Dynamical mean-field theory of indirect magnetic exchange

To analyze the physical properties arising from indirect magnetic exchange between several magnetic adatoms and between complex magnetic nanostructures on metallic surfaces, the real-space extension of dynamical mean-field theory (R-DMFT) appears attractive as it can be applied to systems of almost arbitrary geometry and complexity. While R-DMFT describes the Kondo effect of a single adatom exactly, indirect magnetic (RKKY) exchange is taken into account on an approximate level only. Here, we consider a simplified model system consisting of two magnetic Hubbard sites ("adatoms") hybridizing with a non-interacting tight-binding chain ("substrate surface"). This two-impurity Anderson model incorporates the competition between the Kondo effect and indirect exchange but is amenable to an exact numerical solution via the density-matrix renormalization group (DMRG). The particle-hole symmetric model at half-filling and zero temperature is used to benchmark R-DMFT results for the magnetic coupling between the two adatoms and for the magnetic properties induced in the substrate. In particular, the dependence of the local adatom and the nonlocal adatom-adatom static susceptibilities as well as the magnetic response of the substrate on the distance between the adatoms and on the strength of their coupling with the substrate is studied. We find both, excellent agreement with the DMRG data even on subtle details of the competition between RKKY exchange and the Kondo effect but also complete failure of the R-DMFT, depending on the parameter regime considered. R-DMFT calculations are performed using the Lanczos method as impurity solver. With the real-space extension of the two-site DMFT, we also benchmark a simplified R-DMFT variant.Comment: 14 pages, 8 figure

Maintaining Structural Stability of Poly(lactic acid): Effects of Multifunctional Epoxy based Reactive Oligomers

In order to reduce the effects of hydrolytic degradation and to maintain sufficient viscosity during processing of biomass based poly(l-lactic acid) (PLLA), various epoxy functional reactive oligomers have been characterized and incorporated into the degraded fragments as chain extenders. The molecular weight of PLLA increased with the increase in functionality of the reactive oligomers. No further increase in molecular weight was observed for oligomers with functionality of greater than five. Under our experimental conditions, no gelation was found even when the highest functionality reactive oligomers were used. This is attributed to the preferential reaction of the carboxylic acid versus the negligible reactivity of the hydroxyl groups, present at the two ends of the degraded PLLA chains, with the epoxy groups. The study provides a clear understanding of the degradation and chain extension reaction of poly(lactic acid) (PLA) with epoxy functional reactive oligomers. It is also shown that a higher functionality and concentration of the reactive oligomers is needed, to bring about a sufficient increase in the molecular weight and hence the hydrolytic stability in circumstances when PLA chains suffer significant degradation during processing

On the low fermionic eigenmode dominance in QCD on the lattice

We demonstrate the utility of a spectral approximation to fermion loop operators using low-lying eigenmodes of the hermitian Dirac-Wilson matrix, Q. The investigation is based on a total of 400 full QCD vacuum configurations, with two degenerate flavors of dynamical Wilson fermions at beta =5.6, at two different sea quark masses. The spectral approach is highly competitive for accessing both topological charge and disconnected diagrams, on large lattices and small quark masses. We propose suitable partial summation techniques that provide sufficient saturation for estimating Tr Q^{-1}, which is related to the topological charge. In the effective mass plot of the eta' meson we achieved a consistent early plateau formation, by ground state projecting the connected piece of its propagator.Comment: 15 pages, 25 figures, citations adde

Discovery and saturation analysis of cancer genes across 21 tumor types

Summary While a few cancer genes are mutated in a high proportion of tumors of a given type (>20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalog of cancer genes, we analyzed somatic point mutations in exome sequence from 4,742 tumor-normal pairs across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumor types. Our analysis also identified 33 genes not previously known to be significantly mutated, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes, mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600–5000 samples per tumor type, depending on background mutation rate. The results help guide the next stage of cancer genomics

Quadratic fermionic interactions yield effective Hamiltonians for adiabatic quantum computing

Polynomially-large ground-state energy gaps are rare in many-body quantum systems, but useful for adiabatic quantum computing. We show analytically that the gap is generically polynomially-large for quadratic fermionic Hamiltonians. We then prove that adiabatic quantum computing can realize the ground states of Hamiltonians with certain random interactions, as well as the ground states of one, two, and three-dimensional fermionic interaction lattices, in polynomial time. Finally, we use the Jordan-Wigner transformation and a related transformation for spin-3/2 particles to show that our results can be restated using spin operators in a surprisingly simple manner. A direct consequence is that the one-dimensional cluster state can be found in polynomial time using adiabatic quantum computing.Comment: 14 page

Visualizing dimensionality reduction of systems biology data

One of the challenges in analyzing high-dimensional expression data is the detection of important biological signals. A common approach is to apply a dimension reduction method, such as principal component analysis. Typically, after application of such a method the data is projected and visualized in the new coordinate system, using scatter plots or profile plots. These methods provide good results if the data have certain properties which become visible in the new coordinate system and which were hard to detect in the original coordinate system. Often however, the application of only one method does not suffice to capture all important signals. Therefore several methods addressing different aspects of the data need to be applied. We have developed a framework for linear and non-linear dimension reduction methods within our visual analytics pipeline SpRay. This includes measures that assist the interpretation of the factorization result. Different visualizations of these measures can be combined with functional annotations that support the interpretation of the results. We show an application to high-resolution time series microarray data in the antibiotic-producing organism Streptomyces coelicolor as well as to microarray data measuring expression of cells with normal karyotype and cells with trisomies of human chromosomes 13 and 21

