pmid: 34714662
pmc: PMC8630795
A detailed TDDFT study (with all-electron STO-TZ2P basis sets and the COSMO solvation model) has been carried out on the effect of diprotonation on the UV-vis-NIR spectra of free-base tetraphenylporphyrin and tetrakis(
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doi: 10.1785/0220160120
The collection of earthquake testimonies (i.e., qualitative descriptions of felt shaking) is essential for macroseismic studies (i.e., studies gathering information on how strongly an earthquake was felt in different places), and when done rapidly and systematically, improves situational awareness and in turn can contribute to efficient emergency response. In this study, we present advances made in the collection of testimonies following earthquakes around the world using a thumbnail‐based questionnaire implemented on the European‐Mediterranean Seismological Centre (EMSC) smartphone app and its website compatible for mobile devices. In both instances, the questionnaire consists of a selection of thumbnails, each representing an intensity level of the European Macroseismic Scale 1998. We find that testimonies are collected faster, and in larger numbers, by way of thumbnail‐based questionnaires than by more traditional online questionnaires. Responses were received from all seismically active regions of our planet, suggesting that thumbnails overcome language barriers. We also observed that the app is not sufficient on its own, because the websites are the main source of testimonies when an earthquake strikes a region for the first time in a while; it is only for subsequent shocks that the app is widely used. Notably though, the speed of the collection of testimonies increases significantly when the app is used. We find that automated EMSC intensities as assigned by user‐specified thumbnails are, on average, well correlated with “Did You Feel It?” (DYFI) responses and with the three independently and manually derived macroseismic datasets, but there is a tendency for EMSC to be biased low with respect to DYFI at moderate and large intensities. We address this by proposing a simple adjustment that will be verified in future earthquakes. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Published version
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citations | 31 | |
popularity | Top 10% | |
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FAIR principles have become reference criteria for promoting and evaluating openness of scientific data and for improving datasets Findability, Accessibility, Interoperability and Reusability. This also applies to Research Infrastructures (RIs) in the solid Earth domain committed to provide access to seismological data, ground deformations inferred from terrestrial and satellite observations, geological maps and laboratory experiments. Such RIs are indeed committed since a long time, well before the appearance of FAIR principles, to engage scientific communities involved in data collection, standardization and quality control as well as in implementing metadata and services for qualification, storage and accessibility. By addressing open science and managing scientific data, they are working to adopt FAIR principles, thus having the onerous task of turning these principles into practices. In this work we argue that although FAIR principles have the merit of creating a common background of knowledge to engage communities in providing data in a standard way thus easing interoperability and data sharing, in order to make the adoption of FAIR principles less onerous there is an urgent need of clear models, reference architectures and technical guidelines which can support RI implementers in the realization of FAIR data provision systems. We therefore discuss the state of the art of FAIR principles ecosystem and open new perspectives by discussing a four-stages roadmap that reorganizes FAIR principles in a way that better fits to the approach of RI implementers, and a FAIR adoption process that relates FAIR principles to technologies for their implementation.
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gold |
citations | 10 | |
popularity | Top 10% | |
influence | Average | |
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Virtual Research Environments (VREs), also known as science gateways or virtual laboratories, assist researchers in data science by integrating tools for data discovery, data retrieval, workflow management and researcher collaboration, often coupled with a specific computing infrastructure. Recently, the push for better open data science has led to the creation of a variety of dedicated research infrastructures (RIs) that gather data and provide services to different research communities, all of which can be used independently of any specific VRE. There is therefore a need for generic VREs that can be coupled with the resources of many different RIs simultaneously, easily customised to the needs of specific communities. The resource metadata produced by these RIs rarely all adhere to any one standard or vocabulary however, making it difficult to search and discover resources independently of their providers without some translation into a common framework. Cross-RI search can be expedited by using mapping services that harvest RI-published metadata to build unified resource catalogues, but the development and operation of such services pose a number of challenges. In this paper, we discuss some of these challenges and look specifically at the VRE4EIC Metadata Portal, which uses X3ML mappings to build a single catalogue for describing data products and other resources provided by multiple RIs. The Metadata Portal was built in accordance to the e-VRE Reference Architecture, a microservice-based architecture for generic modular VREs, and uses the CERIF standard to structure its catalogued metadata. We consider the extent to which it addresses the challenges of cross-RI search, particularly in the environmental and earth science domain, and how it can be further augmented, for example to take advantage of linked vocabularies to provide more intelligent semantic search across multiple domains of discourse.
