11,785 research outputs found
Anoxic Biodegradation of Isosaccharinic Acids at Alkaline pH by Natural Microbial Communities
No full textOne design concept for the long-term management of the UK’s intermediate level radioactive
wastes (ILW) is disposal to a cementitious geological disposal facility (GDF). Under the
alkaline (10.013.0) anoxic conditions expected within a GDF, cellulosic wastes will
undergo chemical hydrolysis. The resulting cellulose degradation products (CDP) are dominated
by α- and β-isosaccharinic acids (ISA), which present an organic carbon source that
may enable subsequent microbial colonisation of a GDF. Microcosms established from neutral,
near-surface sediments demonstrated complete ISA degradation under methanogenic
conditions up to pH 10.0. Degradation decreased as pH increased, with β-ISA fermentation
more heavily influenced than α-ISA. This reduction in degradation rate was accompanied
by a shift in microbial population away from organisms related to Clostridium sporosphaeroides
to a more diverse Clostridial community. The increase in pH to 10.0 saw an increase
in detection of Alcaligenes aquatilis and a dominance of hydrogenotrophic methanogens
within the Archaeal population. Methane was generated up to pH 10.0 with acetate accumulation
at higher pH values reflecting a reduced detection of acetoclastic methanogens. An
increase in pH to 11.0 resulted in the accumulation of ISA, the absence of methanogenesis
and the loss of biomass from the system. This study is the first to demonstrate methanogenesis
from ISA by near surface microbial communities not previously exposed to these compounds
up to and including pH 10.0
Comparison of STL, pan-cancer MTL, and pan-disease MTL by ROC AUC and PR AUC for 17 cancer types with >0.5% prevalence.
No full textComparison of STL, pan-cancer MTL, and pan-disease MTL by ROC AUC and PR AUC for 17 cancer types with >0.5% prevalence.</p
Numbers of shared important SNPs at 0.1% FDR between prevalent cancers in pan-cancer MTL.
No full textNumbers of shared important SNPs at 0.1% FDR between prevalent cancers in pan-cancer MTL.</p
Numbers of important SNPs used by pan-cancer MTL to estimate PRS of prevalent cancers.
No full textNumbers of important SNPs used by pan-cancer MTL to estimate PRS of prevalent cancers.</p
Overview of the Author Profiling Task at PAN 2013
No full text[EN] This overview presents the framework and results for the Author Profiling
task at PAN 2013. We describe in detail the corpus and its characteristics,
and the evaluation framework we used to measure the participants performance to
solve the problem of identifying age and gender from anonymous texts. Finally,
the approaches of the 21 participants and their results are described.The author profiling task @PAN-2013 was an activity of the WIQ-EI IRSES project (Grant No. 269180) within the FP 7 Marie Curie People Framework of the European Commission. We want to thank the Forensic Lab of the Universitat Pompeu Fabra Barcelona for sponsoring the award for the winner team. The work of the first author was partially funded by Autoritas Consulting SA and by Ministerio de Economía y Competitividad de España under grant ECOPORTUNITY IPT-2012-1220-430000. The work of the second author was in the framework the DIANA-APPLICATIONS-Finding Hidden Knowledge in Texts: Applications (TIN2012-38603-C02-01) project, and the VLC/CAMPUS Microcluster on Multimodal Interaction in Intelligent Systems. The work of fifth author was funded in part by the Swiss National Science Foundation (SNF) project "Mining Conversational Content for Topic Modelling and Author Identification (ChatMiner)" under grant number 200021_130208.Rangel, F.; Rosso, P.; Koppel, M.; Stamatatos, E.; Inches, G. (2013). Overview of the Author Profiling Task at PAN 2013. CLEF Conference on Multilingual and Multimodal Information Access Evaluation. 352-365. https://riunet.upv.es/handle/10251/46636S35236
Comparison of STL and pan-disease MTL by ROC AUC and PR AUC for 60 non-cancer diseases with >0.5% prevalence.
