structural investigations of SiO₂-containing phosphate glasses

The incorporation of SiO₂ into phosphate glasses is interesting in view of the development of phosphatic biomaterials. The present investigation is concerned with the incorporation of SiO₂ into phosphate base glasses possessing different phosphate structures. Due to their structural characteristics, they can be classified into three groups: glasses with long phosphate chains or rings formed by Q² phosphate structural groups, glasses with shorter phosphate chains formed by Q² and Q¹ groups and glasses with phosphate invert glass structure, possessing ortho(Q°)- and pyrophosphate groups (two Q¹ groups) exclusively. The structures of these glasses in dependence on the incorporated silica were investigated by transmission electron microscopy and by ³¹P MAS NMR. The principles of incorporation are discussed

Übergangssystem

ÜBERGANGSSYSTEM Regionales Übergangsmanagement Berlin (Rights reserved) (-) Issue1 Bestandsaufnahmen (Rights reserved) ( - ) Issue2 Berufsorientierung (Rights reserved) ( - ) Issue3 Übergangssystem (Rights reserved) ( - ) Issue4 Berufswegebegleitung (Rights reserved) ( - ) Issue5 Projektbilanz (Rights reserved) ( -

Bioactive coatings of glass-ceramics on metals

To combine the mechanical properties of high-strength base metals with the biological properties of bioactive materials, coatings of BIOVERIT® glasses and glass-ceramics on CoCr alloys and titanium have been produced. Different kinds of coating processes have been used: dipping, sputtering, plasma spraying, sintering and pasting. Dipping and pasting seem not to be suitable to produce layers because of cracks and low adhesion strength of the coatings (dipping) and the limitations in relation to the implant shape and the thickness of the layers (pasting). Using sputter techniques it is possible to produce dense layers ( < 10µim) with a high adhesion strength. Plasma spraying resuhed in layers with a thickness of 50 to 300µim, but during the plasma spraying process there is a partial evaporation of the highly volatile glass components. Sintering processes are very suitable to produce layers with a high adhesion strength; these layers are long term stable in simulated body fluid

No optical coherence tomography changes in premanifest Huntington's disease mutation carriers far from disease onset.

BACKGROUND Spectral-domain optical coherence tomography (OCT) may detect retinal changes as a biomarker in neurodegenerative diseases like manifest Huntington's disease (HD). We investigate macular retinal layer thicknesses in a premanifest HD (pre-HD) cohort and healthy controls (HC). METHODS Pre-HD mutation carriers underwent standardized ratings and a preset macular OCT scan. Thickness values were determined for each sector of all macular retinal layers, the mean of all sectors and the mean of the inner ring (IR, 3 mm) after segmentation (Heyex segmentation batch). HC were retrospectively included from an existing database. The IR thickness of the ganglion cell layer (GCL), retinal nerve fiber layer (RNFL), GCL + inner plexiform layer (GCIPL), and total retina were included in the exploratory correlation analyses with paraclinical ratings and compared to HC. RESULTS The analyses comprised n = 24 pre-HD participants (n = 10 male, n = 14 female) and n = 38 HC (n = 14 male, n = 24 female). Retinal layer parameters did not correlate with paraclinical ratings. Expected correlations between established HD biomarkers were robust. The IR thicknesses of the GCL, GCIPL, and total retina did not differ between pre-HD and HC. The IR thickness of the RNFL was significantly higher in pre-HD participants (pre-HD: 23.22 μm (standard deviation 2.91), HC: 21.26 μm (1.90), p = .002). DISCUSSION In this cross-sectional cohort of genetically determined pre-HD participants, neurodegenerative features were not detected with retinal layer segmentation. Since our pre-HD collective was more than 16 years before disease onset, OCT may not be sensitive enough to detect early changes

Trace Clustering for User Behavior Mining

Business information systems support a large variety of business processes and tasks, yet organizations rarely understand how users interact with these systems. User Behavior Mining aims to address this by applying process mining techniques to UI logs, i.e., detailed records of interactions with a system\u27s user interface. Insights gained from this type of data hold great potential for usability engineering and task automation, but the complexity of UI logs can make them challenging to analyze. In this paper, we explore trace clustering as a means to structure UI logs and reduce this complexity. In particular, we apply different trace clustering approaches to a real-life UI log and show that the cluster-level process models reveal useful information about user behavior. At the same time, we find configurations in which trace clustering fails to generate satisfactory partitions. Our results also demonstrate that recently proposed representation learning techniques for process traces can be effectively employed in a realistic setting

Driving ability and predictors for driving performance in Multiple Sclerosis: A systematic review