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handle: 2158/1237968
Abstract We present a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) and Multi Temporal (MT) InSAR measurements for investigating the Stromboli volcano (Italy) deformation phenomena. In particular, we focus our analysis on three periods: a) the time interval following the 2014 flank eruption, b) the July–August 2019 eruption and c) the following post-eruptive phase. To do this, we take advantage from an unprecedented set of space-borne and ground-based SAR data collected from April 2015 up to November 2019 along two (one ascending and one descending) Sentinel-1 (S-1) tracks, as well as, in the same period, by two ground-based systems installed along the Sciara del Fuoco northern rim. Such data availability permitted us to first characterize the volcano long-term 3D deformation behavior of the pre-eruptive period (April 2015–June 2019), by jointly inverting the space-borne and ground-based InSAR measurements. Then, the GB-SAR measurements allowed us to investigate the sin-eruptive time span (3rd July 2019 – 30th August 2019) which revealed rapid deformation episodes (e.g. more than 30 mm/h just 2 min before the 3rd July 2019 explosion) associated with the eruptive activity, that cannot be detected with the weekly S-1 temporal sampling. Finally, the S-1 measurements permitted to better constrain the post 2019 eruption deformations (31st August 2019 – 5th November 2019), which are mainly located outside the GB-SAR sensed area. The presented results demonstrate the effectiveness of the joint exploitation of the InSAR measurements obtained through satellite and terrestrial SAR systems, highlighting their strong complementarity to map and interpret the deformation phenomena affecting volcanic areas.
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citations | 35 | |
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influence | Top 10% | |
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Procedures on how data will be collected, processed or generated within the project.
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Report on specification and documentation of web service interface for geological TCS
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This deliverable will have two additional releases, for internal use only, at month 6 and 30
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pmid: 34714662
pmc: PMC8630795
A detailed TDDFT study (with all-electron STO-TZ2P basis sets and the COSMO solvation model) has been carried out on the effect of diprotonation on the UV-vis-NIR spectra of free-base tetraphenylporphyrin and tetrakis(
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bronze |
citations | 13 | |
popularity | Top 10% | |
influence | Average | |
impulse | Top 10% |
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This deliverable will have a first release, for internal use only, at month 24.
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doi: 10.1785/0220160120
The collection of earthquake testimonies (i.e., qualitative descriptions of felt shaking) is essential for macroseismic studies (i.e., studies gathering information on how strongly an earthquake was felt in different places), and when done rapidly and systematically, improves situational awareness and in turn can contribute to efficient emergency response. In this study, we present advances made in the collection of testimonies following earthquakes around the world using a thumbnail‐based questionnaire implemented on the European‐Mediterranean Seismological Centre (EMSC) smartphone app and its website compatible for mobile devices. In both instances, the questionnaire consists of a selection of thumbnails, each representing an intensity level of the European Macroseismic Scale 1998. We find that testimonies are collected faster, and in larger numbers, by way of thumbnail‐based questionnaires than by more traditional online questionnaires. Responses were received from all seismically active regions of our planet, suggesting that thumbnails overcome language barriers. We also observed that the app is not sufficient on its own, because the websites are the main source of testimonies when an earthquake strikes a region for the first time in a while; it is only for subsequent shocks that the app is widely used. Notably though, the speed of the collection of testimonies increases significantly when the app is used. We find that automated EMSC intensities as assigned by user‐specified thumbnails are, on average, well correlated with “Did You Feel It?” (DYFI) responses and with the three independently and manually derived macroseismic datasets, but there is a tendency for EMSC to be biased low with respect to DYFI at moderate and large intensities. We address this by proposing a simple adjustment that will be verified in future earthquakes. NRF (Natl Research Foundation, S’pore) MOE (Min. of Education, S’pore) Published version
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citations | 31 | |
popularity | Top 10% | |
influence | Top 10% | |
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FAIR principles have become reference criteria for promoting and evaluating openness of scientific data and for improving datasets Findability, Accessibility, Interoperability and Reusability. This also applies to Research Infrastructures (RIs) in the solid Earth domain committed to provide access to seismological data, ground deformations inferred from terrestrial and satellite observations, geological maps and laboratory experiments. Such RIs are indeed committed since a long time, well before the appearance of FAIR principles, to engage scientific communities involved in data collection, standardization and quality control as well as in implementing metadata and services for qualification, storage and accessibility. By addressing open science and managing scientific data, they are working to adopt FAIR principles, thus having the onerous task of turning these principles into practices. In this work we argue that although FAIR principles have the merit of creating a common background of knowledge to engage communities in providing data in a standard way thus easing interoperability and data sharing, in order to make the adoption of FAIR principles less onerous there is an urgent need of clear models, reference architectures and technical guidelines which can support RI implementers in the realization of FAIR data provision systems. We therefore discuss the state of the art of FAIR principles ecosystem and open new perspectives by discussing a four-stages roadmap that reorganizes FAIR principles in a way that better fits to the approach of RI implementers, and a FAIR adoption process that relates FAIR principles to technologies for their implementation.
