58 research outputs found

    Pulse Shape Analysis and Identification of Multipoint Events in a Large-Volume Proportional Counter in an Experimental Search for 2K Capture Kr-78

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    A pulse shape analysis algorithm and a method for suppressing the noise component of signals from a large copper proportional counter in the experiment aimed at searching for 2K capture of Kr-78 are described. These signals correspond to a compound event with different numbers of charge clusters due to from primary ionization is formed by these signals. A technique for separating single- and multipoint events and determining the charge in individual clusters is presented. Using the Daubechies wavelets in multiresolutional signal analysis, it is possible to increase the sensitivity and the resolution in extraction of multipoint events in the detector by a factor of 3-4.Comment: 10 pages, 8 figures. submitted to Instruments and Experimental Techniques; ISSN 0020/441

    On Deterministic Sketching and Streaming for Sparse Recovery and Norm Estimation

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    We study classic streaming and sparse recovery problems using deterministic linear sketches, including l1/l1 and linf/l1 sparse recovery problems (the latter also being known as l1-heavy hitters), norm estimation, and approximate inner product. We focus on devising a fixed matrix A in R^{m x n} and a deterministic recovery/estimation procedure which work for all possible input vectors simultaneously. Our results improve upon existing work, the following being our main contributions: * A proof that linf/l1 sparse recovery and inner product estimation are equivalent, and that incoherent matrices can be used to solve both problems. Our upper bound for the number of measurements is m=O(eps^{-2}*min{log n, (log n / log(1/eps))^2}). We can also obtain fast sketching and recovery algorithms by making use of the Fast Johnson-Lindenstrauss transform. Both our running times and number of measurements improve upon previous work. We can also obtain better error guarantees than previous work in terms of a smaller tail of the input vector. * A new lower bound for the number of linear measurements required to solve l1/l1 sparse recovery. We show Omega(k/eps^2 + klog(n/k)/eps) measurements are required to recover an x' with |x - x'|_1 <= (1+eps)|x_{tail(k)}|_1, where x_{tail(k)} is x projected onto all but its largest k coordinates in magnitude. * A tight bound of m = Theta(eps^{-2}log(eps^2 n)) on the number of measurements required to solve deterministic norm estimation, i.e., to recover |x|_2 +/- eps|x|_1. For all the problems we study, tight bounds are already known for the randomized complexity from previous work, except in the case of l1/l1 sparse recovery, where a nearly tight bound is known. Our work thus aims to study the deterministic complexities of these problems

    Recovery of dialysis patients with COVID-19 : health outcomes 3 months after diagnosis in ERACODA

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    Background. Coronavirus disease 2019 (COVID-19)-related short-term mortality is high in dialysis patients, but longer-term outcomes are largely unknown. We therefore assessed patient recovery in a large cohort of dialysis patients 3 months after their COVID-19 diagnosis. Methods. We analyzed data on dialysis patients diagnosed with COVID-19 from 1 February 2020 to 31 March 2021 from the European Renal Association COVID-19 Database (ERACODA). The outcomes studied were patient survival, residence and functional and mental health status (estimated by their treating physician) 3 months after COVID-19 diagnosis. Complete follow-up data were available for 854 surviving patients. Patient characteristics associated with recovery were analyzed using logistic regression. Results. In 2449 hemodialysis patients (mean ± SD age 67.5 ± 14.4 years, 62% male), survival probabilities at 3 months after COVID-19 diagnosis were 90% for nonhospitalized patients (n = 1087), 73% for patients admitted to the hospital but not to an intensive care unit (ICU) (n = 1165) and 40% for those admitted to an ICU (n = 197). Patient survival hardly decreased between 28 days and 3 months after COVID-19 diagnosis. At 3 months, 87% functioned at their pre-existent functional and 94% at their pre-existent mental level. Only few of the surviving patients were still admitted to the hospital (0.8-6.3%) or a nursing home (∌5%). A higher age and frailty score at presentation and ICU admission were associated with worse functional outcome. Conclusions. Mortality between 28 days and 3 months after COVID-19 diagnosis was low and the majority of patients who survived COVID-19 recovered to their pre-existent functional and mental health level at 3 months after diagnosis

    Vascular Remodeling in Health and Disease

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    The term vascular remodeling is commonly used to define the structural changes in blood vessel geometry that occur in response to long-term physiologic alterations in blood flow or in response to vessel wall injury brought about by trauma or underlying cardiovascular diseases.1, 2, 3, 4 The process of remodeling, which begins as an adaptive response to long-term hemodynamic alterations such as elevated shear stress or increased intravascular pressure, may eventually become maladaptive, leading to impaired vascular function. The vascular endothelium, owing to its location lining the lumen of blood vessels, plays a pivotal role in regulation of all aspects of vascular function and homeostasis.5 Thus, not surprisingly, endothelial dysfunction has been recognized as the harbinger of all major cardiovascular diseases such as hypertension, atherosclerosis, and diabetes.6, 7, 8 The endothelium elaborates a variety of substances that influence vascular tone and protect the vessel wall against inflammatory cell adhesion, thrombus formation, and vascular cell proliferation.8, 9, 10 Among the primary biologic mediators emanating from the endothelium is nitric oxide (NO) and the arachidonic acid metabolite prostacyclin [prostaglandin I2 (PGI2)], which exert powerful vasodilatory, antiadhesive, and antiproliferative effects in the vessel wall

    Urinary properdin excretion is associated with intrarenal complement activation and poor renal function

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    Background. Proteinuria predicts progressive renal failure. Next to being a progression marker, non-selective proteinuria itself is thought to be toxic to the tubulointerstitium. In proteinuric states, activation of filtered or locally produced complement is toxic for renal tubular cells and likely contributes to the progression of renal failure. Recent experimental evidence suggests an important role for properdin in promoting intrarenal complement activation. We measured properdin in proteinuric urine and assessed its relation with urinary SC5b-9 levels, the soluble form of the effector phase of complement activation. Methods. Seventy patients with renal disease of different origin but all with a protein excretion of at least 1 g/day were studied. Urinary properdin and SC5b-9 levels were measured using an ELISA technique. Results. Properdin was detectable in the urine of 37 patients (53%). These subjects had higher urinary SC5b-9 levels {median 0.50 U/ml [interquartile range (IQR) 0.13-1.81] versus 0.049 U/ml (IQR 0.024-0.089), P < 0.001}. When adjusted for proteinuria and renal function, properdin excretion was strongly associated with increased urinary SC5b-9 levels (odds ratio 16.2, 95% confidence interval 3.6-74.4). Properdin excretion was associated with worse renal function. Conclusion. Our results suggest that urinary properdin excretion enhances intrarenal complement activation and thus may contribute to the progression of renal damage in proteinuric states.Nephrolog

    Content‐based image retrieval system via sparse representation

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    The aim of image retrieval systems is to automatically assess, retrieve and represent relative images‐based user demand. However, the accuracy and speed of image retrieval are still an interesting topic of many researches. In this study, a new method based on sparse representation and iterative discrete wavelet transform has been proposed. To evaluate the applicability of the proposed feature‐based sparse representation for image retrieval technique, the precision at percent recall and average normalised modified retrieval rank are used as quantitative metrics to compare different methods. The experimental results show that the proposed method provides better performance in comparison with other methods
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