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Efficient Algorithms and Error Analysis for the Modified Nystrom Method
[article]
2014
arXiv
pre-print
Lemma 2 (The Near-Optimal+Adaptive Algorithm (Wang and Zhang, 2013)). ...
Notation The notation used in this paper follows that of Wang and Zhang (2013) . ...
arXiv:1404.0138v1
fatcat:wg5jg5qtl5dwzlc6kccjlf7daa
Fast Generalized Matrix Regression with Applications in Machine Learning
[article]
2019
arXiv
pre-print
Thus, Algorithm 2 is more attractive than the fast SPSD approximation (Wang et al., 2016b) . ...
In this case, our algorithm can be regarded as an approximate modified Nyström method (Wang & Zhang, 2013) . ...
arXiv:1912.12008v1
fatcat:njpyp6vfibhrrc65ycxjlnp2ii
Endovascular Management of May–Thurner Syndrome
2016
Medicine
May-Thurner syndrome (MTS) is caused by venous occlusion because of compression of the iliac vein by the iliac artery and vertebral body, leading to left lower extremity deep venous thrombosis, eventually resulting in a series of symptoms. Endovascular treatment has now become the most preferred method of treatment of MTS. The authors report a 66-year-old woman who was hospitalized because of increasing swelling in her left lower limb for almost 2 weeks. Ultrasonography performed upon admission
doi:10.1097/md.0000000000002541
pmid:26825895
pmcid:PMC5291565
fatcat:chdfkasfnvdylozznmqs7gtjta
more »
... indicated MTS, and venography revealed occlusion of the left common iliac vein and massive thrombosis in the left external iliac and femoral veins. The left lower extremity venous blood flow returned to normal after the patient underwent manual aspiration thrombectomy using a guide catheter, followed by balloon angioplasty and stent placement. The patient achieved complete remission after 1 week and had no in-stent restenosis during the 1-year follow-up. Endovascular treatment is a safe and effective treatment of MTS. (Medicine 95(4):e2541) Abbreviations: CDT = catheter-directed thrombolysis, CDU = color Doppler ultrasonography, CTV = computed tomography venography, DSV = digital subtraction venography, DVT = deep vein thrombosis, MRV = magnetic resonance angiography, MTS = May-Thurner syndrome.
EP-GIG Priors and Applications in Bayesian Sparse Learning
[article]
2012
arXiv
pre-print
In this paper we propose a novel framework for the construction of sparsity-inducing priors. In particular, we define such priors as a mixture of exponential power distributions with a generalized inverse Gaussian density (EP-GIG). EP-GIG is a variant of generalized hyperbolic distributions, and the special cases include Gaussian scale mixtures and Laplace scale mixtures. Furthermore, Laplace scale mixtures can subserve a Bayesian framework for sparse learning with nonconvex penalization. The
arXiv:1204.4243v1
fatcat:uwmmwl5vp5f4bd7vdfrm47l424
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... nsities of EP-GIG can be explicitly expressed. Moreover, the corresponding posterior distribution also follows a generalized inverse Gaussian distribution. These properties lead us to EM algorithms for Bayesian sparse learning. We show that these algorithms bear an interesting resemblance to iteratively re-weighted ℓ_2 or ℓ_1 methods. In addition, we present two extensions for grouped variable selection and logistic regression.
Visualizing NO in live cells by confocal laser scanning microscopy
2012
Chinese Optics Letters (COL)
Determination of NO concentration in live cells is essential to evaluate its related cellular functions. In this letter, the concentration of NO in HeLa cells and rat dorsal root ganglion (DRG) neurons are studied by confocal laser scanning microscopy using DAF-2 DA as a fluorescence probe. The results show the fluorescence intensity of NO in HeLa cells is higher than that in DRG neurons, which indicats that the former exhibits higher NO concentration. Furthermore, the experimental conditions
doi:10.3788/col201210.s11701
fatcat:jlqwdv5cvnewlljikcuktpbaoa
more »
... r low photobleaching and phototoxicity are optimized.
Q|SI〉: A Quantum Programming Environment
[article]
2017
arXiv
pre-print
This paper describes a quantum programming environment, named Q|SI〉. It is a platform embedded in the .Net language that supports quantum programming using a quantum extension of the while-language. The framework of the platform includes a compiler of the quantum while-language and a suite of tools for simulating quantum computation, optimizing quantum circuits, and analyzing and verifying quantum programs. Throughout the paper, using Q|SI〉 to simulate quantum behaviors on classical platforms
arXiv:1710.09500v1
fatcat:f7rotkgxsncufgt2nbmpv2w5vm
more »
... th a combination of components is demonstrated. The scalable framework allows the user to program customized functions on the platform. The compiler works as the core of Q|SI〉 bridging the gap from quantum hardware to quantum software. The built-in decomposition algorithms enable the universal quantum computation on the present quantum hardware.
