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1.
Industrial Management and Data Systems ; 2022.
Article in English | Scopus | ID: covidwho-1878902

ABSTRACT

Purpose: The purpose of this paper is to explore the factors affecting the intention of social networking sites (SNS) users to comply with government policy during the COVID-19 pandemic. Design/methodology/approach: Based on the theory of appraisal and coping, the research model is tested using survey data collected from 326 SNS users. Structural equation modeling is used to test the research model. Findings: The results show that social support has a positive effect on outbreak self-efficacy but has no significant effect on perceived avoidability. Government information transparency positively affects outbreak self-efficacy and perceived avoidability. Outbreak self-efficacy and perceived avoidability have a strong positive impact on policy compliance intention through problem-focused coping. Practical implications: The results suggest that both government and policymakers could deliver reliable pandemic information to the citizens via social media. Originality/value: This study brings novel insights into citizen coping behavior, showing that policy compliance intention is driven by the ability to cope with problems. Moreover, this study enhances the theoretical understanding of the role of social support, outbreak self-efficacy and problem-focused coping. © 2022, Emerald Publishing Limited.

2.
Applied biochemistry and microbiology ; 57(Suppl 1):S11-S26, 2021.
Article in English | EuropePMC | ID: covidwho-1871964

ABSTRACT

Naphthoquinones harboring 1,4-naphthoquinone pharmacophore are considered as privileged structures in medicinal chemistry. In pharmaceutical industry and fundamental research, polyketide naphthoquinones were widely produced by heterologous expression of polyketide synthases in microbial chassis cells, such as Saccharomyces cerevisiae and Escherichia coli. Nevertheless, these cell factories still remain, to a great degree, black boxes that often exceed engineers’ expectations. In this work, the biotransformation of juglone or 1,4-naphthoquinone was conducted to generate novel derivatives and it was revealed that these two naphthoquinones can indeed be modified by the chassis cells. Seventeen derivatives, including 6 novel compounds, were isolated and their structural characterizations indicated the attachment of certain metabolites of chassis cells to naphthoquinones. Some of these biosynthesized derivatives were reported as potent antimicrobial agents with reduced cytotoxic activities. Additionally, molecular docking as simple and quick in silico approach was performed to screen the biosynthesized compounds for their potential antiviral activity. It was found that compound 11 and 17 showed the most promising binding affinities against Nsp9 of SARS-CoV-2, demonstrating their potential antiviral activities. Overall, this work provides a new approach to generate novel molecules in the commonly used chassis cells, which would expand the chemical diversity for the drug development pipeline. It also reveals a novel insight into the potential of the catalytic power of the most widely used chassis cells. Supplementary Information The online version contains supplementary material available at 10.1134/S0003683821100124.

3.
2022 Workshops of the EDBT/ICDT Joint Conference, EDBT/ICDT-WS 2022 ; 3135, 2022.
Article in English | Scopus | ID: covidwho-1871933

ABSTRACT

Knowledge graphs are being used for the detection of money laundering, insurance fraud, and other suspicious activities. Some recent work demonstrated how knowledge graphs are being used to study the impact of the COVID-19 outbreak on the economy. The fact that knowledge graphs are being used in more and more interdisciplinary problems calls for a reliable source of interdisciplinary knowledge. In this paper, we study the integration of knowledge graphs in the domains of economics, banking, and finance. Our integrated knowledge graph has over 610K nodes and 1.7 million edges. By performing statistical and graph-theoretical analysis, we demonstrate how the integration results in more entities with richer information. Its quality was examined by analyzing the subgraphs of the identity links and (pseudo-)transitive relations. Finally, we study the sources of error, and their refinement and discuss the benefit of our integrated graph. © 2022 Copyright for this paper by its authors.

4.
2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; : 7279-7282, 2021.
Article in English | Scopus | ID: covidwho-1861125

ABSTRACT

Due to the Coronavirus Disease (COVID-19) pandemic, the human activities in China and even in the world were reduced in 2020, which also caused the variation of the atmospheric environment, especially atmospheric aerosol emissions. In this paper, the MODIS level-3 gridded atmosphere monthly global joint product in 2019 and 2020 were collected and processed. After preliminary analysis, we found that MODIS annual aerosol optical depth (AOD) over China in 2020 is generally lower than in 2019. In some regions such as Beijing-Tianjin-Hebei and Yangtze River Delta, AOD values dropped the most in February. However, in some months and regions, AOD in 2020 is even higher than in 2019. More studies are still ongoing. © 2021 IEEE.

