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Zhao HM, He HD, Lu KF, Han XL, Ding Y, Peng ZR. Measuring the impact of an exogenous factor: An exponential smoothing model of the response of shipping to COVID-19. TRANSPORT POLICY 2022; 118:91-100. [PMID: 35125683 PMCID: PMC8805997 DOI: 10.1016/j.tranpol.2022.01.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 01/24/2022] [Indexed: 05/25/2023]
Abstract
Following the outbreak of the COVID-19 pandemic, various lockdown strategies restrained global economic growth bringing a significant decline in maritime transportation. However, the previous studies have not adequately recognized the specific impacts of COVID-19 on maritime transportation. In this study, a series of analyses of the Baltic Dry Index (BDI), the China Coastal Bulk Freight Index (CCBFI) and of container throughputs with and without the impact of COVID-19 were carried out to assess changing trends in dry bulk and container transportation. The results show that global dry bulk transportation was largely affected by lockdown policies in the second month during COVID-19, and BDI presented a year-on-year decrease of approximately 35.5% from 2019 to 2020. The CCBFI showed an upward trend in the second month during COVID-19, one month ahead of the BDI. The container throughputs at Shanghai Port, the Ports of Hong Kong, the Ports of Singapore and the Ports of Los Angeles from 2019 to 2020 presented the largest year-on-year drops of approximately 19.6%, 7.1%, 10.6% and 30.9%, respectively. In addition, the authors developed exponential smoothing models of BDI, CCBFI, and container transportation, and calculated the percentage prediction error between the observed and predicted values to examine the impact of exogenous effects on the shipping industry due to the outbreak of COVID-19. The results are consistent with the conclusions obtained from the comparison of BDI, CCBFI, and container transportation during the same period in 2020 and 2019. Finally, on the basis of the findings, smart shipping and special support policies are proposed to reduce the negative impacts of COVID-19.
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Affiliation(s)
- Hong-Mei Zhao
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
- School of Economics and Management, Shanghai Maritime University, Shanghai, 200135, China
| | - Hong-Di He
- Center for Intelligent Transportation Systems and Unmanned Aerial Systems Applications, State Key Laboratory of Ocean Engineering, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Kai-Fa Lu
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
| | - Xiao-Long Han
- Logistics Research Center, Shanghai Maritime University, Shanghai, 200135, China
| | - Yi Ding
- Logistics Research Center, Shanghai Maritime University, Shanghai, 200135, China
| | - Zhong-Ren Peng
- International Center for Adaptation Planning and Design, College of Design, Construction and Planning, University of Florida, PO Box 115706, Gainesville, FL, 32611-5706, USA
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Pampush JD, Fuselier EJ, Yapuncich GS. Using BayesModelS to provide Bayesian- and phylogenetically-informed primate body mass predictions. J Hum Evol 2021; 161:103077. [PMID: 34688978 DOI: 10.1016/j.jhevol.2021.103077] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 09/01/2021] [Accepted: 09/01/2021] [Indexed: 10/20/2022]
Abstract
An accurate prediction of the body mass of an extinct species can greatly inform the reconstruction of that species' ecology. Therefore, paleontologists frequently predict the body mass of extinct taxa from fossilized materials, particularly dental dimensions. Body mass prediction has traditionally been performed in a frequentist statistical framework, and accounting for phylogenetic relationships while calibrating prediction models has only recently become more commonplace. In this article, we apply BayesModelS-a phylogenetically informed Bayesian prediction method-to predict body mass in a sample of 49 euarchontan species (24 strepsirrhines, 20 platyrrhines, 3 tarsiids, 1 dermopteran, and 1 scandentian) and compare this approach's body mass prediction accuracy with other commonly used techniques, namely ordinary least squares, phylogenetic generalized least squares, and phylogenetic independent contrasts (PICs). When predicting the body masses of extant euarchontans from dental and postcranial variables, BayesModelS and PICs have substantially higher predictive accuracy than ordinary least squares and phylogenetic generalized least squares. The improved performances of BayesModelS and PIC are most evident for dentally derived body mass proxies or when body mass proxies have high degrees of phylogenetic covariance. Predicted values generated by BayesModelS and PIC methods also show less variance across body mass proxies when applied to the Eocene adapiform Notharctus tenebrosus. These more explicitly phylogenetically based methods should prove useful for predicting body mass in a paleontological context, and we provide executive scripts for both BayesModelS and PIC to increase ease of application.
