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This paper aims to guide the stakeholder engagement process related to plastic pollution research in marine environments. We draw on advice identified during an online workshop (Ocean Plastic Workshop 2022) organized by Early Career Ocean Professionals (ECOPs) from 11 countries, held in April 2022. International experts and workshop participants discussed their experiences in the collaborative development and implementation of ocean plastic pollution projects held worldwide, guided by three main questions: (i) What is the role of scientists in a multi-stakeholder project? (ii) How should scientists communicate with other stakeholders? (iii) Which stakeholders are missing in collaborative projects, and why are they missing? This multidisciplinary, co-learning approach highlights the value of stakeholder engagement for ocean plastic projects with an end goal to identify and implement ocean plastic solutions via innovative technologies, informing policy, community engagement, or a combination of all three approaches. The target outcomes of the workshop described in this paper include the identification of transdisciplinary (academic-stakeholder) engagement frameworks and specific suggestions that can serve as guidelines for the development of future plastic pollution projects. [ABSTRACT FROM AUTHOR]

Compared with other health disciplines, there is a stagnation in technological innovation in the field of clinical neuropsychology. Traditional paper-and-pencil tests have a number of shortcomings, such as low-frequency data collection and limitations in ecological validity. While computerized cognitive assessment may help overcome some of these issues, current computerized paradigms do not address the majority of these limitations. In this paper, we review recent literature on the applications of novel digital health approaches, including ecological momentary assessment, smartphone-based assessment and sensors, wearable devices, passive driving sensors, smart homes, voice biomarkers, and electronic health record mining, in neurological populations. We describe how each digital tool may be applied to neurologic care and overcome limitations of traditional neuropsychological assessment. Ethical considerations, limitations of current research, as well as our proposed future of neuropsychological practice are also discussed. [ABSTRACT FROM AUTHOR]

There is growing awareness that actions by policymakers and international organizations to reduce poverty, and those to mitigate and adapt to climate change, are inextricably linked and interwoven. This paper examines relevant academic and policy literature and evidence on this relationship and explores the potential for a new form of development that simultaneously mitigates climate change, manages its impacts , and improves the wellbeing of people in poverty. First, as a key foundation, it outlines the backdrop in basic moral philosophy, noting that climate action and poverty reduction can be motivated both by a core principle based on the right to development and by the conventional consequentialism that is standard in economics. Second, it reviews assessments of the current and potential future impacts of weakly managed climate change on the wellbeing of those in poverty, paying attention to unequal effects, including by gender. Third, it examines arguments and literature on the economic impacts of climate action and policies and how those affect the wellbeing of people in poverty, highlighting the importance of market failures, technological change, systemic dynamics of transition, and distributional effects of mitigation and adaptation. Finally, the paper surveys the current state of knowledge and understanding of how climate action and poverty reduction can be integrated in policy design, indicating where further research can contribute to a transition that succeeds in both objectives. [ABSTRACT FROM AUTHOR]

This paper incorporates endogenous migration into a second-generation Schumpeterian growth model to study how migration, innovation, and growth interact with one another. The paper finds that migration always enhances the rates of innovation and growth of the receiving economy, but implementing pro-innovation policies in the receiving economy does not lead to more migration when the gap in technical knowledge between countries is fixed over time. However, when the technology gap is allowed to adjust endogenously, the paper finds that implementing pro-innovation policies in the receiving economy shrinks immigration flows and reduces the cross-country gap of technology. [ABSTRACT FROM AUTHOR]

The "Georgia Jumper" turtle excluder device (TED) is a rare example of a well-accepted conservation tool required by regulation. Mediated by the UGA Marine Extension and Georgia Sea Grant, Georgia's shrimping industry was integral to the design, revision, and implementation of excluder devices, since the earliest "jellyball shooter" proposed to NMFS in 1980. This paper highlights fisher involvement in the creation of the popular "Georgia Jumper" TED. Both the Diffusion of Innovation and the Traditional Ecological Knowledge literatures stress the importance of meaningful engagement of user communities in the development of new management approaches, and make specific recommendations for improving uptake of new methods. Consistent with literature expectations, fisher and industry participation in the development, testing, and implementation of TEDs has been key to the general acceptance of TEDs in Georgia. This paper illustrates the importance of fisher participation in conservation efforts such as these. [ABSTRACT FROM AUTHOR]

This paper relates curiosity to economic development through its impact on human capital formation and technological advancement in pre-modern times. More specifically, we propose that exposure to inexplicable phenomena prompts curiosity and thinking in an attempt to comprehend these mysteries, thus raising human capital and technology, and, ultimately, fostering growth. We focus on solar eclipses as one particular trigger of curiosity and empirically establish a robust relationship between their number and several proxies of economic prosperity. We also offer evidence compatible with the human capital and technological increases we postulate, finding a more intricate thinking process and more developed technology among societies more exposed to solar eclipses. Among other factors, we study the development of written language, the playing of strategy games and the accuracy of folkloric explanations for eclipses, as well as the number of tasks undertaken in a society, their relative complexity and broad technological indicators. Lastly, we document rising curiosity both at the social and individual levels: societies incorporate more terms related to curiosity and eclipses in their folklore, and people who observed a total solar eclipse during their childhood were more likely to have entered a scientific occupation. [ABSTRACT FROM AUTHOR]

