Making Historical Gyroscopes Alive-2D and 3D Preservations by Sensor Fusion and Open Data Access.

The preservation of cultural heritage assets of all kind is an important task for modern civilizations. This also includes tools and instruments that have been used in the previous decades and centuries. Along with the industrial revolution 200 years ago, mechanical and electrical technologies emerged, together with optical instruments. In the meantime, it is not only museums who showcase these developments, but also companies, universities, and private institutions. Gyroscopes are fascinating instruments with a history dating back 200 years. When J.G.F. Bohnenberger presented his machine to his students in 1810 at the University of Tuebingen, Germany, nobody could have foreseen that this fascinating development would be used for complex orientation and positioning. At the University of Stuttgart, Germany, a collection of 160 exhibits is available and in transition towards their sustainable future. Here, the systems are digitized in 2D, 2.5D, and 3D and are made available for a worldwide community using open access platforms. The technologies being used are computed tomography, computer vision, endoscopy, and photogrammetry. We present a novel workflow for combining voxel representations and colored point clouds, to create digital twins of the physical objects with 0.1 mm precision. This has not yet been investigated and is therefore pioneering work. Advantages and disadvantages are discussed and suggested work for the near future is outlined in this new and challenging field of tech heritage digitization.

Influence of single and dual tasks on gait stability and gait speed in the elderly : An explorative study.

BACKGROUND: Gait stability during dual tasks is important for elderly persons, especially for elderly individuals in need of care. A study was conducted to assess gait stability by using Lyapunov exponents (λS) during single task and dual task conditions in independently living elderly people (Go-Goes) and elderly people in need of care (No-Goes). MATERIAL AND METHODS: This study was conducted with 26 participants (average age 82 ± 9.4 years) who were allocated to the Go-Goes or No-Goes group. Outcomes were mediolateral and vertical Lyapunov exponents (λS) from accelerometer data and gait speed under single task and dual task conditions. RESULTS: In both groups significantly higher mediolateral and vertical Lyapunov exponent values as well as significantly lower walking speeds under dual task conditions were found in both groups. The effect sizes were small to moderate for mediolateral λS and large for vertical λS and these differences remained when the analyses were adjusted for walking speed. CONCLUSION: Elderly people showed lower gait stability and gait speed under dual task conditions compared to single task conditions.

FDRN: A fast deformable registration network for medical images.

PURPOSE: Deformable image registration is a fundamental task in medical imaging. Due to the large computational complexity of deformable registration of volumetric images, conventional iterative methods usually face the tradeoff between the registration accuracy and the computation time in practice. In order to boost the performance of deformable registration in both accuracy and runtime, we propose a fast unsupervised convolutional neural network for deformable image registration. METHODS: The proposed registration model FDRN possesses a compact encoder-decoder network architecture which employs a pair of fixed and moving images as input and outputs a three-dimensional displacement vector field (DVF) describing the offsets between the corresponding voxels in the fixed and moving images. In order to efficiently utilize the memory resources and enlarge the model capacity, we adopt additive forwarding instead of channel concatenation and deepen the network in each encoder and decoder stage. To facilitate the learning efficiency, we leverage skip connection within the encoder and decoder stages to enable residual learning and employ an auxiliary loss at the bottom layer with lowest resolution to involve deep supervision. Particularly, the low-resolution auxiliary loss is weighted by an exponentially decayed parameter during the training phase. In conjunction with the main loss in high-resolution grid, a coarse-to-fine learning strategy is achieved. Last but not least, we involve a proposed multi-label segmentation loss (SL) to improve the network performance in Dice score in case the segmentation prior is available. Comparing to the SL using average Dice score, the proposed SL does not require additional memory in the training phase and improves the registration accuracy efficiently. RESULTS: We evaluated FDRN on multiple brain MRI datasets from different aspects including registration accuracy, model generalizability, and model analysis. Experimental results demonstrate that FDRN performs better than the state-of-the-art registration method VoxelMorph by 1.46% in Dice score in LPBA40. In addition to LPBA40, FDRN obtains the best Dice and NCC among all the investigated methods in the unseen MRI datasets including CUMC12, MGH10, ABIDE, and ADNI by a large margin. CONCLUSIONS: The proposed FDRN provides better performance than the existing state-of-the-art registration methods for brain MR images by resorting to the compact autoencoder structure and efficient learning. Additionally, FDRN is a generalized framework for image registration which is not confined to a particular type of medical images or anatomy.

A JND-Based Pixel-Domain Algorithm and Hardware Architecture for Perceptual Image Coding.

