A fast and accurate basis pursuit denoising algorithm with application to super-resolving tomographic SAR

$L_1$ regularization is used for finding sparse solutions to an underdetermined linear system. As sparse signals are widely expected in remote sensing, this type of regularization scheme and its extensions have been widely employed in many remote sensing problems, such as image fusion, target detection, image super-resolution, and others and have led to promising results. However, solving such sparse reconstruction problems is computationally expensive and has limitations in its practical use. In this paper, we proposed a novel efficient algorithm for solving the complex-valued $L_1$ regularized least squares problem. Taking the high-dimensional tomographic synthetic aperture radar (TomoSAR) as a practical example, we carried out extensive experiments, both with simulation data and real data, to demonstrate that the proposed approach can retain the accuracy of second order methods while dramatically speeding up the processing by one or two orders. Although we have chosen TomoSAR as the example, the proposed method can be generally applied to any spectral estimation problems.Comment: 11 pages, IEEE Transactions on Geoscience and Remote Sensin

Development of Eighteen Microsatellite Markers in Anemone amurensis (Ranunculaceae) and Cross-Amplification in Congeneric Species

Polyploidy plays an important role in the evolution of plant genomes. To enable the investigation of the polyploidy events within the genus Anemone, we developed eighteen microsatellite markers from the hexaploid species A. amurensis (Ranunculaceae), and tested their transferability in five closely related species. The number of total alleles (NA) for each resulting locus varied from one to eight. The polymorphism information content (PIC) and Nei’s genetic diversity (NGD) for these microsatellites ranged from 0.00 to 0.71 and 0.00 to 0.91, respectively. For each population, the NA was one to seven, and the values of PIC and NGD varied from 0.00 to 0.84 and 0.00 to 0.95, respectively. In addition, most of these microsatellites can be amplified successfully in the congeneric species. These microsatellite primers provide us an opportunity to study the polyploid evolution in the genus Anemone

Cost-effectiveness of maintenance niraparib with an individualized starting dosage in patients with platinum-sensitive recurrent ovarian cancer in China

Objective: Niraparib improved survival in platinum-sensitive recurrent ovarian cancer (PSROC) patients versus routine surveillance, accompanied by increased costs. Based on the NORA trial, we evaluated for the first time the cost-effectiveness of maintenance niraparib with individualized starting dosage (ISD) in China.Methods: A Markov model was developed to simulate the costs and health outcomes of each strategy. The total costs, quality-adjusted life years (QALYs), and incremental cost-effectiveness ratios (ICERs) were measured. One-way and probabilistic sensitivity analysis were performed to estimate model robustness. Scenario analyses were also conducted.Results: Compared to routine surveillance, niraparib additionally increased QALYs by 0.59 and 0.30 in populations with and without germline BRCA (gBRCA) mutations, with incremental costs of $10,860.79 and$12,098.54, respectively. The ICERs of niraparib over routine surveillance were $18,653.67/QALY and$39,212.99/QALY. At a willingness-to-pay (WTP) threshold of $37,488/QALY, the ISD enhanced the likelihood of cost-effectiveness from 9.35% to 30.73% in the gBRCA-mutated group and from 0.77% to 11.74% in the non-gBRCA mutated population. The probability of niraparib being cost-effective in the region with the highest per capita Gross Domestic Product (GDP) in China was 74.23% and 76.10% in the gBRCA-mutated and non-gBRCA mutated population, respectively. Niraparib was 100% cost-effective for National Basic Medical Insurance beneficiaries under the above WTP thresholds.Conclusion: Compared to routine surveillance, the ISD of niraparib for maintenance treatment of PSROC is cost-effective in the gBRCA-mutated population and more effective but costly in the non-gBRCA mutated patients. The optimized niraparib price, economic status, and health insurance coverage may benefit the economic outcome

