sharma, P., Skali, A., Stadelmann, D., Stafford, C., Stanojević, D., Stefaniak, A., Sternisko, A., Stoica, A., Stoyanova, K., Strickland, B., Sundvall, J., Thomas, J., Tinghög, G., Torgler, B., Traast, I., Tucciarelli, R., Tyrala, M., Ungson, N., Uysal, M., Van Lange, P., van Prooijen, J., van Rooy, D., Västfjäll, D., Verkoeijen, P., Vieira, J., von Sikorski, C., Walker, A., Watermeyer, J., Wetter, E., Whillans, A., Willardt, R., Wohl, M., Wójcik, A., Wu, K., Yamada, Y., Yilmaz, O., Yogeeswaran, K., Ziemer, C., Zwaan, R. and Boggio, P. 2022. Author Correction: National identity predicts public health support during a global pandemic. Nature Publishing Group. https://doi.org/10.1038/s41467-022-29658-x

CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model

Ullah, F., Naeem, M., Naeem, H., Cheng, X. and Alazab, M. 2022. CroLSSim: Cross‐language software similarity detector using hybrid approach of LSA‐based AST‐MDrep features and CNN‐LSTM model. International Journal of Intelligent Systems. 37 (9), pp. 5768-5795. https://doi.org/10.1002/int.22813

MobiScan: an enhanced invisible screen‐camera communication system for IoT applications

Zhang, X., Liu, J., Ba, Z., Tao, Y. and Cheng, X. 2022. MobiScan: an enhanced invisible screen‐camera communication system for IoT applications. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4151

Secure smart contracts for cloud-based manufacturing using Ethereum blockchain

Kumar, A., Abhishek, K., Nerurkar, P., Ghalib, M., Shankar, A. and Cheng, X. 2022. Secure smart contracts for cloud-based manufacturing using Ethereum blockchain. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4129

Editorial: Security of cloud service for the manufacturing industry

Cheng, X., Liu, Z. and Ning, Y. 2022. Editorial: Security of cloud service for the manufacturing industry. Transactions on Emerging Telecommunications Technologies. 33 (4). https://doi.org/10.1002/ett.4369

Secure and energy-efficient smart building architecture with emerging technology IoT

Kumar, A., Sharma, S., Goyal, N., Singh, A., Cheng, X. and Singh, P. 2021. Secure and energy-efficient smart building architecture with emerging technology IoT. Computer Communications. 176, pp. 207-217. https://doi.org/10.1016/j.comcom.2021.06.003

Fuzzy decision trees embedded with evolutionary fuzzy clustering for locating users using wireless signal strength in an indoor environment

Narayanan, S., Baby, C., Perumal, B., Bhatt, R., Cheng, X., Ghalib, M. and Shankar, A. 2021. Fuzzy decision trees embedded with evolutionary fuzzy clustering for locating users using wireless signal strength in an indoor environment. International Journal of Intelligent Systems. 36 (8), pp. 4280-4267. https://doi.org/10.1002/int.22459

PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an explainable diagnosis of COVID-19 with multiple-way data augmentation

Wang, S., Zhang, Y., Cheng, X., Zhang, X. and Zhang, Y. 2021. PSSPNN: PatchShuffle Stochastic Pooling Neural Network for an explainable diagnosis of COVID-19 with multiple-way data augmentation. Computational and Mathematical Methods in Medicine. 2021, pp. 1-18. https://doi.org/10.1155/2021/6633755

Mathematical foundations of moral preferences

Capraro, V. and Perc, M. 2021. Mathematical foundations of moral preferences. Journal of The Royal Society Interface. 18 (175), pp. 1-13. https://doi.org/10.1098/rsif.2020.0880

Does observability amplify sensitivity to moral frames? Evaluating a reputation-based account of moral preferences

Capraro, V., Jordan, J. and Tappin, B. 2021. Does observability amplify sensitivity to moral frames? Evaluating a reputation-based account of moral preferences. Journal of Experimental Social Psychology. 94, pp. 1-10. https://doi.org/10.1016/j.jesp.2021.104103