This paper gives an overview of current thinking by economists about the consequences of ongoing technological progress for labour markets, and discusses policy implications. In economics, the impact of technological progress on labour markets is understood by the following two channels: (i) the nature of interactions between differently skilled workers and new technologies affecting labour demand and (ii) the equilibrium effects of technological progress through consequent changes in labour supply and product markets. The paper explains how the ongoing Digital Revolution is characterized by a complex interplay between worker skills and digital capital in the workplace, and consequent changes in job mobility for workers and in output prices affecting consumer demand for goods and services. In particular, it explains how current worker–technology interactions and the equilibrium effects they entail combine to create economy-wide job polarization with winners and losers from ongoing technological progress. The paper therefore concludes by discussing a set of policy interventions to ensure that the benefits of the Digital Revolution are broadly shared. [ABSTRACT FROM AUTHOR]

This paper examines the importance of output growth and research intensity for productivity growth. Two hypotheses are tested. First, the paper investigates the impact of the two variables on productivity growth when simultaneously considered, assessing whether the basic Kaldorian and Schumpeterian models can be combined. Second, it examines whether research intensity impacts on the magnitude of returns to scale, assessing if countries with higher research intensity benefit from higher returns to scale. The tests reported in the paper provide strong evidence of the importance of demand growth for productivity growth, and on the existence of increasing returns to scale in manufacturing, while also recognizing the relevance of research intensity for productivity growth. Most importantly, the test results suggest that research intensity has a more relevant impact on the magnitude of returns to scale than on productivity growth directly. [ABSTRACT FROM AUTHOR]

Cardiovascular diseases represent a major cause of morbidity and mortality, necessitating research to improve diagnostics, and to discover and test novel preventive and curative therapies, all of which warrant experimental models that recapitulate human disease. The translation of basic science results to clinical practice is a challenging task, in particular for complex conditions such as cardiovascular diseases, which often result from multiple risk factors and comorbidities. This difficulty might lead some individuals to question the value of animal research, citing the translational 'valley of death', which largely reflects the fact that studies in rodents are difficult to translate to humans. This is also influenced by the fact that new, human-derived in vitro models can recapitulate aspects of disease processes. However, it would be a mistake to think that animal models do not represent a vital step in the translational pathway as they do provide important pathophysiological insights into disease mechanisms particularly on an organ and systemic level. While stem cell-derived human models have the potential to become key in testing toxicity and effectiveness of new drugs, we need to be realistic, and carefully validate all new human-like disease models. In this position paper, we highlight recent advances in trying to reduce the number of animals for cardiovascular research ranging from stem cell-derived models to in situ modelling of heart properties, bioinformatic models based on large datasets, and state-of-the-art animal models, which show clinically relevant characteristics observed in patients with a cardiovascular disease. We aim to provide a guide to help researchers in their experimental design to translate bench findings to clinical routine taking the replacement, reduction, and refinement (3R) as a guiding concept. [ABSTRACT FROM AUTHOR]

During the past few decades, developing countries have been pushed by international economic institutions and developed countries to effectively abandon promotion of industrialization and structural transformation as a key developmental agenda. In addition, the 'development' debate of recent decades has tended to focus solely on internal factors as if external economic forces are always benign. Within this context, this paper analyzes the key ideas of Gebrehiwot Baykedagn (GHB) (1886–1919), traces their lineages and considers their feasibility and relevance for current developing economies. In a nutshell, for GHB, the main keys to economic development are the creation, accumulation and use of knowledge and skill, technology, innovation and technical change and the means of economic development are deliberate, dynamic and comprehensive sets of state-directed, synergistic interventions that aim at moving an economy away from 'nature-intensive' economic activities towards knowledge-, skill-, technology- and innovation-based ones. Based on analysis of historical and theoretical evidence, this paper argues that the main ideas of GHB and his colleagues are still valid, feasible and relevant for today's developing economies as long as they are innovatively tailored to the unique context of each country and to the broader international policy context. [ABSTRACT FROM AUTHOR]

An introduction to the journal is presented in which the editor discusses various reports in the issue on the topics including the geography of production and international trade, migration of production to lower-cost countries and self-driving tractors operating through satellite control systems.

This paper uses historical labour market data for Belgium for the period 1846–2011 to illustrate how the employment impacts of the ongoing Digital Revolution after 1980 compare to those of the Second Industrial Revolution before 1980. Our analyses show that the period 1846–1947 was characterized by economy-wide skill-upgrading due to an increase in the demand for skilled relative to unskilled workers because of skill-biased technological change (SBTC). The period 1947–81 is characterized by particularly high labour market turbulence, in part due to a gradual switch from economy-wide skill-upgrading to job polarization. Consequently, the impact of the ongoing Digital Revolution on labour markets after 1980 is not uniquely characterized by exceptionally high labour market turbulence but by the nature of changes in the composition of jobs, namely a process of job polarization. To explain job polarization, the paper discusses the hypothesis of Routine-Biased Technological Change (RBTC) that has recently emerged in the academic literature. [ABSTRACT FROM AUTHOR]

This paper considers the paradoxical co-existence of a productivity slowdown and exciting new technologies. Several potential explanations are reviewed. It is argued that while some are unpersuasive it is too soon to know which carry the most weight. However, the slowdown does not appear to be an artefact of the data. A key, hotly disputed, issue is the future economic impact of today's technological progress. As with previous general purpose technologies, it is likely that there will be powerful effects but only with a lag. This has the implication that while the slowdown is real it is not necessarily permanent. [ABSTRACT FROM AUTHOR]

The article presents the discussion on recognizing excellence and innovation for an outstanding paper published in the European Heart Journal (EHJ) rewarding a Netherlands-based research scientist including men having higher concentrations of angiotensin-converting enzyme 2 (ACE2) in the blood.