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Affiliation(s)
- James D Pampush
- Department of Exercise Science, High Point University, High Point, NC 27260, USA; Department of Physician Assistant Studies, High Point University, High Point, NC 27260, USA.
| | - Edward J Fuselier
- Department of Mathematical Sciences, High Point University, High Point, NC 27260, USA
| | - Gabriel S Yapuncich
- Department of Evolutionary Anthropology, Duke University, Durham, NC 27708, USA; Medical Education Administration, Duke University School of Medicine, Durham, NC 27710, USA
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Yapuncich GS, Bowie A, Belais R, Churchill SE, Walker CS. Predicting body mass of bonobos (Pan paniscus) with human-based morphometric equations. Am J Primatol 2020; 82:e23088. [PMID: 31961002 DOI: 10.1002/ajp.23088] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 11/06/2019] [Accepted: 12/15/2019] [Indexed: 01/31/2023]
Abstract
A primate's body mass covaries with numerous ecological, physiological, and behavioral characteristics. This versatility and potential to provide insight into an animal's life has made body mass prediction a frequent and important objective in paleoanthropology. In hominin paleontology, the most commonly employed body mass prediction equations (BMPEs) are "mechanical" and "morphometric": uni- or multivariate linear regressions incorporating dimensions of load-bearing skeletal elements and stature and living bi-iliac breadth as predictor variables, respectively. The precision and accuracy of BMPEs are contingent on multiple factors, however, one of the most notable and pervasive potential sources of error is extrapolation beyond the limits of the reference sample. In this study, we use a test sample requiring extrapolation-56 bonobos (Pan paniscus) from the Lola ya Bonobo sanctuary in Kinshasa, Democratic Republic of the Congo-to evaluate the predictive accuracy of human-based morphometric BMPEs. We first assess systemic differences in stature and bi-iliac breadth between humans and bonobos. Due to significant differences in the scaling relationships of body mass and stature between bonobos and humans, we use panel regression to generate a novel BMPE based on living bi-iliac breadth. We then compare the predictive accuracy of two previously published morphometric equations with the novel equation and find that the novel equation predicts bonobo body mass most accurately overall (41 of 56 bonobos predicted within 20% of their observed body mass). The novel BMPE is particularly accurate between 25 and 45 kg. Given differences in limb proportions, pelvic morphology, and body tissue composition between the human reference and bonobo test samples, we find these results promising and evaluate the novel BMPE's potential application to fossil hominins.
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Affiliation(s)
- Gabriel S Yapuncich
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina.,Department of Molecular Biomedical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina
| | - Aleah Bowie
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina
| | | | - Steven E Churchill
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina.,Evolutionary Studies Institute, University of the Witwatersrand, Wits, South Africa
| | - Christopher S Walker
- Department of Evolutionary Anthropology, Duke University, Durham, North Carolina.,Department of Molecular Biomedical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, North Carolina.,Evolutionary Studies Institute, University of the Witwatersrand, Wits, South Africa
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Gonzales LA, Malinzak MD, Kay RF. Intraspecific variation in semicircular canal morphology—A missing element in adaptive scenarios? AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 2018; 168:10-24. [DOI: 10.1002/ajpa.23692] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/10/2018] [Revised: 06/06/2018] [Accepted: 07/12/2018] [Indexed: 11/06/2022]
Affiliation(s)
- Lauren A. Gonzales
- Department of Biomedical Sciences University of South Carolina School of Medicine‐Greenville Greenville South Carolina
| | - Michael D. Malinzak
- Department of Evolutionary Anthropology Duke University Durham North Carolina
- Department of Radiology Duke University School of Medicine Durham North Carolina
| | - Richard F. Kay
- Department of Evolutionary Anthropology Duke University Durham North Carolina
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Evaluating morphometric body mass prediction equations with a juvenile human test sample: accuracy and applicability to small-bodied hominins. J Hum Evol 2018; 115:65-77. [DOI: 10.1016/j.jhevol.2017.03.009] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Revised: 03/13/2017] [Accepted: 03/14/2017] [Indexed: 11/18/2022]
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Ruff CB, Niskanen M. Introduction to special issue: Body mass estimation - Methodological issues and fossil applications. J Hum Evol 2017; 115:1-7. [PMID: 29174414 DOI: 10.1016/j.jhevol.2017.09.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 09/23/2017] [Indexed: 11/16/2022]
Affiliation(s)
- Christopher B Ruff
- Center for Functional Anatomy and Evolution, Johns Hopkins University School of Medicine, 1830 E. Monument St., Baltimore, MD 21205, USA.
| | - Markku Niskanen
- Department of Archeology, University of Oulu, Oulu 90014, Finland.
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