Sectoral patterns of technical change: Towards a taxonomy and a theory

The purpose of the paper is to describe and explain sectoral patterns of technical change as revealed by data on about 2000 significant innovations in Britain since 1945. Most technological knowledge turns out not to be “information” that is generally applicable and easily reproducible, but specific to firms and applications, cumulative in development and varied amongst sectors in source and direction. Innovating firms principally in electronics and chemicals, are relatively big, and they develop innovations over a wide range of specific product groups within their principal sector, but relatively few outside. Firms principally in mechanical and instrument engineering are relatively small and specialised, and they exist in symbiosis with large firms, in scale intensive sectors like metal manufacture and vehicles, who make a significant contribution to their own process technology. In textile firms, on the other hand. most process innovations come from suppliers.These characteristics and variations can be classified in a three part taxonomy based on firms: (1) supplier dominated; (2) production intensive; (3) science based. They can be explained by sources of technology, requirements of users, and possibilities for appropriation. This explanation has implications for our understanding of the sources and directions of technical change, firms' diversification behaviour, the dynamic relationship between technology and industrial structure, and the formation of technological skills and advantages at the level of the firm. the region and the country.     

Serendipity: Towards a taxonomy and a theory

Serendipity, the notion of researchers making unexpected and beneficial discoveries, has played an important role in debates about the feasibility and desirability of targeting public R&D investments. The purpose of this paper is to show that serendipity can come in different forms and come about in a variety of ways. The archives of Robert K Merton, who introduced the term to the social sciences, were used as a starting point for gathering literature and examples. I identify four types of serendipity (Walpolian, Mertonian, Bushian, Stephanian) together with four mechanisms of serendipity (Theory-led, Observer-led, Error-borne, Network-emergent). I also discuss implications of the different types and mechanisms for theory and policy.     

Resolving the knowledge paradox: Knowledge-spillover entrepreneurship and economic growth

The knowledge paradox suggests that high levels of investment in new knowledge do not necessarily and automatically generate the anticipated levels of competitiveness of growth. In particular, knowledge investments do not automatically translate into balanced growth and competitiveness. The purpose of this paper is to explain why knowledge investments are inherently unbalanced, so that the competitiveness and growth ensuing from knowledge are not equally spread across individuals, firms, and spatial units of observation, such as regions and countries. Based on a data set linking entrepreneurial activity to growth within the context of German regions, this paper shows that entrepreneurship serves a conduit of knowledge spillovers.     

Nanotechnology for the management of COVID-19 during the pandemic and in the post-pandemic era

Following the global COVID-19 pandemic, nanotechnology has been at the forefront of research efforts and enables the fast development of diagnostic tools, vaccines and antiviral treatment for this novel virus (SARS-CoV-2). In this review, we first summarize nanotechnology with regard to the detection of SARS-CoV-2, including nanoparticle-based techniques such as rapid antigen testing, and nanopore-based sequencing and sensing techniques. Then we investigate nanotechnology as it applies to the development of COVID-19 vaccines and anti-SARS-CoV-2 nanomaterials. We also highlight nanotechnology for the post-pandemic era, by providing tools for the battle with SARS-CoV-2 variants and for enhancing the global distribution of vaccines. Nanotechnology not only contributes to the management of the ongoing COVID-19 pandemic but also provides platforms for the prevention, rapid diagnosis, vaccines and antiviral drugs of possible future virus outbreaks.     

Towards sentiment and Temporal Aided Stance Detection of climate change tweets

Climate change has become one of the most significant crises of our time. Public opinion on climate change is influenced by social media platforms such as Twitter, often divided into believers and deniers. In this paper, we propose a framework to classify a tweet’s stance on climate change (denier/believer). Existing approaches to stance detection and classification of climate change tweets either have paid little attention to the characteristics of deniers’ tweets or often lack an appropriate architecture. However, the relevant literature reveals that the sentimental aspects and time perspective of climate change conversations on Twitter have a major impact on public attitudes and environmental orientation. Therefore, in our study, we focus on exploring the role of temporal orientation and sentiment analysis (auxiliary tasks) in detecting the attitude of tweets on climate change (main task). Our proposed framework STASY integrates word- and sentence-based feature encoders with the intra-task and shared-private attention frameworks to better encode the interactions between task-specific and shared features. We conducted our experiments on our novel curated climate change CLiCS dataset (2465 denier and 7235 believer tweets), two publicly available climate change datasets (ClimateICWSM-2022 and ClimateStance-2022), and two benchmark stance detection datasets (SemEval-2016 and COVID-19-Stance). Experiments show that our proposed approach improves stance detection performance (with an average improvement of 12.14% on our climate change dataset, 15.18% on ClimateICWSM-2022, 12.94% on ClimateStance-2022, 19.38% on SemEval-2016, and 35.01% on COVID-19-Stance in terms of average F1 scores) by benefiting from the auxiliary tasks compared to the baseline methods.     

