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In this technical report, we define a Secure Application Email model and protocol that works on top of existing Internet email architecture that can be used in the development of new services with enanched security. The new Secure Application Email model could represent an evolution of the current Internet email model while keeping a deep level of interoperability between the two models.

Virtual Research Environments (VREs) are "systems" specifically conceived to provide their users with a web-based set of facilities (including services, data and computational facilities) to accomplish a set of tasks by dynamically relying on the underlying infrastructure. VREs are among the key products developed and delivered by the ARIADNEplus project to support the target communities and application scenarios in archaeology. The development of VREs is based on three main activities: (i) the development of software artifacts that realise a set of functions (including those needed for accessing certain datasets), (ii) the deployment of these artifacts in an operational infrastructure following the release procedures and tools presented in the deliverable D13.1 "Software Release Procedures and Tools JRA2", and (iii) the final deployment and operation of well-defined Virtual Research Environments by exploiting the facilities offered by the underlying D4Science infrastructure and its services [1]. This deliverable D13.4 - "VREs Operation Final Activity Report'' is the updated version of D13.2 - "VREs Operation Mid-term Activity Report ''. D13.4 documents the last of the above- mentioned three activities - i.e. the exploitation of the services and technologies offered by the underlying infrastructure to serve the needs of defined scenarios - as implemented in the second period, from January 2021 to November 2022 - of the ARIADNEplus project. Specifically, it focuses on how the components have been exploited and operated to support the development of the ARIADNEplus VRE gateway https://ariadne.d4science.org, its underlying infrastructure, and the VREs from M25 (January 2021) to M47 (November 2022). These activities have been carried out within Work Package 13. Specifically in Task 13.1 Infrastructure Operation (JRA2.1) and Task 13.3 VREs Operation (JRA2.3). In addition to the 5 VREs created and operated in the first period, 3 more VREs were created and operated in the second reporting period, for a total of 8 VREs. One VRE of the second reporting period, namely ARIADNEplus Lab (cf. Section 4.6), was created in July 2021 as the virtual laboratory to support developers, researchers, data managers, and data analysts belonging to the archaeological community worldwide. The "Geoportale Nazionale per l'Archeologia (GNA)" VRE (cf. Section 4.7) was created in January 2022, as the evolution of the existing Geoportal Prototype VRE (cf. Section 4.4), which was developed for the integration, validation, harmonization, visualization, and access of archaeological georeferenced datasets collected in Italy. Finally, the Esquiline VRE (cf. Section 4.8) was created in October 2022 for the integration and display of data originating from 19th century excavations and historical cartography in a spatio-temporal database, allowing the reconstruction of the transformation of an urban landscape through the centuries. As of November 2022, the VREs are serving the needs of more than 400 users in total spread across 21 countries and more than 10.000 user sessions. This required to deal with approximately 100 tickets (59 requests for support, 9 requests for incidents and bugs, 9 requests for Virtual Machine or Container creations).

This deliverable describes the activities carried out within Work Package 15 (WP15) of the ARIADNEplus project by the different partners and describes the results achieved. The work package consists of several individual tasks and subtasks with the overall goal to develop and provide useful services to archaeologists. This means the work package is by nature heterogeneous with stand-alone tasks and services. Efforts have been made to facilitate collaboration between the individual tasks through joint work package meetings. This has resulted in new cross-task contacts being made, and some sharing of expertise to improve services has been done. A service design template aligning the ARIADNEplus services with the requirements from European Open Science Cloud (EOSC) has been created. In connection with this, the ARIADNEplus AO-CAT ontology has been adapted to the requirements from EOSC Resource Data Model (Task 15.1). The Visual Media Service (Task 15.2.1) has had a new format added, allowing for 2D visualisation of LIDAR data in DEM format. In addition, three other standards have been added: gITF, ThreeJS and IIIF, supporting various functionality in the service. The service has also been adapted to support integration with the ARIADNEplus infrastructure in D4Science. A visual wizard has been defined to guide Visual Media Service users to add hotspots to a 3D scene easily and quickly. This extension, initially implemented in 3DHOP will allow archaeologists to create interactive links from the digital 3D model to the related documentation without writing any source code (Task 15.2.2). Task 15.2.3 reworked the Online 3D Database System for Endangered architectural and archaeological Heritage in the south Eastern MEditerRAnea area (EpHEMERA). EpHEMERA is a service provided by the Cyprus Institute to visualize in 3D archaeological excavations, ancient buildings, and their related documentation. In EpHEMERA, it is possible to visualise, online and through standard web browsers, 3D architectural and archaeological models (classified according to a specific type of risk), query the database system and retrieve metadata attached to each digital object, and extract geometric and morphological information about the Cultural Heritage asset. The visualisation and annotation tool of the TSS project have been ported to the OpenLime library and integrated into the Visual Media Service (Task 15.2.1). An additional layer of SVG annotations have been developed and added to the service. The Annotation service have been used and improved in three different pilot projects. (Task 15.3.2) Various strands of work have been done improving services for text mining and Natural Language Processing (Task 15.4). One of these efforts has been building upon the outcomes of the preceding ARIADNE project. A set of archaeological Named Entity Recognition NLP pipelines were reconfigured and deployed for easier use on the General Architecture for Text Engineering (GATE) cloud. Another effort has been on extracting temporal archaeological information using two different parallel approaches, normalisation and named entity recognition. A Python development platform has been used to unify the various services. A Vocabulary Annotation Tool (Task 15.3.1) was developed using the same platform, as part of Task 15.4. The tool facilitates the locating and tagging of vocabulary terms within free text and outputs suggested subject annotations in a range of formats. The GeoPortal service (Task 15.5) is a new REST service designed to manage complex spatio-temporal documents defined by metadata profiles. It was released as a component of the gCube framework. A prototype using the service was deployed and operated to manage archaeological excavation projects (Task 15.7). Two services for querying the RDF AO-Cat metadata records aggregated by the ARIADNEplus Infrastructure was established (Task 15.6): a full-text index service and a SPARQL endpoint. The full- text index service is based on OpenSearch and supports the needed query functionality of the ARIADNEplus portal. The SPARQL endpoint allows performance of semantic queries on the RDF records within the ARIADNEplus data and knowledge cloud.

InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2021 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, eScience, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, i.e. D4Science and OpenAIRE. During 2021 InfraScience members contributed to the publishing of 25 papers, to the research and development activities of 18 research projects (15 funded by EU), to the organization of conferences and training events, to several working groups and task forces.

D4Science is an IT infrastructure specifically conceived to support the development and operation of Virtual Research Environments by the as-a-Service provisioning mode. This report documents the activities performed in 2022 to develop this infrastructure and support several projects and exploitations.

This deliverable D13.2 - "VREs Operation Mid-term Activity Report" describes the activities carried out during the first 24 months of the ARIADNEplus project within Work Package 13. Specifically, in Task 13.1 Infrastructure Operation (JRA2.1) and Task 13.3 VREs Operation (JRA2.3). It reports the procedures governing the operation of the VREs as well as the status of the aggregated resources at mid-term in the ARIADNEplus infrastructure.

The enhancements in IT solutions and the open science movement are injecting changes in the practices dealing with data collection, collation, processing and analytics, and publishing in all the domains, including agri-food. However, in implementing these changes one of the major issues faced by the agri-food researchers is the fragmentation of the “assets” to be exploited when performing research tasks, e.g. data of interest are heterogeneous and scattered across several repositories, the tools modellers rely on are diverse and often make use of limited computing capacity, the publishing practices are various and rarely aim at making available the “whole story” with datasets, processes, workflows. This paper presents the AGINFRA PLUS endeavour to overcome these limitations by providing researchers in three designated communities with Virtual Research Environments facilitating the use of the “assets” of interest and promote collaboration.

This deliverable describes the activities carried out during the first 18 months within Work Package 9 for the SoBigData e-Infrastructure operation activity since its deployment, including a detailed set of usage indicators (i.e. the number of users, accesses to resources, usage of resources from scientists, etc.). It also reports the deployment and procedures governing the operation of the Virtual Research Environments, the catalogue, and the ones for the services devoted to Data Analytics. A total of 15 Virtual Research Environments (VREs) have been created and are operational. In particular, the SoBigData gateway provide its users with: 6 Exploratories VREs paired with the use cases (Demography, Economy & Finance 2.0; Migration Studies; Societal Debates and Misinformation Analysis; Social Impacts of AI and Explainable Machine Learning; Sports Data Science; Sustainable Cities for Citizens); 2 Virtual Lab VREs - SoBigDataLab and OpenScienceGraphLab to exploit and experiment tools and solutions; 3 Applications VREs - TagME, SMAPH, M-Atlas; 2 Project Internal VREs - SoBigData.eu VRE for the communications and collaboration among project and initiative members and SBD-InfraCore VRE for supporting SoBigData-PlusPlus WP9; and 2 Literacy And Training VREs - the SoBigDataLiteracy, supporting Critical Data Literacy of task T.2.4, creating a curated collection of literature of interest for the SoBigData Community, and the e-Learning_Area VRE to host training materials developed within the SoBigData project. As of June '21, the 15 existing VREs served more than 8,000 users by a total of more than 30,000 working sessions, with an average of 1500 working sessions per month with increasing trend. This required to deal with approximately 40 issue tracker tickets (14 requests for support, 6 requests for incidents and bugs, 9 requests for new features, and 9 requests for Virtual Machine or Container creations).

