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Preventing environmental damage from products : An analysis of the policy and regulatory framework in Europe

How to tackle environmental damage from the throwaway society is one of the defining questions of the twenty-first century. We must encourage and support sustainable production and consumption, notably through the establishment of a circular economy. These essays by an international group of leading scholars from a range of disciplines analyse policies and legal instruments and challenge mainstrea

Regulating recyclability under the ecodesign directive : How can we achieve synergies between waste and product policies for electric and electronic equipment to promote recycling?

Introduction: The interaction between different product policies will be crucial for the further advancement of a coherent product policy framework. The Commission has stated that ‘the complex and interlocking approach needed to build a resource-efficient Europe can only be achieved with a policy mix that optimizes synergies and addresses trade-offs between different areas and policies’. In the co

A strategic and comprehensive vision for future R&D in construction ICT

The tremendous development in the past ten last years of the Internet and ICT at large (whether it be in general technologies like semantic modeling, knowledge mining, RFID or mobile technologies, or domain-oriented ones like e-commerce, collaborative spaces, digital mock-ups, etc.) has opened a large spectrum of potential applica-tions of ICT in the Construction sector. The real adaptation and de

Present and future challenges for Europe’s environmental product policy

Concerns about the environmental effects of the ‘throwaway society’ are increasingly influencing policy-making and regulatory action in the EU. The Seventh Environment Action Programme, which aims to guide European environmental policy, sets out a long-term vision for the EU that requires a major shift in the way economic activities are conducted: In 2050, we live well, within the planet’s ecologi

Above and below the surface : Environment, work, death, and upbringing in sixteenth- to seventeenth- century Sweden

This chapter addresses children’s lives and living conditions during the early modern period in Sweden. A case study on the population at one of Sweden’s most important historical mines, the Sala Silver mine forms the basis for a discussion about children’s work, their diets, and how gender roles and social status may have affected their health. Two sources provide complementing and sometimes cont

Class discriminator-based EMG classification approach for detection of neuromuscular diseases using discriminator-dependent decision rule (D3R) approach

Classification of EMG signals is essential for diagnosis of motor neuron diseases like neuropathy and myopathy. Although a number of strategies have been implemented for classification, none of them are efficient enough to be implemented in clinical environment. In the present study, we use ensemble approach of support vector machines for classification of three classes (normal, myopathic and neur

Time domain multi-feature extraction and classification of human hand movements using surface EMG

Hand movement recognition from electromyogram (EMG) signals is a crucial element for design of electrically controlled limb prostheses and for developing human computer interfaces (HCIs). The study focuses on extraction of significant features from raw EMG signals corresponding to six different grasping hand movements and then using them to classify the respective hand movements using different cl

Quality evaluation of wavelet functions for myopulse suppression in electrocardiogram

ECG is susceptible to parasitic myopulses due to the overlapping frequency bandwidth of ECG and EMG. EMG signal has a bandwidth of about 20-500 Hz and overlaps with the ECG frequency range. i.e. 0.05-150 Hz. These interferences occur due to movement of muscles and respiratory actions during ECG recording. Removal of EMG noise from ECG is an important criterion for proper analysis of the signal. In

Biomarker detection on Pancreatic cancer dataset using entropy based spectral clustering

Pancreatic ductal adenocarcinoma (PDAC) is one of most aggressive malignancy. The identification of Biomarker for PDAC is an ongoing challenge. The high dimensional PDAC gene expression dataset in Gene Expression Omnibus(GEO) database, is analyzed in this work. To select those genes which are relevant as well as with least redundancy among them, we use successive approaches like Filter methods and

Pre-ictal epileptic seizure prediction based on ECG signal analysis

Epileptic seizures demonstrate a clear effect of the dominating behavior of the autonomic nervous system on the cardiovascular system, especially on the Heart Rate Variation. Recording of Electroencephalogram (EEG) for detection of the onset of epileptic seizure had been used for constructing automatic seizure detection algorithm. Electrocardiogram (ECG) also can be used to evaluate Heart Rate Var

QSAR model for mast cell stabilizing activity of indolecarboxamidotetrazole compounds on human basophils

Indolecarboxamidotetrazole compounds are well known as potential anti allergic agents due to their mast cell stabilizing activity on human basophils. A quantitative structure activity relationship (QSAR) model has been generated using Multiple Linear regression (MLR) for the prediction of inhibition efficiency of indolecarboxamidotetrazole derivatives. Twenty-one compounds with their activities ex

Rough based symmetrical clustering for gene expression profile analysis

Identification of coexpressed genes is the central goal in microarray gene expression data analysis. Point symmetry-based clustering is an important unsupervised learning technique for recognizing symmetrical convex or non-convex shaped clusters. To enable fast automatic clustering of large microarray data, in this article, a distributed time-efficient scalable parallel rough set based hybrid appr

Cancer gene silencing network analysis using cellular automata

Identification of cancer pathways is the central goal in the cancer gene expression data analysis. A cellular automaton is a dynamic system with cells, which are uniform, interconnected and discrete in nature. Cellular automata are well-known methods to predict network traffics in cellular spaces. Therefore, to predict cancer pathways involved, we propose a 2-dimensional cellular automata approach

Parallel point symmetry based clustering for gene microarray data

Point symmetry-based clustering is an important unsupervised learning tool for recognizing symmetrical convex or non-convex shaped clusters, even in the microarray datasets. To enable fast clustering of this large data, in this article, a distributed space and time-efficient scalable parallel approach for point symmetry-based K-means algorithm has been proposed. A natural basis for analyzing gene

Principles for the design of a policy framework to address product life cycle impacts

Introduction: Product-oriented environmental law is an expanding, poly-thematic subsection of environmental law. First, an increasing number of policy instruments are being used at the international, European and national levels to regulate products, including mandatory performance standards, consumer subsidies, public procurement practices, product bans, taxes and charges and various kinds of man