Encounters and interactions with cybersecurity are now regular and routine experiences for information technology users across a variety of devices, systems and services. Unfortunately, however, despite long-term recognition of the importance of usability in the technology context, the user experience of cybersecurity and privacy is by no means guaranteed to address this criterion. This paper presents an outline of usability issues and challenges in the cybersecurity context, with examples of how it has (or indeed has not) evolved in some established contexts (looking in particular at web browsing and user authentication), as well as consideration of the extent to which any better attention is apparent within more recent and emerging technology contexts (considering the presentation of related features in scenarios including app stores and smart devices). Based on the evidence, cybersecurity is clearly yet to reach a stage where its mention would naturally imply usability, but at the same time the two concepts do not have to represent a contradiction in terms. The resulting requirement is for the increasing recognition of the issue to translate into a greater level of resulting attention and action. [ABSTRACT FROM AUTHOR]

Deoxyribonucleic acid (DNA)-based data storage is a promising new storage technology which has the advantage of high storage capacity and long storage time compared with traditional storage media. However, the synthesis and sequencing process of DNA can randomly generate many types of errors, which makes it more difficult to cluster DNA sequences to recover DNA information. Currently, the available DNA clustering algorithms are targeted at DNA sequences in the biological domain, which not only cannot adapt to the characteristics of sequences in DNA storage, but also tend to be unacceptably time-consuming for billions of DNA sequences in DNA storage. In this paper, we propose an efficient DNA clustering method termed Clover for DNA storage with linear computational complexity and low memory. Clover avoids the computation of the Levenshtein distance by using a tree structure for interval-specific retrieval. We argue through theoretical proofs that Clover has standard linear computational complexity, low space complexity, etc. Experiments show that our method can cluster 10 million DNA sequences into 50 000 classes in 10 s and meet an accuracy rate of over 99%. Furthermore, we have successfully completed an unprecedented clustering of 10 billion DNA data on a single home computer and the time consumption still satisfies the linear relationship. Clover is freely available at https://github.com/Guanjinqu/Clover. [ABSTRACT FROM AUTHOR]

The inherent nature of the renewable energies is to be intermittent. This leads to negative effects on the security and stability of the energy production system. A sensible solution to eliminate or reduce the negative effects is to integrate the energy storage system with a renewable source–based energy production system. Carnot battery is an emerging technology that allows storing electric energy at low cost with no geographical restrictions. To this end, this paper attempts to provide a comprehensive and accurate assessment of the thermodynamic and cost performances as well as energetic and exergetic analyzes of the considered Carnot battery. In this regard, the Carnot battery is comprised of an organic Rankine cycle (ORC), vapor compression heat pump (VHP) and a pumped thermal energy storage (PTES) (to connect the two ORC and VHP sub-cycles). In addition, in both charge and discharge processes, regenerators are utilized to recover waste heat to improve the performance of the storage system. The main objectives of this article are thermodynamic analysis, calculation of degraded exergy and energetic and exergetic efficiencies and obtaining levelized cost of storage (LCOS). Moreover, LCOS (as the objective function) is optimized using the optimization algorithm. The findings indicated that, at the desired temperature (i.e. 100°C), the values of LCOS and total initial cost are 0.3577 USD per kWh and 56.5 million USD, respectively. It was also found that if the regenerators are not used in both charge and discharge processes, the value of LCOS can be nearly 12% greater. [ABSTRACT FROM AUTHOR]

The unprecedented coronavirus disease 2019 (COVID-19) pandemic is a solemn reminder of the need to accelerate pharmaceutical innovation. The desire for fast access to vaccines triggered discussion of unrestricted access to research findings with the hope of facilitating the drug discovery process to combat COVID-19. Increasingly, abolition of the patent system is being discussed in connection with the fight against the pandemic. This may accelerate discovery of and increase access to medicines. However, society's desire for immediate disclosure of research findings conflicts with the inventor's legitimate interest to protect his or her invention as well as the need to recover investments made to develop the drug. The call for immediate disclosure of research results contradicts the interest of the inventor, whose primary goal is to secure his intellectual property rights, usually by applying for patent protection. In Europe, where patent law is based on the principle of absolute novelty, disclosure of the results reduces novelty and prevents subsequent patenting. Consequently, patenting remains the top priority for pharmaceutical companies in Europe, while disclosure of the results is secondary. The following article looks critically at the idea of using the grace period in European patent law to reconcile the conflicting interests of society and inventors in times of pandemic. In this paper, we investigate whether the implementation of a grace period in European patent law like that known in the USA, Japan, or Korea benefits the disclosure of results and increases the flow of information, ultimately leading to the promotion of innovation and rapid drug discovery. This article questions whether the use of a grace period provides a sufficient incentive to the inventor for rapid disclosure. [ABSTRACT FROM AUTHOR]