Simple and Almost Assumption-Free Out-of-Sample Bound for Random Feature Mapping
[article]
2019
arXiv
pre-print
Drineas and Mahoney (2005) , Gittens and Mahoney (2016) , Kumar et al. (2012) , Wang and Zhang (2013) , Musco and Musco (2017) , Tropp et al. (2017) , Wang et al. (2017) established matrix norm ...
arXiv:1909.11207v1
fatcat:6r3pq2k4orb6jolpkzi5ia4zxe
Privacy-Preserving Distributed SVD via Federated Power
[article]
2021
arXiv
pre-print
Similar phenomena have been previously observed in distributed empirical risk minimization (Wang and Joshi, 2019; Li et al., 2019) . ...
Prior work (Gittens and Mahoney, 2016; Woodruff, 2014; Wang et al., 2016) showed that uniform sampling and the partition size in Lemma 24 in Appendix suffice for that M i well approximates M . ...
arXiv:2103.00704v1
fatcat:bzy7fyxoq5axvkvaji2qv55uwi
Alchemist: An Apache Spark <=> MPI Interface
[article]
2018
arXiv
pre-print
The Apache Spark framework for distributed computation is popular in the data analytics community due to its ease of use, but its MapReduce-style programming model can incur significant overheads when performing computations that do not map directly onto this model. One way to mitigate these costs is to off-load computations onto MPI codes. In recent work, we introduced Alchemist, a system for the analysis of large-scale data sets. Alchemist calls MPI-based libraries from within Spark
arXiv:1806.01270v1
fatcat:uoh2w5hiafce7hwoazvmm3wnde
more »
... ns, and it has minimal coding, communication, and memory overheads. In particular, Alchemist allows users to retain the productivity benefits of working within the Spark software ecosystem without sacrificing performance efficiency in linear algebra, machine learning, and other related computations. In this paper, we discuss the motivation behind the development of Alchemist, and we provide a detailed overview its design and usage. We also demonstrate the efficiency of our approach on medium-to-large data sets, using some standard linear algebra operations, namely matrix multiplication and the truncated singular value decomposition of a dense matrix, and we compare the performance of Spark with that of Spark+Alchemist. These computations are run on the NERSC supercomputer Cori Phase 1, a Cray XC40.
A Scalable CUR Matrix Decomposition Algorithm: Lower Time Complexity and Tighter Bound
[article]
2012
arXiv
pre-print
PicasaWeb image dataset (Wang et al., 2012) contains 6.8 million PicasaWeb images. ...
., 2007) and the SIFT features (Lowe, 1999) of the first 50000 images; the features provided by Wang et al. (2012) are all of 3000 dimensions. ...
arXiv:1210.1461v1
fatcat:xhuvuacmczeithgapiqpxgpac4
Sharpened Error Bounds for Random Sampling Based ℓ_2 Regression
[article]
2014
arXiv
pre-print
Given a data matrix X ∈ R^n× d and a response vector y ∈ R^n, suppose n>d, it costs O(n d^2) time and O(n d) space to solve the least squares regression (LSR) problem. When n and d are both large, exactly solving the LSR problem is very expensive. When n ≫ d, one feasible approach to speeding up LSR is to randomly embed y and all columns of X into a smaller subspace R^c; the induced LSR problem has the same number of columns but much fewer number of rows, and it can be solved in O(c d^2) time
arXiv:1403.7737v2
fatcat:z5dowol2mjb5vobgdsiocf3z6e
more »
... d O(c d) space. We discuss in this paper two random sampling based methods for solving LSR more efficiently. Previous work showed that the leverage scores based sampling based LSR achieves 1+ϵ accuracy when c ≥ O(d ϵ^-2 d). In this paper we sharpen this error bound, showing that c = O(d d + d ϵ^-1) is enough for achieving 1+ϵ accuracy. We also show that when c ≥ O(μ d ϵ^-2 d), the uniform sampling based LSR attains a 2+ϵ bound with positive probability.
