Based on research from previous pandemics, studies of critical care survivors, and emerging COVID-19 data, we estimate that up to 30% of survivors of severe COVID will develop PTSD. PTSD is frequently undetected across primary and secondary care settings and the psychological needs of survivors may be overshadowed by a focus on physical recovery. Delayed PTSD diagnosis is associated with poor outcomes. There is a clear case for survivors of severe COVID to be systematically screened for PTSD, and those that develop PTSD should receive timely access to evidence-based treatment for PTSD and other mental health problems by multidisciplinary teams.
Mutations of splice sites, auxiliary splicing elements and the splicing machinery cause a wide range of genetic disease. Here we report that many of the complex effects of splicing mutations can be predicted from background splicing information, with emphasis on BRCA1, BRCA2 and DMD. Background splicing arises from very low level splicing between rarely used background splice sites and from low-level exon skipping between intron splice sites. We show how this information can be downloaded from the Snaptron database of spliced RNA, which we then compared with databases of human splice site mutations. We report that inactivating mutations of intron splice sites typically caused the non-mutated partner splice site to splice to a known background splice site in over 90% of cases and to the strongest background splice site in the large majority of cases. Consequently, background splicing information can usefully predict the effects of splice site mutations, which include cryptic splice activation and single or multiple exon skipping. In addition, de novo splice sites and splice sites involved in pseudoexon formation, recursive splicing and aberrant splicing in cancer show a 90% match to background splice sites, so establishing that the enhancement of background splicing causes a wide range of splicing aberrations. We also discuss how background splicing information can identify cryptic splice sites that might be usefully targeted by antisense oligonucleotides (ASOs) and how it might indicate possible multiple exon skipping side effects of ASOs designed to induce single exon skipping.
The accurate simulation of additional interactions at the ATLAS experiment for the analysis of proton–proton collisions delivered by the Large Hadron Collider presents a significant challenge to the computing resources. During the LHC Run 2 (2015–2018), there were up to 70 inelastic interactions per bunch crossing, which need to be accounted for in Monte Carlo (MC) production. In this document, a new method to account for these additional interactions in the simulation chain is described. Instead of sampling the inelastic interactions and adding their energy deposits to a hard-scatter interaction one-by-one, the inelastic interactions are presampled, independent of the hard scatter, and stored as combined events. Consequently, for each hard-scatter interaction, only one such presampled event needs to be added as part of the simulation chain. For the Run 2 simulation chain, with an average of 35 interactions per bunch crossing, this new method provides a substantial reduction in MC production CPU needs of around 20%, while reproducing the properties of the reconstructed quantities relevant for physics analyses with good accuracy.
Many disciplines are facing a “reproducibility crisis”, which has precipitated much discussion about how to improve research integrity, reproducibility, and transparency. A unified effort across all sectors, levels, and stages of the research ecosystem is needed to coordinate goals and reforms that focus on open and transparent research practices. Promoting a more positive incentive culture for all ecosystem members is also paramount. In this commentary, we—the Local Network Leads of the UK Reproducibility Network—outline our response to the UK House of Commons Science and Technology Committee’s inquiry on research integrity and reproducibility. We argue that coordinated change is needed to create (1) a positive research culture, (2) a unified stance on improving research quality, (3) common foundations for open and transparent research practice, and (4) the routinisation of this practice. For each of these areas, we outline the roles that individuals, institutions, funders, publishers, and Government can play in shaping the research ecosystem. Working together, these constituent members must also partner with sectoral and coordinating organisations to produce effective and long-lasting reforms that are fit-for-purpose and future-proof. These efforts will strengthen research quality and create research capable of generating far-reaching applications with a sustained impact on society.
The ATLAS experiment at the Large Hadron Collider has a broad physics programme ranging from precision measurements to direct searches for new particles and new interactions, requiring ever larger and ever more accurate datasets of simulated Monte Carlo events. Detector simulation with Geant4 is accurate but requires significant CPU resources. Over the past decade, ATLAS has developed and utilized tools that replace the most CPU-intensive component of the simulation—the calorimeter shower simulation—with faster simulation methods. Here, AtlFast3, the next generation of high-accuracy fast simulation in ATLAS, is introduced. AtlFast3 combines parameterized approaches with machine-learning techniques and is deployed to meet current and future computing challenges, and simulation needs of the ATLAS experiment. With highly accurate performance and significantly improved modelling of substructure within jets, AtlFast3 can simulate large numbers of events for a wide range of physics processes.