The enhancements in IT solutions and the open science movement are injecting changes in the practices dealing with data collection, collation, processing, analytics, and publishing in all the domains, including agri-food. However, in implementing these changes one of the major issues faced by the agri-food researchers is the fragmentation of the “assets” to be exploited when performing research tasks, for example, data of interest are heterogeneous and scattered across several repositories, the tools modelers rely on are diverse and often make use of limited computing capacity, the publishing practices are various and rarely aim at making available the “whole story” including datasets, processes, and results. This paper presents the AGINFRA PLUS endeavor to overcome these limitations by providing researchers in three designated communities with Virtual Research Environments facilitating the use of the “assets” of interest and promote collaboration. © 2020 John Wiley & Sons Ltd

This deliverable D5.2 "Virtual Research Environment Operation Report years 1-2" describes the activities carried out during the first 24 months of the DESIRA project within Work Package 5. Specifically in Task 5.1 "Knowledge Infrastructure: the DESIRA Virtual Research Environment" and Task 5.2 "Integration of Services and Tools, and Use Reporting". It reports the procedures governing the operation of the VREs as well as the status of the aggregated resources at mid-term in the DESIRA infrastructure. Virtual Research Environments (VREs) are "systems" specifically conceived to provide their users with a web-based set of facilities (including services, data and computational facilities) to accomplish a set of tasks by dynamically relying on the underlying infrastructure. VREs are among the key products to be developed and delivered by the DESIRA project to support Project coordination, Living Labs activities and Rural Digitization Forums activities. The development of VREs is based on three main activities: (i) the development of software artefacts that realise a set of functions (including those needed for accessing specific datasets), (ii) the deployment of these artefacts in an operational infrastructure following the release procedures and tools, and (iii) the final deployment and operation of well-defined Virtual Research Environments by exploiting the facilities offered by the underlying D4Science infrastructure and its services [1, 2]. This report documents the last of the above three activities - i.e. the exploitation of the services and technologies offered by the underlying infrastructure to serve the needs of defined scenarios - as implemented in the context of the DESIRA project from June 2019 to May 2021. The DESIRA Infrastructure Gateway actually offers end-user access to 14 VREs. As of June 2019, 1 VREs were created and operated. Specifically, the DESIRA Project VRE (cf. Sec 3.1.1) was created before the project kick-off. As of May 2021, these VREs have served the needs of more than 370 users and more than 7.000 user sessions. This required dealing with 177 tickets (103 related to the project management, 28 requests for support and enhancements, five requests for incidents and bugs, 14 requests for VRE creations).

The Blue-Cloud project is piloting a cyber platform bringing together and providing access to multidisciplinary data from observations and models, analytical tools, and computing facilities essential to support research to understand better and manage the many aspects of ocean sustainability. This goal is realised by developing, deploying and operating the Blue-Cloud platform whose architecture consists of two major families of components: (a) the Blue Cloud Data Discovery and Access System to serve federated discovery and access to 'blue data' infrastructures; and (b) the Blue Cloud Virtual Research Environment (VRE) component to provide a Blue Cloud VRE as a federation of computing platforms and analytical services. This Deliverable D4.4 "Blue Cloud VRE Common Facilities (Release 2)" is the revised version of the D4.2 "Blue Cloud VRE Common Facilities (Release 1)". This revised version of the document covers the second period of the project, from M13 up to M27, including the up-to-date information of the services reported on D4.2 and the new services that have been developed and added to the VRE common facilities in the reporting period to serve the needs of the Blue Cloud community. The major changes and new services this deliverable introduces are: an Orchestrator (cf. Sec. 3.3), i.e. a software that allows for a declarative, technology agnostic definition of workflows to coordinate the execution of tasks across diverse services and systems; enhancements to the Workspace service to support tailored storage persistence and satisfy different application scenarios (cf. Sec. 4.1); enhancements in the Publishing Framework (cf. Sec. 6), namely the catalogue extension to deposit catalogue items to Zenodo and the facility to publish geospatial data from the workspace; the facility to interface with the Data Discovery & Access System (cf. Sec. 7.1) to transfer datasets of interest into the workspace for future uses; the notebook to facilitate the exploitation of the WEkEO Harmonised Data Access (HDA) API (cf. Sec. 7.2). This deliverable also updates the Identity and Access Management (cf. Sec. 3.1) and the Analytics Framework (cf. Sec. 5.1 and Sec 5.2) with minor changes reflecting the activities performed in the reporting period. A description of all the services previously documented in D4.2, not modified in the period, is preserved for this document to be self-contained and provide the reader with an overall description of the whole VRE Common Facilities offering. A total of 15 services and components are described in this deliverable by reporting their design principles, architecture and main features. These services and components contribute functionalities to the Blue Cloud VRE Enabling Framework (Identity and Access Management, VRE Management, Orchestrator), Collaborative framework (Workspace and Social Networking), Analytics Framework (Software and Algorithm Importer, Smart Executor), Publishing Framework (Catalogue Service) and improved support for RStudio, JupyterHub, ShinyProxy, and Docker Applications. Additionally, two new VRE services, aiming at bridging two VRE external systems such as the the WEkEO1 catalogue from Copernicus and the Data Discovery and Access from Blue-Cloud with the VRE tools are described. Services and components discussed in this deliverable have contributed to 14 gCube releases, from gCube 4.26 (November 2020) to gCube 5.6.0 (November 2021). They have been used to develop and operate the Virtual Laboratories of the Blue Cloud gateway https://blue-cloud.d4science.org and its underlying infrastructure. At the time of this deliverable the Blue-Cloud gateway and its services are serving more than 730 users with a total of 19000+ working sessions.

