272 research outputs found

    Infrared imaging and acoustic sizing of a bubble inside a MEMS piezo ink channel

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    Piezo drop-on-demand inkjet printers are used in an increasing number of applications because of their reliable deposition of droplets onto a substrate. Droplets of a few picoliters are ejected from an inkjet nozzle at frequencies of up to 100 kHz. However, the entrapment of an air microbubble in the ink channel can severely impede the productivity and reliability of the printing system. The air bubble disturbs the channel acoustics, resulting in disrupted drop formation or failure of the jetting process. Here we study a micro-electro-mechanical systems-based printhead. By using the actuating piezo transducer in receive mode, the acoustical field inside the channel was monitored, clearly identifying the presence of an air microbubble inside the channel during failure of the jetting process. The infrared visualization technique allowed for the accurate sizing of the bubble, including its dynamics, inside the intact printhead. A model was developed to calculate the mutual interaction between the channel acoustics and the bubble dynamics. The model was validated by simultaneous acoustical and infrared detection of the bubble. The model can predict the presence and size of entrapped air bubbles inside an operating ink channel purely from the acoustic response

    Care trajectories of chronically ill older adult patients discharged from hospital:a quantitative cross-sectional study using health insurance claims data

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    Background For older adults, a good transition from hospital to the primary or long-term care setting can decrease readmissions. This paper presents the 6-month post-discharge healthcare utilization of older adults and describes the numbers of readmissions and deaths for the most frequently occurring aftercare arrangements as a starting point in optimizing the post-discharge healthcare organization. Methods This cross-sectional study included older adults insured with the largest Dutch insurance company. We described the utilization of healthcare within 180 days after discharge from their first hospital admission of 2015 and the most frequently occurring combinations of aftercare in the form of geriatric rehabilitation, community nursing, long-term care, and short stay during the first 90 days after discharge. We calculated the proportion of older adults that was readmitted or had died in the 90-180 days after discharge for the six most frequent combinations. We performed all analyses in the total group of older adults and in a sub-group of older adults who had been hospitalized due to a hip fracture. Results A total of 31.7% of all older adults and 11.4% of the older adults with a hip fracture did not receive aftercare. Almost half of all older adults received care of a community nurse, whereas less than 5% received long-term home care. Up to 18% received care in a nursing home during the 6 months after discharge. Readmissions were lowest for older adults with a short stay and highest in the group geriatric rehabilitation + community nursing. Mortality was lowest in the total group of older aldults and subgroup with hip fracture without aftercare. Conclusions The organization of post-discharge healthcare for older adults may not be organized sufficiently to guarantee appropriate care to restore functional activity. Although receiving aftercare is not a clear predictor of readmissions in our study, the results do seem to indicate that older adults receiving community nursing in the first 90 days less often die compared to older adults with other types of aftercare or no aftercare. Future research is necessary to examine predictors of readmissions and mortality in both older adult patients discharged from hospital.</p

    Fuzzy Fibers: Uncertainty in dMRI Tractography

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    Fiber tracking based on diffusion weighted Magnetic Resonance Imaging (dMRI) allows for noninvasive reconstruction of fiber bundles in the human brain. In this chapter, we discuss sources of error and uncertainty in this technique, and review strategies that afford a more reliable interpretation of the results. This includes methods for computing and rendering probabilistic tractograms, which estimate precision in the face of measurement noise and artifacts. However, we also address aspects that have received less attention so far, such as model selection, partial voluming, and the impact of parameters, both in preprocessing and in fiber tracking itself. We conclude by giving impulses for future research

    Voxel-wise comparisons of cellular microstructure and diffusion-MRI in mouse hippocampus using 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND)

