DC-Prophet: Predicting Catastrophic Machine Failures in DataCenters

When will a server fail catastrophically in an industrial datacenter? Is it possible to forecast these failures so preventive actions can be taken to increase the reliability of a datacenter? To answer these questions, we have studied what are probably the largest, publicly available datacenter traces, containing more than 104 million events from 12,500 machines. Among these samples, we observe and categorize three types of machine failures, all of which are catastrophic and may lead to information loss, or even worse, reliability degradation of a datacenter. We further propose a two-stage framework-DC-Prophet-based on One-Class Support Vector Machine and Random Forest. DC-Prophet extracts surprising patterns and accurately predicts the next failure of a machine. Experimental results show that DC-Prophet achieves an AUC of 0.93 in predicting the next machine failure, and a F3-score of 0.88 (out of 1). On average, DC-Prophet outperforms other classical machine learning methods by 39.45% in F3-score.Comment: 13 pages, 5 figures, accepted by 2017 ECML PKD

Management Impacts on Ammonia Volatilization from Swine Manure

Ammonia released from swine manure into the air is becoming an increasingly controversial topic in Iowa. This experiment was conducted to evaluate the potential of several management strategies to reduce ammonia volatilization from swine manure over time. In six benchtop trials using twenty-four 1-L manure storage vessels, treatments were applied to the vessels, and manure and air samples were analyzed for concentrations of ammonia and other forms of nitrogen. Segregated storage of urine and feces, keeping manure cool and still, addition of yucca extract, and acidification reduced ammonia volatilization

Fractionating Choice: A Study on Reward Discrimination, Preference, and Relative Valuation in the Rat (Rattus Norvegicus)

Choice behavior combines discrimination between distinctive outcomes, preference for specific outcomes and relative valuation of comparable outcomes. Previous work has focused on 1 component (i.e., preference) disregarding other influential processes that might provide a more complete understanding. Animal models of choice have been explored primarily utilizing extensive training, limited freedom for multiple decisions and sparse behavioral measures constrained to a single phase of motivated action. The present study used a paradigm that combines different elements of previous methods with the goal to distinguish among components of choice and explore how well components match predictions based on risk-sensitive foraging strategies. In order to analyze discrimination and relative valuation, it was necessary to have an option that shifted and an option that remained constant. Shifting outcomes among weeks included a change in single-option outcome (0 to 1 to 2 pellets) or a change in mixed-option outcome (0 or 5 to 0 or 3 to 0 or 1 pellets). Constant outcomes among weeks were also mixed-option (0 or 3 pellets) or single-option (1 pellet). Shifting single-option outcomes among weeks led to better discrimination, more robust preference and significant incentive contrast effects for the alternative outcome. Shifting multioptions altered choice components and led to dissociations among discrimination, preference, and reduced contrast effects. During extinction, all components were impacted with the greatest deficits during the shifting mixed-option outcome sessions. Results suggest choice behavior can be optimized for 1 component but suboptimal for others depending upon the complexity of alterations in outcome value between options

Beating patterns of filaments in viscoelastic fluids

Many swimming microorganisms, such as bacteria and sperm, use flexible flagella to move through viscoelastic media in their natural environments. In this paper we address the effects a viscoelastic fluid has on the motion and beating patterns of elastic filaments. We treat both a passive filament which is actuated at one end, and an active filament with bending forces arising from internal motors distributed along its length. We describe how viscoelasticity modifies the hydrodynamic forces exerted on the filaments, and how these modified forces affect the beating patterns. We show how high viscosity of purely viscous or viscoelastic solutions can lead to the experimentally observed beating patterns of sperm flagella, in which motion is concentrated at the distal end of the flagella