Temperature is a key parameter in most biological and physical systems. It is, however, an inherent technological challenge to precisely track and control the temperature of small sample volumes when using high- and super-resolution microscopes. Various effects can cause a deviation of the sample temperature from its expected value, specifically in the observed volume or field-of-view. These effects include direct thermal contact of the objective lens and the coverslip via immersion medium, illumination-induced heating, evaporative cooling, or triggered phase transitions. In this paper, we shed light on these phenomena and introduce our newly developed device VAHEAT, which follows a microscopic approach for controlling and measuring the sample temperature. Our system overcomes traditional limitations of temperature sensing and controlling in high-sensitivity microscopy applications, leading to more reproducible experimental results and conquering new experimental parameter ranges. [ABSTRACT FROM AUTHOR]

The paper aims at advancing our understanding of the architecture and diversification dynamics of industrial ecosystems, and identifying policies for the innovative industrial renewal of mature economies. Industrial ecosystems are here defined as multi-tiered production systems involving heterogeneous agents operating in sectoral value chains and contributing to the capability domains of the ecosystem (and its participants) with closely complementary but dissimilar sets of resources and capabilities. The geographical boundaries of the industrial ecosystem are shaped by the evolving interdependencies linking organisations within the ecosystem and by the new linkages consolidating beyond that. Thus, the industrial ecosystem is a structured production space centred mainly on its productive organisations, as well as other institutions, intermediaries and demand-side actors, purposefully involved in co-value creation processes along various types of diversification and innovative industrial renewal trajectories. Drawing on a five-year research programme in the Emilia Romagna industrial ecosystem, a number of case studies are introduced to highlight these trajectories and the underpinning structural learning dynamics. The paper concludes by identifying a number of policy implications, focusing on strategies for enhancing the structural readiness of the industrial ecosystem and promoting smart diversification and innovative industrial renewal policies. [ABSTRACT FROM AUTHOR]

This paper undertakes a critical theoretical and empirical analysis of the traditional approach to analysing the education–economy relationship: skill bias technological change theory. It argues that while leading skill bias theorists have sought to address some of the anomalies that the theory confronts, there remain key data patterns that the theory cannot address. We suggest an alternative account that takes a broader political economy perspective. [ABSTRACT FROM AUTHOR]

In order to mitigate the problem of the ‘memory wall’, various emerging nonvolatile memory (NVM) technologies have been proposed to replace the traditional ones. These emerging NVMs include spin torque transfer random access memory, PCRAM, resistive random access memory, racetrack memory, etc. Compared to traditional memory technologies, they have the advantages of near-zero standby power, high storage density and nonvolatility, which make them competitive for future memory hierarchy design. However, it is inefficient to directly apply these NVMs in existing memory architectures. On the one hand, these NVMs have their own limitations, such as long write latency, high write energy, limited write numbers, etc. Thus, proper architecture modification is required to adopt them into the traditional memory hierarchy. On the other hand, the unique features of these NVMs allow new memory architectures in memory subsystems and also introduce new challenges to be solved at the same time. In this paper, we not only review various emerging NVMs but also study typical related work on these topics to investigate their implications for memory architecture design. [ABSTRACT FROM AUTHOR]

This paper analyses the impact of internationalization on the innovation performance of 40 countries. Internationalization variables are represented by outward and inward foreign direct investment, and by imports and exports; innovation is proxied with triadic patent applications. We take account of the influence of absorptive capacity-in both a linear and non-linear form-in the relationship between internationalization and innovation. Our results suggest that outward FDI is positively associated with patenting. Countries with high absorptive capacity benefit more, though there are diminishing returns. We find there is a negative association between inward FDI and patenting in countries with low absorptive capacity where FDI may displace local infant activities and stun further development of related local knowledge. We find support for the view that the innovation performance of countries with low absorptive capacity benefits from imports as well as from exports. [ABSTRACT FROM AUTHOR]

Economic theory justifies policy when there are concrete market failures. The article shows how in the case of innovation, successful policies that have led to radical innovations have been more about market shaping and creating through direct and pervasive public financing, rather than market fixing. The paper reviews and discusses evidence for this in three key areas: (i) the presence of finance from public sources across the entire innovation chain; (ii) the concept of 'mission-oriented' policies that have created new technological and industrial landscapes; and (iii) the entrepreneurial and lead investor role of public actors, willing and able to take on extreme risks, independent of the business cycle. We further illustrate these three characteristics for the case of clean technology, and discuss how a market-creating and -shaping perspective may be useful for understanding the financing of transformative innovation needed for confronting contemporary societal challenges. [ABSTRACT FROM AUTHOR]

Using the example of Russia, we argue that financialisation in an authoritarian state can take place primarily through formation in financial sector monopoly-like state-related structures controlled by a limited circle of the irreplaceable elite. It occurs because financialisation and new financial technologies in an authoritarian state increase both the opportunities and incentives for dominance of large state-dependent institutions in the financial sector. The authoritarian state and its elite are using financial and information technology developments in accordance with their goals, adopting and enhancing some financial practices and innovations from the experience of developed countries while rejecting, distorting or slowing down others. As a result, on the one hand, within the framework of the formation of such monopoly-like institutions, financialisation is proceeding actively, the role of finance and financial relations in society is increasing everywhere and the use of new financial technologies, digitalisation and financial inclusion are expanding. On the other hand, some financial markets remain underdeveloped because either they imply a certain degree of competition, diversity, institutional quality and independence from state voluntarism, or the state and authoritarian elite have not yet fully elaborated a strategy of integrating these financial markets into the orbit of their interests. Thus financialisation in DEEs with an authoritarian political regime can strengthen and facilitate the dominance of authoritarian elites. We draw these conclusions considering the example of financialisation in Russia in the last two decades, where the banking sector is at the core of the financial system. [ABSTRACT FROM AUTHOR]