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    A key challenge in medical imaging is determining a precise correspondence between image properties and tissue microstructure. This comparison is hindered by disparate scales and resolutions between medical imaging and histology. We present a new technique, 3D Bridging of Optically-clear histology with Neuroimaging Data (3D-BOND), for registering medical images with 3D histology to overcome these limitations. Ex vivo 120 × 120 × 200 μm resolution diffusion-MRI (dMRI) data was acquired at 7 T from adult C57Bl/6 mouse hippocampus. Tissue was then optically cleared using CLARITY and stained with cellular markers and confocal microscopy used to produce high-resolution images of the 3D-tissue microstructure. For each sample, a dense array of hippocampal landmarks was used to drive registration between upsampled dMRI data and the corresponding confocal images. The cell population in each MRI voxel was determined within hippocampal subregions and compared to MRI-derived metrics. 3D-BOND provided robust voxel-wise, cellular correlates of dMRI data. CA1 pyramidal and dentate gyrus granular layers had significantly different mean diffusivity (p > 0.001), which was related to microstructural features. Overall, mean and radial diffusivity correlated with cell and axon density and fractional anisotropy with astrocyte density, while apparent fibre density correlated negatively with axon density. Astrocytes, axons and blood vessels correlated to tensor orientation

    Ascendancy of weekly low-dose methotrexate in usual care of rheumatoid arthritis from 1980 to 2004 at two sites in Finland and the United States

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    Objectives. To analyse consecutive patients with RA in usual rheumatology care between 1980 and 2004 at two settings for the proportion of patients taking MTX, interval from patient presentation to MTX prescription and radiographic and functional status outcomes

    Structural neuroimaging correlates of allelic variation of the BDNF val66met polymorphism.

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    BACKGROUND: The brain-derived neurotrophic factor (BDNF) val66met polymorphism is associated with altered activity dependent secretion of BDNF and a variable influence on brain morphology and cognition. Although a met-dose effect is generally assumed, to date the paucity of met-homozygotes have limited our understanding of the role of the met-allele on brain structure. METHODS: To investigate this phenomenon, we recruited sixty normal healthy subjects, twenty in each genotypic group (val/val, val/met and met/met). Global and local morphology were assessed using voxel based morphometry and surface reconstruction methods. White matter organisation was also investigated using tract-based spatial statistics and constrained spherical deconvolution tractography. RESULTS: Morphological analysis revealed an "inverted-U" shaped profile of cortical changes, with val/met heterozygotes most different relative to the two homozygous groups. These results were evident at a global and local level as well as in tractography analysis of white matter fibre bundles. CONCLUSION: In contrast to our expectations, we found no evidence of a linear met-dose effect on brain structure, rather our results support the view that the heterozygotic BDNF val66met genotype is associated with cortical morphology that is more distinct from the BDNF val66met homozygotes. These results may prove significant in furthering our understanding of the role of the BDNF met-allele in disorders such as Alzheimer's disease and depression

    Fusion in diffusion MRI for improved fibre orientation estimation: an application to the 3T and 7T data of the Human Connectome Project

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    Determining the acquisition parameters in diffusion magnetic resonance imaging (dMRI) is governed by a series of trade-offs. Images of lower resolution have less spatial specificity but higher signal to noise ratio (SNR). At the same time higher angular contrast, important for resolving complex fibre patterns, also yields lower SNR. Considering these trade-offs, the Human Connectome Project (HCP) acquires high quality dMRI data for the same subjects at different field strengths (3T and 7T), which are publically released. Due to differences in the signal behavior and in the underlying scanner hardware, the HCP 3T and 7T data have complementary features in k- and q-space. The 3T dMRI has higher angular contrast and resolution, while the 7T dMRI has higher spatial resolution. Given the availability of these datasets, we explore the idea of fusing them together with the aim of combining their benefits. We extend a previously proposed data-fusion framework and apply it to integrate both datasets from the same subject into a single joint analysis. We use a generative model for performing parametric spherical deconvolution and estimate fibre orientations by simultaneously using data acquired under different protocols. We illustrate unique features from each dataset and how they are retained after fusion. We further show that this allows us to complement benefits and improve brain connectivity analysis compared to analyzing each of the datasets individually
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