Value Concern of Ecological Rationality and Exploration of the Chinese Path to Modernization

The COVID-19 pandemic has raged around the world over the recent years, raising the global community's awareness of the interconnection of human civilizations and urging the reconsideration of the human-nature relationship. The escalating worldwide ecological crises are putting human survival and development at risk. The phenomenon has aroused the awareness of "ecological rationality,” consciousness of "economic value” and appeal for "ecological justice” in the universal sense. The endeavor of promoting ecological civilization has been included as part of the five-sphere integrated plan for building socialism with Chinese characteristics since the 18th National Congress of the Communist Party of China (CPC). General Secretary Xi Jinping's thought on ecological civilization has fully manifested the value and goal of comprehensively promoting ecological civilization and adhering to the Chinese path to modernization. The Chinese path to modernization, which has reflected on and outclassed the Western-style logic for modernization, shows a unique horizon and independent wisdom. Focusing on addressing the uncertainties facing human survival in the New Era and aiming at embracing the future, the Chinese path to modernization has shifted the mindset from economic rationality to ecological rationality, abandoned anthropocentrism, and firmly upheld and fulfilled the code of conduct for rational "economic man.” The endeavor of building an eco-friendly society and an ecological community has showcased the favorable institutional practice in Chinese modernization and China's wisdom, demonstrated rational planning, prudential design and effective implementation for the prospect of mankind and highlighted a progressive trend in human civilization. © 2022 Brill Academic Publishers. All rights reserved.

Psychological intervention for three COVID patients who suffered online violence.

Three patients diagnosed with COVID-19 were all young women in their thirties who have suffered from Internet violence in their personal life after hospitalization. They showed significant emotional distress such as, depression state, acute stress disorder, and dissociative disorder. The current study adopts short-term, individualized and comprehensive psychological interventions, including psychological support, encouragement, listening, safety confirmation, catharsis, psychological suggestion, and stimulation of internal potential to treat patients. The third case was provided with psychological interventions combined with antipsychotic treatment. After timely psychological interventions all three patients achieved sound results.Copyright © 2021 Chinese Medical Journals Publishing House Co.Ltd.

Residual Feature Attentional Fusion Network for Lightweight Chest CT Image Super-Resolution

The diagnosis of COVID-19 requires chest computed tomography (CT). High-resolution CT images can provide more diagnostic information to help doctors better diagnose the disease, so it is of clinical importance to study super-resolution (SR) algorithms applied to CT images to improve the reso-lution of CT images. However, most of the existing SR algorithms are studied based on natural images, which are not suitable for medical images;and most of these algorithms improve the reconstruction quality by increasing the network depth, which is not suitable for machines with limited resources. To alleviate these issues, we propose a residual feature attentional fusion network for lightweight chest CT image super-resolution (RFAFN). Specifically, we design a contextual feature extraction block (CFEB) that can extract CT image features more efficiently and accurately than ordinary residual blocks. In addition, we propose a feature-weighted cascading strategy (FWCS) based on attentional feature fusion blocks (AFFB) to utilize the high-frequency detail information extracted by CFEB as much as possible via selectively fusing adjacent level feature information. Finally, we suggest a global hierarchical feature fusion strategy (GHFFS), which can utilize the hierarchical features more effectively than dense concatenation by progressively aggregating the feature information at various levels. Numerous experiments show that our method performs better than most of the state-of-the-art (SOTA) methods on the COVID-19 chest CT dataset. In detail, the peak signal-to-noise ratio (PSNR) is 0.11 dB and 0.47 dB higher on CTtest1 and CTtest2 at x3 SR compared to the suboptimal method, but the number of parameters and multi-adds are reduced by 22K and 0.43G, respectively. Our method can better recover chest CT image quality with fewer computational resources and effectively assist in COVID-19.

COVID-19 Image Segmentation Algorithms Based on Conditional Generative Adversarial Network

The size and location of the lesions in CT images of novel corona virus pneumonia (COVID-19) change all the time, and the lesion areas have low contrast and blurred boundaries, resulting in difficult segmentation. To solve this problem, a COVID-19 image segmentation algorithm based on conditional generative adversarial network (CGAN) is proposed. Uses the improved DeeplabV3+ network as a generator, which enhances the extraction of multi-scale contextual features, reduces the number of network parameters and improves the training speed. A Markov discriminator with 6 fully convolutional layers is proposed instead of a common discriminator, with the aim of focusing more on the local features of the CT image. By continuously adversarial training between the generator and the discriminator, the network weights are optimised so that the final segmented image generated by the generator is infinitely close to the ground truth. On the COVID-19 CT public dataset, the area under the curve of ROC, F1-Score and dice similarity coefficient achieved 96.64%, 84.15% and 86.14% respectively. The experimental results show that the proposed algorithm is accurate and robust, and it has the possibility of becoming a safe, inexpensive, and time-saving medical assistant tool in clinical diagnosis, which provides a reference for computer-aided diagnosis. © 2022 ACM.