This article considers why despite mass displacement significantly affecting people from Muslim majority countries, Islamic understandings of refuge, protection and assistance remain de‐centered and made peripheral in formulations of asylum and refuge. The paper begins with an interrogation of how knowledge production on Muslim life‐worlds a priori gives emphasis to certain essential characteristics identified as Muslim. It is argued that this collapses understandings of the diversity of being and ‘doing’ Muslim in ways that make less visible everyday lived experiences attuned to the materiality, affect and emotion prompted by readings of Islamic tradition in displacement settings. To do so, I draw on Syrian experiences of displacement in Turkey and Greece to parse out the implications of this (in)visibility for Muslim responses to mass‐displacement and question whether they can be substantively different to modalities of humanitarianism and development anchored in liberal European ontologies. It is argued that by being attentive to the structures of feeling prompted by Islamic traditions pertaining to refuge and protection reveals ways of being and doing Islam outside of statist readings of humanitarianism. Here, the Islamic tradition of jiwār (a right of and to neighbourliness) provides a decolonial vocabulary to respond to state‐defined patterns of hospitality rooted in European knowledge production.
Background In recent years there has been an increased focus on the role of large herbivores in ecosystem restoration and climate change mitigation. There are multiple processes by which large herbivores could potentially influence climate feedback and forcing effects, but the evidence has not yet been synthesised in a systematic and accessible format. Grazing, browsing, trampling, defecation, and seed dispersal by large herbivores can influence vegetation and soils in ways that may directly or indirectly contribute to climate change or mitigation. For example, changes in vegetation could impact wildfire regimes, carbon storage, and albedo, with ultimate impacts on climate. These processes may be influenced by herbivore species composition, density, and functional traits. The main aim of this systematic map is to synthesise the range of research on climate feedback and forcing effects from large herbivores (≥ 10 kg) in terrestrial ecosystems. We also aim to identify knowledge clusters and gaps in the research base, as well as assessing the potential for quantitative analyses. Methods A search of peer-reviewed and grey literature will be conducted using a range of bibliographic databases, search engines and websites. The search strategy will involve using a pre-defined search string with Boolean operators. All search results will be screened for relevance according to specific eligibility criteria. Screening will be conducted in two stages: all articles will initially be screened by title and abstract, then those that meet the eligibility criteria will be screened by full text. At both stages, articles will be excluded if they don’t meet all eligibility criteria or if they meet any exclusion criteria. All articles included as eligible after full text screening will be coded. At each stage (of screening and coding) a proportion of articles will be processed independently by two reviewers to assess inter-reviewer reliability and resolve differences. The evidence will be presented in a searchable database with accompanying visual outputs. A narrative synthesis will be provided outlining the range and distribution of evidence, knowledge gaps and clusters, potential bias, and areas for further research.
The detection of variations of fundamental constants of the Standard Model would provide us with compelling evidence of new physics, and could lift the veil on the nature of dark matter and dark energy. In this work, we discuss how a network of atomic and molecular clocks can be used to look for such variations with unprecedented sensitivity over a wide range of time scales. This is precisely the goal of the recently launched QSNET project: A network of clocks for measuring the stability of fundamental constants. QSNET will include state-of-the-art atomic clocks, but will also develop next-generation molecular and highly charged ion clocks with enhanced sensitivity to variations of fundamental constants. We describe the technological and scientific aims of QSNET and evaluate its expected performance. We show that in the range of parameters probed by QSNET, either we will discover new physics, or we will impose new constraints on violations of fundamental symmetries and a range of theories beyond the Standard Model, including dark matter and dark energy models.
What impact has rising generic competition had on the nature and direction of pharmaceutical innovation? We find broad-based, strong evidence that pharmaceutical companies have diverted their new drug development efforts away from therapeutic markets already well-served by generic drugs. We also find that increasing generic competition induces firms to shift their R&D activity toward more biologic-based products and away from chemical-based products. We conclude by discussing potential implications of our results for long-run innovation policy.
Triboelectric nanogenerators (TENGs) have potential to achieve energy harvesting and condition monitoring of oils, the “lifeblood” of industry. However, oil absorption on the solid surfaces is a great challenge for oil–solid TENG (O-TENG). Here, oleophobic/superamphiphobic O-TENGs are achieved via engineering of solid surface wetting properties. The designed O-TENG can generate an excellent electricity (with a charge density of 9.1 µC m ⁻² and a power density of 1.23 mW m ⁻² ), which is an order of magnitude higher than other O-TENGs made from polytetrafluoroethylene and polyimide. It also has a significant durability (30,000 cycles) and can power a digital thermometer for self-powered sensor applications. Further, a superhigh-sensitivity O-TENG monitoring system is successfully developed for real-time detecting particle/water contaminants in oils. The O-TENG can detect particle contaminants at least down to 0.01 wt% and water contaminants down to 100 ppm, which are much better than previous online monitoring methods (particle > 0.1 wt%; water > 1000 ppm). More interesting, the developed O-TENG can also distinguish water from other contaminants, which means the developed O-TENG has a highly water-selective performance. This work provides an ideal strategy for enhancing the output and durability of TENGs for oil–solid contact and opens new intelligent pathways for oil–solid energy harvesting and oil condition monitoring.