InfraScience is a research group of the National Research Council of Italy - Institute of Information Science and Technologies (CNR - ISTI) based in Pisa, Italy. This report documents the research activity performed by this group in 2020 to highlight the major results. In particular, the InfraScience group confronted with research challenges characterising Data Infrastructures, e\-Sci\-ence, and Intelligent Systems. The group activity is pursued by closely connecting research and development and by promoting and supporting open science. In fact, the group is leading the development of two large scale infrastructures for Open Science, \ie D4Science and OpenAIRE. During 2020 InfraScience members contributed to the publishing of 30 papers, to the research and development activities of 12 research projects (11 funded by EU), to the organization of conferences and training events, to several working groups and task forces.

In the cell cytochrome, c performs different functions depending on the environment in which it acts; therefore, it has been classified as a multifunction protein. When anchored to the outer side of the inner mitochondrial membrane, native cytochrome c acts as a Schweitzer-StennerSchweitzer-Stenner that transfers electrons from cytochrome c reductase to cytochrome c oxidase in the respiratory chain. On the other hand, to interact with cardiolipin (one of the phospholipids making up the mitochondrial membrane) and form the cytochrome c/cardiolipin complex in the apoptotic process, the protein reorganizes its structure into a non-native state characterized by different asymmetry. The formation of the cytochrome c/cardiolipin complex is a fundamental step of the apoptotic pathway, since the structural rearrangement induces peroxidase activity in cytochrome c, the subsequent permeabilization of the membrane, and the release of the free protein into the cytoplasm, where cytochrome c activates the apoptotic process. Apoptosis is closely related to the pathogenesis of neoplastic, neurodegenerative and cardiovascular diseases; in this contest, the biosynthesis and remodeling of cardiolipin are crucial for the regulation of the apoptotic process. Since the role of cytochrome c as a promoter of apoptosis strictly depends on the non-native conformation(s) that the protein acquires when bound to the cardiolipin and such event leads to cytochrome c traslocation into the cytosol, the structural and functional properties of the cytochrome c/cardiolipin complex in cell fate will be the focus of the present review.

The Blue-Cloud project plans to pilot a cyber platform bringing together and providing access to multidisciplinary data from observations and models, analytical tools, and computing facilities essential to support research to understand better and manage the many aspects of ocean sustainability. To achieve this goal, Blue-Cloud is developing, deploying, and operating the Blue-Cloud platform whose architecture consists of two families of components: (a) the Blue Cloud Data Discovery and Access service component to serve federated discovery and access to 'blue data' infrastructures; and (b) the Blue Cloud Virtual Research Environment (VRE) component to provide a Blue Cloud VRE as a federation of computing platforms and analytical services. This deliverable presents the Blue Cloud Virtual Research Environment constituents by focusing on both new services and revised existing services that have been developed in the reporting period to serve the needs of the Blue Cloud community. In particular, this deliverable describes a total of 11 services and components. These services and components contribute functionalities to the Blue Cloud VRE Enabling Framework (Identity and Access Management, VRE Management), Collaborative framework (Workspace and Social Networking), Analytics Framework (Software and Algorithm Importer, Smart Executor), Publishing Framework (Catalogue Service) and improved support for RStudio, JupyterHub, ShinyProxy, and Docker Applications. The services are described below by reporting their design principles, architectures, and main features. The deliverable also describes the procedures and approaches governing services and components released by highlighting how Gitea (as Git hosting service), Jenkins (as automation server), and Maven (as project management and comprehension tool) are used to guarantee continuous integration processes. Services and components discussed in this deliverable contribute to 11 gCube open-source software system releases (from gCube 4.16 up to gCube 4.25.1) and are in the pipeline for the next ones. They have been used to develop and operate the Virtual Laboratories of the Blue Cloud gateway https://blue-cloud.d4science.org and its underlying infrastructure. At the time of this deliverable (November 2020), the gateway hosts a total of 8 VREs and VLabs, including five specifically conceived to support the co-development of some of the Blue-Cloud demonstrators (namely, the Aquaculture Atlas Generation for Demonstrator #5, the Blue-Cloud Lab for several demonstrators, the GRSF pre for Demonstrator #4, the Marine Environmental Indicators for Demonstrator #3, the Zoo-Phytoplankton EOV for Demonstrator #1). This gateway and its tools serve more than 400 users that (since January 2020) performed a total of more than 5000 working sessions, more than 1700 accesses to the Workspace, and more than 750 analytics tasks. These exploitation and uptake indicators are likely to grow in the coming months thanks to data updates and continued use, further development of existing VLabs, and finally, the creation of new ones.

