| 1. |
- Fazey, Ioan, et al.
(author)
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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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In: Energy Research & Social Science. - : Elsevier. - 2214-6296 .- 2214-6326. ; 70
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Journal article (peer-reviewed)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. |
- Duncanson, Laura, et al.
(author)
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Aboveground biomass density models for NASA's Global Ecosystem Dynamics Investigation (GEDI) lidar mission
- 2022
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In: Remote Sensing of Environment. - : Elsevier BV. - 0034-4257 .- 1879-0704. ; 270
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Journal article (peer-reviewed)abstract
- NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.
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| 3. |
- Ahmad, Amais, et al.
(author)
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IMI – Oral biopharmaceutics tools project – Evaluation of bottom-up PBPK prediction success part 4 : Prediction accuracy and software comparisons with improved data and modelling strategies
- 2020
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In: European journal of pharmaceutics and biopharmaceutics. - : Elsevier BV. - 0939-6411 .- 1873-3441. ; 156, s. 50-63
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Journal article (peer-reviewed)abstract
- Oral drug absorption is a complex process depending on many factors, including the physicochemical properties of the drug, formulation characteristics and their interplay with gastrointestinal physiology and biology. Physiological-based pharmacokinetic (PBPK) models integrate all available information on gastro-intestinal system with drug and formulation data to predict oral drug absorption. The latter together with in vitro-in vivo extrapolation and other preclinical data on drug disposition can be used to predict plasma concentration-time profiles in silico. Despite recent successes of PBPK in many areas of drug development, an improvement in their utility for evaluating oral absorption is much needed. Current status of predictive performance, within the confinement of commonly available in vitro data on drugs and formulations alongside systems information, were tested using 3 PBPK software packages (GI-Sim (ver.4.1), Simcyp® Simulator (ver.15.0.86.0), and GastroPlusTM (ver.9.0.00xx)). This was part of the Innovative Medicines Initiative (IMI) Oral Biopharmaceutics Tools (OrBiTo) project.Fifty eight active pharmaceutical ingredients (APIs) were qualified from the OrBiTo database to be part of the investigation based on a priori set criteria on availability of minimum necessary information to allow modelling exercise. The set entailed over 200 human clinical studies with over 700 study arms. These were simulated using input parameters which had been harmonised by a panel of experts across different software packages prior to conduct of any simulation. Overall prediction performance and software packages comparison were evaluated based on performance indicators (Fold error (FE), Average fold error (AFE) and absolute average fold error (AAFE)) of pharmacokinetic (PK) parameters.On average, PK parameters (Area Under the Concentration-time curve (AUC0-tlast), Maximal concentration (Cmax), half-life (t1/2)) were predicted with AFE values between 1.11 and 1.97. Variability in FEs of these PK parameters was relatively high with AAFE values ranging from 2.08 to 2.74. Around half of the simulations were within the 2-fold error for AUC0-tlast and around 90% of the simulations were within 10-fold error for AUC0-tlast. Oral bioavailability (Foral) predictions, which were limited to 19 APIs having intravenous (i.v.) human data, showed AFE and AAFE of values 1.37 and 1.75 respectively. Across different APIs, AFE of AUC0-tlast predictions were between 0.22 and 22.76 with 70% of the APIs showing an AFE > 1. When compared across different formulations and routes of administration, AUC0-tlast for oral controlled release and i.v. administration were better predicted than that for oral immediate release formulations. Average predictive performance did not clearly differ between software packages but some APIs showed a high level of variability in predictive performance across different software packages. This variability could be related to several factors such as compound specific properties, the quality and availability of information, and errors in scaling from in vitro and preclinical in vivo data to human in vivo behaviour which will be explored further. Results were compared with previous similar exercise when the input data selection was carried by the modeller rather than a panel of experts on each in vitro test. Overall, average predictive performance was increased as reflected in smaller AAFE value of 2.8 as compared to AAFE value of 3.8 in case of previous exercise.
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| 4. |
- Bermo, Mohammed, et al.
