Identification of Degraded Land in the Canary Islands; Tests and Reviews

Degraded Land is an area that either by natural causes (fires, floods, storms or volcanic eruptions) or more by direct or indirect causes of human action, has been altered or modified from its natural state. Restoration is an activity that initiates or accelerates the recovery of an ecosystem. It can be defined as the set of actions taken in order to reverse or reduce the damage caused in the territory. In the case of the Canary Islands there is a high possibility for the territory to suffer processes that degrade the environment, given that the islands are very fragile ecosystems. Added to this they are territories isolated from the continent, which complicates the process of restoring them. In this paper, the different types of common degraded areas in the Canary Islands are identified, as well as the proposed solutions for remediation, such as afforestation of agricultural land or landfill closure and restoration

A framework for intelligent policy decision making based on a government data hub

Author ProofThe e-Oman Integration Platform is a data hub that enables data exchanges across government in response to transactions. With millions of transactions weekly, and thereby data exchanges, we propose to investigate the potential of gathering intelligence from these linked sources to help government officials make more informed decisions. A key feature of this data is the richness and accuracy, which increases the value of the learning outcome when augmented by other big and open data sources. We consider a high-level framework within a government context, taking into account issues related to the definition of public policies, data privacy, and the potential benefits to society. A preliminary, qualitative validation of the framework in the context of e-Oman is presented. This paper lays out foundational work into an ongoing research to implement government decision-making based on big data.“SmartEGOV: Harnessing EGOV for Smart Governance (Foundations, Methods, Tools)/NORTE-01-0145-FEDER-000037”, supported by Norte Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development Fund (EFDR

IFN-α with dasatinib broadens the immune repertoire in patients with chronic-phase chronic myeloid leukemia

In chronic myeloid leukemia (CML), combination therapies with tyrosine kinase inhibitors (TKIs) aim to improve the achievement of deep molecular remission that would allow therapy discontinuation. IFN-alpha is one promising candidate, as it has long-lasting effects on both malignant and immune cells. In connection with a multicenter clinical trial combining dasatinib with IFN-alpha in 40 patients with chronic-phase CML (NordCML007, NCT01725204), we performed immune monitoring with single-cell RNA and T cell receptor (TCR) sequencing (n = 4, 12 samples), bulk TCR beta sequencing (n = 13, 26 samples), flow cytometry (n = 40, 106 samples), cytokine analyses (n = 17, 80 samples), and ex vivo functional studies (n = 39, 80 samples). Dasatinib drove the immune repertoire toward terminally differentiated NK and CD8+ T cells with dampened functional capabilities. Patients with dasatinib-associated pleural effusions had increased numbers of CD8(+) recently activated effector memory T (Temra) cells. In vitro, dasatinib prevented CD3-induced cell death by blocking TCR signaling. The addition of IFN-alpha reversed the terminally differentiated phenotypes and increased the number of costimulatory intercellular interactions and the number of unique putative epitope-specific TCR clusters. In vitro IFN-alpha had costimulatory effects on TCR signaling. Our work supports the combination of IFN-alpha with TKI therapy, as IFN-alpha broadens the immune repertoire and restores immunological function.Peer reviewe

Interconnecting Governments, Businesses and Citizens – A Comparison of Two Digital Infrastructures

Part 2: Services and InteroperabilityInternational audiencePublic and private organizations in various areas are setting up digital Information Infrastructures (IIs) for interconnecting government, businesses and citizens. IIs can create value by sharing and integrating data of multiple actors. This can be the basis for value added services and especially collaborations of public and private partners can make IIs thrive. Easier access to integrated services and products (jointly) offered by government and businesses may stimulate transparency and innovations. IIs are under development in many domains, including for open data and international trade. However, there are notable differences in the design, characteristics and implementation of the IIs. The objective of this paper is to compare two diverse IIs in order to obtain a better understanding of common and differing elements in the IIs and their impact. Among the differences are the roles of government, businesses and users, in driving, developing and exploitation of the IIs

Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision making?

Big data promises to transform public decision-making for the better by making it more responsive to actual needs and policy effects. However, much recent work on big data in public decision-making assumes a rational view of decision-making, which has been much criticized in the public administration debate. In this paper, we apply this view, and a more political one, to the context of big data and offer a qualitative study. We question the impact of big data on decision-making, realizing that big data – including its new methods and functions – must inevitably encounter existing political and managerial institutions. By studying two illustrative cases of big data use processes, we explore how these two worlds meet. Specifically, we look at the interaction between data analysts and decision makers. In this we distinguish between a rational view and a political view, and between an information logic and a decision logic. We find that big data provides ample opportunities for both analysts and decision makers to do a better job, but this doesn't necessarily imply better decision-making, because big data also provides opportunities for actors to pursue their own interests. Big data enables both data analysts and decision makers to act as autonomous agents rather than as links in a functional chain. Therefore, big data's impact cannot be interpreted only in terms of its functional promise; it must also be acknowledged as a phenomenon set to impact our policymaking institutions, including their legitimacy

Rationality and politics of algorithms. Will the promise of big data survive the dynamics of public decision making?

Big data promises to transform public decision-making for the better by making it more responsive to actual needs and policy effects. However, much recent work on big data in public decision-making assumes a rational view of decision-making, which has been much criticized in the public administration debate. In this paper, we apply this view, and a more political one, to the context of big data and offer a qualitative study. We question the impact of big data on decision-making, realizing that big data – including its new methods and functions – must inevitably encounter existing political and managerial institutions. By studying two illustrative cases of big data use processes, we explore how these two worlds meet. Specifically, we look at the interaction between data analysts and decision makers. In this we distinguish between a rational view and a political view, and between an information logic and a decision logic. We find that big data provides ample opportunities for both analysts and decision makers to do a better job, but this doesn't necessarily imply better decision-making, because big data also provides opportunities for actors to pursue their own interests. Big data enables both data analysts and decision makers to act as autonomous agents rather than as links in a functional chain. Therefore, big data's impact cannot be interpreted only in terms of its functional promise; it must also be acknowledged as a phenomenon set to impact our policymaking institutions, including their legitimacy