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This article deals with the early development of the Jesus prayer in Early Christian monasticism of the 4th to the 7th century. It proceeds in two steps. First, a quite uniform matrix of practices and aims related to three early monastic authors (John Cassian, Diadochus of Photike, and John Climacus) is discerned. It is evident that the practice is not clearly defined in this period. It is also ap
Surface-enhanced Raman spectroscopy (SERS) is an ultrasensitive vibrational fingerprinting technique widely used in analytical and biosensing applications. For intracellular sensing, typically gold nanoparticles (AuNPs) are employed as transducers to enhance the otherwise weak Raman spectroscopy signals. Thus, the signature patterns of the molecular nanoenvironment around intracellular unlabeled A
This licentiate thesis concerns advanced digital product catalogues, with the main focus on product presentation. A computer based digital product catalogue opens new possibilities for advanced product presentation and integration into the existing compute environment. Several new possibilities for product presentation become available. By use of photorealistic rendering techniques, images showing
Detaljhandeln är en bransch som har fått utstå kritik för att ha svårigheter med innovation. Samtidigt präglas dagens värld av globalisering där information sprids snabbt, bland annat är hållbarhet och grön konsumtion trender som blir större. Innovation är ett begrepp som i de flesta fall associeras med tekniska aspekter, för handeln kan det däremot handla om nya produkter eller affärsmodeller. Hä
Bakgrund: tidigare studier visar att kvinnor upplever att föräldragrupper inte förbereder dem för amning. Det är viktigt att studera hur kvinnor upplever amningsinformation under graviditeten då detta kan öka amningsfrekvensen. Syfte: Att undersöka kvinnors upplevelse av amningsinformation under graviditeten. Metod: en kvalitativ studie gjordes och elva kvinnor intervjuades. Kvalitativ innehålls
Geospatial data have been pervasive and indispensable for various real-world application of e.g. urban planning, traffic analysis and emergency response. To this end, the data integration and knowledge transfer are two prominent issues for augmenting the use of geospatial data and knowledge. In order to address these issue, Semantic Web technologies have been considerably adopted in geospatial dom
Three-dimensional (3D), city models have been applied in a variety of fields. One of the main problems in 3D city model utilization, however, is the large volume of data. In this paper, a method is proposed to generalize the 3D building objects in 3D city models at different levels of detail, and to combine multiple Levels of Detail (LODs) for a progressive distribution and visualization of the ci
With the growth of mobile computing, users will have simultaneous access to multiple overlaid networks, each with different characteristics, services and costs. This paper introduces TOMTEN (TOtal Management Of Transmissions for the ENd-user), a framework for managing resources in both this type of environment as well as the traditional single network environment. TOMTEN is a reactive framework th
With the growth of mobile computing, users will have simultaneous access to multiple networks, each with different characteristics, services and costs. This paper introduces TOMTEN (TOtal Management Of Transmissions for the ENd-user), a framework for managing resources in this environment. TOMTEN is a reactive framework that is only active when either the application is started up or the user indi
Glycoside hydrolase (GH) enzymes apply acid/base chemistry to catalyze the decomposition of complex carbohydrates. These ubiquitous enzymes accept protons from solvent and donate them to substrates at close to neutral pH by modulating the pKa values of key side chains during catalysis. However, it is not known how the catalytic acid residue acquires a proton and transfers it efficiently to the sub
ABSTRACT Background: Prediabetes is a global epidemic with rising prevalence rates, but its diagnosis based on traditional risk factors is challenging. Application of novel machine-intelligence based methods to public health databases could provide valuable insights into the disease process. Aim: To build predictive models to elucidate the determinants of prediabetes using machine learning algorit