(author)
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Utility of SPECT Functional Neuroimaging of Pain
- 2021
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In: Frontiers in Psychiatry. - : Frontiers Media SA. - 1664-0640. ; 12
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Journal article (peer-reviewed)abstract
- Functional neuroimaging modalities vary in spatial and temporal resolution. One major limitation of most functional neuroimaging modalities is that only neural activation taking place inside the scanner can be imaged. This limitation makes functional neuroimaging in many clinical scenarios extremely difficult or impossible. The most commonly used radiopharmaceutical in Single Photon Emission Tomography (SPECT) functional brain imaging is Technetium 99 m-labeled Ethyl Cysteinate Dimer (ECD). ECD is a lipophilic compound with unique pharmacodynamics. It crosses the blood brain barrier and has high first pass extraction by the neurons proportional to regional brain perfusion at the time of injection. It reaches peak activity in the brain 1 min after injection and is then slowly cleared from the brain following a biexponential mode. This allows for a practical imaging window of 1 or 2 h after injection. In other words, it freezes a snapshot of brain perfusion at the time of injection that is kept and can be imaged later. This unique feature allows for designing functional brain imaging studies that do not require the patient to be inside the scanner at the time of brain activation. Functional brain imaging during severe burn wound care is an example that has been extensively studied using this technique. Not only does SPECT allow for imaging of brain activity under extreme pain conditions in clinical settings, but it also allows for imaging of brain activity modulation in response to analgesic maneuvers whether pharmacologic or non-traditional such as using virtual reality analgesia. Together with its utility in extreme situations, SPECTS is also helpful in investigating brain activation under typical pain conditions such as experimental controlled pain and chronic pain syndromes.
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| 5. |
- Denault, Vincent, et al.
(author)
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The Analysis of Nonverbal Communication: The Dangers of Pseudoscience in Security and Justice Contexts : Análisis de la comunicación no verbal: los peligros de la pseudociencia en entornos de seguridad y justicia
- 2020
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In: Anuario de Psicología Jurídica. - : Colegio Oficial de la Psicologia de Madrid. - 1133-0740 .- 2174-0542. ; 30:1, s. 1-12
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Research review (peer-reviewed)abstract
- For security and justice professionals (e.g., police officers, lawyers, judges), the thousands of peer-reviewed articles on nonverbal communication represent important sources of knowledge. However, despite the scope of the scientific work carried out on this subject, professionals can turn to programs, methods, and approaches that fail to reflect the state of science. The objective of this article is to examine (i) concepts of nonverbal communication conveyed by these programs, methods, and approaches, but also (ii) the consequences of their use (e.g., on the life or liberty of individuals). To achieve this objective, we describe the scope of scientific research on nonverbal communication. A program (SPOT; Screening of Passengers by Observation Techniques), a method (the BAI; Behavior Analysis Interview) and an approach (synergology) that each run counter to the state of science are examined. Finally, we outline five hypotheses to explain why some organizations in the fields of security and justice are turning to pseudoscience and pseudoscientific techniques. We conclude the article by inviting these organizations to work with the international community of scholars who have scientific expertise in nonverbal communication and lie (and truth) detection to implement evidence-based practices.
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| 6. |
- Ekström, Andreas, 1979, et al.
(author)
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Impairing cardiac oxygen supply in swimming coho salmon compromises their heart function and tolerance to acute warming.
- 2023
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In: Scientific reports. - 2045-2322. ; 13:1
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Journal article (peer-reviewed)abstract
- Climatic warming elevates mortality for many salmonid populations during their physically challenging up-river spawning migrations, yet, the mechanisms underlying the increased mortality remain elusive. One hypothesis posits that a cardiac oxygen insufficiency impairs the heart's capacity to pump sufficient oxygen to body tissues to sustain up-river swimming, especially in warm water when oxygen availability declines and cardiac and whole-animal oxygen demand increases. We tested this hypothesis by measuring cardiac and metabolic (cardiorespiratory) performance, and assessing the upper thermal tolerance of coho salmon (Oncorhynchus kisutch) during sustained swimming and acute warming. By surgically ligating the coronary artery, which naturally accumulates arteriosclerotic lesions in migrating salmon, we partially impaired oxygen supply to the heart. Coronary ligation caused drastic cardiac impairment during swimming, even at benign temperatures, and substantially constrained cardiorespiratory performance during swimming and progressive warming compared to sham-operated control fish. Furthermore, upper thermal tolerance during swimming was markedly reduced (by 4.4°C) following ligation. While the cardiorespiratory capacity of female salmon was generally lower at higher temperatures compared to males, upper thermal tolerance during swimming was similar between sexes within treatment groups. Cardiac oxygen supply is a crucial determinant for the migratory capacity of salmon facing climatic environmental warming.