Emerging technologies permeate and potentially disrupt a wide spectrum of our social, economic, and political relations. Various state institutions, including education, law enforcement, and healthcare, increasingly rely on technical components, such as automated decision-making systems, e-government systems, and other digital tools to provide cheap, efficient public services, and supposedly fair, transparent, disinterested, and accountable public administration. The increased interest in various blockchain-based solutions from central bank digital currencies, via tokenized educational credentials, and distributed ledger-based land registries to self-sovereign identities is the latest, still mostly unwritten chapter in a long history of standardized, objectified, automated, technocratic, and technologized public administration. The rapid, (often) unplanned, and uncontrolled technologization of public services (as happened in the hasty adoption of distance-learning and teleconferencing systems during Corona Virus Disease (COVID) lockdowns) raises complex questions about the use of novel technological components, which may or may not be ultimately adequate for the task for which they are used. The question whether we can trust the technical infrastructures the public sector uses when providing public services is a central concern in an age where trust in government is declining: If the government's artificial intelligence system that detects welfare fraud fails, the public's confidence in the government is ultimately hit. In this paper, we provide a critical assessment of how the use of potentially untrustworthy (private) technological systems including blockchain-based systems in the public sector may affect trust in government. We then propose several policy options to protect the trust in government even if some of their technological components prove fundamentally untrustworthy. [ABSTRACT FROM AUTHOR]

The advent of high-throughput sequencing technologies has not only revolutionized the field of bioinformatics but has also heightened the demand for efficient taxonomic classification. Despite technological advancements, efficiently processing and analyzing the deluge of sequencing data for precise taxonomic classification remains a formidable challenge. Existing classification approaches primarily fall into two categories, database-based methods and machine learning methods, each presenting its own set of challenges and advantages. On this basis, the aim of our study was to conduct a comparative analysis between these two methods while also investigating the merits of integrating multiple database-based methods. Through an in-depth comparative study, we evaluated the performance of both methodological categories in taxonomic classification by utilizing simulated data sets. Our analysis revealed that database-based methods excel in classification accuracy when backed by a rich and comprehensive reference database. Conversely, while machine learning methods show superior performance in scenarios where reference sequences are sparse or lacking, they generally show inferior performance compared with database methods under most conditions. Moreover, our study confirms that integrating multiple database-based methods does, in fact, enhance classification accuracy. These findings shed new light on the taxonomic classification of high-throughput sequencing data and bear substantial implications for the future development of computational biology. For those interested in further exploring our methods, the source code of this study is publicly available on https://github.com/LoadStar822/Genome-Classifier-Performance-Evaluator. Additionally, a dedicated webpage showcasing our collected database, data sets, and various classification software can be found at http://lab.malab.cn/~tqz/project/taxonomic/. [ABSTRACT FROM AUTHOR]

Implementing eHealth requires technological advancement, universal broadband and internet access, and devices to conduct telemedicine and remote patient monitoring in end-stage kidney disease patients receiving home dialysis. Although eHealth was beginning to make inroads in this patient population, the COVID-19 pandemic spurred telemedicine usage when many regulations were waived during the Public Health Emergency to limit the spread of infection by endorsing social distancing. At the same time, two-way communication automatic peritoneal dialysis cyclers were introduced to advance remote patient monitoring. Despite the numerous advantages and potential benefits afforded by both procedures, challenges and untapped resources remain to be addressed. Continuing research to assess the use of eHealth and technological innovation can make eHealth a powerful tool in home dialysis. We review the past, present and future of eHealth and remote patient monitoring in supporting home dialysis. [ABSTRACT FROM AUTHOR]

The Cost of Energy Review recommended that, in the face of radical technical change, government should: move towards an Equivalent Firm Power capacity auction, integrating the renewables; establish independent public system operators at the national and regional levels; and move towards an economy-wide carbon price. These have met resistance from vested interests, in defence of the economic rents that have accumulated from the dense web of interventions that have accumulated. The paper shows that the first two of these reforms are nevertheless inevitable with active demand, storage, and decentralized generation technologies inverting the old assumptions of passive demand, no storage, and ever larger-scale generation that have underpinned the electricity industry for the past century. Delay in implementation means continued excess costs of energy and delays innovation. [ABSTRACT FROM AUTHOR]

This paper explores journalists' reactions to economic constraints and technological transformations in two cities: Toulouse, France, and Seattle, United States. Through semi-structured interviews, we show that journalists in both places either endure these conditions, invest in them as professional opportunities, or ignore them altogether. Drawing on Bourdieu, we argue that these distinct responses are shaped in part by a journalist's position in the field: those in low positions tend to endure; those in intermediate positions generally invest; and those in high positions are likely to ignore. We also suggest that the meanings of these responses vary according to the distinctive fields in which journalists are embedded, with the reactions of Toulouse journalists generally less market-oriented than their Seattle counterparts. These findings, and the theoretical perspective that enables them, are positioned in relation to case studies that analyze journalists' reactions and comparative survey research that explores similarities and differences in such reactions. [ABSTRACT FROM AUTHOR]

