18 research outputs found
Induced innovation in energy technologies and systems: a review of evidence and potential implications for CO2 mitigation
We conduct a systematic, interdisciplinary review of empirical literature assessing evidence on induced innovation in energy and related technologies. We explore links between demand-drivers (both market-wide and targeted); indicators of innovation (principally, patents); and outcomes (cost reduction, efficiency, and multi-sector/macro consequences). We build on existing reviews in different fields and assess over 200 papers containing original data analysis. Papers linking drivers to patents, and indicators of cumulative capacity to cost reductions (experience curves), dominate the literature. The former does not directly link patents to outcomes; the latter does not directly test for the causal impact of on cost reductions). Diverse other literatures provide additional evidence concerning the links between deployment, innovation activities, and outcomes. We derive three main conclusions. (1) Demand-pull forces enhance patenting; econometric studies find positive impacts in industry, electricity and transport sectors in all but a few specific cases. This applies to all drivers - general energy prices, carbon prices, and targeted interventions that build markets. (2) Technology costs decline with cumulative investment for almost every technology studied across all time periods, when controlled for other factors. Numerous lines of evidence point to dominant causality from at-scale deployment (prior to self-sustaining diffusion) to cost reduction in this relationship. (3) Overall Innovation is cumulative, multi-faceted, and self-reinforcing in its direction (path-dependent). We conclude with brief observations on implications for modeling and policy. In interpreting these results, we suggest distinguishing the economics of active deployment, from more passive diffusion processes, and draw the following implications. There is a role for policy diversity and experimentation, with evaluation of potential gains from innovation in the broadest sense. Consequently, endogenising innovation in large-scale models is important for deriving policy-relevant conclusions. Finally, seeking to relate quantitative economic evaluation to the qualitative socio-technical transitions literatures could be a fruitful area for future research
A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
Background: The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods: This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results: Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan‒Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. Conclusions: A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients.11 página
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Assessing the effectiveness of energy efficiency measures in the residential sector gas consumption through dynamic treatment effects: Evidence from England and Wales
Improving energy efficiency (EE) is vital to ensure a sustainable, affordable, and secure energy system. The residential sector represents, on average, 18.6% of the total final energy consumption in the OECD countries in 2018, reaching 29.5% in the UK (IEA, 2020a). Using a staggered differences-in-differences approach with dynamic treatment effects, we analyse changes in residential gas consumption five years before and after the adoption of energy efficiency measures. The analysis includes energy efficiency interventions involving the installation of new heating-related insulation equipment—i.e., of loft insulation and cavity walls, supported by energy efficiency programmes in England and Wales between 2005 and 2017—using a panel of 55,154 households from the National Energy Efficiency Data-Framework (NEED). We control for, among other factors, energy prices and the extent to which gas consumption changes are dependent on household characteristics and variations in weather conditions. Our results indicate that the adoption of EE measures is associated with significant reductions in household residential gas consumption one year after their implementation. However, the effect does not last in the long run and energy savings disappear four years after the retrofitting of cavity wall insulation measures and after two years following the installation of loft insulation. The disappearance of energy savings in the longer run could be explained by the energy performance gap, the rebound effect and/or by concurrent residential construction projects and renovations associated with increases in energy consumption. Notably, for households in deprived areas, the installation of these efficiency measures does not deliver energy savings. These results confirm the existence of effects that reduce the energy savings from the adoption of these efficiency technologies over time and indicates that, for some groups, these net savings do not seem to materialize.Cambridge Social Sciences and Humanities Grant Schem