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| 7. |
- Galaz, Victor, et al.
(author)
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Artificial intelligence, systemic risks, and sustainability
- 2021
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In: Technology in society. - : Elsevier BV. - 0160-791X .- 1879-3274. ; 67
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Journal article (peer-reviewed)abstract
- Automated decision making and predictive analytics through artificial intelligence, in combination with rapid progress in technologies such as sensor technology and robotics are likely to change the way individuals, communities, governments and private actors perceive and respond to climate and ecological change. Methods based on various forms of artificial intelligence are already today being applied in a number of research fields related to climate change and environmental monitoring. Investments into applications of these technologies in agriculture, forestry and the extraction of marine resources also seem to be increasing rapidly. Despite a growing interest in, and deployment of AI-technologies in domains critical for sustainability, few have explored possible systemic risks in depth. This article offers a global overview of the progress of such technologies in sectors with high impact potential for sustainability like farming, forestry and the extraction of marine resources. We also identify possible systemic risks in these domains including a) algorithmic bias and allocative harms; b) unequal access and benefits; c) cascading failures and external disruptions, and d) trade-offs between efficiency and resilience. We explore these emerging risks, identify critical questions, and discuss the limitations of current governance mechanisms in addressing AI sustainability risks in these sectors.
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| 8. |
- Gebresenbet, Girma, et al.
(author)
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A concept for application of integrated digital technologies to enhance future smart agricultural systems
- 2023
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In: Smart Agricultural Technology. - : Elsevier. - 2772-3755. ; 5
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Journal article (peer-reviewed)abstract
- Future agricultural systems should increase productivity and sustainability of food production and supply. For this, integrated and efficient capture, management, sharing, and use of agricultural and environmental data from multiple sources is essential. However, there are challenges to understand and efficiently use different types of agricultural and environmental data from multiple sources, which differ in format and time interval. In this regard, the role of emerging technologies is considered to be significant for integrated data gathering, analyses and efficient use. In this study, a concept was developed to facilitate the full integration of digital technologies to enhance future smart and sustainable agricultural systems. The concept has been developed based on the results of a literature review and diverse experiences and expertise which enabled the identification of stat-of-the-art smart technologies, challenges and knowledge gaps. The features of the proposed solution include: data collection methodologies using smart digital tools; platforms for data handling and sharing; application of Artificial Intelligent for data integration and analysis; edge and cloud computing; application of Blockchain, decision support system; and a governance and data security system. The study identified the potential positive implications i.e. the implementation of the concept could increase data value, farm productivity, effectiveness in monitoring of farm operations and decision making, and provide innovative farm business models. The concept could contribute to an overall increase in the competitiveness, sustainability, and resilience of the agricultural sector as well as digital transformation in agriculture and rural areas. This study also provided future research direction in relation to the proposed concept. The results will benefit researchers, practitioners, developers of smart tools, and policy makers supporting the transition to smarter and more sustainable agriculture systems.
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| 9. |
- Leard, Lorriana E., et al.
(author)
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Consensus document for the selection of lung transplant candidates: An update from the International Society for Heart and Lung Transplantation
- 2021
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In: Journal of Heart and Lung Transplantation. - : Elsevier BV. - 1053-2498 .- 1557-3117. ; 40, s. 1349-1379
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Journal article (peer-reviewed)abstract
- Tens of thousands of patients with advanced lung diseases may be eligible to be considered as potential candidates for lung transplant around the world each year. The timing of referral, evaluation, determination of candidacy, and listing of candidates continues to pose challenges and even ethical dilemmas. To address these challenges, the International Society for Heart and Lung Transplantation appointed an international group of members to review the literature, to consider recent advances in the management of advanced lung diseases, and to update prior consensus documents on the selection of lung transplant candidates. The purpose of this updated consensus document is to assist providers throughout the world who are caring for patients with pulmonary disease to identify potential candidates for lung transplant, to optimize the timing of the referral of these patients to lung transplant centers, and to provide transplant centers with a framework for evaluating and selecting candidates. In addition to addressing general considerations and providing disease specific recommendations for referral and listing, this updated consensus document includes an ethical framework, a recognition of the variability in acceptance of risk between transplant centers, and establishes a system to account for how a combination of risk factors may be taken into consideration in candidate selection for lung transplantation.
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