Assembly and proving of a wave front sensing confocal Scanning Laser Ophthalmoscope

Confocal Scanning Laser Ophthalmoscopy is used to image the fundus of the living eye. In theory, this technique can be used to observe single cells of the retina. Unfortunately, vision of most eyes is decreased by higher-order aberrations, that cannot be corrected by glasses or contact lenses. This is also the reason why resolution in confocal Scanning Laser Ophthalmoscopy is not as high as expected. By the use of adaptive optics (AO) resolution can be dramatically increased. Implementing a wave front sensor into a conventional confocal Scanning Laser Ophthalmoscope (cSLO), therefore, is the first step to set up a compact adaptive-optical cSLO. In this work a Shack-Hartmann wave front sensor was implemented into a slightly modified Heidelberg Retina Tomograph (HRT) and aberrations of model eyes were measured. Results show that this system is now ready for testing on living eyes

Geometric multigrid for the gyrokinetic Poisson equation from fusion plasma applications

In order to face climate change and to preserve our ecosystem, we have to reduce the overall emission of carbon dioxide into the atmosphere. A promising addition to renewable energies is nuclear fusion. Delivering an almost infinite amount of clean and safe energy and with almost inexhaustible resources on earth, plasma fusion would solve all the world's climate and energy problems. However, being extremely complex, the reaction cannot be maintained for sufficient long time, yet, as it is extremely unstable. As the construction and operation of fusion reactors, e.g. tokamaks, is exceptionally expensive, numerical simulations are required in order to increase our knowledge about the fusion process. One existing code for plasma simulations in a tokamak is called GyselaX, in which a subroblem consists in solving a two dimensional Poisson equation on many cross-sections of the reactor geometry. The EoCoE (Energy Oriented Center of Excellence: toward exascale for energy) project, funded by the European Commission, aims for the improvement of the current solver for this equation in order to reduce the simulation times. In [1] and [2], a geometric multigrid approach using finite differences for the discretization and a combined line smoothing procedure has been developed. Additionally, an implicit extrapolation technique is used to increase the approximation order of the solution. In this master's thesis, this GmgPolar solver is detailed and implemented in C++. Moreover, several improvements have been applied to the solver and some parts of the code have been parallelised. As the full optimization and parallelisation exceeds the scope of this thesis, future work will be required, before comparing the solver with two other possible approaches and integrating it into GyselaX to reduce the simulation time. [1] Kühn, M. J.; Kruse, C.; Rüde, U. Energy-Minimizing, Symmetric Discretizations for Anisotropic Meshes and Energy Functional Extrapolation, SIAM J. Sci. Comput.Vol. 43(4), pp. A2448-A2473 (2021). [2] Kühn, M. J.; Kruse, C.; Rüde, U. Implicitly extrapolated geometric multigrid on disk-like domains for the gyrokinetic Poisson equation from fusion plasma applications, Preprint: https://hal.archives-ouvertes.fr/hal-03003307/, Submit-ted to Journal of Scientific Computing, 2021

Supporting 3rd-grade students’ model-based explanations about groundwater: A quasi-experimental study of a curricular intervention

Scientific modelling is a key practice in which K-12 students should engage to begin developing robust conceptual understanding of natural systems, including water. However, little past research has explored primary students’ learning about groundwater, engagement in scientific modelling, and/or the ways in which teachers conceptualize and cultivate model-based science learning environments. We are engaged in a multi-year project designed to support 3rd-grade students’ formulation of model-based explanations (MBE) for hydrologic phenomenon, including groundwater, through curricular and instructional support. In this quasi-experimental comparative study of five 3rd-grade classrooms, we present findings from analysis of students’ MBE generated as part of experiencing a baseline curricular intervention (Year 1) and a modelling-enhanced curricular intervention (Year 2). Findings show that students experiencing the latter version of the unit made significant gains in both conceptual understanding and reasoning about groundwater, but that these gains varied by classroom. Overall, student gains from Year 1 to Year 2 were attributed to changes in two of the five classrooms in which students were provided additional instructional supports and scaffolds to enhance their MBE for groundwater. Within these two classrooms, the teachers enacted the Year 2 curriculum in unique ways that reflected their deeper understanding about the practices of modelling. Their enactments played a critical role in supporting students’ MBE about groundwater. Study findings contribute to research on scientific modelling in elementary science learning environments and have important implications for teachers and curriculum developers

Potential of pesticide reduction and effects on pests, weeds, yield and net return in winter rye (Secale cereale L.)

