Risk Governance of Emerging Technologies Demonstrated in Terms of its Applicability to Nanomaterials

Nanotechnologies have reached maturity and market penetration that require nano-specific changes in legislation and harmonization among legislation domains, such as the amendments to REACH for nanomaterials (NMs) which came into force in 2020. Thus, an assessment of the components and regulatory boundaries of NMs risk governance is timely, alongside related methods and tools, as part of the global efforts to optimise nanosafety and integrate it into product design processes, via Safe(r)-by-Design (SbD) concepts. This paper provides an overview of the state-of-the-art regarding risk governance of NMs and lays out the theoretical basis for the development and implementation of an effective, trustworthy and transparent risk governance framework for NMs. The proposed framework enables continuous integration of the evolving state of the science, leverages best practice from contiguous disciplines and facilitates responsive re-thinking of nanosafety governance to meet future needs. To achieve and operationalise such framework, a science-based Risk Governance Council (RGC) for NMs is being developed. The framework will provide a toolkit for independent NMs' risk governance and integrates needs and views of stakeholders. An extension of this framework to relevant advanced materials and emerging technologies is also envisaged, in view of future foundations of risk research in Europe and globally

Process support for evolving active architectures

This work is supported by the EC Framework V project ArchWare (IST-001-32360), and the UK Engineering and Physical Sciences Research Council (EPSRC) under grants GR/R51872 (Reflective Application Framework for Distributed Architectures) and GR/R67743 (my Grid: Directly Supporting the E-Scientist).Long-lived, architecture-based software. systems are increasingly important. Effective process support for these systems depends upon recognising their compositional nature and the active, role of their architecture in guiding evolutionary development. Current process approaches have difficulty with run-time architecture changes that are not known a priori, and dealing with extant data during system evolution. This paper describes an approach that deals with these issues. It is based on a process-aware architecture description language (ADL), with explicit compose and decompose constructs, and with a hyper-code representation for dealing with extant data and code. An example is given to illustrate the ease-of-use benefits of this approach.Postprin

Role of stationary phase and eluent composition on the determination of log P values of N-hydroxyethylamide of aryloxyalkylen and pyridine carboxylic acids by reversed-phase high-performance liquid chromatography

The partition coefficients, P, between n-octanol and water of a number of growth stimulating substances, N-hydroxyethylamide of aryloxyalkylen- and pyridine carboxylic acids were obtained from Pomona College (C log P), and Rekker's (log PRekker) revised fragmental constant system was used to calculate log P data sets. Both of these data sets were correlated with two different substance lipophilicity parameters, log kw and 0. Log kw was obtained by extrapolation of log retention factor (k) to 0% organic modifier measured in reversed-phase liquid chromatography (RPLC) systems. 0 values were obtained from the slopes and intercepts of these relationships. The RPLC experiments were performed on four commercially available reversed-phase columns. Binary mixtures of methanol–water, methanol–phosphate buffer (pH 7.0), methanol–tricine buffer (pH 7.0) and acetonitrile–water were used as mobile phases for the determination of log kw values. For the methanolic eluents linear regression provided satisfactory correlations (r>0.99) for the relationships log k vs. organic modifier content in the eluent, while for the acetonitrile-containing eluents a second-degree polynominal regression was necessary. For all four RPLC columns, by linear regression satisfactory correlations (r>0.99) were obtained between log kw and log P data using methanolic eluents. In such eluents 0 values were shown to be the second-best lipophilicity parameters. For acetonitrile-containing eluents the use of second-degree polynominal regression was necessary and, in contrast to methanol, significant influence of the applied column on regression results was observed. For acetonitrile-containing eluents the 0-index does not provide satisfactory results for our substances. No difference in regression results between the use of buffered and non-buffered eluents was observed

Exploring the Impact of Recycling on Demand-Supply Balance of Critical Materials in Green Transition: A Dynamic Multi-Regional Waste Input-Output Analysis

Addressing our climate urgency requiresvarious renewableand low-carbontechnologies, which often contain critical materials that face potentialsupply risks. Existing studies on the critical material implicationsof green transition have used various methodologies, each with prosand cons in providing a system understanding. Here, we integratedthe dynamic material flow analysis and input-output modelingprinciples in an integrated multi-regional waste input-outputmodel to assess the demand-supply balance and recycling potentialsfor cobalt, lithium, neodymium, and dysprosium under various energyscenarios projected to 2050. We show that although all four criticalmaterials are likely to face strong growth in annual demand (as highas a factor of 25 compared to the 2015 level), only cobalt has a highercumulative demand by 2050 than the known reserves. Nevertheless, consideringthe sheer scale of demand increase and long lead time of opening orexpanding new mines, recycling efforts are urgently needed to supplementprimary supply toward global green transition. This model integrationis proven useful and can be extended to more critical materials andgreen technologies.Anintegrated dynamic model reveals demand-supplybalance and recycling potentials of cobalt, lithium, neodymium, anddysprosium in green transition

Automating Software Development Process Using Fuzzy Logic

In this chapter, we aim to highlight how fuzzy logic can be a valid expressive tool to manage the software development process. We characterize a software development method in terms of two major components: artifact types and methodological rules. Classes, attributes, operations, and inheritance and part-of relations are examples of object-oriented artifact types. Each type is characterized by a set of properties whose values determine the membership of an artifact to other types. The relation between the property values and the membership values is defined by the heuristics that are typically expressed informally using textual forms in a natural language. The causal order among artifacts identifies the software process. Especially in the early phases of the development process, property values correspond to software engineer¿s perceptions

HPLC behavior and hydrophobic parameters of some anilides

The chromatographic behavior of para substituted anilides of 2,2-dimethylpropanoic, benzoic and alpha -phenyl acetic acid has been studied by reversed-phase high performance liquid chromatography HPLC was performed on a C-18 column with various aqueous methanol mobile phases. The Influence on the retention of anilide type and additional substituents in the molecule is discussed. Several chromatographic hydrophobicity parameters (CHP) have been calculated by linear correlation between log k of the investigated compounds and the concentration of methanol in the mobile phase. The chromatographic hydrophobicity parameters were compared with the log P values calculated by Rekker's fragmental method. The results show moderate correlations of CHIP with log Mus, multiple linear regressions have been applied. It was found that besides log P even the electronic effects of individual polar groups capable of hydrogen bonding proved to be very important in hydrophobic characterization of the molecule