Towards the prediction of climate

The prediction of long-term climatic changes is not only intrinsically interesting and challenging, but directly relevant to social and economic planning, not least in the context of fuel policy. For the moment, prediction relies heavily on the construction of a long-term data bank for past climatic patterns: for the European region it has been possible to build this up for every season of every year since about 1500.     

Towards climate resilient urban energy systems: a review

Climate change and increased urban population are two major concerns for society. Moving towards more sustainable energy solutions in the urban context by integrating renewable energy technologies supports decarbonizing the energy sector and climate change mitigation. A successful transition also needs adequate consideration of climate change including extreme events to ensure the reliable performance of energy systems in the long run. This review provides an overview of and insight into the progress achieved in the energy sector to adapt to climate change, focusing on the climate resilience of urban energy systems. The state-of-the-art methodology to assess impacts of climate change including extreme events and uncertainties on the design and performance of energy systems is described and discussed. Climate resilience is an emerging concept that is increasingly used to represent the durability and stable performance of energy systems against extreme climate events. However, it has not yet been adequately explored and widely used, as its definition has not been clearly articulated and assessment is mostly based on qualitative aspects. This study reveals that a major limitation in the state-of-the-art is the inadequacy of climate change adaptation approaches in designing and preparing urban energy systems to satisfactorily address plausible extreme climate events. Furthermore, the complexity of the climate and energy models and the mismatch between their temporal and spatial resolutions are the major limitations in linking these models. Therefore, few studies have focused on the design and operation of urban energy infrastructure in terms of climate resilience. Considering the occurrence of extreme climate events and increasing demand for implementing climate adaptation strategies, the study highlights the importance of improving energy system models to consider future climate variations including extreme events to identify climate resilient energy transition pathways.     

Towards a taxonomy of research misconduct: The case of business school research

This paper examines the growing pressures and incentives encouraging research misconduct, along with the consequences, as illustrated by the case of business school research. Drawing on a review of the literature on different theoretical approaches to analysing organizational misconduct, we develop a formal taxonomy distinguishing appropriate conduct from blatantly inappropriate misconduct but with a specific focus on the ‘grey’ areas between these extremes in the form of questionable and inappropriate behaviour. We identify various sources of research misbehaviour and different categories of those affected. The aim is to provide a clearer understanding of what research behaviour is deemed appropriate or not, which stakeholders it affects, and the pressures and incentives likely to exacerbate such misconduct. We conclude with a discussion of how the taxonomy can help shape future good research practice (thereby setting a better example to students), and offer some propositions for future research.     

Work from home during the COVID-19 pandemic: An observational study based on a large geo-tagged COVID-19 Twitter dataset (UsaGeoCov19)

As COVID-19 swept over the world, people discussed facts, expressed opinions, and shared sentiments about the pandemic on social media. Since policies such as travel restriction and lockdown in reaction to COVID-19 were made at different levels of the society (e.g., schools and employers) and the government, we build a large geo-tagged Twitter dataset titled UsaGeoCov19 and perform an exploratory analysis by geographic location. Specifically, we collect 650,563 unique geo-tagged tweets across the United States covering the date range from January 25 to May 10, 2020. Tweet locations enable us to conduct region-specific studies such as tweeting volumes and sentiment, sometimes in response to local regulations and reported COVID-19 cases. During this period, many people started working from home. The gap between workdays and weekends in hourly tweet volumes inspire us to propose algorithms to estimate work engagement during the COVID-19 crisis. This paper also summarizes themes and topics of tweets in our dataset using both social media exclusive tools (i.e., #hashtags, @mentions) and the latent Dirichlet allocation model. We welcome requests for data sharing and conversations for more insights.UsaGeoCov19 link: http://yunhefeng.me/geo-tagged_twitter_datasets/.     

Information avoidance in the age of COVID-19: A meta-analysis

Guided by three major theoretical frameworks, this meta-analysis synthesizes 17 empirical studies (15 articles with 18,297 participants, 13 of them are from non-representative samples) and quantifies the effect sizes of a list of antecedents (e.g., cognitive, affective, and social factors) on information avoidance during the COVID-19 context. Findings indicated that information-related factors including channel belief (r = -0.35, p < .01) and information overload (r = 0.23, p < .01) are more important in determining individual's avoidance behaviors toward COVID-19 information. Factors from the psychosocial aspects, however, had low correlations with information avoidance. While informational subjective norms released a negative correlation (r = -0.16, p < .1) which was approaching significant, positive and negative risk responses were not associated with information avoidance. Moderator analysis further revealed that the impacts of several antecedents varied for people with different demographic characteristics (i.e., age, gender, region of origin), and under certain sampling methods. Theoretically, this meta-analysis may help determine the most dominant factors from a larger landscape, thus providing valuable directions to refine frameworks and approaches in health information behaviors. Findings from moderator analysis have also practically inspired certain audience segmentation strategies to tackle occurrence of information avoidance during the COVID-19 pandemic.     