Rapid industrialization and urbanization significantly contribute to air pollution in China. Essential constituents of air pollution are fine and coarse particulate matter which are the total mass of aerosol particles with aerodynamic diameters smaller than ≤2.5 μm (PM2.5) and ≤10 μm (PM10), respectively. These particles may cause severe health effects, and impact the atmospheric environment and climate. However, the limited number of ground-based measurements at sparsely distributed air quality monitoring stations hamper long-term air pollution impact studies over large areas. Although spatial data on PM2.5 and PM10 are available from reanalysis models, the accuracy of such data may be reduced in comparison with ground data and may vary regionally and seasonally. Therefore, a long-term evaluation of reanalysis-based PM2.5 and PM10 against ground-based measurements is needed for China. In this study, surface-level PM2.5 and PM10 concentrations from 2014 to 2020 obtained from the Copernicus Atmospheric Monitoring Service (CAMS), and from the second version of Modern-Era Retrospective analysis for Research and Applications (MERRA-2) were evaluated using ground-based measurements obtained from 1675 air quality monitoring stations distributed across China. High PM2.5 and PM10 (μg/m3) concentrations from ground-based measurements were observed in many parts of China (including the North China Plain: NCP, Yangtse River Delta:YRD, Pearl River Delta: PRD, Central China, Sichuan Basin: SB, and northwestern region: Tarim Basin). The patterns of the spatial distributions of PM2.5 and PM10 obtained from CAMS and MERRA-2 across China are similar to those of the ground-based monitoring data, but the concentrations from both models are substantially different. CAMS significantly overestimates PM2.5 and PM10 over most regions, in particular over urban and desert areas, whereas MERRA-2 seasonal and annual mean concentrations were more accurate over the highly polluted areas in central and eastern China. The lowest PM2.5 and PM10 concentrations were observed over the Tibetan Plateau and Qinghai, where CAMS and MERRA-2 datasets were substantially underestimated. Furthermore, both CAMS and MERRA-2 under-and over-estimate the PM concentrations in both low and high pollution conditions. Overall, this study contributes to understanding of the reliability of reanalysis data and provides a baseline document for improving the CAMS and MERRA-2 datasets for studying local and regional air quality in China.
An extensive, representative, and, multi-country tailored survey questionnaire eliciting social practices with heat as an energy service and the relative perceptions about heating devices was submitted to a randomized sample of more than 6,000 potential end-users in Europe within the framework of the Horizon 2020 project SWS-HEATING. The project is developing an innovative seasonal thermal energy storage unit for residential use. Moreover, within the project, the role of occupancy variability and use conditions in the performance of the proposed system is assessed. The present study focuses on tailor-made user-building interaction models to be implemented into dynamic simulation for the assessment of the proposed and similar systems starting from the sociological assessment of such large-scale survey results. These models take advantage from the knowledge raised by the findings of the social survey to frame for the first time occupants’ behavior scenarios representative of South, central, and North European countries. In this way, the influence of cultural context and demographic factors and their relation to heating practices are considered when developing these tailored occupant behavior models. Results show the non-negligible influence (up to 43% in the coldest climate) of implementing these models on predicted building heating energy needs, as quantitative demonstration of the role of societal-related variables on final energy use estimation.
Emerging markets often experience instability due to rapid changes to the institutional environment, social changes like rapid urbanization, or even unrest. We argue that emerging market multinationals (EMNEs) manage such instability by constructing and changing locational portfolios, and qualitatively analyze six cases in South Africa over a period that included the entrenchment of Apartheid, increasing resistance to it, the immediate post-Apartheid era, and finally the period of state capture. The four periods of (in)stability – initial tenuous stability, extreme instability, comprehensive stability, and finally growing instability – differently affected EMNEs’ location choices. EMNEs went to proximate developing countries when the home country was relatively stable, but left for host countries in the developed world once the home country became unstable. Few EMNEs capitalized on their experience there once home-country stability returned, instead returning to emerging markets. These patterns are best explained by a portfolio logic that takes into account home-country environmental dynamism.
