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- Fazey, Ioan, et al.
(författare)
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Transforming knowledge systems for life on Earth : Visions of future systems and how to get there
- 2020
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Ingår i: Energy Research & Social Science. - : Elsevier. - 2214-6296 .- 2214-6326. ; 70
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Tidskriftsartikel (refereegranskat)abstract
- Formalised knowledge systems, including universities and research institutes, are important for contemporary societies. They are, however, also arguably failing humanity when their impact is measured against the level of progress being made in stimulating the societal changes needed to address challenges like climate change. In this research we used a novel futures-oriented and participatory approach that asked what future envisioned knowledge systems might need to look like and how we might get there. Findings suggest that envisioned future systems will need to be much more collaborative, open, diverse, egalitarian, and able to work with values and systemic issues. They will also need to go beyond producing knowledge about our world to generating wisdom about how to act within it. To get to envisioned systems we will need to rapidly scale methodological innovations, connect innovators, and creatively accelerate learning about working with intractable challenges. We will also need to create new funding schemes, a global knowledge commons, and challenge deeply held assumptions. To genuinely be a creative force in supporting longevity of human and non-human life on our planet, the shift in knowledge systems will probably need to be at the scale of the enlightenment and speed of the scientific and technological revolution accompanying the second World War. This will require bold and strategic action from governments, scientists, civic society and sustained transformational intent.
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| 2. |
- Eichenlaub, Manuel, et al.
(författare)
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Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems
- 2024
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Ingår i: Diabetes Technology & Therapeutics. - : Mary Ann Liebert. - 1520-9156 .- 1557-8593. ; 26:4, s. 263-275
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Tidskriftsartikel (refereegranskat)abstract
- Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC), that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels is suggested that enables the collection of comparator data with these characteristics. This work is an important step towards establishing a future standard for the performance evaluation of CGM systems.
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| 3. |
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| 4. |
- Heydari, Azim, et al.
(författare)
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A New Combined PV Output Power Forecasting Model Based on Optimized LSTM Network
- 2023
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Ingår i: 2023 IEEE IAS Global Conference on Emerging Technologies, GlobConET 2023. - : Institute of Electrical and Electronics Engineers (IEEE).
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Konferensbidrag (refereegranskat)abstract
- One of the most challenging problems in designing and implementing effective management strategies and demand responses in renewable-rich grids is the uncertainty associated with the power output (PO) of solar photovoltaic (PV) systems. The exact and trustworthy prediction of PV power can provide substantial decision support for planning and operating power systems. This paper develops an intelligent PV output power (PV-OP) forecasting model. The proposed PV-OP forecasting model consists of an Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) signal decomposition model to decompose the original PV output power signal to different frequencies, LSTM neural network as a main forecaster engine, and multi-objective NSGA-II optimization algorithm as a hyperparameters optimizer. The developed PV power forecasting model was validated using the PV power datasets of an off-grid village located in Chalokwa, Zambia. The obtained results confirmed the performance and accuracy of the proposed PV output power forecasting model.
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| 6. |
- Murray, Alison E., et al.
(författare)
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Roadmap for naming uncultivated Archaea and Bacteria
- 2020
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Ingår i: Nature Microbiology. - : NATURE PUBLISHING GROUP. - 2058-5276. ; 5:8, s. 987-994
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Tidskriftsartikel (refereegranskat)abstract
- The assembly of single-amplified genomes (SAGs) and metagenome-assembled genomes (MAGs) has led to a surge in genome-based discoveries of members affiliated with Archaea and Bacteria, bringing with it a need to develop guidelines for nomenclature of uncultivated microorganisms. The International Code of Nomenclature of Prokaryotes (ICNP) only recognizes cultures as 'type material', thereby preventing the naming of uncultivated organisms. In this Consensus Statement, we propose two potential paths to solve this nomenclatural conundrum. One option is the adoption of previously proposed modifications to the ICNP to recognize DNA sequences as acceptable type material; the other option creates a nomenclatural code for uncultivated Archaea and Bacteria that could eventually be merged with the ICNP in the future. Regardless of the path taken, we believe that action is needed now within the scientific community to develop consistent rules for nomenclature of uncultivated taxa in order to provide clarity and stability, and to effectively communicate microbial diversity. In this Consensus Statement, the authors discuss the issue of naming uncultivated prokaryotic microorganisms, which currently do not have a formal nomenclature system due to a lack of type material or cultured representatives, and propose two recommendations including the recognition of DNA sequences as type material.