Discovery and saturation analysis of cancer genes across 21 tumour types

Although a few cancer genes are mutated in a high proportion of tumours of a given type (>20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600–5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics

The Democratic Biopolitics of PrEP

PrEP (Pre-Exposure Prophylaxis) is a relatively new drug-based HIV prevention technique and an important means to lower the HIV risk of gay men who are especially vulnerable to HIV. From the perspective of biopolitics, PrEP inscribes itself in a larger trend of medicalization and the rise of pharmapower. This article reconstructs and evaluates contemporary literature on biopolitical theory as it applies to PrEP, by bringing it in a dialogue with a mapping of the political debate on PrEP. As PrEP changes sexual norms and subjectification, for example condom use and its meaning for gay subjectivity, it is highly contested. The article shows that the debate on PrEP can be best described with the concepts ‘sexual-somatic ethics’ and ‘democratic biopolitics’, which I develop based on the biopolitical approach of Nikolas Rose and Paul Rabinow. In contrast, interpretations of PrEP which are following governmentality studies or Italian Theory amount to either farfetched or trivial positions on PrEP, when seen in light of the political debate. Furthermore, the article is a contribution to the scholarship on gay subjectivity, highlighting how homophobia and homonormativity haunts gay sex even in liberal environments, and how PrEP can serve as an entry point for the destigmatization of gay sexuality and transformation of gay subjectivity. ‘Biopolitical democratization’ entails making explicit how medical technology and health care relates to sexual subjectification and ethics, to strengthen the voice of (potential) PrEP users in health politics, and to renegotiate the profit and power of Big Pharma

Tuberculosis Incidence Rates during 8 Years of Follow-Up of an Antiretroviral Treatment Cohort in South Africa: Comparison with Rates in the Community

BACKGROUND: Although antiretroviral therapy (ART) is known to be associated with time-dependent reductions in tuberculosis (TB) incidence, the long-term impact of ART on incidence remains imprecisely defined due to limited duration of follow-up and incomplete CD4 cell count recovery in existing studies. We determined TB incidence in a South African ART cohort with up to 8 years of follow-up and stratified rates according to CD4 cell count recovery. We compared these rates with those of HIV-uninfected individuals living in the same community. METHODOLOGY/PRINCIPAL FINDINGS: Prospectively collected clinical data on patients receiving ART in a community-based cohort in Cape Town were analysed. 1544 patients with a median follow-up of 5.0 years (IQR 2.4-5.8) were included in the analysis. 484 episodes of incident TB (73.6% culture-confirmed) were diagnosed in 424 patients during 6506 person-years (PYs) of follow-up. The TB incidence rate during the first year of ART was 12.4 (95% CI 10.8-14.4) cases/100PYs and decreased to 4.92 (95% CI 3.64-8.62) cases/100PYs between 5 and 8 years of ART. During person-time accrued within CD4 cell strata 0-100, 101-200, 201-300, 301-400, 401-500, 501-700 and ≥700 cells/µL, TB incidence rates (95% CI) were 25.5 (21.6-30.3), 11.2 (9.4-13.5), 7.9 (6.4-9.7), 5.0 (3.9-6.6), 5.1 (3.8-6.8), 4.1 (3.1-5.4) and 2.7 (1.7-4.5) cases/100PYs, respectively. Overall, 75% (95% CI 70.9-78.8) of TB episodes were recurrent cases. Updated CD4 cell count and viral load measurements were independently associated with long-term TB risk. TB rates during person-time accrued in the highest CD4 cell count stratum (>700 cells/µL) were 4.4-fold higher that the rate in HIV uninfected individuals living in the same community (2.7 versus 0.62 cases/100PYs; 95%CI 0.58-0.65). CONCLUSIONS/SIGNIFICANCE: TB rates during long-term ART remained substantially greater than rates in the local HIV uninfected populations regardless of duration of ART or attainment of CD4 cell counts exceeding 700 cells/µL

iSAM2 : incremental smoothing and mapping using the Bayes tree

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Sage for personal use, not for redistribution. The definitive version was published in International Journal of Robotics Research 31 (2012): 216-235, doi:10.1177/0278364911430419.We present a novel data structure, the Bayes tree, that provides an algorithmic foundation enabling a better understanding of existing graphical model inference algorithms and their connection to sparse matrix factorization methods. Similar to a clique tree, a Bayes tree encodes a factored probability density, but unlike the clique tree it is directed and maps more naturally to the square root information matrix of the simultaneous localization and mapping (SLAM) problem. In this paper, we highlight three insights provided by our new data structure. First, the Bayes tree provides a better understanding of the matrix factorization in terms of probability densities. Second, we show how the fairly abstract updates to a matrix factorization translate to a simple editing of the Bayes tree and its conditional densities. Third, we apply the Bayes tree to obtain a completely novel algorithm for sparse nonlinear incremental optimization, named iSAM2, which achieves improvements in efficiency through incremental variable re-ordering and fluid relinearization, eliminating the need for periodic batch steps. We analyze various properties of iSAM2 in detail, and show on a range of real and simulated datasets that our algorithm compares favorably with other recent mapping algorithms in both quality and efficiency.M. Kaess, H. Johannsson and J. Leonard were partially supported by ONR grants N00014-06-1-0043 and N00014-10-1-0936. F. Dellaert and R. Roberts were partially supported by NSF, award number 0713162, “RI: Inference in Large-Scale Graphical Models”. V. Ila has been partially supported by the Spanish MICINN under the Programa Nacional de Movilidad de Recursos Humanos de Investigación