Insights into entrepreneurship: impact of entrepreneur psychological capital and employee well-being on business sustainable performance during and post-Covid-19 era

Since Covid-19 is an enduring disease that pushed the world to reshape business strategies to overcome the unprecedented situations in all sectors such as the sports industry. Although substantial research has been carried out to inspect this phenomenon globally. Nevertheless, how entrepreneurial initiatives can contribute to tackling the situation is still lacking. This study attempts to uncover the relationships between entrepreneur psychological capital (EPC) and business sustainable performance (BSF). Second, this study strives to reveal the relationships between employee wellbeing (EWb) and BSP. In addition, education is treated as a moderating factor to unfold the relationships among factors, i.e., EPC, EWb, and BSF. Data were collected from eight hundred (n = 800) participants who were associated with the Chinese sports industry from March to July 2022. The results demonstrated interesting and fruitful findings based on SEM statistical model. First, a positive connection was found between EPC and BSF. Second, it found a positive link between EWb and BSF. Finally, the study highlighted a significant moderating impact of education among implicit relationships, i.e., EPC, EWb, and BSF. This study provides insights into entrepreneurship, entrepreneur psychological capital, and employee wellbeing on how it can optimize the performance of a business during and post-Covid-19 era. Besides, certain shortcomings along with future potential lines are reported for future researchers. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

A Hybrid Brain Storm Optimization Algorithm to Solve the Emergency Relief Routing Model

Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in the coronavirus disease outbreak that began in 2019. This study develops a model for the emergency relief routing problem (ERRP) to distribute post-disaster relief more reasonably. Unlike general route optimizations, patients' suffering is taken into account in the model, allowing patients in more urgent situations to receive relief operations first. A new metaheuristic algorithm, the hybrid brain storm optimization (HBSO) algorithm, is proposed to deal with the model. The hybrid algorithm adds the ideas of the simulated annealing (SA) algorithm and large neighborhood search (LNS) algorithm into the BSO algorithm, improving its ability to escape from the local optimum trap and speeding up the convergence. In simulation experiments, the BSO algorithm, BSO+LNS algorithm (combining the BSO with the LNS), and HBSO algorithm (combining the BSO with the LNS and SA) are compared. The results of simulation experiments show the following: (1) The HBSO algorithm outperforms its rivals, obtaining a smaller total cost and providing a more stable ability to discover the best solution for the ERRP;(2) the ERRP model can greatly reduce the level of patient suffering and can prioritize patients in more urgent situations.

Platform Behavior under Market Shocks: A Simulation Framework and Reinforcement-Learning Based Study

We study the behavior of an economic platform (e.g., Amazon, Uber Eats, Instacart) under shocks, such as COVID-19 lockdowns, and the effect of different regulation considerations. To this end, we develop a multi-agent simulation environment of a platform economy in a multi-period setting where shocks may occur and disrupt the economy. Buyers and sellers are heterogeneous and modeled as economically-motivated agents, choosing whether or not to pay fees to access the platform. We use deep reinforcement learning to model the fee-setting and matching behavior of the platform, and consider two major types of regulation frameworks: (1) taxation policies and (2) platform fee restrictions. We offer a number of simulated experiments that cover different market settings and shed light on regulatory tradeoffs. Our results show that while many interventions are ineffective with a sophisticated platform actor, we identify a particular kind of regulation - fixing fees to the optimal, no-shock fees while still allowing a platform to choose how to match buyers and sellers - as holding promise for promoting the efficiency and resilience of the economic system. © 2023 ACM.