Power grid-oriented cascading failure vulnerability identifying method based on wireless sensors

Li, S., Chen, Y., Wu, X., Cheng, X. and Tian, Z. 2021. Power grid-oriented cascading failure vulnerability identifying method based on wireless sensors. Journal of Sensors. 2021, pp. 1-12. https://doi.org/10.1155/2021/8820413

Task bundling in worker-centric mobile crowdsensing

Zhao, T., Yang, Y., Wang, E., Mumtaz, S. and Cheng, X. 2021. Task bundling in worker-centric mobile crowdsensing. International Journal of Intelligent Systems. 36 (9), pp. 4936-4961. https://doi.org/10.1002/int.22497

Telling people to "rely on their reasoning" increases intentions to wear a face covering to slow down COVID-19 transmission

Capraro, V. and Barcelo, H. 2021. Telling people to "rely on their reasoning" increases intentions to wear a face covering to slow down COVID-19 transmission. Applied Cognitive Psychology. 35 (3), pp. 693-699. https://doi.org/10.1002/acp.3793

ShadowFPE: new encrypted web application solution based on shadow DOM

Guo, X., Huang, Y., Ye, J., Yin, S., Li, M., Li, Z., Yiu, S. and Cheng, X. 2021. ShadowFPE: new encrypted web application solution based on shadow DOM. Mobile Networks and Applications. 26 (4), pp. 1733-1746. https://doi.org/10.1007/s11036-019-01509-y

The evolution of trust and trustworthiness

Kumar, A., Capraro, V. and Perc, M. 2020. The evolution of trust and trustworthiness. Journal of The Royal Society Interface. 17 (169), pp. 1-10. https://doi.org/10.1098/rsif.2020.0491

Learning context-aware outfit recommendation

Abugabah, A., Cheng, X. and Wang, J. 2020. Learning context-aware outfit recommendation. Symmetry. 12 (6), pp. 1-13. https://doi.org/10.3390/sym12060873

Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm

Liu, W., Huang, Y., Ye, Z., Cai, W., Yang, S., Cheng, X. and Frank, I. 2020. Renyi’s entropy based multilevel thresholding using a novel meta-heuristics algorithm. Applied Sciences. 10 (9). https://doi.org/10.3390/app10093225

Reliability analysis of an air traffic network: from network structure to transport function

Li, S., Zhang, Z. and Cheng, X. 2020. Reliability analysis of an air traffic network: from network structure to transport function. Applied Sciences. 10 (9). https://doi.org/10.3390/app10093168

Preferences for efficiency, rather than preferences for morality, drive cooperation in the one-shot Stag-Hunt game

Capraro, V., Rodriguez-Lara, I. and Ruiz-Martos, M. 2020. Preferences for efficiency, rather than preferences for morality, drive cooperation in the one-shot Stag-Hunt game. Journal of Behavioral and Experimental Economics. 86. https://doi.org/10.1016/j.socec.2020.101535

XOR multiplexing technique for nanocomputers

Yu, L., Diao, M., Chen, X. and Cheng, X. 2020. XOR multiplexing technique for nanocomputers. Applied Sciences. 10 (8). https://doi.org/10.3390/app10082825

Using social and behavioural science to support COVID-19 pandemic response

Bavel, J., Baicker, K., Boggio, P., Capraro, V., Cichocka, A., Cikara, M., Crockett, M., Crum, A., Douglas, K., Druckman, J., Drury, J., Dube, O., Ellemers, N., Finkel, E., Fowler, J., Gelfand, M., Han, S., Haslam, S., Jetten, J., Kitayama, S., Mobbs, D., Napper, L., Packer, D., Pennycook, G., Peters, E., Petty, R., Rand, D., Reicher, S., Schnall, S., Shariff, A., Skitka, L., Smith, S., Sunstein, C., Tabri, N., Tucker, J., van der Linden, S., van Lange, P., Weeden, K., Wohl, M., Zaki, J., Zion, S. and Willer, R. 2020. Using social and behavioural science to support COVID-19 pandemic response. Nature Human Behaviour. 4 (5), pp. 460-471. https://doi.org/10.1038/s41562-020-0884-z

