670 research outputs found

    Concordane of OSTA and lumbar spine BMD by DXA in identifying risk of osteoporosis

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    OBJECTIVE: To investigate the accuracy of Osteoporosis Self-assessment Tool for Asians (OSTA) in identifying the risk of osteoporosis in postmenopausal women. To validate use of OSTA risk index by comparing it with the bone mineral density (BMD) of lumbar spine measured by dual energy X-ray absorptiometry (DXA). METHODS: The data of lumbar spine BMD (LS BMD) measurements by DXA of 218 postmenopausal women of Han nationality in Sichuan province were compared with OSTA risk index. The concordance of OSTA and LS BMD were calculated and analyzed by fourfold table and receiver operating characteristic (ROC) curve. RESULTS: The prevalence of osteoporosis in these women was 40.4% and 61.5%, with the LS BMD T score cutoffs -2.5 and -2.0, respectively. The sensitivity, specificity, and accuracy of OSTA risk index compared with T score cutoff -2.5 of LS BMD were 59.1%, 56.9% and 57.8%, respectively, while they were 57.5%, 63.1%, 59.6% by T score cutoff -2.0. CONCLUSION: For identifying risk of osteoporosis, the concurrence was lower than those reported studies when comparing LS BMD measurements to OSTA risk index in Chinese Han nationality postmenopausal women of Sichuan province. Physicians should identify women who need BMD measurement according to more factors rather than age and body weight

    Preparation of Kaolin Composites and Its Adsorption for Sb(Ⅲ)

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    Antimony is an important element in the production of flame retardants and semiconductor materials. In the process of antimony mining, it may cause local environmental pollution, which has adverse effects on human health, and the development of economical and efficient adsorbents to remove antimony from wastewater has become a hot research topic. In this paper, the hydrothermal synthesis method was adopted, and purified Kaolin was selected as the carrier, potassium permanganate, manganese chloride and ferric chloride are the metal sources, urea is the precipitant, and sodium dodecyl benzene sulfonate is the structure guide agent. Under the conditions of 5% mass fraction of dispersant, loading temperature of 140 ℃, reaction time of 8 h, mass ratio of iron to manganese of 1.84:1, and mass of precipitant of 0.9 g, the composites prepared were effective in adsorbing the Sb(Ⅲ) from the wastewater. The optimum adsorption efficiency of the prepared composites on Sb(Ⅲ) is 92.83%, which showed excellent adsorption performance

    Computer simulation of the reliability of wire bonds and ribbon bonds in power electronics modules

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    Aluminium wires are widely used in power electronics modules to connect power semiconductor devices and other parts of the module electrically. Recently, other interconnect techniques have been proposed such as ribbon bond to improve the reliability, performance and reduce costs of power modules. The reliability of ribbon bond technique for an IGBT power module under power cycling is compared with that of conventional wire bond in this study using electro-thermal nonlinear Finite Element Analysis. The results showed that a single ribbon of 2000μm x 200μm will replace three wire bonds of 400μm in diameter to achieve a similar module temperature distribution under same power load. Using the equivalent plastic strain increment per cycle, it is seen that the ribbon bond is more reliable than the wire bonds. The impact of neglecting joule heat in the wire/ribbon bonds during power cycling simulation has also been investigated

    Hepatocyte Injury Induced by Contrast‐Enhanced Diagnostic Ultrasound

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/149493/1/jum14883_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/149493/2/jum14883.pd

    Big-model Driven Few-shot Continual Learning

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    Few-shot continual learning (FSCL) has attracted intensive attention and achieved some advances in recent years, but now it is difficult to again make a big stride in accuracy due to the limitation of only few-shot incremental samples. Inspired by distinctive human cognition ability in life learning, in this work, we propose a novel Big-model driven Few-shot Continual Learning (B-FSCL) framework to gradually evolve the model under the traction of the world's big-models (like human accumulative knowledge). Specifically, we perform the big-model driven transfer learning to leverage the powerful encoding capability of these existing big-models, which can adapt the continual model to a few of newly added samples while avoiding the over-fitting problem. Considering that the big-model and the continual model may have different perceived results for the identical images, we introduce an instance-level adaptive decision mechanism to provide the high-level flexibility cognitive support adjusted to varying samples. In turn, the adaptive decision can be further adopted to optimize the parameters of the continual model, performing the adaptive distillation of big-model's knowledge information. Experimental results of our proposed B-FSCL on three popular datasets (including CIFAR100, minilmageNet and CUB200) completely surpass all state-of-the-art FSCL methods.Comment: 9 pages 6 figure

    Quantitative assessment of damage during MCET: a parametric study in a rodent model

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    Abstract Background Myocardial cavitation-enabled therapy (MCET) has been proposed as a means to achieve minimally invasive myocardial reduction using ultrasound to produce scattered microlesions by cavitating contrast agent microbubbles. Methods Rats were treated using burst mode focused ultrasound at 1.5 MHz center frequency and varying envelope and pressure amplitudes. Evans blue staining indicated lethal cardiomyocytic injury. A previously developed quantitative scheme, evaluating the histologic treatment results, provides an insightful analysis for MCET treatment parameters. Such include ultrasound exposure amplitude and pulse modulation, contrast agent dose, and infusion rate. Results The quantitative method overcomes the limitation of visual scoring and works for a large dynamic range of treatment impact. Macrolesions are generated as an accumulation of probability driven microlesion formations. Macrolesions grow radially with radii from 0.1 to 1.6 mm as the ultrasound exposure amplitude (peak negative) increases from 2 to 4 MPa. To shorten treatment time, a swept beam was investigated and found to generate an acceptable macrolesion volume of about 40 μL for a single beam position. Conclusions Ultrasound parameters and administration of microbubbles directly influence lesion characteristics such as microlesion density and macrolesion dimension. For lesion generation planning, control of MCET is crucial, especially when targeting larger pre-clinical models.http://deepblue.lib.umich.edu/bitstream/2027.42/115462/1/40349_2015_Article_39.pd
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