This deliverable D13.1 - "Software Release Procedures and Tools JRA2" describes the activities carried out during the first six months of the ARIADNEplus project within Task 13.4 (T13.4) Software integration and release (JRA2.4) (Work Package 13 - WP13) and describes the procedures governing the release of software, methods, and tools for the ARIADNEplus infrastructure. This task is in charge of managing the process of the software maintenance, enhancement, and provisioning in JRA work packages. Thus, it i) defines release and provisioning procedures; ii) establishes the release plan; iii) coordinates the release process; iv) operates the tools required to support the release and provisioning activities; v) validates the software documentation; vi) takes care of the distribution of the software and its provisioning. This task benefits from the practices established and experience gained within the D4Science infrastructure. The procedures are documented through a set of documentation pages for single facilities hosted by the gCube wiki. In particular, this report provides the instructions and rules for three main patterns governing the provision of software and tools to the ARIADNEplus infrastructure. The first pattern is related to the provision of software to the gCube infrastructure enabling technology. This pattern describes the procedures for the storage of software and its management; the continuous integration of the software to build releasable software artefacts; and the generation of software distribution packages. The second pattern is related to the provision of software methods elaborated by the ARIADNEplus community requiring execution within the ARIADNEplus infrastructure. The third pattern is instead related to the provisions and integration of tools into the ARIADNEplus infrastructure.

Deliverable D10.2 - "BlueBRIDGE Resources Federation Facilities: Revised Version" reports the release of the BlueBRIDGE facilities for integration of resources from external infrastructures and management of integrated resources. It is structured as follows: a description for each facility is available on this document in conjunction witha list of the main features, information about the design and architecture of it, a number of use cases and finally how it can be deployed. In case more information is needed or a more detailed documentation is available, URLs to the project 's wiki are provided. The set of the available facilities are split in three main categories: (a) facilities for integrating computing infrastructure resources, aiming on exploiting the computational power offered by external infrastructures in order to execute CPU intensive jobs, (b) facilities for integrating data infrastructure resources, where a number of components have been developed in order to integrate data from different data infrastructures to in the Virtual Research Environments (VREs), including biodiversity, geospatial and generic OAI-PMH repositories and (c) facilities for federated resources management, for effectively and efficiently managing the federated resources made available thanks to bridges developed in the previous categories. The sections that follow provide the description and the details for each distinct facility, aiming on offering a complete guide to the intended readers. The intended readers of this deliverable are (a) the community in the large willing to be informed on the solutions BlueBRIDGE offers for federated resources management, (b) the gCube developer community to know how to integrate, use and build on top of the facilities described by the document, and (c) the gCube administrators to know how to setup, configure and manage the integration of a gCube infrastructure with external resources.

Deliverable D9.2 - "BlueBRIDGE VRE Commons Facilities: Revised Version" is the revised version of the D9.1 deliverable, intended to report the release of the BlueBRIDGE facilities for Data Access, Data Discovery, Data Storage, Data Analytics and Data Publishing. It is conceived to include the latest developments and releases that took place between the 2 versions of the reports. The deliverable is of type "Other" and the following document is intended to provide its readers with an easy-to-use description of the actual components, services and systems contributing to form the BlueBRIDGE VRE Commons Facilities. This document is structured as follows: a description for each facility is available, in conjunction with links to the project's wiki, providing more detailed descriptions and additional information for each component. This revised version of the document aims at providing a complete picture of the available facilities for Accessing, Discovering, Storing Data, Analysing and Publishing Data developed through the project's lifetime. The deliverable is divided in two main sections. The first one follows the structure of Work Package 9; specifically, it documents the various releases and versions of the facilities available for Accessing, Discovering and Storing Data (T9.1), for Analysing Data (T9.2) and for Publishing Data (T9.3). The second section comprises facilities for managing and using VREs that span across all the three WP9 tasks. Specifically, it includes dedicated parts documenting the various releases and versions of services for defining, creating and deploying VREs (VRE Management facilities) together with a set of applications allowing to use the VRE through a thin client (VRE Enabling facilities). The deliverable provides, for each facility, a description, the documentation for developers and system administrators, how-to guides and usage instructions for different use cases and links to open source code and binaries. Further details and the complete documentation for the facilities are available on the gCube wiki at https://wiki.gcube-system.org/gcube/About_gCube. The intended readers of this deliverable are (a) the community in the large willing to be informed on the solutions BlueBRIDGE offers for VRE management, Data Access, Discovery, Storage, Analytics and Publishing, and (b) the gCube developer community to know how to integrate, use and build on top of the facilities described by the document.