Adaptive dynamic disturbance strategy for differential evolution algorithm

Wang, T., Wu, K., Du, T. and Cheng, X. 2020. Adaptive dynamic disturbance strategy for differential evolution algorithm. Applied Sciences. 10 (6). https://doi.org/10.3390/app10061972

Hybridization of cognitive computing for food services

Zhang, X., Yang, S., Srivastava, G., Chen, M. and Cheng, X. 2020. Hybridization of cognitive computing for food services. Applied Soft Computing. 89. https://doi.org/10.1016/j.asoc.2019.106051

Facial landmark detection via attention-adaptive deep network

Sadiq, M., Shi, D., Guo, M. and Cheng, X. 2019. Facial landmark detection via attention-adaptive deep network. IEEE Access. 7, pp. 181041-181050. https://doi.org/10.1109/ACCESS.2019.2955156

Annual and non-monsoon rainfall prediction modelling using SVR-MLP: an empirical study from Odisha

Yhang, X., Mohanty, S., Parida, A., Pani, S., Dong, B. and Cheng, X. 2020. Annual and non-monsoon rainfall prediction modelling using SVR-MLP: an empirical study from Odisha. IEEE Access. 8, pp. 30223-30233. https://doi.org/10.1109/ACCESS.2020.2972435

A sparse Bayesian learning method for structural equation model-based gene regulatory network inference

Li, Y., Liu, D., Chu, J., Zhu, Y., Liu, J. and Cheng, X. 2020. A sparse Bayesian learning method for structural equation model-based gene regulatory network inference. IEEE Access. 8, pp. 40067-40080. https://doi.org/10.1109/ACCESS.2020.2976743

Lying on networks: the role of structure and topology in promoting honesty

Capraro, V., Perc, M. and Vilone, D. 2020. Lying on networks: the role of structure and topology in promoting honesty. Physical Review E. 101 (3). https://doi.org/10.1103/PhysRevE.101.032305

Social setting, intuition, and experience in lab experiments interact to shape cooperative decision-making

Capraro, V. and Cococcioni, G. 2015. Social setting, intuition, and experience in lab experiments interact to shape cooperative decision-making. Proceedings of the Royal Society B: Biological Sciences. 282 (1811). https://doi.org/10.1098/rspb.2015.0237

Social heuristics and social roles: Intuition favors altruism for women but not for men

Rand, D., Brescoll, V., Everett, J., Capraro, V. and Barcelo, H. 2016. Social heuristics and social roles: Intuition favors altruism for women but not for men. Journal of Experimental Psychology: General. 145 (4), pp. 389-396. https://doi.org/10.1037/xge0000154

Liking but devaluing animals: emotional and deliberative paths to speciesism

Caviola, L. and Capraro, V. 2020. Liking but devaluing animals: emotional and deliberative paths to speciesism. Social Psychological and Personality Science. 11 (8), pp. 1080-1088. https://doi.org/10.1177/1948550619893959

Priming intuition disfavors instrumental harm but not impartial beneficence

Capraro, V., Everett, J. and Earp, B. 2019. Priming intuition disfavors instrumental harm but not impartial beneficence. Journal of Experimental Social Psychology. 83, pp. 142-149. https://doi.org/10.1016/j.jesp.2019.04.006

Time pressure and honesty in a deception game

Capraro, V., Schulz, J. and Rand, D. 2019. Time pressure and honesty in a deception game. Journal of Behavioral and Experimental Economics. 79, pp. 93-99. https://doi.org/10.1016/j.socec.2019.01.007

Gender differences in the trade-off between objective equality and efficiency

Capraro, V. 2020. Gender differences in the trade-off between objective equality and efficiency. Judgment and Decision Making. 15 (4), pp. 534-544.

The effect of norm-based messages on reading and understanding COVID-19 pandemic response governmental rules

Bilancini, E., Boncinelli, L., Capraro, V., Celadin, T. and Di Paolo, R. 2020. The effect of norm-based messages on reading and understanding COVID-19 pandemic response governmental rules . Journal of Behavioral Economics for Policy. 4, pp. 45-55.