Objective: To provide an overview of the evidence on driving ability in persons with multiple sclerosis (PwMS), specifically to (i) study the impact of MS impairment on driving ability and (ii) evaluate predictors for driving performance in MS. Methods: To identify relevant studies, different electronic databases were screened in accordance with PRISMA guidelines; this includes reference lists of review articles, primary studies, and trial registers for protocols. Furthermore, experts in the field were contacted. Two reviewers independently screened titles, abstracts, and full-texts to identify relevant articles targeting driving in people with MS that investigated driving-related issues with a formal driving assessment (defined as either an on-road driving assessment; or naturalistic driving in a car equipped with video cameras to record the driving; or a driving simulator with a steering wheel, a brake pedal, and an accelerator). Results: Twenty-four publications, with 15 unique samples (n = 806 PwMS), were identified. To assess driving ability, on-road tests (14 papers) and driving simulators (10 papers) were used. All studies showed moderate to high study quality in the CASP assessment. About 6 to 38% of PwMS failed the on-road tests, showing difficulties in different areas of driving. Similarly, PwMS showed several problems in driving simulations. Cognitive and visual impairment appeared to most impact driving ability, but the evidence was insufficient and inconsistent. Conclusion: There is an urgent need for more research and standardized guidelines for clinicians as one in five PwMS might not be able to drive safely. On-road tests may be the gold standard in assessing driving ability, but on-road protocols are heterogeneous and not infallible. Driving simulators assess driving ability in a standardized way, but without standardized routes and driving outcomes, comparability between studies is difficult. Different aspects, such as cognitive impairment or vision problems, impact driving ability negatively and should be taken into consideration when making decisions about recommending driving cessation.publishedVersio

Experimental realization of a 3D long-range random hopping model

Randomness and disorder have strong impact on transport processes in quantum systems and give rise to phenomena such as Anderson localization [1-3], many-body localization [4] or glassy dynamics [5]. Their characteristics thereby depend on the strength and type of disorder. An important class are hopping models, where particles or excitations move through a system which has randomized couplings. This includes, e.g., spin glasses [5], coupled optical waveguides [6], or NV center arrays [7]. They are also key to understand excitation transport in molecular and biological systems, such as light harvesting complexes [8]. In many of those systems, the microscopic coupling mechanism is provided by the dipole-dipole interaction. Rydberg systems [9] are therefore a natural candidate to study random hopping models. Here, we experimentally study a three-dimensional many-body Rydberg system with random dipole-dipole couplings. We measure the spectrum of the many-body system and find good agreement with an effective spin model. We also find spectroscopic signatures of a localization-delocalization transition. Our results pave the way to study transport processes and localization phenomena in random hopping models in detail. The inclusion of strong correlations is experimentally straightforward and will allow to study the interplay between random hopping and localization in strongly interacting systems.Comment: 7 pages, 4 figure

Speckle-tracking echocardiography combined with imaging mass spectrometry assesses region-dependent alterations

Left ventricular (LV) contraction is characterized by shortening and thickening of longitudinal and circumferential fibres. To date, it is poorly understood how LV deformation is altered in the pathogenesis of streptozotocin (STZ)-induced type 1 diabetes mellitus-associated diabetic cardiomyopathy and how this is associated with changes in cardiac structural composition. To gain further insights in these LV alterations, eight-week-old C57BL6/j mice were intraperitoneally injected with 50 mg/kg body weight STZ during 5 consecutive days. Six, 9, and 12 weeks (w) post injections, echocardiographic analysis was performed using a Vevo 3100 device coupled to a 30-MHz linear-frequency transducer. Speckle-tracking echocardiography (STE) demonstrated impaired global longitudinal peak strain (GLS) in STZ versus control mice at all time points. 9w STZ animals displayed an impaired global circumferential peak strain (GCS) versus 6w and 12w STZ mice. They further exhibited decreased myocardial deformation behaviour of the anterior and posterior base versus controls, which was paralleled with an elevated collagen I/III protein ratio. Additionally, hypothesis-free proteome analysis by imaging mass spectrometry (IMS) identified regional- and time-dependent changes of proteins affecting sarcomere mechanics between STZ and control mice. In conclusion, STZ-induced diabetic cardiomyopathy changes global cardiac deformation associated with alterations in cardiac sarcomere proteins

Crowd-sourced plant occurrence data provide a reliable description of macroecological gradients

Deep learning algorithms classify plant species with high accuracy, and smartphone applications leverage this technology to enable users to identify plant species in the field. The question we address here is whether such crowd-sourced data contain substantial macroecological information. In particular, we aim to understand if we can detect known environmental gradients shaping plant co-occurrences. In this study we analysed 1 million data points collected through the use of the mobile app Flora Incognita between 2018 and 2019 in Germany and compared them with Florkart, containing plant occurrence data collected by more than 5000 floristic experts over a 70-year period. The direct comparison of the two data sets reveals that the crowd-sourced data particularly undersample areas of low population density. However, using nonlinear dimensionality reduction we were able to uncover macroecological patterns in both data sets that correspond well to each other. Mean annual temperature, temperature seasonality and wind dynamics as well as soil water content and soil texture represent the most important gradients shaping species composition in both data collections. Our analysis describes one way of how automated species identification could soon enable near real-time monitoring of macroecological patterns and their changes, but also discusses biases that must be carefully considered before crowd-sourced biodiversity data can effectively guide conservation measures