No full textComparison of STL and pan-disease MTL by ROC AUC and PR AUC for 60 non-cancer diseases with >0.5% prevalence.</p
PRS estimation for malignant melanoma by STL and MTL.
No full text(A–C) Density plots of malignment melanoma PRS estimated by (A) STL, (B) pan-cancer MTL, and (C) pan-disease MTL. Each panel contains two overlapping density plots: a blue one for the control test cohort and an orange one for the case test cohort. The separation between the control and case density plots is greater in the two MTL panels than in the STL panel. (D) Receiver operating characteristic (ROC) curves of STL (blue), pan-cancer MTL (orange), and pan-disease MTL (green) for malignant melanoma PRS with the baseline (indigo dotted line). Both pan-cancer MTL and pan-disease MTL have larger ROC AUC than STL. (E) Precision-recall (PR) curves of STL (blue), pan-cancer MTL (orange), and pan-disease MTL (green) for malignant melanoma PRS with the disease prevalence as the baseline (indigo dotted line). The two MTL models also have larger PR AUC than STL.</p
Uncovering Plagiarism - Author Profiling at PAN
No full text[ES] PAN is a yearly workshop and evaluation lab on uncovering plagiarism, authorship, and social software misuse. Since 2009, PAN has been organizing benchmark activities on uncovering plagiarism, authorship, and social software misuse . An additional task - author profiling - has also recently been proposed. Author profiling, instead of focusing on individual authors, studies how language is shared by a class of people. Author profiling is a problem of growing importance in applications in forensics, security and marketing. For instance, a person working in the area of forensic linguistics may need to know the linguistic profile of a suspected text message (language used by a certain type of person) and identify characteristics (with language as evidence). Similarly, from a marketing viewpoint, companies may be interested in determining, through the analysis of blogs and online product reviews, what types of people like or dislike their products.Rosso, P.; Rangel Pardo, FM. (2014). Uncovering Plagiarism - Author Profiling at PAN. Ercim News. (96):49-49. https://riunet.upv.es/handle/10251/49303S49499
Overview of PAN 2018 : author identification, author profiling, and author obfuscation
No full textAbstract: PAN 2018 explores several authorship analysis tasks enabling a systematic comparison of competitive approaches and advancing research in digital text forensics. More specifically, this edition of PAN introduces a shared task in cross-domain authorship attribution, where texts of known and unknown authorship belong to distinct domains, and another task in style change detection that distinguishes between single-author and multi-author texts. In addition, a shared task in multimodal author profiling examines, for the first time, a combination of information from both texts and images posted by social media users to estimate their gender. Finally, the author obfuscation task studies how a text by a certain author can be paraphrased so that existing author identification tools are confused and cannot recognize the similarity with other texts of the same author. New corpora have been built to support these shared tasks. A relatively large number of software submissions (41 in total) was received and evaluated. Best paradigms are highlighted while baselines indicate the pros and cons of submitted approaches
Measuring dissociation rate constants of protein complexes through subunit exchange: experimental design and theoretical modeling.
No full textProtein complexes are dynamic macromolecules that constantly dissociate into, and simultaneously are assembled from, free subunits. Dissociation rate constants, k(off), provide structural and functional information on protein complexes. However, because all existing methods for measuring k(off) require high-quality purification and specific modifications of protein complexes, dissociation kinetics has only been studied for a small set of model complexes. Here, we propose a new method, called Metabolically-labeled Affinity-tagged Subunit Exchange (MASE), to measure k(off) using metabolic stable isotope labeling, affinity purification and mass spectrometry. MASE is based on a subunit exchange process between an unlabeled affinity-tagged variant and a metabolically-labeled untagged variant of a complex. The subunit exchange process was modeled theoretically for a heterodimeric complex. The results showed that k(off) determines, and hence can be estimated from, the observed rate of subunit exchange. This study provided the theoretical foundation for future experiments that can validate and apply the MASE method
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