Fine-grained action recognition by motion saliency and mid-level patches

Liu, F., Zhao, L., Cheng, X., Dai, Q., Shi, X. and Qiao, J. 2020. Fine-grained action recognition by motion saliency and mid-level patches. Applied Sciences. 10 (8). https://doi.org/10.3390/app10082811

A game theoretic analysis of resource mining in blockchain

Singh, R., Dwivedi, A., Srivastava, G., Wisznieska-Mayszkiel, A. and Cheng, X. 2020. A game theoretic analysis of resource mining in blockchain. Cluster Computing. 23 (3), pp. 2035-2046. https://doi.org/10.1007/s10586-020-03046-w

"Do the right thing" for whom? An experiment on ingroup favouritism, group assorting and moral suasion

Bilancini, E., Boncinelli, L., Capraro, V., Celadin, T. and Di Paolo, R. 2020. "Do the right thing" for whom? An experiment on ingroup favouritism, group assorting and moral suasion. Judgment and Decision Making. 15 (2), pp. 182-192.

Micro-distortion detection of lidar scanning signals based on geometric analysis

Liu, S., Chen, X., Li, Y. and Cheng, X. 2019. Micro-distortion detection of lidar scanning signals based on geometric analysis. Symmetry. 11 (12), pp. 2-13. https://doi.org/10.3390/sym11121471

Translucent players: explaining cooperative behavior in social dilemmas

Capraro, V. and Halpern, J. 2019. Translucent players: explaining cooperative behavior in social dilemmas. Rationality and Society. 31 (4), pp. 371-408. https://doi.org/10.1177/1043463119885102

Verifying cryptographic protocols

Ma, X. and Cheng, X. 2005. Verifying cryptographic protocols. IEEE Journal of Intelligent Cybernetic Systems.

Verifying security protocols by knowledge analysis

Ma, X. and Cheng, X. 2008. Verifying security protocols by knowledge analysis. International Journal of Security and Networks. 3 (3), pp. 183-192. https://doi.org/10.1504/IJSN.2008.020092

A security design for cloud computing: an implementation of an on premises authentication with Kerberos and IPSec within a network

Umar, M. and Cheng, X. 2012. A security design for cloud computing: an implementation of an on premises authentication with Kerberos and IPSec within a network. International Journal of Advanced Research in Computer Science. 3 (1), pp. 10-16. https://doi.org/10.26483/ijarcs.v3i1.6040

Comparative experiments on resource discovery in P2P networks

Gautam, S. and Cheng, X. 2014. Comparative experiments on resource discovery in P2P networks. Journal of Next Generation Information Technology. 5 (1), pp. 89-98.

Unbalanced private set intersection cardinality protocol with low communication cost

Lv, S., Ye, J., Yin, S. and Cheng, X. 2020. Unbalanced private set intersection cardinality protocol with low communication cost. Future Generation Computer Systems. 102, pp. 1054-1061. https://doi.org/10.1016/j.future.2019.09.022

Increasing altruistic and cooperative behaviour with simple moral nudges

Capraro, V., Jagfeld, G., Klein, R., Mul, M. and de Pol, I. 2019. Increasing altruistic and cooperative behaviour with simple moral nudges. Scientific Reports. 9 (1). https://doi.org/10.1038/s41598-019-48094-4

The evolution of lying in well-mixed populations

Capraro, V., Perc, M. and Vilone, D. 2019. The evolution of lying in well-mixed populations. Journal of The Royal Society Interface. 16 (156). https://doi.org/10.1098/rsif.2019.0211

Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface

Men, J., Xu, G., Han, Z., Sun, Z., Zhou, X., Lian, W. and Cheng, X. 2019. Finding sands in the eyes: vulnerabilities discovery in IoT with EUFuzzer on human machine interface. IEEE Access. 7, pp. 103751-103759. https://doi.org/10.1109/ACCESS.2019.2931061

Behavior modelling and individual recognition of sonar transmitter for secure communication in UASNs