The ability of a C-terminal truncated form of TRAF2 to bind synthetic vesicles has been quantitatively studied by steady-state fluorescence energy transfer from the protein to large unilamellar vesicles (LUVs) prepared with different lipid mixtures. The dissociation constants, the free energy of binding, and the average number of phospholipids interacting with truncated TRAF2 have been evaluated from the corresponding binding curves. The results indicate that the protein strongly interacts with the lipid bilayer, preferentially in the monomeric state. These findings have been discussed in terms of their possible role in the activity of TRAF2 in vivo.

Deliverable D3.1 "Open Science Data Analytics Technologies" is a deliverable of type Demonstrator meaning that it manifests in artefacts (software releases) other than reports. In particular, the deliverable is about the software realising the Data Analytics & Processing Layer of the AGINFRA+. This software is part of a large software system named gCube (www.gcube-system.org). The gCube system offers a large array of services supporting the entire lifecycle underlying a research activity (data management and collation, analytics, collaboration, sharing) and the possibility to combine these services in Virtual Research Environments1. In the context of AGINFRA PLUS the following gCube components have been primarily exploited, consolidated and enhanced to serve the analytics needs arising in the context of the project use cases. DataMiner, i.e. a service enacting its users to perform data analytics tasks by relying on an array of analytics methods and a distributed and heterogeneous computing infrastructure. This service is available by a web-based GUI as well as via a web-based API based on the OGC WPS standard. SAI (Statistical Algorithm Importer), i.e. a service enacting its users to make available their own analytics methods via the DataMiner service. In addition to that, the entire analytics solution made available for AGINFRA PLUS cases counts on (i) a shared workspace realising a cloud-based file manager for managing content of interest and sharing this content with co-workers, (ii) a social networking area enabling users to post messages and have discussions, (iii) a flexible catalogue enabling to publish and discover items of interest including "research objects" resulting from an analytics task. This technology is deployed in its latest version in every Virtual Research Environment supporting AGINFRA PLUS cases2. The major enhancements to the technology pertaining to AGINFRA PLUS have been included in three gCube major releases3 4.7 (October 2017), 4.8 (November 2017), and 4.9 (under production).In particular, with these releases a new"black-box" oriented approach (https://wiki.gcubesystem. org/gcube/Statistical_Algorithms_Importer:_Java_Project#Black_Box_Integration)has been envisaged and implemented to enact analytics method owners and developers to easily integrate theirsolutions into the DataMinerservice. Among the supported black-box typologies there is that for KNIME workflows, i.e. analytics methods implemented by a KNIME workflow. KNIME is among the key technologies supporting the Food Safety Risk Assessment cases. In order to enact the execution of KNIME-based black-boxes, the distributed computing part of the data analytics platform has been extended to integrate the KNIME execution engine. Other cases are counting on the same mechanism to integrate entire applications (WOFOST4) as well as Python-based methods.

Deliverable D10.1 - "BlueBRIDGE Resources Federation Facilities" reports the release of the BlueBRIDGE facilities for integration of resources from external infrastructures and management of integrated resources. The deliverable covers the first nine months of the BlueBRIDGE project. An update to this deliverable is expected at project month M28 with Deliverable D10.2.

This document reports on the integration of Federated Cloud resources in the D4Science platform, built on top of the gCube framework. The document introduces the D4Science platform, how it is currently exploited by scientific communities and motivates the need for the integration. The most relevant usage scenarios are analysed and corresponding requirements are identified. The extension to the gCube framework is defined in terms of overall architecture and description of single components. A number of enhancements have been selected for future evaluation and realization.

Deliverable D9.1 - "BlueBRIDGE VRE Commons Facilities" reports the release of the BlueBRIDGE facilities for Data Access, Data Discovery, Data Storage, Data Analytics and Data Publishing. Those facilities are implemented through web services, libraries, and mediators over technologies that are offered as services operated and made accessible through VREs This deliverable is of type "Other" and consists of a set of wiki pages hosted by the BlueBRIDGE project wiki [1] plus a set of documentation pages for single facilities hosted by the gCube wiki [2].

This report describes the PARTHENOS e-infrastructure architecture: the hardware and the services. Hardware is organized as a dynamic cloud of virtual machines, supporting computation and storage, while the services are organized into e-infrastructure middleware, storage, and end user services.