Truth and opinion in climate change discourse: the Gore-Hansen disagreement

In this paper, I discuss the "inconvenient truth" strategy of Al Gore. I argue that Gore's notion of truth upholds a conception of science and policy that narrows our understanding of climate change discourse. In one notable exchange, Gore and NASA scientist, James Hansen, disagreed about whether scientific statements based on Hansen's computer simulations were truth or opinion. This exchange is featured in An Inconvenient Truth, yet the disagreement is edited from the film and presented simply as an instance of Hansen speaking "inconvenient truth". In this article, I compare the filmic representation of Hansen's testimony with the congressional record. I place their exchange in a broader historical perspective on climate change disputation in order to discuss the implications of Gore's perspective on truth.     

Recapitulating the Lung Pathophysiology of COVID-19 in a Human Organ Chip

正Coronavirus disease 2019 (COVID-19) pandemic,caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2),have posed a big threat to human life.The human lung takes the primary hit,characterized by the process ranging from mild syndrome to severe lung injury,     

Corporate commitment to climate change: The effect of eco-innovation and climate governance

Climate change represents a significant problem to the planet which raises concerns from stakeholder groups about corporate commitment to climate change issues. In this paper, we explore the effect of eco-innovation and climate governance on corporate commitment to climate change. We develop a unique measure for climate change commitment by considering four components, viz. whether a company supports the Sustainable Development Goal 13 on climate action, whether a company is aware that climate change can represent commercial risks or opportunities, whether a company reports Scope 3 CO₂ emissions and whether a company sets a target for emission reduction. We measure eco-innovation by using a score collected from the Eikon database that reflects a company's capacity to reduce environmental costs, eco-innovation intensity measured as environmental expenditures over revenues. We also create an index computed as a composite score by totalling five eco-innovation proxies collected from the Eikon database that reflect companies' efforts to reduce environmental impact. Concerning climate governance, we focus on three proxies, namely the existence of an environmental committee, climate incentives and the existence of sustainability reports. Based on a sample of companies listed on the London Stock Exchange for the period of 2014–2020, we find that corporate eco-innovation is positively associated with climate change commitment. We argue that firms that adopt innovative approaches to efficiently control pollution and resource use and reduce their environmental impact are more committed to climate change. We also find that climate governance is positively associated with climate change commitment. We claim that companies that integrate climate change issues in governance can help address climate change risks and opportunities. Our empirical evidence provides recommendations for managers and policymakers to promote the adoption of eco-innovative technologies and integrate climate change issues in governance, which can contribute to corporate commitment to climate change.     

新时代城市空间结构变革与转型

城市空间结构是城市可持续发展治理及规划的重要抓手。如何科学认识新时期城市空间结构是深化城市认知并进行人与自然和谐调控的基础。文章简要回顾传统城市空间结构理论的时代背景,通过对新时期技术革命、政策和社会经济环境的分析,指出城市空间结构在组织原则、组织方式、优化目标及要素成分方面的变革性转向,阐明传统理论用于解释新时代城市治理的局限性。提出从人地地域系统理论出发重构城市空间结构研究范式、重新认识城市空间结构载体空间、强化城市空间结构关系解析,以及革新城市空间结构测度体系等新时代认识路径。未来应对城市空间结构认知方面挑战的关键举措,即重构城市空间结构理论、集成城市空间结构解析关键技术、融合应用多源数据、建设城市空间结构优化调控的数字孪生平台。     

COVID-19 and Gut Microbiota: A Potential Connection

Currently, world is facing a global outbreak causing a pandemic threat known as COVID-19. This infectious disease is triggered by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Gut microbiota harbours multi species community with a strong impact on host immune homeostasis. However, our knowledge about this gut microbiota and its symbiotic relationship with immune activation in association with SARS-CoV-2 is limited. Unbalanced bacterial flora with too many opportunistic infections can shift immune system towards a cascade of inflammatory responses leading to multi organ damage. This review will highlight immune-regulation via various mechanisms in SARS-CoV-2 infection. Diet has an unbelievable influence on gut microbiome that allows a new state of homeostasis to be reached through timing, frequency and duration of intake. This review article focuses on gut, lung microbiota and immunomodulation with specific attention on immune activation by gut microbiota.     