Shi, F., Chen, Z. and Cheng, X. 2020. Behavior modelling and individual recognition of sonar transmitter for secure communication in UASNs. IEEE Access. 8, pp. 2447-2454. https://doi.org/10.1109/ACCESS.2019.2923059

Introduction of key problems in long-distance learning and training

Liu, S., Li, Z., Zhang, Y. and Cheng, X. 2019. Introduction of key problems in long-distance learning and training. Mobile Networks and Applications. 24 (1), pp. 1-4. https://doi.org/10.1007/s11036-018-1136-6

Vulnerabilities and limitations of MQTT protocol used between IoT devices

Dinculeană, D. and Cheng, X. 2019. Vulnerabilities and limitations of MQTT protocol used between IoT devices. Applied Sciences. 9 (5). https://doi.org/10.3390/app9050848

Imbalanced big data classification based on virtual reality in cloud computing

Xie, W. and Cheng, X. 2020. Imbalanced big data classification based on virtual reality in cloud computing. Multimedia Tools and Applications. 79 (23-24), pp. 16403-16420. https://doi.org/10.1007/s11042-019-7317-x

Platform of quality evaluation system for multimedia video communication based NS2

Yu, G., Xu, J. and Cheng, X. 2018. Platform of quality evaluation system for multimedia video communication based NS2. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-018-1164-x

Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network

Xie, X., Zhang, Z., Wang, J. and Cheng, X. 2019. Cloud resource prediction model based on triple exponential smoothing method and temporal convolutional network. Journal on Communications. 40 (8), pp. 143-150. https://doi.org/10.11959/j.issn.1000-436x.2019172

An authentication scheme to defend against UDP DrDoS attacks in 5G networks

Huang, H., Hu, L., Chu, J. and Cheng, X. 2019. An authentication scheme to defend against UDP DrDoS attacks in 5G networks. IEEE Access. 7, pp. 175970-175979. https://doi.org/10.1109/ACCESS.2019.2957565

Incremental association rule mining based on matrix compression for edge computing

Zhou, D., Ouyang, M., Kuang, Z., Li, Z., Zhou, J. and Cheng, X. 2019. Incremental association rule mining based on matrix compression for edge computing. IEEE Access. 7, pp. 1730444-173053. https://doi.org/10.1109/ACCESS.2019.2956823

The power of moral words: loaded language generates framing effects in the extreme dictator game

Capraro, V. and Vanzo, A. 2019. The power of moral words: loaded language generates framing effects in the extreme dictator game. Judgment and Decision Making. 14 (3), pp. 309-317.

Author correction: Group size effects and critical mass in public goods games

Pereda, M., Capraro, V. and Sánchez, A. 2019. Author correction: Group size effects and critical mass in public goods games. Springer Nature. https://doi.org/10.1038/s41598-019-49306-7

Group size effects and critical mass in public goods games

Pereda, M., Capraro, V. and Sánchez, A. 2019. Group size effects and critical mass in public goods games. Scientific Reports. 9 (1). https://doi.org/10.1038/s41598-019-41988-3

Grand challenges in social physics: in pursuit of moral behavior

Capraro, V. and Perc, M. 2018. Grand challenges in social physics: in pursuit of moral behavior. Frontiers in Physics. 6. https://doi.org/10.3389/fphy.2018.00107

Doing good vs. avoiding bad in prosocial choice: a refined test and extension of the morality preference hypothesis

Tappin, B. and Capraro, V. 2018. Doing good vs. avoiding bad in prosocial choice: a refined test and extension of the morality preference hypothesis. Journal of Experimental Social Psychology. 79, pp. 64-70. https://doi.org/10.1016/j.jesp.2018.06.005

Does the truth come naturally? Time pressure increases honesty in one-shot deception games

Capraro, V. 2017. Does the truth come naturally? Time pressure increases honesty in one-shot deception games. Economics Letters. 158, pp. 54-57. https://doi.org/10.1016/j.econlet.2017.06.015

Gender differences in moral judgment and the evaluation of gender-specified moral agents

Capraro, V. and Sippel, J. 2017. Gender differences in moral judgment and the evaluation of gender-specified moral agents. Cognitive Processing. 18 (4), pp. 399-405. https://doi.org/10.1007/s10339-017-0822-9

