Bayesian anomaly detection methods for social networks

Learning the network structure of a large graph is computationally demanding, and dynamically monitoring the network over time for any changes in structure threatens to be more challenging still. This paper presents a two-stage method for anomaly detection in dynamic graphs: the first stage uses simple, conjugate Bayesian models for discrete time counting processes to track the pairwise links of all nodes in the graph to assess normality of behavior; the second stage applies standard network inference tools on a greatly reduced subset of potentially anomalous nodes. The utility of the method is demonstrated on simulated and real data sets.Comment: Published in at http://dx.doi.org/10.1214/10-AOAS329 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Finding Groups in Gene Expression Data

The vast potential of the genomic insight offered by microarray technologies has led to their widespread use since they were introduced a decade ago. Application areas include gene function discovery, disease diagnosis, and inferring regulatory networks. Microarray experiments enable large-scale, high-throughput investigations of gene activity and have thus provided the data analyst with a distinctive, high-dimensional field of study. Many questions in this field relate to finding subgroups of data profiles which are very similar. A popular type of exploratory tool for finding subgroups is cluster analysis, and many different flavors of algorithms have been used and indeed tailored for microarray data. Cluster analysis, however, implies a partitioning of the entire data set, and this does not always match the objective. Sometimes pattern discovery or bump hunting tools are more appropriate. This paper reviews these various tools for finding interesting subgroups

Enhancing surface finish of additively manufactured titanium and cobalt chrome elements using laser based finishing

Additive manufacturing (AM) offers the possibility of creating a complex free form object as a single element, which is not possible using traditional mechanical machining. Unfortunately the typically rough surface finish of additively manufactured parts is unsuitable for many applications. As a result AM parts must be post-processed; typically mechanically machined and/or and polished using either chemical or mechanical techniques (both of which have their limitations). Laser based polishing is based on remelting of a very thin surface layer and it offers potential as a highly repeatable, higher speed process capable of selective area polishing, and without any waste problems (no abrasives or liquids).In this paper an in-depth investigation of CW laser polishing of titanium and cobalt chrome AM elements is presented. The impact of different scanning strategies, laser parameters and initial surface condition on the achieved surface finish is evaluated

The synthesis and analysis of lignin-bound Hibbert ketone structures in technical lignins

This work was supported by EPSRC Ph.D. studentships (EP/1518175 (DMB), EP/1517938 (AN)), the Industrial Biotechnology Innovation Centre (Ph.D. studentship to DMB), CRITICAT Centre for Doctoral Training (Ph.D. studentship to IP; EP/L016419/1), EPSRC grants EP/J018139/1 and EP/K00445X/1 (SOJO) and an EPSRC Doctoral Prize Fellowship (CSL).Understanding the structure of technical lignins resulting from acid-catalysed treatment of lignocellulosic biomass is important for their future applications. Here we report an investigation into the fate of lignin under acidic aqueous organosolv conditions. In particular we examine in detail the formation and reactivity of non-native Hibbert ketone structures found in isolated organosolv lignins from both Douglas fir and beech woods. Through the use of model compounds combined with HSQC, HMBC and HSQC-TOCSY NMR experiments we demonstrate that, depending on the lignin source, both S and G lignin-bound Hibbert ketone units can be present. We also show that these units can serve as a source of novel mono-aromatic compounds following an additional lignin depolymerisation reaction.PostprintPeer reviewe

Defective Lipid Droplet-Lysosome Interaction Causes Fatty Liver Disease as Evidenced by Human Mutations in TMEM199 and CCDC115

BACKGROUND &amp; AIMS: Recently, novel inborn errors of metabolism were identified because of mutations in V-ATPase assembly factors TMEM199 and CCDC115. Patients are characterized by generalized protein glycosylation defects, hypercholesterolemia, and fatty liver disease. Here, we set out to characterize the lipid and fatty liver phenotype in human plasma, cell models, and a mouse model.METHODS AND RESULTS: Patients with TMEM199 and CCDC115 mutations displayed hyperlipidemia, characterized by increased levels of lipoproteins in the very low density lipoprotein range. HepG2 hepatoma cells, in which the expression of TMEM199 and CCDC115 was silenced, and induced pluripotent stem cell (iPSC)-derived hepatocyte-like cells from patients with TMEM199 mutations showed markedly increased secretion of apolipoprotein B (apoB) compared with controls. A mouse model for TMEM199 deficiency with a CRISPR/Cas9-mediated knock-in of the human A7E mutation had marked hepatic steatosis on chow diet. Plasma N-glycans were hypogalactosylated, consistent with the patient phenotype, but no clear plasma lipid abnormalities were observed in the mouse model. In the siTMEM199 and siCCDC115 HepG2 hepatocyte models, increased numbers and size of lipid droplets were observed, including abnormally large lipid droplets, which colocalized with lysosomes. Excessive de novo lipogenesis, failing oxidative capacity, and elevated lipid uptake were not observed. Further investigation of lysosomal function revealed impaired acidification combined with impaired autophagic capacity.CONCLUSIONS: Our data suggest that the hyperchole-sterolemia in TMEM199 and CCDC115 deficiency is due to increased secretion of apoB-containing particles. This may in turn be secondary to the hepatic steatosis observed in these patients as well as in the mouse model. Mechanistically, we observed impaired lysosomal function characterized by reduced acidification, autophagy, and increased lysosomal lipid accumulation. These findings could explain the hepatic steatosis seen in patients and highlight the importance of lipophagy in fatty liver disease. Because this pathway remains understudied and its regulation is largely untargeted, further exploration of this pathway may offer novel strategies for therapeutic interventions to reduce lipotoxicity in fatty liver disease.</p