Long pentraxin 3 as a marker of COVID-19 severity: evidences and perspectives

IntroductionSeveral laboratory tests are characteristically altered in Coronavirus Disease 2019 (COVID-19), but are not totally accurate in predicting the disease outcome. The long pentraxin 3 (PTX3) is quickly released directly at inflammation sites by many immune cell types. Previous studies have shown that PTX3 correlated with disease severity in various inflammatory conditions. Our study investigated the use of PTX3 as a potential marker of COVID-19 severity and compared its performance in detecting a more severe form of the disease with that of routine laboratory parameters.Materials and methodsStored serum samples of RT-PCR confirmed COVID-19 cases that had been obtained at hospital admission were retrospectively analysed. Intensive care unit (ICU) stay was considered a surrogate endpoint of severe COVID-19. Pentraxin 3 was measured by a commercial enzyme-linked immunosorbent assay.ResultsA total of 96 patients were recruited from May 1st, 2020 to June 30th, 2020; 75/96 were transferred to ICU. Pentraxin 3 was higher in ICU vs non-ICU patients (35.86 vs 10.61 ng/mL, P < 0.001). Univariate and multivariate logistic regression models demonstrated that the only significant laboratory predictor of ICU stay was PTX3 (OR: 1.68 (1.19-2.29), P = 0.003), after controlling for comorbidities. The Receiver Operator Characteristic curve analysis showed that PTX3 had a higher accuracy compared to C-reactive protein (CRP), lactate dehydrogenase (LD), ferritin in identifying ICU patients (AUC of PTX3 = 0.98; CRP = 0.66; LD = 0.70; ferritin = 0.67, P < 0.001). A cut-off of PTX3 > 18 ng/mL yielded a sensitivity of 96% and a specificity of 100% in identifying patients requiring ICU.ConclusionHigh values of PTX3 predict a more severe COVID-19.     

Navigating the impact-innovation double hurdle: The case of a climate change research fund

This paper analyses how the funding for research grants was allocated from a specific research fund which aimed to support innovative research projects with the potential to have research impact by reducing carbon emissions. The fund received a total of 106 proposals, of which 27 were successful at obtaining financial support. Our aims were to test which factors influenced the funding decision and to discover whether or not and to what extent the fund met its intended objectives through the allocation of monies. The allocation process and its outcomes were analysed using correlation, logistical and linear regression to test our research hypotheses. Using this research funding process as a single study, we found that trying to clear the impact-innovation double hurdle in a single funding initiative ultimately compromises both goals. This paper therefore contributes to our understanding of innovation management within the context of carbon emission reduction and explains which factors influenced success in securing research monies through the funding process.     

Laboratory medicine in pandemic of COVID-19

After the outbreak in China in the year 2019, severe acute respiratory syndrome Coronavirus 2 (SARS-CoV-2) quickly spread around the world causing a protracted pandemic. Approximately one-third of infections appear to be asymptomatic. Symptomatic disease is characterized primarily by symptoms of respiratory tract infection of varying severity. But Coronavirus Disease 2019 (COVID-19) is much more than an acute respiratory disease because SARS-CoV-2 affects many organs inducing a vast number of symptoms such as cardiovascular, neurological, gastrointestinal, dermatological, with numerous complications. Short and long-term effects of infection, severe ones, and especially mild forms of the disease which affect a huge number of patients need to be further investigated. Laboratory medicine has a crucial role in early diagnosis of the disease, recognition of the patients who need hospital care, and close monitoring of hospitalized patients to timely identify associated clinical complications as well as follow-up of patients with long-term COVID-19.     

Agile and adaptive governance in crisis response: Lessons from the COVID-19 pandemic

Countries around the world have had to respond to the COVID-19 outbreak with limited information and confronting many uncertainties. Their ability to be agile and adaptive has been stressed, particularly in regard to the timing of policy measures, the level of decision centralization, the autonomy of decisions and the balance between change and stability. In this contribution we use our observations of responses to COVID-19 to reflect on agility and adaptive governance and provide tools to evaluate it after the dust has settled. Whereas agility relates mainly to the speed of response within given structures, adaptivity implies system-level changes throughout government. Existing institutional structures and tools can enable adaptivity and agility, which can be complimentary approaches. However, agility sometimes conflicts with adaptability. Our analysis points to the paradoxical nature of adaptive governance. Indeed, successful adaptive governance calls for both decision speed and sound analysis, for both centralized and decentralized decision-making, for both innovation and bureaucracy, and both science and politics.