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The saga of MAX IV, the first multi-bend achromat synchrotron light source

This paper describes how MAX IV, the first Multi-Bend Achromat (MBA) Synchrotron Radiation Light Source, was developed and realized. It describes the process of defining the scientific case and the development of the accelerator concepts. This was a highly interactive and intense optimization process, which went on during a long time with tight communication between the laboratory and the various

The Kärger vs bi-exponential model : Theoretical insights and experimental validations

We revise three common models accounting for water exchange in pulsed-gradient spin-echo measurements: a bi-exponential model with time-dependent water fractions, the Kärger model, and a modified Kärger model designed for restricted diffusion, e.g. inside cells. The three models are compared and applied to experimental data from yeast cell suspensions. The Kärger model and the modified Kärger mode

Longitudinal left ventricular function is globally depressed within a week of STEMI

Sixty percent of stroke volume (SV) is generated by atrioventricular plane displacement (AVPD) in a healthy left ventricle (LV). The aims were to determine the effect of ST-elevation myocardial infarction (STEMI) on AVPD and contribution of AVPD to SV and to study the relationship between AVPD and infarct size (IS) and location. Patients from CHILL-MI and MITOCARE studies with cardiovascular magne

The fracture mechanics in cutting : A comparative study on hard and soft polymeric materials

An experimental campaign has been carried out with the aim of providing an insight into the fracture processes occurring during the cutting of different types of polymers, with features ranging from typically brittle to soft hyperelastic behaviour. The steady state of cutting is investigated using a sharp thin blade, and tracking the insertion force versus the penetration displacement. For soft, h

Drivers of disruption? Estimating the Uber effect

A frequent belief is that the rise of so-called “gig work” has led to the displacement of workers in a wide range of traditional jobs. This paper examines the impacts of the flagship of the gig economy—Uber—on workers employed in conventional taxi services. Our analysis exploits newly collected data on the staggered rollout of Uber across metropolitan areas in the United States and a difference-in

Familial risk of pleural mesothelioma increased drastically in certain occupations : A nationwide prospective cohort study

Objective: We aimed to explore the effect of occupation on familial risk of pleural mesothelioma in a nationwide cohort study design. Method: The nationwide Swedish Family-Cancer Database includes all Swedes born after 1931 and their biological parents, totalling 16.1 million individuals with about 2.3 million cancer patients. Hazards ratios (HRs) were calculated adjusting for age, sex and region

Ejection fraction in left bundle branch block is disproportionately reduced in relation to amount of myocardial scar

Introduction: The relationship between left ventricular (LV) ejection fraction (EF) and LV myocardial scar can identify potentially reversible causes of LV dysfunction. Left bundle branch block (LBBB) alters the electrical and mechanical activation of the LV. We hypothesized that the relationship between LVEF and scar extent is different in LBBB compared to controls. Methods: We compared the relat

Pretreatment with ticagrelor may offset additional inhibition of platelet and coagulation activation with bivalirudin compared to heparin during primary percutaneous coronary intervention

Background: It remains unknown if bivalirudin compared to heparin confers any additional inhibition of platelet and coagulation activation during primary percutaneous coronary intervention (PPCI) after pretreatment with ticagrelor. Methods: In this substudy of VALIDATE-SWEDEHEART trial, 103 patients pretreated with ticagrelor were randomized before PPCI to heparin or bivalirudin. Blood samples wer

Improving modified differential evolution for fuzzy clustering

Differential evolution is a real value encoded evolutionary algorithm for global optimization. It has gained popularity due to its simplicity and efficiency. Use of special kind of mutation and crossover operators differentiates it from other evolutionary algorithms. In recent times, it has been widely used in different fields of science and engineering. Among recently developed various variants o

Immunoinformatics study of procyanidins as mast cell stabilizers

Background: Allergens are foreign proteins that stimulate the production of immunoglobulin E (IgE), when they come in contact with human body. These allergens after binding with IgE through FcεRI receptor, triggers the signal transduction reaction in mast cell and basophil cells, leading to allergic reactions by releasing some mediators. Four correctly written as surface-exposed tryptpphans Trp 87

Immunoinformatics based vaccine design for zea M 1 pollen allergen

Objective: Zea m1 is one of the most common aeroallergens, causing allergy. This pollen allergen, present in maize, is responsible for type I hypersensitivity reaction. Despite having available X ray crystal structure of this pollen allergen, no definite vaccine has been developed for allergic disorder in humans. Method: In our present study, an epitope-based peptide vaccine against Zea m 1 pollen

Landcover change detection using PSO-evaluated quantum CA approach on multi-temporal remote-sensing watershed images

Computer science plays a major role in image segmentation and image processing applications. Despite the computational cost, PSO evaluated QCA approaches perform comparable to or better than their crisp counterparts. This novel approach, proposed in this chapter, has been found to enhance the functionality of the CA rule base and thus enhance the established potentiality of the fuzzy-based segment

Automatic mixed pixel detection using a new hybrid Cellular automata approach on satellite image

Mixed-pixels classification in land-cover regions is a challenging task in remote sensing imagery. To classify mixed-pixels, vagueness is always the main characteristic by handling uncertainty. We propose a hybrid approach for pixel classification using Rough sets and Cellular automata models to solve this problem. Multiple belongingness and vagueness among data can be handled efficiently using Ro

Watershed image analysis using a PSO-CA hybrid approach

Pixel classification of watershed satellite image is a challenging task in remote sensing. Uses of Particle Swarm Optimisation and Cellular Automata are significant methods in watershed image segmentation. This paper proposes a method of pixel classification using a new hybrid Particle Swarm Optimization-Cellular Automata approach. The proposed unsupervised method identifies clusters using 2-Dimen

Indian river watershed image analysis using fuzzy- CA hybrid approach

Image segmentation among overlapping land cover areas in satellite images is a very crucial task. Detection of belongingness is the important problem for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of Fuzzy C-Means and Cellular automata methods. This new unsupervised method is able to detect clusters using 2-Dimensional Cellular Automa

GA optimized fuzzy controlled DPLL using discrete energy separation algorithm

In this paper a novel digital phase lock loop (DPLL) is introduced with Teager energy operator (TEO) incorporated discrete energy separation algorithm DESA2. The output of the DESA2 is controlled using genetic algorithm (GA) optimized fuzzy controller. The input and output membership functions are optimized using GA along with the input and output controller gains of the fuzzy controller. This kin

Tilaiya reservoir catchment segmentation using hybrid soft cellular approach

Image segmentation among overlapping land cover areas in satellite images is a very crucial task. Detection of belongingness is the important problem for classifying mixed pixels. This paper proposes an approach for pixel classification using a hybrid approach of Fuzzy C-Means and Cellular automata methods. This new unsupervised method is able to detect clusters using 2-Dimensional Cellular Automa

A new isotropic locality improved kernel for pattern classifications in remote sensing imagery

Kernel based learning algorithms are sensitive to the choice of appropriate kernel function and parameter setting. Classification accuracies yielded by the kernel based classifiers may show variation depending on the choice of the kernel and its associated parameters. Suggesting an efficient kernel function and effective setting of kernel parameters are thus important problems for kernel based cla

Fuzzy evaluated quantum cellular automata approach for watershed image analysis

Fuzzy approaches in a low-level image processing method to partition the homogeneous regions are important challenges in image segmentation. The analysis of the fuzziness in data produces comparable or improved solutions compared with the respective crisp approaches. The novel approach proposed in this chapter has been found to enhance the functionality of the fuzzy rule base and thus enhance the