Deliberation favours social efficiency by making people disregard their relative shares: evidence from USA and India

Capraro, V., Corgnet, B., Espín, A. and Hernán-González, R. 2017. Deliberation favours social efficiency by making people disregard their relative shares: evidence from USA and India. Royal Society Open Science. 4 (2). https://doi.org/10.1098/RSOS.160605

To know or not to know? Looking at payoffs signals selfish behavior, but it does not actually mean so

Capraro, V. and Kuilder, J. 2016. To know or not to know? Looking at payoffs signals selfish behavior, but it does not actually mean so. Journal of Behavioral and Experimental Economics. 65, pp. 79-84. https://doi.org/10.1016/j.socec.2016.08.005

Data provenance with retention of reference relations

Wang, C., Yang, L., Wu, Y., Wu, Y., Cheng, X., Li, Z. and Liu, Z. 2018. Data provenance with retention of reference relations. IEEE Access. https://doi.org/10.1109/ACCESS.2018.2876879

People making deontological judgments in the Trapdoor dilemma are perceived to be more prosocial in economic games than they actually are

Capraro, V., Sippel, J., Zhao, B., Hornischer, L., Savary, M., Terzopoulou, Z., Faucher, P. and Griffioen, S. 2018. People making deontological judgments in the Trapdoor dilemma are perceived to be more prosocial in economic games than they actually are. PLoS ONE. 13 (10). https://doi.org/10.1371/journal.pone.0205066

Editorial: Recent advances of content understanding in image and multimedia

Liu, S., Cheng, X. and Min, G. 2017. Editorial: Recent advances of content understanding in image and multimedia. Recent Patents on Computer Science. 10 (1), pp. 2-5. https://doi.org/10.2174/221327591001170808093310

Gender differences in altruism on Mechanical Turk: expectations and actual behaviour

Branas-Garza, P., Capraro, V. and Rascon Ramirez, E. 2018. Gender differences in altruism on Mechanical Turk: expectations and actual behaviour. Economics Letters. 170, pp. 19-23. https://doi.org/10.1016/j.econlet.2018.05.022

Channel state information-based detection of Sybil attacks in wireless networks

Wang, C., Zhu, L., Gong, L., Zhao, Z., Yang, L., Liu, Z. and Cheng, X. 2018. Channel state information-based detection of Sybil attacks in wireless networks. Journal of Internet Services and Information Security. 8 (1), pp. 2-17. https://doi.org/10.22667/JISIS.2018.02.28.002

Gender differences in lying in sender-receiver games: a meta-analysis

Capraro, V. 2018. Gender differences in lying in sender-receiver games: a meta-analysis. Judgment and Decision Making. 13 (4), pp. 345-355.

Hierarchical invasion of cooperation in complex networks

Vilone, D., Capraro, V. and Ramasco, J. 2018. Hierarchical invasion of cooperation in complex networks. Journal of Physics Communications. 2 (2). https://doi.org/10.1088/2399-6528/aaab2e

Do the right thing: experimental evidence that preferences for moral behavior, rather than equity or efficiency per se, drive human prosociality

Capraro, V. and Rand, D. 2018. Do the right thing: experimental evidence that preferences for moral behavior, rather than equity or efficiency per se, drive human prosociality. Judgment and Decision Making. 13 (1), pp. 99-111.

Research on trust model in container-based cloud service

Xie, X., Yuan, T., Zhou, X. and Cheng, X. 2018. Research on trust model in container-based cloud service. Computers, Materials and Continua. 56 (2), pp. 273-283. https://doi.org/10.3970/cmc.2018.03587

Introduction of recent advanced hybrid information processing

Liu, S., Li, Z., Cheng, X. and Lin, Y. 2018. Introduction of recent advanced hybrid information processing. Mobile Networks and Applications. 23 (4), pp. 673-676. https://doi.org/10.1007/s11036-018-1013-3

Accurate Sybil attack detection based on fine-grained physical channel information