This paper presents a hardware efficient pixel-domain just-noticeable difference (JND) model and its hardware architecture implemented on an FPGA. This JND model architecture is further proposed to be part of a low complexity pixel-domain perceptual image coding architecture, which is based on downsampling and predictive coding. The downsampling is performed adaptively on the input image based on regions-of-interest (ROIs) identified by measuring the downsampling distortions against the visibility thresholds given by the JND model. The coding error at any pixel location can be guaranteed to be within the corresponding JND threshold in order to obtain excellent visual quality. Experimental results show the improved accuracy of the proposed JND model in estimating visual redundancies compared with classic JND models published earlier. Compression experiments demonstrate improved rate-distortion performance and visual quality over JPEG-LS as well as reduced compressed bit rates compared with other standard codecs such as JPEG 2000 at the same peak signal-to-perceptible-noise ratio (PSPNR). FPGA synthesis results targeting a mid-range device show very moderate hardware resource requirements and over 100 Megapixel/s throughput of both the JND model and the perceptual encoder.

The change of longitudinal relaxation rate in oxygen enhanced pulmonary MRI depends on age and BMI but not diffusing capacity of carbon monoxide in healthy never-smokers.

OBJECTIVE: Oxygen enhanced pulmonary MRI is a promising modality for functional lung studies and has been applied to a wide range of pulmonary conditions. The purpose of this study was to characterize the oxygen enhancement effect in the lungs of healthy, never-smokers, in light of a previously established relationship between oxygen enhancement and diffusing capacity of carbon monoxide in the lung (DL,CO) in patients with lung disease. METHODS: In 30 healthy never-smoking volunteers, an inversion recovery with gradient echo read-out (Snapshot-FLASH) was used to quantify the difference in longitudinal relaxation rate, while breathing air and 100% oxygen, ΔR1, at 1.5 Tesla. Measurements were performed under multiple tidal inspiration breath-holds. RESULTS: In single parameter linear models, ΔR1 exhibit a significant correlation with age (p = 0.003) and BMI (p = 0.0004), but not DL,CO (p = 0.33). Stepwise linear regression of ΔR1 yields an optimized model including an age-BMI interaction term. CONCLUSION: In this healthy, never-smoking cohort, age and BMI are both predictors of the change in MRI longitudinal relaxation rate when breathing oxygen. However, DL,CO does not show a significant correlation with the oxygen enhancement. This is possibly because oxygen transfer in the lung is not diffusion limited at rest in healthy individuals. This work stresses the importance of using a physiological model to understand results from oxygen enhanced MRI.

Light scattering microscopy measurements of single nuclei compared with GPU-accelerated FDTD simulations.

Single cell nuclei were investigated using two-dimensional angularly and spectrally resolved scattering microscopy. We show that even for a qualitative comparison of experimental and theoretical data, the standard Mie model of a homogeneous sphere proves to be insufficient. Hence, an accelerated finite-difference time-domain method using a graphics processor unit and domain decomposition was implemented to analyze the experimental scattering patterns. The measured cell nuclei were modeled as single spheres with randomly distributed spherical inclusions of different size and refractive index representing the nucleoli and clumps of chromatin. Taking into account the nuclear heterogeneity of a large number of inclusions yields a qualitative agreement between experimental and theoretical spectra and illustrates the impact of the nuclear micro- and nanostructure on the scattering patterns.

Determining the Numerical Stability of Quantum Chemistry Algorithms.

We present a simple, broadly applicable method for determining the numerical properties of quantum chemistry algorithms. The method deliberately introduces random numerical noise into computations, which is of the same order of magnitude as the floating point precision. Accordingly, repeated runs of an algorithm give slightly different results, which can be analyzed statistically to obtain precise estimates of its numerical stability. This noise is produced by automatic code injection into regular compiler output, so that no substantial programming effort is required, only a recompilation of the affected program sections. The method is applied to investigate: (i) the numerical stability of the three-center Obara-Saika integral evaluation scheme for high angular momenta, (ii) if coupled cluster perturbative triples can be evaluated with single precision arithmetic, (iii) how to implement the density fitting approximation in Møller-Plesset perturbation theory (MP2) most accurately, and (iv) which parts of density fitted MP2 can be safely evaluated with single precision arithmetic. In the integral case, we find a numerical instability in an equation that is used in almost all integral programs. Due to the results of (ii) and (iv), we conjecture that single precision arithmetic can be applied whenever a calculation is done in an orthogonal basis set and excessively long linear sums are avoided.

Szentiamide, an N-formylated cyclic depsipeptide from Xenorhabdus szentirmaii DSM 16338T.

Szentiamide (1) a new cyclic hexadepsipeptide was isolated from the culture broth of the entomopathogenic bacterium Xenorhabdus szentirmaii DSM 16338T. The structure was elucidated by analysis of one- and two-dimensional NMR spectra and high resolution mass spectrometry. The amino acids were determined to be D-leucine, L-threonine, D-phenylalanine, D-valine, L-tyrosine and L-tryptophane after hydrolysis and derivatization with D-FDVA [Nalpha-(2,4-dinitro-5-fluorophenyl)-D-valinamide].