94 research outputs found

    Tariff-based regulatory sandboxes for EV smart charging: Impacts on the tariff and the power system in a national framework

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    Electrification of private transport is a fundamental step for decarbonizing mobility. Electric vehicles (EV) can be a burden for the power system if vehicle-grid integration is not implemented by design. Market-based smart charging projects are effective, but their massive diffusion is limited. A fundamental instrument toward a large adoption of smart charging is the inclusion of smart charging-oriented measures in regulatory sandboxes, conveniently acting on electricity tariff. This paper presents a set of possible toolboxes for smart charging to show the potential that regulatory measures can have on steering the infrastructure deployment and the charging activity. Each proposed toolbox addresses a specific charging mode, including domestic, workplace, and public access charging. Proposed measures are target-oriented and evaluated based on their environmental, technical, and economic impacts. These include the carbon footprint of the electricity used for EV charging, the impact in terms of peak power withdrawal from the public grid and the charging cost born by EV users. Additionally, the assessment about the impact of prospected measures on the electricity tariffs' income is provided. Results show the possibility of reducing the evening EV-related peak load by 30% to 50% via home smart charging. Also, a 10% decrease in carbon footprint is achieved by valley-filling with work charging. Charging at the destination can reduce the system cost for the new distribution infrastructure, dropping the number of new dedicated connection points for public charging. The cost of incentives is partially repayable considering the additional EV penetration fostered by the reduced charging costs

    Epidermal growth factor receptor tyrosine kinase inhibitors for the treatment of non-small-cell lung cancer: results and open issues

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    The medical treatment of non-small-cell lung cancer (NSCLC) has progressively changed since the introduction of “targeted therapy”. The development of one of these molecular drug categories, e. g., the epidermal growth factor receptor (EGFR) tyrosine-kinase (TK) selective inhibitors, such as the orally active gefitinib and erlotinib, offers an interesting new opportunity. The clinical response rates obtained with their employment in unselected patient populations only account for approximately 10%. Because of this, over the last two years numerous studies have been performed in order to identify the patient subsets that could better benefit from these agents. Not only patient characteristics and clinical-pathological features, such as never-smoking status, female gender, East Asian origin, adenocarcinoma histology, bronchioloalveolar subtype, but also molecular findings, such as somatic mutations in the EGFR gene, emerge as potentially useful prognostic and predictive factors in advanced NSCLC. Further, specifically designed clinical trials are still needed to completely clarify these and other open issues that are reviewed in this paper, in order to clarify all the interesting findings available in the clinical practice

    Intellectual Property, Open Science and Research Biobanks

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    In biomedical research and translational medicine, the ancient war between exclusivity (private control over information) and access to information is proposing again on a new battlefield: research biobanks. The latter are becoming increasingly important (one of the ten ideas changing the world, according to Time magazine) since they allow to collect, store and distribute in a secure and professional way a critical mass of human biological samples for research purposes. Tissues and related data are fundamental for the development of the biomedical research and the emerging field of translational medicine: they represent the “raw material” for every kind of biomedical study. For this reason, it is crucial to understand the boundaries of Intellectual Property (IP) in this prickly context. In fact, both data sharing and collaborative research have become an imperative in contemporary open science, whose development depends inextricably on: the opportunities to access and use data, the possibility of sharing practices between communities, the cross-checking of information and results and, chiefly, interactions with experts in different fields of knowledge. Data sharing allows both to spread the costs of analytical results that researchers cannot achieve working individually and, if properly managed, to avoid the duplication of research. These advantages are crucial: access to a common pool of pre-competitive data and the possibility to endorse follow-on research projects are fundamental for the progress of biomedicine. This is why the "open movement" is also spreading in the biobank's field. After an overview of the complex interactions among the different stakeholders involved in the process of information and data production, as well as of the main obstacles to the promotion of data sharing (i.e., the appropriability of biological samples and information, the privacy of participants, the lack of interoperability), we will firstly clarify some blurring in language, in particular concerning concepts often mixed up, such as “open source” and “open access”. The aim is to understand whether and to what extent we can apply these concepts to the biomedical field. Afterwards, adopting a comparative perspective, we will analyze the main features of the open models – in particular, the Open Research Data model – which have been proposed in literature for the promotion of data sharing in the field of research biobanks. After such an analysis, we will suggest some recommendations in order to rebalance the clash between exclusivity - the paradigm characterizing the evolution of intellectual property over the last three centuries - and the actual needs for access to knowledge. We argue that the key factor in this balance may come from the right interaction between IP, social norms and contracts. In particular, we need to combine the incentives and the reward mechanisms characterizing scientific communities with data sharing imperative

    Intellectual Property, Open Science and Research Biobanks

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    Regulating electricity distribution networks under technological and demand uncertainty

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    The regulation of electricity distribution networks faces new challenges, as consumer preferences for network services change, distributed energy resources are connected in increasing number, and advanced information and communication technologies become ubiquitous. This work discusses how, within this new context, national regulatory authorities in Great Britain and Italy already employ advanced regulatory instruments for establishing firms’ allowed revenues under technological and demand uncertainty. Identified areas of improvement are then addressed via the proposal of an original regulatory approach. This builds on elements from practice and academia and formulates the ex-post regulatory estimate of efficient total expenditures in a modular manner. As illustrated with an example and thoroughly discussed in the paper, this approach preserves the desirable features of the existing mechanisms and adds to them in several ways. The main contribution regards the efficient treatment of benchmark errors, which occur when regulators fail to anticipate the emergence of a new cost saving technology or network management practice. Providing incentives for cost efficiency while granting firms the freedom to innovate is, indeed, crucial at a time when, as described by EU Directive 2019/944, the complexity of the tasks carried out by distribution operators continues to increase
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