Wang, C., Zhu, L., Gong, L., Zhao, Z., Yang, L., Liu, Z. and Cheng, X. 2018. Accurate Sybil attack detection based on fine-grained physical channel information. Sensors. 18 (3). https://doi.org/10.3390/s18030878

DivORAM: Towards a practical oblivious RAM with variable block size

Liu, Z., Huang, Y., Li, J., Cheng, X. and Shen, C. 2018. DivORAM: Towards a practical oblivious RAM with variable block size. Information Sciences. 447, pp. 1-11. https://doi.org/10.1016/j.ins.2018.02.071

M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices

Gao, C., Lv, S., Wei, Y., Wang, Z., Liu, Z. and Cheng, X. 2018. M-SSE: an effective searchable symmetric encryption with enhanced security for mobile devices. IEEE Access. 6, pp. 38860-38869. https://doi.org/10.1109/ACCESS.2018.2852329

A distributed anomaly detection system for in-vehicle network using HTM

Wang, C., Zhao, Z., Gong, L., Zhu, L., Liu, Z. and Cheng, X. 2018. A distributed anomaly detection system for in-vehicle network using HTM. IEEE Access. 6, pp. 9091-9098. https://doi.org/10.1109/ACCESS.2018.2799210

Crime pattern recognition based on high-performance computing

Eissa, A., Cheng, X. and Petridis, M. 2018. Crime pattern recognition based on high-performance computing. 2017 International Conference Next Generation Community Policing. Heraklion, Crete, Greece 25 - 27 Oct 2017

A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface

Liu, S., Pan, Z. and Cheng, X. 2017. A novel fast fractal image compression method based on distance clustering in high dimensional sphere surface. Fractals. 25 (04), pp. 1740004-1-11. https://doi.org/10.1142/s0218348x17400047

Push, don't nudge: behavioral spillovers and policy instruments

d'Adda, G., Capraro, V. and Tavoni, M. 2017. Push, don't nudge: behavioral spillovers and policy instruments. Economics Letters. 154, pp. 92-95. https://doi.org/10.1016/j.econlet.2017.02.029

Deliberation favours social efficiency by making people disregard their relative shares: evidence from US and India

Capraro, V., Corgnet, B., Espín, A. and Hernán-González, R. 2017. Deliberation favours social efficiency by making people disregard their relative shares: evidence from US and India. Royal Society Open Science. 4 (2). https://doi.org/10.1098/rsos.160605

Partner selection supported by opaque reputation promotes cooperative behavior

Capraro, V., Giardini, F., Vilone, D. and Paolucci, M. 2016. Partner selection supported by opaque reputation promotes cooperative behavior. Judgment and Decision Making. 11 (6), pp. 589-600.

Degradation and encryption for outsourced PNG images in cloud storage

Wang, Y., Du, J., Cheng, X., Liu, Z. and Lin, K. 2016. Degradation and encryption for outsourced PNG images in cloud storage. International Journal of Grid and Utility Computing. 7 (1), pp. 22-28. https://doi.org/10.1504/IJGUC.2016.073773

Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud

Xie, X., Liu, R., Cheng, X., Hu, X. and Ni, J. 2016. Trust-Driven and PSO-SFLA based job scheduling algorithm on Cloud. Intelligent Automation & Soft Computing: An International Journal . 22 (4), pp. 561-566.

Numeric characteristics of generalized M-set with its asymptote

Liu, S., Cheng, X., Fu, W., Zhou, Y. and Li, Q. 2014. Numeric characteristics of generalized M-set with its asymptote. Applied Mathematics and Computation. 243, pp. 767-774. https://doi.org/10.1016/j.amc.2014.06.016

Local semantic indexing for resource discovery on overlay network using mobile agents

Singh, M., Cheng, X. and Belavkin, R. 2014. Local semantic indexing for resource discovery on overlay network using mobile agents. International Journal of Computational Intelligence Systems. 7 (3), pp. 432-455. https://doi.org/10.1080/18756891.2013.856257