Path Planning of Follow-up Transport Robot Based on Machine Vision

With the upgrading and innovation of the logistics industry, the requirements for the level of transportation smart technologies continue to increase. The outbreak of the COVID-19 has further promoted the development of unmanned transportation machines. Aimed at the requirements of intelligent following and automatic obstacle avoidance of mobile robots in dynamic and complex environments, this paper uses machine vision to realize the visual perception function, and studies the real-time path planning of robots in complicated environment. And this paper proposes the Dijkstra-ant colony optimization (ACO) fusion algorithm, the environment model is established by the link viewable method, the Dijkstra algorithm plans the initial path. The introduction of immune operators improves the ant colony algorithm to optimize the initial path. Finally, the simulation experiment proves that the fusion algorithm has good reliability in a dynamic environment. © 2022 IEEE.

A Multivent System for Non-invasive Ventilation: Solving the Problem of Ventilator Shortage during the COVID-19 Pandemic

The COVID-19 pandemic has caused a severe global problem of ventilator shortage. Placing multiple patients on a single ventilator (ventilator sharing) or dual patient ventilation has been proposed and conducted to increase the cure efficiency for ventilated patients. However, the ventilator-sharing method needs to use the same ventilator settings for all the patients, which cannot meet the ventilation needs of different patients. Therefore, a novel multivent system for non-invasive ventilation has been proposed in this study. The close loop system consists of the proportional valve and the flow-pressure sensor can regulate the airway pressure and flow for each patient. Multiple ventilation circuits can be combined in parallel to meet patients’ventilation demands simultaneously. Meanwhile, the mathematical model of the multivent system is established and validated through experiments. The experiments for different inspired positive airway pressure (IPAP), expired positive airway pressure (EPAP), inspiratory expiratory ratio (I:E), and breath per minute (BPM) have been conducted and analyzed to test the performance of the multivent system. The results show that the multivent system can realize the biphasic positive airway pressure (BIPAP) ventilation mode in non-invasive ventilation without interfering among the three ventilation circuits, no matter the change of IPAP, EPAP, I:E, and BPM. However, pressure fluctuation exists during the ventilation process because of the exhaust valve effect, especially in EPAP control. The control accuracy and stability need to be improved. Nevertheless, the novel designed multivent system can theoretically solve the problem of ventilator shortage during the COVID-19 pandemic and may bring innovation to the current mechanical ventilation system. Author

Urban Mobility in the Postpandemic Stage: A Comprehensive Investigation of a Variety of Cities in China

The global outbreak of coronavirus disease 2019 (COVID-19) has affected the urban mobility of nations around the world. The pandemic may even have a potentially lasting impact on travel behaviors during the post-pandemic stage. China has basically stopped the spread of COVID-19 and reopened the economy, providing an unprecedented environment for investigating post-pandemic travel behaviors. This study conducts multiple investigations to show the changes in travel behaviors in the post-pandemic stage, on the basis of empirical travel data in a variety of cities in China. Specifically, this study demonstrates the changes in road network travel speed in 57 case cities and the changes in subway ridership in 26 case cities. Comprehensive comparisons can indicate the potential modal share in the post-pandemic stage. Further, this study conducts a case analysis of Beijing, where the city has experienced two waves of COVID-19. The variations in travel speed in the road network of Beijing at different stages of the pandemic help reveal the public's responses towards the varying severity of the pandemic. Finally, a case study of the Yuhang district in Hangzhou is conducted to demonstrate the changes in traffic volume and vehicle travel distance amid the post-pandemic stage based on license plate recognition data. Results indicate a decline in subway trips in the post-pandemic stage among case cities. The vehicular traffic in cities with subways has recovered in peak hours on weekdays and has been even more congested than the pre-pandemic levels;whereas the vehicular traffic in cities without subways has not rebounded to pre-pandemic levels. This situation implies a potential modal shift from public transportation to private vehicular travel modes. Results also indicate that commuting traffic is sensitive to the severity of the pandemic. This may be because countermeasures, e.g., work-from-home and suspension of non-essential businesses, will be implemented if the pandemic restarts. The travel speed in non-peak hours and on non-workdays is higher than pre-pandemic levels, indicating that non-essential travel demand may be reduced and the public's vigilance towards the pandemic may continue to the post-pandemic stage. These findings can help improve policymaking strategies in the post-pandemic new normal. © 2023 American Society of Civil Engineers.

