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Aydoğdu B, Samad H, Bai S, Abboud S, Gorantis I, Salah AA. Analyzing international airtime top-up transfers for migration and mobility. INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS 2023:1-18. [PMID: 37362634 PMCID: PMC10212232 DOI: 10.1007/s41060-023-00396-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2022] [Accepted: 05/04/2023] [Indexed: 06/28/2023]
Abstract
International airtime top-up transfers enable prepaid mobile phone users to send top-ups and data bundles to users in other countries, as well as make payments, in real time. These are heavily used by migrants to financially assist their families in their home countries and consequently could be a valuable source of information for migration and mobility analysis. However, top-up transfers are understudied as a form of money remittance in migration. In this paper, we explore the determinants and the potential of top-up transactions to complement remittance and migration statistics. Our results show that such data can provide insights into migrant groups, particularly for irregular migration and for estimating the real-time distribution of migrant groups for a given country.
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Affiliation(s)
- Bilgeçağ Aydoğdu
- Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands
| | - Hanif Samad
- DT One, 1 Raffles Place, Tower 2, Singapore, 048616 Singapore
| | - Shiqi Bai
- Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands
| | - Sami Abboud
- DT One, 1 Raffles Place, Tower 2, Singapore, 048616 Singapore
| | - Ilias Gorantis
- Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands
| | - Albert Ali Salah
- Information and Computing Sciences, Utrecht University, Princetonplein 5, 3584 CC Utrecht, The Netherlands
- Department of Computer Engineering, Boğaziçi University, 34342 Bebek, Istanbul, Turkey
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Cao L. AI and data science for smart emergency, crisis and disaster resilience. INTERNATIONAL JOURNAL OF DATA SCIENCE AND ANALYTICS 2023; 15:231-246. [PMID: 37035277 PMCID: PMC10041487 DOI: 10.1007/s41060-023-00393-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/09/2023] [Indexed: 04/07/2023]
Abstract
The uncertain world has seen increasing emergencies, crises and disasters (ECDs), such as the COVID-19 pandemic, hurricane Ian, global financial inflation and recession, misinformation disaster, and cyberattacks. AI for smart disaster resilience (AISDR) transforms classic reactive and scripted disaster management to digital proactive and intelligent resilience across ECD ecosystems. A systematic overview of diverse ECDs, classic ECD management, ECD data complexities, and an AISDR research landscape are presented in this article. Translational disaster AI is essential to enable smart disaster resilience.
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Affiliation(s)
- Longbing Cao
- School of Computer Science, University of Technology Sydney, Sydney, NSW 2007 Australia
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Ouyang H, Liu J, Yin Y, Cao S, Yan R, Ren Y, Zhou D, Li Q, Li J, Liao X, Ji W, Du B, Si Y, Hu C. Epidemiology and Comparative Analyses of the S Gene on Feline Coronavirus in Central China. Pathogens 2022; 11:pathogens11040460. [PMID: 35456135 PMCID: PMC9031646 DOI: 10.3390/pathogens11040460] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 04/08/2022] [Accepted: 04/09/2022] [Indexed: 02/06/2023] Open
Abstract
Feline coronavirus (FCoV) infections present as one of two forms: a mild or symptom-less enteric infection (FEC) and a fatal systemic disease termed feline infectious peritonitis (FIP). The lack of epidemiology of FCoV in central China and the reason why different symptoms are caused by viruses of the same serotype have motivated this investigation. Clinical data of 81 suspected FIP cases, 116 diarrhea cases and 174 healthy cases were collected from veterinary hospitals using body cavity effusion or fecal samples. Risk factors, sequence comparison and phylogenetic studies were performed. The results indicated that FIPV was distinguished from FECV in the average hydrophobicity of amino acids among the cleavage sites of furin, as well as the mutation sites 23,531 and 23,537. FIPV included a higher minimal R-X-X-R recognition motif of furin (41.94%) than did FECV (9.1%). The serotype of FCoV was insignificantly correlated with FIP, and the clade 1 and clade 2 strains that appeared were unique to central China. Thus, it is hypothesized that this, along with the latent variables of an antigenic epitope at positions 1058 and 1060, as well as mutations at the S1/S2 sites, are important factors affecting FCoV transmission and pathogenicity.
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Affiliation(s)
- Hehao Ouyang
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Jiahao Liu
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Yiya Yin
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Shengbo Cao
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
| | - Rui Yan
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Yi Ren
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Dengyuan Zhou
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
| | - Qiuyan Li
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
| | - Junyi Li
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Xueyu Liao
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Wanfeng Ji
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
| | - Bingjie Du
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
| | - Youhui Si
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
- Hubei Hongshan Laboratory, Wuhan 430070, China
- Correspondence: (Y.S.); (C.H.)
| | - Changmin Hu
- State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, China; (H.O.); (S.C.); (D.Z.); (Q.L.); (B.D.)
- College of Veterinary Medicine, Huazhong Agricultural University, Wuhan 430070, China; (J.L.); (Y.Y.); (R.Y.); (Y.R.); (J.L.); (X.L.); (W.J.)
- Correspondence: (Y.S.); (C.H.)
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Abstract
The SARS-CoV-2 virus, the COVID-19 disease, and the resulting pandemic have reshaped the entire world in an unprecedented manner. Massive efforts have been made by AI communities to combat the pandemic. What roles has AI played in tackling COVID-19? How has AI performed in the battle against COVID-19? Where are the gaps and opportunities? What lessons can we learn to enhance the ability of AI to battle future pandemics? These questions, despite being fundamental, are yet to be answered in full or systematically. They need to be addressed by AI communities as a priority despite the easing of the omicron infectiousness and threat. This article reviews these issues with reflections on global AI research and the literature on tackling COVID-19. It is envisaged that the demand and priority of developing "pandemic AI" will increase over time, with smart global epidemic early warning systems to be developed by a global collaborative AI effort.
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Affiliation(s)
- Longbing Cao
- University of Technology SydneySydneyNSW2007Australia
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Behera J, Pasayat AK, Behera H. COVID-19 Vaccination Effect on Stock Market and Death Rate in India. ASIA-PACIFIC FINANCIAL MARKETS 2022; 29:651-673. [PMCID: PMC8913195 DOI: 10.1007/s10690-022-09364-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 06/16/2023]
Abstract
The COVID-19 epidemic has brought attention to the vulnerability of new illnesses, and immunization remains a viable option for resuming normal life. This paper examines the influence of COVID-19 vaccination on the death rate and the performance of stock market in India. For this study, COVID-19 vaccination and death rate data is gathered from the Ministry of Health and Family Welfare (MoHFW) portal, and the data for the stock index is taken from the Bombay Stock Exchange (BSE), India. In order to achieve a precise representation of feature significance and distribution, EDA (Exploratory Data Analysis) is utilized in this study. The impact of COVID-19 immunization on the mortality rate and stock market index is investigated using both statistical analysis and Machine Learning Regression-based models. The models are remarkably accurate in reproducing actual result. The empirical study suggests that vaccination has a strong positive impact on the stock market and reducing the death rate. Furthermore, the policies recommended by government and monetary authorities coupled with COVID-19 vaccine supported the stock market recovery in pandemic.
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Affiliation(s)
- Jyotirmayee Behera
- Department of Mathematics, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu 603203 India
| | - Ajit Kumar Pasayat
- Indian Institute of Technology, Kharagpur, Kharagpur, West Bengal 721302 India
| | - Harekrushna Behera
- Department of Mathematics, SRM Institute of Science and Technology, Kattankulathur, Chengalpattu, Tamil Nadu 603203 India
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