Fractal property of generalized M-set with rational number exponent

Liu, S., Cheng, X., Lan, C., Fu, W., Zhou, J., Li, Q. and Gao, G. 2013. Fractal property of generalized M-set with rational number exponent. Applied Mathematics and Computation. 220, pp. 668-675. https://doi.org/10.1016/j.amc.2013.06.096

Mechanical verification of cryptographic protocols

Cheng, X., Ma, X., Huang, S. and Cheng, M. 2010. Mechanical verification of cryptographic protocols. Network Security. https://doi.org/10.1007/978-0-387-73821-5_5

DNSsec in Isabelle – replay attack and origin authentication

Kammueller, F., Kirsal-Ever, Y. and Cheng, X. 2013. DNSsec in Isabelle – replay attack and origin authentication. SMC 2013: IEEE International Conference on Systems, Man, and Cybernetics. Manchester, UK 13 - 16 Oct 2013 IEEE. pp. 4772-4777 https://doi.org/10.1109/SMC.2013.812

A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA

Wang, S., Li, W., Cheng, X., Wang, Y. and Jiang, Y. 2012. A face recognition algorithm using a fusion method based on Adaboost Bidirectional 2DLDA. Advances in Information Sciences and Service Sciences. 4 (23), pp. 181-188. https://doi.org/10.4156/AISS.vol4.issue23.23

A cooperative particle swarm optimizer with statistical variable interdependence learning

Sun, L., Yoshida, S., Cheng, X. and Liang, Y. 2012. A cooperative particle swarm optimizer with statistical variable interdependence learning. Information Sciences. 186 (1), pp. 20-39. https://doi.org/10.1016/j.ins.2011.09.033

Survey of grid resource monitoring and prediction strategies.

Hu, L., Cheng, X. and Che, X. 2010. Survey of grid resource monitoring and prediction strategies. International Journal of Intelligent Information Processing. 1 (2).

Efficient identity-based broadcast encryption without random oracles.

Hu, L., Liu, Z. and Cheng, X. 2010. Efficient identity-based broadcast encryption without random oracles. Journal of Computers. 5 (3), pp. 331-336.

Solving job shop scheduling problem using genetic algorithm with penalty function

Sun, L., Cheng, X. and Liang, Y. 2010. Solving job shop scheduling problem using genetic algorithm with penalty function. International Journal of Intelligent Information Processing. 1 (2), pp. 65-77.

Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization

Cheng, X., Che, X. and Hu, L. 2010. Bandwidth prediction based on nu-support vector regression and parallel hybrid particle swarm optimization. International Journal of Computational Intelligence Systems. 3 (1), pp. 70-83. https://doi.org/10.2991/ijcis.2010.3.1.7

Resource discovery using mobile agents

Singh, M., Cheng, X. and Belavkin, R. 2010. Resource discovery using mobile agents. Frontier of Computer Science and Technology (FCST), 2010 Fifth International Conference. Changchun, Jilin Province 18 - 22 Aug 2010 IEEE. pp. 72 -77 https://doi.org/10.1109/FCST.2010.93

Resource discovery using mobile agents

Singh, M., Cheng, X. and He, X. 2009. Resource discovery using mobile agents. in: Tao, D., Xu, D. and Li, X. (ed.) Semantic Mining Technologies for Multimedia Databases. New York, USA Information Science Reference. pp. 419-448

New e-Learning system architecture based on knowledge engineering technology

Li, Y., Chen, Z., Huang, R. and Cheng, X. 2009. New e-Learning system architecture based on knowledge engineering technology. 2009 IEEE International Conference on Systems, Man and Cybernetics. San Antonio, TX, USA 11 - 14 Oct 2009 IEEE. pp. 5140-5144 https://doi.org/10.1109/ICSMC.2009.5346013

Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals

Li, Y., Guo, H., Gao, G., Huang, R. and Cheng, X. 2009. Ubiquitous e-learning System for dynamic mini-courseware assembling and delivering to mobile terminals. in: Kim, J., Delen, D., Jinsoo, P., Ko, F., Rui, C., Hyung, J., Lee, W. and Kou, G. (ed.) NCM 2009: Fifth International Joint Conference on INC, IMS, and IDC; [proceedings]. IEEE. pp. 1081-1086