Scaling Attributed Network Embedding to Massive Graphs

Given a graph G where each node is associated with a set of attributes, attributed network embedding (ANE) maps each node vin G to a compact vector Xv, which can be used in downstream machine learning tasks. Ideally, Xv should capture node v's affinity to each attribute, which considers not only v's own attribute associations, but also those of its connected nodes along edges in G. It is challenging to obtain high-utility embeddings that enable accurate predictions; scaling effective ANE computation to massive graphs with millions of nodes pushes the difficulty of the problem to a whole new level. Existing solutions largely fail on such graphs, leading to prohibitive costs, low-quality embeddings, or both. This paper proposes PANE, an effective and scalable approach to ANE computation for massive graphs that achieves state-of-the-art result quality on multiple benchmark datasets, measured by the accuracy of three common prediction tasks: attribute inference, link prediction, and node classification. PANE obtains high scalability and effectiveness through three main algorithmic designs. First, it formulates the learning objective based on a novel random walk model for attributed networks. The resulting optimization task is still challenging on large graphs. Second, PANE includes a highly efficient solver for the above optimization problem, whose key module is a carefully designed initialization of the embeddings, which drastically reduces the number of iterations required to converge. Finally, PANE utilizes multi-core CPUs through non-trivial parallelization of the above solver, which achieves scalability while retaining the high quality of the resulting embeddings. Extensive experiments, comparing 10 existing approaches on 8 real datasets, demonstrate that PANE consistently outperforms all existing methods in terms of result quality, while being orders of magnitude faster.Comment: 16 pages. PVLDB 2021. Volume 14, Issue

Poly[[(2,2′-bipyridine)­(μ3-2-sulfonatobenzoato)lead(II)] dihydrate]

In the title compound, {[Pb(sbc)(bpy)]·2H2O}n [bpy is 2,2′-bipyridine (C10H8N2) and sbc is the 2-sulfonatobenzoate dianion (C7H4O5S)], the PbII ion is bonded to four O atoms including carboxyl­ate and sulfonate from three sbc dianions, and two N atoms from a chelating 2,2′-bipyridine ligand. The sbc ligand acts as a μ3-bridging ligand by one O atom of the sulfonate group and the two O atoms of the carboxyl­ate. Of these two last O atoms, one builds up a dinuclear framework arranged around an inversion center whereas the second one links each dinuclear unit, forming a chain extending along the b axis. These polymeric chains are linked through O—H⋯O hydrogen bonds involving the water mol­ecules, forming a layer parallel to (10)

Life fingerprints of nuclear reactions in the body of animals

Nuclear reactions are a very important natural phenomenon in the universe. On the earth, cosmic rays constantly cause nuclear reactions. High energy beams created by medical devices also induce nuclear reactions in the human body. The biological role of these nuclear reactions is unknown. Here we show that the in vivo biological systems are exquisite and sophisticated by nature in influence on nuclear reactions and in resistance to radical damage in the body of live animals. In this study, photonuclear reactions in the body of live or dead animals were induced with 50-MeV irradiation. Tissue nuclear reactions were detected by positron emission tomography (PET) imaging of the induced beta+ activity. We found the unique tissue "fingerprints" of beta+ (the tremendous difference in beta+ activities and tissue distribution patterns among the individuals) are imprinted in all live animals. Within any individual, the tissue "fingerprints" of 15O and 11C are also very different. When the animal dies, the tissue "fingerprints" are lost. The biochemical, rather than physical, mechanisms could play a critical role in the phenomenon of tissue "fingerprints". Radiolytic radical attack caused millions-fold increases in 15O and 11C activities via different biochemical mechanisms, i.e. radical-mediated hydroxylation and peroxidation respectively, and more importantly the bio-molecular functions (such as the chemical reactivity and the solvent accessibility to radicals). In practice biologically for example, radical attack can therefore be imaged in vivo in live animals and humans using PET for life science research, disease prevention, and personalized radiation therapy based on an individual's bio-molecular response to ionizing radiation

H-infinity filtering with randomly occurring sensor saturations and missing measurements

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2012 ElsevierIn this paper, the H∞ filtering problem is investigated for a class of nonlinear systems with randomly occurring incomplete information. The considered incomplete information includes both the sensor saturations and the missing measurements. A new phenomenon of sensor saturation, namely, randomly occurring sensor saturation (ROSS), is put forward in order to better reflect the reality in a networked environment such as sensor networks. A novel sensor model is then established to account for both the ROSS and missing measurement in a unified representation by using two sets of Bernoulli distributed white sequences with known conditional probabilities. Based on this sensor model, a regional H∞ filter with a certain ellipsoid constraint is designed such that the filtering error dynamics is locally mean-square asymptotically stable and the H∞-norm requirement is satisfied. Note that the regional l2 gain filtering feature is specifically developed for the random saturation nonlinearity. The characterization of the desired filter gains is derived in terms of the solution to a convex optimization problem that can be easily solved by using the semi-definite program method. Finally, a simulation example is employed to show the effectiveness of the filtering scheme proposed in this paper.This work was supported in part by the Engineering and Physical Sciences Research Council (EPSRC) of the UK under Grant GR/S27658/01, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 61028008 and 60974030, the National 973 Program of China under Grant 2009CB320600, and the Alexander von Humboldt Foundation of Germany