Predictive model of response to tafamidis in hereditary ATTR polyneuropathy

BACKGROUNDThe hereditary transthyretin (TTR) amyloidoses are a group of diseases for which several disease-modifying treatments are now available. Long-term effectiveness of these therapies is not yet fully known. Moreover, the existence of alternative therapies has resulted in an urgent need to identify patient characteristics that predict response to each therapy.METHODSWe carried out a retrospective cohort study of 210 patients with hereditary TTR amyloidosis treated with the kinetic stabilizer tafamidis (20 mg qd). These patients were followed for a period of 18-66 months, after which they were classified by an expert as responders, partial responders, or nonresponders. Correlations between baseline demographic and clinical characteristics, as well as plasma biomarkers and response to therapy, were investigated.RESULTS34% of patients exhibited an almost complete arrest of disease progression (classified by an expert as responders); 36% had a partial to complete arrest in progression of some but not all disease components (partial responders); whereas the remaining 30% continued progressing despite therapy (nonresponders). We determined that disease severity, sex, and native TTR concentration at the outset of treatment were the most relevant predictors of response to tafamidis. Plasma tafamidis concentration after 12 months of therapy was also a predictor of response for male patients. Using these variables, we built a model to predict responsiveness to tafamidis.CONCLUSIONOur study indicates long-term effectiveness for tafamidis, a kinetic stabilizer approved for the treatment of hereditary TTR amyloidosis. Moreover, we created a predictive model that can be potentially used in the clinical setting to inform patients and clinicians in their therapeutic decisions.info:eu-repo/semantics/publishedVersio

Human islets expressing HNF1A variant have defective beta cell transcriptional regulatory networks

Using an integrated approach to characterize the pancreatic tissue and isolated islets from a 33-year-old with 17 years of type 1 diabetes (T1D), we found that donor islets contained beta cells without insulitis and lacked glucose-stimulated insulin secretion despite a normal insulin response to cAMP-evoked stimulation. With these unexpected findings for T1D, we sequenced the donor DNA and found a pathogenic heterozygous variant in the gene encoding hepatocyte nuclear factor-1alpha (HNF1A). In one of the first studies of human pancreatic islets with a disease-causing HNF1A variant associated with the most common form of monogenic diabetes, we found that HNF1A dysfunction leads to insulin-insufficient diabetes reminiscent of T1D by impacting the regulatory processes critical for glucose-stimulated insulin secretion and suggest a rationale for a therapeutic alternative to current treatment

A Correlation between Protein Function and Ligand Binding Profiles

We report that proteins with the same function bind the same set of small molecules from a standardized chemical library. This observation led to a quantifiable and rapidly adaptable method for protein functional analysis using experimentally-derived ligand binding profiles. Ligand binding is measured using a high-throughput NMR ligand affinity screen with a structurally diverse chemical library. The method was demonstrated using a set of 19 proteins with a range of functions. A statistically significant similarity in ligand binding profiles was only observed between the two functionally identical albumins and between the five functionally similar amylases. This new approach is independent of sequence, structure or evolutionary information, and therefore, extends our ability to analyze and functionally annotate novel genes

Generalized Hurst exponent and multifractal function of original and translated texts mapped into frequency and length time series

A nonlinear dynamics approach can be used in order to quantify complexity in written texts. As a first step, a one-dimensional system is examined : two written texts by one author (Lewis Carroll) are considered, together with one translation, into an artificial language, i.e. Esperanto are mapped into time series. Their corresponding shuffled versions are used for obtaining a "base line". Two different one-dimensional time series are used here: (i) one based on word lengths (LTS), (ii) the other on word frequencies (FTS). It is shown that the generalized Hurst exponent $h(q)$ and the derived $f(\alpha)$ curves of the original and translated texts show marked differences. The original "texts" are far from giving a parabolic $f(\alpha)$ function, - in contrast to the shuffled texts. Moreover, the Esperanto text has more extreme values. This suggests cascade model-like, with multiscale time asymmetric features as finally written texts. A discussion of the difference and complementarity of mapping into a LTS or FTS is presented. The FTS $f(\alpha)$ curves are more opened than the LTS onesComment: preprint for PRE; 2 columns; 10 pages; 6 (multifigures); 3 Tables; 70 reference

God\u27s Church Is Just: A Specific Discussion Of Some Cases of Church Discipline

https://digitalcommons.acu.edu/crs_books/1364/thumbnail.jp