Systematic review of the outcomes and trade-offs of ten types of decarbonization policy instruments
The literature evaluating the technical and socio-economic outcomes of policy instruments used to support the transition to low-carbon economies is neither easily accessible nor comparable, and often provides conflicting results. We develop and implement a framework to systematically review and synthesize the impact of ten types of decarbonisation policy instruments on seven technical and socio-economic outcomes. Our systematic review shows that the selected types of regulatory and economic and financial instruments are generally associated with positive impacts on environmental, technological, and innovation outcomes. Several instruments are often associated with short-term negative impacts on competitiveness and distributional outcomes. We discuss how these trade-offs can be reduced or transformed into co-benefits by designing R&D and government procurement, deployment policies, carbon pricing and trading. We show how specific design features can promote competitiveness and reduce negative distributional impacts, particularly for small firms. An online interactive Decarbonisation Policy Evaluation Tool allows further analysis of the evidence.H2020 Framework European Commissio
Detección y cuantificación de la expresión génica de bacterias anaerobias asociadas con biocorrosión en instalaciones petroleras
El agua de producción es generada durante los procesos de explotación de los yacimientos petroleros. Ésta puede ser tratada y re-inyectada a los yacimientos maduros para la recuperación mejorada de hidrocarburos (EOR por sus siglas en inglés – Enhanced Oil Recovery). La inyección de agua es una estrategia común dentro de los procesos EOR, suministra presión y ayuda a empujar y barrer el aceite remanente en la roca para dirigirlo a los pozos productores. El mantenimiento de la calidad del agua de producción evita grandes pérdidas económicas en el proceso de explotación, con esta medida se evita la degradación del hidrocarburo y el amargamiento del gas y del aceite en los yacimientos, y se controla la biocorrosión en las instalaciones petroleras propiciada por microorganismos. El gen dsrAB codifica la subunidad alfa y beta de la sulfito-reductasa desasimilatoria, implicada en la respiración por sulfato de las bacterias reductoras de sulfato (BSR). El gen nifD codifica la subunidad alfa de la nitrogenasa para la fijación de nitrógeno, proceso acoplado a la reducción de Fe (III). El objetivo de este estudio fue conocer las comunidades bacterianas que habitan aguas de producción con alta salinidad, y que están involucradas con la biocorrosión de instalaciones petroleras marinas, a través de la obtención de secuencias de genes funcionales, como dsrAB y nifD de los órdenes Desulfovibrionales, Desulfobacterales y Desulfuromonadales. Adicionalmente, se cuantificó la expresión génica de dsrA en agua congénita de yacimientos petroleros con alta temperatura. Se obtuvieron cinco librerías de clonas con las secuencias adquiridas de diferentes muestras de agua de producción, con y sin dosificación de biocida. Los análisis filogenéticos con las secuencias dsrAB mostraron a las BSR Desulfomicrobium, Desulfovibrio y Desulfohalobium, así como Desulfococcus, Desulfosarcina, Desulfobacter, Desulfobacterium y Desulfobulbus. El análisis del gen nifD mostró a las bacterias reductoras de Fe (III) (Desulfuromonadales): Desulfuromusa, Pelobacter, Malonomonas, y Desulfuromonas. La abundancia relativa en todas las aguas de producción fue: Desulfovibrionales representado por un 55.28% de las clonas analizadas, Desulfobacterales por 26.83%, y 17.89% para el orden Desulfuromonadales. La diversidad calculada por el índice Shannon (H’), mostró valores similares entre todas las muestras de agua de producción analizadas. Hubo dominancia del taxón Desulfovibrio en una de las aguas de producción con biocida. Los niveles de transcripción del gen dsrA del orden Desulfovibrionales se cuantificaron en sistemas incubados a 40ºC y 60ºC con salinidad aproximada de 100 g/L NaCl. Se generaron tres librerías de clonas que mostraron a Desulfovibrio, Desulfomicrobium, Desulfohalobium y Desulfonatronum (Desulfovibrionales) y a Desulfosarcina y Desulfobulbus (Desulfobacterales). En los sistemas a 60ºC con alta salinidad se detectaron BSR no cultivables. La expresión de dsrA se abatió sustancialmente cuando los sistemas fueron desarrollados en salinidad de agua de mar, lo que sugirió que la reducción de sulfato sucede en el agua congénita del yacimiento a altas concentraciones de NaCl. Los hallazgos de este estudio proveen información importante sobre la diversidad y la actividad de BSR halófilas, y que son habitantes comunes del agua asociada a los yacimientos petroleros