Planetary gears (PGs) play a critical role in hybrid electric vehicles (HEVs) by combining the output torques of different powertrain components and delivering the resulting torque to the wheels. Whilst previous studies show that the number of planetary gears affects performance of HEVs, there is no prior study to systematically investigate such effects on energy consumption. This paper quantifies the energy efficiency improvement of HEVs due to increasing the number of PGs from one to two, and from two to three. This is done by comparing the minimum energy consumption for different topologies when the rest of the powertrain components – namely electric motors, batteries and engine – are the same. To calculate the minimum energy consumption, the paper proposes an optimal energy management strategy (EMS) for each topology to find the optimum sequence of clutch engagement and torque distribution. The minimum energy consumption of a vehicle with different number of PGs is then evaluated using the automotive simulation models (ASM) from dSPACE. Results show that, for the same electric motors and engine, increasing the number of PGs from one to two and from two to three reduces energy consumption by 5% and 1.5%, respectively.
Here we propose a framework for considering the justice issues of industrial cluster decarbonisation, a pressing challenge confronting many industrialised economies. Industrial clusters are large, multi-point source emitters, users of energy and employers of regional and national significance. In the UK, establishing low carbon industrial clusters is one of several grand challenges of industrial strategy. Theorising the just transition of industrial clusters requires concepts from multiple literatures. We abstract relevant themes from the intersections of the literatures of just transitions, innovation studies and sociotechnical transitions, and public participation in spatial planning, and illustrate their empirical relevance. The broad themes of our framework are (i) politics, space and institutions, with sub-themes of justice, democracy, financialization; (ii) new processes and procedures, with sub-themes of legal recognition of public concerns, community-based planning, community capacity enhancement and life cycle impact assessment; and (iii) correlates of acceptance and resistance, with sub-themes of environmental values, perceived loss of amenity, pre-existing politics, perceptions of just process and trust in the developer. The framework is intended to both guide the design of just transition processes ex-ante and evaluate these post-hoc.
In our tendency to discuss the objective properties of the external world, we may fail to notice that our subjective perceptions of those properties differ between individuals. Variability at all levels of the color vision system creates diversity in color perception, from discrimination to color matching, appearance, and subjective experience, such that each of us lives in a unique perceptual world. In this review, I discuss what is known about individual differences in color perception and its determinants, particularly considering genetically mediated variability in cone photopigments and the paradoxical effects of visual environments in both contributing to and counteracting individual differences. I make the case that, as well as being of interest in their own right and crucial for a complete account of color vision, individual differences can be used as a methodological tool in color science for the insights that they offer about the underlying mechanisms of perception. Expected final online publication date for the Annual Review of Vision Science, Volume 8 is September 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
The present work proposes an integration of a novel fin structure and Al2O3 nanoparticles as an enhancement technology to improve the melting performance of phase change materials (PCMs) for latent heat thermal energy storage systems. A mathematical model of the melting process of PCMs with nanoparticles in a triple-tube heat exchanger is formulated and validated against the experimental data. The effect of different fin layouts and different volume fractions of nanoparticles on the melting process is discussed and reported, including the evolution and deformation of solid–liquid interfaces, the distribution of isotherms, and the time-varying profile of liquid fraction and average temperature over the entire melting process. The results indicate that the melting characteristic is improved by applying the enhanced strategies of novel fins and nanoparticles. Compared to the original structure, the melting time of four different novel fins is reduced by 80.35%, 77.62%, 77.33%, and 80.65%, respectively, which are attributed to the heat transfer enhancement by adding fin configurations to the system. Al2O3 nanoparticles (at 3%, 6%, and 9%) are integrated into the PCMs, and the results show that the melting time is decreased by 13.1%, 15.6%, and 18.8%, respectively. It can be concluded that the combination of fins and nanoparticles is an efficient way to enhance the meting process of phase change materials for thermal energy storage systems.
This article contributes to the studies on the transition towards circular business models in incumbent entrepreneurial firms. The focus of our research is the plastic packaging industry, a paradigmatic case of firms with a high environmental impact who are currently under pressure to change their business models. Following a grounded theory approach, we conducted an exploratory research on five case studies, longitudinally analyzed over two years. The results of our research suggest that the circularity challenge raises dilemmas about how to interpret the transition to sustainability. On one hand, the transition may be interpreted in a reactive way, based on compliance to the law and the highest possible levels of continuity. On the other hand, the transition may be interpreted in a proactive way, based on radical experimentation and openness to change. Our results highlight that the reactive-proactive dilemma unfolds at three interconnected levels: the firm’s network (including the customers), the entrepreneur, and the organization. Our study also suggests that the entrepreneur is in a position to play a pivotal role in the multi-level adoption of a proactive (or reactive) view. More specifically, our longitudinal analysis suggests that if the effectiveness and impact of transition to circularity is to be maximized, then a multi-level proactive view of the circularity transition is key to transforming the three interconnected levels (network, entrepreneur, organization) into a proper, sustainability-oriented innovation ecosystem.
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