The binding of lipids (free fatty acids as well as acidic phospholipids) to cytochrome c (cyt c) induces conformational changes and partial unfolding of the protein, strongly influencing cyt c oxidase/peroxidase activity. ATP is unique among the nucleotides in being able to turn non-native states of cyt c back to the native conformation. The peroxidase activity acquired by lipid-bound cyt c turns out to be very critical in the early stages of apoptosis. Nucleotide specificity is observed for apoptosome formation and caspase activation, the cleavage occurring only in the presence of dATP or ATP. In this study, we demonstrate the connection between peroxidase activity and oleic acid-induced conformational transitions of cyt c and show how ATP is capable of modulating such interplay. By NMR measurement, we have demonstrated that ATP interacts with a site (S 1) formed by K88, R91, and E62 and such interaction was weakened by mutation of E62, suggesting the selective role in the interaction played by the base moiety. Interestingly, the interactions of ATP and GTP with cyt c are significantly different at low nucleotide concentrations, with GTP being less effective in perturbing the SI site and in eliciting apoptotic activity. To gain insights into the structural features of cyt c required for its pro-apoptotic activity and to demonstrate a regulatory role for ATP (compared to the effect of GTP), we have performed experiments on cell lysates by using cyt c proteins mutated on amino acid residues that, as suggested by NMR measurements, belong to S1. Thus, we provide evidence that ATP acts as an allosteric effector, regulating structural transitions among different conformations and different oxidation states of cyt c, which are endowed with apoptotic activity or not. On this basis, we suggest a previously unrecognized role for ATP binding to cyt c at low millimolar concentrations in the cytosol, beyond the known regulatory role during the oxidative phosphorylation in mitochondria.

The aim of this meta-analysis was to evaluate the association between ALS and occupational exposure to physical (ELF-EMF) and chemicals (solvents, heavy metals and pesticides) agents.We considered articles published from 1980 up to April 2013; in total, 750 publications were evaluated. The studies had to satisfy the following criteria: 1) cohort or case-control studies; 2) the presence of individual exposures; 3) clinical diagnosis of sporadic ALS or sporadic ALS on the death certificate. We followed the evaluation of quality in two steps. The first step classified studies according to a rating system based on a mix of criteria developed by scientific organizations, especially developed for studies of risk factors for ALS. The ratings obtained range from I (highest) to V (lowest). The data on risk factors derived from studies with Armon ratings of I, II, and III can reach levels of evidence A (established risk factor), B (likely risk factor), or C (possible risk factor). The second step evaluated the exposure and a score from 1 to 4 was assigned to each item; an exposure with a score of 3 or 4 was considered sufficient. Different analyses were performed on ALS and exposure to metals, solvents, pesticides and electromagnetic fields. In our study the heterogeneity was assessed both by χ2-based Q-tests and through the index of inconsistency I² while the measure RR/OR and CI of 95% to estimate the relationship between ALS and the various considered risk factors was employed.The association between exposure to pesticides and ALS as a whole is weak and not significant. With regard to the results of individual studies the following critical synthesis can be reported: 1) the selected studies showed a low level of association between ALS and electromagnetic fields; 2) as regards the solvents, the association with ALS in some studies is combined with a slightly increased risk, particularly in women, and in others a slight but significant linear association is observed; 3) for the metals, in some cases there was a stronger association in women than in men; for individual metals, there was an association especially with chromium and lead; 4) lastly, with regard to the products of agricultural pesticides in general, there was an association with ALS in men but not in women, with a dose-response relationship.The lack of statistically significant association between occupational exposure and ALS is mainly due to the methodological diversity of the studies and the lack of prospective studies at the workplace.

The ENVRI Integration, Harmonisation and Publication software comprises a number of components, services and subsystems offering facilities enabling the integration and harmonization of data. The actual deliverable is thus the software realising such facilities. This document briefly describes the software components realising version 2 of these facilities and offers a series of links to the software itself and its accompanying documentation

In this paper, we exploit the potential offered by site-directed mutagenesis to achieve direct adsorption of horse cyt c on a bare gold electrode surface. To this issue, the side chain T102 has been replaced by a cysteine. T102 is close to the surface exposed C-terminal residue (E104), therefore the T102C mutation is expected to generate an exposed cysteine side chain able to facilitate protein binding to the electrode via the sulphur atom (analogously to what observed for yeast iso-1-cyt c). Scanning Tunnelling and Tapping Mode Atomic Force Microscopy measurements show that the T102C mutant stably adsorbs on an Au(111) surface and retains the morphological characteristics of the native form. Cyclic voltammetry reveals that the adsorbed variant is electroactive; however, the heterogeneous electron transfer with the electrode surface is slower than that observed for yeast iso-1-cyt c. We ascribe it to differences in the tertiary architecture of the two proteins, characterized by different flexibility and stability. In particular, the region where the N- and C-terminal helices get in contact (and where the mutation occurs) is analyzed in detail, since the interactions between these two helices are considered crucial for the stability of the overall protein fold.