5.
2021 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2021 ; : 5692-5695, 2021.
Article in English | Scopus | ID: covidwho-1861116

ABSTRACT

Affected by the Coronavirus Disease (COVID-19) pandemic, almost all students in China have to study online at home from February to June, 2020. In this paper, we discussed the forms of online courses and took Jiangsu Normal University as an example to introduce the online courses of remote sensing in China. The results of the satisfaction survey show that more than 90% of the respondents agree with online courses and believe that online courses can at least meet basic learning needs in the age of COVID-19, and more than 60% of respondents claimed that they had met or exceeded their learning expectations. The major advantages of online course include reducing the gathering of people and thus the risk of infection. However, there are still some problems with online courses, and we hope that these problems can be solved well in the future. © 2021 IEEE

6.
Embase; 2021.
Preprint in English | EMBASE | ID: ppcovidwho-337392

ABSTRACT

The coronavirus disease 2019 (COVID-19) has been ravaging throughout the world for more than two years and has severely impaired both human health and the economy. The causative agent, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) employs the viral RNA-dependent RNA polymerase (RdRp) complex for genome replication and transcription, making RdRp an appealing target for antiviral drug development. Here, we reveal that RdRp can recognize and utilize nucleoside diphosphates (NDPs) as a substrate to synthesize RNAs with an efficiency of about two thirds of using nucleoside triphosphates (NTPs) as a substrate. NDPs incorporation is also template-specific and has high fidelity. Moreover, RdRp can incorporate β-d-N4-hydroxycytidine (NHC) into RNA while using diphosphate form molnupiravir (MDP) as a substrate. We also observed that MDP is a better substrate for RdRp than the triphosphate form molnupiravir (MTP).

7.
35th AAAI Conference on Artificial Intelligence, AAAI 2021 ; 6A:4821-4829, 2021.
Article in English | Scopus | ID: covidwho-1857257

ABSTRACT

The COVID-19 pandemic has spread globally for several months. Because its transmissibility and high pathogenicity seriously threaten people’s lives, it is crucial to accurately and quickly detect COVID-19 infection. Many recent studies have shown that deep learning (DL) based solutions can help detect COVID-19 based on chest CT scans. However, most existing work focuses on 2D datasets, which may result in low quality models as the real CT scans are 3D images. Besides, the reported results span a broad spectrum on different datasets with a relatively unfair comparison. In this paper, we first use three state-of-the-art 3D models (ResNet3D101, DenseNet3D121, and MC3 18) to establish the baseline performance on three publicly available chest CT scan datasets. Then we propose a differentiable neural architecture search (DNAS) framework to automatically search the 3D DL models for 3D chest CT scans classification and use the Gumbel Softmax technique to improve the search efficiency. We further exploit the Class Activation Mapping (CAM) technique on our models to provide the interpretability of the results. The experimental results show that our searched models (CovidNet3D) outperform the baseline human-designed models on three datasets with tens of times smaller model size and higher accuracy. Furthermore, the results also verify that CAM can be well applied in CovidNet3D for COVID-19 datasets to provide interpretability for medical diagnosis. Code: https://github.com/HKBU-HPML/CovidNet3D. Copyright © 2021, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.

8.
Annals of Behavioral Medicine ; 56(SUPP 1):S391-S391, 2022.
Article in English | Web of Science | ID: covidwho-1849012
9.
Annals of Behavioral Medicine ; 56(SUPP 1):S119-S119, 2022.
Article in English | Web of Science | ID: covidwho-1848905
10.
2nd International Conference on Electronics, Communications and Information Technology, CECIT 2021 ; : 802-806, 2021.
Article in English | Scopus | ID: covidwho-1831730

ABSTRACT

Artificial intelligence (AI) has entered tourism and become a new service in a tour guide. AI technology can help tourism by providing customized services and attracting visitors to fight with the crisis of the COVID-19 epidemic. This paper introduces how AI tour guide services contribute to tourism and its main issues. The future development of AI tour guides also was discussed at the end and the authors believe lifelong machine learning is the key to developing AI tour guides. © 2021 IEEE.