Technological revolutions are often accompanied by substantial stock price reversals, but previous literature has produced competing explanations for why this is the case. This paper brings new evidence to this debate using data from the innovation-driven British Bicycle Mania of 1895–1900, in which cycle share prices rose by over 200% before collapsing by more than 75%. These price patterns are not fully explained by fundamentals or by changes in the nature of risk associated with cycle shares. Instead, the evidence from the Bicycle Mania supports the hypothesis of Perez (2009), who argues that new technology, high short-term profits and loose monetary conditions increase the level of speculative investment, 'decoupling' share prices from fundamentals. [ABSTRACT FROM AUTHOR]

Performance measurement is most often considered as the apolitical application of the use of information, collected and used to demonstrate effectiveness against a set of criteria. In reality, many complexities are hidden behind this seemingly rational and technical enterprise. This paper establishes a conceptual framework for the collection of articles in this volume. It examines the politics of performance measurement — who decides what should be measured, how, and why — and its consequences. It analyses why performance measurement is important, outlines its explicit and implicit purposes and the fundamental assumptions underpinning it, and describes its problems, paradoxes and consequences. A chain of performance measurement is then proposed and two contrasting versions of it (one rational-technical and one realistic-political) are presented. This social structural and political institutional approach to performance measurement highlights dynamics, interactivity and power. In doing so, it discloses the politics and consequences of performance measurement. [ABSTRACT FROM AUTHOR]

This paper proposes a conceptual framework on knowledge accumulation and depletion in industrial districts (IDs). The framework introduces three types of endogenous cognitive processes, namely learning, forgetting and unlearning, affected by internal and external dynamics. Such processes determine the reconfiguration of the ID cognitive structure based on the expansion and contraction of local knowledge. We apply the framework to three empirical cases: the Stoke-on-Trent ceramic ID, the Prato textile ID and the Macerata–Fermo footwear IDs. The empirical analysis describes the reconfiguration of the ID cognitive structure in relation to different cross-boundary relations, such as the introduction of a new policy, technological change and internationalisation. The results inform us that the contraction of some productive specialisations through forgetting may not be just the prelude of decline, but rather a condition fostering the exploration of new learning opportunities within paths of manufacturing recovery. [ABSTRACT FROM AUTHOR]

Motivation Emergent biological dynamics derive from the evolution of lower-level spatial and temporal processes. A long-standing challenge for scientists and engineers is identifying simple low-level rules that give rise to complex higher-level dynamics. High-resolution biological data acquisition enables this identification and has evolved at a rapid pace for both experimental and computational approaches. Simultaneously harnessing the resolution and managing the expense of emerging technologies—e.g. live cell imaging, scRNAseq, agent-based models—requires a deeper understanding of how spatial and temporal axes impact biological systems. Effective emulation is a promising solution to manage the expense of increasingly complex high-resolution computational models. In this research, we focus on the emulation of a tumor microenvironment agent-based model to examine the relationship between spatial and temporal environment features, and emergent tumor properties. Results Despite significant feature engineering, we find limited predictive capacity of tumor properties from initial system representations. However, incorporating temporal information derived from intermediate simulation states dramatically improves the predictive performance of machine learning models. We train a deep-learning emulator on intermediate simulation states and observe promising enhancements over emulators trained solely on initial conditions. Our results underscore the importance of incorporating temporal information in the evaluation of spatio-temporal emergent behavior. Nevertheless, the emulators exhibit inconsistent performance, suggesting that the underlying model characterizes unique cell populations dynamics that are not easily replaced. Availability and implementation All source codes for the agent-based model, emulation, and analyses are publicly available at the corresponding DOIs: 10.5281/zenodo.10622155, 10.5281/zenodo.10611675, 10.5281/zenodo.10621244, respectively. [ABSTRACT FROM AUTHOR]

The focus of this paper is on the unexpected and undesirable consequences of social interaction with technological innovations, which we analyse with the support of two frameworks to better comprehend their social implications. The first, techno-social framework, consists of Allenby and Sarewitz's taxonomy of technological social function. In the second, cognitive, framework, we introduce concepts from dual-systems theory. The frameworks provide a lens through which to view techno-cultural examples. This sets the stage for our case study in which we investigate an interactive game installation. Using data analytics, we uncover hidden effects due to the social interactions between the players and to their physical attributes. We conclude that there is a pressing need for innovators to broaden the scope of their evaluations to not just evaluate innovative technologies at the initial engineering/design phase but also to conduct evaluations at later phases of adoption and appropriation that focus on social contexts-of-use. [ABSTRACT FROM AUTHOR]

In this paper, the need of multi-criteria evaluation (MCE) for a desalination technology selection is emphasized through a case study. Decision context, problem formulation and the relative importance of 11 complete, operational and non-redundant criteria were established which represented the behavior of the MCE problem. TOPSIS and PROMETHEE-2 methods were identified as the appropriate MCE techniques and the five alternatives were evaluated using these methods separately. The respective results indicated that ED was the most applicable technology for the selected community and ranked the usage of electrodialysis, reverse osmosis, vapor compression, multiple effect distillation and multi-stage flash in the decreasing order of priority. [ABSTRACT FROM AUTHOR]