Gut microbiota and allogeneic transplantation
2015
Journal of Translational Medicine
In recent years, the Open Access *Correspondence: shusenzheng@zju.edu.cn † Weilin Wang and Shaoyan Xu contributed equally to this work and should be considered co-first authors 3 Collaborative Innovation ...
doi:10.1186/s12967-015-0640-8
pmid:26298517
pmcid:PMC4546814
fatcat:fhosovzwyveythyesh2bkqlfji
Inhibitor of Pancreatic Cancer by RHIL1RA—Letter
2017
Clinical Cancer Research
We have read the article with interest by Zhuang and colleagues (1) on the combination of IL1R antagonist and gemcitabine in gemcitabine-resistant pancreatic ductal adenocarcinoma (PDAC). The article showed that gemcitabine-induced NF-kB and ERK activation in gemcitabine-resistant PDAC cells can be reversed by anakinra, an FDA-approved IL1R antagonist. However, there are still some key points that should be discussed with more details. The mutational activity of KRAS has been detected in 85% to
doi:10.1158/1078-0432.ccr-16-3270
pmid:28620000
fatcat:y7nvfigb6rbxre6wn4yh2mf5em
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... 90% of PDAC and 70% of KRAS-mutant PDAC with NF-kB activation. Mutations were found in the second base of codon 12 of KRAS in almost all pancreatic cancer cell lines, except Hs766T and BxPC-3 (2). However, the sensitivity of gemcitabine was not consistent with the mutation of KRAS; both CFPAC-1 and BxPC-1 are sensitive to gemcitabine. So NF-kB signal pathway, as a key downstream of KRAS, might be the critical point. As demonstrated by the authors, gemcitabine-resistant pancreatic cancer cell lines like AsPC-1 showed activation of NF-kB after the use of gemcitabine, which was considered as a pivotal mechanism of gemcitabine resistance. But unfortunately, previous studies demonstrate controversial opinions on the correlation between the activation of NF-kB and gemcitabine resistance in PDAC. In the study by Pan and colleagues (3) , the authors found that NF-kB activity did not correlate with sensitivity to gemcitabine, and gemcitabine treatment did not activate NF-kB either in vitro or in vivo both in gemcitabine-sensitive/resistant pancreatic cancer cell lines. Our group also found that gemcitabine could reduce the activation of NF-kB both in BxPC-3/CFPAC-1 (gemcitabine sensitive) and AsPC-1/PANC-1 (gemcitabine resistant) cell lines. What is more, gemcitabine could not induce NF-kB activation in BxPC-3/GEM cell line in some studies (4), which means that NF-kB activation was not a general result after gemcitabine treatment in different gemcitabine-resistant cell lines, even in the same pancreatic cancer cell line. All the results indicated that NF-kB activation may not be a mechanism of gemcitabine resistance in PDAC, and further evidence is required. According to previous research, Ling and colleagues (5) revealed that KRAS G12D -induced IL1a activated NF-kB and its target genes IL1a and p62 to initiate IL1a/p62 feedback loop, which may be an important mechanism between KRAS mutation and NF-kB activation in the development of PDAC. In conclusion, we congratulate Zhuang and colleagues: IL1a may be a useful therapeutic target for a subset of pancreatic cancer, but we believe that its mechanism of reversing gemcitabine resistance remains controversial.
Mg Alloys Development and Surface Modification for Biomedical Application
[chapter]
2011
Magnesium Alloys - Corrosion and Surface Treatments
Wang,et.al 2010). Note that the positive pulse was wider than negative one in order to develop a Ca-P coating of certain thickness. ...
Denissen et.al. 1980) , HA had excellent biocompatibility and bioactivity and was used to improve the surface biocompatibility of Ti, Mg and stainless steel alloys (Wang, et al, 2010; Kuo, et al, 2002 ...
doi:10.5772/13187
fatcat:iwtndyc2c5a5jhrpbj3hhoyet4
Mutations in COMP cause familial carpal tunnel syndrome
2020
Nature Communications
Carpal tunnel syndrome (CTS) is the most common peripheral nerve entrapment syndrome, affecting a large proportion of the general population. Genetic susceptibility has been implicated in CTS, but the causative genes remain elusive. Here, we report the identification of two mutations in cartilage oligomeric matrix protein (COMP) that segregate with CTS in two large families with or without multiple epiphyseal dysplasia (MED). Both mutations impair the secretion of COMP by tenocytes, but the
doi:10.1038/s41467-020-17378-z
pmid:32686688
fatcat:covyhnbkrbht3jqkobnkxo3miy
more »
... tion associated with MED also perturbs its secretion in chondrocytes. Further functional characterization of the CTS-specific mutation reveals similar histological and molecular changes of tendons/ligaments in patients' biopsies and the mouse models. The mutant COMP fails to oligomerize properly and is trapped in the ER, resulting in ER stress-induced unfolded protein response and cell death, leading to inflammation, progressive fibrosis and cell composition change in tendons/ligaments. The extracellular matrix (ECM) organization is also altered. Our studies uncover a previously unrecognized mechanism in CTS pathogenesis.
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