11.
Chinese Traditional and Herbal Drugs ; 53(8):2460-2469, 2022.
Article in Chinese | EMBASE | ID: covidwho-1818643

ABSTRACT

Objective: Overview the systematic review/Meta analysis of Lianhua Qingwen (连花清瘟) combined with conventional western medicine in the treatment of coronavirus disease 2019 (COVID-19). Methods: Systematic reviews/Meta-analysis of Lianhua Qingwen combined with western conventional in the treatment of COVID-19 from CNKI, Wanfang, CBM, VIP, PubMed, Embase, Cochrane Library, and Web of Sciencewere search, retrieved as of October 1, 2021. Two investigators screened the literature according to the inclusion and exclusion criteria, and determined the final inclusion of the literature. AMSTAR-2 scale, GRADE system, and PRISMA statements were used to evaluate the methodological quality and GRADE the evidence quality. Results: A total of eight systematic reviews/Meta analyses were included, including six in Chinese and four in English. The quality evaluation and evidence quality classification results show that the quality of the literature and the level of evidence were low. Conclusion: The existing evidence shows that Lianhua Qingwen combined with conventional western has a good effectin the treatment of COVID-19. However, due to the low methodological quality and evidence quality level of the systematic review/Meta analysis and the low level of evidence quality, more high-quality researchs are needed to obtain high-quality research results for verification.

12.
Dermatologica Sinica ; 40(1):52-53, 2022.
Article in English | EMBASE | ID: covidwho-1818370
13.
Clinical Cancer Research ; 27(6 SUPPL 1), 2021.
Article in English | EMBASE | ID: covidwho-1816884

ABSTRACT

The COVID-19 pandemic brought with it TX changes for many patients (pts) with AMEL, as it did for other pts with cancer. The long-term impacts of mandated area lockdowns, social distancing, medical society guidelines, and patient preference will not be fully understood for some time. The first step to learning from the pandemic is to assess how AMEL care was rendered in 2020. We performed a retrospective analysis of systemic TX for AMEL in KPNC, an integrated community healthcare system with approximately 4 million pts and about 150 de novo diagnoses of AMEL annually. We performed a chart review of pts with AMEL who were treated with standard of care systemic therapy, either immune-checkpoint inhibitors (ICI) or BRAF/MEK inhibitors (BRAF/MEKi), from January 1 to March 15, 2020, as a control group, and between March 15 and May 20, during the first wave of the COVID-19 pandemic in California with follow-up through November 4, 2020. Between January 1 and March 15, 26 pts started palliative ICI of whom 11 started combination PD1 (PD1i) and CTLA4 inhibitors. Among 15 pts who started on single-agent PD1i, 14 pts received short-interval TX (SIT), while 1 started long-interval TX (LIT). All 21 pts who started perioperative PD1i pre-pandemic, started on SIT. Between March 15 and May 20, 21 pts started palliative ICI, of whom only 3 started combination TX. Among pts who started palliative single-agent PD1i 40% started on LIT in this initial phase of the pandemic. 27 pts started perioperative ICI during this time. We found 3 started with neoadjuvant therapy and 78% started on LIT. Among 78 pts who were already on palliative single-agent ICI at the start of the COVID-19 pandemic, 15% remained on SIT and 24% changed to LIT. Sixteen pts (21%) also interrupted palliative ICI between March 15 and April 15 after a median time on TX of 45 weeks and for 63% the cited reason for interruption on chart review was the COVID 19 pandemic. Three of these pts who stopped ICI changed to BRAF/MEKi, the remainder continue in active follow-up as of November 2020. Among 72 pts already receiving perioperative ICI in March 2020, 19% remained on SIT, 35% changed to LIT, and 11% were already on LIT. 39% of pts interrupted perioperative ICI after a median time of 20 weeks on TX and 46% of these cited COVID 19 as the reason for interruption. Three pts have since resumed peri-operative TX, but the others remain in active follow-up off therapy. Between 3/15 and 5/30/2020, we noted a 325% increase in pts started on BRAF/MEKi;69% of pts received therapy for palliative intent. The start of the COVID-19 pandemic saw many different changes in AMEL TX in KPNC, with increased use of single-agent ICI, LIT, and oral therapy, in line with public health guidance, oncology societal guidelines and patient preference. It will be important to assess the long-term outcomes relating to these changes, including the impact of early discontinuation of ICI, to help guide future Melanoma care during and after the pandemic.