Researchers are rapidly developing and deploying highly portable MRI technology to conduct field-based research. The new technology will widen access to include new investigators in remote and unconventional settings and will facilitate greater inclusion of rural, economically disadvantaged, and historically underrepresented populations. To address the ethical, legal, and societal issues raised by highly accessible and portable MRI, an interdisciplinary Working Group (WG) engaged in a multi-year structured process of analysis and consensus building, informed by empirical research on the perspectives of experts and the general public. This article presents the WG's consensus recommendations. These recommendations address technology quality control, design and oversight of research, including safety of research participants and others in the scanning environment, engagement of diverse participants, therapeutic misconception, use of artificial intelligence algorithms to acquire and analyze MRI data, data privacy and security, return of results and managing incidental findings, and research participant data access and control. [ABSTRACT FROM AUTHOR]

In this paper, we present disruption of household routines as a method to study home technology usage. Using three case studies as guidance, we show how disrupting household practices—either through changing the technology, task or division of labor—can provide valuable insight into current and future technology usage, and can guide the design of future technologies. Based on our case studies, we outline best practices and challenges with respect to the pragmatics of disruptive research methods.RESEARCH HIGHLIGHTS We present disruption as a method for studying technology use in homes.Grounded in three case studies, we provide best practices for using this method.We address pragmatic and ethical challenges of using disruption as a method. [ABSTRACT FROM AUTHOR]

Recent methodological innovation is giving rise to an increasing number of applied papers in medical and epidemiological journals in which natural direct and indirect effects are estimated. However, there is a longstanding debate on whether such effects are relevant targets of inference in population health. In light of the repeated calls for a more pragmatic and consequential epidemiology, we review three issues often raised in this debate: (i) the use of composite cross-world counterfactuals and the need for cross-world independence assumptions; (ii) interventional vs non-interventional identifiability; and (iii) the interpretational ambiguity of natural direct and indirect effect estimates. We use potential outcomes notation and directed acyclic graphs to explain ‘cross-world’ assumptions, illustrate implications of this assumption via regression models and discuss ensuing issues of interpretation. We argue that the debate on the relevance of natural direct and indirect effects rests on whether one takes as a target of inference the mathematical object per se, or the change in the world that the mathematical object represents. We further note that public health questions may be better served by estimating controlled direct effects. [ABSTRACT FROM AUTHOR]

This paper critically examines the feasibility and desirability of green growth in India. Currently, its environment is being plundered at all levels, local, national, and global. The stresses that result raise the fundamental question of whether the aspirations of Indians for greater material comfort can ever be fulfilled. The current 5-year plan aims for ‘Faster and More Inclusive Sustainable Growth’ but it is clear that the emphasis of the Plan is mostly on growth and inclusion, rather than sustainability. A modelling exercise reported here suggests that a ‘visionary development’ growth scenario with major social and environmental benefits is possible for India at low cost. However, combining that scenario with a low-carbon growth trajectory consistent with international aspirations to limit climate change would be significantly more expensive. As it is not clear that the Indian people would be willing to bear these extra costs, some combination of accelerated low-carbon innovation, technology transfer from developed countries, and climate finance from outside the country will be needed if green growth is to take root in India. [ABSTRACT FROM AUTHOR]

Inequality in the distribution of income and wealth has come to the fore as a core concern across the industrialized world. Here we examine what has happened to income inequality across the rich countries in recent decades. We discuss the range of factors that appear to be driving inequality upwards, notably the role of technological change, globalization, and national institutions and policies. We look at how rising inequality might undermine economic growth and squeeze the middle, and assess the extent to which it has actually done so. We assess whether rising inequality is associated with worsening outcomes and inequalities across various social domains. Finally, we review emerging evidence on the role that rising inequality may be playing in the 'revolt of the angry' and rise of populism. [ABSTRACT FROM AUTHOR]

While economic theory suggests a wide range of potential determinants of income inequality, there is little consensus regarding the most relevant ones. Such a lack of consensus reflects, to an important extent, the impact of model uncertainty. Using model-averaging techniques—specifically WALS (weighted-average least squares)—to get at a robust set of determinants, our results underscore the multiplicity of factors behind rising national-level inequalities. In the cross-section, the level of development and demographics, as well as unemployment and globalization, seem to be key drivers. Trade and financial globalization have asymmetric effects, with trade integration associated with lower inequality, and financial globalization with higher inequality. Financial deregulation and technological change seem to be important drivers of inequality, particularly in advanced economies. [ABSTRACT FROM AUTHOR]

This article explores the challenges and strategies involved in breeding sheep that are better adapted to harsh environments, with a particular focus on climate change. It emphasizes the importance of considering adaptability to challenging environments in sheep breeding and the need to address genotype by environment interaction. The article discusses the specific challenges and opportunities in sheep breeding, particularly in extensive systems, and highlights the potential for using new phenotypes and reaction norm analysis to improve genetic selection for traits related to environmental stressors. It also discusses the potential of technologies such as digital phenotyping and genomic selection, although further development and investment are required. The article concludes by discussing the challenges of implementing these strategies in commercial breeding programs, particularly in South Africa, and suggests that incentivized participation and certification initiatives may help overcome these challenges. Overall, a combination of genetic selection, technological advancements, and environmental interventions is needed to improve the resilience and fitness of sheep in the face of climate change. [Extracted from the article]