Rapid, sensitive detection of intact SARS-CoV-2 using DNA nets and a smartphone-linked fluorimeter

We report a single-step, room-temperature, 5-10 minute SARS-CoV-2 saliva self-monitoring method that overcomes the limitations of existing approaches through the use of fluorophore-releasing Designer DNA Nanostructures (DDNs) that bind with the multivalent pattern of spike proteins on the exterior intact virions and an inexpensive smartphone-linked, pocket-size fluorimeter, called a "V-Pod” for its resemblance to an Apple AirPod™ headphone case. We characterize the V-Pod fluorimeter performance and the DDN-based assay to demonstrate a clinically relevant detection limit of 104 virus particles/mL for pseudo-typed WT SARS-CoV-2 and 105 virus particles/mL for real pathogenic variants, including Delta, Omicron, and D614g. © 2023 SPIE.

Cellular and Molecular Atlas of Peripheral Blood Mononuclear Cells from a Pregnant Woman after Recovery from COVID-19

Objective This study aimed to investigate the immune response of a pregnant woman who recovered from the coronavirus disease 2019 (COVID_RS) by using single-cell transcriptomic profiling of peripheral blood mononuclear cells (PBMCs) and to analyze the properties of different immune cell subsets. Methods PBMCs were collected from the COVID_RS patient at 28 weeks of gestation, before a cesarean section. The PBMCs were then analyzed using single-cell RNA sequencing. The transcriptional profiles of myeloid, T, and natural killer (NK) cell subsets were systematically analyzed and compared with those of healthy pregnant controls from a published single-cell RNA sequencing data set. Results We identified major cell types such as T cells, B cells, NK cells, and myeloid cells in the PBMCs of our COVID_RS patient. The increase of myeloid and B cells and decrease of T cells and NK cells in the PBMCs in this patient were quite distinct compared with that in the control subjects. After reclustering and Augur analysis, we found that CD16 monocytes and mucosal-Associated invariant T (MAIT) cells were mostly affected within different myeloid, T, and NK cell subtypes in our COVID_RS patient. The proportion of CD16 monocytes in the total myeloid population was increased, and the frequency of MAIT cells in the total T and NK cells was significantly decreased in the COVID-RS patient. We also observed significant enrichment of gene sets related to antigen processing and presentation, T-cell activation, T-cell differentiation, and tumor necrosis factor superfamily cytokine production in CD16 monocytes, and enrichment of gene sets related to antigen processing and presentation, response to type II interferon, and response to virus in MAIT cells. Conclusion Our study provides a single-cell resolution atlas of the immune gene expression patterns in PBMCs from a COVID_RS patient. Our findings suggest that CD16-positive monocytes and MAIT cells likely play crucial roles in the maternal immune response against severe acute respiratory syndrome coronavirus 2 infection. These results contribute to a better understanding of the maternal immune response to severe acute respiratory syndrome coronavirus 2 infection and may have implications for the development of effective treatments and preventive strategies for the coronavirus disease 2019 in pregnant women.Copyright © Wolters Kluwer Health, Inc. All rights reserved.

Exploration of college students' psychological problems based on online education under COVID-19

As a result of the COVID-19 pandemic, many college students have been isolated at home and unable to walk into class as usual. This series of protective measures to avoid the spread of the disease may have an additional psychological impact on the lives of college students. The purpose of this study was to propose a strategy for using an intelligent online learning system based on content recommendations and electronic questionnaires in the educational domain. We invited 3000 isolated university students (47.6% male and 52.4% female) to an online trial. It proved to be effective in helping us intervene in students' psychological problems quickly, objectively, efficiently, and in real-time. In addition, our analysis of the data collected from the intelligent online learning system showed that the degree to which college students' psychological problems were affected by isolation was closely related to students' grade level, family background, major category, and computer proficiency. The current study suggests that the mental health of college students should be well monitored during segregation. Targeted psychological counseling is more necessary for students in upper grades, low-income families, liberal arts majors, and those with weak computer proficiency to reduce the emotional impact of segregation on students.

A literature review on the impact of the COVID-19 pandemic on consumer behaviour: implications for consumer-centric logistics

PurposeThe COVID-19 pandemic has resulted in significant changes in consumer behaviour, which has had a cascading effect on consumer-centric logistics. As a result, this study conducts a focused literature review of pandemic-related consumer behaviour research to address two research questions: 1) what are the pandemic's direct effects on consumer consumption behaviour, with an emphasis on changes in their basic and psychological needs? and 2) what are the consequences of behavioural changes on consumer-centric logistics?Design/methodology/approachThe scientific procedure and rationales for systematic literature review (SPAR-4-SLR) protocol and the theory, context, characteristics and methodology (TCCM) framework were adopted as a guideline to map, refine, evaluate and synthesise the literature. A total of 53 research articles were identified for further analysis.FindingsUsing Maslow's hierarchy of human needs as a theoretical guide, this review synthesises the COVID-19 pandemic's effects on consumer behaviour into four categories: abnormal buying behaviour, changes in consumer preferences, digitalisation of shopping behaviour and technology-related behaviour. Furthermore, four consumer-centric logistics propositions are proposed based on the four aspects of consumer behavioural changes.Originality/valueThis study outlines the significant behavioural changes in consumers in the face of the COVID-19 pandemic and how these changes impact consumer-centric logistics, with implications for managing consumers' involvement in logistics and pointing out future research directions.

