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

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

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

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

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

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

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

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

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

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

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

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

This chapter examines the long-run relationship between public opinion, party politics, and the welfare state. It argues that when large parties receive a clear signal concerning the median voter’s position on the welfare state, vote-seeking motivations dominate and the large parties in the party system converge on the position of the median voter. When the position of the median voter is more dif

AD730TM is a novel superalloy developed for the hot section part in aero engine and gas turbine machinery with enhanced performance. The material is characterized by its excellent high temperature properties for being an alloy possible to manufacture by cast and wrought process compared to other superalloys in the same class such as Inconel718. The material with higher temperature capability means

A higher gas turbine efficiency can be achieved by increasing the operating temperature in hot sections. AD730™ is a recently-developed wrought/cast nickel-based superalloy which can maintain excellent mechanical properties above 700. However, machining of AD730™ could be a difficult task like other nickel-based superalloys. Therefore, studies are needed with respect to the machinability of this n

We consider multigrid methods for finite volume discretizations of the Reynolds averaged Navier–Stokes equations for both steady and unsteady flows. We analyze the effect of different smoothers based on pseudo time iterations, such as explicit and additive Runge–Kutta (AERK) methods. Furthermore, by deriving them from Rosenbrock smoothers, we identify some existing schemes as a class of additive W

A key challenge in developing bioinspired composites is the fabrication of well-defined 3D hierarchical structures ranging from nano to the macroscale. Herein, the development of a synthetic polymer-apatite composite realized by integrating bottom-up self-assembly and additive manufacturing (AM) is described. The resulting composite exhibits a bioinspired hierarchical structure over its 3D macrosc