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| 7. |
- Stridh, Bengt, Universitetslektor, 1957-, et al.
(författare)
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Uncertainties in Yield Assessments and PV LCOE : Report IEA-PVPS T13-18:2020 November 2020
- 2020
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- Yield assessments (YA) and Long-Term Yield Predictions (LTYP) are a prerequisite for business decisions on long term investments into photovoltaic (PV) power plants. Together with cost data (CAPEX, OPEX and discount rate), the output of a YA and LTYP (utilisation rate, performance loss rate and lifetime) provides to the financial investors the parameters needed for the calculation of the Levelised Cost of Electricity (LCOE) and to assess the cash flow model of an investment with relative Internal Rate of Return (IRR) and Net Present Value (NPV).YA and LTYP outputs should be provided with a related exceedance probability. This gives the right tool to stakeholders involved in PV projects to take the best decision in terms of riskaversion. A reduction in the uncertainty of the energy yield can lead to higher values for a given exceedance probability and hence a stronger business case. Various efforts in the literature show the importance of having a common framework that can assess the impact of technical risks on the economic performance of a PV project.The most important parameter influencing the energy yield assessment is the site-specific insolation. Several aspects need to be considered: reliability of the database, interannual variability, long term trends.Site adaptation techniques combine short-term measured data and long-term satellite estimates. Short periods of measured data but with site-specific seasonal and diurnal characteristics are combined with satellite-derived data having a long period of record with not necessarily site-specific characteristics. Upon completion of the measurement campaign, which is typically around one-year, different methodologies can be applied between the measured data at the target site, spanning a relatively short period, and the satellite data, spanning a much longer period. The complete record of satellite data is then used in this relationship to predict the long-term solar resource at the target site. Assuming a strong correlation, the strengths of both data sets are captured and the uncertainty in the long-term estimate can be reduced. In Müller et al [1] an analysis on long-term trends for measured in-plane irradiance, Performance Ratio and energy yield for 44 rooftop installations in Germany was performed showing an average increase of in-plane irradiance of 1.1 %/year or about 11 %/decade over the period 2008 to 2018 for these systems. The increase in irradiance was especially higher than the observed Performance Loss Rate so that the energy yields of the systems analysed increased over the years with an average trend of 0.3 %/year. The typical output of Yield Assessments should report the contribution to each derating factor, starting from the Global Horizontal Irradiation to the energy injected in the grid. The starting point of PR = 100 is considered after applying the horizon shading as this become the annual insolation seen by the PV modules. The following table shows a best practice in providing an overview of gains/losses along each modelling step and the related uncertainty. The uncertainty related to each modelling step can be provided already referred to the irradiation/yield value or to the parameter that is modelled. The value in the table for the specific yield (including its uncertainty) is to be understood as an average value over the entire operating period. The possible deviations between the yields for individual recorded years and the specific yield calculated can be assessed by including interannual variability. For example, for temperature-dependent losses, the value of uncertainty could be referred to the temperature variability of the profile used in the assessment or to the temperature model used in the assessment. The ambient temperature variability and the various temperature models will lead to a different contribution in terms of yield loss and in terms of uncertainty.An emerging challenge in YAs is also due to the deployment of novel technologies (e.g. bifacial PV modules) with a contribution in terms of uncertainty that needs to be properly assessed.Building upon the knowledge available in the literature and the previous IEA PVPS Task 13 report [2], in this report we have moved forward from the uncertainty framework in yield assessment to two real implementations of it and the impact that uncertainties can have on lifetime yield predictions, on the LCOE and on the cash-flow.One of the most relevant question that we have tried to answer is also the following: How reliable are YA’s?This is an apparently simple question; however, the answer is not equally simple. Typically, investors require one YA. In some cases, more YAs might be requested if results are unclear. The various YAs can be averaged to assign a purchase value to a given project. In any case the question remains unanswered: why different assessors obtain different answers? Is one YA more reliable than others?
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