14.
Transportation Research Record ; 2676:634-642, 2022.
Article in English | Scopus | ID: covidwho-1808020

ABSTRACT

Bike share programs are becoming increasingly popular across U.S. cities. However, their impact on persistent disparities in cycling by gender, race, and socioeconomic status remains understudied. We examined whether subscribers of Citi Bike, New York City’s (NYC) largest bike share program, reflect the sociodemographic profile of NYC cyclists. Using NYC Community Health Survey data, we described adult NYC residents of neighborhoods with ≥ 1 Citi Bike stations who rode a bicycle at least once a month. Citi Bike members were also described using first-time subscriber survey data. We compared the sociodemographic characteristics of these groups via a z-score with pooled variance. Approximately 2.2 million residents lived in 15 NYC neighborhoods with ≥1 Citi Bike station, and 449,000 (20.5%) reported cycling at least once a month in the past 12 months. Among first-time Citi Bike subscribers, 23,223 (11.5%) completed the survey. Compared with NYC cyclists, Citi Bike subscribers were more likely to be women, aged 24 to 45, White, college graduates, and from a household with an income > 400% than the poverty level. Compared with the general population, cyclists were more likely to be White, male, and from a household with an income > 400% than the poverty level. Race/ethnicity and socioeconomic status (not gender) disparities were larger among Citi Bike subscribers than NYC cyclists. With the emergence of cycling as an alternative transportation during the COVID-19 pandemic and the extension of bike share programs, this highlights the need for ongoing, systematic monitoring of bike share user socioeconomic characteristics to evaluate equitable use and access. © National Academy of Sciences: Transportation Research Board 2021.

15.
Cambridge Journal of Economics ; 46(2):251-274, 2022.
Article in English | Scopus | ID: covidwho-1806315

ABSTRACT

Recent debates about whether the standard full-time working week (35-40 h) can be replaced by a shorter working week have received extensive attention. Using 2015 European Working Conditions Survey data, this study contributes to these debates by exploring the relationships between job quantity, job quality and employees' mental health. Overall, we find that a job's quality matters more than its quantity as measured in hours per week. The results show that actual working hours are hardly related to employees' mental health but job quality, especially intrinsically meaningful work, less intensified work and having a favourable social environment, has positive effects on employee mental health, even in jobs with short working hours. Moreover, although working less than one prefers (under-employment) has negative effects, these negative effects become much smaller in size and non-significant in good quality jobs, especially in jobs with skill discretion and good job prospects. These findings develop the debates about a shorter standard working week by emphasising the continued and crucial importance of job quality in debates on the future of work. These results also suggest that policymakers should pay particular attention to job quality when addressing the dramatic reduction in total hours of employment in Europe following the COVID-19 crisis. © 2021 The Author(s) 2021. Published by Oxford University Press on behalf of the Cambridge Political Economy Society.

16.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-333669

ABSTRACT

BACKGROUND: Thrombotic complications occur at high rates in hospitalized patients with COVID-19, yet the impact of intensive antithrombotic therapy on mortality is uncertain. RESEARCH QUESTION: How does in-hospital mortality compare with intermediate-versus prophylactic-dose anticoagulation, and separately with in-hospital aspirin versus no antiplatelet therapy, in treatment of COVID-19? STUDY DESIGN AND METHODS: Using data from 2785 hospitalized adult COVID-19 patients, we established two separate, nested cohorts of patients (1) who received intermediate- or prophylactic-dose anticoagulation ("anticoagulation cohort", N = 1624), or (2) who were not on home antiplatelet therapy and received either in-hospital aspirin or no antiplatelet therapy ("aspirin cohort", N = 1956). Propensity score matching utilizing various markers of illness severity and other patient-specific covariates yielded treatment groups with well-balanced covariates in each cohort. The primary outcome was cumulative incidence of in-hospital death. RESULTS: Among propensity score-matched patients in the anticoagulation cohort (N = 382), in a multivariable regression model, intermediate-compared to prophylactic-dose anticoagulation was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.518 [0.308-0.872]). Among propensity-score matched patients in the aspirin cohort (N = 638), in a multivariable regression model, in-hospital aspirin compared to no antiplatelet therapy was associated with a significantly lower cumulative incidence of in-hospital death (hazard ratio 0.522 [0.336-0.812]). INTERPRETATION: In this propensity score-matched, observational study of COVID-19, intermediate-dose anticoagulation and aspirin were each associated with a lower cumulative incidence of in-hospital death. SUMMARY CONFLICT OF INTEREST STATEMENTS: No conflict of interest exists for any author on this manuscript.