Internet of Things (IoT) sensor networks are an emerging technology at the center of the datafication and optimization of far-reaching environmental infrastructures—from "smart cities" to workplace efficiencies. However, this low-power, low-cost technology is also well suited to local deployments in rural communities, which are often overlooked by digital development initiatives. Therefore, we used a social construction of technology approach to study how various U.S.-based IoT stakeholders—including designers and advocates as well as citizen stakeholders—understand and value sensor network technologies. Through observational methods, in-depth interviews, and participatory design research in a rural Upstate New York municipality, we worked to design sensor networks with rural community members to generate data about and for community members to further local knowledge. We found that designing rural sensor networks requires stakeholders to navigate obstacles of communication about sensors and communication through sensors to facilitate secure, ethical, and localized sensing in rural communities. [ABSTRACT FROM AUTHOR]

Various occupations are increasingly confronted with promises that new technologies will transform their work long before these technologies are deployed in their workplace. Although we know how new technologies are framed when they are introduced to work, we have limited understanding of how practitioners frame an emerging technology before it is deployed. Building on frame literature and examining the case of artificial intelligence (AI) in diagnostic radiology, I show how radiologists go beyond technological promises by engaging in constructing multiple frames ex ante (pre-frames). These pre-frames are neither technology-centric nor work-centric, but rather are dialectic technology–work frames, through which their accounts of both technology and work are simultaneously (re)constructed. They not only help radiologists settle around certain ways of relating AI to their work, but also unsettle their accounts by unearthing unresolved debates, raising new questions, and impelling them to consider divergent reaction strategies. [ABSTRACT FROM AUTHOR]

The use of error-corrected Next Generation Sequencing (ecNG) to determine mutagenicity has been a subject of growing interest and potentially a disruptive technology that could supplement, and in time, replace current testing paradigms in preclinical safety assessment. Considering this, a Next Generation Sequencing Workshop was held at the Royal Society of Medicine in London in May 2022, supported by the United Kingdom Environmental Mutagen Society (UKEMS) and TwinStrand Biosciences (WA, USA), to discuss progress and future applications of this technology. In this meeting report, the invited speakers provide an overview of the Workshop topics covered and identify future directions for research. In the area of somatic mutagenesis, several speakers reviewed recent progress made with correlating ecNGS to classic in vivo transgenic rodent mutation assays as well as exploring the use of this technology directly in humans and animals, and in complex organoid models. Additionally, ecNGS has been used for detecting off-target effects of gene editing tools and emerging data suggest ecNGS potential to measure clonal expansion of cells carrying mutations in cancer driver genes as an early marker of carcinogenic potential and for direct human biomonitoring. As such, the workshop demonstrated the importance of raising awareness and support for advancing the science of ecNGS for mutagenesis, gene editing, and carcinogenesis research. Furthermore, the potential of this new technology to contribute to advances in drug and product development and improve safety assessment was extensively explored. [ABSTRACT FROM AUTHOR]

Background This study aims to analyze the health resource allocation efficiency in Sichuan Province from 2010 to 2018 and provide other countries with China's experience. Methods We used the super efficiency slack based model (SBM) model and Malmquist index to analyze the super efficiency and inter-period efficiency of health resource allocation in 19 cities in Sichuan Province from 2010 to 2018 and propose the input-output optimization scheme of health resource allocation in 2018. Finally, the Tobit model was used to estimate the influencing factors of health resource allocation efficiency. Results The total allocation of health resources in Sichuan Province was increasing in addition to the total number of visits from 2010 to 2018. The super efficiency SBM results identified that the sample's average score was between 0.651 and 3.244, with an average of 1.041, of which 15 cities had not reached data envelopment analysis effectiveness. According to the Malmquist index, the average total factor productivity index of Sichuan Province was 0.930, which showed an imbalance in resource input, and its fluctuation was mainly related to the technological progress index and scale efficiency. The efficiency score was affected by the average annual income of residents, population density and education level. Conclusions The amount of health resource allocation in Sichuan Province had shown an overall upward trend since 2010. However, resource allocation efficiency was not high, and there were problems such as significant regional differences, insufficient technological innovation capabilities and unscientific allocation of resource scale. To optimize the resource allocation structure, we suggest that the relevant departments pay attention to the impact of natural disasters, the average annual income of residents, population density and education level on efficiency to allocate health resources scientifically. [ABSTRACT FROM AUTHOR]

This article studies how innovation reacts to climate change and shapes its economic impacts, focusing on U.S. agriculture. We show in a model that directed innovation can either mitigate or exacerbate climate change's potential economic damage depending on the substitutability between new technology and favorable climatic conditions. To empirically investigate the technological response to climate change, we measure crop-specific exposure to damaging extreme temperatures and crop-specific innovation embodied in new variety releases and patents. We find that innovation has redirected since the mid-twentieth century toward crops with increasing exposure to extreme temperatures. Moreover, this effect is driven by types of agricultural technology most related to environmental adaptation. We next show that U.S. counties' exposure to induced innovation significantly dampens the local economic damage from extreme temperatures. Combining these estimates with the model, we find that directed innovation has offset 20% of potential losses in U.S. agricultural land value due to damaging climate trends since 1960 and that innovation could offset 13% of projected damage by 2100. These findings highlight the vital importance, but incomplete effectiveness, of endogenous technological change as a source of adaptation to climate change. [ABSTRACT FROM AUTHOR]