Reducing the intensity of pesticide use is a societal and political issue. One way to realize this is to reduce the dose of applied pesticides. The impact of strict dose reductions on yield and net return in winter rye was examined in a longterm field trial at the experimental field of the Julius Kühn Institute in Dahnsdorf (Brandenburg) over a 13-year period (2004-2016). Pesticide treatments included a situation-related strategy (100% strategy) and two other strategies in which the doses were reduced by 25% and 50% compared to the 100% strategy. Treatment decisions were based on control thresholds in the 100% strategy. Fungal pathogens and weeds occurred in all years and had to be controlled. Insect pests were negligible. Averaged over all years, there was a significant difference of 4% in yield between the 100% strategy and the 50% strategy. In contrast, no differences were found in terms of net return. There was also no accumulation of weeds in the reduced strategies. This positive result is due to the close monitoring of the plots as well as the six-year crop rotation and shows that it is possible to reduce pesticide use in winter rye

Textile based dye-sensitized solar cells with natural dyes

Natural dyes extracted from hibiscus petals, elderberries and mallow flowers were investigated in dye-sensitized solar cells. Two approaches were followed: 1. Hybrid glass/fabric cells with titanium dioxide on glass as working electrode and a textile counter electrode; 2. hybrid fabric/glass cells with zinc oxide as working electrode on textile and a glass counter electrode. The zinc oxide layer on cotton was prepared by electroless deposition whereas the titanium dioxide coated glass electrodes were obtained directly from the manufacturer. In both cases the redox couple consisted of iodine / triiodide and the counter electrode was based on an electrically conductive fabric

Pancreatoduodenectomy with or without Pyloric Preservation: A Clinical Outcomes Comparison

Pyloric preservation (PP) can frequently be performed at the time of pancreatoduodenectomy (PD), although some reports have linked it to inferior outcomes such as delayed gastric emptying (DGE). We reviewed records in a single-surgeon practice to assess outcomes after PD with or without PP. There were 133 PDs with 67 PPPDs and 66 PDs. Differences between PPPD and PD groups included cancer frequency, tumor size, OR time, blood loss, and transfusion rate. However, postoperative morbidity rate and grade, NG tube duration, NGT reinsertion rate, DGE, and length of stay were similar. There was no difference among patients with pancreatic cancer. No detrimental outcomes are associated with pyloric preservation during PD. Greater intraoperative ease and superior survival in the PPPD group are due to confounding, tumor-related variables in this nonrandomized comparison. Nevertheless, we intend to continue the use of PP with our technique in patients who meet the stated criteria

Anatomy Completor: A Multi-class Completion Framework for 3D Anatomy Reconstruction

In this paper, we introduce a completion framework to reconstruct the geometric shapes of various anatomies, including organs, vessels and muscles. Our work targets a scenario where one or multiple anatomies are missing in the imaging data due to surgical, pathological or traumatic factors, or simply because these anatomies are not covered by image acquisition. Automatic reconstruction of the missing anatomies benefits many applications, such as organ 3D bio-printing, whole-body segmentation, animation realism, paleoradiology and forensic imaging. We propose two paradigms based on a 3D denoising auto-encoder (DAE) to solve the anatomy reconstruction problem: (i) the DAE learns a many-to-one mapping between incomplete and complete instances; (ii) the DAE learns directly a one-to-one residual mapping between the incomplete instances and the target anatomies. We apply a loss aggregation scheme that enables the DAE to learn the many-to-one mapping more effectively and further enhances the learning of the residual mapping. On top of this, we extend the DAE to a multiclass completor by assigning a unique label to each anatomy involved. We evaluate our method using a CT dataset with whole-body segmentations. Results show that our method produces reasonable anatomy reconstructions given instances with different levels of incompleteness (i.e., one or multiple random anatomies are missing). Codes and pretrained models are publicly available at https://github.com/Jianningli/medshapenet-feedback/ tree/main/anatomy-completorComment: 15 page