Enhancing wind erosion monitoring and assessment for U.S. rangelands

Wind erosion is a major resource concern for rangeland managers because it can impact soil health, ecosystem structure and function, hydrologic processes, agricultural production, and air quality. Despite its significance, little is known about which landscapes are eroding, by how much, and when. The National Wind Erosion Research Network was established in 2014 to develop tools for monitoring and assessing wind erosion and dust emissions across the United States. The Network, currently consisting of 13 sites, creates opportunities to enhance existing rangeland soil, vegetation, and air quality monitoring programs. Decision-support tools developed by the Network will improve the prediction and management of wind erosion across rangeland ecosystems. © 2017 The Author(s)The Rangelands archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact [email protected] for further information

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: Anisotropic galaxy clustering in Fourier-space

We investigate the anisotropic clustering of the Baryon Oscillation Spectroscopic Survey (BOSS) Data Release 12 (DR12) sample, which consists of $1\,198\,006$ galaxies in the redshift range $0.2 < z < 0.75$ and a sky coverage of $10\,252\,$deg$^2$. We analyse this dataset in Fourier space, using the power spectrum multipoles to measure Redshift-Space Distortions (RSD) simultaneously with the Alcock-Paczynski (AP) effect and the Baryon Acoustic Oscillation (BAO) scale. We include the power spectrum monopole, quadrupole and hexadecapole in our analysis and compare our measurements with a perturbation theory based model, while properly accounting for the survey window function. To evaluate the reliability of our analysis pipeline we participate in a mock challenge, which resulted in systematic uncertainties significantly smaller than the statistical uncertainties. While the high-redshift constraint on $f\sigma_8$ at $z_{\rm eff}=0.61$ indicates a small ($\sim 1.4\sigma$) deviation from the prediction of the Planck $\Lambda$CDM model, the low-redshift constraint is in good agreement with Planck $\Lambda$CDM. This paper is part of a set that analyses the final galaxy clustering dataset from BOSS. The measurements and likelihoods presented here are combined with others in~\citet{Alam2016} to produce the final cosmological constraints from BOSS

The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample

We present cosmological results from the final galaxy clustering data set of the Baryon Oscillation Spectroscopic Survey, part of the Sloan Digital Sky Survey III. Our combined galaxy sample comprises 1.2 million massive galaxies over an effective area of 9329 $deg^2$ and volume of 18.7 $Gpc^3$, divided into three partially overlapping redshift slices centred at effective redshifts 0.38, 0.51, and 0.61. We measure the angular diameter distance DM and Hubble parameter H from the baryon acoustic oscillation (BAO) method after applying reconstruction to reduce non-linear effects on the BAO feature. Using the anisotropic clustering of the pre-reconstruction density field, we measure the product DM*H from the Alcock-Paczynski (AP) effect and the growth of structure, quantified by $f{\sigma}8(z)$, from redshift-space distortions (RSD). We combine measurements presented in seven companion papers into a set of consensus values and likelihoods, obtaining constraints that are tighter and more robust than those from any one method. Combined with Planck 2015 cosmic microwave background measurements, our distance scale measurements simultaneously imply curvature ${\Omega}_K =0.0003+/-0.0026$ and a dark energy equation of state parameter w = -1.01+/-0.06, in strong affirmation of the spatially flat cold dark matter model with a cosmological constant (${\Lambda}$CDM). Our RSD measurements of $f{\sigma}_8$, at 6 per cent precision, are similarly consistent with this model. When combined with supernova Ia data, we find H0 = 67.3+/-1.0 km/s/Mpc even for our most general dark energy model, in tension with some direct measurements. Adding extra relativistic species as a degree of freedom loosens the constraint only slightly, to H0 = 67.8+/-1.2 km/s/Mpc. Assuming flat ${\Lambda}$CDM we find ${\Omega}_m = 0.310+/-0.005$ and H0 = 67.6+/-0.5 km/s/Mpc, and we find a 95% upper limit of $0.16 eV/c^2$ on the neutrino mass sum