The classification of public research organizations: Taxonomical explorations
AbstractThis article addresses, conceptually and empirically, the classification of public research organizations (PROs) understood as non-university and non-enterprise research-focused organizations that are public by nature or in which the government has an influence. The construction of archetypes of research performing organizations has been a standard method of analysis, as reflected in the Frascati Manual that guides national statistical offices to delineate the perimeter of the institutional sector of PROs. However, this practice has often overlooked the emergence of new types because traditional approaches to classification tend to characterize previously defined mutually exclusive categories, rather than allow evidence to reveal categories ex-post. This gives rise to a number of concerns related to the scientific validity of the classification of entities in the organizational field of research. The present article discusses conceptual and methodological issues associated with different classificatory strategies. It also presents the empirical results of a taxonomical exploration that allows the identification of categories not determined ex-ante. Our empirical strategy consists in applying clustering techniques on a number of organizational dimensions, chosen based on theoretical grounds and proxied by variables determined by data availability. We implement it on a pilot dataset of 197 research-focused organizations from eight different European countries.This study has been supported by the European Union, under the 7th
Framework Programme (grant agreement no. 313082) and the Spanish
Ministry of Economy, Industry and Competitiveness (grant CSO2016-79045-C2-1-R)
C2-1-R)
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Economic modelling fit for the demands of energy decision makers
Decision makers need sector-specific, policy-focused, dynamic economic models with rich representations of technological progress. These allow them to understand how the energy transition is likely to unfold with different policies and what its impacts might be. A new generation of models is emerging to meet these demands, but more action is needed
Bisulfite reductase gene expression of thermophilic sulphate-reducing bacteria from saline connate water of oil reservoirs with high temperature
Endocannabinoid long-term depression revealed at medial perforant path excitatory synapses in the dentate gyrus
The endocannabinoid system modulates synaptic plasticity in the hippocampus, but a link between long-term synaptic plasticity and the type 1 cannabinoid (CB1) receptor at medial perforant path (MPP) synapses remains elusive. Here, immuno-electron microscopy in adult mice showed that similar to 26% of the excitatory synaptic terminals in the middle 1/3 of the dentate molecular layer (DML) contained CB1 receptors, and field excitatory postsynaptic potentials evoked by MPP stimulation were inhibited by CB1 receptor activation. In addition, MPP stimulation at 10 Hz for 10 min triggered CB, receptor-dependent excitatory long-term depression (eCB-eLTD) at MPP synapses of wild-type mice but not on CB1-knockout mice. This eCB-eLTD was group I mGluR-dependent, required intracellular calcium influx and 2-arachydonoyl-glycerol (2-AG) synthesis but did not depend on N-methyl-d-aspartate (NMDA) receptors. Overall, these results point to a functional role for CB1 receptors with eCB-eLTD at DML MPP synapses and further involve these receptors in memory processing within the adult brain.We thank all members of P. Grandes laboratory for their helpful comments, suggestions, and discussions during the performance of this study. The authors thank Giovanni Marsicano (INSERM, U1215 Neurocentre Magendie, Endocannabinoids and Neuroadaptation, Bordeaux, France. University de Bordeaux, France), Beat Lutz (Institute of Physiological Chemistry and German Resilience Center, University Medical Center of the Johannes Gutenberg University Mainz, Germany) and Susana Mato (Achucarro Basque Center for Neuroscience, Science Park of the UPV/EHU, Leioa, Vizcaya, Spain) for providing the CB1 receptor knock-out mice. This work was supported by MINECO/FEDER, UE (grant number SAF2015-65034-R to PG); The Basque Government (grant number BCG IT764-13 to PG); Red de Trastornos Adictivos, Instituto de Salud Carlos III (ISC-III) and European Regional Development Funds-European Union (ERDF-EU; grant RD16/0017/0012 to PG); PhD contract from MINECO (BES-2013-065057 to SP); Vanier Canada Graduate Scholarship (NSERC to CJF)