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gold |
citations | 10 | |
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Virtual Research Environments (VREs), also known as science gateways or virtual laboratories, assist researchers in data science by integrating tools for data discovery, data retrieval, workflow management and researcher collaboration, often coupled with a specific computing infrastructure. Recently, the push for better open data science has led to the creation of a variety of dedicated research infrastructures (RIs) that gather data and provide services to different research communities, all of which can be used independently of any specific VRE. There is therefore a need for generic VREs that can be coupled with the resources of many different RIs simultaneously, easily customised to the needs of specific communities. The resource metadata produced by these RIs rarely all adhere to any one standard or vocabulary however, making it difficult to search and discover resources independently of their providers without some translation into a common framework. Cross-RI search can be expedited by using mapping services that harvest RI-published metadata to build unified resource catalogues, but the development and operation of such services pose a number of challenges. In this paper, we discuss some of these challenges and look specifically at the VRE4EIC Metadata Portal, which uses X3ML mappings to build a single catalogue for describing data products and other resources provided by multiple RIs. The Metadata Portal was built in accordance to the e-VRE Reference Architecture, a microservice-based architecture for generic modular VREs, and uses the CERIF standard to structure its catalogued metadata. We consider the extent to which it addresses the challenges of cross-RI search, particularly in the environmental and earth science domain, and how it can be further augmented, for example to take advantage of linked vocabularies to provide more intelligent semantic search across multiple domains of discourse.
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handle: 2158/1237968
Abstract We present a joint exploitation of space-borne and ground-based Synthetic Aperture Radar Interferometry (InSAR) and Multi Temporal (MT) InSAR measurements for investigating the Stromboli volcano (Italy) deformation phenomena. In particular, we focus our analysis on three periods: a) the time interval following the 2014 flank eruption, b) the July–August 2019 eruption and c) the following post-eruptive phase. To do this, we take advantage from an unprecedented set of space-borne and ground-based SAR data collected from April 2015 up to November 2019 along two (one ascending and one descending) Sentinel-1 (S-1) tracks, as well as, in the same period, by two ground-based systems installed along the Sciara del Fuoco northern rim. Such data availability permitted us to first characterize the volcano long-term 3D deformation behavior of the pre-eruptive period (April 2015–June 2019), by jointly inverting the space-borne and ground-based InSAR measurements. Then, the GB-SAR measurements allowed us to investigate the sin-eruptive time span (3rd July 2019 – 30th August 2019) which revealed rapid deformation episodes (e.g. more than 30 mm/h just 2 min before the 3rd July 2019 explosion) associated with the eruptive activity, that cannot be detected with the weekly S-1 temporal sampling. Finally, the S-1 measurements permitted to better constrain the post 2019 eruption deformations (31st August 2019 – 5th November 2019), which are mainly located outside the GB-SAR sensed area. The presented results demonstrate the effectiveness of the joint exploitation of the InSAR measurements obtained through satellite and terrestrial SAR systems, highlighting their strong complementarity to map and interpret the deformation phenomena affecting volcanic areas.