Exploration of industrial risk contagion characteristics and mechanism under geopolitical events: evidence from China

Based on the TVP-VAR-DY and TVP-VAR-BK models, this article examines the characteristics and mechanisms of systemic risk contagion in the Chinese industries under geopolitical events by selecting data spans from 1 January 2010 to 31 August 2022. First, dynamic analysis of full-sample risk contagion shows that there is a significant climb in total risk during geopolitical events. Then the static analysis of risk contagion in the full sample specifically shows the correlation between risk contagion and industry chain between the financial and real sectors. Besides, the sub-sample analysis illustrates that during geopolitical events such as the Sino-US Trade War, the COVID-19 Pandemic and the Russia-Ukraine Conflict, Chinese industrial stock indexes show short-term risk spillovers from key industries related to geopolitical events, and gradually spread along the industrial chain in the long run compared to the Chinese ‘Stock Market Crash'. Through further mechanistic tests, we find that the irrational behaviour of investors in the market exacerbates short-term risk contagion, while the financial distress of real firms due to financing constraints exacerbates long-term risk contagion. In addition, geopolitical risk, economic uncertainty, and policy uncertainty as macro variables also have an impact on the short-run and long-run risk contagion. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Cultivating public health youth talents with illustrious virtue and lofty aspirations to undertake glorious tasks of a new era: Minute Cultivating public health youth talents with illustrious virtue and lofty aspirations to undertake glorious tasks of a new era: Minutes of the Sixteenth National Postgraduates Symposium on Environmental and Occupational Medicine s of the Sixteenth National Postgraduates Symposium on Environmental and Occupational Medicine

From October 22 to 23, 2021, the 16th National Postgraduates Symposium on Environmental and Occupational Medicine was successfully held in Central South University, sponsored by the Editorial Board of Journal of Environmental and Occupational Medicine and Xiangya School of Public Health of Central South University, and co-organized by School of Public Health of South China University and Shanghai Preventive Medicine Association. Keeping in view the outbreak of COVID-19, the symposium was held in the form of "offline+online". More than 100 teachers and students from more than 30 universities and research institutions across China attended the conference. A total of 114 excellent papers were submitted to this conference. Focusing on the theme of "Research and practice: Healing the schism", young scholars' forum as well as postgraduates' academic exchanges at the main venue and four parallel sessions were launched. This conference not only provided an excellent platform for postgraduate students in the field of environmental and occupational medicine nationwide to share academic trends and exchange academic research, but also expanded the influence of the Journal of Environmental and Occupational Medicine.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

SCI-indexed papers and research hotspots of provincial centers for disease control and preven tion in China from 2011 to 2020