Although the tertiary structures of mitochondrial cytochromes c (cyts c) seem to be remarkably similar, there are variations in their amino acid sequences, stability and functional properties. GdnHCl-induced unfolding experiments on engineered yeast and horse cyt c were carried out with the aim to to clarify, at molecular level, some aspects concerning the stability of this class of proteins. The results obtained are discussed in the light of the three-dimensional structures of the two proteins.

An increasing body of evidence ascribes to misfolded forms of cytochrome c (cyt c) a role in pathophysiological events such as apoptosis and disease. Here, we examine the conformational changes induced by lipid binding to horse heart cyt c at pH 7 and study the ability of ATP (and other nucleotides) to refold several forms of unfolded cyt c such as oleic acid-bound cyt c, nicked cyt c, and acid denatured cyt c. The CD and fluorescence spectra demonstrate that cyt c unfolded by oleic acid has an intact secondary structure, and a disrupted tertiary structure and heme environment. Furthermore, evidence from the Soret CD, electronic absorption, and resonance Raman spectra indicates the presence of an equilibrium of at least two low-spin species having distinct heme-iron(III) coordination. As a whole, the data indicate that binding of cyt c to oleic acid leads to a partially unfolded conformation of the protein, resembling that typical of the molten globule state. Interestingly, the native conformation is almost fully recovered in the presence of ATP or dATP, while other nucleotides, such as GTP, are ineffective. Molecular modeling of ATP binding to cyt c and mutagenesis experiments show the interactions of phosphate groups with Lys88 and Arg91, with adenosine ring interaction with Glu62 explaining the unfavorable binding of GTP: The finding that ATP and dATP are unique among the nucleotides in being able to turn non-native states of cyt c back to native conformation is discussed in the light of cyt c involvement in cell apoptosis.

Species distribution modeling is a process aiming at computationally predicting the distribution of species in geographic areas on the basis of environmental parameters including climate data. In order to further promote the diffusion of such an approach it is fundamental to develop a flexible, comprehensive, and robust environment enabling practitioners to produce species distribution models more efficiently. A promising way to build such an environment is offered by modern infrastructures promoting the sharing of resources, including hardware, software, data and services. We describe an approach to species distribution modeling based on the D4Science Infrastructure that can offer a rich array of data and data management services by leveraging other infrastructures (including Cloud), by discussing the services needed to support the phases of such a complex process.

The ENVRI Integration, Harmonisation and Publication software comprises a number of components, services and subsystems offering facilities enabling the integration and harmonization of data. The actual deliverable is thus the software realising such facilities. This document briefly describes the software components realising version 1 of these facilities and offers a series of links to the software itself and its accompanying documentation

Species distribution modeling is a process aiming at computationally predicting the distribution of species in geographic areas on the basis of environmental parameters including climate data. In order to further promote the diffusion of such an approach it is fundamental to develop a flexible, comprehensive, and robust environment enabling practitioners to produce species distribution models more efficiently. A promising way to build such an environment is offered by modern infrastructures promoting the sharing of resources, including hardware, software, data and services. We describe an approach to species distribution modeling based on the D4Science Infrastructure that can offer a rich array of data and data management services by leveraging other infrastructures (including Cloud), by discussing the services needed to support the phases of such a complex process.

A certain species' niche, i.e. those environmental conditions and resources which permit that species can survive and reproduce, is a basic piece of knowledge for monitoring ocean's populousness from both commercial point of view (to steer fishery activities to defined areas) and from the biological one (to monitor dying species). In the context of the European iMarine project (www.i-marine.eu), the Networked Multimedia Information Systems Laboratory (NeMIS) of the CNR Institute of Information Science and Technology (ISTI) has developed a tool for generating probabilistic species distribution maps that are proved to closely involve the interest of both industrial and scientific communities. This tool exploits Cloud Computing techniques to compare systems able to calculate the probability that a certain species can thrive in a given ocean's area, i.e., the probability that such a zone corresponds to its ecological niche.

Species distribution modeling is a process aiming at computationally predicting the distribution of species in geographic areas on the basis of environmental parameters including climate data. Such a quantitative approach has a lot of potentialities in many areas that include setting up conservation priorities, testing biogeographic hypotheses, assessing the impact of accelerated land use. In order to further promote the diffusion of such an approach it is fundamental to develop a flexible, comprehensive, and robust environment capable of enabling practitioners and communities of practice to produce species distribution models more efficiently. A promising way to build such an environment is offered by modern infrastructures promoting the sharing of resources, including hardware, software, data and services. This paper describes an approach to species distribution modeling based on a Hybrid Data Infrastructure that can offer a rich array of data and data management services by leveraging other infrastructures (including Cloud). It discusses the whole set of services needed to support the phases of such a complex process including access to occurrence records and environmental parameters and the processing of such information to predict the probability of a species' occurrence in given areas. Copyright c 0000 John Wiley & Sons, Ltd.