17.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333598

ABSTRACT

BACKGROUND: The severity of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is highly heterogenous. Studies have reported that males and some ethnic groups are at increased risk of death from COVID-19, which implies that individual risk of death might be influenced by host genetic factors. METHODS: In this project, we consider the mortality as the trait of interest and perform a genome-wide association study (GWAS) of data for 1,778 infected cases (445 deaths, 25.03%) distributed by the UK Biobank. Traditional GWAS failed to identify any genome-wide significant genetic variants from this dataset. To enhance the power of GWAS and account for possible multi-loci interactions, we adopt the concept of super-variant for the detection of genetic factors. A discovery-validation procedure is used for verifying the potential associations. RESULTS: We find 8 super-variants that are consistently identified across multiple replications as susceptibility loci for COVID-19 mortality. The identified risk factors on Chromosomes 2, 6, 7, 8, 10, 16, and 17 contain genetic variants and genes related to cilia dysfunctions ( DNAH7 and CLUAP1 ), cardiovascular diseases ( DES and SPEG ), thromboembolic disease ( STXBP5 ), mitochondrial dysfunctions ( TOMM7 ), and innate immune system ( WSB1 ). It is noteworthy that DNAH7 has been reported recently as the most downregulated gene after infecting human bronchial epithelial cells with SARS-CoV2. CONCLUSIONS: Eight genetic variants are identified to significantly increase risk of COVID-19 mortality among the patients with white British ancestry. These findings may provide timely evidence and clues for better understanding the molecular pathogenesis of COVID-19 and genetic basis of heterogeneous susceptibility, with potential impact on new therapeutic options.

18.
20th and 21st Joint COTA International Conference of Transportation Professionals - Advanced Transportation, Enhanced Connection ; : 681-690, 2021.
Article in English | Web of Science | ID: covidwho-1790152

ABSTRACT

COVID-19 has been affecting every aspect of societal life including human mobility since December, 2019. In this paper, we study the impact of COVID-19 on human mobility patterns at the state level within the United States. From the temporal perspective, we find that the change of mobility patterns does not necessarily correlate with government policies and guidelines, but is more related to people's awareness of the pandemic, which is reflected by the search data from Google Trends. Our results show that it takes on average 14 days for the mobility patterns to adjust to the new situation. From the spatial perspective, we conduct a state-level network analysis and clustering using the mobility data from Multiscale Dynamic Human Mobility Flow Dataset. As a result, we find that 1) states in the same cluster have shorter geographical distances;2) a 14-daydelay again is found between the time when the largest number of clusters appears and the peak of Coronavirus-related search queries on Google Trends;and 3) a major reduction in other network flow properties, namely degree, closeness, and betweenness, of all states from the week of March2 to the week of April 6 (the week of the largest number of clusters).

19.
PubMed; 2022.
Preprint in English | PubMed | ID: ppcovidwho-332928

ABSTRACT

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure. One-sentence summary: Efficient Editing of SARS-CoV-2 genomic RNA by Host APOBEC deaminases and Its Potential Impacts on the Viral Replication and Emergence of New Strains in COVID-19 Pandemic.