[Background] The COVID-19 pandemic hints at the importance of modernizing disease control system. To understand the scientific research strength of our country's disease control system in recent years is conducive to formulating more targeted policies or measures to promote the modernization of the disease control system. [Objective] To understand the scientific research strength and research hotspots of China's provincial-level centers for disease control and prevention (CDCs) from 2011 to 2020, and provide evidence for the development of scientific research work, discipline construction, and talent team construction in CDCs in the future. [Methods] The Science Citation Index Expanded (SCIE) and Social Science Citation Index (SSCI) of the Web of Science Core Collection were used to retrieve SCI-indexed English papers published by 31 provincial CDCs (excluding Taiwan Province, Hong Kong and Macau Special Administrative Regions) in our country from 2011 to 2020, and to screen literature with provincial CDCs as the first affiliation for bibliometric analysis and visual analysis. Bibliometric analysis included the SCI-indexed publications of different provincial CDCs (as co-affiliation and the first affiliation), the number of SCI-indexed papers published by provincial CDCs (as the first affiliation) and funding rates by years, the high-frequency authors of SCI-indexed papers published by provincial CDCs (as the first affiliation) and their distribution, and the characteristics of the journals. Visual analysis software Citespace 5.8.R1 was used to draw keyword co-occurrence maps, cluster information tables, and emergence maps to provide information on research hotspots and their evolution. [Results] From 2011 to 2020, the number of SCI-indexed papers from 31 provincial CDCs was 8 420 (including co-affiliation), of which 2 060 papers listed provincial CDCs as the first affiliation. The provincial CDCs of Zhejiang, Jiangsu, Shanghai, Beijing, Shandong, and Guangdong were the leading six institutes in terms of the total number of SCI-indexed papers contributed as co-affiliation or the first affiliation. There was a large gap in the total number of SCI-indexed papers among the provincial CDCs. The highest total number of SCI-indexed papers contributed by provincial CDCs as the first affiliation was Zhejiang CDC (448 papers), while the lowest number was Xinjiang CDC (only 1 paper). From 2011 to 2020, the total number of SCI-indexed papers contributed by the 31 provincial CDCs as the first affiliation showed an overall increasing trend. Except for 2011, which was 63.1%, the funding rates in other years exceeded 70%. In terms of high-frequency authors, 13 first authors published >=10 SCI-indexed papers: Zhang Yingxiu from Shandong CDC had the highest number of SCI-indexed papers (47), followed by Hu Yu from Zhejiang CDC. Zhejiang, Jiangsu, Beijing, Guangdong, Shanghai, and Shandong still ranked the top six of >=4 first authored-SCI papers. In terms of journal characteristics, the top 20 journals with the highest number of SCI papers published a total of 862 papers, accounting for 41.8% (862/2 060), and PLOS ONE ranked the first (188 papers). The research hotspots were mainly concentrated in the fields of infection, child health, and epidemiology. The main keywords of the first three cluster categories were related to the research fields of adolescent overweight and obesity, HIV, and vaccine immunity. The results of keyword emergence showed that research hotspots shifted from overweight, obesity, and body mass index to antibodies, vaccines/vaccination, and cohorts. [Conclusion] The past ten years have witnessed increasing numbers of SCI-indexed papers published by provincial CDCs in our country and a stubbornly high funding rate. However, the gap among the provincial CDCs is still large seeing that economically developed eastern provincial CDCs published more SCI-indexed papers. Research hotspots have gradually shifted from overweight, obesity, and body mass index to antibodies, vaccines/vaccination, and cohorts.Copyright © 022 Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Trans/feminist collaborative autoethnographic storying of gender-based violence, during the COVID-19 pandemic

In this paper, we reported on the lattice distortion, surface morphologies, vacancy defects and electrochemical performance that had been observed in Na3V2(PO4)2F3 prepared at different annealing temperatures. X-ray diffraction indicated that all the samples were single phase materials with tetragonal structure and exhibited lattice distortion with the increase of annealing temperatures. A possible mechanism causing the strain-induced lattice distortion had been discussed. Moreover, scanning electron microscopy and positron annihilation techniques were used to study the grain size and vacancy defects as a function of annealing temperatures. The superior electrochemical performance of Na3V2(PO4)2F3 electrode was obtained at the annealing temperature of 350 degrees C with 167.73 F center dot g-1 specific capacitance and 85% capacitance retention. The better electrochemical performance was due to the synergistic effects of grain size and vacancy defect regulated by the annealing temperatures. These results could provide experimental basis for enhancing electrochemical performance of Na3V2(PO4)2F3 in sodium-ion battery area applications. (c) 2023 Elsevier B.V. All rights reserved.

From Yellow Peril to Model Minority: Asian stereotypes in social media during the COVID-19 pandemic

Heightened racial tensions during the COVID-19 pandemic contributed to the increase and rapid propagation of online hate speech towards Asians. In this work, we study the relationship between the racist narratives and conspiracy theories that emerged related to COVID-19 and historical stereotypes underpinning Asian hate and counter-hate speech on Twitter, in particular the Yellow Peril and model minority tropes. We find that the pandemic catalyzed a broad increase in discourse engaging with racist stereotypes extending beyond COVID-19 specifically. We also find that racist narratives and conspiracy theories which emerged during the pandemic and gained widespread attention were rooted in deeply-embedded Asian stereotypes. In alignment with theories of idea habitat and processing fluency, our work suggests that historical stereotypes provided an environment vulnerable to the racist narratives and conspiracy theories which emerged during the pandemic. Our work offers insight for ongoing and future anti-racist efforts. © 2023 ACM.