20.
Chinese Science Bulletin-Chinese ; 67(7):670-684, 2022.
Article in Chinese | Web of Science | ID: covidwho-1770629

ABSTRACT

Cities account for more than 70% of global carbon emissions and play an important role in mitigating climate change and achieving carbon peak and carbon neutrality. As the Paris Agreement emphasizes the need to reach global peaking of greenhouse gas emissions as soon as possible, it is significant to predict carbon emissions at the city level. However, the current COVID-19 pandemic has dramatically impacted global socioeconomic development and carbon emissions, downplaying the reference value for most urban carbon emission prediction models. In fact, existing studies on urban carbon emission prediction have also suffered from some shortcomings, such as unclear analyses of the impact of the pandemic, single scenario prediction, unified setting of growth rates, and failure to provide decision support for the government's carbon peak work. Therefore, a multi-scenario study on urban carbon emission prediction and carbon peak in the post-pandemic period would provide local governments with scientific data to make their carbon peak action plan. To that end, we set five-carbon emission scenarios: business as usual (BAU), high emissions (HE), extremely high emissions (EHE), low emissions (LE) and extremely low emissions (ELF). Based on the Monte Carlo method, we adjust the probabilities of different periods and different carbon emission scenarios to simulate uncertain evolution of carbon emissions as well as carbon emission reduction. Combining multi-scenario analyses with the Mann-Kendall trend test and Theil Sen's trend slope estimation method, we predict carbon emissions of the Pearl River Delta Urban Agglomeration (PRD) from 2021 to 2035 and analyze the evolution path of PRD's carbon emissions as well as its potential for carbon peak and carbon emission reduction from 2006 to 2035. Discussions are made on the possibility of achieving conditional areas' carbon peak goal in 2025 in Guangdong and China's carbon peak goal in 2030. We find that: (1) Carbon emissions of PRD increased rapidly from 2006 to 2016. Dynamic simulation shows that carbon emissions a significant peak in 2020 and decrease to 248.85 M similar to 270.06 Mt in 2035. Carbon intensity decreases by 84.18 degrees 4-85.21% from 2006 to 2035. Based on the emission reduction of the BAU scenario, the cumulative carbon emission reduction potential of the LF, scenario and ELF, scenario is as high as 304.86 M and 587.22 Mt from 2021 to 2035. Carbon emission reduction potential based on dynamic simulation of random combination scenario is between 81.68 and 128.25 Mt, with a probability of 67.65% to achieve further emission reduction. The probability of reducing 27.44 Mt carbon emissions is the largest. (2) Shenzhen, Zhuhai, Huizhou and Dongguan are four cities that show an inverted "U" shaped evolution path to achieve carbon peak. All of them reach the carbon peak no later than 2020. From 2006 to 2035, especially after the carbon peak, carbon emissions of these cities will decrease significantly. Their carbon emissions will reduce by 14.15 M-15.40 Mt, 9.17 M-9.94 Mt, 24.07 M-26.08 Mt and 22.36 M-24.24 Mt in 2035, respectively. The cumulative carbon emission reduction potential from 2021 to 2035 is -7.99 M-8.69 Mt, -3.48 M-4.87 Mt, -5.97 M-15.39 Mt and-8.77 M-12.62 Mt, respectively. However, being earlier to reach a carbon peak reduces their carbon emission reduction potential from 2021 to 2035. (3) Guangzhou, Foshan, Zhongshan, Jiangmen and Zhaoqing are five cities that could potentially reach carbon peaks but with divergent evolution paths. Some scenarios are at risk of not reaching a carbon peak. The possibility for Guangzhou, Foshan and Zhongshan to achieve the carbon peak target of conditional areas in Guangdong Province in 2025 is more than 96.01%, while that for Jiangmen and Zhaoqing is less than 20.08%. Moreover, there is a possibility of 2.04% for Jiangmen and Zhaoqing not to reach a carbon peak. In 2035, the emission reduction of the five cities will be 56.90 M-61.87 Mt, 44.35 M-48.16 Mt, 23.92 M-25.91 Mt, 33.78 M-36.58 Mt and 20.15 M-21.88 Mt, respectively. The cumulative carbon emission reduction potential of these cities from 2021 to 2035 is significant. which is -23.75M-26.60 Mt, 17.51 M-22.17 Mt, -6.64 M-12.19 Mt, -7.57 M-17.82 Mt and -3.86 M 11.79 Mt, respectively. (4) Being earlier to reach a carbon peak is conducive for cities to reduce carbon emissions. The curve of cumulative carbon emission reduction potential shows that the marginal potential of carbon emission reduction increases with time. So early adoption of emission reduction measures and early realization of carbon peak will promote carbon emission reduction. When making action plans for carbon peak, we should prevent cities from reaching false carbon peak during the platform period, pay attention to the demonstration and acceleration effect of carbon peak cities with relatively high carbon emissions, and explore the carbon emission reduction potential of cities that have difficulties in reaching carbon peak by optimizing their energy structure and utilization efficiency.

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